c/EPA
United States
Environmental Protection
Agency
Environmental Research
Laboratory
Corvallis OR 97330
EPA-600 3-79-044
April 1979
Research and Development
Bioenvironmental
Impact of a Coal-
Fired Power Plant
Fourth Interim
Report, Colstrip,
Montana
December 1978
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RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development, U.S. Environmental
Protection Agency, have been grouped into nine series. These nine broad cate-
gories were established to facilitate further development and application of en-
vironmental technology Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface in related fields.
The nine series are:
1 Environmental Health Effects Research
2. Environmental Protection Technology
3. Ecological Research
4. Environmental Monitoring
5. Socioeconomic Environmental Studies
6. Scientific and Technical Assessment Reports (STAR)
7 Interagency Energy-Environment Research and Development
8. "Special" Reports
9. Miscellaneous Reports
This report has been assigned to the ECOLOGICAL RESEARCH series. This series
describes research on the effects of pollution on humans, plant and animal spe-
cies, and materials. Problems are assessed for their long- and short-term influ-
ences. Investigations include formation, transport, and pathway studies to deter-
mine the fate of pollutants and their effects. This work provides the technical basis
for setting standards to minimize undesirable changes in living organisms in the
aquatic, terrestrial, and atmospheric environments.
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.
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EPA-600/3-79-044
April 1979
THE BIOENVIRONMENTAL IMPACT OF A COAL-FIRED POWER PLANT
Fourth Interim Report, Colstrip, Montana
December, 1978
Edited by
Eric M. Preston and Thomas L. Gullett
Terrestrial Systems Division
Corvallis Environmental Research Laboratory
Corvallis, OR 97330
CORVALLIS ENVIRONMENTAL RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
CORVALLIS, OR 97330
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DISCLAIMER
This report has been reviewed by the Corvallis Environmental Research
Laboratory, U.S. Environmental Protection Agency, and approved for publica-
tion. Mention of trade names or commercial products does not constitute
endorsement or recommendation for use.
11
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FOREWORD
Effective regulatory and enforcement actions by the Environmental Protec-
tion Agency would be virtually impossible without sound scientific data on
pollutants and their impact on environmental stability and human health.
Responsibility for building this data base has been assigned to EPA's Office
of Research and Development and its 15 major field installations, one of which
is the Corvallis Environmental Research Laboratory (CERL).
The primary mission of the Corvallis Laboratory is research on the ef-
fects of environmental pollutants on terrestrial, freshwater, and marine
ecosystems; the behavior, effects and control of pollutants in lake systems;
and the development of predictive models on the movement of pollutants in the
biosphere.
The Colstrip, Coal-fired Power Plant Project is a first attempt to gener-
ate methods to predict the bioenvironmental effects of air pollution before
damage is sustained. The results will aid planners in assessing the ecologi-
cal impact of energy conversion activities on grasslands prior to site selec-
tion.
J. C. McCarty
Acting Director, CERL
111
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PREFACE
The Environmental Protection Agency has recognized the need for a ra-
tional approach to the incorporation of ecological impact information into
power facility siting and managment decisions in the northern great plains.
Two capabilities need to be developed. First, in evaluating alternative
sites, planners need to be able to predict the kinds and magnitudes of impacts
to be expected so that adverse consequences to the environment can be mini-
mized. Secondly, for routine facility management after siting, environmental
monitoring methods are needed for detecting incipient ecological damage in
time for mitigation efforts to be effective.
Research funded by the Colstrip, coal-fired power plant project is a
first attempt to generate the methods needed to predict the bioenvironmental
effects of air emissions from coal-fired power plants before damage is sus-
tained. The work can be subdivided into three chronological phases: 1) the
identification of information requirements and the expansion of data and
information bases to fill these requirements, 2) the integration and synthesis
of newly generated data with existing information to define relationships
permitting maximum predictive capability, 3) provide the information in a
format useful to planners and decision makers involved in siting coal-fired
power plants. Several iterations of phases 1 through 3 may be necessary in
the long term.
Project rationale and design have been presented in detail in introduc-
tory sections of previous interim reports. Until now effort has been largely
confined to Phase 1. As the project proceeds, progressively more resources
will be devoted to Phases 2 and 3. In the present report, Sections 24 and 25
deal with the synthesis and integration of data bases to generate methods for
ecological impact assessment and prediction. The rate of transition in empha-
sis is primary dictated by the adequacy of data bases available for synthesis.
Research effort for Phase 1 falls roughly into two broad categories: 1)
ecological effects monitoring in the vicinity of two 350 megawatt coal-fired
power plants at Colstrip, Montana, and 2) field and laboratory process studies
designed to elaborate the mechanisms through which coal-fired power plant
emissions cause their effects.
Pre-construction documentation of the environmental characteristics of
the grassland ecosystem in the vicinity of Colstrip, Montana began in the
summer of 1974. This documentation continued until Colstrip generating unit 1
began operation in September, 1975. Since then, key characteristics of the
ecosystem have been monitored regularly to detect possible pollution impacts.
The current results relevant to this effects monitoring appear in Section 1-8.
IV
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In 1974, A Zonal Air Pollution System (ZAPS) was designed to stress 0.5
hectare areas of native grassland with measured concentrations of S02. In the
summer of 1975, field stressing experiments were begun to provide the data
necessary to develop dose-response models of S02 stress on a grassland eco-
system. A second Zonal Air Pollution System (ZAPS II), was constructed in
1976. Both ZAPS I and ZAPS II were operated during the growing seasons of
1976 and 1977. The design of these experimental systems has been described in
previous interim reports. Their behavior is further described in the present
report. Effects on microorganisms, producers and consumers have been moni-
tored throughout the stressing experiments. In addition, field experiments
have been conducted to evaluate the effects of S02 stress on alfalfa and small
grains of agricultural importance in the northern plains. The results of
these experiments to date are summarized in Sections 9-20.
Trace element emissions from coal-fired power plants may also influence
ecosystem behavior. Laboratory experiments have been conducted to evaluate
the behavior of mercury and other selected trace elements on selected soils
and plants. These results are presented in Sections 21-23.
The final two sections represent preliminary attempts to utilize informa-
tion presented in previous sections and previous interim reports to address
the project's objectives.
v
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ABSTRACT
The purpose of the Colstrip, Coal-fired Power Plant Project is to develop
information that will aid in assessing the potential bioenvironmental impacts
of air emissions from coal-fired power plants on northern plains ecosystems
before damage occurs. The project has three major components: (1) a case
study of the ecological impact of the coal-fired generating units at Colstrip,
Montana, (2) a series of field and laboratory process studies designed to
elaborate the mechanisms of S02 action on grasslands chronically fumigated at
low-levels, (3) development of a methodology for incorporating ecological
effects information into the power plant siting process.
COLSTRIP STUDIES
Pre-construction documentation of the environmental characteristics of
the grassland ecosystem in the vicinity of Colstrip, Montana began in the
summer of 1974. This continued until Colstrip generating Unit 1 began opera-
tion in September 1975. Since then, key characteristics of the ecosystem
have been monitored to detect air pollution and its ecological effects.
Both natural aerosols and those generated by the coal-fired power plants
at Colstrip, Montana, were studied. The background aerosols were found to
consist of irregular-shaped particles composed primarily of alumino-silicates
with relatively high concentrations of the metallic elements for a rural
area. Aerosols generated by the power plant were relatively large (approxi-
mately 1 pm), glassy, alumino-silicate spheres with a high incidence of
calcium and sulfur when collected in the plume near the power plant. At
large distances downwind they became small (<.4 pm) sulfur-containing spheres.
These artificial aerosols increase the available ice-nuclei concentration by
an order of magnitude, and may be significant to the formation and distribu-
tion of precipitation.
Plant community studies indicate that graminoids and lichens are the
dominant vegetational components influencing cover, number, and diversity at
the grassland study sites near Colstrip. The abundance of annual grasses
varies markedly among sites, and this strongly affects diversity through
reduced equitability. Previous grazing history and variations in yearly
climatic conditions, which are primarily responsible for the observed differ-
ences in plant species composition, have so far masked any pollution effects.
The data suggest a predictive relationship between plant diversity and range
condition.
Two lichen species have been monitored for signs of stress since 1974.
There were sharp respiration rate increases in September 1977 in both Usnea
k^tz and Parmelia chlorockroa at sites closest to Colstrip. Chlorophyll
content of Usnea hi-rta thalli may have decreased between 1975 and 1977.
vi
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The characteristics of four different years of pine foliage collected
during 1977 at pristine and chronically polluted sites are compared. All air
pollution damage symptoms are mimicked macroscopically by abiotic and biotic
causal agents in pristine environments. The foliar symptoms being measured
over time on foliage from chronically polluted areas increased or decreased
in comparison to those found in pristine areas.
Pre- and post-operational assessments of the ground level plume contact
area were made using terrestrial insects as biological indicators. Post-
operational changes in fluoride levels in bee tissues were statistically
significant in 1976 and 1977 at downwind sites 15-20 km from Colstrip.
Trends in bird populations have been monitored for three consecutive
years in the vicinity of Colstrip. Since 1975, the avian community has
become increasingly dominated by Meadowlarks while the relative abundances of
raptors, blackbirds and Lark Buntings have decreased. Much of the local
variation in bird species diversity is strongly correlated with habitat
factors.
Baseline trends in the histology of thymus and thyroid glands of western
meadowlarks near Colstrip are reported.
FIELD AND LABORATORY EXPERIMENTS
\
In 1974, a Zonal Air Pollution System (ZAPS) was designed to stress 0.5
hectare areas of native grassland with measured concentrations of S02.
Field stressing experiments were initiated during the summer of 1975. A
second ZAPS was constructed in 1976. Both ZAPS I and ZAPS II were operated
during 1976 and 1977.
Soil and meteorological characteristics at ZAPS are presented.
Average geometric mean S02 exposure concentrations for 3 growing seasons
(1975, 1976, 1977) on ZAPS I plots were near 1 pphm, 2 pphm, 4 pphm and 7
pphm for the Control, Low, Medium, and High treatments, respectively. Expo-
sure concentrations on ZAPS II for 2 growing seasons (1976, 1977) were near
1 pphm, 3 pphm, 5 pphm, and 7 pphm for Control, Low, Medium, and High treat-
ments, respectively. Standard geometric deviations of S02 concentrations on
the plots were approximately 3 pphm. S02 concentrations on the ZAPS plots
showed substantial inter-seasonal and intra-seasonal variation. Concentra-
tions were generally higher at night than during the day, but otherwise
patterns of intra-seasonal variability were not consistent between ZAPS plots
or between years. Intra-season variation was greatest on High treatment
plots and least on Control plots. Seasonal frequencies of S02 concentrations
were approximately log-normally distributed and showed reasonably good
separation in fumigation histories of the treatment plots. Though median S02
concentrations of the Control plots were small, these plots were subject to
short-term acute fumigations due to drift from other plots. S02 concen-
trations decreased with decreasing height above the ground within the plant
canopy.
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Soils from each of the fumigation plots were analyzed for their hydrogen
oxidation potential using Alcaligenes paradoxus as a representative micro-
organism. After 1 year of fumigation, only the High treatment plot exhibited
a detectable depression in hydrogen oxidation potential. However, after 2
years, there was a significant decrease in hydrogen oxidation potential
associated with increasing S02 exposure.
The dominant grass species on the plots are resistant to acute visible
injury from S02 exposure. For most, exposure to 1.6 ppm or greater concen-
trations of S02 for four hours or longer is required to produce typical
symptoms. Threshold doses for acute injury have apparently not been exceeded
even on the highest treatment since no acute visible injury symptoms have
appeared.
Chronic visible injury for western wheatgrass, Agropyron smithi-i, on
the S02 treated plots is expressed by an increased leaf senescence without
specific pattern. Leaf senescence occurs earlier and at a more rapid rate
than on controls. A gradient of increasing chlorosis from the lower to
higher treatment plots was evident in remote imagery after one season of
treatment. Unfortunately, within plot heterogeneity made changes of less
than 15% in biomass dynamics and net primary productivity impossible to
detect with the harvesting method used in 1975. No change attributable to
treatment was detected. Harvesting methods with greater precision were used
during 1976 and 1977 which allowed changes of about 10% to be detected. To
date, no statistically significant changes in net primary productivity have
appeared. Fluctuations in species composition and diversity have thusfar
shown no consistent relationship to S02 treatment.
While the mechanism of S02 action has not been demonstrated, field
observations and review of the literature allowed development of the follow-
ing working hypothesis. On the entry to the leaf, S02 is rapidly dissolved
to form sulfite which is toxic in relatively low concentrations and thought
to be responsible for acute leaf injury. Sulfite is slowly oxidized to
sulfate which is much less toxic than sulfite and may be used directly as a
nutrient. As long as S02 is not absorbed at a rate exceeding the cell's
capacity to change sulfite to sulfate, acute leaf injury is unlikely.
However, as the concentration of sulfate increases over time, toxic levels
may be reached causing chlorosis and resulting in an increased rate of leaf
senescence.
At the exposure rates on the ZAPS plots, western wheatgrass plants
apparently grew at a sufficient rate to incorporate the S02 into normal
metabolites early in the growing season. Later in the growing season, when
metabolic activity slowed, toxic levels of sulfur compounds may have accumu-
lated and accelerated senescence. Thusfar, the increased rate of senescence
has been observed only in western wheatgrass on the medium and high treat-
ments. Sulfur accumulation was apparently insufficient to cause early senes-
cence on the low treatments.
Whatever the mechanism, S02 causes foliar senescence to begin earlier
and therefore reduces the functional life of the leaves of western wheat-
grass. This may require that more photosynthate be allocated to maintain
Vlll
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active photosynthetic machinery at the expense of other plant processes, such
as root storage or seed production. Gradual depletion of root carbohydrate
reserves could eventually reduce the capacity of the system to overwinter
successfully, sustain grazing, or tolerate additional air pollution.
Sexual reproduction was also apparently impaired by S02 treatment on
some plots in some species. This was manifested variously as decreases in
seed weight, % germination, germination rate, and seed viability depending
upon the species. Such effects upon seed production and viability have
direct implications for seed farmers in the northern Great Plains, but there
may also be significant implications for the viability of the ecosystem.
Sexual reproduction provides the genetic mechanism to. adapt over the long-
term to new environmental stresses such as air pollution. If sexual repro-
duction is impaired, a smaller range of genotypes will be available upon
which adaptive selection can operate.
Grasses on the treated plots appeared to accumulate sulfur in direct
proportion to the median S02 concentration they experience, though evidence
of accumulation on the Control and Low treatments is inconclusive. On the
medium and high plots, accumulation proceeds through the growing season.
Though much of the accumulated sulfur is cycled through dead above ground
material at the end of the growing season, each spring, sulfur accumulation
seems to begin from a higher baseline level than was present at the same time
during the previous spring. The long-term implications of this are difficult
to predict. The increased sulfur availability may prove advantageous to the
plants if sulfur levels are deficient and low availability of other nutrients
does not limit metabolic utilization of the excess sulfur. If the excess
sulfur cannot be utilized, accumulation of toxic concentrations of sulfur
compounds may occur progressively earlier in the growing season year after
year. This could lead to progressively earlier leaf senescence and accelerate
the gradual loss of vitality previously discussed.
S02 exposure has apparently modified the forage quality of western
wheatgrass plants on the treated plots. Crude protein content decreased from
about 10% to about 8% following the second year of exposure on ZAPS I. This
change appears to be a very low threshold effect. The reduction in crude
protein content occurred even on the low treatment. This effect could have
dramatic implications for the stocking capacities of grazing land in the
northern Great Plains. Ranchers that can sustain stock by feeding native
grasses having 10% crude protein may have to provide a protein supplement if
the level were reduced to
Mycorrhizal fungi are normally associated with the rhizomes of western
wheatgrass. This is apparently a mutualistic association in which the fungi
utilize a portion of the host's root carbohydrates while facilitating phos-
phorus transport from humus to the plant. Occurrence of mycorrhizal fungi
decreased in direct proportion to increased median S02 exposure concentration
on the treated plots. The cause of decreased association is still unclear.
It is possible that carbohydrate available to the fungi decreased because of
decreased photosynthate or increased sulfur translocation to the rhizomes and
roots. The significance of decreased mycorrhizal fungal association for the
long-term viability of the grasses cannot adequately be evaluated at this
IX
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time, but any reduction in the ability of primary producers to make use of
the otherwise available nutrients would likely be detrimental to primary
productivity.
Lichens are an important winter forage for deer and are particularly
sensitive to S02 stress. Lichen coverage has been severely reduced on the
treated plots. Both the amount of photosynthetic tissue and respiration rate
are affected.
Though a majority of invertebrate groups failed to show substantial
population level treatment responses, there were important exceptions.
Ground beetles of the genus Canthon consume and/or fragment large quantities
of organic material such as feces, carrion, and vegetative matter. Fragmen-
tation creates greater surface area upon which decomposer microflora may work
thus facilitating decomposition. These beetles have responded markedly to
S02 fumigation. Beetle numbers (as measured by pitfall trapping) have de-
creased dramatically on all treated plots. The exposure threshold causing
this effect is apparently quite low. It is not yet known whether reduced
numbers result from S02 avoidance or a change in life table parameters.
Grasshoppers sever many shoots that they do not consume. This material
becomes above ground litter and begins decomposing. This process may reduce
total photosynthetic surface of affected plants by removing live shoots
and/or it may bring standing dead material into the litter layer where
decomposition may occur more rapidly. In any event, the rate of such grass-
hopper wastage of live and standing dead material must be influenced by
grasshopper grazing rates which in turn must be some function of grasshopper
numbers and consumption rate per grasshopper. Controlled feeding trials in
laboratory cages showed that two grasshopper species selectively rejected
western wheatgrass that had been previously exposed to SC>2 on the High
treatment plot (ZAPS I). Preliminary work also suggests that grasshopper
numbers may decrease on some treated plots. Though the decrease appears to
be modest, such effects on grasshoppers could influence the rate of flow of
carbon into the litter layer.
Below ground microarthropods, nematodes, tardigrades and rotifers are
important to mineralization of nutrients bound in below ground organic
material. Any changes in populations of these organisms may substantially
affect rates in the below ground portion of nutrient cycles. Responses of
below ground organisms to S02 treatment has been mixed. Mites have shown no
detectable treatment effect. Though total nematode population numbers have
not changed, the proportion of saprophagous nematodes has decreased and the
proportion of plant feeding nematodes has increased on ZAPS I. Nematodes on
ZAPS II have not shown any detectable treatment effects. Tardigrade numbers
were reduced in all but one of the treated plots (medium plot, ZAPS II) in
1977. Rotifers appeared to be reduced in the high treatment plots only.
While the magnitude of the above effects on nutrient cycling cannot yet
be quantified, several decomposition processes may take longer as a result of
SQ2 exposure at levels on the treated plots. A new equilibrium will have to
be reached between carbon fixation and nutrient cycling subsystems.
x
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Predatory ground beetles of the family Carabidae have shown a decline in
numbers directly proportional to median S02 exposure during 1975 and 1976 on
both ZAPS sites. This decline in numbers could result from a direct effect
of S02 on predator avoidance or mortality or an indirect effect due to an
effect of 862 on prey species. The effects on various arthropod numbers
mentioned earlier may affect their availability as food which may in turn
affect the population dynamics of small mammals.
A capture-mark-release study of deer mice (Peromyscus manioulatus) and
prairie voles (Micpotus ochrogastev} was conducted on the ZAPS sites at
monthly intervals from April to September 1976. Throughout most of the
trapping period, the number of occupied traps on all fumigated plots decreased
relative to Control plots on both ZAPS, and remained relatively higher on
Control plots from mid-season to the end of all trapping.
Aerial photography of the ZAPS sites has been collected since 1974.
Highly significant correlations were observed between image densities and S02
levels on the fumigation plots. Leaf senescence of western wheatgrass
showed similar relationships. Color infrared film exposed during the active
growth season gave the best results.
Several experiments were conducted at Oregon State University's Schmidt
Research Farm to determine the effects of various SC-2 treatments on yield of
small grains growing in a field environment. The results of a chronic expo-
sure experiment strongly suggested that the yields of Durum wheat and barley
could be suppressed by weekly, 72-hour exposures to S02 concentrations as low
as 15 pphm. Average yield reduction for the 15 pphm treatment were 42% and
44% compared to controls for Durum wheat and barley, respectively. The yield
of spring wheat was not reduced by the S02 treatment. An analysis of a
multiple exposure experiment demonstrated that 1) varying the frequency of 3-
hour exposures to S02 concentrations up to 120 pphm from as often as once
every week to as infrequently as once every 5 weeks had no effect on yields
of the small grain crops and alfalfa and 2) at 3-hour exposures, increasing
SC-2 concentration from 0 to 120 pphm had no effect on yield. A growth stage
experiment demonstrated there was no growth stage at which the small grain
crops or alfalfa were most sensitive to a 3-hour exposure to S02 concentra-
tions up to 120 pphm. The growth of tops and roots of range grasses and
alfalfa was not affected during the fall season by 3-hour exposure to concen-
trations of SC-2 up to 120 pphm.
The fate of mercury in five surface soils from southeastern Montana was
studied in the laboratory. Western wheatgrass seedlings grown on soils
amended with mercuric nitrate showed aerial tissue concentration factors of
0.01 to 0.12.
The uptake of mercury vapor by plants was affected by both illumination
and temperature. Among six species examined, the mercury uptake differed
between species and a pronounced difference existed between C3 and C^
plants, owing to their differences in biochemical processes.
The toxicity of selected trace elements emitted from coal-fired power
plants was determined for several biological functions in the blue-green
algae, Andbaena cylindrical.. This organism performs the basic biological
xi
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functions of nitrogen fixation, photosynthesis, respiration, and growth, was
easily adaptable to existing measurement techniques, is of significance in
the grassland biome, and provides an excellent multifunctional organism for
testing the effects of emission contaminants. The elements tested were F,
Na, Cl, Br, Li, K, Sr, Ba, Cr, Mn, Ni, Cu, Zn, Cd, Hg, Pb, and As. In order
of decreasing toxicity Hg, Cu, Cr, Ni, Cd, and Pb exerted strong inhibition
at levels of 1 mM or below. In assays of biological functions Hg, Cu, Zn,
Cd, and Pb exhibited strong toxicity at 1 mM or lower levels.
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CONTENTS
Page
Foreword
Preface
Abstract
List of Contributors xviii
Acknowledgements xxi
Sections
ECOLOGICAL EFFECTS MONITORING IN THE COLSTRIP VICINITY
1. Aerosol Characterization in the Vicinity of Colstrip,
Montana
C. C. Van Valin, R. F. Pueschel, D. L. Wellman,
N. L. Abshire, G. M. Lerfald, and G. T. McNice 2
Atmospheric Characterization Laboratories 4
Remote Sensing Laboratory 43
2 Baseline Characteristics of Producer and Invertebrate
Populations and Certain Abiotic Parameters in the
Colstrip Vicinity
J. L. Dodd, J. W. Leetham, T. J. McNary, W. K.
Lauenroth, and G. L. Thor 53
Soil and Temporal Dynamics of Soil Water and Pre-
cipitation 54
Producers and Primary Production 54
Invertebrate Populations 60
3 Plant Community Monitoring
J. E. Taylor and W. C. Leininger 107
Plant Community Analysis 112
Photographic Studies 119
4 Summary of Observations of Usnea hirta and Pavmelia
chloToohroa in the Colstrip Area, 1974-77
S. Eversman 132
5 Foliar Pathologies of Ponderosa Pine Near Colstrip
C. C. Gordon, P. C. Tourangeau, and P. M. Rice 141
Growth/Health/Damage Characteristics of Pine
Needles 150
Fluoride, Needle Length, and Fascicular Cross-
Sectional Area 171
xiii
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Anova with GB-1, BNW-1, BNW-2, BNW-3 (1976 and
1977 Collections) 175
Understory Species 186
6 Honeybees and Other Insects as Indicators of Pollution
Impact from the Colstrip Power Plants
J. J. Bromenshenk 215
Fluoride 223
Trace Metals 228
Radionuclides 230
7 Trends in Bird Populations in the Vicinity of Colstrip
E. M. Preston and S. K. Thompson 240
Species Composition 242
Seasonal Changes in the Spatial Patterns of Bird
Populations 248
8 Baseline Histology of the Thyroid and Thymus Glands of
Western Meadowlarks Near Colstrip
M. D. Kern and J. P. Wiggins 257
Normal Histology of the Thyroid Gland of Western
Meadowlarks 266
Normal Histology of the Thymus Gland of Western
Meadowlarks 270
THE EFFECTS OF CONTROLLED FIELD EXPOSURES TO S02 ON BIOLOGICAL
SYSTEMS OF THE NORTHERN GREAT PLAINS
9 Temporal Variation in S02 Concentration on ZAPS
J. J. Lee, E. M. Preston, and D. B. Weber 284
Interseasonal Trends 293
Intraseasonal Trends 293
Frequency Distributions of S02 Concentrations on
the Plots 293
Diel Patterns 300
Effect on Micrometeorological Variables on Real
Time S02 Concentrations 300
10 Spatial Variation of Sulfur Dioxide Concentrations on ZAPS
During the 1977 Field Season
E. M. Preston and T. L. Gullett 306
Extensive Study 307
Vertical Distribution of SOZ 307
Horizontal SOZ Distribution 315
Conversion Factors for Sulfation Values 322
Intensive Study 326
xiv
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11 Soil and Meteorological Characteristics at ZAPS
J. L. Dodd, W. K. Lauenroth, R. G. Woodmansee,
G- L. Thor, and J. D. Chilgren ............. 331
12 The Effect of S02 on Soil Microorganism Activity
J. C. McFarlane, R. D. Rogers, and D. V.
Bradley, Jr ....................... 377
13 Effects of Chronic Low Level S02 Exposure on Producers
and Litter Dynamics
J. L. Dodd, W. K. Lauenroth, G. L. Thor, and
M. B. Coughenour .................... 384
Aboveground Plant Biomass Dynamics and Net Primary
Productivity ...................... 384
Belowground Plant Biomass Dynamics ............ 388
Phenology ......................... 391
Effects of Controlled Levels of S02 °n the Nutri-
ent Quality of Western Wheatgrass and Prairie
June Grass ....................... 396
Sulfur ....................... 397
Ash ........................ 401
Crude Protein ................... 401
Cell Wall Constituents ............... 404
Dry Matter Digestion ................ 404
Effects of Controlled Levels of SOz on Growth and
Senescence of Western Wheatgrass ............ 408
Effects of Controlled Levels S02 on Physiology of
Western Wheatgrass ................... 428
Distribution of 35S02 Sulfur and 14C02 Carbon by
Native Mixed-Grass Prairie and Possible 62 Effects . . . 441
Simulation Models: Sulfur Cycle and Ecosystem
Level Model ....................... 466
Decomposition-Litter Biomass Dynamics ........... 467
14 The Effects of "Low Level SCV Exposure on Sulfur Accumu-
lation and Various Plant Life Responses of Some Major
Grassland Species on the ZAPS Sites
P. M. Rice, L. H. Pye, R. Boldi, J. O'Loughlin,
P. C. Tourangeau, and C. C. Gordon ........... 494
Sulfur Accumulation in Plants ............... 508
Washing Experiment ..... . .............. 531
Fluoride Uptake ...................... 532
Vegetative Phenology ................... 532
Seed Work ......................... 541
Mycorrhizal Studies .................... 554
15 Response of Selected Small Grains, Range Grasses and Al-
falfa to Sulfur Dioxide
R. G. Wilhour, G. E. Neely, D. E. Weber, and
L. C. Grothaus ......... •• ........... 592
xv
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Field Exposure Study 597
Range Grass and Alfalfa Study 603
16 Plant Community Changes Due to Low Level SC-2 Exposure
J. E. Taylor and W. C. Leininger 610
Plant Community Analysis 612
Canopy Coverage 612
Diversity 619
Phenology 626
Lichens 626
17 Effects of Low-Level S02 on Two Native Lichen Species
S. Eversman 642
18 Responses of Ground-Dwelling Insects to Sulfur Dioxide
J. J. Bromenshenk 673
19 Effects of Controlled Levels of SC-2 on Invertebrate
Consumers
J. W. Leetham, T. J. McNary, and J. L. Dodd 723
Biomass and Population Dynamics of Invertebrate
Fauna 724
The Effect of Chronic S02 Air Pollution on
Acrididae (Grasshoppers) Population Dynamics
and Behavior 738
Nematode Populations 759
Tardigrade and Rotifer Populations 761
20 Small Mammal Investigations at ZAPS: Demographic Studies
and Responses to Gradient Levels of S02
J. D. Chilgren 764
Species Composition and Description 768
Sex and Age Composition 768
Population Characteristics 770
Survival 772
Home Range 773
Home Range and Biomass: Relationships to Popula-
tion Density 775
Experimental Effects 775
AN EXPERIMENTAL EVALUATION OF THE FATE AND IMPACT OF SELECTED TRACE
ELEMENT STACK EMISSIONS IN THE SOIL-PLANT ENVIRONMENT
21 The Fate and Bioenvironmental Impact of Mercury in Soils
E. R. Landa 792
The Volatile Loss of Soil-Applied Inorganic Dival-
ent Mercury 802
xvi
-------
The Volatile Loss of Mercury from Soils Amended
with Methylmercury Chloride 808
The Retention of Metallic Mercury Vapor by Soils 813
The Effect of Mercuric Chloride on Carbon Mineral-
ization in Soils 818
The Uptake from Soils of Inorganic Divalent Mer-
cury by Plants 820
22 Uptake of Metallic Mercury Vapor by Soils and Various Plant
Species
C. L. Browne and S. C. Fang 829
Estimation of Whole-Plant Resistance to Gaseous
Exchange 838
Factors Influencing the Uptake of Hg Vapor by
Wheat 843
Differential Uptake of Hg Vapor by Plants 850
In Vi-tPO Conversion of Elemental Mercury Vapor
by Homogenized Leaves of Various Plant Species 852
Sorption of Mercury Vapor by Soils 856
23 Effects of Stack Emissions Upon Primary Aspects of Photo-
synthesis and Photosynthetically-Linked Nitrogen Fixation
R. M. Tetley and N. I. Bishop 866
The Action of Oxygen and Select Metabolic Inhibi-
tors on Photosynthesis, Respiration, and Nitro-
gen Fixation 870
Effects of Trace Elements on Photosynthesis,
Nitrogen Fixation, Respiration and Growth in
Andbaena 878
Effects of Select Elements on Growth of Salv-ina
and Azolla 887
Inhibition by Select Trace Elements 887
PRELIMINARY SYNTHESIS
24 The Use of Remote Sensing in Evaluating SOz Damage to
Grasslands
J. E. Taylor, W. C. Leininger, and T. R. Osberg 899
Aerial Photography 904
Analysis of Photography 904
Densitometric Analysis 904
Vegetation Mapping 910
General Discussion 910
25 Methodology Development for Siting Power Plants
J. L. Dodd, W. K. Lauenroth, and W. J. Parton 926
xvii
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LIST OF CONTRIBUTORS
N. L. Abshire
U.S. Department of Commerce
NOAA
Environmental Research Laboratories
Boulder, Colorado 80302
N. I. Bishop
Department of Botany
Oregon State University
Corvallis, Oregon 97331
R. Boldi
Environmental Studies Laboratory
University of Montana
Missoula, Montana 59801
D. V. Bradley, Jr.
U.S. EPA/EMSL
P.O. Box 15027
Las Vegas, Nevada 89114
J. J. Bromensbenk
Environmental Studies Laboratory
University of Montana
Missoula, Montana 59801
C. L. Browne
Department of Agricultural Chemistry
Oregon State University
Corvallis, Oregon 97331
J. D. Chilgren
U.S. EPA/CERL
200 SW 35th Street
Corvallis, Oregon 97330
M. B. Coughenour
Natural Resource Ecology Laboratory
Colorado State University
Fort Collins, Colorado 80521
J. L. Dodd
Natural Resource Ecology Laboratory
Colorado State University
Fort Collins, Colorado 80521
S. Eversman
Department of Biology
Montana State University
Bozeman. Montana 59715
S. C. Fang
Department of Agricultural Chemistry
Oregon State University
Corvallis, Oregon 97331
C. C. Gordon
Environmental Studies Laboratory
University of Montana
Missoula, Montana 59801
L. C. Grothaus
U.S. EPA/CERL
200 SW 35th Street
Corvallis, Orgon 97330
T. L. Gullett
U.S. EPA/CERL
200 SW 35th Street
Corvallis, Oregon 97330
M. D. Kern
Department of Biology
The College of Wooster
Wooster, Ohio 44691
E. R. Landa
Department of Soil Science
Oregon State University
Corvallis, Oregon 97331
W. K. Lauenroth
Natural Resource Ecology Laboratory
Colorado State University
Fort Collins, Colorado 80521
J, J. Lee
U.S. EPA/CERL
200 SW 35th Street
Corvallis, Oregon 97330
J. W. Leetham
Natural Resource Ecology Laboratory
Colorado State University
Fort ColliAs, Colorado 80521
W. C. Leininger
Department of Animal and Range Sciences
Montana State University
Bozeman, Montana 59715
xvi 11
-------
G. M. Lerfald
U.S. Department of Commerce
NOAA
Environmental Research Laboratories
Boulder, Colorado 80302
J. C. McFarlane
U.S. EPA/EMSL
P.O. Box 15027
Las Vegas, Nevada 89114
T. J. McNary
Natural Resource Ecology Laboratory
Colorado State University
Fort Collins, Colorado 80521
G. T. McNice
U.S. Department of Commerce
NOAA
Environmental Research Laboratories
Boulder, Colorado 80302
G. E. Neely
U.S. EPA/CERL
200 SW 35th Street
Corvallis, Oregon 97330
J. O'Loughlin
Environmental Studies Laboratory
University of Montana
Missoula, Montana 59801
T. R. Osberg
U.S. EPA/EPIC
Vint Hills Farm Station
Box 1587
Warrenton, Virginia 22186
W. J. Parton
Natural Resource Ecology Laboratory
Colorado State University
Fort Collins, Colorado 80521
E. M. Preston
U.S. EPA/CERL
200 SW 35th Street
Corvallis, Oregon 97330
R. F. Pueschel
U.S. Department of Commerce
NOAA
Environmental Research Laboratories
Boulder, Colorado 80302
L. H. Pye
Environmental Studies Laboratory
University of Montana
Missoula, Montana 59801
P. M. Rice
Environmental Studies Laboratory
University of Montana
Missoula, Montana 59801
R. D. Rogers
U.S. EPA/EMSL
P.O. Box 15027
Las Vegas, Nevada 89114
J. E. Taylor
Department of Animal and Range Sciences
Montana State University
Bozeman, Montana 59715
R. M. Tetley
Department of Botany
Oregon State University
Corvallis, Oregon 97331
S. K. Thompson
U.S. EPA/CERL
200 SW 35th Street
Corvallis, Oregon 97331
G. L. Thor
Natural Resource Ecology Laboratory
Colorado State University
Fort Collins, Colorado 80521
P. C. Tourangeau
Environmental Studies Laboratory
University of Montana
Missoula, Montana 59801
C. C. Van Valin
U.S. Department of Commerce
NOAA
Environmental Research Laboratories
Boulder, Colorado 80302
D. B. Weber
U.S. EPA/CERL
200 SW 35th Street
Corvallis, Oregon 97330
xix
-------
D. E. Weber
U.S. EPA/CERL
200 SW 35th Street
Corvallis, Oregon 97330
D. L. Wellman
U.S. Department of Commerce
NOAA
Environmental Research Laboratories
Boulder, Colorado 80302
J. P. Wiggins
Department of Biology
The College of Wooster
Wooster, Ohio 44691
R. G. Woodmansee
Natural Resource Ecology Laboratory
Colorado State University
Fort Collins, Colorado 80521
R. G. Wilhour
U.S. EPA/CERL
200 SW 35th Street
Corvallis, Oregon 97330
xx
-------
ACKNOWLEDGEMENTS
Many individuals have contributed to the preparation of this document.
The editorial assistance of Susan With, Karen Randolph and others is much
appreciated.
Our work could not proceed without the help and support of the people of
southeastern Montana, especially the ranchers on whose land we are working and
the personnel and persons residing at and near Fort Howes Ranger Station,
Custer National Forest. The Kluver's and the McRae's have been particularly
supportive.
xxi
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ECOLOGICAL EFFECTS MONITORING IN THE COLSTRIP VICINITY
-------
SECTION 1
AEROSOL CHARACTERIZATION IN THE VICINITY OF
COLSTRIP, MONTANA
C. C. Van Valin, R. F. Pueschel, D. L. Wellman,
N. L. Abshire, G. M. Lerfald, and G- T. McNice
ABSTRACT
Both natural aerosols and those generated by the
coal-fired power plant at Colstrip, Montana, were
studied over a three-year period from 1975, before the
power plant was operational through 1977 when it was
in full operation. A multi-sensor approach was
employed which included complete particle and gas
analysis from ground-based and airborne laboratories
supported by a variety of remote sensing devices
(laser radar, acoustic sounder, and solar photometry).
The background aerosols were found to consist of
irregular-shaped particles, primarily alumino-silicates
with relatively high concentrations of the metallic
elements for a rural area. Aerosols generated by the
power plant were relatively large (approximately 1 ym),
glassy, alumino-silicate spheres with a high incidence
of calcium and sulfur when collected in the plume near
the power plant, becoming smaller (<.4 ym) sulfur-
containing spheres at large distances downwind. The
elemental shift to sulfur is attributed to a gas-to-
particle conversion process. These artificial aerosols
increased the available ice-nuclei concentration by an
order of magnitude, which could be significant to the
formation and distribution of precipitation. As the
plume traveled downwind, even under a stable tempera-
ture inversion layer, it was found to break up into
inhomogeneous parcels.
INTRODUCTION
This program is designed to characterize the aerosol content of the
Colstrip power plant plume and to aid the U.S. Environmental Protection
Agency at Corvallis, Oregon, in the assessment of its impact on the eco-
system. Particles emitted by coal-fired plants (e.g., ash), or formed from
-------
gases emitted (e.g., sulfates or chlorides) produce an array of effects on
the ecosystem. They may produce direct biological effects through contact
with leaves and soil; they may affect solar radiation reaching the biosphere
by absorption and blanketing mechanisms, thus altering surface temperatures.
Aerosol properties such as solubility, crystalline formation, size, shape,
surface structure, and chemical composition will bear on the formation and
distribution of rain, snow, and hail, either near the source or far downwind,
depending on the temperature structure (inversions) and on mixing and diffu-
sion characteristics of the atmosphere downwind from the source.
Small particles are an especially significant part of the pollution
emitted by fossil fuel power plants, even when the stack emission has been
carefully filtered (we exclude, for this report, water droplet clouds and
fogs from the term aerosols) . Aerosols may range from a cluster of a few
molecules to particles several tens of micrometers across. The larger
aerosol particles fall out rapidly and are not frequently observed in the
atmosphere except in the immediate vicinity of their source. However,
particles up to several micrometers in diameter may remain suspended in the
atmosphere for long periods, up to weeks or months. Thus, if stack filters
are not effective in removing small particles, the plume may produce sig-
nificant pollution which may accumulate in the vicinity, or may be swept by
winds over long distances.
MATERIALS AND METHODS
In order to determine the amount of such material, its source, its
distribution in the atmosphere, its composition, its size and shape distribu-
tions, the effects of weather conditions on its formation and its effect on
the high plains heat budget, it was necessary to use a combination of remote,
in-situ and airborne sensors, before and after contamination by the power
plant, and over sufficient time to obtain representative averages. These
sensors were contained in a mobile atmosphere characterization laboratory,
an airborne atmospheric characterization laboratory, and a mobile remote
sensing laboratory, all of which were described in detail in the Third
Interim Report (Abshire et at. , 1978).
The observation schedule was established to bracket the high plains
growing season each year with two intensive measurement periods, roughly
centered about June 1 and September 1. The specific intervals are:
Year Spring Fall
1975 18 May - 15 June 17 Aug - 15 Sept
1976 21 May - 5 June 20 Aug - 11 Sept
1977 21 May - 4 June 20 Aug - 4 Sept
During 1975, the power plant was not in operation so that this data repre-
sents clear air baseline, as previously described (Abshire et al.., 1978).
In 1976, the plant was in intermittent operation, and in 1977, it was in full
operation.
-------
The ground-based equipment was located at Hay Coulee, 12 kilometers
southeast of Colstrip, during most of the measurement periods, the only
exception occurring during the second week of the fall 1977 experiment, when
the remote sensing laboratory was moved to the top of a butte, four kilo-
meters southeast of the plant (the Battelle No. 1 site).
The airborne laboratory recorded data over most of the area within a
50-kilometer radius of the power plant, either operating in the plume or in
response to the requirements of the two ground-based laboratories.
RESULTS AND DISCUSSION
Atmospheric Characterization Laboratories
The aerosol content of the plume and its vicinity was classified accord-
ing to number, size, shape and elemental composition. This classification
permits distinction between combustion-produced aerosols, which for energetic
reasons must be small and spherical, and naturally-formed particles that need
not be spherical, and that have a preferred size range of 0.6 to 1.0 ym
diameter. Furthermore, the elemental composition of the particles hints
toward the types of compounds that are formed and their water solubility.
These properties determine the effects of the aerosol on visibility, on the
colloidal stability of clouds, and eventually on amounts and frequency of
precipitation.
Parameters Measured
Measurements of meteorological and aerosol parameters begun during the
two 1975 observation periods at Hay Coulee were continued. Wind direction
and velocity, temperature, relative humidity, light scattering coefficient
(bscat)» total aerosol population (Aitken nuclei (AN)) and solar energy
received, were measured continuously. Nuclepore membrane filters were
collected at specified times; ice nuclei (IN) collected on the filter were
measured in a thermal diffusion chamber and selected filters were examined
in the scanning electron microscope with an energy dispersive x-ray accessory
(SEM-EDX) to determine the elemental composition of individual particles.
The acoustic ice nucleus counter was also utilized to measure IN concentra-
tions. Cloud condensation nuclei (CCN) were measured at specified times with
the thermal diffusion chamber-photographic method.
Instruments carried by the aircraft, a Cessna 206 six-place single
engine, high-wing airplane, were utilized to measure temperature, relative
humidity, AN, bScat> ozone (03), nitric oxide (NO), nitrogen dioxide (N0£),
and sulfur dioxide (S02) continuously during the flight. Filter samples were
collected for subsequent analysis for IN and for particulate properties by
SEM-EDX. CCN were measured by the thermal diffusion-photographic method.
Observations
The Colstrip power plant was in limited operation for only two or three
days during the period 21 May - 5 June 1976. In consequence, the measure-
ments mainly reiterated the findings of the 1975 field periods (Schnell et
-------
al.t 1976; Parungo et aZ., 1978; Pueschel et aZ., 1974; Van Valin &t
1976), i.e., the natural aerosol is relatively abundant in the metallic
elements and is therefore slightly more effective in the ice nucleation than
is the natural aerosol in most other locations that we have investigated; the
CCN concentration is generally within the range of 500-1000 cm~3, and bsc
is typical of clean environments.
The period 28 August - 11 September 1976 was dry, with warm days and
cool nights. During the night the winds were light and variable; daytime
experienced wind velocities of 2 to 6 m sec"1, predominantly westerly. Rela-
tive humidity increased to maxima just before sunrise, typically reaching 80
percent. Coincident with the maxima in relative humidity were maxima in
bscat; During eleven successive 24-hour periods, the average maximum was
1.27 X 10~4m~l and the average minimum was 0.36 X 10~4m~l; bscat was, on
the average, 3.5 times greater during the time of highest relative humidity
than during the period of lowest relative humidity (Figure l.la). It is
not reasonable to believe that the aerosol character changed from night to
day, and this is therefore interpreted as evidence of a rather hygroscopic
aerosol population, with optically effective particle size increasing, during
periods of higher humidity, from absorption of water. This is supported by
the finding of high concentrations of Cl- and S-containing particles (Figure
1.2). Both elements form anions that can lead to water soluble substances.
The day-to-night variation in bscat was much less extreme during the two
study periods of 1977, being about a factor of two, on the average, with
approximately equal minimum values. Figures l.la, b, and c are the record
for the continuously measured parameters during 20 August - 10 September
1976, 20 May - 4 June 1977, and 20 August - 3 September 1977, respectively.
Figures 1.2 and 1.3 are derived from SEM-EDX examination of filter
samples collected in the mobile laboratory at Hay Coulee and with the air-
borne laboratory in the vicinity of Colstrip and Hay Coulee on May 27 and 29,
1977. On May 27, Hay Coulee experienced a fairly intense plume fumigation,
as shown by the increase in AN to 6.0 X lO^cm"3, as compared to a background
concentration of 3.2 X 103cm~3 (Figure l.lb). Hay Coulee had not, to our
knowledge, experienced any plume exposure on May 29, 1977. Therefore,
samples were collected from these two days that were to provide pre-exposure
and during-exposure samples on the day of fumigation, plus samples collected
at similar times-of-day on a non-exposure day, as well as some aircraft
samples over Hay Coulee and in the plume close to Colstrip. In all cases
except one, 75 particles were examined on each filter; the May 29 Air #5B
sample was so lightly loaded that 75 particles could not be found within the
prescribed 1 mm2 part of the filter. The particles were classified according
to diameter in ranges 0.1 - 0.4 ym, 0.6 - 1.0 ym, and 1.5 - 10.0 ym, and
according to shape, whether spherical or irregular. As it turned out, this
sample selection yielded considerably more information and understanding of
plume behavior and composition than we had expected, as well as posing some
questions regarding particle origin that we have not yet answered. The May
27 Ground //I and Air //I analyses show, because of their similarity, that
these samples were collected in the same air mass. An unanswered question
in connection with these two samples is: why do these samples contain so
many spherical particles, 31 and 45 percent, respectively, when the available
-------
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AU6 27.76 HAY COULEE
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AUC 28.76 COLSTRIP
°0. 2. 4. 6. 8. 10. 12. 14. 1C. 18.20.22.24.
AUS 28.76 HAY COULEE
Figure l.la.
Continuously measured parameters at Hay Coulee, August 27
September 7, 1976. Reading from right to left, vertical
scales on the left of each graph refer to plots numbered
1, 2, 3, and 4 respectively. The 'horizontal scale refers
to Mountain Daylight Time.
-------
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AUS 30.7S HAY COULEE
Figure l.la. Continued.
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AU6 31.7S COLSTRIP
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SEP 5.76 COLSTRIP
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Figure l.la. Continued.
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SEP 4.76 CXSTRJP
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SEP 4,76 HAY COULEE
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SEP 5.76 HAY COULEE
Figure l.la. Continued.
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SEP S.7S HAY COULEE
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Figure I.la. Continued.
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MAY 20.77 HAY COULEE
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MAY 21.77 HAY COULEE
Figure l.lb.
Continuously measured parameters at Hay Coulee, May 20 -
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to Mountain Daylight Time.
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MAY 25,77 COLSTRIP
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MAY 25,77 HAY COULEE
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Figure l.lb. Continued.
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MAY 26.77 COLSTRIP
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MAY 2«.77 COLSTRIP
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HAY 31.77 COLSTRIP
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JUNE 5.77 COLSTHIP
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JUNE 4,77 COLSTKIP
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JUNE 4,77 HAY COULEE
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AU6 21,77 HAY COULEE
Z. 4. C. I.II.ll.14.lt.It.tl.«.14
AUC 11.77 HAY CPM.EE
Figure l.lc.
Continuously measured parameters at Hay Coulee, August 20 -
September 3, 1977. Reading from right to left, the vertical
scales on the left of each graph refer to plots numbered
1, 2, 3, and 4 respectively. The horizontal scale refers
to Mountain Daylight Time.
25
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AUG 22-23,77 HAY COULEE
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Figure l.lc. Continued.
26
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AUS 23,77 HAY COULEE
t. 2. 4. t. I. 10.12. 14. 1C. II. «. 22.24.
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Figure l.lc. Continued.
27
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AU6 25.77 HAY COULEE
t. 2. 4. C. 8.10. f2. 14. It. II.1C.ZZ.14.
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Figure l.lc. Continued.
29
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2. 4. 6. «. 10.12. 14. IS. 11.20.22.24.
AUS 28.77 HAY COULEE
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Figure l.lc. Continued.
30
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Figure l.lc. Continued.
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Figure l.lc. Continued.
32
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2. 4. 6. 8.10.12.14.16.18.20.22.24.
SEP 2.77 HAY COULEE
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vb. 2. 4. S. 8.10.12.14.16.18.20.22.24.
SEP 3,77 HAY CO'JLEE
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SCP 1.77 HAY COW.II
Figure l.lc. Continued.
33
-------
May 27. 1977
COLSTRIP 2
Ground ttl
!»|l".' P S Cl I It'- Ctli'cll
0553 0653 MOT
903 nib Hay Coulee
30 sec Scan
ft (mien
30 paltks HI 04/im
30 panties 06 I 0 ^m
IS 10.0 /, :n
08
52n sjtenU Mrt«*s 02 10.0 /im
COLSTRIP 2
May 27, 1977 Ground a3 140B 1529 MOT
Hurdle 01 100 ^m
.' . ; I [111 Ctlltl!>
1 ml|IISi f S 0 » Clli CfMilibU
01 0.4
OS 10
IS pttles IS 100
3« sfkcoul fjrtcks HI 10
BO
E 40
May 27 1977
COLSTRIP 1
Air a ] 0726 074) MOT
4100' over Hay Couler
01 101) un-
*> it 11 it
^liLI flJL
untili ''.;••:•.' Milt ,'>
11 iilist 7 I 01 tifi"ti»iTih
at
£ "
a.
90
>.«MI ; t s ti i,. • . «i •• •!
15 uttete
0:4 ,
86
IS
lilllli r i ti i ClliCill'lil
Figure 1.2.
SEM-EDX derived classification of aerosol samples collected on membrane filters that
were collected at Hay Coulee field site and with the aircraft over Hay Coulee on May
27, 1977. The top bar graph shows the elemental occurrence in the 75 particles that
were examined. The next three graphs, reading downward, show elemental occurrence in
the particles as classified according to particle diameter. The bottom two graphs
show elemental occurrence in the particles as classified according to particle shape;
the inclusive size ranges are shown for all particles in these two shape classifi-
cations .
-------
. May 29. 1977
CDLSTRIP 2
Ground #1 0554 0713 MOT
911 mb at Hay Coulee
LI-
lll| lit: F I 0 I ClllCf ••'•!•
1.1 14
1.1 II n •
i i III
I)
14
May 29. 1977
COLSTRIP 2
Ground #2
1202 1351 MOT
t i (i i
o m«i id, » i Cl I Cite t< life I. an
n
«• fl
f I (I t Clt>
01
a
»i*|iiSi ' ',.:.>'.
JULU
pride I)
oirte 0.1
3d Mrtete D.S I.I ^m
15 prate 15 11.1 ^m
! spbencal prtcto 01 ?0.um
41 ••
01 100
r •. ; i Cl'i f. t,i, t ;,,,
Figure 1.3. Same as for Figure 1.2, but, for samples collected May 29, 1977 at Hay Coulee
field site (Ground //I and #2), with the aircraft in the power plant plume
near Colstrip, and with the aircraft over Hay Coulee, respectively.
-------
uo
to
40
n
ii 1 rt
-
-
r-M R-,
hiM;r -. f i • s till Ci ».i!' •'"
4fl
-
•
P S Cl R Cili
n
00 in
c 40
-5
o P S C
»)»l»ISi P S Cl « Csli CiHn'eHiZn
19 particles 01 114 /j.m
30 particles 06 10 p.m
15 particles 15 10 0 /j.m
3 spherical particles 0.1 0 6 p.m
61 non srjtiefical particles 01 • 10.0 /j.m
Figure 1.3. Continued.
-------
evidence shows that there was no connection with the power plant plume? The
unusually high incidence of Cl in the spherical particles is also puzzling
but may be indicative of some source other than the coal-burning power plant.
The May 27 Ground #3 sample was collected during the fumigation; spheri-
cal and irregularly-shaped particles appear in equal numbers. The elemental
composition of the non-spherical particles is typical of natural aerosols
collected at Hay Coulee. Almost all of the spherical particles contain S,
in fact, some 60 percent contain nothing but S (considering detection only
for Na and heavier elements). It is obvious in this sample, and apparent
to a lesser degree in all the other examples shown here, that almost all of
the spherical particles are found in the smallest size range.
Unexpected information was provided by SEM-EDX analysis of the May 29
samples. Both of the ground samples were almost identical to the Hay Coulee
fumigation sample of May 27, i.e., approximately half of the particles were
spherical, were in the smallest size range, and of these, on the order of
60 percent contained S. Subsequent examination of the instrumental record
disclosed no obvious indication of plume fumigation, but the wind direction
was northwesterly, although variable, and the AN concentration did exceed
1.2 X 10^cm~3 in sporadic episodes during the day.
The May 29 Air //I sample was collected in the plume about 1.6 kilometers
from the power plant. Here, two-thirds of the particles were spherical, with
a larger average diameter than for the spherical particles collected at
greater distances from the power plant. Almost all the spherical particles
contained both Si and Ca, with only about half containing S. The striking
difference of elemental composition of spherical particles collected at 1.6
kilometers downwind as compared with that at a distance of 12 kilometers
leads one to surmise that the particles that were in the plume at the shorter
distance had all settled out by the time (one to three hours) that part of
the plume reached Hay Coulee, and that these glassy mineral spheres had been
replaced by ^$04 or (NH4)2S04 particles that were the result of S02 oxida-
tion, with subsequent gas-to-particle transformation. This hypothesis is
supported by airborne measurements. Two examples can be cited at present:
(1) On August 27, 1977, between 0925 and 1035 MDT, measurements made in
the plume (Figure 1.4) showed by far the greatest amount of light scattering
at the shortest distance downwind. bscat at greater distances was much less,
with an indication of further decline with increasing distance. A less
notable maximum followed by reduction of concentration with distance was
measured for NO and N02. However, measurements of AN showed much higher
(as much as an order of magnitude) concentrations at the greater downwind
distances.
(2) On September 1, 1977, plume measurements were done to a distance
of 50 kilometers downwind (near Ashland, Montana). AN concentrations were
similar, at this distance, to concentrations measured at shorter distances,
with the consequent requirement for the formation of particles to compensate
for dilution as the plume expanded. We estimate the particle formation rate
at lOllsec-1 in the plume, on the basis of the AN concentration measurements
and attempts to measure width and depth of the plume. Plume dimension
37
-------
I01
27 Aug 77
Airborne Measurements
Ceiling 1150m AGL
Intermittent Light Rain
Altitude =6I5± 130m AGL
0925 0935 0945 0955 1005 1015 1025 1035
MDT
Figure 1.4.
AN, bscat, NO, NC>2 measurements with the air-
craft in the Colstrip power plant plume.
38
-------
measurements are very difficult at any distance greater than 15 kilometers
because the plume becomes very patchy, and is also nearly invisible- it is
detectable only by means of particle and gas measuring instruments.' Hence
the imprecise nature of this estimate must be appreciated. This rate of
particle formation is several orders of magnitude lower than that found in
the smoke plume from the Four Corners power plant in northwest New Mexico
(Pueschel and Van Valin, 1978).
The unexpected finding of plume particles in the Hay Coulee filter
sample on May 29, 1977 prompted us to make a retrospective examination of
the continuous AN concentration record of the last measurement period for
evidence of plume exposure at Hay Coulee. Table 1.1 is a compilation of the
pertinent information. We have listed all times when the AN concentration
increased to at least double the level before and after. Episodes that, in
our judgment, represented plume exposure are indicated by a "P" in the left-
hand column. Any examples of steady AN concentration readings were inter-
preted as being due to natural causes not related to the plume; this kind
of variation in AN concentration is common. Plume exposure was judged to
have occurred when changes were large in comparison to the background, were
abrupt, and were ^individually of short duration. On this basis, Hay Coulee
seems to have experienced plume exposure 21 different times for a total of
about 30 hours out of 340 hours of observation from 1300 MDT, August 20 to
1700 MDT, September 3, 1977. CCN and IN concentrations and bscat are also
listed in Table 1.1 whenever measurements were taken during an episode of
elevated AN concentration; in addition, for comparison we have included many
examples of CCN, IN, and bscat levels when the AN concentrations were normal
background. CCN levels seem not to be correlated with AN, but IN measure-
ments with the continuously operating acoustic counter show IN concentrations
to be five times or more above normal levels when plume parcels were present.
The IN concentration by the filter method was much less correlated to plume
presence; this method utilizes an integrated sample collected for one hour,
and may be poorly suited to the short-lived episodes of exposure that occur
at Hay Coulee. Also, these two methods of IN measurements respond to
different mechanisms of ice crystal formation. While the predominant
response to the acoustic counter is to contact nucleation, the nucleation
and growth process of ice crystals on the filter is determined by the
deposition or condensation-followed-by-freezing mechanisms. Which of these
two mechanisms predominates on the filters depends upon the water solubility
of the IN and upon the super-saturation with respect to water within the
thermal diffusion chamber where the filters were developed.
Figure 1.5a shows the record of AN and CCN concentrations at Hay Coulee
on August 23, 1977, during an unmistakable plume strike from 0828 to 0845
MDT, a lesser exposure from about 1000 to 1010 MDT, and for the following
time beginning at 1040 MDT, when there was no plume exposure, but the AN
concentration reached a maximum of 2.8 X 10W3. During exposure, the AN
concentration reached 4.8 X loW3, the IN was off scale on the hlgh side,
and the patchy nature of the plume is indicated by the fact that, between
pulses, the AN concentration fell almost to normal background levels.^ Figure
1.5b shows the record of AN measurements made with the instrumented aircraft
39
-------
Table 1.1. AEROSOL PARAMETERS MEASURED AT ILAY COULEE SITE, 20 AUGUST to 3 SEPTEMBER, 1977.
Wind
Elevated AN Direc- Velo- Other, AN CCN Filter Method Acousti
AN Concen. Max. Concen. Character of tion city Time of Avg. Concen. scat No. of Average No. of Concen. Concen.
Pate Begin End (X 103cm~3) AN Elevation msec"1 Measurements (X 103cm-l) (X KrV"1) Meas. (cm'3) Meas. (XT1) (I'1)
P
P
8-20 2100 2400
8-21 0000 0630
8-21
8-21 1200 1700
8-21 2240 2400
8-22 0000 0200
6.8 Intermittent calm
7.8 Continuous, calm
steady, gradu-
ally declining
0855-1025 2.2 1 3.1
24.0 Continuous, Ig. N 3 5 602 ± 295 2 2.3 >10
variation
4.1 Continuous, calm
variable
7.3 Continuous, calm
8-22 0345 0430
8-22
P 8-22 1406 1515
P 8-22 2107 2230
P 8-23 0828 0854
P 8-23 1000 1010
8-23 1040 1900
8-24 0800 0900
8-24
8-24 1820 2120
8-25 0020 0120
P 8-25 0636 0639
P 8-25 0810 0900
F 8-25 1009 1047
8-25 1058 1730
8-26 0000 0940
8-26
8-27
P 8-27 1500 1530
5.0
steady, declin-
ing gradually
Continuous, steady calm
20.0
10.0
48.0
10.0
28.0
8.0
7.8
5.1
8.8
8.5
10.0
46.0
8.0
4.4
Continuous ,
several pulses
Continuous, sev-
eral pulses first
Many strong pulses
Weak pulses
Continuous, steady
Gradual rise &
fall
Continuous, steady
Continuous, steady
Weak pulses
Continuous ,
variable
Continuous,
variable
Continuous ,
variable, thun-
derstorm @ 1730
Continuous, steady
Continuous ,
variable
NNE
N
calm
NW
N
N,NE
SW
NW
NNW
WNW
N
NNW
4 0622-1110 1.9
3
2
3
3
2
1010-1155 2,6
<2
7
3
6
4
variable
gusty
It & variable
WNW
1000-2400 2-3
1235-1445 2.0
3
4
4
2
14
2
4
4
2
2
5
3
.6 6
.48 2
472 ± 258 2 10.3
577 ± 231 1 7.8
1260 1 5.5 >10
1130 ± 494 2 5.4 2.0
525 2.0
578 ± 372
385 ± 305 1 8.6
1 1.6
490
460
434 ± 264 2 6.6 4.0
1190 1 3.8
1 2.7
338 ± 205
840
-------
Table 1.1. Continued.
Date
P 8-27
8-27
P 8-27
8-28
8-28
8-28
8-28
8-29
P 8-29
8-29
8-30
8-30
P 8-30
P 8-30
8-31
8-31
P 8-31
9-1
P 9-1
P 9-1
P 9-1
9-1
9-2
9-2
9-3
P 9-3
P 9-3
Elevated - AN
AN Concen. Max. Concen.
Begin End (X 103cm~3)
1653
2230
1310
1605
1830
1840
2030
1530
1000
1113
1448
2200
0000
1043
1300
1725 5.3
2300 7.6
1500 10.0
1830 15.0
2300 10.0
1905 8.0
2120 6.5
1655 6.0
1057 6.4
1234 11.1
1830 6.3
2400 6.9
0600 7.4
1200 19.2
1445 15.0
Wind
Direc- Velo-
Character of tion city
AN Elevation msec"!
Continuous,
variable
Continuous,
variable
Continuous,
steady
Continuous,
variable
Continuous,
steady
Intermittent
Intermittent
Intermittent
Continuous ,
variable
Continuous,
variable
Intermittent
Continuous, s
Continuous, s
ground fog
Continuous ,
variable
Continuous,
variable
N 6(G18)
W <2
It. & variable
NNW 4
It. & variable
NW 10
NNW 8
NW 3
NW 4
NNW 6
NNW 4
teady It & variable
teady, calm
NNW <2
NNW <2
Other, AN
Time of Avg. Concen.
Measurements (X 103cm-l)
1800-2000 1.0
0200-0600 1.5
0805-1145 2.8
1800-2400 2,0
1300-1600 3.0
0200-0600 1.5
0825-1720 3.0
0400-0600 1.8
0720-1445 2.6
0200-0400 0.8
0720-1210 2-3
0000-0600 1.8
scat
(x lo-V-1)
.48
.47
.45
.50
.51
.65
.51
.60
.65
.52
.50
.55
.55
.55
.51
.57
.58
.55
.58
.55
.58
.65
.75
.60
.62
.70
.65
IN IN
CCN Filter Method Acoust
No. of Average No. of Concen. Concen
Meas. (cnT3) Meas. (JT1) (JT1)
18 560 ± 206
2 500 1 5.3
4 525 ± 185
6 1162 ± 379 1 3.5 10
14 535 ± 304
2 1470
12 478 ± 191 2 10.4
2 810 10
2 600 >10
2 910 >10
6 630 ± 153 1 4.6 >10
2 770 2 4.7
1 9.7
-------
E
o
V
% 10'
HAY COULEE - 23 AUG. 1977
E-t Aitken Nucleus Counter
06
« 6
o
z 4
O>
o
2
0,
08
Lr
NCAR Acoustic Ice Nucleus Counter
J L
06
12
MDT
ro
E
o
o>
o
AIRBORNE-OVER HAY COULEE
23 AUGUST 1977
5_
10'
103L-
:30
75m AGL , 320m AGL
In Plume
Out of Plume
I
8:40
8:50 9:00
Time MDT
9:10 9:20
Figure 1.5a. (TOP)
AN and IN concentrations measured at Hay Coulee
showing power plant plume exposure from 0828 to
0854 MDT, and from 1000 to 1010 MDT.
Figure 1.5b
(BOTTOM) AN concentration measurements with the aircraft
during the time of the Hay Coulee plume exposure.
The elevation of the ,Hay Coulee site is 930 m MSL.
42
-------
over Hay Coulee, both within and outside of the plume. These measurements
are entirely consistent with, and supportive of, the measurements at the
mobile laboratory in Hay Coulee.
Remote Sensing Laboratory
Measurements from Hay Coulee
The ground-based and airborne atmospheric characterization laboratories
were supported by the remote sensing laboratory as described in the Third
Interim Report (Abshire et al, , 1978). The laser radar (lidar) system
measured optical backscatter coefficients throughout a hemispherical volume
of three-kilometer radius. A complete set of measurements was recorded every
hour on the hour; continuously whenever the aircraft was in the area; and at
any other time there was an indication of plume activity. The effluent
directly above the power plant was also probed from Hay Coulee, but the most
interesting periods—before the daily breakup of the temperature inversion—
were generally unavailable due to the intervention of a ridge into the line
of sight between Hay Coulee and Colstrip. Average backscatter values within
the lowest 500 meters are shown for each day in Table 1.2. Above 500 meters,
backscatter values approaching clear air molecular scattering were usually
obtained. Backscatter values frequently doubled in a series of short epi-
sodes indicating a plume strike or close approach, but there were seldom
periods of prolonged high backscatter.
The lidar was usually operated in a dual polarization mode which allowed
it to separate the backscatter of spherical particles, such as found in the
power plant plume, from irregular particles, such as found in strip mine
dust. The system was operated in a dual wavelength mode at 0.6943 urn and
at 0.3472 ym, on September 3, 1977. Comparison on simultaneous backscatter
values at the two wavelengths contains information regarding particulate
size distribution, which is important in the determination of fallout rates.
Reduction of the dual wavelength data was not completed in time to be
included in this report.
The acoustic sounder was operated continuously during each observation
period, providing a record of the existence and height of the temperature
inversion. The usual pattern was observed with an inversion forming about
midnight and breaking up during the mid-morning hours. Occasionally surface
cooling from rain showers would cause the inversion layer to form before
sundown and persist through the night into the next morning. The times
during which a temperature inversion was detected are also shown in Table
1.2.
All of the solar photometry described in the Third Interim Report
(Abshire et al., 1978) was continued. In 1976, the following instruments
were added:
(a) An infrared pyrheliometer with bandwidth 8-12 ym.
(b) An eight-channel photometer with channels each 0 01 ym wide and
centered at 0.305, 0.317, 0.338, 0.382, 0.501, 0.875, 0.914, and 1.062 ym.
43
-------
Table 1.2. SUMMARY OF 1977 REMOTE SENSING DATA
Average Daily
Optical Backscatter
Temperature
Inversion Times
Day
141
142
143
144
145
146
147
149
150
151
152
153
154
155
232
233
234
235
236
239
240
241
242
243
244
245
246
247
Date
May 21
May 22
May 23
May 24
May 25
May 26
May 27
May 29
May 30
May 31
June 1
June 2
June 3
June 4
Aug. 20
Aug. 21
Aug. 22
Aug. 23
Aug. 24
Aug. 27
Aug. 28
Aug. 29
Aug. 30
Aug. 31
Sep. 1
Sep. 2
Sep. 3
Sep. 4
in lowest 500 m
Morning Evening
(m~lster~l) Breakup Formation
5.7 X 10~7
5.6 X 10 '
4.1 X 10 '
5.8 X 10~'
6.4 X 10 '
4.0 X 10 '
3.0 X 10 '
3.8 X 10 '
3.2 X 10 '
3.2 X 10 '
4.2 X 10~'
6.4 X 10~'
— "O
1..3 X 10 "
4.2 X 10
5.3 X 10~7
6.6 X 10 '
6.4 X 10 '
5.2 X 10~'
4.7 X 10 '
3.6 X 10 '
3.3 X 10 '
4.7 X 10 '
3.2 X 10 '
3.3 X 10 '
3.6 X 10~'
4.2 X 10 '
4.0 X 10 '
6.8 X 10
0900
0830
1100
1000
1400
0900
0830
0900
1000
1030
1130
0930
0900
0930
0930
0900
1100
0900
1030
0600
No
No
0900
No
0930
0930
1130
MST 2200 MST
2100
2300
2200
1830
1730
2200
2400
2200
2100
2230
2400
2300
None
0100*
2200
1830
2000
0100*
1700
Inversion
Inversion
2130
Inversion
0130*
2100
None
No Data
Location
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Hay Coulee
Top of Butte
Top of Butte
Top of Butte
Top of Butte
Top of Butte
Top of Butte
Top of Butte
Top of Butte
Top of Butte
•k
Next Day
44
-------
Figure 1.6 shows a plot of optical depth derived from the 8-12 ym infrared
photometer. Knowledge of infrared optical depth, combined with measurements
at visible wavelengths, contains information relating to scattering charac-
teristics of clouds and aerosols and permits estimation of heat loss by
infrared radiation from the ground.
The wavelength bands of the eight-channel photometer were chosen to
provide data on the total water vapor in the sun-instrument path, (0.941
and 0.875 urn), total ozone content (0.305, 0.317, and 0.338 ym) and the size
distribution of aerosol particles in the path (0.338, 0.382, 0.501, 0.875,
and 1.062 ym).
An instrument which measures the angular distribution of radiation at
angles up to eight degrees from the sun was added in the spring of 1977.
The shape of the intensity variation as a function of angular distance from
the sun's center (solar aureole variation), varies with the size of scatter-
ing particles in the sun-instrument path. Thus, measurement of this angular
variation can be used to deduce the size distribution of aerosols, including
cloud particles for at least thin clouds. Figure 1.7 shows plots of the
angular scattering function under a variety of conditions. The results
obtained for the aerosol size distribution from the multi-wavelength photo-
meter measurements are directly related to those obtained from solar aureole
measurements.
Theory indicates that solar aureole measurement should work best to
determine size distributions of larger particles (e,g., >0.5 urn), while
multi-wavelength photometric measurements may be the best method of deter-
mining size distributions of smaller particles (e.g., <2 ym) . The two
methods are therefore likely to complement one another and should give
results that are in agreement in the region of overlap.
Photographic records of sky conditions using wide-angle time-lapse
photography have been obtained for each of the Colstrip experiments beginning
with Spring 1976. This photographic record has proven extremely valuable
in the determination of cloud types, geometry, and motions, or the presence
of dust, smoke or any other conditions which might affect the observations.
Clouds are mainly composed of larger particles, either water droplets
or ice crystals. They generally affect the infrared radiation more than
the visible wavelengths. Thin clouds, such as cirrus, and white broken^
cumulus do not result in significant reduction in total incoming radiation
when averaged over time (say, an hour) because scattering and reflection
compensate for the reduction in the direct component. A completely overcast
sky with the sun's disc not discernible usually results in the incoming
radiation being in the range of 15 percent to 25 percent for a clear day.
Only very preliminary analysis has been done on the 1977 spring and fall
Colstrip solar photometry data. If these data are analyzed and compared to
the 1975 and 1976 data, it should be possible to determine quite precisely
the effects of the Colstrip power plant and the mining operations on the in-
coming solar spectrum. (Particular emphasis should be given to the 1977
fall data which were taken from the butte, nearer the power plant.)
45
-------
10,
CO
00
Q_
CD
DAY - r«« FHin :,3t. ro loi"
CHANNEL • 3
IOt_AM . 0 l6/CK)f T
DIVISOR • 101 CXXiO
POLY REDUCTION C(«-l 'S
-O 4ICKXM- «
0 IOXKH- -3
O OOOOO O
V-LARCE - 10 O
V-SHALL • -O ^
FIRST SLIDING AWRAOE UINDOU SIZE -
SECOND SLIDING AV(-HACE UINDOU SIZE -
PLOTTING RESCX U1 ION - 6O
0
oe or oe
Figure 1.6,
O9 10 11 12 13 M 15 1* 17 18 1» 20
TIME MST
Optical depth derived from the infrared pyrheliometer,
-------
10
Solar Aureole Photometer
10
tf)
c
10
-6
IP i'
|rt If
•a
a>
N
^ 10'
£
l_
o
\\
10
•8
2
-12'
8 -4'
Above Sun
0
4 8°
Below Sun
12
Key;
1 Th.in Strat.ur; cloutJ-haDo around
rjuij w:ii.h red l>onndary at; 3 r'v
Mos1;ly clear r.ky v;.i.t,h f;hln, tur
bulent wave clour] Gtrands barel
visible,
/i
-f'loro-ln -aureole J'l-t vj nlbl.o
due l.o vory t;hi.n ;;',ratus Blonds.
Aerosol h-n7f! r^con ox; I to ne
d °f" rofj s
Figure 1.7. Examples of solar aureole angular scattering functions
47
-------
Measurements from the Butte
For the second week of the fall 1977 period, the lidar system was moved
from Hay Coulee to the top of a butte four kilometers southeast of the power
plant (the Battelle No. 1 site). All of the previous remote sensing measure-
ments were continued. In addition, from this vantage point, it was possible
to track the plume as far as ten kilometers downwind each morning before the
temperature inversion broke up. Data were recorded tracking both the plume
and dust from the strip mines, using the polarization signatures of the two
to separate them. Figure 1.8 is an example of the polarization signatures
from both the plume and strip mine dust. This was recorded while helping the
Battelle helicopter avoid the area of dust (which was invisible to the eye)
while it was flying in and out of the power plant plume.
Two scan geometries were employed when tracking the plume from this
site. In the "horizontal scan" mode, the lidar was scanned horizontally from
the power plant downwind, with the elevation angle adjusted slightly to keep
the system pointing at the center of the plume. This mode allowed the recon-
struction of a horizontal backscatter profile and could be completed in
roughly ten minutes. In the "vertical slice" mode, the system was scanned
vertically up or down through the plume at a fixed azimuth angle, generating
a vertical profile of the plume at that azimuth. The telescope was then
moved five degrees and another vertical slice recorded, and so on. This
technique required more time (approximately 45 minutes) to complete a scan,
but produced vertical, as well as horizontal, information.
Since these were new types of information for us, the computer data
reduction programs required had not been written and are still being devel-
oped. Some results of these scans have emerged and, although preliminary in
nature, are very informative. Figure 1.9 shows a data set using the verti-
cal slice mode. At the top is a plan view showing the relative positions of
several vertical slices. The backscatter profiles of each vertical slice
were projected onto a plane at an azimuth of 30 degrees, roughly normal to
the prevailing wind. It is these profiles which are displayed in the lower
portion of the figure. The range of backscatter coefficients in each pro-
file is subdivided into thirds by the profile contours. Each profile is
constructed to the same scale, with the vertical being magnified five times
relative to the horizontal to bring out more vertical detail. This data
set was recorded at 0730, September 3, 1977, with the plume trapped in
stable air under a temperature inversion. The horizontal diffusion of the
plume as it proceeds downwind is apparent. The 330-degree and 340-degree
profiles suggest the separation of a section from the lower portion of the
plume and the fallout of heavier particles. This is being investigated
through the dual wavelength backscatter coefficients. The last four,
especially the 80-degree profile, show the plume to be non-uniform in
sections, even six kilometers downwind from the stack. This propagation of
the plume in relatively small, but dense parcels support similar observa-
tions from the atmospheric characterization aircraft and ground station.
This highly preliminary analysis of the plume tracking data provides
convincing evidence of the importance of the technique to understanding
diffusion processes under the stable boundary layer.
48
-------
NOAA DUAL POLARIZATIOM LIDAR SIGNAL AT COLSTRIP, MONTANA,
COAL-FIRED POWER PLANT
T
VD
INSTRUMENTED HELICOPTER BEING
DIRECTED INTO POWER PLANT PLUME
AND AWAY FROM STRIP MINE DUST
O
i— •
h-
-------
NOAA LIDAR OPTICAL BACKSCATTER CONTOURS
OF THE COLSTRIP. MONTANA, POWER PLANT PLUME, SEPT. 3, 1977.
COLSTRIP
fclKM-fl
i
v$ ?V%F
'%\i^
.5V -nor "•'-';>; "."'OC -
t..Mo,Nx
oooocpo^
314.3*
SLIGHTLY DOWNWIND
3T5*
150 M DOWNWIND
900 M DOWNWIND
1.8 KM DOWNWIND
2.4 KM DOWNWIND
Lt _ ^ ' -,1Q_.,j> ,£... _. . _
3.6 KM DOWNWIND
orvc?o.:'00L-.",.;o.>,:corc.ooc;..:<-i5'.-:;3>:-.:: -.'•'•t: • stsii1 ?• ~ .^.
v^70'"t:- •• :•=.-,-" " ".v*V "'
AZ " %0* , - -^ '•
6SCAT - ?.5 X 11*^ ;- •-
•scooooooi;occocoo;sccooofli?o:co.:"t^5oC7"Ti:r-i'
^OOOOOOODOOOOOOOOCOOOOOOOOCC&CQOCOOOOOOOOCWOOtOCGOKX/CyOOOCOOOOO^C-^''; ''€•• iOC'Or^^lit
WK9PO«WOQip'KK>Q06OOwOM6MOeeoO9am
4.7 KM DOWNWIND
Ti^: V --- "' -1
" -." ". • :;••••. ' .'- -..:,-. .-I.TJ v;T -' 1^1 >t . <_•
^u: i~ _ ;:. •.. :-.- :; i
^T. -.;»: • -o-j "QCA- > r'-_L
3.1 KM DOWNWIND
ooooooooo&oocooooctioo&xSWCi'Crt"'*;)-;;'i ~^-_
5.7 KM DOWNWIND
Figure 1.9. Vertical slices of the plume obtained by the lidar. The
vertical and horizontal scales shown apply to all of the
contour plots. The vertical is expanded 5X to bring out
the complex structure.
50
-------
CONCLUSIONS
The most important findings of this report are as follows:
(1) The aerosol in the vicinity of Hay Coulee may be classified into
two main types of particles; (a) a man-made aerosol that consists of small
spherical particles (dominating the 0.1vim
-------
from its source when inversion trapping is dominant. Such data can lead to
an understanding of site-specific diffusion processes, the identification of
local "hot-spots", and the construction of particle fallout maps.
REFERENCES
Abshire, N. L., V. E. Derr, G- T. McNice, R. Pueschel, and C. C. Van Valin.
1978. Integrated Aerosol Characterization Monitoring, Colstrip,
Montana. In: The Bioenvironmental Impact of a Coal-Fired Power Plant,
Third Interim Report, Colstrip, Montana, E. M. Preston and R. A. Lewis,
eds., EPA-600/3-78/021, U.S. Environmental Protection Agency, Corvallis,
Oregon, pp. 291-321.
Parungo, F. P., E. Ackerman, R. H. Proulx, and R. F. Pueschel. 1978.
Nucleation Properties of Fly Ash in a Coal-Fired Power Plant Plume.
Atmospheric Environment, to be published.
Pueschel, R. F., and C. C. Van Valin. 1978. Cloud Nucleus Formation in a
Power Plant Plume. Atmospheric Environment, in press.
Pueschel, R. F., C. C. Van Valin, and F. P. Parungo. 1974. Effects of Air
Pollutants on Cloud Nucleation. Geophysical Research Letters, 1(1).
pp. 51-54.
Schnell, R. C., C. C. Van Valin, and R. F. Pueschel. 1976. Atmospheric
Ice Nuclei: No Detectable Effects from a Coal-Fired Power Plant Plume.
Geophysical Research Letters, 3(11). pp. 657-660.
Van Valin, C. C., R. F. Pueschel, F. P. Parungo, and R. H. Proulx. 1976.
Cloud and Ice Nuclei from Human Activities. Atmospheric Environment,
10(1). pp. 27-31.
52
-------
SECTION 2
BASELINE CHARACTERISTICS OF PRODUCER AND INVERTEBRATE
POPULATIONS AND CERTAIN ABIOTIC PARAMETERS IN
THE COLSTRIP VICINITY
J. L. Dodd, J. W. Leetham, T. J. McNary,
W. K. Lauenroth and G. L. Thor
ABSTRACT
Presented in this section is a culmination of
the various facets of the studies conducted on the four
field sites near the Colstrip power plant. A majority
of the data has been reported in previous interim
reports and is not repeated here. Presented here are
some physical and chemical properties of the soils of
the four sites; some recently developed data on
herbage and litter dynamics and plant phenology, the
chemical composition of the major plant species and
their variation among sites, and finally a summariza-
tion of the arthropod population censusing done in
1974 and 1975. The principal objective of this por-
tion of the overall coal-fired power plant project was
to establish a set of baseline data prior to the
introduction of air pollutants from the Colstrip power
plant. The data presented here and in previous reports
provide ecosystem level baseline data on the four field
sites in hopes that future comparisons can be made
after extended periods of pollutant exposure. A
majority of the data indicates a good homogeneity among
the four field plots with occasional variation in
specific components such as certain plant or arthropod
species being present in greater densities at one or
more sites.
53
-------
INTRODUCTION
Most of the information characterizing baseline conditions of the
Colstrip study sites has been reported in the Third Interim Report (Lauenroth
&t al. y 1978). The purpose of this section is to report information that was
not available at the time the earlier report was prepared. This section does
not repeat information in detail, but does make reference to it. New infor-
mation being reported is largely on abiotic and invertebrate characteristics.
SOIL AND TEMPORAL DYNAMICS OF SOIL WATER AND PRECIPITATION
Soils
Soils of the Colstrip sites have been described in a previous interim
report (Lauenroth et al. , 1978). The soils of the areas are of three
series—Kobar clay loam, Lonna loam, and Yamac silt loam and differ among the
four study sites. Physical and chemical characteristics of the soils have
been determined through analyses of samples taken from pits excavated on each
study site (Appendix Tables 2.1-2.4).
Soil Water and Precipitation
Seasonal dynamics of soil water and growing season precipitation were
monitored for the Colstrip sites in 1975 but not in 1974 and were reported in
a previous interim report (Lauenroth et al., 197 ). Soil water monitoring
was discontinued in 1976 and precipitation for 1976 are reported in Appendix
Table 2.5.
PRODUCERS AND PRIMARY PRODUCTION
Herbage and Litter Biomass Dynamics and Plant Phenology
Aboveground biomass dynamics for 1974 and 1975 were reported in the
third interim report (Lauenroth et al. , 1978) and are not repeated in this
report. Seasonal biomass dynamics were not monitored during 1976 and 1977.
Sampling of herbage components for the Colstrip study sites was limited to
one sample date in 1976 and in 1977. The single sample date was chosen to
coincide with the peak of live standing crop by examination of the 1974 and
1975 data. Data from the single harvest date are discussed in connection
with net primary production estimates for the sites (see section entitled
Colstrip Sites Net Primary Production).
Crown and belowground biomass dynamics for the four Colstrip sites were
determined in 1974 and 1975, and belowground biomass was determined for one
date in 1977. The estimates of crown biomass are quite variable but do
indicate an overall similarity in mean standing crop among the four study
sites (Table 2.1). Significant temporal changes in crown biomass are not
apparent.
54
-------
TABLE 2.1. CROWN BIOMASS DYNAMICS, COLSTRIP STUDY SITES, 1974-1975" (G • M~2 ASH FREE)
Oi
Date
11 May 1974
11 June 1974
29 June 1974
27 July 1974
16 August 1974
26 September 1974
20 April 1975
17 May 1975
23 June 1975
15 July 1975
11 August 1975
17 September 1975
Hay
X
70.5
72.6
77 A
29.7
12.9
68.4
59.5
88.2
41.6
64.5
49.2
90.0
Coulee
SE
19.6
20.5
14.2
3.8
4.5
14.6
10.1
16.1
6.2
12.2
20.1
24.5
Kluver
X
76.4
56.0
60.4
55.0
25.2
77.3
189.5
59.0
47.6
85.9
99.9
99.2
West
SE
20.3
11.1
12.3
14.4
7.5
14.8
26.5
14.6
10.1
26.0
44.1
13.2
Kluver
X
53.8
58.0
53.5
39.2
30.1
87.1
45.6
67.3
50.5
58.7
70.8
100.6
East
SE
10.5
18.3
17.2
7.6
11.6
10.3
9.8
16.3
11.6
15.1
24.9
34.2
Kluver
X
41.6
30.9
55.5
35.4
10.5
43.6
47.6
29.1
47.8
43.2
North
SE
6.4
6.7
14.1
3.9
1.6
6.7
15.4
4.1
13.3
14.5
Crown data were not collected in 1976 and 1977.
-------
Belowground biomass dynamics were based on measurements of plant parts
(roots and rhizomes) in the surface 10 cm of the soil profile (Table 2.2).
Previous analyses indicated that this layer includes about 50% of total
belowground plant biomass (Lauenroth &t al. , 1978). Belowground biomass
estimates ranged from <400 to >600 g • m~2 over the four study sites, but
consistent differences among study sites were not apparent. A seasonal trend
of decreasing biomass from early spring and summer to late summer was found
for nearly all sites in both years. The belowground biomass data utilized
here include both live and dead material. Therefore, seasonal dynamics do
not necessarily reflect live dynamics, but rather reflect the balance between
additions through growth and losses through decomposition.
Litter dynamics were similar across the study sites (Table 2.3).
Although within-season dynamics are inconsistent among years and treatments,
all four sites have about the same amount of litter standing crop. There
also appears to be a general increase in litter standing crop from 1974 to
1977 on all sites except Hay Coulee.
Colstrip Sites Net Primary Production
Estimates of net primary production for the Colstrip Site from 1974
through 1977 were obtained by summing the peak standing crops of current
years production for each of the five functional groups (Table 2.4). In
1976 and 1977, the sites were clipped only once, on dates that we believed
corresponded fairly well to the occurrence of peak aboveground standing crop.
These data are difficult to analyze due to the occurrence of extreme increases
in grasshopper populations on some of the sites in some of the years. The
area most affected was the Kluver West site from 1975 through 1977, although
Kluver North was also affected. The precipitation in this area varied sig-
nificantly over the years (much lower in 1977 than in 1974, 1975, or 1976),
further complicating the pattern of net primary production. Tlte cool season
grasses group was the major component of total net production in each year on
all study sites. The grasshopper and precipitation fluctuations make it
impossible to draw any conclusions about the short-term effects of power
plant emissions on net primary production.
Chemical Composition of Major Plant Species
During the field sampling periods in 1974 and 1975 subsamples of all
plant materials that were harvested in the production studies were prepared
for chemical analysis. These samples were dried, ground, and stored in
plastic vials in a constant temperature (~23°C) room at the Natural Resource
Ecology Laboratory.
Routine analyses for dry matter, ash, nitrogen, phosphorus, and total
sulfur were made on the major species within 6 months of collection. The
remainder of the plant materials in the tissue bank will be preserved for
future reference. Although many of the chemical constituents will change
with storage time, some will not. The bank should prove valuable in future
studies designed to compare baseline chemical characteristics with chemical
56
-------
TABLE 2.2. BELOWGROUND BIOMASS DYNAMICS ' (0-10 CM, G • M 2 ASH FREE)
Ln
Hay Coulee
Date
11 May 1974
11 June 1974
29 June 1974
27 July 1974
16 August 1974
26 September 1974
20 April 1975
17 May 1975
23 June 1975
15 July 1975
11 August 1975
17 September 1975
18 July 1977
X
576.6
411.2
468.3
403.8
395.5
439.6
428.4
548.9
549.7
470.1
385.6
318.0
419.3
SE
42.0
35.8
21.9
39.4
34.7
41.1
54.1
25.8
76.8
35.6
58.2
23.7
38.4
Kluver
X
555.6
425.5
485.6
563.6
412.0
419.8
611.8
529.3
512.2
452.8
359.4
491.5
459.8
West
SE
41.5
32.8
27.8
65.4
37.8
34.4
46.3
64.5
50.0
43.7
35.9
25.3
39.2
Kluver
X
472.7
467.1
492.2
459.6
484.7
351.3
642.5
570.8
588.3
447.9
378.4
505.9
491.5
North
SE
57.2
61.9
43.7
25.6
63.8
63.8
53.5
77.2
95.8
39.3
35.7
90.5
29.6
Kluver
X
425.4
442.2
493.7
427.6
433.2
333.0
439.7
461.4
424.7
371.1
473.1
East
SE
33.6
36.2
22.4
18.1
21.0
19.6
35.6
33.3
23.7
19.2
31.3
Belowground biomass data were not collected in 1976.
-------
TABLE 2.3. LITTER STANDING CROP (X ± SE, ASH FREE G - M~2)
Ln
00
Hay Coulee
Date
11 May 1974
11 June 1974
29 June 1974
26 July 1974
16 August 1974
26 September 1974
X
22 April 1975
18 May 1975
20 June 1975
15 July 1975
11 August 1975
16 September 1975
X
29 June 1976
18 July 1977
X
161
172
201
172
128
192
171
162
170
179
154
231
218
186
181
227
SE
17
11
13
12
12
15
10
14
11
15
26
18
16
14
Kluver
X
177
175
183
140
139
167
163
159
166
160
207
191
177
195
313
West
SE
13
12
6
12
19
13
9
20
10
15
14
18
14
Kluver
X
234
157
169
171
198
230
193
193
205
163
218
277
189
207
235
313
North
SE
21
22
15
18
10
24
22
19
16
32
33
16
15
14
Kluver
X
158
154
171
161
153
148
157
144
157
152
204
206
144
200
310
East
SE
16
12
19
18
18
13
17
19
14
16
39
13
18
-------
TABLE 2.4. PEAK STANDING CROPS
Functional
groups
Cool season
grasses
1974
1975
1976
1977
Warm season
grasses
1974
1975
1976
1977
Cool season
forbs
1974
1975
1976
1977
Warm season
forbs
1974
1975
1976
1977
Half shrubs
1974
1975
1976
1977
Aboveground
net production
1974
1975
1976
1977
Hay
67.
94.
75.
36.
16.
14.
14.
4.
10.
15.
18.
6.
0.
0.
0.
1.
13.
14.
7.
1.
Coulee
8 ±
5 ±
5 +
2 ±
4 ±
5 ±
9 ±
8 ±
5 ±
3 ±
2 ±
4 ±
0 ±
0 ±
1 ±
4 ±
1 ±
6 ±
8 ±
5 ±
107
138
117
50
5.8
6.9
4.1
2.3
4.1
3.4
2.6
1.5
2.3
2.4
2.6
2.4
0.0
0.0
0.7
1.4
4.4
5.4
5.1
0.6
.8
.9
.1
.3
Kluver
103.
106.
55.
33.
4.
9.
2.
1.
9.
14.
10.
4.
3.
0.
2.
0.
0.
0.
0.
0.
2 ±
3 ±
6 ±
5 ±
1 ±
6 ±
9 ±
7 ±
3 ±
7 ±
2 ±
4 ±
3 ±
0 ±
1 ±
4 ±
0 ±
0 ±
0 ±
0 ±
119
130
70
40
West
8.2
10.7
6.9
2.3
1.6
2.1
1.2
1.0
2.1
4.3
1.9
1.4
1.4
0.0
2.1
0.4
0.0
0.0
0.0
0.0
.9
.6
.8
.0
Kluver North
57.
73.
70.
22.
14.
7.
6.
1.
14.
25.
32.
11.
0.
0.
0.
0.
37.
36.
9.
10.
6 ±
6 ±
7 ±
5 ±
1 ±
3 ±
6 ±
9 ±
0 ±
8 ±
0 ±
1 ±
0 ±
0 ±
0 ±
0 ±
0 ±
3 ±
3 ±
3 ±
122
143
118
45
5.1
5.8
6.0
2.1
3.2
3.5
2.1
0.8
1.2
2.2
2.4
1.7
0.0
0.0
0.0
0.0
5.2
7.9
1.7
2.7
.7
.0
.6
.8
Kluver
60.8 ±
91.8 ±
95.1 ±
32.9 ±
6.1 ±
8.5 ±
2.1 ±
1.3 ±
9.0 ±
12.1 ±
14.0 ±
3.8 ±
0.0 ±
0.0 ±
0.6 ±
0.3 ±
29.6 ±
52.4 ±
8.5 ±
1.6 ±
105.
164.
120.
39.
East
3.4
5.7
5.8
3.7
2.6
5.1
1.0
0.8
3.8
2.9
2.2
1.8
0.0
0.0
0.6
0.3
6.3
10.7
2.3
0.7
5
8
3
9
Current and aboveground net primary production (X ± SE). Peaks for 1976
and 1977 estimated from one harvest date only, 28 June 1976 to 16 July
1977.
59
-------
characteristics of plants from the same study sites 5 or 10 years after
continuous operation of the Colstrip power plant complex.
Differences in chemical constituents among the four study sites for live
Agropyron smith-it, the dominant grass, are minimal (Table 2.5). Ash content
ranges from 5.6% to 9.4% but is usually about 7%, regardless of site of time
of season. By contrast, nitrogen content ranges from above 2% in May to less
than 1% in August. Although the sulfur content of live Agropyron smtthti
also appears to decrease with advance of the season, it does not decrease as
rapidly as does foliar nitrogen. Little can be said of the intraseasonal
changes in phosphorus concentrations from our sparse 1974 data and we did not
determine phosphorus levels in 1975.
INVERTEBRATE POPULATIONS
Introduction
This section will present the results of arthropod censusing during the
1974 and 1975 field seasons. The field sampling was done on the four estab-
lished study plots near Colstrip, i.e., Hay Coulee, Kluver West, Kluver
North, and Kluver East. A general description of the region has been given
by Lauenroth et at. (1975) and Taylor et at. (1976) has given detailed
descriptions of the four study plots. For convenience, Taylor's descriptions
are summarized in Table 2.6.
There have been very few studies of the total arthropod community of
northern mixed grass prairie systems (McDaniel, 1971; Reigert and Varley,
1972; Willard, 1974; Reigert et at., 1974). This study, in addition to the
primary purpose of providing baseline data for the coal-fired power plant
emissions study, is an attempt to provide a detailed description of the
arthropod community of a representative site within the northern mixed grass
prairie.
Methods and Materials
The field and laboratory techniques were discussed in brief previously
in the Third Interim Report, but will be given here in greater detail for
reference purposes. The techniques are the same as those followed at Pawnee
Site, the primary field research site of the US/IBP Grassland Biome project.
Specific details of all equipment and procedures are given by Leetham (1975).
The arthropod community was sampled in three phases by three different
techniques, each of which was directed at a major component of the community.
The three phases were aboveground arthropods, soil macroarthropods, and soil
Excerpted from J. W. Leetham, T. J. McNary, R. Kuhmar, J. Lloyd, R. Lavigne,
J. L. Dodd and W. K. Lauenroth. 1978. Arthropod consumer dynamics in some
mixed-prairie grasslands in the northern Great Plains. (In preparation)
60
-------
TABLE 2.5. CHEMICAL CONSTITUENTS OF LIVE AGRQPYRON SMITHII PLANT SAMPLES FOR COLSTRIP STUDY SITES
Ash
Site Date
Hay Coulee 29 June 1974
16 August 1974
1 May 1975
1 June 1975
15 July 1975
11 August 1975
28 June 1976
Kluver West 30 June 1974
22 August 1974
1 May 1975
1 June 1975
16 July 1975
12 August 1975
29 June 1976
Kluver North 1 July 1974
12 August 1974
1 May 1975
1 June 1975
1 July 1975
12 August 1975
Rep. 1
6.9
6.4
9.4
7.2
7.4
6.9
7.1
6.4
6.6
7.4
7.1
7.0
6.5
6.7
5.9
6.3
7.4
7.1
8.4
6.0
Rep. 2
6.4
4.5
8.1
7.3
7.6
6.8
6.6
5.6
8.2
6.3
7.7
6.1
6.1
5.8
6.3
7.6
6.6
6.4
7.5
Nitrogen Phosphorus Sulfur
Rep. 1
1.3
0.9
2.5
1.5
1.1
0.8
1.1
1.1
0.9
2.1
1.4
1.1
0.8
1.1
1.2
0.8
2.4
1.5
1.2
0.8
Rep. 2 Rep. 1
1.2 .19
0.8 .13
2.6
1.6
1.1
0.8
1.2
1.3 .18
.10
2.3
1.5
1.1
0.9
1.1
1.3 .12
1.0 .10
2.4
1.5
1.2
1.0
Rep. 2 Rep. 1
.17 .09
.10 .07
.11
.10
.07
.06
.08
.14 .07
.07
.07
.09
.05
.06
.07
.15 .09
.09 .10
.10
.09
.06
.07
Rep. 2
.10
.07
.10
.11
.06
.06
.08
.10
.09
.09
.08
.06
.08
.09
.10
.10
.10
.10
.08
29 June 1976
6.4
6.4
1.2
1.3
.08
08
-------
TABLE 2.5. CONTINUED.
Ash
Site
Kluver East
Date
2 July 1974
13 August 1974
1 June 1975
17 July 1975
Rep. 1
8.5
8.3
7.0
7.6
Rep. 2
7.6
6.6
7.6
Nitrogen Phosphorus Sulfur
f py \ f py "\ f ^/ *\
Y /Q / \. fO J \ •' O /
Rep. 1
1.2
0.9
1.5
1.2
Rep. 2 Rep. 1
1.3 .17
.10
1.4
1.1
Rep. 2 Rep. 1 Rep. 2
.16 .11 .11
.08
.07 .08
.05 .08
30 June 1976 7.7 7.1 1.2 1.3 .07 .07
Ni
-------
TABLE 2.6. GENERAL CHARACTERISTICS OF THE FOUR FIELD SITES NEAR COLSTRIP, MONTANA
Field plot
Distance (km)
and direction
from Colstrip
Elevation
(m)
Slope and
exposure
Principal plants
Soil type
ON
Hay Coulee
Kluver West
Kluver North
Kluver East
11.6 SB
11.6 ESE
14.7 E
18.3 ESE
927
917
902
904
4% NNE
6% N
5% NE
3.5% NE
Agropyron smithii
Artemisia tridentata
Koeleria oristata
Bromus japonious
Stipa comata
Agropyron smithii
Bromus japonicus
BTOTTIUS
Stipa comata
Artemisia frigida
Agropyron smithii
Bromus japonious
Agropyron smithii
Agropyron oristata
Artemisia frigida
Bromus japonicus
Colluvial clay loams
Colluvial sandy loams
Colluvial sandy loam
Residual and
colluvial clay loams
Derived from Taylor et at.,, 1975.
-------
microarthropods. The aboveground arthropods included those individuals
occurring in or above the soil surface litter. The soil macroarthropods
included those individuals occurring below the surface litter and incapable
of passing through a 1-mm opening sieve while the soil microarthropods were
those individuals occurring in or below the surface litter material and small
enough to pass through the 1-mm sieve. Because of difficulty in applying the
latter, physical separation of the soil macro- and microarthropods, the
separation was ultimately based on taxonomic criteria. Thus the soil micro-
arthropods included the soil acarines, primitive or apterygote insects,
Pauropoda, Symphyla, Tardigrada, and one "higher" group of insects, the
Homoptera-Pseudococcidae. The soil macroarthropods included the remainder of
the soil-dwelling arthropods. The surface litter material was included in
the microarthropod samples because we felt the very small individuals
occurring there were poorly represented in the litter material in the above-
ground samples while the opposite argument was applied to the macroarthropods.
The aboveground arthropods were sampled by dropping a cage of known size
over predetermined sample locations without disturbing the arthropods. The
trap, covering a 0.5-m2 circular area, was dropped from a 5.5 m (18 ft) cart-
mounted boom. After trap emplacement, the arthropods were removed by vacuum
in a two-stage process designed to increase the efficiency of sampling. In
the first stage the trap and vegetation were vacuumed lightly to remove the
active arthropods without including a lot of litter. The second stage was
the complete removal of all vegetation and litter by clipping and vacuuming.
The first-stage material was frozen and later handsorted while the second
stage material was subjected to Berlese-type extraction for 48 h for removal
of the arthropods which were killed and preserved in 70% ethanol.
The soil macroarthropods were sampled by taking 12.5 cm (5 ft) diam. by
15 cm deep soil cores and wet sieving them through a series of three sieves
with mesh openings of 4, 2, and 1 mm. The retained material was then sus-
pended in a saturated solution of magnesium sulfate (MgSOi+) to separate
organic and inorganic material. The final material was handsorted for
arthropods. The soil cores were taken within the area where the aboveground
sample was taken.
The soil microarthropods were sampled by taking soil cores 4.8 cm diam.
by 10 cm deep in such a way as to minimize soil compaction and retain the
core in two 5-cm long aluminum sleeves. The core was taken outside the area
used for the aboveground sample where the litter had not been removed. The
soil core was divided into the two 5-cm sections and each was later subjected
to Macfadyen-type high-temperature gradient Tullgren extraction as developed
by Merchant and Crossley (1970). The arthropods were killed and preserved in
70% ethanol. In addition to the 10-cm deep cores, one sampling was made to
60-cm depth on the Kluver East plot in April 1975. The purpose of this
sampling was to determine the vertical distribution of the soil microarthro-
pods. The 60-cm cores were divided into and extracted by 5-cm increments.
The extraction period for each core segment was 7 days which allowed for
complete desiccation of the sample.
All aboveground arthropod and soil macroarthropod samples were sorted
and identified at the University of Wyoming, Laramie, while the soil
64
-------
microarthropod samples were processed at Colorado State University,
Fort Collins. For all sample types, the arthropods were identified to at
least family and, where possible, to genus and species, and each type was
assigned to a trophic or functional grouping. Representative specimens or
groups of specimens of each taxonomic group were dried at approximately 65°C
for a minimum of 24 h then weighed for dry weight biomass. Total counts and
biomass determinations were projected to a m2 basis.
The trophic categories used were: root tissue feeder, root sap feeder,
fungivore, aboveground plant tissue feeder, aboveground plant sap feeder,
pollen and nector feeder, seed feeder, predator, parasitoid, omnivore,
scavenger, non-feeding, and unknown. A detailed discussion of these groups
is given by McDaniel (1971). Assignment of the various arthropods to these
trophic groups was based on literature reference, gut content analysis,
and/or recommendations by authorities to whom representatives were sent for
identification and/or verification. In cases where immature stages differed
from adults in feeding habits, the general trophic assignment was based on
which stage had the greatest effects on the total system. An example is the
parasitic Hymenoptera where the parasitoid larvae are probably exerting a
much greater effect than non-feeding or nectar feeding adults; therefore, all
specimens were given the "parasitoid" assignment.
The frequency and magnitude of sampling was essentially the same in each
of the two years of field work. The number of sampling dates for each group
in each year is presented in Table 2.7. No samples were taken in the dormant
or winter season. Each field plot was divided into two replicates and each
was gridded into 1-m2 sampling subunits. At each field date, five sampling
units were chosen in each replicate (10 per field plot) by use of a random
numbers table. Within each sampling unit, one sample for each major arthro-
pod category was taken, i.e., one drop trap sample and one macro- and one
microarthropod soil core. Beginning with the third field date in 1975
(13 June 1975) two macroarthropod cores were taken at each sample location.
The resulting data were summarized by replicate and treatment (field plot).
Results and Discussion
The present count of identified arthropod types collected during the two
seasons of field sampling includes 100 families of insects representing 17
orders, 54 families of the four major suborders of mites (Acarina), four
families of spiders (Araneida), one family of Chilopoda, one species of
terrestrial Copopod (unidentified to species), Pauropoda, Symphyla, and
Tardigrada. Not all material collected has been identified to genus or
species or, in some cases to family, and some material is undescribed (par-
ticularly in the Acarina). A general overview of the taxonomic structure of
the arthropod community is presented in Figure 2.1. The percentages used
were derived by combining the results of all three types of sampling averaging
over time and across field plots. Biomass was used because we felt it gave a
better representation of the community structure than numbers since the
overwhelming numbers of Acarina would have made the remaining taxa appear
insignificant. Also presented is the relative contribution to the total by
each portion of the community (i.e., aboveground and soil micro- and
65
-------
TABLE 2.7. FIELD SAMPLING DATES FOR ARTHROPODS FOR 1974 AND 1975
Aboveground
arthropods
1974
11 May*
*
25 June
5 July
1975
21 April
23 May
20 June
Soil
macroarthropods
1974
14 May
23 June
19 July*
1975
19 April
19 May
13 June
Soil
microarthropods
1974
*
14 May
*
16 June
— —
1975
19 April
18 May
20 June
1 Aug. 14 July
18 Aug.
8 Aug.
12 Sept. 11 Sept.
12 Aug. 23 July
9 Aug. 17 July
f\
19 Aug. 6 Aug.
*
11 Sept. 17 Sept,
•ft
20 Aug.
12 Sept.
12 Aug.
16 Sept.
*
Sampling dates from which data were used for statistical analysis.
66
-------
Total Arthropods
Aboveground Arth.
Soil Macroarthropods
Soil Microarthropods
Araneae
Acarina (total)
Mesostigmata
Prostigmata
Astigmata
Cryptostigmata
Collembola
Diplura
Orthoptera
Isoptera
Hemiptera
Homoptera
Coleoptera
Mecoptera
Lepidoptera
Diptera
Hymenoptera
|25.5
769.34 mg-m
':ft&^^
Mil 5.9
5.3
07.1
38.0
27.3
310.0
1.7
323.8
100.0
324.4
mmmmmmmiz.s
327.7
:36I.7
M 29.2
346.4
0
10 20 30 40
TOTAL BIOMASS (%)
50
Figure 2.1.
General taxonomic structure of the arthropod community of a
southeastern Montana mixed-grass prairie, based on averaging
time-weighted means from each of the four field plots from the
1974 and 1975 seasons for biomass. Numbers indicate standard
error as a percent of the total.
67
-------
macroarthropods) . The figures listed in the right column are the standard
error given as a percentage of the mean of the four plots. These data are
given to provide an indication of the variability between field plots. Only
the major taxa are given in Figure 2.1. Those collected but not shown
include Chilopoda, Pauropoda, Symphyla, Tardigrada, Plecoptera, Protera,
Psocoptera, Thysanoptera, Tricoptera, Neuroptera, and Odonata. The
Coleoptera is the dominant group and one of the most stable across sites.
The Acarina are also quite stable across the four field sites, while most of
the insect orders show high variability. A vast majority of the total insect
biomass occurs in the soil and surface litter (approximately 88%) . A more
detailed breakdown of the insect community on each of the four field sites is
given in Table 2.8. The very high biomass on the Hay Coulee site was caused
by collection of Cicada immatures (Homoptera-Cicadidae) just before they
emerged. Normally, those immatures are known to occur at depths of 40-60 cm
for most of their developmental stages.
Figure 2.2 is a general trophic breakdown of the insect community at the
four field sites. The figures are presented for the three major groupings or
sampling schemes. All herbivore types were combined for simplification.
Herbivory is the predominant feeding type in both aboveground and soil
macroarthropod groups but ranks only third in the soil microarthropods.
Predation, however, is very important in both soil groups but is not nearly
as important above ground. Fungal feeding is the predominant feeding type in
the soil microarthropods. The soil macroarthropod data are the most variant
across the four sites while the soil microarthropod and aboveground arthropod
data are similar in their variability across sites.
In order to determine possible significant differences between the four
sites in the various components of the arthropod community as well as signif-
icant year differences or seasonal fluctuations a repeated measures analysis
of variance was used. The analysis was applied to each of the three arthro-
pod sampling components and the model used was the same except for the sample
dates for each since some variability in the number and spacing of the dates
occurred. The model used was:
Y. ... = y + t. + TT , ., + z. + d(z). ,.. + tz. . + td(z)M,., + e. .,
H ijkp
where t = treatment and i = 1, . .., 4 (1 = Hay Coulee, 2 = Kluver West, 3 =
Kluver North, and 4 = Kluver East); TT = replicate within treatment and p = 1,
2 for each; z = year and j = 1, 2 (1 = 1974, 2 = 1975); d(z) = date within
year and k = 1, ..., n for j = 1; k = 1, ..., for j = 2; and n = the total
number of dates used for a given response; and e = error = TTZ + ird(z) . The
sampling dates used in each of the three tests are indicated in Table 2.7.
Additionally, certain soil macroarthropod groups were tested using only the
last four dates in 1975. The model for this test was:
Y., = y + t. + TT , .N + d, +td., + e...
ikp i p(i) k ik ikp
68
-------
TABLE 2.8. GENERAL STRUCTURE OF THE ARTHROPOD COMMUNITY OF THE FOUR FIELD SITES'
Arthropods Hay Coulee Kluver West
Numbers • m~2
Aboveground arthropods 79 (0.1) 62 (0.1)
Soil macroarthropods 139 (0.2) 184 (0.2)
Kluver North Kluver East
101 (0.1) 70 (0.
87 (0.1) 93 (0.
1)
1)
Soil microarthropods
Total
85,905 (99.7) 118,039 (99.7) 117,787 (99.8) 90,954 (99.8)
86,123 118,284
Biomass (mg * m~2)
Aboveground arthropods 70.6 (6.3) 130.3 (17.2)
Soil macroarthropods
Soil microarthropods
Total
1,012.7 (89.7)
45.5 (4.0)
1,128.8
571.2 (75.4)
55.7 (7.4)
757.2
117,975
101.1 (16.7)
456.0 (75.2)
49.6 (8.1)
606.7
91,117
62.7 (10.8)
476.4 (81.8)
43.3 (7.4)
582.4
Based on means of 1974 and 1975 time weighted means except for soil macroarthropods for
which only 1975 data are used.
t
Percent of total.
-------
co 90r
Q
O
Q.
O 80
QC
I
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cr 70
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Ffi
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7.4 6.3 4.8 1.6
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q\- Herbi- Preda- Omni- Sea/en- Non-
vores vores tors vores gers feeding
TREATMENTS BY TROPHIC GROUP
Figure 2.2.
Trophic structure of the arthropod community on the four field
sites. Percentages are based on means of 1974 and 1975 time-
weighted means except the soil macroarthropods for which only
1975 data are used. Numbers above bars indicate mean of all four
treatments.
70
-------
where the terms and subscripts are the same as before, except d = date for
1975 only and k = 1, ..., 4 (for last four sampling dates of 1975) and e =
ird.
For the other groups of soil macroarthropods tested, only the last four
dates in both 1974 and 1975 were used. The deletion of certain dates was
because of problems in the field and laboratory techniques that were cor-
rected at the third sampling in 1975, thus making the last four samplings in
1975 the most reliable data. For the soil microarthropods, only five of the
six 1975 samplings were used since they corresponded with the five samplings
of 1974, thus giving the test for year effect more validity. Only the major
taxonomic and trophic groups were tested and each set of data (aboveground
arthropods and soil micro- and macroarthropods) was treated separately. The
analyses were designed to test for year, treatment, and date main effects and
interactions. The results of the statistical tests (including means) are
presented in Tables 2.9-2.17. Only the results for biomass are presented
since, as mentioned previously, we feel they represent the faunal structure
better than those for numbers. Where the results for numbers deviate from
that for biomass, they will be discussed in text.
Of the 14 taxonomic and trophic groups (including total) of aboveground
arthropods tested, only the Coleoptera failed to show a significant change in
numbers and/or biomass from 1974 to 1975 (P < 0.05). Of those that changed,
only the Araneida numbers and scavenger biomass showed a decrease in popula-
tion size from 1974 to 1975. It is suspected by the authors, that increased
efficiency of sampling in 1975 may have had significant effects on the
observed results of increased populations in 1975 since many logistical
problems of the initial 1974 season had been largely overcome by 1975.
Significant differences between the aboveground arthropod populations of
the four plots were few. For P < 0.05, only the Hemiptera and the trophic
groups of scavengers, plant sap feeders, and predators showed different
populations. Three groups, i.e., total, Orthoptera, and omnivores, had sig-
nificant differences at 0.05 < P < 0.10; however for numbers, the Orthoptera
was highly significant (P < 0.01). There were some significant interactions
noted and these data are presented in Figures 2.3 and 2.4. The high
orthopteran populations at the Kluver West plot are due to high grasshopper
(mostly Melanoplus sp.) populations in 1975. The rancher on whose land the
plot is located confirmed that the area around the plot is a notorious
grasshopper outbreak area. It can be seen in Figures 2.3a,b that there were
substantially higher grasshopper populations in 1975 than in 1974. Very high
populations have been noted in this same plot in 1976 and 1977, although no
sampling was done. The high Hemiptera and resulting plant sap-feeding
populations on Kluver North were due to the lygaeid Nysius sp. collected in
very high numbers primarily in May and June of both years.
As was mentioned earlier, certain difficulties with both the field and
laboratory techniques used for soil macroarthropods caused the data from 1974
and early 1975 to be less reliable than desired and hence the significant^
population increases in 1975 as noted in Table 2.10 are most probably arti-
fical. The data from the last four sampling dates in 1975 are considered
reliable. Because of these difficulties we cannot make any conclusions as to
71
-------
TABLE 2.9. ANOVA RESULTS FOR ABOVEGROUND ARTHROPOU-BIOMASS (MG • M~2)-YEAR AND TREATMENT EFFECTS
Aboveground
arthropods
Araneida
Orthoptera
Hemiptera
Homoptera
Coleoptera
Hymenoptera
Diptera
Plant tissue feeders
Plant sap feeders
Plant pollen feeders
Predator
Omnivore
Scavenger
*
Total arthropods
Year
1974
2.45
11.92
3.97
4.16
18.47
2.76
0.93
30.05
7.75
0.36
5.71
1.84
5.85
53.13
1975
1.60
79.76
5.54
6.70
15.89
8.33
1.68
94.24
9.57
2.58
5.35
7.24
2.82
126.13
ANOVA
P(Y)
.3472
.0000
.0419
.0061
.2327
.0000
.0087
.0000
.0906
.0069
.7720
.0000
.0007
.0000
Hay Coulee
2.60
31.72
3.02
6.35
13.31
6.00
1.31
43.95
7.25
9.93
5.84
5.10
2.76
70.53
Field i
Kluver
West
1.08
76.80
5.27
5.43
20.32
4.88
1.32
92.92
9.52
2.98
4.43
3.38
8.17
125.06
>lot
Kluver
North
3.33
43.61
8.30
6.08
23.24
6.40
1.44
67.55
12.69
0.83
7.91
5.38
4.18
100.82
Kluver
East
1.10
31.22
2.42
3.86
12.39
4.89
1.14
44.17
5.18
0.13
3.94
4.67
2.23
62.10
ANOVA results
P(T)
.0168
.0738
.0284
.3894
.2172
.4755
.9675
.1412
.0216
.1572
.0483
.0732
.0033
.0943
Q value P(T*Y)
1.829
.0482
5.04
5.63 .0188
3.95
6.73 .0330
.0078
fro
Total aboveground arthropods, but does not necessarily equal the sum of those listed.
-------
TABLE 2.10. ANOVA RESULTS TO SOIL MACROARTHROPODS-fllOMASS (MG • M~2)-YEAR AND TREATMENT EFFECTS
Field jjlot
Aboveground
arthropods
Orthoptera
Coleoptera
Hymenoptera
Plant tissue feeders
Uomoptera
Root tissue feeders
Root sap feeders
Predators
*
Total arthropods
Year
1974
12
86
9
42
125
.30
.74
.13
.94
.73
1975
4.56
324.68
63.77
123.96
132.53
183.10
295.21
343.63
614.01
ANOVA
PCO
.1169
.0000
.0478
.0130
.0000
Hay Coulee
1
238
67
132
275
247
551
264
567
.57
.44
.57
.28
.67
.05
.34
.16
.15
Kluver
West
4.30
225.04
62.34
73.05
21.22
120.14
42.44
508.53
352.14
Kluver
North
18.
197.
11.
39.
69.
180.
199.
407.
286.
00
65
35
99
32
58
10
34
70
Kluver
East
9.87
161.72
7.55
88.48
163.93
184.63
387.97
194.49
273.50
ANOVA results
P(T) Q value P(TxY)
.1671 '.0253
.6799
.5124
.7125
.3450
.9367
.4752
.0279 265.79
.0429 290.53
Total soil macroarthropods, but does not necessarily equal the sum of those listed.
u>
TABLE 2.11. ANOVA RESULTS FOR SOIL MICROAKTHKOl'ODS-BIOMASS (MG • M~2)~YEAR AND TREATMENT EFFECTS
'
Field plot
Aboveground
arthropods
Acar i.formes
Astigmata
Cryptostigmata
Prostigmata
Par as it if ormes
Mesostigmata
Fungivores
Herbivores
Predators
*
Total arthropods
Year
1974
28.74
1.65
13.76
13.32
5.43
21.52
8.16
14.84
212.4.
1975
22.51
0.65
7.70
14.15
4.56
19.61
11.30
10.44
219.4
ANOVA
P(Y)
.0014
.0026
.0000
.3512
.1678
.3818
.0199
.0000
.9134
Hay Coulee
23.14
0.64
10.53
11.97
5.39
20.38
6.27
13.07
131.39
Kluver
West
28.29
1.10
12.69
14.59
4.33
24.26
13.47
12.07
280.37
Kluver
North
26.57
1.86
9.22
15.58
5.78
17.70
10.56
13.08
325.51
Kluver
East
24.38
1.00
10.48
12.89
4.54
19.92
8.62
12.34
126.41
P(T)
.2306
.3031
.1598
.3205
.2444
.3024
.0796
.7824
.4311
ANOVA results
Q value P(TxY)
.0570
Total soil microarthropods, but does not necessarily equal the sum of those listed.
-------
TABLE 2.12. ANOVA RESULTS FOR ABOVEGROUND ARTHROPODS-BIOMASS (MG • M~2)-DATE EFFECT FOR 1974
Aboveground
arthropods
Araneida
Orthoptera
Hemiptera
Homoptera
Coleoptera
Hymenoptera
Diptera
Plant tissue feeders
Plant sap feeders
Plant pollen feeders
Predators
Omnivores
Scavengers
Total arthropods
11 May
1.92
5.65
7.21
2.66
16.96
4.06
0.31
55.01
9.48
0.00
4.5.3
4.05
6.23
81.32
25 June
1.83
24.18
10.68
8.70
32.85
6.79
2.05
38.95
17.87
1.40
8.92
3.89
13.90
89.21
Sampling
5 July
4.88
12.04
2.58
5.55
26.16
3.70
2.11
32.23
7.68
0.70
9.65
1.70
4.94
58.34
dates
1 Aug
1.78
14.89
0.37
2.59
5.57
0.22
0.27
18.13
3.16
0.02
2.43
0.10
1.95
26.04
ANOVA results
18 Aug
2.23
12.84
0.52
3.51
7.94
0.46
0.58
18.22
4.06
0.04
3.03
0.34
3.63
29.56
12 Sept
2.10
1.91
2.44
1.93
22.98
1.30
0.26
17.79
4.26
0.02
5.69
0.98
4.47
33.81
P(D)
.9421
.0000
.0287
.0001
.0024
.0079
.5194
.0000
.9687
.1049
.0370
.0000
.0257
Q value
5.490
6.466
17.214
5.140
1.988
7.669
4.54
6.037
68.79
P(DXT)
.0000
.0147
.0013
.0000
V
Total aboveground arthropods, but does not necessarily equal the sum of those listed.
-------
TABLE 2.13. ANOVA RESULTS FOR ABOVEGROUND ARTHROPODS-BIOMASS (MG • M~2)-DATE EFFECT FOR 1975
Ui
Aboveg round
arthropods
Araneida
Orthoptera
Hemiptera
Homoptera
Coleoptera
Hymenoptera
Diptera
Plant tissue feeders
Plant sap feeders
Plant pollen feeders
Predators
Omnivores
Scavengers
Total arthropods
Sampling dates
21 Apr
0.24
1.78
3.40
2.38
29.93
3.05
1.08
29.87
3.55
1.96
4.40
2.80
3.48
47.91
23 May
0.28
14.58
4.18
3.03
29.64
13.24
2.73
38.28
4.51
0.25
6.46
12.26
6.01
69.43
20 June
5.59
35.25
12.97
10.82
19.76
19.45
2.42
49.78
22.02
4.23
10.84
19.36
5.13
127.36
14 July
2.49
147.43
8.07
12.76
8.56
11.56
3.12
159.84
14.30
3.52
7.35
8.78
0.22
196.99
8 Aug
0.16
192.95
2.74
7.51
3.15
2.04
0.72
197.24
9.49
1.96
1.18
0.64
0.35
213.15
11 Sept
0.86
86.60
1.89
3.73
4.31
0.67
0.00
90.46
3.53
3.54
1.75
0.67
1.74
101.92
ANOVA results
P(D)
.0000
.0000
.0000
.0000
.0000
.0001
.0000
.0000
.3410
.0242
.0000
.0228
.0000
Q value
66.522
5.490
6.466
17.214
5.140
1.988
68.923
7.669
9.080
4.54
6.037
68.79
P(DxT)
.0037
.0004
.0140
.0517
.0005
.0005
.0104
.1090
.0001
.0329
.0093
Total aboveground arthropods, but does not necessarily equal the sum of those listed.
-------
TABLE 2.14. ANOVA RESULTS FOR SOIL MACROARTHROPODS-BIOMASS (MG • M 2)-DATE EFFECTS FOR
1974
Soil
macroarthropods
Coleoptera
Hymenoptera
Orthoptera
Plant tissue feeding
*
Total arthropods
19 July
16.44
11.80
0.00
0.00
28.33
Sampling
12 Aug
81.26
12.68
10.16
13.34
163.05
dates
19 Aug
68.43
4.98
0.00
50.16
73.41
11 Sept
180.83
7.07
39.06
108.27
238.15
ANOVA results
P(D) Q value
.2359
.9486
.0008 26.11
.3074
.4430
P(DxT)
.0141
X
jL.
"Total soil macroarthropods, but does not necessarily equal the sum of those listed.
-------
TABLE 2.15.
ANOVA RESULTS FOR SOIL MACROARTHROPODS-BIOMASS (MG
1975
M~2)-DATE EFFECTS FOR
Soil
macroarthropods
Coleoptera
Hymenoptera
Orthoptera
Plant tissue feeding
Homoptera
Predator
Root tissue feeding
Root sap feeding
*
Total arthropods
20 June
249.30
74.21
13.86
139.61
120.95
301.11
214.32
362.84
553.59
Sampling
30 July
224.86
96.85
2.52
86.10
362.86
243.90
128.84
725.69
771.32
dates
8 Aug
509.62
62.48
0.63
101.78
45.97
648.17
344.71
91.95
702.94
ANOVA results
11 Sept
314.96
21.54
1.26
168.35
0.37
181.34
44.53
0.37
427.19
P(D)
.0051
.5513
.4773
.5371
.0174
.0159
.2495
.0402
.0795
Q value P(DXT)
216.42
302.06 .0181
385.63
702.67 .0363
.0036
Total soil macroarthropods, but does not necessarily equal the sum of those listed.
-------
TABLE 2.16. ANOVA RESULTS FOR SOIL MICROARTHROPODS-BIOMASS (MG • M~2)-DATE EFFECTS FOR 1974
oo
Soil
microarthropods
Acariformes
Astigmata
Cryptostigmata
Prostigmata
Parasitiformes
Mesostigmata
Fungivores
Herbivores
Predators
*
Total arthropods
Sampling dates
14 May
39.47
1.30
21.95
16.22
5.30
42.69
9.00
18.43
133,150
1 6 June
33.54
4.10
13.26
16.19
6.36
22.32
7.90
14.57
125,210
9 July
25.72
0.81
12.18
12.72
4.40
14.33
7.67
13.26
75,571
20 Aug
17.86
0.91
8.43
8.52
4.62
10.48
5.21
14.38
55,869
12 Sept
27.08
1.14
12.97
12.96
6.46
17.80
11.02
13.60
80,668
ANOVA results
P(D)
.0001
.0001
.0001
.0012
.4317
.0000
.3808
.0963
.0000
Q value
11.587
1.989
7.165
5.621
13.902
39,286
P(DXT)
.0233
.0001
Total soil microarthropods, but does not necessarily equal sum of those listed.
-------
TABLE 2.17. ANOVA RESULTS FOR SOIL MICROARTHROPODS-BIOMASS (MG • M 2)-DATE EFFECTS FOR 1975
Soil
microarthropods
Acari formes
Astigmata
Cryptostigmata
Pro stigmata
Parasitiformes
Mesostigmata
Fungivores
Herbivores
Predators
*
Total arthropods
Sampling dates
18 May
48.41
1.78
14.72
31.90
7.35
62.62
17.36
14.98
250,655
24 June
25.08
0.64
8.71
15.73
9.31
15.75
11.69
20.78
114,584
17 July
14.92
0.23
5.54
9.15
3.63
7.64
4.94
9.34
51,766
12 Aug
12.35
0.14
3.71
8.49
1.10
5.18
9.16
4.34
55,414
16 Sept
11.78
0.48
5.83
5.46
1.43
6.85
13.34
2.74
37,301
ANOVA results
P(D)
.0000
.1458
.0008
.0000
.0000
.0000
.0021
.0000
.0000
Q value
11.587
7.165
5.621
3.936
13.902
8.291
5.78
39.286
P(DXT)
.0048
.0914
Total soil microarthropods, but does not necessarily equal sum of those listed.
-------
200
E
J
(S)
o
CD
100
^ a
o1-^
1974 1975
200
100
_ b
— Hay Coulee
--Kluver West
••- Kluver North
— Kluver East
1974 1975
10
0
_ c
1974 1975
Figure 2.3. Treatment by year means (biomass) for three aboveground
arthropod groups: a = total aboveground arthropods,
b = Orthoptera, and c = scavengers.
N
40
r- Q
CVI
E 30
20
10
\
b
1974 1975
c
— Hay Coulee
- Kluver West
- Kluver North
— Kluver East
\
1974 1975
1974 1975
Figure 2.4. Treatment by year means (numbers) for three aboveground
arthropod groups: a = Hemiptera, b = plant sap feeders,
and c = omnivores.
80
-------
population fluctuations of soil macroarthropods between the two years. Very
little significant differences were found between the four field plots. Only
the total (P = 0.0429) and the trophic group predator (P = 0.0279) showed
significantly higher populations at one or more plots. Only the Orthoptera
(primary grasshopper eggs) numbers and biomass (P = 0.0353 and 0.0253,
respectively) showed a significant treatment x year interaction.
Seven of the eight microarthropod taxa and trophic groups tested showed
significantly different (P < 0.05) populations from 1974 to 1975, most
showing declines in 1975 (Table 2.10). Two exceptions were the prostigmatid
numbers (P = 0.0303) and total herbivore number (P = 0.0039) and biomass (P =
0.0199) which showed increases in 1975. Total microarthropod numbers and
biomass showed increases in 1975; however, neither were significant (P =
0.2066 and 0.9134, respectively). Except for possibly predators (P = 0.057)
none of the groups tested showed significant year x treatment interactions,
indicating the year differences are probably valid for all four field plots.
No significant differences between plots (P < 0.05) were found for any
of the taxonomic and trophic groups of soil microarthropods tested, although
variability between the plots is evident in the data (Table 2.10). At P =
0.0776 and P = 0.0796, the herbivore group showed significant treatment
effect for numbers and biomass, respectively. The most apparent trend among
the data was for higher populations to occur at the Kluver West and Kluver
North plots. This could very likely be due to the predominance of the bunch
grass St-ipa sp. at these two sites.
Aboveground arthropod population trends across the growing seasons
tended to follow the patterns of aboveground standing live vegetation, i.e.,
peaking in mid summer and declining toward fall. Nearly all taxonomic and
trophic groups tested showed significant (P < 0.05) population changes within
one or both seasons, most of which had their highest populations near the
July sampling. A notable exception is the total arthropods and its major
constituent, the Orthoptera, which showed peak populations in the late summer
of 1975. The data for these two groups in 1975 are presented in Figures 2.5
and 2.6. The same trend is seen for the trophic group plant tissue feeders.
Numerous significant date by treatment interactions (P < 0.05) are indicative
that the observed trends do not necessarily apply equally to all plots. Some
of these interactions are presented in Figures 2.7, 2.8, 2.9, and 2.10.
Generally, the Kluver East plot has the least change in biomass of various
arthropod groups across the growing seasons.
Because of the technical problems encountered in sampling the soil
macroarthropods, population changes across the seasons are very difficult to
interpret with even greater complications arising due to significant interac-
tions of treatment and date (Tables 2.14 and 2.15). Generally the soil
arthropods were composed largely of Homoptera-Cicadidae (root sap feeders)
and Coleoptera-Carabidae (largely predatory) and Elateridae (root chewing
wire worms). The Cicadids were sampled as mature, emerging nymphs which are
generally missed by shallow soil sampling because they normally spend multiple
seasons at 40-60 cm depth feeding on root sap and move to the soil surface
just prior to emergence to the adult stage. Cicadids were taken at all but
the Kluver West plot.
81
-------
200
(VI
I
100
o>
E
c/)
<
o
00
r a
Hay Coulee
Kluver West
Kluver North
Kluver East
II May
25Jun 5Jul lAug ISAug !2Sep
400
300
200
100
0.
\
\
2IApr 23May 20Jun !4Jul 8Aug
HSep
Figure 2.5.
Time traces for total aboveground arthropod biomass for 1974 (a)
and 1975 (b) for four field plots at Colstrip, Montana.
82
-------
400
300
o>
c/)
200
O
5 100
Hay Coufee
Kluver West
Kluver North
Kluver East
/\
\
\
2IApr 23May 20Jun !4Jui 8Aug
USep
Figure 2.6. Time traces of Orthoptera biomass for four field plots for 1975
at Colstrip, Montana.
83
-------
30
_ a
20
E
o>
to
a
CD
30
20
10
10
0
\
Hay Coulee
Kluver West
Kluver North
Kfever East
May
lAug ISAug
!2Sep
\
\
/
/
2lApr
23Moy 2OJun
MSep
Figure 2.7. Time traces for Hemiptera biomass for 1974 (a) and 1975 (b) on
four field plots at Colstrip, Montana.
84
-------
50
CVJ
I
25
o»
(f)
<
2
O
CD
11 May
J L
25Jun 5Jul lAug ISAug
— Hay Coulee
- Kluver West
— Kluver North
— Kluver East
2IApr
23May
8Aug
!2Sep
b
Sep
Figure 2.8. Time traces for Coleoptera biomass for 1974 (a) and 1975 (b) on
four field plots at Colstrip, Montana.
85
-------
12
8 '0
CM
I
£ 8
o>
E
CO c
CO b
o
CD
1,756.3 1,260.5
Hay Coulee
Kluver West
Kluver North
Kluver East
20Jun
30Jul5Aug
MSep
Figure 2.9. Time traces of total soil macroarthropod biomass for four field
plots at Colstrip, Montana in 1975.
86
-------
8
O
O
X 6
CM
I
E
O
CD
Hay Coulee
Kluver West
Kluver North
Kluver East
1
J L
20Jun
30Jul 8Aug
USep
Figure 2.10.
Time traces for Coleoptera (soil macroarthropod) biomass for
four field plots at Colstrip, Montana in 1975.
87
-------
The soil microarthropods generally showed a consistent population trend
of being high in the spring and declining as the season progresses (Tables
2.16 and 2.17). In 1974 the population showed a resurgence in early fall.
These trends are quite closely atuned to soil water dynamics for the seasons.
Nearly all groups tested showed significant population changes (P < 0.05) in
one or both seasons and essentially all followed the above trend of high
spring and low summer population levels. Only four groups showed significant
date x treatment interactions and these data are presented in Figures 2.11,
2.12, 2.13, and 2.14.
For all three types of arthropod data, summaries consisting of means and
standard errors have been calculated for all sample dates in both years. The
summaries are at the order, suborder, family, and trophic group levels and
are done by replicate with treatment summaries. These data are stored at the
Natural Resource Ecology Laboratory, Colorado State University, Fort Collins.
Anyone interested in any particular facet of these data should contact either
Dr. Jerrold L. Dodd or John Leetham. The data are much too voluminous to
include here.
Summary and Conclusions
The task of characterizing in depth the complete arthropod fauna of any
given ecosystem type is a formidable one and becomes more complex the larger
the defined ecosystem type. Because of the immense variability of types and
function of the arthropods, it is indeed difficult to devise techniques with
which to efficiently census the fauna of a given ecosystem type. The objec-
tive in this study was to utilize some techniques developed during the US/IBP
Grassland Biome studies to census the arthropod fauna of a northern mixed-
grass prairie ecosystem located near the site of a major coal-fired power
plant. The censusing was to establish a set of baseline data which may be
utilized at a later date to evaluate the long-term effects of the atmospheric
pollutants generated by the power plant. Because of the design of the
censusing program, only large-scale faunal changes will be detected when
return sampling is done. Small-scale, subtle changes may not be detected, or
at least not until they have had time to effect larger ramifications in the
ecosystem. Nevertheless, the data collected here can provide a reasonably
good baseline from which to work.
General characteristics of the arthropod fauna show that an overwhelming
majority of the arthropod biomass and numbers occur in the soil (Figure 2.1,
Table 2.8). This is not unexpected considering the comparatively xeric
conditions of the area and the fact that a majority of the herbage biomass is
plant roots. This situation is common to the drier grassland types. A
majority of the soil arthropod biomass is made up of Coleoptera and Homoptera
immatures (Figure 2.1). However, from a number's view point, the soil
acarines are by far the dominant group. The variability of the arthropod
fauna within a grassland ecosystem type is exemplified by the grasshopper
populations at the four field sites. Slight variations in the controlling
environmental factors can result in substantial population variations. Thus
the substantially higher Melanoplus populations at the Kluver West plot may
be due in part to the sandier soil of the area. Sandy loam soils have been
88
-------
150
100
50
O
O
O
OJ
I
cr
LU
GO
— Hay Coulee
- - Kluver West
• — Kluver North
—- Kluver East
!4May I6jun 9Jul
20Aug !2Sep
300 n
*3I6,600
250
ISMay 24Jun ITJul !2Aug
ISSep
Figure 2.11.
Time traces for total soil microarthropod biomass for 1974 (a)
and 1975 (b) on four field plots at Colstrip, Montana.
89
-------
O>
E
CO
CO
40
w 30
20
2 10
m
0
\
\.
Hay Coulee
Kluver West
._ Kluver North
Kluver East
18 May
24Jun
ITJul
!2Aug
IGSep
Figure 2.12.
Time traces for total biomass of acarine suborder Prostigmata
on four field plots in 1975 at Colstrip, Montana.
90
-------
IO
CVJ
I
E
•
o»
J 5
O
CD
' \ \
Hay Coulee
-Kluver West
- Kluver North
— Kluver East
_L
'14 May
ISJun
1
9Jul
20Aug !2Sep
Figure 2.13. Time traces for total biomass of the acarine suborder
Mesostigmata on four field plots in 1974 at Colstrip,
Montana.
Hay Coulee
w
I
Kluver North
Kluver East
o»
£
O
CD
---- Kluver West
!4May
!6Jun
9Jul
20Aug !2Sep
Figure 2.14.
Time traces for total biomass of the soil microarthropod trophic
group Predator in 1974 on four field plots at Colstrip, Montana.
91
-------
shown to be preferred by Melanoplus species (Isely, 1938) for oviposition
sites.
Probably the foremost criterion for utilizing all four field sites for
future monitoring is how uniform they are in both floral and faunal aspects.
Generally, there are few significant differences between two or more plots
for the various taxonomic and trophic groups, although the actual data show
substantial variability from plot to plot. Based on our data, the four field
plots are good replicates for most of the arthropod groups present. Of
course for certain groups such as the grasshoppers where significant dif-
ferences do occur, the specific outlier plot or plots should not be used for
future reference.
The trophic structure of the arthropod fauna is variable among the three
divisions sampled (Figure 2.2). The aboveground arthropods are largely
herbivores in some way or another. The soil macroarthropods are also largely
herbivores; however, there are more predators than above ground. The soil
microarthropods are quite different in that herbivores rank third behind
fungivores and predators. Herbivory is much less important to the tiny
microarthropods, primarily acarines, than the larger insects. They have been
able to exploit the large supply of fungal material in the soil and litter
zones.
There is a very substantial difference between the season population
dynamics of the aboveground arthropods and the soil microarthropods. The
aboveground types show population trends similar to the aboveground herbage,
•i.e-t increasing to a mid-season high then declining into winter. This is
expected since most of the arthropods are herbivores. By contrast, the soil
microarthropods show early spring population highs with declines through the
summer and possibly a rebound in fall. This trend is basically the same as
the expected soil water cycle, i.e., wetter from spring and early summer
rains, drying down in late summer, then rewetting from fall precipitation.
Soil macroarthropod trends could not be depicted from our data. The actual
trends may be very complicated due to variations in emergence patterns among
species. Since many of the macroarthropods are immatures of various insects
that also would be classed as aboveground arthropods in the adult stage,
their population trends might be coordinated with the availability of food
resources for the adult. Thus, a given species may show peak numbers of
immatures in the soil late in the growing season when soil water is low but
then present high numbers of emerging adults since their primary aboveground
food source is then available.
92
-------
REFERENCES
Isely, F. B. 1938. The Relation of Texas Acrididae to Plants and Soils
Ecol. Monogr., 8:551-604.
Lauenroth, W. K., J. L. Dodd, R. K. Heitschmidt, and R. G. Woodmansee. 1975.
Biomass Dynamics and Primary Production in Mixed Prairie Grasslands in
Southeastern Montana: Baseline Data for Air Pollution Studies. In:
Proceedings of the Fort Union Coal Field Symposium, W. Clark, ed.
Eastern Montana College, Billings, Montana, pp. 559-578.
Lauenroth, W. K. , J. L. Dodd, R. K. Heitschmidt, and J. W. Leetham. 1978.
Effects of S02 and Other Coal-firing Plant Emissions on Producer,
Invertebrate Consumer, and Decomposer Structure and Function in the
Vicinity of Colstrip, Montana. In: The Bioenvironmental Impact of a
Coal-fired Power Plant, E. M. Preston and R. A. Lewis, eds. 3rd Interim
Rep. EPA-600/3-78-021, U.S. Environmental Protection Agency. Corvallis,
Oregon, pp. 13-40.
Leetham, J. W. 1975. A Summary of Field Collecting and Laboratory Pro-
cessing Equipment and Procedures for Sampling Arthropods at Pawnee Site.
US/IBP Grassland Biome Tech. Rep. No. 284. Colorado State University,
Fort Collins, Colorado. 49 pp.
McDaniel, B. 1971. Studies of Populations of Adults and Immature Insects
and Mites from Two Treatments at Cottonwood, South Dakota. US/IBP
Grassland Biome Tech. Rep. No. 112. Colorado State University,
Fort Collins, Colorado. 99 pp.
Merchant, V. A., and D. A. Crossley. 1970. An Inexpensive High Efficiency
Tullgren Extractor for Soil Microarthropods. J. Ga. Entomol. Soc.,
5:83-87.
Riegert, P. W., and J. L. Varley. 1972. Aboveground Invertebrates. I.
Population Dynamics. Canadian/IBP Grassland Biome Tech. Rep. No. 6.
University of Saskatchewan, Saskatoon, Saskatchewan, Canada. 45 pp.
Riegert, P. W. , J. L. Varley, and J. R. Willard. 1974. Aboveground Inverte-
brates: V. A Summary of Populations, Biomass and Energy Flow.
Canadian/IBP Grassland Biome Tech. Rep. No. 67. University of
Saskatchewan, Saskatoon, Saskatchewan, Canada. 28 pp.
Taylor, J. E., W. C. Leininger, and R. J. Fuchs. 1976. Site Descriptions
and Effects of Coal-fired Power Plant Emissions on Plant Community
Structure. In: The Bioenvironmental Effects of a Coal-fired Power
Plant, R. A. Lewis, N. R. Glass, and A. S. Lefohn, eds. 2nd Interim Rep.
EPA-600/3-76-013, U.S. Environmental Protection Agency, Corvallis,
Oregon, pp. 11-39-
Willard, J. R. 1974. Soil Invertebrates: VIII. A Summary of Populations_
and Biomass. Canadian/IBP Grassland Biome Tech. Rep No. 56. University
of Saskatchewan, Saskatoon, Saskatchewan, Canada. HO pp.
93
-------
APPENDIX
TABLE 2.1. PHYSICAL CHARACTERISTICS OF COLSTRIP STUDY SITE SOILS
Sample
number
Horizon
Depth
(cm)
Gravel Sand
(7} (7"\
\/a} \/Q)
Silt
(%)
Clay
(%)
*
Texture
Bulk
density
Hay Coulee, North Pit
228P
400P
234P
401P
402P
229P
230P
270P
271P
404P
272P
273P
274P
275P
262P
264P
403P
265P
267P
268P
269P
311P
312P
313P
314P
315P
Al
Dupl.
B2
Cl
Dupl.
C2
C3
Al
B21
Dupl.
B22
B3
Cl
C2
Al
B2
Dupl.
B3ca
Clca
IIC1
IIC2
Al
B2
B3
Clca
C2ca
0-12
0-12
12-22
22-60
22-60
60-98
98-152
0-12
12-20
12-20
20-33
33-43
43-90
90-152
0-10
10-20
10-20
20-33
33-62.5
62.5-85
85+
0-10
10-31
31-40
40-118
118-156
2.76
2.76
2.35
3.06
3.06
2.12
2.02
Hay Coulee,,
1.87
1.64
1.64
1.47
2.17
1.98
1.66
Kluvev West,
8.08
4.14
4.14
7.34
4.31
59.37
4.22
Kluver West,
7.84
4.19
29.98
5.97
15.31
23
24
18
15
15
28
26
South
40
52
49
58
63
63
45
East
52
43
41
40
54
76
62
West
54
52
59
55
72
40
40
46
44
45
48
45
Pit
40
15
19
16
14
15
28
Pit
24
26
29
32
22
8
20
Pit
24
21
19
22
13
37
36
36
41
40
24
29
20
33
32
26
23
22
27
24
31
30
28
24
16
18
22
27
22
23
15
CL
CL
SiCL
SiC
SiC
L
CL
L
SCL
SCL
SCL
SCL
SCL
SCL
SCL
CL
CL
CL
SCL
SL
SL
SCL
SCL
SCL
SCL
SL
1.18
1.18
1.20
1.33
1.33
1.29
1.59
1.25
1.37
1.37
1.42
1.49
1.28
1.40
1.59
94
-------
TABLE 2.1. CONTINUED.
Sample
number
245P
246P
247P
248P
249P
250P
296P
297P
298P
299P
300P
301P
302P
283P
284P
285P
286P
287P
288P
Horizon
Al
B2
B3ca
Cl
C2
C3
Al
Bl
B2
B3
Cl
C2
C3
Al
B2ca
B3ca
Clca
C2ca
C3
Depth
(cm)
0-10
10-30
30-48
48-64
64-90
90-152
0-13
13-24
24-40
40-50
50-84
84-114
114-152
0-10
10-20
20-28
28-46
46-108
108-152
Gravel Sand
f cr/ \ / o1/ \
\ /O / V /Q J
Kluuev North,
2.60
4.62
0.33
3.83
0.29
0.13
Kluver North,
1.59
0.37
1.44
1.53
0.73
0.68
0.00
Kluver East,
66.39
3.02
0.79
1.38
0.40
31.47
East
61
58
48
45
41
44
West
58
58
60
58
55
56
54
South
35
34
34
35
64
61
Silt
Pit
15
18
23
26
27
26
Pit
21
18
16
18
16
16
20
Pit
31
34
34
33
13
14
Clay
24
24
29
29
32
30
21
24
24
24
29
28
26
34
32
32
32
23
25
— _ —
*
Texture
SCL
SCL
SCL
SCL
CL
CL
SCL
SCL
SCL
SCL
SCL
SCL
SCL
CL
CL
CL
CL
SCL
SCL
Bulk
density
1.25
1.44
1.54
1.57
1.11
1.38
1.51
1.58
1.54
1.29
1.38
1.59
1.59
C = clay, L = loam, Si = silt, S = sand.
95
-------
TABLE 2.2. WATER-HOLDING CAPACITY (% WT) OF COLSTRIP STUDY SITE SOILS
VO
ON
Sample
number
228P
400P
234P
401P
402P
229P
230P
270P
271P
404P
272P
273P
274P
275P
262P
264P
403P
265P
267P
268P
269P
Horizon
Al
Dupl.
B2
Cl
Dupl.
C2
C3
Al
B21
Dupl.
B22
B3
Cl
C2
Al
B2
Dupl.
B3ca
Clca
IIC1
IIC2
Depth
(cm)
0-12
0-12
12-22
22-60
22-60
60-98
98-152
0-12
12-20
12-20
20-33
33-43
43-90
90-152
0-10
10-20
10-20
20-33
33-62.5
62.5-85
85+
0
64.46
43.23
51.02
47.32
42.87
53.70
49.73
44.46
41.94
44.07
44.81
54.28
50.64
43.70
34.03
58.41
bar
Hay Coulee*
62.70
57.55
54.21
47.94
Hay Coulee,
48.35
53.08
49.71
41.99
41.90
44.62
Kluver West,
45.76
52.06
52.17
43.85
35.66
26.74
.33
North
25.11
23.34
20.16
21.63
South
17.89
16.92
15.78
14.35
12.83
17.42
East
13.96
18.23
20.26
15.77
9.09
12.91
bar
Pit
23.10
22.68
20.06
20.93
Pit
19.09
16.45
14.89
14.40
12.90
17.44
Pit
14.96
18.36
18.87
16.06
9.94
13.68
1
19.49
17.42
14.05
13.88
14.31
11.57
12.53
11.19
10.08
13.93
12.04
14.60
14.17
13.01
7.46
9.36
bar
19.
17.
13.
13.
14.
14.
12.
10.
10.
13.
12.
12.
14.
13.
7.
7.
38
24
93
07
42
20
69
85
32
63
59
43
27
34
32
41
15
9.79
9.92
6.15
6.63
7.70
9.19
7.87
5.87
5.84
6.93
6.49
8.82
7.10
5.66
3.96
4.65
bar
9.90
9.53
6.63
6.75
7.82
8.78
7.22
5.96
5.40
6.39
6.44
9.10
7.26
5.72
4.55
4.72
-------
TABLE 2.2. CONTINUED.
Sample Depth
number Horizon (cm)
0 bar
.33 bar
1 bar
15 bar
Kluvex> Westj West Pit
311P
312P
313P
314P
315P
245P
246P
247P
248P
249P
250P
296P
297P
298P
299P
300P
301P
302P
Al
B2
B3
Clca
C2ca
Al
B2
B3ca
Cl
C2
C3
Al
Bl
B2
B3
Cl
C2
C3
0-10
10-31
31-40
40-118
118-156
0-10
10-30
30-48
48-64
64-90
90-152
0-13
13-24
24.40
40-50
50-84
84-114
114-152
40.86
48.02
58.81
42.44
34.82
42.76
45.99
42.77
41.34
33.81
Kluver North^
46.14
51.03
49.91
49.54
52.48
43.68
44.37
50.75
51.08
55.18
53.76
60.64
Kluver North;
43.19
57.02
48.35
48.48
48.70
47.05
43.48
41.92
51.71
50.81
49.34
50.36
45.83
44.12
15.20
13.45
23.56
14.62
10.56
East
14.68
15.95
20.15
17.39
21.64
18.00
West
13.60
13.09
11.27
15.68
14.80
12.76
14.36
11.96
19.31
14.90
12.06
Pit
13.79
15.41
19.56
17.75
20.06
17.77
Pit
12.33
16.01
13.04
15.40
15.75
13.38
10.64
11.43
10.26
11.61
7.41
10.61
11.47
9.92
11.61
7.57
11.35
12.59
14.75
14.95
16.39
14.29
11.45
12.12
14.36
15.46
16.16
15.74
10.45
11.06
11.06
13.08
11.97
13.60
10,
11,
10,
13.
12.
21
18
74
06
56
4.86
6.93
5.87
5.32
3.65
5.02
7.60
5.29
5.31
3.49
7.43
7.25
8.17
7.56
8.78
7.58
7.15
7.15
8.13
7.38
8.72
7.89
11.02
6.10
6.50
6.81
7.05
6.58
4.83
5.67
6.48
6.20
7.05
6.60
5.28
-------
TABLE 2.2. CONTINUED.
VO
oo
Sample Depth
number Horizon (cm)
0 bar
.33 bar
1 bar
15 bar
Kluvei3 Easts South Pit
283P
284P
285P
286P
287P
288P
Al
B2ca
B3ca
Clca
C2ca
C3
0-10
10-20
20-28
28-46
46-108
108-152
57,79
53.77
50.11
54.42
38.08
34.44
52.23
55.16
31.00
54.37
38.24
36.38
18.00
22.38
22.55
20.73
12.30
11.87
18.15
20.37
23.44
21.04
12.55
12.25
15.31
15.83
16.24
15.63
9.31
9.55
15.00
15.59
16.79
15.59
9.27
10.24
8.76
8.30
8.68
8.48
4.72
4.79
8.09
8.86
8.19
8.02
4.55
4.59
-------
TABLE 2.3. CHEMICAL CONSTITUENTS OF COLSTRIP STUDY SITE SOILS
Sample
number
Horizon
Depth
(cm)
Organic
matter
Lime
N
Total P
Inorganic
P
Bicarbonate
P
Hay Coulee, North Pit
MD
270P
271P
404P
272P
273P
274P
275P
262P
264P
403P
265P
267P
268P
269P
Al
B21
Dupl.
B22
B3
Cl
C2
Al
B2
Dupl.
B3ca
Clca
IIC1
IIC2
0-12
12-20
12-20
20-33
33-43
43-90
90-152
0-10
10-20
10-20
20-33
33-62.5
62.5-85
85+
1.5
1.0
1.1
0.9
0.9
0.7
0.3
1.6
1.3
1.6
1.2
0.7
0.4
0.3
7.4
7.4
7.4
8.3
8.5
8.4
8.9
Hay Coulee
7.1
7.1
7.0
9.9
8.0
8.1
8.4
5.0
4.6
11.8
23.6
22.6
15.8
15.2
j South
0.0
0.0
0.0
4.2
11.4
14.8
15.6
Kluvev West, East
6.7
7.5
7.6
8.0
8.2
8.4
8.5
0.0
1.8
2.4
14.2
12.8
11.2
10.8
0.108
0.105
0.110
0.068
0.037
0.028
0.018
Pit
0.108
0.081
0.082
0.075
0.062
0.055
0.021
Pit
0.105
0.101
0.100
0.090
0.052
0.025
0.016
0.045
0.042
0.041
0.045
0.042
0.040
0.034
0.050
0.050
0.045
0.056
0.050
0.039
0.036
0.030
0.030
0.026
0.033
0.035
0.034
0.030
0.030
0.035
0.031
0.039
0.037
0.032
0.032
1
2
1
1
1
1
5
2
2
2
2
1
1
2
5
1
1
1
1
1
1
-------
TABLE 2.3. CONTINUED.
o
o
Sample
number Horizon
Depth
(cm)
Organic
matter
(7\
\/o)
Inorganic
Lime N Total P P
pH (%) (%) (%) (%)
Bicarbonate
P
(%)
245P
246P
247P
248P
249P
250P
Al
B2
B3ca
Cl
C2
C3
0-10
10-30
30-48
48-64
64-90
90-152
1.2
1.1
1.0
0.8
1.0
0.6
296P
297P
298P
299P
3 OOP
301P
302P
Al
Bl
B2
B3
Cl
C2
C3
0-13
13-24
24-40
40-50
50-84
84-114
114-152
1.5
0.9
1.0
1.0
0.7
0.4
0.4
Kluvev West* West Pit
7.0 0.0
7.0 0.0
8.1 12.6
8.5 15.6
8.6 10.0
Kluver North^ East
6.8 0.0
7.7 0.8
8.2 10.8
9.3 11.4
8.5 12.6
8.5 7.2
Kluve? Norths West
6.8 0.0
7.0 0.0
7.6 2.0
7.8 1.6
8.5 13.2
8.5 14.0
8.4 17.8
0.089
0.073
0.064
0.038
0.013
Pit
0.085
0.081
0.059
0.052
0.047
0.031
Pit
0.105
0.070
0.074
0.083
0.046
0.027
0.021
0.040
0.043
0.052
0.046
0.043
0.045
0.042
0.038
0.045
0.047
0.040
0.038
0.040
0.030
0.033
0.036
0.036
0.036
0.041
0.032
0.031
0.028
0.032
0.032
0.033
0.036
2
1
1
1
1
2
2
1
1
1
7
3
4
1
2
3
1
3
-------
TABLE 2.3. CONTINUED.
Sample
number
Horizon
Depth
(cm)
Organic
matter
PH
Kluvev East
283P
284P
285P
286P
287P
288P
Al
B2ca
B3ca
Clca
C2ca
C3
0-10
10-20
20-28
28-46
46-108
108-152
1.8
1.3
1.2
1.0
0.4
0.3
7.5
8.0
7.9
8.2
8.5
8.3
Lime
j South
2.2
13.0
17.0
18.4
14.0
12.0
N
Pit
0.125
0.101
0.088
0.085
0.020
0.014
Total P
0.056
0.043
0.040
0.040
0.036
0.034
Inorganic
P
0.032
0.032
0.030
0.029
0.032
0.030
Bicarbonate
P
2
1
1
1
3
4
-------
TABLE 2.4. EXCHANGEABLE IONS OF COLSTRIP STUDY SITE SOILS (MEQ • 100 G-i SOIL)
-1
Sample
number
Horizon
Depth
(cm)
CEC
Ca
Mg
Na
K
K
(ppm)
Hay Coulee, North Pit
270P
271P
404P
272P
273P
274P
275P
262P
264P
403P
265P
267P
268P
269P
Al
B21
Dupl.
B22
B3
Cl
C2
Al
B2
Dupl.
B3ca
Clca
IIC1
IIC2
0-12
12-20
12-20
20-33
33-43
43-90
90-152
0-10
10-20
10-20
20-33
33-62.5
62.5-85
85+
<0.1
<0.1
<0.1
1.2
1.9
36.4
71.6
0.2
0.1
<0, 1
<0. 1
<0, 1
0.1
0.3
0.4
0.1
<0.1
0.1
<0.1
<0.1
27.7
16.8
28.6
13.0
10.5
13.8
14.1
Hay Coulee,
23.3
28.2
17.0
21.4
15.5
12.4
14.7
Kluvev West,
21.8
26.7
15.1
20.8
15,5
9.1
—
—
, —
__
—
—
— —
South Pit
16.0
19.0
10,8
—
—
—
•».—
East Pit
14.3
—
—
•*»•—
—
—
0.2 10.0
5.7
7,4
5.3
4.6
0.2
0.2
0.1
0.8
1.4
3.2
4.4
0.1
0.3
0.6
0.6
0.3
0.2
0.1
0.1
0.1
0.6
0.4
0.4
0.2
0
0.1
0.1
1
230
240
110
65
55
40
55
225
140
170
90
55
40
55
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.6
0.6
0.6
0.3
0.2
0.1
0.1
215
215
235
105
75
35
50
-------
TABLE 2.4. CONTINUED.
o
Sample
number
311P
312P
313P
314P
315P
245P
246P
247P
248P
249P
250P
296P
297P
298P
299P
300P
301P
302P
Horizon
Al
B2
B3
Clca
C2ca
Al
B2
B3ca
Cl
C2
C3
Al
Bl
B2
B3
Cl
C2
C3
Depth
(cm)
0-10
10-31
31-40
40-118
118-156
0-10
10-30
30-48
48-64
64-90
90-152
0-13
13-24
24-40
40-50
50-84
84-114
114-152
S04 CEC Ca Mg Na
Kluver West* West Pit
0.1 9.8 6.6 2.3 <0.1
1.9 12.8 10.2 2.3 <0.1
<0.1 8.8 — — <0.1
<0.1 7.8 — — 0.1
3.9 5.0 — — 0.5
Kluvev North* East Pit
0.4 24.4 15.3 5.2 0.1
<0.1 25.6 — — 0.1
<0.1 24.7 — — 0.1
<0.1 24.5 ~ — 0.1
<0.1 29.6 — — 0.3
1.7 24.7 — — 1.0
Kluvetf North* West Pit
0.2 18.1 13.0 3.6 <0.1
0.2 20.4 14.3 4.7 <0.1
<0.1 11.5 — — <0.1
^ w « 1. JL ^ • o — — — — ^ U • JL
<0.1 10.4 — — <0.1
<0.1 10.2 — — 0.1
0.3 7.1 — — 0.1
K
0.4
0.4
0.2
0.1
0.1
0.4
0.2
0.2
0.2
0.2
0.2
0.4
0.5
0.3
0.3
0.2
0.2
0.1
K
(ppm)
175
155
60
50
50
175
90
65
75
65
80
160
180
115
110
65
65
55
-------
TABLE 2.4. CONTINUED.
Sample
number
283P
284P
285P
286P
287P
288P
Horizon
Al
B2ca
B3ca
Clca
C2ca
C3
Depth
(cm)
0-10
10-20
20-28
28-46
46-108
108-152
S04 CEC Ca Mg
Kluver East, South Pit
<0.1 25.5
<0.1 20.6
<0.1 18.6
<0.1 15.4
0.3 10.0
13.5 10.6
Na
<0.1
<0. 1
0.1
0.1
0.1
0.8
K
0.6
0.2
0.1
0.1
0.1
0.1
K
(ppm)
235
95
50
45
35
40
-------
TABLE 2.5.
PRECIPITATION AMOUNTS AT COLSTRIP VICINITY STUDY
SITES, 1976 *
Date
4-15 f
4-21
4-23
4-27
4-28
4-29
5-05
5-06
5-11
5-12
5-14
5-17
5-24
5-26
5-29
5-31
6-02
6-03
6-05
6-07
6-09
6-11
6-13
6-15
6-17
6-18
6-21
6-23
6-24
6-25
6-28
7-02
7-05
7-13
7-16
7-30
8-03
Hay
Coulee
§
0.84
0.64
0.24
1.01
0.02
0.20
0.63
0.23
___—
0.03
0.18
0.34
0.03
0.16
0.40
0.15
0.03
0.60
1.06
0.53
0.46
0.63
0.03
0.20
0.14
0.30
-
0.05
East
_
0.54
1.80
_.
_. — _
0.66
0.14
0.00
— -
_r,_r-
0.22
0.10
_,
0.68
_, — „
1.57
0.46
0.53
0.46
0.15
0.10
0.20
0.40
— — -~"—
Kluver
North
0.56
0.60
_,—,-
1.78
— — T- —
— , —
0.80
0.25
0.07
_,
0.36
_ — — —
0.00
— — —
0.59
__.«. f^.
__.._
2.03
0.46
0.29
0.70
0.25
0.04
0.17
~~~"
West
— . —
0.66
_,
1.58
— — —
— — ——
— — —
0.83
0.32
0.20
_-__—
—
0.30
«•»_.»•«• —
0.01
*"** ^™ "*" ^™
-™ — «" —
2.14
0.50
0.23
0.97
0.21
0.02
0.14
(continued)
105
-------
TABLE 2.5. (continued)
Date
8-16
8-19
8-24
8-26
8-28
9-03
9-07
9-15
9-20
9-27
10-04
10-06
10-07
10-18
10-27
11-02
11-18
Hay
Coulee
0.04
0.02
„
0.36
0.03
0.05
0.22
0.06
0.28
0.05
0.35
0.01
0.03
East
0.07
0.25
0.02
0.38
_,
0.30
0.09
0.18
-0.65 ^
._._
Kluver
North
0.07
0.00
0.10
— , —
0.33
0.02
0.22
0.03
— , —
0.17
-0.65 y
....
West
0.05
0.13
0.10
0.30
0.02
0.07
0.02
— , —
0.28
-0.65 ^
_
"™ ^™ ™™ ™™
Inches accumulated following previous reading
1 Beginning date of record
§
Hyphens indicate no reading taken
^ Til
r 7 snow
106
-------
SECTION 3
PLANT COMMUNITY MONITORING
J. E. Taylor and W. C. Leininger
ABSTRACT
Plant community studies have been conducted
near Colstrip since 1974. These include estimates
of species cover, diversity (based on number and
canopy coverage), and phenology. Photographic
records, both aerial and ground-level, also are
being made. Data are collected within the ex-
closures established by the EPA and on three
contiguous relict knolls along Rosebud Creek.
In addition, an aerial photo transect from Col-
strip southeast to Greenleaf Creek is periodi-
cally flown. Graminoids and lichens are the
dominant vegetational components influencing
cover, number, and diversity. The abundance of
annual grasses varies markedly among sites, and
this strongly affects diversity through reduced
equitability. Previous grazing history and vari-
ations in yearly climatic conditions, which are
primarily responsible for the observed differences
in plant species composition, have so far masked
any pollution effects. Our data suggest a pre-
dictive relationship between plant diversity and
range condition. Phenology data have been more
useful in interpreting aerial photography than
in directly monitoring plant community changes.
May and June aerial photo missions were flown
with fixed wing aircraft in 1977. In August, the
Colstrip sites were flown at larger scale from a
helicopter. This photography contributes to the
long-term baseline/response record. In addition,
site mapping is proceeding with these photographic
base maps.
107
-------
INTRODUCTION
This research was begun 15 July 1974 to monitor bioenvironmental effects
of coal-fired electric generating plants in southeastern Montana. Our
objectives are:
1. To characterize pre-treatment native plant communities in
areas likely to be affected by fossil fuel power plants.
2. To develop measurement techniques and monitor changes in plant
community structure, diversity, phenology and species composi-
tion following air pollution stress.
3. To develop methods which can be used to predict bioenvironmental
changes following fossil fuel power generation in other areas.
The data reported in this section cover only our research activities
in the vicinity of Colstrip, Montana. In addition to four exclosures es-
tablished and maintained by the EPA, three relatively pristine knolls are
being examined (Figure 3.1.). Previous work and study site descriptions
have been summarized by Taylor and Leininger (1977).
MATERIALS AND METHODS
Plant community analysis and photographic monitoring are discussed in
detail below.
Plant Community Analysis
Canopy Coverage
Canopy coverage estimates were made on all study sites in either late
August or early September, 1977. Sample plots within study areas were
located by placing a cord with meter-spaced knots in a random meandering
pattern through the sample area. Then 2 x 5 dm plot frames were placed at
each knot and canopy coverage estimated using the procedures of Daubenmire
(1959). Two sets (lines) of 25 frames each were sampled.
Species Diversity
The diversity index used was the Shannon-Weaver function (Shannon and
Weaver, 1949):
HT = - £
Ni
N
log,
Where HT = Index of diversity
S = number of species
Ni- = number of ith species
N = total number of all species
For canopy coverage diversity, percent canopy estimates were used.
Canopy coverage and species and individuals per species were recorded for
each frame concurrently. Both kinds of data have been analyzed to character-
ize the species diversity of each study site.
108
-------
POWDER RIVES COUNTY
Figure 3.1.
Study sites in the vicinity of Colstrip.
(1= Hay Coulee, 2 = Kluver West, 3 = Kluver North,
4 = Kluver East, 5 = McRae Knolls)
109
-------
In addition to diversity, these data were used to calculate evenness
(equitability) and species richness.
Evenness was calculated with the equation of Pielou (1969) .
m Where JT = Evenness
o - HT = Shannon-Weaver index
-, o
2 S = total number of species
Species richness is the numerical sum of species which were used to
calculate H1 .
In order to reduce variances and still be able to calculate standard
errors, data were grouped by five consecutive frame sums (cover) or means
(number) before H? or J' were calculated. S was the total number of species
encountered in each five-frame group.
There were a number of species on the sites which were never encountered
in the diversity samples. A list of all species observed is presented as
Appendix 3.1.
Plant Phenology
Upon each visit to an experimental site, the modal phenological stage
of each identifiable plant species is characterized. The classification
system is shown in Table 3.1.
TABLE 3.1. PLANT PHENOLOGY INDEX
Stage of Growth
1
2
3
4
5
6
7
8
9
10
11
12
First growth
First leaves fully expanded
Active vegetative growth
Vegetative growth mostly complete
Boot stage, first floral buds
Exsertion of grass inflorescences, earliest flowers
Reproductive culms fully extended
Anthesis, full flowering
Fruit developing
Fruit ripe
Dehiscence
Vegetative maturity, summer or winter dormancy,
leaf drop, annuals dead
Note: seedlings, basal rosettes, etc., handled in notes; fall greenup
recorded as Code 3.
110
-------
Photographic Studies
Ground Level Photography
Ground level photography provides a detailed record of plant species,
phenology, and pathologic signs. This assists in the interpretation of
aerial imagery. Also, vertical ground photo plots may be measured and
analyzed for cover, number, frequency, pattern, and plant volume. Plant
volume, which can be used to estimate biomass, may be obtained by combining
canopy coverage and height, the latter measured with a parallax wedge.
Plant density and pattern also can be studied from these pictures.
At the Hay Coulee and Kluver sites, two photo plots were established in
each exclosure, while one photo plot was placed on each of the three McRae
Knolls.
The photo plots are 1 meter square in area, and are marked for reloca-
tion. Each is photographed in color and black-and-white film emulsions.
Stereoscopic photography is used for ease of plant identification. Most
of the plots have also been photographed with infrared color film. More
details are given by Taylor et at., 1976.
Aspect photographs are made from vantage points within and overlooking
study areas. These are taken with color and infrared color film, the latter
to compare with aerial coverage.
For each photo plot an index of species identification has been pre-
pared. The combination of plot photographs and plot indices makes a permanent
record of species presence and distribution. Sequential records allow the
evaluation of temporal changes.
Aerial Photography
Low level aerial photography gives a more generalized view of plant
species and community distribution, pathology, and cover than does ground
photography. Further, it yields more detail than higher level imagery and
so represents a useful compromise between detail and comprehensiveness of
coverage.
Low level aerial imagery is most practical for making detailed vege-
tation maps, sensing population-level stresses, or any other purposes re-
quiring large scale synoptic views. It also aids in developing interpre-
tations of smaller scale, high level photography (Taylor, 1976).
For our overflights we use a Cessna 182 airplane which can easily
handle the required elevation range of 500 to 7,000 feet above the ground.
The plane we use is leased from Miles City Aero Services, Miles City,
Montana. This aircraft has been modified by the addition of a 30.5 cm
diameter belly port, which accepts a special camera mount, designed and
manufactured by W. E. Woodcock of Miles City (Woodcock, 1976). The mount
supports a Hasselblad EL/M motor driven camera (70 mm format). It is fitted
with 50 or 80 mm lenses, depending on the desired photo scale.
Ill
-------
In addition to the mounted camera, a second Hasselblad is used as a
hand camera for making oblique photographs from the air. This kind of
photography supplements the more traditional vertical imagery, in that it
is more representative of familiar aspects of scenes for interpretation,
display, etc.
In August, 1977 we contracted with Hawkins and Power, Greybull, Wyoming,
for a helicopter photo mission over the Colstrip sites. Flying altitudes
ranged from 73 to 218 meters, yielding negative scales from 1:900 to 1:2700-
Color negative film was exposed in hand-held Hasselblad cameras while the
helicopter was slowly traversing the targets. Vertical photography was
achieved with a bubble level attached to the camera back.
Color prints of this coverage will be used as base photographs for
detailed vegetation mapping during the 1978 growing season.
We use three primary film types, with other materials for special
purposes. Our main films are color, color infrared and black-and-white
(H&W VTE Pan). Each of these has advantages for particular use.
RESULTS AND DISCUSSION
Plant Community Analysis
Canopy Coverage
The overall canopy coverage (Figure 3.2., Table 3.2.) varies among sites
primarily because of variations in graminoid and lichen composition. The
dominant influences among all sites are soils and previous grazing inten-
sities.
Graminoids represent the largest component of the total vegetation, and
the most significant for livestock grazing. Little difference is observable
among sites, except for the lower canopy cover on Kluver East and Kluver
West. Kluver East apparently is still being influenced by its past grazing
intensity, even though it has been excluded from livestock grazing for four
growing seasons. Also, a substantial portion (over 50%) of its graminoid
composition is contributed by crested wheatgrass. Another third is annual
brome grasses. These species are all early season growers, and were present
in reduced abundance at the time of sampling. Kluver West supported a high
population density of grasshoppers in 1977. This influence was apparent in
reduced cover of both graminoids and forbs.
The reason for the striking variation in lichen cover from one site to
the next still is obscure. Lichens will be studied more intensively in the
coming years.
Mosses never have been a significant component of the vegetation on
these sites. Shrubs vary, but this is inherent in the sites, probably
because of edaphic and microclimatic differences.
112
-------
h-'
UJ
2
<
1
0
0
100 -i
90-
80-
70-
60-
50-
40-
30-
20-
10
^•^MM
1
cc
;
|xxj>
I
*— ^"M
r _ ^~ "I
1
HAY K.WE:
>ULEE
[~] GRAMINOIDS
~~| FORBS
LICHENS
MOSSES
SHRUBS
KNOLL
C
Figure 3.2. Canopy coverage on Colstrip Sites, 1977.
-------
TABLE 3.2. CANOPY COVERAGE (PERCENTAGE) FOR COLSTRIP STUDY SITES, 1977.
SPECIES
GRAMINOIDS
Agropyron oristatum
A. srnithii
A. spicatwn
Aristida longiseta
Bouteloua graoilis
Bromus japonicus
B. tectorum
Carex eleocharis
C. filifolia
Koeleria oristata
Poa sandbergii
Schedonnardus paniculatus
Stipa comata
S. viridula
Vulpia octoflora
FORBS
Alyssum desertorum
Antennaria rosea
Arabis holboellii
Aster sp.
A. falcatus
Astragalus purshii
Comandra wribellata
Erysimum asperum
Gaura coccinea
Grindelia squarrosa
Hay Coulee
31 Aug.
10.95
23.55
5.35
.05
9.45
4.65
.60
.30
.10
.05
.05
Kluver West
1 Sept.
4.20
2.50
1.15
.15
.95
.15
2.30
22.90
.05
.05
Kluver North
1 Sept.
3.35
.05
20.50
.65
.15
.30
2.30
18.40
.05
.05
Kluver East
2 Sept.
19.20
2.65
.65
10.40
.15
1.00
.10
.45
.05
.15
.35
McRae
Knoll A
3 Sept.
1.25
1.05
14.30
.90
14.75
.35
.60
19.75
.05
.05
McRae
Knoll B
3 Sept.
2.10
7.55
.05
8.15
.95
.05
5.75
13.80
.15
13.80
.05
.05
.05
.10
McRae
Knoll C
31 Aug.
1.65
2.20
18.40
26.80
.50
.25
21.05
,05
1.00
.40
-------
TABLE 3.2. (continued)
Ul
SPECIES
FORBES (continued)
Lactuca sevriola
Lomatiim sp .
Lugodesmia ^unsea
Mammillaria missoiwiensis
Medic ago saliva
Melilotus officinalis
Opunlia fragilis
0. polyacanlha.
Phlox hoodii
Poly gala alba
Polygonum wlwipaTim
Psoralea apgophylla
Sphaevaloea coQcinea
Taraxacum offloinale
Tragopogon dubius
HALF- SHRUBS AND SHRUBS
Artemisia oana
A. dracunculus
A. fvigida
A. tvidentata
Atviplex nu'ttallii
Ceratoides lanata
Chrysothamnus nauseosus
Xanthoeephalum sapothrae
Hay Coulee Kluver West Kluver North Kluver East
31 Aug. 1 Sept. 1 Sept. 2 Sept.
.05
.10
.20 .05
.75
.05 .30
.05
.15
2.00 .65 .50 .85
3.85 1.00 6.05 2.30
.80
.05
2.80 .05 9.50 3.15
4.20
.75
McRae
Knoll A
3 Sept.
3.75
2.05
.05
1.15
.10
.45
.35
2.85
McRae McRae
Knoll B Knoll C
3 Sept. 31 Aug.
.80
.05
1.50
.75
.05 .40
.80
1.60
.10
.55
.05
.95 .10
1.45
.05
2.80 2.30
.75
.95
.30
.30
-------
TABLE 3.2. (continued)
SPECIES
OTHERS
Bare ground
Litter
Moss
Lichens
Rock
TOTAL VEGETATION
TOTAL GRAMINOIDS
TOTAL FORBS
TOTAL SHRUBS
Hay Coulee
31 Aug.
13.25
73.15
.80
4.60
.35
75.55
54.90
6.70
8.55
Kluver West
1 Sept.
14.80
64.75
.10
11.05
1.05
47.75
34.35
2.00
.05
Kluver North
1 Sept.
22.30
64.35
.05
3.20
.10
65.95
45.70
7.45
9.55
Kluver East
2 Sept.
15.15
58.10
.05
23.25
.10
64.90
34.40
4.05
3.15
McRae
Knoll A
3 Sept.
7.30
81.55
2.70
.40
66.60
52.95
8.10
2.85
McRae
Knoll B
3 Sept.
23.20
58.80
.45
8.40
2.40
73.20
51.30
6.55
6.50
McRae
Knoll C
31 Aug.
12.85
74.15
2.05
2.25
1.00
80.30
70.85
2.80
2.35
-------
Species Diversity
Inter-site diversity, evenness, and species richness based on canopy
coverage and number are shown in Figure 3.3.
As in the past years, the diversity (cover) at Hay Coulee and Knoll B
is significantly higher than that at the other sites. This tendency does not
appear at Hay Coulee when diversity is based on plant numbers. Furthermore,
number-based diversity is much more variable over all than that derived from
cover. This is attributable to variation in annual grass composition.
Where large numbers of annual grasses are present, evenness is depressed,
resulting in a corresponding reduction in the diversity index.
Species richness varies among sites, with Hay Coulee and Knoll B
having the most species. In some instances, notably Kluver North, the low
richness has a dampening effect on diversity, although evenness is high.
The sensitivity of diversity indices to differences in sites and range
condition has been discussed previously (Taylor et al. •> 1975). When even-
ness and richness are examined individually they follow similar patterns
and help to elucidate diversity trends.
Plant Phenology
Phenological data are presented in Appendices 3.2 and 3.3.
The most intense phenological sampling in 1977 was done on the McRae
Knoll site. We felt that since the Knolls had not received any livestock
use for a number of years, there would be no confounding deferment effect
which all of the other sites have exhibited since they were fenced in 1974.
Further, the Knolls represent a variety of soils, exposures, and plant
communities in a relatively small area. Finally, we had more aerial photo-
graphy and better background data due to a related graduate study on the site,
We have been disappointed in the inability of phenology measurements to
reflect subtle seasonal or annual changes in plant community structure. It
appears that an adequate phenological baseline would require a number of
years to develop, since this parameter is so variable, even in the absence
of substantial stress.
Phenology data have been helpful in explaining some species signatures
in aerial photography. A key of plant species identification based on
phenological changes in photographic signatures will be completed during
Spring, 1978. This key should be very useful in interpreting aerial photo-
graphy on a variety of sites in the Northern Great Plains.
117
-------
B
30
29
28
27
26
£25
12-4
y 2.3
z>
u_ 22
cr
uj 2 I -
UJ 2.0
•2L 19
O
^ 1-8-
\ 7
1.6
I 5
1.4
A
< x CANOPY
> o NUMBERS
I-
1 1 1 1 1 1 1
HAY KLUVER KLUVER KLUVER McRAE McRAE McRAE
COULEE WEST NORTH EAST KNOLL KNOLL KNOLL
ABC
.7-
co
CO
UJ
>
UJ .6
.5-
t
x x CANOPY
NUMBERS
HAY KLUVER KLUVER KLUVER McRAE McRAE McRAE
COULEE WEST NORTH EAST KNOLL KNOLL KNOLL
ABC
14-1
13-
12 -
CO
CO
UJ
-Z
X
o
o:
10-
co 9 -
O
LJ
0.
CO
8-
7-
6-
x » CANOPY
• • NUMBERS
X±S-
HAY KLUVER KLUVER KLUVER McRAE McR_AE McRAE
COULEE WEST NORTH EAST KNOLL KNO'LL KNOLL
ABC
Figure 3.3.
A=Diversity Index (HT),
B=Evenness (J'), and
C=Species Richness (s)
for Colstrlp Sites,
1977.
118
-------
Photographic Studies
Ground Level Photography
We are continuing to obtain ground level plot photos and oblique aspect
pictures of each study location. This visual record has proven extremely
useful in corroborating temporal differences detected in quantitative
sampling.
Preliminary photo analysis has suggested that some kinds of quanti-
tative data (cover and density) can be derived with stereoscopic analysis
of photo plots. This work will be expanded in the future.
Aerial Photography
Because of the lack of overt stress signs attributable to air pollution,
the aerial monitoring of the Colstrip sites is limited to one or two obser-
vations annually. The primary value of this photography now is as a con-
tinuing record of any subtle changes which might be occurring. In the event
of cumulative stress sufficient to trigger undesirable vegetational changes,
the rate and nature of such changes will be documented. A list of the aerial
photo coverage of the Colstrip sites is included in the comprehensive list in
Appendix 24.1.
CONCLUSIONS
A record of plant community diversity, cover, and phenology is
continually being collected and refined in the vicinity of Colstrip, Montana.
The native vegetational communities represented at the various experimental
sites are being thoroughly characterized, so that any changes which may occur
due to chronic exposure to air pollutants may be documented.
Thus far, no effects positively linked with air pollution have been
observed. It is quite likely that at the level of stack emissions currently
being received, it will take a number of years before any effects are noted.
Procedures developed here should have wide application in other grass-
land situations where coal-fired power plants are being contemplated or
operated.
119
-------
REFERENCES
Daubenmire, R. F. 1959. A Canopy-Coverage Method of Vegetational Analysis.
Northw. Sci., 33(l):43-64.
Pielou, E. C. 1969. An Introduction to Mathematical Ecology. J. Wiley &
Sons, N.Y. 286 pp.
Shannon, C., and W. Weaver. 1949. Mathematical Theory of Communication.
Univ. Illinois Press, Urbana. 117 pp.
Taylor, John E. 1976. Photographic Monitoring of Air Pollution Impacts on
Rangeland. Abstr. Ann. Mtg. Soc. Range Mange., Omaha, Nebraska, p. 19-
Taylor, J. E. and W. C. Leininger. 1977. Baseline Vegetational Studies
near Colstrip, Montana. Montana State University Mimeo, Bozeman. 67 pp.
Taylor, J. E., W. C. Leininger, and R. J. Fuchs. 1975. Baseline Vegeta-
tional Studies near Colstrip. In: Proc. Ft. Union Coal Field Symp.,
Mont. Acad. Sci., Billings, Montana, pp. 537-551.
Taylor, J. E., W. C. Leininger, and R. J. Fuchs. 1976. Monitoring Plant
Community Changes due to Emission from Fossil Fuel Power Plants in
Eastern Montana. In: The Bioenvironmental Impact of a Coal-fired
Power Plant, Second Interim Report, Colstrip, Montana, June, 1975.
R. A. Lewis, N. R. Glass, and A. S. LeFohn, eds. EPA-600/3-76-013,
U. S. Environmental Protection Agency, Corvallis, Oregon, pp. 14-40.
Woodcock, W. E. 1976. Aerial Reconnaissance and Photogrammetry with Small
Cameras. Photogrammetric Eng. and Remote Sensing, 42(4):503-511.
120
-------
APPENDIX 3.1.
PLANT SPECIES ENCOUNTERED IN COLSTRIP STUDY SITES, 1974 - 1977,
SYMBOL
SPECIES
Hay
Coulee
Kluver
East
Kluver
West
Kluver
North
McRae
Knoll A
McRae
Knoll B
McRae
Knoll C
GRAMINOIDS
AGCR
AGSM
AGSP
ARLO
BOCU
BOGR
BRJA
BRTE
CAMO
CALO
CAREX
GAEL
CAFI
KOCR
MUCU
ORHY
POA
POPR
POSA
SCPA
SCSC
SPCR
STCO
STVI
VUOC
Agropyron cristatim
A. smithii
A. spieatum
Aristi-da longiseta
Bouteloua curt-ipendula
B. grao-itis
Bromus japonicus
B. teatoriun
Calamagrost'is montanensis
Calamovilfa longifoli-a
Carex species
C. eleochar-is
C. filifolia
Koeleri-a cpistata
Muhlenberg-ia cuspidata
Oryzopsis hymenoides
Poa species
P. pratensis
P. sandbergii
Schedonnardus panioulatus
Sch-izachyrium scoparium
SpOTobolus GTyptandrus
Stipa oomata
S. viridula
Vulpia ootofloTa
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
-------
APPENDIX 3.1. (continued)
SYMBOL
SPECIES
Hay Kluver Kluver Kluver McRae McRae McRae
Coulee East West North Knoll A Knoll B Knoll C
to
KJ
ACMI
AGGL
ALTE
AIDE
AMPS
ANOC
ANPA
ANTEN
ANRO
ARHO
ARLU
ASTER
ASCA
AS FA
ASTRA
ASCR
ASGI
ASPU
ASST
CANU
CASE
GEAR
CIUN
COL I
COUM
COCA
CREPI
CRYPT
DEB I
DESCU
FORBS
Achi'llea mille folium
Agoseris glauoa
Allium text-lie
Atyssum desertorum
Ambrosia psilostachya
Androsaoe occidentalis
Anemone patens
Antennaria species
A. TO sea
Arab-is holboellii
Artemisia ludovioiana
Aster species
A. oampestris
A. falcatus
Astragalus species
A. orassioarpus
A. gilviflorus
A. purshii
A. striatus
Caloohortus nuttallii
Castilleja sessiliflora
Cerastium arvense
Cirsium undulatum
Collomia linearis
Comandra umbellata
Conyza oanadensis
Crepis species
Cryptanthe species
Delphinium biootor
Desourainia species
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
-------
APPENDIX 3.1. (continued)
ho
U5
SYMBOL
DRABA
ECPA
ERIGE
ERDI
ERPU
ERAN
ERAS
EVPI
GACO
GRSQ
HASP
HEHI
HEVI
HYFI
LAPU
LASE
LEPID
LEDE
LEMO
LIPU
LIFE
LIRI
LIIN
LIRU
LOMAT
LOOR
LYJU
MAMI
MESA
MEOF
SPECIES
FORBS (cont.)
Draba species
Eohinaoea palli-da
Ev-igevon species
E. DiveTgens
E. pumilus
Ep-iogonum annuum
Erysimwn asperum
Evolvulus p-Llosus
Gaura cocc-inea
Gri.ndel'ia squarTosa
Haplopappus spinulosus
Eedeoma hispida
HeteTotheca wlllosa
Hymenopappus filifolius
Lactuoa pulchella
L. sevriola .
Lep-id-ium species
L. densifloTum
LeuoocT-inum montanum
Liatris punotata
L'Lnwn pevenne
L, T-igidum
L-ithospeTmwn incisim
L. Tudevale
Lomati-im species
L. orientale
Lygodesm-ia juncea
Marrml11ar"la missouri-ensis
Medicago sativa
Mel-ilotus officinalis
Hay
Coulee
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Kluver
East
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Kluver
West
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Kluver
North
X
X
X
X
X
X
X
X
X
X
X
X
X
McRae
Knoll A
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
McRae
Knoll B
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
McRae
Knoll C
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
-------
APPENDIX 3.1. (continued)
SYMBOL
SPECIES
Hay Kluver Kluver Kluver
Coulee East West North
McRae McRae McRae
Knoll A Knoll B Knoll C
MIL I
OESE
OPUNT
OPFR
OPPO
ORLU
OXYTR
PENST
PEAL
PEPU
PHLOX
PHHO
PLPA
PLSP
POAL
POVI
PSAR
PSES
RACO
SENEC
SECA
SIAL
SOLID
SOMI
SOOC
SPCO
TAOF
TRDU
VINU
YUGL
FORBS (cont.)
Mirabili-s linearis
Oenothera seTTalata
Opuntia species
0. fragilis
0. polyaoant'ha
Ovthooavpus luteus
Oxytropis species
Penstemon species
P. albidus
Petalostemon purpurewn
Phlox species
P. hoodii
Plantago patagonioa
P. spinulosa
Poly gala aTba
Polygonim vivipaTum
Psoralea argophylla
P. esoulenta
Ratibida oolumnifera
Seneoio species
S. oanus
Sisymbrium altissimwn
Solidago species
S. mi-s souri-ensi-s
S. oooidentalis
Sphaeraloea oooo-inea
Taraxacum offioinale
Tragopogon dub-ius
Viola nuttalli-i-
Yucca glauca
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
-------
APPENDIX 3.1. (continued)
SYMBOL
SPECIES
Hay Kluver Kluver Kluver McRae McRae McRae
Coulee East West North Knoll A Knoll B Knoll C
ho
Ln
FORBS (cont.)
ZYVE Zygadenus verienosus
HALF-SHRUBS AND SHRUBS
ARCA Artemisia oana
ARDR A. dpaounoulus
ARFR A. fx>igida
ARTR A. tridentata
ATCA Atriplex canescens
ATNU A. nuttallii
CELA CeTato'ides lanata
CHNA Chrysotharmus nauseosus
JUSC Juni-perus seopulorum
PRVI Prunus wivg'in'iana
RHTR Rhus trilobata
ROSA Rosa species
XASA Xanthocephalim sarothi>ae
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X X
X X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
-------
APPENDIX 3.2.
I/
PHENOLOGICAL PROFILE FOR COLSTRIP VALIDATION SITES, 1977—
PHENOLOGICAL CODE
SPECIES
Hay Coulee Kluver West Kluver North Kluver East
3 Sept. 1 Sept. 1 Sept. 2 Sept.
GRAMINOIDS
Agropyron cr-istatwn
A. smith-ii
A. sp-icatwn
Aristida long-iseta
Bouteloua graoilis
Bromus japonicus
B. teetorim
Calamovilfa long-ifol-ia
Car ex f-it-ifolia
Koeler-ia cri,stata
Poa sandbergi-i
Schedonnardus pan-iouiatus
Sporobolus cTyptandTus
Stipa comata
S.
FORBS
Ach-lllea millefol-iim
Alyssum desertonm
Ambrosia ps'ilostac'hya
Antennar-ia species
Asolep-ias vertiGiHata
Aster species
Astragalus drwrmond-i-i
A. purshLi-
Calochortus nuttall'i'i
Chaenaoti-s douglasii
Chenopodiim albwn
C-irsiim undulatum
Erigeron diver gens
Eriogonum annuwn
Erysirrrum asperwn
Evolvulus p-ilosus
Gaura cocc-inea
Gr-indel-ia squarrosa
Eeterofheoa villa sa
Laotuoa serr-iola
L-inwn perenne
— Codes are given on p. 110
3 & 12
12
11
12
12
12
11
3
3 & 12
3 & 12
3
3
3 & 12
12
12
12
8 & 11
3 & 12
12
8
11
12
10
12
12
12
12
12
12
12
12
12
12
3 & 12
12
12
12
8
11
11
11
12
12
12
12
12
11
12
11
12
10
12
12
11
3 & 11
12
12
12
3 & 8
12
12
11 & 3
12
11
11
12
12
12
4
12
12
12
12
12
3 & 11
8
3
12
12
8
12
126
-------
APPENDIX 3.2. (continued)
PHENOLOGICAL CODE
SPECIES
Hay Coulee Kluver West Kluver North Kluver East
3 Sept. 1 Sept. 1 Sept. 2 Sept.
FORBS (cont.)
Lomatiwn species
Lygodesmia juncea
MccmmLllaria missowdensls
Melilotus offioinalls
Opunti-a fTag-ills
0. polyaoantha
Penstemon species
Phlox hoodll
Plantago splnulosa
Polygala alba
Polygomm wivipaTum
Psoralea argophylla
Rattbida eolwnnifeva
Seneolo canus
Sisymbz>-iwn altlss-imum
Solldago m-issonr-iensi-s
Sphaeralcea oocdnea
Taraocacum offic-inale
Tragopogon dublus
Artemis-la cana
A. draeunculus
A. frigida
A. tridentata
Ceratoides lanata
Prunus virg-iniana
Xanthocephalim sarotlwae
12
12
12
12
12
12
12
12
12
12
12
9
12
3 & 12
3 & 12
9
9
9
9
10
12
8
3 & 12
12
6
6
12
12
12
12
11
12
12
12
3
12
10
10
10
11
12
12
12
12
3
3 & 12
127
-------
APPENDIX 3.3.
I/
PHENOLOGICAL PROFILE FOR McRAE KNOLLS, 1977 —
(Pooled for 3 Knolls)
PHENOLOGICAL CODE
SPECIES
April April
14 27
June
3
June
27
July
22
Sept.
3
GRAMINOIDS
Agropyron smithii
A. spicatwn
Aristida longiseta
Bouteloua ourtipendula
B. graoiiis
Brornus sp. *
B. inermis
B. japonicus
B. teotorwn
Calamovilfa longifolia
Car ex filifolia
Elymus oanadensis
Koeleria cristata
Muhlenbergia ouspidata
Oryzopsis hymenoides
Poa prat ens-is
P. sandbergii
Schizachyrium scopariim
Sporobolus QTyptandrus
Stipa oomata
S. wiT-idula
Vulpia octoflora
FORBS
Aoliillea millefol-iwn
Alliim textile
Ambrosia psilostaohya
Androsaoe oooidentalis
Antennaria sp.
Arabis holboellii
Artemisia ludovioiana
1
1
1
1
2
2
12
4
2
3
12
1
1
1
3
12
1
12
3
3
1
2
3
3
1
8
3
4
12
3
3
12
5
4
3
6
4
3
5
6
6
3
10
8
3
6
8
8
3
6
5
7
4
7
7
3
3
8
10
11
3
11
10
3
10
11
11
3
3
9
9
3
12
10
3
3
12
12
11
3
11
10
10
11
11
11
12
8
12
9
11
8
11
12
12
7
11
12
10
5
12
12
12
5
3 & 12
12
11
11
12
3
11-12
12
12
9
3
3
9
12
12
3 & 12
11
3 & 12
12
12
12
9
12
12
12
9
Includes B. japonicus and B. tectorum, which were indistinguishable on
some dates.
I/
Codes are given on p.110.
128
-------
APPENDIX 3.3. (continued)
PHENOLOGICAL CODE
SPECIES
April
14
April
27
June
3
June
27
July
22
Sept.
3
FORBS (cont.)
Asolepias sp.
Aster campestris
A. faloatus
Astragalus eras si carpus
A. gilviflorus
A. purshii
Calochortus nuttallii
Camelina microcarpa
Campanula rotundifolia
Castilleja sessiliflora
Chaenactis douglassii
Chenopodium album
Cirsium undulatum
Cleome serrulata
Comandra umbellata
Crepis sp.
Cryptanthe bradburiana
Delphinium bioolor
Echinaoea pallida
Erigeron divergens
Eriogonum annuum
E. multioeps
Erysimum asperum
Evolvulus pilosus
Gaura ooooinea
Gil-la oongesta
Gvindelia squarrosa
Helianthus annuus
Heterotheoa villosa
Laotuoa pulehella
L. serriola
Leuooorinum montanum
Liatris punctata
Linum perenne
L. rigidum
Lithospermum inoisim
Lomatium orientale
Lygodesmia juneea
Medicago sativa
Melilotus officinalis
Musineon divarioatum
8
11
12
2
1
2
1
3
12
3
2
3
1
1
12
4
6
1
12
6
12
3
3
3
5
3
8
7
1
3
5
2
1
2
2
4
8
3
8
4
9
6
9
7
5
3
5
9
4
7
3
9
6
3
4
3
3
12
7
5
11
5
5
4
10-11
9
9
9
8
9
1 & 8
9
8
8
3
4
10
7
4
8
6
3
3
12
10
9
12
8
7
12
5
4
12
12
10
8
3 & 10
12
9
8
4
12
12
5
10
8
10
10
12
12
10
10
12
10
10
9
12
12
12
12
12
12
3 & 12
10
12
12
12
8
3 & 12
12
12
12
8
11
9
12
12
12
9
12
11
12
12
10
11
129
-------
APPENDIX 3.3. (continued)
PHENOLOGICAL CODE
SPECIES
April April June June July Sept.
14 27 3 27 22 3
FORBS (cont.)
Oenothera serrulata
Opuntia fragilis
0. polyacantha
Oxytropis sp.
0. besseyi
0. lambertii
Penstemon sp.
P. albidus
Petalostemon purpureum
Phlox hoodii
Plan-tago patagonica
Poly gala alba
Potent-ilia sp.
Psoralea argophylla
P. tenuiflora
Ratibida columnifera
Smilacina sp.
Solidago missouriensis
S. mollis
S. occidental-is
Sphaeralcea coccinea
Taraxacum officinale
Tradescantia occidentalis
Tragopogon dubius
Vicea americana
Viola nuttallii
Yucca glauca
Zygadenus venenosus
HALF-SHRUBS AND SHRUBS
Artemisia cana
A. dracunculus
A. frigida
A, tridentata
Atriplex nuttallii
Ceratoides lanata
Chrysotkamnus nauseosus
Rhus trilobata
Ribes aurem
R. setosum
12
1
1
1
2
12
1
1
2
2
1
2
1
1
1
1
1
1
1
1
3
2
2
2
2
3
2
7
3
3
5
3
4
3
3
3
3
3
3
5
6
6
5
7
5
7
5
9
6
8
10
9
7
7
4
5
5
5
8
7
8
8
7
3
6
12
7
5
9
3
8
12
6
12
10
10
10
3
3
3
3
4
7
3
9
9
3
4
3
3
8
3
10
9
12
10
12
11
12
12
9
12
11
5
6
5
5
9
9
6
10
10
12
10
12
12
12
12
12
12
11
12
12
3
& 12
11
10
10
7
6
12
12
12
3 & 12
12
11
12
12
12
11
10
9
9
8
12
3 &
12
3 &
12
12
12
12
12
9
9
9
10
10
8
11
12
12
130
-------
APPENDIX 3.3. (continued)
PHENOLOGICAL CODE
April April June June July Sept.
SPECIES 14 27 3 27 22 3
HALF-SHRUBS AND SHRUBS (cont.)
Rosa avkansana 4
R. woodsii 1279 10 10
Symphovioarpo s oceidentalis 12 1 5 8 9 10
Xanthocephalwn sarothpae 1233 5 8
TREES
Acer negundo 12 2 8 12 12 12
Amelanohier alnifol-ia 7 9 12 12
Fraxinus pennsylvan-ica 12 2 33 12 12
Juniperus soopulorum 9 12 12
Populus deltoi-des 12 12 12
Prunus virginiana 1 3 99 10 11
Shepherd-la avgentea 1 2 33 10 12
131
-------
SECTION 4
SUMMARY OF OBSERVATIONS OF USNEA HIRTA AND
PARHELIA CHLOROCHROA IN THE COLSTRIP AREA, 1974-77
S. Eversman
ABSTRACT
In this portion of the lichen project, I have been
monitoring the respiration rates, total sulfur content,
percentage of algal plasmolysis, and general thallus
appearance of two lichen species since 1974. The res-
piration rates of Usnea hirta (L.) Wigg. and Parmel-ia
ohloTOchToa Tuck. samples rose significantly in Sep-
tember, 1977, compared to previously collected samples.
Usnea Trivta demonstrated a small decrease in relc'iive
absorbance of light by chlorophyll from 1975 to 1977.
INTRODUCTION
The objectives of this portion of the lichen project have been to:
1) identify baseline lichen community information for the grassland and
ponderosa pine vegetation types; 2) establish baseline anatomical and
physiological conditions of two native lichen species, Usnea hi-Tta (L.) Wigg.
and Parme1i,a cKloTOohroa Tuck. , and 3) continually monitor the species and
communities to detect changes in them that may be attributable to
coal-burning power plants.
The major epiphytic lichen on the ponderosa pine tree is Usnea
A major terricolous lichen is Papme'l'ia chlovockpoa. I have collected and
stored samples of these lichens since 1975, recording respiration rates,
percentages of plasmolyzed algal cells and general thallus condition, and
determining sulfur contents. In 1977, chlorophyll absorption was also
measured.
In addition to analysis of individual samples, I have been annually
recording terrestrial community composition using a point-drop method
(Eversman, 1978) in designated exclosure in the Colstrip area. Epiphytic
lichen communities on the ponderosa pine sites in the Colstrip area and in
parts of the Custer National Forest have been determined by recording per-
centage of epiphytic lichen coverage on tree trunks by species.
132
-------
Traditionally, epiphytic community analyses in polluted areas have
indicated disappearance of lichens (and mosses) in areas close to a polluted
source, with progressive reappearance of species as distance from the source
increases. The ponderosa pines in the immediate Colstrip area, i.e., within
1-20 km, support a very sparse epiphytic community compared with areas of the
Custer National Forest to the south and east. This was true before the
power generating plants were constructed. Therefore, a completely community-
oriented approacu has been impractical. Emphasis has been, and will continue
to be, on the characteristics of individual lichen species, with comparisons
between years and with results from the SO fumigation studies (ZAPS sites).
MATERIALS AND METHODS
The sites and methods have been described previously (Eversman, 1977).
Three ponderosa pine sites, P17, P18, and P19, were added in 1977; site P9
was deleted. Usnea hivta samples from site P10 were transplanted to the new
sites in April, 1977, and samples were collected in September, 1977. I
collected Parmeli,a chloTookroa from the four primary grassland sites and
Usnea hivta from the ponderosa pine sites in July and September each year
(Figure 4.1) .
Respiration rates were determined manometrically for all samples
collected 1975-77. Chlorophyll extract absorbance was determined for
300-mg samples by making three 3-ml methanol extractions, adding methanol
to 10 ml, then reading absorbance on a Beckman DU spectrophotometer at
665 nm. Algal cell counts are made by making 3 microscope slides of lichen
thallus, and counting 100 cells on each slide recording the numbers of
plasmolyzed algal, cells.
RESULTS AND DISCUSSION
This report includes only results of individual species analysis from
1977 that can be compared with 1974-76 information and with the ZAPS sites
results.
Table 4.1 gives annual readings of respiration rates of Paimelia
chloToohToa samples by grassland site. Analysis of variance of most sites
indicated that the samples collected September 1977 had a significantly
(P < .01) greater respiration rate than samples collected at any other time.
A comparison of all samples grouped by month and year indicated that res-
piration rates of P. Morochroa samples collected from the ground on the
ZAPS sites and from the grassland sites showed no significant differences
among ZAPS and field sites in 1975 and 1976.
Comparisons of relative chlorophyll absorbance at 665 nm (Table 4.2) of
field samples and those from ZAPS sites (10-cm height, ZAPS I site,September,
1977, Table 17.7) indicated that the field sample chlorophyll content
except for Kluver East and Hay Coulee samples, was generally higher than
chlorophyll content of those of ZAPS samples. There was no significant
difference among field (Colstrip area grassland) sites.
133
-------
Northern Cheyenne
Reservation
Custer
National Forest
Figure 4.1.
Locations of lichen study sites in the-Colstrip area. Pl-19 are
ponderosa pine sites; Gl-7 are grassland sites. TC is ZAPS I
site.
134
-------
TABLE 4.1. RESPIRATION RATES OF PARHELIA CHLOROCHROA SAMPLES COLLECTED FROM
GRASSLAND SITES 1974-1977.
Location
Gl. Hay
Coulee
G2. McRae
Knolls
G3 . Kluver
West
G4 . Kluver
North
G5 . Kluver
East
Other
Kluver NE-1
BNW #2
Kluver E-l
Pasture
Collection
Number
1
2
3
4
5
6
7
8
1
2
1
2
3
4
5
6
7
1
2
3
4
5
6
1
2
3
4
5
6
Dates
7-20-74
8-30-74
6-26-75
5-14-76
7-16-76
9-15-76
7-07-77
9-13-77
9-15-76
7-07-77
7-21-74
7-07-75
7-16-76
9-15-76
6-20-77
7-17-77
9-13-77
7-21-74
7-07-75
7-16-76
9-15-76
7-07-77
9-13-77
7-21-74
6-26-75
7-14-76
9-15-76
7-07-77
9-13-77
9-13-77
9-13-77
9-13-77
5-14-76
_*
X
314
332
215
458
290
274
310
585
341
367
218
293
272
302
505
252
561
342
349
242
262
314
556
227
r\ -f "7
317
322
321
301
512
606
420
546
371
C1.95
35
68
31
53
47
55
72
85
52
420
25
36
26
37
408
67
586
29
26
9
85
104
127
54
r- /%
50
65
98
209
75
ANOVA F
84217563 83.87
2 1 0.070
7542361 21.15
621543 112.49
634251 35.55
129
127
455
86
^Respiration rates are expressed as mean yl 02 consumed g-hr , of 3 samples
with ± .95 confidence interval.
Results of one-way analysis of variance (ANOVA) and the F value Samples
not sharing the same underline are significantly different (P < .05).
135
-------
TABLE 4.2.
RELATIVE ABSORBANCE AT 665 ran LIGHT BY CHLOROPHYLL EXTRACTS OF PARMELIA CHLOROCEEOA AND
USNEA HIRTA SAMPLES COLLECTED 1975-1977 FROM GRASSLAND AND PONDEROSA PINE SITES.
Usnea
ohloroohroa
GO
Collection
Site Date
East Otter Creek 9-15-75
9-15-75
3-25-77
SEAM 1 7-16-75
7-06-77
7-06-77
SEAM 2 7-16-75
7-06-77
Home Creek Butte 7-16-75
9-15-77
Ft. Howes - tr 9-15-76
- tr 8-17-77
nat 8-17-77
Poker Jim - tr 9-15-76
nat 7-06-77
tr 7-06-77
MVS - nat 9-17-75
nat 7-07-77
tr 7-07-77
X
.273
.258
.211
.294
.230
.246
.373
.221
.251
.240
.223
.243
.188
.168
.156
.120
.213
.378
.174
C1.95
.219
.051
.086
.086
.125
.116
.030
.034
.095
.010
.146
.138
.095
.069
.056
.077
.013
.142
.047
Collection
Site
Kluver West
Kluver North
Kluver East
Hay Coulee
ZAPS I A
B
C
D
Other Sites
Kluver NE-1
Kluver E-l
Date
6-25-75
6-23-77
9-13-77
6-25-75
9-13-77
6-25-76
9-14-77
5-14-76
7-07-77
9-14-77
9-14-77
9-14-77
9-14-77
9-14-77
9-13-77
9-13-77
X
.154
.204
.162
.075
.176
.081
.112
.103
.108
.149
.039
.116
.066
.031
.232
.124
C1.95
.228
.043
.065
.034
.043
.052
.034
.034
.060
.060
.034
.006
.051
0
.102
.069
Values are given as mean relative absorbance of 3 samples with ± .95 confidence interval
-------
Table 4.3 gives respiration rates for Usnea hirta samples from 18
ponderosa pine sites, with analysis of variance for most sites between years
of collection. Site P10 (East Otter Creek) and P15 (Fort Howes Ranger
Station) are considered to be the control sites. The ground-slope of P10
faces southeast, away from the power plant; Fort Howes is a north-facing
slope separated by many hills from the power plants. Other sites are ridges
facing Colstrip.
The latest collection at each site, generally September 1977, has the
highest rate of respiration for most of the sites. These sites, including
grassland sites, are clustered in the Colstrip area, and extend to the
southeast for 70 km. Analyses of variance give these results: 1) Field
samples from all sites in July and September 1975, 1976, and 1977, have
significantly higher respiration rates than samples from ZAPS D (I and II).
2) In 1975 and 1976, there are significant differences between field sites
and samples from ZAPS C, I and II. The results are less clear-cut in 1977.
Part of this is because of the indistinct differences obtained on the ZAPS
sites, plots B and C (Table 17-6). 3) There are no regular or significant
differences between samples from ponderosa pine sites and those from ZAPS A
and B. Samples from the immediate Colstrip areas, P17, P18, and P19, ex-
hibited the same sharp increase in respiration rate obtained on ZAPS I-B
and II-A sites. This is interpreted as a stress response, but whether
or not it is due to transplanting stress, of S02 or both, is not yet certain,
Results of chlorophyll absorption determinations of U. hirta in 1975-
1977 are in Table 4.2. There seems to be a general area-wide decrease,
but not significant, in chlorophyll absorption from 1975-1977. The total
mean values decreased from 0.277 in 1975, to 0.211 in 1976, to 0.207 in
1977.
CONCLUSIONS
There may be indications of stress on lichens in the Colstrip area.
There are sharp respiration rate increases in September 1977 in both
Usnea hirta and ParmeHa chlorochroa samples collected at sites closest to
Colstrip, and a general decrease in chlorophyll absorption in U. hirta.
137
-------
TABLE 4.3 RESPIRATION RATES OF USNEA HIRTA SAMPLES COLLECTED FROM
PONDEROSA PINE SITES 1975-1977.
Location
PI.
P2.
P3.
P4.
P5.
P6.
P7.
P8.
P10
Sarpy
Creek
Castle
Rock +
Kluver
NE-1 =1=
Kluver
E-l 4=
McRae
Hill 4=
Kluver
West
trees
Diamond
Ranch
Buttes 4=
Morning
Star
View =F
native
. East
Otter
Creek
(transplant
source)
Collection
Number
1
2
3
1
r\
3
1
2
1
2
3
4
1
2
i
2
o
A
Date
9-15-75
9-16-76
9-12-77
9-15-75
Q 1 /i 7 A
y J-H- / D
9-12-77
7-08-77
9-13-77
9-15-75
9-15-76
7-07-77
9-13-77
9-13-75
9-13-77
7-16-78
9-15-76
9-13-77
6-20-77
1 6-23-76
2 ! 6-23-77
3 6-23-77
1
2
3
1
9-15-75
9-19-76
7-07-77
7-07-77
1 '• 3-23-76
2 i 6-23-76
3 ! 7-15-76
4 j 8-09-76
5 j 9-15-76
1 i 4-27-77
2 i 6-21-77
3 7-07-77
4
5
6
8-04-77
8-16-77
9-15-77
x'c
640
658
694
640
499
588
620
660
640
573
645
642
640
750
669
633
600
519
744
629
578
640
828
643
728
709
744
463
668
633
743
695
620
735
516
681
C1.95
30
323
380
30
214
124
221
57
30
133
77
62
30
271
124
132 1
ANOVA F
321 0.93
132 8.71
1 2 0.50
3412 2.49
21 8.04
1234 6.28
5 j
127 |
\
i
112 123 3.76
80
298
30
153
134
75
84
112
142
102
132
159
112
100
99
27
136
231 4.03
21453 12.57
142635 3.85
138
-------
TABLE 4.3 (Cont.)
Location
Pll.
P12.
P13.
P14.
P15.
Pi fi
XT XU .
P17.
Seam
Site 1
Seam
Site 2
Home
Creek
Butte
Three
Mile
top
bottom
Fort
Howe*?
i. J.V-/ W v— C?
transplant
i
Collection
Number
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
4
natives 1
2
3
4
5
"P/-\lfQV> T "1 Tn
.C U IXC i. O -L.111
Butte
transplants
natives
BNW
//I
1
2
3
1
2
3
4
5
1
2
i
Date ?
i
7-16-75
7-15-76
7-06-77
7-16-75 f
545
454
746
548
7-15-76 ! 497
7-06-77 ! 629
1
t
t
7-16-75
7-15-76
9-15-77
7-16-75
8-09-76
9-15-76
7-16-75
8-09-76
9-15-76
5-13-75
9-15-76
6-21-77
8-17-77
5-13-75
5-14-76
462
486
765
528
667
692
539
547
500
829
597
675
688
493
576
9-15-76 479
6-21-77 543
8_17_77 487
9-15-75 | 640
9-15-76 669
7-06-77
7-17-75
5-13-76
7-16-76
9-15-76
7-06-77
4-27-77
9-13-77
615
i 630
794
610
654
452
743
964
C1.95
25
27
94
18
119
62
38
119
244
25
189
80
43
99
215
42
107
52
119
54
281
.ANOVA F
312 4.42
312 14.59
321 28.17
321 22.55
213 0.51
1432 18.63
24153 1.13
124
99
119
30 213 0.90
185
144
52
456
77
129
47
159
395
24135 12.03
2JL 3'84
139
-------
TABLE 4.3. (Cont.)
Location
P18
F19
. BNW
// 2
. BNW
# 3
1
Collection
Number
1
2
i
2
Date
4-27-77
9-13-77
4-27-77
9-13-77
-*
X
743
1006
743
935
fT
.95
159
55
159
387
t
ANOVA F
231 9.06
2 1 4.21
Location P9 abandoned after serving as source for 1975 transplants
t
Respiration rates are expressed as yl 0_ consumed g-hr , the mean of 3
samples with ± .95 confidence interval fci).
Results of one-way analysis of variance (ANOVA) and the F value. Samples
not sharing the same underline are significantly different (P < .05).
Transplants from East Otter Creek site.
REFERENCE
Eversman, S. 1978. Soil and Epiphytic Lichen Communities of the Colstrip,
Montana Area. In: The Bioenvironmental Impact of a Coal-Fired
Power Plant, Third Interim Report, Colstrip, Montana. E. M. Preston
and R. A. Lewis, eds. EPA-600/3-78-021, U. S. Environmental
Protection Agency, Corvallis, Oregon, pp. 50-64.
140
-------
SECTION 5
FOLIAR PATHOLOGIES OF PONDEROSA PINE NEAR COLSTRIP
C. C. Gordon, P. C. Tourangeau, P. M. Rice
ABSTRACT
The growth/health/damage characteristics of four
different years of pine foliage collected during 1977
at "pristine" and chronically-polluted sites are
compared and discussed. Growth characteristics of
needle cross-sectional areas and needle lengths are
compared within and between sites via anova. Fluoride
and sulfur concentrations found in needles and
fascicular sheaths from 1977 pine foliage samples are
compared with the findings of 1975 and 1976 studies
reported in the EPA Third Interim Report (TIR).
Similar data obtained from four ponderosa pine-
skunkbush sites being studied with DOE funding in
southeastern Montana are also reported.
Data are presented on the growth/health/damage
characteristics, such as needle mottling, tip necrosis,
and insect damage on pine foliage exposed for different
time periods in chronically-polluted areas. This portion
of our study demonstrates that all air pollution damage
symptoms manifested by the pine foliage being studied
can be and are mimicked macroscopically by abiotic and
biotic causal agents in pristine environments. The
foliar symptoms being measured over time are shown to
increase or decrease in comparison to those found in
pristine areas.
A discussion is presented on a tentative concep-
tual model of chronic air pollution damage to conifer
species. This model is based on sulfur and fluoride
levels in different-aged foliage, as well as on the
increases and decreases of average amounts of growth/
health/damage characteristics of pine foliage over
extended exposure periods.
Fluoride levels found in the foliage of understory
species from the ponderosa pine-skunkbush sites are
also reported.
141
-------
INTRODUCTION
This portion of our EPA-CERL-sponsored studies (Corvallis, Oregon,
Environmental Research Laboratory) in southeastern Montana discusses the
implications of the growth/health/damage characteristics of ponderosa pine
foliage collected from permanent sites located at various distances from
Colstrip, Montana, the site of two 350 MW power plants. Our study also
includes the determination of sulfur and fluoride levels in this foliage and
selected understory species of shrubs, forbs, and grasses. Quantification of
the groxtfth/health/damage characteristics of ponderosa pine foliage collected
from other polluted and pristine ecosystems have rarely been reported in the
scientific literature before studies were initiated in southeastern Montana;
in fact, according to the literature, these characteristics were only occa-
sionally measured and quantified for any coniferous species.
It was our original hypothesis that if the growth/health/damage charac-
teristics of ponderosa pine foliage from southeastern Montana could be
established and quantified before the two Colstrip 350 MW units began oper-
ating in late 1975 and mid-1976, any impacts from the chronic levels of the
power plants' gaseous and particulate emissions upon the foliage could be
ascertained in the future. Ponderosa pine is the dominant tree species in
southeastern Montana and is the only one utilized for timber production
throughout the area. Its susceptibility to phytotoxic gases such as S02, 03,
HF, and/or combinations of these gases has been well established by the field
studies of Katz and McCallum (1939), Scheffer and Hedgcock (1955), Compton
et al. (1960, 1968), Carlson (1974), Carlson and Dewey (1971), Evans and
Miller (1972), Treshow et al. (1967), Cobb et al. (1968), Gordon (1974),
Miller et al. (1977), and Tourangeau et al. (1977).
Although all of these investigators have studied ponderosa pine as a
bioindicator of air pollution impacts, quantification of the effects upon
foliage has been limited. For instance, the ongoing studies of Miller et al.
(1977) in the San Bernardino National Forest demonstrate that air pollution
impacts have reduced the growth of 30-year-old ponderosa pine by 83% in areas
with the highest ozone concentrations. This study has not yet established
several foliar pathologies (tip necrosis, basal scale, basal necrosis, mottle,
insect and fungal damage), quantified measurements of needle retention, or
determined the concentrations of phytotoxic gases such as sulfur and fluoride
in foliage. If these are not quantified for the San Bernardino ponderosa
pines in both non-impacted and impacted areas, all measured effects (annual
increment growth) could eventually be attributed primarily to oxidants
without differentiation from other abiotic agents or natural attrition, all
of which can cause one or more of the many foliar pathologies found in
pristine and/or polluted areas.
Ponderosa pines in the San Bernardino National Forest are retaining only
two years of foliage (Miller et al. , 1977), which represents only a 17+ month
exposure period from candle stage. This is approximately 43 months less than
the average needle retention time of ponderosa pine in southeastern Montana,
an area with much less rainfall. Without quantification of foliar pathologies
and chemical analysis of different-aged foliage (different exposure time),
there is absolutely no way to distinguish between impacts of the different
142
-------
causal agents (phytotoxic gases, acidic precipitation, fungal and insect
foliar infestations, and natural abiotic agents such as frost, drought, and
mineral deficiencies) in order to determine the relationship between varying
chronic concentrations of phytotoxic gases in the ambient air and impacts
upon the forest ecosystem.
A good example of the need to quantify baseline sulfur levels in
ponderosa pine foliage to determine chronic air pollution impacts is Katz and
McCallum's (1939) study in the smelter town of Trail, B.C. They carried out
extensive controlled S02 fumigation on two conifer species (ponderosa pine
and Douglas-fir) in Summerland, B.C., 100 miles west'of Trail, B.C., to
determine the impacts of different concentrations of S02 at varying durations.
They reported an average baseline sulfur level (prior to fumigation) of 600
to 700 ppm, with a range of 200 to 1,100 ppm, for the three different-aged
foliage (one-, two-, and three-year) of ponderosa pine being tested.
In their field studies around Trail, B.C., and 90 miles south along the
Columbia River in Washington, Katz and McCallum reported average sulfur
concentrations in the oldest foliage (three-year) ranging from 5,000 ppm
(10 miles from Trail) to 1,200 ppm (78 miles from Trail), with an average of
1,500 ppm (90 miles downwind of the smelter). This average level of sulfur
90 miles south of the smelter was more than two times higher than concen-
trations found in pine foliage from the Summerland, B.C., area. But the fact
that foliage pathologies attributable to the air pollution problem were not
quantified during the seven-year study allowed the investigators to assume
they had a control area in their annual growth increment studies before and
after the smelter "abated its emission." If they had carried out needle
pathology work to quantify needle retention, tip necrosis, mottle, basal
necrosis, and insect and fungal damage, they would have realized that they
were actually comparing annual incremental growth of foliage from acute and
chronic fumigation zones and that they had no control zone except at
Summerland, which they didn't utilize for their control growth studies.
Basically, there is not a single pre- or post-air pollution investi-
gation in the literature today which reports conifer growth/health/damage
characteristics as bioindicators of air pollution impacts. Our past and
current studies (1976, 1977) in southeastern Montana adequately demonstrate
that the damage characteristics of pine foliage, such as needle tip necrosis,
mottle, basal necrosis and scale, and insect and fungal damage, occur
naturally in pristine environments. Any increase or decrease of these
characteristics cannot be ascertained after the advent of air pollution
unless they were quantified prior to the impact and unless one recognizes
that air pollution damage to pine foliage is mimicked by other causal agents.
We maintain ponderosa pine-skunkbush sites in the immediate vicinity of
the two 350 MW coal-fired power plants at Colstrip as well as several miles
downwind (80 km) (Figure 5.1). These sites were established on the highest
terrain believed to be most likely impacted by the power plant emissions.
The first Colstrip unit (350 MW) went on-line in September, 1975, and the
second (350 MW) in mid-1976. Since operations began, they have been func-
tioning at various degrees of megawatt capacity; until 1977, neither averaged
better than half of their capacity.
143
-------
MILES CITY/
FORSYTH
BNWI^BIMWZ
© SE 2
©S3
LAME DEER
BUSBY
KmO 5 JO 15 2p 25 30
Mi 0 5 10 15 20
ASHLAND
OSE4
Figure 5.1. Ponderosa pine-skunkbush collection sites in the
vicinity of Colstrip, Montana
Figure 5.2a depicts the coal consumption of Colstrip Units 1 and 2
during 1976 and 1977, and Figure 5.2b depicts the percent of gross megawatt
generation capacity reached by the two units from January to November, 1977.
When comparing the coal consumed during the growing season of 1977 (March
through September) with that of 1976, it is apparent that more phytotoxic
gases probably were emitted during 1977 than during 1976. Unfortunately, the
Montana Department of Health and Environmental Sciences (1977) recently
declared that its own 1976 and 1977 air monitoring data on S02, NOX, and HF
were unreliable; consequently, we do not have usable air quality data from
this agency for the early operation periods of the two units.
144
-------
1
125
100
50
\ / 7-
V / "v—UNIT 2 1976
UNIT I 1976
JAN.
MAR.
MAY
JULY
SEPT
NOV.
Figure 5.2a. Monthly coal consumption of Colstrip Units 1 and 2
during 1976 and 1977.
80
60
O
O 40
20
(T
LU
0-
UNIT 2
JAN
MAR.
MAY
JULY SEPT.
NOV.
Figure 5.2b. Percent of gross megawatt generation capacity of
Colstrip Units 1 and 2 during 1977.
145
-------
Stack gas and particulate analyses of Colstrip Unit 2 emissions were
conducted in March, 1977, by personnel of Battelle Pacific Northwest
Laboratories (BPNL) (Crecelius et al. , 1978). These studies show that parti-
culates being emitted are extremely small, 80% being less than .5 micron in
diameter, and that the scrubbers (wet Venturi) are 99.7% efficient in removing
ash from the stack gases. This work also disclosed that the fly ash emissions
are enriched in As, Se, Sb, Hg, F, Pb, V, Cu, and Zn, in comparison to concen-
trations of fly ash retained by the scrubbing system. These more volatile
elements are released at a significant rate compared to the less volatile
elements.
The Battelle study did not report the rate of SC^ emissions from the
stack. However, data were obtained from personnel of the Montana State
Department of Health and Environmental Sciences (DHES) (1978) on stack gas
investories compiled by a consulting firm for the Colstrip utility companies.
The S02 data are from nine stack tests conducted on Unit 2 when it was oper-
ating at 327.8 MW per hour capacity. At this capacity, it released between
960 and 1,333 pounds of S02 per hour, and assuming an average of 1,146 pounds
per hour, both units would collectively release 1^ tons per hour, 27.5 tons
per day, or approximately 10,000 tons per year. This is about 1,000 tons
more per year than predicted by the Westinghouse Corporation's Environmental
Impact Statement (EIS) in their revision estimates for the Montana State
Department of Natural Resources and Conservation (DNRC) hearings in 1976.
An emission rate of 10,000 tons of S02 is approximately 2% times less than
the annual emissions of the three oil refineries and the 180 MW coal-fired
power plant (25,638 tons per year) located within a 15-mile radius of our
Billings, Montana, ponderosa pine-skuiikbush site GB-1.
The NOX stack emissions from the two Colstrip units have not been deter-
mined at this time, but according to Westinghouse estimates, they should be
approximately 20,600 tons per year or 56 tons per day. Westinghouse also
predicted that approximately 7,000 pounds of fluoride would be released
annually from Units 1 and 2. This amounts to approximately 19.2 pounds per
day or .8 pound per hour, approximately 12 pounds per day more than found by
either state agencies or by Crecelius et al. (1978). This is also five times
less fluoride per day (19 vs. 100 pounds) than is emitted by the three oil
refineries and the 180 MW coal-fired power plant in the Billings, Montana,
area.
The importance of these figures on stack emissions will become apparent
later in this section of our Colstrip report in a discussion of the impacts
of air pollution at a few of the Colstrip sites and the Billings site where
SOo and/or fluorides have caused quantifiable effects upon the bioindicator
species (ponderosa pine) we are utilizing.
Ambient air monitoring for ozone in the Colstrip area by DHES, EPA, and
BPNL disclosed that the average concentration is .04 to .05 ppm, with the
highest range being .08 ppm.
In an unpublished annual progress report of the Energy Research and
Development Administration (ERDA) , Gordon et al. (1978b) reported incident
146
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rainfall collections in the Colstrip area with pH values ranging from 4.1 to
8.1; some of the lower pH values were not a result of COo dissolved in the
precipitation. z
Plume strikes during the fall and winter of 1977 at the EPA Hay Coulee
site (10 km southeast of Colstrip) were documented by Weber and Olson (1978).
Data from continuous analyzers showed instantaneous S02 concentrations of
29 pphm. Since this monitoring site is located in a valley, with a high
ridge between it and Colstrip, it can be assumed that plume strikes are
also occuring at our ponderosa pine-skunkbush sites located on the most
elevated ridges in the Colstrip area where only static air monitoring
data (sulfation and formate plates) are being gathered.
In this EPA annual report, we are utilizing data collected on growth/
health/damage characteristics of ponderosa pine foliage as well as sulfur
and fluoride levels in foliage from both EPA sites and four DOE sites, DOE
studies are being used because: (1) Three of the sites (BNW-1, BNW-2, and
BNW-3) are located in the closest proximity to Colstrip, an area subject to
low, chronic air pollution impacts, and the fourth (GB-1) is located in
Billings, Montana, an area of elevated chronic air pollution, and (2) 1977
was the last year of funding for the EPA-sponsored study on our ponderosa
pine sites, and therefore we would like to demonstrate in this final report
the usefulness of various conifer foliage characteristics as bioindicators of
chronic air pollution impacts.
METHODS AND MATERIALS
Collection, Measurement, and Evaluation of Ponderosa Pine Foliage
The geographical locations of the five study sites sampled during 1975
and 1976 have been described by Gordon et al. (1978a) in the EPA Third
Interim Report (hereinafter TIR). Although vegetation was collected at the
Whitetail study site (SE-4) during 1975 and 1976, no sampling was done at
this site during the 1977 field season because it was felt that further
removal of the necessarily large amounts of foliar material required might
eventually be detrimental to the trees. Yaeger Butte, located in the Custer
National Forest (NW 1/4 of Section 26, T4S, R4SE)., was sampled during 1977 as
a substitute for SE-4. This site, southeast of Colstrip, was established in
1973 with five trees and expanded in 1975 to ten trees. In addition to
Yaeger Butte (hereinafter SE-4), the other sites sampled in 1975, 1976, and
1977 were S-3, S-5, SE-2, and E-l. Foliage was collected only from the
upper crown of the trees using the methods detailed in the TIR.
During 1976 and 1977, three sites were sampled in the immediate vicinity
of Colstrip, and one site was sampled in Billings, Montana. The sites near
Colstrip, BNW-1, BNW-2, and BNW-3, are located 4.5 km SSE, 5 km SE, and 3 km
NE of the power plants. The GB-1 site is located 500 meters south of the
Montana Power Company's Corette coal-fired steam plant in Billings. Each
site is composed of ten permanently-marked trees. The upper crown foliage
was collected from the site of the tree facing the emission source.
147
-------
Using the methods detailed in the TIR, needle length, fascicular cross-
sectional area, and percent needle retention were measured. Foliage was
evaluated for the presence and extent of those seven pathologies enumerated
in the TIR. During 1975, 1976, and 1977, two previously unreported path-
ologies were also evaluated: percent needles affected by weevil (probably
Scythropos elegans) (Gordon et at. , 1976) and percent needles affected by
pathologies not readily categorized. This latter characteristic is called
simply "other" pathology and includes necrotic/chlorotic manifestations on
needles caused by unidentified parasitic or saprophytic fungi, insect
punctures, unclassified abiotic causal agents, or physical damage. This
report includes the evaluations of these two pathologies in 1975, 1976 and
1977 collections.
Additionally, the category percent total necrosis was divided into the
following components: mottle chlorosis, tip burn necrosis, weevil necrosis,
and necrosis and chlorosis resulting from "other" pathologies. Each of these
is a visual estimate of the affected portion of the total surface area of
100 needles per internode per tree. THE READER SHOULD BE CAREFUL NOT TO
CONFUSE THE CATEGORIES OF MOTTLE CHLOROSIS, TIP BURN NECROSIS, WEEVIL NECROSIS,
AND OTHER NECROSIS WITH THE CATEGORIES OF MOTTLE, TIP BURN, TIP NECROSIS,
WEEVIL, OR OTHER PATHOLOGIES, RESPECTIVELY, SINCE THE FORMER CATEGORIES REFER
TO THE AMOUNT OF LEAF SURFACE OF 100 NEEDLES PER INTERNODE PER TREE (OR 1,000
NEEDLES PER INTERNODE PER SITE) AFFECTED BY THESE INDIVIDUAL PATHOLOGIES,
WHILE THE LATTER REFERS TO THE NUMBER (OR PERCENTAGE) OF THESE 1,000 NEEDLES
PER INTERNODE PER SITE MANIFESTING THESE PATHOLOGIES.
The needle pathology tip necrosis is also called tip burn in the text
of this report. The reason for using both terms to describe the same
pathology is that at some of the ponderosa pine sites (GB-1 and BNW sites) ,
this needle pathology is caused by the presence of phytotoxic gases (S02> HF)
which we call tip burn, while at other sites (SE-4 and S-3) this needle
pathology is being caused by such causal agents as drought, frost, or natural
attrition. Results are reported herein for the 1975, 1976, and 1977
collections.
Understory vegetation was collected at all study sites during all three
years. However, attempts were made during 1977 to collect at least six to
eight separate samples of eight to ten species at each site. Of the 19 under-
story species collected during 1975 and 1976 (TIR), three were not collected
during 1977 because of limited availability or identification difficulties:
Aristida long-iseta (red three-awn), Vioia spp. (vetch), and Chrysothamnus
nauseosus (common rubber rabbit-brush).
Chemical Analyses of Vegetation
Methods used to analyze fluoride in vegetation were referenced and
summarized in the TIR. The method used for sulfur analysis in vegetation is
as follows:
A 0.10 gm aliquot of dried, ground plant material is combusted in an
oxygen atmosphere in a Leco induction furnace, and the S02 generated is
measured by iodometric titration. The amount and concentration of titrant
148
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used results in a burette reading calibrated as percent total sulfur for
a 1.0 gm sample. For a 0.10 gm sample, the percent sulfur is ten times that
indicated by the burette. Antimony metal is placed in the gas delivery tube
leading to the titration vessel to mitigate halogen interference, while
sodium azide is added to the titration vessel to eliminate nitrogen
interference.
Analysis of Vegetation Data
In the TIR, we reported that the results of 1975 and 1976 collections
after the data were subjected to analysis of variance (hereinafter anova).
Before anova, each derived variate was coded to the arcsine for percentages,*
and the coded variates and sample statistics were decoded for the presentation
of results. Data for measured variates (sulfur, fluoride, needle length, and
area) were not transformed before anova.
Data reported herein for fascicular cross-sectional area, needle length,
and sulfur and fluoride levels in pine foliage were first coded to the log-^Q,*
and the coded variates and sample statistics were decoded for presentation
of results. These data were interrogated by three- and four-level nested
anova as detailed in the TIR. The following years of foliage origin were
used for anova:
1975 collection: 1974, 1973, 1972
1976 collection: 1975, 1974, 1973
1977 collection: 1976, 1975, 1974
Anova was computed on the date from sites S-5, SE-4, E-l, SE-2, and S-3
for the 1975, 1976, and 1977 collections. These results are presented first.
Anova was recomputed on data from the latter sites and GB-1, BNW-1, BNW-2,
and BNW-3 for the 1976 and 1977 collections. These results are presented next.
Sulfur analyses of 1977 samples are not complete as of this writing
and therefore have not been subjected to statistical interpretation; the
available data are summarized. Chemical measurements on understory species
are also incomplete, and the available data are presented in summary form.
The derived variates (basal necrosis, basal scale, needle retention,
healthy needles, mottled needles, tip burn, needles affected by weevil or
"other" causes, total necrosis and the chlorosis or necrosis resultant from
individual categories) were ranked for graphical presentation of results.
For example, Figure 5.3 shows the average ranks for needle retention on 1973
to 1976 foliage from nine sites from the 1977 collection. In the preparation
of this figure (and all other figures for derived variates, Figures 5.4 through
5.43), data on each year's foliage from all plots were pooled and ordered
*eoded variate = arcsin j.yariate
Deeded variate = log (variate +1)
149
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from lowest to highest values. Each variate was then assigned a rank (average
ranks were computed when ties occurred) so that the lowest and highest values
had the lowest and highest ranks, respectively. The ranks were then resorted
back into their original samples,* and the average rank (_) was computed for
each year of foliage origin at each site. A detailed description of the
procedures used to determine average ranks is presented in Appendix 5.1.
No statistically significant differences are implied by any of the
figures depicting the average ranks for derived variates. However, the
position of the average rank for one sample is relative to that of all other
samples. For example, in Figure 5.14, the average rank of tip burn necrosis
on 1973 foliage from site SE-4 was decisively lower than the rank of tip
burn necrosis on foliage from site E-l. Also, the average ranks depicted
segregate the plots into three groups in terms of tip burn necrosis in the
1973 and 1974 foliage. Sites S-5, BNW-2, SE-4, and S-3 had lower average
ranks than BNW-1 and E-l; sites GB-1, BNW-3, and SE-2 are higher in average
rank than all other sites.
All statistical analyses on derived variates employed non-parametric
methods in lieu of single classification anova (Sokal and Rohlf, 1969;
Conover, 1971). For treatment effects, the Kurskal-Wallis test was used;
for two-sample tests, the Wilcoxon two-sample test was used.
RESULTS
Growth/Health/Damage Characteristics of Pine Needles
1977 Collections Between Sites
When interpreting the data presented in the following graphs, the
reader should keep in mind the different ages of foliage and thus the
different periods of exposure to the environment. During 1977, pine foliage
from the nine sites was sampled from June 25 through mid-September. Because
bud break and the candle stage of ponderosa pine usually occur around the
first of May in southeastern Montana, the 1976 foliage had been exposed to
the environment for approximately 15 to 18 months before being collected.
The 1975 foliage had been exposed 27+ months, and the 1974 and 1973 foliage
had been exposed for 39+ and 51+ months, respectively. When discussing
pathologies and growth characteristics in this report, we will use the
approximate exposure periods of 15, 27, 39, and 51 months for different-aged
foliage.
Figures 5.3 through 5.6 depict the average ranks of needle retention,
percent healthy needles, and two pathologies, mottle and tip burn. Figure
5.3, showing average ranks of needle retention at the nine sites, demonstrates
that the characteristic was similar at all sites on 15- and 27-month-old
foliage (1976 and 1975). However, between the 27- and 39-month exposure
periods, needle retention was substantially reduced at GB-1 in comparison to
*A "sample," as used in this context, refers to the ten variates from
each year of foliage origin from each plot.
150
-------
300i
275-
A 250
V
E 225
R
A 200
G
E I75
R ISO
A
N I25
K
IOO
75
50
25-
10
NEEDLE RETENTION
77 Collection
\ "W
\ V\Y^ '<«
\ \V\
\ \^ '•• \-BNW-2
\ \ \ '• V^S-S
\ \\".'-SE-4
\ \V BNW-1
V YN\-BNW-3
GB-1\^ SE-2
I976 I975 I974 I973
YEAR OF FOLIAGE
Figure 5.3. Ranks of needle retention,
1977 collection.
325
300
275
A 250'
V
E 225
R
A 200
G
E 175
R 150
A
N 125
K
100
75
50
35
PERCENT HEALTHY
77 Collection
BNW-:
GB-I
1976 1975 1974
YEAR OF FOLIAGE
S-3
BNW-2
1973
Figure 5.4. Ranks of healthy needles,
1977 collection.
300
275
A 250
V
E 225
R
A 200
G
E 175
R 150
A
N 125
K
IOO
75
50'
25
MOTTLE
77 Collection
BNW-I
X r- BNW-2
1976 1975 1974
YEAR OF FOLIAGE
1973
Figure 5.5. Ranks of needle mottle,
1977 collection.
325
300
275
A 250
V
E 225
R
A 200
G
E 175
R 150
A
N 125
K
IOO
75
50
35
TIP BURN
1976 1975 1974
YEAR OF FOLIAGE
1973
Figure 5.6. Ranks of tip burn,
1977 collection.
151
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the eight Colstrip sites. Needle retention decreased dramatically at all
sites during the 39- and 51-month exposure periods (1974 and 1973 foliage) in
comparison to any other 12-month period depicted on the graph.
In Figure 5.4, the average ranks of percent healthy needles of different-
aged foliage are depicted for the 1977 study period. The data on this
figure demonstrate that the percent totally green needles on 51-month old
foliage (1973) from the S-3 and BNW-2 Colstrip sites was higher than that
found on 27-month foliage (1975) at the GB-1 Billings site and the BNW-3
Colstrip site. Between the 27- and 39-month exposure periods, the percent
healthy needles at GB-1 reached essentially zero, while at S-3, SE-4, and S-5,
(the more pristine Colstrip sites) and BNW-2 (4.2 km east of the Colstrip
power plant), there were still some totally green needles after 51 months
exposure.
Figure 5.5 depicts the average ranks of percent needles affected by
mottle on different-aged foliage from the 1977 collection period. This
pathology is often associated with air pollution studies. However, it was
also common on foliage collected in the Colstrip area before the introduction
of any industrialization or measurable levels of phytotoxic gases (pre-
September, 1975). Between the 15- and 27-month exposure periods, there was
a sharp rise in the average rank of needle mottling at all nine sites. But
between the 27- and 39-month exposure periods, the percent mottle decreased
at BNW-3 and SE-4 and increased slightly at BNW-1 and BNW-2. Between the
39- and 51-month exposure periods, this pathology decreased substantially
at both the Colstrip E-l site and the Billings GB-1 site and was less
prevalent on 1973 needles from GB-1, the most polluted of the ponderosa pine-
skunkbush sites than on foliage from the most pristine Colstrip site (S-3).
The sharp reduction and the gradual leveling off of mottling between
27- and 51-month-old foliage was evident with a few of the other pathologies
on older needles. The reason for this will continually become more evident
as the extent of other needle characteristics are reported. However,
referring back to Figure 5.3, there is a very dramatic reduction in needle
retention between 1975 and 1974 foliage from GB-1 and at all sites between
1974 and 1973 foliage. Needles being cast between the 39- and 51-month
periods are believed to have the largest amount of mottling and a few other
pathologies.
Figure 5.6 shows the average ranks of tip burn on different-aged
foliage during 1977. After 15 months exposure, the amount of tip burn at
GB-1 and BNW-3 was substantially higher than that at the other seven sites.
By the time the pine foliage had been exposed for 51 months at the nine
different sites, there was a large scattering in the average ranks of tip
burn between sites.
Figures 5.7 through 5.10 depict two abiotic-caused pathologies, basal
scale and basal necrosis, and two insect-caused needle pathologies, defoliator
and weevil. Figure 5.7 shows the average ranks of basal scale on different-
aged foliage from the nine different sites. The percent basal scale was
very similar on 15-month-old foliage from all sites and increased over
exposure times (27, 39, and 51 months) at similar rates on all sites.
152
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BASAL SCALE 77 Collection
BASAL NECROSIS 77 Collection
325
275
A 250
V
E 225
R
A 200
G
E 175
R 150
A
N 125
K
100
75
50
35
rBNW-3
/>BNW-1
xS-5
'— BNW-2
376 I975 I974
YEAR OF FOLIAGE
I973
Figure 5.7. Ranks of basal scale,
1977 collection.
325
300'
275
A 250
V
E 225
R
A 200
G
E I75
R ISO
A
N I25
K
IOO
75
50
35
, E-1
I976 I975 I974
YEAR OF FOLIAGE
I973
Figure 5.8. Ranks of basal necrosis,
1977 collection.
325
300
275
A 250
V
E 225
p
A 200
G
E I75
R ISO
A
N I25
K
IOO
75
50-
v.
DEFOLIATOR /E_,
77 Collection /
/
' BNW-I
f -^SE-2
^^^^^•v' -3? BNW-2
^ ^^^^-•"" ...X'S-3
.-•/— *?v-... S*** •''"""/
.{"/'^>«£'7r ^ ^ SE~ 4
Y ^^ XNGB-I
I976 1975 1974
YEAR OF FOLIAGE
1973
Figure 5.9. Ranks of defoliator,
1977 collection.
325
300
275
A 250
V
E 225
A 200
G
E 175
R 15
A
N 125
K
100
75
50
35
WEEVIL
77 Collection
^--S-5
BNW-3
GB-I
1976 1975 1974
YEAR OF FOLIAGE
Figure 5.10. Ranks of weevil,
1977 collection.
153
-------
This pathology was illustrated well in photomicrographs in the TIR and will
not be duplicated in this report.
Figure 5.8 shows the average ranks of basal necrosis which increased
rapidly over time (15 to 39 months) in foliage collected from GB-1, but began
to level off between the 39th and 51st months, as it did at the BNW-3 site.
During the last four years, histological and stereoscopic examinations of
basal needle tissues manifesting basal necrosis and basal scale have finally
led to the conclusion that these two pathologies are caused by abiotic agents
(acidic solutions and acidic particulate) and not by insects.
On Figure 5.9 are shown the average ranks of percent defoliator in
different-aged foliage from all sites. In comparison to basal scale and
basal necrosis over time, defoliator increased substantially at three sites
(BNW-1, SE-2, and E-l), and there was very little change in the amount of
this insect damage over time at the most polluted sites (GB-1 and BNW-2).
There was little to no evidence that weevil damage (Figure 5.10) increased
with exposure periods or the age of the foliage. GB-1 was least affected by
weevil. This pattern was also evident for defoliator.
Figures 5.11 and 5.12 present two graphs which depict the average
ranks of "other" pathologies and total necrosis manifested by different-aged
needles at all sites. As previously mentioned, "other" pathologies refers to
needle damage caused by saprophytic and parasitic fungi, insect punctures,
unidentified abiotic causal factors, and physical damage.
As seen in Figure 5.11, the percent of "other" pathologies increased over
time, and this appeared to be similar to the trends observed in basal scale
and basal necrosis. Foliage from GB-1 and S-3 had the least amount of
"other" pathologies measured in 39- to 51-month-old needles; these two sites
are our most polluted and most pristine study sites, respectively.
Figure 5.12 illustrates the amount of total necrosis caused by all
needle pathologies at the nine sites during 1977. Total necrosis, the reader
is reminded, is the amount of damaged surface area of the needles being
retained on their respective internodes. At the GB-1 site, 15-month-old
foliage (1976) had the least amount of needle surface damage. Total necrosis
was more prevalent on 39-month-exposed needles (1974 foliage) from this site
than on either 39- or 51-month foliage from any other site. We believe
the drop in rank of total necrosis between the 39- and 51-month-old foliage
was due to the casting of the needles most damaged in the older foliage.
The total amount of necrosis/chlorosis which a needle can sustain before
being cast during a given time period is not totally understood. Our past
three years of study indicate that a needle is cast after 40% to 50% of its
surface is damaged or destroyed. During the 1978 growing season, we will
attempt to employ a modification of the techniques being used by Miller &t at.
(1977) to collect needles cast from trees in polluted and pristine environ-
ments .
Figures 5.13 through 5.16 depict the ranks of the amount of needle surface
damage on different-aged needles caused by one or possibly more agents (tip
154
-------
325
300-
275
OTHER PATHOLOGIES
77 Collection
••E-l
1976 1975 1974 1973
YEAR OF FOLIAGE
Figure 5.11. Ranks of other pathologies,
1977 collection.
325
3C£H
275
A 250
V
E 225
R
A 200
G
E 175
R 150
A
N 125
K
100
75
50
35
TOTAL NECROSIS
77 Collection
li'76 1975 1974
YEAR OF FOLIAGE
1973
Figure 5.12. Ranks of total necrosis,
1977 collection.
155
-------
burn and mottle can be caused by such causal agents as air pollution, frost,
drought, etc.). Figure 5.13 shows the ranks of the amount of needle surface
area affected by mottle chlorosis on different-aged foliage collected and
measured in 1977. Over time, the older foliage (1974 and 1973) from GB-1,
BNW-1, and E-l had substantially more needle surface area affected than
foliage from other sites. The slight decrease in the amount of mottle
chlorosis between 39- and 51-month-old foliage from GB-1 and BNW-1 was more
pronounced when the percent of needles manifesting this pathology was ranked
(Figure 5.5). However, the general trend was towards a leveling off or a
decrease in the prevalence of mottling while the amount of surface area
affected remained essentially the same.
The ranks of needle surfaces manifesting tip burn necrosis are shown
in Figure 5.14. In 15-month-old foliage, the amount of needle surface
manifesting this pathology was substantially higher at BNW-3 and GB-1 than
at the other seven sites. In 27-month-old foliage, it increased dramatically
in 15-month-old foliage at BNW-3, GB-1, and SE-2. There was a moderate
increase at BNW-1, BNW-2, S-5, and SE-4 and no increase at S-3. The amount
of tip burn necrosis leveled off between the 39- and 51-month exposure
periods in foliage from GB-1, which was similar to the pattern of mottle
chlorosis at this site. It also tended to level off on pine foliage between
the 27- and 51-month period at BNW-3, while at BNW-2 it decreased on 1973
needles in comparison to 1974 needles.
The data on tip burn necrosis on 1973 foliage from the 1977 collection
at sites GB-1, BNW-3, and SE-2 were subjected to the Kruskal-Wallis test.
The Kruskal-Wallis statistic was .633 and was not significant (p > .50). This
suggests that the three plots were not significantly different in tip burn
necrosis. The Wilcoxon two-sample test was used to compare the sites as
pairs and the results of these tests are shown below:
SE-2
BNW-3
GB-1 BNW-3
44.5
44.0
50.0
None of the values above are significant (p > .20 for each pair). The
distribution of tip burn necrosis at the three sites for 1973 were
essentially the same.
The ranked amounts of needle surface damaged by weevil at the different
sites are depicted in Figure 5.15, which shows that this endemic insect
damage was fairly similar on all-aged foliage within any of the nine sites
during 1977. However, there were substantial differences between sites, such
as the amount of weevil damage at the pristine S-5 Colstrip site versus
that at the polluted GB-1 site.
156
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MOTTLE CHLOROSIS
77 Collection
300
275
A 250
V
E 225
R
A 200
G
E 175
R 150
A
N 125
K
100
75
50-
25-
10
GB-1
BNW-1
E-1
S-5
^ SE-4
-T- •••.::• BNW-2
ii"-— S-3
SE-2
BNW-3
1976 1975 1974 1973
YEAR OF FOLIAGE
325
300-
275
A 250
V
E 225
R
A 200
G
E I75
R I50
A
N I25
K
IOO
75
50
35
TIP BURN NECROSIS
77 Collection
~.__ GB-1
^-—- BNW-3
-SE-2
BNW-1
I976 I975 1974
YEAR OF FOLIAGE
1973
Figure 5.13. Ranks of mottle chlorosis, Figure 5.14. Ranks of tip burn necrosis
1977 collection. 1977 collection.
WEEVIL NECROSIS
OTHER NECROSIS/CHLOROSSS
325
300-
275
A 250
V
Ef\f\C
225
R
A 200
G
E I75
R ISO
A
N I25
K
IOO-
75
50-
X«N
77 Collection
300-
s*. s.5 275
s^ "^'"^
// \ A 250
S / '^ BNW-2 V
^ C^— .-*' 7' SE-4 R
.>>$< / A 200'
^'^ — ^ "^ .•— -*••>. / G
^^*x"'---. /\ E I75
S'*. ^V^ '•• / "^ C.-3
/ ^ >s/-. R I50
V X P1 A
^•'' \ \^< SE-2 N '25'
'\ iOO-
"•'•-.. N BNW-3
'•'.. 75-
x GB'1 50-
-j r-
35
• • • "^ • • • ^ t^f ^^ 9 • ^B^ ^^ f ^K^/ ^^ 1 > ^B> ^^^ B • '^^ ^^ f *^
1977 Collection ^
, SE-2
. A.-SE-4
. ,c/^^-5
>'/l///^ BNW-3
,*/' S // BNW-1
/^ //,// : ^"3
/ V /y/
/ f A/ / ' BNW-2
/ *'// '/
/ /y s ^
//& /•
"7 y V7/ X^
*-•» • • X^ * fi s
^o ' /^ j- ' '/ /
/ ? /
'y / • '
/
'
10-7
-------
Figure 5.16 depicts the ranks of needle necrosis caused by the "other"
category of causal agents. The amount of needle area damaged by these
causal agents was less at the Billings GB-1 site than at four of the Colstrip
sites. However, different-aged foliage from all sites generally displayed
similar amounts of damage. This graph demonstrates that foliage from both
pristine and polluted sites manifest the various symptoms of the "other"
pathology at similar rates.
1977 Collections Within Sites
For the sake of brevity, and because most of the data on growth/health/
damage characteristics for ponderosa pine foliage collected at the Colstrip
sites is very similar, thus repetitive, we are presenting here the ranks of
pathologies for only four sites. These sites were selected because: (1) One
is a site where continuous chronic air pollution damage has occurred for
several years (GB-1); (2) one is a site in close proximity to the Colstrip
power plant (BNW-3, 2.5 km northwest), and (3) two are sites located substan-
tial distances south of Colstrip (S-3, 28 km and S-5, 80 km) and are only
impacted occasionally by the plumes of these two power plants.
Figures 5.17 through 5.20 depict the ranks of seven damage character-
istics and one health characteristic of foliage collected from the four
ponderosa pine sites and analyzed during 1977. Figures 5.17 and 5.18 show
the ranks of needle pathologies on foliage from sites S-3 and S-5. At S-3,
the most prevalent pathology on 15-month-old foliage (1976) was mottling, and
the least prevalent was basal scale. Mottling remained the most prevalent
pathology on all-aged foliage, while basal scale became the third most preva-
lent pathology in 39- and 51-month-old foliage. Tip burn necrosis on all-
aged foliage from S-3 remained constant, and it is interesting to note that
in 51-month-old foliage from this site, there were more totally green needles
than needles damaged by tip necrosis, weevil, or defoliator insects.
At site S-5, mottling of 15-month-old foliage was less prevalent than
weevil, basal necrosis, and the "other" category of damage, but at exposure
periods of 27 months and more, mottling was surpassed only by the "other"
category. As on foliage from S-3, basal scale damage at the S-5 site was
the least prevalent on 15-month-old foliage and became the third most
prevalent damage on 51-month-old foliage.
If we had categorized both basal needle pathologies as a single needle
pathology when we first started the project, this pathology would probably
be ranked even higher in prevalence than it appears in our current studies.
However, since a single needle base could have both basal scale and basal
necrosis and thus be tallied in each of these two columns on the data work
sheets, there is currently no way to change our evaluation methods to
incorporate these into a single pathology and still allow us to compare them
with previous data (1975-1977),
Figure 5.19 shows the average ranks of the seven pathologies on
different-aged foliage from site BNW-3. One immediately notes on this graph
that percent healthy needles was ranked below all other foliage characteris-
tics during the 27-month exposure period; the previous two graphs demonstrate
158
-------
SITE S-3 77 Collection
300
275
A 250-
V
E 225
R
A 200
G
E 175
R 150
A
N 125
K
100
75
50
25-
10
SITE S-5 77 Collection
BASAL NEC.
.> % HEALTHY
WEEVIL
325
300
275
A 250
V
E 225
R
A 200
G
E 175
R 150
TIP NEC.
1976 1975 1974 1973
YEAR OF FOLIAGE
DEFOLIATOR A
N 125-
K
100-1
75
50-1
35
OTHER
MOTTLE
BASAL
SCALE
WEEVIL
TIP NEC.
BASAL NEC.
DEFOLIATOR
PERCENT
HEALTHY
1976 1975 1974 1973
YEAR OF FOLIAGE
Figure 5.17. Ranks of pathologies
at site S-3.
Figure 5.18. Ranks of pathologies
at site S-5.
SITE BNW-3 77 Collection
325
300
275
A 250
V
E 225
R
A 200
G
E 175
R 150
A
N 125-
K
100-
75-
50-
35
TIP NEC.
BASAL
/ SCALE
BOTHER
C—-MOTTLE
BASAL
NEC.
DEFOLIATOR
WEEVIL
PERCENT
HEALTHY
1976 1975 1974
YEAR OF FOLIAGE
1973
Figure 5.19. Ranks of pathologies
at site BNW-3.
300
275
A 250
V
E 225
R
A 200
G
E 175
R 150-
A
N 125
K
100
75
50
25-
10
SITE GB-1 77 Collection
TIP
NEC.
BASAL SCALE
^MOTTLE
_.---BASAL NEC.
DEFOLIATOR
WEEVIL
% HEALTHY
I976 I975 I974 I973
YEAR OF FOLIAGE
Figure 5.20. Ranks of pathologies
at site GB-1.
159
-------
that this was not the case in S-3 foliage and occurred in foliage from S-5
only between the 39- to 51-month exposure periods.
Tip necrosis and "other" necrosis initially were equally ranked in
prevalence at the 15-month exposure period. In all older foliage, tip
necrosis continued to be the most prevalent pathology at BNW-3. Mottling
increased substantially between the 15- and 27-month period and then
decreased in the older foliage (1974 and 1973). Mottling has been used in
determining "air pollution impacts" in various studies in the literature.
However, the data we have thus far gathered at both pristine (S-3 and S-5)
and chronically-polluted sites (GB-1) (see Figure 5.5) on the prevalence of
this pathology indicate that the amount of baseline mottling would have to
be established before it could be used as an indicator of air pollution
impacts.
The ranks of basal scale indicate an initial low prevalence in the
15-month foliage and then, in an almost perfect linear manner, show an
increase which surpassed all other pathologies except tip necrosis in the
oldest foliage (1973). Both weevil and defoliator remained constant and
similar in prevalence in all-aged foliage. As previously illustrated in
Figures 5.9 and 5.10, both weevil and defoliator damage at BNW-3 were less
prevalent than at most pristine sites, and only foliage from GB-1 was
consistently less damaged by these two foliar insects than BNW-3 foliage.
Figure 5.20 illustrates the prevalence of pathologies in foliage
collected in 1977 from our most polluted ponderosa pine site, GB-1. After
foliage was exposed to the environment of the Billings site for approximately
27 to 39 months, there were no needles that did not manifest some pathology,
and thus no healthy needles were recorded. Mottle was slightly more
prevalent on 15-month-old foliage than tip necrosis and percent other
necrosis, but on the oldest foliage, mottle was ranked as less prevalent
than basal scale, tip necrosis, and the "other" necrosis/chlorosis category.
In the next set of figures, one will note that not only was mottling less
prevalent on these older needles (1973), but less needle surface area was
affected.
The pattern for the prevalence of defoliator and weevil damage in the
various-aged foliage from the GB-1 site was very similar to that observed
on foliage from the BNW-3 site (Figure 5.19).
Figures 5.21 through 5.24 depict the pathologies which caused the most
and least prevalent amounts of needle surface damage. Rather than discuss
each graph separately, it is more illustrative to discuss all four together,
although the different pathologies are not ranked here between sites but
within each site. The ranks of tip necrosis damage to needle tissue within
all four sites on Figures 5.21 through 5.24 adequately demonstrate that this
pathology was the major manifestation of tissue damage on pine foliage from
BNW-3 and GB-1 but was responsible for the least amount of damage on foliage
from S-3 and S-5. At these latter sites, the unidentified abiotic and biotic
causal agents of the "other" pathology were more prevalent than any other
pathology on 51-month-old foliage. The "other" necrosis/chlorosis category
at BNW-3 and GB-1 was also ranked higher than mottle and weevil damage on the
160
-------
A
A
200
180
160
140
R
A 120
G
E 100
R
A 80
N
K 60
40
20
SITE S-3 77 collection
TOTAL
NEC.
OTHER
NEC./CHLO.
MOTTLE
CHLO.
WEEVIL
NEC.
_- — -TIP NEC.
1976 1975 1974
YEAR OF FOLIAGE
1973
Figure 5.21. Ranks of needle damage
at site S-3.
200
180
A I6°
E
R
A 120
G
E 100
R
A 80
N
* 60
40
204
SITE S-5 77 collection
1976 1975 1974
YEAR OF FOLIAGE
TOTAL
NEC/CHLO.
OTHER
•''NEC/CHLO
WEEVIL
NEC,
MOTTLE
NEC.
TIP NEC.
1973
Figure 5.22. Ranks of needle damage
at site S-5.
A
200
180
160
140
A 120
G
E 100
R
A 80
N
K 60
40
SITE BNW-3
TOTAL
NECVCHLO.
TIP NEC.
OTHER
NEC./CHLO.
MOTTLE
CHLO.
WEEVIL
NEC.
1976 1975 1974
YEAR OF FOLIAGE
1973
Figure 5.23. Ranks of needle damage
at site BNW-3.
200
180
. 160
A
E
R
A 120
G
E 100
R
A 80
N
K 60
40
20-
SITE GBH 77 collection
TOTAL
NEC./CHLO.
TIP NEC.
- OTHER
NEC./CHLQ
MOTTLE
CHLO.
.WEEVIL
NEC
1976 1975 1974 1973
YEAR OF FOLIAGE
Figure 5.24. Ranks of needle damage
at site GB-1.
161
-------
51-month foliage. The amount of needle tissue being damaged by pine weevil
at GB-1 and BNW-3 was ranked very low in comparison to other types of
pathologies, with the exception of mottling at BNW-3. One notes on
Figure 5.19, that mottling was ranked substantially higher than weevil on
the 27- to 51-month-old foliage from this site, After comparing the ranks
of mottling with weevil damage on Figure 5.19 and then comparing them on
Figure 5.23, it is apparent that one pathology can be substantially more
prevalent than another (Figure 5.19)'butnot necessarily cause more tissue
damage (Figure 5.23).
All Collections of 1973 and 1974 Needle Between Sites
The next series of graphs show the average ranks of growth/health/
damage characteristics of 1973 and 1974 needles as they were quantified
during each collecting and study period of 1975, 1976, and 1977 at the
Colstrip sites only. Pathologies on trees from the Colstrip BNW sites were
not evaluated until the spring of 1976.
When interpreting the patterns of different pathologies on 1973 and
1974 needles over the three-year period, the reader should keep ±n mind the
amount of time of exposure of the foliage. In 1975, for instance, the 1974
needles had been exposed to their environment for approximately 15 months and
1973 needles for approximately 27 months before being collected. In 1977,
the 1974 needles had been exposed for approximately 39 months and 1973 needles
for approximately 51 months.
Figures 5.25 through 5.38 illustrate the rank of needle retention,
percent healthy needles, tip necrosis, and percent mottle of 1973 and 1974
foliage over the last three years.
Figure 5.25, which depicts the average ranks of needle retention at the
five Colstrip sites, shows that 1973 foliage from SE-2 and E-l was cast
faster during all exposure periods (27 to 51 months) than at S-3. This
same trend was evident in 1974 foliage from E-l and SE-2 (15 to 39 months).
The order of average ranks of needle retention on 51-month foliage (1977
collection of 1973 needles) from all five states was almost identical to the
rank sequence for 1974 foliage at the 39-month exposure period (1977). As
one studies the ranks of needle pathologies in the following graphs, it should
be noted that foliage from SE-2 and E-l usually rank higher in most
pathologies than foliage from the other three sites. Needle casting is a
continuous phenomenon over time even in "pristine areas" such as the Ouster
National Forest. It is essential to determine which needles are being
prematurely cast and why before the impacts of chronic air pollution to
coniferous forest species can be understood.
Figure 5.26 depicts the average ranks of percent healthy 1973 and 1974
foliage. The almost linear loss of totally green needles being retained on
1973 and 1974 internodes over time demonstrates that foliar exposure periods
takes its toll on the chlorophyllic food-producing tissues, even in "pristine"
areas. In general, the rank sequence of 51-month (1973) foliage and 39-month
(1974) foliage on the five sites was similar to that of needle retention.
162
-------
Figure 5.27 illustrates the average ranks of tip necrosis on 1973 and
1974 needles over time. The 1973 foliage from SE-2 had a higher percentage
of tip necrosis at all exposure periods than occurred at other sites except
E-l. The 1973 and 1974 foliage from S-3 and S-4, after 51- and 39-month
exposure periods, respectively, had substantially less tip necrosis than
foliage from other sites.
The occurrence and increase in mottling (Figure 5.28) over time on 1973
and 1974 foliage were extremely similar at all sites. While there were
substantial differences in prevalence between exposure periods (15 vs. 39 or
27 vs. 51 months), differences during the same exposure period were slight.
Figures 5.29 through 5.32 depict the average ranks of basal scale, basal
necrosis, weevil, and defoliator damage to 1973 and 1974 needles over time.
As demonstrated in Figure 5.29, the rank of basal scale leveled off in the
39-month-old foliage (1973) from three of the pine sites (S-5, S-3, and E-l).
This means that either the increase in this pathology abruptly ceased on
this year's foliage between the 39- and 51-month exposure periods or that
the needles being cast from the 1973 internodes were those with basal scale.
The substantial difference in rank between the 1973 and 1974 foliage over
time demonstrates, or strongly suggests, that this pathology is directly
related to exposure time at these pristine pine sites.
The average ranks of basal scale are depicted in Figure 5.30. One notes
when studying the data on this graph that both 1973 and 1974 foliage
collected in 1977 from S-5 had substantially less basal necrosis than was
evident during the 1976 study period. Foliage from this site also showed
the largest increase of basal necrosis between the 1975 and 1976 collection
periods. Figure 5.32 demonstrates that the rank of percent defoliator on
1973 and 1974 foliage from S-5 also dropped substantially in prevalence
between the 1976 and 1977 study periods. Thus, these two types of damage
would seem to have been very prevalent on both years foliage which were
prematurely cast from the internodes during this time.
Figure 5.31 depicts the ranks of weevil damage at the five Colstrip pine
sites. Probably the trend most evident in this graph is the similarity of
weevil damage prevalence on 1973 and 1974 needles within a site but not
between sites. We do not know why this prevalence decreased slightly at
most sites on both-aged foliage during 1976, but the phenomenon could have
been partially caused by measurable differences of rainfall between 1976 and
1977 in southeastern Montana.
Trends in the prevalence of defoliator damage (Figure 5.32) on both years
foliage from within plots, such as SE-2, E-l, and S-5, were similar to
patterns observed for weevil damage (Figure 5.31). However, defoliator
prevalence within plots on 1973 and 1974 needles over time was not evident
at sites S-3 and SE-4. Probably the most obvious pattern of insect damage
on 1973 and 1974 needles, as depicted for both weevil (Figure 5.31) and
defoliator (Figure 5.32), was that they did not increase continuously and/or
substantially over time (15-51 months), as did the other pathologies such
as basal scale, basal necrosis, and tip necrosis.
164
-------
Figure 5.27 illustrates the average ranks of tip necrosis on 1973 and
1974 needles over time. The 1973 foliage from SE-2 had a higher percentage
of tip necrosis at all exposure periods than occurred at other sites except
E-l. The 1973 and 1974 foliage from S-3 and S-4, after 51- and 39-month
exposure periods, respectively, had substantially less tip necrosis than
foliage from other sites.
The occurrence and increase in mottling (Figure 5.28) over time on 1973
and 1974 foliage were extremely similar at all sites. While there were
substantial differences in prevalence between exposure periods (15 vs. 39 or
27 vs. 51 months), differences during the same exposure period were slight.
Figures 5.29 through 5.32 depict the average ranks of basal scale, basal
necrosis, weevil, and defoliator damage to 1973 and 1974 needles over time.
As demonstrated in Figure 5.29, the rank of basal scale leveled off in the
39-month-old foliage (1973) from three of the pine sites (S-5, S-3, and E-l).
This means that either the increase in this pathology abruptly ceased on
this year's foliage between the 39- and 51-month exposure periods or that
the needles being cast from the 1973 internodes were those with basal scale.
The substantial difference in rank between the 1973 and 1974 foliage over
time demonstrates, or strongly suggests, that this pathology is directly
related to exposure time at these pristine pine sites.
The average ranks of basal scale are depicted in Figure 5.30. One notes
when studying the data on this graph that both 1973 and 1974 foliage
collected in 1977 from S-5 had substantially less basal necrosis than was
evident during the 1976 study period. Foliage from this site also showed
the largest increase of basal necrosis between the 1975 and 1976 collection
periods. Figure 5.32 demonstrates that the rank of percent defoliator on
1973 and 1974 foliage from S-5 also dropped substantially in prevalence
between the 1976 and 1977 study periods. Thus, these two types of damage
would seem to have been very prevalent on both years foliage which were
prematurely cast from the internodes during this time.
Figure 5.31 depicts the ranks of weevil damage at the five Colstrip pine
sites. Probably the trend most evident in this graph is the similarity of
weevil damage prevalence on 1973 and 1974 needles within a site but not
between sites. We do not know why this prevalence decreased slightly at
most sites on both-aged foliage during 1976, but the phenomenon could have
been partially caused by measurable differences of rainfall between 1976 and
1977 in southeastern Montana.
Trends in the prevalence of defoliator damage (Figure 5.32) on both years
foliage from within plots, such as SE-2, E-l, and S-5, were similar to
patterns observed for weevil damage (Figure 5.31). However, defoliator
prevalence within plots on 1973 and 1974 needles over time was not evident
at sites S-3 and SE-4. Probably the most obvious pattern of insect damage
on 1973 and 1974 needles, as depicted for both weevil (Figure 5.31) and
defoliator (Figure 5.32), was that they did not increase continuously and/or
substantially over time (15-51 months), as did the other pathologies such
as basal scale, basal necrosis, and tip necrosis.
164
-------
240
220
20CH
BASAL SCALE
73-74 NEEDLES
IN TIME
A 180
V
E
R
A
G 140
160
A
N 100
K
80
60
40
/
" -,'—- S-573
x-S-3 74
// SE-2 74
//,- SE-4 74
S-5 74
' 1975-77 COLLECTION
1975
1977
1976
Collection
Figure 5.29. Ranks of basal scale,
1975-77 collection.
WEEVIL
S-5 73
240
220
20CH
A 180
V
E
R
A
G 140
160
R
A
N 100
K
80
60
40
1973-74 NEEDLES IN TIME
1975-77 COLLECTION
/ S-5 74
/ SE-4 74
/s SE-4 73
'/
/' ' S-3 74
"^•^///
1975
1976
Collection
1977
Figure 5.31.
Ranks of weevil,
1975-77 collection
BASAL NECROSIS
240 1973.74 NEEDLES IN TIME / / q, , 7A
1975-77 COLLECTION //^SE-1 73
200
A 180
V
R
A
G 140
R
A
N lOOi
K
80
60
40
1975
1977
1976
Collection
Figure 5.30. Ranks of basal necrosis,
1975-77 collection.
DEFOLIATOR
A
V
E
R
A
G
E
R
N
K
240
220
200-
180
160
140
120
100
80
60
Af\
1973-74 NEEDLES IN TIME /
/
1975-77 COLLECTION /
/
/
/
A / ^SE-2 73
*£"<\^ / '
^1 ^/ /•••' E-' 74
/^/' /<^kSE"274
/ / V' ^S> S-5 73
jl ^3( ..•'/*? s'3 73
/:-7 *" y\/^- . -- S E- 4 74
^' // ..-^^Jl^--^.-11--" S"3 7<*
'"x7 / ..--7: ^s"^ s~5 74
x^ / ' . . . ^j.- • • ' • • •-/ i — cc. ^ -7^
___..,— ;».•.•••• Ot •» f O
"77
/
1 j
/
1975
1976
Collection
Figure 5.32. Ranks of defoliator,
1975-77 collection.
165
-------
Figure 5.33 illustrates the ranks of needle pathologies in the "other"
pathology category at the five Colstrip sites during the 1974 through 1977
period; Figures 5.34 through 5.36 depict the growth/health characteristics of
1973 and 1974 pine foliage collected during 1976 and 1977 at all nine sites.
Trends of the "other" pathology on 1973 and 1974 foliage at the Colstrip
sites were very similar to those of mottling (Figure 5.28), There was a
continuous increase in prevalence as the 1973 and 1974 needles were exposed
for longer periods.
To demonstrate how the five Colstrip sites compared with the three BNW
sites and the Billings site, growth/health/damage characteristics of 1973
and 1974 foliage during the 1976 and 1977 collecting periods have been
ranked for all nine sites. Again, it should be noted that 1973 needles
collected during 1976 were approximately 39 months old, and the 1974 foliage
was approximately 27 months old. Therefore, in 1977, the 1973 and 1974
needles were approximately 51- and 39-months-old, respectively.
Figure 5.34 illustrates the ranks of needle retention at all nine
sites during the 1976 and 1977 collection periods. Needle retention on 1973
foliage was less prevalent at GB-1 than at all other sites, and 1974 foliage
(39-month exposure period) from this site displayed less needle retention
during 1977 than 51-month (1973) foliage at S-5 and S-3. If one looks back
at Figure 5.25, the addition of the three BNW sites and GB-1 to the rank
system reduced the slope of needle retention for the five Colstrip sites.
Figure 5.35 depicts the average ranks of the prevalence of percent
healthy 1973 and 1974 needles during the 1976 and 1977 collection periods.
Both 1973 and 1974 foliage from GB-1 and BNW-3, exposed for 27 to 51
months, had substantially less totally green needles than foliage from the
other sites, except 51-month-old foliage (1973) from SE-2 and E-l. Also,
both 1973 and 1974 foliage from BNW-2 had more totally green needles than
foliage from the other Colstrip sites.
Figure 5.36 illustrates the ranks of tip burn on 1973 and 1974 foliage
during 1976 and 1977. This pathology was more prevalent at GB-1 and the
BNW-1 sites than any of the Colstrip sites. One notes that there was no
change in the prevalence of tip necrosis on 1973 needles from GB-1 between
1976 and 1977. Discussion of the tests for significance between the amount
of tip burn on foliage from GB-1, BNW-3? and SE-2 was presented earlier.
Figure 5.37 presents the ranks of mottle which occurred on 1973 and
1974 foliage during 1976 and 1977. It is immediately apparent that this
pattern at both GB-1 and BNW-3 was opposite that seen at other ponderosa
pine sites. The importance of this trend of reduced needle mottling over
time in chronically-polluted areas cannot be overestimated. Returning to
Figure 5.5, one notes that percent mottle increased between 1974 and 1975
foliage from GB-1. However, its prevalence on 1974 foliage actually
decreased between the 1976 and 1977 collection periods because of premature
needle casting. Thus, while a single year's study on damage characteristics
can provide substantial information, it does not allow an investigator to
interpret the trends of the prevalence of certain pathologies over time
at sites such as BNW-3 and GB-1.
166
-------
260-
240
220'
200'
A 180.
E 160
R
A 140
G
E 120
A
60
40
20
OTHER PATHOLOGIES
1973-74 NEEDLES IN
1975-77 COLLECTION
-E-l 74
1975
1977
1976
Collection
Figure 5.33. Ranks of other pathologies,
1975-77 collection.
PERCENT HEALTHY
1976-77 Collection
3251 ^ 1973-74 NEEDLES
300-
275
A 250
V
E 225
R
A 200
G
E 175
R 150 -
A
N 125-
K
100
75
50
35
S-3 74
^SE-4 74
-BNW-2 74
^S-5 74
S-3 73
BNW-2 73
--E-I 74
-BNW-1 74
xSE-2 74
SE-4 73
S-5 73
-SE-2 73
^-GB-I 74
M3B-I 73
1976
Figure 5.35
Collection
1977
300
275
A 250
V
E 225
R
A 200
G
E 175
R 150-
A
N 125-
K
100-
75-
50-
25-
10
% NEEDLE RETENTION
1973-74 NEEDLES IN TIME
1976-77 COLLECTION
S-3 74
^SE-4 74
--S-5 74
-BNW-1 74
^ BNW-2 74
E-1 74
BNW-3 74
SE-2 74
S-3 73
^S-S 73
-GB-1 74
BNW-2 73
SE-4 73
BNW-1 73
iH igure
325
300-
275
A 250
V
E 225
R
A 200
G
E I75
R ISO
A
N I25
K
IOO
75
50
35
I976 I977
Collection
5.34. Ranks of needle retention,
1976-77 collection.
TIP BURN
1973-74 NEEDLES IN TIME
1976-77 COLLECTION GEH 74
'GB-I 73
BNW-3 74
SE-2 73
BNW-1 73
SE-2 74
E-l 73
BNW-1 74
E-l 74
S-5 73
rS-5 74
i-BNW-2 73
BNW-2 74
S-3 74
SE-4 74
1976
Collection
1977
Ranks of healthy needles,
1976-77 collection.
Figure 5.36. Ranks of tip burn,
1976-77 collection.
167
-------
325i
300-
275-
A 250-
V
E 225-1
?
A '~OCH
G
t 175
K 150
A
N 125
K
100-i
75
50
35
MOTTLE 1976-77 Collection
' 1973-74 NEEDLES IN TIME
S-5
S-3
BNW-I 73
-E-l 73
S-3 73
-S-5 73
-SE-4 74
SE-4 73
BNW-3 73
BNW-3 74
SE-2 73£r /
' — SE-2 74
1976
325
300-
275
A 250
V
E 225
R
A 200-1
G
E 175
R 150
A
N 125-1
K
100-
75-
50-
35
BASAL SCALE
1973-74 NEEDLES IN TIME
1976-77 COLLECTION
BNW-3 73
BNW-I 73
GB-I 73
E-l 73
SE-2 73
SE-4 73
S-3 73
S-5 73
BNW-2 73
GB-I 74
BNW-3 74
E-l 74
74
BNW-74
S-5 74
BNW-2 74
Collection
1977
1976
Collection
1977
Figure 5.37. Ranks of needle mottle,
1976-77 collection.
Figure 5.38. Ranks of basal scale,
1976-77 collection.
A
V
E
R
A
G
E
R
A
N
K
325
300
275
250
225
200
175
150
125
100-
75-
50-
35
BASAL NECROSIS
1973-74 NEEDLES IN TIME
1976-77 COLLECTION /
E-1 73
GB-1 73
GB-1 74
SE-2 73
BNW-1 73
BNW-2 73
SE-4 73
S-3 73
E-1 74
BNW-3 73
SE-2 74
BNW-3 74
BNW-1 74
S-5 73
SE-4 74
S-3 74
BNW-2 74
S-5 74
325
300
275-
A 250
V
E 225
R
A 200-
G
E 175
R 150
A
N 125
K
100
75
50
WEEVIL
1973-74 NEEDLES IN TIME
1976-77 COLLECTION ^ s-5 73
BNW-2 74
BNW-2 73
SE-4 74
SE-4 73
/-S-5 74
-S-3 74
-I 73
S-3 73
S-2 74
BNW-1 74
BNW-3 74
SE-2 73
-E-l 74
'E-l 73
BNW-3 73
GB-73
GB-I 74
I976
I977
1976
Collection
Collection
1977
Figure 5.39. Ranks of basal necrosis,
1976-77 collection.
Figure 5.40.
Ranks of weevil,
1976-77 collection.
168
-------
Figure 5.38 depicts the ranks of basal scale on 1Q71 a™i IQV/ f T
from the nine sites during 1976 and 1977. At E-I s-3 S 5 SE 4 and rfl
197^ndCl977tendldl TlGVel n^ °r deCreaSe °n l^s'fo'iie'^t; ^he^"1'
1976 and 1977 collections. Only at GB-1 was there a decrease in the
T^inThLf i- T SCai%Qn 19?4 f°liage durlng these two Collection periods
Turning back to Figure 5.29, one sees the trend for basal scale in 1973
and 1974 needles from the five Colstrip sites, but in Figure 5.7, this trend
is not evident from a single year's collection or analysis of different-aged
foliage.
Figure 5.39 depicts the ranks of basal necrosis on 1973 and 1974 foliage
over the 27- to 51-month exposure periods. At S-5, there was a decrease in
this pathology on both 1973 and 1974 foliage during the two collection
periods. It also decreased on 1973 foliage at BNW-3 during this time. The
same trend is more discernible in the data on Figure 5.30 but was not
evident at site S-5 as shown on Figures 5.8 and 5.10.
Figure 5.40 illustrates the prevalence of weevil damage on 1973 and
1974 foliage over time. Probably the most interesting aspect of the graph
is that it confirms the trends for this needle pathology on foliage from
the GB-1 and BNW-3 sites depicted in Figure 5.15. The fact that we found
less insect damage at GB-1 is supported by the rank of defoliator damage on
Figure 5.41 as well as the rank of the "other" pathology category on Figure
5.42.
The rank of defoliator damage on 1973 and 1974 foliage (Figure 5.41)
from S-5 is of interest because it might be inferred from Figure 5.9 that
the percent of this pathology on 1973 foliage increased between the 39- and
51-month (1974 and 1973) exposure periods. However, Figure 5.41 shows
that there was an almost identical amount of defoliator damage on 1973 and
1974 foliage in 1976 and that there was a substantially larger decrease
of defoliator damage in 1974 needles than in 1973 needles. Thus it would
be more correct to infer that the needles cast from 1974 internodes had
more defoliator insect damage than those being cast from 1973 internodes
at this site during the 12-month period.
Figure 5.43 illustrates the ranks of percent total necrosis on 1973
and 1974 needles during 1976 and 1977. Turning back to Figure 5.12, again
one can ascertain the importance of comparing damage pathologies over time
versus a single collection period. As previously stated in this text, we
have found that when total necrosis affects between 40% and 50% of a needle
surface, that needle will probably be cast from the internode. Most of the
figures on needle pathologies from the 1977 collection previously discussed
in this section demonstrate some increase of needle pathologies from younger
needles (1975-1976) to older needles (1973-1974). Figure 5.3 shows that
needles are being cast continuously at varying rates on all internodes
studied.
As depicted in Figure 5.43, the percent of total necrosis on ""and
1974 needle surface areas from GB-1 remained constant dunng 1976 and 1977,
although there was substantial needle casting dunng this two-year period
(Figure 5.34). This same trend was also apparent on 1973 and 1974 needles
169
-------
DEFOLIATOR 1976-77 Collection
325-j
300-
275 \
A 250
V
E 225
K
A 200
G
E 175
R 150
A
N 125
K
IOO-]
75
50-1
1973-74 NEEDLES IN TIME
— E-l 73
E-l 74
SE-2 73
BNW-2 73
BNW-2 74
SE-2 74
S-3 73
S-5 73
SE-4 74
S-3 74
BNW-3 73
—S-5 74
SE-4 73
GB-! 73
1976
Figure 5.41
1977
Collection
Ranks of defoliator,
1976-77 collection.
325
300-1
275
A 250
V
E 225-1
R
A 200
G
E 175
R 150
A
N 125
K
100-1
75
50-
35
OTHER PATHOLOGIES
1973-74 NEEDLES IN TIME
1976-77 COLLECTION
, E-l 73
S-5 73
1976 1977
Collection
Figure 5.42. Ranks of other pathologies
1976-77 collection.
TOTAL NECROSIS
1973-74 Needles In Time
1976-77 Collection
325
300-
275
A 250-
M
E 225-1
R
A 200-I
G
E 175
R 150
A
N 125
K
100-1
75
50
35
GB-! 74
——. GB-I 73
SE-2 73
BNW-3 73
BNW-I 73
x SE-2 74
E-l 73
^''S -SE-4 73
BNW-3 74
-! 74
.- S-3 73
74
1976
Collection
1977
Figure 5.43. Ranks of total necrosis,
1976-77 collection.
170
-------
from BNW-3 and on 1973 needles from BNW-1 during 1976 and 1977 collection
periods. The fact that the amount of necrosis on 1973 and 1974 foliage did
not change between the 27-month (1974 needles collection in 1976) and 51-
month (1973 needles collected in 1977) exposure periods strongly suggest that
there is a very quantifiable limit of total needle surface which can be
damaged prior to being prematurely cast. As illustrated in Figures 5.52 and
5.62, the mean fluoride and sulfur levels in different-aged foliage collected
from GB-1 tend to level out rather than increase in foliage. We suspect that
the damaged needles being prematurely cast from the pine trees at the GB-1
site are not only the most damaged, thus the leveling trend seen in Figure 5.43,
but have the highest fluoride and sulfur concentration. This hypothesis will
be discussed in some detail in the following section.
Fluoride, Needle Length, and Fascicular Cross-Sectional Area
Because it was necessary to substitute the Yaeger Butte site, SE-4,
during 1977 collections for the Whitetail site sampled during 1976, 1977 data
from SE-4 was used in three-level nested anova on 1975 and 1976 collections.
F ratios for indicated levels for 1975, 1976, and 1977 collections are shown
in Table 5.1. F ratios in parentheses in Table 5.1 are the values reported
in the TIR for the appropriate level. As may be seen in this table, substi-
tution of the Yaeger Butte site had minimal influence on significant treatment
effects; in the 1975 collection, a significant treatment effect for cross-
sectional area between the tree ages was shown. A treatment effect (p = .0566)
was seen for needle length in the 1976 collection between tree ages. Signi-
ficant effects at these levels were not detected with the Whitetail site
(Table 5.1).
Figure 5.44 depicts the mean values and 95% confidence intervals for
fascicular cross-sectional area of upper crown foliage, younger and older
trees, for all sites in the 1975 collection. The mean values between younger
and older trees within site SE-4 were significantly different at p £ .05.
Figure 5.45 depicts the mean values and 95% confidence intervals for
needle length at all sites in the 1976 collection, upper crown, for younger
and older trees. The mean values for S-3 were significantly different at
p <_ .02.
Table 5.1 also shows F ratios for the indicated levels for anova
computed on the data from the 1977 collection. Significant treatment effects
(P < .05) were detected between sites for needle length, while a treatment
effect between years of foliage within tree ages was detected for fascicular
cross-sectional area.
Figure 5.46 depicts the mean values and 95% confidence intervals for
fascicuSr cLs-sectional area of 1974, 1975, and 1976 upper crownjfclia
from all plots in the 1977 collection. Mean values for cross -sectional
areas (Figure 5 46) for 1975 foliage were smaller than those for 1974
dreas figure D.; 101 ^ ... T,c nQ7S < 1974) were also observed during
Although these relative positions (19/i> < wi*) ^ -^w arp*i-Pr than
-i ^- . ^f 1Q7^ f nT iase were slightly greater man
1976, the cross-sectional areas of 1973 loliage we 5 confidence
those of 1974. (For illustration 're 5.46
intervals for 1973 foliage from the 1976
171
-------
TABLE 5.1.
F RATIOS FOR FLUORIDE, NEEDLE LENGTH, AND FASCICULAR
CROSS-SECTIONAL AREA FOR THE THREE-LEVEL NESTED ANOVAS
FOR THE 1975, 1976, and 1977 COLLECTIONS
Level
Fluoride
Needle Length
Fascicular Cross-
Sectional Area
1975 Collection
Variable
24.988* (9.144)* 5.664* (10.480)* 5.206* (5.660)*
Between Sites
Between Tree Ages
Within Sites
Between Years of
Foliage Within
Tree Ages
Between Sites
Between Tree Ages
Within Sites
Between Years of
Foliage Within
Tree Ages
.249 (1.939) 1.452 (1.217) 2.944* (1.348)
1.253 (.751) 1.313 (1.374)
.496 (.500)
1976 Collection
Variable
2.757 (2.025) 7.289* (10.286)* 6.754* (6.629)*
1.761 (1.532) 2.604 (1.767) 1.170 (1.265)
.680 (.819)
.700 (.858)
.945 (.979)
Between Sites 4.784'
Between Tree Ages
Within Sites 1.037
Between Years of
Foliage Within .849
Tree Ages
1977 Collection
Variable
31.269*
.270
1.213
2.306
2.360
2.076*
*Indicates F ratio significant @ p j< .05; F ratios in parentheses are those
reported in the TIR.
probability level for this F ratio is .0591.
172
-------
1975
COLLECTION
S-5
SE-4
E-l
SE-2
YOUNGER
OLDER
AREA 1.5
2.0
S-3
2.5
3.0
3.5 MM2
Figure 5.44. Mean values and 95% confidence intervals for fascicular
cross-sectional area, upper crown, younger and older trees
S-5
SE-4
1976
.ECTION
100
_^t
-T-
120
E-l
w
T1
A
f
140
M
•
E-2^
Sr»
3
160
YOUNGER
OLDER
180 MM
Figure 5.45. Mean values and 95% confidence intervals for needle
length, upper crown, younger and older trees.
173
-------
1977 COLLECTION
YEAR OF
NEEDLE
^1976
•1975
#1974
(1973
S-3
Sc> A
O v ^
T
A
SE-4 *r '
Ei
1
E, COLLECTED 19"
SE-2 — • —
A
A f
^ ^
^
^
' T
3 • *
AREA MM2 |,Q
1,5
2.0
2,5
3,0
3.5,
Figure 5.46. Mean values and 95% confidence intervals for fascicular
cross-sectional area, all tree ages.
YEAR OF
COLLECTION
1975
1976
S-5
SE-4
E-l
SE-2
S-3
PPM F
0,5
1,0
1.5
2.0
2.5
Figure 5.47. Mean values and 95% confidence intervals for fluoride,
all tree ages, all years' foliage.
174
-------
for site E-l.) In the 1976 collection, 15-month foliage (1975 needles) had
the smallest cross-sectional area. During 1977, 15-month foliage O976
needles generally had the greatest area at each site. This suLests that
those biological and edaphic variables which influence fasciculfr ros -
sectional area are similar across all sites.
Significant (p < .05) treatment effects between sites were noted for ppm
?,ln }975 collection> ^ile no treatment effects were noted in the
1976 collection (Table 5.1). The treatment effect between sites in the 1977
collection (Table 5.1) was significant at p £ .06 (p = .0591). Figure 5.47
depicts the mean values and 95% confidence intervals for fluoride in the
upper crown position of all years' foliage combined for all sites from three
years' collections.
The differences in mean values for fluoride between sites from the 1975
collection are obvious (Figure 5.47). The same trend was similar on the
1976 collection. In 1977, differences in fluoride between sites were becoming
apparent, with the exception of foliage from E-l where the mean values were
similar to those measured in 1975.
Table 5.2 shows F ratios for the four-level nested anovas for 1975-1976
collections and 1975-1977 collections. The F ratios enclosed in parentheses
are those reported in the TIR in which data from the Whitetail site were used.
In both 1975-1976 and 1975-1977 collections, significant treatment
effects were noted between sites within collections for all variables and
between collections for fluoride only (Table 5.2). These effects were the
same whether the Yaeger Butte site or the Whitetail site was used.
These results are consistent and support those reported in the TIR.
Samples of ponderosa pine foliage collected from geographically separate
sites, from different tree ages within a site, or from different ages of
foliage cannot a priori be considered to be samples from the same population
for all characteristics.
Anova with GB-1, BNW-1, BNW-2, BNW-3 (1976 and 1977 Collections)
F ratios for three-level nested anova computed for all sites on 1976 and
1977 collections are shown in Table 5.3. Significant treatment effects
(p £ .05) between sites for the 1976 collection are shown for fluoride and
needle length, and between the years of foliage for fluoride.
The mean values and 95% confidence intervals for needle length collected
in 1976 from younger and older trees at all sites are shown in Figure 5.48.
Although the F ratio for the treatment between tree ages (Table 5.3) was not
significant (p = .1266), data on Figure 5.48 are shown between tree ages
because of the difference previously shown for site S-3 (Figure 5.45 and
Table 5.1). The mean values (Figure 5.48) for needle length of foliage from
younger trees at GB-1, S-5, SE-4, SE-2, and S-3 (younger trees) are very
similar. The BNW sites showed a difference in mean values for older^and
younger trees (younger < older), although the differences were not significant
However, the differences between younger and older trees were approximately
10 mm at each of the BNW sites.
175
-------
TABLE 5.2. F RATIOS FOR FLUORIDE, NEEDLE LENGTH, AND FASCICULAR
CROSS-SECTIONAL AREA FOR THE FOUR-LEVEL NESTED ANOVAS
FOR THE 1975-1976 AND 1975-1977 COLLECTIONS
Fascicular Cross-
Level Fluoride Needle Length Sectional Area
1975-1976 Collections
Variable
Between Collections 8.957* (7.557)* .007 (.048) .350 (1.252)
Between Sites
Within Collections 9-598* (5.925)* 6.584* (10.369)* 5.832* (6.289)*
Between Tree Ages
Within Sites .695 (1.731) 1.937 (1.481) 1.827 (1.293)
Between Years of
Foliage Within 1.019 (.784) .958 (1.066) .708 (.741)
Tree Ages
1975-1977 Collections
Variable
Between Collections 4.622* .0118
Between Sites
Within Collections 7.244* 8.801*
Between Tree Ages
Within Sites .829 1.247
Between Years of
Foliage Within .954 1.050
Tree Ages
.290
4.239*
1.582
1.082
*Indicates F ratio significant @ p £ .05; F ratios in parentheses are those
reported in the TIR.
176
-------
TABLE 5.3. F RATIOS FOR FLUORIDE, NEEDLE LENGTH, AND FASCICULAR
CROSS-SECTIONAL AREA FOR THE THREE-LEVEL NESTED ANOVAS
FOR THE 1976 AND 1977 COLLECTIONS
Level
Fluoride
Needle Length
Fascicular Cross-
Sectional Area
1976 Collection
Variable
Between Sites
315.218*
6.951*
2.516
Between Tree Ages
Within Sites
.563
1.693
1.834
Between Years of
Foliage Within
Tree Ages
1.920*
.978
1.185
Between Sites
1977 Collection
Variable
99.448*
25.632*
1.777
Between Tree Ages
Within Sites
.560
.294
1.482
Between Years of
Foliage Within
Tree Ages
1.956*
1.382
1.454:
*Indicates F ratio significant @ p £ .05.
*The probability level for this F ratio is .0554.
177
-------
GB-
BNW-I
4
4
YOUNGER TREES
Jf OLDER TREES
BMW-2
4
BNW-3
S-5
SE-4
4
4
F976 COLLECTION
E-l
SE-2
S-3
4
4
100 120 140 160 180 200MMLength
Figure 5.48. Mean values and 95% confidence intervals for needle
length, younger and older trees.
178
-------
The mean values and 95% confidence intervals for needle cross-sectional
area collected in 1977 from younger and older trees at all sites are shown in
Figure 5.49. This data is shown for tree ages because of the differences
evident at S-5 and SE-4 (Figure 5.44 and Table 5.1). Although F ratios for
the treatment between tree ages for cross-sectional area were not significant
at p <_ .05, they were at p <_ . 10 (p = .095). Although all older trees sampled
did not have needles with fascicular cross-sectional areas larger than younger
trees (and vice versa), the tree ages are different at some sites. Following
the trend evident in needle length (Figure 5.48), the GB-1 site did not have
needles which were either larger or smaller in cross-sectional area than
needles from the other sites.
The mean values and 95% confidence intervals for fluoride in 1973, 1974,
and 1975 needles from the 1976 collection at all sites are shown in Figure
5.50- It is obvious that the years of foliage were different (1975 < 1974 or
1973) within GB-1 as well as between GB-1 and all other sites regarding total
fluoride. BNW-1 had higher fluoride levels than S-5, SE-4, E-l, SE-2, or S-3.
However, only GB-1 showed an obvious difference in fluoride between years of
foliage origin.
In the 1977 collection, significant treatment effects (p £ .05)
(Table 5.3) were detected between sites for fluoride and needle length, and
between years of foliage for fluoride and fascicular cross-sectional area.
The mean values and 95% confidence intervals for fascicular cross-sectional
area for 1974, 1975, and 1976 foliage from the 1977 collection are shown on
Figure 5.51 for GB-1 and the BNW sites. The same data are shown on Figure
5.46 for the other sites. A similar trend is evident in both figures: The
1976 foliage had a larger average cross-sectional area than 1975 foliage;
however, 1975 foliage was not significantly different than 1974 foliage.
Figure 5.52 shows the mean values and 95% confidence intervals for
fluoride in 1974, 1975, and 1976 foliage collected in 1977 from all sites.
The difference in fluoride between years of foliage from GB-1 was clear; 1975
foliage from this site showed approximately the same average fluoride content
in 1976 as in 1977 (Figures 5.50 and 5.52, respectively), and values for 1974
foliage were reduced from about 60 ppm (Figure 5.50) to about 43 ppm (Figure
5.52). The mean values for fluoride in foliage from BNW-1 were greater in
1976 than in 1977 (Figures 5.50 and 5.52, respectively). Figure 5.53 shows
the mean values and 95% confidence intervals for fluoride in each year's
foliage for 1976 and 1977 collections from BNW sites only.
During the 1977 collection, fascicular sheaths from all sites were
retained for fluoride and sulfur analyses. Fluoride determinations have been
completed, and anova was computed on the data. F ratios for the indicated
levels are shown on Table 5.4. Significant treatment effects between sites
and between years of foliage were detected. Mean values and 95% confidence
intervals for fluoride in fascicular sheaths from each year of foliage for
the 1977 collection period are shown in Figure 5.54. Differences in mean
fluoride values between sites and between years of foliage are obvious.
None of these values exceeded 6 ppm for sites S-5, SE-4, E-l, SE-3, or S-3.
However, at BNW-2 and BNW-3, only 1976 sheaths had values below 6 ppm. Mean
fluoride values for 1974 and 1975 foliage at these two sites and mean fluoride
values for all years of foliage at BNW-1 were greater than 7 ppm.
179
-------
GB-I
1976 COLLECTION
•YOUNGER TREES
BOLDER TREES
BNW-I
BMW-2
BNW-3
S-5
4
SE-4
E-l
SE-2
S-3
MM
1.5 2.0 2.5 3.0 3.5 AREA
Figure 5.49. Mean values and 95% confidence intervals for needle
cross-sectional area, younger and older trees.
180
-------
1976 COLLECTION
S-5
SE-4
E-l
•—*-•
SITE GB-I
20
40
60
80
SE-2
S-3
1975
1974
1973
BNW-I
BNW-2
BNW-3
F" 1.0 2.0 3O 4.0 5.0 6.0 PPM
Figure 5.50. Mean values and 95% confidence intervals for fluoride
in 1973, 1974, and 1975 foliage.
181
-------
GB-I
BNW-I
BNW-3
1977 COLLECTION
41976
• 1975
*I974
' f
BNW-2
MM* 1.5 2.0 2.5 3.0 3.5 AREA
Figure 5.51. Mean values and 95% confidence intervals for fascicular
cross-sectional area in 1974, 1975, and 1976 foliage.
182
-------
S-5
SE-4
•—*•
E-l
SE-2
S-3
BNW-I
BNW-2
BNW-3
+
1977 COLLECTION
SITEGB-I
—*—
20
+
• 1976
• 1975
* 1974
40
60
F" 1.0 2.0 3.0 4.0 5.0 6.0 PPM
Figure 5.52. Mean values and 95% confidence intervals for fluoride
in 1974, 1975, and 1976 foliage.
183
-------
SITE BNW-I
1975
1974
1973
1976
COLLECTION
•f
1976
1975
1974
1977
COLLECTION
1.0 2O 3.0 4.0 5.0 PPM FLUORIDE
Figure 5.53. Mean values and 95% confidence intervals for fluoride
in 1973, 1974, 1975, and 1976 foliage at site BNW-1.
TABLE 5.4.
F RATIOS FOR FLUORIDE IN FASCICULAR SHEATHS
FOR THE 1977 COLLECTION
Level
Variable Fluoride
in Sheaths
Between Sites
Between Tree Ages
Within Sites
Between Years of
Foliage Within
Tree Ages
185.532*
.133
6.886*
*Indicates F ratio significant @ p _< .05
184
-------
S-5
•-*—•
1977 COLLECTION
SE-4
E-l
SE-2
S-3
BNW-f
BNW-2
BNW-3
•*-«
I—• 1
SITE 6B-1
20 30 40 50 60
41976
• 1975
*I974
; r~Y~
1 *
H
F"0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 ppm
Figure 5.54. Mean values and 95% confidence intervals for fluoride
in fascicular sheaths of 1974, 1975, and 1976 foliage.
185
-------
The mean values and 95% confidence intervals for sulfur in pine needles
from S-3 for 1976 and 1977 collections are shown in Figure 5.55. Figure 5.56
shows results of the 1977 collection from the BNW sites. As can be seen,
foliage from BNW-2 generally contained less sulfur than foliage from BNW-1 or
BNW-3. Figures 5.57 and 5.58 show mean values and 95% confidence intervals
for sulfur in foliage from the 1976 and 1977 collections from BNW-1 and BNW-3.
BNW-1 showed a slight reduction in mean sulfur concentrations in 1977 below
those measured in 1976 (Figure 5.57), as did site S-3 (Figure 5.55). The
sulfur values at BNW-3 did not show a parallel decrease for the 1977 collec-
tion; rather there is a slight increase in 1977 over 1976 (Figure 5.58).
Figure 5.59 shows mean values and 95% confidence intervals for sulfur in
fascicular sheaths from the three BNW sites collected in 1977. As with
fluoride (Figure 5.54), the mean sulfur concentration increased with increasing
year of foliage origin. Figures 5.60 and 5.61 show the mean values and 95%
confidence intervals for sulfur in fascicular sheaths from BNW-1 and BNW-3,
respectively, for 1976 and 1977 collections. Sulfur decreased in 1977 from
the 1976 levels at BNW-1 (Figure 5.60) but not at BNW-3 (Figure 5.61).
Figure 5.62 shows the mean values and 95% confidence intervals for
sulfur in needles and fascicular sheaths from GB-1, 1977 collection. Sulfur
in needles increased from the 1977 to the 1976 years of foliage, remained
very similar through 1974 foliage, and decreased from 1974 through 1972. In
contrast, sulfur concentrations in fascicular sheaths showed an increase with
older foliage. Figure 5.63 shows the mean values and 95% confidence intervals
at GB-1 for sulfur in ponderosa pine needles, 1976 and 1977 collections.
The mean values shown on Figure 5.62 are about twice those measured at
the Colstrip sites (compare with Figure 5.55 and 5.56). While there was a
slight decrease in sulfur at GB-1 in 1977 from the levels measured in 1976,
the decrease was not observed in all years of foliage (Figure 5.63).
Understory Species
Basic statistics for fluoride in understory species collected at sites
S-5, SE-4, E-l, SE-2, and S-3 are arrayed in Table 5.5. Fluoride analyses
have yet to be completed on the BNW and GB-1 sites. Sulfur measurements on
understory species from any of the sites have not been completed.
DISCUSSION
Growth/Health/Damage Characteristics of Pine Foliage
Quantification of the growth/health/damage characteristics of pine
foliage exposed to pristine and chronically-polluted environments for 15 to
51 months has revealed very subtle pathological damage in ponderosa pine
foliage in both environments. This damage may not be apparent to even
trained and experienced air pollution field researchers. For instance, the
upper and lower canopies of the ponderosa pine trees at the Billings GB-1
site are not so visibly damaged that one can use field observations to
conclude that pines here are retaining less healthy or even less needles than
those at the pristine S-3 site.
186
-------
SITE S-3
NEEDLES
1976
1975
1974
1973
1972
1976 COLLECTION
1977
400 500 600 700 800
PPM SULFUR
Figure 5.55. Mean values and 95% confidence intervals for sulfur
in pine needles from site S-3.
1977 COLLECTION
NEEDLES
1977
1976
1975
1974
1973
1972
BNW- I
BNW-2
BNW-3
300 400 500 600 700 800 900 1000
PPM SULFUR
Figure 5.56. Mean values and 95% confidence intervals for sulfur
in pine needles from the BNW- sites.
187
-------
1977
1976
1975
1974
1973
1972
SITE BNW-I NEEDLES
1976 COLLECTION, Jf 1977 COLLECTION
400 500 600 700 800
PPM SULFUR
900 1000 1100
Figure 5.57. Mean values and 95% confidence intervals for sulfur
in pine needles from site BNW-1.
1977
1976
1975
1974
1973
1972
SITE BNW-3 NEEDLES
1976 COLLECTION, ^1977 COLLECTION
300 400 500 600 700 800 900
PPM SULFUR
Figure 5.58. Mean values and 95% confidence intervals for sulfur
in pine needles from site BNW-3.
188
-------
SHEATHS
1977 COLLECTION
1976
1975
1974
1973
1972
LJIV TV 1
• • BNW-2
~~"~~ A A BNW-3
A
100 200 300 400 500 600 700
PPM SULFUR
Figure 5.59. Mean values and 95% confidence intervals for sulfur
in fascicular sheaths from the BNW sites.
SITE BNW-1
1976
1975
1974
1973
SHEATHS
1976 COLLECTION
1977 COLLECTION
0 100 200 300 400 500 600 700
PPM SULFUR
Figure 5.60.
Mean values and 95% confidence intervals for sulfur
in fascicular sheaths from site BNW-1.
189
-------
SITE BNW-3
SHEATHS
1976
1975
1974
1973
4 1976 COLLECTION
*I977 COLLECTION
0 100 200 300 400 500 600 700
PPM SULFUR
Figure 5.61. Mean values and 95% confidence intervals for sulfur
in fascicular sheaths from site BNW-3.
IOUU
1400
1200-
1000-
800-
600-
400-
1
<
oi I c. v;
)
/
/
/
•
>D-| "INttULLS
• SHEATHS
,
NEEDLES
^^^
1 ^+*~~
^^
4
,.&**
/
/'
i
6^X '
/ i
|
1
•
f ( 1977 COLLECTION )
977 1976 1975 1974 1973 1972
Figure 5.62. Mean values and 95% confidence intervals for sulfur
in needles and fascicular sheaths from GB-1.
190
-------
1976
1975
1974
1973
1972
SITE GB-I NEEDLES
COLLECTION, • 1976, • 1977
900 1000 1100 1200 1300 1400 1500 1600
PPM SULFUR
Figure 5.63. Mean values and 95% confidence intervals for sulfur in needles
from GB-1.
-------
TABLE 5.5. BASIC STATISTICS FOR FLUORIDE IN UNDERSTORY SPECIES
Site
S-5
SE-4
E-l
SE-2
S-3
S-5
SE-4
E-l
SE-2
S-3
S-5
SE-4
E-l
S-3
SE-4
E-l
S-3
S-5
SE-4
SE-2
n x s
Artemesia oana
(Silver Sage)
8 1.9 .29
8 2.71 1.53
8 2.23 -62
8 1.88 .72
8 1.28 .43
Agropyron spicatum
(Bluebunch Wheatgrass)
8 .99 .32
8 2.98 1.12
8 .9 .57
8 1.1 .32
8 2.29 .59
Yucca glauca
(Yucca)
8 1.15 .36
8 2.86 .56
8 .91 .24
8 3.3 .42
Psoralea sp.
(Scurf Pea)
7 4.87 1.46
5 3.4 1.77
8 3.36 1.0
Gutierrezi-a sarothrae
(Brown Snakeweed)
8 3.7 1.03
8 3.84 1.00
8 2.2 .69
SL_
X
.10
.54
.22
.25
.15
.11
.4
.2
.11
.21
.13
.2
.08
.15
.55
.79
.36
.36
.35
.24
Site
S-5
SE-4
E-l
SE-2
S-3
S-5
SE-4
E-l
SE-2
S-3
S-5
SE-4
S-3
E-l
SE-2
S-3
S-5
SE-4
n x s
Artemesia frigida
(Fringed Sage)
8 3.4 .99
7 3.8 1.87
8 2.8 1.06
8 1.96 .55
8 3.35 .25
Rhus tr-ilobata
(Skunkbush)
8 1.18 .52
8 4.1 1.37
8 1.94 .51
8 1.78 .42
8 1.96 .62
Festuca -idahoens-is
(Idaho Fescue)
8 2.28 .49
8 1.2 1.19
8 2.03 .92
Andropogon scopar'ius
(Little Bluesteift)
8 3.36 1.45
8 .81 .36
8 .8 .35
Artemesia ludoniciana
(Prairie Sage)
6 5.7 4.37
8 5.25 2.28
S—
x
.35
.71
.37
.19
-09
.18
.48
.18
.15
.22
.17
.42
.32
.51
.13
.14
1.78
.81
(continued)
192
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TABLE 5.5. BASIC STATISTICS FOR FLUORIDE IN UNDERSTORY SPECIES
(continued)
Site
S-5
SE-4
SE-2
SE-2
n x s s—
X
Balsamovh-iza sag-ittata
(Arrowleaf Balsamroot)
8 4.14 1.52 .54
8 4.58 1.48 .52
ATtemesi-a tr-Ldentata
(Big Sage)
8 .84 .54 .19
Juniperus scopulorvan
(Rocky Mountain Juniper)
8 2.24 .42 .15
Site n x s
Lupinus sp.
(Lupine)
S-5 8 2.44 .35
S-3 8 3.44 .72
St-ipa Qomata
(Needle and Thread)
SE-2 8 1.89 .63
Prunus virgin-iana
(Chokecherry)
S-3 8 .75 .19
s—
x
.12
.26
.22
.07
193
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Our studies during the last three years have taught us that chronic air
pollution damage is not necessarily manifested by pine foliage exposed for
12 or even 24 months. Damage must be measured during the entire tenure of
foliage on the trees. Thus, if field researchers find only slight patho-
logical symptoms on current to three-year-old foliage (27 months), they do
not necessarily have scientific evidence significant enough to conclude that
chronic air pollution damage is not occurring. In fact, after this study in
southeastern Montana is completed, it might be advantageous to do some rede-
fining and to separate the rapid chronic air pollution damage (one growing
season) occurring in the San Bernardino Forest of California (Miller &t al. ,
1977) and the Flathead National Forest of Montana (Carlson, 1978) from the
slow, insidious chronic damage (two to five growing seasons) we are. finding
at a few of the Colstrip sites and at the Billings GB-1 site. It is very
likely that past air pollution field investigations were utilizing chronically-
damaged coniferous forest sites as controls to compare or quantify impacts of
the acute and/or severe chronic damage to conifer sites they were studying.
If one compares a low chronically-damaged conifer site to a severe chronically-
damaged conifer site, one really has not accurately ascertained the full
impacts of the air pollution episodes.
Earlier in the results section, we cautioned the reader on the use of a
single-year study to determine air pollution impacts on the growth/health/
damage characteristics of pine foliage. We hope that our reasons for sugges-
ting this caution become apparent as one compares the results of our 1977
findings, presented in Figures 5.3 through 5.24, to data presented on the
1973 and 1974 foliage exposed for three years (Figures 5.25 through 5.33) or
for two years (Figures 5.34 through 5.43).
Several of the growth/health/damage characteristics quantified during a
given study period tend to show the same patterns as other characteristics
which occur over a longer period of time. The first such characteristic is
needle retention, which is illustrated in Figures 5.3, 5.25, and 5.34. One
notes that the trends on all of these graphs are identical. All three,
particularly Figure 5.3, demonstrate that needles are continuously being cast
from all-aged internodes, especially between the 39- and 51-month exposure
periods at the Colstrip sites. At the chronically-polluted GB-1 site, the
major amount of premature needle casting occurred between the 27- and 39-
month exposure period. During the 1978 study season, we will continue to
quantify percent needle retention on older foliage (1973 and 1974) where
possible at several of the pine sites.
Percent healthy needles is a characteristic which also maintains a
uniform trend when quantified over several growing seasons (Figure 5.4). The
most obvious changes in the number of healthy needles were quantified at GB-1,
and the largest amount of premature needle casting occurred at this Billings
site.
The amount of needle mottle quantified during a single study period is
not necessarily a characteristic which an investigator can utilize to deter-
mine air pollution impacts. For instance, one notes in Figure 5.5 that the
prevalence of this pathology was less in 15-month-old foliage from the GB-1
site than on foliage from the three Colstrip sites; mottle was also less
194
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prevalent on 51-month exposed foliage from GB-1 than on foliage from six
Colstrip sites. Even in quantifications of the amount of needle tissue
damaged by mottling (Figure 5.13), the two Colstrip sites had similar damage
on 15-, 27-, and 51-month-old foliage. The results we have thus far accumu-
lated strongly suggest that premature casting from various-aged internodes is
removing substantial amounts of mottled needles.
We believe that needle tip necrosis (or tip burn) can be used in both
single and extended study periods. However, one should use some caution when
studying this pathology on older foliage. As depicted in Figure 5.36, the
prevalence of tip burn remained very similar on 27- and 51-month-old foliage
from BNW-3 and GB-1 during this extended period. An investigator quantifying
this pathology on various-aged foliage might infer that it ceases after
needles reach a certain age. If this were true, all the prematurely cast
needles of this-aged foliage (Figures 5.3 and 5.34) would not show any tip
burn. This is extremely improbable because, as the data on Figures 5.6, 5.14,
5.27, and 5.36 indicate, the incidence of tip necrosis keeps pace with pre-
mature needle casting in chronically-polluted areas.
We have placed quotation marks around the word "pristine" when describing
the remote pine sites in southeastern Montana (S-5, SE-4, and S-3), because
basal scale and basal necrosis were prevalent and quantified throughout the
area before the Colstrip power plants began operations.
Event rainwater samples collected before and after the Colstrip coal-
fired units went on-line had pH values ranging from over 8.0 to lows of 4.1
(COo free). Because of these lower acidic levels, it is our belief that the
Colstrip study area was not pristine before the power plants began operations,
even though no detectable levels of phytotoxic gases, except for ozone (.03 ±
.01 ppm), were reported after thousands of hours of ambient air monitoring by
EPA (Northern Cheyenne Tribe, 1976) and the Montana Department of Health and
Environmental Sciences (1976). Thus, while we have continued to utilize the
term "pristine" to describe several of our ponderosa pine-skunkbush sites
located 25 to 80 km from Colstrip, the term relates only to the lack of phyto-
toxic gases in the ambient air and not to event rainfall with pH values below
5.4. Data from our precipitation chemistry studies of event rainfalls in
southeastern Montana were reported by Gordon et at. (1978b) in an annual
report to ERDA (former name of present DOE) which is currently in draft form.
After nine years of histological studies, we now consider basal scale
and basal necrosis to be different manifestations of the same pathology.
This long period of indecision is too complex to be discussed here, but it
should be noted that other investigators, including Wood and Pennypacker
(1975), Farrier (1972), and Keifer and Saunders (1972), have reported that
basal needle necrosis can be either identified insects, mites, or unidentified
entomological species. We do not doubt that insects are present beneath the
fascicular sheaths of pine needles and that some of these species feed upon
the tissues of the needle base; we have many photographs and photomicrographs
of this phenomenon. However, both basal necrosis and basal scale that we
have quantified in polluted and pristine areas and checked with histological
studies were caused almost invariably by an abiotic agent. This agent is
derived from either acidic precipitation or particulate matter which becomes
195
-------
lodged between the fascicular sheath and the needle epidermis, and precipi-
tates off an acidic solution when moistened by rain, dew, or mist.
Figures 5.7 and 5.8 depict the incidence of basal scale and necrosis on
pine foliage collected during 1977. The data on both graphs demonstrate that
the incidence of basal needle tissue damage increased constantly with the
exposure period of the foliage at all nine sites, the exceptions being basal
necrosis at BNW-3, S-5, and SE-4 (Figure 5.8). While there may have been
significant differences between the incidence of basal scale and basal
necrosis on the same-aged foliage from the nine different sites during 1977,
this has not been tested and will be reported later in either the EPA Fifth
Interim Report or the next DOE Annual Report.
The basal needle pathologies are particularly interesting because they
were only slightly more prevalent on the 27- and 39-month old foliage from
GB-1 than on foliage from the Colstrip sites. On Figures 5.17 and 5.20, the
incidence of both basal scale and basal necrosis demonstrates that these two
pathologies were more prevalent on 51-month-old foliage than the majority of
other needle pathologies being quantified. Figure 5.30 shows that both 1973
and 1974 needles prematurely cast from the Colstrip site S-5 between the 1976
and 1977 collection periods included a substantial number of needles with
necrotic basal tissue. A similar pattern of needles damaged by basal scale
and basal necrosis and prematurely cast from the older internodes can be seen
in Figures 5.38 and 5.39 at a few of the sites.
Unfortunately, the incidence or even presence of basal needle tissue
damage has been and is being ignored by air pollution field researchers.
But personnel of the University of Montana Environmental Studies Laboratory
have demonstrated that this pathology is present on all conifer species used
as bioindicators in various areas of the United States and Canada.
The incidence of pine needle defoliators was fairly constant on all-aged
foliage collected within a given site. To us this means that insects causing
the damage are endemic and at most sites consistute a very small percentage of
the needle pathologies, as attested by the data on Figures 5.17 through 5.20.
Damage caused by the pine needle weevil (Scythropus elegans} was also
approximately equal on any given year's foliage collected within a site. One
of the more interesting aspects of the data thus far gathered is the low inci-
dence of damage caused by this insect at the chronically-polluted GB-1 and
BNW-3 sites. Whether this was due to the presence of pollution or was just a
coincidence is not known. However, studies over extended periods will
probably disclose whether GB-1 ponderosa pine trees simply have escaped a
higher endemic population than the Colstrip sites or if air pollution reduced
the population.
"Other pathologies" is an inclusive category for damgage caused by
unidentified fungi and possible insect punctures (small necrotic spots) and
physical damage caused by bruising or strong winds and/or hail. This is an
important category which should be utilized and quantified in air pollution
studies. It should be noted that very little fungal-caused needle damage has
been observed at any of our ponderosa pine sites during the entire study
196
-------
period, and the injury discussed here was caused primarily by unidentified
insects, abiotic agents, and physical damage. Figure 5.11 demonstrates that
other pathology damage continually increased over exposure periods; it never
decreased on 27- to 51-month-old foliage. Because the amount of damage
caused by weevil, defoliator, or abiotic pathologies such as basal scale,
basal necrosis, mottle, etc. was reduced at some sites during the 39- to 51-
month exposure periods by premature needle casting, we suspect that a large
portion of the unidentified needle damage quantified in the other pathology
category was caused by abiotic factors not related to air pollution.
The other pathology category was not the most prevalent pathology at S-3
(Figure 5.17), although it was responsible for the largest amount of necrosis
and constituted the major amount of needle surface damage on 51-month-old
foliage (Figure 5.21). This pathology was also very prevalent at sites BNW-3
and GB-1 (Figures 5.19 and 5.20) where only tip necrosis caused more damage
to 51-month-old foliage (Figures 5.23 and 5.24). If air pollution field
investigations do not utilize a category for needle damage with no readily
ascertainable cause, this type of damage may be categorized as air pollution
damage.
The measurement of total necrosis is, as previously mentioned, an esti-
mation by the investigators of the total amount of needle surface area of
different-aged foliage damaged by all abiotic and biotic causal agents. We
also believe that when 40% to 50% of a needle surface becomes necrotic/
chlorotic in either pristine or polluted areas, the needle will be cast from
the stem within a 12-month period, regardless of its age. It should not be
inferred that needles will not be cast until this much of their surface area
is damaged; in some areas, pine needles manifesting substantial amounts of
basal needle pathologies (basal scale and basal necrosis) can be cast before
their leaf surface is substantially damaged.
Figure 5.43 depicts total necrosis on 1973 and 1974 foliage as quanti-
fied during the 1976 and 1977 study period. Figure 5.34 illustrates the
prevalence of needle retention during these same study periods. When
comparing total necrosis to the needle loss in 1973 and 1974 GB-1 foliage
during this two-year study period, the prevalence of total necrosis remained
constant, while the incidence of needle casting rapidly increased. During
this same time, the prevalence of tip burn (Figure 5.36) remained constant at
GB-1, and mottling decreased on both years' foliage (Figure 5.37). The inci-
dence of weevil, defoliator, and other pathologies was fairly constant on
1973 and 1974 foliage from GB-1 during these two years.
There are only two alternate explanations for the fact that the preva-
lence of total necrosis remained constant on 1973 and 1974 needles at GB-1
between the 27- and 51-month exposure periods, while premature needle casting
rapidly increased at the same time:
(1) The amount of total needle tissue damage increased on the
remaining and therefore healthier needles during this 12-
month period. Thus, the most severely-damaged needles in
1976 were cast before the 1977 study period.
197
-------
(2) The 1973 and 1974 foliage prematurely cast between the 27-
and 51-month exposure periods was composed mostly of healthier
needles, and the most damaged remained on their respective
internodes.
Currently it is our hypothesis that the first alternative is the most
likely and that the remaining needles on the older internodes have increased
pathologies during the 27- to 51-month exposure period. More recently, nylon
netting bags with five compartments, one for each internode, have been
attached to the branches of the ponderosa pine trees at four sites. The
purpose of this study is to collect, over a six-month period, the prematurely
cast needles from each of the five internodes retaining foliage. These
premature needles will be analyzed for pathologies and sulfur and fluoride
content to test our hypothesis that needles being prematurely cast are more
damaged by certain pathologies and contain higher sulfur and fluoride levels
than those being retained.
The results of our measurements of needle length and fascicular cross-
sectional area demonstrate that sometimes there were significant differences
within plots and between plots in different-aged foliage of both younger and
older trees. However, these two growth characteristics may not be useful for
determining chronic air pollution impacts. We noticed that lengths and cross-
sectional area of needles from the chronically-polluted GB-1 site were quite
similar to those from the five Colstrip sites (S-5, SE-4, E-l, SE-2, and S-3).
The ponderosa pine trees at the Billings GB-1 site have been impacted by
substantial amounts of phytotoxic gases since about 1967 (Montana DHES, 1976),
when the 180 MW coal-fired power plant went on-line. If the pines at this
site, after ten years of fumigation with damaging levels of HF and SC^, are
still producing needles with the same general lengths and cross-sectional
areas as needles from pristine sites, these two growth characteristics may
not be of use for determination of chronic air pollution damage. However,
these types of needle measurements may be useful in studies of areas subject
to acute or high levels of chronic air pollution impacts (damage manifested
within a year). For instance, Miller et al. (1977) reported that shorter
needles were found on ponderosa pine foliage damaged by phytotoxic pollutants
in the San Bernardino National Forest. Thus, use of these two growth charac-
teristics should not be dismissed until it is determined how severely pines
must be fumigated under field conditions before showing a loss of needle
surface.
Fluoride levels in different-aged needles from the Colstrip sites
generally remained constant over the past three years at concentrations lower
than those reported in the literature as causing damage to ponderosa pine
foliage. Unpublished studies by Gordon (1977) on fluoride accumulation in
damaged ponderosa pine foliage collected in The Dalles, Oregon, area found
fluoride concentrations in damaged needles averaging from 10 to 14 ppm,
depending on the study site. In a 1977 field study of chronic fluoride
pollution impact to several species of pine and fir in Columbia Falls,
Montana, Carlson (1978) found concentrations of 10 to 12 ppm fluoride in
damaged pine foliage.
198
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Fluoride concentrations in different-aged foliage from BNW-1 and BNW-3
were slightly higher than levels found in foliage from the more distant
Colstrip sites, SE-2 and S-5. However, fluoride levels alone do not appear
to be the cause of the increased needle pathologies at BNW-1 and BNW-3.
Fluoride levels in fascicular sheaths from all three BNW sites were
substantially higher than those found at the more distant Colstrip ponderosa
pine sites. It is difficult to determine the source of these elevated
fluoride levels because of the large amount of coal dust in the immediate
Colstrip vicinity where the BNW sites are located. The utility companies
operating the two power plants at Colstrip have been cited by the EPA for
violations of particulate level standards at this operation. Analyses of
some of the coal being mined at Colstrip showed fluoride concentrations
ranging from approximately 30 to 80 ppm (Montana DHES, 1974), less than levels
found in the soils of the area. However, substantial amounts of fine parti-
culate coal dust probably become airborne in the area during blasting in the
open pit mines. Thus, we are not currently attributing the elevated fluoride
levels found in the foliage and the fascicular sheaths at the BNW sites to
either power plant emissions or coal dust from mining operations, because it
is more likely that both contribute to the increase.
The elevated fluoride levels found in both needles and fascicular sheaths
from the Billings site were consistently and surprisingly high during the last
two years. Total fluoride emissions from the four stationary sources in a
15-mile radius of GB-1 (three oil refineries and one 180 MW coal-fired power
plant) are approximately 90 pounds per day (Montana DHES, 1974, 1977). That
the fluoride concentrations in the ambient air of this site are causing a
portion of the foliar damage to pines is without doubt. However, total S02
emissions from the stationary sources in the Billings area are approximately
57 tons per day (Montana DHES, 1974) or 2.4 tons per hour, and this gas also
is impacting and accumulating in the pine foliage at the GB-1 site.
What constitutes a "normal sulfur concentration" in ponderosa pine
foliage from a pristine area has been an issue of some debate in the liter-
ature on the subject. As previously mentioned, Katz and McCallum (1939)
reported in an extended field study that the mean sulfur levels in ponderosa
pine foliage from Summerland, B.C., were 600 to 700 ppm; three-year-old
foliage from what he considered a control area 90 miles downwind from Trail,
B.C., contained levels as high as 1,500 ppm.
Sulfur levels in pine foliage from the more distant Colstrip sites
remained extremely consistent during the last three years, and it is difficult
to accept a level of 1,500 ppm sulfur in ponderosa pine as typical on foliage
from a true control site. This belief is strengthened by sulfur concen-
trations we found in current and older pine needles and fascicular sheaths
collected from GB-1 (Figures 5.62 and 5.63) and the findings of Carlson
(1974) in a field study on damaged Douglas-fir and ponderosa pine foliage
around a Kraft pulp and paper mill here in Missoula, Montana. Unlike
fluoride, low ambient sulfur concentrations taken in by pine foliage can be
translocated out of this tissue as sulfate (Faller et al. , 1970). Fluoride,
on the other hand, migrates to the edges of leaf tissues (Compton and Remmert,
1960; Jacobson et al. , 1966; Tourangeau et al. , 1977) where it accumulates
199
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excessively in comparison to whole leaf tissues. It is not known whether
these elevated sulfur levels in older foliage (1972-1976) remained fairly
constant at around 1,300 ppm because of: (1) Translocation of sulfur out of
the leaf tissue or (2) needles with the most elevated levels being prematurely
cast. We strongly suspect that this second supposition is applicable to areas
where severe chronic and acute fumigation damage is occurring, but sulfate
translocation probably explains the uniform sulfur levels at the Billings
site. This supposition will be studied during the 1978 and 1979 study period
using special needle catch traps to selectively collect samples of different-
aged needles being prematurely cast from the internodes of trees at both the
Billings and Colstrip sites.
After quantifying and studying the pine foliage growth/health/damage
characteristics which occurred during the last three years, we have prepared
a tentative conceptual model (Figure 5.64) to explain the occurrence rates of
low level chronic air pollution symptoms such as necrosis, needle retention,
and fluoride and/or sulfur accumulation. The model will be tested on the
results of 1978 and 1979 studies, which will include data obtained from
analyses of selectively-collected, prematurely-cast needles from polluted and
pristine areas in southeastern Montana. This conceptual model is based on
three major hypotheses, each of which is dependent on the others:
(1) Regardless of the cause(s) of needle necrosis or damage, when
the entire surface area of a needle becomes more than 40%
necrotic (38% to 50%), it will be cast from the stem during
the year that level of necrosis occurs.
(2) If the needle damage is being caused by the accumulation of
low, chronic levels of phytotoxic gases, such as fluoride
and/or S02 in the foliage, prematurely cast needles will
have accumulated more elevated levels of one or both of these
elements than the less-damaged foliage retained on the same
internode.
(3) There will be a reduction in certain necrotic symptoms, such
as mottle and basal scale, on needles being retained on older
internodes. The amount of other necrotic symptoms, such as
basal necrosis and tip necrosis, will not decrease signifi-
cantly on that same foliage.
These three tentative hypotheses were the result of our studies of
trends in ranks, as well as raw data, of needle pathologies and sulfur and/or
fluoride levels in different-aged foliage collected over the last three years
from both "pristine" and polluted sites (S-3 and SE-4 vs GB-1 and BNW-3).
Data from past field studies carried out by Katz and McCallum (1939)
and McGovern and Balsillie (1973) were utilized to test one of these hypo-
theses. Since none of the investigating teams presented any quantification
of needle pathologies, the only hypothesis which could be tested was that
sulfur levels in older needles being retained on internodes in areas of
chronic air pollution would be less than levels in needles from the same year
which were prematurely cast from internodes. Utilizing sulfur levels found
200
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CHRONIC
DAMAGE
ACUTE
DAMAGE
o 50
PERCENTOF/
% OF NEEDLE
NECROTIC
' %-5O%
NEEDLE
540
NECROTIC
OTHER PATHOLOGIES
/ NECROSIS
TIP NECROSIS
TIME OF EXPOSURE
Figure 5.64. Occurrence rates of low level chronic air pollution symptoms.
-------
in three years of pine foliage collected at increasing distances from Trail,
B.C., for three consecutive years (1934-1936) by Katz, one can plot the
sulfur accumulation data for any given year by increasing distance (Figure
5.65), or one can utilize the sulfur accumulation levels in 1934 needles^from
1934 to 1936 and plot this data on time of exposure (Figure 5.66). In Figure
5.65, foliage at the six-mile collection site was cast somewhere between the
17th and 29th month collecting periods. Only two years of sulfur data is
plotted, and no major trend in sulfur accumulation in the different-aged
needles is apparent. However, when sulfur levels in 1934 foliage are plotted
over the three-year study period (Figure 5.66), the trend indicates a reduc-
tion of sulfur in 1934 needles between the 17th and 29th month of exposure.
This reduction in sulfur might be caused by translocation out of the older
leaves to the stems and roots, and studies on this possibility should be
undertaken. However, currently we suspect that this reduction in 29-month
exposed needles was due to premature needle casting of those needles with the
most elevated sulfur levels.
The McGovern and Balsillie (1973) studies included the collection and
analysis of only two years (current and one-year-old) of Jack pine foliage,
and thus it is difficult to demonstrate a trend in sulfur accumulation.
However, by selecting those sulfur data which demonstrate the largest change
(reduction) between the current and one-year-old foliage, it is possible to
not only plot the reduction^in sulfur in selected samples during a 12-month
period but ascertain the trends for trace metals also analyzed by McGovern
and Balsillie. In Figure 5.67 are the average sulfur levels of 6- and 18-
month-old (± 4 months) Jack pine foliage collected during 1971 and 1972
from six collection sites at varying distances and directions from Sudbury,
Ontario. This figure also includes the levels of six metals found in the
two different-aged foliage during the collecting periods. Both nickel and
zinc are generally lower in older foliage while arsenic, copper, and iron
increase over these 12-month periods. If the damaged needles being
prematurely cast in chronically-polluted areas are those with the most
elevated levels of sulfur, and the needles retained on that year's internodes
therefore show lower sulfur levels, this hypothesis could be utilized and
tested for toxic trace metals in evergreen conifer species, assuming the
investigator collects the same year's foliage for more than two consecutive
years.
Comparison of sulfur and fluoride levels in different-aged foliage from
the Colstrip sites to levels in similar-aged foliage from the polluted GB-1
Billings site adequately demonstrates that the Colstrip sites are not being
subjected to the kind of ambient air concentrations as the latter. The lowest
levels of ambient S02 and HF which can cause measurable impact on ponderosa
pine and other susceptible conifer or understory species has been the subject
of many studies because of the need to establish protective ambient air
standards for these two gases. It is not our intention at this time to
suggest "safe levels" for these two gases in the ambient air. However, .the
data we have accumulated on fluoride and sulfur levels in pine foliage and
the growth/health/damage characteristics of pine foliage collected from both
pristine and chronically-polluted areas of southeastern Montana strongly
suggest that short-term controlled fumigation studies or a single season
field study are totally inadequate to quantify impacts of these two gases.
202
-------
5000-
MORRIS KATZS TRAIL B.C. STUDY, 1939
6 MILES, 1935 COLLECTION
17 MILES, 1935 COL.
or
ID
ID
CO
4000
£3000
CL
2000
933
-1935
5 MONTHS
FOLIAGE
„/-- 6 MILES, 1936 COLLECTION
PONDEROSA PINE
BY DISTANCE FROM TRAIL
1934^- 17 MILES, 1936 COL
27 MILES, 1935 COL.
47 MILES, 1935 COL
27 MILES,1936 COL.
47 MILES, 1936 COL.
29 MONTHS
FOLIAGE
17 MONTHS
FOLIAGE
Figure 5.65. Sulfur levels in three years of ponderosa pine foliage
collected at increasing distances from Trail, B.C.
6000i
5000
en
ID
4000
ID
CO
3000
Q_
Q_
2000-
1000^
DISTANCE FROM
TRAIL
11 MILES
17 MILES
21 MILES
15 MILES
33 Ml.
52 Ml.
-19 Ml.
27 Ml.
5 MONTHS
FOLIAGE
17 MONTHS
FOLIAGE
29 MONTHS
FOLIAGE
Figure '5.66. Sulfur levels in 1934 needles by foliage age and
distance from Trail, B.C.
203
-------
CO
O
SUDBURY STUDY, McGOVERN 8 BALSILLIE 1973
BLIND RIVER 100 MILES WEST
KUKAGAMI LAKE 26 Ml NE
GRASSY L. 40 Ml NE
TIMAGAMI 50 Ml NE
MORGAN 15 Ml NW
PPM
128
CALLUM 18 Ml EAST 64
1700
a.
_j
CO
Q.
Q.
1500
I30O
1000
32
16
8
6 -MONTHS-18
CO.
AS.
6 - MONTHS - 18 6 - MONTHS - 18
1970-COLLECTION-1971
Figure 5.67. Sulfur levels in Jack pine foliage collected around Sudbury, Ontario
-------
For instance, Linzon (1971) used the data from a field study on vege-
tation damaged by emissions from two aluminum plants to conclude that 35 ppm
in foliage represented an injury threshold. After reviewing the literature,
McCune (1969) concluded that no foliar injury would occur at concentrations
of 0.8 ppb HF in the ambient air. All of these suggestions or conclusions
may be suspect after one notes that Sidhu (1977), after studying fluoride-
damaged coniferous and understory species around a phosphate plant, concluded
that ambient fluoride concentrations of 0.20 to 0.25 ppb should not be
exceeded more than 40% of the time. In a long-term study, Facteau and
Mellenthin (1976) found adverse effects to cherry orchard species in The
Dalles, Oregon, area where the fluoride levels were usually less than 0.30 ppb.
Past field studies, as well as controlled fumigation chamber studies on
S02 impacts on vegetation, also have led researchers and personnel of state
and federal regulatory agencies to suggest a variety of ambient air standards
to protect vegetation from 862 damage. For instance, Katz and McCallum
(1952) concluded from their fumigation and field studies in a large area
around Trail, B.C., "that vegetation will not suffer from sulfur dioxide if
ground concentrations are maintained at a low level, if concentrations higher
than 0.3 to 0.5 ppm do not occur, and if the duration of concentrations at
the 0.3 ppm level is short in any single gas visitation." Dreisinger (1965)
concluded that if the necessary environmental factors are optimum, plant
injury thresholds for ambient S02 are 0.95 ppm for one hour, 0.55 ppm for two
hours, 0.35 ppm for four hours, and 0.25 ppm for eight hours.
EPA rescinded its 24-hour secondary 802 ambient air standard of 0.10 ppm,
as well as the annual 862 standard of 0.02 ppm, but maintained its three-hour
standard of a maximum of 0.50 ppm, not to be exceeded once per year. These
actions generally reflect the suggestions and conclusions of researchers such
as Katz and McCallum (1952) and Dreisinger (1965). However, the results of
our current study suggest that chronic 862 and HF damage to pine species
occurs at substantially lower levels than suggested by most air pollution
investigators. Before this study, most of the field research studies on air
pollution were initiated after the pollution damage commenced. For instance,
those of Katz and McCallum (1939) in Trail, B.C., where he and his co-workers
conducted extensive field studies from 1930 to 1937 utilizing conifer species
as a bioindicator of air pollution impacts, and those of Linzon (1958),
Dreisinger and McGovern (1970, 1971), McGovern and Dreisinger (1970), and
McGovern and Balsillie (1974) who carried out extended studies from 1950
until the present in the severely air pollution-impacted area of Sudbury,
Ontario. There is little evidence in any of the above publications that the
authors could and actually did differentiate between conifers impacted by air
pollution and normal healthy growth of coniferous forests.
Another major reason we hypothesize that chronic air pollution
damage to pine species occurs at low ambient levels of phytotoxic gases is
that chronic air pollution-caused symptoms on pine foliage can mimic those
occurring on pine foliage in pristine environments. Conifers in a pristine,
healthy forest have foliage damaged by abiotic and biotic causal agents which
slowly increase with the advent of low chronic air pollution. It is therefore
difficult for an investigator using the typical macroscopic foliar symptoms
(tip burn and mottle) to measure this subtle increase without first
205
-------
quantifying the "normal" levels of damage within a pristine forest. An
investigator will also have difficulty separating the characteristics of a
chronically-air polluted area from those of a normal, pristine area by deter-
mining "baseline concentrations" of sulfur and/or fluoride in foliage
collected 50 to 100 miles from an acutely damaged area such as Sudbury,
Ontario, or Trail, B.C. This, we believe, is especially true in these two
areas, because the acute damage to the forest ecosystems occurred many years
before any extensive investigation was initiated.
REFERENCES
Carlson, C.E. 1974. Sulfur Damage to Douglas-Fir Near a Pulp and Paper Mill
in Western Montana. Report No. 74-13. USDA Forest Service, Division of
State and Private Forestry, Missoula, Montana. 41 pp.
. 1978. Fluoride Induced Impact on a Coniferous Forest Near the
Anaconda Aluminum Plant in Northwestern Montana. Ph.D. Thesis,
University of Montana, Missoula, Montana. 165 pp.
, and J.E. Dewey. 1971. Environmental Pollution by Fluorides in
Flathead National Forest and Glacier National Park. USDA Forest Service,
Division of State and Private Forestry, Forest Insect and Disease Branch,
Missoula, Montana. 57 pp.
Cobb, F.W., Jr., D.L. Wood, R.W. Stark, and J.R. Parmeter, Jr. 1968. Photo-
chemical Oxidant Injury and Bark Beetle (Coleoptera: Scolytidae) Infes-
tation of Ponderosa Pine. IV. Theory on the Relationships Between
Oxidant Injury and Bark Beetle Infestation. Hilgardia, 39(6):141-152.
Compton, O.C., F.W. Adams, W.M. Mellenthin, S. Elliot, N. Chestnut, and D.W.
Bonney. 1968. Fluorine Levels in Crops of The Dalles Area, 1965-67:
Cherry, Peach, and Pine Trees and the Ambient Air. Special Report 261.
Agricultural Experiment Station, Oregon State University, Corvallis,
Oregon. 40 pp.
, and L.F. Remmert. 1960. Effects of Air-borne Fluorine on Injury
and Fluorine Content of Gladiolus Leaves. Proc. Am. Soc. Hort. Sci. ,
75:663-675.
, L.F. Remmert, and W.M. Mellenthin. 1960. Comparison of Fluorine
Levels in Crops Before and After Aluminum Factory Operations in The
Dalles Area. Miscellaneous Paper 95. Agricultural Experiment Station,
Oregon State College, Corvallis, Oregon. 27 pp.
Conover, W.J. 1971. Practical Nonparametric Statistics. John Wiley & Sons,
Inc., New York. 462 pp.
Crecelius, E.A., L.A. Rancitelli, and S. Garcia. 1978. Power Plant Emissions
and Air Quality. In: Potential for Gaseous and Heavy Metal Contami-
nation from Energy Extraction Processes in the Northern Great Plains and
the Consequent Uptake and Turnover in Range Ecosystems. ERDA Annual
Report, Activity RX-02-03. Ames Laboratory, Iowa State University, Ames,
Iowa. pp. 9-33.
206
-------
Dreisinger, B.R. 1965. Sulphur Dioxide Levels and the Effects of Gas on
Vegetation Near Sudbury, Ontario. Presented at the 58th Annual Meeting
of the Air Pollution Control Association, Toronto, Ontario.
, and P.C. McGovern. 1970. Sulphur Dioxide Levels and Resultant
Injury to Vegetation in the Sudbury Area During the 1969 Season.
Department of Energy and Resources Management, Sudbury, Ontario. 33 pp.
. 1971. Sulphur Dioxide Levels and Vegetation Injury in the Sudbury
Area During the 1970 Season. Department of Energy Resources and Manage-
ment, Sudbury, Ontario. 38 pp.
Evans, L.S., and P.R. Miller. 1972. Ozone Damage to Ponderosa Pine: A
Histological and Histochemical Appraisal. Am. J. Bot., 59:297-304.
Facteau, T.J., and W.M. Mellenthin. 1976. Fluoride Investigations in The
Dalles Area 1968-1974. Technical Bulletin 132. Agricultural Experiment
Station, Oregon State University, Corvallis, Oregon. 56 pp.
Faller, von H., K. Herwig, and H. Kuhn. 1970. Assimulation of Sulphur
Dioxide (S^c^) from the Air. I. Influence on the Plant Yield. Plant
and Soil, 33:177-191.
Farrier, M.H. 1972. Report on Insects and Mites in Relation to the Long-
Short Needle Syndrome of Scotch Pines and Their Abundance in Christmas
Tree Plantations in Western Maryland and Northern West Virginia.
Unpublished report prepared for the Virginia Electric and Power Company
Richmond, Virginia. 57 pp.
Gordon, C.C. 1974. Environmental Effects of Fluoride: Glacier National
Park and Vicinity. EPA-908/1-74-001, U.S. Environmental Protection
Agency, Denver, Colorado. 150 pp.
. 1977. Accumulation of Fluoride in Vegetation Growing in the
Vicinity of the Martin Marietta Aluminum Plant, The Dalles, Oregon.
Unpublished report to the orchard growers of The Dalles, Oregon,
prepared at the Environmental Studies Laboratory, University of Montana,
Missoula, Montana. 10 pp.
, C.E. Carlson, and P.C. Tourangeau. 1976. A Cooperative Evaluation
of Potential Air Pollution Injury and Damage to Coniferous Habitats on
National Forest Lands Near Colstrip, Montana. Report No. 76-12. USDA
Forest Service, Northern Region, Missoula, Montana, and Environmental
Studies Laboratory, University of Montana, Missoula, Montana. 89 pp.
, P.C. Tourangeau, and P.M. Rice. 1978a. Investigation of the
Impact of Coal-Fired Power Plant Emissions upon the Disease/Health/
Growth Characteristics of Ponderosa Pine-Skunkbush Ecosystems and Grass-
land Ecosystems in Southeastern Montana. In: The Bioenvironmental
Impact of a Coal-Fired Power Plant, Third Interim Report, Colstrip,
Montana, December, 1977, E.M. Preston and R.A. Lewis, eds.
EPA-600/3-78-021, U.S. Environmental Protection Agency, Corvallis,
Oregon, pp. 65-139.
207
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1978b. Potential for Gaseous Contamination from Energy Extraction
Processes in the Northern Great Plains. In: Potential for Gaseous and
Heavy Metal Contamination from Energy Extraction Processes in the
Northern Great Plains and the Consequent Uptake and Turnover in Range
Ecosystems, ERDA Annual Report, Activity RX-02-03. Ames Laboratory,
Iowa State University, Ames, Iowa. pp. 53-137.
Jacobson, J.S., L.H. Weinstein, D.C. McCune, and A.E. Hitchcock. 1966. The
Accumulation of Fluorine by Plants. J. Air Poll. Contr. Assoc.,
16(8):412-417.
Katz, M. , and A.W. McCallum. 1939. Effects of Sulfur Dioxide on Vegetation.
NRC No. 815. National Research Council of Canada, Ottawa, Ontario.
447 pp.
1952. The Effects of Sulfur Dioxide on Conifers. In: Air
Pollution Proceedings, U.S. Technical Conference on Air Pollution,
Louis McCade, ed. New York, Toronto, London. pp. 84-96.
Keifer, H.H., and J.L. Saunders. 1972. Ti"Lsetacus campnodus, n. sp.
(Acarina: Eriophyidae), Attacking P-inus sylvestris. Ann. Entomol. Soc.
Am., 65(l):46-49.
Linzon, S.N. 1958. The Influence of Smelter Fumes on the Growth of White
Pine in the Sudbury Region. Ontario Department of Lands and Forests,
Ontario Department of Mines, Toronto, Ontario. 45 pp.
. 1971. Fluoride Effects on Vegetation in Ontario. In:
Proceedings of the Second International Clean Air Congress, H.M. Englund
and W.T. Berry, eds. Academic Press, New York. pp. 277-289.
McCune, D.C. 1969. On the Establishment of Air Quality Criteria, With
Reference to the Effects of Atmospheric Fluorine on Vegetation. Air
Quality Monograph 69-3. American Petroleum Institute, New York. 33 pp.
McGovern, P.C., and D. Balsillie. 1973. Sulphur Dioxide (1972)—Heavy Metal
(1971) Levels and Vegetative Effects in the Sudbury Area. Air Management
Branch, Ontario Ministry of the Environment, Sudbury, Ontario. 50 pp.
1974. Effects of Sulphur Dioxide and Heavy Metals on Vegetation
in the Sudbury Area (1973). Ontario Ministry of the Environment,
Sudbury, Ontario. 47 pp.
> and B.R. Dreisinger. 1970. Sulphur Dioxide Levels in the Wawa
Area During 1969- Department of Energy and Resources Management,
Sudbury, Ontario. 23 pp.
Miller, P.R., R.N. Kickert, O.C. Taylor, R.J. Arkley, F.W. Cobb, Jr., D.L.
Dahlsten, P.J. Gersper, R.F. Luck, J.R. McBride, J.R. Parmeter, Jr.,
J.M. Wenz, M. White, and W.W. Wilcox. 1977. Photochemical Oxidant and
Air Pollution Effects on a Mixed Conifer Forest Ecosystem—A Progress
Report. EPA-600/3-77-104, Environmental Protection Agency, Corvallis,
Oregon. 339 pp.
208
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Montana Department of Health and Environmental Sciences. 1974. Annual Air
Quality Data Summary for Montana for 1973, J. Gelhaus, ed. Air Quality
Bureau, Environmental Sciences Division, Helena, Montana.
1976. Air Quality Assessment of Colstrip, Montana, Prior to
Development of Coal-Fired Power Plants, J. Gelhaus, ed. Air Quality
Bureau, Environmental Sciences Division, Helena, Montana. 90 pp.
• 1977. Personal Communication. Air Quality Bureau, Environmental
Sciences Division, Helena, Montana.
• 1978. Annual Air Quality Data Summary for Montana for 1977, J.
Gelhaus, ed. Air Quality Bureau, Environmental Sciences Division,
Helena, Montana. 89 pp.
Northern Cheyenne Tribe. 1976. The Northern Cheyenne Air Quality Redesig-
nation Report and Request. Northern Cheyenne Tribe, Inc., Lame Deer,
Montana. 190 pp.
Sidhu, S.S. 1977. Fluoride Levels in Air, Vegetation, and Soil in the
Vicinity of a Phosphorus Plant. Presented at the 70th Annual Meeting
of the Air Pollution Control Association, Toronto, Ontario, June 20-24.
16 pp.
Sokal, R.R., and F.J. Rohlf. 1969- Biometry. W.H. Freeman & Company,
San Francisco, California. 776 pp.
Tourangeau, P.C., C.C. Gordon, and C.E. Carlson. 1977. Fluoride Emissions
of Coal-Fired Power Plants and Their Impact Upon Plant and Animal
Species. Fluoride, 10(2):47-62.
Treshow, M., F.K. Anderson, and F. Horner. 1967. Responses of Douglas-Fir
to Elevated Atmospheric Fluorides. For. Sci., 13(2):114-120.
Weber, D., and C. Olson. 1978. Preliminary Data on Colstrip Stack Plume
Intercepts Measured at Hay Coulee, 8-24-77 to 1-12-78. Presented at the
EPA Colstrip Coal-Fired Power Plant Project Workshop, Corvallis, Oregon,
January 17-19.
Wood, F.A., and S.P. Pennypacker. 1975. Evaluation of the Effects of Air
Pollution on Vegetation in the Mt. Storm, West Virginia-Oakland,
Maryland area. Presented at the 68th Annual Meeting of the Air
Pollution Control Association, Boston, Massachusetts, June 15-20.
209
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APPENDIX 5.1
PROCEDURE FOR THE DETERMINATION OF AVERAGE RANKS
Appendix Figure 5.1 is a reproduction of Figure 4.7 from the Third
Interim Report, which shows the mean values and 95% confidence intervals for
percent basal necrosis in 1972, 1973, and 1974 foliage, upper and lower crown
positions, from plots E-l and SE-2 (now called sites) collected in 1975. This
figure was prepared after the data were coded to the arcsin for percentages.
Appendix Figure 5.2 is a histogram of 120 observations used in the
preparation of Appendix Figure 5.1. The data were not coded to the arcsin
for percentages before Appendix Figure 5.2 was prepared. The arcsin transfor-
mation would not make these data more Gaussian because of the large number of
zeros. The number of variates in the class intervals in this figure are
shown below in Appendix Table 5.1.
APPENDIX TABLE 5.1.
NUMBER OF VARIATES FOR CLASS INTERVALS
FOR APPENDIX FIGURE 5.2
Class Interval
Number of Variates
0
2
4
6
8
10
12
14
18
32
71
24
7
7
2
3
1
2
2
1
Appendix Figure 5.3 shows the average ranks for percent basal necrosis
in the 1972, 1973, and 1974 years of foliage, upper and lower crown positions,
for sites E-l and SE-2, 1975 collection. While Appendix Figure 5.1 shows the
mean values and 95% confidence intervals for these same data after arcsin
coding, Appendix Figure 5.3 shows these data after ranking of the uncoded
variates.
The procedure for the determination of the average ranks as shown in
Appendix Figure 5.3 involves ordering all of the 120 variates from lowest
(XT, X-
X
120
). The variates are then ranked from
value to highest
1 to n (Rj, R2, R3 . . . R^. The ranked data are then segregated into the
original samples and the average rank computed for each sample by
(NX
n
Appendix Table 5.2 shows the variates, their ranks, and the average rank
for the data shown in Appendix Figure 5.3.
210
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1974
1973
197?
•1
1
1
1 —
1 UPPER CROWN
1
• 1
1974
1973
1972
PLOT
E-l
LOWER CROWN
UPPER CROWN
PLOT
SE-2
LOWER CROWN
i
10
I
15
20
25
PERCENT BASAL NECROSIS
Appendix Figure 5.1
Mean values and 95% confidence intervals for
percent basal necrosis in the upper and lower
crowns of 1972, 1973, and 1974 foliage collected
at plots (sites) E-l and SE-2 in 1975.
211
-------
Appendix Figure 5.2.
10 20 30 40
PERCENT BASAL NECROSIS
50
Histogram of 120 variates used to compute mean values
and 95% confidence intervals for percent basal necrosis
in 1972-74 foliage collected at E-l and SE-2 in 1975.
(T
UJ
O
o:
UJ
UJ
UJ
Q_
100
90
80
70
60
50-
40-
30
LOWER CROWN
UPPER CROWN
1974
1973
YEAR OF FOLIAGE ORIGIN
1972
Appendix Figure 5.3
Average ranks for percent basal necrosis in 1972-74
foliage collected at sites E-l and SE-2 in 1975.
212
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APPENDIX TABLE 5.2.
VARIATES FOR PERCENT BASAL NECROSIS AND THEIR RANKS
IN UPPER AND LOWER CROWN FOLIAGE FROM SITES E-l AND
SE-2, 1975 COLLECTION (1972-74 YEARS OF FOLIAGE)
Percent
Basal Necrosis Rank
Site E-1/Upper Crown/ 1972 Foliage
0 36.0
1 77.5
1 77.5
4 100.5
5 105.0 Average Rank
8 111.0
9 112.0 97.4
11 115.0
18 118.0
31 120.0
Site E-1/Upper Crown/ 1973 Foliage
0 36.0
0 36.0
0 36.0
1 77.5
2 89-5 Average Rank
2 89.5
2 89.5 78.0
5 105.0
5 105.0
14 116.5
Site E-1/Upper Crown/ 1974 Foliage
0 36.0
0 36.0
0 36.0
0 36.0
0 36.0 Average Rank
0 36.0
0 36.0 42.9
0 36.0
0 36.0
5 105.0
Percent
Basal Necrosis Rank
Site E-1/Lower Crown/ 1972 Foliage
0 36.0
1 77.5
2 89.5
3 97.0
4 100.5 Average Rank
4 100.5
6 108.5 95.7
9 112.5
14 116.5
18 118.5
Site E-1/Lower Crown/ 1973 Foliage
0 36.0
0 36.0
0 36.0
1 77.5
1 77.5 Average Rank
1 77.5
2 89.5 72.5
2 89.5
3 97.0
6 108.5
Site E-1/Lower Crown/ 1974 Foliage
0 36.0
0 36.0
0 36.0
0 36.0
0 36.0 Average Rank
0 36.0
0 36.0 44.3
0 36.0
1 77.5
1 77.5
(continued)
213
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APPENDIX TABLE 5.2
(continued)
VARIATES FOR PERCENT BASAL NECROSIS AND THEIR RANKS
IN UPPER AND LOWER CROWN FOLIAGE FROM SITES E-l AND
SE-2, 1975 COLLECTION (1972-74 YEARS OF FOLIAGE)
Percent
Basal Necrosis Rank
Site SE-2/Upper Crown/1972 Foliage
0 36.0
0 36.0
0 36.0
0 36.0
0 36.0 Average Rank
0 36.0
0 36.0 48.6
0 36.0
3 97.0
4 100.5
Site SE-2/Upper Crown/1973 Foliage
0 36.0
0 36.0
0 36.0
0 36.0
0 36.0 Average Rank
0 36.0
0 36.0 50.5
1 77.5
2 89.5
2 89.5
Site SE-2/Upper Crown/ 1974 Foliage
0 36.0
0 36.0
0 36.0
0 36.0
0 36.0 Average Rank
0 36.0
0 36.0 36.0
0 36.0
0 36.0
0 36.0
Percent
Basal Necrosis Rank
Site SE-2/Lower Crown/1972 Foliage
0 36.0
0 36.0
0 36.0
0 36.0
0 36.0 Average Rank
0 36.0
0 36.0 56.0
2 89.5
5 105.0
10 114.0
Site SE-2/Lower Crown/ 1973 Foliage
0 36.0
0 36.0
0 36.0
0 36.0
0 36.0 Average Rank
0 36.0
1 77.5 58.3
2 89.5
2 89.5
7 110.0
Site SE-2/Lower Crown/ 1974 Foliage
0 36.0
0 36.0
0 36.0
0 36.0
0 36.0 Average Rank
0 36.0
0 36.0 45.5
0 36.0
1 77.5
2 89.5
214
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SECTION 6
HONEYBEES AND OTHER INSECTS AS INDICATORS OF POLLUTION IMPACT
FROM THE COLSTRIP POWER PLANTS
J. J. Bromenshenk
ABSTRACT
In 1977, I continued post-operational assessments
of the distribution and magnitude of impacts from the
Colstrip power plants using terrestrial insects as
biological indicators of environmental quality. I con-
centrated on insect species and systems that from my
baseline and comparative studies appeared to be parti-
cularly sensitive or susceptible to pollution stress
and are important or "key" species, both ecologically
and economically, of ecosystems of southeastern Montana.
These included: (1) Pollinators (honeybees) which are
bioaccumulators or biocollectors of noxious substances
from their surroundings and which may be very suscep-
tible to poisoning or less obvious types of damage from
these materials; (2) insects on ponderosa pines, with
the emphasis on the scale insect Matsucocous secretus
Morrison, which resides under the sheath of pine needles,
often occurs proximal to areas of needle injury, and
belongs to a genus of insects reported to proliferate in
areas subjected to pollution stress, and (3) ground-
dwelling beetles, saprophagic and predatory insects,
whose abundance may be adversely affected by exposure to
long-term, low levels of sulfur oxides (see Section 18).
Honeybees proved to be efficient scavengers of
substances other than the fluorides which I originally
examined. Significant post-operational changes of
fluoride levels in bee tissues at sites near Colstrip
compared to controls and baseline levels continued to
be observed. Pilot studies indicated that bees also
accumulate arsenic and possibly zinc and radionuclides,
both naturally-occurring and anthropogenic forms. Bio-
assays for other trace elements are ongoing. Levels of
radionuclides should provide indices to the scavenging
efficacy of bees in terms of the particle size of pollu-
tants.
215
-------
Several lines of evidence supported the hypotheses
that insects can be used to detect and to elucidate
effects of environmental pollutants on terrestrial eco-
systems and that impacts on insect systems may induce
changes in fundamental ecosystem components and processes.
INTRODUCTION
During the 1977 growing season, I continued post-operational assessments
of the distribution and the magnitude of impacts from the Colstrip power
plants using terrestrial insects, primarily honeybees, as biological indi-
cators of environmental quality. In 1974, I hypothesized that methods could
be developed to predict the bioenvironmental impacts of coal-fired power
plants before damage occurred, based on the use of indicator species of
insects as early warning systems and as continuous monitors of atmospheric
pollutants. The Colstrip environmental assessment project was unique because
it provided both an opportunity to conduct baseline studies in a relatively
pristine area before the power plants began operation (in 1975 and 1976) and
to monitor post-impact changes in ecosystems of the Northern Great Plains.
Following my preliminary investigations (Bromenshenk, 1976, 1978a), I
directed my studies towards those insect species and systems which appeared
to be particularly sensitive or susceptible to pollution and which were
important ecologically and economically to the grasslands and timber stands
of southeastern Montana. These included: (1) Pollinators, especially honey-
bees, which gather noxious substances from their environment and which may be
susceptible to poisoning from these substances; (2) insects living on ponder-
osa pine, with emphasis on the scale insect Matsuoocous secTetus Morrison,
which resides under the sheath of pine needles, which often was observed at
sites with trees showing basal necrosis or burn of needles such as is typical
of acid rain injury, and which may increase in numbers in areas subjected to
pollution stress (based on studies of M. p-ini by Siewniak, 1971) , and
(3) ground-dwelling beetles, including important saprophagic and predacious
species, which appear to be affected by chronic, low-level concentrations of
S02 (covered in Section 18).
I continued to characterize and study insect-induced injuries to pine
foliage through histopathological examinations in order to delineate insect
pathologies from other biotic (fungi, viral, bacterial) and abiotic (frost,
drought, phytotoxins, acid rain) factors. Results for 1977 from these studies
and those concerning the Matsucoccus scale were, for the most part, incomplete
at the time of preparation of this report (May, 1978) and as such shall appear
in a later report. The bulk of the work on damage to pines by insect pests
is included in Section 5 of this report and concentrates on damage rather
than absolute insect population densities.
I shall concentrate here on the results of my honeybee studies during
1977 in the vicinity of Colstrip. A detailed account of the rationale for
the insect work, baseline data, methods, and the selection criteria for subse-
quent investigations appeared in the Third Interim Report (Bromenshenk, 1978a)
216
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Honeybees forage large areas (about 10,000 acres, according to Toshkov
et dl.3 1973), visit innumerable flowers, and travel tremendous distances. The
gathering of one pound of honey necessitates a total flight distance equiva-
lent to three orbits around the earth (Crane, 1975), and a honeybee colony
may gather as much as 200 pounds of honey during a single season. Honeybees
collect water for drinking, for dilution of food, and for evaporative cooling
of their hives. They forage for pollen, nectar, and honeydew to be used as
food, and they search for resin to seal and weather-proof their hives. Honey-
bees are behaviorally and morphologically adapted for the collection of these
materials, but they do not seem to be able to screen out other substances that
settle on the surfaces of plants, on the bees themselves, or which are adsorbed
on nectar and honeydew or absorbed in water. Since their respiratory passages
communicate directly to the air and lack protective linings such as mucous
membranes, bees inhale fine dusts, mists, or gases; although hairs surrounding
the spiracles probably filter out larger particles.
Honeybees are biological magnifiers of contaminants. Pollutants accumu-
late on or in their body tissues. In general, the levels of contaminants are
highest in the tissues of adult bees and are much lower in pollen, nectar.
floral parts, or water (Lillie, 1972; Bromenshenk, 1978a, 1978b; Bromenshenk
and Gordon, 1978).
Honeybees are social insects and can be managed. Therefore, they provide
in quantity materials for sampling (^.e-, bees, pollen, and nectar or honey).
By sampling vegetation and water in the vicinity of a bee colony and by using
physico-chemical measurements of air quality, one can obtain a very compre-
hensive profile of the environmental quality of the area and examine transpor-
tation routes of contaminants through honeybee systems. Presumably, honeybees
should serve as a model for the passage of these materials through other
pollination systems.
Although useful to man as a detector of pollutants, honeybees can be
harmed by an accumulation of toxic substances. The vigor of their colonies
may be affected and there may be other effects such as reductions in polli-
nation and honeybee production (Bromenshenk, 1978a, 1978b; Debackere, 1972;
Steche, 1975).
In 1974, I initiated studies of the concentrations of sulfur and fluoride
in honeybee systems. I chose honeybees based on their reported sensitivity
to industrial pollution and on their ecological importance as pollinators.
Beekeeping is a major agricultural industry in Montana, and 6,600 colonies
are located in the Colstrip vicinity. In the Third Interim Report, which
included results of my studies from 1974 through 1976, I concluded that honey-
bees are excellent detectors of fluoride accumulation and that they might
also be excellent detectors of other anthropogenic trace elements (Bromenshenk,
1978a). Baseline levels of fluoride in bees near Colstrip in 1974 and 1975
averaged about 8 ppm. The concentration of fluoride in bees from apiaries
downwind from the Colstrip power complex increased as much as twofold the
year after the two 350 MW power plants began operations. Fluoride in bees
from apiaries located upwind or at distances greater than 40 km from the
power plants did not increase. The increase of fluoride levels in or on the
bodies of bees did not correlate with the fluoride content of water supplies
217
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or pollen. In fact, pre- and post-operational levels of fluoride in water and
pollen were not significantly different.
Water supplies are a possible source of fluoride. Both before and after
operation of the Colstrip power plants, body tissue levels of fluorides in
bees from a beeyard near Rosebud, Montana, averaged as much as 200 ppm, a
level greater than that in bees we sampled near an aluminum reduction facility
in northwestern Montana. Artesian well water which was used by the bees at
this location had 20 to 50 times as much fluoride as the surface waters at
other apiaries in the Colstrip area. Fluoride levels in pollen and floral
parts collected at this site were not elevated over levels from other sites.
In my 1974 through 1976 studies, I was not able to detect significant
differences in sulfur in bee tissues either near Colstrip or in bees maintained
at the ZAPS S02 fumigation plots. Relatively high and variable baseline
sulfur levels (3,500 to 4,800 ppm) in bee tissues (probably present in protein
bonds) presumably masked any changes attributable to small incremental
increases of anthropogenic sulfurs in the surroundings (Hillmann, 1972) of the
honeybees.
MATERIALS AND METHODS
In 1977, bees were sampled from 16 apiaries (see Figure 6.1) during late
June and again in mid-September. Most hives could not be sampled until June
at the earliest because "migrant" colonies were brought in by the beekeeper
from California in early May and then stockpiled along Rosebud Creek about
35 km northeast of Colstrip until they could be distributed throughout the
region. September was the latest that most of the apiaries could be sampled
because most of the hives were taken back to California in October.
A few hives have been left by a Rosebud county beekeeper each winter at
12 sites near Colstrip. These were used for comparison to the migrant
colonies. Apiaries located south and east of the town of Ashland are owned
by two beekeepers who do not practice migratory beekeeping. These colonies
have never been taken out of the region and as such could be used for compar-
ison to the transported colonies and as monitors, for long distance transport
of pollutants. Approximately 300 bees (30 gm wet weight) were obtained at
the entrance to each hive by using a high velocity, battery-powered, acrylic
plastic vacuum apparatus, which drew the bees directly into plastic jars.
All samples were immediately frozen under dry ice and stored in plastic Whirl
Paks®at -10°C until they could be analyzed. Three to five grams of pollen
were obtained from each hive by removing pellets of pollen from honeycombs
with a plastic pick. Pollen was stored in plastic vials at room temperature
until analyzed. Honey was taken from each hive by drawing a plastic vial
across recently capped honeycombs and was stored in the same containers at
-10°C.
Ten individual hives were sampled for bees, pollen, and honey at each
apiary location. Also, a pooled sample of approximately 1,000 bees (100 gm
wet weight) was obtained by sampling bees from every hive at each location
(15 to 50 hives). Pooled samples provided both an average sample from each
location and sufficient quantities of material for tests, such as quality
218
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.—I
N
Figure 6.1. Colstrip study area; locations of apiary sampling sites.
219
-------
assurance tests and determinations for radionuclides, which require large
numbers of bees.
Since I did not find appreciable levels of insecticides in honeybees
during 1974 through 1976 (Bromenshenk, 1978a), I did not attempt to determine
pesticide levels in the 1977 samples. If an unusual mortality or a report of
heavy pesticide usage had occurred, then I would have performed these time-
consuming and relatively expensive analyses.
Fluoride and Sulfur Analyses
Before being tested for fluoride and sulfur levels, whole bees and pollen
were oven-dried and ground to pass a 40-mesh screen. An Orion specific ion
probe was used for fluoride determinations, while sulfur determinations were
performed using a Leco Induction Furnace. Previously, I reported difficulties
in analyzing honey because of its extremely hygroscopic properties. Tong
et at. (1975) detected sulfurs in honey, so I have continued to modify and
improve methods for analyzing honey. I believe that I can now dry honey
effectively by spraying or spreading it on a hot drum, a procedure used commer-
cially to make dried honey (White, 1975). Honey analyses should be completed
by autumn of 1978, but they were not complete as of - the date of this report.
Trace Metals
Because I have found that honeybees are good indicators of the presence
of fluoride pollutants, I decided to investigate the possibility of monitoring
other elements emitted by the Colstrip power plants. Literature reviews
(Bromenshenk, 1976; Debackere, 1972; Lillie, 1972) indicated that bees were
known to accumulate arsenic and lead and that these substances have caused
severe bee losses. In an on-going case brought, by George Grant Ballantyne,
Cloverdale Apiaries (Plaintiff vs. The Anaconda Company, District Court of
the Fifth Judicial District of the State of Montana, 1976), the plaintiff
alleges that his bees were killed by arsenic emitted by a copper smelter
72 km away. Data presented in the case clearly demonstrated that arsenic,
lead, and cadmium do accumulate in or on the tissues of bees and can be
detected by standard atomic absorption spectrophotometry procedures. The
concentrations of these substances appeared to be related to the location of
the bees with respect to an emission source.
I have not found any references to cadmium accumulation in bees or of
its toxicity to bees, but this element is reported to be toxic to living
organisms in all of its forms (Fulkerson and Goeller, 1973). As part of a
pilot study, I chose to examine the accumulation of cadmium, lead, arsenic,
and zinc because of data indicating the presence of these anthropogenic
contaminants in both the ambient air and vegetation in the area surrounding
Colstrip (Munshower and DePuit, 1976) and in stack emissions (Crecelius et at. ,
1978).
I am analyzing bees for these substances using standard atomic absorption
spectrophotometry procedures (Rowe, 1973) and a nitric-perchloric wet ash
digestion procedure (Behan and Kinraide, 1970) which I have tested and which
have proved to be successful. I intend to perform a series of standard
220
-------
addition calibrations of lead, cadmium, zinc, and arsenic to the bee matrix
to provide quality assurance tests of the analytical procedures. Since I have
tissue banks of frozen bees from 1974 to the present and since I can subsample
bees collected for fluoride and sulfur analyses, no additional sampling effort
is required for trace element determinations. This work is being carried out
with the assistance of Dr. F. F. Munshower (Montana State University), who has
the necessary equipment and qualified personnel to perform analyses for trace
amounts of cadmium and arsenic; I am performing the zinc and lead analyses.
Preliminary results will be presented in this report.
Radionuclides
In an attempt to determine the scavenging efficiency of honeybees for
airborne particulates, I sent to Battelle Pacific Northwest Laboratories
(BPNL) a sample of bees from an apiary located downwind from the Colstrip
power plants near the EPA Hay Coulee air quality monitoring site.
Naturally-occurring radionuclides, such as the isotope Beryllium7 which
is formed in the stratosphere, fall upon the earth at a relatively constant
and measurable rate. Other radioactive materials, such as fallout from the
Chinese weapons testing, also reach the surface of the earth and the rates of
fallout can be measured. By comparing the levels of these radioactive
materials in or on bee tissues to those on static surfaces, such as leaves
and some specifically-designed collection plates, one should be able to
determine if bees accumulate radionuclides above the levels of stationary
objects. This should provide an index to scavenging or accumulating effi-
ciency. In addition, because different radionuclides have different particle
sizes, one should be able to determine the size range of the particles the
bees are likely to pick up during their foraging flights by expressing the
levels of accumulation of these materials as ratios to some standard (in this
1 3 *7
case using Cesium ) and taking into account known or measurable particle size.
This procedure has been used by BPNL to determine deposition rates of marine
aerosols on the sea surface (Crecelius et at. , 1978).
I became interested in the particulate scavenging efficiency of honeybees
after computing the respiration rates of bees in flight using data published
by Wigglesworth (1972). It did not seem conceivable that bees could accumu-
late by respiration alone as much fluoride as observed in bees from industrial
areas. Whereas ingestion of fluoride-contaminated water or pollen appears to
be a possible route of transport of fluoride into bees, this did not seem to
be the route of passage of the increased fluoride seen in bees downwind from
the Colstrip power plants (Bromenshenk, 1978a). Therefore, at least in some
instances, particularly in Colstrip, I hypothesized that flying bees act as
miniature impactors, picking up pollutants not only from surfaces of flowers
or in water but also as they fly through contaminated atmospheres. At present,
a preliminary feasibility test has been completed and the results are encour-
aging (included in the results section of this report). The majority of the
radionuclide work will be performed during the 1978 field season.
221
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RESULTS
The year 1977 was unusual as regards beekeeping. Drought conditions
sharply reduced colony yield. According to the Montana Crop and Livestock
Reporting Service, the average yield per colony dropped to 57 pounds from
112 pounds in 1976 and 94 pounds in 1975. Montana usually ranks first or
second in the nation in yield per colony, but this year Montana dropped to
fifth and, in terms of total honey production, fell from sixth to twelfth.
At some locations, floral resources were so poor that colonies were in danger
of starvation. This occurred near Colstrip for the first time since the
initiation of our studies in 1974. Some apiary locations were not used at all
during the 1977 growing season, and bees were taken out of non-productive
(in terms of honey storage) apiaries by mid-summer. Thus, I did not have as
many sample locations to work with as in previous years, and some locations
sampled in June could not be sampled in September because the bees had been
moved to other sites. I sampled 15 sites both in June and in September, so
the sample grid was more or less complete. At some of the vacated sites, a
few hives or at least one hive remained, so I had some data. The drought was
an unusual occurrence, and I do not anticipate that it should be a problem
during the 1978 growing season, since the snowfall up to April was unusually
heavy. In spite of drought, the number of bee colonies in Montana has
increased by 6 percent (96,000 colonies were registered in 1977).
Fluoride
As I have mentioned, when compared to baseline or pre-operational levels,
fluoride concentrations in or on honeybees sampled in September of 1976
increased by as much as twofold at apiaries located as far as 15 km downwind
(based on prevailing wind patterns) from the Colstrip power plants. At that
time, one of the two power generators had been in operation 12 months; the
other only three months. Neither power plant had operated continuously, and
both had operated at approximately one-third capacity.
Baseline samples of soil, vegetation, and water indicated that naturally-
occurring fluoride from geochemical sources in these areas occurred at low
levels and did not display steep gradients of change. Thus, one would expect
the concentration of fluoride in bees' food and water sources to be rather
uniform.
Bees do not forage at random but display a preference for particular
flowers and foraging areas (Doull, 1971). If an area becomes subjected to
air pollution, one would then expect the concentrations of contaminants such
as fluoride to be related to factors such as topography and meteorology. In
other words, some areas would be more exposed to ambient pollution. Bees
foraging in areas of greater impact should come in contact with more contami-
nants than bees foraging cleaner areas. Bees can forage up to 8 km from their
hives, although they usually remain within 2 to 3 km (McGregor, 1976). Thus,
since bees from different hives may forage in different directions, bees from
one hive might bring back a relatively large quantity of pollutants while bees
from another might bring back relatively little.
Because of this preferential foraging, I hypothesized that the variance
of fluoride levels in bees in pollution-stressed areas should increase as the
mean increased. Since my ability to monitor this was limited by a small
222
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sample size at any given location, I increased the number of individual hives
being sampled from four in 1974, 1975, and 1976 to ten in 1977.
The number of beehives per apiary near Colstrip has varied from as few as
16 to as many as 50. Using Stein's two-stage sample test to determine the
number of observations necessary for a mean with a confidence interval of a
prescribed base, I evaluated the number of observations (n) based on 1975 and
1976 data and using the equation:
n =
t
tl
d2
where t is the tabulated t>Q5 value for the desired confidence interval and
degrees of freedom, d the half-width of the desired confidence interval, and
s2 the sample variance. According to my computations, increasing the number
of hives sampled from four to ten should decrease the confidence interval to
64 percent of the original width but would more than double collection time.
Increasing sample size to 15 (the maximum size likely to be found at all
sites) should decrease the confidence interval an additional 12 percent but
would triple the collection time. Collection time is an important consider-
ation because of the work necessary to obtain pollen, honey, bees, and water
from individual hives plus a pooled sample of bees from all of the hives in
each beeyard. One person usually could sample only two beeyards during an
11-hour day. Since I sample as many as 20 apiaries, ten hives per apiary
would take a minumum of ten days, and 15 hives would take 15 days. This
assumes good weather conditions. However, in autumn, rain and mud often
interfere with sampling, and it often takes several extra days to get to all
of the beeyards. I decided that increasing the sample size to ten was warran-
ted but that the time needed to sample 15 would be prohibitive.
The results of fluoride analysis of the September, 1977, samples are
compared to those for autumn of 1975 and 1976 in Figure 6.2. Increasing the
sample size from four to ten hives narrowed the confidence limits to within
the parameters estimated by Stein's two-way test. The data for fluoride in
honeybees and statistical analyses are presented in Appendix 6.1.
I intend to examine the data for fluorides in honeybees by a variety of
statistical techniques. However, at the time of preparation of this report,
I had not completed the analyses of fluoride in bees collected during June
and July. Also, preliminary tests suggested that the fluoride values for 1977
might not be normally distributed. Therefore, for this report, I have utilized
non-parametric tests in lieu of parametric tests such as the anova analyses of
variance which assumes normalcy of distributions (Sokal and Rohlf , 1969).
Fluoride concentrations in adult worker honeybees from individual hives
at given locations were considered to be the basic group for comparisons of
pre- and post-operational data. Using a Dec-20 computer, fluoride values for
honeybee workers were ranked. First, all variates from all groups were pooled.
The pooled variates were then sorted from lowest to highest (XQ, Xj_, X2 . . .
X ). Then, the pooled and sorted observations were ranked from low to high
(Ri , Ro, £3 • • • RH) into the original groups and average ranks computed as:
223
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I
SW-!
SW-2
SW-3
s-4
s-5
I SE-2
-J
U, NE-2
K
NE-3
NE-4
N-2
SE-I!
M977
• 1976
. 1975
0 4 8 12 16 20 24
x PPM FLUORIDE IN BEES
Figure 6.2.
Mean fluoride and 95% confidence intervals. 1975 and
1976 values are from four independent samples; 1977
values are from ten independent samples, except for
SE-11 and NE-2, which are each from three samples.
224
-------
n
This was done for the autumn sample collections for all sites and all years
combined (1975-77), for the 14 principal sites by year (1975 and 1977), and
for six sites downwind from Colstrip in terms of prevailing winds and within
20 km of Colstrip for each year (1975 and 1976).
The tests employed include the Kruskal-Wallis and the Wilcoxon two-sample
tests. The Kruskal-Wallis tests the null hypothesis that all the populations
have the same distribution of fluoride concentrations. The alternative hypo-
thesis is that some populations provide higher distribution values than others,
A significant value for the Kruskal-Wallis statistic causes us to reject the
former and to accept the latter. The results are presented in Table 6.1.
TABLE 6.1. KRUSKAL-WALLIS TEST OF FLUORIDE IN ADULT WORKER HONEYBEES
Site
Year
Kruskal-Wallis
Statistic, H
df
Critical
All Sites
(n = 48)
1975-77
151.50
47
63.98
P < 0.001
Principal
Sites
(n = 14)
S-4, S-5,
SE-2, NE-2,
NE-3, NE-4
(downwind from
Colstrip)
1975
1977
1975
1976
1977
21.78
54.74
2.52
12.14
18.77
13
13
5
5
5
22.36
22.36
11.07
11.07
11.07
n. s.
P £ 0.001
n.s.
P < 0.05
P £ 0.005
Based on these results, I accepted the null hypothesis for 1975. Pre-
operational fluoride distributions were the same at all locations. For 1976
and 1977 (post-operational), honeybees displayed a higher distribution of
fluoride concentrations than during 1975.
The Wilcoxon two-sample test was used to determine whether there was a
significant difference in the distributions of the levels of fluoride in or
on bees at a given location (apiary) from one year to the next. In other
words, I used it to test if the distribution of post-operational concentra-
tions of fluoride in 1977 was greater than those of the pre-operational concen-
trations or those of the 1976 post-concentrational period. If X designates
1975 values, Y 1976 values, Z 1977 values, and E expected, then the null hypo-
theses may be stated as follows:
225
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A HQ: E(Y) £ E(X)
(one-tailed test)
El: E(Y) > E(X)
B HQ: E(Z) >; E(Y)
(one-tailed test)
H!: E(Z) < E(Y)
These comparisons were made using the average rank data graphed in Figure 6.3
for those sites for which change in average rank appeared to have occurred.
The Wilcoxon test results are presented in Table 6.2.
TABLE 6.2. WILCOXON TWO-SAMPLE TEST
Site
NE-3
S-4
NE-2
NE-4
S-5
SW-2
Year
1975-77
1975-77
1976-77
1976-77
1976-77
1976-77
Wilcoxon
Statistic, T
35.
30.
39.
34.
39.
35.
00
00
00
00
00
00
Critical
Value
27
30
38
33
38
35
P
P £ 0.
P £ 0.
P £ 0.
P £ 0.
P £ 0.
P £ 0.
001
05
005
05
005
025
Based on the Wilcoxon two-sample test, I concluded that the distribution
of fluoride levels in honeybees at two sites near Colstrip, NE-3 and S-4,
was significantly greater for 1977 than for 1975. However, at four sites
near Colstrip, NE-2, NE-4, S-5, and SW-2, the distribution of fluoride in
honeybees was significantly smaller for 1977 than for 1976.
Based on the Kruskal-Wallis and Wilcoxon tests and the average rank data
depicted in Figure 6.3, the distribution of fluoride concentrations in honey-
bees in 1977 tended to be equal to or higher than that of baseline levels at
sites within 20 km of Colstrip and less than that of baseline levels at sites
more than 40 km away. As compared to 1976, the distribution of 1977 fluoride
values tended to be equal to or lower than those of the previous year. If
changes in fluorides in honeybees are caused by emissions from the Colstrip
power plants, then one would expect these changes to correspond to wind
patterns which would carry the plume to the areas at which higher values
occurred. Figure 6.4 summarizes 1976 and 1977 wind data for May through
September, i.e., the period the honeybees were present at sites within 20 km
of Colstrip. Wind data was supplied by the Montana State Department of Health
226
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ho
240-
210-
/
120- K\
,*l t
60- ||
30-
II ^™T™"""""""l^"™"!"™"™"11 i II I I i * '
-1976
-1977
Figure 6.3. Average rank of fluorides in honeybees from southeastern Montana used in the
application of the Kruskal-Wallis test.
-------
and was measured atop a 98.3 m tower astride a 65.6 m hill, 1,400 m north-
northeast of the Colstrip power plants.
1976
1977
Figure 6.4. Wind roses for Colstrip, Montana, May through September,
1977; measured at 164 m above the surrounding terrain,
1,400 m north-northeast of the power plants.
As I reported in the Third Interim Report to EPA (Bromenshenk, 1978a),
increases in mean fluorides in bees in 1976 compared to 1975 occurred at those
sites downwind and as far as 20 km from Colstrip. In 1977, the two apiaries
demonstrating significantly greater distributions of fluoride over those of
the 1975 baseline also occurred in quadrants receiving frequent winds.
It should be noted that although the most prevalent winds during the 1977
growing season came from the same quadrants as in 1976, the wind directions
were more variable in 1977 than in 1976.
The mean fluoride content of apiary water supplies was 0.34 ppm (S^- = .04)
in autumn of 1977. The fluoride content of these same water supplies was
0.46 ppm (S^- = .06) in autumn of 1976. The correlation coefficient for
fluoride in water for September of 1976 and 1977 was significant (r = .81,
df = 10, P <_ 0.01 by Snedecor's tabular values for the t test of r), indicating
a high degree of association. Mean fluoride in honeybees sampled in 1977 did
not correlate with fluoride in water (r = 0.14, df = 11, not significant by
Snedecor's tabular values). Thus, mean fluoride in honeybees did not appear
to be dependent on changes of fluoride levels in water.
j'race Metals
The results of our preliminary determinations of arsenic and zinc concen-
trations in honeybees are presented in Table 6.3. Too few arsenic analyses
were completed at the time of this report for any meaningful pre- and post-
operational comparisons. However, it is readily apparent that honeybees from
southeastern Montana have accumulated much less arsenic than bees from an
228
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TABLE 6.3. ARSENIC AND ZINC BIOASSAYS OF HONEYBEES FROM COLSTRIP, MONTANA
Date
Sample
Ppm
Average Bee
Weight (dry)
yg Arsenic/
Average Bee
ARSENIC (Bioassays by D. Neuman and F. Munshower, Montana State University)
Autumn
1974
Autumn
1976
Spring
1975
Spring
1976
Colstrip
S-5
S-l
N-l
N-l
S-l
S-5
S-l
S-5
Columbia Falls
003
004
Butte
005
0.81
0.69
0.38
0.62
0.40
0.19
0.67
0.47
0.57
2.03
3.06
ZINC (Bioassays by Environmental Studies
Autumn
1974
Spring
1977
Colstrip
NE-3
NE-4
SE-2
SW-1
S-5
E-l
NE-3
NE-4
NE-10
SE-6
SE-12
S-l
S-4
S-5
SW-1
SW-2
SW-3
N-l
87
68
80
82
93
112
97
101
99
97
95
90
137
157
136
126
123
124
0.029
0.030
0.034
0.030
0.038
0.043
0.026
0.028
0.028
0.026
0.035
Laboratory,
0.036
0.037
0.029
0.030
0.030
0.028
0.026
0.030
0.027
0.031
0.033
0.028
0.033
0.029
0.029
0.028
0.025
0.027
0.024
0.021
0.013
0.018
0.015
0.008
0.017
0.013
0.016
0.054
0.106
University of Montana)
yg Zinc/
Average Bee
3.13
2.52
2.34
2.46
2.79
3.14
2.52
3.03
2.67
3.01
3.15
2.52
4.52
4.55
3.94
3.53
3.08
3.35
229
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apiary near Butte or bees from one of the two apiaries sampled near Columbia
Falls. In the Butte area, a copper smelter is a known source of arsenic
pollutants. In the Columbia Falls area, the apiary at which over 2 ppm arsenic
occurred in the bees is located downwind from an aluminum reduction facility;
bees from this beeyard also had approximately 80 ppm fluoride, as compared to
about 25 ppm fluoride and 0.57 ppm arsenic at an apiary upwind from the
aluminum plant.
Figure 6.5 depicts average arsenic levels in the tissues of worker honey-
bees from different areas of Montana and includes data submitted by the
plaintiff in the case against the Anaconda Company mentioned earlier in this
report. Figure 6.5 demonstrates that honeybees from polluted areas may contain
more than 20 times as much arsenic as honeybees from Colstrip.
MEAN PPM ARSENIC JN ADULT WORKER HONEYBEES
0 2.5 .5.0 7.5 10.0 12.5
BUTTE
ANACONDA
COLUMBIA
FALLS
COLSTRIP
Figure 6.5. Arsenic in honeybees from clean and polluted areas of
Montana.
The levels of zinc in honeybees from sites near Colstrip in autumn of
1974 averaged 87 ppm, while zinc in bees in the spring of 1977 averaged 115
ppm. The higher level in the spring of 1977 could reflect a seasonal vari-
ability. I am currently analyzing samples obtained in September, 1977, to
determine if zinc concentrations remained at this level. Snowfall at some
locations near Rosebud Creek in 1976-77 had relatively high concentrations of
zinc (K. Beisinger, EPA-Duluth, personal communication). Rosebud Creek is
where most of the apiaries near Colstrip are located.
Radionuclides
The results of a preliminary test for radionuclides in bees obtained in
September of 1977 from site S-5 are presented in Table 6.4. Potassium40 is a
normal constituent of biological tissues; Be7 is formed in the stratosphere.
It was assumed that the other radionuclides were released by a Chinese atmos-
pheric weapons test conducted almost a year before the sample period.
Radionuclides can be detected in or on the bodies of honeybees, and
these materials do occur in different quantities. More extensive tests will
be conducted during the 1978 growing season. The results and data interpre-
tation should be available for inclusion in the Fifth Interim Report.
230
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TABLE 6.4. RADIONUCLIDES ON OR IN HONEYBEES, SITE S-5,
COLSTRIP, MONTANA, SEPTEMBER, 1977
Disintegrations/Minute/100 gm Enrichment Factor
Element (wet weight) (ratio to Cs137)
Be7
Ce144
Ce141
Cs137
K40
Nb95
Zr95
44.5
22.1
3.38
1.76
453.0
31.6
14.5
25.30
12.50
1.92
1.00
257-00
18.00
8.24
DISCUSSION
The purpose of all of the studies discussed in this report has been to
determine the bioenvironmental impacts of coal-fired power plants and to
generate methods to predict the bioenvironmental effects of air pollution
from these facilities before damage is sustained. The ultimate objective is
to provide planners and decision makers with a means of assessing and miti-
gating the ecological and related socio-economic impacts of siting coal energy
conversion plants in the Northern Great Plains. Because this project is
concerned with the impacts of emissions from the two 350 MW power plants at
Colstrip, Montana, a brief description of these emissions is needed before our
research can be discussed.
We began our investigations in August, 1974. The first Colstrip power
plant (Unit 1) went on-line in September, 1975. Unit 2 began operations in
June, 1976. Neither generating plant averaged better than 50 percent capacity,
except for brief periods, until March, 1977 (Section 5).
The effects of emissions from these power plants on air quality have
been monitored at a variety of sites by EPA-Corvallis, Battelle Pacific
Northwest Laboratories, State of Montana, National Oceanic and Atmospheric
Administration, and the Montana Power Company. Unfortunately, the available
air quality data provides only a very superficial profile of the plume
dispersion parameters (O'Toole et al. , 1978). However, the plume has been
detected several times a week at the monitoring station at Hay Coulee, approx-
imately 11 km southeast of Colstrip. This indicates that fumigation will
probably occur at other areas downwind of Colstrip. The Hay Coulee monitor
is situated between the apiaries at S-5 and SE-1, about 10 km and 15 km,
respectively, from Colstrip.
231
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Crecelius et al. (1978) reported that particles emitted by ^.he stack of
Unit 2 in March, 1977, were extremely small (80 percent less than 0.5 ym in
diameter) and were enriched in fluoride, arsenic, zinc, lead, mercury,
vanadium, copper, selenium, and antimony. These authors reported that because
69 percent (by weight) of the particles from the stack were less than 0.3 ym
in diameter, the flyash from the power plant could remain airborne for days
or weeks and be transported 100 to 1,000 km unless removed by rain, washout,
or agglomeration of the particles.
Crecelius' et al. data on concentrations of elements in stack flyash from
Unit 2 included 39 elements. The stack concentrations of those elements that
I examined in honeybees are as follows:
Element ppm ± SD
F 2,130 400
As 221 20
Zn 221 79
Pb 252 25
In addition, Crecelius et at. suspected sulfur dioxide and several elements
(Hg, F, As, Se) to be present in significant concentrations as a vapor in the
stack gases.
These researchers also sampled the plume using a DC-3 airplane during
February, 1977, and a helicopter during August, 1977. The results of the
samplers indicate that the plume could be followed 50 km downwind, that
particle size increased from primarily submicron (0.01 to 0.1 ym) near the
stack to one micron particles beyond 8 km, while particle numbers per cm^
decreased, and that plume width and thickness increased with distance from
the stack. Using the helicopter, the plume could be traced down to 10 m above
the ground, 5 km southeast of Colstrip. They concluded that their plume
sampling supported our data showing rising concentrations of sulfur and
fluoride in vegetation (Section 5). I believe that their data also supports
our observations of increasing fluoride levels in mice (Gordon et al. , 1978)
and in honeybees.
The 1976 and 1977 wind rose data, obtained from a 306 m tower on a hill
just north of the Colstrip power plants, indicates that winds frequently blow
towards the southeast and the northwest. Winds also come from the southeast,
but there were no apiaries located northwest of Colstrip because there were no
suitable forage locations for honeybees in that area.
Although I do not have air quality data for 1977 for any of the apiaries
northeast of Colstrip, I have frequently observed the plume from the power
plants descending to the ground and following drainage routes to the northeast
in a direction that presumably would carry it directly over the NE-2 and NE-4
apiaries. Thus, it would appear that those beeyafds at which I observed
232
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post-operational increases in mean fluoride content or higher distribution
functions of fluorides in bees were subjected to plume strikes. But I lack
data concerning air quality at these locations. Because of this, I intend to
place sulfation and formate plates near these apiaries during the 1978 growing
season.
Why did the distribution of fluoride levels in honeybees at four sites
near Colstrip decrease in September, 1977, from that of September, 1976? A
similar change was observed in the concentrations of fluorides in vegetation
at some of the sites near Colstrip. I have hypothesized several explanations
for this response:
(1) The winds were more variable in 1977 than in 1976 so that pollution
episodes may have been more frequent at downwind beeyards in 1976.
(2) Because of the "drought," honeybee production-was about one-half
that of either of the previous two years (G. Simpson, beekeeper,
personal communication). During periods of poor forage availability,
honeybees reduce flight activity and foraging, sending out mainly
scout bees (Doull, 1971), so that the amount of time during which
large numbers of bees might encounter fumigations by the plume would
be reduced. This would be particularly true if bees were picking up
contaminants primarily during flight rather than from material which
had settled on vegetation or in water.
(3) Both mean fluoride and distribution functions of fluoride levels in
bees from apiaries 40 to 80 km from Colstrip tended to be lower than
those of 1975 (baseline) levels. At one location, the levels were
significantly lower. This would support the hypothesis that
decreased flight and foraging could result in decreased gathering
of substances such as fluoride. An alternate explanation could be
that the 1977 data reflect some type of seasonal difference, but my
1975 and 1976 studies did not reveal any significant seasonal vari-
ability in fluorides in honeybees (Bromenshenk, 1978a). Whatever
the explanation, the mean fluoride and the distribution of fluoride
levels in honeybees sampled in September of 1977 tended to be some-
what lower than expected throughout the entire region.
(4) Although the Colstrip power plants operated relatively continuously
in 1977 and at a greater capacity than in 1976 (Montana Power
Company data, see Section 5), during mid-August through September,
they operated at a level only 16 percent greater than that of 1976,
based on coal consumption. Presumably, they emitted proportionally
greater amounts of fluorides in 1977. A worker bee lives about five
to six weeks during the peak activity periods of summer and early
fall. They do not begin to fly until approximately 20 days old, so
the time during which they would be likely to be in direct contact
with air pollutants would be two or three weeks. Thus, the opera-
tional history of the power plants during the month preceeding the
sample period rather than on an annual basis is probably more impor-
tant in relation to levels in honeybees, unless long-term accumu-
lation in food and water supplies is involved.
233
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(5) There is the possibility that less fluoride was emitted at Colstrip
in 1977 than in 1976 resulting from changes such as differences in
the fluoride content of the coal utilized. Also, it is possible
that some of the fluoride detected in the honeybees may have been
released by activities such as blasting in the coal strip mine at
Colstrip, although one would not expect that much, if any, fluoride
released in the mines would be carried over intervening ridges to
apiary locations several kilometers distant.
Preliminary data concerning trace elements clearly demonstrate that
honeybees accumulate a variety of elements in addition to fluoride and support
my belief that honeybees can be used as efficient detectors of a variety of
pollutants.
The radionuclide studies are based on techniques developed by Battelle
Pacific Northwest Laboratories to determine deposition rates of continental
aerosols on desert plants and marine aerosols on the sea surface. The initial
results indicate that the method should be applicable to the Colstrip plants,
assuming that the stack particulates act in a manner similar to ambient
aerosols (Crecelius et at. > 1978). This procedure should provide data on the
scavenging efficiency of honeybees as compared to deposition of aerosols on
vegetation and soil. Data for all three should facilitate determinations of
the rate of particulate deposition in regions downwind from Colstrip.
CONCLUSIONS
I have conducted two years of post-operational investigations into the
bioenvironmental impacts of the coal-fired power plants at Colstrip, using
indicator species of insects as early warning systems of damage and continuous
monitors of atmospheric pollutants. Whereas this section concentrates on the
use of honeybees as accumulators of anthropogenic contaminants and suscepti-
bility of pollinators to poisoning from these substances, I also have been
monitoring insect damage to ponderosa pines (Section 5) and the impacts of
exposures to long-term low-level concentrations of sulfur dioxide on ground-
dwelling, saprophagous and predatory beetles at the EPA ZAPS (Section 18).
Honeybees sampled in autumn of 1977 continued to demonstrate significant
post-operational changes in terms of the distribution of fluoride levels in
their body tissues at apiaries downwind and within 25 km of the power plants.
Mean fluoride levels in bees declined somewhat compared to 1976, and fluoride
levels returned to the 1975 baseline levels at some but not all locations.
At distant sites (40 to 80 km), the September, 1977, fluoride levels were as
low or lower than baseline levels. In one instance, the fluoride levels were
significantly lower. This suggests a regional depression of fluoride concen-
trations in honeybees which was offset near Colstrip by emissions from the
power plants. An unusually dry growing season almost halved production per
hive and presumably would have decreased flight and foraging activities by
honeybees. This may have decreased the amount of contact honeybees had with
fluoride contaminants in the area.
The prevalent winds at Colstrip from May through September of 1977
continued to blow towards those apiaries located southeast and northeast of
234
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the power plants. However, in 1977, the winds were more variable and blew
less frequently to the southeast and northeast than in 1976. Thus, there was
a good possibility that plume strikes occurred less often at the downwind
apiary sites in 1977.
Only one power plant was in operation throughout the 1976 growing season.
The other went on-line in mid-summer of that year. During the 1977 growing
season, both plants were on-line and had increased their output. Presumably,
pollutants being emitted also increased proportionally. However, based on
coal consumption data provided by the utility companies, total power plant
operation during the month prior to our September, 1977, sampling of apiaries
was only about 16 percent greater than in the same period in 1976.
Data drawn from a variety of ambient air quality studies in the Colstrip
region for 1977 provided evidence that the plume from the power plant frequently
hits the ground 5 to 12 km southeast of Colstrip. This supports my observa-
tions of increased fluoride distribution functions in honeybees in this area.
Presumably, the plume also may strike the ground at similar distances north-
east of the stacks, but there have been no attempts to monitor it there.
I am convinced that honeybees are excellent indicators for fluoride
impacts, and I have initiated studies of other trace elements in honeybees.
At present, I have not completed enough analyses for meaningful pre- and post-
operational evaluations of these contaminants at Colstrip. However, I have
found that arsenic levels in bees from apiaries near recognized sources such
as a copper smelter were as much as 20 times that in Colstrip bees. Zinc in
honeybees near Colstrip in the spring of 1977 was 1.3 times higher than levels
in the fall of 1975, although this could reflect seasonal variability- How-
ever, zinc is one of the elements emitted by the Colstrip power plants.
Several radionuclides have been detected in or on the tissues of worker
honeybees. Included were radionuclides associated with the Chinese atmospheric
weapons tests, almost a year prior to the sample period. The purpose of the
radionuclide studies, which have just begun, is to provide data concerning the
scavenging efficiency of honeybees as related to particle size of pollutants.
In view of the contaminants that honeybees accumulate and the degree of
magnification of these materials in bee systems compared to that in their
environs, the effects of these substances on the bees themselves and on
pollination systems should be more intensely studied. Thus far, the build-up
of toxic materials in bees near Colstrip has not reached that reported to be
injurious to bees. However, neither power plant has been in continuous or
full capacity operation, and two years of post-operational studies is a rela-
tively short period considering that contaminants may slowly accumulate in the
surrounding ecosystems. Thus, I still do not have enough information to
predict long-term consequences of the power plant emissions to honeybees. I
believe that it is important that such information (for prediction) be gathered
since the Northern Great Plains is an area of burgeoning coal development and
power plant construction. This becomes of utmost importance to beekeepers and
growers, not only of the Great Plains but elsewhere, because thousands of
colonies of honeybees are transported in autumn to the West Coast and the
Southwest where they are used to pollinate almond groves, orchards, and
235
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vegetable crops. Then, in the spring, they are returned to the Great Plains
where they produce one of the largest honey and wax crops in the nation.
REFERENCES
Behan, M.J., and T. Kinraide. 1970. Rapid Wet Ash Digestion of Coniferous
Foliage for Analysis of Potassium, Phosphorus, Calcium, and Magnesium.
Bulletin 39. Montana Forest and Conservation Experiment Station, School
of Forestry, University of Montana, Missoula, Montana. 7 pp.
Bromenshenk, J.J. 1976. Investigations of the Effects of Coal-Fired Power
Plant Emissions Upon Insects, Report of Progress. In: The Bioenviron-
mental Impact of a Coal-Fired Power Plant, Second Interim Report,
Colstrip, Montana, June, 1975, R.A. Lewis, N.R. Glass, and A.S. Lefohn,
eds. EPA-600/3-76-013, U.S. Environmental Protection Agency, Corvallis,
Oregon, pp. 112-129 and 286-312.
. 1978a. Investigations of the Impact of Coal-Fired Power Plant
Emissions Upon Insects. I. Entomological Studies in the Vicinity of
Colstrip, Montana. II. Entomological Studies at the Zonal Air Pollution
System. In: The Bioenvironmental Impact of a Coal-Fired Power Plant,
Third Interim Report, Colstrip, Montana, December, 1977, E.M. Preston
and R.A. Lewis, eds. EPA-600/3-78-021, U.S. Environmental Protection
Agency, Corvallis, Oregon, pp. 146-312 and 473-507.
. 1978b. Yet Another Job for Busy Bees. The Sciences, 18(6):12-15.
, and C.C. Gordon. 1978. Terrestrial Insects Sense Air Pollutants.
In: Proceedings of the Fourth Joint Conference on Sensing of Environ-
mental Pollutants, November 6-11, 1977, New Orleans, Louisiana. American
Chemical Society, Washington, D.C. pp. 66-70.
Crane, E., ed. 1975. Honey, A Comprehensive Survey. Crane, Russack, and
Company, Inc., New York. 608 pp.
Crecelius, E.A., L.A. Rancitelli, and S. Garcia. 1978. Power Plant Emissions
and Air Quality. In: Potential for Gaseous and Heavy Metal Contami-
nation from Energy Extraction Processes in the Northern Great Plains and
the Consequent Uptake and Turnover in Range Ecosystems. ERDA Annual
Report, Activity RX-02-03. Ames Laboratory, Iowa State University, Ames,
Iowa. pp. 9-33.
Debackere, M. 1972. Industriele Luchtvervuiling en Bijenteelt (Industrial
Pollution and Apiculture). Vlaams Imkersblad., 2(6):145-155.
Doull, K.M. 1971. An Analysis of Bee Behavior as it Relates to Pollination.
Am. Bee J., 111(7):266,273; (8):302-303; (9):340-341.
Fulkerson, W., and H.E. Goeller, eds. 1973. Cadmium, the Dissipated Element.
ORNL NSF-EP-21. Oak Ridge National Laboratory, Oak Ridge, Tennessee.
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Gordon, C.C., P.C. Tourangeau, and P.M. Rice. 1978. Potential for Gaseous
Contamination from Energy Extraction Processes in the Northern Great
Plains. In: Potential for Gaseous and Heavy Metal Contamination from
Energy Extraction Processes in the Northern Great Plains and the Conse-
quent Uptake and Turnover in Range Ecosystems. ERDA Annual Report,
Activity RX-02-03. Ames Laboratory, Iowa State University, Ames, Iowa.
pp. 53-137.
Hillmann, R.C. 1972. Biological Effects of Air Pollution on Insects,
Emphasizing the Reactions of the Honey Bee (Apis melUfera L.) to Sulfur
Dioxide. Ph.D. Thesis, The Pennsylvania State University, University
Park, Pennsylvania. 159 pp.
Lillie, R.J. 1972. Air Pollutants Affecting the Performance of Domestic
Animals, A Literature Review. Agriculture Handbook No. 380. USDA
Agricultural Research Service, Washington, D.C. 109 pp.
McGregor, S.E. 1976. Insect Pollination of Cultivated Crop Plants.
Agriculture Handbook No. 496. USDA Agricultural Research Service,
Washington, D.C. 411 pp.
Munshower, F.F., and E.J. DePuit. 1976. The Effects of Stack Emissions on
the Range Resource in the Vicinity of Colstrip, Montana. Research
Report 98. Montana Agricultural Experiment Station, Montana State
University, Bozeman, Montana. Ill pp.
O'Toole, J.J., C.C. Gordon, L.A. Rancitelli, E.A. Crecelius, S. Garcia,
F.F. Munshower, E.J. DePuit, P.C. Tourangeau, and P.M. Rice. 1978.
Potential for Gaseous and Heavy Metal Contamination from Energy
Extraction Processes in the Northern Great Plains and the Consequent
Uptake and Turnover in Range Ecosystems. ERDA Annual Report, Activity
RX-02-03. Ames Laboratory, Iowa State University, Ames, Iowa. pp. 1-8.
Rowe, C.J. 1973. Food Analysis by Atomic Absorption Spectroscopy. Varian
Techtron Pty., Ltd., Palo Alto, California. 47 pp.
Siewniak, M. 1971. Uszkadzanie Sosny Pospolitej (Pinus sylvestris) Przez
Czerwca Korowinowca (Matsucoccus pini Green, 1925; Margarodidae,
Coccoidea). Sylwan, 115(12):35-41.
Sokal, R.R., and F.J. Rohlf. 1969. Biometry. The Principles and Practice
of Statistics in Biological Research. W.H. Freeman & Company,
San Francisco, California. 776 pp.
Steche, W. 1975. Industrial Development and Its Effects on Beekeeping.
Apiacata, 10(3):119-124.
Tong, S.C., R.A. Morse, C.A. Bache, and D.J. Lisk. 1975. Elemental Analysis
of Honey as an Indicator of Pollution. Arch. Environ. Health, 30:329-332
Toshkov, A.S., M.M. Shabanov, and N.I. Ibrishimov. 1973. Attempts to Use
Bees to Prove Impurities in the Environment. Comptes rendus de
1'Academie bulgare des Sciences, 27 (5):699-702.
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White, J.W., Jr. 1975. Composition of Honey and Physical Characteristics of
Honey. A Comprehensive Survey, E. Crane, ed. Crane, Russack, and
Company, Inc., New York. pp. 157-239.
Wigglesworth, V.B. 1972. The Principles of Insect Physiology. John Wiley
and Sons, Inc., New York. 827 pp.
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APPENDIX TABLE 6.1. MEAN FLUORIDE IN ADULT HONEYBEES (SEPTEMBER, 1977)
Site
NE-2
NE-3
NE-4
NE-IO*
SE-11
SE-6
SE-12
S-4
S-5
SE-2
SW-1
SW-2
SW-3
1
16.6
17.3
19.4
155.5
9.0
6.5
13.4
13.7
11.1
11.1
11.7
10.5
11.0
2
11.8
16.6
11.0
38.1
7.0
5.8
10.6
11.6
9.2
8.6
13.5
9.2
10.8
Hive Number/Ppm Fluoride
34567
8.7 8.6 7.9
15.2 14.8 13.2
10.4 10.1 10.1
54.1 47.2 15.3
5.8
5.8 5.4 4.7
7.5 7.2 6.5
11.1 10.4 10.2
8.8 8.0 7.9
7.4 7.2 7.2
11.7 11.1 10.7
8.2 7.7 7.2
10.5 10.3 9.2
7.6
11.0
8.4
8.2
—
4.6
6.4
9.0
7.7
7.2
10.5
7.0
8.8
5.6
10.9
6.2
5.3
—
4.5
6.1
8.4
7.0
6.6
8.3
7.0
8.3
*Each value represents a combined sample from 15-30 hives
IHives 4-10 located farther from water source containing
SINGLE
HIVE,
Site Ppm
SUBSAMPLED: N-2 3.7
SE-1 8.4
Fluoride
3.7
6.9
3.0
6.5
8
5.6
10.3
6.2
4.0
—
3.8
5.7
7.7
6.6
6.4
8.2
6.4
7.9
*
fluoride
x~
3.5
7.3
9 10
5.4 4.8
9.2
5.5 4.8
3.8 3.6
— —
3.5 3.2
5.7 5.2
7.3
6.4 6.3
6.3 5.9
6.9 6.6
5.6 5.0
7.5 6.6
*
SD
0.4
1.0
X
8.3
13.2
9.2
33.5
7.3
4.8
7.4
9.9
7.9
7.4
9.9
7.4
9.1
SE
0.23
0.58
SD
3.6
3.0
4.2
47.1
1.6
1.1
2.6
2.1
1.5
1.5
2.3
1.6
1.5
Combined
SE Sample*
1.14
0.98
1.34
14.88
0.93
0.34
0.82
0.68
0.47
0.48
0.72
0.52
0.48
12.0
13.8
13.2
—
7.8
6.3
6.7
10.8
8.0
7.9
7.7
7.0
8.1
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SECTION 7
TRENDS IN BIRD POPULATIONS IN THE VICINITY OF COLSTRIP
E. M. Preston and S. K, Thompson
ABSTRACT
Trends in bird populations have been monitored for
three consecutive years in the vicinity of two 350 mega-
watt coal-fired power plants in Colstrip, MT. A census
route patterned after the North American breeding Bird
Survey was laid out along an anticipated gradient of
pollution impact. Census data collected prior to opera-
tion of the power plants (1975) is compared with those
collected after operation began (1976-77). Eighty-one
species have been observed thus far. On the average,
Western Meadowlarks accounted for 38% of the birds ob-
served. Twenty-one additional species each contributed
one percent or more to total abundance. Since 1975, the
bird community has become increasingly dominated by
Meadowlarks while the relative abundances of raptors,
blackbirds and Lark Buntings have decreased. Species
evenness (J?) has decreased steadily since 1975 while
the average number of species observed per site has
increased. Much of the local variation in bird species
diversity is strongly correlated with habitat factors.
The presence of human structures, the proportion of area
cultivated, the proportion of pine-juniper forest, the
presence of riparian habitat and the distance from
Colstrip were positively associated with species diver-
sity. The presence of strip mining and the proportion
of native grass coverage were negatively correlated with
diversity. The ranges of bird species tend to be re-
stricted by environmental factors within the study area.
Consequently, the spatial distributions of species along
the census route are often bimodal with one mode over
zero counts and the other mode representing the most
common count of the species. The negative binomial cannot
adequately describe such a bimodal situation. However,
it can be modified to allow for added zeros. The spatial
distributions of Western Meadowlarks and Lark Buntings
can be usefully described by the negative binomial with
added zeros. The three parameters of the distribution
240
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are intuitively interpretable and may ultimately
prove to be useful indicators of changes in patterns
of space utilization.
INTRODUCTION
With the projected expansion of utilization of coal from the West, the
Northern Great Plains are likely to be exposed to air pollution from coal-
fired power plants. Chronic exposure to air pollution may cause changes in
the native grassland ecosystem structure and dynamics. Birds are the most
visible vertebrates of the grasslands from spring to late fall. They are
potentially important indicator species because they are long-lived secondary
consumers. They are unlikely to show acute effects of pollutants but may
suddenly and belatedly exhibit severe damage when pollutants have accumulated
to toxic levels in organ systems (Stickel, 1975). Their long lives enhance
potential for accumulation of pollutants. We summarize here trends observed in
bird community structure in the vicinity of two 350 megawatt coal-fired power
plants in Colstrip, Montana.
MATERIALS AND METHODS
Census data were used to infer species dispersion and relative abundance
patterns. The census was patterned after the widely employed North American
Breeding Bird Survey (Robbins and Van Velzen, 1970). The observer starts one
half hour before local sunrise and makes 60 three-minute stops at 0.8 km
intervals along a predetermined route (see Lewis et at. 1976). At each stop,
the number of birds of each species seen in a 400 m radius and heard, regard-
less of distance, is recorded. Since bird species have differential detect-
ability, the census data provide no information on absolute abundance (Emlen,
1971). However, it should be possible to detect changes in species relative
abundance patterns by comparing data obtained during a baseline period with
those obtained using the same census technique at other times.
The census route was selected to provide sampling stations at varying
distances from the Colstrip power plants along an anticipated gradient of
pollution impact. Stops ranged from 1.2 km to 18.2 km from the Colstrip power
plants. The stations cover a wide range of habitats including open grassland,
streams, rolling hills with ponderosa pine and juniper coverage, cliffs and
habitats affected by a wide range of human impacts including urban activities,
railroad right-of-way, farming, ranching, and mining.
The 1975 breeding season is considered the baseline period since the
power plants were not operational at that time. The route was censused on
nine dates between May 6 and September 11, 1975. Generating Unit 1 began
operation in September 1975 and Unit 2 in June 1976. The route was censused
21 times between April 21 and September 23, 1976, and 12 times between April
19, and September 9, 1977.
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We hope to be able to relate structural descriptive parameters, such as
species diversity, species richness, species evenness and degree of dispersion
to changes in functional relationships between species and their environments.
Species diversity was measured by the Shannon-Weaver function s
(HT =-Z P± Iog2 P±
n=l
(Shannon and Weaver, 1949). Species richness (S) was measured by the number of
species present, and evenness in species frequencies was measured by J'= HT/log2S
(Pielou, 1969, 1975). To inspect overall temporal trends in these parameters,
total Hf, total S and total J' were calculated from lumped census data for
all sites on each sampling date. Plots of H1 vs. number of sites included
indicated that H' stabilized after approximately 40 sites had been included.
Spatial and site specific trends were inspected by calculating total across
season H', S, and J' from lumped data from representative sampling dates for
each site. In between year comparisons care was taken to lump similar sample
numbers and dates in calculating total across season values.
Habitat types at the census sites were quantified from aerial photographs
taken from small aircraft 2500 feet above the ground. Native grassland,
pine-juniper forest, and grain agriculture are the dominant habitat types.
The percent area covered by these types within 400 m of census sites was
estimated to the nearest 20%. Riparian habitat, strip mining operations, and
human structures were classified as present or absent.
RESULTS AND DISCUSSION
The survey data provide information on spatial and temporal patterns in
the distribution and abundance of species. The data can be used to monitor
changes in dispersion and species composition associated with changes in the
environment.
Species Composition
Both qualitative and quantitive changes in species composition can occur.
Qualitative changes involve changes in species makeup resulting from the loss
of species, the colonization of new species, or both. Such changes usually
follow gradual quantitive changes in species relative abundance. They can be
detected by inspection of a list of species occurrences during successive
years. One year time intervals are appropriate because there are many seasonal
changes in species occurrence not associated with long term trends. Annual
species lists do not reflect most of these confounding changes. By studying
contrasts between the life history strategies of those species favored versus
those disfavored by pollution impact, insights into the wide ranging ecological
effects being manifested at the systems level may be achieved. If generalist
species tend to be replacing or increasing at the expense of specialists,
retrograde succession may be indicated. If a few specialist species with
similar adaptations seem to be favored over others, a directional shift in
environmental selective pressures is indicated. Inspection of unique adapta-
tions in the newly favored species may permit the new selective pressures to
be deduced.
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Table 7.1 summarizes the species composition observed during the breeding
seasons of 1975, 1976, and 1977 in the Colstrip vicinity. Eighty-one species
have been observed thus far. An average of 63.3 species were observed during
any one year. The bird community is numerically dominated by Meadowlarks
which on the average account for 37.5 percent of the birds observed. Twenty-
one additional species each contributed one percent or more to total abundance
and were detected all three years.
The relative abundances of several species showed clear trends over the
three year period. Western Meadowlarks increased dramatically between 1976
and 1977. The Eastern Kingbird, Barn Swallow, Yellow Warbler and American
Goldfinch also showed consistent increases. The dominant raptors (Red-Tailed
Hawk and Sparrow Hawk) have decreased consistently since 1975. Also, a pair
of Golden Eagles which nested near the census route in 1975 and 1976 were not
seen in 1977. Raptors are among the species most sensitive to habitat fragmen-
tation and their apparent numerical decline may be significant. Other species
showing consistent numerical decline were the Black-Capped Chickadee, Red-
Winged Blackbird, Brewer's Blackbird and Lark Bunting. At this point, the
significance of these trends cannot be fully evaluated.
Overall H' decreased sharply between 1976 and 1977. This decrease was
greater than typically is observed in annual fluctuations in bird communities
(Jarvinen and Vaisanen, 1976). Evenness (J1) has decreased consistently since
1975.
TABLE 7.1. AVIAN SPECIES OBSERVED ON THE ROADSIDE CENSUS IN THE COLSTRIP
VICINITY DURING 1975, 1976, AND 1977*
SPECIES
Common Name
Scientific Name
Proportional Abundance
1975
1976
1977
Canada Goose
Mallard
Blue Winged Teal
Turkey Vulture
Cooper's Hawk
Red-Tailed Hawk
Rough-Legged Hawk
Golden Eagle
Marsh Hawk
Prairie Falcon
Sparrow Hawk
Ruffed Grouse
Sharp-Tailed Grouse
Ring-Necked Pheasant
American Coot
Killdeer
Common Snipe
Upland Sandpiper
Brant a oanadens'is
Anas platyrhynchos
A. disooTS
Cathartes aura
Aoo'ip'iter cooperi-
Buteo jamaioensis
B. lag opus
Aquila ohrysaetos
Circus cyaneus
Faloo mexioanus
F. sparverius
Bonasa urnbellus
Pedloeoetes phaslanellus
Phasi-anus oolc'hlcus
Fulioa amerioana
Charadr-lus vooi-ferus
Capella gallinago
Bartrami-a long'ioauda
24
5
12
7
140
24
339
15
2
2
12
22
9
67
2
3
12
1
6
19
2
118
1
27
299
2
11
7
14
93
2
68
291
1
38
243
-------
Table 7.1 Continued.
SPECIES
Proportional Abundance
Common Name
Scientific Name
1975
1976
1977
Solitary Sandpiper
Northern Phalarope
Mourning Dove
Black-Billed Cuckoo
Great Horned Owl
Poor-Will
Common Nighthawk
Chimney Swift
Belted Kingfisher
Common Flicker
Red-Headed Woodpecker
Hairy Woodpecker
Eastern Kingbird
Western Kingbird
Cassin's Kingbird
Say's Phoebe
Western Wood Pee Wee
Horned Lark
Violet Green Swallow
Barn Swallow
Cliff Swallow
Black Billed Magpie
Common Raven
Common Crow
Pifion Jay
Black-Capped Chickadee
White-Breasted Nuthatch
House Wren
Winter Wren
Rock Wren
Gray Catbird
Brown Thrasher
Sage Thrasher
American Robin
Thrush
Mountain Bluebird
Cedar Waxwing
Loggerhead Shrike
Starling
Yellow Warbler
Ovenbird
Common Yellowthroat
Yellow-Breasted Chat
American Redstart
Tpinga solitaria 1
Lobipes lobatus 5
Zenaidura macroupa 787 775 802
Cocoyzus eTybh'Popt'ha'lmus 2 6
Bubo wirgin-ianus 1
Phalaenoptilus nuttall'ii 2 2 12
Chopdeiles minor 10 9 17
Chaetupa peligica 29 3
Megacepyle alcyon 2 1
Colaptes auratus 92 143 69
Melanerpes epythpooephalus 721
Dendpocopos villosus 1 48
Tyrannus tyrannus 123 155 223
T. veptioalis 131 87 127
T. voo-iferans 10 8
Sayornis say a 22 14 17
Contopus soTdi-dutus 30 9
ET&mophila alpestris 2 2
Tetchyc-ineta thalassina 20 61
Hirundo rustica 107 121 153
Petrochelidon pyrrhonota 228 681 320
Pica pica 17 16 37
Corvus co-pax 5
C. brachyphynchos 77 85 87
GyrmoThinus cyanocephala 249 162 45
Papus atp-Lcap-illus 114 70 16
Sitta capolinensis 2 1
Troglodytes aedon 5 2 45
T. troglodytes 7 1
Salpinetes obsoletus 1 22
Dumetella carolinensis 1 6
Toxostoma Tufum 10 13 8
Oreoscoptes montanus 3
TuPdus migratorius 196 176 185
517
Sialia cuTPucoides 39 15 14
Borribyci-lla cedropwn 5
Lanius ludoui-cianus 17 10 2
Stupnus vulgapis 19 39 43
Dendroi,ca petechia 56 131 204
Seiupus aupooapillus 2
Geothlypis trichas 10 1
loter-ia vipens 17 26 37
Setophaga rut-lcilla 5
244
-------
Table 7.1 Continued.
SPECIES
Proportional Abundance
Common Name
Scientific Name
1975
1976
1977
Western Meadowlark
Red-Winged Blackbird
Northern Oriole
Brewer ' s Blackbird
Common Crackle
Brown-Headed Cowbird
Black-Headed Grosbeak
Lazuli Bunting
American Goldfinch
Red Crossbill
Rufous-Sided Towhee
Lark Bunting
Savannah Sparrow
Vesper Sparrow
Lark Sparrow
Dark-Eyed Junco
Chipping Sparrow
Clay-Colored Sparrow
White-Crowned Sparrow
Stuvnelta negleota
A.ge1ai,us tr"ico1ov
Icterus galbula
Euphagus cyanocephalus
Qutscalus qu'lsoula
Molothvus ateT
Pheuct'Lous melanocep'halus
Passevina amoena
Spinus tristis
Loxia curvirostra
Pipilo erythpophthalmus
Calamospiza melanocory s
PasseToulus sandwichens-is
Pooecetes gram-ineus
Chondestes grammacus
Junco hyemalis
Spizella passeT-ina
S. pallida
ZonotTichia leuaophpys
HT
J'
S
N (x!0°)
// Censuses
N/census
3448
361
2
605
12
140
22
56
36
36
1165
157
479
465
31
5
5
3.77
.63
61
4130
9
458.9
3457
239
15
428
14
178
4
7
187
54
669
180
755
475
1
14
3.80
.62
66
16060
21
764.8
4339
119
5
359
7
103
2
173
22
91
382
59
324
578
104
72
3.65
.61
63
865
12
721.2
*This is not an exhaustive species list for the area. It contains only those
species observed by the census methods. Also, several rare, tentatively
identified species have been omitted.
Quantitative changes in species composition are often expressed by the
Shannon-Weaver function (HT). This is a weighted measure influenced by both
the total number of species present (.S) and the relative abundance of species.
Trends in H1, JT and S during the breeding seasons of 1975 through 1977
are shown in Figure 7.1. Diversity (H') rises rapidly in early spring with
the arrival of migrant species. It then plateaus with maximum values in early
to midsummer. A gradual decline follows through September. The seasonal
patterns were very similar for the three years censused.
Between year differences in across seasonal values of H' for individual
sites were greater than for the overall area values in Table 7.1. It has been
suggested that increased species diversity contributes positively to commumity
245
-------
1975
1976
1977
MAY
JUNE
JULY AUGUST SEPTEMBER
DATE
Figure 7.1. Seasonal trends in S J1, and H' in the Colsrip vicinity.
stability (Woodwell and Smith, 1969). Annual fluctuations of species relative
abundance patterns as reflected in H? are one indication of stability. One
might expect low diversity sites to show greater between year variability in
H1 than high diversity sites. This is apparent, in general, with the 60
sampling sites censused. Mean across season H' for the three years censused
was negatively correlated with it's standard deviation (r = -.36, P < 0.01).
Low diversity sites apparently have greater annual fluctuation in species
abundance patterns than high diversity sites. The mathematical nature of H'
could contribute to this result. The addition <3f rare species to a sample
with low H1 usually causes a greater change than the addition of the same rare
species to a sample initially yielding a high Hf value.
246
-------
Average across season HT and S for birds in the pine savannah southeast
of Colstrip are intermediate between typical values for grasslands and those
for shrublands (Table 7.2). This is expected since the sampling stations
range from open grassland to forest. Average JT is lower than would be pre-
dicted by the trends for H' and S. Variability in H1 and S, and Jf is very
similar to that found in other grassland and shrubland censuses (Tramer,
1969). Since the baseline year (1975), species richness has increased and
evenness has decreased. This supports the previous observation that the bird
community is becoming more highly dominated by abundant species even though
new, rare species are being recorded.
It is possible to account for much of the present site variation in bird
species diversity by variations in habitat. Multiple correlation analysis has
been used to determine the degree of association of HT with habitat factors.
For each of the sixty sampling sites, cumulative across season-H' has been
regressed against the proportion of grassland, proportion of pine-juniper
forest, proportion of agricultural land, presence or absence of riparian
habitat, presence or absence of strip mines, presence or absence of human
structures, and distance from Colstrip.
TABLE 7.2. CUMULATIVE ACROSS SEASON SPECIES' DIVERSITY, EVENNESS, AND RICHNESS
Colstrip 1975
Colstrip 1976
Colstrip 1977
Typical Grassland i
Typical Shrubland 1
Species Diversity5
(H')
2.47+0.16
2.73+0.09
2.56+0.18
1.93+0.24
3.14+0.16
Evenness* Species Richness*
(Jf) (S)
0.73+0.02
0.71+0.03
0.67+0.03
0.84+0.03
0.85+0.24
10.95+0.98
14.45+0.86
14.21+1.21
5.74+1.00
14.08+2.31
* Cumulative across season values averaged for 60 sampling sites + 2 standard
errors.
1 from Tramer (1969)
The results of the correlation analyses are shown in Table 7.3. The
multiple regression equations were statistically significant for all three
years (P < 0.005 in all cases) indicating that the habitat variables selected
were significantly associated with HT. Presence of human structures, the
proportion of pine-juniper coverage, the proportion of area cultivated, the
presence of riparian habitat, and distance from Colstrip were positively
associated with species diversities. The presence of strip mining and the
proportion of native grass coverage were negatively correlated with species
diversity.
Over the three year study period, the presence of human structures had
the highest positive correlation with diversity but the strength of this
relationship has steadily decreased. The correlation with the proportion of
247
-------
pine coverage has increased. In all three years, regressions of Hf against
presence of human structures and pine coverage yielded higher F values than
regressions against other possible combinations of variables. The habitat
modification associated with human structures (deciduous trees, watering
tanks, shrubs, etc.) are apparently favorable to enrichment of species diver-
sity in this environment. Presence of pine-juniper forest permits greater
habitat stratification than is present in grasslands and this may lead to
higher diversity. Presence of riparian habitat is also strongly correlated
with species diversity. It provides a qualitatively different habitat and may
be the major water source for most species.
One might expect environmental impact to be related to distance from the
power plant. Distance might well be a surrogate index of stress. However, in
all years, distance of the sampling site from Colstrip accounted for very
little of the variance in site diversity and the strength of the correlation
has steadily decreased.
TABLE 7.3. PARTIAL CORRELATION OF H1 WITH VARIABLE LISTED
Year R^ STRUG PINE STRIPM RIP GRASS AG DIST
1975 .54 .53 .02 -.35 .46 -.35 .31 .31
1976 .45 .43 .07 -.20 .37 -.37 .35 .16
1977 .43 .38 .12 -.10 .41 -.47 .32 .05
Key: R2 = proportion of variabity in HT accounted for by regression against
the 8 variables listed.
STRUG = presence of human structures (+/-)
PINE = proportion of site covered by Ponderosa Pine.
STRIPM = presence of strip mining activity in immediate vicinity (+/-)
RIP = presence of riparian habitat (+/-)
GRASS = proportion of site covered by native grasses
AG = proportion of site cultivated
DIST = Distance from Colstrip
Seasonal Changes in the Spatial Patterns of_ Bird Populations
Patterns in the use of space reflect adaptive behavioral choices made by
species. These patterns may change seasonally in response to changes in
habitat factors and/or changes in physiological state of the birds. We wished
to develop statistical descriptive methods to summarize the spatial patterns
observed. Such methods are potentially useful in quantifying a species response
to environmental change.
A number of ecological and behavioral factors may underlie the observed
dispersion pattern of a species (Weins, 1976; Rotenberry & Weins, 1976). The
pattern may reflect adaptive behavioral mechanisms for resource allocation.
These may range from rigorous territorial defense to foraging flocks and
colonial nesting. If only a portion of the area sampled provides suitable
248
-------
habitat, individuals may tend to congregate in the suitable portions. Behav-
ioral effects on dispersion are then superimposed on the tendency to aggregate
in favorable habitat. It would be useful to be able separate the effects of
resource distribution from behavioral effects on species dispersion patterns.
The ratio of the sample variance to the sample mean (S2/x) has been
commonly used as an index of the dispersion pattern in plant and animal popula-
tions (Greig-Smith, 1964' Pielou 1969). If the individuals of a population
are randomly distributed over the study area, the number of individuals per
sample site is expected to follow a Poisson distribution, and the ratio of the
variance to the mean is 1. If individuals tend to aggregate the ratio is
greater than 1.
Figure 7.2 shows the seasonal changes in the S2/x ratio from May to
September for Western Meadowlark, the most abundant bird species in the Colstrip
study area. The pattern is consistent for the three years. The exceptionally
high peak during 1976 occured on a day when a flock of 73 meadowlarks was
seen. A clumped distribution is evident at all times but varies seasonally in
degree. Territorial behavior tends to disperse individuals during spring and
early summer. Later in summer, the tendency to flock increases.
IX
\
OJ
CO
O
CO
01
UJ
Q_
CO
Q
O
X
LU
O
20.0-
MAY
JUN
JUL AUG
DATE
SEP
OCT
Figure 7.2. Seasonal changes in the Index of Dispersion for Western Meadowlarks
249
-------
The negative binomial distribution is often used as an empirical statis-
tical distribution to describe animal and plant populations that are clumped
(Elliot, 1971; Pielou, 1977). However, the observed distributions in the
Colstrip bird censuses are often bimodal, with one mode over zero counts and
the other mode representing the most common count of that species where it is
observed (Figure 7.3).
The negative binomial distribution can not adequately describe such a
bimodal situation. However, it can be modified to allow for added zeros.
One way to interpret such a distribution, suggested by Pielou (1969), is to
assume a certain proportion of the sites are not inhabited, for environmental
reasons that may not be detected by the observer. Given that a site is
habitable, the number of individuals observed at the site follows a negative
binomial distribution. Even if a site is habitable, there may still by
chance be no individuals present. The habitablility of sites can change
seasonally for a bird species, as the moisture supply fluctuates, plants
progress phenologically, or prey species vary in availability.
The negative binomial distribution with added zeros can be written so
that the three parameters are intuitively interpretable (see Appendix 7.1 for
mathematical details). 0 is the proportion of sites which are habitable, M
is the expected number of individuals at a site which is habitable, and K is
a parameter which indicates the degree of clumping or aggregation of the popula-
tion within the habitable area. As the distribution of individuals among
sites approaches a random pattern, 1/k approaches zero (i.e* k approaches
infinity). 1/k increases (k decreases) as clumping increases.
Likelihood ratio tests showed that in almost all cases the distribution
with added zeros gave a significantly better description of the data than
the ordinary negative binomial model. Significance levels were calculated
using the approximate chi-square distribution of twice the logarithm of the
likelihood ratio (Bickel, P.J. and Doksum, K.A. 1977, p. 229).
Figure 7.3 shows observed and estimated distributions for Western Meadow-
larks and Lark Buntings in spring, when the tendency to flock is low, and late
summer when the largest flocks are seen. The parameters of the fitted distri-
butions were estimated by maximum likelihood (see Appendix 7.1).
Western Meadowlark is widely distributed in the study area. Lark Bunting
is patchily distributed, but is quite common at certain sites. The spring
histograms clearly show the bimodal nature of the distributions. The sites
with zero counts may be uninhabitable to the species, or perhaps individuals
are simply congregating elsewhere. Lark buntings leave a large proportion of
sites uninhabited even in late spring when no tendency to congregate or form
flocks is evident. In late summer, the dramatic increase in flocking in both
species is evidenced both by the heavy tails of the distributions and the
increased proportion of sites with no individuals.
Strictly speaking, the parameter 0 does not imply habitability in a
biological sense. A more accurate interpretation of the model is that for a
proportion 00) of the census sites the distribution of observed birds can be
approximated by a negative binomial distribution, wh'ile no birds of that
250
-------
ho
Ln
.2
i
:REQUENCY
o
u_
.84
> :
< -06
HJ .05
cr
.04
.03
.02
.0
r>
WESTERN MEADOWLARK >57J
5/£/ 75
.15
-•-
—
•
-
•
•
.12
— .09
~~| .06
—j •
* A .03
'In
71
x
~
-
Z\
"V"
WESTERN MEADOWLARK
8/26/75
TT] • •
i~l — I~*T- • • • • • •
0 1 2 3 4 5 6 7 8 9 10 w 0 1 2 3 4 5 6 7 8 9 10 1 112 13 14 15 16 17 18 192021 22232425
;i
—
-
_
-
a
LARK BUNTING LARK BUNTING
6/11/75 .87 r p^ 8/26/75
',
-
•
•
.04
.03
•
.02
.01
,-•- — 1 n
^
-
-
v^
•
• • •
TTTTTT^
0 I 234567
01 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 192021222324
NUMBER OF BIRDS AT STATION
Figure 7.3. Frequency distributions of Western Meadowlarks and Lark Buntings as observed
(•) and as described by the negative binomial with added zeros.
-------
species are found on the remaining (1 - 0) proportion of the sites. The
purpose of using such a two-part statistical distribution in describing the
spatial distribution of birds is to get a useful measure of changes in aggre-
gation which takes into account the fact that some species are more restricted
than others in their range within the study area. A change in spatial pattern
caused by air pollution or other environmental disturbance could be detected
as a change in overall density (y), a restriction or expansion of the range
of the species within the study area (0), or changes in social organization
such as changes in territoriality or flocking behavior (k).
CONCLUSIONS
1. The bird fauna in the Colstrip vicinity is numerically dominated by
Western Meadowlarks and this dominance has increased since 1975.
2. The relative abundances of raptors, blackbirds, and Lark Buntings have
apparently decreased since 1975.
3. Much of the local variation in bird species diversity is correlated with
habitat factors.
4. Statistical distributions with added zeros are useful in describing the
spatial distributions of common bird species in the Colstrip area.
ACKNOWLEDGEMENT S
Larry Doe, Eric Preston, and John Chilgren performed the census during
1975, 1976, and 1977, respectively.
REFERENCES
Bickel, P.J. and K.A. Doksum. 1977. Mathematical Statistics; Basic Ideas and
Selected Topics. Holden-Day, San Francisco.
Elliott, J.M. 1971. Some Methods for the Statistical Analysis of Samples of
Benthic Invertebrates. Freshwater Biological Association, Scientific
Publication no. 25.
Emlen, J. 1971. Population Densities of Birds Derived From Transect Counts.
Auk, 88(2):323-342.
Greig-Smith P. 1964. Quantitative Plant Ecology. Butterworth1s, Washington,
D.C. 256 p.
Jarvinen, 0. and R. Vaisanen. 1976. Between-year Component of Diversity in
Communities of Breeding Land Birds. Oikos, 27(1):34-39.
252
-------
Lewis, R.A., M.L. Morton, and S. Jones. 1976. The Effects of Coal-Fired
Power Plant Emissions on Vertebrate Animals in Southeastern Montana.
In: R.A. Lewis, N.R. Glass, and A.S. Lefohn, eds. The Bioenvironmental
Impact of a Coal-fired Power Plant, 2nd Interim Report. EPA-600/3-76-
013, U.S. Environmental Protection Agency, Corvallis, Oregon, pp. 140-187
MacArthur, R.H. and J.W. MacArthur. 1961. On Bird Species Diversity. Ecol-
ogy, 42(3):594-598.
Pielou, E.G. 1969. An Introduction to Mathematical Ecology. Wiley-Inter-
science, New York 286 p.
Pielou, E.G. 1975. Ecological Diversity. Wiley Interscience, New York.
165 p.
Pielou, E.G. 1977. Mathematical Ecology. Wiley Interscience, New York.
385 p.
Robbins, C.S. and W.T. Van Velzen. 1970. Progress Report on the North
American Breeding Bird Survey. In: Bird Census Work and Environmental
Monitoring, S. Svenson, ed. Bull. Ecol. Res. Comm. No. 9. Lund, Sweden.
pp. 22-30.
Rotenberry, J.T. and J.A. Wiens. 1976. A Method for Estimating Species Dis-
persion from Transect Data. Am. Midi. Nat., 95(1):64-78.
onannon, C.E. and W. Weaver. 1949. The Mathematical Theory of Communication.
University of Illinois Press, Urbana.
Stickel, W.H. 1975. Some Effects of Pollutants in Terrestrial Ecosystems.
In: Ecological Toxicology Research, A.D. Mclntyre and C.F. Mills,
eds. Plenum Press, New York.
Tramer, E.J. 1969. Bird Species Diversity: Components of Shannon's formula.
Ecology, 50(5):927-929.
Weins, J.A. 1974. Climatic Instability and the Ecological Saturation of Bird
Communities in North American Grasslands. Condor, 76(4):385-400.
Weins, J.A. 1976. Population Responses to Patchy Environments. Ann. Rev.
Ecol. Syst., 7:81-120.
Woodwell, G.M. and H.H. Smith. 1969. Diversity and Stability in Ecological
Systems. Brookhaven Symp. Biol. No. 22. BNL 50175. Brookhaven National
Laboratory, Upton, N.Y. 264 p.
253
-------
APPENDIX 7.1 The negative binomial distribution with added zeros
The negative binomial probability density function can be written:
X
x=0,l,2,...
x
_
where = [k (k+1) (k+2) ... (k+x-1)] -r
x x.
/k-Hr-1 \
TIT j_ » _c r\ i ^" ' "• ^\ t
Note: if x=0, f J = 1
The mean and variance of the distribution are
E(x) = y
Var (x) = y + ^~
As — approaches zero, the variance approaches the mean and the negative bino-
mial distribution approaches the Poisson distribution (Elliott, 1971). Thus,
the estimated value of y~ can be used as a measure of the degree to which
K.
individuals in the population are more clumped than random.
Pielou (1969) gives an interpretation of statistical distributions with
added zeros in terms of habitability of sites. Suppose, that census sites are
either habitable or uninhabitable to a species due to factors that may be
unknown to us. Individuals of the species follow the distribution in question
only at the habitable sites.
The density function of the negative binomial with added zeros can be
parameterized:
g(x) if x=0
0 g(x) if x=l,2,3,...
254
-------
where 0 is the proportion of census sites that are "habitable" to
that species at that time of year and g(x) is the negative binomial
density function.
The distribution f(x) can be reparametrized as
1~9 if x=0
9 p(x) if x=l,2,3,...
where 9 is the proportion of sites that have one or more birds of the
species and p(x) is the zero-truncated negative binomial distribution:
e = 0 i-gco) = 0 i-
/k+x-l\ / k \ k /u\x
/ \r \ \r
i-g(o) \ x
Maximum likelihood estimates of the parameters are obtained from census
data as follows. Let ^ represent the vector of observed counts for a census.
For notational convenience, order the observations so all the zero counts come
first.
x is the number of birds of that species observed at site i
i
m is the number of sites where none were observed.
n is the number of sites, 60 on our survey.
255
-------
The likelihood function for f(x) given this data is:
L (6, y, k; *) = n f(X±)
m n
= n (i - 6) n e P(X)
1=1 i=m+l
*-(—)
\y+k/
-1
Maximization is more readily carried out with the log - likelihood function:
n x. -1 n
In L (9, y, k; £) = m In (1-9) + (n-m) In Q + y In (k+j ) - ^ In x±!
i = m+1
n
i = m+1 j=0
n
+ (n-m) k In k - (n-m) k In (y+k) + V x. In y - Y x. In (y +k)
i=m+l X i=m+l 1
- (n-m) In
i
The partial derivatives used to find the values of 0, y, and k which maximize
this equation are:
9 In L
8 0
8 In L
3 U
n
8 In L ^
8k Z_
i=m+l
1-0 '
_
1 1
y y+k
x . — 1
I k
j=o
0
n k
A , vi i in) . -
i y+k
i=m+l
P -
1
1 i
j_ | ..,._
\ — y
f ' M . , , k\
n
i 7" x.
14- i
i m+1 + (n-m)
J y+k
— 1 » + -Ln vTT/i
\y+k ul+k /
i , i / k \ k j/
L + J.H l , i ) ~ . i "r
y+k y+k
(^) - !
By setting the partial derivative equal to zero, the maximum likelihood estimate
for 0 is seen to be n-m. The estimates for y and k must be found iteratively.
n
The proportion of "habitable" sites (0) can be estimated as:
f^ /Si
- / k k'
y ^ y+k^
Where 0, 0, y, and k are maximum likelihood estimates of 0, 0, y, and k.
256
-------
SECTION 8
BASELINE HISTOLOGY OF THE THYROID AND THYMUS GLANDS OF
WESTERN MEADOWLARKS NEAR COLSTRIP
M, D. Kern and J. P. Wiggins
ABSTRACT
The objective of this part of the Colstrip Project is
to provide baseline histological information
concerning selected tissues of the Western Meadowlark
(Stumella neglecta) for use in (1) assessing the
impact of pollutants on birds residing near coal-
fired power plants, and (2) formulating a siting
protocol for coal-fired power plants in the Great
Plains region. The histology of the meadox-jlark's
thyroid and thymus glands (collected between April
and September, 1975-1977) is presented in this
section. The thyroid of adult meadowlarks becomes
increasingly active between April and July, as the
period of reproduction concludes and just prior to
the postnuptial molt, and remains highly active while
molt is in progress (July through September). There
are no sex-related differences in the activity of the
gland. However, juveniles have more active thyroids
than adults during June. Of five histological
parameters examined, nuclear diameter and epithelial
height appear to be the most sensitive indicators of
small changes in the activity of the thyroid gland.
The thymus of adult meadowlarks recrudesces during
the reproductive season (Hay-June) and is fully
developed and active when the postnuptial molt begins
(July). It remains enlarged and active into September,
Juvenile birds have larger and more active thymus
glands than molting adults.
INTRODUCTION
A general objective of the research program at Colstrip is to identify
bioindicators in the vicinity of coal-fired power plants which (1) are
sensitive to perturbations in the environment, particularly to the chronic
257
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emissions of power sources, (2) exhibit obvious and/or immediate responses
to pollutants, (3) can be monitored easily and inexpensively, and (4) can
be used to predict the long-term impact of pollution on the ecosystem.
The program focuses on all trophic levels of the grassland ecosystem at
Colstrip. The dominant consumers which are being examined in the uppermost
trophic levels include the deermouse (Peromyscus maniculatus) and the
Western Meadowlark (Stumella neglecta). This section deals with the thyroid
and thymus glands of the latter species.
These findings are a small segment of a larger effort to identify
specific avian organs which are sensitive to low levels of toxic, but
non-lethal, emissions of stationary power sources. Organs selected for
study include
1. those which are stress indicators: the adrenal and thyroid glands
2. those involved in immune responses: the bursa of Fabricius, thymus,
and spleen
3. those which detoxify pollutants: the liver, kidney, and lung
and 4. those important for the breeding success of meadowlarks: the
reproductive organs.
We propose to develop statements about (1) how seasonal changes in organ
structure reflect seasonal changes in organ function, (2) how organ structure
is affected by pollution challenge, and (3) how changes in organ structure
can be used to indicate existing levels of toxicity and to predict long-term
population changes if exposure to pollutants persists at such levels. We
anticipate that information of this nature will be useful in developing a
siting protocol for coal-fired power plants in the Great Plains region. It
is particularly important to gather information about terrestrial vertebrate
forms such as meadowlarks because they are readily visible to the public,
are likely to be immediately missed should they disappear, and because
studies of chronic pollution stress on birds generally are few (Truhaut
1975).
Rationale for the Project
In general, the vertebrate species which disappear earliest from
polluted ecosystems are carnivores (Stickel, 1975). Since Western
Meadowlarks are largely carnivorous and are the dominant avian species in the
grassland ecosystem at Colstrip, Montana, they may a priori be expected to
disappear from the vicinity of coal-fired power sources rather quickly.
Unlike the members of lower trophic levels, birds accumulate pollutants,
frequently for considerable periods of time, before they become visibly
distressed and suddenly disappear (Stickel, 1975). It would be useful
therefore by selective sampling to be able to determine (1) x^hich avian
organ-systems selectively accumulate pollutants and at what rates, as well
258
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as (2) which organ-systems are most readily damaged by pollutants, in order
to anticipate when levels of these toxicants will become so high that they
impair the survival of the group.
The organ-systems most likely to be affected by toxicants are those that
deal directly or indirectly with them under normal circumstances. These are
precisely the ones selected for study: (1) detoxifying organs, (2) immune
system, (3) stress-mediating organs, and (4) reproductive organs. Birds have
already proven useful as bioindicators of aerial pollution in highly
industrialized areas of Japan. Doves in these areas develop lung pathologies
when aerial pollution levels are 10-times lower than those necessary to
produce analogous pathologies in human lungs (Lewis, Glass, and Lefohn, 1975),
In effect, they provide an early warning system when industrial emissions
approach critical toxic levels. Birds are particularly well suited to
monitor aerial emission levels because (1) their lungs are structurally
analogous to the high volume samplers used in aerial pollutant scavengingt
and (2) they are far-ranging organisms which sample air over considerable
distances from power sources. Since they also feed in the same areas,
examination of their livers and kidneys provides a method of separately, but
concurrently, monitoring the accumulation (and damage) of pollutants obtained
through the diet, as well as those which lodge in the lungs and are obtained
from the surrounding air.
Vertebrate responses to pollution challenge vary seasonally and are a
function of such things as species, age, sex, social rank, and physiological
status. It is therefore important to begin by describing the normal
structure of avian organ-systems as a reference with which to compare the
same organ-systems after birds have been exposed to the emissions of coal-
fired power plants.
Major Objectives of the Avian Histological Project
In the larger view, the major objectives of the avian histological
project are
1. To evaluate the normal histology of selected organs of Western
Meadowlarks collected during the preopevat-ional phase of the Cols trip
Project. Such organs were collected between 1975 and 1977. The power
plant at Colstrip has been operating since the summer of 1976 at levels
ranging between 30 and 90% of peak capacity. Organs collected during
1976 and 1977 are considered preoperational in kind because they come
from areas either not polluted at all or only minimally polluted.
2. To evaluate the histology of the same selected organs of Western
Meadowlarks collected during the postoperational phase of the Colstrip
Project (1978-1979), or from ecologically similar sites near power
sources elsewhere in the North Central Great Plains.
3. To identify organ-systems of the Western Meadowlark^which are reliable
and sensitive indicators of air quality and which will be particularly
useful biomonitors of emissions from coal-fired power plants.
259
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4. To integrate histological measurements with other information available
for meadowlarks taken at Colstrip in order to identify correlations
which may be useful as (1) bioindicators of pollution challenge, and/or
(2) predictors of the cumulative effects of pollutants on birds in
general. Much ancillary information on meadowlarks is currently stored
in the Information Storage and Retrieval System at the Corvallis
Environmental Research Laboratory. It contains information about body
and organ weight; body molt; carcass composition and caloric content;
together with data on the breeding biology, ectoparasites, and lesions of
meadowlarks collected during 1975-1977. The data bank also contains
information about seasonal changes in weather and air quality at Colstrip,
Additional information will be added to the system during the upcoming
postoperational phase of the program.
In the narrower view of the vertebrate program at Colstrip, only
objective 1 and part of objective 4 will be met.
Progress to-Date
!-ficroscopic slides have been prepared from most of the meadowlark
tissues collected during the preoperational phase of the Colstrip Project
and are on hand for evaluation. To-date, we have surveyed all thyroid glands
collected prior to July 1977, and many of those collected in July-September
1977. (We have not yet received all tissues collected during the latter
months of 1977.) In addition, we are midway through the thymus glands
collected preoperationally; and have begun work on liver and adrenal glands.
On the following pages, x;e present a progress report concerning the
quantitative and descriptive histology of the thyroid gland and preliminary
remarks concerning the thymus.
Thyroid Gland
Studies of the avian thyroid gland are numerous (all but the most recent
are reviewed by Falconer, 1971; Assenmacher, 1973; and Ringer, 1975; more
recent studies include those of Hohn and Braun, 1977). These illustrate the
importance of the thyroid gland in
1. Normal somatic grox^th
2. Calorigenesis.—Not only is the thyroid necessary for the maintenance of
normal metabolism and concurrently for the production of heat in birds,
but in many cases seasonal changes in its activity are inversely related
to changes in ambient temperature (see, for example, Burger, 1938; Hohn,
1950; Davis and Davis, 1954; Wilson and Earner, 1960). High ambient
temperatures, for example, reduce the secretory activity of the thyroid
gland of domestic fowl, whereas low ambient temperatures have the
opposite effect (reviewed by Falconer, 1971; and Ringer, 1975).
3. Molt.—Several studies illustrate the fact that thyroid activity
increases shortly before or during periods of seasonal molt (reviewed by
Payne, 1972; and Assenmacher, 1973). This is particularly well shown by
mallards. The thyroid activity increases one month earlier in drakes
260
-------
than in hens: the male also begins to molt one month earlier than the
female (Hohn, 1961). On the other hand, the molt of several species
occurs without a change in thyroid activity (reviewed by Payne, 1972).
Furthermore, thyroidectomy may or may not abolish seasonal molts; and
injections of thyroxine may or may not precipitate a molt. As Payne
(1972, p. 128) says "... thyroid activity seems to be related to molt,
but the apparent role of the thyroid in molt differs from species to
species". One manner in which the gland is involved in feather
replacement is that it stimulates cell division and growth within feather
papillae (Voi£kevich,1966; Hocker, 1967).
4. Reproduction.—As with molt, the role of the thyroid in reproductive
activities varies considerably from one avian species to another. In
some (domestic fowl, House Sparrows, Baya Weavers), annual gonadal
recrudescence apparently requires thyroxine. In others (European
Starlings and several subtropical Indian finches), the thyroid is not
necessary for gonadal growth. In fact, thyroid activity diminishes
during the breeding season of some species (Red Fodies, White-crowned
Sparrows, Spotted Munias). In still other cases, however, it increases
near the end of the reproductive period (European Starlings, European
Blackbirds, Mallards, Wood Pigeons) and is apparently responsible for
gonadal regression (Baya Weavers and Mannikins). This complex subject
has recently been reviewed by Assenmacher (1973).
5. Migration.—The role of the thyroid in the control of migratory behavior
and premigratory fattening is unclear (Berthold, 1975). Although thyroid
activity is elevated in some species during migration (Putzig, 1938;
George and Naik, 1964) and injections of thyroxine induce migratory-like
behavior in some forms (Merkel, 1938), the gland probably does not play a
principal regulatory role in this seasonal event.
If the thyroid gland is a major regulator of any one of the above
activities in meadowlarks, and if it is sensitive to pollutants, then upsets
in its activity will be translated into aberrancies in seasonal cycles.
Environmental perturbations can alter thyroid activity within 7-14 days
(Gelineo, 1955; Hahn, Ishibashi, and Turner, 1966) and histologieal features
of the gland sometimes change before mensurable changes in glandular activity
occur (Saatman and van Tienhoven, 1964). It may accordingly be possible to
predict the timing and magnitude of altered seasonal events secondary to
pollutant-induced changes in thyroid function simply by evaluating thyroid
histology on a routine basis.
With this in mind, there are several normal correlations which need to
be described between thyroid activity and other seasonal events of
meadowlarks. These will be exhaustively addressed once the data for July-
September, 1977, become available to us. They include correlations between
various histological indices of thyroid activity (described below) and
seasonal cycles of body x^eight, body fat, molt, reproduction,
adrenocortical activity, and ambient temperature.
261
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Thymus Gland
It is now well established that the avian thymus is a central lymphoid
organ and the site of development of T-dependent lymphocytes which (1)
migrate to peripheral organs, such as the spleen, and (2) are responsible for
cell-mediated immune responses. T-dependent lymphocytes produce cytotoxic
substances called lymphokines which destroy foreign bodies and are
responsible for the rejection of skin grafts and for hypersensitivity
reactions (the topic of avian iitununity is reviewed by Cooper et aZ., 1966;
and more recently by Moticka, 1975; a thorough general discussion of this
subject is also presented by Raviola, 1975a). Lymphokines also stimulate
macrophages (which ingest and destroy foreign materials) and B-dependent
lymphocytes (which produce antibodies).
Until recently it was thought that the avian thymus, like its mammalian
counterpart, involuted x^hen a bird reached sexual maturity (Hodges, 1974).
However, it is now apparent that this organ recrudesces periodically in many
species coincident with periods of molt and/or reproduction. This occurs in
Ring-necked Pheasants (Anderson, 1970); mallards, House Sparrows, and
American Robins (Ilohn, 1956); Yellow-vented Bulbuls (Ward and D'Cruz, 1968);
Red-billed Diochs (Bacchus and Kendall, 1975; Kendall, 1975; Ward and Kendall,
1975); and even occasionally in domestic fowl (Payne, 1971).
The thymus is also a site of formation of red and white blood cells and
it has been suggested that by recrudescing it provides (1) lymphoid cells to
deal with the stress associated with molt (Anderson, 1970), or (2)erythro-
cytes required for the rapid somatic growth of immature birds; the rapid
recovery of body lipids and proteins which are depleted during breeding; and
to nourish the growing feathers during periods of molt (Bacchus and Kendall,
1975; Ward and Kendall, 1975).
The thymus of immature birds is particularly sensitive to stress and
will involute prematurely under conditions which produce hypertrophy of the
adrenal cortex and production of adrenocortical hormones (Payne, 1971). This
organ is therefore potentially useful for determining if pollutants from
coal-fired power plants selectively affect young birds. Although not reported
in the literature, it is plausible that pollutants of this kind may even
prevent or abbreviate the recrudescence of the adult thymus gland. In either
case, changes which are deleterious to the whole bird will probably appear
initially as structural changes of thymic tissue.
At Colstrip, the wet weight of the raeadowlark's thymus increases
annually just before the postnuptial molt takes place (Preston and Lewis,
1978). Whether these changes in weight reflect changes in glandular activity
needs to be determined. We are now analyzing the thymuses of the meadowlarks
collected on site between 1975 and 1977 with this end in mind.
262
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MATERIALS AND METHODS
Histological Measures of Thyroid Function
We have examined five histometric indicators of thyroid activity:
(1) follicle size, (2) the number of follicles per unit area of thyroid
gland, (3) the colloid content of the gland, (4) the diameter of nuclei in
epithelial cells lining the follicles, and (5) the height of these epithelial
cells.
We have assumed that the microscopic sections of the thyroid gland come
from its center and represent conditions typical of the whole gland. We have
also assumed that an active thyroid gland is characterized by small follicles
containing little colloid (and therefore relatively large numbers of
follicles per unit area), large epithelial nuclei, and a high follicular
epithelium; whereas inactive glands feature large follicles distended with
considerable colloid (and therefore relatively small numbers of follicles per
unit area), flattened epithelial nuclei, and a squamous follicular epithelium.
This functional interpretation of the gland's histology is consistent with the
views of virtually all previous investigators.
One or more of our methods have been employed successfully in earlier
studies of the avian thyroid gland (Burger, 1938; Voitkevich, 1966; von Faber,
1967; Erpino, 1968; Ljunggren, 1968; Raitt, 1968; Payne and Landolt, 1970;
Hohn and Braun, 1977). Other methods are sometimes used, including
calculation of the per cent of the total gland consisting of epithelium and
stroma (Wilson and Farner, 1960; Hohn and Braun, 1977) or activity scales
based on nuclear diameter and epithelial height (Ljunggren, 1968). All
appear to adequately measure the activity of thyroid tissue and we arbi-
trarily settled on the five listed above. For each indicator, we used
Stein's formula to determine how many observations should be made to
demonstrate significant differences at the 5% level (Steel and Torrie, 1960,
p. 86).
Folliculav size was determined by measuring the maximal diameter of 10
randomly selected follicles in sections of each gland, using an ocular
micrometer and magnifications of 400.
To determine the number of follicles per unit area of gland (follicular
density), we counted the number of complete follicles positioned within an
ocular grid in 20 randomly selected fields within the section. The
magnification used was 400 and the area of tissue encompassed by the grid was
0.056 mm2.
The colloid content of each gland is a single visual estimate of the
volume of secretion in the entire gland, on a scale of 0 to 5, in x-^hich
colloid may be absent (rating of 0), or present in trace (1), small (2),
moderate (3), large (4), or very large (5) amounts. Estimates were made
after scanning the section at a magnification of 40.
263
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In order to determine the average nuclear diameter of epithelial cells
in each gland, 20 nuclei were randomly selected from the section and
measured with an ocular micrometer at a magnification of 1000. Nuclei in
columnar and cuboidal epithelia are commonly spherical and accordingly
nuclear diameter is constant wherever measured; however, in squamous
epithelia the nuclei are either oval or distinctly flattened and have maximal
and minimal diameters. We therefore used a measure of nuclear size which
includes the maximum and minimum diameters of the nucleus. In this case,
(maximum diameter) + (minimum diameter)
Nuclear Diameter = 2
The heights of 20 epithelial cells randomly selected from follicles in
the center of each section were averaged to obtain an index of epithelial
height for each gland. Measurements were made at magnifications of 1000.
Wherever appropriate, we evaluated the results statistically by
analysis of variance, the Student's t-test, linear regression, or Duncan's
multiple range test with Kramer's modification for samples with unequal num-
bers of observations (Duncan, 1955; Kramer, 1956; Steel and Torrie, 1960).
Histological Measures of Thymus Function
We are using seven histological indicators to evaluate thymic activity.
These are derived from parameters used in earlier studies of the avian thymus
(Hohn, 1956; Ward and D'Cruz, 1968; Anderson, 1970; Bacchus and Kendall,
1975; Kendall, 1975). They include (1) the mitotic activity of the gland,
(2) the presence or absence of a distinct cortex, (3) the cross-sectional
area of cortex and/or medulla, (4) the number and morphology of Hassal's
corpuscles, (5) the size of large cysts associated with Hassal's corpuscles,
(6) the types and relative numbers of cells in the thymic cortex, and (7) the
number of extravascular erythrocytes in the cortex.
The mitotic activity of each thymus is estimated after scanning the
cortex (if present) or entire section (in the absence of a cortex) at
magnifications of 400 for mitotic figures. Activity is rated on a scale of
0 to 5, in which mitotic figures may be absent (rating of 0), or present in
small (1), mild (2), moderate (3), large (4), or very large (5) numbers.
Kendall (1975) uses this index to identify enlarging thymus glands
selectively: in queleas, the mitotic activity is quite high in enlarging
glands, but low in fully developed, regressing, or fully regressed glands.
Differentiation of thymic tissue is quantified in each lobe of the gland
by assigning the number 1 to the lobe if it has a distinct cortex, and the
number 2 if the cortex is absent. The overall condition of each gland is the
average of individual numerical values assigned to each of its lobes. The
presence of a cortex is the indicator most frequently used to determine
whether the thymus is functional or not. A cortex is present in enlarging,
fully enlarged, and regressing glands, but not in fully regressed glands
(Hohn, 1956; Ward and D'Cruz, 1968; Anderson, 1970; Bacchus and Kendall,
1975) .
264
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No measurements of the area of the cortex have been reported in the
literature to-date. We suggest that variations in the cross-sectional area
of this region may reflect its lymphopoietic activity. Areas of the cortex,
medulla, and the total cross-sectional area of each section are obtained by
tracing the image of each lobe and its zones onto a piece of paper, using a
camera lucida and magnifying the section by a factor of 4.45. A planimeter
is then used to measure the areas of cortex, medulla, and whole lobe on the
tracing. The latter can be converted into areas of tissue without difficulty
because 1.0 cm2 of the tracing - 0.0505 cm2 of tissue. Since these areas are
measured in a single section of each lobe of the thymus, we necessarily
assume that the section comes from the center of the lobe and that conditions
here are representative of conditions in the entire lobe. The error is most
likely minimal anyway because the proportions of cortex and medulla for each
bird are average values based on measurements in several lobes of the gland.
All Hassal's corpuscles in the section are counted and classified as
"early" or "late" on the basis of their morphology. These designations come
from Bacchus and Kendall (1975) and are fully described in the following
section of this paper.
The function of Hassal's corpuscles is not known. They may actively
remove cells from the thymus under specific conditions (Blau, 1967), or they
may be nothing more than degenerating masses of thymic cells (Raviola,
1975&) . However, they are a constant feature of the gland and their numbers
increase when it involutes* In queleas, regressing glands contain large
numbers of late corpuscles, whereas enlarging glands contain few-to-none
(adult birds) or only early corpuscles (immature birds) (Bacchus and Kendall,
1975). Censuses of these corpuscles may permit us to distinguish enlarging
from regressing thymuses.
We also measure the maximal diameter of the largest cyst associated with
each late Hassal's corpuscle, using an ocular micrometer and magnifications
of 400; and make an estimate of the most common number of cysts in the late
corpuscles within each lobe, again at magnifications of 400. TJe suggest that
these enumerations may provide a means of distinguishing regressing from
fully regressed thymuses.
In addition, we make censuses of the cells in the cortex of the
meadowlark's thymus. The census data are still preliminary so we have not
included them in this paper. Nevertheless, we present the census method and
the rationale for its use below.
The method is a modification of that used by Kendall (1975). We
identify and count the number of cortical cells which occur in five randomly
selected quadrants of an ocular grid. One corner of the grid is placed on
the capsule of the thymus. All of the cells in the central plane of focus in
the five quadrants are then identified and counted. Only cells completely
enclosed by the edges of the quadrant are included. Censuses are made under
oil at magnifications of 1500. To avoid bias, randomly selected areas of
cortex on both sides of each lobe are used in the census. Tie also avoid
areas of cortex containing large blood vessels in order to minimize the
265
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number of intravascular cells in the data; however, small capillaries
frequently occur in the quadrants and an occasional blood cell from one of
them is incorporated into the results. A total of six areas of cortex
(30 quadrants) are evaluated per lobe of each gland. This amounts to 153 ym
of cortex (each quadrant encloses ^ 5.1 ym of tissue).
Kendall (1975) uses the cell populations in the cortex of queleas to
distinguish between enlarging, fully developed, and regressing thymuses.
Mitotic figures, for example, are only numerous in the enlarging adult gland.
Lymphocytes are more numerous in enlarging glands than in regressing or
regressed ones. On the other hand, enlarging glands contain fewer cortical
erythrocytes than enlarged, regressing, or regressed ones. Finally, the
total number of cells in the cortex is conspicuously reduced in regressing
glands. Although Kendall's conclusions are based on a relatively small
number of adult queleas, they suggest that cortical cell populations can be
used to determine the functional status of the thymus and we have therefore
applied this census technique to meadowlark tissues.
Since it has been suggested that the thymus has an erythropoietic
function (Bacchus and Kendall, 1975; Uard and Kendall, 1975), we also make a
visual estimate of the number of erythrocytes free in the cortical tissue of
each lobe, after scanning the section at a magnification of 400. Erythro-
cytes may be absent (in which case the lobe is assigned a rating of 0), or
present in small (1), mild (2), moderate (3), large (A), or very large (5)
numbers. Ue have just begun to make these estimates and accordingly do not
include them in the following section of this paper.
For each index of thymic activity, we used Stein's formula to determine
the number of observations necessary to obtain statistical differences at
the 5% level (Steel and Torrie, 1960, p. 86).
RESULTS AND DISCUSSION
Normal Histology of the Thyroid Gland of Western Meadowlarks
The histological organization of the meadowlark1s thyroid gland is
typical of that found in birds generally (see descriptions in such references
as Falconer, 1971; and Assenmacher, 1973). The gland consists of numerous
secretory follicles laden with more or less colloid and lined with a simple
layer of epithelial cells, the height of which varies according to the
activity of the gland (see above). Variable amounts of stromal material
occur between the follicles and consist of connective and vascular tissue.
Variations in the Histology of the
Thyroid Gland of T7estern Meadowlarks
Between April and September
Data concerning monthly changes in thyroid histology, together with
information concerning the effects of year, sex, and age on the gland,
appear in Tables 8.1-8.3. There were few differences between data collected
266
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TABLE 8.1. MONTHLY CHANGES IN THE HISTOLOGY OF THE THYROID GLAND OF ADULT
WESTERN MEADOWLARKS (Sturnella negleata) AT COLSTRIP, MONTANA
ho
Year Month
1976 Apr
May
Jun
Jul
Aug
Sep
1977 Apr
May
Jun
Jul
Aug
Sep
n
22
16
5
3
5
2
25
62
55
16
7
9
Nuclear
Diameter1 • 2
(um)
3.19 ±
3.24 ±
3.76 ±
3.67
3.82 ±
3.30
3.07 ±
3.29 ±
3.49 ±
3.98 ±
4.49 ±
4.39 ±
0.10 ab
0.12 ab
0.21 b
abc
0.21 be
ab d
0.09 a
0.06 ab
0.06 b
0.12 cd
0.18 c
0.16 c
Epithelial
Height1'2
(ym)
3.64 ±
4.21 ±
5.28 ±
4.93
5.36 ±
3.65
3.78 ±
4.74 ±
5.24 ±
5.94 ±
5.84 ±
5.89 ±
0.30 a
0.35 ab
0.63 abc
abc
0.63 abc
abc
0.28 a
0.18 b
0.19 b
0.35 c
0.53 b
0.47 b
Follicular
Diameter1' 2
(lim)
36.4 ±
37.7 ±
39.1 ±
43.7
33.5 ±
39.5
45.0 ±
37.3 ±
36.7 ±
40.7 ±
48.5 ±
45.7 ±
1.9
2.2
3.9
3.9
1.8
1.1
1.2
2.2
3.3
2.9
a
ab
ab
ab
ab
ab
b
a
a
ab
b
ab
Follicular
Density1' 2
(follicles/mm2)
644
657
508
428
503
537
573
610
562
535
423
433
.6 ±
.1 ±
.9 ±
.6
.6 ±
.5
.2 ±
.7 ±
.5 ±
.7 ±
.2 ±
.9 ±
32.1 a
37.5 a
67.9 abc
abc
67.9 abc
abc
30.4 abc
19.6 ab
19.6 abc
37.5 abc
57.1 c
50.0 ab
Colloid Content
of
Follicles1' 2' 3
1.76 ±
1.74 ±
1.63 +
1.58
1.43 ±
1.87
1.87 ±
1.61 ±
1.64 ±
1.83 ±
2.03 ±
1.92 ±
0.06 ab
0.07 ab
0.12 ab
ab
0.12 a
ab
0.06 b
0.04 a
0.04 a c
0.07 ab
0.10 b
0.09 be
'Values in these columns are means ± SEM; data for Jul-Sep 1977 are incomplete
2Means in each column are statistically different (P < 0.01) from each other when not followed by the same
letter (Duncan's multiple range test with Kramer's modification for groups with unequal numbers of observations)
3The amount of colloid was rated on a scale of 0 to 5 (none to abundant) for each gland. The data appear in
this column as Sp where p is a number between 0 and 5. The square root transformation is necessary for
parametric analysis of ordinal data (Steel, R.G.D., and J.H. Torrie. 1960. Principles and Procedures of
Statistics with Special Reference to the Biological Sciences. McGraw-Hill Took Co., Inc., New York. p. 157).
-------
KJ
ON
00
TABLE 8.2. MONTHLY CHANGES IN THE HISTOLOGY OF THE THYROID GLAND OF ADULT WESTERN
MEADOWLARKS (Sturnella neglecta) AT COLSTRIP, MONTANA - 1976 AND 1977
DATA COMBINED WHERE POSSIBLE
Sampling
Period
1976 Apr
1977 Apr
1976 May
1977 y
1976
1977 Jun
lln Jul
1976 Aug
1977 Aug
1976 Sep
1977 Sep
n
22
25
78
60
19
5
7
2
9
Nuclear
Diameter1' 2
(pm)
[3.12 ± 0.07 al
3.28 ± 0.05 a
3.51 ± 0.06 b
3.93 ± 0.11 cd
4.21 ± 0.13 cdl
3,30 abc
4.39 ± 0.16 d
Epithelial
Height1' 2
(ym)
[3.17 ± 0.21
4.63 ± 0.16
5.24 ± 0.18
5.78 ± 0.32
[5. 64 ± 0.41
[s.48 ± 0.43
Follicular
Diameter1' 2
(pm)
']
b
be
c
bcl
bcl
36
45
37
36
41
[«
[44
.4 ± 1.9
.0 ± 1.8
.4 ± 1.0
.9 ± 1.3
.2 ± 2.0
.2 t 2.5
.6 ± 2.6
a
b
a
a
ab
abl
abl
Follicular
Density1' 2
(follicles/mm2)
j~607.1 ±
619.6 ±
558.9 ±
519.6 ±
[457.1 ±
|~453.6 ±
21.4 al
17.9 a
19,6 ab
33.9 ab
25.0 b
44.6 hi
Colloid Content
of
Follicles1' 2« 3
fl.82 ± 0.04
1.63 ± 0.04
1.64 ± 0.04
1.79 0.06
1.43 ± 0.12
2.03 + 0.10
[l.91 ± 0.08
bcl
a
ab
abc
a
c
•]
Values in the columns are means ± SEM; data for Jul-Aug 1977 are incomplete.
2Means in each column are statistically different (P < 0.01) from each other when not followed by the same
letter (Duncan's multiple range test with Kramer's modification for groups with unequal numbers of
observations).
3The amount of colloid was rated on a scale of 0 tp 5 (none to abundant) for each gland. The data appear in
this column as /p where p is a number between 0 and 5. The square root transformation is necessary for
parametric analysis of ordinal data (Steel, R.G.D., and J.H. Tprrie, 1960. Principles and Procedures of
Statistics with Special Reference to the Biological Sciences, McGraw-Hill Book Co., Inc., New York. p. 157).
-------
TABLE 8.3, AGE-r AND SEX-rRELATED DIFFERENCES IN THE HISTOLOGY OF THE THYROID GLAND
OF THE WESTERN MEADOWLARK (Stuxmella neglecta)
VO
Sampling
Period
Apr
1976-1977
May
1976-1977
Jun
1976-1977
Jul
1976-1977
Aug
1976-1977
Sep
1976-1977
Age-Sex1'
Ad
Ad
Ad
Ad
Ad
Ad
Ju
Ju
Ad
Ad
Ju
Ju
Ad
Ad
Ju
Ju
Ad
Ad
Ju
Ju
- M
- F
- M
- F
- M
- F
- M
- F
- M
- F
- M
- F
- M
- F
- M
- F
- M
- F
- M
- F
2 n
41
6
44
34
40
20
3
5
6
13
11
1
4
8
10
12
4
7
19
17
Nuclear
Diameter3' "
( m)
3.14 ±
2.98 ±
3.27 ±
3.30 ±
3.44 ±
3.65 ±
4.43
4.62 ±
3.43 ±
4.15 ±
4.11 ±
4.80
3.93 ±
4.35 ±
4.22 ±
4.59 ±
4.10 ±
4.24 ±
4.02 ±
4.10 ±
0.07
0.19
0.07
0.08
0.10 a
0.14 a
ab
0.28 b
0.25
0.17
0.19
0.31
0.22
0.20
0.18
0.31
0.24
0.14
0.15
Epithelial
Height 3» "
( m)
3.72 ±
3.63 ±
4.68 ±
4.57 ±
5.19 ±
5.35 ±
8.17
8.20 ±
5.50 ±
5.91 ±
6.33 ±
8.00
5.25 ±
5.84 ±
5.87 ±
6.76 ±
5.20 ±
5.64 ±
5.17 ±
5.52 ±
0.22
0.57
0.21
0.24
0.25 a
0.35 a
b
0.70 b
0.57
0.43
0.47
0.78
0.55
0.50
0.45
0.79
0.60
0.36
0.38
Follicular
Diameter3* "
( m)
41.4 ±
38.1 ±
38.0 ±
36.6 ±
36.8 ±
37.2 ±
24.9
30.0 ±
43.0 ±
40.4 ±
36.2 ±
29.2
39.9 ±
43.4 ±
41.2 ±
39.2 ±
39.6 ±
47.4 ±
40.7 ±
40.1 ±
1.4
3.6
1.3
1.5
1.3 a
1.8 a
b
3.7 b
3.6
2.3
2.5
4.1
2.9
2.6
2.4
4.1
3.1
1.9
2.0
Follicular
Density3
(follicles/mm2)
600.0 ± 23.2
648.2 ± 62.5
603.6 ± 23.2
641.1 ± 26.8
550.0 ± 21.4
578.6 ± 30.4
523.2
457.1 ± 58.9
391.1 ± 53.6
532.1 ± 37.5
467.9 ± 39.3
594.6
428.6 ± 66.1
471.4 ± 46.4
455.4 ± 41.1
451.8 ± 37.5
546.4 ± 66.1
400.0 ± 50.0
525.0 ± 30.4
489.3 ± 32.1
Colloid
Content of
Follicles3' 5
1.83 ± 0.04
1.76 ± 0.11
1.64 ± 0.04
1.63 ± 0.05
1.66 ± 0.05
1.60 ± 0.06
1.38
1.46 ± 0.13
1.74 ± 0.12
1.81 ± 0.08
1.71 ± 0.09
1.42
1.68 ± 0.14
1.83 ± 0.10
1.97 ± 0.09
1.64 ± 0.08
1.78 ± 0.14
1.99 ± 0.11
1.87 ± 0.07
1.84 ± 0.07
*Data for Jul-Sep 1977 are not yet complete.
2Ad * adult; Ju » juvenile; M = male; F = female.
3Values in these columns are means ± SEM. Ho statistically significant differences exist between age-sex
categories within any month except Jun.
"*Means in Jun differ at the 1% level of significance if not followed by the same letter (Duncan's multiple range
test with Kramer's modification for groups with unequal numbers of observations).
5The amount of colloid was rated on a scale of 0 to 5 (none to abundant) for each gland. The data appear in
this column as Sp where p is a number between 0 and 5. The square root transformation is necessary for parametric
analysis of ordinal data (Steel, R.G.D., and J.H. Torrie. 1960. Principles and Procedures of Statistics with
Special Reference to the Biological Sciences. McGraw-Hill Book Co., New York. p. 157).
-------
in any month during 1976 and data from the same month in 1977 (Table 8.1)
and it was therefore possible in most cases to lump data for the two years
(Table 8.2).
The following trends are evident in the data:
1. Nuclear diameter, epithelial height, and colloid content of thyroid
follicles are the most sensitive histometric indicators of small
changes in thyroid activity (Tables 8.1 and 8.2).
2. The significant changes which take place in nuclear and follicular
diameter, epithelial height, and colloid content of adult thyroid glands
between April and September (Table 8.2) suggest that thyroid activity
increases during the April-June period and is high in the July-September
period (at the time of the postnuptial molt).
3. No sexual differences exist in the activity of the adult or juvenile
thyroid gland (Table 8.3).
(In some avian species, notably mallards (Hohn, 1949) and Wood Pigeons
(Ljunggren, 1968), the male gland is consistently heavier than that of
the female. In Wood Pigeons, females also have more follicles, but less
colloid than males during the breeding season. On the other hand, sexual
differences are absent in Gambel Quail (Raitt, 1968), as they appear to
be in Western Meadowlarks.)
4. Age-specific differences in thyroid activity exist only in June, when
young birds are fledging. At this time, differences in nuclear diameter,
epithelial height, and follicular diameter indicate that the juvenile
thyroid is more active than the adult gland (Table 8.3). This is not
surprising given that (1) the thyroid is involved in feather growth and
thermoregulation, and (2) the feathers of recently fledged meadowlarks
are still growing so that their insulation value is limited.
5. Significant correlations exist between every pair of histometric indices
we used to monitor the activity of adult thyroid glands. However, many
of the correlations are weak (r < ±0.45). The most highly correlated
pairs of measures are
a. nuclear diameter with
epithelial height: r = +0.81 (P < 0.01; df = 180)
b. epithelial height with the
colloid content of the gland: r = -0.61 (P < 0.01; df = 180)
c. follicular diameter with the
colloid content of the gland: r = +0.61 (P < 0.01; df = 180).
Normal Histology of the Thymus Gland of Western Meadowlarks
The thymus gland of the Western Meadowlark consists of a series of
independent lobes closely associated with the jugular veins and the trachea.
270
-------
Each lobe is a separate histological unit. We do not find the marked
histological variation between lobes of a single gland which Bacchus and
Kendall (1975) report in queleas. To the contrary, the lobes of any
meadowlarkfs thymus are relatively uniform histologically.
In general, the histology of any lobe is similar to that described by
Payne (1971) and Hodges (1974) for the domestic fowl, provided the
additional features described by Bacchus and Kendall (1975) and Kendall
(1975) for queleas are included.
The thymic parenchyma of each lobe is housed in a thin capsule of
collagen. Septa extend inward from the capsule and partially subdivide the
lobe into lobules. Short secondary septa occasionally arise from primary
septa and further subdivide the lobules into segments. Capsule and septa
are well vascularized.
The parenchyma is supported by a network of reticular cells and
presumably their fibers (which are not visible in our preparations). A
peripheral cortex is present in the lobule, presumably when the gland is
active. It tends to be sharply demarcated from the centrally located
medulla. Cells are especially numerous in the cortex. Most common here are
small lymphocytes which account for 70-90% of all cortical cells in the
meadowlark (preliminary census data). (Percentages of small lymphocytes in
the cortex of meadowlarks are roughly the same as those found by Kendall
(1975) in queleas.) Small numbers of many other cell types also occupy the
cortex: medium- and large-sized lymphocytes, erythroblasts, erythrocytes,
plasma cells, fibroblasts, pycnotic elements, and mitotic figures. The
blood supply of this area is a network of small capillaries.
Large spaces are also occasionally present in the peripheral cortex
near the capsule. They may be lymphatics or ducts of the air sac system.
They are commonly empty, although some occasionally contain laminated
concretions and homogenous droplets. Bacchus and Kendall (1975) found
similar spaces in the thymuses of queleas and called them "clear channels".
The density of the medulla is less than that of the cortex, primarily
because there are fewer cells here. However, the types of cells in the two
areas are the same. On the other hand, the medulla is more highly vasculari-
zed than the cortex and contains small veins and arterioles, in addition to
capillaries. Vacuolation is both common and widespread in reticular cells
throughout the medulla. Most of the vacuoles are intracellular, but some
large ones are not. Many contain an homogenous eosinophilic fluid. In
addition, large cysts pepper this region. Some of them are ciliated, but
none have ducts like those described by Bacchus and Kendall (1975). They
tend to be empty.
Units called Hassal's corpuscles are a constant feature of the medulla.
They are composed of large epithelioid cells with eosinophilic cytoplasm,
cytoplasmic vacuoles of various sizes, and large primitive mesenchymal-like
nuclei. Three varieties can be distinguished in the meadowlark1s thymus:
1. Early Hassal's corpuscles.—These units are small and contain few or no
cysts; if cysts are present, they are always empsty.
271
-------
2. Late Bassal's corpuscles.—These are larger and contain numerous cysts,
of which one is generally very large and surrounded by several others of
small size. Many of the cysts contain debris or cells (leucocytes and/or
erythrocytes).
3. Laminated Hassal's corpuscles,—These units are structurally similar to
the classical mammalian Hassal's corpuscle (described in Bloom and
Fawcett, 1975). They consist of concentric layers of epithelioid cells
encircling a large central cyst which is frequently filled with cells
and/or debris.
The laminated form of corpuscle is not common in meadowlarks: each gland
has only one or two such corpuscles. In contrast, numerous early and late
units occur in most thymus glands. For purposes of analysis, we have lumped
laminated corpuscles with the late variety.
The medulla also possesses large numbers of myoid or skeletal muscle
cells. They are large, tubular elements with markedly eosinophilic, fibril-
lar cytoplasm and one or more peripheral nuclei. They are scattered
individually throughout the medulla.
Variations in the Histology of the
Thymus Gland of Western Meadowlarks
Between April and September
Preliminary data concerning monthly changes in the histology of the
thymus gland, together with information concerning the effects of year, sex,
and age on the gland, appear in Tables 8.4-8.7. We have not finished the
thymus material and accordingly no statistical analyses have been done yet.
Nonetheless, some trends appear to be emerging from the data at hand
and we enumerate them here:
1. The thymus of adult meadowlarks recrudesces during the reproductive
season (May and June), and is fully developed and active when the
postnuptial molt begins (July). These tentative conclusions are
supported by the following observations:
a. the cortex began to differentiate in adult meadowlarks during
May and June (Tables 8.4 and 8.6)
b. the mitotic activity of the thymus increased perceptibly during
May and June, 1976 and 1977 (Table 8.6)
c. the thymus of adult meadowlarks increased in wet weight during
May and June, 1975 (Preston and Lewis, 1978).
2. However, a substantial number of adults still possess regressed thymuses
in May and June. This tentative conclusion is supported by the following
histological observations:
272
-------
TABLE 8.4. PRELIMINARY INFORMATION CONCERNING MONTHLY CHANGES IN THE HISTOLOGY
OF THE THYMUS GLAND OF WESTERN MEADOWLARKS (Stumella negleota)
U>
Year
1975
1976
1977
Month
May
Jun
Apr
May
Jun
Jul
Aug
Sep
Apr
May
Jun
1 n
3
1
1
5
—
3
8
5
7
49
8
Average
Number of Mitotic
Thymic Lobea Actlvitv
Evaluated
Per Bird
1.7
2.0
1.0
3.4
__-
5.0
7.1
4.8
2.9
4.6
5.6
of
Thymus2
1.0
1.0
1.0
1.2
1.7
1.5
1.0
1.0
1.2
1.1
Degree of
Differentiation
of Thymus into
Cortex and
Medulla3
1.0
1.0
2.0
1.2
— _
1.0
1.0
1.0
2.0
1.7
1.6
X-Section.al Area (cm2>
Cortex
1
0
1
1
2
2
0
1
.24
.63
__
.34 ( 3)
—
.22
.52
.10
__
.72 (19)
.12 ( 3)
Medulla
1.69
0.68
— _
0.50 ( 3)
—
1.48
1.96
1.76
— —
1.36 (19)
2.16 ( 3)
Total
2.96
1.31
6.08
1.63
—
2.70
4.47
4.87
1.13
1.48
2.53
C/M
Ratio1* 5
1.01
0.85
__
1.37
—
1.31
1.41
0.90
__
0.68
0.56
( 3)
(19)
( 3)
1 The monthly values are averages computed from birds of both sexes and two age categories (juveniles and
adults).
z'The mitotic activity of each lobe of the thymus was estimated on a scale of 0 to 5 (none to very high).
3Each lobe of the thymus was assigned the number "I" if it had a distinct cortex and medulla; the number "2"
if it lacked a distinct cortex and medulla.
''Values in parentheses in the table are numbers of observations which differ from the "n" value for the row.
5C/M Ratio * the ratio of the cross-sectional areas of the cortex (C) and medulla (M).
-------
TABLE 8.5.
PRELIMINARY INFORMATION CONCERNING MONTHLY CHANGES IN HASSAL'S CORPUSCLES
IN THE THYMUS GLAND OF WESTERN MEADOWLARKS (Stuimella negleata)
Number of Hassal's Corpuscles Per Section2
Year
1975
1976
1977
Month1
May
Jun
Apr
May
Jun
Jul
Aug
Sep
Apr
May
Jun
n
3
1
1
5
—
3
8
5
7
49
8
Early Hassal's
Corpuscles
4.7
6.5
9.0
4.6
—
9.7
21.1
25.3
11.6
19.7
42.1
Late llassal's
Corpuscles
17.3
16.0
19.0
10.2
—
19.8
26.8
26.4
11.5
18.7
25.0
Total llassal's
Corpuscles
22.0
22.5
28.0
14.8
—
23.5
47.8
51.7
23.1
38.4
67.1
Density of
Ilassal's
Corpuscles
(No. /cm2)
9.9
20.0
4.6
9.9
—
9.1
12.7
13.3
23.2
28.3
28.9
Number of
Cysts Per
Late
T'assal's
Corpuscle
2.0
3.0
3.0
2.0
—
2.7
3.0
2.4
2.7
2.9
2.8
Largest
Diameter
of
Cysts
(pm)
25.7
28.2
25.8
25.6
—
32.6
54.3
44.0
21.9
42.3
43.1
*The monthly values are averages computed from birds of both sexes and two age categories (juveniles and
adults).
2Criteria used to distinguish early and late llassal's corpuscles are modified from Bacchus and Kendall
(1975. Histological Changes Associated with Enlargement and Regression of the Thymus Glands of the
Red-billed Quelea Quelea quelea L. (Ploceidae: Heaver-birds). Phil. Trans. Roy, Soo. London Bt Biol.
Sai.t 273:65-78) and presented in detail in the text of this paper.
-------
TABLE 8.6. PRELIMINARY INFORMATION CONCERNING AGE- AND SEX-RELATED DIFFERENCES EACH MONTH
IN THE HISTOLOGY OF THE THYMUS GLAND OF WESTERN MEADOWLARKS (Stumella negleeta)
Ln
Sampling
Period1
Apr
1976-1977
May
1975-1977
Jun
1975-1977
Jul
1976
Aug
1976
Sep
1976
Age-Sex2
Ad
Ad
Ad
Ad
Ad
Ad
Ju
Ad
Ad
Ju
Ju
Ad
Ad
Ju
- M
- M
- F
- M
- F
- F
- M
- M
- F
- M
- F
- 11
- F
- F
n
8
27
30
6
3
1
2
2
1
1
4
1
2
2
Average Degree of
Number of Mitotic Differential
Thymic Lobes Activity of Thymus ir
Evaluated of Cortex and
Per Bird Thymus 3 Medulla'*
2.6
4.3
4.4
4.5
6.7
3.0
6.0
7.0
13.0
8.0
5.5
2.0
4.5
6.5
1.0
1.1
1.1
1.0
1.3
2.0
1.5
2.0
1.0
3.0
1.0
1.0
1.0
1.0
2.0
1.6
1.6
1.7
1.3
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
:ion X-Sectional Area (cm
Cortex
—
0.57 (12)
1.13 (13)
1.10 ( 2)
0.90 ( 2)
0.77
1.44
1.03
1.65
4.98
2.87
1.45
1.57
2.95
Medulla
—
1.15 (12)
1.43 (13)
1.97 ( 2)
1.61 ( 2)
0.66
1.89
0.99
1.39
3.78
2.13
1.34
2.57
3.69
2)
Total
—
1.36
1.76
2.38
2.41
1.43
3.33
2.01
3.04
8.76
4.99
2.80
4.14
6.64
C/M
Rati(
0.00
0.66
0.94
0.69
0.58
1.34
1.32
1.08
1.57
1.64
1.47
1.20
0.86
0.80
>5
(12)
(13)
( 2)
( 2)
*Data for each age-sex group collected in 1975, or 1976, through 1977 were lumped in Apr through Jun.
Data for Jul through Aug 1977 are not yet available. Values in parentheses in the table are numbers of
observations which differ from the "n" value for the row.
2Ad = adult; Ju = juvenile; M = male; F » female.
3The mitotic activity of each lobe of the thymus was estimated on a scale of 0 to 5 (none to very high).
"*Each lobe of the thymus was assigned the number "1" if it had a distinct cortex and medulla; the number "2"
if it lacked a distinct cortex and medulla.
5C/M Ratio >= the ratio of the cross-sectional areas of the cortex (C) and medulla (M).
-------
bo
TABLE 8.7, PRELIMINARY INFORMATION CONCERNING AGE- AND SEX^-RELATED DIFFERENCES EACH MONTH
IN HASSAL'S CORPUSCLES WITHIN THE THYMDS GLAND OF WESTERN MEADOWLARKS (Stuzmella
neglecta)
Number of Hassal's Corpuscles
Sampling
Period1
Apr
1976-1977
May
1975-1977
Jun
1975-1977
Jul
1976
Aug
1976
Sep
1976
Age-Sex2
Ad
Ad
Ad
Ad
Ad
Ad
Ju
Ad
Ad
Ju
Ju
Ad
Ad
Ju
- M
- M
- F
- M
- F
- F
- M
- M
- F
- M
- F
- M
- F
- F
n
8
27
30
6
3
1
2
2
1
1
4
1
2
2
Early Hassal's
Corpuscles
11.1
16.1
19.0
37.3
39.8
5.0
12.1
10.6
15.3
34.4
24.5
13.5
20.5
36.1
Late Hassal's
Corpuscles
12.4
14.4
21.0
21.6
28.7
11.7
14.8
15.5
29.1
39.1
28.7
12.5
13.4
46.4
Per Section3
Total Hassal's
Corpuscles
23.7
30.5
40.0
58.9
68.6
16.7
26.9
26.0
44.4
73.5
52.5
26.0
33.8
82.5
Density of
Ilassal * s
Corpuscles
(No. /cm2)
21.0
25.0
26.3
26.1
31.3
11.5
7.9
14.7
15.6
8.5
12.1
16.4
9.9
15.0
Number of
Cysts Per
Late
Hassal's
Corpuscle
2.8
2.8
2.7
2.7
3.0
2.0
3.0
3.0
3.0
2.0
3.3
3.0
2.0
2.5
Largest
Diameter
of
Cysts
(iJm)
22.4
33.6
45.6
36.1
52.2
94.8
31.5
48.2
64.6
53.5
55.1
19.2
28.0
77.5
*Data for each age-sex group collected in 1975, or 1976, through 1977 were lumped in Apr through Jun.
Data for Jul through Aug 1977 are not yet available.
2Ad = adult; Ju = juvenile; M = male; F = female.
'Criteria used to distinguish early and late Hassal's corpuscles are modified from Bacchus and Kendall (1975.
Histological Changes Associated with Enlargement and Regression of the Thymus Glands of the Red-billed Quelea
Quelea quelea L. (Ploceidae: Weaver-birds). Phil. Trans. Roy. Soo. London B, Biol. Sci.t 273:65-78) and
presented in detail in the text of this paper.
-------
a. the density of Hassal's corpuscles (total number per unit area of
adult gland) is substantially higher during the April-June period
than during the July-September period (Table 8,7)
b. differentiation of the cortex had not begun in April and was not
complete (i.e., average values do not equal 2.0) in all adults in
May and June (Table 8.6).
3. The thymus of adult meadowlarks remains enlarged and active between July
and at least September (when collections stopped). This tentative
conclusion is supported by the following histological observations:
a. a cortex was present in the thymuses of all adult meadowlarks
between July and September (Tables 8.4 and 3.6)
b. the density of Hassal's corpuscles x
-------
CONCLUSIONS
Tae thyroid gland of the '..'estern Meadowlark consists of secretory
follicles which are laden with colloid and lined with a simple epithelium.
Connective and vascular tissues occur between the follicles.
Five histological measures of thyroid activity were used to evaluate the
gland. Nuclear diameter and epithelial height appear to be the most sensi-
tive indicators of small changes in glandular function. Four histometric
criteria (diameter and colloid content of the follicles; diameter of epi-
thelial nuclei; and height of the follicular epithelium) indicate that the
thyroid gland of adult meadowlarks is relatively inactive during the breeding
season, becomes increasingly active during subsequent gonadal regression, and
is highly active during the period of postnuptial molt which follows. No
sexual differences exist in thyroid glands of adult or juvenile meadowlarks
during reproductive and molt periods. Age-specific differences occur only in
June when young birds are fledging. At this time, the juvenile gland is more
active than the adult gland. These conclusions are based on the examination
of thyroid glands from 363 meadowlarks collected during txvo field seasons
(1976-1977).
The thymus gland of the Western Meadowlark consists of a series of
independent lobes closely associated with the jugular veins and the trachea.
The individual lobes of each meadowlark are histologically similar to each
other. The parenchyma of the gland consists of an inner medulla and an outer
cortex, or of a medulla only. If a cortex is present, it is extremely dense
and cellular. Small lymphocytes account for 70-90% of the cells in this
region. The rest are reticular cells, medium- and large-sized lymphocytes,
erythroblasts, erythrocytes, plasma cells, fibroblasts, and mitotic and
pycnotic elements. Large spaces are also present. They are commonly empty,
but may contain laminated concretions and droplets of an homogenous fluid.
A network of small capillaries vascularizes the cortex.
The medulla is less dense than the cortex, primarily because it contains
fewer cells. However, the same cell types occur in both medulla and cortex.
Reticular cells in the medulla are commonly vacuolated. Many large extra-
cellular vacuoles and cysts are also present. They frequently contain
eosinophilic fluid. The cysts are frequently ciliated. Numerous IIassal?s
corpuscles of several kinds (early, late, laminated) and scattered individual
myoid cells also populate the medulla. Capillaries, veins, and arterioles
vascularize this region.
A preliminary survey suggests that the thymus gland of adult
meadowlarks recrudesces during the reproductive season and is fully developed
and active when the postnuptial molt begins. It remains enlarged and
functional during the molt period. Juvenile birds have larger and more
active thymus glands than molting adults. These tentative conclusions are
based on examination of thymus glands from 90 meadowlarks collected during
three field seasons (1975-1977).
278
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282
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THE EFFECTS OF CONTROLLED FIELD EXPOSURES TO S02 ON BIOLOGICAL
SYSTEMS OF THE NORTHERN GREAT PLAINS
283
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SECTION 9
TEMPORAL VARIATION IN SO2 CONCENTRATION ON ZAPS
J. J. Lee, E. M. Preston, and D. B. Weber
ABSTRACT
Sulfur dioxide concentrations on the ZAPS plots
were monitored with a real-time flame photometric
sulfur gas anlyzer during the 1976 and 1977 field
seasons. By monitoring multiple locations within same
plots, intra-plot comparisons were possible. By
monitoring comparable locations on all plots, inter-
plot comparisons were possible. Sources of uncer-
tainty in the S02 measurements are evaluated. S02
concentrations on the ZAPS plots show substantial
inter-seasonal and intra-seasonal variation. Concen-
trations are generally higher at night than during the
day, but otherwise patterns of intra-seasonal varia-
bility are not consistent between ZAPS plots or be-
tween years. Intra-season variation is greatest on
high treatment plots and least on Control plots.
Seasonal frequencies of S02 concentrations are approx-
imately log-normally distributed and show reasonably
good separation in fumigation histories of the treat-
ment plots. Though median S02 concentrations on the
Control (A) plots are small, these plots are subject
to short-term acute fumigations due to drift from
other plots. S02 concentrations are strongly corre-
lated with the inverse of wind speed and slightly
correlated with solar radiation, temperature-stability
class, and relative humidity.
INTRODUCTION
Each Zonal Air Pollution System (ZAPS) study site consists of four 0.5
hectare (1 1/4 acre) treatment plots located along a line with 61 m interven-
ing buffer zones to reduce interference between plots (see Lee and Lewis,
1978). Sulfur dioxide (S02) concentrations are continually measured at vari-
ous standard locations on ZAPS I and ZAPS II (Figure 9.1) throughout the
growing season. While not all locations on all plots are monitored, location
c^ is used on all plots, providing a basis for inter-plot comparisons. Use of
multiple locations within some plots allows intra-plot comparisons.
284
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20'
20
70'
70'
70'
70'
Q
•
70'
70'
70'
240'
28 O'
c
s
H
V
COMPRESSOR
SULFUR DIOXIDE TANKS
I KW HEATER
VALVE
I" Al PIPE, 1/32" HOLES
EVERY 10*
I" Al PIPE, NO HOLES
SAMPLERS
Figure 9.1. Standard probe locations,
285
-------
SC>2 flow rates from the SC-2 tanks to the delivery pipes were essentially
the same in 1976 and 1977 as in 1975, namely 0, 0.7, 1.7, and 3.3 standard
liters per minute on plots A, B, C, and D, respectively. Concentrations
varied stochastically according to micrometeorological conditions.
In this section, we describe data collection and synthesis procedures and
discuss sources of uncertainty in the S02 measurements. We present averages
and peaks observed during the 1976 and 1977 field seasons, as well as the
results of investigating the variation of S02 concentrations with micrometeor-
ological variables.
MATERIALS AND METHODS
Design of the Monitoring System
Figure 9.2 is a schematic diagram of the S02 monitoring system. S02
concentrations on the plots were monitored by recording the output from a
Meloy model SA160-2 flame photometric sulfur gas analyzer operating in loga-
rithmic mode. Samples were continuously drawn through teflon tubing extending
to the monitoring locations by a time-share device (Adgo Co.). The continuous
streams travel to the solenoids where they are diverted either to the sulfur
gas analyzer via the sample manifold or out the exhaust via the common mani-
fold. A stepping switch in the time share device provides 7.5 minutes of
continuous electrical energy per hour to each of the solenoids sequentially-
During this 7.5 minutes, the energized solenoid directs the incoming sample
gas into the sample manifold while the remaining seven non-energized solenoids
divert sample gas through the common manifold to the exhaust. Gas flow
through the line being sampled is produced by the sulfur gas analyzer while
gas flow through the remaining seven lines is maintained by the common mani-
fold pump.
The sulfur gas analyzer was calibrated against NBS-SRM 1627 permeation
tubes using either a Model 303 gas mixing system (Analytical Instrument Devel-
opment, Inc.) or a Model 330 Dynacalibrator (Metronics).
Sources of Uncertainty in SC>2 Measurements
Response Characteristics of the System
Several factors affect the time required for the monitoring system to
respond to change in S0£ concentrations on the sample plots. First, as sample
line length increases, the time required for the sample to reach the analyzer
increases. During 1975, 1976, and 1977, sample line length varied from 98
meters to 299 meters. Gas streams produced by the common manifold pump take
less than 5 minutes to reach the time-share device. Secondly, teflon sample
lines with two different wall thicknesses were used. The thinner tubing has a
longer response time due to larger cross-sectional area for transport through
the lines. Thirdly, the system responds more quickly to higher sulfur levels
than to low ones. Fourthly, response time is influenced by the degree of S02
conditioning of the teflon sample lines. Lines which have been conditioned
longer respond more quickly than those conditioned for a shorter period.
286
-------
OO
ANALYZER
SAMPLE LINES
SAMPLE MANIFOLD-
SAMPLE LINES
SOLENOIDS
COMMON
MANIFOLD
COMMON
MANIFOLD
PUMP
EXHAUST
Figure 9.2. Schematic diagram of the sulfur analyzer hookup with sample lines from the field
in operation at the ZAPS study site.
-------
Therefore, response time is probably somewhat longer earlier in the season
than later in the season. Since response time is influenced by several
factors in ways difficult to quantify, no comprehensive scheme of response
characteristics is attempted. It can be said, however, that fine time detail
(instantaneous peaks) are not measurable by the system. Line lengths were
equalized at the start of the 1978 field season. This should make response
characteristics at different measuring points somewhat more similar.
Non-linearity of Calibration Curves
Calibration curves relating analyzer response to the logarithm of S02
concentration typically became non-linear at S02 concentrations below roughly
2 pphm. Available calibration equipment did not permit determination of the
precise nature of the non-linearity. Since linear extrapolation on these
calibration curves to zero analyzer response lead to estimated S02 concentra-
tions equal to or greater than 0.9 pphm, it is highly probable that linear
extrapolation from calibration curves leads to an overestimate of true S02
levels in the region between 0 pphm and 2 pphm. The true value, in nearly all
cases, will lie between 0.1 pphm (probable background concentrations) and the
value estimated from the calibration curve. These values were used to specify
upper and lower bounds for any S02 concentration falling in the questionable
region of the calibration curves.
Carbon Dioxide Interference During Calibration With the Metronics Calibrator
It has recently been shown that carbon dioxide concentration signifi-
cantly affects the response characteristics of FPD sulfur gas analyzers (Weber
et a1.> 1978). Carbon dioxide depresses response by a factor log proportional
to C02 concentration (Weber et at. , 1978).
Two calibration devices have been used on the ZAPS monitors. The first,
manufactured by Analytical Instrument Development Inc., was used on ZAPS I
previous to May 25, 1977 and on ZAPS II previous to May 27, 1977. This cali-
brator uses a tank of compressed air as a carrier for creating the calibration
gas. Tank air contains C02 levels similar to ambient levels.
A second device, which uses the air inside the monitoring shed as a
carrier for the calibration gas (Metronics) has been used since June 1977. In
the monitoring shed with one person performing an S02 calibration, we measured
C02 levels of roughly 485 ppm. Ambient C02 concentration is roughly 330 ppm.
The degree of C02 interference during past calibrations is impossible to
quantify precisely, since C02 levels present in the monitoring shed during
previous calibrations are not precisely known. Upper bounds for the C02
interference effect have been estimated assuming a C02 level of 485 ppm during
all calibrations using the Metronics Dynacalibrator. Calibration curves can
then be corrected for this interference using relationships defined by Weber
et at. (1978). The problem was solved during the 1978 field season by attach-
ing Metronics' pump inlets to tubing running to external air.
288
-------
Dilution of Sample Due to Leaks in Sample Lines
Any leaks in sample lines will cause sample dilution and cause errors in
estimates of sample S02 levels. Sample lines were walked regularly to check
by visual inspection for holes caused by small mammals, researcherl, etc
Dunng 1978, we checked for leaks in sample lines with vacuum measurement.
This procedure demonstrated that small leaks could go undetected by the pre-
viously utilized Visual inspection method. Thus, small errors could have been
introduced through undetected leaks in sample lines during 1976 and 1977
However, sample lines were checked regularly and carefully by visual inspec-
tion and it is unlikely that substantial S02 measurement errors were intro-
duced by sample line leaks.
Uncertainties Introduced During Data Transcription
Response of the sulfur gas analyzers to S02 is recorded continuously on
analog strip charts. Comparisons of data obtained by direct readout from a
digital voltmeter with data transcribed from strip charts indicate that analog
data can be converted to digital data with error limits of ± 3%.
The Average chart value (millivolts) used is that which balances curve
length; i.e., total curve length above this point equals total curve length
below this point for the 7.5 minute sample interval. Since the S02 analyzer
output is linear in the logarithm of the concentration, this estimates the
average logarithm. Assuming log-normality, this is the best estimate of the
median logarithm, and thus of the median rather than average concentration.
The adequacy of this procedure was tested by short term, intensive study.
Several points were recorded for each 7.5 minute interval for ZAPS I from
April 16 through April 23, 1977. For each interval, the average and median of
these points was compared to the "equal length" value. The results (Table
9.la) indicate that the three procedures are equivalent, and that the "equal
length" measurement adequately estimates the average scale reading.
TABLE 9.la. RELATIONS BETWEEN EQUAL CURVE LENGTH, MEDIAN, AND AVERAGE SCALE
READINGS, ZAPS II, PROBE Dd, 4/16/76 - 4/23/76
y = average scale reading
xi = "equal curve length" scale reading
X2 = median scale reading
Regression: Ey = ax.
xi a r
xi .9947 .9990 .9981
x2 1.0013 .9989 .9978
289
-------
Uncertainty Introduced by Using 7,5 Minute Median, Rather Then Average,
Concentrations Obtained from the Above Intensive Study
A regression of average concentrations with the median concentrations
(Table 9.1b) indicates that the 7.5 minute median is approximately 2% less
than the corresponding 7.5 minute average. Since, for log-normal distribu
tions,
Mean = (median) e 2 ,
where a = In (SGD),
this implies a SGD of 1.22 for time intervals of less than 7.5 minutes. This
low value is close to the theoretical minimum SGD of 1.0, and reflects the
high correlation between concentrations over short time intervals.
TABLE 9.1b. COMPARISON OF 7.5 min MEDIAN AND AVERAGE S02 CONCENTRATIONS, ZAPS
II, PROBE Dd, 4/16/76 - 4/23/76
Y = Average S02 Concentration
X = Median S02 Concentration
Ey = Ax
A = 1.021 ± .003
r = .9996
r2 = .9991
Variable Vacuums Between Sample Lines
As previously noted during 1976 and 1977, sample line lengths to differ-
ent monitoring positions varied. As the analyzer pump attempts to draw sample
air through the line a vacuum is created whose magnitude is proportional to
line length. The magnitude of this vacuum influences analyzer response.
Since every sample line had a unique length, each also had a unique calibra-
tion curve. However, a common calibration curve for all sample lines was
assumed in estimating S02 levels. Measurements of the effect on analyzer
response of vacuums generated by different line lengths demonstrated that
errors introduced by assuming a common calibration curve for each line are
generally less than 3%.
Synthesis Procedures
At each ZAPS site, a total of eight sample lines feed to a time-share
device. These lines are selected sequentially, so that any one line is con-
nected to the S02 analyzer for a single 7.5 minute interval each hour. The
output from the analyzer, which is linear in the logarithm of the concentra-
tion, is continuously recorded on a strip chart. One of the lines passes
through a zero-S02 filter, providing a check for drift. The other seven
probes are located on the plots, with at least one probe per plot.
290
-------
The 7.5 minute averages for each probe are used directly to estimate
weekly, monthly and seaonal geometric means (GM), standard geometric devia-
tions (SGD), and arithmetic means (AM). To estimate the sequence of 1-hr,
3-hr, and 24-hr averages, we need continuous readings for each probe. These
are estimated using the concentrations for each 7.5 minute interval concentra-
tion at the probe being monitored. The synthesis procedure thus consists of
five major steps:
(1) Obtain average S02 concentrations for each 7.5 minute interval for
probe being monitored.
(2) Use (1) to estimate concentrations at standard probe.
(3) Calculate hourly and longer average concentrations at standard
probe.
(.4) Use (3) to estimate average concentrations at other probes.
(5) Form weekly GM's and SGD's of the 1-hr, 3-hr, and 24-hr averages;
also, keep account of violations of Federal and State air quality
standards.
A generalized flow chart for the synthesizing computer program is shown
in Figure 9-3.
The first major step consists of reading average values for each interval
from the strip chart, subtracting the zero-filter reading (usually zero) to
allow for drift, and entering this value into the calibration equations.
Since errors in S02 concentration estimates caused by COa interference
and non-linearity of calibration curves cannot be expressed as simple percent-
ages of estimated concentrations, each strip chart average was entered into
two calibration equations. In one, the HIGH run, the calibration equation was
adjusted to yield a maximum estimate that could result from from the above
sources of uncertainty. In the other, the LOW run, the calibration equation
was adjusted to yield the corresponding minimum estimate. Summary statistics
were computed for both the HIGH run and LOW run. The range of values presen-
ted in RESULTS AND DISCUSSION brackets the true values.
The second major step is accomplished by scaling all data to the same
geometric mean. After all data for a week are read, the GM's for all probes
for that week are calculated. The concentration for each 7.5 minute interval
for the standard probe, s, is estimated by multiplying the measured concentra-
tion at probe i by the ratio of weekly GM's,
GM
(1) C (est) = C (jaeas) ^~- -
S 1 \jli^
This is equivalent to centering the normal distributions of logarithms at the
same value. Earlier analysis of ZAPS data indicated that S02 concentrations
at various locations (except for the control plot) varied similarly when
291
-------
OUTPUT DAILY ^_
SUMMARY ^
READ 7.5-MIN AVERAGE SCALE VALUES
FOR ALL PROBES FOR A GIVEN HOUR
SUBTRACT FILTER READING FROM EACH
PROBE AVERAGE TO OBTAIN CORRECTED
VALUE
OBTAIN 7.5-MIN MEDIAN S02 CONCENTRA-
TIONS FROM CALIBRATION EQUATION
'AND CORRECTED VALUES .
V
I STORE MEDIAN CONCENTRATIONS
CALCULATE WEEKLY GM I
FOR EACH PROBE I
\
f
-^RECALL DATA FOR A
ESTIMATE 7.5-MIN MEDIANS AT
STANDARD PROBE, s, FROM OTHER
PROBES, 1
GM,
C (est) = C- (obs) -^f-
\f
CALCULATE HOURLY AVERAGES AT
STANDARD PROBE
, 8n
C, = ± i Ce .
' 8n-5 5'J
CALCULATE THREE-HOUR AVERAGES AT
STANDARD PROBE FROM HOURLY
AVERAGES
1 3m
C " '
CALCULATE 24-HOUR AVERAGE AT i
STANDARD PROBE FROM 3-HR. AVERAGES;
8
8
CALCULATE AVERAGES AT NON-STANDARD
PROBES i FROM STANDARD PROBE s
ave
ave
Figure 9.3. Flow chart of data synthesis procedures,
292
-------
normalized to the same^M (Lee and Lewis, 1978). This procedure is consistent
with most models of pollutant dispersion, in which the concentration ™ esti-
The estimated 7.5 minute medians at the standard probe are combined into
averages for non-overlapping time intervals of one hour and longer For
example, for a given day, all 7.5 minute medians between midnight and 1 a.m
are averaged, all those between 1 a.m. and 2 a.m., etc. This standard pro-
cedure (Larsen, 1971) yields 24 one-hour averages, 3 eight-hour averages, and
1 24-hour average per day. Averages for each non-standard probe, i, are
estimated by multiplying the standard averages by the ratio GM.: GM
i s
Concentrations for the plot receiving no direct S02 input (the Control
plot, A) are excluded from this averaging process since these were usually
below the detection threshold of the analyzer. For this probe, the 7.5 minute
median is used to represent the entire hour, and 3-hour and 24-hour averages
are based on these. Averages for this probe are thus much more sensitive to
short term fluctuations, and consequently less reliable, than averages for
other probes.
RESULTS AND DISCUSSION
Interseasonal Trends
The seasonal data summaries are given in Table 9.2, as are the 1-hour,
3-hour, and 24-hour peaks experienced during each season. The frequency of
violations of Montana and Federal S02 standards during the growing seasons are
also provided. Results are shown for both the High and Low run. Although S02
flow rates were not changed, both average and peak concentrations were gener-
ally higher in 1977 than in 1976 for ZAPS I. While median concentrations on
ZAPS II were similar in 1976 and 1977, individual measurements were more
variable in 1977.
Intraseasonal Trends
Sulfur dioxide concentrations varied considerably during the course of
each growing season (Figure 9.4). The D-plots are particularly variable.
Data for the 1977 field season, ZAPS I, Plot C seemed unusually high compared
to those for 1975, 1976, and ZAPS II, C. Additional evidence presented in
Section 10 (Figure 10.11) suggests that these values were artificially high.
Values shown have been adjusted as described in Section 10. ZAPS II seems to
have had a somewhat more uniform fumigation history than ZAPS I.
Frequency Distributions of S02 Concentrations on the Plots
Frequency distributions of S02 concentrations on the ZAPS plots are
approximately log-normal (Figure 9.5). Deviation from log-normality appears
to have increased in 1977 compared to 1976 on both ZAPS I and ZAPS II. Cumu-
lative frequency distributions for different treatment plots are generally
distinct while distributions for various points monitored within a treatment
293
-------
TABLE 9.2a. ZAPS I SEASONAL SUMMARY, 1976
(pphm S02)
Probe Ac 6M = .2-.9 SGD = 3,0, 1.5 Arithmetic Mean = .5-1.1
1-Hour Ave Exceeded 25 pphm 0 Times: 0 Percent
3-Hour Ave Exceeded 50 pphm 0 Times: 0 Percent
24-Hour Ave Exceeded 10 pphm 0 Times: 0 Percent
24-Hour Ave Exceeded 14 pphm 0 Times: 0 Percent
1-Hour Peak 13-13 3-Hour Peak 7.6-7.8 24-Hour Peak 2.4-3.1
Probe Bd GM = 1.4-1.9 SGO = 3.8, 2.2 Arithmetic Mean = 2.9-3.0
1-Hour Ave Exceeded 25 pphm 25-29 Times: .7-.8 Percent
3-Hour Ave Exceeded 50 pphm 1-1 Times: .1 Percent
24-Hour Ave Exceeded 10 pphm 2-2 Times: 1.3 Percent(a)
24-Hour Ave Exceeded 14 pphm 1-1 Times: .6 Percent
1-Hour Peak 45-50 3-Hour Peak 28-32 24-Hour Peak 9,7-10.6
Probe Be GM = 1.8-2.2 SGD = 3.6, 2.5 Arithmetic Mean = 3.9-4.0
1-Hour Ave Exceeded 25 pphm 22-35 Times: .6-1.0 Percent
3-Hour Ave Exceeded 50 pphm 1-1 Times: .1 Percent
24-Hour Ave Exceeded 10 pphm 1-2 Times: .6-1.3 Percent(c)
24-Hour Ave Exceeded 14 pphm 1-1 Times: .6 Percent
1-Hour Peak 61-63 3-Hour Peak 37-40 24-Hour Peak 9.5-11.6
Probe Bb GM = 1.4-1.9 SGD = 3,6, 2.3 Arithmetic Mean = 2.9-3.0
1-Hour Ave Exceeded 25 pphm 11-19 Times: .3-.5 Percent
3-Hour Ave Exceeded 50 pphm 1-1 Times: .1 Percent
24-Hour Ave Exceeded 10 pphm 1-1 Times: .6 Percent
24-Hour Ave Exceeded 14 pphm 1-1 Times: .6 Percent
1-Hour Peak 41-51 3-Hour Peak 25-33 24-Hour Peak 7.0-9,6
Probe Cc GM = 3.7-3.9 SGO = 3.1, 2.7 Arithmetic Mean = 7.3-7.3
1-Hour Ave Exceeded 25 pphra 131-166 Times: 3.8-4.8 Percent(a)
3-Hour Ave Exceeded 50 pphm 9-14 Times: .8-1.2 Percent(b)
24-Hour Ave Exceeded 10 pphm 27-32 Times: 17.2-20.4 Percent(a)
24-Hour Ave Exceeded 14 pphm 8-14 Times: 5.1-8,9 Percent(b)
1-Hour Peak 127-162 3-Hour Peak 82-99 24-Hour Peak 27-30
Probe DC GM = 6.5-6.7 SGD = 2.9, 2.5 Arithmetic Mean = 11.4-11.4
1-Hour Ave Exceeded 25 pphm 363-431 Times: 10.5-12.4 Percent(a)
3-Hour Ave Exceeded 50 pphm 43-54 Times: 3.7-4.6 Percent(b)
24-Hour Ave Exceeded 10 pphm 71-82 Times: 45.2-52.2 Percent(a)
24-Hour Ave Exceeded 14 pphm 51-53 Times: 32.5-33,8 Percent(b)
1 Hour Peak 264-353 3-Hour Peak 171-216 24-Hour Peak 60-74
Probe Db GM = 5.8-6.1 SGD = 3.2, 2.8 Arithmetic Mean = 11.7-11,7
1-Hour Ave Exceeded 25 pphm 335-394 Times: 9.7-11.4 Percent(a)
3-Hour Ave Exceeded 50 pphm 40-49 Times: 3.4-4.2 Percent(b)
24-Hour Ave Exceeded 10 pphm 65-74 Times: 41.4-47.1 Percent(a)
24-Hour Ave Exceeded 14 pphm 46-50 Times: 29.3-31.8 Percent(b)
1-Hour Peak 234-313 3-Hour Peak 157-222 24-Hour Peak 59-73
(a) violates Montana standards
(b) violates Federal standards
(c) possible violation of Montana standards
294
-------
TABLE 9.2b. ZAPS II SEASONAL SUMMARY, 1976
(pphm S02)
Probe Ac GM = .2-1.4 SGD = 3.4, 1.2 Arithmetic Mean = .5-1.4
1-Hour Ave Exceeded 25 pphm 0 Times: 0 Percent
3-Hour Ave Exceeded 50 pphm 0 Times: 0 Percent
24-Hour Ave Exceeded 10 pphm 0 Times: 0 Percent
24-Hour Ave Exceeded 14 pphm 0 Times: 0 Percent
1-Hour Peak 6.0-6.0 3-Hour Peak 3.9-3.9 24-Hour Peak 1.7-1.7
Probe Be GM = 2.6-2.9 SGD = 2.3, 1.8 Arithmetic Mean = 3.7-3.7
1-Hour Ave Exceeded 25 pphm 9-9 Times: .24 Percent
3-Hour Ave Exceeded 50 pphm 0 Times: 0 Percent
24-Hour Ave Exceeded 10 pphm 2-3 Times: 1.2-1.7 Percent(a)
24-Hour Ave Exceeded 14 pphm 1-1 Times: .6 Percent
1-Hour Peak 68-74 3-Hour Peak 40-43 24-Hour Peak 15-16
Probe Bb GM = 2.6-2.9 SGD = 2.5, 1.9 Arithmetic Mean = 4.0-4.0
1-Hour Ave Exceeded 25 pphm 8-9 Times: .2-.2 Percent
3-Hour Ave Exceeded 50 pphm 0 Times: 0 Percent
24-Hour Ave Exceeded 10 pphm 2-3 Times: 1.2-1.7 Percent(a)
24-Hour Ave Exceeded 14 pphm 0 Times: 0 Percent
1-Hour Peak 60-62 3-Hour Peak 35-36 24-Hour Peak 13-14
Probe Cc GM = 4.1-4.4 SGD = 2.3, 1.9 Arithmetic Mean = 5.5-5.5
1-Hour Ave Exceeded 25 pphm 59-63 Times: 1.6-1.7 Percent(a)
3-Hour Ave Exceeded 50 pphm 2-2 Times: .2 Percent
24-Hour Ave Exceeded 10 pphm 12-16 Times: 7.0-9.3 Percent(a)
24-Hour Ave Exceeded 14 pphm t 5-5 Times: 2.9 Percent(b)
1-Hour Peak 110-125 3-Hour Peak 67-72 24-Hour Peak 24-27
Probe Cb GM = 4.0-4.3 SGD = 2.5, 2.0 Arithmetic Mean = 5.8-5.9
1-Hour Ave Exceeded 25 pphm 43-47 Times: 1.2-1.3 Percent(a)
3-Hour Ave Exceeded 50 pphm 1-1 Times: .1 Percent
24-Hour Ave Exceeded 10 pphm 9-10 Times: 5.2-5.8 Percent(a)
24-Hour Ave Exceeded 14 pphm 1-1 Times: .6 Percent
1-Hour Peak 87-87 3-Hour Peak 59-60 24-Hour Peak 19-19
Probe DC GM = 6.4-6.9 SGD = 3.0, 2.3 Arithmetic Mean = 10.6-10.6
1-Hour Ave Exceeded 25 pphm 286-289 Times: 7.8-7.8 Percent(a)
3-Hour Ave Exceeded 50 pphm 11-14 Times: .9-1.1 Percent(b)
24-Hour Ave Exceeded -10 pphm 72-72 Times: 41.9 Percent (a)
24-Hour Ave Exceeded 14 pphm 37-38 Times: 21.5-22.1 Percent(b)
1-Hour Peak 199-225 3-Hour Peak 117-130 24-Hour Peak 44-48
Probe Db GM = 7.0-7.5 SGD = 3.3, 2.7 Arithmetic Mean = 14.0-14.0
1-Hour Ave Exceeded 25 pphm 366-371 Times: 9.9-10.0 Percent(a)
3-Hour Ave Exceeded 50 pphm 12-14 Times: 1.0-1.1 Percent b
24-Hour Ave Exceeded 10 pphm 83-84 Times: 48.8-48.3 Percent a
24-Hour Ave Exceeded 14 pphm 46-47 Times: 26.7-27.3 Percent(b)
1-Hour Peak 193-218 3-Hour Peak 113-126 24-Hour Peak 43-47
(a) violates Montana standards
(b) violates Federal standards
295
-------
TABLE 9.2c. ZAPS I SEASONAL SUMMARY, 1977
(pphm S02)
Probe Ac GM = .2-1.6 SGD = 4.5, 1.7 Arithmetic Mean = 1.1-2.1
1-Hour Ave Exceeded 25 pphm 2-5 Times: O-.l Percent
3-Hour Ave Exceeded 50 pphm 0 Times: 0 Percent
24-Hour Ave Exceeded 10 pphm 0 Times: 0 Percent
24-Hour Ave Exceeded 14 pphm 0 Times: 0 Percent
1-Hour Peak 26-28 3-Hour Peak 20-21 24-Hour Peak 3.6-4.6
Probe Bd GM = 3.5-3.7 SGD =2.1, 2.4 Arithmetic Mean = 5.3-5.5
1-Hour Ave Exceeded 25 pphm 70-104 Times: 1.7-2.5 Percent(a)
3-Hour Ave Exceeded 50 pphm 0 Times: 0 Percent
24-Hour Ave Exceeded 10 pphm 9-15 Times: 5.0-8.8 Percent(a)
24-Hour Ave Exceeded 14 pphm 1-2 Times: 5.1 Percent(d)
1-Hour Peak 55-66 3-Hour Peak 40-48 24-Hour Peak 15-16
Probe Be GM = 3.2-3.4 SGD = 2.2, 2.1 Arithmetic Mean = 4.6-4.8
1-Hour Ave Exceeded 25 pphm 68-85 Times: 1.6-2.0 Percent(a)
3-Hour Ave Exceeded 50 pphm 0 Times: 0 Percent
24-Hour Ave Exceeded 10 pphm 9-11 Times: 5.0-6.1 Percent(a)
24-Hour Ave Exceeded 14 pphm 3-5 Times: 1.6-2.8 Percent(b)
1-Hour Peak 51-56 3-Hour Peak 38-41 24-Hour Peak 19-21
Probe Bb GM = 3.7-3.9 SGD = 2.5, 2.4 Arithmetic Mean = 6.0-6.3
1-Hour Ave Exceeded 25 pphm 92-122 Times 2.2-2.9 Percent(a)
3-Hour Ave Exceeded 50 pphm 0 Times: 0 Percent
24-Hour Ave Exceeded 10 pphm 15-22 Times: 8.3-12.1 Percent(a)
24-Hour Ave Exceeded 14 pphm 3-4 Times: 1.7-2.2 Percent(b)
1-Hour Peak 57-66 3-Hour Peak 42-48 24-Hour Peak 18-19
Probe Cc GM = 5.3-5.6 SGD = 2.7 , 2.7 Arithmetic Mean = 9.5-10.2
1-Hour Ave Exceeded 25 pphm 289-333 Times: 6.9-7.9 Percent(a)
3-Hour Ave Exceeded 50 pphm 4-10 Times: .3-.7 Percent(b)
24-Hour Ave Exceeded 10 pphm 57-62 Times: 31.5-34.3 Percent(a)
24-Hour Ave Exceeded 14 pphm 21-24 Times: 11.6-13.3 Percent(b)
1-Hour Peak 98-102 3-Hour Peak 64-71 24-Hour Peak 32-36
Probe DC GM = 8.3-9.4 SGD = 3.1, 2.5 Arithmetic Mean = 14.1-15.3
1-Hour Ave Exceeded 25 pphm 606-677 Times: 14.4-16.1 Percent(a)
3-Hour Ave Exceeded 50 pphm 43-66 Times: 3.0-4.7 Percent(b)
24-Hour Ave Exceeded 10 pphm 120-126 Times: 66.3-69.6 Percent(a)
24-Hour Ave Exceeded 14 pphm 72-85 Times: 39.8-47.0 Percent(b)
1-Hour Peak 137-161 3-Hour Peak 96-116 24-Hour Peak 43-51
Probe Db GM = 7.0-7.5 SGD = 2.6, 2.5 Arithmetic Mean = 11.5-12.5
1-Hour Ave Exceeded 25 pphm 487-553 Times: 11.6-13.2 Percent(a)
3-Hour Ave Exceeded 50 pphm 40-50 Times: 2.8-3.5 Percent(b)
24-Hour Ave Exceeded 10 pphm 92-95 Times: 50.8-52.5 Percent(a)
24-Hour Ave Exceeded 14 pphm 48-57 Times: 26.5-31.5 Percent(b)
1-Hour Peak 120-147 3-Hour Peak 88-104 24-Hour Peak 51-61
(a) violates Montana standards
(b) violates Federal standards
(c) possible violation of Montana standards
(d) possible violation of Federal standards
296
-------
TABLE 9.2d. ZAPS II SEASONAL SUMMARY, 1977
(pphm S02)
Probe Ac GM = .4-1.6 S6D = 4.2, 1.2 Arithmetic Mean = 1.0-1.6
1-Hour Ave Exceeded 25 pphm 2.0 Times: .05 Percent
3-Hour Ave Exceeded 50 pphm 0 Times: 0 Percent
24-Hour Ave Exceeded 10 pphm 0 Times: 0 Percent
24-Hour Ave Exceeded 14 pphm 0 Times: 0 Percent
1-Hour Peak 33-38 3-Hour Peak 12-14 24-Hour Peak 3.0-3.4
Probe Be GM = 2.9-3.0 SGD = 2.1, 1.9 Arithmetic Mean = 4.1-4.3
1-Hour Ave Exceeded 25 pphm 42-68 Times: 1.1-1.7 Percent(a)
3-Hour Ave Exceeded 50 pphm 0 Times: 0 Percent
24-Hour Ave Exceeded 10 pphm 4-10 Times: 2.2-5.5 Percent(a)
24-Hour Ave Exceeded 14 pphm 0-2 Times: 0.0-1.1 Percent
1-Hour Peak 66-83 3-Hour Peak 38-45 24-Hour Peak 13-15
Probe Bb GM = 3.0-3.2 SGD = 2.5, 2.2 Arithmetic Mean = 5.1-5.4
1-Hour Ave Exceeded 25 pphm 55-85 Times: 1.4-2.1 Percent(a)
3-Hour Ave Exceeded 50 pphm 0-2 Times: 0.0-0.2 Percent(d)
24-Hour Ave Exceeded 10 pphm 7-14 Times: 3.9-7.7 Percent(a)
24-Hour Ave Exceeded 14 pphm 3-3 Times: 1.7 Percent(b)
1-Hour Peak 86-112 3-Hour Peak 46-57 24-Hour Peak 16-20
Probe Cc GM = 4.7-4.9 SGD = 2.2, 2.1 Arithmetic Mean = 6.7-7.6
1-Hour Ave Exceeded 25 pphm 233-274 Times: 5.8-6.8 Percent(a)
3-Hour Ave Exceeded 50 pphm 5-8 Times: .4-.6 Percent(b)
24-Hour Ave Exceeded 10 pphm 47-50 Times: 26.0-27.6 Percent(a)
24-Hour Ave Exceeded 14 pphm 14-20 Times: 7.7-11.0 Percent(b)
1-Hour Peak 123-160 3-Hour Peak 82-99 24-Hour Peak 28-32
Probe Cb GM = 4.6-4.8 SGD = 2.3, 2.3 Arithmetic Mean = 7.0-7.4
1-Hour Ave Exceeded 25 pphm 237-279 Times: 5.9-7.0 Percent(a)
3-Hour Ave Exceeded 50 pphm 6-7 Times: .4-.5 Percent(b)
24-Hour Ave Exceeded 10 pphm 46-49 Times: 25.4-27.1 Percent(a)
24-Hour Ave Exceeded 14 pphm 16-19 Times: 8.8-10.5 Percent(b)
1-Hour Peak 118-152 3-Hour Peak 74-88 24-Hour Peak 25-29
Probe DC GM = 7.5-8.2 SGD = 2.7, 2.4 Arithmetic Mean = 11.9-13.0
1-Hour Ave Exceeded 25 pphm 493-540 Times: 12.3-13.5 Percent(a)
3-Hour Ave Exceeded 50 pphm 35-55 Times: 2.6-4.0 Percent(b)
24-Hour Ave Exceeded 10 pphm 100-108 Times: 55.3-59.7 Percent(a)
24-Hour Ave Exceeded 14 pphm 62-67 Times: 34.2-37.0 Percent(b)
1-Hour Peak 191-253 3-Hour Peak 150-186 24-Hour Peak 50-61
Probe Db GM = 7.2-8.1 SGD = 3.3, 2.8 Arithmetic Mean = 15.0-16.9
1-Hour Ave Exceeded 25 pphm 479-548 Times: 12.0-13.7 Percent(a)
3-Hour Ave Exceeded 50 pphm 42-56 Times: 3.1-4.1 Percent(b)
24-Hour Ave Exceeded 10 pphm 93-102 Times: 51.4-56.4 Percent(a)
24-Hour Ave Exceeded 14 pphm 61-72 Times: 33.7-39.8 Percent(b)
1-Hour Peak 217-290 3-Hour Peak 186-235 24-Hour Peak 63-77
(a) violates Montana standards
(b) violates Federal standards
(c) possible violation of Montana standards
(d) possible violation of Federal standards
297
-------
to
V£>
CO
a
1975
1976
1977
o A plot
B plot
a C plot
• D plot
APR MAY JUN JUL AUG SEP OCT APR MAY JUN JUL AUG SEP OCT
MONTH
Figure 9.4. Intra-seasonal variation in S02 concentrations on the ZAPS plots (High run)
-------
100
ZAPS I
ZAPS n
MD
0,01 O.I I
10 ' 50 90 99 99.9 0.01 O.I I 10 50 90
CUMULATIVE FREQUENCY ABOVE GIVEN CONCENTRATION
99 99.9 99.99
Figure 9.5
Cumulative frequency distributions of 862 concentrations at various locations on the ZAPS
plots (Low run).
-------
plot approximate each other. Separation of cumulative frequency distributions
of different treatments plots is greatest near median concentrations and least
at the extremely high and low concentrations. On ZAPS I, frequencies of high
S02 concentrations in the C and D treatment plots converged during 1977. On
ZAPS II, frequencies of high concentrations on plot B, monitoring location b_
converged with those of plot C during both 1976 and 1977.
Diel Patterns
The diel pattern at location c_, averaged over each season, is shown in
Figure 9.6. Each point represents the seasonal GM of all 7.5 minute averages
occurring during a particular hour of the day. The unusually high concentra-
tions observed on ZAPS I, C in 1977 were apparently caused by a monitoring
problem during part of the season. Figure 9.7 shows the corresponding SGD's
for ZAPS II, 1977. Nocturnal concentrations are typically higher and more
variable than diurnal concentrations.
Effect of Micrometeorological Variables on Real Time S02 Concentrations
We have generally assumed that ZAPS S02 concentrations varied with micro-
meteorological conditions. We have examined this relation for ZAPS II for the
period April 17 through June 25, 1977. The variables considered were hourly
averages of:
C SOz concentration pphm
U wind speed kmph
SR scale reading proportional to
solar radiation volts
R relative humidity %
I temperature-stability class unitless
Variable I was determined by the difference, AT, between the air and ground
temperature as follows:
AT < - 1°F ,1=1 "Unstable"
-1° F <_ A T <_ 1° F, I = 2 "Neutral"
AT>1°F ,1=3 "Stable"
Except for R, these variables are generally considered important determinants
of large scale pollutant dispersion (Turner, 1969). Wind speed is usually the
most important variable, primarily due to direct dilution, but also to the
generally increased rate of vertical (turbulant) mixing with higher wind
speeds. I and SR are typically used to classify vertical mixing conditions
with more stable conditions (poor mixing and higher concentrations) being
associated with higher I values and lower SR values. R was included to test
whether relative humidity could significantly affect S02 concentrations by
affecting surface sorption of S02 .
The results of linear regressions of these variables with concentration
are given in Table 9.3a. As expected, inverse wind speed (1/U) was most
important, explaining 38% of the variability of C. Solar radiation (SR) was
next in importance, accounting for another 6.5% of the variability. Variable
300
-------
10
Q.
Q.
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_ D
A A
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ZAPS I, 1976
n a
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9
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16
18
20 22
24
15
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• n
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1 1 1 1 1
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n
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1 I
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ZA
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8 10 12 14
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16
18
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22
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ZA
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A A A A A A g ••••
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0
8 10 12 14
Hour of Day
16
18
20 22
24
15
| 10
a.
a.
• —
5 5
o
n
— r ] T | i | i | i I i I i 1 i i i
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a
A
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i
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•
n a a a a _
A A A A A
o o o o o
1 1,1
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10 12 14
Hour of Day
16
18
20
22
Figure 9.6.
Geometric mean of 7.5 minute medians vs. hour of day
A, A = PLOT B, D = PLOT C, • = PLOT D (High run).
0 = PLOT
301
-------
3.U
2.5
0
(D 2.0
CO
1.5
1.0
i 1 i 1 i 1 i 1 i i i i i i . i .
ZAPS
• • • •
• • D
i- D D •
nA
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D
AA o *
-A
A
•
o •
• A A A A
• ^ • •
- n n D n • n n
O A D D A
0 00 AAAA A
O O O O AA O
OOQOOOOO
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
24 6 8 10 12 14 16
1 I 1 ' 1 > 1
H, 1977
_
• •
• •
•
• &
n A n D -
A AA
A
c
A
o
o o o o o o
1 1 1 1 i 1 1
18 20 22 24
Hour of Day
Figure 9.7.
Standard geometric deviation of 7.5 minute medians for growing
season vs. hour of day. 0 = PLOT A, A = PLOT B, D = PLOT C,
• = PLOT D (High run).
302
-------
TABLE 9.3. RELATION OF MICROMETEOROLOGICAL VARIABLES TO S02 CONCENTRATIONS
9.3a.
VARIABLES USED IN LINEAR REGRESSION OF VARIABLES
1/U SR I R r2
x .383
X X .418
X X .448
X X X .456
X X X X .460
C = 4.08 - .017 SR + 52.44/U
9.3b.
VARIABLES USED IN LINEAR REGRESSION OF LOG OF VARIABLES
U 1 + SR I r2
X .506
X X .536
X X .580
X X X .604
In C = 3.76 - .0830 In (1 + SR) - .754 In U
9.3c.
RELATION BETWEEN In U AND In C FOR DAY AND NIGHT
C = a + b In U
a b
Night 4.2 ± .1 -0.95 ± .06
Day 3.1 ± .1 -0.62 ± .06
r2 = .594
Confidence intervals are at 95% level.
303
-------
I added 3.5% over 1/U, but less than 1% over 1/U and SR, and is of only minor
importance. Although statistically significant, the addition of relative
humidity R to the regression added very little (0.4%) to r .
Higher r2 values were obtained by using the logarithms of C, U, and 1 +
SR (Table 9.3b). The relative importance of the variables was the same, with
In U accounting for 51% of the variability of In C, ln(l + SR) another 7%, and
I only 2% more than In U and ln(l + SR). One unexpected result is that the
absolute value of the coefficient of In U is less than 1; most models predict
values greater than 1. The effect of wind speed is thus less than expected
from straight dilution. This result reflects the persistance of low concen-
trations at low wind speeds during the daytime. For example, for U = 1.6
kmph, nocturnal concentrations are 75% higher than diurnal. The night-day
difference in the dependance of concentration on windspeed is shown in Table
9.3c. At night, C is inversely proportional to U, as expected. During day-
light hours, however, C decreases more slowly with increasing windspeed. One
possibility is that mixing with clean air directly above ZAPS is greater
during the day than at night. The regression equation given in 9.3c is a
significantly better fit than that given in 9.3b, and is the equation of
choice.
CONCLUSIONS
S02 concentrations on the ZAPS plots show substantial inter-season and
intra-season variation. Concentrations are generally higher at night than
during the day, but otherwise patterns of intra-seasonal variability are not
consistent between ZAPS plots or between years. Intra-seasonal variation is
greatest on D plots and least on A plots. Plots A, B and C on ZAPS II seem to
have had less variable fumigation histories than the comparable plots on ZAPS
I.
Seasonal frequency distributions of S02 concentrations are approximately
log-normal and show differences in the fumigation histories of the plots.
Though median concentrations on the A plots are small, these plots are subject
to short-term acute fumigations due to drift from other plots.
concentrations on the plots are strongly correlated with the inverse
of wind speed. Solar radiation and temperature stability class, and relative
humidity are also statistically significantly correlated with S02 concentra-
tion but are considerably less important in accounting for variability than
inverse wind speed.
ACKNOWLEDGEMENTS
The operation of the ZAPS sites was supervised in the field by Tom
Gullett during 1977. Tom also performed the quality assurance procedures
on the S02 monitoring system. Ted Tletcher performed much of the day to
day maintenance of the fumigation system.
304
-------
REFERENCES
Larsen, R. I. 1971. A Mathematical Model for Relating Air Quality Measure-
ments to Air Quality Standards. E.P.A. Report AP-89.
Lee, J. J. and R. A. Lewis. 1978. Zonal Air Pollution System, Design and
Performance. In: The Bioenvironmental Impact of a Coal-Fired Power
Plant, Third Interim Report, E. M. Preston and R. A. Lewis, eds. EPA-
600/3-78-021, U.S. Environmental Protection Agency, Corvallis, Oregon.
pp. 332-344.
Turner, D. B. 1969- Workbook of Atmospheric Dispersion Estimates. U.S. Dept
HEW. 84 pp.
Weber, D. , K. B. Olsen, and J. D. Ludwick. 1978. Field Experience with
Ambient Level Flame Photometric Sulfur Detectors. Manuscript, U.S.
Environmental Protection Agency, Corvallis, Oregon. 13 p.
305
-------
SECTION 10
SPATIAL VARIATION OF SULFUR DIOXIDE CONCENTRATIONS
ON ZAPS DURING THE 1977 FIELD SEASON
E. M. Preston and T. L- Gullett
ABSTRACT
Sulfur dioxide concentrations on the ZAPS plots were
monitored with Huey sulfation plates at various points in
horizontal and vertical space. These concentrations (as
implied from sulfation rates) decreased with decreasing
height above the ground within the plant canopy. Prevail-
ing winds cause drift of S0£ from the fumigated plots onto
A-plots (Control). Though sulfation rates were highly
variable at points within fumigated plots, only the D-
plots (High treatment) showed statistically significantly
different mean sulfation rates at different monitoring
locations at 35 cm height. Differences on these plots
correlate well with wind patterns. Stable dilution of S02
appears to be achieved within one to two meters of the gas
delivery orifices.
INTRODUCTION
The distribution of introduced sulfur dioxide gas over the experimental
plots has been a concern since the beginning of the ZAPS study. Until the
present study, all monitoring of the sulfur fumigation has been accomplished
with a Meloy 160-2 sulfur gas analyzer coupled with Teflon tubing from one to
three locations on each of the fumigated plots. All sampling was done at 35
cm height above ground (approximate canopy height). In order to determine
the horizontal and vertical distribution of S02, a series of Huey sulfation
plates were set out at various locations and heights over the entire study
site. The plates, which adsorb ambient sulfur dioxide and retain it as lead
sulfate, were placed in the field for a specified length of time, collected
at the end of the period and then analyzed for sulfate content. Results of
this analysis were then used to describe the distribution pattern for the
sulfur dioxide over the ZAPS site.
306
-------
MATERIALS AND METHODS
The treatment plots, usually referred to as A, B, C, and D, represent
control, low, medium and high concentration treatments respectively. In this
study the intervals were also investigated as separate plots making a total
of seven.
This study was composed of INTENSIVE and EXTENSIVE segments. The primary
purpose of the EXTENSIVE study was to index the general relative concentra-
tions of S02 at various points in vertical and horizontal space on the plots.
Plates were widely spaced over each of the seven plots (Figure 10.1). One
pole was placed in the center of each quadrant of each plot and a fifth pole
placed in one of the two following positions: on plots A, B, C, and D, next
to the real-time sulfur analyzer sample position c (Section 9) and on the
interval plots, in the geometric center of the plot. On all poles, plates
were placed at 15, 35, 75 and 150 centimeters above the ground. The exposure
period in nearly all cases was 31 days. The study was repeated on both ZAPS
I and II for 4 test periods (5-24-77 -» 6-24-77; 6-25-77 -> 7-25-77; 7-26-77 -»
8-25-77; 8-26-77 -» 9-25-77).
The major purpose of the INTENSIVE part of the study was to determine
the dispersion pattern of the S02 immediately upon leaving the delivery
system. Sulfation plates were placed in a tight pattern around five gas
delivery orifices on plot B. The study area for the INTENSIVE study is shown
in Figure 10.2. The spatial relationship between pole and orifice is shown
in Figure 10.3. Poles had plates at 15, 35, 75 and 150 cm. The study was
repeated for both ZAPS I and II for 3 test periods (7-05-77 -» 8-05-77;
8-06-77 -> 9-05-77; 9-05-77 -> 10-06-77).
In all instances, the sulfation plates were placed into holders (adjust-
able Broom Clamp #2B, A.I. Platt Co., Fairfield, Conn.) attached to poles
that had been driven into the ground. The plates were held parallel to the
ground with the open face down. Sulfate determination of the exposed plates
was conducted by Environmental Management Planning Laboratory in Nashville,
Term.
RESULTS AND DISCUSSION
Extensive Study
Vertical Distribution of S02
cm
The only useable data for vertical distribution of S02 plates at 15
above ground was obtained during the fourth test period. During other test
periods, low level plates were destroyed by insects and rodents. Therefore
only values from test period 4 were used to compare gas concentrations at
different heights. The average sulfation rates for each plot at each height
are shown in Figure 10.4. On ZAPS I, the highest gas level occurred at 75 cr
followed closely by the 35 cm height. The gas escape orifices on the ZAPS I
site are located on the sides of the delivery pipes and direct the gas parallel
307
cm
-------
(A)
•4
(A-B)
5.
/• v
(B)
(B-C)
(0
(C-D)
(D)
150 -r
Height of
Sulfation 75
Plates (cm)
35
15-
"V—S02 Release Point
Ground Level
Figure 10.1, Location of sulfation plate monitoring
positions on the EXTENSIVE grid,
Typical Treatment Plot
Figure 10.2.
Location of INTENSIVE study area on ZAPS, plot B. Monitoring
locations for the EXTENSIVE study on this plot are also indicated,
308
-------
Center of
Plot "B"
XX
* •
)
•
)
•x
E
OJ
.
C
•
•
c
E
E
4
2m
2m
4m
7m
11 m
real time sampler
location C
pole position 5
X = Gas orifice
• = Pole with sulfation plates
Figure 10.3.
Spatial relationship of gas delivery orifices and sulfation
plate monitoring locations in the INTENSIVE study.
309
-------
Treatment Plots
0 100 200 300 400 500 600 700 800 900 1000
SULFATION RATE (fjig SO^/test period)
-p Intervals
^a
Q
O
50
|20
90
LU
O 60
CD
h- 30
A-B B-C , C-D
j I I 1 i
1
0 100 200 300 400
SULFATION RATE (pq SO^/test period)
500
Figure 10.4.
Vertical profile of sulfation rates during
test period 4 (8-26-77 •+ 9-25-77).
310
-------
WIND SPEED
Figure 10.5.
Hypothetical vertical profile of wind speeds in a
grassland canopy: (A) logarithmic profile, (B)
exponential profile, (C) logarithmic profile.
to the ground while the ZAPS II gas is directed toward the ground by orifices
located in the bottom of the delivery pipes which are also set slightly
closer to the ground. These differences in construction may account for the
different stratification patterns seen at the 35-75 cm level between the two
sites. On both ZAPS I and II, the 15 cm level received about 75% and the 150
cm level received about 85% as much gas as did the 35 cm level.
Several factors contribute to the vertical distribution of sulfation
rates shown in Figure 10.4. Gases are transported by a combination of diffu-
sion and air movement. Canopy air flows can largely determine the rate of
S02 transport to biota from the ZAPS S02 delivery system. Figure 10.5 shows
a hypothetical vertical distribution of wind speeds above and within a grass-
land canopy. Horizontal winds flowing over the canopy surface are slowed by
frictional drag on the vegetation. Immediately above the canopy, the mean
horizontal wind velocity decreases logarithmically with decreasing height.
Within the canopy, a canopy-eddy layer exists in which wind speed decreases
exponentially. In the lowest part of the plant-air layer a logarithmic wind
311
-------
profile resumes with wind speed decreasing to zero at ground level (Inoue,
1963). The degree of vertical mixing of S02 at various vertical distances
from the S02 delivery pipes on the ZAPS plots should vary directly with wind
speeds at those heights and therefore should decrease with decreasing height
above ground level.
The sulfation rate of sulfation plates appears to vary directly with the
square root of wind speed (Liang et al., 1973). Thus, if wind speed decreases
with height in the canopy, measured sulfation rate would be expected to
decrease moderately with height even if S02 concentrations remained constant.
S02 concentrations would also be expected to decrease with decreasing height
because transport of the plume by turbulent mixing decreases with decreasing
height and some S02 is removed from the air by adsorption and/or absorption
by the biota within the canopy. The observed vertical profile of sulfation
rates (Figure 10.4) are consistent with these expectations.
It is of interest to determine whether or not the vertical profile of
sulfation rates within the canopy on the fumigated plots is substantially
different from that which might be expected during fumigation from a power
plant plume. It is possible that the observed vertical profile of sulfation
on the fumigated plots has been unduly influenced by turbulent mixing generated
by the delivery of S02 under pressure from the gas delivery system. Some
insight can be gained by comparing the vertical distribution of sulfation
rates on the fumigated plots with those on the intervals, which are not
influenced by gas delivery systems. Mixing above the canopy is potentially
influenced by ambient turbulent air flow, and on the fumigated plots, by
turbulence caused by the pressurized delivery of S02. Below the canopy,
turbulent air flow is influenced by these two factors and also modified by
the canopy. If the turbulence caused by the gas delivery system were a major
influence on sulfation rates, the vertical profiles in sulfation rates on
fumigated plots should be different from those on intervals. Figure 10.6 shows
the change in sulfation rates between 35 cm and 15 cm within the canopy as a
function of sulfation rate at 35 cm. This change is directly linearly
proportional to the sulfation rates at 35 cm height. The proportionality on
the intervals is similar to that on the fumigated plots. This suggests that
the canopy is the dominant moderating influence and that the gas delivery
system influences the vertical distribution of sulfation rates very little.
This is not true, however, for sulfation rates measured above the canopy
(Figure 10.6). While the change in sulfation rates between 35 and 150 cm
height are directly proportional to the sulfation rate at 35 cm on the fumi-
gated plots, the relationship does not hold for the intervals. The S02
delivery systems apparently have a major influence on the vertical profile of
sulfation rates measured above the canopy. The data available suggest that
the vertical profile of S02 concentrations implied by the vertical profile of
sulfation rates within the canopy is primarily the result of micrometeorologi-
cal and biological processes and is not an artifact of the design of the gas
delivery systems.
If-S02 exposure concentrations are vertically stratified within an
ecosystem, quantification of the dose delivered to particular ecosystem
components becomes a complex problem, particularly when these components are
312
-------
crcr
n- - 50°
^ ^ 1 400
CD
yj CL
300
200
100
0
-100-
300
o>
-J -J
Above Canopy
E E
o a
o> 200
Q.
100
0
0
Below Canopy
a
a
D.D
Fumigated plots
Interval plots
200 400 600 800
SULFATION RATE AT 35cm
SO^/test period 4)
1000
Figure 10.6.
Vertical changes in sulfation rates (mean of 5 pole
positions, test period 4) above and below the canopy
as a function of sulfation rate at canopy height.
313
-------
OJ
60
O
cr
o
LU
QQ
LU
X
50
20
10
SOo Release
\
„ Flying
insects
Taller vegetation;
^/'macro arthropods
Shorter
•-^vegetation
.Ground
Dwellers
Figure 10.7.
Hypothetical S02 flux in native grassland canopy. Solid arrows represent relative
amounts of S02 reaching various strata. Open arrows represent relative amounts of
S02 absorbed at biotic receptor sites within various strata.
-------
also vertically stratified spatially and/or temporally. In a native grassland
ecosystem there is considerable vertical stratification of ecosystem compo-
nents. Figure 10-7 illustrates a hypothetical gas exchange system within a
native grassland canopy. For discussion, the canopy has been divided into 5
strata. The width of arrows in the left-hand half of the diagram represents
the magnitude of S02 fluxes through the strata. The decreasing flux with
height (solid arrows) results from reduced vertical mixing and the net vertical
removal of S02 by tissues within each stratum (open arrows). The relative
magnitudes of vertical fluxes versus tissue fluxes have been assigned arbi-
trarily. These would be expected to vary temporally and probably spatially.
The vertical flux gradient would vary with the degree of ventilation and
tissue flux. Tissue flux would vary between strata depending upon the
number of available S02 removal sites within each stratum.
The right-hand portion of Figure 10.7 indicates the vertical distribution
of some of the important biotic components of a native grassland ecosystem on
the ZAPS sites. Low flying insects would generally receive the greatest
dose. Vegetation would receive a variety of dosages throughout its height.
Dosages received by macroarthropods would vary temporally depending on their
temporal patterns in the use of vertical space. Ground dwelling organisms
would generally receive the lowest overall dose.
Horizontal S02 Distribution
To characterize the distribution of S02 concentrations in horizontal
space on the ZAPS plots, we compared sulfation at the five pole positions at
35 cm height (roughly canopy height) with oneway ANOVA. Plot locations were
considered treatments and test periods were considered replications.
On treatment plots, there were no statistically significant differences
in sulfation rates among pole positions except on the D plots (Table 10.1,
Figure 10.8). On the D plots, pole 1 had higher sulfation rates than other
poles on ZAPS I and poles 1 and 4 had higher sulfation rates than others on
ZAPS II. On ZAPS I, there is a trend for sulfation in pole positions 1 and 4
to be greater than that on poles 2 and 3. To see if this trend could be de-
tected statistically, paired-t tests were used to compare summed average sul-
fation values (Table 10.1) for poles 1 and 4 with the summed values for poles
2 and 3. Test periods were considered replications. Once again, only the D
plots showed a significant difference (Table 10.2).
Eversman (Section 17) reports that sulfation (at 50 cm height) was
greatest near the center of plot D on ZAPS I (Figure 10.8). The differences
between Eversman1s relative sulfation rates at pole positions and those
reported here illustrate that locations with small differences in vertical
position may have dramatic differences in relative S02 concentrations.
The two factors likely to have the greatest influence on the spatial
distribution of S02 concentrations are the gas delivery system and wind. The
gas delivery system was intended to deliver a spatially uniform concentration
of S02 at canopy height. However, any drop in pressure along the delivery
pipes would cause locally lower concentrations of S02 to be delivered.
315
-------
TABLE 10.1. MEAN SULFATION RATES AT VARIOUS POINTS
IN HORIZONTAL SPACE ON THE ZAPS PLOTS
ZAPS I
Mean sulfation rates of four test periods
at 35 cm height at Pole positions
LSD
Plot
A
Interval
A-B
B
Interval
B-C
C
Interval
C-D
D
A
Interval
A-B
B
Interval
B-C
C
Interval
C-D
D
1
50
74
187
149
386
236
1013
56
93
228
118
528
215
1216
2
40
67
173
108
370
169
633
49
88
228
108
482
253
799
345
(|jg SOS/test
period)
69
90
172
138
338
209
512
45
116
204
154
426
262
950
38
119
184
201
378
392
652
ZAPS II
59
188
174
170
446
360
1271
41
76
204
146
364
242
625
70
123
193
146
422
266
597
(0.05)
58
75
103
74
160
112
271
58
132
108
51
114
160
230
F
0.44
0.69
0.14
1.87
0.11
5.20
4.50
0.24
0.83
0.42
2.31
1.39
1.01
13.72
P
NS
NS
NS
NS
NS
<.01
<.05
NS
NS
NS
NS
NS
NS
<.01
316
-------
TABLE 10.2. MEAN DIFFERENCES BETWEEN SUMMED SULFATION RATES FOR POLES
1 AND 4 AND SUMMED SULFATION RATES FOR POLES 2 AND 3
Plots
D* (jJg S0=)
SD (Mg S0=)
t
P
D
s
D
t
P
ZAPS I
A B C D
20 25 -20 520
20 68 146 161
-2.03 0.75 -0.27 6.48
NS NS NS <.01
ZAPS II
21 -30 67 759
39 106 163 151
1.11 -.57 0.82 10.07
NS NS NS <.005
f\
D = average difference in sulfation rates at 35 cm height between
upper plot positions and lower plot positions !(pole positions
1 + 4) - (pole positions 2 + 3)1.
S = Standard deviation of D.
t = paired t statistic.
317
-------
ZAPS I
A
d a
c
b e
Interval
A-B
e b
c
d a
B
d e
a
b c
Interval
B-C
e d
c
b a
C
c e
d
a b
Interval
C-D
e d
b
c a'
D
c e
d
a' b
(from Eversman)
c b
a
d e
a
c b
e c
b
d a
c
a
b
a c
d
b e
ZAPS n
e b
c
d a
a
c
b
b d
a
a c
d c
b
e a
• c
a
b
o p
j £ f\ C.
a -a c
63
b' a'
Figure 10.8.
Ranks of sulfation values at different positions on the ZAPS
plots. Letters sharing the same super and/or subscripts are
not significantly different from other letters within the
same plot (P <-05). Ranks are based on average values for
all test periods at 35 cm height, a -> e = greatest sulfation
rate -> least sulfation rate.
318
-------
Frictional forces would increase the chances of significant pressure drop
with increasing distance from the pump. Such a pressure drop could cause the
observed trend on the ZAPS I and the D plots (Figure 10.8).
Similar results could also be produced by wind patterns. If wind dis-
placement of S02 were equal (on the average) in all directions, positions at
the periphery of fumigated plots would tend to get diluted while interior
positions receiving drift from the periphery, would tend to have higher S02
concentrations. If wind displacement were not equal in all directions,
peripheral points receiving the greatest dilution would have the lowest S02
concentrations while those points receiving the greatest drift should have
the highest average concentrations. In addition, all plots may have their
S02 supplemented by S02 drifting from other fumigated plots. The magnitude
of this can be gauged somewhat by sulfation measured on the A plots since
these receive S02 by drift alone. The seasonal average concentrations on the
A plots were about 27% of those on adjacent B plots (ZAPS I = 25.9%, ZAPS II
= 27.2%).
Wind affects the measured sulfation values in at least two ways. First,
in the ideal case where a single gaseous material at constant ambient concen-
tration and temperature is being sampled, the theoretical model proposed by
Liang et al. (1973) suggests that sulfation rate varies directly with the
square root of wind speed. Secondly, wind dilutes and mixes S02 delivered to
the plots. Under theoretically ideal conditions, one might expect S02
concentration to be reduced in proportion to the reciprocal of some power of
wind speed equal or greater than one. Based on the above two assumptions, we
developed an index of sulfation potential which varies with wind speed and
its duration. One sulfation hour was defined as the square root of wind
h. .... i - -I
speed for that hour divided by wind speed for that hour ( " = ;, L ). With
ws Vws
this index, a light wind produces a low sulfation potential but also a weak
S02 dilution. A stronger wind will produce a high S02 absorbance potential
but a much stronger S02 dilution yielding a lower potential sulfation rate.
The dilution factor quickly over powers the increased S02 absorption potential
caused by increased wind speed. This effect would be even more dramatic if
it were assumed that dilution varied with the reciprocal of a power of wind
speed greater than one. The higher the index, the higher the expected sulfa-
tion rate during that hour.
To characterize how wind might be expected to influence measured sulfation
at various locations, the Sulfation Potential Index for each wind direction
in each test period was calculated (Table 10.3). Wind speed and direction at
two meters height measured in the B-C plot intervals was assumed typical of
wind patterns on all plots. This assumption may be violated rather seriously,
particularly as one approaches the canopy. Unfortunately, no more appropriate
documentation of wind patterns on the plots exists. Wind speeds were divided
into ten categories between 0.0 and 8.9 m/sec. The number of hours that wind
speed in each category occurred from each of eight directions (N, NE, E, SE,
S, SW, W, NW) in each test period was determined. The Sulfation Potential
Index for each test period was calculated as the summation of the number of
hours that winds occurred in each speed category multiplied by the reciprocal
of the square root of average wind speed for that category for each compass
319
-------
TABLE 10.3. SULFATION POTENTIAL INDICES* OF WINDS COMING FROM
COMPASS DIRECTIONS DURING DIFFERENT TEST PERIODS
ZAPS I
(Values adjusted to a common total of 744 hours/test period)
j,
(Hrs - (m/sec) 2)
Test
Period
1
2
3
4
Wind Direction
N
31
24
24
22
NE
18
21
20
11
E
22
17
22
25
SE
44
23
36
42
S
24
27
29
28
SW
14
22
14
8
W
17
25
21
14
NW
17
12
22
23
Total
187
171
188
173
Total
101
86
145 108
58
77
74
ZAPS II
(Values adjusted to a common total of 760 hrs/test period)
_j,
{Hrs - (m/sec) 2)
Test
Period
1
2
3
4
Wind Direction
.N
20
18
21
29
NE
22
25
28
17
E
46
34
30
47
SE
14
21
15
15
S
16
12
11
12
SW
15
9
14
10
W
41
48
52
35
NW
16
14
20
22
Total
190
181
191
187
Total
88
157
65
51
48
176
72
*o -14: .- TD 4- ^- T
*Siilfation Potential
Index
10
v
— Zj
1=1
( V
wlT) (HrSi)
ws .
i
10
v
— L
1=1
Hrs.
i
Vws_.
ws
.th
. = average wind speed (m/sec) for the i category.
.Hrs. — the number of hrs that ws. persisted during the given test
period.
320
-------
ZAPS I
ZAPS n
Co
N
Test Period: 1
Resultant of Sulfation Potential vectors
with components along short axis of plots
D
Sum of Sulfation Potential vector^
^"components along long axis of plots
Figure 10.9. Sulfation potential of winds coming from various directions during different test periods
-------
direction. Since sulfation rate should be proportional to this index, these
index values indicate the potential effect on sulfation rates of winds from
each wind direction during each test period.
Figure 10.9 illustrates the relative influence of winds from different
directions on Sulfation Potential for the four test periods. The approximate
orientation of the ZAPS plots is also indicated. Two composite vectors
derived from the Sulfation Potential vectors are illustrated. In one, all
vector components capable of contributing to S02 drift along the long axis of
the ZAPS plots have been summed. This should indicate the net direction and
sulfation potential to be expected. On both sites, the trend is for S02 to
drift from higher concentration plots to lower concentration plots. On ZAPS
I the tendency is large while on ZAPS II the tendency is slight.
The second vector indicated is the resultant of all vectors having
components which could cause drift along the short axis of the plots. On
ZAPS I this resultant would carry S02 diagonally across the plots and could
cause the observed sulfation "hot spot" at pole 1, plot D (Table 10.1). On
ZAPS II, drift with high sulfation potential is directed on less of a diagonal
and could produce the observed more nearly equal sulfation rates at poles 1
and 4. Since the magnitude of this resultant is greater on ZAPS II than on
ZAPS I, one would expect mean differences between summed sulfation rates for
poles 1 and 4 and sumed sulfation rates for poles 2 and 3 to be greater on
ZAPS II than on ZAPS I. This has been demonstrated (Table 10.2). Though the
observed trends in sulfation seem to be explainable by wind patterns, defi-
ciencies in the gas delivery system cannot be ruled out.
Figure 10.10 shows average sulfation for each test period on each plot
at 35 cm height. An expected value is provided for comparison. On ZAPS II,
plot D, this value is the mean sulfation rate for the four test periods.
Expected values for the other plots on ZAPS II were computed assuming interplot
ratios of 0:2:5:10 for A:B:C:D. On ZAPS I, expected values were computed
similarly but only including data for test periods 1, 2, and 4 in computation
of the expected value for plot D. Data for test period 3 on ZAPS I were
unusually and unexplainably low. Therefore, separate expected values were
computed for test period 3 applying the above procedure.
In general, S02 concentration ratios between fumigated plots are reason-
ably close to the hypothetical 0:2:5:10 delivery rates. Lower concentration
plots tend to be higher than expected due probably to the net drift from the
higher plots towards the lower plots indicated in Figure 10.9. Drift of S02
reaches the control plots and ambient concentrations average about one fourth
of those of the B plots.
Conversion Factors For Sulfation Values
Pole position 5 for sulfation measurements coincides with monitoring
location £ for the real-time flame photometric analyzers on all experimental
plots. Having both real-time S02 analyzers and sulfation plates monitoring
S02 levels allowed computation of conversion factors for estimating mean S02
levels from sulfation data collected at other points on the plots. The
322
-------
1000
£|~o 800
<"fc
cr a.
z £ soo
LJjCO 400
co^-
200
0
" ZAPS n
—
rTlJ 1
•*.
^•H
^Wi
•^M
.
•^•1
I^M
•••
*m^
^^
•^
-
—
-
I 234e I 234e I 234e I 234e
800
600
400
0
ZAPS I
I24e 3e3 I24e 3e3 I24e 3e3 I24e 3e3
A B C D
e = expected e3 = expected for test period 3
Figure 10.10. Average sulfation rates at 35 cm height on fumigated plots
323
-------
15
10
o.
QL
CO
z
o
•z.
UJ
o
•ZL
O
o
CM
O
CO
UJ
o:
UJ
o
h-
LJ
2
I
H
cc
<
0
15
10
0
15
10
0
20
15
10
xo
ZAPS i ZAPS n
1 1 //-1 1 I
Test Period
1
Slope = .48*
Intercept = 0.66
R2 1.00
Slope = .30
Intercept = 1.98
R2 - 0.95
—I 1
o x
Test Period
D 2.
xo
Slope - .54*
Intercept = 0.46
R2 = 1.00
1
-- B
"OX,
Slope = .34
Intercept = 1.00
R2 = 0.99
—I 1
Test Period
3
Slope = .83*
Intercept = 1.58
R2 =1.00
—I 1
Slope = .34
Intercept = 2.11
R2 = 0.98
Test Period
x D .o «
Slope =.71
Intercept = 0.25
R2 = 0.98
_J I
Slope = .37
Intercept =-0.02
R2 = 1.00
_L
0 10 20 30 0 10 20 30 40
,2,
SULFATION RATE (/*g S0|/cm/day)
o average of 5 pole positions at 35cm height
x location c at 35cm
A plot
Figure 10.11.
Relationship between sulfation rate and average S02 concen-
tration during various time periods on the ZAPS plots.
* regression parameters based on data values for Plots A,
B, and D only.
324
-------
sulfation plates also serve as a check on performance of the real-time analy-
zers.
Figure 10.11 displays the relationship between mean S02 concentrations
and sulfation rates on the plots for each test period. All measurements were
made at 35 cm height. Mean S02 concentrations (ordinates) were estimated
from the real-time monitoring data by the arithmetic average for ALL (high
run and low run values, as described in Section 9) 7.5-minute median concen-
trations. Two estimates of sulfation rates (abscissas) are displayed. The
first is the sulfation rate of the sulfation plate at pole positon 5 on each
plot. The second is the mean sulfation rate for all 5 pole positions on each
plot. The regression parameters shown, unless otherwise noted, are the least
squares best linear fit between mean S02 concentrations and average sulfation
rates at the five pole positions on each plot.
On ZAPS I, the regression lines are variable between test periods but
they are nearly constant on ZAPS II. The slopes of the regression lines are
steeper on ZAPS I than on ZAPS II. Sulfation rates tended to be lower on
ZAPS I than on ZAPS II. The reasons for these differences between sites are
unclear. Micrometeorological conditions at the two sites are quite similar
(Section 11) and there is no reason to suspect that plates from the 2 sites
were treated differently during analysis.
For ZAPS II, the conversion factor of
pphm S02
.35
jjg S03/cm^/day
suggested by Corning Laboratories* appears to be reasonably accurate.
However, the variability in conversion factors observed on ZAPS I suggests
that these change in time and space. Assuming a constant conversion factor
of
pphm S02
•35
to estimate mean S02 concentrations from sulfation data could lead to under-
estimates greater than 2-fold.
For ZAPS I, Test periods 1, 2, and 3, the mean S02 concentrations for
plot C are elevated considerably above those predicted by the linear regres-
sions of points from the other three plots. The magnitude of this descrepan-
cy decreases as the season progresses and seems to have essentially corrected
itself by test period 4. The descrepancies are 89%, 75%, and 49% higher than
expected for test periods 1, 2, and 3 respectively. This suggests a monitoring
error in real-time measurements on ZAPS I, C during test periods 1, 2, and 3.
^mimeographed sheet supplied to sulfation plate users.
325
-------
An additional indication that ZAPS I, C readings were artificially high comes
from comparing these with readings on ZAPS II, C and ZAPS I, C taken during
previous seasons. In all cases, the ZAPS I, C, 1977 readings appeared to be
too high. Such elevated readings could be caused by a partially plugged
sampling line leading from the C plot or any other mechanical problem in the
time share sampling device increasing resistance to gas flow. On the basis
of these indications, the ZAPS I, C, 1977 real-time readings reported in
Section 9 (Table 9.2, Figure 9.4) have been reduced by the appropriate percent-
ages for test periods 1, 2, and 3.
In most cases the sulfation rates at pole position 5 are similar to the
mean sulfation rate for all five pole positions. This is inferred from the
near coincidence of points in Figure 10.11. There are some exceptions to
this on the D plots. On ZAPS I, D during test period 4 and on ZAPS II, D
during test periods 2, 3, and 4, sulfation at pole position 5 is substantially
lower than mean sulfation for the D plots. As previously shown, the distribu-
tion of sulfation rates on the D plots are non-random with greatest sulfation
occurring at pole positions 1 and 4. This suggests that with the exception
of the D plots where distributions of S02 in horizontal space are non-random,
pole position 5 (location c) is a good place to monitor in order to estimate
average concentrations in horizontal space on the plots.
Intensive Study
As in the EXTENSIVE study, vertical distribution of sulfation rates was
examined through comparison of average sulfation values for the different
heights (Table 10.4). Only data for the period 9/05/77 through 10/06/77 from
poles within 2 m of the gas delivery pipes have been included in Table 10.4.
This test period was used because it is the only one with any appreciable
data for the 15 cm plates.
TABLE 10.4. AVERAGE SULFATION VALUES (AND STANDARD ERROR) FOR
15, 35, 75 AND 150 cm HEIGHTS, ZAPS I AND II,
9-05-77 -> 10-06-77 EXPRESSED AS MICROGRAMS SULFATE
AND AS A MULTIPLE OF 35 cm VALUE t
15 cm 35 cm 75 cm 150 cm
178.3(2.3) 277.8(5.6) 332.1(6.9) 211.6(2.2)
0.64** 1 1.20** 0.76**
II 218.5(5.3) 358.0(8.7) 316.3(5.0) 201.2(3.6)
0.61** 1 0.88** 0.56**
t Only poles within 2 m of delivery pipes are included
** = Significantly different at P <.01
326
-------
ZAPS I, with the gas delivered horizontally from about 75 cm height
above the ground, received more sulfur at the 75 cm level than at the 35 cm
level. ZAPS II, with the downward discharge of gas from the less elevated
delivery system, experienced greater sulfur at the 35 cm level than at the
75 cm level. Table 10.5 shows that these relationships hold when based on
the combined values for three test periods.
TABLE 10.5. AVERAGE SULFATION VALUE (AND STANDARD ERROR)
FOR 35, 75 AND 150 cm HEIGHTS, ZAPS I AND II,
ALL TEST PERIODS COMBINED, EXPRESSED AS MICRO-
GRAMS SULFATE AND AS A MULTIPLE OF 35 cm VALUE
ZAPS 35 cm 75 cm 150 cm
I 228.1(5.6) 281.0(6.9) 172.0(4.2)
1 1.23** 0.75**
II 285.3(8.9) 254.0(8.3) 156.4(5.3)
1 0.89* 0.55**
* = Significantly different at P <0.05
** = " " " P <0.01
The fine detail of horizontal distribution of fumigation gas was also
examined with the INTENSIVE study. Positions were monitored 1, 2, 4, and 7
from the gas delivery pipes. If the crossed fumigation pipes are seen as
dividing the study area into four sections, (Figure 10.2) then the poles 1
and 2 m from the pipes were sampling in three of the quadrants while the
poles 4 and 7 m distant were sampling just in one. Only the 1 m and 2 m
sulfation plates located in the southeasterly quadrant were used in comparing
sulfation values at different horizontal distances from the delivery system.
There were no statistically significant differences in the amounts of sulfur
received at different distances from the pipes on either of the two ZAPS
sites (Table 10.6). However, at 35 cm height on ZAPS II there was a reduction
in sulfur concentration between the 1 m distance and the 2 m, 4 m, and 7 m
ones. This may iiave been due to the slightly lower S02 delivery heights on
ZAPS II. Here, S02 encounters less air turbulence and requires a slightly
greater distance from the discharge orifice to reach stable dilution.
m
m
327
-------
TABLE 10.6. AVERAGE SULFATION VALUES (AND STANDARD ERROR) FOR 35, 75 AND
150 cm PLATES, 1, 2, 4 AND 7 m DISTANT FROM DELIVERY PIPES, ALL
TEST PERIODS COMBINED EXPRESSED AS MICROGRAMS SULFATE AND AS
MULTIPLES OF 1 m DISTANCE
Height
ZAPS I
ZAPS II
1 m
2 m
4 m
7 m
35 cm 230.28(10.33) 220.24(11.84) 236.33(22.76) 228.33(21.26)
0.96
1.03
0.99
75 cm 304.47(15.04) 268.90(13.84) 294.33(25.46) 264.00(30.62)
0.88
0.97
0.87
150 cm 176.97(7.61) 168.10(9.27) 184.67(17.33) 179.33(22.64)
0.95
1.04
1.01
35 cm 321.40(18.16) 273.38(15.86) 277.67(16.50) 258.00(16.07)
0.85
0.86
0.80
75 cm 272.10(19.32) 256.62(16.01) 259.33(15.07) 255.00(21.36)
0.94
0.95
0.94
150 cm 159.21(10.77) 168.05(9-09) 176.33(17.05) 181.67(11.89)
1.06
1.11
1.14
Horizontal dispersion of sulfation rates are compared between ZAPS I and
ZAPS II in Table 10.7. No significant difference exists at the 75 and 150 cm
heights, but, ZAPS II, which apparently receives significantly more sulfur
than ZAPS I at the 35 cm level, has a gradient of decreasing sulfur concentra-
tion with increasing distance from the gas delivery pipes.
CONCLUSIONS
Sulfation rates decrease with decreasing height above the ground within
the plant canopy. The implied vertical profile of S02 concentrations is
328
-------
TABLE 10.7. ZAPS II SULFATION VALUES (EXPRESSED AS MULTIPLES OF ZAPS I) FOR
35, 75 AND 150 cm HEIGHTS, 1, 2, 4, AND 7 m FROM DELIVERY PIPES
ZAPS II
Distance from
Pipe (m)
1
2
4
7
35 cm
1 . 40**
1.24*
1.17
1.13
75
0
0
0
0
cm
.89
.95
.88
.97
150 cm
0.90
1.00
0.95
1.01
* P <0.05
** P <0.01
consistent with expectations derived from knowledge of atmospheric mixing
processes and S02 removal potential within plant canopies. This implied
vertical profile of S02 concentrations on the ZAPS plots is similar to that
which might be expected within a grassland canopy experiencing fumigation
from the plume of a coal-fired power plant.
Vertical stratification of S02 concentrations makes dose characterization
complex. S02 exposure within the canopy depends upon the temporal pattern in
which constituent organisms make use of vertical and horizontal space.
Prevailing wind patterns cause drift of S02 onto the A plots at both
ZAPS sites. Seasonal averages of S02 concentrations on these plots are
roughly one fourth of the concentrations on the B-plots. While S02 concentra-
tions vary considerably in horizontal space at canopy height, only the D-
plots have statistically significantly different mean concentrations between
positions monitored. The pattern of sulfation rates shown on the D plots
correlates well with expectations derived from the limited available knowledge
of wind patterns on the plots.
Mean concentrations of S02 at 35 cm height on the plots are in direct
proportion to the delivery rates of S02 to the plots.
Conversion factors relating sulfation rates to S02 concentrations are
variable in time and space. Errors in estimates of 2 to 3 fold could be
expected by assuming a constant conversion factor throughout the season.
The Intensive Study suggests that mixing occurs fairly rapidly with
distance from the gas delivery orifices. On ZAPS I, stable S02 dilution
appears to be reached within about one meter of the gas delivery orifices.
329
-------
On ZAPS II, stable dilution may not be reached until two meters from the
orifices.
REFERENCES
Inoue, E. 1963. On the Turbulent Structure of Airflow within Crop Canopies
J. Meteorol. Soc. Japan, 41(6):317-325.
Liang, S.F., C.V. Sternling, and T.R. Galloway. 1973. Evaluation of the
Effectiveness of the Lead Peroxide Method for Atmospheric Monitoring of
Sulfur Dioxide. J. Air Poll. Cont. Assoc., 23(7):605-607.
330
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SECTION 11
SOIL AND METEOROLOGICAL CHARACTERISTICS AT ZAPS
J. L. Dodd, W. K. Lauenroth, R. G. Woodmansee,
G. L. Thor and J. D. Chilgren
SOIL DESCRIPTION: PHYSICAL AND CHEMICAL TRAITS
Soils of both ZAPS sites have been characterized by standard soil
descriptions (R. G. Woodmansee) and extensive physical and chemical analyses.
Three soil pits were excavated on ZAPS I and five on ZAPS II. The ZAPS I pits
were located between the control and low plots (west pit), between the low and
medium plots (middle pit), and adjacent to the northwest edge of the control
plot (northwest pit) . The ZAPS II pits were located immediately west of the
control, between the control and low plots, between the low and medium plots,
between the medium and high plots, and immediately east of the high plot.
Soils at ZAPS I were classified as Farland silty clay loams (Table 11.1)
and at ZAPS II as Thurlow clay loams (Table 11.2). Physical and chemical
characteristics of the soil pits are presented in Tables 11.3 to 11.8.
Soils of the study sites possess substantial within-site variability in
physical and chemical characteristics because of variance in both parent
material and micro-topographic position, which is common on native rangelands.
SOIL WATER DYNAMICS AND PRECIPITATION
Soil water dynamics for ZAPS I and II were determined by gravimetric
sampling. Summaries of soil water dynamics on the ZAPS sites are shown in
Figures 11.1 and 11.2. A more detailed account appears in Tables 11.9 to
11.13. In general, soil water content was maintained at much higher levels in
1975 and 1976 than in 1977. This was partly because of lower precipitation
during the 1977 growing season (Table 11.14) and apparently lower evapotrans-
piration rates in the early part of the 1975 and 1976 seasons (Section 13).
Precipitation was greatest in May and June at both ZAPS in 1976 and 1977.
July was particularly arid in 1977. On individual days, precipitation was
characteristically in quantities of 0.25-15 mm, the mode being 1-5 mm both
years (Figures 11.3 and 11.4).
331
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TABLE 11-1. PROFILE DESCRIPTION FOR ZAPS I. FARLAND SILTY CLAY LOAM SOIL SERIES, WEST PIT
Depth
Horizon (cm) Description
All 0-15 Brown (10 YR 5/3); very dark brown (10 YR 3/3); clay loam; massive; soft, friable, non-
sticky and slightly plastic; noneffervescent; medium acid (pH 5.8); clear smooth
boundary; many fine roots; few fine pores.
A12 15-25 Gray brown (2.5 Y 5/2); dark brown (10 YR 4/3); silt loam; weak massive and columnar
blocky; soft, very friable, nonsticky, slightly plastic; noneffervescent; slightly acid
(pH 6.1); clear wavy; many fine roots; many fine pores.
B21 25-39 Yellowish brown (10 YR 5/4); yellowish brown crushed (10 YR 5/6); dark brown coats (10
YR 4/4); silty clay loam; weak columnar prisms parting to weak massive blocky; hard,
very firm, sticky, plastic; noneffervescent; medium acid (pH 5.9); clear wavy; common
fine roots; many fine pores.
B22 39-79 Light olive brown (2.5 Y 5/4); yellowish brown crushed (10 YR 5/4); dark brown coats
(10 YR 4/3); clay loam; strong coarse prisms parting to moderate coarse blocky; very
hard, extremely firm, very sticky, very plastic; noneffervescent; neutral (pH 7.0);
clear wavy; common fine roots; few fine pores.
B3ca 79-91 Light olive brown (2.5 Y 5/4); light olive brown crushed (2.5 Y 5/4); olive brown coats
(2.5 Y 4/4); clay loam; weak coarse prisms; very hard, extremely firm, very sticky, very
plastic; slightly effervescent; moderately alkaline (pH 7.9), threads and very small
pockets (1 mm); gradual wavy; few fine roots; many fine pores.
Clca 91-134 Light olive brown (2.5 Y 5/4); olive brown (2.5 Y 4/4); clay loam; massive; very hard,
extremely firm, very sticky, very plastic; slightly effervescent, moderately alkaline
(pH 8.0), small pockets (2.3 mm); clear wavy; very few fine roots; many fine pores.
C2ca 134- Light olive brown (2.5 Y 5.5/4); light olive brown bulk (2.5 Y 5/4), pale yellow lime
streaks (2.5 Y 8/4); clay loam; massive; hard, firm, very sticky, very plastic; slightly
effervescent; moderately alkaline (pH 8.0), large pockets (7 mm); not reached boundary.
Remarks: The Al thickness ranges 15-25 cm, solum depth 90-105 cm, thickness of B 66-75.
332
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TABLE 11.2. PROFILE DESCRIPTIONS FOR ZAPS II. THURLOW CLAY LOAM SOIL SERIES, PIT WEST OF CONTROL
Depth
Horizon (cm) Description
All 0-2 Grayish brown (10 YR 5.5/2) dry; very dark grayish brown (10 YR 3/2) moist; loam; struc-
tureless; loose, nonsticky, nonplastic; noneffervescent; slightly acid (pH 6.1); abrupt
wavy boundary; many fine roots.
A12 2-12 Dark brown (10 YR 4/3) dry and moist; clay loam; thin platy; firm, hard, slightly sticky
and slightly plastic to plastic; noneffervescent; slightly acid (pH 6.4); clear wavy
boundary; many fine roots.
B21 12-30 Yellowish brown (10 YR 5/4) dry; dark brown (10 YR 4/3) moist; clay loam; moderate,
medium prisms breaking to strong medium and coarse subangular blocky structure; hard,
firm, sticky, and slightly plastic to plastic; noneffervescent; neutral (pH 7.0); clear,
wavy boundary; many fine roots.
B22 30-44 Brown crushed (10 YR 5/3) dry; dark brown coats (10 YR 3.5/3) dry; dark brown crushed
(10 YR 4/3) moist; very dark grayish brown coats (10 YR 3/2) moist; clay loam;
strong coarse prisms breaking to strong very coarse subangular blocky structure; very
hard, very firm, sticky and plastic; noneffervescent; neutral (pH 7.3); clear, wavy
boundary; many fine roots.
B23ca 44-80 Yellowish brown coats (10 YR 5/4) dry, peds too hard to crush; dark brown coats (10 YR
4/3) moist, peds too hard to crush; clay loam; very strong medium prisms breaking to
very strong medium subangular blocky structure; very hard, extremely firm, sticky and
slightly plastic to plastic; effervescent, pockets and riffins of lime; moderately
alkaline (pH 8.1); clear, wavy boundary; common fine roots.
B3 80-100 Yellowish brown coats (10 YR 5/4) with patches of dark brown (10 YR 4/3) and very dark
grayish brown (10 YR 3/2) dry, peds too hard to crush; dark brown coats (10 YR 3/3)
moist; clay loam; weak medium prisms breaking to moderate medium subangular blocky
structure; very hard, extremely firm, slightly sticky to sticky and plastic; non-
effervescent (sic), a few fine wires of lime present but not enough to cause
effervescence; moderately alkaline (pH 7.9); pockets of iron and gypsium; diffuse,
wavy boundary; common fine roots.
Cl 100-152 Brown (10 YR 5/3) dry; dark brown (10 YR 4/3) moist; clay loam; structureless; very hard,
very firm, slightly sticky and slightly plastic to plastic; effervescent, lime in small
pockets; moderately alkaline (pH 8.0); few fine roots.
Remarks: This pit is probably a representative Thurlow profile and lies at the west end of the ZAPS II site.
The soils to the east of this pit are underlain first (moving eastward) by one buried profile and
at the eastern end of the site two buried profiles are represented. However, the current, pedo-
genic profiles of these soils are similar to the profile described herein. The depth of the
Thurlow solum ranges from 100 cm (described here) to 28 cm however some current pedogenic activity
is apparent in the shallower buried A horizons.
-------
TABLE 11.3. PHYSICAL CHARACTERISTICS OF ZAPS I SITE SOILS
Sample
number
322P
324P
325P
32 6P
327P
328P
32 9P
32 3P
405P
336P
337P
406P
338P
33 9P
340P
341P
Horizon
All
A12
B21
B22
B3ca
Clca
C2ca
All
All
A12
A3
A3
B21
B22
B23ca
B3ca
All
A12
B2
B3
C
Depth
(cm)
0-15
15-25
25-39
39-79
79-91
91-134
134±
0-9
0-9
9-15
15-32
15-32
32-49
49-67
67-86
86-104
0-2
2-24
24-77
77-92
92+
Gravel
(%)
ZAPS
1.96
1.85
1.50
0.17
0.10
1.89
2.37
ZAPS I
2.12
2.12
3.23
1.82
1.82
1.99
4.03
0.30
0.23
ZAPS I,
Sand Silt
f°/\ (
-------
TABLE 11.4. WATER-HOLDING CAPACITY OF ZAPS I SITE SOILS
Sample
number
Horizon
Depth
(cm)
0 bar
0.33 bar
1 bar
15 bar
ZAPS I, West Pit
322P
324P
325P
326P
327P
328P
329P
All
A12
B21
B22
B3ca
Clca
C2ca
0-15
15-25
25-39
39-79
79-91
91-134
134+
38.32
36.37
47.48
61.34
55.64
54.47
53.48
38.23
38.41
47.27
61.04
59.01
48.96
53.77
14.40
11.50
12.45
20.72
17.38
22.45
23.04
12.00
12.30
13.69
24.41
16.98
20.91
21.06
9.75
7.73
9.96
17.43
14.76
19.01
15.63
8.75
7.57
9.51
18.04
14.95
16.62
15.81
4.19
4.28
3.94
11.26
9.02
9.67
9.66
4.40
4.52
4.01
10.79
9.51
9.75
9.20
ZAPS I, Middle Pit
GJ
Ul
323P
405P
336P
337P
406P
338P
339P
34 OP
341P
All
All
A12
A3
A3
B21
B22
B23ca
B3ca
0-9
0-9
9-15
15-32
15-32
32-49
49-67
67-86
86-104
50.14
61.31
49.87
59.18
65.66
59.96
56.88
50.87
50.44
49.81
56.35
61.19
56.25
56.69
19.47
18.18
20.88
25.62
16.02
22.79
22.94
20.34
17.71
18.42
23.92
25.49
21.57
23.17
14.36
11.53
15.24
19.05
20.62
18.06
18.05
13.66
13.53
15.32
19.35
17.96
18.37
17.91
6.58
8.29
9.00
12.06
12.90
11.55
11.31
6.46
7.56
9.01
11.58
13.12
11.39
10.87
% wt
-------
TABLE 11.5. CHEMICAL CONSTITUENTS OF ZAPS I SITE SOILS
Sample
number
Horizon
Depth
(cm)
Organic
matter
pH
Lime
N
Total P
Inorganic
P
Bicarbonate
P
ZAPS I, West Pit
322P
324P
325P
326P
327P
328P
329P
All
A12
B21
B22
B3ca
Clca
C2ca
0-15
15-25
25-39
39-79
79-91
91-134
134+
1.2
0.6
1.0
0.6
0.4
0.4
0.4
6.1
6.1
5.9
7.0
7.9
8.0
8.0
0.0
0.0
0.0
0.0
1.2
3.0
2.8
0.078
0.043
0.081
0.049
0.030
0.030
0.031
0.030
0.028
0.035
0.041
0.035
0.034
0.038
0.017
0.020
0.021
0.032
0.030
0.030
0.035
OJ
OJ
ZAPS I, Middle Pit
323P
405P
336P
337P
406P
338P
339P
340P
34 IP
All
All
A12
A3
A3
B21
B22
B23ca
B3ca
0-9
0-9
9-15
15-32
15-32
32-49
49-67
67-86
86-104
1.8
2.2
1.3
1.0
1.2
1.1
1.0
0.9
0.9
5.8
5.7
6.1
6.2
6.2
6.8
7.1
7.7
7.9
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
0.8
0.119
0.128
0.089
0.079
0.081
0.078
0.077
0.065
0.059
0.034
0.036
0.030
0.030
0.030
0.038
0.045
0.043
0.045
0.020
0.023
0.016
0.016
0.016
0.025
0.031
0.031
0.033
1
4
1
1
1
1
4
2
1
5
1
2
3
2
1
1
ZAPS I, Northwest Pit
All
A12
B2
B3
C
0-2
2-24
24-77
77-92
92+
4.0
1.6
0.8
0.6
0.5
6.1
5.8
7.3
7.8
8.1
0.0
0.0
0.5
0.8
1.8
0.275
0.103
0.070
0.046
0.040
0.051
0.052
0.040
0.037
0.040
0.021
0.034
0.030
0.028
0.035
12
1
1
1
1
-------
TABLE 11.6. EXCHANGEABLE IONS OF ZAPS I SITE SOILS
Co
Sample
number
322P
324P
325P
326P
327P
328P
329P
Horizon
All
A12
B21
B22
B3ca
Clca
C2ca
Depth
(cm)
0-15
15-25
25-39
39-79
79-91
91-134
134+
so,
0.1
2.0
0.6
<0. 1
<0. 1
0.7
1.4
CEC
ZAPS I,
7.2
6.7
14.2
24.6
17.3
17.3
17.8
CA
West Pit
4.4
3.1
4.7
9.4
—
—
—
Mg
1.8
2.2
6.5
14.5
—
—
— —
Na
<0.1
<0. 1
0.1
0.2
0.2
0.3
0.4
K
0.4
0.3
0.4
0.3
0.3
0.3
0.3
K
(ppm)
165
100
165
125
105
120
110
ZAPS I, Middle Pit
323P
405P
336P
337P
406P
338P
339P
34 OP
341P
All
All
A12
A3
A3
B21
B22
B23ca
B3ca
0-9
0-9
9-15
15-32
15-32
32-49
49-67
67-86
86-104
0.5
1.4
0.3
0.6
1.9
<0. 1
1.7
<0. 1
<0. 1
13.8
13.6
14.2
14.6
19.8
21.8
26.6
21.9
19.7
7.8
7.3
7.5
6.5
8.9
9.3
10.5
—
•— M
2.8
3.2
4.4
5.5
6.6
10.2
14.4
—
— _*
<0.1
0.1
0.1
0.1
0.1
0.3
0.6
0.7
0.8
0.5
0.6
0.4
0.3
0.4
0.4
0.4
0.4
0.4
200
225
175
135
145
140
165
140
140
meq
100 g-1 soil.
-------
TABLE 11.7- PHYSICAL CHARACTERISTICS OF ZAPS II SITE SOILS
Horizon
All
A12
B21
B22
B23ca
B3
Cl
All
A12
B21
B22
IIA1
IIB2
IIIA1
IIIB2
Cl
Depth
(cm)
ZAPS II
0-2
2-12
12-30
30-44
44-80
80-100
100+
ZAPS
0-3
3-13
13-29
29-47
47-63
63-75
75-112
112-125
125+
Sand Silt
Clay
*
Texture
, Pit West of Control
34
32
34
43
37
43
38
II,
36
32
27
34
30
28
27
36
38
ZAPS II
All
A12
B2
IIA1
IIB2
IIB3
IIC1
All
A12
B2
IIA1
IIB21
IIB22
IIB3
IIC
All
A12
B21
B22
IIB23
IIB24
IIIA1
IIIB2
0-2
2-11
11-40
40-56
56-88
88-130
130+
ZAPS
0-3
3-11
11-28
28-43
43-65
65-79
79-118
118+
ZAPS
0-3
3-11
11-24
24-40
40-73
73-119
119-136
136-152
29
25
26
30
26
30
33
II,
28
27
—
22
22
25
20
24
II,
24
24
20
26
20
32
22
26
41
34
33
28
28
27
32
Control-Low Pit
39
34
34
32
27
27
32
28
30
, Low-Medium Pit
35
33
35
33
29
33
32
Medium-High Pit
40
32
—
35
36
39
39
36
Pit East of High
40
40
45
42
44
33
37
37
25
34
33
29
35
30
30
25
34
39
34
43
45
41
36
32
36
42
39
37
45
37
35
32
41
—
43
42
36
41
40
36
36
35
32
36
35
41
37
L
CL
CL
CL
CL
CL
CL
L
CL
CL
CL
C
C
C
CL
CL
CL
C
CL
CL
C
CL
CL
CL
C
—
C
C
CL
C
C
CL
CL
CL
CL
CL
CL
C
CL
C = clay, L = loam, Si = silt, S = sand.
338
-------
TABLE 11.8. CHEMICAL CONSTITUENTS OF ZAPS II SITE SOILS
Horizon
All
A12
B21
B22
B23ca
B3
Cl
All
A12
B21
B22
IIA1
IIB2
IIA1
IIB2
Cl
All
A12
B2
IIA1
IIB2
IIB3
IIC1
All
A12
B2
IIA1
IIB21
IIB22
IIB3
IIC
All
A12
B21
B22
IIB23
IIB24
IIIA1
IIIB2
Depth
(cm)
0-2
2-12
12-30
30-44
44-80
80-100
100+
0-3
3-13
13-29
29-47
47-63
63-75
75-112
112-125
125+
0-2
2-11
11-40
40-56
56-88
88-130
130+
0-3
3-11
11-28
28-43
43-65
65-79
79-118
118+
0-3
3-11
11-24
24-40
40-73
73-119
119-136
136-152
Organic Total
matter Lime N P
(%) PH (%) (%) (%)
ZAPS II, Pit West of Control
5.8 6.1 <0.1 0.319 0.074
2.5
1.5
1.1
1.0
1.2
1.4
4.0
1.3
1.6
0.9
1..0
1.3
3.2
1.4
0.8
0.7
1.8
1.3
1.4
1.1
0.9
0.8
4.2
1.9
—
3.0
2.0
1.3
1.7
1.3
4.8
2.0
1.7
5.4
1.9
0.9
1.0
2.4
6.4
7.0
7.3
8.1
7.9
8.0
ZAPS II,
6.3
6.6
7.7
7.8
7.7
7.8
7.8
8.3
8.3
ZAPS II
7.9
6.6
7.4
7.9
7.8
8.4
8.4
ZAPS II,
6.8
6.9
—
7.8
7.8
7.9
8.4
8.4
ZAPS II,
7.0
7.2
7.8
6.6
7.6
7.8
7.8
8.1
<0.1 0.153 0.055
<0.1 0.119 0.053
0.7 0.090 0.048
1.2 0.083 0.045
1.8 0.082 0.057
4.8 0.080 0.060
Control-Low Pit
<0.1 0.261 0.068
<0.1 0.102 0.049
0.8 0.107 0.054
1.2 0.074 0.048
1.1 0.075 0.038
1.1 0.098 0.045
2.0 0.187 0.061
5.4 0.089 0.057
4.7 0.061 0.057
, Low-Medium Pit
4.7 0.054 0.057
<0.1 0.143 0.055
1.2 0.085 0.058
1.1 0.095 0.049
1.4 0.075 0.051
4.7 0.066 0.049
8.2 0.052 0.054
Medium-High Pit
<0.1 0.261 0.071
<0.1 0.142 0.059
— — -
2.3 0.154 0.059
2.9 0.120 0.061
2.4 0.085 0.060
3.7 0.109 0.065
5.2 0.065 0.061
Pit East of High
<0.1 0.285 0.076
<0.1 0.128 0.061
2.6 0.110 0.060
<0.1 0.327 0.079
3.2 0.123 0.065
1.4 0.072 0.059
2.1 0.070 0.059
3.4 0.115 0.058
Inorganic
P
(%)
0.044
0.040
0.040
0.036
0.037
0.043
0.047
0.040
0.040
0.038
0.040
0.024
0.032
0.040
0.043
0.049
0.044
0.041
0.043
0.035
0.041
0.039
0.045
0.044
0.043
—
0.040
0.044
0.050
0.048
0.047
0.043
0.049
0.045
0.048
0.050
0.047
0.046
0.041
Bicarbonate
P
(%)
10
2
1
1
1
1
3
13
2
1
1
1
1
7
2
2
1
1
1
1
1
1
4
10
1
—
2
1
1
1
2
3
1
1
8
1
1
1
1
339
-------
E
o
if)
O
i
O
01
UJ
o
CO
28
24
20
16
12
8
4
28
24
20
16
12
8
4
Control
Medium
Low
High
Mar Apr May Jun Jul Aug Sep
Mar Apr May Jun Jui Aug Sep
Figure 11.1. Seasonal dynamics of soil water (cm) for ZAPS I, 1975-1977
E
o
in
O
UJ
I
O
CO
32
28
24
20
16
12
8
4
28
24
20
16
12
8
4
1976
1977
Control
i r
Medium
Low
i i
i i
High
Mar Apr May Jun Jul Aug Sep
Mar Apr May Jun Jul Aug Sep
Figure 11.2. Seasonal dynamics of soil water (cm) for ZAPS II, 1976-1977,
340
-------
TABLE 11.9. SEASONAL DYNAMICS OF SOIL WATER, ZAPS I, 1975
Treatment
Control
Low
Medium
High
Depth
(cm)
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
12 May
3.73 ± 0.07
3.73 ± 0.16
4.03 ± 0.12
4.49 ± 0.17
3.73 ± 0.27
3.58 ± 0.27
3.31 ± 0.20
26.60
3.68 ± 0.34
3.69 ± 0.22
4.16 ± 0.17
4.18 ± 0.23
3.96 + 0.22
3.62 ± 0.09
3.87 ± 0.02
27.15
3.89 ± 0.11
3.73 ± 0.03
3.83 ± 0.22
3.60 ± 0.66
2.81 ± 0.68
2.45 ± 0.36
2.83 ± 0.48
23.14
26 May
3.53 ± 0.18
3.51 ± 0.09
4.13 ± 0.19
4.28 ± 0.27
3.66 ± 0.15
3.60 ± 0.30
3.08 ± 0.49
25.68
3.37 ± 0.03
3.49 ± 0.12
3.73 ± 0.11
4.07,± 0.13
3.27~± 0.32
2.54 ± 0.16
2.48 ± 0.07
22.95
3.33 ± 0.16
3.59 ± 0.15
4.53 ± 0.61
3.76 ±. 0.19
3.62 + 0.03
3.57 ± 0.05
3.46 ± 0.06
25.86
3.60 ± 0.20
3.25 + 0.37
4.12 ± 1.15
3.17 ± 0.50
2.47 ± 0.60
2.55 ± 0.52
2.58 ± 0.37
21.74
10 June
3.57 ± 0.14
3.12 ± 0.04
4.32 ± 0.21
4.13 ± 0.40
3.73 ± 0.03
3.14 ± 0.13
2.84 ± 0.10
24.85
3.24 ± 0.09
3.19 ± 0.14
3.93 ± 0.09
4.33 ± 0.13
3.67 ± 0.11
3.18 ± 0.17
2.56 ± 0.13
24.10
3.28 ± 0.25
3.27 ± 0.15
3.69 ± 0.42
3.75 ± 0.22
3.58 ± 0.06
3.55 ± 0.07
2.86 ± 0.06
23.99
3.58 ± 0.18
3.32 ± 0.04
3.79 ± 0.22
3.77 + 0.23
3.21 + 0.36
2.97 ± 0.43
2.46 ± 0.71
23.11
22 June
3.84 ± 0.18
3.71 ± 0.12
4.00 ± 0.09
4.01 ± 0.13
3.49 + 0.24
3.15 ± 0.47
2.77 ± 0.35
24.98
3.66 ± 0.10
3.54 ± 0.14
3.88 ± 0.10
4.15 ± 0.15
3.72 ± 0.02
3.11 ± 0.17
2.64 ± 0.48
24.71
3.51 ± 0.12
3.65 ± 0.16
4.21 ± 0.18
3.92 ± 0.14
3.71 ± 0.17
3.62 ± 0.09
3.78 ± 0.19
26.41
4.04 ± 0.11
3.87 ± 0.17
3.75 ± 0.13
4.02 ± 0.17
3.46 ± 0.30
3.42 ± 0.50
3.17 ± 0.48
25.73
7 July
1.38 ± 0.06
2.07 ± 0.13
2.83 ± 0.36
3.45 ± 0.44
3.04 ± 0.27
2.94 ± 0.09
2.76 ± 0.07
18.47
1.16 ± 0.15
2.36 ± 0.15
3.38 ± 0.15
3.67 ± 0.38
3.08 ± 0.27
2.85 ± 0.26
2.76 ± 0.27
19.25
1.39 ± 0.15
2.78 ± 0.17
3.27 ± 0.12
3.30 ± 0.08
3.28 ± 0.08
3.43 ± 0.11
3.30 t 0.03
20.76
1.59 ± 0.12
2.68 ± 0.38
3.03 ± 0.10
3.52 ± 0.06
3.43 ± 0.01
2.79 ± 0.48
3.08 ± 0.26
20.11
21 July
1.20 ± 0.07
1.46 ± 0.13
1.98 ± 0.02
2.68 ± 0.05
2.86 ± 0.25
2.77 ± 0.36
2.62 + 0.37
15.57
0.65 ± 0.05
0.95 ± 0.20
2.11 + 0.08
2.65 ± 0.24
2.58 ± 0.05
2.37 ± 0.09
2.18 + 0.08
13.49
0.98 ± 0.16
1.45 ± 0.09
2.39 ± 0.04
2.82 ± 0.10
2.95 ± 0.06
3.17 ± 0.01
2.65 ± 0.40
16.40
1.04 ± 0.10
1.40 ± 0.15
1.97 ± 0.08
2.82 + 0.13
2.77 ± 0.07
2.71 ± 0.05
3.40 ± 0.83
16.11
5 August
0.58 t 0.01
0.97 ± 0.13
1.71 t 0.14
1.72 ± 0.20
1.94 ± 0.11
2.55 ± 0.07
2.61 ± 0.28
12.08
0.58 ± 0.04
1.05 ± 0.09
1.54 ± 0.13
1.94 ± 0.11
1.90 ± 0.13
2.14 ± 0.24
2.81 ± 0.69
11.96
0.86 ± 0.08
1.94 ± 0.51
1.90 ± 0.18
2.17 ± 0.17
1.91 ± 0.09
2.12 ± 0.10
2.40 ± 0.30
13.30
0.88 ± 0.04
1.16 ± 0.14
1.82 ± O.'ll
2.08 ± 0.22
1.94 ± 0.19
1.84 ± 0.40
2.03 ± 0.15
11.75
18 August
1.33 t 0.18
1.37 ± 0.05
1.98 ± 0.09
2.09 ± 0.29
2.07 ± 0.17
2.33 ± 0.06
2.64 i 0.23
13.81
1.15 ± 0.05
1.28 ± 0.13
1.72 ± 0.09
2.11 ± 0.07
1.93 ± 0.14
1.99 ± 0.22
2.02 ± 0.20
12.21
1.37 ± 0.13
1.66 ± 0.11
2.08 ± 0.10
2.03 ± 0.14
2.08 + 0.09
2.16 ± 0.11
2.39 ± 0.08
13.76
1.12 ± 0.09
1.39 ± 0.11
1.78 + 0.09
2.21 ± 0.18
2.68 ± 0.65
1.98 + 0.01
2.09 + 0.07
13.36
2 September
0.83 ± 0.04
1.34 ± 0.19
1.72 ± 0.03
1.87 ± 0.28
1.64 ± 0.56
2.15 ± 0.09
2.15 ± 0.03
11.71
0.72 ± 0.10
1.02 ± 0.08
1.59 ± 0.03
1.94 ± 0.08
1.93 ± 0.10
2.02 ± 0.20
1.62 ± 0.36
10.85
0.89 ± 0.09
1.43 ± 0.05
1.79 ± 0.08
1.88 ± 0.02
1.76 ± 0.03
1.96 ± 0.15
2.35 ± 0.35
12.05
0.75 ± 0.25
1.34 ± 0.10
1.90 ± 0.10
1.52 ± 0.56
2.01 ± 0.26
1.85 ± 0.13
1.99 ± 0.32
11.37
15 September
0.43 ± 0.05
1.19 ± 0.07
1.88 ± 0.30
1.86 ± 0.30
1.80 ± 0.13
2.09 ± 0.08
2.26 ± 0.08
11.51
0.43 ± 0.03
1.01 ± 0.07
1.55 ± 0.11
1.77 ± 0.10
1.54 + 0.07
1.66 ± 0.12
1.71 ± 0.15
9.67
0.65 ± 0.11
1.30 ± 0.11
1.71 ± 0.04
1.59 ± 0.04
1.61 ± 0.01
1.72 ± 0.07
1 .80 ± 0.19
10.37
0.76 ± 0.05
1.22 ± 0.14
1.74 ± 0.03
1 .90 ± 0.08
1.87 ± 0.07
1.86 ± 0.08
1.83 ± 0.20
11.19
cm, X ± SE.
-------
TABLE 11.10. SEASONAL DYNAMICS OF SOIL WATER, ZAPS I, 1976*
GJ
Treatment
Control
Low
Medium
High
Depth
(cm)
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
20 March
3.55 ± 0.04
3.21 ± 0.14
3.35 ± 0.36
2.69 ± 0.40
3.64 ± 0.23
3.27 £ 0.51
3.42 ± 0.95
3.01 ± 0.00
2.19 i 0.00
3.57 ± 0.08
2.82 ± 0.50
3.14 ± 0.05
3.26 ± 0.25
1.90 ± 0.10
1.96 ± 0.12
4.12 ± 0.24
3.64 ± 0.07
3.39 ± 0.45
3.41 ± 0.70
2.89 ± 0.69
2.57 ± 0.50
14 April
3.48 ± 0.13 3.
3.05 ± 0.17 3.
3.61 ± 0.82 3.
2.96 ± 1.01 3.
3.90+0.00 2.
2.42 ± 0.00 2.
3.
3.
3.
3.
2.
1.
3.
3.
3.
3.
3.
2.
2.
3.
3.
3.
3.
2.
2.
3.
20 April
78 ±
80 ±
56 ±
04 ±
86 t
94 ±
63 ±
60 ±
92 ±
30 ±
04 ±
89 ±
61 t
66 ±
72 i
41 ±
31 ±
85 ±
75 ±
23.
86 ±
71 ±
92 t
47 ±
73 ±
74 ±
29 ±
23.
0.19
0.05
0.72
0.95
0.58
0.37
0.09
0.02
0.24
0.46
0.08
0.06
0.03
0.19
0.55
0.59
0.62
0.67
0.00
32
0.13
0.25
0.24
0.66
0.49
0.50
0.00
71
16 May
3.36 ± 0.16
2.98 ± 0.22
4.45 ± 0.27
2.91 ± 0.33
3.99 ± 1.05
3.47 ± 0.38
3.44 ± 1.11
24.58
3.26 ± 0.05
3.36 ± 0.11
3.87 ± 0.07
3.86 ± 0.32
3.05 ± 0.17
2.75 ± 0.10
2.05 ± 0.42
22.19
3.38 ± 0.19
3.38 ± 0.30
3.39 ± 0.61
3.27 ± 0.06
3.29 ± 0.60
3.17 ± 0.60
2.36 + 0.80
22.24
3.37 ± —
3.28 ± —
3.50 ± 0.28
3.13 ± 0.52
2.95 ± 0.50
2.93 ± 0.33
2.44 ± 0.13
21.60
1 June
3.09 + 0.10
3.52 ± 0.23
3.91 ± 0.29
2.47 ± 0.21
2.83 ± 0.73
2.32 + 0.15
2.54 ± 0.25
20.67
3.29 ± 0.07
3.32 + 0.04
3.83 ± 0.17
4.17 + 0.19
3.26 ± 0.19
2.67 ± 0.30
1.96 ± 0.12
22.50
3.10 + 0.19
3.75 ± 0.26
3.98 ± 0.07
3.58 ± 0.38
2.99 ± 0.33
1.97 ± 0.04
1.70 ± 0.10
21.08
3.48 ± 0.16
3.56 + 0.14
3.78 ± 0.12
4.00 ± 0.07
2.92 ± 0.35
2.95 ± 0.52
2.81 ± 0.35
23.49
13 June
2.62 ± 0.
2.54 ± 0.
3.21 ± 0.
2.92 ± 0.
2.70 ± 0.
2.72 ± 0.
2.59 ± 0.
19.31
2.38 ± 0.
2.37 ± 0.
3.05 ± 0.
3.27 ± 0.
2.58 ± 0.
2.44 + 0.
2.25 ± 0.
18.34
2.45 ± 0.
2.65 ± 0.
3.35 ± 0.
3.30 + 0.
3.25 ± 0.
3.12 ± 0.
2.79 ± 0.
20.93
21 June
19 3.49 ± 0.17
27 3.27 + 0.28
25 3.61 ± 0.55
46 3.82 ± 0.67
41 3.20 ± 0.66
44 3.39 ± 0.75
34 2.98 ± 0.40
23.75
13
07
15
20
14
02
17
18
14
05
05
07
14
35
2.49 ± 0.21
2.53 ± 0.19
3.24 ± 0.12
3.51 ± 0.08
3.00 ± 0.35
2.78 ± 0.31
2.23 ± 0.29
19.78
24 June
3.63 + 0.24
2.99 ± 0.38
3.35 ± 0.61
3.10 ± 0.56
2.96 + 0.56
2.69 ± 0.45
2.65 ± 0.34
21.36
3.45 ± 0.11
3.55 ± 0.07
4.13 + 0.39
3.98 ± 0.58
3.49 ± 0.17
2.67 + 0.29
3.28 ± 0.56
24.55
3.38 ± 0.11
3.44 ± 0.18
3.80 ± 0.20
3.63 + 0.16
2.74 ± 0.50
3.08 ± 0.66
2.70 ± 0.71
22.76
3.84 ± 0.16
4.01 + 0.24
3.94 ± 0.18
3.92 t 0.27
3.15 ± 0.48
2.72 ± 0.49
2.27 ± 0.50
23.86
1 July
2.46 ± 0.25
3.12 ± 0.11
3.04 + 0.84
3.23 ± 0.47
2.82 + 0.32
2.65 ± 0.31
2.68 + 0.45
20.01
-------
TABLE 11.10. CONTINUED
OJ
-P-
CO
Treatment
Control
Low
Medium
High
Depth
(cm)
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
8 July 14 July
1.66 ± 0.25 1.85 ± 0.28
2.26 ± 0.15 1.71 ± 0.02
2.85 ± 0.62 2.71 ± 0.49
3.00 ± 0.65 2.61 ± 0.58
2.80 ± 0.49 2.50 ± 0.34
2.72 ± 0.44 2.42 ± 0.31
2.74 ± 0.59 2.44 ± 0.34
18.02 16.24
1.43 1 0.09
2.51 ± 0.12
3.24 ± 0.14
3.65 ± 0.24
2.98 ± 0.25
2.71 ± 0.14
2.45 i 0.18
18.97
1.60 ± 0.20
2.40 ± 0.20
3.15 ± 0.03
3.27 ± 0.20
3.42 ± 0.17
2.97 ± 0.34
2.32 ± 0.43
19.12
1.77 ± 0.15
2.61 ± 0.20
3.37 ± 0.25
3.65 ± 0.15
3.08 ± 0.15
2.71 ± 0.39
2.58 ± 0.44
19.77
22 July 29 July
1.89 ± 0.29 0.87 t 0.09
1.65 ± 0.12 1.47 ± 0.21
2.49 ± 0.25 1.65 ± 0.47
2.77+0.50 1.64 ± 0.45
2.87 ± 0.42 2.00 ± 0.37
2.91 ± 0.28 1.94 + 0.19
2.94 ± 0.30 2.13 ± 0.34
17.51 11.70
/L.86 + 0.07
2.06 ± 0.06
2.41 ± 0.24
3.10 ± 0.16
2.75 ± 0.14
2.56 ± 0.17
2.54 ± 0.14
17.27
1.99 ± 0.27
2.10 ± 0.13
2.71 i 0.16
2.74 ± 0.19
2.64 ± 0.31
2.94 ± 0.16
3.00 ± 0.36
18.13
2.03 ± 0.06
1.87 ± 0.16
2.56 ± 0.16
3.23 ± 0.33
2.85 ± 0.58
2.46 ± 0.30
2.44 ± 0.38
17.45
5 August
1.02 ± 0.18
1.30 ± 0.02
1.95 ± 0.27
1.94 ± 0.52
2.21 ± 0.09
1.85 i 0.18
2.17 ± 0.23
12.45
1.07 ± 0.03
1.21 ± 0.03
1.62 ± 0.18
2.33 ± 0.02
2.31 ± 0.09
2.30 ± 0.10
2.36 ± 0.15
13.21
] .18 i 0.15
1.53 ± 0.05
1.86 ± 0.12
1.87 ± 0.10
2.05 ± 0.16
1.97 ± 0.15
2.05 ± 0.25
12.50
2.17 t 0.47
1.96 ± 0.83
2.36 ± 0.51
2.75 i 0.61
2.18 i 0.10
2.16 ± 0.02
3.14 i 0.97
16.71
13 August 19 August
0.56 ± 0.07 0.59 ± 0.23
0.88 ±0.10 1.05 ±0.19
1.52 ± 0.29 1.91 ± 0.10
1.77 ± 0.19 1.87 ± 0.31
1.77 ± 0.29 1.99 ± 0.20
2.11 ± 0.09 1.86 ± 0.08
1.89 ± 0.19 1.86 + 0.22
10.49 11.14
0.52 + 0.05
1.02 ± 0.14
1.60 ± 0.20
2.08 ± 0.01
1.93 ± 0.04
1.94 ± 0.21
1.91 ± 0.09
11.01
0.62 ± 0.14
1.12 ± 0.15
1.50 ± 0.01
1.62 ± 0.02
1.58 ± 0.11
1.57 ± 0.14
1.70 ± 0.20
9.71
0.67 ± 0.07
1.24 ± 0.15
1.71 ± 0.05
1.92 ± 0.08
1.65 ± 0.05
1.84 ± 0.12
1.97 ± 0.26
11.00
26 August 6 September
0.63 ± 0.07 0.48 t 0.08
1.29 ± 0.26 0.97 ± 0.09
1.73 ± 0.17 1.39 ± 0.18
1.99 ± 0.32 1.76 ± 0.24
1.85 ± 0.12 1.61 i 0.25
1.72 ± 0.09 1.41 t 0.08
2.24 + 0.27 1.80 i 0.26
11.45 9.42
0.49 i 0.08
1.07 ± 0.03
1.44 ± 0.14
1.88 ± 0.09
1.63 ± 0.03
1.57 i 0.10
1.71 ± 0.19
9.78
0.60 ± 0.14
1 .03 ± 0.16
1.43 ± 0.10
1.58 ± 0.09
1.46 ± 0.03
1.59 ± 0.16
1.69 ± 0.19
9.37
0.61 i 0.10
1.11 ± 0.10
1.55 ± 0.10
1.76 ± 0.08
1.38 ± 0.00
li53 ± 0.00
1 .63 ± 0.00
9.57
cm, X ± SE.
-------
TABLE 11.11 SEASONAL DYNAMICS OF SOIL WATER, ZAPS I, 1977
OJ
Treatment
Control
Low
Med ium
High
Depth
(cm)
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
14 Aprtl
3.76 ± 0.19
3.23 ± 0.13
4.40 t 0.18
4.50 ± 0.25
4.10 ± 0.21
3.75 ± 0.28
3.52 ± 0.42
27.26
3.78 ± 0.29
3.34 ± 0.05
3.78 ± 0.16
4.05 ± 0.01
4.08 ± 0.19
4.28 ± 0.16
3.82 ± 0.06
27.13
3.13 ± 0.11
3.46 ± 0.20
3.84 ± 0.36
4.19 ± 0.15
3.99 ± 0.05
3.91 ± 0.15
3.76 ± 0.13
26.27
3.49 ± 0.20
3.81 ± 0.15
3.98 ± 0.33
4.49 ± 0.28
4.04 ± 0.22
3.76 ± 0.44
3.76 ± 0.00
27.34
20 April 29 April
3.31 ± 0.29 1.84 ± 0.19
3.30 i 0.19 2.94 ± 0.31
3.93 ± 0.09 4.24 ± 0.17
4.44 ± 0.25 4.05 ± 0.25
3.75 ± 0.09 3.32 ± 0.29
2.43 ± 0.43 2.91 ± 0.37
2.28 ± 0.04 2.72 ± 0.47
23.44 22.03
2.07 ± 0.16
2.91 ± 0.10
3.91 ± 0.05
4.17 ± 0.09
3.99 ± 0.07
3.47 ± 0.39
2.63 i 0.89
23.15
1.84 ± 0.09
2.91 ± 0.04
3.97 ± 0.06
4.03 ± 0.08
3.71 ± 0.09
3.82 ± 0.26
3.45 ± 0.33
23.73
2.22 ± 0.18
3.33 ± 0.14
3.87 ± 0.04
4.27 ± 0.15
3.71 ± 0.12
3.76 ± 0.07
3.43 ± 0.19
24.58
5 May 12 May 17 May
1.69 ± 0.10 1.30 + 0.03 2.18 ± 0.18
2.99 ± 0.75 2.37 ± 0.36 1.96 ± 0.18
3.61 ± 0.35 3.18 ± 0.23 3.38 ± 0.09
3.95 ± 0.25 3.79 ± 0.30 3.52 ± 0.22
J.dO ± 0.10 3.37 ± 0.31 3.60 ± 0.21
3.33 ± 0.20 2.72 ± 0.50 2.93 ± 0.53
3.06 ± 0.55 2.59 ± 0.38 2.85 ± 0.62
22.42 19.32 20.41
0.99 ± 0.02
1.96 ± 0.05
3.27 ± 0.12
4.12 ± 0.10
3.69 ± 0.05
3.55 ± 0.17
3.59 ± 0.10
21.16
1.19 ± 0.18
1.89 ± 0.12
3.43 ± 0.04
3.67 ± 0.04
3.51 ± 0.09
3.71 ± 0.14
3.72 ± 0.17
21.11
1.25 ± 0.18
2.24 ± 0.19
3.43 ± 0.05
3.69 ± 0.13
3.70 ± 0.11
3.47 ± 0.12
2.91 ± 0.36
20.68
23 May
2.28 ± 0.16
2.33 ± 0.41
3.07 ± 0.18
3.63 ± 0.35
3.21 ± 0.25
2.62 ± 0.21
2.45 ± 0.21
19.59
2.13 ± 0.12
2.10 ± 0.32
2.96 ± 0.14
3.91 ± 0.16
3.64 ± 0.08
3.54 ± 0.07
3.56 ± 0.06
21.85
2.55 ± 0.10
2.09 ± 0.17
3.20 ± 0.10
3.61 ± 0.14
3.52 ± 0.14
3.59 ± 0.19
3.52 ± 0.03
22.07
2.72 ± 0.10
2.34 ± 0.15
3.31 ± 0.09
3.91 ± 0.06
3.52 ± 0.10
3.45 ± 0.12
3.45 ± 0.06
22.70
-------
TABLE 11.11. CONTINUED
OJ
Treatment
Control
Low
Medium
High
Depth
(cm) 30 May
0-15 1.59 ± 0.05
15-30 1.86 + 0.22
30-45 2.48 ± 0.12
45-60 3.10 + 0.24
60-75 3.11 ± 0.26
75-90 3.15 ± 0.30
90-105 3.05 ± 0.36
TOTAL 18<35
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
16 June 2 July
3.64 ± 0.15 1.21 ± 0.13
3.29 ± 0.06 1.86 ± 0.10
3.08 ± 0.10 2.25 ± 0.18
2.97 ± 0.16 2.80 ± 0.23
2.50 ± 0.08 2.60 ± 0.40
2.30 ± 0.10 2.51 ± 0.07
2.28 ± 0.12 2.39 ± 0.30
20.08 15.62
3.13 ± 0.13
3.26 + 0.11
3.10 ± 0.36
3.29 ± 0.30
3.05 + 0.41
3.42 ± 0.51
3.16 ± 0.64
22.42
3.37 i 0.19
3.60 ± 0.24
3.87 ± 0.23
2.75 ± 0.24
2.64 ± 0.17
2.92 ± 0.15
3.21 ± 0.17
22.36
3.57 ± 0.06
3.38 ± 0.31
3.34 ± 0.45
3.20 ± 0.12
3.14 ± 0.18
3.29 ± 0.24
3.09 ± 0.10
23.01
15 July 2 August
0.93 ± 0.19 0.68 ± 0.12
1.39 ± 0.18 1.16 ± 0.08
1.98 ± 0.28 1.44+0.09
2.46 ± 0.26 1.68 ± 0.31
2.58 ± 0.48 1.78 + 0.25
2.42 ± 0.04 1.84 ± 0.05
2.63 ± 0.12 1.85 ± 0.15
14.39 10.44
0.44 ± 0.02
0.83 ± 0.07
1.30 ± 0.10
1.76 ± 0.02
1.73 ± 0.04
1.82 ± 0.12
1.98 ± 0.05
9.86
0.57 ± 0.05
0.93 ± 0.11
1.47 ± 0.07
1.51 ± 0.11
1.52 ± 0.17
1.61 ± 0.23
1.80 ± 0.24
9.42
0.64 ± 0.12
1.03 ± 0.13
1.44 ± 0.07
1.96 ± 0.15
1.88 ± 0.28
1.97 ± 0.11
1.92 ± 0.10
10.85
18 August
0.72 ± 0.05
1.10 ± 0.10
1,82 ± 0.13
2.09 ± 0.23
2.29 i 0.15
2.37 ± 0.17
2.38 ± 0.03
12.76
0.68 ± 0.02
0.95 ± 0.10
1.37 ± 0.12
1.93 ± 0.12
1.61 ± 0.07
1.80 ± 0.17
2.08 ± 0.22
10.41
0.69 ± 0.13
1.21 ± 0.13
1.76 ± 0.15
1.71 ± 0.10
1.69 ± 0.10
1.91 ± 0.17
1.90 ± 0.17
10.87
0.62 ± 0.12
0.97 ± 0.13
1.38 ± 0.03
1.69 ± 0.05
1.76 ± 0.07
2.06 ± 0.17
1.81 ± 0.10
10.29
9 September
0.64 t 0.06
1.09 ± 0.05
1.62 ± 0.16
1.90 ± 0.36
2.24 ± 0.00
2.20 ± 0.00
2.37 ± 0.00
12.06
0.73 ± 0.03
1.33 ± 0.07
1.75 ± 0.13
1.90 ± 0.01
1.68 ± 0.11
1.76 ± 0.11
1.83 ± 0.16
10.97
0.80 ± 0.10
1.47 ± 0.02
1.87 ± 0.09
1.74 ± 0.08
1.67 ± 0.10
1.73 + 0.16
1.82 ± 0.16
11.09
0.59 ± 0.17
1.33 ± 0.13
1.72 ± 0.04
1.87 ± 0.18
1.74 ± 0.10
2.23 ± 0.08
2.10 ± 0.26
11.58
cm, X ± SE.
-------
TABLE 11.12. SEASONAL DYNAMICS OF SOIL WATER, ZAPS II, 1976
Treatment
Control
Low
Medium
High
Depth
(cm)
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
20 March
3.64 ± 0.48
2.95 ± 0.23
2.22 ± 0.36
1.97 ± 0.68
1.93 ± 0.24
1.60 ± 0.05
4.35 ± 0.37
3.08 ± 0.09
2.89 ± 0.35
2.75 ± 0.37
2.23 ± 0.05
2.41 ± 0.00
4.25 ± 0.41
3.49 ± 0.17
3.40 ± 0.51
3.11 ± 0.81
3.06 ± 0.00
2.93 ± 0.00
3.82 ± 0.11
2.61 ± 0.09
1.79 ± 0.04
1.65 ± 0.05
1.66 ± 0.04
1.68 ± 0.00
14 April
3.31 ± 0.12
2.74 ± 0.02
2.41 ± 0.55
2.42 ± 0.54
2.09 ± 0.48
1.81 ± 0.12
3.82 ± 0.37
2.61 ± 0.96
2.87 ± 0.95
2.84 ± 0.68
2.71 ± 0.68
2.90^± 0.00
3.34 ± 0.10
3.23 ± 0.48
3.39 ± 0.80
3.22 ± 0.80
3.00 ± 0.71
2.47 ± 0.22
2.80 ± 0.00
21.45
3.47 ± 0.08
2.85 ± 0.35
2.30 ± 0.26
1.86 ± 0.07
1.85 ± 0.09
1.58 ± 0.26
1.66 ± 0.00
20 April
3.67 ± 0.08
3.63 ± 0.39
2.64 ± 0.47
2.48 ± 0.47
2.11 ± 0.28
1.91 ± 0.13
TOTAL
15.57
346
-------
|ABLE 11.12. CONTINUED
Treatment
Control
Low
Medium
High
Depth
(cm)
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
5 May 16 May
4.23 ± 0.15 3.59 ± 0.09
3.41 ± 0.10 2.92 ± 0.35
3.24 ± 0.29 3.40 ± 0.16
3.04 ± 0.74 2.94 ± 0.50
1.92 ± 0.56 2.15 ± 0.50
1.81 ± 0.48 1.97 ± 0.39
1.44 ± 0.38
18.39
4.43 ± 0.12
4.34 ± 0.36
3.97 ± 0.21
2.90 ± 0.51
2.69 ± 0.54
2.17 ± 0.00
3.77 ± 0.20
3.91 ± 0.23
4.00 ± 0.19
13.48 ± 0.55
2.83 ± 0.85
2.99 ± 0.73
4.08 ± 0.07
3.83 ± 0.10
3.91 ± 0.11
3.64 ± 0.26
2.34 ± 0.22
1.66 ± 0.05
26 May
3.11 ± 0.29
3.08 ± 0.05
3.21 ± 0.12
2.55 ± 0.36
1.75 ± 0.07
1.56 ± 0.11
1.68 ± 0.14
16.93
2.87 ± 0.42
3.42 ± 0.33
3.44 ± 0.36
3.49 ± 0.65
2.64 ± 0.65
2.11 ± 0.26
1.93 ± 0.13
19.89
2.55 ± 0.11
3.04 ± 0.41
3.48 ± 0.38
3.09 ± 0.57
2.87 ± 0.72
2.92 ± 0.63
2.52 ± 0.66
20.47
2.73 ± 0.09
2.95 ± 0.17
3.29 ± 0.05
2.48 ± 0.50
1.86 ± 0.22
1.55 ± 0.02
1.55 ± 0.06
16.41
347
-------
TABLE 11.12. CONTINUED
Treatment
Control
Low
Medium
High
Depth
(cm) 2 June
0-15 2.22 ± 0.17
15-30 2.46 ± 0.16
30-45 2.36 ± 0.16
45-60 2.50 ± 0.26
60-75 1.73 ± 0.19
75-90 1.72 ± 0.03
90-105 1.94 ± 0.06
TOTAL 14.93
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
13 June 21 June
2.65 ± 0.23 3.26 ± 0.21
1.86 ± 0.09 3.18 ± 0.36
2.05 ± 0.11 3.00 ± 0.14
1.94 ± 0.10 2.17 ± 0.17
1.48 ± 0.04 1.68 ± 0.04
1.40 ± 0.06 1.55 ± 0.06
1.55 ± 0.05 1.57 ± 0.09
12.93 16.41
3.64 ± 0.14
4.16 ± 0.26
3.35 ± 0.15
2.73 ± 0.22
2.49 ± 0.17
2.16 ± 0.09
2.26 ± 0.38
20.81
3.38 ± 0.21
3.91 ± 0.20
3.84 ± 0.17
3.08 ± 0.35
2.74 ± 0.48
2.90 ± 0.47
2.75 ± 0.45
22.61
3.18 ± 0.18
3.37 ± 0.09
3.35 ± 0.16
2.40 ± 0.35
1.77 ± 0.12
1.64 ± 0.03
1.64 ± 0.04
TOTAL
17.34
348
-------
TABLE 11.12. CONTINUED
Treatment
Control
Low
Medium
High
Depth
(cm) 24 June
0-15 3.80 ± 0.16
15-30 3.27 ± 0.24
30-45 2.88 ± 0.20
45-60 2.59 ± 0.15
60-75 1.99 ± 0.05
75-90 1.60 ± 0.10
90-105 1.70 ± 0.09
TOTAL 17.84
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
1 July 8 July
2.69 ± 0.23 1.84 ± 0.10
3.11 ± 0.32 2.21 ± 0.23
2.70 ± 0.12 2.13 ± 0.19
2.44 ± 0.24 1.89 ± 0.14
1.85 ± 0.10 1.47 ± 0.07
1.59 ± 0.09 1.49 ± 0.04
1.63 ± 0.04 1.51 ± 0.14
16.01 12.54
3.01 ± 0.04
3.50 ± 0.03
2.78 ± 0.11
2.37 ± 0.22
2.22 ± 0.10
2.07 ± 0.03
2.11 ± 0.35
18.06
2.58 ± 0.13
2.96 ± 0.01
2.83 ± 0.23
2.47 ± 0.28
2.50 ± 0.42
2.60 ± 0.35
2.39 ± 0.48
18.33
2.80 ± 0.04
3.05 ± 0.17
2.72 ± 0.20
1.88 ± 0.15
1.63 ± 0.07
1.60 ± 0.05
1.65 ± 0.02
15.33
349
-------
TABLE 11.12. CONTINUED
Treatment
Control
Low
Medium
High
Depth
(cm)
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
15 July
2.50 ± 0.23
2.03 ± 0.05
1.93 ± 0.13
2.05 ± 0.14
1.79 ± 0.14
1.66 ± 0.05
1.65 ± 0.05
13.61
2.14 ± 0.24
2.29 ± 0.19
2.38 ± 0.09
2.27 ± 0.24
2.21 ± 0.01
2.03 ± 0.05
2.04 ± 0.21
15.36
2.36 ± 0.24
2.34 ± 0.13
2.52 ± 0.12
2.47 ± 0.13
2.52 ± 0.10
2.56 ± 0.14
2.38 ± 0.20
17.16
2.34 ± 0.07
1.95 ± 0.04
2.15 ± 0.12
1.91 ± 0.13
1.64 ± 0.13
1.64 ± 0.02
1.72 ± 0.08
13.35
22 July 29 July
2.20 ± 0.37 1.43 ± 0.12
2.01 ± 0.23 1.59 ± 0.24
2.03 ± 0.22 1.63 ± 0.19
2.22 ± 0.05 1.85 ± 0.03
1.87 ± 0.14 1.62 ± 0.06
1.56 ± 0.02 1.44 ± 0.05
1.69 ± 0.11 1.45 ± 0.04
13.57 11.02
1.46 ± 0.15
1.93 ± 0.10
2.08 ± 0.03
1.99 ± 0.16
1.84 ± 0.09
1.89 ± 0.13
2.01 ± 0.29
13.20
1.31 ± 0.16
1.48 ± 0.20
1.98 ± 0.16
1.97 ± 0.13
2.02 ± 0.22
2.35 ± 0.30
2.22 ± 0.30
13.34
1.22 ± 0.03
1.46 ± 0.11
1.75 ± 0.02
1.64 ± 0.15
1.59 ± 0.06
1.48 ± 0.08
1.56 ± 0.05
10.69
350
-------
TABLE 11.12. CONTINUED
Treatment
Control
Low
Medium
High
Depth
(cm) 5 August
0-15 2.02 ± 0.19
15-30 1.23 ± 0.26
30-45 1.65 ± 0.10
45-60 1.76 ± 0.05
60-75 1.63 ± 0.08
75-90 1.28 ± 0.26
90-105 1.48 ± 0.12
TOTAL 11.06
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
13 August
1.28 ± 0.13
1,60 ± 0.14
1.64 ± 0.13
1.84 ± 0.09
1.69 ± 0.05
1.62 ± 0.03
1.68 ± 0.20
11.33
1.18 ± 0.09
1.86 ± 0.13
1.94 ± 0.16
1.10 ± 0.13
1.48 ± 0.19
1.94 ± 0.15
1.06 ± 0.06
1.37 ± 0.12
1.50 ± 0.09
19 August
1.05 ± 0.07
1.45 ± 0.15
1.50 ± 0.11
1.52 ± 0.08
1.49 ± 0.02
1.41 ± 0.05
1.51 ± 0.20
9.93
351
-------
TABLE 11.12. CONTINUED
Depth
Treatment (cm)
Control 0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
Low 0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
Medium 0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
High 0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
26 August 3 September 10 September
1.25 ±
1.58 ±
1.54 ±
1.80 ±
1.61 ±
1.61 ±
1.60 ±
1.
1.
2.
2.
2.
1.
2.
1.
1.
1.
1.
2.
2.
1.
11
39
98
05
26
03
99
12
13
22
67
91
95
02
06
88
0.09 1.01 ± 0.05 1.
0.18 1.23 ± 0.09 1.
0.13 1.32 ± 0.21 1.
0.03 1.46 ± 0.07 1.
0.10 1.42 ± 0.01 1.
0.04 1.26 ± 0.06 1.
0.10 1.28 ± 0.14 1.
.00
+
+
+
+
+
+
+
•
+
+
+
+
+
+
+
12.
1.
1.
1.
1.
1.
1.
1.
11
55
70
51
62
63
72
10
+
+
+
+
+
+
+
0.
0.
0.
0.
0.
0.
0.
82
0.
0.
0.
0.
0.
0.
0.
71
0.
0.
0.
0.
0.
0.
0.
8.
12
13
06
21
22
14
20
12
12
09
12
17
04
06
08
18
06
05
04
05
15
,97
1.
1.
2.
2.
1.
1.
2.
1.
1.
1.
1.
2.
2.
2.
1.
1.
1.
1.
1.
1.
1.
.83
21
42
44
64
44
39
47
10
20
93
11
07
82
95
01
13
17
67
95
90
00
12
14
12
05
25
59
57
43
37
48
9
+
+
+
+
+
+
+
•
+
+
+
+
+
+
+
•
+
+
+
+
+
+
+
•
+
+
+
+
+
+
+
•
0.
0.
0.
0.
0.
0.
0.
02
0.
0.
0.
0.
0.
0.
0.
08
0.
0.
0.
0.
0.
0.
0.
95
0.
0.
0.
0.
0.
0.
0.
72
09
22
09
05
06
04
09
07
08
06
19
07
05
18
19
27
15
16
22
15
21
08
15
08
09
02
05
10
cm, X ± SE.
352
-------
TABLE 11.13. SEASONAL DYNAMICS OF SOIL WATER, ZAPS II, 1977*
Treatment
Control
Depth
(cm)
0-15
15-30
30-45
45-60
60-75
75-90
90-105
20 April
3.27 i 0.09
3.56 i 0.33
3.78 i 0.07
3.87 t 0.10
3.49 1 0.57
3.15 J 0.47
2.97 t 0.66
29 April
2.27 ± 0.09
3.20 ± 0.15
3.71 ± 0.17
3.63 t 0.03
3.35 ± 0.35
2.90 ± 0.55
2.49 ± 0.64
5 May
2.08 * 0
2.82 1 0
3.35 i 0
3.65 1 0
3.72 ± 0
3.02 ± 0
2.57 1 0
07
29
04
17
06
42
68
12 May
1.70 t 0.05
2.51 t 0.34
2.93 t 0.10
3.28 ± 0.16
3.35 ± 0.21
2.84 1 0.56
2.48 1 0.64
17
2.80
2.66
3.10
3.40
3.22
2.44
2.76
May
± 0.05
! 0.26
1 0.10
± 0.10
1 0.25
± 0.42
1 0.77
23
2.77
2.33
2.62
3.03
3.08
2.59
2.32
May
1 0.11
1 0.22
* 0.06
± 0.17
1 0.27
1 0.68
± 0.65
30
2.13
2.16
2.44
2.95
2.65
2.46
2.22
May
» 0.07
* 0.18
* 0.05
± 0.25
± 0.22
» 0.40
± 0.32
16 June
4.16 * 0.07
3.36 * 0.29
2.28 * 0.22
2.22 t 0.03
2.29 * 0.13
2.10 » 0.08
2.02 ; 0.28
15 July
1.02 1 0.28
1.49 * 0.14
1.70 t 0.23
1.94 ± 0.08
1.62 ± 0.01
1.66 ± 0.03
1.56 ± 0.08
16
.17
.60
.61
66
.70
.56
.65
August
• 0.08
» 0.20
I 0.14
» 0.05
i 0.05
± 0.05
i 0.03
9 September
1.12 * 0.10
1.48 • 0.16
1.11 * 0.19
1.60 • 0.13
1.55 ± 0.06
1.57 1 0.05
1.40 ± 0.06
24.09
21.56
19.09
17.01
10.99
10.98
Low
Medium
High
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
0-15
15-30
30-45
45-60
60-75
75-90
90-105
TOTAL
3.51 t 0.06
4.39 i 0.17
4.68 ± 0.17
4.72 t 0.34
4.56 ± 0.36
4.50 ± 0.07
3.89 1 0.64
30.25
2.82 t 0.25
3.55 ± 0.26
4.10 ± 0.19
4.37 ± 0.17
4.05 ± 0.60
3.67 ± 0.67
3.61 ± 0.67
26.27
2.82 ± 0.12
3.27 ± 0.24
3.61 ± 0.33
3.78 t 0.07
3.81 ± 0.11
3.46 ± 0.22
3.11 ± 0.57
23.86
2.30 1 0.12
3.40 ± 0.07
4.02 ± 0.08
4.23 t 0.21
4.30 1 0.10
4.09 ± 0.16
3.85 ± 0.43
26.19
2.16 i 0.19
3.04 ± 0.15
3.98 1 0.12
3.96 ± 0.06
4.08 1 0. 13
4.27 ± 0.08
3.80 ± 0.32
25.29
2.03 * 0.13
2.78 * 0.26
3.55 1 0.17
3.75 * 0.14
3.72 * 0.14
3.69 * 0.12
3.55 ± 0.16
23.07
2.95
2.78
4.03
3.91
4.17
4.03
4.18
t 0.03
t 0.17
t 0.77
i 0.25
± 0.02
t 0.20
± 0.74
26.06
2.76
2.50
3.32
3.57
3.49
3.63
3.41
22
2.73
2.44
3.21
3.33
3.47
3.54
3.44
22
± 0.19
± 0.18
* 0.12
± 0.27
+ 0.43
± 0.52
± 0.61
.67
* 0.04
± 0.15
* 0.27
* 0.17
; 0.09
* 0.05
» 0.26
.16
2.44
2.63
2.92
3.28
3.68
3.60
3.69
22
2.11
2.29
2.64
3.26
3.42
3.62
3.26
20
2.33
1.99
2.63
3.16
3.20
3.51
3.39
20
± 0.08
t 0.15
* 0.06
1 0.02
± 0.07
1- 0.27
1 0.37
.24
* 0.02
± 0.18
i 0.13
» 0.02
* 0.21
t 0.09
± 0.46
.60
± 0.12
± 0.11
1 0.14
t 0.12
1 0.05
1 0.16
J 0.11
.21
1.50 *
2.05 t
2.27 i
2.24 t
2.24 t
2.31 ±
2.69 ±
15.
1.34 ±
1.81 ±
2.14 ±
2.23 ±
2.20 t
2.51 *
3.01 t
15.
1.50 t
1.76 t
1.99 *
1.98 1
1.89 ±
1.89 ±
1.94 ±
0.03
0.15
0.06
0.07
0.03
0.23
0.50
30
0.08
0.24
0.10
0.17
0.15
0.19
0.69
25
0.22
0.06
0.15
0.04
0.09
0.12
0.11
12.95
1.25 i 0.01
1.97 ± 0.13
2.18 1 0.05
2.19 1 0.18
2.04 ± 0.06
2.00 t 0.09
2.12 t 0.28
13.75
1.17 1 0.16
1.68 1 0.27
2.01 t 0.15
2.04 1 0.15
2.11 t 0.13
2.14 * 0.07
2.05 ± 0.08
13.21
1.27 i 0.12
1.42 ± 0.15
1.78 t 0.12
1.67 t 0.07
1.68 1 0.07
1.64 * 0.10
1.66 1 0.06
11.13
1.27 ± 0.03
1.82 t 0.18
1.94 t 0.10
1.95 t 0.17
1.85 t 0.09
1.83 ± 0.08
1.98 t 0.17
12.64
1.15 1 0.15
1.71 ± 0.27
1.94 t 0.08
1.89 ± 0.15
2.47 £ 0.50
2.05 1 0.06
1.82 t 0.18
13.04
1.08 ! 0.06
1.38 i 0.13
1.58 1 0.06
1.59 t 0.07
1.63 ± 0.08
1.65 1 0.07
1.54 1 0.21
10.45
cm, X 1 SE.
353
-------
TABLE 11.14. GROWING SEASON PRECIPITATION (MM) FOR THE ZAPS SITES
FOR 1975, 1976, AND 1977 COMPARED WITH LONG-TERM
AVERAGE AT BROADUS, MONTANA
Date
May
1-15
16-31
Total
June
1-15
16-31
Total
July
1-15
16-31
Total
August
1-15
16-31
Total
September
1-15
16-31
Total
1975
72
32
104
34
75
109
12
17
29
12
2
14
2
4
6
ZAPS I
(ram)
1976
29
68
97
67
35
102
25
13
38
4
6
10
5
9
14
ZAPS II
(ram) Long-term
1977
17
28
45
77
14
91
10
8
18
13
5
18
2
34
36
1976
22
22
44
57
37
94
27
14
41
10
7
17
5
9
14
1977 average*
18
28
46 57
79
19
98 80
7
7
14 35
11
7
18 27
2
38
40 30
Long-term average as recorded at Broadus, Montana located on
Powder River approximately 50 km northeast of sites, 1932-1977.
354
-------
TABLE 11.15. METEOROLOGICAL VARIABLES AT ZAPS I, 1976
U>
Ln
Ln
Air temperature (°C)
Average
Maximum
Minimum
Relative Humidity (%)
Average
Maximum
Minimum
A/11-17
13
27
5
43
79
22
18-24
7
17
-1
57
99
6
4/25-5/1
5
19
0
74
99
23
Apr
7
27
-1
65
99
6
5/2-8
11
23
-3
51
99
15
9-15
14
26
3
55
99
28
16-22
15
26
5
60
99
24
23-29
13
26
3
62
99
25
May
13
26
-3
56
99
15
5/30-6/5
18
28
8
61
99
22
6-12
19
31
8
59
99
24
13-9
12
25
5 ^
67
99
23
20-26
14
29
5
62
99
26
6/27-7/3
19
30
8
55
99
23
June
15
31
5
59
99
23
Air temperature (°C)
Average
Maximum
Minimum
Relative Humidity (%)
Average
Max imum
Minimum
7/4-10
24
33
15
56
94
23
11-17
22
35
10
52
99
16
18-24
24
37
15
50
99
16
25-31
23
32
13
48
91
18
July
22
37
10
52
99
16
8/1-7
22
36
13
56
99
11
8-14
23
32
13
47
97
26
15-21
25
35
16
43
99
15
22-28
21
36
3
40
99
18
Aug
21
36
3
46
99
11
8/29-9/4
24
37
13
33
65
13
9/5-11
20
39
4
33
99
9
12-18
20
33
10
56
99
19
19-25
17
27
10
52
99
18
26-10/2
17
31
2
45
99
14
Air temperature (°C)
Average
Maximum
Minimum
Relative Humidity (%)
Average
Maximum
Minimum
Sep
18
39
2
44
99
9
10/3-9
10
19
5
70
99
40
10-16
—
—
—
—
—
—
17-23
—
—
—
—
—
Oct
15
31
5
48
99
15
-------
TABLE 11.16. METEOROLOGICAL VARIABLES AT ZAPS I.I, 1976
OJ
Ln
OS
Air Icinpcrnture (°C)
Average
Maximum
Minimum
Relative Humidity (%)
Average
Maximum
Minimum
4/11-17
10
57
51
—
—
—
18-24
6
16
0
63
99
30
4/25-5/1
5
19
0
74
99
26
Apr
6
52
-1
71
99
30
5/2-8
10
22
-3
53
99
22
9-15
13
25
3
55
99
31
16-22
15
25
5
62
99
30
23-29
14
28
4
59
99
22
May
12
28
-3
56
99
22
5/30-6/5
19
29
-6
60
97
24
6-12
20
32
8
60
99
22
13-9
13
25
5
68
99
14
20-26
15
31
6
69
99
30
6/27-7/3
19
31
9
63
99
31
June
19
32
-6
62
99
14
Air temperature (°C)
Average
Maximum
Minimum
Relative Humidity (%)
Average
Maximum
Minimum
7/4-10
25
33
15
64
99
34
11-17
22
35
11
56
99
21
18-24
25
37
15
54
99
22
25-31
22
32
12
52
96
23
July
22
37
11
57
99
21
8/1-7
21
36
12
67
99
19
8-14
22
31
13
51
95
29
15-21
25
35
15
46
99
21
22-28
23
35
11
46
99
24
Aug
21
36
11
50
99
19
8/29-9/4
23
35
11
36
62
17
9/5-11
19
38
5
40
99
7
12-18
19
32
8
60
99
25
19-25
15
27
7
59
99
22
26-10/2
17
31
2
47
99
19
Air temperature (°C)
Average
Maximum
Minimum
Relative Humidity (%)
Average
Maximum
Minimum
Sep
17
38
2
50
99
7
10/3-9
10
20
5
72
99
43
10-16
—
—
—
—
—
—
17-23
4
11
-3
60
99
38
Oct
8
31
-3
57
99
20
-------
TABLE 11.17. METEOROLOGICAL VARIABLES AT ZAPS I, 1977
Un
Air temperature (°C)
Average
Maximum
Minimum
Relative Humidity (%)
Average
Maximum
Minimum
4/14-23
9
21
-17
50
98
18
24-30
16
26
6
38
88
19
Apr
11
26
-17
43
98
18
5/1-7
12
23
0
48
97
19
8-14
18
26
6
49
94
16
15-21
10
20
3
65
98
22
22-28
15
27
4
56
99
20
May
13
27
0
53
99
16
5/29-6/4
18
31
3
46
97
25
6/5-11
20
30
6
56
99
30
12-18
16
24
8
67
99
31
19-25
21
33
12
52
88
28
26-7/2
20
30
7
43
90
22
June
18
33
6
53
99
22
7/3-9
19
30
10
54
92
23
Air temperature (°C)
Average
Maximum
Minimum
Relative Humidity (%)
Average
Maximum
Minimum
10-16
21
35
9
49
99
14
.17-23
24
38
13
43
90
12
24-30
21
35
12
53
99
19
July
20
38
9
49
99
12
7/31-8/6
18
28
8
58
99
25
8/7-13
16
30
6
59
99
15
14-20
20
31
7
53
99
25
21-27
19
35
7
65
99
14
28-9/13
17
33
7
58
99
19
Aug
17
35
6
58
99
14
9/4-10
21
33
5
49
99
18
11-17
17
31
6
55
99
19
18-24
13
25
5
64
99
24
25-10/1
11
22
2
74
99
29
Sep
16
33
5
58
99
18
-
Air temperature (°C)
Average
Maximum
Minimum
Relative Humidity (%)
Average
Maximum
Minimum
10/2-8
7
17
-1
72
99
26
9-15
3
15
-5
55
99
23
Oct
4
17
-5
66
99
23
-------
TABLE 11.18. METEOROLOGICAL VARIABLES AT ZAPS II, 1977
OO
Air temperature (°C)
Average
Maximum
Minimum
Relative Humidity (%)
Average
Maximum
Minimum
4/17-23
8
21
0
54
98
17
24-30
16
27
5
37
89
16
Apr
11
27
0
46
98
16
5/1-7
13
23
1
48
94
15
8-14
19
26
7
49
92
12
15-21
10
20
3
63
94
20
22-28
15
27
4
57
96
17
May
13
27
1
53
96
12
5/29-6/4
18
31
4
46
96
22
6/5-11
20
32
7
59
96
29
12-18
16
25
8
73
97
36
19-25
20
32
10
59
97
31
26-7/2
21
31
6
52
96
25
June
18
32
6
58
97
22
7/3-9
19
31
9
62
98
21
Air temperature (°C)
Average
Maximum
Minimum
Relative Humidity (%)
Average
Maximum
Minimum
10-16
21
35
8
51
97
12
17-23
25
38
15
47
96
10
24-30
23
36
12
52
98
15
July
21
38
8
52
98
10
7/31-8/6
20
31
10
55
96
23
8/7-13
18
32
8
60
98
14
14-20
20
30
8
54
96
25
21-27
19
35
7
66
98
16
28-9/3
17
32
6
60
98
18
Aug
18
35
6
59
98
14
9/4-10
20
32
4
51
96
18
11-17
17
31
6
57
96
17
18-24
13
24
5
65
96
27
25-10/1
11
22
2
71
96
29
Sep
15
32
4
59
96
17
Air temperature (°C)
Average
Maximum
Minimum
Relative Humidity (%)
Average
Maximum
Minimum
10/2-8
6
16
-2
67
94
24
9-15
3
15
-4
52
96
21
Oct
4
16
-4
61
96
21
i
-------
1976
(jO
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£«-*•
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;/x
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0.25-1.0 1.0-5.0 5-10 10-15 15-20 20-30
QUANTITY OF PRECIPITATION (mm)
>30
Figure 11.3. Histogram of incidence and quantity of precipitation, 1976
-------
1977
cr.
o
a
-o
>-
O
2
UJ
ID
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30
Figure 11.4. Histogram of incidence and quantity of precipitation, 1977
-------
METEOROLOGICAL VARIABLES AT ZAPS
Instrumentation
Air temperature and relative humidity were measured with a hydrothermo-
graph (Bendix Model 594) placed in an instrument shelter 1.5m above ground.
Wind speed and direction were monitored at 2.1 m above ground with a portable
system consisting of a balsa vane and 3-cup anemometer (Ecowind IIIB, Wong
Laboratories). The threshold for both indicators was 33.5 cm/sec. Wind
direction was recorded as an analog signal on a scale marked N-E-S-W-N, while
wind speed was recorded as an integrated signal, a mark for every 0.8 km of
air passage. The unit was DC powered and recorded on a Gulton recorder
(Model 288/F2146).
Meteorological Variables
Data for air temperature (°C) and relative humidity (%) are presented
in Tables 11.15 and 11.16 for ZAPS I and Tables 11.17 and 11.18 for ZAPS II
for years 1976 and 1977, respectively. These tables summarize data by week
and month, the monthly summary following the 7-day data.
Air Temperature
Monthly averages for ZAPS I and ZAPS II in 1976 and 1977 were similar,
differing by no more than 1°C. However, air temperature was higher in 1977
on both ZAPS in April and June but lower in other months. The absence of
freezing temperatures occurred in early May 1977 but not until after the
first week of June in 1976. The warmest month in both years was July, which
averaged 20°C or above in both years. Also, the average maximum was 37 to
38°C for July.
Relative Humidity
This undergoes characteristic diurnal fluctuations because warm air can
hold more moisture. Most maximum RHs were 99% (saturated), which occurred
at night. During the growing season at ZAPS I, June showed the highest of
the minimum RHs, correlating with abundant precipitation in 1976
(Table 11.14). In 1977, June was the wettest month; hence, the minimum RHs
were 22-31%. The lowest RH recorded for any month occurred in June 1977 at
ZAPS II. July was also the month of least precipitation in 1977 (see
Table 11.14).
Wind Speed and Direction
A series of histograms depicting wind speed in meters sec l and wind
direction at eight points of the compass are in Figures 11.5 to 11.32.
Each figure contains information for one month and shows the duration of a
361
-------
particular range of wind speeds in a given direction
figures is:
The breakdown of
Figures 11.5 - 11.11:
11.12 - 11.18:
11.19 - 11.25:
11.26 - 11.32:
ZAPS I, 1976
ZAPS I, 1977
ZAPS II, 1976
ZAPS II, 1977
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Figure 11.5. Histograms of wind speed and direction for ZAPS I, April, 1976
362
-------
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Figure 11.6.
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Histograms of wind speed and direction for ZAPS I, May, 1976
1
1
NE E SE
40
32
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ct
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x 16
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NE E SE S SW W NW N
Figure 11.7. Histograms of wind speed and direction for ZAPS I, June, 1976.
363
-------
100
80
£ 60
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Figure 11.8. Histograms of wind speed and direction for ZAPS I, July, 1976,
\\J\J
80
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Figure 11.9- Histograms of wind speed and direction for ZAPS I, August, 1976.
364
-------
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SW W NW N NE E SE S SW W NW N
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Figure 11.10
100
80
£ 60
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SW W NW N NE E SE S SW W NW N
Histograms
1976.
0
—
—
—
-\
1
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1
1
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NE E SE
40
32
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1
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of wind speed and direction for ZAPS I,
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-
—
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II
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60
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September
— /
sec
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SW W NW N NE E SE S SW W NW N
4.9-6.7 m sec~l
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NE E SE S SW W NW N
Figure 11.11. Histograms of wind speed and direction for ZAPS I, October,
1976.
365
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48
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01 5b
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x 24
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0
20
16
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12. Histograms of wind sp<
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"n 0
•. p
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100
80
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Lrection for ZAPS I, April, 1977
r~
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Figure 11.13. Histograms of wind speed and direction for ZAPS I, May, 1977
366
-------
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80
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Figure 11.14
Histograms of wind speed and direction for ZAPS I, June, 1977.
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Figure 11.15. Histograms of wind speed and direction for ZAPS I, July, 1977
367
-------
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Figure 11.16.
E
m
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Histograms
of
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wind speed and direction for
1
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—
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NW N
I, August,
1977.
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100
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Figure 11.17. Histograms of wind speed and direction for ZAPS I, September,
1977.
368
-------
ow
48
£ 36
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x 24
12
n
0-2. 2 msec'1
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S
SW
W NW
N
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—
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1
NE E SE S SW W NW N NE E SE
1
S
Figure 11.18. Histograms of wind speed and direction for
1977.
40
32
co 24
ir ^H
O
3C 16
8
0
0-2.2 m sec'1
i— i ~
~ __
~ i— 1
n n
1 JL. 4i
1 V 'i1 'i' — 'l' I — l I li
40
32
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8
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l
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ZAPS
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October,
n 2.7-4.5 m sec'1
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NE E SE S SW W NW N NE E SE
-^ on
60
48
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12
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4.9-6.7 m sec~
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x 8
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n
1
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> 7 m sec
^
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T
l
T
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NE E SE S SW W NW N
NE E SE S SW W NW
Figure 11.19. Histograms of wind speed and direction for ZAPS II, April,
1976.
369
-------
60i
48
£ 36
^3
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x 24
12
0
-
-
—
_
i i 1
NE E SE
40
32
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0
x 16
8
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1
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SW W NW
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N
—
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96
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NE E SE S SW W NW N
4.9-6.7 m sec'1
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>7 m sec '
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NE E SE S SW W NW N
NE E SE S SW W NW N
Figure 11.20. Histograms of wind speed and direction for ZAPS II, May, 1976,
CO
cr
t^
32
24
16
8
O
_ O-2.2msec~t
~*
-
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m
•••
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cc 36
0
x 24
12
n
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NE E SE S SW W NW N
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2.7-4.5 m sec"1
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NE E SE S SW W NW N
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x 16
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4.9-6.7 m sec''
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co 12
cr { 7 m sec
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•~TT 11 " I -*rl 1 • i i . ,
NE E SE S SW W NW N
NE E SE S SW W NW N
Figure 11.21. Histograms of wind speed and direction for ZAPS II, June, 1976,
370
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64
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ID
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1 32
16
0
—
-
0-2.2 m sec'1
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11 ii II
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112
£ 84
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NE E SE S SW W NW N NE E SE S SW W NW N
Figure 11.22. Histograms of wind speed and direction for ZAPS II, July. 1976
80
64
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,_, p-2.2msec~/
-
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100
80
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NE E SE S SW W NW N NE E SE S SW W NW N
__ on — 1
60
48
£ 36
ID
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Figure 11.23. Histograms of wind speed and direction for ZAPS II, August,
1976.
371
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372
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373
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374
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376
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SECTION 12
THE EFFECT OF S02 ON SOIL MICROORGANISM ACTIVITY
J.C. McFarlane, R.D. Rogers, and D.V. Bradley, Jr.
ABSTRACT
Soils from each of the Zonal Air Pollution Study (ZAPS)
fumigation plots were analyzed for their hydrogen
oxidation potential using Alcaligenes paradoxus as a
representative microorganism. In the ZAPS I soils,
there was a significant decrease in activity associated
with increasing SOz insult. In the ZAPS II soils, no
trend was present except that the microorganism activity
in the highest SOz fumigation was significantly lower
than all other plots. The results of these tests in-
dicate that after 1 year of fumigation, only the most
severe insult resulted in a detectable depression.
However, after 2 years the soil microbiota was signi-
ficantly affected by the S02 fumigation. These tests
also indicate that the insult measurement technique
employed might serve as a monitoring tool with
sufficient sensitivity to detect this insult.
INTRODUCTION
In recent studies (McFarlane et al. 3 1978a), it was found that the
activity of the hydrogen-oxidizing microorganisms found in soils could be
assayed very easily and accurately. One of the organisms, Alcaligenes
paradoxuS; (Rogers et al., 1978) was found to be one of the predominant
hydrogen-oxidizing soil microorganisms. All soils tested thus far (McFarlane
et al. 3 1978b) have had an inherent hydrogen-oxidizing activity. In cell
cultures these organisms can exist as either heterotrophs, which use the
supplied organics or as autotrophs, which use the energy released in the
enzymatic oxidation of elemental hydrogen. Their activity in natural soils
varies with each soil type and is regulated presumably by the availability of
either mineral or organic nutrients.
In laboratory experimentation (Rogers, 1978, personal communication), it
has been shown that the rate of hydrogen oxidation is a sensitive indicator
of the availability of mercury and cadmium in soil and solution. In these
377
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cases it appeared that the effect of the toxins was directly on the enzyme
system since decreased hydrogenase activity was observed while no change in
cell numbers was detected. This sensitivity to pollutants in the laboratory
was the reason for testing the applicability of this biological monitor under
conditions of insult in the field. The ZAPS study afforded an excellent test
system where test plots were more or less uniform regarding soil type and
pollutant concentration. Differences in the hydrogen oxidation activities
determined by this assay are thought to represent an index of biochemical
alterations in soil microorganisms. Laboratory experimentation with mercury
and cadmium (unpublished) in solution and in soil have indicated that the
hydrogen fixation activity indicates the insult of those pollutants. Tests
are currently underway to determine if this test may be used as an index of
the overall biological insult of a pollutant.
MATERIALS AND METHODS
Soils were collected in November 1976 from each of the ZAPS fumigation
plotst. Composite samples of the top 5 cm were collected at random and mixed
together for each treatment plot. In the laboratory the soils were mixed and
the large rocks and pebbles were removed by screening the soil through a 2 mm
soil sieve. The moisture content of the soils when they arrived was 5.0% ±
0.7% for the ZAPS I soils and 10.2% ± 4.9% for the ZAPS II soils. The
waterholding capacity (WHC) of the soils at each site was similar; the WHC of
ZAP I soils was 5.1 ± 0.1 ml/20 g and the WHC for the ZAPS II soils was 7.1
± 0.4 ml/20 g.
Two hundred grams of each soil was placed in large petri dishes (15 cm)
and sufficient water was added to bring these samples to 50% of their water
holding capacities. The soils were incubated in 15 cm, closed petri dishes
for 7 days at 30°C and the water content of each soil was adjusted as re-
quired. The incubation period was used to bring the microorganism popula-
tions into equilibrium.
Evaluation of the hydrogen oxidation potential of the soils was deter-
mined as follows. Twenty grams (equivalent dry weight) of soil was placed in
each of seven, 1-liter round flasks which served as reaction vessels. Because
it was critical to know the amount of water added to each reaction vessel,
the water content of the soil was determined gravimetrically at the start of
the activity test, and a second check on soil water content was made imme-
diately prior to analysis. Initially, enough water was added to bring each
sample to 140% of its water-holding capacity. The flasks were closed with
rubber stoppers and the resultant soil slurry was spread over the inner
surface by shaking.
Five millicuries of elemental tritium was obtained in a 1-liter cylinder
pressurized with nitrogen. The specific activity of tritium in the cylinder
was quantitatively determined by a test similar to the procedure used in
t We thank Dr. John Taylor for collecting the soil samples.
378
-------
these experiments (McFarlane et al. , 1978c) . After the flasks had been
flushed withxair, 5 ml of elemental tritium (580 nCi) was injected through
the rubber stopper with a gas-tight syringe. These bottles were then stored
at 30 C for various periods of time before analysis. The reaction was
stopped by opening the flask to allow the remaining elemental tritium to
escape, and by adding 50 ml of benzene. The water was distilled in a benzene
and water azeotrope (Moghissi et al. , 1973) and the amount of tritium recover
ed as water was determined by liquid scintillation counting.
The reaction rate was determined by analyzing replicate samples at
various times. This produced a series of measurements which yielded curves
that are described by a regression function known as the exponential growth
model:
(1) Y - P! [1-EXP (-P2t)] +E
where: Y = the amount of elemental tritium (HT) converted to HTO
at any time
PI = the asymptotic tritium content (nCi)
Pa = the reaction rate parameter (hours * )
t = time in hours
E = the error function, assumed to be Gaussian
Each data set was fit to this regression model using a non-linear least
squares program.
The derivative of formula (1) with respect to time gives the velocity
of the reaction:
At time zero the velocity is maximal and equals Pi?2- If the concentration
of oxidized tritium is expressed in terms of percent or as a fraction, P],
equals 1.0 and P2 therefore equals the maximum velocity of the reaction.
The dimensions in these tests were in units of the fraction of tritium con-
verted per hour.
RESULTS AND DISCUSSION
The results of these tests generated a family of curves (Figure 12.1)
which represent different rates of tritium oxidation. The maximum velocities
occurred at T = 0. In these experiments, the concentration of atmospheric
hydrogen was assumed to be 0.50 ppm (volume: volume) (Ehhalt et al. , 1975)
and was the dominant source of elemental hydrogen. The tritium source also
contained elemental hydrogen since in the preparation H2 was used for the
first dilution. This amounted to 10.5 ppm of hydrogen in the tritium bottle
and resulted in an additional 0.05 ppm of hydrogen in each 1-liter flask.
379
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100-
ZAPS1
10
Time (Hours
12 14 16 18 20
ZAPS 2
8 10
Time I Hours I
12 14 16 18 20
Fig. 12.1 Percent of elemental tritium oxidized by soil microorganisms
380
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Since tritium was present in trace concentrations, the oxidation reactions
primarily involved elemental hydrogen and the concentration of atmospheric
hydrogen determined the original or maximum velocity. These rates are there-
fore similar to those expected under field conditions which favor soil micro-
organism activity.
Maximum velocities were calculated for each study plot and are presented
in Table 12.1. In the ZAPS I soils (2 years of fumigation) there was a de-
creasing gradient in microorganism activity which was correlated with increas-
ing S02 insult. In the ZAPS II soils the same pattern was not evident. Vari-
ability was higher in the rate analyses for the ZAPS II soils and therefore
no statistical differences were evident for the microorganism activity in the
lower SOz concentrations. Nevertheless, there was a significant difference
between the high and low S02 treatments.
TABLE 12.1. MAXIMUM HYDROGEN OXIDATION RATES BY SOIL MICROORGANISMS AFTER
VARIOUS SO2 FUMIGATION TREATMENTS
Treatment
Designation P2 = Vmax (% oxidized/hour)
ZAPS I
Control
Low
Medium
High
ZAPS II
Control
Low
Medium
High
28
23
21
14
20
21
25
17
a*
b
b
c
X
X
X
y
^Letters represent groupings which are significantly different using Duncan s
multiple range test.
During collection, transport, screening, mixing and pretreatment incuba-
tion, ample opportunity was given for these soils to return to equilibrium
with environmental conditions. The residual effect from S02 fumigation is
therefore surprising. The reason for this correlation between the micro-
organism activity and S02 insult is unknown. It is tempting to postulate
that alterations in dissolved salts, pH or other factors were responsible.
However, when some of the physical parameters of these soils (Table 12,2) were
examined no obvious correlations were evident. The possibility obviously
exists that the correlations are an accidental artifact and were not
associated with S02.
The lack of correlation between the three lowest S02 fumigations with
microorganism activity in the ZAPS II soils may have resulted from the lack
of effect after only 1 year of treatment or it might indicate random soil
381
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sampling error. On the other hand, the pattern of activity observed in ZAPS I
and between the high SOa level and all lower fumigation levels in ZAPS II
suggest that this test may serve as an important bio-indicator of perturba-
tion. Thus, although this study was not conclusive proof, it is nevertheless
a strong indication that additional study is warranted.
TABLE 12.2. SOIL CHARACTERISTICS FOR THE ZAPS I AND ZAPS II SITES
Plots
Organic
Matter
pH in 0.01
mCaClz
pH in H20
Electrical
Conductivity
1:5 in H20
(x 103 m mho)
Settling
volume of
15-g soil (ml)
Exchangeable
Al (meq/100 g)
Exchangeable
H (meq/100 g)
Extractable
cations in
BaClz
(meq/100 g) ;
Na
K
Mg
Ca
Total
Particle
Size (%):
Sand
Silt
Clay
Texture
A
1.79
5.3
6.5
0.12
19.0
0
0
0.05
0.71
2.18
3.57
6.51
47.0
37.7
15.3
L
1
6
7
0
20
0
0
0
1
2
6
10
49
36
13
L
ZAPS
B
.77
.6
.2
.20
.0
.19
.16
.74
.20
.29
.9
.7
.4
I
C
1.58
6.8
7.0
__
19.0
0
0
0.08
0.53
3.20
8.59
12.37
45.5
37.3
17.2
L
ZAPS II
D
1.33
6.4
6.9
0.39
18.0
0
0
0.08
0.58
2.89
6.20
9.75
41.9
41.8
16.3
L
A
2.59
6.8
7.2
0.45
22.0
0
0
0.37
1.50
4.44
11.76
18.07
29-8
38.0
32.0
CL
B
2.
5.
6.
0.
23
0
0
0.
1.
4.
8.
13.
32.
40.
27.
L to
00
9
8
15
.0
08
24
04
54
90
6
4
0
CL
1
7
7
—
23
0
0
0
0
3
13
18
24
49
28
L
C
.96
.1
.3
—
.0
.08
.77
.94
.58
.37
.2
.6
.2
to Silt
t
D
2.94
7.0
7.4
0.52
24.0
0
0
0.51
1.53
5.25
15.28
22.57
24.7
52.9
22.4
Silt
382
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REFERENCES
Ehhalt, D.H. , L. E. Hiedt, R. H. Lueb and W. Pollock. 1975. The Vertical
Distribution of Trace Gases in the Stratosphere. Pageoph, 113:389-402.
McFarlane, James C., Robert D. Rogers, and Donald V. Bradley. 1978a.
Tritium Oxidation in Surface Soils. Environmental Science and Technology
(accepted for publication).
McFarlane, J.C., R.D. Rogers, and D.V. Bradley, Jr. 1978b. Tritium Oxi-
dation in Surface Soils—A Survey of Soils Near Five Nuclear Fuel Re-
processing Plants (in review).
McFarlane, J.C., R.D. Rogers and D.V. Bradley, Jr. 1978c. Elemental Tritium
Analysis by Bio-Oxidation (in review).
Moghissi, A.A. , E. W. Bretthauer, and E. H. Compton. 1973. Separation of
Water from Biological and Environmental Samples for Tritium Analysis.
Analytical Chemistry, 45:1565-1566.
Rogers, R.D. , D.V. Bradley and J.C. McFarlane. 1978. The Role of Hydrogen-
Oxidizing Microorganism, Alcaligenes paradoxus, in Environmental Tritium
Oxidation (in review).
383
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SECTION 13
EFFECTS OF CHRONIC LOW LEVEL S02 EXPOSURE ON
PRODUCERS AND LITTER DYNAMICS
J. L. Dodd, W. K. Lauenroth, G. L. Thor and M. B. Coughenour
ABSTRACT
The effects of controlled levels of S02 on pro-
ducers and litter dynamics of a Montana grassland were
investigated for three consecutive growing seasons
(1975-1977). The main findings of the study were that
net primary productivity was apparently not reduced;
the dominant grass, Agropyvon smithi-i, showed premature
leaf senescence and possibly increased growth rates;
litter dynamics were apparently not affected; nutri-
tional quality was reduced; assimilation and
distribution of 35S and 1LfC are discussed.
INTRODUCTION
This section consists of a discussion of the research progress made by a
group of scientists at Colorado State University investigating the effects of
controlled levels of S02 on a northern Great Plains grassland. The section
is organized by subsection and within each subsection an attempt is made to
document the progress in a given research area that has been made since
reporting the first year (1975) results in Dodd et al. (1978). We have also
included certain information in appendix form to make it available for use by
other investigators on the Colstrip coal-fired power plant project. Much of
the information included herein has received only preliminary analysis and
should therefore be interpreted with caution.
ABOVEGROUND PLANT BIOMASS DYNAMICS
AND NET PRIMARY PRODUCTIVITY
The effect of controlled levels of S02 fumigation on biomass dynamics
and aboveground net primary productivity was studied at the two ZAPS sites.
The harvest method, as described by Lauenroth et at. (1975), was utilized in
collecting biomass data. In 1976 the size of the circular quadrats was
384
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changed from 0.5 to 0.25 m2, and the number of quadrats clipped per treatment
was increased from 10 to 20.
The seasonal dynamics of biomass for all species combined (Figure 13.1)
were quite similar across treatments for the ZAPS I site in 1975 and 1976.
The ZAPS II site, which was initiated in 1976, showed a slightly lower rate
of net productivity on the control treatment than on the S02 treatments. The
control plot probably had lower productivity because cattle had grazed it
more in the years preceding the current experiment than they had the three
treated plots. This differential grazing pressure likely resulted from the
fact that the control plot was much closer to a corner livestock gate than
were the treated plots. If heavier grazing pressure were applied to the
control treatment, we would expect a lower level of net primary production in
the first few years after exclusion of the livestock. Eventually the succes-
sional process should return the control plot to the same level of produc-
tivity as the treated plots. Unfortunately, this is the same direction of
change that we might expect if the 862 treatments depress productivity.
Another possible explanation for the difference in productivity between the
control and the S02-treated plots is related to soils. It was stated earlier
(Section 11) that soils of the control are somewhat different than those of
the treated plots. We do not know if these differences and differences in
soil water content (Section 11) are sufficient to account for the produc-
tivity differences. Care must be taken in interpreting future changes on
these study plots.
The major contributors to total biomass on both ZAPS sites are cool
season grasses, and as expected, the trend of biomass production for cool
season grasses (Figure 13.2) closely follows the trend for total biomass.
There does not appear to be any correlation between S02 treatment and seasonal
trend for this group of plants.
The other major contributors to total biomass are the cool season forbs
(Figure 13.3). Again, there does not appear to be any treatment effect.
Warm season grasses and half shrubs also do not appear to respond in any
clear manner to the treatments (Figures 13.4 and 13.5).
The two most important cool season grasses on our study sites are
western wheatgrass and prairie June grass. The seasonal dynamics for western
wheatgrass (Figure 13.6) closely follow those for cool season grasses since
it is the major contributor to that category. Because of its dominance on
the ZAPS sites and in the northern Great Plains, we are particularly inter-
ested in any possible response by western wheatgrass to the treatments.
Treatment effects were not detectable on either ZAPS site for any of the
years studied.
Prairie June grass (Figure 13.7) shows a trend on ZAPS I for 1975 and
1976 in which the growth rate during the major growth period (April through
June) is greatest on the low treatment, intermediate on the control and
medium treatment, and lowest on the high treatment. However, the ZAPS II
site reveals a reversal of that trend, indicating that this is probably due
to variation on the sites rather than a response to treatment.
385
-------
CM
I
o>
CO
CO
o
00
180
160
140
120
100
80
60
40
20
0
ZAPS-I
Apr May Jun Jul
1975
Control
Low
Medium
High
Aug Sep
M
CO
CO
g
CO
200
180
160
140
(20
100
80
60
40
20
0
ZAPS-I
I I I
Mar Apr May Jun Jul Aug Sep
1976
Jun Jul
1977
Figure 13.1. Seasonal change in current years production for all species
combined, ZAPS I and II, 1975-1977.
Net primary productivity is presented in Table 13.1. We sampled only
once in 1977, between 10 and 15 July, but are making the assumption that this
sampling was close to the occurrence of the peak biomass for the year. This
assumption is based on the timing of peak biomass for 1976. For 1975 and
1976, peak current production figures cited are the sums of peaks for the
various functional groups based on frequent harvest data.
Examination of the data for total aboveground net production peaks does
not show any treatment effect. We do see a change in production figures for
each site over the years with an increase occurring from 1975 to 1976 and
then a reduction between 1976 and 1977. The yearly trends in the functional
groups generally reflect that trend. The interseasonal changes are due to
year-to-year fluctuations in precipitation and the subsequent availability of
soil water. Both 1975 and 1976 were wetter than normal years, especially in
May and June, while 1977 was drier than normal (Section 11).
386
-------
TABLE 13.1. PEAK STANDING CROPS OF CURRENT PRODUCTION AND ABOVEGROUND NET PRODUCTION
LJ
OO
Functional
groups
Control
Cool season
grasses
1975 104.
1976 133.
1977
Warm season
grasses
1975
1976
1977
Cool season
forbs
1975
1976
1977
Warm season
forbs
1975
1976
1977
Half shrubs
1975
1976
1977
Aboveground
net production
1975
1976
1977
77.
6.
6.
4.
24.
31.
23.
1.
1.
1.
1.
6.
0,
4 ±
4 ±
0 ±
6 ±
1 ±
4 ±
6 ±
6 ±
5 ±
2 ±
9 ±
8 ±
,9 ±
,7 ±
,3 ±
138
179
107
14.1
12.0
8.5
3.7
3.0
1.6
3.3
5.0
3.7
0.6
1.5
1.7
1.8
6.7
0.3
.7
.7
.0
Low
126.7 ±
130.6 ±
79.5 ±
9.5 ±
15.1 ±
1.6 ±
15.0 ±
27.0 ±
24.5 ±
3.8 ±
2.4 ±
5.1 ±
0
0
0
155
175
110
ZAPS
I
Medium
16.1
10.5
12.2
2.9
5.0
0.8
2.3
3.7
3.9
2.6
1.0
2.2
.0
.1
.7
120.3 ±
122.7 ±
80.0 ±
8.4 ±
5.1 ±
1.4 ±
17.0 ±
33.6 ±
28.4 ±
5.3 ±
5.3 ±
0.3 ±
14.9 ±
4.3 ±
0.6 ±
165.
171.
110.
11.5
7.6
6.5
2.7
2.0
0.6
2.6
4.7
5.0
4.3
2.8
0.3
10.7
2.6
0.4
9
0
7
High
98.4 ±
109.4 ±
59.1 ±
12.3 ±
10.3 ±
1.2 ±
35.7 ±
51.9 ±
31.1 ±
5.3 ±
7.2 ±
5.9 ±
17.1 ±
6.6 ±
3.7 ±
168.
185.
101.
17.
10.
5.
4.
3.
0.
8.
6.
2.
5.
2.
2.
12.
4.
2.
8
4
0
2
7
2
8
7
5
5
8
4
1
9
5
3
7
6
ZAPS II
Control Low Medium High
131.4 ± 7.1 175.0 ± 17.4 148.9 ± 11.3 179.0 ± 12.9
98.3 ± 6.9 154.1 ± 11.6 115.4 ± 8.9 136.6 ± 11.5
8.0 ± 3.9 0 7.5 ± 4.5 3.5 ± 3.0
0.1 ± 0.0 0 0.1 ± 0.1 2.6 ± 2.0
16.0 ± 2.8 30.0 ± 6.1 21.1 ± 4.9 16.9 ± 5.2
11.5 ± 2.1 22.8 ± 4.0 23.7 ± 4.2 17.6 ± 4.3
0000
0 1.4 ±1.4 0 0
2.2 ± 2.2 2.0 ± 2.0 3.6 ± 2.4 3.1 ± 1.3
5.0 ± 2.4 0 1.9 ± 1.0 3.1 ± 2.5
157.6 207.0 181.1 202.5
114.9 178.3 141.1 159.9
Peaks for 1975 and 1976 were determined from frequent harvest data (see biomass dynamics discussion) while peaks for 1977 were from a
single mid-July harvest date (X + SE, g • m~2) .
-------
OJ
CO
CO
o
CD
140
120
100
80
60
40
20
0
ZAPS-I
// i i i
Apr May Jun Jul Aug Sep
1975
Control
Low
Medium
High
180
160
^ 140
3? 120
co 100
I 80
2 60
CD
40
20
0
ZAPS -E
\J, I
Mar Apr May Jun Jul Aug Sep
1976
Jun Jul
1977
Figure 13.2. Seasonal change in current years production of cool season
grasses, ZAPS I and II, 1975-1977.
Cool season grass production shows an interesting pattern on ZAPS I in
1976 and 1977. Peak values appear to be inversely related to S02 concen-
trations; however, the pattern was not repeated on ZAPS II. Cool season
forbs showed a reversed trend in which peak values increased with SC>2 con-
centrations. Again, ZAPS II did not reveal the same trend. Based on the
data we have collected thus far, we must conclude that no detectable treatment
effects have occurred.
BELOWGROUND PLANT BIOMASS DYNAMICS
Crowns (mostly the subterranean portions of stem bases), roots, and
rhizomes are the belowground organs of plants and are the principal storage
organs for herbaceous plant species. It is, therefore, important to know
what the response of this part of the producer system is to S0£ stress.
Unfortunately, state-of-the-art sampling techniques do not provide a satis-
factory way to sample the living portion of this critical compartment.
Therefore, we have measured dynamics of these components on a live-plus-dead
388
-------
esi
E
CJ>
CO
CO
o
OQ
80
60
40
20
0
Apr May Jun Jul Aug Sep
1975
Control
Low
Medium
High
04
E
.5?
CO
CO
80
60
40
20
n
ZAPS-H
r'rt-"^ 1 I I | T "~~~ i < \ 1
CO
Mar Apr May Jun Jul Aug Sep
1976
Jun Jul
1977
Figure 13.3. Seasonal change in current years production for cool season
forbs, ZAPS I and II, 1975-1977,
M
CO
CO
g
CD
60
40
20
0
ZAPS-I
Apr
Low
Medium
High
Jul
3"7R
y t 3
•ol
um
Aug Sep
(M
£
3
CO
O
CD
60
40
20
0
r ZAPS-H
-
___-— _
Apr May Jun Jul Aug Sep Jun Jul
1976 1977
Figure 13.4.
Seasonal change in current years production of warm season
grasses, ZAPS I and II, 1975-1977.
389
-------
CM
t
—
CO
CO
o
CO
60
40
20
ZAPS -I
—
—
0 APr
f "* »-^-. """"^
May Jun Jul Aug Sep"
1975
Control
Low
Medium
High
CJ
_-»
E 60
40
0
ZAPS-H
_/1_
Mar Apr May Jun Jul Aug Sep
1976
Jun Jul
1977
Figure 13.5. Seasonal change in current years production of half shrubs,
ZAPS I and II, 1975-1977.
CM
E
\
o>
CO
CO
o
CO
100
80
60
40
20
0
ZAPS -I
Apr May Jun Jul Aug Sep
1975
140
Control
Low
Medium
High
OJ
E 120
^ 100
CO
co 80
g 60
m 40
20
0
ZAPS-LI
_/ / I
Mar Apr May Jun Jul Aug Sep
1976
Jun Jul
1977
Figure 13.6. Seasonal change in current years production for western
wheatgrass, ZAPS I and II, 1975-1977.
390
-------
ZAPS -I
Apr May Jun Jul Aug Sep
1975
-- Control
------ Low
-------- Medium
--- High
CVJ
e
o>
CO
CO
O
00
I£U
IOO
80
60
40
20
0
ZAPS -n
Mar Apr May Jun Jul
1976
Aug Sep Jun Jul
1977
Figure 13.7. Seasonal change in current years production for prairie
June grass, ZAPS I and II, 1975-1977.
basis (ash-free organic weight) and expect to be able to detect only gross
changes.
Following three and two years of S02 stress on the ZAPS I and ZAPS II
sites, respectively, we were unable to detect any consistent treatment effect
on belowground plant biomass dynamics (Tables 13.2, 13.3, and 13.4). Rhizome
biomass appears to have been reduced by three years of exposure of the com-
munity to S02 (ZAPS I, 1977), but we are reluctant to accept this as
significant until we can confirm it by 1978 sampling.
In an attempt to discern the dynamics of the living portion of the
rhizome compartment, we measured nonstructural carbohydrate concentrations in
samples of western wheatgrass rhizomes throughout the 1976 season (Table
13.5). Again, S02 treatment effects on the most labile portion of the live
rhizome were not detected. At this time we cannot conclude that the seasonal
dynamics of the living portion of belowground live plant biomass are or are
not altered by exposure of the aboveground organs to S02. We can only
conclude that the short-term effects are either nonexistent or not of
sufficient magnitude to detect with our sampling procedures.
PHENOLOGY
Phenological development of the major plant species was recorded, by
treatment, for the ZAPS study sites from 1975 through 1977. The 1975 results
391
-------
TABLE 13.2. STANDING CROP OF PLANT CROWNS
ZAPS I
Date
19 April 1975
31 May 1975
15 June 1975
13 July 1975
7 August 1975
17
21
20
15
10
9
19
Control
64 + 10
35+4
70+9
53 ± 8
71 ± 14
September 1975 77 ± 12
March 1976
May 1976
June 1976
July 1976
August 1976
68+8
46 ± 7
94 ± 9
63 ± 10
54+7
September 1976 80 ± 9
Low
74 ± 9
79 ± 13
42 ± 5
55 ± 15
48 ± 9
57 ± 10
80 ± 11
59 ± 8
73 ± 9
64 ± 9
70 + 10
76 ± 9
Medium
83 + 29
56+8
56+8
43 ± 9
48 ± 8
47 ± 6
80 ± 8
71 + 10
78 + 10
61 ± 8
69 ± 13
98+8
High
70 ±
46 +
37 +
33 ±
47 +
29 +
74 ±
54 +
74 ±
63 *
67 ±
81 ±
12
6
7
7
8
4
9
8
9
6
10
8
Control
61
41
74
69
56
83
+ 8
± 5
± 7
+ 9
± 7
± 8
ZAPS ii
Low Medium
57 ± 5 55 ± 6
44+7 43+6
74+9 77 ± 7
83+7 68 ± 10
64 ± 7 79+7
98 ± 9 85+9
High
61 ± 8
54 ± 7
75 ± 9
81+7
64 ± 7
104 + 11
X ± SE, g • m~2, ash-free
TABLE 13.3.
Date
19 April 1975
31 May 1975
15 June 1975
13 July 1975
7 August 1975
17 September
21 March 1976
20 May 1976
15 June 1976
10 July 1976
9 August 1976
19 September
12 July 1977
STANDING CROP
Control
36 +
22 ±
39 ±
26 ±
27 ±
1975 33 ±
24 +
44 +
28 ±
50 +
41 ±
1976 47 ±
62 ±
6
4
5
4
4
4
3
5
2
5
3
6
8
*- ->
X + SE, g • m~2, ash-free,
OF RHIZOMES'
ZAPS
Low
15 + 2
13 ± 3
21 ± 5
32 + 9
19 + 4
24 ± 6
19 ± 3
32 ± 5
21 ± 2
31 ± 3
27+4
38 ± 4
37 + 5
k
I
Medium
28 + 7
23 ± 5
22 + 4
24 + 3
26 + 4
30 ± 6
27 + 4
30 ± 4
22 + 3
34 + 5
25 + 3
34 + 5
43 ± 7
High
29 ±
22 +
27 +
24 ±
19 ±
26 ±
25 +
30 ±
25 +
23 +.
31 +
38 +
26 +
Control
4
3
6
5
3
2
3
2
2
5
5
4
31
18
18
25
26
27
35
i 3
+ 2
± 2
± 2
i 3
4 3
± 4
ZAPS II
Low Medium
23 ± 2 30 ± 6
23 ± 2 28+5
29 * 3 31 + 5
36+3 24+3
33+4 31 ± 5
39+3 26 ± 4
38 ± 5 40+8
High
25 + 3
29 + 4
2.9 ± 3
25 ± 3
28 + 5
32 + 4
36 ± 5
0-10 cm depth
have been reported in Dodd et al. (1978). The 1976 and 1977 results are
reported in Appendix Tables 13.1 and 13.2.
In 1975 and 1976 we used a 14-stage phenophase classification scheme and
Dr. John Taylor, another investigator on the Colstrip coal-fired power plant
project, used a 16-stage scheme. To standardize the phenology studies
conducted by different investigators in the Colstrip program, Dr. Taylor met
with our group in December 1976 and we developed a common 12-stage classi-
fication scheme. This scheme and its relationship to the previous schemes is
shown in Table 13.6. Phenology data presented in Appendix Tables 13.1 and
392
-------
TABLE 13.4. STANDING CROP OF ROOTS
Date
19 April 1975
31 May 1975
15 June 1975
13 July 1975
7 August 1975
17 September 1975
21 March 1976
20 May 1976
15 June 1976
10 July 1976
9 August 1976
19 September 1976
12 July 1977
Control
714 ± 69
564 ± 36
673 + 39
490 ± 60
523 ± 51
618 ± 46
597± 40
565± 38
651± 32
506± 26
506± 28
485± 30
492+ 30
ZAPS
Low
573 ± 42
461 ± 35
512 ± 51
652 ± 75
479 ± 20
509 ± 39
605± 49
489± 27
547± 23
506± 32
565+ 57
500± 24
497± 35
I
Medium
697 ± 88
487 ± 47
539 ± 40
655 ± 54
527 + 39
531 + 26
605± 26
531± 23
504± 25
504± 31
530± 37
548+ 25
505± 25
ZAPS TT
High
769 ± 59
614 ± 29
493 + 36
625 ± 35
482 + 48
520 ± 35
596+ 26
505+ 19
538+ 25
552+ 23
501± 26
5131 28
558+ 22
Control
599 ± 22
477 + 25
554 ± 25
624 ± 28
452 + 25
534 + 36
519 + 29
Low
553 + 22
510 ± 18
635 ± 24
721 ± 30
555 + 48
600 + 27
651 ± 42
Medium High
550 ± 26 525 ±
624 ± 36 613 ±
685 ± 35 601 ±
668 ± 29 649 +
588 + 37 572 ±
570 ± 39 625 ±
617 ± 39 519 ±
23
21
21
38
33
22
28
*X ± SE, g • m~2,
ash-free,
0-1 cm depth
TABLE 13.5. PERCENT TOTAL AVAILABLE CARBOHYDRATE CONCENTRATION IN
Control
Date
26 March
26 May
24 June
19 July
16 August
20 September
Average
26 March
26 May
24 June
19 July
16 August
20 September
Average
Rep. 1
9
9
16
24
10
14
5
14
20
16
14
Rep. 2
8
9
10
21
14
12
7
7
12
27
19
14
Low
Rep. 1
11
10
12
17
19
12
13
9
5
11
18
19
12
Rep. 2
ZAPS I
11
12
12
13
17
17
13
ZAPS II
9
7
15
19
25
15
RHIZOMES OF
Medium
Rep. 1
11
11
11
12
24
11
13
11
8
12
21
27
23
17
Rep. 2
11
11
9
15
20
14
13
7
7
12
13
17
19
12
WESTERN WHEATGRASS
High
Rep. 1 Rep. 2
7 10
13 8
9 15
13 12
16 14
11 10
11 11
8 9
11 6
6 7
9 12
20 21
18 23
12 13
13.2 are according to the 12-stage scheme. The 1976 data were collected
using the 14-stage scheme and converted to the 12-stage scheme.
Rates of phenological progression do not appear to have been greatly
altered by the S02 treatments for any of the species observed in either ZA£>b
experiment. However, there is some indication that the rate of phenological
393
-------
TABLE 13.6. COMPARISON OF PHENOLOGY SCHEMES
MSU
4,
4,
5
5
6
6
7,
8,
9
10
11,
2,
15,
Codes
Pre-1977
CSU
14 2
5 3
4, 5
6
7
8
8 9
9 10
11
12
12 13
13, 14, 1
16
CSU -MSU
1977
1
2
3
4
5
6
7
8
9
10
11
12
Growth stage
First growth
First leaves fully expanded
Active vegetative growth
Vegetative growth mostly complete
Root stage, first floral buds
Exsertion of grass inflorescences, earliest
flowers
Reproductive culms fully extended
Anthesis, full flowering
Fruit developing
Fruit ripe
Dehiscence
Vegetative maturity, summer or winter dormancy,
leaf drop , annuals dead
progression between anthesis (stage 8) and dehiscence (stage 11) may have
been delayed by the S02 treatments for Agropyvon smithii in 1977 on both ZAPS
sites. This may or may not be a significant effect.
Although major changes in phenologies! progression did not result from
exposure to chronic levels of S02, the phenology data indicate key differ-
ences among species and among years. Western wheatgrass and prairie June
grass, the two most abundant species on the sites, differ considerably in
their phenological development (Figure 13.8). Although both species are cool
season species and initiate active vegetative growth at about the same time
(April), prairie June grass completes vegetative growth and attains sexual
maturity (anthesis) 2 to 4 weeks earlier than does western wheatgrass.
Active vegetative growth (stage 3) was initiated later in 1977 than in
1976 for many species. Western wheatgrass was about 2 weeks later and
prairie June grass was about a month later.
394
-------
12
10
x 1975
- 1976
1977
Mar
Sep
Figure 13.8.
Phenologieal progression of Agropyron smithU and Koelerla
cristata for ZAPS I control treatment, 1975-1977 (see
Table 13.6 for phenology code).
395
-------
EFFECTS OF CONTROLLED LEVELS OF S02 ON
THE NUTRIENT QUALITY OF WESTERN WHEATGRASS
AND PRAIRIE JUNE GRASS*
The principal economic value of northern Great Plains grasslands is
directly related to their capacity to produce quality grazing forage. The
range livestock industry is the single most important economic use of these
grasslands. Alteration of forage quality by air pollutants as a result of
energy development would adversely affect this industry.
Sulfur is essential in ruminant diets since it is an important constitu-
ent in protein synthesis. Rumen microorganisms require elemental sulfur for
synthesis of microbial protein (Loosli et at. , 1949; Thomas et al. , 1951;
Starks et al., 1954). Cellulose digestion, in vitro, has been shown to
increase with addition of sulfate to prepared rations (Hunt et at. , 1954;
Martin et al. , 1964; Barton et al. , 1971). However, sulfur has been reported
to be toxic to rumen microorganisms in vitro at a concentration of 100 ppm
from sodium sulfate (Hubbert et al. , 1955) and at 30 ppm from sodium sulfite
(Trenkle et al., 1958).
The objective of the research reported here was to examine the effects
of S02 fumigation on the nutritive quality of two of the most important
forage species in the northern Great Plains grasslands, western wheatgrass
(Agropyron smithii Rydb.) and prairie June grass (Koelevia cri-stata (L.)
Pers.). Nutritive quality was assessed by examining crude protein, cell-wall
constituents, ash, sulfur content, and digestibility of dry matter in vitro.
Field Sampling Procedures
Plant tissue for chemical analyses was collected on four dates for two
years. Sample dates for 1975 were 16-17 May, 12-15 June, 10-13 July, and
4-7 August. In 1976 Site I was always sampled prior to Site II and sample
dates were 17-24 May, 15-23 June, 10-17 July, and 9-16 August.
Harvest quadrats were located randomly in each replicate on each sample
date. All vegetation was then clipped and separated by species into current
live, recent dead (current year's dead), or old dead (previous year's dead).
Subsamples of current live plant tissue for western wheatgrass were chemi-
cally analyzed for each sample date at both sites and years; prairie June
grass was analyzed for all sample dates at Site I, 1976.
*
Major portion of this section taken from a manuscript authored by C. C.
Schwartz, W. K. Lauenroth, R. K. Heitschmidt, and J. L. Dodd. Effects of
controlled levels of sulphur dioxide on the nutrient quality of western
wheatgrass, Journal of Applied Ecology 15(3):869-874, 1978.
396
-------
Laboratory Techniques
Crude protein (Kjeldahl N x 6.25) and ash were determined by procedures
in A.O.A.C. (1965). Cell-wall constituents (CWC) were determined by proce-
dures outlined by Van Soest and Wine (1967). Total sulfur concentrations
were determined with a Leco Induction Furnace (Laboratory Equipment Corp.,
St. Joseph, Michigan).
Digestion of dry matter (DMD) was determined in vitro using techniques
described by Tilley and Terry (1963) and Pearson (1970). Samples were ground
in a Wiley mill to pass through a 0.5-mm screen. Inoculum was prepared by
adding one part of strained rumen fluid to four parts of prewarmed (38.5°C)
standard buffer solution (McDougall, 1948; Table 13.11) saturated with C02.
Inocula were obtained from a fistulated bovine cow maintained on grass hay.
Duplicate 250-mg samples were tested for each replicate on each date.
Data were analyzed with a repeated measure analysis of variance (ANOVA)
repeating across time (Winer, 1971). ANOVA tests were performed on data for
western wheatgrass and for prairie June grass. Throughout the text, refer-
ence is made to year-site effects for western wheatgrass. The year-site
source of variation contrasts Site 1-1975, Site 1-1976, and Site 11-1976 and
therefore includes both differences between 1975 and 1976 and between Sites I
and II. Tukey's Q values were utilized to identify significant differences
between means (Snedecor and Cochran, 1967). Significant differences referred
to in the text are at the P = 0.01 level for analysis of variance and P =
0.05 for Q values.
Appendix Tables 13.3 and 13.4 include results of chemical analysis of
western wheatgrass and prairie June grass plant tissue collected from ZAPS I
and II plots for 1975 and 1976. Similar analyses have been made of plant
tissue of other species collected on the fumigation sites and results are on
file at the Natural Resource Ecology Laboratory, Colorado State University,
Fort Collins.
Results and Discussion
Sulfur
Analysis of sulfur data for western wheatgrass indicated significant
year-site, treatment, date, treatment x date, and treatment x year-site
effects (Table 13.7). There were also significant treatment, date, and
treatment x date (P < 0.02) effects for prairie June grass on Site 1-1976.
Sulfur concentrations of plants in the high and medium treatments were
significantly greater than plants in the control for all dates except June
when no difference was noted between plants in the control and medium plots
(Figure 13.9). Sulfur concentration of plants in the low treatment_was not
significantly different from that of plants in the control. Comparisons
between sulfur accumulation rates in tissue were greatest in the high treat-
ment, (0.0022% per day) followed by the medium (0.0015% f ^Ltf did not
(0.0002% per day) treatments. Concentrations in the control plants did not
397
-------
TABLE 13.7. PERCENT SULFUR CONCENTRATION OF WESTERN WHEATGRASS
AND PRAIRIE JUNE GRASS TISSUE
Site and
treatment
Dates
Year
May
June
July
August
Treatment
mean
Site I
Control
Low
Medium
High
Date mean
Site I
Control
Low
Medium
High
Date mean
Site II
Control
Low
Medium
High
Date mean
1975
1976
1976
Western wheatgrass
0.13
0.14
0.13
0.13*
0.07
0.11
0.16
0.23
0.15*
0.13
0.14
0.16
0.32
0.1951
0.11
0.14
0.21
0.23
0.18
t
0.09
0.13
0.21
0.24
J,
0.17
0.11
0.12
0.17
0.35
•>,
0.19
0.10
0.14
0.24
0.28
0.191
0.09
0.13
0.22
0.32
*
0.19
0.10
0.17
0.27
0.43
0.24"
0.12
0.13
0.26
0.33
0.21
t
0.08
0.15
0.29
0.41
0.241
0.10
0.14
0.28
0.48
0.25
0.11
0.14'
0.21*
0.241
0.09
0.13
0.22"1
0.301
t
0.11
•i
0.14
0.221
0.40s1
t
Site I
§/
1976
Prairie June grass
Control
Low
Medium
High
Date mean
0.09
0.08
0.18
0.21
^
0.14
0.09
0.13
0.21
0.24
&
0.17
0.08
0.16
0.21
0.27
sV
0.16
0.07
0.18
0.25
0.38
4.
0.221
0.08
0.141"
0.21*
0.28§
Any two means not sharing common superscripts within a row or
column within a year-site are significantly different (P < 0.05).
change with time. Similar trends in sulfur concentration by treatment and
date were apparent for prairie June grass.
Comparisons of year-site differences indicated sulfur levels were signif-
icantly higher (P < 0.01) on Site 11-1976 (0.22%) than on Site 1-1976 (0.18%)
and Site 1-1975 (0.17%). The year-site x treatment interaction resulted from
different sulfur levels in the high treatment at all .site-years (Figure
13.10).
398
-------
0.50
0.40
cr 0.30
u_
CO
0.20
0.10
Control
Low
Medium
High
May
Jun
Jul
Aug
DATE
Figure 13.9. Change in percent sulfur in western wheatgrass for four dates on
four treatments: control (0 pphm S02), low (2 pphm S02) ,
medium (5 pphm S02) , and high (10 pphm S02) . Plotted values
are means from Sites 1-1975, 1-1976, and 11-1976. Treatment
means with overlapping vertical lines are not significantly
different at P = 0.1 (Q = 0.05).
399
-------
12
Site I - 1975
Site I - 1976
-Site IE - 1976
0.40
£.
cr
0.30
o>0.20
0.10
UJ
h-
o
cc
CL
10
8
.60
o
h-
C/)
yj
o
Q
cr
UJ
cr
Q
Control Low Medium
High Control
TREATMENT
Low Medium High
Figure 13.10,
Changes in sulfur (%), protein (%), and digestion of dry
matter in vitro (%) in western wheatgrass for four treatments
(control, 0 pphm; low, 2 pphm; medium, 5 pphm; high, 10 pphm)
for three site years. Site year means within a fumigation
level with overlapping vertical lines are not significantly
different at P = 0.05 (Q = 0.05) for sulfur, at P = 0.05 (Q -
0.08) for protein, and at P = 0.05 (Q = 2.9) for dry matter
digestion.
400
-------
Comparisons between Site 1-1975 and Site 1-1976 revealed sulfur concen-
trations were significantly higher in 1976 than in 1975. This was probably
because of the increased period of fumigation in 1976 (196 days) compared to
that in 1975 (151 days). P
Ash
Ash concentrations in western wheatgrass tissue paralleled sulfur con-
centrations with higher levels of ash occurring with higher concentrations of
sulfur (Table 13.8). However, the magnitude of fluctuations in ash concen-
trations across dates was greater than that of fluctuations in total sulfur.
The significant year-site, year-site x treatment, and date x year-site
effects were similar to results reported for sulfur analysis.
Total ash concentrations were greater on Site II in 1976 (8.5%) than on
Site I (7.5%). This was probably a result of differences in sulfur concen-
trations. Ash levels in plant tissue were determined by ashing plants at
500°C. At this temperature, sulfate salts remain as ash residue. Sulfur
dioxide from fumigation is converted to sulfate salts in plant tissues
(Thomas et- al. , 1951). If this conversion is considered stochiometrically by
converting a sulfur molecule (molecular weight: 32) to a sulfate salt mole-
cule containing two calcium ions (molecular weight: 2 x 20 - 40), the
resulting increase in molecular weight is approximately four times greater
for the sulfate salt than for the sulfur molecule. Differences in sulfur
concentration from control to high treatments varied between 0.13% to 0.29%
for both species and site. Likewise, differences in ash concentrations
varied from 0.6% to 2.2% between the control and the high treatment. The
four-fold increase in weight from sulfur to sulfate salt would therefore
account for an increase of 0.6% to 1.0% in ash weight if all sulfur molecules
were in the form of calcium sulfate. If the cation involved was potassium,
the increase in molecular weight from sulfur to potassium sulfate would be
5.4 times greater and would account for a 0.9% to 1.3% increase in ash
weight. It was probable that the major increase in ash content across
treatments was a direct result of increased sulfate salt concentrations
rather than a change in plant ash as a result of fumigation. Ziegler (1975)
stated that in spruce needles, S02 caused an increase in calcium, magnesium,
silicon, and, during springtime, potassium.
Crude Protein
Concentrations of crude protein in western wheatgrass and prairie June
grass varied significantly between sampling dates with highest values
occurring in May and lowest in August (Table 13.9). This relationship
obtained regardless of sulfur treatment.
Comparisons between year-sites for western wheatgrass indicated signifi-
cantly lower concentrations of crude protein for two years (Site 1-1976,
8.8%) of fumigation compared to either value for one year (Site 1-1975,
10.6%; Site 11-1976, 10.2%) of treatment. The significant year-site x
treatment interaction (Figure 13.10) illustrated the source of lower crude
401
-------
TABLE 13.8. PERCENT ASH CONTENT OF WESTERN WHEATGRASS AND PRAIRIE
JUNE GRASS TISSUE
Site and
treatment
Dates
Year May
June
July
August
Treatment
mean
Western wheatgrass
Site I
Control
Low
Medium
High
Site I
Control
Low
Medium
High
Site II
Control
Low
Medium
High
Site I
Control
Low
Medium
High
1975
—
8.5
8.4
8.3
1976
6.9
7.1
7.2
8.2
1976
9.0
8.3
9.6
9.4
1976
8.5
9.0
10.0
10.5
7.7
7.8
8.1
8.1
6.5
7.4
7.1
7.9
7.6
6.4
8.3
8.2
Prairie June
10.2
9.6
9.9
11.8
6.8
6.4
7.7
8.3
6.6
6.9
7.0
8.3
8.6
8.4
9.0
9.2
grass
10.0
10.1
11.6
12.4
7-6
7.2
7.8
8.6
6.9
7.9
8.2
9.5
8.3
7.4
9.0
9.3
9.9
10.4
10.6
12.9
*
7.4
7.5*
8.0f
8.3f
*
6.7
7.3f
7.4f
8.5*
8.4*
*
7.6
8.9*
9.0*
*
9.6
9.9*1"
10. 4f*
11. 9§
* t 4= §/
Any two means not sharing common superscripts within a column
and year-site are significantly different (P < 0.05).
402
-------
TABLE 13.9. PERCENT PROTEIN (KJELDAHL N x 6.25) CONTENT OF WESTERN
WHEATGRASS AND PRAIRIE JUNE GRASS TISSUE
Site and
treatment
Dates
Year May
June
July August
Treatment
mean
Western wheatgrass
Site I
Control
Low
Medium
High
Site I
Control
Low
Medium
High
Site II
Control
Low
Medium
High
1975
15.6
15.0
15.6
16.2
1976
14.4
13.8
12.5
11.9
1976
14.4
15.0
14.4
15.6
10.6
10.6
10.6
11.2
9.4
8.8
9.4
8.1
11.9
11.9
10.0
11.9
Prairie June
Site I
Control
Low
Medium
High
* t */
! — ±! Ar>tr fT.
1976
11.2
10.4
10.6
10.6
T/-» •m^flns not sharim
8.2
8.3
8.2
8.4
g common
8.1 6.9
7.5 6.2
8.1 6.9
7.5 6.2
9.4 6.1
6.9 5.0
6.9 5.8
6.9 5.6
8.8 6.2
10.0 7.5
8.1 6.2
9.4 7.5
grass
7.1 7.6
7.1 6.7
7.1 7.3
6.8 7.4
— . . — • — —
superscripts within a
*
10.4
JL*
•K
9.8
*
10.4
*
10.4
*
9.8
8.4*
A I
8.6 T
4-J.
8.2f*
*
10.3
&
11.1
•k
9.8
*
11.1
*
8.5
*
8.1
*
8.4
&
8.1
column and
Any two means not snaiJ.ii6 v.Wu-uw» «-r----- > fK-i^ldahl N
year-site are significantly different (P < 0.05) (Kjeldahl N
6.25).
403
-------
protein concentrations. Crude protein levels of plant tissue from fumigated
plots were significantly lower than those from the control at Site 1-1976.
Plots fumigated for one year (Site 1-1975, Site 11-1976) were not different
from each other or their controls (Figure 13.10). Protein concentrations on
control plots were not significantly different between the three year-sites.
It appeared that crude protein levels were lower on treated plots compared to
the control at Site 1-1976.
The significant reduction of crude protein in western wheatgrass in
treated plots compared to the control at Site 1-1976 was attributed to sulfur
dioxide fumigation. Heitschmidt (1977) reported increased leaf senescence of
western wheatgrass during both years of fumigation at Site I. Since crude
protein content was clearly related to plant age, this alone would provide an
explanation for the reduction, except that increased senescence occurred in
both 1975 and 1976; significant reduction in concentration of crude protein
was detected only in 1976. Although decreases in forage quality as a result
of sulfur dioxide fumigation have been alluded to by other workers (Guderian,
1977) , to our knowledge reduced crude protein in grasses has not previously
been reported.
Most proteins in plant tissue are enzymatic in structure. Bailey and
Cole (1959), Zelitch (1960), and Cecil and Wake (1962) have demonstrated that
sulfur dioxide can inactivate or inhibit many enzyme systems; it is possible
that these same mechanisms are responsible for reductions in total plant
proteins.
Cell Wall Constituents
Cell-wall constituents (CWC) varied significantly (P < 0.01) between
dates (Table 13.10) for both grass species. There was also a significant (P
< 0.01) year-site and date x year-site interaction for western wheatgrass.
Percentage of CWC was lowest in May samples and increased during other
months. Trends in the year-site x treatment interaction indicated that the
percent CWC at Site 11-1976 was lower than the other two sites during the
June sampling period; all other dates and sites were not different. We have
no explanation for this difference.
The nonsignificant treatment and treatment x date interaction indicated
S02 fumigation did not measurably alter the fiber content of plant tissue.
Significant effects were hypothesized since increases in leaf senescence
(Heitschmidt, 1977) should increase total fiber content. These results
verify that the significant reductions in crude protein resulting from two
years of treatment were not simply the results of differences in proportions
of live and dead tissue among treatments.
Dry Matter Digestion
Digestion of dry matter (DMD) in vitro (Table 13.11) varied signifi-
cantly across dates for both grass species. Plant tissue was highly
404
-------
TABLE 13.10. PERCENT CELL-WALL CONSTITUENTS OF WESTERN WHEATGRASS
AND PRAIRIE JUNE GRASS TISSUE
Site and
treatment
Dates
Year May
June
July
August
Treatment
mean
Western wheatgrass
Site I
Control
Low
Medium
High
Site I
Control
Low
Medium
High
Site II
Control
Low
Medium
High
1975
65.8
64.8
63.0
60.4
1976
64.9
68.1
66.5
63.0
1976
61.5
60.7
60.8
62.5
71.6
74.6
74.1
70.5
70.9
71.5
70.0
67.6
61.8
65.0
66.1
67.3
Prairie June
Site I
Control
Low
Medium
Hieh
1976
60.0
62.8
62.9
64.1
68.1
67.1
66.5
65.4
69.3
69.1
70.1
69.6
69.3
68.0
69.3
66.4
64.0
64.9
65.8
65.9
grass
66.0
64.7
65.6
67.7
65.7
67.1
67.7
69.3
68.4
65.9
67.1
65.7
64.8
65.0
64.9
63.4
61.4
60.9
59.5
60.6
68.1
68.9
68.7
67.5
68.4
68.4
68.2
65.7
63.0
63.9
64.4
60.6
63.9
63.9
63.4
64.6
405
-------
TABLE 13.11. PERCENT DRY MATTER DIGESTION OF WESTERN WHEATGRASS
AND PRAIRIE JUNE GRASS TISSUE
Site and
treatment
Dates
Year May
June
July
August
Treatment
mean
Western wheatgrass
Site I
Control
Low
Medium
High
Site I
Control
Low
Medium
High
Site II
Control
Low
Medium
High
1975
72.0
64.3
70.0
69.0
1976
60.5
66.9
66.7
69.2
1976
62.8
62.4
60.6
58.2
53.8
54.3
55.1
59.7
56.1
54.4
52.7
54.6
49.4
48.6
50.4
50.6
Prairie June
Site I
Control
Low
Medium
High
1976
64.0
61.9
64.7
62.0
46.8
50.2
54.6
54.8
51.5
47.4
50.4
51.7
48.6
50.8
50.2
47.9
46.2
44.4
44.5
45.0
grass
46.4
47.9
47.6
46.0
45.5
43.6
44.8
46.4
42.9
45.1
43.3
46.5
41.8
41.8
40.8
38.7
50.4
45.0
52.4
50.2
55.6
52.4
55.2
56.8
50.0
49.2
48.8
48.0
52.0
54.4
53.2
54.4
51.9
51,2
54.8
53.2
406
-------
digestible in May when plants were more succulent and steadily declined
thereafter. This seasonal change was consistent regardless of treatment.
Digestion of dry matter was significantly higher on treatments fumigated
for one year (Site 1-1975, 55.2; Site 11-1976, 53.6) compared to two years of
fumigation (Site 1-1976, 49.2). The year-site x treatment interaction was
significant (P < 0.02) and the trend (Figure 13.10) was similar to changes in
crude protein concentration. Reduced DMD of western wheatgrass tissue when
fumigated for two years was probably the result of increased leaf senescence
and reduced protein concentrations because of S02 fumigation. Differences in
DMD on control plots at Site I in 1975 and 1976 were attributed to
differences in growth stage and plant development.
Although there was a reduction in DMD with two years of S02 fumigation,
coefficients of digestion for treatment levels were not significantly lower
than the control at Site 1-1976; total protein levels were significantly
lower. This nonsignificant effect could have been a result of increased
microbial activity caused by higher sulfur levels on treated plant tissues.
As discussed earlier, some investigators have shown increased fiber digestion
with increased levels of sulfur. This potential sulfur-microbe interaction
rendered it difficult to determine effects of S02 fumigation on digestion of
dry matter. It could also indicate that changes in nutrient quality, par-
ticularly protein, are not a direct result of increased leaf senescence. As
a result, additional studies, including in vivo digestion trials, are
pertinent to the understanding of this problem of sulfur fumigation on forage
digestibility.
Conclusions
(1) Sulfur content of plant tissue increased with increasing S02
treatment.
(2) Ash concentrations increase in a parallel manner with sulfur
concentrations.
(3) Crude protein in western wheatgrass was decreased significantly by
two years of treatment.
(4) Cell wall constituents were not altered by S02 treatment.
(5) Dry-matter digestibility was reduced by two years of treatment and
seemed to parallel crude protein.
Summary
Effects of low-level sulfur dioxide (S02) fumigation on nutrient quality
of western wheatgrass and prairie June grass were investigated. Analyses
indicated significantly higher levels of sulfur on fumigated vs. control
plots. Accumulation rates of sulfur in tissues were greatest in the high
treatment (0.0022% per day) followed by the medium (0.0015% per day) and low
407
-------
(0.0002% per day) treatments. Concentrations of sulfur in control plants did
not change with time. Ash concentrations paralleled sulfur concentrations
and major increases in ash content of plant tissue were attributed to the
increased levels of sulfur. Crude protein levels varied seasonally, regard-
less of fumigation level, with the highest concentrations in May and the
lowest in August. There were significantly lower levels of crude protein on
treatment plots fumigated for 2 years compared to controls. This significant
reduction was attributed to S02 fumigation. Cell-wall constituent analysis
indicated 862 fumigation did not measurably alter the fiber content of plant
tissue. Digestion of dry matter was significantly higher on treatments
fumigated for one year than those fumigated for two years. In general,
digestion of dry matter paralleled crude protein concentrations.
EFFECTS OF CONTROLLED LEVELS OF S02
ON GROWTH AND SENESCENCE OF WESTERN WHEATGRASS*
An important component of our investigations of the effects of sulfur
dioxide on primary production and biomass dynamics has been concerned with
the growth and development of western wheatgrass (Agvopyvon smith-ii). In
this section we report these results in two parts. The first presents
information from the 1975 and 1976 growing seasons.* The second section
contains data collected during the 1977 growing season and is presented
without statistically based interpretations.
Growth and Senescence (1975-1976)
Few studies of the effects of long- or short-term exposures of grasses
or grasslands to low-level S0£ concentrations have been conducted. Bell and
Clough (1973) exposed ryegrass (Lolium perenne L.) plants to a 12-pphm con-
centration of S02 for nine weeks and found a 46% reduction in dry-weight
yield. Similarly, they reported a 52% reduction in dry weight when ryegrass
plants were exposed to 6.7 ppm S02 for 26 weeks. Bleasdale (1973) found
similar responses in ryegrass exposed to low levels of "coal-smoke." In both
of these studies the reduction in growth occurred without detectable visible
leaf injury. Katz (1949) found that reductions in yield of alfalfa
(Medioago sativa L.) induced by S02 exposures did not occur without visible
injury of the leaves. Other studies utilizing low-level S02 exposures have
shown at least temporary reductions in photosynthetic rates of plants (which
could possibly lead to reduced yields) without measurable leaf injury (Thomas
et at. , 1950; Daines, 1968; Bennett and Hill, 1973; Siji and Swanson, 1974;
Malhorta and Hocking, 1976).
Major portion of this section taken from manuscript authored by R. K.
Heitschmidt, W. K. Lauenroth, and J. L. Dodd. Effects of controlled levels
of sulphur dioxide on western wheatgrass in a southeastern Montana grassland,
Journal of Applied Ecology 15(3):859-868, 1978.
408
-------
The objectives of the present study were to determine the effects of S02
on western wheatgrass (Agropyron smithU Rydb.), the dominant species of most
grasslands of the northern Great Plains. Our specific objectives were to
determine the effects of S02 on leaf area, leaf surfaces, relative growth
rates, net assimilation rates, and leaf area ratios of western wheatgrass.
During the June, July, August, and September biomass sample dates in 1975 and
the May, June, July, and August biomass sample dates in 1976, 20 western
wheatgrass plants were collected randomly from each treatment replicate for
leaf area analyses. All leaf blades were then removed and mounted between
two pieces of clear adhesive acetate and total and necrotic adaxial surface
area of each leaf determined visually, utilizing a clear acetate 0.5-cm2
grid.
Leaf injury was defined as the percentage of necrotic leaf area in
excess of control plants. Missing leaves or portions of missing leaves were
considered necrotic. Missing areas were estimated by subtracting the portion
present from the average total area for leaves of similar age.
Methods employed in growth analyses were developed following Radford
(1967). Biomass of an individual western wheatgrass plant (mg • plant"1) was
calculated using our biomass estimates and density data collected both in
1975 and 1976 by John Taylor (unpublished) . From these data we calculated
relative growth rates (RGR), net assimilation rates (NAR), and leaf area
ratios (LAR) .
Statistical analyses consisted of analysis of variance (ANOVA) with
Tukey's Q values utilized to contrast paired means (Snedecor and Cochran,
1967). Throughout the manuscript reference is made to year-site effects
which contrast Site 1-1975, Site 1-1976, and Site 11-1976 and therefore
includes both differences between years and sites. Leaf area analyses were
limited to the months of June, July, and August since statistical analyses of
the September 1975 and May 1976 data indicated no significant treatment
effects.
Results
Growing Conditions
Mean monthly temperatures reflect a warmer growing season in 1976 than
in 1975, particularly during May, August, and September (Figures 13.11 and
13.12). In 1975, the mean temperatures for these months were^ll.l , 20.6 ,
and 15.5°C, respectively, while in 1976 they were 13.2°, 23.4°, and 19.3°C,
respectively. As expected, vapor pressure deficits were highly correlated
with temperature, and differences between 1975 and 1976 in vapor pressure
deficits were similar to temperature differences.
Long-term precipitation records at Broadus, Montana, indicated May and
June were wetter than normal in both 1975 and 1976, July and August were near
normal, and September was drier than normal (Section 11). Since Broadus is
located approximately 50 km northeast of the sites, the applicability of
these data for describing deviations from normal conditions at the sites is
409
-------
30-
Monthly Mean Temperatures
r-30
IwcciMy IVICUM I cinder ui uica ..
Monthly Mean VPD
Weekly Mean VPD M
25H
^j
o
UJ
o:
h- 15
CH
UJ
Q_
UJ 10-
^_
5-
A
A
; >
-' \
/ \
.' v
/-•x
y
/\
. _..._,':_\._
f N
MAY
/ \
' 1
X
/
/
/\ /
/ \ / \ /
/ \- V
/
,•
r
/\
' i
/ \ x-J / »
i ' "^ ' '
/' '
X-' /
...__..._... ^— r- • — •
/ N/
• - ^
-••• «e-i_ ^ I
^
JUNE
JULY
1
\ i \
V \
y
• /
\ ' \. -
\
I
\ /
\/ \ /
. .
\ 1
I
\ /
\ /
\ /
\l
AUGUST
\ /'\
'/ \
\
\
\
\
\
\
\
\ .
V
-25
-20
*di
%^*
E
-15 £
Q
^
-10
-5
SEPTEMBER
Figure 13.11. Monthly and weekly mean temperatures (°C) and vapor pressure
deficits (VPD) (mm Hg) for the 1975 growing season.
limited. However, local ranchers also indicated both years were
characterized by above-average spring precipitation.
Total soil water in the 105-cm profile did not vary significantly (P >
0.10) between treatments on Site I in 1975 or 1976. However, there were
significant (P < 0.01) treatment differences on Site II. The low and medium
treatment plots averaged a significantly greater quantity of soil water than
did the control or high treatment plots. Examination of soil water by 15-cm
increments across all sample dates indicated differences in total soil water
resulted from minor differences throughout the profile rather than from large
differences at any specified depth.
In order to evaluate differences in total soil water among Site 1-1975,
Site 1-1976, and Site 11-1976, total soil water of each of the respective
control plots was contrasted across eight sample dates. Analysis was limited
to control plots since they were sampled more frequently than treatment
plots. The ANOVA indicated significant (P < 0.01) year-site and date dif-
ferences and a significant year-site *• date interaction. Mean centimeters of
soil water for the eight sample dates contrasted were 18.4 cm for Site I-
1975, 16.5 cm for Site 1-1976, and 12.8 cm for Site 11-1976, with all means
significantly different. The year-site * date interaction (Figure 13.13)
410
-------
25-
^ 20-
O
o
*"""
LU
§"•
^
o:
LU
^ 10-
^
s-
5-
" Monthly ME
•an Temperatures
r-30
Weekly Mean Temperatures
Monthly Mean VPD
Weekly Mean VPD X '\
\
\
\
V .
*
'\
\
APRIL
i
/•-. 1
i ^'
— 7": f • — i
/' V
j
i
j
/
/ '
' \ / ^
•y
h
1 MAY
A
• \
\
\i —
\
\ I
V
*^ — ;
\
\ 1
X /""^^
'
JUNE 1
/ \
/ r'\ I N
/• \ / • , / \
r *: * v i ^r
! \J '\. /' \
i \ y i
/ v
/
x-v^
/ v
_^ \
^ \ : T
/ . .
""-?'; / ~\
, \
^ , v f
I ^
JULY 1 AUGUST
•\
1 •
/
'^ \ l\
\ i \
\i v
: \
V \
A
/ \
x x
' \
i — y
\ / \
V \
\_
-25
-20
'o*
X
-I
Q
&
-10
SEPTEMBER
Figure 13.12. Monthly and weekly mean temperatures (°C) and vapor pressure
deficits (VPD) (mm Hg) for the 1976 growing season.
suggested differences between treatments were primarily the result of dif-
ferences during the spring months. Difference between total soil water of
the two sites in 1976 was primarily attributed to greater rainfall in May on
Site I than on Site II.
Subtle Effects on Leaf Area
The date effect emphasizes the characteristics of the growing season of
this region (Table 13.12). Temperatures through the end of June in both 1975
and 1976 were cool and precipitation was abundant. However, near mid-July
growing conditions became less favorable as soil water was depleted and
average air temperatures increased. These conditions caused a reduction in
growth as reflected by the lack of an increase in leaf area from July to
August.
Measurements of total leaf area indicate minor differences in growing
conditions between 1975 and 1976 and between sites in 1976 (Figure 13.14).
Rapid increase in total leaf area from June to July in 1975 was attributed to
more favorable soil water conditions than in 1976 (Figure 13.13). Absence of
growth from July to August in 1975 was attributed to the very warm
temperatures during this time interval (Figure 13.11). Williams (1974)
411
-------
26-
24-
22-
20-
E
o
cr
UJ
18-
O
CD
12-
10-
8-
6-
Site I - 1975
Site I - 1976
Site H- 1976
APRIL I MAY I JUNE
AUGUST ' SEPTEMBER
JULY
Figure 13.13.
Seasonal dynamics of total soil water (cm) to a depth of 105 cm
in control plots for 1975 and 1976 growing seasons on Site I
and 1976 growing season on Site II.
412
-------
TABLE 13.12. MEAN VALUE OF WESTERN WHEATGRASS PLANTS FOR VARIOUS MEASURED PARAMETERS*
Parameters
Total leaf area (cm2)
Mean relative leaf growth rate (cm2 • cm~2 •
week"1)
Number of leaves
Total necrotic leaf area (%)
Necrotic leaf area of four oldest leaves (%)
Biomass (mg)
i— i
CO T -1
Mean relative growth rate (mg • mg i • week i)
May June
26.1 f
a
0.29
a
3.6
a
23.6
a
23.1
a
78.0 170. Ou
a b
0.70 0.19,
a b
Date
July
35.9,
D
0.07,
D
4'9b
31.4,
D
37.8,
D
244.0
c
0.10
c
August
36. 4^
D
0.00
c
5-2b
45.4
c
54.9
c
267. 0J
u
0.03,
a
September
—
—
—
267. 0J
a
0.00,
a
Mean values are averages of control, low, medium, and high S02 treatments for Site 1-1975,
Site 1-1976, and Site 11-1976. Average biomass and mean relative growth rates based only
on data from Site I in 1975 and 1976.
Means in a row followed by the same letter are not significantly different at P = 0.05.
-------
50
45
40
CVJ
E
o
35
LU
o:
U.
<
UJ
30
25
- Site I -1975
- Site I -1976
- Site U -1976
JUNE
JULY
AUGUST
Figure 13.14. Two-way interaction effects of date and year-site on total leaf
area (cm2) for individual western wheatgrass plants. Means
with overlapping vertical lines are not significantly different
at P = 0.05 (Q = 4.7).
414
-------
reported a marked decrease in the net photosynthetic rate of western wheat-
grass when temperatures exceeded 20°C. In 1976 (Figure 13.12) average
temperatures during this time interval were several degrees cooler than in
1975, and with ample soil water, plants on Site I continued to grow. However,
on Site II plants did not continue growth into August because of greater
water stress. The combined effect of these differences in growth conditions
between 1975 and 1976 and between the two sites in 1976 was responsible for
the significant year-site effect (Table 13.13).
The significant date x treatment interaction suggests S02 fumigation
altered plant growth rates from June to August (Figure 13.15), although the
only significant difference was in August when total leaf area of plants in
the high treatment was significantly greater than in the control. However, a
treatment effect was indicated by evaluating the rate of increase in total
leaf area between each sample date. To evaluate these differences, we
calculated mean relative leaf growth rates (RLGR) (cm2 • cm~2 • week"1) for
plants within each treatment between each sample date. The significant (P <
0.01) year-site and date effects (Tables 13.12 and 13.13) reflect differences
in growing conditions between the 1975 and 1976 growing seasons and the two
sites in 1976. In contrast to the total leaf area analyses, a significant (P
< 0.05) treatment effect was indicated in RLGR (Table 13»14).
The effect of S02 treatment on RLGR can be more clearly understood by
examination of the two-way interaction effect of date and treatment (Table
13.15). From the beginning of the growing season to mid-June, RLGR was
similar in all treatments. From mid-June to mid-July RLGR of plants in the
medium and high treatments was significantly greater than in the control and
low treatments. From mid-July to early August RLGR was not significantly
different between the control, medium, and high treatments. However, RLGR
for plants in the low treatment was significantly greater than for plants in
the control and medium treatments. In addition, lack of a significant year-
site x treatment interaction suggested this trend occurred both years on
Site I and on Site II in 1976. These results indicate a stimulation in leaf
growth as a result of S02 exposure.
To determine if the increase in leaf area was the result of larger
leaves, we compared the size of the four oldest leaves and their respective
RLGR. The significant (P < 0.01) date x leaf age x treatment x year-site
interaction indicated no treatment differences. Therefore, we assumed the
increase in total leaf area resulted from a greater number of leaves per
plant.
Significant treatment, year-site, and date effects (P < 0.05) were
revealed by the ANOVA for number of leaves, as well as significant date x
treatment and date x year interactions. The date x treatment interaction
(Figure 13.15) indicated plants in the low treatment averaged significantly
fewer leaves in July than plants in the control, medium, and high treatments.
However, by August plants in the control plots possessed significantly fewer
leaves than those in treatment plots. The date x year-site interaction
revealed a response similar to the total leaf area analyses except total
number of leaves increased significantly from July to August in 1973 while
total leaf area did not increase significantly. This apparent inconsistency
415
-------
*
TABLE 13.13. MEAN VALUE OF WESTERN WHEATGRASS PLANTS FOR VARIOUS MEASURED PARAMETERS'
Parameters
Total leaf area (cm2)
Mean relative
week"1)
leaf growth rate (cm2 • cm"2 •
Site I
1975
40.2 f
a
0.16
Year-site
Site I
1976
33.3,
D
0.12,
Site II
1976
24.8
c
0.08
Number of leaves
Total necrotic leaf area
Necrotic leaf area of four oldest leaves (%)
Biomass (mg)
Mean relative growth rate (mg • mg"1 • week"1)
5.0
a
31.6
a
41.4
a
180.0
a
0.26
4.1
a
38.8
a
230.0,
D
0.15,
4.0
34.8
35.9,
Mean values are averages of control, low, medium, and high S02 treatments for June, July,
and August sample dates. Biomass and mean relative growth rates based only on data from
Site I in 1975 and 1976 and includes May, June, July, August, and September sample dates.
t
Means in a row followed by same letter are not significantly different at P = 0.05.
-------
50r
Control
— — Low
Medium
High
E
o
LU
oi
45 r
40
35
30
25
JUNE
JULY
AUGUST
-7 40
ss
O 30
Q:
o
LU
20
<
LU
10
6.0
to
LU
LU 5.0
u.
o
85 40
CD
JUNE
JULY
AUGUST
Figure 13.15.
Two-way interaction effects of date and treatment on total leaf
area (cm2) , total necrotic leaf area (%) , and total number of
leaves for individual western wheatgrass plants. Means with
overlapping vertical lines on the same date are not signifi-
cantly different at P = 0.05 (Q = 6.0) for total leaf area, at
P = 0.05 (Q = 6.1) for total necrotic leaf area, and at P =
0.05 (Q = 0.5) for total number of leaves.
was attributed to shrinkage in leaf area from senescing tissue. The signifi-
cant two-way interaction effects of date x treatment and date x year-site
provided insight into the cause for the significant date, year-site, and
treatment effects (Tables 13.12 to 13.14). Based on the close relationship
between total leaf area and number of leaves per plant, it was apparent the
suggested growth stimulation resulted from an increase in number of leaves
per plant.
Visible Effects on Leaf Surfaces
Statistical analyses of percentage of necrotic leaf area per plant
indicated significant (P < 0.01) treatment and date effects and a significant
date x treatment interaction. Although significant differences did occur
between plants in the low treatment and the medium and high treatments none
were significantly different from plants in the control and thus no leaf
injury could be attributed to S02 fumigation (Table 13.14).
417
-------
TABLE 13.14. MEAN VALUES OF WESTERN WHEATGRASS PLANTS FOR VARIOUS MEASURED PARAMETERS'
Treatments (S02)
Parameters
Control
Low
Medium
High
-o-
M
00
Total leaf area per plant (cm2)
Mean relative leaf growth rate (cm2 • cm"2 •
week"1)
Number of leaves per plant
Total necrotic leaf area (%)
Necrotic leaf area of four oldest leaves (%)
Biomass (mg)
Mean relative growth rate (mg
~~1 • week"1)
7.4
t
0.10
4.4
32.0
ab
36.5
223.0
7.6
0.12
ab
4.5
ab
27.8
31.5
186.0,
6.9
0.12
ab
4.6
ab
36.2,
41.9
be
185.0,
7.3
0.14,
4.7,
37.0,
44.5
227.0
Mean values are averages of Site 1-1975, Site 1-1976, and Site 11-1976 for June, July, and
August sample dates. Biomass and mean relative growth based only on data from Site I in 1975
and 1976 and includes May, June, July, August, and September sample dates.
t
Means in a row followed by same letter are not significantly different at P = 0.05.
-------
TABLE 13.15. TWO-WAY INTERACTION EFFECTS OF DATE AND TREATMENT
ON MEAN RELATIVE LEAF GROWTH RATE FOR WESTERN
WHEATGRASS PLANTS
Treatment
Beginning of growth
to mid-June
Mean relative leaf growth rate:
Mid-June to
mid-July
Mid-July to
early August
Control
Low
Medium
High
0.30
a
0.30
a
0.29
a
0.29
a
0.04
a
0.03
a
0.11,
b
0.11,
D
-0.03
a
0.03,
b
-0.04
a
0.01 ,
ab
cm
2 • cm~2 • week
The date x treatment interaction indicated a lower percentage of leaf
necrosis for plants in the control and low treatments in June than for plants
in the medium and high treatments (Figure 13.15). However, by July only
plants in the low treatment had a significantly less amount of leaf necrosis
and by August no differences were noted. The significant date effects
reflected an increase in necrosis in all treatments with increasing plant age
(Table 13.12).
Visual examination of leaf surfaces of treatment plants did not reveal
any abnormal patterns of necrosis which could be attributed to S02 fumigation.
Based on studies by Thomas (1956), Bleasdale (1973), and Bell and Clough
(1973) , we assumed an increase in leaf senescence would be the most probable
mode of western wheatgrass to express visible injury from chronic S02 fumi-
gation. In order to evaluate this hypothesis, an analysis of the percentage
of necrotic leaf area of the four oldest leaves of each plant was undertaken.
Significant (P < 0.01) treatment, leaf age, and date effects were
revealed in the ANOVA based on the four oldest leaves. Because of the
complexity of the ANOVA model, numerous interactions were significant. Those
interactions related to both date and leaf age were found to agree closely
with the main effects of date and leaf age which suggested leaf necrosis
increased with increasing leaf age and time (Table 13.12).
Treatment effects were similar to those found in the analyses for
percentage of necrotic leaf area for the entire plant (Table 13.14). However,
the addition of a significant difference between average percentage of
necrotic leaf area for plants in the control and high treatments, based on^
the four oldest leaves of each plant, confirmed an increase in leaf necrosis
as a result of S02 fumigation.
419
-------
Examination of the significant three-way interactions more clearly
elucidated treatment effects. The date x leaf age x treatment interaction
generally indicated an increase in leaf necrosis with increasing S02
concentration for all ages of leaves in all months except July (Figure 13.16).
In July, percentage of necrotic leaf area in the first (oldest leaf), second,
and third leaves of plants in the low treatment was significantly less than
for plants in the control or two higher treatments. The date x treatment x
year-site interaction supported this trend for both 1975 and 1976 on Site I
and 1976 on Site II.
Subtle Effects on Plant Growth
Because of differences in range condition among the four treatment plots
of Site II, growth analyses were limited to Site I.
Analysis of variance for average dry weight biomass of individual plants
for the May through September sample dates indicated significant (P < 0.01)
year, treatment, and date effects and a significant year x date interaction.
The year x date interaction emphasized differences in growing seasons between
the two years. Because of earlier growth initiation in 1976, equivalent
biomass was attained approximately one month earlier than in 1975. In addi-
tion, standing crop biomass began to decrease by September 1976. This was
probably because of increased leaf shedding.
The significant year effects indicated greater biomass in 1976 than in
1975 when averaged across all dates (Table 13.13). The year x date inter-
action, however, suggested this conclusion was misleading with regard to peak
biomass which was equal in both years. The significant treatment effect
indicated individual plant biomass in the control and high plots was signif-
icantly greater than in the low and medium plots (Table 13.14). No explana-
tion for these differences can be provided other than sampling variation in
either biomass or density. The date effect indicated a continuation of
growth until August with no significant growth between August and September
(Table 13.12). Again, this emphasizes the characteristic growing season
typical of this region.
The ANOVA for mean relative growth rates (RGR) (mg • mg"1 • week"1)
indicated significant (P < 0.01) year and date effects and a significant year
x date interaction. The year x date interaction revealed the cause for the
significant year effect (Table 13.13). The higher RGR throughout the 1975
growing season resulted primarily from a higher RGR between growth initiation
to mid-May in 1975 than in 1976. Although average biomass of individual
plants was only 54 mg in May 1975, as compared to 102 mg in May 1976, the RGR
was greater in 1975 than in 1976 since time from initial growth to mid-May
was less in 1975 (31 days) than in 1976 (59 days). Mean relative growth
rates decreased rapidly after mid-June in both 1975 and 1976 which emphasizes
growing season characteristics.
Although no significant treatment effects were noted in the RGR analyses,
we assumed possible differences in leaf area ratios (LAR) and aboveground net
assimilation rates (NAR) may have resulted from the apparent stimulation in
420
-------
100
Leaf I
Leaf 2
Leaf 3
Leaf 4
\
H
Control Low Medium High Control Low Medium High Control Low Medium High
JUNE JULY AUGUST
Figure 13.16.
Three-way interaction effects of date, leaf age, and S02
treatment on percentage of necrotic leaf area for individual
western wheatgrass plants. Oldest leaf is Leaf 1. Treatment
means with overlapping vertical lines on same date are not
significantly different at P = 0.05 (Q = 10.4).
leaf growth attributed to S02 treatment as indicated in the leaf area analy-
ses. Statistical analyses of the average LAR and NAR for individual plants
indicated no significant treatment effects although differences in dates and
years were noted. These differences were attributed to temporal variations
in growing seasons.
Discussion
Because of the relationships between subtle and visible effects of
chronic S02 fumigations on western wheatgrass, discussion of the results
pertinent to the first two objectives overlap. Thus, we discuss visible
effects first and then relate these to subtle effects.
Recently, Tingey et al. (1976) exposed western wheatgrass plants,
collected near our study areas, to acute levels of S02. Exposures at concen-
trations of 100 to 125 pphm S02 for 4 h were necessary to induce acute visible
injury on leaf blade surfaces. This injury frequently occurred as small
bifacial lesions and interveinal streaks of necrotic tissue ranging in color
from light tan to ivory. Injury frequently developed first near the leaf tip
of younger leaves and near the bend of the leaf in older leaves.
Visual examination of leaf surfaces in our study revealed no abnormal
lesions or interveinal streaks which could be attributed to S02 treatment.
An increase in leaf senescence was the only apparent visible injury incurred
421
-------
as a result of S02. Furthermore, the magnitude of this increase was insuffi-
cient to permit visual detection on individual plants. An increase in leaf
senescence was first suggested in the analyses based on the entire leaf
surface of each plant and was confirmed from the significant interaction of
date x leaf age x treatment in the analysis of the four oldest leaves.
Furthermore, it seems apparent this response was dependent on dosage of S02
received since it was related to both duration of exposure (date) and
concentration (treatment).
Previous research investigating effects of chronic S02 exposures on
perennial ryegrass has suggested an increase in leaf senescence resulting
from S02 treatment (Thomas, 1956; Bleasdale, 1973; Bell and Clough, 1973).
However, the mechanism whereby S02 may cause an increase in leaf senescence
is not totally understood. It is generally accepted that after entry into
the leaf, S02 is rapidly dissolved on the moist surfaces of the mesophyll
cells to form sulfite which in turn is slowly oxidized to sulfate (Thomas
et al. , 1950; Ziegler, 1975). Thomas and Hendricks (1956) reported sulfate
was approximately 1/30 as toxic to a plant as was sulfite. It follows that
as long as S02 is not absorbed at a rate exceeding the cell's capacity to
oxidize sulfite to sulfate, sulfite is prevented from reaching toxic levels.
However, as the concentration of sulfate increases over time, toxic levels of
sulfate are eventually attained (Malhorta and Hocking, 1976) and thus,
increased leaf senescence is observed.
Our data suggest that until approximately mid-June, western wheatgrass
plants grew at a rate sufficient to incorporate the S02-sulfur into normal
metabolites, thereby preventing toxic levels of sulfite or sulfate from
accumulating. Lack of a treatment effect in May 1976 emphasizes the impor-
tance of rapid growth rates. Sulfur dioxide treatments were initiated approx-
imately six weeks later in 1975 than in 1976 and therefore, significantly
greater dosages of S02 were encountered on corresponding dates in 1976 than
in 1975. Treatment means for the percentages of necrotic leaf area on Site I
were not significantly different between June 1975 and June 1976. Thus, it
is apparent sulfate was prevented from reaching toxic levels by incorporation
into normal metabolic processes and leaf senescence was therefore delayed.
Recently, Schwartz e~t at. (1978) (see preceding section) reported increasing
concentrations in total sulfur with increasing S02 concentrations in western
wheatgrass tissue subsampled from our harvest samples of live tissue. Their
data indicate a sharp increase in total sulfur concentrations after mid-June
with similar concentrations in June of both 1975 and 1976.
Previous research has indicated plants are most sensitive to S02 injury
when conditions are most favorable for optimal growth (Katz, 1949; Daines,
1968). However, data supporting this generalization were primarily attained
from acute levels of exposure rather than from chronic levels similar to
those utilized in this study. The importance of optimal growth rates in
acute exposures is to provide an avenue of ingress of S0£ into the plant
through the open stomata. Our results suggest that rapid growth prevented
sulfate from attaining a toxic concentration. Once metabolic activity began
to slow, either because of maturation of older leaves or adverse growing
conditions, toxic levels of sulfate were assumed to have accumulated. Both
growing seasons were characterized by a wet season followed by a dry season
422
-------
with a rather abrupt transition occurring during July. Therefore, the time
period of moderate growth rates was limited and low levels of S02'fumigation
were insufficient for toxic levels of sulfate to accumulate. Thus, plants in
the low S02 treatment did not express an acceleration in leaf senescence
although plants in the medium and high treatments did experience increased
senescence.
The decrease in percentage of senescing leaf tissue of the three oldest
leaves in the low treatment in July (Figure 13.16) on Site I in 1975 and 1976
and Site II in 1976 is perplexing. Two explanations for this decrease seem
plausible: (1) inherent differences in growing conditions between the con-
trol and treatment plots accelerated leaf senescence in the control plants,
or (2) a stimulation in leaf growth, as a result of S02 treatment, reduced
leaf senescence in the low treatment.
The first explanation is formulated strictly on field observations
during the two years of data collection. On Site I we assume differences in
available soil water existed between treatment plots. On Site II differences
in available soil water between the control and low treatment and possible
differences in previous grazing intensities are assumed to have existed. The
following observations support these assumptions.
Several large areas of slight surface depressions were noted in the
control plot on Site I. These areas were assumed to have resulted from
previous removal of top soil either by wind or water. Surface soils within
these areas had a higher clay content than soils throughout the remainder of
the plot. In addition, vegetation within these areas generally reflected
greater water stress than adjacent vegetation. It is assumed the high clay
content of the soil in these areas induced greater water stress on the
vegetation and a reduction in growth and increased leaf senescence resulted.
This was most evident in July since growing conditions in June were closer to
optimal than in July and considerable water stress masked differences between
all treatments in August. Although these areas were avoided when sampling,
their influence may have exceeded visual detection.
Similarly, on Site II differences in total soil water discussed pre-
viously may have caused decreased growth and accelerated leaf senescence. In
addition, visual examination of the control plot suggested heavy grazing
occurred on the plot prior to fencing in 1975. Therefore, a possible
decrease in plant vigor in 1976 could be expected (Tomanek and Albertson,
1953; Laycock, 1967). Again, increased leaf senescence and a reduction in
growth may have resulted.
Based on the above observations, interpretation of the treatment effects
of this study is significantly altered from an interpretation disregarding
any inherent difference between treatment plots. The significant date x
treatment interaction in the analyses of the total leaf surface, number of
leaves, and percentage of necrotic leaf area for individual plants supports a
reduction in growth on the controls and increased leaf senescence near
mid-July (Figure 13.15). In addition, the reduced senescence displayed in the
low treatment in July can be hypothesized to have resulted from an abnormal
but relatively higher rate of senescence in the control plants. The critical
423
-------
dosage required to induce an acceleration in leaf senescence probably was not
attained in the low S02 treatment until after the July sample date. However,
it is questionable whether S02 dosage in the low treatment was ever suffi-
cient to induce increased leaf senescence since no significant differences
were apparent between plants in the control and low treatments. In addition,
leaf senescence was higher in the control plot than the treatment plots in
August 1976 on Site I. This fact certainly adds credence to this explanation.
The second explanation, involving a stimulation in leaf growth because
of S02 treatment, was indicated by analyses of average number of leaves for
individual plants and average RLGR during June, July, and August. Further-
more, the treatment x date interactions, discussed previously, provided
support for this explanation.
Total leaf surface of the control plants increased at a relatively
constant rate from June to August (Figure 13.15). However, a period of
accelerated leaf growth was evident from June to July in the medium and high
treatments and from July to August in the low treatment. These periods of
accelerated growth were primarily the result of an increase in number of
leaves and not larger leaves. Lack of significant treatment x year inter-
actions suggests these periods of accelerated growth were replicated in all
three year-sites. Furthermore, the presence of significant treatment effects
in the ANOVA for number of leaves and RLGR supports a stimulation of leaf
growth because of S02 treatment. Treatment means indicate increasing number
of leaves and increasing RLGR with increasing S02 concentration (Table
13.14).
Although inherent differences in growing conditions may have occurred
between the control and treatment plots, evidence of a stimulation in leaf
growth with increasing S02 persists when data from control plots are
disregarded. Thus, we conclude leaf growth was stimulated by chronic S02
fumigations.
At least two explanations can be hypothesized whereby a stimulation in
growth, as a result of S02 fumigation, appears logical. The first explana-
tion requires extension of the dosage response, which we concluded increased
leaf senescence, to include a dosage response stimulating leaf growth. Since
rapid leaf growth occurred near the time of accelerated senescence, we suggest
S02 directly stimulated leaf growth at a dosage near that required to cause an
increase in senescence. Since the threshold dosage required to induce
accelerated leaf senescence would be influenced by tissue age and exposure
time, analyses of the percentage of necrotic leaf area for the entire plant
render support to this hypothesis. Because of accelerated growth from June to
July in the medium and high treatments, leaf senescence by mid-July was
similar in the control, medium, and high treatments (Figure 13.15). This
resulted because a proportionally greater quantity of young leaf tissue was
present in the treatment plots. Percentage of total necrotic leaf area was
thereby reduced since dosage was insufficient to accelerate senescence in the
younger leaf tissue. However, dosage was sufficient to accelerate senescence
in the older leaves (Figure 13.16).
424
-------
The reduced senescence displayed by the four oldest leaves of the low
treatment plants in July is hypothesized to have resulted from the inter-
action effects of simultaneous accelerated growth and senescence. Since leaf
senescence begins at the leaf tip and gradually advances toward the base, it
is apparent that age of leaf tissue is important in normal senescence. It
follows that tissue at the leaf tips receives a greater dosage "of S02 than
the younger tissue near the intercalary meristem at the leaf base. We have
measured higher concentrations in total sulfur in leaf tips than in bases in
fumigated plants (Ziegler, 1975). We assume tissue near the leaf tip
received a dosage of S02 by July, sufficient to induce accelerated senescence
while tissue near the base received a dosage sufficient to stimulate growth.
The interaction of decreasing leaf area because of senescence and
increasing leaf area because of growth may possibly account for the lack of
any significant treatment effects on size of leaves. Average RLGR from June
to July for the four oldest leaves was -0.027, 0.002, 0.016, and 0.010 cm2 •
cm"2 • week"1 in the control, low, medium, and high treatments, respectively.
Although these rates were not significantly different, they do provide trend
information whereby the July data can be explained. We assume leaves of the
control plants were not growing at a sufficient rate to counteract the
shrinkage accompanying normal leaf senescence and thus, an overall negative
rate of leaf growth resulted. In the high treatment, leaf senescence
occurred at an accelerated rate, because of dosage, but leaves were also
growing at an accelerated rate sufficient to counteract shrinkage and thus an
overall positive increase in leaf area occurred. This was also true in the
medium treatment. In the low treatment, rate of growth was sufficient to
nullify the effect of senescence and therefore percentage of necrotic leaf
area was low.
For S02 to act as a growth stimulant, we assume S02-sulfur can act as a
source for normal sulfur requirements. Previous research has indicated at
least a portion of a plant's sulfur requirements can be met by direct uptake
of S02 if present at very low concentrations (Faller, 1971; Bromfield, 1972;
Cowling et at., 1973; Cowling and Lockyer, 1976).
From these studies it is apparent S02 can act as a source of sulfur,
particularly when sulfate in the growing medium is inadequate to meet normal
sulfur requirements of a plant. Furthermore, under conditions of adequate
sulfur nutrition, low levels of S02 appear to possibly stimulate aboveground
growth (Faller, 1970, 1971). Nonsignificant increases have been reported in
the grain yield of little club wheat (Trit-icm aestivum L.) (Swain and
Johnson, 1936) and the dry matter yield of alfalfa (Thomas et al. , 1943) when
plants were exposed to low levels of S02 in the presence of adequate sulfur
nutrient.
Contrary evidence suggesting a depression of perennial ryegrass yield
when exposed to low concentrations of S02 has been provided by Bell and
Clough (1973). Plants exposed to 6.7 pphm S02 throughout a 26-week growth
period reduced number of tillers by 41%, number of leaves by 44/0, dry weight
of live leaves by 50%, and leaf area per plant by 51% when compared to _
control plants. Similar results were reported during both summer and winter
growing conditions. However, six weeks after sowing, when plants were mostly
425
-------
at the three-leaf stage, length of the second leaf of the control and SC>2
treatment plants was measured. These measurements indicated treatment plants
had a slight but significantly larger second leaf than control plants. No
explanation was provided for this apparent stimulation in leaf size.
Bleasdale (1973) reported plants grown in continuously scrubbed air
exceeded the yield of plants grown in continuously polluted air by 20% to
135%. In addition, number of leaves and number of tillers per plant were
significantly reduced when plants were grown in continuously polluted air.
However, when plants were exposed to polluted air for only a portion of each
day, marked increases in dry-weight, in number of leaves, and in number of
tillers per plant were noted. The author suggested intermittent exposure to
S02 enhanced cell division by interfering with the balance between oxidized
and reduced sulfur radicals which Hammett (1930) suggested was an important
factor in controlling normal cell division. Similar conditions may have
promoted the increase in number of leaves per plant associated with increasing
S02 in our study. Sulfur dioxide concentrations during nighttime often
exceeded daytime concentrations by a factor of ten because of reduced wind
velocities and reduced thermal uplift during the night.
Since soils within our study areas are not considered sulfur deficient,
our results appear to conflict with the two studies above. However, both
studies do suggest some possible stimulation in leaf growth which may be
applicable here. It should also be noted that ryegrass is considered a
sensitive species to SOj? fumigation whereas the results reported by Tingey
et at. (1976) indicate western wheatgrass is more resistant.
It may also be hypothesized that the stimulation in growth was the
indirect result of increased senescence. It has been well documented that
net photosynthetic rates change as leaves age (Thorne, 1963; Moss and Peaslee,
1965; Jewiss and Woledge, 1967; Lupton, 1968; Risser and Johnson, 1973).
Since normal leaf senescence is dependent on leaf age, it may be postulated
that removal of the oldest leaves would increase the average photosynthetic
rate of the plant. If average photosynthetic rate was increased, then the
resulting effect might be a stimulation in growth. Kulman (1971) noted an
increase in aboveground growth of trees when the older, less photosyntheti-
cally active leaves were removed. Thus it can be hypothesized that the
increased rate of senescence caused by S02 increased the average photosyn-
thetic rate of western wheatgrass and this in turn stimulated shoot growth.
It has also been shown that senescing leaves act as a net exporter of
certain minerals and metabolites (Brady, 1973). For example, it has been
estimated 90% of the nitrogen and phosphorus and 70% of the potassium may
eventually be transported from senescing leaves (Williams, 1955). Thus,
various hypotheses may be postulated as to why accelerated leaf senescence
might stimulate leaf production.
The third objective was to evaluate the effects of chronic SQ2 fumiga-
tions on relative growth rates, net assimilation rates, and leaf area ratios
of individual plants. Although alterations in total leaf area and rate of
senescence were attributed to S02 treatment, the magnitude of these altera-
tions was insufficient for detection at the plant level of organization.
426
-------
However, it must be emphasized that the sensitivity of our growth analyses
was at a level where changes of rather large magnitudes would be necessary
for detection of significant differences. Although alterations in growth
parameters probably occurred at various times between each sample date, the
accumulative effects were not detectable because of the variation in sample
estimates. In addition, only aboveground growth was examined and it is
feasible that major treatment differences in RGR and NAR may have occurred in
the belowground portion of each plant.
Summary of 1975 and 1976 Studies
The effects of three different concentrations of sulfur dioxide (S02) on
western wheatgrass (Agropyron smithii Rydb.) in a Montana grassland were
studied. The response of western wheatgrass was examined at three levels of
organization: organ (leaf), organism (plant), and community.
Forty western wheatgrass plants were collected from each treatment in
June, July, August, and September 1975 and in May, June, July, and August
1976. Leaves were removed and mounted between two clear pieces of acetate
and total adaxial leaf area and necrotic area were recorded. Aboveground
biomass was sampled monthly, by the harvest method, over the 6-month growing
season. Abiotic parameters monitored were: precipitation, soil water,
temperature, relative humidity, and S02 concentrations.
It was concluded that S02 fumigation stimulated leaf growth. This
stimulation was reflected by greater numbers of leaves per individual western
wheatgrass plant rather than larger leaves. Increased leaf number appeared
to be directly related to both time and concentration of S02 exposure (dosage
response). Two hypotheses were advanced as plausible explanations for
stimulation of leaf production. The first was based on the assumption that
S02 directly stimulated growth while the second suggested stimulation was an
indirect effect of S02.
No abnormal lesions on leaf surfaces were evident which could be attrib-
uted to S02 treatment. However, an increase in leaf necrosis was concluded
to have occurred with increasing S02 treatment. The increased necrosis was
not visibly distinguishable from normal leaf senescence.
(
Examination of the response of individual plants indicated no signifi-
cant alterations in aboveground relative growth rates, net assimilation
rates, or leaf area ratios. However, it was suggested that caution be exer-
cised when relating these conclusions to long-term effects because of the
magnitude of variability associated with the analyses of the responses at the
organism and community levels or organization.
Growth and Senescence (1977)
Data collection procedures were altered for the 1977 growing season to
accommodate a change in emphasis of our research program from biomass dynam-
ics and primary production to physiological responses. Because we would no
427
-------
longer be sampling biomass at frequent intervals during the growing season,
estimates of growth and senescence for 1977 are based on repeated measure-
ments on 20 plants in each treatment plot. Measurements of total height,
length, and width at the base of each leaf, length of green tissue on each
leaf, and total number of leaves were made at one- to two-week intervals from
13 April to 17 August. On 17 August each plant was harvested, labeled, and
stored for chemical analysis. Leaf area was calculated by assuming that the
leaves were triangles. This certainly results in a small error since the
leaves are not exact triangles. Since there is no indication that leaf shape
is altered by S02 either from the literature or our own work, we believe that
this is a valid method to compare treatments.
Because we have not had time to carefully analyze these data, the
results presented here will be limited to those that correspond to the sig-
nificant findings from the 1975 to 1976 work. These are significant
increases in the number of leaves per plant and in leaf senescence with
increasing S02 concentration.
Leaf numbers for the control and treatments on Site I indicated no
differences throughout the growing season (Figure 13.17). In addition, there
were no differences in the timing of leaf development. Results for Site II
were similar except that there was a slight increase in leaf numbers on the 5
and 10 pphm treatments (Figure 13.18).
Figures 13.19-13.26 illustrate the dynamics of leaf area for leaves 1-4
on Site I and II, respectively. The generalization that can be made from all
of these data is that S02 causes senescence to begin earlier and reduces the
functional life of the leaves of western wheatgrass. Leaf 2 from Site I may
be used as an example to illustrate both of these points. The first dates
when measurable dead material was observed were 28 May, 28 May, 9 May, and
25 April for the control, low, medium, and high treatments, respectively.
The dates of total senescence in the same order were 28 July, 28 July,
23 June, and 10 June. These dates were selected using overlap of the standard
error bars as an indication of no significant difference. The functional
lives of these leaves were then 106, 106, 71, and 58 days. This is only a
very rough expression of the functional lives of these leaves because the
data also indicate increasing S02 increased the rate that 100% senescence was
approached. Once we begin to understand the relationships of leaf age and
S02 to photosynthesis of western wheatgrass, we will be in a better position
to describe the functional significance of increased senescence.
EFFECTS OF CONTROLLED LEVELS OF S02 ON
PHYSIOLOGY OF WESTERN WHEATGRASS
Investigations begun in 1977 emphasized physiological responses of
western wheatgrass both under field and laboratory conditions. Variables
measured in the field included air temperature, relative humidity, wind
speed, solar radiation, leaf water potential, stomatal conductance, and
lltC02 fixation. Laboratory investigations are just beginning at this time
and variables to be monitored are air temperature, dew point temperature,
428
-------
UJ
UJ
O
o:
UJ
m
CONTROL
LOW
10
UJ
LU 5
MEDIUM
HIGH
-I 1-
Apr May Jun Jul Aug Apr May Jun Jul Aug
Figure 13.17. Mean number of leaves per plant, ± 1 SE, ZAPS I, 1977.
light intensity, sulfur dioxide concentration, stomatal conductance,
transpiration, photorespiration, dark respiration, and net photosynthesis.
Methods
Field Investigations
Carbon fixation under control and high S02 concentrations (10 pphm) was
measured using 14C02 and a labeling technique described by Shimshi (1969).
Intact leaves are exposed to 14C02 for a short period of time (15 s) , har-
vested immediately and placed in a test tube on dry ice to minimize loss of
lt+C as a result of respiration. Samples are taken to the laboratory and
prepared for liquid scintillation courting by the procedures described by
Tieszen et al. (1974).
Stomatal conductance was measured with a mass flow porometer modified
for use on narrow leaf grasses. Leaf water potential was measured with a
pressure bomb (Scholander et al. , 1965). Water potential was measured on
leaves immediately following exposure to 14C02.
429
-------
10
UJ
<
LU
u_
o
cr
m 10
CONTROL
UJ
tr
LU
MEDIUM
LOW
HIGH
H 1 1
H 1 1
Apr May Jun Jul Aug Apr May Jun Jul Aug
Figure 13.18. Mean number of leaves per plant, ± 1 SE, ZAPS II, 1977.
100
CONTROL
CM
<
LU
50
Total
Live
50-
0
MEDIUM
Aiv-
-\ 1 1
-! , ,
LOW
HIGH
fr—M 1 1
Apr May Jun Jul Aug Apr May Jun Jul Aug
Figure 13.19. Area of Leaf 1, live area, and senesced area, ± 1 SE, ZAPS I,
1977.
430
-------
I50r
100
CM
50
a:
<
u.
<
u
CONTROL
Total
Live
Dead
LOW
100
50
MEDIUM
HIGH
Apr May Jun Jul Aug Apr May Jun Jul Aug
Figure 13.20. Area of Leaf 2, live area, and senesced area, ± 1 SE, ZAPS I,
1977.
Description of the Laboratory C02 Exchange System (Figure 13.27)
Air is supplied by the laboratory compressor system. The air is then
pressure-regulated to a low value and scrubbed clean of all C02, moisture,
ozone, and any other impurities using molecular sieves. An adjustable
humidifier provides the capability to adjust the dew point of the air stream
to any desired value. Carbon dioxide gas is then added to the air stream to
provide a 310-ppm concentration using a "mixing tee" which was designed to
provide complete mixing of the C02 into the carrier air stream. Sulfur
dioxide is then added to the air stream through another (stainless steel)
mixing tee. A temperature controller will provide flexibility in
regulating the air stream temperature.
The gas stream then is split into two branches. The first branch goes
to the Beckman Infrared Gas Analyzer (IRGA) reference cell for determination
of the C02 content of the input stream. The second branch is routed through
431
-------
200r CONTROL
150
100
CM
O
LL)
o:
50
- Total
- Live
- Dead
r LOW
UJ
MEDIUM
HIGH
May Jun Jul Aug Apr May Jun Jul Aug
Figure 13.21. Area of Leaf 3, live area, and senesced area, ± 1 SE, ZAPS I,
1977.
432
-------
200
150
100
-------
E
o
LU
o:
LL
<
LU
I00r CONTROL
Total
Live
Dead
50
/' ~\-
I * N,
-i-r1 i
.-LOW
J*\.
lOOr
50
MEDIUM
HIGH
Apr May Jun Jul Aug Apr May Jun Jul Aug
Figure 13.23. Area of Leaf 1, live area, and senesced area, ± 1 SE, ZAPS II,
1977.
a Plexiglass leaf cuvette situated under an adjustable 1000-watt Holophane
sodium lamp. Temperature control for the cuvette is provided by a heat-
absorbing water layer filter between the lamp and the cuvette, and by water
circulated from a Masterline temperature-controlled bath to a water jacket
in the cuvette. After passing through the cuvette, part of the stream is
monitored for C02 content by the IRGA sample cell.
In order to monitor the humidity and S02 content of the air stream
entering and exiting the cuvette, samples are taken from both sides of the
cuvette and routed, by a time-sharing device, to a dew point hygrometer and
an S02 analyzer. The IRGA requires a stream of air with constant C02 concen-
tration to serve as a purge, and this is provided by a division of the air
stream after the scrubbers. When each stream of air has served its purpose,
it is routed to a "dump" where it is disposed.
Results
Field Investigations
Since field studies have been in progress for only one field season,
only a sample of the information we are collecting will be presented here.
Average diurnal patterns of environmental variables, leaf water potential,
434
-------
150
CONTROL
Tptal
Live
Dead
LOW
CVI
E
o
LU
cr
lOOh
May Jun Jul Aug Apr May Jun Jul Aug
Figure 13.24. Area of Leaf 2, live area, and senesced area, ± 1 SE, ZAPS II,
1977.
and 11+C02 uptake for a 3-day period in early July are presented for the
control and high S02 treatment in Figure 13.28. Maximum air temperature was
23°C, occurring at 1600. Winds were light and variable ranging from zero at
0600 to 3 m • s"1. Predawn relative humidites averaged 75% and decreased to
30% at 1000 and remained constant throughout the remainder of the day.
Maximum radiation was 70 cal • cm"2 • h"1 at 1500.
Predawn leaf water potentials were greater than -5 bars for both the
control and high treatment. Leaf water potentials decreased rapidly reaching
-20 bars by 0700 for the control. Minimum leaf water potentials were -35
bars for the control at 1400 and -30 for the high treatment at 1600.
Uptake of ^C02 was maximum for the control between 0800 and 0900 at
13 mg 14C02 - dm'2 • h"1 and remained low for the remainder of the days. The
435
-------
200
150
100
CM
6
o
LU
on
50
CONTROL
Total
Live
Dead
LOW
r MEDIUM
100
50
/
rHIGH
Apr May Jun Jul Aug Apr May Jun Jul Aug
Figure 13.25. Area of Leaf 3, live area, and senesced area, ± 1 SE, ZAPS II,
1977.
436
-------
200
150
100
CONTROL
Total
Live
Senesced
LOW
Apr May Jun Jul Aug Apr May Jun Jul Aug
Figure 13.26. Area of Leaf 4, live area, and senesced area, ± 1 SE, ZAPS II,
1977.
437
-------
Temperature
Controller
Dwyer
Flowmeter
Dwyer
Flowmeter
Gilmont
Flowmeter
Environmental
stabilizer stream
to analyzer
Dew Fbint
Hygrometer
Gilmont
Flowmeter
I
Drier ite
Leaf
Cuvette
i
Drier ite
C02
Sample
Cell
I C02
! Reference
! Cell
Dump
Figure 13.27. Laboratory C0£ exchange system.
438
-------
30
I
.2 CM
o
*-
O oi
£ c
0- 3
•B 60
J
.2 40-
'c
20H
o-
20
^ 754
~ 50
E
1 25-\
It 60-
J
o 40-
"c
o>
? 20-1
o-
20
h
I
O O>
a J
15-
ioH
5H
6789^ ^M \2 13 14 15 16 17
Time of Day (hrs)
0
6 7 8 9 10 II 12 13 14 15 16 17
Time of Day (hrs)
Figure 13.28. Diurnal patterns of gross photosynthesis, leaf water potential,
and selected abiotic variables for western wheatgrass on the
control (c) and high (h) treatments in early July 1977. (All
physiological data are from observations collected during a
3-day interval; abiotic data are averages for the same 3-day
period.)
439
-------
37.5-1
30.0-
o
* 22.5
o
"c
15.0-
w
*•
o
7.5-
I.5H
0
8 9 10 II
Time of Day (hrs)
i
12
13
14
15
16
17
Figure 13.29. Diurnal patterns of leaf water potential in western wheatgrass
for one day in July 1977 (A = control, D = high treatment).
dynamics of uptake were less clear for the high treatment.
that fixation rates may have averaged 13 mg 1I+C02 * dm"2 •
greatest portion of the days.
The data indicate
h-1 for the
A more detailed view of diurnal changes in leaf water potential is
presented in Figure 13.29. These data are averaged across all leaves for
each plant measured. On this particular day there were substantial dif-
ferences in leaf water potential between the control and high treatment
plants. Predawn leaf water potentials were near zero. Water deficits
developed rapidly in control plants with leaf water potential decreasing
to -23 bars at 0900. Leaf water potential decreased less rapidly in plants
from the high treatment and was -15 bars at 1000. Minimum leaf water
potentials for plants from both areas were measured in late afternoon.
Laboratory Investigations
Our work with physiological responses of western wheatgrass to S02 under
controlled conditions is just beginning. Figure 13.30 presents preliminary
data on the response of net C02 exchange of western wheatgrass as a function
440
-------
25-1
CVJ
20-
CVJ
o
O
15-
o
o
UJ
o
I
o
X
LU
o
10-
5-
OJ
o
o-
0
100 200 300
C02 CONCENTRATION (ppm)
400
Figure 13.30. C02 exchange versus C02 concentration.
of C02 concentration. The three plants used in this experiment indicate a
range of responses of net photosynthesis to C02 concentration. The regres-
sion line with a r2 of 0.93 indicates the average for the three plants.
DISTRIBUTION OF 35S02 SULFUR AND
14C09 CARBON BY NATIVE MIXED-GRASS
PRAIRIE AND POSSIBLE S09 EFFECTS*
Introduction
The pattern by which assimilated carbon is distributed within plants is
of considerable interest to those who wish to understand fully the role
played by primary producers in ecosystems. Realistic conceptual or mathemati-
cal models of ecosystems demand an understanding of both above- and below-
ground productivity as well as the often slighted integration of the two. A
focal point for such an integration lies, of course, with the primary
Excerpted from a dissertation in preparation by Michael B. Coughenour,
"Grassland Sulfur Cycle and Ecosystem Responses to Low-Level S02."
441
-------
producers themselves, for it is they that exert the primary control over
partitioning of productivity. Many researchers have looked in detail at the
manner in which this distribution is governed by external influences such as
light, water, temperature, and nutrients (Wardlaw, 1968, 1969, 1976;
Davidson, 1969a; Lush and Evans, 1974; Barta, 1976; Evans and Wardlaw, 1976).
Fewer have actually examined directly the process as it occurs in natural
ecosystems (Dahlman and Kucera, 1968; Warembourg and Paul, 1973; Caldwell
and Camp, 1974; Singh and Coleman, 1974), and it is indeed difficult to find
adequate discussion which relates work of the prior group of researchers to
the work of the latter. Little attempt has been made to integrate above- and
belowground productivity in terms of both the proximal and ultimate forces
operating to cause observed distributions found in the field. Plant
physiologists tend to search for mechanisms at a high level of resolution
while ecologists prefer to incorporate highlights of such mechanisms into the
lower resolution problem of adaptive significance.
Roots and shoots are each involved in the exploitation of resources, but
from different pools. The apportionment of assimilate and hence biomass
between roots and shoots is perhaps indicative of an optimal allocation
pattern by the plant to insure that above- and belowground resources are
supplied in the proper proportions. This aspect of the integration of root
and shoot functioning is indeed intriguing. Aboveground growth patterns have
often been viewed as adaptations for maximal photosynthetic production,
minimal water losses, and so forth, but are in fact constrained by the
necessity that a certain proportion of photosynthate is partitioned to roots
for collection of minerals and water, and structural support. If the plant
has belowground perennating organs, the success of subsequent year's growth
is also in the balance. In fact, non-structural carbohydrates stored by
perennial grasses seem to play^an important role in determining regrowth
success (Weinmann, 1961; Coyne and Cook, 1970; Trlica and Cook, 1972; Bokhari,
1977).
Inorganic nutrients are also distributed and redistributed in specific
patterns by plants. Over two decades ago Williams (1955) provided an exten-
sive review on these processes. The essential feature of this work was the
integration of mineral uptake and redistribution with the processes of growth
and senescence to explain observations of net losses of mineral elements
from specific plant parts. Thus he developed the "concept of the integrated
control of the movement of nitrogen and phosphorus in the plant." In this
theory nutrient uptake is determined by the external supply and the internal
demand created by growth, where the external supply is more likely to be
controlled by growth demands than vice versa. As each organ develops, there
is at first a period of net import and accumulation of the nutrient. This is
followed by a period in which import and export are balanced, and finally,
during senescence export prevails. Senescing organs may than act as a
nutrient source for younger organs. Uptake by roots is consequently cur-
tailed to the extent that the nutrient is already present and reutilizable
within the plant. More recently Clark's (1977) observations of internal
recycling of nitrogen in shortgrass prairie have given support to Williams'
ideas and re-emphasized their possible ecological significance. Short
grasses were observed to remobilize considerable quantities of nitrogen from
senescing tissues and transport it to belowground 'organs from whence it could
442
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be reutilized the following season. The adaptive significance of this
behavior is that the plants conserve nutrients rather than release them to a
common pool for which there is competition from other plants, microbes and
leaching losses. It also decreases the dependence of the plant on microbial
mineralization from dead material.
With the advent of the industrial age, emissions of S02 by man-made
sources have come to equal or exceed natural contributions such as fire and
volcanism. Almquist (1974) estimated 80 million metric tons of S02 to arise
annually from fossil fuel combustion and Kellogg et al. (1972) estimated 50
million metric tons annually. The current trend for increasing the relative
contribution of fossil fuels to the national energy budget can be expected
only to accentuate this situation. Ecosystems provide a considerable service
to us in their capacity to remove this S02 from the atmosphere. It has been
established that plants can derive a significant portion of their sulfur
supply from the atmosphere (Alway et al. , 1937; Thomas et al., 1943; Olsen,
1957; Ulrich &t al., 1967; Cowling et al., 1973). In the absence of a
sulfur supply to roots, plants seem capable of deriving their entire supply
from this source (Faller, 1971). There is also substantial evidence for a
non-metabolically active process by which live and dead leaf surfaces and
soil may remove S02 from the atmosphere (Seim, 1970; Fowler and Unsworth,
1974; Garland et al. , 1974; Owers and Powell, 1974; Whelpdale and Shaw, 1974).
From such observations, the question first arises as to what the relative
contribution of soil, leaf surfaces, and active processes are in this
removal. A more interesting question, though, is the relationship of sulfur
source to the internal distribution by the plants. Sulfur uptake and redis-
tribution under natural circumstances may or may not have evolved under the
S02 concentrations found today, depending on the extent of volcanism when the
uptake mechanisms were evolving. Not only are normal uptake mechanisms
specifically adapted to environmental substrate concentrations (Crowley, 1975)
but, in addition, atmospheric substrate concentrations themselves may be
under an adaptive homeostatic control by and for the biosphere (Lovelock and
Margulis, 1974). This study will investigate whether or not low levels of
atmospheric sulfur dioxide interfere with the adaptive mechanisms of sulfur
uptake from the soil and internal redistribution by the plant.
Another aspect of S02 effect concerns the direct influence of this gas
on photosynthesis. This subject has been treated extensively elsewhere and
is not of primary concern to this study. My concern is the possible indirect
effect it may have on the distribution of assimilate. This would arise if
S02 were to affect photosynthesis but not the process of shoot growth, for
the distributional fate of assimilated carbon in the plant rests on a system
of priorities among organs. This is the conclusion one can draw from
findings that leaves which are in active growth retain all their assimilates
and import from older leaves, while older leaves export but do not import,
and exports first go upward to younger leaves but only after this demand is
met do they subsequently move downward to roots (Williams, W™)- Lt 1S
thus conceivable, in the short term, that no changes would be observed in
aboveground growth even though root growth is altered. For example smaller
reductions in leaf weight than root weight for radish under 5 PP^ S°| tove
been reported (Tingey et al. , 1971), and ozone has been shown to reduce root
growth indirectly through effects on shoot metabolism (Tingey, w/<*).
443
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Consequently, a primary objective here will be to employ a sensitive technique
for in-field evaluation of photosynthate partitioning as possibly affected
by low concentrations of atmospheric SC>2.
Methods
An -in situ approach was taken to determine biomass, carbon fixation
and redistribution, passive sulfur deposition on leaf and litter surfaces,
active sulfur uptake, and sulfur redistribution (Figure 13.31). To evaluate
temporal changes in allocation patterns, data were to be gathered throughout
the growing season.
A common approach is to simply collect state-variable measurements with
time (harvest method). By this method carbon allocation is deduced from
ash-free biomass dynamics and sulfur allocation from total sulfur analysis.
However, the precision of this method is limited by large sample variability
often encountered in the field, actual flows cannot be measured directly, and
measurements of live root biomass are complicated by the presence of dead
roots. Another approach giving more precise estimates of flows entails the
use of radio tracers. This approach, however, has limitations in accuracy
when applied in a field situation, because of the practical constraints
associated with small sample sizes. Large areas cannot be labeled, and the
small areas which are labeled require far more extensive analysis than
similar-sized samples in the harvest method.
Experimental Design and S02 Treatments
Experimental design consisted of two main effects, date and S02 treat-
ment. Three dates in 1976 were chosen to represent early (19 May), mid
(26 July), and late (5 September) growing season. The S02 treatment consisted
of a continuous S02 fumigation throughout the growing season at 30-day median
concentration of 10 pphm, while the control was not fumigated. The S02 fumi-
gation was initiated in June of 1975, discontinued over the winter of 1975-
1976, and reinitiated at the start of the 1976 growing season (April).
A detailed description of the S02 delivery and monitoring system can be
found in Lee et al. (1976). Sulfur dioxide was distributed through a network
of aluminum pipes positioned approximately 0.75 m above the ground. Concen-
tration was continuously monitored by a Melloy laboratories sulfur analyzer
for a 7.5-minute period every hour. Median concentration was determined
daily from the total number of 7.5-minute samples. Both the fumigated and
control treatments covered approximately .52 ha ground surface.
On each date, three plots were selected per treatment for labeling,
giving a total of 18 plots. Four root cores were taken on each plot and
divided into segments of 0-5, 5-10, and 10-20 cm. This yielded a total of
72 cores and 216 segments. Sulfur labeling was performed on the two later
dates only.
444
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PROCESS FLOWS
LITTER
AND SOIL
RHIZOMES
AND CROWN3
0-5 ROOTS
5
-10 ROOTS
10-20 ROOTS
Figure 13.31.
Flows measured in process study.
(a) photosynthetic carbon fixation
(b) assimilation through stomates and deposition onto live leaf
surfaces
(c) deposition onto dead leaf surfaces
(d) translocation of C and S belowground
depths
In statistical analyses, aboveground results were treated separately
from belowground results. Aboveground observations were subjected to a
two-way factorial analysis of variance with repeated 'ons e 1OW
ground observations were subjected to a ^^
variance with sub samp ling. This method allowed tor
as well as treatments and dates and accounted
within core segments of the same plot Above- and
date main effects were tested a§a^f/?Jfw^f Rested against a depth x
Depth effects (and interactions with depth) were testea g ,
plot (treatment x date) error term. Means were compared using Tukey
and
Labeling and Harvesting
g
445
-------
This method also was used successfully by Singh and Coleman (1973, 1974),
Caldwell and Camp (1974) and refined somewhat by Warembourg and Paul (1973).
Details of the method used here correspond most closely with procedures
outlined by Singh and Coleman (1974). A flow chart (Figure 13.32) is
presented to demonstrate the sequence of procedures.
Plots of 0.5 m2 area were selected for visual homogeneity of cover,
dominance by A. smithi-i, and presence of green biomass. Late in the season,
more of the treatment cover had died, leaving only scattered patches of green
material in favorable microsites. These patches were chosen for study on the
grounds that location of a study plot on the mostly dead interspaces would
not yield adequate information on the behavior of live material that was
present.
Labeled 14C02 was released from a Na2lt+C03 solution inside the
polyethylene tent by injection of excess 3N H^PO^. into the solution with a
long-needled hypodermic syringe. A total of 450 yCi lifC was released per
plot. To compensate for photosynthetic C02 depletion, additional measured
quantities of Na2C03 were injected into the acidified solution. These
quantities were pre-estimated to match expected net photosynthetic rates.
Labeled 35S02 were released simultaneously with lt+C02 on the later two
sampling dates. Sodium sulfite (Na235S03) with 231 pCi • g""1 (July) and
331 yCi • g"1 (September) activity was measured into single plot quantities
and resealed in small wide-mouthed vials. In the field, the vials were
unsealed and positioned in the tents alongside the Na2llfC03 solutions.
Dropwise addition of 50% H2SOtf with the hypodermic needle released 35S02 from
the salt. A total of 723 (July) and 766 yCi 35S (September) was released per
plot. The high specific activity of the Na235S03 allowed sufficient 35S to
be released without introduction of significant quantities of S02. The con-
centration of S02 originating from the Na235S03 was calculated to be only
5.3 (July) and 3.9) ng S02 • cm"3 (September).
The radiotracers were released in late morning, and the tents removed
5-6 hours later. No attempt was made to control temperature or humidity in
the tents. By the end of the period, temperatures were several degrees
higher than ambient and considerable water had condensed on the tent walls.
The plots were allowed to equilibrate 5-6 days before harvesting, when all
aboveground herbage was clipped from the plot.
Live material was separated by species and dead material by the cate-
gories A. smithii or "other." Live species represented by less than 1 g •
m~2 were generally pooled as "other live." Coarse litter material was then
removed by hand and fine litter by a portable vacuum cleaner. Four root
cores were taken per plot with a 7.5-cm diameter coring tube to a depth of
20 cm. The cores were segmented by depth strata in the field. These root
core segments were hand washed with fine jets of water over a 60-mesh screen.
Material from the 0-5 cm layer was separated into roots, crowns, and rhizomes
except for May in which crowns were not separated. All samples were oven-
dried, weighed, ground to pass a 20-mesh screen, and mixed. Litter samples
were divided into coarse and fine fractions with a 28-mesh sieve.
446
-------
PROCEDURE
LABEL
GROUND SAMPLE
EQUILIBRATE
HARVEST
ROOT WASH,
DRY, GRIND, WEIGH
ASH
WET COMBUSTION
SO,
TOTAL S
35£
DRY COMBUSTION
C02',S°2
SCRUB
I
"c
Figure 13.32. Flow chart of experimental procedures.
lkC Analysis
The method employed to determine 14C was modified from Jeff ay and
Alvarez (196la). These workers used a wet combustion technique but indicated
dry combustion could be substituted. The major feature of the technique was
the use of HC1 solution as a gas wash to remove decomposition products other
than C02. The method was tested (Jeffay and Alvarez, 1961b) with dually
labeled (14C-35S) samples and 35S did not interfere with the lkC
determinat ion.
A 30-mg subsample was weighed into a black ashless sample wrapper
suspended in a wire mesh basket within an oxygen-filled 500 ml Erlenmeyer
flask. Combustion was initiated with a focused beam of infra-red light. The
resulting gases were then passed in an N2 carrier stream through two IN HC1
solutions to remove S02. Carbon dioxide was subsequently absorbed by 6 ml of
2:1 by volume 2-methoxyethanol and ethanolamine. Gas washing tubes were
employed in the wash and absorbtion to increase contact area between gas and
solution. Three milliliters of the absorbing solution was transferred to a
scintillation vial with a disposable pipet. A scintillation cocktail con-
sisting of 4.66 g - I'1 butyl-PBD [2-(4* tent-butylphenyl)-5-(4 -biphenyl)-
1,3,4-oxadiazole] in a 2:1 by volume toluene and 2-methoxyethanol was then
added, and the mixture counted. Quench curves were run for L rrom
commercially prepared standards.
447
-------
Total Sulfur and 35S Analyses
Total sulfur and 35S were determined on the same subsample. Total
sulfur analysis was by a method modified from Stewart and Whitfield (1965).
A 200-400 mg sample was weighed into a 25 x 200 mm test tube to which 3 ml of
50% Mg(N03)2 was added. The tubes were then heated on a hot plate for 2.5
hours. Following this initial digestion, they were placed in a sand bath and
ashed in a muffle furnace for 3 hours at 550°C. Ten milliliters 2N HC1 was
then added with slight heat and shaking. After overnight settling,
2-milliliter aliquots were taken from the supernatant and diluted to 10 ml
with dionized water for turbidimetry. Barium sulfate was precipitated by
addition of 0.5 g 28-48 mesh BaCl2 crystals. The suspension was left
standing for 60 seconds, shaken for 60 seconds, and after a total of 5 min-
utes, optical density was read at 495 nm. Time of standing and size of
BaCl2 crystals must be standardized for repeatable results (Butters and
Chenery, 1959). Other workers have used dipropylene glycol rather than water
during precipitation to increase the stability of the BaSO^ suspension (Krober
and Howell, 1958). Orthophosphoric acid may also be added to decolorize iron
in soil or root samples (Butters and Chenery, 1959).
The BaSO^ suspension was combined with the remainder of the original
supernatant in a scintillation vial, and an additional 0.5 g BaCl2 crystals
were added. The combined BaSOt,. suspension was then centrifuged at 1800 rpm
for 15 minutes. A water aspirator equipped with a hypodermic needle was used
to draw off the supernatant. The precipitate was counted after suspension in
600 mg Cab-0-Sil gel with 15.0 ml of Brays' dioxane-based cocktail (Bray,
1960).
Secondary 35S standards were prepared for determination of quench
curves. A lkC primary standard and the unknown 35S solution were counted
with a GM device under various absorber thicknesses. By knowing the 1I+C true
activity, one could then regress count rate against absorber thickness,
extrapolate to zero thickness, and thus determine the efficiency of the GM
device. Because 35S and lifC have very similar energy spectra, this effi-
ciency can be used to calculate the true 35S activity at the extrapolated
zero absorber thickness for the 35S solution. A quenching agent (CCl^) was
then added to the standardized solutions in varying amounts.
A test sample containing only lifC label was subjected to this procedure
to determine whether 1L|"C interfered with the 35S counts. A small amount of
14C contamination was present even after the Mg(N03)2 oxidation. To account
for this contamination, samples were recounted after a period of radioactive
decay. Because 11+C has a half life (5730 yr) which is very large relative to
that of 35S (88 days), any radioactive decay after the interval between
counts could be ascribed to 35S. The basic decay equation can be manipulated
to give the desired result: letting Nj equal count rate on first date, N2
equal count rate second date, and ti equal time interval between count dates,
the manipulation is:
448
-------
- N2/Nl) =
- N2) = Nl(i - e"Ati)
Letting the measured decay over i- • h^ A - M \r j i
which represents the true^S 1 """ "*
Nl* =
(1 - e "bi)
Activity at time of manufacturer standardization can be calculated as:
(4)
N = N!*/e~Xto (5)
where t0 = time interval between standardization and first count date. Time
o c
interval between counts was between 0.5 and 1.0 half life of ^S.
General
Both isotopes could be counted under the same window settings because of
their energy similar spectra. The external standard-channels ratio technique
was used to determine counter efficiency. Counting time was 1-20 minutes
depending on sample activity.
Raw data for biomass, ash, and count rates was processed by computer to
yield ash-free biomass, flux rates • g : and flux rate • m~2 ground surface.
Because S02 uptake and deposition is proportional to atmospheric S02 concen-
tration (Hill, 1971), flux rates for sulfur were normalized with respect to
concentration. This facilitated comparisons between the two dates in which
different 35S02 concentrations were used. The resulting quantities are
referred to as deposition velocities (Vg), where Vg = F/C. If concentration
(C) is given in yg S • cm"3 and flux rate (F) is given in yg S • g"1 biomass
• h"1, Vg takes the units of cm3 • g"1 biomass • h"1. When F is given in yg
S • m~2 ground • h"1, Vg takes the units of cm3 • m~2 ground • h"1 which is
then converted to cm • sec"1.
Aboveground results viewed in terms of flux per gram of biomass can
readily be converted to a flux per unit leaf area as
zi = JL!_ . DWT
LA DWT * LA
449
-------
where F' is absolute flux (yg S02), LA is leaf area (cm2), and DWT is dry
weight. Flux per unit ground area also reflects the magnitude of aboveground
biomass as
GA DWT GA
where GA is ground area (m"~2) .
Count rates of 35S were scaled so that the mean plot total deposition
velocity for control treatments in July and September agreed with Owers and
Powell's (1974) mean Vg for grassland of 0.7 cm • sec"1. Thus, all count
rates were multiplied by the same scaling factor. Reasons for scaling
include: (a) actual 35S02 concentrations were not monitored in the tents,
(b) large amounts of 35S02 were probably absorbed on tent walls, (c) not all
of the 35S02 was released from the salt, and (d) the primary intent of this
study was to make relative comparisons between units of the study rather than
to measure deposition rates absolutely. The value of Vg =* 0.7 seems appropri-
ate because (a) it was determined for a grassland, (b) it was measured on a
ground rather than leaf area basis, (c) measurements were under similar cli-
matic conditions as would be found here, (d) sulfur deposited on stem bases
and ground surface was accounted for, (e) reference concentration height was
20 cm, similar to tent height, and (f) the tracer method used for its
estimation is a more direct approach than inference from concentration
profiles.
As for 35S, 12+C count rates were scaled. This was found to be necessary
because abiotic conditions in the tents were not representative of real
ambient conditions and ll4C02 concentrations in the tent were not monitored.
The scale was chosen so that aboveground relative growth rates in May for
Agropyron smi-fhi-l agreed with field observations for the period mid-May to
mid-June of 1.07 mg C • g"1 biomass C • h"1 (Heitschmidt, 1977). As a result
of scaling, comparisons of absolute values must be confined within this
study.
Results
lt+C02 Assimilation and Translocation
Aboveground growth rates were significantly higher in May than other
dates for Agropyron smithii (Table 13.16). The other species collectively
maintained high relative growth rates throughout the season; however, their
contribution to total aboveground biomass declined, leaving absolute growth
increments dependent mostly on A. smlthi'l. For total live material, the
growth rate was significantly different between all dates with a progressive
drop-off throughout the season. This decline was greater from May to July
than from July to September. No significant treatment effects or interactions
were noted for aboveground growth.
450
-------
TABLE 13.16. RELATIVE AND ABSOLUTE GROWTH RATES ('^C COUNTS ARE SCALED)
Ln
plant pacts rag C
Affhillea mi I li folium
Agropyron smithii
Antetmaria rosea
Aristida longiseta
Artemisia, frigida
Beuteloua gracil-is
Bromus japonicus
K&eleria aristata
Pc?a prat&nsis
Poa secwnda
Stipa comata
Stipa viridula
Taraxicum officinale
Tragopogon dubius
Other
Total
Rhizomes
0-5 cm roots & crowns
5-10 cm roots
10-20 cm roots
May
• g ^ • hr ^ mg C • m 2 • hr s
0.151
0.452
0.133
0.264
0.974
0.354
0.198
0.348
0.441
0.031
0.034
0.019
0.024
0.015
20.93
0.120
7.55
12.07
2.26
0.341
2.33
45.61
1.54
26.8
2.73
2.81
mg C • g~> • hr~' mg C • m"2 • hr"1
0.259
0.402
0.276
0.233
0.207
0.318
0.262
0.347
0.209
0.340
0.014
0.029
0.026
0.033
1.37
20.54
0.390
1.91
1.01
0.381
0.389
1.59
1.50
29.08
0.645
18.36
3.39
4.37
July
tng C • g"1 • hr"1 mg C • m"2 • hr~l
0.316
0.154
0.230
0.180
0.967
0.348
0.106
0.028
0.019
0.029
0.030
0.033
2.78
25.76
8.46
1.28
0.677
1.57
23.82
2.20
2.23
19.25
3.36
4.26
mg C • g ' • hr ' mg C • n 2 • tit '
0.214
0.126
0.769
0.230
0.448
0.545
0.258
0.467
0.500
0.278
0.051
0.029
0.042
0.077
0.074
24.29
1.52
1.08
0.85
2.73
13.10
0.722
1.11
, 1.80
47.20
3.40
3.56
25.98
7.05
7.08
Septet
mg C • g"' • hr"1 mg C • m"2 • hr"1
2.666
0.115
0.058
0.187
0.140
0.027
0. 175
0.247
0.009
0.009
0.004
0.003
0.012
0.009
23.72
11.89
1.19
0.32
0.868
0.313
1.49
39.79
0.774
1.03
',.41
3.39
3.93
2.17
nber
Eg C • g ' • hr ! mg C • m 2 • hr '
0.057
0.199
0.225
0.198
0.008
0.009
0.004
0.003
0.033
0.004
0.085
26.52
2.27
28.87 -
0.594
1.07
2,49
1.42
0.345
0.453
-------
Taken over all depths and treatments, the highest relative root growth
rates were in July (Figure 13.33). Roots in the 0-5 cm layer grew at a
faster rate in May and July than in September, while below 5 cm, roots grew
fastest in July. A significant treatment x date interaction (P = 0.032) was
found because the treatment effect was noted only in July. At this time,
aboveground biomass was lower on fumigated plots (Table 13.17) yet root
growth rates were higher. There was neither a significant depth x treatment
interaction (P =,0.06) nor a significant three-way interaction of depth x
date x treatment (P = 0.093). The significant treatment x date interaction
seemed attributable to July, when 5-10 and 10-20 cm roots were growing at a
faster rate in the S02 treatment.
The percentage of total 14C found below ground (Figure 13.34) declined
from 45.27% in May and 51.46% in July to 17.04% in September. Strictly,
total translocation below ground would also have to include root respiration,
exudation, and sloughing. For example, Warembourg and Paul (1973), working
on a similar floristic composition grassland, found roots respired 9% to 15%
of the total plant assimilate, or 20% to 29% of the total translocate. Singh
and Coleman (1977) found shortgrass prairie roots to respire 9% to 19% of
total plant assimilate. Therefore, the partitioning of carbon observed here
represents the relative increments in biomass (here referred to rather
loosely as "growth") between roots and shoots or between depths rather than
the allocation of total assimilate. Also, if these figures were adjusted on
the assumption that 30% of the roots were actually found below 20 cm, the
proportion of total growth occurring belowground would be 51% in May, 57% in
July, and 22% in September.
A greater percentage of total belowground growth was found in deeper
depths later in the season (Figure 13.34). A greater percentage was also
found in rhizomes as the season progressed, and between July and September
crowns also received an increased percentage. These results agree with those
of Singh and Coleman (1973) who found maximum growth in the 0-10 cm depth
from late May to July and maximum 10-20 cm growth from late July to September,
The results, however, conflict with their finding that relative allocation to
crowns decreased with time. The findings here correspond to those of
Warembourg and Paul (1973), who found decreased percentages in 0-10 cm roots
in late season and in 10-25 cm roots in mid-season.
35S02 Fluxes and Distributions
Certain species were notably more active in SO2 uptake than others
(Table 13.18). Aohillea miltefoHum and Taraxieum offiovnale ranked highest
in dry weight basis S02 assimilation rates. Antennae-la vosea, Ar-ist'idx
IsOngiseta, and A^temis'ia frigida were among the lowest. There was a date
effect for Agvopyron smithii (P = 0.046) with less uptake in July as well as
a treatment effect (P = 0.02) with less uptake on the control. For total
live material, no significant treatment effect was observed (P = 0.08), but
the trend was for less uptake on the control. Tragopogon dubius and
Taraxiim off-lo-inale seemed especially affected by treatment, and while
statistical analyses were not performed for these species, uptake appeared
lower in the control. On the other hand, 'Koelevla ovistata exhibited higher
452
-------
ROOTS^
0-5 cm1.-
and f
CROWNS
90r
ROOTS
5-10 cm
p- 60
o
030
O)
<
/ \
s \
' \
^ \
- '^-^~~^^^
^""^v.
1 1 >
o:
ROOTS
I0-20cm
9O
60
30
O
May July Sept
4
3
2
IJ
0>
0>
E
— *
/)
•*
3
2
1;
/
. /
- x/--
*r ^*
*
~—± 1 J
4
3
2
o 0.6
o>
0.4
10
E
o
|0.3
I-
o O.I
O
<
0.3
O.I
May July Sept
July Sep
Figure 13.33.
Belowground 14C net translocation per hour, total sulfur, and
35S net translocation. Solid lines refer to control. Dashed
lines refer to continously fumigated 10 pphm treatments.
uptake on the control. Dry deposition onto dead material was not affected by
date or treatment. The difference between deposition rates on AgTOpyron
smifhii, live and dead materials was more pronounced on fumigated treatments.
Deposition onto litter material was not affected by date or treatment.
A significant depth (P = 0.0001) and depth by date interaction (P =
0.0019) was found for translocation of 35S to roots (Figure 13.33). Signifi-
cantly more sulfur was translocated on a dry weight basis to 0-5 cm roots in
September than in July, but significantly less was translocated to 5-10 and
10-20 cm roots in September than in July. Depths behaved similarly in July,
but in September 5-10 and 10-20 cm roots received less than crowns or 0-5 cm
roots. The increase in translocation to the 0-5 cm layer from July to
September indicates that this layer became a more efficient sulfur sink as
the season progressed. The opposite was true at 5-20 cm.
Although treatments behaved differently with respect to sulfur distribu-
tion on a ground area basis (Figure 13.35), they are lumped as one since
treatment differences in biomass, which affect these distributions (see
453
-------
TABLE 13.17. STANDING CROP OF PLANT MATERIALS ON LABELLED TEST PLOTS., 1976
Species
May
July
September
Control 10 pphm Control 10 pphm Control 10 pphm
Live
Agropyron smithii 46.3 51.1 167.3*
Koeleria cristata 28.6* 8.2* 36.8*
Stipa viridula 0.0 1.2 0.0
Stipa comata 6.4 0.0 7.1
Poa pratensis 0.0 0.0 0.0
Poa secunda 12.4 4.9 0.0
Tragopogon dubius 1.7 4.6 4.5
Aehillea millefolium 0.1 5.3 8.8
Artemisia frigida 0.0 0.0 0.0
Antennaria rosea 0.0 0.0 0.0
Bromus japonicus 0.9 1.4 0.0
Taraxiewn officinale 0.0 1.5 0.7
Aristida longiseta 0.0 0.0 0.0
Bouteloua gracilis 0.0 0.0 0.0
Other 6.7 7.2 0.0
Total 103.3 85.4 225.2
Dead
Agropyron smithii 75.5 77.3 88.9
Other 44.9 25.7 83.3
Total 120.4 103.0 172.2
Litter
Coarse 108.8* 171.9* 99.5*
Fine 17.9 19.7 71.2
Total 126.7* 191.5* 170.7*
Belowground
Rhizomes 43.88 43.26 72.89
Crowns — — 106.45
0-5 cm roots + crowns 810.81* 657.01* 670.20
0-5 cm roots — — 563.74
5-10 cm roots 140.03 130.17 108.40
10-20 cm roots 117.58 127.70 120.39
113.5*
6.1*
0.0
2.8
0.0
24.0
3.6
0.0
3.7
12.1
0.0
2.4
1.4
0.0
0.0
169.6
65.5
83.3
148.8
211.8*
115.0
327.8*
66.53
102.61
646.27
543.65
95.60
102.11
103.4
6.2*
0.0
0.0
11.6
0.0
0.0
8.9
0.0
20.7
0.0
0.0
0.0
1.7
8.5
161.2
63.7
25.3
89.0
164.3*
74.4
238.7*
95.67
128.30
1118.22*
989.91*
230.79*
212.98*
133.3
0.0*
0.0
0.0
0.0
0.0
0.8
1.5
0.0
0.0
0.0
0.0
0.0
0.0
10.1
145.8
74.8
17.5
92.3
215.4*
85.3
300.7*
69.92
98.32
576.95*
478.62*
103.75*
103.97*
Indicates treatment difference (g
m
Equation 7), were present. On all dates the greatest quantities were in or
on aboveground herbage with 39% in July and 54% in September. Litter material
received the next greatest proportion with 33% in July and 29% in September.
Dead aboveground material received 24% in July and 11% in September, while
belowground materials received only 4% in July and 7% in September. The
percentage of sulfur-35 in all harvested live material (above and belowground)
that was translocated belowground ranged from 8.0% on fumigated plots to
14.8% on control plots in September. Seasonal trends were reversed with a
seasonal decrease from 9% to 1.8% on the control and an increase from 2.9% to
14.8% on the fumigated plots. These figures compare with 5.2% found in aspen
to 24.3% in sugar maple seedlings after 8 days (Jensen and Kozlowski, 1975)
and a range of 1.4% to 2.6% for tobacco (Faller, 1971).
454
-------
I4C - Belowground
July
September
3.45%
Crown
!8.35°/c
0-5cm Roots
+ Crown
73.85 %
7.75 ,o
Rhizome
Roots
33.30 %
10-20 cm
Roots
12.32%
-10 cm
Roots
10.40%
10-20 cm
Roots
10-20 cm
Roots
5-IOcm
Roots
%of total found
belowground
Assume 70 %
of the roots
-45.27 %
51.34 %
51.46 %
57.05 %
17:04%
22.36%
Figure 13.34. Distribution of 14C belowground assimilate on ground area
basis.
Distribution among rooting depths and organs was unaffected by treatment
(Figure 13.36). A highly significant depth x date interaction (P - 0) indi-
cated both the overwhelming importance of 0-5 cm roots and the apparent
increase in 0-5 cm sink strength as the season progressed, with 66% in July
and 80% in September found there. Translocation to crowns seemed unaffected
by date, with an average of 11.3% being translocated there, or to rhizomes
with 4.7% sent there on both dates. Roots below 5 cm received a smaller
proportion with time with 17.9% in July and 4.8% in September.
Total Sulfur
Total sulfur (Table 13.19) was significantly higher on the fumigated
treatment for Agropyron smithii (P = 0.003) and for the rest of the live
material taken as a group (P = 0.0001). Sulfur content of coarse litter
increased with time on the control treatment but decreased with time on
fumigated plots. Sulfur content of fine litter increased between May and
July on both treatments and declined little in September. Levels were signif-
icantly higher under fumigation for coarse litter only in May, while in fine
litter, the treatment effects were apparent at all dates (P = 0.024).
Belowground results (Figure 13.33) were somewhat unexpected. Taken over
all dates and treatments, there were significantly greater sulfur contents in
roots on the control treatment (P = 0.05). The only exceptions to this were
in July below 5 cm, but these were not of sufficient magnitude to cause
significant two or three-way interactions. A significant depth effect (P -
0.036) was found with rhizomes and 10-20 cm roots having lower values than 0-
5 cm roots plus crowns or 5-10 cm roots. On the control plots, the data
455
-------
TABLE 13.18. RELATIVE S02 DEPOSITION VELOCITIES
Species
July
Control
10 pphm
DWT
GA
DWT
GA
September
Control
DWT
GA
10 pphm
DWT
GA
31.19 0.115
0.224
0.004
0.0004
0.001
16.45 0.01
13.45 0.289
23.17 0.274
Live
Aohillea millifoliwn 20.32 0.027
Agropyron smith-Li 7.72 0.129 19.74
Antennaria rosea 3.58
Aristida longiseta 2.86
Artemisia frigida 3.72
Boutetoua gracilis
Koeleria cristate.
Poa pratensis
Poa seounda 41.78
Stipa eomata 11.73 0.008 11.87 0.003
Taraxiaum offioianale 50.22 0.003 77.98 0.018
Tragopogon dubius 16.88 0.007 38.63 0.014
Other
Total
Dead
Agropyron smifhii 7.15 0.063 9.44 0.061
Other 10.73 0.089 17.59 0.146
Total 8.87 0.152 14.16 0.207
Litter
Coarse 0.082 0.223
Fine 0.074 0.144
Total 0.156 0.367
Rhizome 0.0013 0.0015
Crown 0.0035 0.0036
Total belowground
plant material
(+ roots) 0.029 0.031
Above and belowground
total 0.626 0.879
30.61
18.31
6.15
19.03
11.73
30.05
20.17
17.60
8.44
9.30
8.73
0.027
0.189
0.013
0.003
0.007
0.035
0.100
0.017
0.391
0.54
0.023
0.077
0.100
0.122
0.222
0.0019
0.0073
0.068
0.75S
32.47
22.74
0.005
0.303
35.48
23.61
6.43
13.45
8.16
0.036
0.344
0.048
0.023
0.071
0.071
0.100
0.171
0.0019
0.0032
0.030
0.616
*, q
JDS counts are scaled so mean of July and September control plots total V = 0.7 cm
sec
sec"
DWT = dry weight basis (cm3 • C DWT"1 • h"1), GA = ground area basis (cm
suggested a draw-down in sulfur concentration below 5 cm between May and
July but not at 0-5 cm. Between July and September, all layers on control
plots showed an accumulation of sulfur. On the fumigated treatments, 5-10
and 10-20 cm depths accumulated sulfur from May to July, and there was
decrease from July to September, a marked contrast to control plots. Total
sulfur in the 0-5 cm layer appeared consistently greater on control plots at
all dates and increased with time on both treatments.
456
-------
35
SO,
Live 38.7
September
Live 53.7 °/<
Belowground
70%
Coarse /Fine \ Dead
Litter /Litter
I2.4%/ 16.10/
% total
assimilated
sulfur found
belowground
Opphm lOpphm
Q nc.0
9-O5/°
Opphm lOpphm
14.85% 8.07%
Figure 13.35- Distribution of dbS02-sulfur for entire labeled plots.
Discussion
14C02 Assimilation and Distribution
Soil water has often been thought to be a primary determinant of relative
root to shoot growth, but such reports are often conflicting. Some findings
indicate that drought stress favors root growth relative to shoot growth
(Davidson, 1969b, Evans and Wardlaw, 1976). Although translocation to roots
is not, in the strictest sense, identical to root growth (because not all the
translocate may be incorporated into live tissue), the quantities of assimi-
late translocated to roots is useful as a general indicator of relative root
and shoot growths. With this qualification, the finding of 10% more net ^
translocation belowground in July (when 0-30 cm soil water was less) than in
May is of interest (Singh and Coleman, 1973). On the other hand, Agropyron
cristatim translocated greater percentages belowground under wet conditions
(Sosebee and Wiebe, 1971) and root growth was suppressed under water stress in
Loliym temulentym (Wardlaw, 1969).
Total soil water in the top 105 cm of soil averaged over the entire
treatment areas was increasing from 14 cm in May and ae«e"£« *r™24 Cm "
July, with lowest levels in September (9 cm). All labelingda tea had
water contents below the maximum observed of 24 cm on 21 June (Section
457
-------
Roots
0-5 cm
65.7 %
.7%
Rhizome
September
1.5%
3.3°/c
Crown
10.9%
47%
Rhizome
Figure 13.36. Belowground distribution of 35S02~sulfur,
458
-------
TABLE 13.19. TOTAL SULFUR ANALYSES
VO
May
Control
Species
Live
Agropyron smithii
Koeler-La oristata
Stipa viridula
Stipa oomata
Poo. pratensis
Poa seaunda
Tragopogon dubius
Aohillea millifolium
Artemisia frigida
Antennaria rosea
Bromus japoniaus
Taraxiaum offieinale
Aristida longiseta
Bouteloua graailis
Other
Total
Dead
Agropyron smithii
Other
Total
Litter
Coarse
Fine
Total
Rhizomes
Crowns
mg S/g
0.7
3.9
2.1
3.9
4.8
4.4
4.5
4.2
0.7
0.8
0.7
1.8
2.1
mg S/m2
33.34
107.84
13.71
49.43
8.23
0.40
4.27
34.27
245.50
50.23
32.24
82.47
82.04
30.52
112.60
22.90
10
mg S/g
2.4
3.9
5.9
4.0
7.6
4.4
5.5
5.4
6.6
1.0
1.9
4.3
4.3
2.0
pphm
mg S/m'-
124.63
34.63
5.88
26.74
34.72
22.43
7.70
8.07
50.17
314.86
76.10
52.28
128.38
703.32
77.25
780.60
21.60
July
Control
mg S/g
0.7
3.2
3.1
7.0
5.9
8.5
0.7
0.2
1.1
3.9
1.2
1.3
mg S/ro2
117.10
121.64
23.16
27.43
52.37
6.36
348.02
62.20
173.60
255.80
109.08
263.40
327.50
21.80
138.30
10
mg S/g
3.4
5.1
4.4
8.2
9.4
2.6
5.5
12.2
4.4
1.2
5.2
2.8
7.0
1.9
1.4
pphm
mg S/m2
385.90
28.70
12.55
198.63
37.73
9.61
66.39
28.72
6.20
774.43
78.60
444.40
523.00
546.82
774.80
1321.60
31.50
143.60
September
Control
mg S/g
0.7
3.2
4.7
1.3
1.0
2.0
2.7
0.7
0.7
1.5
3.9
1.2
1.4
mg S/m2
72.40
111.21
43.10
11.25
21.34
3.55
14.50
277.35
44.60
17.74
62.30
241.03
286.60
527.60
28.70
179.60
10 pphm
mg S/g mg S/m2
3.9 519.90
4.1 3.94
5.6 51.97
575.80
2.0 149.60
1.7 29.39
180.00
1.4 291.71
6.3 525.80
817.50
1.0 17.50
1.1 108.10
Agropyron
..
i' analyzed by Leco Induction Furnace method.
-------
Figure 11.1). Thus, soil water was somewhat low on all dates but more so in
September. Location of plots on green patches in September probably biased
soil water such that labeled plots in September were wetter than the entire
treatment areas in which soil water was estimated. Thus, soil water on my
study plots was likely similar on all dates.
The translocation system is insensitive to water stress, but transloca-
tion can be altered by water stress indirectly through effects on growth
(Wardlaw, 1968). This hypothesis taken with observations that growing shoots
have higher priority over assimilate than roots (Williams, 1965) would lend
support to findings that growth belowground is more limited by water stress
than that aboveground. Since there were no significant differences in
absolute growth rates aboveground between dates (Table 13.16) and soil water
on the study plots (versus that on entire treatment areas) was similar on all
dates, soil water was probably not a proximal cause for these distributions.
Translocation also may be related to the phenology of the plant. Phleim
pvatense translocated less to roots during ear emergence than at stem growth
initiation (Balasko and Smith, 1973). Loliwn perenne under continuously
favorable soil water translocated about 50% to roots in the 4-leaf stage but
less than 10% in the 13-leaf stage (Ryle, 1970a). On the other hand, the
proportion of photoassimilate found in shortgrass prairie roots increased
with phenological stage (Singh and Coleman, 1977).
Temperature conditions also may play a role. High temperature pretreat-
ment reduced the percentage export of 1LfC from barley leaves (C3 species) but
increased export from sorghum leaves (C4 species) (Wardlaw, 1976). In the
1976 review, Evans and Wardlaw concluded that low temperatures tended to
favor root growth relative to shoot growth. Davidson (1969a) established
that under constant air temperature, an increase or decrease in soil tempera-
ture from 20°C favored higher root to shoot ratios in Lol-Lum pevenne and Poa
pratensis. Here, air temperatures in the tents during labeling were 25-30°C
in May, 28-30°C in July, and 29-32°C in September, so no real differences
between dates were likely. Soil temperatures most likely continued to
increase throughout the season.
Lowered light regimes seem to decrease translocation to roots (Ryle,
1970b, Lush and Evans, 1974, Ryle and Powell, 1976). Also, Mitchell (1954)
found assimilate in ryegrass to be partitioned to areas of growth nearest to
the source of the assimilate when plants were shaded. Incident light was
probably nearly equal in May and July but lower in September. I suggest that
the higher soil temperatures and the lower available light, in view of the
above findings, might support a lowered root growth relative to shoot growth
late in the season as observed. These findings also agree with direct obser-
vations of root growth by Ares (1976) in a shortgrass prairie where root
growth was maximum when leaf expansion was greatest and soil water highest.
The partitioning of total translocate among plant parts and root layers
(Figure 13.34) seem best explained in terms of soil water and the role of 0-
5 cm roots, crowns, and rhizomes as storage organs for early spring growth.
In early parts of the season, the optimal strategy would be to partition a
large quantity of translocate to new roots at shallow depths in order to
460
-------
establish a functional root biomass that, in the later parts of the season
(when the top of the profile is dry), can intercept rain immediately. In
terms of competition between plants, species which as individuals are able to
utilize mid- and late-season rain most efficiently would have a selective
advantage. Such plants would require an adequate concentration of roots
higher in the profile. This is, perhaps, the explanation for the tremendous
concentration of root biomass in the 0-5 cm layer (Table 13.17). Later in
the season during dry-down of the top soil layers, the advantage shifts to
deeper depths, where the conditions for root growth are still favorable.
Increased percentages going to storage organs, such as crowns and rhizomes,
in late season may be part of a strategy to maintain high reserves over
winter and thus gain a competitive advantage during growth initiation in the
spring.
Treatment Effects on Root Growth
Treatment effects on root growth below 5 cm in July may have been an
artifact of species composition differences in rooting patterns, a definite
possibility because of the greater abundance of Koelerid oristata on control
plots. To test for a correlation of root growth rate at the 5-10 and 10-20
cm depths with species composition, an analysis of covariance model was
constructed with two covariates: the ratio of biomass and the ratio of 14C
assimilation per square meter between Agropyron smithii and K. oristata. The
covariates together were related to a highly significant portion of the
variation at both the 5-10 cm depth (P = 0.003) and at the 10-20 cm depth (P
= 0.001). Even after this significant adjustment for species composition had
been made, somewhat significant treatment effects persisted at both depths (P
= 0.10, P = 0.06). Care must be taken in interpretation of these results,
for it is possible for the response to be correlated with species composition
yet that causality not be present.
The observed response could have been caused by the following: (a) K.
eristata has lower root growth at these depths (b) A. smithii has lower root
growth at these depths (c) Poa pratensis has greater root growth at these
depths. If (a) were true, it seems likely that a greater root biomass would
have been observed on the fumigated treatment at these depths in May and
July, which was not the case (Table 13.19). In addition, K. oristata is
known to have shallower rooting systems than A. smithii (Coupland and Johnson,
1965). If (b) were true, one would expect a similar response in September
where a similar difference in A. smifhii abundance between treatments was
found. If (c) were true, one would have seen the reverse pattern in May,
which was not the case.
Finding greater shoot biomass on the control plots with no treatment
differences in root biomass indicates greater root/shoot ratios on treated
plots and, therefore, a greater partitioning of photosynthate to roots of the
treated plots. This would enhance the validity of the apparent stimulation.
On the other hand, it may be indicative of an a priori difference between
treatment plots caused by some other factor(s).
461
-------
35S02 Flux into Leaves
The most limiting step in the process of S02 diffusion into live leaves
is stomatal resistance. Barley leaves with open stomates take up 6 times
more S02 than leaves with closed stomates (Spedding, 1969), and greater S02
uptake by plants has been observed in lighted than in dark conditions
(Garsed and Read, 1977). Capture of assimilated S02-sulfur depends also on
leaf age. Thus, middle-aged leaves in tobacco captured more than either
young expanding leaves or older leaves. However, this difference was not
attributed to differences in stomatal opening between leaves of different
ages (Craker and Starbuck, 1973). Guderian, (1970) found the same relation-
ship but did attribute it to differences in stomatal opening between leaves of
different ages.
Concentrations of S02 as low as 2.45 pphm may decrease stomatal resis-
tance in V-icia faba (Biscoe et al. , 1973) . Concentrations between 10 and
50 pphm also have been found to stimulate stomatal opening (Unsworth et at.,
1972). In moist air, stomates may be stimulated to open and in dry air to
close in response to S02 (Majernik and Mansfield, 1972). Thus, humid condi-
tions and S02 in the tent would have favored opening. I suggest that the
greater S02 uptake by A. smlfhiA, and total live material on the fumigated
treatment was caused by a stimulation of stomatal opening by S02. (S02
within the tents at labeling was almost entirely from captured ambient S02,
S02 released from the label resulted in only nanograms-cm~3 concentrations.)
Factors Which Influence Sulfur Distribution
The distribution of sulfur in the plant under normal circumstances is
governed by a combination of its mobility and the relative strength of sinks
among plant parts. Free sulfur is mobile in the phloem (Bukovac and Wittwer,
1957) and the xylem but is captured quickly in metabolic processes and
immobilized in areas with high growth rates (Biddulph e~t at. , 1958) . Others
have found that meristematic tissues of roots and leaves capture most foliar-
applied S02 sulfur (Garsed and Read, 1974). Thus, the fate of sulfur is
highly dependent on sink strengths created by growth demands. The distribu-
tion pattern is further influenced by the proximity of the source to the
sink. Even with highly mobile phosphorus, translocation to roots from foliar
application has been found to be related to the proximity of the fed leaves
to the roots, with older more proximal leaves exporting more (Koontz and
Biddulph, 1957). Another factor affecting the fate of S02 sulfur in perennial
plants is the vela't'ive sink strengths of roots to shoots whereby roots may
accumulate sulfur when sink strength in leaves is low because of senescence.
Distribution of Assimilated 35S02
On the control, a greater percentage of assimilated sulfur was sent to
roots in September (14.8%) than in July (9.0%), which seems explainable in
terms of aboveground growth demand, where the relative quantity of sulfur
translocated to roots is expected to be dependent on the degree to which it
is not needed by shoot growth. Relative shoot growth was significantly
462
-------
higher in July (Table 13.16) as was absolute growth (although not signifi-
cantly) . This indicates a more active shoot metabolism in July and thus an
increased capacity to capture sulfur in growth; roots therefore received
less.
The decline in translocation of S02 sulfur to 5-10 and 10-20 cm in
September coupled with a simultaneous decline in root growth (Figure 13.33)
supports the notion that lowered growth rates decrease sink strength. It
does not, however, prove the theory, because the total quantity of recovered
14C in the roots in July is not absolutely known to have been incorporated
into structural components (as opposed to labile storage pools). Increase in
translocation to the 0-5 cm layer along with the increased total sulfur at
that depth indicates this layer became a more efficient sink as the season
progressed. The cause for this sink strength appears not to lie in greater
growth demands. Sulfur contents of these roots also seem not to be the cause
as one would then have observed a treatment difference. Until captured by
growth, sulfur is mobile in the plant (Biddulph et at. , 1958). Mobile ions
are in a dynamic state with transport between tissues and between organs
occurring continuously (Bowling, 1976). Lateral transport of ions between
upward (xylem) and downward (phloem) transport pathways causes a circulation
of ions in the plant (Weatherly, 1969). Thus, under conditions of lower
growth demand at all rooting levels, the dynamic equilibrium between depths
might have been governed more by the distribution of root biomass. Thus, the
great concentration of roots in the 0-5 cm layer might help explain the
increase in translocation to that depth in September.
Total Sulfur Concentrations
The relationship between root relative growth rates (growth in the loose
sense) and total sulfur on the control treatment (Figure 13.33) indicates that
during periods of high growth, total sulfur was lowest. Part of the explana-
tion lies in a dilution of root sulfur by carbon growth, but the increasing
sink strength of shoots between May and July may help explain the apparent
draw-down in sulfur concentrations at 5-10 and 10-20 cm. On the fumigated
treatment, there was a trend for accumulation of sulfur at 5-20 cm between
May and July, possibly because shoots derived a major portion of their sulfur
supply from the atmosphere. For example, cotton may derive 30% and ash
seedlings 92% of their supply from S02 even with adequate sulfur levels in the
rooting media (Jensen and Kozlowski, 1975). The lowered short demands may
then have allowed 5-20 cm roots on the high treatments to accumulate sulfur.
Between July and September, all layers on control plots accumulated
or maintained their sulfur levels despite a reduction in root growth. This
was the period during which absolute aboveground growth rates declined (Table
13.16). As such, the sink strength for sulfur aboveground also declined,
leaving the roots free to accumulate according to or in excess of their
demands. The reverse trend was found below 5 cm on the fumigated plots over
this time period, possibly because a feedback mechanism may operate to
decrease root uptake when shoots have an adequate supply. Indeed, bU2
fumigated plants do take less sulfur from the soil (Thomas et al., 1943,
Faller 1971) .
463
-------
Summary and Conclusions
The observed partitioning of growth among shoots, storage, organs, and
different rooting depths supports the general hypothesis of a strong seasonal
control. Greater proportions of photosynthate were sent to roots early in the
season. Soil water showed more potential as the ultimate rather than the
proximal cause of this relationship. Increasing soil temperatures compared
to air temperatures, incident light, and possibly phenology might be more
important as proximal cues. Maximal growth above and belowground generally
occurred from early to mid season. Because approximately 48% of precipi-
tation is normally received in April, May, and June (National Oceanic and
Atmospheric Administration, 1976) these plants would profit most from a
growth pattern that most fully exploits this resource. The C-3 photosynthetic
pathway of the dominant species, which favors growth early in the season
before the onset of higher late season temperatures, might be such an
adaptation.
Distribution of root growth with depth seemed to be well correlated with
soil water distribution. Early in the season, plants exhibited intense root
activity nearest the surface, which would be advantageous for the immediate
interception of rain events later in the season. The greater relative
partitioning of growth to 5-20 cm late in the season seemed to be related to
the more favorable conditions for root growth there as the top layers become
more dry.
It appears that low concentrations of sulfur dioxide may have increased
partitioning of photosynthate to 5-20 cm roots in mid season. The mechanism
by which this effect would be brought about depends on a system of priorities
among organs for capture of assimilate. If S02 sulfur has a fertilizing
effect that stimulates photosynthesis more than shoot growth, root growth
could be favored over shoot growth. The lack of a significant effect in the
0-5 cm layer suggested that other factors (such as soil drought) may have
been restricting growth at this depth. Effects observed in this study
probably represent the extreme case, as plots examined here were located on
green patches at the time of the observed stimulation and, therefore, are
representative only to the extent that the total system was covered with
green biomass at that time. This stimulation is in contrast to findings for
radish (Tingey et al., 1971), possibly because of differing species suscepti-
bilities to negative S02 effects, the difference between ideal growth chamber
conditions and the stresses of the field, or because this system (or at least
these study plots) indeed may have been sulfur limited. Only very intensive
root biomass measurements made over an extended period of fumigation are
likely to reveal the real extent and mechanism of the observed treatment
effect.
Removal of S02 from the atmosphere by this system was governed to a
large degree by the presence of aboveground biomass; however, litter and soil
(fine litter) also played important roles. Deposition rates onto dead leaf
surfaces were not markedly different than those onto live shoots, which
suggests that estimates of removal based on stomatal resistance alone are not
adequate. The removal process seemed to be controlled primarily by the
magnitude of the absorbing surface area rather than by the gas exchange
464
-------
process of the plants. Increased removal rates by live material on fumigated
plots over control plots suggested that stomatal opening may have been-
stimulated by S02. This increase was overshadowed, however, by the role
played by passive deposition onto leaf surfaces, litter, and soil. The small
quantities of total deposition found translocated to roots suggested that
aboveground growth demands prevented large quantities from reaching roots.
Distribution of total sulfur in the plants was not unaffected by S02
fumigation. The suprising finding of lower sulfur contents in roots of
fumigated plants suggested that root uptake was decreased as the source of
sulfur shifted to the atmosphere. Fumigated shoots may have derived a sig-
nificant portion of their sulfur from the atmosphere, thereby lessening the
reliance on sulfur stored in deeper rooting layers. Thus, in the later part
of the season, sulfur concentrations at 5-20 cm on the control treatment
increased or remained constant but decreased or remained constant on the
fumigated treatment. Roots in the 0-5 cm layer appeared to act as an effi-
cient sink for sulfur translocated from shoots late in the season, yet there
were lowered total sulfur concentrations in these roots on the fumigated
plots. This result suggested that root uptake was governed by concentrations
in shoots at least as much as by those in roots. It is possible that hor-
mones controlling root uptake rates are manufactured in the shoots and
translocated belowground when shoot demand is high.
Roots at 5-20 cm failed to accumulate sulfur on the fumigated treatment
at the end of the growing season. This would not be detrimental to growth
the following season provided the source of sulfur for aboveground growth
remains in the atmosphere. Should the fumigation cease, however, there would
be an increased reliance on rapid uptake from the soil. It is interesting to
speculate what would happen to root sulfur over many years of fumigation.
Perhaps it would decline to some minimal level as reliance on root uptake
diminishes. Perhaps, as sulfur accumulates in the soil under fumigation,
root uptake would again increase because of the response of Michaelis-Menten
enzyme kinetics to increased substrate concentrations. The principal short-
term effect appears to be a decrease in the strength of coupling of the plant
to the soil with respect to sulfur. This also decreases the relationship of
a plant to its neighbors with respect to this substrate. Perhaps real
changes in community composition would occur in ecosystems where soil sulfur
is deficient. Root uptake would no longer secure a competitive advantage to
species short of sulfur. Composition would be expected to shift away from
species with superior root uptake capabilities towards those with the capacity
to derive their supply from the atmosphere. This assumes, of course, no
side effects of S02 on metabolic machinery.
The overall response of this system to S02 fumigation at low levels was
subtle indeed. Changes observed here could, if unchecked over many years,
lead to fundamental changes in the structure and functioning of the ecosys-
tem. Continued sulfur loading into this system eventually may facilitate
H2S04 acidification as the buffering capacity of the soil eventually is
exceeded, which, in turn, may drive the system into a much different Conforma-
tion. It is unknown how realistic, or how far in the future, such a response
is.
465
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A closing consideration is the extent to which this perturbation would
be imposed on northern Great Plains ecosystems. It is likely that fossil
fuel combustion in the region will continue to rise for some time in view of
the vast reserves of coal located here and the increasing demand for electri-
cal energy. According to Montana law, the maximum allowable annual arith-
metic mean concentration is only 1/5 that used here (2 pphm), while the
24-hour maximum is identical to that used here (10 pphm). But these concen-
trations are more likely to be observed locally in the vicinity of the power
facility, or at a distance as intermittent events. Because fumigation in
this study was continuous, the observed responses probably would be confined
to areas local rather than distant to S02 sources. More distant ecosystems
would be less likely to be perturbed from their natural steady state because
of the unreliability of S02 as a sulfur source or as an influence on primary
production.
SIMULATION MODELS: SULFUR CYCLE AND
ECOSYSTEM LEVEL MODEL*
During the past two years, an effort has been made to develop sulfur
cycling and S02 deposition submodels and to incorporate them into an ecosys-
tem level simulation model of the northern mixed-grass prairie. The ecosys-
tem level model used was an improved version of the ELM model described by
Innis (1978). The model was adapted to simulate the identical grassland type
as that being studied by other Colstrip coal-firing power plant (CCFPP)
investigators to determine the ecological effects of controlled field expo-
sure to S02 (see Sections 9-20). The modeling work has been completed and
will be reported in full in a dissertation by the first author later this
year. The following is a summary report of results derived by exercising the
model to test a number of hypotheses.
The ecosystem level model which includes abiotic, producer, and
decomposer-nitrogen submodels was successfully constructed, and integrated
with the sulfur cycling, and S02 deposition submodels. Comparisons of
observed and simulated soil water dynamics, primary producer dynamics, shoot
nitrogen, shoot sulfur, and litter biomass were generally favorably.
One exercise of the model involved a 2-year simulation run with ambient
concentration of S02 held at 10 pphm throughout each growing season. S02
deposited sulfur had significant impacts on the cycling of sulfur. The total
addition of sulfur amounted to 48.2 kg S • ha"1 • yr"1. The sum of all sys-
tem flows of sulfur was increased by 3.2 and 5.8 g S • m~2 over each of the
two growing seasons. When direct S02 fluxes are subtracted from these quan-
tities, an indirect increase in total system sulfur flows becomes 1.1 and 3.1
g S • m~2. All sulfur state variables (standing crop of sulfur in various
compartments) together were perturbed four to nine times over their normal
Condensed from a dissertation by Michael B. Coughenour entitled "Grassland
Sulfur Cycle and Ecosystem Responses to Low-Level 302-"
466
-------
deviations, indicating the sulfur cycling system to have deviated from
steady-state behavior.
Implementation of a restriction on plant growth at N/S ratios greater
than 15 produced a significant model response to sulfur fertilization by S02-
This response has been somewhat exaggerated over reality, but indicates the
possibility is real. These results additionally showed that if aboveground
growth is stimulated more than net photosynthesis, a decrease in belowground
growth may be observed, which would explain the previously mentioned indica-
tions of a growth depression in rhizomes. Fertilization also brought about
numerous secondary effects through the increase in net aboveground primary
production.
Several other hypotheses regarding direct effects on primary producers
were tested in the ecosystem context. An inhibition of photosynthesis
decreased belowground growth much more than that above ground and this effect
carried over on decomposer-related activity. A stimulation of photosynthesis
increased production below ground and had no effect above ground. Increase'd
senescence lowered peak standing crop, decreased total net photosynthesis,
and depressed belowground growth.
DECOMPOSITION-LITTER BIOMASS DYNAMICS
Litter standing crop data for the two ZAPS sites are tabulated in
Table 13.20. The general trend that is noted is an increase in the amounts
of litter on all treatments over time. Litter will tend to increase on these
sites to a new position of equilibrium as accumulation rates exceed decompo-
sition rates now that cattle grazing has been prevented. Litter standing
crop increased from 1976 to 1977 by 31% on ZAPS I and by 43% on ZAPS II, but
on ZAPS I the increase from 1975 to 1976 was only 9%. An analysis of the
yearly increases in litter on each treatment did not reveal any relationship
to S02 treatment; however, at some time in the future we may be able to
detect an effect by the S02 gas and sulfur content of the litter on
decomposition rates.
467
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TABLE 13.20. INTRASEASONAL DYNAMICS OF LITTER STANDING CROP
oo
ZAPS I
Date
20 April 1975
5 May 1975
15 June 1975
13 July 1975
13 August 1975
18 September
1975
Season average
21 March 1976
17 May 1976
15 June 1976
10 July 1976
9 August 1976
17 September
1976
Season average
12 July 1977
Control
112
102
165
123
172
156
126
122
130
139
212
232
214
± 6
± 16
± 8
± 15
± 17
± 20
138
± 18
± 11
± 11
± 10
± 20
± 17
160
± 13
Low
112 ± 21
174 ± 21
137 ± 14
155 ± 17
192 ± 15
149 ± 19
153
180 ± 12
176 ± 21
173 ± 13
170 ± 17
187 ± 17
181 ± 18
178
241 ± 20
Medium
135 ± 16
168 ± 24
178 ± 17
155 ± 18
193 ± 17
193 ± 17
170
167 ± 15
151 ± 12
154 ± 12
188 ± 10
188 ± 13
218 ± 26
178
221 ± 16
High
39 ± 7
179 ± 23
124 ± 12
154 ± 16
189 ± 22
100 ± 33
148
122 ± 10
152 ± 17
144 ± 17
174 ± 16
157 ± 10
141 ± 13
148
191 ± 16
Control
146 ± 10
104 ± 8
133 ± 18
146 ± 8
196 ± 18
88 ± 11
136
244 ± 15
ZAPS II
Low
175 ± 16
149 ± 19
196 ± 23
242 ± 25
214 ± 20
107 ± 14
181
231 ± 16
Medium
155 ± 13
188 ± 17
172 ± 16
183 ± 21
201 ± 23
123 ± 14
170
220 ± 16
Average
by
High
145
152
206
223
201
142
251
± 13
± 12
± 27
± 29
± 24
± 13
178
± 17
date
100
156
151
147
187
175
152
149
164
183
195
154
227
*_
X ± SE, oven-dry ash-free, g
m
-------
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477
-------
APPENDIX
TABLE 13.1. PHENOLOGY AT ZAPS I, 1976 AND 1977 (A = CONTROL, B = LOW, C =• MEDIUM, D = HIGH)
-P-
*^l
00
Aahillea
mi I lifo Him
Date
18-3-76
29-3-76
12-4-76
19-4-76
30-4-76
10-5-76
15-5-76
26-5-76
2-6-76
10-6-76
16-6-76
24-6-76
1-7-76
8-7-76
15-7-76
22-7-76
29-7-76
5-8-76
12-8-76
19-8-76
26-8-76
3-9-76
9-9-76
11-4-77
19-4-77
25-4-77
2-5-77
9-5-77
lfi-S-77
1U J 1 1
.24-5-77
7_A— 77
/ D / /
15-6-77
O A £ 77
/*»— D— / /
30-6-77
7-7-77
22-7-77
6-8-77
12-8-77
18-8-77
25-8-77
1-9-77
8-9-77
15-9-77
22-9-77
A
1
1
2
2
2
3
5
6
7
7
8
8
8
8
8
8
11
11
12
1
1
2
3
5
5
J
6
8
9
9
11
12
B
1
1
2
2
2
3
5
6
8
8
8
8
8
8
8
8
11
11
1?
1
1
2
3
5
c
J
6
8
9
9
11
12
C
1
1
2
2
2
3
5
6
7
8
8
8
8
8
8
11
11
12
1
1
2
3
5
5
J
6
8
9
9
11
12
D
1
1
2
2
2
3
5
6
7
7
8
8
8
8
8
8
11
11
12
1
1
2
3
5
5
J
6
8
9
10
11
12
A
1
2
2
3
3
3
3
3
3
3
4
4
5
6
7
8
9
9
10
10
11
11
11
1
1
2
3
3
3
J
3
A
H
4
5
6
8
9
11
11
11
11
11
11
11
Agropyron
amithii
B
1
2
2
3
3
3
3
3
3
3
4
5
5
6
7
8
9
9
10
10
11
11
11
1
1
2
3
3
3
J
3
A
H
4
5
6
8
9
11
11
11
11
11
11
11
C
1
2
2
3
3
3
3
3
3
3
4
4
5
6
7
8
9
9
9
10
11
11
12
1
1
2
3
3
3
J
3
A
H
4
A
4
5
7
8
9
10
11
11
11
11
11
11
D
1
2
2
3
3
3
3
3
3
3
4
4
5
6
7
8
9
9
10
10
11
12
1
1
2
3
3
3
J
3
A
H
4
5
—
8
9
10
11
11
11
11
11
11
Antennaria
rosea
A
12
2
9
9
9
11
11
11
12
1
1
2
2
5
s
J
9
i ft
1 V/
10
12
—
B
12
2
9
9
10
11
11
11
11
11
12
1
1
2
2
5
"5
J
9
i n
i. w
10
1 1
•11
12
C
12
2
9
9
10
11
11
11
11
11
12
1
1
2
2
5
5
J
9
1 f)
± \j
10
12
D
12
2
9
9
10
11
11
11
12
1
1
2
2
5
5
J
9
i n
1 w
10
12
A
2
2
2
3
3
4
4
4
4
4
5
6
6
7
7
7
8
1
2
2
3
3
3
3
3
J
4
4
4
4
5
5
5
7
7
7
7
8
Artemisia
friqida
B
1
3
2
2
3
3
3
4
4
4
4
4
5
6
6
7
7
7
8
1
2
2
3
3
3
3
3
•J
4
4
4
4
5
5
5
7
7
7
8
9
C
1
2
2
3
3
3
4
4
4
4
4
5
6
6
7
7
7
7
1
2
2
3
3
3
J
3
3
J
4
4
4
4
5
5
5
7
7
7
7
8
D
1
1
2
2
2
3
3
3
4
4
4
4
4
5-
6
7
7
7
7
8
1
2
2
3
3
3
j
3
4
4
—
4
5
5
5
6
8
8
9
9
A
12
12
1
1
1
3
5
6
6
6
7
9
10
11
11
11
12
0
0
1
2
3
J
3
—
8
9
9
10
11
11
11
11
11
11
11
Aristida
longiseta
B
12
12
1
1
1
3
5
6
6
6
.7
9
10
11
11
11
12
1
1
2
3
J
3
A
*t
5
8
9
9
10
11
11
11
11
11
11
11
C
12
12
1
1
1
3
5
6
6
6
7
9
10
11
11
11
11
12
—
1
1
2
3
.?
3
A
*+
5
8
9
9
10
11
11
11
11
11
11
11
D
12
12
1
1
1
2
5
6
6
6
7
9
10
11
11
11
12
— .
1
1
2
3
j
3
5
8
9
9
10
11
11
11
11
11
11
11
A
12
4
4
6
7
8
9
10
10
11
12
0
0
1
2
•j
j
3
4
6
7
9
10
11
11
11
11
11
11
11
Boute loua
qracilis
B
12
2
3
3
4
4
6
7
8
9
10
10
11
12
—
0
1
2
3
4
6
7
9
10
11
11
11
11
11
11
11
C
12
2
4
4
7
7
8
9
10
10
11
11
12
___ .
0
1
2
3
4
6
7
9
10
11
11
11
11
11
11
11
D
12
3
4
4
7
7
8
9
10
10
11
12
__
__
1
2
3
4
6
—
9
10
11
11
11
11
11
11
11
A
2
2
3
4
5
6
6
6
8
9
9
9
11
11
11
12
1
1
2
3
4
4
8
9
10
12
Bromua
japonicus
B
2
2
4
5
6
6
6
8
9
9
9
11
11
11
12
1
1
2
3
4
4
8
9
9
10
12
C
2
2
4
5
6
6
6
8
9
9
9
11
11
11
12
1
1
2
3
4
4
8
9
9
10
12
D
2
2
4
5
6
6
6
8
9
9
9
11
11
11
12
1
1
2
3
4
4
8
9
__
12
-------
TABLE 13.1. (CONTINUED)
Date A
18-3-76
29-3-76
12-4-76
19-4-76
30-4-76
10-5-76
15-5-76 8
26-5-76 8
2-6-76 8
10-6-76 11
16-6-76 11
24-6-76 11
1-7-76 12
8-7-76
15-7-76
22-7-76
29-7-76
5-8-76
12-8-76
19-8-76
26-8-76
3-9-76
9-9-76
11-4-77
19-4-77
25-4-77
2-5-77
9-5-77
16-5-77
24-5-77
7-6-77
15-6-77
24-6-77
30-6-77
7-7-77
22-7-77
6-8-77
12-8-77
18-8-77
25-8-77
1-9-77
8-9-77
15-9-77
22-9-77
Cerastium
arvense
B C D A
2
3
3
3
8 5
8886
8886
11 11 11 7
11 11 11 7
11 11 11 8
12 12 12 9
10
11
11
11
12
1
1
2
3
4
6
7
8
8
9
10
11
12
Koe lev-La
oristata
B
2
3
3
3
5
6
6
7
7
8
9
10
10
11
11
12
1
1
2
3
4
6
7
8
8
9
10
11
12
C
2
3
3
3
4
5
6
6
7
7
8
9
10
10
11
11
12
1
1
2
3
4
6
7
8
8
9
10
11
12
Lepidium Phlox
densiflorum hoodi
DABCDABCD
2
3
3
4
5
6 11 11 11 11
6 11 11 11 11
7 12 12 11 12
7 12
8
9
10
11
11
11
12
1
1
2
3 8888
4 9999
6 10 10 10 10
7 10 10 10 10
8 11 11 11 11
8 12 12 12 12
9 12 12 12 12
10
—
12
Plantago Poa
patagonia pratensis
ABCDABCDA
3
3
3
3
5
6
6
7
4444 8
555 8
7777 8
8888 11
8888 11
8888 12
10 10 10 10
10 10 10 11
11 11 11 11
11 11 11 11
12 12 12 12
2
2
3
3
6
88888
88888
9
10
11 11 11 11 11
12 12 12 — 12
Poa
secunda.
B
3
3
3
3
5
6
6
7
8
8
9
11
11
12
2
2
3
3
6
8
8
9
10
11
12
C D
3 3
3 3
3 3
5 5
6 6
6 6
7 7
8 8
8 8
9 9
11 11
11 11
12 12
2 2
2 2
3 3
3 3
6 6
8 8
8 8
9 9
10 10
11 11
12 12
-------
TABLE 13.1. (CONTINUED)
•t-
00
o
Fsoralea.
argophylla
Date
18-3-76
29-3-76
12-4-76
19-4-76
30-4-76
10-5-76
15-5-76
26-5-76
2-6-76
10-6-76
16-6-76
24-6-76
1-7-76
8-7-76
15-7-76
22-7-76
29-7-76
5-8-76
12-8-76
19-8-76
26-8-76
3-9-76
9-9-76
11-4-77
19-4-77
25-4-77
2-5-77
9-5-77
16-5-77
24-5-77
7-6-77
15-6-77
24-6-77
30-6-77
7-7-77
22-7-77
6-8-77
12-8-77
18-8-77
25-8-77
1-9-77
8-9-77
15-9-77
22-9-77
A
12
3
4
6
9
10
10
10
10
10
11
11
12
1
— —
__
4
4
5
8
8
9
9
12
B
3
3
4
6
10
10
10
10
10
10
11
11
12
1
—
—
4
4
5
8
8
9
9
12
C
4
5
5
10
10
10
10
10
10
11
11
12
1
1
—
4
4
4
5
8
8
9
9
12
D
4
5
6
9
10
10
10
10
10
11
11
12
1
—
—
4
4
5
8
8
—
9
12
Sphaeralaea
cooai-Ytae
A
12
12
3
3
4
5
5
9
9
9
10
10
11
11
11
12
4
—
—
4
5
4
6
8
9
9
10
11
12
B
12
12
2
3
4
5
5
9
9
9
10
10
11
11
11
12
4
—
—
4
5
4
6
8
9
9
10
11
12
C
12
1
2
3
4
5
5
9
9
9
9
10
11
11
11
12
4
—
—
4
5
4
6
8
9
10
10
11
12
D
3
4
5
5
9
9
9
9
10
11
11
11
12
—
—
—
4
5
4
6
8
9
9
-
11
12
A
1
1
3
3
3
7
8
9
10
10
11
11
11
12
1
1
2
4
4
4
6
7
9
10
10
11
12
Stipa
aomata
B
1
1
3
3
3
7
8
9
10
10
11
11
11
12
1
1
2
4
4
4
6
7
9
10
10
11
12
C
1
1
3
3
3
8
8
9
10
10
11
11
11
12
1
1
2
4
4
4
6
7
9
9
10
11
12
D
1
1
3
3
3
7
7
9
10
10
11
11
11
12
1
1
2
4
4
4
6
7
9
10
—
11
12
A
1
2
4
6
6
7
9
11
11
11
11
11
12
1
1
2
3
—
—
6
6
9
10
10
11
12
Stipa
viridula
B
6
6
9
10
10
11
11
11
12
1
1
2
3
—
—
6
6
9
10
10
11
12
C
2
4
6
6
9
10
10
11
11
11
12
1
1
2
i
3
—
—
6
6
9
10
10
11
12
D
6
6
7
9
10
10
11
11
11
12
1
1
2
3
—
—
6
6
9
10
—
11
12
Taraxacum
offioinale
A
1
2
5
5
7
8
10
10
11
11
11
11
11
11
11
11
11
11
12
1
1
2
8
9
10
11
11
12
12
B
1
2
5
6
7
8
10
10
11
11
11
11
11
11
11
11
11
11
12
1
1
2
8
9
10
11
11
12
12
C
1
2
5
6
7
9
10
11
11
11
11
11
11
11
11
11
11
11
12
1
1
2
8
9
10
11
11
12
12
D
1
2
5
6
7
8
10
11
11
11
11
11
11
11
11
11
11
11
12
1
1
2
8
9
10
11
11
12
12
Tragopogon
dubiuB
A
2
2
3
3
5
5
6
7
8
8
10
10
10
10
10
10
11
12
1
2
2
3
3
4
4
9
9
10
10
11
12
B
2
3
3
5
6
7
8
8
10
10
10
10
11
11
11
12
1
2
2
3
3
4
4
9
9
10
10
11
12
C
2
2
3
3
5
5
6
7
8
8
10
10
10
10
11
11
11
12
1
2
2
3
3
4
4
9
9
10
10
11
12
D
2
2
3
5
5
6
7
8
9
10
10
10
10
11
11
11
12
1
2
2
3
3
4
4
9
9
10
10
—
12
A
7
11
9
11
11
11
11
11
12
1
1
2
—
8
8
8
8
9
10
—
10
12
Vicia
americana
B
8
7
11
11
11
11
11
12
1
1
2
—
8
8
8
8
9
10
10
10
12
C
8
11
11
11
11
11
12
1
1
2
—
8
8
8
8
9
10
—
10
12
D
8
8
11
11
11
11
11
11
12
1
1
2
—
8
8
8
8
9
10
—
—
12
-------
TABLE 13.2. PHENOLOGY AT ZAPS II, 1976 AND 1977 (A " CONTROL, B = LOW, C - MEDIUM, D => HIGH)
00
Aehillea
millifoliwn
Date
18-3-76
29-3-76
12-4-76
19-4-76
2-5-76
10-5-76
15-5-76
26-5-76
2-6-76
10-6-76
16-6-76
24-6-76
1-7-76
8-7-76
15-7-76
22-7-76
29-7-76
5-8-76
12-8-76
19-8-76
26-8-76
3-9-76
9-9-76
11-4-77
19-4-77
25-4-77
2-5-77
9-5-77
16-5-77
24-5-77
7-6-77
15-6-77
24-6-77
30-6-77
7-7-77
22-7-77
6-8-77
12-8-77
18-8-77
25-8-77
1-9-77
8-9-77
15-9-77
22-9-77
A
1
1
2
2
2
3
5
6
7
7
8
8
8
8
8
8
11
11
12
1
1
2
4
5
5
6
8
8
9
9
10
11
12
B
1
1
2
2
2
3
5
6
7
7
8
8
8
8
8
8
11
11
12
1
1
2
4
5
5
6
8
8
9
9
10
11
12
C
1
1
2
2
2
3
5
6
7
7
8
8
8
8
8
8
11
11
12
1
1
2
4
5
5
6
8
8
9
9
10
11
12
D
1
1
2
2
2
3
5
6
7
7
8
8
8
8
8
8
11
11
12
1
1
2
4
5
5
6
8
8
9
9
10
11
12
A
1
2
3
3
3
3
3
3
3
4
5
5
6
6
8
9
9
10
10
11
11
11
1
1
2
3
3
3
3
4
4
4
5
7
8
10
11
11
11
11
11
11
11
Agropyron
smithii
B
1
2
3
3
3
3
3
3
3
3
4
5
6
7
8
9
9
10
11
11
12
1
1
2
3
3
3
3
4
4
4
5
7
8
9
10
11
11
11
11
11
11
C
1
2
3
3
3
3
3
3
4
4
4
5
6
8
9
9
10
11
11
12
1
1
2
3
3
3
3
4
4
4
5
6
8
9
10
11
11
11
11
11
11
Antennari-a
vosea
D A B C D
1
2
3
3
3
3 3
38888
3 10 10 10 10
3 11 11 11 11
4 11 11 11 11
4 11 11 11 11
5 11 11 11 11
6 11 11 11 11
8 12 12 12 12
8
9
9
10
11
11
12
1
1
22222
3
3
3
3
4
4
4
5
7
8
9
10
11
11
11
11
11
11
Artemisia
friffida
A
1
1
3
3
3
3
3
3
3
4
4
4
4
4
4
5
6
6
7
7
7
8
1
2
2
3
3
3
3
3
4
4
5
5
5
5
5
6
6
6
8
7
8
B
1
1
3
3
3
3
3
4
4
4
4
4
5
6
6
7
7
7
8
1
2
2
3
3
3
3
3
4
4
5
5
5
5
6
6
7
6
7
8
9
C
1
1
3
3
3
3
3
4
4
4
4
4
5
6
6
7
7
8
8
1
2
2
3
3
3
3
3
4
4
5
5
5
5
6
6
6
6
6
6
9
D A
1
1
3
3
3 1
3 2
3 5
4 6
4 6
4 6
4 7
4 9
5 10
6 11
6 11
7 11
7
7
7
1
2
2
3
3
3
3
3
4
•4
5
5
5
5
6
8
8
9
10
10
10
Aristida
longiseta
B C D A
1
2
111
222
5553
6664
6664
6667
7777
9998
10 10 10 9
11 11 11 10
10 11 11 10
11 11 11 11
11 11 11
12
12 12
„
-
-
1
2
3
3
4
4
4
6
7
9
10
11
11
11
11
11
11
11
Bouteloua
qraoi Us
B
1
4
4
7
7
8
9
10
10
11
12
_
-
-
1
2
3
3
4
4
4
6
7
9
10
11
11
11
11
11
11
11
C
1
2
3
4
4
7
7
8
9
10
10
11
12
-
-
1
2
3
3
4
4
4
6
7
9
10
11
11
11
11
11
11
11
D
1
2
3
3
4
5
7
7
8
9
10
10
11
11
12
1
2
3
3
4
4
4
6
7
9
10
11
12
11
11
11
11
11
A
2
2
3
5
5
6
6
6
8
9
9
10
11
11
11
12
1
1
2
3
4
4
6
7
8
9
11
12
Bromus
japonicus
B
2
2
3
5
5
6
6
6
8
9
9
10
11
11
11
12
1
1
2
3
4
4
6
7
8
9
11
12
C
2
2
5
5
6
6
6
8
8
9
10
11
11
11
12
1
1
2
3
4
4
6
1
8
9
11
12
D
2
2
3
5
5
6
6
6
8
9
9
10
11
11
11
12
1
1
2
3
4
4
6
7
8
9
11
12
-------
TABLE 13.2. (CONTINUED)
00
N3
Date
18-3-76
29-3-76
12-4-76
19-4-76
2-5-76
10-5-76
15-5-76
26-5-76
2-6-76
10-6-76
16-6-76
24-6-76
1-7-76
8-7-76
15-7-76
22-7-76
29-7-76
5-8-76
12-8-76
19-8-76
26-8-76
3-9-76
9-9-76
11-4-77
19-4-77
25-4-77
2-5-77
9-5-77
16-5-77
24-5-77
7-6-77
15-6-77
24-6-77
30-6-77
7-7-77
22-7-77
6-8-77
12-8-77
18-8-77
25-8-77
1-9-77
8-9-77
15-9-77
22-9-77
Cevast-ium
arvense
A B C D A
2
2
3
4
5
78886
88886
11 11 11 7
11 11 11 11 7
11 11 11 11 8
12 12 12 12 9
10
11
11
11
12
1
1
3
3
5
6
7
8
8
10
10
11
12
Koe leria
cristata
B
2
2
4
5
6
6
7
7
8
9
10
11
11
11
12
1
1
3
3
5
6
7
8
8
10
10
11
12
C
2
2
5
5
6
6
7
7
8
9
10
10
11
11
12
1
1
3
3
5
6
7
8
8
10
10
11
12
Lepidiwn Lomutiwn Phlox Plantago Poa
denaiflomm orientate hoodi patagonia pratensie
D A
2
2
3
3
5 9
6 9
6 10
7 11
7 12
8
9
10
11
11
11
12
1
1
3
3
5
6
7
8
8
10
10
11
12
BCDABCDABCDABCDABCD
9 9
999
10 10 11
11 11 11 5455
11 11 11 5555
12 12 12 7877
8889
8889
8889
10 10 10 10
11 11 11 11
11 11 11 11
11 11 11 11
12 12 12 12
5 5 5 5 — ----- 1111
77777777 1111
88888888 2222
99998888 3333
10 10 10 10 9 9 9 9
10 10 10 10 9 9 9 9 3333
10 10 10 10 10 10 10 10 8888
11 11 11 11 11 11 11 11 8888
12 12 12 12 12 12 12 12 8888
—
11 11 11 11
-------
TABLE 13.2. (CONTINUED)
CO
GJ
_.„ —
Poa
ocawida
Da to
18-3-76
29-3-76
12-4-76
19-4-76
2-5-76
10-5-76
15-5-76
26-5-76
2-6-76
10-6-76
16-6-76
24-6-76
1-7-76
8-7-76
15-7-76
22-7-76
29-7-76
5-8-76
12-8-76
19-8-76
26-8-76
3-9-76
9-9-76
11-4-77
1 9—4—7 7
25-4-77
2-5-77
9-5-77
16-5-77
24-5-77
7-6-77
15-6-77
24-6-77
30-6-77
7-7-77
22-7-77
6-8-77
12-8-77
18-8-77
25-8-77
1-9-77
8-9-77
15-9-77
22-9-77
A
3
3
3
5
6
6
7
8
8
9
11
11
12
2
2
3
5
6
8
8
8
10
11
U
3
3
3
5
6
6
7
8
8
9
11
11
12
2
2
3
7
6
8
8
8
10
11
C
3
3
3
5
6
6
7
8
8
9
H
11
12
2
2
3
7
6
8
8
8
10
11
I'ooralca
ar^oph/lla
I) A H C
3
3
3
5
6
6 3-
7
8444
8544
9556
11 9 9 9
11 10 10 10
12 10 10 10
10 10 10
10 10 10
10 10 10
11 11 11
11 11 11
12 11
12
2
2
3
7
6
8
8
a
10
11
Sphaera laea
concinae
I) A
3
4
4 5
4 5
5 9
9 9
10 9
10 9
10 10
10 11
10 H
11 11
11 12
4
5
5
6
8
9
9
10
11
12
B
3
4
5
5
9
9
9
9
H
11
11
11
12
4
5
5
6
8
9
9
10
11
12
C
3
4
5
5
9
9
9
10
10
11
11
11
12
4
5
5
6
8
9
9
10
11
12
U
3
4
5
5
9
9
9
10
11
11
11
11
12
4
5
5
6
8
9
9
10
11
12
A
1
1
3
3
3
7
8
9
10
10
11
11
11
12
1
1
2
4
4
6
7
9
10
10
11
12
coma ta
B
1
1
3
3
3
7
8
9
10
10
11
11
11
12
1
1
2
4
4
6
7
9
10
10
11
1?
C
1
1
3
3
3
8
8
9
10
10
11
11
11
12
1
1
2
4
4
6
7
9
9
10
11
12
I)
1
1
3
3
3
7
7
9
10
10
11
11
11
12
1
1
2
4
4
6
7
9
10
U
12
A
1
2
4
6
6
7
9
11
11
11
11
11
12
1
1
2
—
6
6
9
10
10
11
12
vi.ridula
H
6
6
9
10
10
11
11
11
12
1
1
2
__
6
6
9
JO
10
11
12
C
2
4
6
6
9
10
10
11
11
11
12
1
1
2
6
6
9
10
10
11
12
D
6
6
7
9
10
10
11
11
1)
12
1
1
2
6
6
9
10
11
12
Taraxacum
__offi,cirnle_
A 1! C
1
2
5
5
7
8
10
10
11
11
11
11
11
11
11
11
11
11
12
1
1
2
g
10
11
1!
12
12
1
2
5
6
7
8
10
10
11
11
11
11
11
11
11
11
11
11
12
1
1
2
g
10
11
11
12
12
1
2
5
6
7
9
10
11
11
11
11
11
11
11
11
11
11
11
12
1
1
2
10
11
H
12
12
Trafjopoyon
iliibiua
D
1
2
5
6
7
8
10
11
11
11
11
11
11
11
11
H
11
11
12
1
1
2
o
10
11
11
12
12
A
2
2
3
3
5
5
6
7
8
8
10
10
10
10
10
10
11
12
1
2
2
0
4
4
9
9
10
10
11
12
B
2
3
3
5
6
7
8
8
10
10
10
10
11
11
11
12
1
2
2
3
4
4
9
9
10
10
11
12
C
2
2
3
3
5
5
6
7
8
8
10
10
10
10
11
11
11
12
1
2
2
3
4
4
9
9
10
10
11
12
D
2
2
3
5
5
6
7
8
9
10
10
10
10
11
11
11
12
1
2
2
3
4
4
9
9
10
10
_-
12
A
7
11
9
11
11
11
11
11
12
1
1
2
Q
8
8
8
9
10
—
10
12
Vicia
amcriciina
B
8
7
11
11
11
11
11
12
1
1
2
Q
8
8
8
9
10
10
10
12
C
8
11
11
11
11
11
12
1
1
2
8
8
8
8
9
10
—
10
12
D
S
8
11
11
11
11
11
11
12
1
1
2
g
8
8
8
9
10
—
12
-------
TABLE 13.3. CHEMICAL CONSTITUENTS OF LIVE AGROPYRON SMITHII AND KOELERIA CRISTATA
Ash
Nitrogen
Phosphorus
Sulfur
Site
Date
Rep. 1
Rep. 2
Rep. 1
Rep. 2
Rep. 1
Rep. 2
Rep. 1
Rep. 2
Agpopyron smithii
ZAPS I, Control
ZAPS I, Low
ZAPS I, Medium
1 June 1975
1 July 1975
1 August 1975
17 May 1976
15 June 1976
10 July 1976
9 August 1976
17 September 1976
1 May 1975
1 June 1975
1 July 1975
1 August 1975
17 May 1976
16 June 1976
11 July 1976
10 August 1976
17 September 1976
17 May 1975
1 June 1975
1 July 1975
1 August 1975
7.6
6.7
7.8
6.9
6.3
6.8
6.5
7.0
8.3
8.1
6.4
7.8
7.2
7.6
7.5
8.0
8.1
8.4
8.1
8.1
8.1
7.7
6.9
7.3
6.9
6.7
6.4
7.3
7.0
8.7
7.5
6.3
6.7
6.9
7.2
6.4
7.7
7.5
8.0
7.2
7.5
1.9
1.3
1.1
2.3
1.6
1.3
1.0
0.8
2.6
1.6
1.3
1.1
2.2
1.3
1.1
0.8
0.6
2.7
1.5
1.3
1.2
1.8
1.3
1.1
2.2
1.5
1.2
0.9
0.7
2.4
1.8
1.2
1.0
2.1
1.4
1.0
0.8
0.6
1.8
1.4
1.0
.22
.14
.12
.27
.23
.15
.16
.36
.20
.18
.15
.23
.14
.10
.22
.22
.16
.20
.26
.15
.13
.11
.09
.13
.05
.09
.10
.08
.12
.13
.15
.14
.14
.15
.14
.18
.10
.18
.14
.23
.25
.24
.08
.10
.10
.09
.09
.09
.09
.09
.13
.14
.13
.13
.07
.13
.13
.20
.17
.19
.23
.28
-------
TABLE 13.3. CONTINUED
Site
Date
Ash
Nitrogen
Phosphorus
Sulfur
Rep. 1 Rep. 2 Rep. 1 Rep. 2 Rep. 1 Rep. 2 Rep. 1 Rep. 2
Agropyron smithii (cont.)
ZAPS I, Medium
(cent.)
ZAPS I, High
oo
Ln
ZAPS II,
Control
ZAPS II, Low
18 May 1976
18 June 1976
12 July 1976
11 August 1976
17 September 1976
17 May 1975
1 June 1975
1 July 1975
1 August 1975
19 May 1976
19 June 1976
13 July 1976
12 August 1976
17 September 1976
21 May 1976
20 June 1976
14 July 1976
14 August 1976
22 May 1976
21 June 1976
15 July 1976
13 August 1976
18 September 1976
7.7
7.2
6.9
8.7
8.7
8.3
7.9
8.4
10.1
8.7
8.4
8.5
9.1
9.4
9.2
7.6
8.9
8.6
8.4
6.5
8.1
7.7
8.5
6.7
7.0
7.1
7.7
7.9
8.3
8.2
8.2
7.1
7.8
7.4
8.1
9.8
9.2
8.8
7.7
8.3
8.0
8.1
6.4
8.7
7.1
8.9
2.0
1.4
1.1
1.0
0.6
2.6
2.0
1.2
1.0
1.9
1.3
1.1
0.9
0.7
2.2
0.3
1.3
1.0
2.5
2.0
1.5
1.1
0.9
2.1
1.5
1.1
0.9
0.6
2.7
1.9
1.2
1.0
1.9
1.3
1.0
0.9
0.7
2.3
1.9
1.4
1.1
2.4
1.8
1.7
1.1
1.0
31
23
18
12
.31
.26
.17
.12
.16
.22
.23
.31
.25
.13
.21
.27
.31
.25
.23
.35
.42
.37
.14
.09
.09
.11
.12
.12
.16
.15
.16
.16
.21
.21
.27
.26
.13
.24
.28
.35
.22
.25
.30
.40
.35
.12
.12
.10
.09
.16
.13
.17
.15
.15
-------
TABLE 13.3. CONTINUED
Site
Date
Ash
Nitrogen
Phosphorus
Sulfur
Rep. 1 Rep. 2 Rep. 1 Rep. 2 Rep. 1 Rep. 2 Rep. 1 Rep. 2
ZAPS II,
Medium
ZAPS II, High
CO
ON
23 May 1976
22 June 1976
16 July 1976
15 August 1976
18 September 1976
24 May 1976
23 June 1976
17 July 1976
16 August 1976
18 September 1976
Agropyvon smithi-i (cont . )
2.3
1.6
1.3
1.0
2.4
1.7
1.4
1.2
10.1
8.1
9.2
9.5
9.4
8.1
9.5
9.7
9.0
8.0
8.8
8.5
8.6
9.4
8.2
8.8
9.0
10.5
2.2
1.6
1.3
1.0
0.8
2.6
2.1
1.5
1.2
1.3
.23
.23
.27
.25
.30
.31
.45
.52
.19
.23
.27
.31
.34
.39
.41
.44
.35
Koeleyla cristata
ZAPS I, Control
ZAPS I, Low
1 June 1975
1 July 1975
17 May 1976
15 June 1976
10 July 1976
9 August 1976
1 July 1975
17 May 1976
16 June 1976
11 July 1976
10 August 1976
10.6
9.8
8.7
10.0
10.0
10.0
9.9
8.8
9.9
10.1
10.3
10.3
8.4
10.3
10.0
9.7
9.5
9.2
9.5
10.0
10.6
1.8
1.3
1.8
1.3
1.2
1.3
1.3
1.7
1.4
1.1
1.1
1.6
1.7
1.3
1.1
1.1
1.2
1.6
1.3
1.1
1.0
,20
.19
.25
.20
.20
.10
.09
.06
.11
.08
.08
,15
.08
.14
.16
.18
.13
.11
.07
.08
.07
.14
.09
.12
.15
.18
-------
TABLE 13.3. CONTINUED
00
Ash
f7\
\/o)
Site
Date
Rep. 1
Rep. 2
Nitrogen
(%)
Rep. 1
Rep. 2
Phosphorus Sulfur
(V\ (7\
\/o) \'°)
Rep. 1 Rep. 2 Rep. 1
Rep. 2
Koeleria cristatci (cont.)
ZAPS I,
Medium
ZAPS I, High
ZAPS II,
Control
1 June 1975
17 May 1976
18 June 1976
12 July 1976
11 August 1976
17 September 1976
1 July 1975
19 May 1976
19 June 1976
13 July 1976
12 August 1976
20 June 1976
14 July 1976
14 August 1976
18 September 1976
10.5
10.0
10.4
11.6
10.7
11.3
10.4
12.4
12.1
13.4
13.3
11.1
10.0
9.5
10.5
10.0
12.3
10.5
11.3
12.6
12.3
12.6
10.2
1.7
1.7
1.3
1.1
1.2
0.9
1.8
1.4
1.1
1.2
1.3
1.0
1.7
1.3
1.1
0.9
1.4
1.6
1.3
1.0
1.2
1.3
1.4
.24 .13
.17
.21
.23
.25
.10
.22
.21
.28
.30
.37
.07
.18
.21
.25
.20
.39
.22
.21
.27
.39
.23
.06
ZAPS II, Low
21 June 1976
13 August 1976
9.4
1.3
.14
10.3
1.4
.10
-------
TABLE 13.3. CONTINUED
•P-
oo
oo
Ash
(%)
Site
Date
Rep. 1
Rep. 2
Nitrogen Phosphorus Sulfur
(%) (%) (%)
Rep. 1
Rep. 2 Rep. 1
Rep. 2 Rep. 1
Rep. 2
Jtoelevla eristata (cont.)
ZAPS II,
Medium
ZAPS II, High
23 May 1976
22 June 1976
12 July 1976
15 August 1976
18 September 1976
24 May 1976
23 June 1976
17 July 1976
16 August 1976
12.0
10.7
12.2
10.4
10.3
12.4
11.5
11.1
10.7
11.0
12.0
9.8
12.2
11.3
13.2
11.8
10.8
1.9
1.3
1.3
1.3
2.1
1.4
1.3
1.5
1.8
1.3
1.3
1.3
1.1
1.8
1.4
1.5
1.5
.21
.20
.24
.27
.27
.26
.33
.39
.21
.26
.22
.27
.18
.23
.28
.32
.35
-------
TABLE .13.4. CHEMICAL CONSTITUENTS OF LIVE AGROPYRON SMITHII AND KOELERIA CRISTATA
Site
T.A.C. Mg Fl
(% wt) (mg kg"1) (mg kg"1)
Date Rep. 1 Rep. 2 Rep. 1 Rep. 2 Rep. 1 Rep. 2
ZAPS I, Control
00
vo
ZAPS I, Low
ZAPS I, Medium
17 May 1975
1 June 1975
1 July 1975
1 August 1975
17 May 1976
15 June 1976
10 July 1976
9 August 1976
17 September 1976
17 May 1975
1 June 1975
1 July 1975
1 August 1975
17 May 1976
16 June 1976
11 July 1976
10 August 1976
17 September 1976
17 May 1975
1 June 1975
1 July 1975
1 August 1975
Agropyron smithii
12.0
7.4
12.0
13.0
10.7
10.8
12.4
13.7
10.7
9.7
6.6
11.0
13.0
9.2
10.7
14.4
15.5
13.3
12.0
5.9
8.5
12.0
13.5
12.0
12.0
10.8
11.7
15.2
15.1
12.0
11.0
9.0
11.0
14.0
10.9
9.4
14.7
15.7
11.4
5.6
9.5
12.0
.14
.18
.20
.19
.15
.15
.13
.15
.13
.14
.16
.12
.12
.15
.17
.14
.15
.10
.12
.13
.11
.15
2.1
0.7
1.5
1.4
1.9
1.3
1.2
1.0
2.0
2.4
1.0
1.5
1.4
0.9
0.9
1.0
1.3
1.8
-------
TABLE 13.4. CONTINUED
Site
ZAPS I, Medium
(cont.)
ZAPS I, High
so
o
ZAPS II, Control
ZAPS II, Low
T.A.C.
(% wt)
Mg
(rag kg"1)
Fl
(mg kg"1)
Date
Rep. 1 Rep. 2 Rep. 1 Rep. 2 Rep. 1 Rep. 2
Agropyron smithi-i, (cont.)
18 May 1976
18 June 1976
12 July 1976
11 August 1976
17 September 1976
17 May 1975
1 June 1975
1 July 1975
1 August 1975
20 May 1976
19 June 1976
13 July 1976
12 August 1976
17 September 1976
21 May 1976
20 June 1976
14 July 1976
14 August 1976
22 May 1976
21 June 1976
15 July 1976
13 August 1976
18 September 1976
8.3
9.5
11.9
12.0
10.9
11.0
8.5
8.1
11.0
11.6
11.3
9.7
11.4
12.3
7.7
12.6
12.2
12.1
7.6
12.2
10.5
12.4
11.8
8.4
,5
,3
10,
12,
14.2
13.6
9.8
9.4
11.0
10.4
11.2
10.9
11.9
12.5
8.9
13.3
11.2
11.5
7.3
13.0
9.7
11.8
12.0
.15
.13
.11
.13
.14
.14
.14
2.0
1.9
1.1
2.1
1.8
1.6
1.8
-------
TABLE 13.4. CONTINUED
Site
Date
T.A.C.
(% wt)
Rep. 1 Rep. 2
Mg
(mg kg"1)
Rep. 1 Rep. 2
Fl
(mg kg"1)
Rep. 1 Rep. 2
smithii (cont.)
ZAPS II, Medium
ZAPS II, High
ZAPS I, Control
23 May 1976
22 June 1976
16 July 1976
15 August 1976
18 September 1976
24 May 1976
23 June 1976
17 July 1976
16 August 1976
18 September 1976
17 May 1975
1 June 1975
1 July 1975
1 August 1975
17 May 1976
15 June 1976
10 July 1976
9 August 1976
9.7
8.2
10.2
10.8
8.1
8.9
8.3
9.4
Koe levia
13.0
7.2
11.0
10.0
19.9
9.6
9.2
14.1
8.8
8.5
10.9
12.4
9.7
8.9
9.6
10.0
10.7
8.7
eristata
12.0
6.8
11.0
13.0
14.1
10.5
10.8
12.2
.15
.18
.17
.22
.15
.19
.17
.18
1.9
1.8
-------
TABLE 13.4. CONTINUED
Site Date
ZAPS I, Low 1 May 1975
1 June 1975
1 July 1975
1 August 1975
17 May 1976
16 June 1976
11 July 1976
10 August 1976
ZAPS I, Medium 17 May 1975
1 June 1975
1 July 1975
1 August 1975
17 May 1976
18 June 1976
12 July 1976
11 August 1976
17 September 1976
ZAPS I, High 17 May 1975
1 June 1975
1 July 1975
1 August 1975
T.
(%
Rep. 1
Koetevia or
13.0
7.7
8.9
14.0
12.0
9.6
10.3
13.7
13.0
11.0
8.9
13.0
10.4
10.9
9.6
12.6
11.4
10.0
8.1
8.7
11.0
A.C.
wt)
Rep. 2
istata (cont
11.0
6.2
8.8
14.0
14.0
9.7
12.6
15.6
12.0
7.5
8.6
14.0
12.6
10.5
13.5
10.5
13.0
7.5
7.7
11.0
Mg
(mg kg"1)
Rep . 1 Rep
.)
.16
.18
.16
.19
.17
.13
.15
.16
.17
.16
.15
.17
. 2
16
16
14
18
18
17
16
19
16
16
18
18
Fl
(mg kg"1)
Rep. 1 Rep. 2
3.8 2.8
1.6 2.0
1.3
2.8 1.2
-------
TABLE 13.4. CONTINUED
OO
Site
Date
T
(
Rep. 1
.A.C. Mg Fl
% wt) (mg kg"1) (mg kg"1)
Rep. 2 Rep. 1 Rep. 2 Rep. 1 Rep. 2
Koelevla ori-stata (cont.)
ZAPS I, High
(cont. )
ZAPS II, Control
ZAPS II, Low
ZAPS II, Medium
ZAPS II, High
19 May 1976
18 June 1976
13 July 1976
12 August 1976
20 June 1976
14 July 1976
14 August 1976
21 June 1976
13 August 1976
22 May 1976
22 June 1976
12 July 1976
15 August 1976
24 May 1976
23 June 1976
17 July 1976
16 August 1976
10.9
6.8
6.0
10.1
11.3
15.1
9.2
9.1
9.9
14.7
10.3
6.6
8.5
11.9
12.5
9.5
7.7
10.8
6.6
15.3
15.5
10.2
8.7
9.9
14.5
10.4
8.4
8.9
13.9
-------
SECTION 14
THE EFFECTS OF "LOW LEVEL S02" EXPOSURE ON SULFUR ACCUMULATION AND
VARIOUS PLANT LIFE RESPONSES OF SOME MAJOR GRASSLAND SPECIES ON THE ZAPS SITES
P. M. Rice, L. H. Pye, R. Boldi, J. O'Loughlin
P. C. Tourangeau, C. C. Gordon
ABSTRACT
Organisms on the ZAPS sites accumulated total sulfur
in a gradient which paralleled ambient S02 concentration.
However, significant edge effects occurred on the treatment
plots. Experimental designs to detect biological responses
should consider this source of variance. Accumulation,
partitioning, and cycling of sulfur was studied in six ^
prairie vegetation species. A peak of sulfur in live
tissues during greenup periods was masked by subsequent
fumigation. Sulfur in plants increased as a function of
ambient S02 concentration and time over the active growth
period. Plants of similar growth habit and phenological
timing accumulated sulfur at similar rates. Species spec-
ific differences in sulfur partitioning were found, A.
dead shoots acting as an apparent sink. Sulfur in roots
of perennial grasses correlated positively with shoot sul-
fur. Sulfur inputed during previous years appeared in
live shoots during subsequent years' growth. This carry
over of sulfur is termed the residual sulfur effect. Data
from two sites with an 80-year fumigation 'history indicated
that the residual sulfur effect causes a cumulative increase
in biologically incorporated sulfur. Rainfall can remove
13 percent of the sulfur held by leaves, but storm size
is biased towards low volume rainfall events that may
actually increase S02 scavenging. Overwintering of shoots
releases 69 percent of their sulfur content. Ground
sampling could not confirm aerially delineated patterns
of S02 drift off the treatment plots. Premature leaf
senescence was associated with increasing S02, while
leaf initiation rates were generally unaffected. In-
creasing variance in fluoride content suggests a dis-
ruption of normal root uptake processes. Seed germination
capacity, speed of germination, and seed weight were de-
pressed on the higher treatment plots in several perennial
494
-------
range grasses. ^The presence of an endomycorrhizal phyco-
mycete in A. sm^th^^ was reported. Population levels of
the beneficial associate declined with S02 treatment
Histological preparation indicates that the normal mor-
phology of fungi was disrupted at low S02 treatment
levels with an alteration of the symbiosis to a potential-
ly pathologic state.
INTRODUCTION
Vegetation Studies
Opinions about the levels of S02 which can damage vegetation are probably
as numerous as published fumigation studies and field studies. Most theories
were derived either from field studies in areas subject to acute S02 plant
damage (such as Duck Town, Tennessee; Sudbury, Ontario; Trail, British
Columbia, and Anaconda, Montana) or from studies of pollution levels and
effects in cities monitored by the National Air Pollution Control Agency
during the 1960s and reported in the EPA S02 criteria document. Sulfur
dioxide effects have also been studied in exacting controlled fumigation
studies by numerous investigators examining the anatomical or physiological
impacts of S02 dosages at various durations on a variety of plant species.
Because the individuals actually conducting field or controlled fumigation
studies have reported diverse and sometimes opposing results, researchers
from federal and state agencies, industries, universities, and private labora-
tories have tried to devise more sophisticated methodologies to determine
the potential and real impacts of S02 upon plant species and/or plant
communities. Current sophistication in controlled S02 fumigation studies is
apparent in the open top field chamber studies and the wind tunnel fumigation
studies by Ashenden and Mansfield (1977).
The EPA-CERL controlled fumigation studies conducted during the last
three years in the Custer National Forest of southeastern Montana represent
the first attempt by researchers to determine S02 effects in an established
grassland ecosystem. This area of Montana is particularly suitable for such
an open field experiment because it is pristine and has received little or no
measurable S02 or fluoride contamination in the past (Northern Cheyenne Tribe,
1976; Gordon et al.9 1976). This study is also of immense importance to the
farming and ranching communities and Indian tribes of southeastern Montana;
during the next decade, southeastern Montana, as well as northern Wyoming,
may become the site of large stationary S02 sources, including coal-fired
power plants and gasification or liquefaction industries.
Currently, there is a tremendous paucity of literature concerning the
potential impacts of S09 and all other phytotoxic gases upon most of the
flora and fauna species of this agricultural land. Even more serious is the
lack of adequate data on the interrelationships between species of this grass-
land; the potential indirect impacts of S02 damage on one or two species will
be difficult to detect or quantify in this relatively short study.
495
-------
While the ZAPS study is the most extended controlled fumigation study
reported in the literature, it represents only a fraction of the time that
field researchers in the United States, Canada, and Europe have spent
attempting to document the impacts of S02 pollution on the ecosystems
surrounding large stationary emissions sources. Furthermore, we believe that
ecosystems are not damaged or destroyed in the first decade of pollution but
rather gradually over a longer period of operation of that source, as in
Anaconda, Montana.
We caution the reader to remember that the impacts and lack of impacts
reported and discussed herein occurred during a very short period of time in
the evolution of this grassland ecosystem. We are further restricted by the
uncertainties inherent to known field methodologies and our own lack of under-
standing of the interrelationships among the species of this ecosystem.
During 1976 and 1977, our ZAPS studies included a substantial amount of
sulfur analyses of plant foliage and root tissues from the different treatment
plots. Because it has long been known that chronic exposure to S0£ fumigation
causes excessive sulfur accumulation in the foliage of plant species, we
hypothesized that the grass, forb, and shrub species fumigated at the
different treatment levels would accumulate different levels of sulfur over
the growing season. While this may seem an easily-satisfied hypothesis, it
was important that it be tested because the baseline sulfur levels of all the
plant species on the ZAPS plots were not known.
Numerous researchers have conducted "long-term" fumigation studies that
did not include determination of pre- and post-fumigation sulfur levels in
the plant tissue (Booth et al., 1976; Bleasdale, 1973; Cocking, 1973; Hill
et al., 1974; Ashenden and Mansfield, 1977; Section 15* etc.). If the
seasonal baseline or normal sulfur concentrations in plant tissues of unfer-
tilized, indigenous species are established before this vegetation is fumi-
gated or impacted by chronic levels of S02, investigators could determine
subsequent sulfur accumulation and any related morphological or physiological
damage. There have never been any studies to determine a possible relation-
ship between excessive sulfur accumulation and vegetative or reproductive
structure damage.
Our studies of vegetation collected at the ZAPS sites, as well as from
our ponderosa pine/skunkbush sites and the EPA exclosure sites on the McRae
and Kluver ranches, indicate that sulfur accumulation can be determined in
plant foliage exposed to chronic S02 pollution episodes. While there are
seasonal variations of sulfur levels in foliage from the pristine lands of
southeastern Montana,this variability should not interfere with the usefulness
of these concentrations as indicators of S02 fumigation or trespass.
We have been studying the possibility that root tissues of perennial
grasses at the ZAPS sites contain residual sulfur. If portions of the sulfur
taken in by the foliage are transported to the root tissue during or after
the growing season, some of this sulfur might be returned to leaf tissues
during the next growing season; biologically-incorporated sulfur may also
continue to increase over long periods of time (five to ten years).
496
-------
Our studies of sulfur in western wheatgrass roots collected on the ZAPS
sites, as well as in Anaconda, Montana, indicate that this residual sulfur
may play an extremely important role in long-term chronic air pollution
impacts. In the spring of 1977, soil from the Anaconda area was transported
to the University of Montana botany gardens, and four species of plants
common on the ZAPS sites were established in this soil. Studies on residual
sulfur in the foliage and roots of these four species will be conducted
during the 1978 growing season and reported in the Fifth Interim Report.
We are continuing our work on viability and germination rates of seeds
collected from the different S02 treatment levels on ZAPS land II. Seed
viability and germination studies of samples collected during the 1977
growing season will commence in May of this year, and the results will be
included in the Fifth Interim Report. Thus far, our survey of the literature
has not revealed any similar studies of fumigated grass and forb species.
During 1976, we established a plot with plant communities similar to
those on the ZAPS sites. This Off Plot Control (OPC) is located about 2 km
from the ZAPS to protect it from any fugitive S02- It was our hypothesis
that if fugitive S02 from the treatment plots was drifting across the ZAPS IA
and IIA plots and impacting the vegetation, data obtained from the OPC would
help us ascertain the impacts of the fugitive gas. Because the grassland
ecosystems on the ZAPS sites were pristine before the commencement of this
fumigation study, we feel that a true comparison between the vegetation fumi-
gated by the different delivery treatments will be difficult to ascertain
when the control plots are also being fumigated.
&
Mychorrhizal Studies
No quantitative analyses of vesicular-arbusicular (VA) or endomycorrhizal
(EDM) populations within native U.S. grasslands have ever been conducted, nor
have the effects of S02 fumigation on endomycorrhizal populations ever been
studied. Reasons for the lack of such investigations are the necessary exper-
tise required and the tedious methodology that must be employed. Such method-
ologies have lagged far behind the increasing importance that is currently
attributed to mycorrhizae (M) and their associated symbionts and hosts.
EDM are ubiquitous in their association with angiosperms, their alliance
including members of the largest and economically most important crop species
belonging to the Gramineae and Leguminosae. Additional phyla known to be
mycorrhizal are Bryophyta (especially Hepaticae), Pteridophyta and Conifer-
ophyta (Ainsworth and Sussman, 1968). Ectomycorrhizae (ECM), differentiated
from EDM by the former's formation of Hartig nets and their failure to pene-
trate hosts intracellularly, are found on most woody angiosperms and gymno-
sperms and gymnosperms such as P^LUA spp. and KcW spp. Endophytes of ECM
typically belong to the class Basidiomycetes, while those of EDM are thought
to belong to class Phycomycetes. A recent monograph (Gerdemann and Trappe,
1973) describes the
*This study was primarily carried out Laurel Pye a graduate student in
the Botany Department at the University of Montana Field studies continuing
through 1978 will be reported in the Fifth Interim Report.
497
-------
taxonomy, occurrence, and distribution of EDM endophytes which, for the most
part, belong to the family Endogonaceae.
The mycorrhizal relationship is a dynamic symbiotic biochemical-
physiological interaction. The presence of mycorrhizae can generally be
assumed because they not only date back to the Devonian but are more often
present on plants than not (Baylis, 1972a, 1974). Although mycorrhizae are
usually considered beneficial and symbiotic, the mycorrhizal relationship has
also been labeled "reciprocally parasitic" (Hacskaylo, 1972) and "potentially
pathogenic" (Harley, 1959). While some have argued that mycorrhizal infes-
tation represents the end product of specialized parasitism (Garrett, 1956),
others reject this idea and maintain that "there seems no need to assume that
such conditions need not only arise from a long period of evolution, or that
parasites must always evolve from avirulence to symbioses" (Bawden, 1957).
Only in the past two decades has the mycorrhizal condition taken on
significance and become a matter of serious scientific investigation. This
increased concern resulted from both the ubiquity of mycorrhizae in natural
habitats and the disturbance of such through man's manipulation of the
environment.
Phosphorous is among the most common and important elements in a plant,
its distribution being always roughly parallel to that of protein. Of equal
importance is the highly reactive, complex, organic, cation-binding compound
phytate, otherwise known as phytic acid or inositol hexaphosphate. It is in
this form that phosphorous is most often found both within plants and the
organic humus layer of soil (Russell, 1973).
Because mycorrhizae can very efficiently transport phosphorous from the
humus layer to the plant, most plants are mycorrhizal. Mycorrhizae have
evolved as an integral part of a system by which a plant secures sufficient
phosphorous, lack of which most often limits plant growth (Baylis, 1972b). In
a detailed review of the literature, Mosse (1973) stated, "results confirm
that mycorrhizal roots take up more phosphate than non-mycorrhizal roots,
that it is translocated to the hosts' shoots . . . and that the striking
effects of inoculation on plant growth and phosphate uptake have been demon-
strated beyond a doubt."
Experiments have shown that mycorrhizal roots are capable of absorbing
3 to 16 times as much available organic phosphorous as non-mycorrhizal roots
(Sanders and Tinker, 1973). Similar results have been reported by Baylis
(1967), Ross (1971), Gerdemann (1964, 1968), Gray and Gerdemann (1969, 1973),
Voigt (1969), Murdoch et al. (1967), Jackson et al. (1972), Sanni (1976a,
1976b), and Sanders et al. (1977). In addition, zinc deficiency symptoms in
peach and stunted growth in citrus have been related to inadequate nutrition
in non-mycorrhizal soils (Gilmore, 1971; Kleinschmidt and Gerdemann, 1972).
Because of the efficiency with which they take up phosphorous and
associated cations, mycorrhizae also stimulate: (1) flower production in
petunia, (2) formation of fruit in strawberry, (3) development of pollen in
maize, and (4) the amount of vascular tissue in all of these plants (Daft
and Okusanya, 1973). Mycorrhizal infection in cotton has also been correlated
498
-------
with earlier flowering and boll maturation (Rich and Bird, 1974) while
infection in tomato has been reported to stimulate ontogeny and to delay
leaf senescence (Daft and Nicolson, 1969). Furthermore, mycorrhizae have been
found to strongly stimulate both growth and nodulation of legumes and the
persistence of anaerobic, nitrogen-fixing bacteria such as Azotobacter and
Clostridium (Richards and Voigt, 1964; Daft and El-Giahmi, 1974; Crush, 1974;
Mosse, 1977). The enhancement of hormone levels by mycorrhizae has been impli-
cated as the cause of many such symptoms. The production of growth-promoting
cytokinins, such as Zeatin and Zeatin riboside, have been demonstrated in the
case of the ECM endophyte Rhizopogon roseolus (Miller, 1967).
Several experimenters have demonstrated that current fertilization
practices, whereby soil fertility levels are greatly augmented with super-
phosphates, have a depressing effect on mycorrhizal levels (Daft and Nicolson,
1966; Ross, 1971; Khan, 1972; Mosse, 1973). In the case of soybeans, for
example, "phosphorous concentration in foliage of mycorrhizal plants at the
lowest phosphate fertilization level was found to be greater than that of non-
mycorrhizal plants at the highest phosphate level" (Ross, 1971). The effect
probably is a disruption of the symbiotic state due to a change in host plant
metabolism rather than a direct inhibition of fungal growth (Mosse, 1973).
The ability of air pollutants, such as SC^, to alter plant metabolism or
disrupt the symbiotic state as exhibited by lichens is well-documented.
Whether S0£ similarly disrupts the symbiotic mycorrhizal state is an important
and yet unanswered question. Before one can consider the impact S02 may have
on mycorrhizae, one must consider those factors, besides phosphorous, which
"naturally" determine infection levels.
Nicolson (1960) has stressed the fact that mycorrhizal infection levels
are influenced primarily by the degree of habitat stability and the amount of
undecomposed organic matter present. He found high levels of infection in
plant communities that were stable but did not have high levels of organic
matter; large amounts of organic matter can stimulate microbial activity
which eventually may damage the endophytes. In a European grassland study,
no consistent change of infection was found to occur with change in sub-surface
geology or soil pH, but highest infection levels occurred in the shallowest
soils (Read et al. , 1976). These findings suggested to the authors that
nutrient levels or water stress might determine levels of infection. The same
authors have also suggested that high infection levels indicate an intensely
competitive situation whereby the nutrient status of an environment is
depleted and the resistance of the host to infection is thus reduced.
Recent experiments have revealed that mycorrhizal infection and root
competition combine to produce a result quite different than the effect of
each factor separately. Trinick (1977) found growth of red clover stimulates
infection in Lupinus cosentvini Gus. Eolous lanatus L. was found to have only
a slight advantage in yield over LoUum perenne L. when singularly subjected
to root competition or mycorrhizal infection, while the combination resulted
considerable depression of Loliwn perenne L. (Fitter, 19/7).
in
Any determination of infection, however, must be reviewed with discre-
tion because conflicting results have been reported. Mejstrik (1972) found
499
-------
that soil factors which reduce host growth, such as soil nutrient levels, also
reduce frequency and intensity of mycorrhizal development; therefore, a host
plant "weakened" by low nutrient levels is not necessarily subject to a higher
level of infection as was suggested earlier. Soil fertility levels in Spain
also had little effect on mycorrhizae populations (Hayman et al., 1976).
In addition, one must take into account experimenters' methodology in
determining root infection levels. Mosse (1973) reported that spore numbers
may or may not be significantly correlated with root infection. Amounts of
external mycelium also cannot always be correlated with root infection levels
(Nicolson, 1960). Finally, one cannot liberally interpret the results of any
"artificial" glasshouse or potculture experiment, unless the ecological or
competitive status of the host in a plant community is accounted for.
Most papers published on sulfur and its effect on fungi describe sulfur
as a fungicide, a fact recorded by early classical writers (Ainsworth and
Sussman, 1965). Although sulfur, in the form of elemental sulfur or lime sul-
fur (calcium polysulfide and calcium thiosulfate) is fatal to numerous fungal
species, particularly powdery mildews, it is fatal only to a limited range of
the higher plants (Marten, 1959; Ainsworth and S-ussman, 1965).
Experiments have been conducted in which sulfur was supplied as magnesium
sulfate, dilute ^S-^o^ and S^o^" to potted and inoculated host plants.
Results indicated the following: (1) In the case of red clover (Trifo'i'lwn
pratense L.) and maize (Zea mays L.), mycorrhizal roots take up sulfur more
efficiently than non-mycorrhizal roots (Gray and Gerdemann, 1973), and (2) in
the case of P-inus radiata ECM, "the bulk of sulfur destined for the shoot of
the host is not metabolized by the fungus but has a more direct pathway
through the mycelium from ambient solution to host roots, whereupon it is
transported to host shoots and then progressively accumulated by shoot apices
from older leaves" (Biddulph et al. , 1958; Morrison, 1962). Heagle (1973)
noted a study by Sobotka (1964) in which the impact of SC>2 on mycorrhizae was
examined under field conditions. He found the ECM associated with spruce to
be abnormal in an S02~polluted area.
Variable responses to SC>2 have been recorded in several pathogenic fungi
(Hibben, 1966; Couey, 1965). It is thought, however, that pollutants such as
SC>2 are causal agents encouraging the spread of fungal disease in forests and
crops (Grywacz, 1971; Heagle, 1973; Treshow, 1968, 1975). If air pollutants
can bring about any one of the following conditions: (1) Change in external-
internal host biochemistry; (2) alternation in quantity or quality of host or
fungal exudates, or (3) cellular or organelle structural variation, then
behavior modification, e.g., host recognition of pathogens or symbionts, is
likely to occur.
Both ECM and EDM are thought to play a considerable role in disease
deterrence (Zak, 1964; Harley, 1959; Marx, 1972; Slankis, 1974). Possible
resistance factors are physical barriers created by the presence of mycor-
rhizae, exudates produced in conjunction with the symbiotic relationship, or
merely the healthier state imparted by the relationship. The means and
extent to which mycorrhizae serve in such a protective capacity are not yet
clear. A recent study of the Cotton Stunt Disease Complex showed that damage
500
-------
to cotton by phytopathogenic nematodes is magnified when the symbiotic mycor-
rhizal state is impaired (Rich and Bird, 1974; Bird et al. , 1974).
The fungal endophyte which forms VA mycorrhizae has been identified in
most cases as one of several species belonging to the family Endogonaceae
(Mosse, 1973). All phases of their growth are quite unique and distinct in
their appearance^from other fungal infection types that might occur within a
grass root. It is advisable in any case to examine specimens under both a
binocular and light microscope to note the continuity which should occur
between external and internal phases because profuse connections of this sort
are not readily formed by Pythiwn spp. or other obligate parasites whose
growth is normally restricted in soil. A few species, such as Pythium spp.,
are known to form VA type infections in rare instances (Ainsworth and Sussman,
1968).
It is also possible to discern the presence of mycorrhizae on grass roots
because of their conspicuous sandy encasements. Such encasements often give
roots a typical yellowish brown felty appearance. Nicolson (1959) and Harley
(1959) published detailed descriptions of the grass endophyte; these descrip-
tions are summarized in the following account.
Exterior hyphae are of two types. The first type is thick-walled with a
diameter of 20y to 27y, aseptate, multinucleate, and filled with a dense
cytoplasm and conspicuous oil globules. Such hyphae often run for a consid-
erable distance along a root's length, branching at times to bear exterior
vesicles or to pass into the soil or host root hairs. Branching from the
latter are thin-walled hyphae with a diameter of 3y to 5y. These hyphae are
considered to be ephemeral because after a period of active growth they become
septate or shriveled and are easily lost from the main hyphae. This process
causes many angular protrusions in the main hyphae. Several authors have
attributed this "response" of the thin-walled hyphae to be "an inherent
capability elicited when the hyphae are mechanically wounded or exposed to
other types of deleterious or degenerative processes" (Gerdemann, 1955;
Kinden and Brown, 1975).
Morley and Mosse (1976) described the appearance of abnormal hyphae.
Such hyphae are characterized by "abortive" entry points, masses of irregular,
vesicle-like swellings around functional entry points and short, distorted
swollen or finger-like hyphae arising at the entry point from exceptionally
large, irregularly-shaped hyphae.
Development of the endophyte is most profuse in the inner cortical area.
Although one author observed what he thought to be mycorrhizae in the endo-
dermis and pericycle (Shterenberg and Kostyak, 1967), most workers agree that
mycorrhizae are never found in the endodermis, pericycle and enclosed vascular
tissue, nor in the meristimatic region of actively growing root tips.
Kinden and Brown (1975) suggested that the actual penetration of a host
cell wall by the endophyte is more than a strictly mechanical process and
that it may well involve some type of enzyme degradation because cortical
cells are neither ruptured nor damaged by the endophyte's presence Their
electron microscopy studies showed that a host ™^** ™??*l *° th
invading endophyte by depositing wall material which does not reduce the
activity of the endophyte but confines or localizes it.
501
-------
Penetration hyphae begin to disintegrate with the formation of arbuscules
in inner cortical cells. Arbuscules are a highly branched terminal structure
and are considered to be a complex haustorium (Cox and Sanders, 1974). When
present, arbuscules appear as a dense granular mass in the lumen of a cortical
cell. Arbuscular formation is usually greatest when the host is still in a
vegetative state (Saif, 1977). Arbuscules are not permanent structures and
invariably undergo disintegration or "digestion" by the host. An increase in
host cytoplasmic volume and numbers of mitochondria and ribosomes has been
shown to occur conjunctively with the deterioration process (Kinden and Brown,
1975). The authors suggested that this process releases substantial quantities
of mineral nutrients which are absorbed by the host. Cox and Tinker (1976),
however, think this is unlikely and that nutrient release to the host is
accomplished by transfer across living fungal-host membranes.
Vesicle formation takes place after arbuscular appearance, but before
their disintegration. Both internal and external vesicles can occur; they
are considered to be analogous (Butler, 1939), although this is not unequiv-
ocally accepted (Mosse, 1973). External vesicles are borne either terminally
or intercalary on hyphae and exhibit great variation in size and shape.
Vesicle walls are two-layered, and the smooth, thick inner wall is surrounded
by a thin, rough outer wall. Although highly vacuolate when they first appear,
vesicles become increasingly dense and laden with oil globules as they age.
Vesicles are thought to function as both food storage organs and infec-
tious chlamydospores (Butler, 1939; Nicolson, 1959). A recent ultrastructural
study suggests that they function in either capacity (Kinden and Brown, 1975).
Such vesicles are the only type of spore known for mycorrhizae in grass roots
(Gerdemann and Trappe, 1973; Nicolson, 1959). External vesicles with attached
hyphae may appear singly or in aggregates.
Although the literature does not mention at what stage in the host's
development external vesicles are formed, internal vesicles are known to
increase in number with the onset of flowering or fruiting (Saif, 1977).
Formation of interior vesicles is considered to be a "constant" or mature
state of endophyte development because the numbers of penetration hyphae
become greatly reduced with their appearance. In grasses, interior vesicles
can be released into the soil as spores after roots become senescent and the
cortex is sloughed off. In some cases, the formation of interior vesicles is
so profuse that the root becomes disrupted (Gerdemann and Trappe, 1973).
Whether such disruptions are normal is questionable. Of additional interest
is the finding that vesicles alone were produced on low productivity soils
supporting cotton, while vesicle, arbuscule, and spore production all took
place on similar high productivity soils (Bird et at., 1974).
Both cytological and physiological changes induced in the host by the
presence of mycorrhizae have been described. Gross morphological changes
induced in the root system, such as ECM-induced differentiation into short
infected and long roots in Pinus spp., are not obvious in grass roots. Baylis
(1972a, 1974) has discussed the possible adaptive strategies of various root
systems in relation to EDM infection. He has concluded that fatter roots with
a persistent renewable cortex are much more dependent on mycorrhizae than
those with highly reticulate, proteoid, or hairy roots or those with exception-
ally abundant and long root hairs.
502
-------
One can hypothesize the following: If a plant cannot maintain the mycor-
rhizal relationship or no longer needs the increased absorptive capacities
for water and minerals which mycorrhizae provide, obvious environmental-
physiological changes must have taken place to offset the loss of the endo-
phyte. In the root system of a plant, such changes either denote that the
plant has found another means to make up for the loss of the endophyte through
possible variations in root structure or growth rate, or the plant no longer
has to or is capable of competing with other community associates for
nutrients, that is, that the community has become stabilized or is faced with
drastic successional decline.
The purpose of the mycorrhizae investigation was first to ascertain the
presence or absence of endomycorrhizae with Agropyron smithi-i Rydb. on the
ZAPS sites. The very low S02 dosages needed to disrupt the symbiotic state,
as exhibited by lichens and the known sensitivity of many fungi to sulfur have
been discussed. In light of this sensitivity, it was further hypothesized
that the symbiotic mycorrhizal state would also be disrupted at very low S02
dosage levels and that a downward trend in mycorrhizal populations would
therefore be evident across the ZAPS plots. Conversely, various fumigation
studies have reported that S02 stimulates photosynthesis and plant yield. It
was thus conceivable that low S02 dosages might also have an initial invigor-
ating effect on mycorrhizal populations.
MATERIALS AND METHODS
Sulfur Accumulation in Plants
Collection, sample preparation, and chemical analyses methods employed
in 1977 were similar to those used in 1976 (Third Interim Report — here-
after TIR) , with the following modifications in collection procedures:
(1) An exclosure 2 km northeast of ZAPS I was chosen as a control plot
(Off Plot Control or OPC) to avoid the effects of any fugitive S02.
An area within the exclosure, with a vegetation community similar
to that on the ZAPS sites, was divided into ten marked subplots.
Some control sampling had been done in 1976 about 1.5 km southwest
of ZAPS I, but this area was not enclosed, and sample size and
frequency of sampling were limited.
(2) Subplot samples were kept separate unless the sample volume was so
small as to necessitate a composite of vegetation from a particular
treatment plot. This generally resulted in ten samples per tissue
per species per treatment plot and allowed more detailed analysis
of variability both within a treatment plot (between subplots) and
between treatment plots (A, B, C, D, OPC).
(3) Several 1976 collections were separated by subplot. Plant tissues
from perimeter subplots had lower sulfur levels than interior
samples. Given our limited sampling resources, we decided to elimi-
nate the suspected edge effect on data variability by sampling only
interior subplots. This reduced the number of possible subplots
per treatment from 86 to 44. For the division of a ZAPS plot into
subplots, refer to Figure 14.41, which is presented later in this
section.
503
-------
(4) Tragopogon dubius was collected only once in 1976 (TIR) . This
species exhibited unusually high sulfur levels in contrast to the
other species being studied. Because of this, T. dubius was sampled
on a regular basis during 1977.
Data analyses of sulfur variates are facilitated by log^o transformations,
These transformations help normalize the data and improve homogeneity of
variances, allowing comparison of treatment plots by t and F tests. Screening
data for statistical outliers (Grubbs, 1969; Dixon and Massey, 1957) also
improved homoscedasticity. An observation was rejected from plot comparison
only if it met all of the following criteria: (1) Preliminary screening for
equal variance (Bartlett's chi-square) revealed heteroscedasticity; (2) the
suspected value exceeded that suggested by the Dixon Criteria at the 95%
significance level; (3) repeated chemical analyses established the veracity of
the first chemical determination, and (4) the subplot exhibiting the unusual
datum point demonstrated the same statistical aberration during at least one
other collection period. The fourth criterion insured that the abnormality
was not a sampling error but did, in fact, exist on the treatment plots. An
example of the effects of removing outlying sulfur observations on mean values
and 95% confidence intervals for total sulfur is presented in Appendix 14.1.
Linear regression proved useful in analyzing the sulfur accumulation
data for the period after the spring greenup and through the growing season
(TIR) . The sulfur accumulation curves over the entire period of investigation
suggest a polynomial of at least three degrees when there is no fall greenup
(1976) and minimally four degrees when a fall greenup is observed (1977). To
ignore quadratic and higher order components in S0£ impact models will lead
only to a gross oversimplification of the system and distort the accuracy of
predictions. To date (March, 1978), we have made no attempt to ascertain the
adequacy of our data base to describe the curvilinear relationships. We hope
to do this in the future and thereafter make any necessary modifications in
our collection procedures if sampling opportunities permit. Accordingly, no
detailed analysis through time is presented herein, but the pattern of sulfur
accumulation is portrayed as a review of graphs.
Washing Experiments
Agropyron smith-Li, and KoeleTia cvistata samples collected in mid-
September, 1976, on ZAPS IID were randomly split to determine both the sulfur
content of plant material after a wash, simulating a heavy rainfall event and
the sulfur leached from the plant material due to overwintering. The
unprocessed plant part's were placed in a screened jar and rinsed with rapidly
flowing tap water for three minutes to produce the effects of an intense
individual rainstorm. Overwintering was simulated by washing the plant in
distilled water for four days at room temperature. The water in the soaking
experiment was changed after the second day. After washing or soaking, the
material was dried and ground as usual for sulfur analysis. The data were
examined with a paired-t test.
504
-------
Fluoride Uptake
Live and dead tissue of both A. smithii and K. cvistata collected from
ZAPS HA and IID in September, 1976, were analyzed for fluoride content.
Methods were detailed in the TIR. The variance ratios were examined by the
F test, and the equality of the mean fluoride levels was compared by an
approximate F test based on synthetic degrees of freedom (Snedecor, 1956).
The 1977 vegetative phenology study was similar to our 1976 study (TIR),
with the following modifications: (1) To reduce edge effects, the perimeter
subplots were not used; (2) the number of subplots with tagged plants was
increased from 10 to 20, thus expanding the number of marked plants per treat-
ment plot from 50 to 100, and (3) the Off Plot Control (OPC) was included in
the study. There were nine observation periods from early May through late
September. A. smifhii continued to be the only species scored. Tagged plants
were located at a minimum distance from the delivery system pipes of one meter
and a minimum of two meters from the nearest gas release point.
Seed Work
For the purpose of this study, germination is defined as the ability of
the seed to produce two millimeters of radicle or epicotyl elongation under
growth chamber conditions considered to be optimal for the species. This is
to be distinguished from viability, which is the existence of a seed embryo
in which all structures essential for the establishment of a seedling are
alive and intact. Viability is determined by treating the seed with a vital
stain (2, 3, 5-triphenyl tetrazolium chloride) to color the respiring tissues
of the embryo. If the hypocotyl tip of a tap-rooted species does not stain,
the embryo is not considered viable. However, a species capable of developing
seminal roots can still establish a seedling even if the hypocotyl tip is
dead. Viability then is an indication of the potential for successful seed-
ling germination and does not include consideration of conditions for breaking
dormancy or a favorable germination environment.
Seeds of four grasses (Agropyron smifhii3 KoeleTia oristata3 Poa
sandbergii; and Stipa viridulcC) and a composite forb (Tragopogon dubius) were
collected from both ZAPS sites during 1976. A. smithii and T. dubius were
also collected from the Off Plot Control. Seed heads were clipped from a
minimum of ten plants per treatment plot. The seed heads from each treatment
plot were combined to form a single sample. The material was stored for
approximately one year to allow after-ripening. Seeds were then hand-stripped
from the heads.
Replicates for germination tests were obtained on a weight basis inde-
pendent of the number of seeds. This technique serves to reduce sorting bias
in obtaining subsamples and standardizes the total tissue mass in the trial.
When the total weight of seeds from any treatment plot was limited, the avail-
able material was equally apportioned among four replicates. When larger
seed volumes were available, enough seed to obtain a standard weight was
randomly selected from the sample. In both cases, the total number of seeds
per replicate was determined after weighing out the sample. The data on
average seed weights were also derived from these subsamples. Replicate
505
-------
subsamples for tetrazolium viability tests were composed of fixed numbers of
seeds. These seeds were removed from a grid table at randomly pre-selected
intersections. Five replicates per treatment plot were used in the tetra-
zolium tests.
Germination tests were to proceed for 30- and 45-day periods, depending
on species. These tests were conducted in growth chambers under moisture and
temperature regimes which encourage bacterial and fungal growth. Two methods
of restricting this fungal growth were pre-tested. Seeds were twice washed
with a solution of Clorox and distilled water plus a wetting agent (12 cc
Clorox, 500 cc distilled water, 3 drops Tween 80). A second method (Eddleman,
1977a) consisted of dry dusting the seeds with 50% Ortho Captan (N-[trichlor-
methyll]thio 4-Cyclohexene-l,2,-dicarboximide) and using an Ortho solution
(two teaspoons per liter water) as the water supply for germination. In both
cases, the petri dishes and cellulose pads which supported the seeds were
autoclaved for 15 minutes at 15 pounds pressure. The Ortho treatment proved
to be more effective in reducing fungal growth.
Seed storage requirements, stratification, and optimal germination condi-
tions tend to be species specific. The work of Eddleman (1977a, 1977b) and
Eddleman and Doescher (1977) provided the basis for selection of conditions
and techniques suitable for germination testing. The procedures were modi-
fied for our particular study objectives. Basic methodologies for tetrazolium
testing were derived from the Association of Official Seed Analysts (1970).
Specific staining procedures for the species of interest were derived by pre-
trial experimentation.
After Ortho dusting, all seeds in a replicate weight were transferred to
the sterilized cellulose pads and petri dishes under a laminar flow hood.
Replicates were randomly assigned to a position in the growth chamber, then
rotated daily after the germination counts were made. The number of seeds
germinating each day was recorded, and at the end of the test period the
number of ungerminated seeds was counted.
Basic data consisted of the number of seeds germinating on a particular
day. The total number germinating during the test period was divided by the
total number of seeds per replicate. Their percentages were subjected to
arcsine transformation and treated by anova and Duncan's New Multiple Range
Test (Duncan, 1955). Results are presented as untransformed percentages.
Seed weights were analyzed by anova and Duncan's NMRT. Viability results were
treated similarly to the percent germination. The rate of germination was
analyzed as relative cumulative frequencies. The number of seeds germinating
on any day was divided by the total number of seeds germinating and the
result added to that from all previous days. The resultant relative cumula-
tive frequency distributions were then compared by the Smirnov Test (Smirnov,
1939). The appropriate .95 quantiles were computed based on the asymptotic
distribution for unequal n's:
m + n
W
.95 ~ mn
as suggested by Conover (1971). The rate of germination was integrated to a
single number, the coefficient of rate of germination (CRG):
506
-------
n
where gn is the accumulated germination on a given day minus the germination
percent on the previous day (g(n_n) and divided by the number of days of
incubation (n) (Maguire, 1962). The more rapid the "germination," the greater
the CRG. This was modified in that g and g/n_n were based on only those
seeds which did germinate. Thus, assessment of germination speed was done
independently of total germination success, as was the relative cumulative
frequency distribution analyses. Days to 50% of final germination were also
computed to compare germination speed of ZAPS seeds to those reported by
Eddleman (1977b) as typical of southeastern Montana seed sources. Finally,
the relative frequency distributions based on percent of total germination
were graphed to display the day of peak germination and the pattern of germi-
nation timing.
Mycorrhizal Studies
In the spring of 1977, a paper entitled "Colorimetric Quantification of
Vesicular-Arbuscular Mycorrhizal Infection in Onion," by Becker and Gerdemann,
was published. The article presented an abbreviated method for quantifying
EDM by using a spectrophotometer to measure the yellow coloration imparted to
infected onion roots.
Spectrophotometer absorbance readings of the pigment, extracted from the
roots with hot water were found to be highly correlated at 400 nm with
percentage of yellow roots by weight. Percentage of yellow roots by weight
also correlated well with length or, similarly, percentage of infected roots.
Becker and Gerdemann suggested that the extraction method could be substituted
for determination of percent infection by clearing and staining.
While uninfected onion roots are typically white, the exact nature of
the yellow pigment, other than its tendency to break down with exposure to
light, remains unknown. Our investigation included an attempt to determine
whether such a pigment occurs in infected roots of Agropyron smlthO, and
whether Becker and Gerdemannfs method could be employed on vegetation from
the ZAPS sites.
In the field, roots of A. smlfhii were not noticeably yellow, especially
when compared to those of Koele^ia erista-ta, although some appeared to be
much more white or brown than others. K. OTistata roots were found to be
mycorrhizal, but A. smithii roots were used for this investigation because a
larger percentage of the young active roots of this species were thought to
be near the soil surface due to its rhizomatous habit.
Collections of whole plants from the ZAPS sites were made twice during
the summer of 1977. To assure an adequate sample size, at least .5 g fresh
weight of A. smithii were collected from each of the 90 ZAPS and OPC plots.
Each of these root samples were separated from plants whose leaves and
remaining roots were later analyzed for total sulfur content. In the labora-
tory, the roots were washed to remove soil, debris, and foreign and noticeably
dead or decaying roots. Roots were blotted dry and weighed into .5 g samples
507
-------
immediately after washing. Samples were then processed in an autoclave at
121°C for 30 minutes to obtain a hot water extract.
After absorbance readings of root samples were completed, root infection
was once again assessed by a modification of Newman's point intersection
method as done by Sparling and Tinker (1975) and to some extent by Nicolson
(1960). Such a method consists of placing the same .5 g root sample, now
cleared by KOH and stained with trypan blue in lactophenol, in a petri dish
at ten randomly chosen fields of vision under a binocular scope. At each
field of vision, the ratio of mycorrhizal to non-mycorrhizal roots inter-
sected by a rotated ocular graticule is then determined.
Data obtained from the determination of percentage of infected 'roots
exhibited a considerable amount of variation within individual ZAPS plots.
In most cases, assumptions of analysis of variance could not be met, and non-
parametric methods were utilized instead. Whether a difference in infection
levels existed between the plots was determined by the Kruskal-Wallis test.
Further pairwise comparisons between each of the treatment plots were made
with the Wilcoxon two-sample test.
RESULTS
Sulfur Accumulation in Plants
The pattern of sulfur accumulation from April through October, 1976, is
portrayed in Figures 14.1 through 14.20 for Agropyron smith-Li., Koeleria
oTistata3 Aohill^ea mLllefoli-wn^ Artemisia frig-ida, St-ipa vim-duta^ and
Ar-istida longiseta. The plotted values represent arithmetic means, and the
data are tabulated in Appendix 14.2.
The spring greenup exhibited an initial peak in sulfur content. This
was particularly evident on the A and B plots where accumulated sulfur from
subsequent fumigation at the lower ambient concentrations did not mask the
greenup. Nutrient levels were relatively high compared to biomass in spring
grass. Rapid increase of aboveground tissue weight then led to relatively
less sulfur. Under continued fumigation, sulfur levels increased until mid-
July and then began to decline as growth ceased. Although fall greenups are
normal in prairie regions when moisture is adequate, this did not occur in 1976,
Sulfur introduced into ecosystems may continue to cycle in that system
either by storage in plant tissues or by availability in the soil system.
The buildup of biologically available sulfur may be small from any one year
to the next. However, if input is intense, or of low level but long duration,
a detrimental increase could be expected to occur. Sulfur initially intro-
duced by fumigation and carried over into live tissue in subsequent years
will be defined as residual sulfur.
The first collection of live plant material in 1976 on ZAPS I was made
after one year of fumigation (1975) but before the 1976 fumigation began.
One might expect to see the greenup sulfur levels to be the highest on ZAPS
ID and lower on IA. This "residual sulfur" trend was exhibited by A. smithii,
A. millefoliwn3 and A. frig-ida but was reversed in K. eristata.
508
-------
Un
O
5000
4000-
3000
2000
1500
i
; 1000
800
600
400
90 120 150 180 210 240 270 300
JULIAN DATE
Figure 14.1. Average 1976 sulfur levels in
live A. smithii from ZAPS I.
5000-1
4000
3000
oc
^ 2000
ID
^ 1500
5
Q. 1000
°" 800
600
90 120 150 180 210 240 270 300
JULIAN DATE
Figure 14.3. Average 1976 sulfur levels in
live A. smithii from ZAPS II.
*»
5000
4000-
3000
i
2000
1500
1000
800
600
400
90 120 150 180 210 240 270 300
JULIAN DATE
Figure 14.2. Average 1976 sulfur levels in
dead A. smithii from ZAPS I.
5000
4000-
3000-
2000
1500
1000-
800 :
600
400-
/V-o
/'?'•
/ / ^^~~~ ^*-* - A
'/ ^"'
JULIAN DATE
90 120 150 180 210 240 270 300
Figure 14.4. Average 1976 sulfur levels in
dead A. smithii from ZAPS II.
-------
5000
4000
3000
oc
§2000
w 1500
£ 1000
800
600
400
90 120 150 180 210 240 270 300
JULIAN DATE
Figure 14.5. Average 1976 sulfur levels in
live K, cristate* from ZAPS I.
5OOO
4000
30CX>|
o:
GJ2000
g 1500
Q. 1000
°- 800
600
400
90 120 150 180 210 240 270 300
JULIAN DATE
Figure 14.7 Average 1976 sulfur levels in
live K. cristata from ZAPS II.
4000i
3000
-------
5000
4000
3000
a:
^2000
« 1500
5
a- 1000
CL
800
600
400
B
90 120 150 180 210 240 270 300
JULIAN DATE
6000
5000
4000
3000
j2000
^1500
a. 1000
800
600
5001
B
90 120 150 180 210 240 270 300
JULIAN DATE
Figure 14.9. Average 1976 sulfur levels in
live A. m-ille folium from ZAPS I
6OOO
5000
4OOO
30OO
£2000
^1500
1000
800
600
50O
Figure 14.10. Average 1976 sulfur levels in
dead A. millefolium from ZAPS I
5OOO!
4OOO
30OO
a:
2 2000
_i
^ 1500
| IOOO
800
600
500
90 120 150 180 2K> 240 270 300
JULIAN DATE
90 120 ISO BO 210 24O 270 3OO
JULIAN DATE
Figure 14.11. Average 1976 sulfur levels in
live A. millefolium from ZAPS II
Figure 14.12. Average 1976 sulfur levels in
dead A. millefol-iwri from ZAPS II
-------
Ui
M
N3
6000
5000
4000
3000
o:
§2000
5> 1500'
1000
800
600-
90 120 150 180 210 240 270 300
JULIAN DATE
Figure 14.13. Average 1976 sulfur levels in
live A. frigida from ZAPS I.
5000
4000
§3000
u.
32000
5 1500
1000
800
90 120 ISO BO 210 24O 270 3OO
JULIAN DATE
5000i
4000
3000
cc
^2000
£1000
800
600J
90 120 150 180 210 240 270 300
JULIAN DATE
Figure 14.14. Average 1976 sulfur levels in
dead A. frigida from ZAPS I.
6000
5000
4000
^2000
0>
1500
1000
800
600
/\X'
90 120 150 180 210 240 270 300
JULIAN DATE
Figure 14.15. Average 1976 sulfur levels in
live A. frigida from ZAPS II.
Figure 14.16. Average 1976 sulfur levels in
dead A. frigida from ZAPS II.
-------
Ul
M
OJ
5000-
400O
3000-
QC.
22CKKH
w 1500 ^
g- 1000
800
600
90 120
150 180 210
JULIAN DATE
240 270 300
Figure 14.17. Average 1976 sulfur levels in
live S. viriduta from ZAPS II,
300CH
ac
§
1500
1000
800
600
120 150 180 210
JULIAN DATE
240 270 300
4000-
3000
o:
22000
_j
5 isoo
1000
800
600
400-
90 120 150 180 210 240 270 30O
JULIAN DATE
Figure 14.18. Average 1976 sulfur levels in
dead 5. viridula from ZAPS II.
400CH
3000
1500 ]
a: 1000
CL
800
600
400
90 120 150 180 210 240 270 300
JULIAN DATE
Figure 14.19. Average 1976 sulfur levels in
live A. longiseta from ZAPS I
Figure 14.20. Average 1976 sulfur levels in
dead A. longiseta from ZAPS I,
-------
Sulfur determination at the initiation of fumigation in 1977 provides
some additional data (Figures 14.21 and 14.22). ZAPS II now has been fumi-
gated for two years. A. smifhii- exhibits residual sulfur on both ZAPS I and
II (chemical analyses of other species have not been completed). These rela
tive levels are summarized as ranks in Table i4.1 (1 being the lowest sulfur
content; 4 the highest) for all cases applicable to testing the hypothesis.
An analysis by Friedman's two-way anova yields: P = .136. K. cr-istata data
runs counter to the trend and thus reduces the x2 (chi-square) value.
TABLE 14.1. RESIDUAL SULFUR BUILDUP (FRIEDMAN'S TEST)
Species
X2r = 5.55
Plot
Site
Year
B
IR. = 9.5 15
df = 3
D
A.
A.
A.
K.
A.
A.
smisfhi-i
smith-ii,
sm-itki-i
cristata
milslefolium
frig-ida
I
I
II
I
I
I
1976
1977
1977
1976
1976
1976
1.5
1
1
4
1
1
2
3
2
3
3
2
1.5
2
3
1
2
3
4
4
4
2
4
4
12.5 22
P = .136
The collection of multiple subplot samples in 1977 allowed 95% confidence
limits to be set for the various collections. Examination of collection 21
(made at the initiation of fumigation) reveals that samples from all ZAPS
plots had significantly higher sulfur levels (a = .05) than samples from the
OPC and that vegetation from both ID and IID displayed significantly higher
concentrations than samples from the other plots (Figure 14.27). These data
support the concept of residual sulfur, at least in the case of A. smith-ii,.
The recently dead tissue of both A. smlth-ii. and A. mille folium contained
more sulfur than the live on B, C, and D plots (Figures 14.2, 14.4, 14.10,
and 14.12). Dead tissues of K. cristate^ A. frigida, A. longiseta, and
S. viridula generally contained less sulfur than the live tissues.
The 1977 collection will allow statistical analyses of those observa-
tions. The partitioning of sulfur (or any element) in live and dead tissues
is of interest in the following contexts: (1) Leaf senescence often is pre-
ceeded by translocation of nutrients to other plant tissues; (2) compartmen-
talization of toxins, particularly in tissues about to be shed, is a possible
detoxification strategy; (3) older tissues can be expected both to have
received higher dosages and to senesce first, and (4) sulfur deposited in
"dead" tissues becomes an input source to other compartments (decomposers,
grazers, soil) through biological breakdown and physical leaching (see
Washington Experiments).
514
-------
4000
3000
ct
1500
1000
800
600
5000
4000
3000
90 120 150 180 210 240 270 300
JULIAN DATE
Figure 14.21. Average 1977 sulfur levels in
live A. smithii from ZAPS I.
A. smithii AND K. cristate LIVE
a:
3
2 1500
2
a. 1000-
°" 800
600
400
90 120 150 180 210 240 270 300
JULIAN DATE
Figure 14.22. Average 1977 sulfur levels in
live A. smithii from ZAPS II.
Ln
I—1
Ui
3000-
^
$
^J
«^j
{/\
2000-
ft
ft
1000-
200 J
95 % CONFIDENCE LIMITS j
LOG TRANSFORMATION j j
j | 4000-
A smithii — - -T -j-
! :
K.cristata-- ip 1
IO : j
i
ID -I
3000-
IB " IID §
! , •• k
IT IIB T ^
1 ! , : nc OPC. 2000-
IA "A If i ^
T^ T i L ^
1000-
'
600-
Figure 14.23. Sulfur levels in live 200"
A. smithii AND K. cris
95% CONFIDENCE LIMIT
LOG TRANSFORMATIO
tata DEAD
S -
N
A. smithii —
K.cristata
1C
IB
IA II A
j \
~ 4-
IIB
' 1
- 1 i
j
:
ID
I
.
T IID
O.PC.
i
|
Ti
:
A. smithii and K. cristata
from both ZAPS in 1976.
Figure 14.24. Sulfur levels in dead
A. smithii and K. cristata
from both ZAPS in 1976.
-------
The leaves of live A. smithii and K. QTistata seemed to contain similar
amounts of sulfur (Figure 14.23) on six of the nine plots in mid-September,
1976. K. eristata contained less sulfur on the OPC, IA, and 1C plots. An
examination of sulfur levels throughout the 1976 season suggests that on the
B, C, and D plots (Figures 14.1 and 14.5; Figures 14.3 and 14.7), the two
species had similar sulfur content and that the depression of K. ovistata on
1C was due to sampling variability. K. oristata from both A plots had less
sulfur during most of the year than A. smithii.
Although the live tissues of K. oristata and A. smithii exhibited similar
sulfur levels, the dead leaves of K. ovistata contained less sulfur than those
of A. smithii (Figure 14.24). It is also of interest to note that the sulfur
content of dead A. smithii on IID was greatly elevated.
Across treatment plots (A, B, C, D) and within sites (I, II), the sulfur
accumulation tended to differ significantly (Table 14.2), but this was not
invariably the case. Across-site comparisons of purportedly similar or
dissimilar treatments do not always meet expectations of sulfur accumulated.
As an example, compare live tissue of IB and IIB or IB and IIC (Figure 14.23).
This suggests that the a priori combining of other treatment results from the
two sites may not always be desirable, as this assumes equal dosages received
by the plant canopy.
TABLE 14.2. SULFUR ACCUMULATION IN MID-SEPTEMBER, 1976 (COLLECTION 9)
Plot
Species
Material
Site
B
D
A.
A.
A.
A.
A.
A.
K.
K.
K.
K.
K.
K.
smithii
smithii
smltln^
smith-Li
smithii
smithii
cristata
cvistata
cristata
oristata
cristata
cristata
Live
Live
Dead
Dead
Roots
Roots
Live
Live
Dead
Dead
Roots
Roots
I
II
I
II
I
II
I
II
I
II
I
II
731
735
490
814
728a*
719a
568
790
581
502
756ab
729a
1538
1122
1549
1429
733a
773ab
1524a
1044
1286a
903
721a
772a
2143
1820
1961
2505
718a
786b
1552a
1731
1244a
1956
828b
822a
3059
2547
2639
4068
827
866
3150
3101
2115
2467
966
927
*Means sharing the same letter do not differ significantly (a = .05);
Duncan's Multiple Range Test, Log-^Q transformation applied.
Belowground sulfur levels in both K. GTistata and A. smithii increased
with the intensity of fumigation (Table 14.2). The ratio of increase across
the plots was much less than seen in tops during these -first few years of
fumigation. Higher sulfur levels in roots in the fall on higher fumigation
516
-------
plots are one possible source of the "residual sulfur" carried into the subse-
quent growing season.
Root sulfur levels tended to be similar for both species, but K.
were somewhat more variable. Also, on 1C and ID, sulfur concentrations in
K. eristata were significantly elevated relative to A. smithii (Figure 14.25).
The accumulation curves for live A. smithii, in 1977 are presented in
Figures 14.21 and 14.22. The spring peak is evident on the A and B plots but,
again, masked by continuing fumigation on the C and D plots. The sulfur
content of the grass from the C and D plots increased through the first half
of the fumigation period but decreased or remained static on the A and B plots
This is an interesting contrast to the pattern of accumulation in 1976 on the
B plots and reflects the limited soil moisture in the spring. The rate of
change also decreased on the C and D plots in 1977, although the peak values
were only slightly depressed. A major and consistent difference was found on
the A plots where the levels were elevated over those observed in 1976. A
fall greenup occurred in 1977, with a resultant relative increase in live
tissue sulfur. This was evident on the OPC, IA, and IIA plots (Figure 14.26)
when contrasted to the previous collection period (late October vs. late
September). The means of samples from these plots exceeded 1,500 ppm, levels
which were not seen except during the spring greenup.
The 95% confidence limits for sulfur levels in A. smithi-i throughout the
1977 fumigation period are portrayed in Figures 14.27 through 14.36. Data
are tabulated in Appendix 14.3. Concentrations in vegetation from ZAPS II
were often higher than in samples from corresponding treatments on ZAPS I
through mid- July, but they were similar later in the season. Differences
were usually significant across the plots.
Root sulfur levels in 1977 also tended to rise with increasing levels of
fumigation treatment, but unanticipated shifts also were observed (Figures
14.37 through 14.39). The IIB A. smithi-i roots had elevated sulfur levels
relative to samples from the other low and medium plots. Sulfur concentra-
tions in the 1C and ID mid- July collections seem particularly depressed
relative to other plots.
The root sulfur levels in late April (collection 21), mid- July
(collection 26), and mid-September (collection 29) are contrasted in Figure
14.40. The pattern appears to be one of decreasing sulfur levels, with the
exception of samples from 1C and ID which showed a sharper decline in mid-
July. The smallest change was observed on the OPC. In spite of these treat-
ment plot irregularities, significant correlation was observed between the
sulfur content of live tops and their roots. In the mid-July collection, 88
samples from the nine treatment plots gave a Spearman's Rank Correlation of
.301 (P < .005), and 41 matched samples from the OPC and ZAPS II had an
associated Spearman's rho of .312 (P < .025).
The 1976 sulfur accumulation data suggested an edge effect in dosage
delivered. Perimeter subplots, particularly those on the corners and extrem-
ities of the plots, such as 1, 5, 11, 21, and 25 (Figure 14.41), seemed
consistently low for the treatment plot from which they were collected. This
led to the modification of collection procedures to escape edge effects.
517
-------
lOOCh
90CH
i
si
800H
700H
600-
A.smithii AND K.cristata
95% CONFIDENCE LIMITS
LOG TRANSFORMATION
A.smithii —
K.cristata
IA
HA
IIB
IB
ROOTS
-- 1C
(ID
ID
IIC
O.PC.
Figure 14.25. Root sulfur levels in A. smithii and K. GTistata
from both ZAPS during mid-September, 1976.
350C
iOOC
to
a
a.
IOOC
A. smithii - Live
Fall Greenup 1977
SULFUR LEVELS
BEFORE (COLLECTION 30) Q
AFTER (COLLECTION 31 ) I
II
IB
ID
Figure 14.26. Sulfur levels in live A. smithii from both ZAPS
during the fall greenup in 1977.
518
-------
Ln
^^
X
t
•
u.
ID
5000
4000
300O
2000
w 1000
^c
«2
9- -7nr»
LAIC. Arm I. I l*ULI_C.l>MUni C\ I
TREATMENT PLOT
Figure 14.27. Sulfur levels in A. smithii
during late April, 1977.
^^
x
H
w
z
o:
5000
4000-
3000
2000
u.
§
_J
w 1000;
Ml U MAY 1 UULLti; I IUN £.£. )
, «, I1
{
I I
Q- OPC IA IIA IB IIB 1C IIC ID HD
TREATMENT PLOT
Figure 14.28. Sulfur levels in A. smithii
during mid-May, 1977.
—
X
i
5000
4000
300O
- 2000
a:
ID
U_
ID
w 1000
9- 7nn
LATE MAY (COLLECTION Z3 ) _
X
H
i !
SOOOi
4000
3000
? 2000
IK
3
1 • u-
{.I -J
II =>
w 1000;
— -. r-^ ^ r— , T-— Q- 700
Miu JUIXt I CULLECTION 24)
p i1
i ,« '
1 1
TREATMENT PLOT
Figure 14.29. Sulfur levels in A. smithii
during late May, 1977.
-- « v «» ^ f «^ || ^^
TREATMENT PLOT
Figure 14.30. Sulfur levels in A. smithii
during mid-June, 1977.
-------
X
i
5000
4000
3000
- 2000
(T
Cfl
1000
S: 700
EARLY JULY (COLLECTION 25)
1
OPC IA IIA IB IIB 1C IIC ID IID
TREATMENT PLOT
Figure 14.31. Sulfur levels in A. smithii
during early July, 1977.
to
o
—
X
H
<
5000
4000-
3000
2000
or
ID
LL.
ID
w 1000
CL -7/in
i_^r\v_i ^wvjwo i \ vsvyL.i_uv* i ivy in t_
II
II
I I1
1 1
Q.
OPC IA IIA IB IIB 1C IIC ID IID
TREATMENT PLOT
Figure 14.33. Sulfur levels in A. smithii
during early August, 1977.
5000
4000
3000
? 2000
or
LL
w 1000
CL 700
MID JULY ( COLLECTION 26
1
I
H
OPC IA IIA IB IIB 1C IIC 10 110
TREATMENT PLOT
Figure 14.32. Sulfur levels in A. smithii
during mid-July, 1977.
LATE AUGUST (COLLECTION 28)
i
JUWW
4000-
3000-
2000-
fr*
LL.
LL
Z)
w 1000-
s ;
Q- 700 J
CL
II
II
T T n
OPC IA IIA iR n R ir nr in n n
TREATMENT PLOT
Figure 14.34. Sulfur levels in A. smithii
during late August, 1977.
-------
—
I
\—
CO
\
5000 1
4000
3000
2000
Qr
ID
U_
ID
w 1000
2
9- vnn
Miu-btKI tMBtR ( COLLECTION 2
M
ii
ii
1T
_
OPC IA IIA
TREATMENT PLOT
Figure 14.35. Sulfur levels in A. smifhii
during mid-September, 1977.
Ui
NJ
_
x
i
CO
\
5000-
4000-
3000-
2000
u.
ID
w 1000-
2 !
Q- 700 J
Q.
|_HIC OC.ri C.IYIDC.H \ VrWI-Ut.V/ 1 IVM*
II
n
T T J
I I
i T
I
OPC IA II A IB II R 1C IIC ID II D
TREATMENT PLOT
Figure 14.36. Sulfur levels in A.
during late September, 1977
-------
Ui
K>
K)
LATE APRIL (collection no.2l)
000
noo
woo
*>
S
9OO
in
TOO
600
OPCIS IS IB IB 1C TTC ID TOT
MID-JULY (collection no 26)
1200
IIOO
1000
v>
o
o
X
I
0.
900
800
700
600
500
OPC TA HA IB SB 1C DC 10 10
Figure 14.37. Root sulfur levels in A. smithii
during late April, 1977.
Figure 14.38. Root sulfur levels in Ai smith/ii,
during mid-July, 1977.
-------
MID SEPT. (collection no.29)
12001
1100
CO
o
o
IOOO
900
Ln
NJ
? 800
K
2
Q.
Q.
700
600
500
1977 COLLECT I ON
IKK
IOOO
800
-704
oe
600
o.
Q.
900
OPC IA
IB IB 1C 1C iD
212629
ZIB
21 2629
ZIC
29
21 2629
ZEB
21 2629
ZttC
Zi 2629
ZED
Figure 14.39. Root sulfur levels in
A. smithi-i during mid-
September, 1977.
Figure 14.40.
Root sulfur levels in A. sririthi-i during late
April (21), mid-July (26), and mid-September
(29), 1977.
-------
NWJ NE
SAMPLING GRID POSITIONS O
SW T SE
8
-©
MIXING SHED
Figure 14.41. Subplot junction numbers and sampling grid positions,
524
-------
The perimeter pipe lines were not sampled in 1977, and the same series of sub-
plots (blocks) were sampled on all treatment plots for an individual collection
period. Even after the elimination of the most obvious problem areas, signi-
ficant subplot variability remained within treatment plots B, C, and D
(Table 14.3). This difference in horizontal distribution of dosage was quite
pronounced in some collections and less so in others (P exact ranged from
.0032 to .6306). An overall analysis of combined probabilities (Table 14.3)
(Fisher, 1954) indicated very highly significant differences within the treat-
ment plots in terms of sulfur concentrations. Since similarly designated
subplots on different treatment plots share in common only their spatial
relationship to the gas delivery system, this difference in plant tissue
sulfur is not due to edaphic features or inherent in the plants themselves.
TABLE 14.3. COMBINED PROBABILITIES FROM TWO-WAY ANOVAS TO DETECT
WITHIN- TREATMENT PLOT DIFFERENCES IN DOSAGE DELIVERED
Collection FS
Number (Subplots) dflsdf9 P In P
A. «£>
21
22
23
24
25
26
27
28
29
30
1.461
2.941
.786
1.464
1.412
3.231
3.529
.889
3.369
1.349
5,25
3,15
9,45
8,40
7,35
9,45
8,40
8,45
9,45
5,45
.2393
.0697
.6306
.2011
.2327
.0043
.0061
.5426
.0032
.2449
-1.4300
-2.6636
-0.4611
-1.6040
-1.4580
-5.4491
-5.0995
-0.6114
-5.7446
-1.4069
k = 10 Z = -25.9281
V = 2k = 20 2 = -2 ln p = 51.856 P < .001
The collections were examined in more detail to ascertain the pattern of
dosage difference (Table 14.4). Only complete blocks were examined. The end
of pipe and lower corner subplots (such as 10NW and 7SW) received the low
dosages, while more central subplots (such as 9NW and 14SW) received the high
dosages. This pattern is similar to that encountered in 1976 when all five
pipelines were sampled.
Drift Plots
Aerial imagery of ZAPS I taken in 1975 was analyzed for S0£-induced
stress by Calspan Corporation (Schott et at., 1976) and Montana State
University (Taylor, 1976). Both groups delineated suspected S02~impacted
areas surrounding the intentionally-fumigated plots. The "drift plots" (TIR)
were established in 1976 in an attempt to provide ground level verification
of the photographic techniques by measuring the relative sulfur content of
525
-------
TABLE 14.4. ORDERED SUBPLOT DIFFERENCES IN DOSAGE
FOR PLOTS B, C, AND D DURING 1977
Collection
Number
Subplots*
21
22
23
24
25
26
27
28
29
30
10SW
17SW
12SW
20SE
7SW
10NW
7SE
8NW
10NE
10NW
20NW
12NE
8SW
7SE
17SW
17NW
7SW
7SW
8SW
7NE
8SW
18SW
10NW
13NW
8NW
7NW
2 ONE
17NW
17SE
10SE
7SE
20SW
19SW
12SE
10SE
12SW
20NW
12SW
9NE
19SE
18SW
7NE
13NE
14NW
18SE
12NE
10SW
20SE
8SW
14SE
14SE
9SW
17NE
9SW
19SE
8SW
8SE
17NW
18NE
18SE
14SW
19SW
13NW
20SW
19NW
13SW
10SE 9NE
9NW
18SW
8NE 9NW
9SE 14SW
12NW USE
14NW 12SE
14SW 12SE
14NE
19NE
12NE
Underlined subsets do not differ significantly (P £ .05) (Duncan's Multiple
Range Test). Subplots are ordered from those receiving the lowest dosage to
those receiving the highest dosage.
plant tissues in the suggested zones adjacent to the treatment plots. Using
the mid-July, 1976, plant collection, we could not identify a cluster pattern
of differing sulfur levels within the drift areas (TIR) . The drift plots
vegetation had significantly lower sulfur concentrations than vegetation from
IB. However, the mean values for the drift plots tended to be higher than
those for plot IA tissues but were never significantly so (P = .05).
The mid-September, 1976, drift plot collections are discussed in the
following paragraphs. The ZAPS I treatment plots and drift plots all were
collected within one day of each other in mid-September. The following
comparisons will be made without prediction based on regression through time,
as was necessary for the mid- July analyses (TIR) .
On the drift plots as a whole, sulfur concentrations in the green leaf
tissue of both A. smithii and K. oristata were higher (a = .05) than those in
both the necrotic leaf material and the belowground parts. K. cristata green
leaf and belowground tissues had higher sulfur values than the respective
526
-------
A. smi-tfrii, material, while concentrations in tissue categorized as dead were
similar for both species (Table 14.5). The correlation for sulfur in the
green tissue was examined to determine whether there was any correspondence
by specific drift plot between the two species. A positive correlation was
assumed (one-tailed test, a = .05) and a significant Spearman's rho (.3065)
was computed. This confirmed that the plants on certain drift plots were
enriched as a function of location.
TABLE 14.5. SULFUR LEVELS IN MID-SEPTEMBER, 1976,
DRIFT PLOT COLLECTIONS
Species x ppm 95% Confidence Limits
Material Sulfur (log transformations) n
A. smith-ii
Live 752 692-818 35
Dead 673 615-737 36
Roots 613 737-690 18
K. cy*istata
Live 944 865-1029 39
Dead 702 639-772 40
Roots 693 642-749 20
Three approaches were used in an attempt to identify specific clusters
of high readings. No approach was considered successful, but each will be
described briefly.
(1) The 1975 photo interpretations (stress contours) were applied as an
overlay to a grid derived from the 1976 sulfur readings. The
photographically-identified areas of interest were large compared
to the ground level sulfur grid (in excess of 50%), and/or the hier-
archy of stress intensity provided limited resolution (three levels
from Montana State University, six possible levels from Calspan).
The 1C and ID plots were easily identifiable, but the resolution of
both photo maps and the ground level grid was inadequate.
(2) The second approach was a runs test above and below the median.
The sulfur levels for particular tissue/species were categorized as
being greater or less than the median and sequenced by the distance
of the particular drift plot from the ZAPS sites. This necessitated
the reduction of ZAPS I to a point source with emissions centered
527
-------
approximately 25 m northwest of the western edge of the ID plot.
The number of runs was always non-significant (a = .05) but tended
towards the low side, suggesting a contagious pattern. The major
weakness in the approach was, of course, the reduction of the site
to a point source with a hypothetical center of emissions. A
ground level grid much more widely dispersed, relative to the ZAPS I,
would be desirable.
(3) The third approach was an examination of sulfur levels of four tiers
of drift plots (TIR, Table 13.2, p. 408) relative to the ZAPS plots.
Concentrations in live K. oristata were found to be elevated in the
two tiers closest to the treatment plots, relative to the two most
distant tiers. Dead K. cr-istata did not repeat this pattern. Live
and dead A. smithii tended to exhibit higher sulfur levels in tiers
adjacent to the ZAPS sites, but this trend was not consistently
significant.
In summary, analysis of sulfur levels in plant tissues did not confirm
the photo imagery. This conclusion does not constitute a denial of the photo-
graphic interpretation. The design of the ground level grid was inadequate
for confirmation. In order to confirm, or invalidate, the imagery using
vegetation analyses, the following requirements would have to be met:
(1) Interpreted imagery should be quickly returned to field personnel (mini-
mally within the same growing season); (2) the scale of imagery maps and
photos should be similar to that of the USGS 7%-minute series topographic
maps or smaller; (3) the ground level sampling grid should cover a substan-
tially larger area than that employed in 1976, and (4) the density of the
ground level sampling grid should be adjusted to allow identification of
change in areas where suspected S02 stress is rapidly changing.
Anaconda Sites
During mid-February, 1977, A. smith-it was collected at several sites in
the vicinity of the Anaconda copper smelter in Anaconda, Montana. Chemical
analyses of these plant samples revealed sulfur concentrations far in excess
of those expected, based on the ambient concentration at these sites, in
comparison with our experimental work at the ZAPS sites. Three additional
A. smith-ii- collections were made in 1977 at two Anaconda sites where ambient
S02 levels have been determined with continuous analyzers.
The Highway Junction site is 3 km northeast of the smelter stack and had
an average ambient S02 concentration of 1.09 pphm for the period of active
growth (April through July 15) and 1.96 pphm for the photosynthetic day (7 am
to 4 pm) . This is an arithmetic average, which is the customary manner of
summarizing S02 monitoring data in the state of Montana. The data are from
1976, the most recent year for which tapes were available (Montana State
Department of Health, Air Quality Bureau), but are quite typical of the concen-
trations historically recorded at that site. The Pumphouse site is located
approximately 9 km northeast of the smelter. The average arithmetic SC-2
concentration of the April through mid-July, 1976, period was .43 pphm, a
reduction corresponding to its increased distance from the smelter.
528
-------
Climatic regimes at the Anaconda and the ZAPS sites are similar (Figure
14.42), although the Anaconda weather data, unlike Colstrip data, include the
drought period of the 1930s.
Sulfur concentrations in live and dead A. snrLthi-i from the Highway
Junction site (Table 14.6) equalled or exceeded the sulfur content of plants
from the ZAPS D plots at equivalent times in the growing season. Belowground
tissue levels were threefold to tenfold higher than those observed in samples
from the D plots. Sulfur levels in the aboveground samples from the Pumphouse
site equalled or exceeded those of the C plots. Roots from this site had
concentrations three to seven times higher than roots from the C plots. This
occurred at ambient concentrations more typical of the ZAPS A or B plots
(Table 14.7).
TABLE 14.6.
SULFUR CONCENTRATIONS (PPM) IN AGROPYRON SMITHII
FROM ANACONDA SITES DURING 1977
Pumphouse Site
Late May Mid-July Mid-Sept
Highway Junction Site
Late May Mid-July Mid-Sept
Live
Dead
Roots
2075
1855
3700
2009
—
5595
2490
2450
2925
2696
5900
2642
3081
—
4607
3935
4551
8882
TABLE 14.7.
ARITHMETIC MEAN AMBIENT S02 CONCENTRATIONS (PPHM)
AT ANACONDA SITES AND ZAPS A AND B PLOT PROBES FOR
THE ACTIVE GROWTH PERIOD (APRIL THROUGH MID-JULY)
Site*
Probe-
All Day 7 am to 4 pm
Anaconda
Highway Junction
Pumphouse
1.09
.43
1.97
—
6 am to 3 pm
ZAPS
ZAPS
ZAPS
ZAPS
ZAPS
ZAPS
ZAPS
IAC
1 1 Ac
IBcl
IBC
IBb
IIBC
IIBb
.90
.78
4.79
4.20
5.47
3.68
4.66
.76
.76
4.22
3.81
3.75
3.45
4.08
*Anaconda data is 1976 from most recent tapes available. ZAPS
data is 1977.
ISmall subletters refer to probe location.
529
-------
Ui
OJ
o
70
UL
o
|'60
LU
^50
g40
o30
a:
LU
>) ANACONDA
(29yrs.)COLSTRIP
i '
0.5
0 0.5 1.0 2.0 3.0
AVERAGE MONTHLY RAINFALL IN INCHES
Figure 14.42. Climatograph for Anaconda and Colstrip; number indicates month
of year.
-------
Washing Experiment
The data derived from the simulated "rainfall event" (three-minute wash)
and "overwintering" (four-day soak) tests are portrayed in Table 14.8. Only
one sample of live A. smLthii, was of sufficient volume for washing. Of the
six trials with multiple samples, only the data from the "rainfall event"
with dead K. ovistata had a t value with a probability greater than .10. This
non-significant value may have resulted from unrepresentative division of the
limited number of dead K. cristata culms available for the split in this one
set of samples. The measured sulfur levels in some of these washed samples
were considerably higher (as much as 1,500 ppm) than their "paired" unwashed
samples, indicating that the older and younger leaves were not evenly split,
and the variance increased accordingly.
TABLE 14.8.
REDUCTION OF PLANT SULFUR LEVELS BY SIMULATED
RAINFALL EVENT AND OVERWINTERING
x ppm Sulfur
D
%D
paired-t
A. smithii-—Live
Unwashed/Washed
2,825 2,117
A. smithii-—Dead
Unwashed/Washed
4,135 3,775
Unwashed/Soaked
4,135 975
4,100 639
K. cr-istata—Live
Unwashed/Washed
3,475 2,787
K. evistata—Dead
Unwashed/Washed
2,615 2,593
Unwashed/Soaked
2,615 721
-708
-360
-2,225
-3,461
-54%
•85%
10
10
9
2.518
4.678
11,946
-688 -20%
-21
-1%
.066
-1,743 -67%
P < .025
PI .005
P < .001
1.775 P < .10
P < .95
11.515 P < .001
Two sets of data are presented for dead A. smithii. subjected to the over-
wintering treatment. The case with ten paired samples included an over-
wintered sampled with a sulfur content of 4,000 ppm. A test for outliers
gave an r = .857 (P < .001) (Dixon and Massey, 1957). In either case, the
reduction in sulfur was highly significant. "Simulated overwintering" caused
an average sulfur reduction of 69%. The last sulfur analysis for dead
531
-------
A. snrith'L'i from IID in 1976 was 4,135 ppm, while the first analysis of dead
(overwintered) materials in the spring of 1977 was 1,312, a reduction of 68%.
The samples overwintered in the laboratory began to decay, and this enhanced
the reduction in tissue sulfur levels. Similar biological activity also occurs
under the snow cover and during spring thaws but at a slower rate. This is
the period of most active fungal and bacterial decay in semi-arid climates.
Spring and early summer collections of dead plant tissue would be of limited
value in assessing air pollution-caused increases in sulfur titre.
The "rainfall event" data suggest an average reduction of 14%. The
large volumes of water used in this simulation exceeded those of any rainstorm,
although the duration of actual rainfall events is longer. It would seem that
rainfall before a sampling period would not substantially reduce the measured
level of tissue sulfur (at least at D plot fumigation levels) because the
major portion of the sulfur is either in the plant or strongly adhered to the
cuticle.
Intensity of rainfall in Rosebud and Powder River counties tends to be
weighted towards low volume storms. A cumulative frequency duration of storm
size for the growing season (April, May, and June) is presented in Figure
14.43, demonstrating that 87.8% of the rainfall events are less than .5 inch.
The summer (July, August, and September) pattern is similar with 91.1% of the
storms less than .5 inch. These data are based on the period 1950 through
1976 at Colstrip, Montana, and are typical of southeastern Montana. Low
intensity storms that do not establish a leaf-flushing action (such as T or
trace storm) may actually increase sulfur levels in or on plant tissues
because of the hygroscopic nature of SO?.
Fluoride Uptake
Fluoride levels of plant tissue were determined to assess whether soil
fluoride uptake was influenced by S02 fumigation. Only the mid-September,
1976, collection from HA and IID was utilized. These data are summarized in
Table 14.9. If a was chosen to be .10, three of the four cases compared
would exhibit a significant increase in the variability of fluoride content
of plant tissues from IID tissues in contrast to vegetation from HA. This
increased variance may reflect greater stress on transpiration and root uptake
processes on IID. The comparison of mean fluoride levels for the two treatment
plots did not generate any evidence to support a difference in this parameter.
Vegetative Phenology
The data derived from the 1977 vegetative phenology of A. smlfhU are
summarized in Tables 14.10a and 14.10b. During any observation period the
total leaf number per hundred culms was quite similar across the OPC and
ZAPS I plots (Figure 14 44). No significant differences were observed among
these five treatment plots. The leaf counts from the five plots were combined
and a Gompertz curve fit to describe the progression of I^O-F 4- j ,
from May through September (Figure 14.45)' Sf^gfde'lo^nt ±1^
from mid-May until mid-July when growth plateaued at an average of S « i o! L
per culm. A few culms developed additional leaves during late Julv * A A\
but made no substantial contribution to final leaf <*r*0o f* o •* August
btage ^.9 leaves per culm).
532
-------
I.OCH
0-S-r-T-i
T.05.10.20 .50 .75 1.00 1.25 1.50 1.75
RAINFALL IN INCHES
Figure 14.43. Typical distribution of storms by size in southeastern
Montana.
533
-------
Ui
TABLE 14.9. SOIL FLUORIDE UPTAKE AS INFLUENCED BY S02 FUMIGATION
IIA IID
Species x ppm n s2 x ppm n s2
K.
A.
ovistata
Live 2.09 8 .576 vs 2.73 10 2.725
Dead 3.00 7 .540 vs 4.13 6 2.131
smithii,
Live 1.78 9 .309 vs 2.07 6 1.367
Dead 4.07 10 5.791 vs 2.87 7 3.936
i
Variance
F =
Sl2/s22
4.731
3.946
4.424
1.471
Ratio
P
(exact)
.037
.095
.047
.625
Equality of Means*
F P
s
1.189 .25 < P < .50
2.954 .10 < P < .25
0.321 .50 < P < .75
1.262 .25 < P < .50
*Approximate test of
when c^2 ^ a22J P based on synthetic degrees of freedom (Snedecor, 1956).
-------
TABLE lA.lOa. 1977 VEGETATIVE PHENOLOGY OF AGROPYRON SMITHII AND TEST FOR INDEPENDENCE OF LEAF NECROSIS ON ZAPS I
(jj
Observation
Date 12
OPC
Total
Live
Necrotic
% Necrotic
IA
Total
Live
Necrotic
% Necrotic
IB
Total
Live
Necrotic
% Necrotic
1C
Total
Live
Necrotic
% Necrotic
ID
Total
Live
Necrotic
% Necrotic
Chi-square*
Total Leaf No.
RXC Test of
Independence
1
,13,14 May
307
307
0
0
306
306
0
0
305
305
0
0
307
307
0
0
304
304
0
0
0.022
G
l-P(G)
2
28,29 May
383
335
48
12.5
385
348
37
9.6
382
351
31
8.1
380
332
48
12.6
377
311
66
17.5
0.098
18.184
,001
3
15,16,17 Jun
471
372
99
21.0
474
365
109
23.0
485
396
89
18.4
479
356
123
25.7
467
325
142
30.4
0.414
22.169
<.001
A
2,3,4 Jul
557
418
138
24.8
547
389
158
28.9
572
442
130
22.7
567
393
174
30.7
541
358
183
33.8
1.223
25.983
<,001
5
12,20 Jul
582
377
205
35.2
559
312
247
44.2
610
430
180
29.5
601
356
245
40.8
581
343
238
41.0
2.675
33.990
<.001
6
4,5,6 Aug
584
330
246
42.1
562
271
291
51.8
616
399
217
35.2
605
325
280
46.3
590
316
274
46.4
2.893
36.780
<.001
7
22,23,24 Aug
590
301
289
49.0
563
238
325
57.7
619
362
257
41.5
605
290
315
52.1
592
281
311
52.5
2.908
33.983
<.001
ft
10,11 Sept
589
248
341
57.9
564
164
402
71.3
619
259
360
58.2
605
209
396
65.5
592
208
384
64.9
2.820
31.093
<.001
Q
28 Sept
592
130
462
78.0
562
65
497
88.4
619
94
525
84.8
608
51
557
91.6
591
55
536
90.7
3.124
59.877
<.001
Maximal Nonsignificant
Sets a £.05
D C 0 A B
D C A 0 B
D C A 0 B
A D C 0 B
A D C 0 B
A D C 0 B
A C D B 0
C p A B 0
*Critical chi-square X2
9.488
*SourceJ Sokal and Rohlf, 1969
-------
TABLE 14.10b. 1977 VEGETATIVE PHENOLOGY OF AGROPYRON SMITHII AND TEST FOR INDEPENDENCE OF LEAF NECROSIS ON ZAPS II
Ul
Observation
Date
OPC
Total
Live
Necrotic
% Necrotic
HA
Total
Live
Necrotic
% Necrotic
IIB
Total
Live
Necrotic
Z Necrotic
IIC
Total
Live
Necrotic
% Necrotic
IID
Total
Live
Necrotic
% Necrotic
Chi-square*
Total Leaf No.
RXC Test of
Independence
1
10,11,12 May
307
307
0
0
321
321
0
0
334
334
0
0
323
323
0
0
326
326
0
0
1.200
G
l-P(G)
2
26,27 May
383
335
48
12.5
419
367
52
12.4
422
367
55
13.0
406
354
52
12.8
414
338
76
18.4
2.394
8.438
.077
3
14,15 Jun
471
372
99
21.0
508
384
124
22.4
521
394
127
24.4
463
336
127
27.4
523
369
154
29.4
6.446
10.890
.028
4
1,2 July
557
418
138
24.8
607
446
161
26.5
611
446
165
27.0
599
417
182
30.4
648
423
225
34.7
6.994
18.363
.001
5
18,19 July
582
377
205
35.2
615
360
255
41.5
630
393
237
37.6
625
375
250
40.0
680
377
303
44.6
7.965
13.475
.009
6
3,4 Aug
584
338
246
42.1
616
264
352
57.1
632
304
328
51.9
631
310
321
50.9
695
327
368
52.9
10.337*
29.050
< .001
7
21,22 Aug
590
301
289
49.0
618
199
419
67.8
633
250
383
60.5
632
260
372
58.9
695
286
409
58.8
9.339
44.984
< .001
8
9,10 Sept
589
248
341
57.9
617
91
526
85.3
632
147
485
76.7
632
186
446
70.6
694
175
519
74.8
9.347
122.980
< .001
9
26,27,28 Sept
592
130
462
78.0
616
39
577
93.7
631
90
541
85.7
632
122
510
80.7
694
86
608
87.6
8.998
77.528
< ,001
Maximal Nonsignificant
Sets a < .05
D B C 0 A
D C A B 0
D C B A 0
D A C B 0
A D B C 0
A B C D 0
A B D C 0
A D B C 0
*Critical chi-8quare
9.488
Source: Sokal and Rohlf, 1969
-------
Ui
U)
CRITICAL X2
= 9.488
700-
600-
tr
UJ
|500-
ID
u-400-
UJ
^ 300-
g 200
MID
MAY
^^ • » 1 • • ^^ V VkM* ^ ^ | )C^ 1 XI 1 ^"^ • • ^^^ ^^
TREATMENT- OABCD
]
LATE MID EARLY MID EARLY LATE MID LATE
MAY JUNE JULY JULY AUG AUG SEPT SEPT
X
,022 .098 .414 1.223 2.675 2.893 2.908 2.820 3.124
Figure 14.44. Total leaf number per hundred culms for Agropyron smith-ii on ZAPS I and OPC
during 1977. Critical X.05(4)
D for each observation period.
treatments are ordered OPC, A, B, C,
-------
6i
5-
4-
-sj
3
GOMPERTZ CURVE
Y = C 5.965 3C.265 (-572X)]
150
180 210 240 270
JULIAN DATE
Figure 14.45. Development of A. smithli leaf stage number for the OPC and
ZAPS I in 1977.
538
-------
Leaf number on IID was higher than on the rest of the ZAPS II plots and the
OPC (Table 14.10b). By early August, 6.9 leaves per culm was the average on
IID, while OPC = 5.8, IIA = 6.12, IIB = 6.3, and IIC = 6.3 (Figure 14.46).
The timing of development on ZAPS II was similar to that on ZAPS I plots, with
IID showing a trend for further development.
Leaf stage development in 1977 was similar to the pattern observed in
1976 (TIR): rapid growth until mid-July and a gradual reduction during the
rest of the season. The average leaf number on all plots was 6.27 in 1976,
as opposed to 6.16 in 1977. However, no significant differences across the
plots were measured in 1976.
The amount of leaf necrosis (ratio necrotic leaves to green leaves)
across the treatment plots is summarized in the last row of Tables 14.10a and
14.10b. Doubling the sample size in 1977 to 100 plants per treatment plot
increased the resolution across the plots but did not produce a significant
separation of all the treatment plots. During the period of rapid growth
(through mid-July, observation 5), significant premature senescence was most
apparent on the plots receiving the higher levels of fumigation. During late
May on ZAPS I (observation 2), the ID plot had significantly more necrotic
leaves than IA and IB. The OPC, IA, IB, and 1C plots were statistically
indistinguishable.
During mid-June, the ID plants were also significantly more necrotic,
this time in contrast to OPC and IB, while OPC, IA, IB, and 1C were again
statistically similar. By early July (observation 4), A, srrrit'h'i'i on ID was
more necrotic than on the OPC and IB plots, and the plants on 1C showed a
significant increase in necrotic leaves in contrast to IB. The OPC, IA, and
IB plots continued to be inseparable as a group.
A second process became evident by late July (observation 5). The
number of necrotic leaves increased rapidly on the IA plot after plant growth
ceased. This plot was similar to 1C and ID but exhibited significantly more
necrosis than the OPC and IB. An identical relationship was evident through
early August (observation 6). By late August (observation 7), all plots but
the OPC showed less necrosis than IB, the OPC being similar to IB. In early
September, IA, 1C, and ID remained indistinguishable from each other. The
plants on IA showed more necrosis than those on IB or the OPC, and
on 1C had more necrotic leaves than the OPC. By the end of September
(observation 9), the 1C and ID plots exhibited more necrosis than IB and the
OPC, and IA showed more necrosis than the OPC.
In conclusion, the level of necrosis was highest on the 1C and ID plots,
as one might expect. The level of necrosis upon cessation of growth was
higher on IA than might be anticipated. Although it was not significant, this
pattern of necrotic development was observed on ZAPS I in 1976 (TIR).
During 1977 on ZAPS II, plots IIB and IID remained statistically indistin-
guishable throughout the collection season. In mid-June (observation 3),
plants on IID were significantly more necrotic than those on the OPC. In
early July (observation 4), IID showed more necrosis than both the OPC and
IIA. Starting in mid-July (observation 5), the level of necrosis seemed to be
539
-------
Ul
4N
O
700
600
tr
UJ
i500
ID
2!
UL400-
^ 300
&200-
I
MID
MAY
CRITICAL X2 .05(143 ^9.488
TREATMENT - OABCD
• •
<
I
-
LATE MID EARLY MID EARLY LATE MID LATE
MAY JUNE JULY JULY AUG AUG SEPT SEPT
X
1.200 Z394 6.446 6.994 7965 10.337 9.339 9.347 8.998
Figure 14.46. Total leaf number per hundred culms for Agropyron smithii on ZAPS II and OPC
during 1977. Critical X2.Q5(4)= 9.488; treatments are ordered OPC, A, B, C,
D for each observation period.
-------
increasing on the IIA plot, following the pattern on ZAPS I. Vegetation on
IID was still more necrotic than vegetation on the OPC. In early August
(observation 6), necrosis continued to increase on IIA, the only significant
difference being that the OPC was less necrotic than IIA, IIB, and IID. By
late August (observation 7), the amount of necrosis was significantly higher
on IIA than on IIC, IID, or the OPC; vegetation on the OPC displayed signifi-
cantly less necrosis than on all other plots. In early September (observation
8), necrosis was most prevalent on IIA and least prevalent on the OPC. There
was no detectable difference between IIB, IIC, and IID at this time. The
final observation period (9) in mid-September showed that the largest amount
of necrosis occurred on IIA, this plot being significantly elevated over all
other treatments. Plot IID was more necrotic than IIC or the OPC, and IIB
was also more necrotic than the OPC.
The overall pattern on ZAPS II was one of greatest necrosis on vegetation
on the most fumigated plot and least necrosis on IIA and OPC vegetation
through the period of leaf development and expansion. After growth ceased,
the vegetation on IIA began to become necrotic at a faster rate than vegeta-
tion on the other treated plots. The pattern was similar on ZAPS I, with the
exception of the intermediate to low level of necrosis displayed by vegetation
on IB. On ZAPS II in 1976, the IIA plot exhibited a similar but non-significant
pattern of low level necrosis early in the season but. showed a relatively high
amount of necrosis late in summer.
Seed Work
A. smithi-i germination was so low as to preclude data analysis. A total
of 5,113 seeds from all treatments exhibited a total germination success of
only 0.12% after wet stratification under dark conditions at 4°C for 30 days.
The germination test was conducted at an alternating 20°C/5°C diurnal cycle
under dark conditions. The stratification and germination conditions were
recommended by Eddleman who also has found limited seed fertility in
A. smithi'l (1977b). To ascertain whether the low germination success was a
consequence of continued dormancy or improper germination environment, a
tetrazolium test was made on seeds from IA. Seeds selected for fill (presence
of embryo) were soaked at 35°C for two hours, then bisected longitudinally.
No viable embryos were detected after 20 hours staining in 0.1% tetrazolium
at 35°C. Approximately 30% of the caryopses were occupied by insect bodies
which had exhausted the endosperm. The lack of germination success appears
to be due to a lack of viable embryos.
Lack of viable seed is typical of A. smithO,. Jorgensen (1970) reported
germination success ranging from 0% to 4.0% on eleven sites in central Montana
over a two-year period. A. sm-Lthii, reproduction tends to be primarily by
vigorous rhizome growth. Nevertheless, seed production is still important.
New seed maintains the vitality of a stand and allows long-term changes in
the population. Germination success as high as 80% (Hoover, &£ at. , 1948) has
has been reported in good seed crop years.
Germination success results for Sti-pa vtvidula are reported in Tables
14.11 and 14.12. Germination success was quite low, ranging from 0.6% to 3.9%,
and no significant treatment effects were noted. The data on seed weights
541
-------
TABLE 14.11 SEED GERMINATION CRITERIA
Criteria A. smithii
^Collection Date 17, 19 Sept
Recommended Date
*Average Weight Range 2.58-
(grams x 10~4/seed) 3.35 x 10~3
1976 Average Weight
(grams x 10~^/seed)
Ln
5 *Days to 50% Germination
Days to 50% Germination
*Range of % Germination 0-0.6
1976 Average % Seed Fill
and Range
After Ripening No
Stratification 30 days, 4°C, dark
Germination Temperature
Day/Night (°C) 20°/5°
Hours Light No
S. viridula
6 August
7-17 July
1.19-
2.06 x 10~3
3.47 x 10"3
5
0.6-3.9
89 (78-100)
12 mo
No
20°
No
K: eristata
6 July
1-30 July
1.90-
2.50 x 10-"
2.03 x 10'"
6-7
5
32.9-55.2
65 (33-91)
4 mo
No
20°
No
P. sandbergii
4, 7 July
10 June- 17 July
3.19-
4.73 x 10""
4.58 x 10""
10-11
12
21.9-56.5
78 (65-90)
4 mo
No
10°
8
T. dubius
15 July
6.04-
7.58 x 10~3
5-8
66.1-94.7
No
No
20°
No
*Data for 1976 ZAPS seed collections; all other data and recommendations from Eddleman (1977a, 1977b).
-------
TABLE 14.12. PERCENT GERMINATION, PERCENT VIABILITY, AND SEED WEIGHTS
FOR 1976 COLLECTIONS FROM ZAPS
Species
St-ipa vividula
Percent
Germination
Seed Weight
(grams x 10~3/seed)
Percent
Germination
Seed Weight
(grams x 10~3/seed)
Plots*
IA
0.7
IA
1.57
IIC
0.6
IIA
1.19
1C
1.6
IB
2.02
IID
0.8
IID
1.30
IB
1.8
ID
2.02
IIA
2.4
IIC
1.47
ID
1.8
1C
2.06
IIB
3.9
IIB
1.63
Koelerta cTistata
Percent
Germinat ion
Percent Viable
Percent Viable
(selected)
Seed Weight
(grams x 10~Vseed)
ID
32.9
ID
18.4
ID
17.2
ID
1.90
1C
48.7
IA
40.2
1C
35.1
IA
2.31
IA
52.6
1C
40.6
IA
41.9
IB
2.42
IB
55.2
IB
56.9
IB
52.4
1C
2.50
Underlined subsets do not differ significantly (P <_ -05) (Duncan's
Multiple Range Test).
(continued)
543
-------
TABLE 14.12. PERCENT GERMINATION, PERCENT VIABILITY, AND SEED WEIGHTS
(continued) FOR 1976 COLLECTIONS FROM ZAPS.
Species
Poa sandbergii
Percent
Germination
Seed Weight
(grams x 10~Vseed)
Percent
Germinat ion
Seed Weight
(grams x 10~Vseed)
Tragopogon dubius
Percent
Germination
Seed Weight
(grams x 10~3/seed)
Percent
Germination
Seed Weight
(grams x 10" 3 /seed)
•
— " • —
_ — ._
Plots*
ID
39.2
ID
3.66
IID
21.9
IIA
3.19
IA
66.1
ID
6.04
OPC
80.9
IID
6.67
1C
53.0
1C
4.05
IIA
25.1
IID
3.41
OPC
80.9
IA
6.76
IIB
84.2
IIC
6.69
IA
53.3
IB
4.63
IIB
25.9
IIB
3.75
IB
87.8
1C
6.85
IIC
85.1
OPC
6.95
IB
56.5
IA
4.73
IIC
44.0
IIC
4.33
1C ID
88.6 91.0
OPC IB
6.95 7.58
IIA IID
90.2 94.7
IIA IIB
6.98 6.98
Underlined subsets do not differ significantly (P £ .05) (Duncanfs
Multiple Range Test).
544
-------
suggest a depression in average weight on the control plots. These data are
suspect. Eddleman (1977b), reporting that July 12 is the average date for
the peak of ripe seed and that 50% shatter occurs by July 17, comments,
"There appears to be little more than a week for optimum collection." Our
1976 collections were made quite late (August 6) and seem to consist almost
entirely of seed that never matured. Eddleman1s (1977b) average seed weight
for 1976 was 3.47 x 10~3 grams, while our average was from 1.19 to 2.06 x
10~3 grams. At the time of collection, we felt we had missed the shatter but
were not fully aware of the consequences. Under the recommended germination
conditions (20°C, dark, no stratification, approximately one year after
ripening period), germination success should have been much higher. The
limited total germination also precluded the calculation of rate of germi-
nation parameter.
The K. cristata collection from ZAPS I was made on July 6. This date is
in agreement with that recommended (Table 14.11), and the range of seed
weights includes the regional average for that year. Germination testing was
carried out at 20°C under dark conditions. A significant depression in germi-
nation success was observed for seeds collected from the D plot (Table 14.12).
A corresponding reduction in seed weight was also observed.
Tetrazolium viability tests were conducted to confirm the germination
test. The seeds were soaked for 24 hours at room temperature. Soaking
softened the seeds and prevented splitting when the endosperm was pierced by
a needle. Piercing allows rapid absorption of the tetrazolium solution. The
replicates (five per treatment, 20 seeds per replicate) were then treated
with 1.0% tetrazolium at 35°C for 24 hours. The stained seeds were then
treated with lactophenol for one hour to make the palea transluscent and
allow inspection of the embryo. A significant reduction in viability
(Table 14.12) was again noted in seeds from ID, confirming the observed
reduction in germination success.
A third test was made on K. GT'istata seeds to select seeds for fill.
This was done by backlighting the seeds on a light table. After these seeds
were stained and cleared (lactophenol), a notable pattern in insect infes-
tation was seen (see Bromenshenk, Section 18). Under backlighting, the dark-
bodied insects appeared similar to seed embryos. The seeds containing insects
were removed from the subsequent data analyses. Again, a significant depres-
sion in viability was observed in seeds from plot ID (Table 14.12). The 1C
plot was also found to be significantly depressed relative to IB.
The proportion of viable embryos would be expected to be equal to or
greater than the proportion of seeds showing successful germination. The
data suggest a lower proportion of viable seeds than the germination test.
The most direct explanation may be that the viability tests were made four
months after the germination test. The extra time and possible storage
environment stresses may have reduced viability of these seeds. Although the
trials were not designed to test this hypothesis, anova was performed for the
same plots, contrasting the germination success with the percent viable and
the percent viable (selected). The resultant F values are presented in
Table 14.13. Seeds from 1C and ID seem to be becoming nonviable at a faster
rate than those from IA and IB.
545
-------
TABLE 14.13. F VALUES FROM ANOVA OF GERMINATION SUCCESS
AND VIABILITY TESTING
% Germination vs % Germination vs % Viable vs
Plot % Viable % Viable (selected) % Viable (selected)
ID
1C
IB
IA
20.090*
1.380
0.109
4.429
22.186*
10.262*
0.419
3.510
0.182
0.898
0.739
0.084
*P < .05
Both viability trials were performed at the same time. If we were able
to effectively select for fill by the backlighting technique, we might expect
to see an increase in percent viable. No significant changes in viability
were observed (Table 14.13). This suggests that almost all the seeds
contained an embryo, and the observed depression in germination success and
viability across the treatment occurred after the formation of the embryo.
Therefore, S02 fumigation may not have prevented embryo development itself.
Possible fill identification problems under backlighting and the limited data
base caution against drawing either of these conclusions at this time.
The large numbers of germinating K. cristata seeds allow a detailed exami-
nation of the pattern and speed of germination of this species. Germination
was rapid and intense (Figure 14.47), with the day of peak germination (day 6)
being the same for all treatment plots. Note: In Figures 14.47 to 14.52, the
proportion of seeds successfully germinating is reiterated in the body of the
graph, while the vertical axis portrays the relative frequency of those seeds
which did germinate. There were six days to 50% germination in seeds from IA
and IB, while seeds from 1C and ID required more time (Table 14.11). The
response of seeds from both ZAPS sites in 1976 was slower than that reported
for the region (5 days), but the difference was not significant.
The relative cumulative frequencies (Table 14.14) allow a detailed exami-
nation of the speed of germination over the entire 30-day period. The response
was fastest on IA and IB and significantly slower on 1C and ID. On days 6 and
7, ID was also lagging significantly behind 1C. The entirentime period is
integrated in the coefficient of rate of germination (CRG =£[gn - g(n_i)]/n).
This coefficient was not subjected to statistical analyses,-'-but it can be
seen to decrease with increasing levels of fumigation.
Poa sandbergii seeds were collected on July 4 from ZAPS I and on July 7
from ZAPS II, within the recommended period (Table 14.11). The range of
observed seed weights are typical of this species. Germination trials were
546
-------
o Koelaria cristata
day 6
UJ
K
o
£10-
UJ
o
a:
UJ
IA
53%
10
20
30-
a:
o
10-
LU
O
LU 0
CL
day 6
1
1C
49%
10 20
DAYS
1976 COLLECTION
\ day 6
30 4
10
day 6
30
Ul
IB
55%
20
ID
33%
30
10 20 30
DAYS
Figure 14.47. Germination peak and distribution for Koelaria evistata
collected in 1976 from ZAPS I.
547
-------
TABLE 14.14. RELATIVE CUMULATIVE FREQUENCIES FOR GERMINATION OF
KOELERIA CRISTATA DURING 1976 ON ZAPS I
Day
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
CRG
n
IA
0
0
0
0
21.4ef
58. 8e
75. le
90. 2e
94. 6e
96. le
97. 2e
n e
98. 3e
98. 8e
99. Oe
99. 4e
n e
if e
_
^
_
99. 8e
100. Oe
ti e
it e
ii e
_
^
ir e
ii e
15.65
546
IB
0
0
0
0
23. Oe
51.5ef
73. 8e
91. le
95. 8e
97.1e
97. 8e
98. 5e
99. Oe
99. 2e
n e
» e
ii e
99. 4e
_
99. 9e
n e
ii e
n e
ii e
ti e
ii e
15.56
548
— — — — — — _
Plot*
1C
0
0
0
0
12.88
47. 8f
73. 4e
84.9ef
92. 4e
95. Oe
96. 5e
98. 2e
98. 6e
97. Oe
n
99. 4e
n e
100. Oe
ii e
ii e
it e
it e
» e
Usy
c.
ii e
14.96
469
• — —
ID
0
0
0
0
13.9f§
38.4
57.9
80. 7f
87. 9e
90. 5e
91. 7s
94. le
95. 5e
96. 5e
98. 2e
98. 4e
" e
n e
98. g6
99. le
it e
99. 6e
it e
*™"
•••
99. 8e
ti e
14.23
416
*Treatment-days within a row sharing the same letter do not differ
significantly (P <_ .05) (modified Smirnov Test).
548
-------
conducted at 10°C with an eight-hour light period for 30 days. No tetrazolium
assessments of viability were made.
The success of germination was significantly reduced on ID (Table 14.12),
in comparison to the other three ZAPS I plots. This reduction in percent
germination was paralleled by a reduction in the weights of seeds from the
plots receiving higher S02 fumigation: 1C and ID were significantly lower
than IA and IB.
As with K. cristata, the total number of P. sandbergii seeds germinating
was large enough to allow examination of the pattern of germination response
through time. Germination in the species was rapid (Figure 14.48). Day of
peak germination was 11 for all four treatment plots, but a less intense peak
was observed on day 9 in the seeds from IA. Days to 50% germination are
around 12 for this species and occurred on day 11 for all plots in these
trials (Table 14.11).
The relative cumulative frequency distributions are presented in Table
14.15. Significant differences were observed for days 8 through 11. Plot IA
exhibited the most rapid rate of germination, and 1C was the slowest. Plots
IB and ID were similar through the entire time period but were significantly
slower than IA on some days. The CRG reveals a similar but less detailed
pattern. The speed of germination was greatest on IA, reduced but similar on
IB and ID, and slowest on 1C.
P. sandbepgH seed from ZAPS II was germinated under conditions identi-
cal to those from ZAPS I. Plot IID showed the lowest germination success,
although the difference was not significant, while total germination success
was significantly higher on IIC (Table 14.16). The weight data revealed IIC
seeds to be heavier than those from IIA and IID but not from IIB.
Analyses of the germination pattern through time revealed a depression
corresponding to higher fumigation levels in spite of the higher germination
success on plot IIC. Day of peak germination was 11 on plots IIB, IIC, and
IID, while IIA peaked a day earlier (Figure 14.49). Additionally, the peak
for IID appears truncated, with relatively more germination occurring late in
the trial. This was reflected by the fact that 50% of final germination was
reached on day 11 by seeds from IIA, IIB, and IIC but not until day 13 on IID.
The relative cumulative frequency distributions (Table 14.16) show that
the plot IIA sample had the most rapid germination. The speeds of germination
on IIB and IIC were similar, but both were significantly slower than that of
IIA. Response speed on IID was drastically reduced in comparison to the other
three treatments. The relative magnitude of the CRG again integrates the
overall trend, with speed of germination decreasing with increasing level of
fumigation.
Tragopogon dubius was the only forb used in our seed germination studies.
This plant is a diploid weed of European origin which can establish itself in
areas which are relatively undisturbed (Hitchcock and Cronquist, 1973). The
studied grasses were all perennials, but T. dubious acts as an annual, bien-
nial, or winter annual (Hitchcock and Cronquist, 1973; Van Bruggen, 1976) and
549
-------
o Poo sondbergii
H
30-
1976 COLLECTION
UJ
e>
20-
10-
UJ
o
o:
UJ
a- 0
day 11
IA
53%
day 11
IB
56%
10
20 30 4 10
20 30
o
f=30-
(T.
& 20-
10-
UJ
o
UJ Q-r-
CL 4
dav 11
.
re
53%
day 11
10 20
DAYS
30 4
10 20
DAYS
30
Figure 14.48. Germination peak and distribution for Poa sandbergii
collected in 1976 from ZAPS I.
550
-------
TABLE 14.15. RELATIVE CUMULATIVE FREQUENCIES FOR GERMINATION OF
POA SANDBERGII DURING 1976 ON ZAPS I
Day
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
CRG
n
IA
0
0
0
0
0
0
0
6.6 e
27.8
40.5 e
65.2 e
_
83.2 e
88.2 e
92.2 e
94.3 e
96.3 e
97.0 e
97.8 e
98.1 e
98.9 e
98.9 e
—
—
—
99.7 e
"
M
100.0 e
II
9.13
377
Plot*
IB
0
0
0
0
0
0
0
2.4e
14.6 ®
28.0 *f
57.8 ef
_
75.8 e
80.4 e
86.0 e
90.4 e
94.5 e
96.2 e
97.7 e
98.2 e
98.7 e
98.7 e
-
—
—
99.2 e
"
99.7 e
"
99. 9e
8.57
410
1C
0
0
0
0
0
0
0
.5 c
7.5 ®
20.5
51.2 t
_
75.6 e
84.9 e
89.9 e
93.1 e
94.9 e
95.8 e
96.5 e
97.4 e
98.3 e
98.3 e
-
-
—
99.9 e
11
n
100.1 e
"
8.35
440
ID
0
0
0
0
0
0
0
o £ e
2.6
16.5 e
31.0 e|
58.0 et
—
79.0 e
86.1 e
90.6 e
92.5 e
94.1 e
94.7 e
96.9 e
97.1 e
98.7 e
99.2 e
—
-
-
i;
99.5 e
99.8 e
i?
"
8.69
310
*Treatment-days within a row sharing the same letter do not differ
significantly (P <_ .05) (modified Smirnov Test).
551
-------
Poa sondbergii
1976 COLLECTION
|30-
2
cc
UJ
o
_, 20-
£
0
H|0-
UJ
0
* _[
^ /^ 1
:RCENT TOTAL GERMINATION F
-> — ro GJ r
? 9 9 '
-&•
•i
1
1
r
day 11
r/
dav 10
y '
IA J IB
25% L, 26%
v V
"— ,Pi rJ Ln-n, ,„
0 20 30 4 10 20 30
day 11
Y
day 11
• — . *n* x% 1 <••*• •«.
1C S ID
44% J 1 22%
W f i
L, kn
^~? n r1 L n m
CL ~ 4 10 ?O 3fi 4 lh ?h -*n
DAYS
DAYS
Figure 14.49. Germination peak and distribution for Poa sandberg-Lj,
collected in 1976 from ZAPS II.
552
-------
TABLE 14.16. RELATIVE CUMULATIVE FREQUENCIES FOR GERMINATION OF
POA SANDBERGII DURING 1976 ON ZAPS II
Day
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
CRG
n
IIA
0
0
0
0
0
0
0
2.7e
21. 3e
45.9
62. 2e
—
82. 3e
86. le
91. 4e
94. le
95. 2e
96. Oe
96. 8e
96. 8e
97. 9e
98. 7e
—
-
—
99. 8e
100. 2e
n
M
M
8.95
264
Plot*
IIB
0
0
0
0
0
0
0
0.9e
12.0ef
33. 4e
60. 8e
—
76. 2e
81. Oe
87. Oe
90.1ef
93. 5e
94. 4e
96. le
96. 6e
97. 8e
n
—
—
—
99. 5e
n
100. Oe
100. 5e
M
8.62
233
IIC
0
0
0
0
0
0
0
Oe
11.5e§
24. 8e
53. 9e
-
77. 5e
84. le
87. 3e
91. 3e
95. Oe
97. Oe
98. 2e
99. le
100. Oe
ii
—
-
—
100. 6e
n
n
101. 2e
n
8.53
347
I ID
0
0
0
0
0
0
0
Oe
0.9f§
8.6
23.6
-
50.9
62.3
71.4
78. 7f
85. le
87. 8e
90. le
91. 9e
95. le
95. 6e
-
—
-
98. 3e
99. 7e
n
100. 2e
M
7.30
220
*Treatment-days within a row sharing the same letter do not differ
significantly (P £ .05) (modified Smirnov Test).
553
-------
never as a perennial. This species also exhibited the exceptionally high
levels of sulfur (TIR). Sulfur in leaves from the OPC averaged 4,108 ppm,
while leaves from the ID plot averaged 7,575 in 1976. Much more extensive
collections were made in 1977, but chemical analysis has not been completed.
T. dubius seeds were collected on July 15. Germination trials were
conducted at 20°C under dark conditions. An OPC sample was available for
inclusion in the trials. The IA plot displayed a significant reduction in
germination success when compared to the other treatments (Table 14.17). The
trial for the ZAPS II samples revealed no significant differences (Table 14.18)
Seed weights from ZAPS II exhibited no difference, while ZAPS I seeds from
the D plot were significantly lighter, and IB seeds were significantly heavier
than those from the other three treatments.
The pattern of germination is displayed in Figures 14.50 through 14.52.
Day of peak germination was day 5 for seeds from all plots, except 1C (day 7)
and IA (day 9). There was also a tendency for a biomodal response, but this
could be an artifact of the limited (137 or less) total number of seeds germi-
nating in each sample. Days to 50% germination also tended to be variable,
ranging from day 5 to day 8 (Table 14.11), with no pattern corresponding to
the level of S02 treatment.
The relative cumulative frequency distributions differed greatly
(Tables 14.17 and 14.18), but the shift in speed of response did not corre-
spond in any consistent way with plot treatment levels. Similarly, the CRGs
were highly varied and followed no recognizable pattern. Within the limits
of the sample size employed (replicates of four, total seed numbers from 198
to 497, germination numbers from 174 to 452), it appears that the seed of
this species is independent of the level of S02 fumigation.
Mycorrhizal Studies
Regression of percent mycorrhizal infection on both absorbance (Figure
14.53) and theoretical S02 dosage (Figure 14.54) from collection 29 (mid-
September) on ZAPS II was found to be significant at the P <_ .001 and P £ .05
levels, respectively. Thus a large and significant portion of the percent
mycorrhizal infection levels, as determined by visual examination, could be
explained by theoretical S02 dosage and by spectrophotometer absorbance
readings of the root extracts. The resultant trend, as seen in Figures 14.53
through 14.56 was for those plants from the high S02 dosage plots (C and D)
to exhibit both low absorbance readings and relatively lower percent mycor-
rhizal infection levels.
Roots of A. smithii were not easily distinguishable in the field on the
basis of color. However, when stained and microscopically examined, A. smithii
root samples from the OPC collection 26 (mid-July) consisted of a larger
number of fat roots with a yellow-gold coloration, compared to those from
ZAPS IIC and IID. Roots from the higher treatment plots tended to have many
more thin, dark brown roots. Until additional sampling and further analysis
of absorbance data is conducted, however, the 95% confidence limits (Figure
14.53) indicate that absorbance readings alone do not provide the desired
accuracy for prediction of percent mycorrhizal infection levels on the ZAPS.
554
-------
TABLE 14.17. RELATIVE CUMULATIVE FREQUENCIES FOR GERMINATION OF
TRAGOPOGON DUBIUS DURING 1976 ON ZAPS I
Day
1
2
3
4
5
"6
7
S
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
CRG
n
OPC
0
0
0
0
20. Oe
37. le
56, 5e
62. 8e
66. 8e
73. le
79. 4e
80. Oe
82. 3e
84.6efh
85.7ef
88.6ef§h
89.7ef
91.4ef
93. le
94. 8e
96. 5e
n e
n e
-
—
—
98. 2e
99. 3e
99. 9e
ii e
it e
13.25
175
IA
0
0
0
0
11 .9e^
29.6s
43. 9e
55.2ef
74. Oe
79. 5e
82. 9e
84.3ef
86. 7e
93.9e§
97. Oe
97. 7f
98. Oe
M e
98. 7f
n e
99. Oe
M e
n e
—
—
—
n e
99. 3e
99. 6e
n e
99. 9e
12.90
293
Plot*
IB
0
0
0
0
23. 6e
39. le
54. 6e
64. 9e
71. 2e
76. 9e
81. 5e
83.8s
87. 2e
94.7f§i
96.4e§
" gf
n e
" eg
M eg
n e
97. Oe
it e
M e
-
—
—
99. 3e
M e
ii e
99. 9e
M e
13.73
174
1C
0
0
0
0 _
7.2f
15.4
31.4
52.0
58.7
64.4
73. 7f
76. 8e
78. 9h
80. 4f
81. 4h
82. 4f
83.9f§
85.4f§h
86. 9e
n e
92. 6e
97. 8e
-
-
—
100.4s
n e
ii e
M e
100.9s
11.72
194
ID
0
0
0
0
55.8
85.7
90.6
93.3
94.2
95.3
96.2
96.4
96.8
97. 21
97.4e§
1. ef
M e
M e
M eh
97.6s
M e
98.7s
99.1s
-
-
—
M e
M e
99. 3e
99.5s
99.9s
17.67
452
*Treatment-days within a row sharing the same letter do not differ signi-
ficantly (P < .05) (modified Smirnov Test).
555
-------
TABLE 14.18. RELATIVE CUMULATIVE FREQUENCIES FOR GERMINATION OF
TRAGOPOGON DUBIUS DURING 1976 ON ZAPS II
Day
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
CRG
n
OPC
0
0
0
0
20. Oe
37. le
56. 5e
62. 8e
66. 8e
73. le
79.4efh
80.0ef§h
82. 3e
84. 6e
85. 7e
88. 6e
89. 7e
91. 4e
93. le
94. 8 e
96. 5e
n e
ii e
—
—
_
98. 2e
99. 3e
99. 9e
ii e
ii e
13.25
175
HA
0
0
0
0
61. 9f
75. 8f
84. Of
85. Of
88. lf
90. 7f
93.3f§
H f
93. 8e
94. 3e
n e
94. 8e
95. 3e
95. 8e
ii e
n e
n e
98. 9e
H e
_
_
_
99. 4e
M e
n e
99. 9e
ii e
19.98
194
-
Plot*
IIB
0
0
0
0
49. 7f
80. 4f
85. 9f
90. 3f
M f
90. 9f
" ng
91.5fh
92. 6e
M e
93. 7e
94. 3e
96. 5e
M e
n e
n e
M e
97. 6e
98. 2e
— .
«
_
98. 8e
99. 9e
it e
H e
H e
17.09
181
••
IIC
0
0
0
0
25. 7e
37. 7e
50. 8e
57. 6e
65. 5e
73. 9e
79 . leh
80.7ef
83. 3e
84. 9e
85. 4e
85. 9e
87. 5e
90. 6e
92. 7e
95. 3e
95. 8e
96. 9e
97. 4e
^
^^
99. Oe
ii e
99. 5e
11 e
it e
13.24
191
IID
0
0
0
0
31. 9e
41. 3e
54. 9e
66. 2e
68. le
69. 5e
71. 8e
77.0e§
84. Oe
87. 3e
90. 6e
92. Oe
92. 9e
ti e
ti e
n e
93. 4e
96. 7e
98. le
_
99. 5e
n e
H e
100. Oe
n e
13.73
213
*Treatment-days within a row sharing the same letter do not differ signi-
ficantly (P £ .05) (modified Smirnov Test).
556
-------
o Trggopogon dubius
1976 COLLECTION
cc
LU
CD
I ^ v*
_J
^^
A c
011N30d3c
o
g30-
1
cc
£20-
0
h-
LJ
O
i.i C\ —
MM
5
I
r
n
r
i
'i
-
./
i
•*
/
L
7
\
10
da1^
U
d
r
?
h
a:
p
••Mi
^ 9
IA
C
2(
1C
89 '
LL-^-|
5*2
)
«
/o
30 <
1
1=1 0. J
day 5
" r
L IB
n 88%
M
1 pi 1 1 PI
* 10 20 30
1 55.8
\
\ day 5
1 rD
91%
V
10 20
DAYS
30
10 20
DAYS
30
Figure 14.50. Germination peak and distribution for Tragopogon dubius
collected in 1976 from ZAPS I.
557
-------
g TragopOQon dubius 1976 COLLECTION
H (3x61.9
|30-p\
LU
^20-
o
H
^ 10-
Ld
O
a:
LJ
a. 0 -
4
z:
0
£=30-
z
cc
MhM)
hi
£20-
-j
^
o
h-
LJ
% 0
-
•
\
Lr
a- 4
\ day 5
HA
90 %
rn n
i * * n
5x
T
49. r
\ day 5
IB
84%
s
L^rJl n, ^
9 f /
10 20 30 4 10 20 30
day 5
EC
n 85 %
H
_
K^^ —
10 20 30 4
••
\ day 5
JL ID
95%
MM
HI
u\ ^ .
\ 10 20 30
DAYS DAYS
Figure 14.51. Germination peak and distribution for Tragopogon dubius
collected in 1976 from ZAPS II.
558
-------
o Tragopogon dubius
30-
1976 COLLECTION
LU
C9
O
h-
t; 10-
LJ
O
cr
LU
o_ n
day 5
*P
OFF PLOT
CONTROL
81%
in
n (1
LJ U LJ | l-L^
4 10 20 30
Figure 14.52. Germination peak and distribution for Tragopogon dubius
collected in 1976 from the Off Plot Control.
559
-------
ZAPS-29 SEPT. 1977
= ~I2.16491+206.182X
-z.
o
H
O
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Figure 14.54
I 23456789 10
THEORETICAL S02 DOSE, PPHM
Regression of percent mycorrhizal infection on
theoretical S02 dosage from collection 29 (mid-
September) during 1977 on ZAPS II.
560
-------
JULY a SEPT.- 1977
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IIA MB IIC I ID
Figure 14.55. Percent mycorrhizal infection on ZAPS
I and II from collection 26 (July)
during 1977.
OPC IIA IIB IIC lib
26 29 26 29 26 29 26 29 26 29
COL LECTION S
Figure 14.56.
Percent mycorrhizal infection on
ZAPS II from collections 26 and
29 (July and September) during
1977.
-------
The data representing the mycorrhizal infection levels, as determined by
Newman's point intersection technique as well as the corresponding absorbance
readings, can be found in Appendix 14.4. The Kruskall-Wallis test indicated
significant (P < .001) differences for the visually determined infection
levels in both collection 26 (H = 31.384, k = 8) and collection 29
(H = 26.314, k = 4).
Specific plot pairs were examined for significant (P <. -05) differences
by the Wilcoxon two-sample test. Assuming no change in infection levels
(H : y = y ), two alternative hypotheses were made:
(1) H : y > y . Mycorrhizal populations decrease as the dosage deliv-
ered to the plot increases (for collection 26, when mycorrhizal
data is available for both sites, a ZAPS II plot is considered to
have received a higher canopy level concentation [see Section 10,
Figure 10.4] than the "same" ZAPS I plot, so that infection levels
for ZAPS I plot X > ZAPS II plot X).
(2) H2: \il < y2. Mycorrhizal infection levels are stimulated to
increase as the dosage of SC>2 increases.
For collection 26, under the first alternative hypothesis (Table 14.19a),
it can be seen that the infection level is depressed on the higher treatment
plots. This pattern is particularly strong on 1C, IIC, and IID, in contrast
to the OPC and IB and to a lesser degree for IA, IIA, and IIB. Consistent
with this alternative, 1C and ID show higher infections than the similarly
designated ZAPS II plots. Examining the second alternative hypothesis
(Table 14.19b), the mid-July collection 26 also reveals significant (P j< .05)
differences that could be associated with a SC^ stimulation effect. The B
plots are higher than the A plots, but the pattern is broken by ID, and the
limited number of significant cases (4 out of 36) can be ascribed in part to
the expected number of Type 1 errors involved in multiple pair comparisons.
For the fall collection 29, under the first alternative hypothesis
(Table 14.20a), the mycorrhizal levels are strongly depressed, with the
increasing ambient S02 concentrations on the ZAPS II site itself. Examining
the second alternative hypothesis (Table 14.20b), the IIA and IIB plot infec-
tion levels are elevated, in contrast to the OPC.
Of interest was the significant (P 5 .05) discovery that percent mycor-
rhizal infection levels were negatively correlated (Spearman's rho = -0.238,
n = 88) with total sulfur accumulated in leaves on the OPC and ZAPS I and II
from collection 26. Although a positive correlation was found between sulfur
in leaves and sulfur in roots (rs = 0.301, n = 88) from the same collection,
a significant (P 5 .05) correlation (rs = -0.088, n = 88) was not found
between percent mycorrhizal infection and total sulfur in the roots. A
similar analysis of collection 29, which was comprised of ZAPS II and the
OPC (ZAPS I was not scored for mycorrhiza), demonstrated a continuance of
these relationships into the fall. The mycorrhizal infection decreased in
individual plants as the sulfur content of the leaves increased (rg = -0.602,
n = 42) . Root sulfur was correlated (rg = 0.312, n = 4) with leaf sulfur,
but sulfur in the roots did not appear to be directly (a = .05) associated
with a change in infection levels (rs = -0.051, n = 41).
562
-------
TABLE 14.19a. WILCOXON TWO-SAMPLE TEST FOR DIFFERENCES IN PERCENT
MYCORRHIZAL INFECTION ON ZAPS I AND ZAPS II FROM
COLLECTION 26 DURING MID-JULY, 1977, UNDER Hj
Percent
Infection
OPC
66
IB
65
ID
62
IIB
58
IA
58
IIA
58
1C
56
IID
49
IIC
35
31*
30*
27
23*
23*
23*
21*
14
IID
49
17*
16*
13*
9
9
9
7
1C
56
10*
9*
6
2
2
2
i
IIA
58
8
7
4
0
0
.e. :
IA IIB ID
58 58 62
884
773
4 4
0
IB
65
1
H0: ]i1 = y2
El: yz > y2
The plot (PI) receiving the
lower S02 dosage will have
higher infection levels.
*P £ .05
TABLE 14.19b. WILCOXON TWO-SAMPLE TEST FOR DIFFERENCES IN PERCENT
MYCORRHIZAL INFECTION ON ZAPS I AND ZAPS II FROM
COLLECTION 26 DURING MID- JULY, 1977, UNDER H2
Percent
Infection
OPC
66
IB
65
ID
62
IIB
58
IA
58
IIA
58
1C
56
IID
49
IIC
35
31
30
27*
23
23
23
21
14*
IID
49
17
16
13
9
9
9
7
1C
56
10
9
6*
2
2
2
1
IIA
58
8
7*
4
0
0
.e. :
IA IIB ID
58 58 62
884
773
4 4
0
H : y = y
0 1 2
H : y < y
2 1 2
Increased S02 dosage on
plot (y ) will increase
infection levels.
IB
65
1
a
*P < .05
563
-------
TABLE 14.20a. WILCOXON TWO-SAMPLE TEST FOR DIFFERENCES IN PERCENT
MYCORRHIZAL INFECTION ON ZAPS II AND THE OPC FROM
COLLECTION 29 DURING SEPTEMBER, 1977, UNDER Hx
Percent
Infection
HA
62
IIB
53
IIC
42
OPC
41
IID
23
39*
30*
19*
18*
OPC
41
21
12
1 i.e.:
IIC
42
20*
i 1 ^ n
IIB
53
9*
, : u, > y.
The plot (yi) receiving the
lower S02 dosage will have
higher infection levels.
*P < .05
TABLE 14.20b. WILCOXON TWO-SAMPLE TEST FOR DIFFERENCES IN PERCENT
MYCORRHIZAL INFECTION ON ZAPS II AND THE OPC FROM
COLLECTION 29 DURING SEPTEMBER, 1977, UNDER H2
Percent
Infection
HA
62
IIB
53
IIC
42
OPC
41
IID
23
39
30
19
18
a
OPC
41
21*
12*
1
i.e. :
IIC
42
20
11
IIB
53
9
H0: yj = y2
H. -.I <• 1 1
2 . y i ^ y2
Increased SO? dosaee on a
plot (y
infecti
2) will increase
on levels.
*P < .05
564
-------
The morphology of both the mycorrhiza and the A. smithii roots were
studied microscopically and a series of photomicrographs prepared (Figures
14.57 and 14.58). Highly swollen and abnormally large interior vesicles were
found in roots from the IB plot, collection 26 (Figure 14.58G). Samples from
IIB, collections 26 and 29, contained an extremely large number of exterior
vesicles and attached hyphae (Figure 14.57C) compared to roots from any of
the other plots sampled, particularly IID, collection 29, where no exterior
vesicles could be found. A general reduction in root width and an increased
browning were observed to be associated with increased SC>2 dosage on the
ZAPS II collection 26. ZAPS I collection 26 and ZAPS I and II collection 29
were not examined for such characteristics.
DISCUSSION
In 1975, we hypothesized that the plant species on the medium and high
treatment plots of the ZAPS sites would be severely damaged or killed outright
during the growing season. In the TIR, we stated that this hypothesis had not
proven valid after continuous fumigation during two growing seasons on ZAPS I
and one growing season on ZAPS II (Gordon et al. , 1978). Studies carried
out on these sites during the 1977 growing season demonstrated that damage to
the plant species cannot be easily detected by field observation of necrotic
foliage or measured quantitatively by loss of plant diversity or biomass
(Dodd et al. , 1978). If the initial indications of damage in a grassland
ecosystem cannot be ascertained either by acute visible leaf injury or through
quantification of loss of diversity and/or net productivity after two or three
years of continuous SC>2 fumigation at levels exceeding the average annual S02
concentrations in Anaconda, Montana (Montana DHES, 1978), or Sudbury, Ontario
(McGovern and Balsillie, 1974; Linzon, 1973), the research efforts on the
ZAPS sites have created even more uncertainty about the phytotoxicity of S02-
For instance, why do the aerial infrared photographs taken of the ZAPS
sites in 1975, 1976, and 1977 (Taylor, 1976; Schott et al. , 1976; Osberg,
1978) visually demonstrate a definite gradation of reflectance across the
different treatment plots on each of the ZAPS sites during and after the
growing season, and yet no significant S02~caused necrotic or chlorotic
spotting or flecking has been reported to date? We have observed significant
amounts of early senescence of western wheat-grass foliage on the higher
treatment plots (Gordon et al. , 1978), as had Dodd et al. (1978), but no one
has reported any typical S02~caused foliar necrosis on the treatment plots.
Therefore, any serious vegetation damage which may be occurring on the ZAPS
sites is not being manifested as "typical" S02~caused foliar necrosis. If
this is the case, field and controlled fumigation chamber research studies,
which primarily depend upon quantification of the amount of S02~caused
necrotic foliage to ascertain the dose-duration-response of plant species
(Hill et al. , 1974; Davis et al. , 1966), are basically academic exercises
which can form no basis for truly protective ambient S02 standards.
The ZAPS field investigation is a unique study and represents the first
attempt to fumigate relatively large areas of a grassland ecosystem during
several growing seasons. Because it is a unique experiment, great care must
be taken to interpret the fumigations and their various parameters. One of
565
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Figure 14.57. Endomycorrhizae of Agropyron smith-it.
A. Exterior vesicles and hyphae from ZAPS plot IIB,
collection 26.
B. Cross-section of root from the OPC, collection 29,
showing interior vesicles in outer cortical cells.
C. Mass of exterior vesicles and hyphae from ZAPS plot IIB,
collection 26.
D. Interior vesicles in outer cortex as viewed through
epidermis; whole mount of root from OPC, collection 26.
Figure 14.58. Endomycorrhizae of AgropyTon smith-ii.
E. Arbuscular stage in whole mount of root from ZAPS
plot IIB, collection 26.
F. Cross-section of root from OPC, collection 29,
showing hyphae entering through root hair.
G. Enlarged, abnormal interior vesicles in root from
ZAPS plot IB, collection 26.
H. Interior vesicles and hyphae in whole mount of root
from ZAPS plot IIB, collection 26.
566
-------
Figure 14.57. Endomycorrhizae of Agropyron smithii.
567
-------
Figure 14.58. Endomycorrhizae of Agropyron smithU.
568
-------
the major problems on the ZAPS sites has been to determine the actual amount
of S02 impacting the flora and fauna on treatment plots. Ambient concen-
trations determined by the continuous analyzer are significantly higher
(Section 10) than the concentrations maintained within the plant canopy on
the intentionally-fumigated plots, reflecting the location of the sampling
probes at the extreme top of the canopy. The interrelationship of dose and
species response cannot be fully described at this time, as the available
ambient data only describe an upper limit of the S02 concentrations. Until
the vertical profile of S02 concentrations is quantified, this limitation of
the ZAPS work to setting protective ambient air standards for grasslands must
be recognized.
Another major problem that became evident during the three seasons of
fumigation was the fact that the A plots, or controls, on both ZAPS sites
were receiving quantifiable levels of S02. Thus there are, in actuality, no
real control plots at the ZAPS sites. While this is not an insurmountable
problem, it is important to remember that the sulfur concentrations in
the physiological responses of flora and fauna on the A plots cannot be used
as zero dosage comparisons to species on the B, C, and D plots. In Section 5
of this report, Gordon &t al. reported the problems encountered in the
Trail, B.C., study (Katz et at. , 1939), because the investigators believed
that a control area actually existed 70 to 90 miles downwind from a smelter.
The ambient S02 concentrations in southeastern Montana before the coal-fired
power plants at Colstrip began operations have been reported by several state
and federal agencies, as well as other investigating teams (Department of
Health and Environmental Sciences, Department of Natural Resources and Conser-
vation, the Environmental Protection Agency, PEDCo-Environmental Specialists,
Inc., the Northern Cheyenne Tribe, and Battelle Pacific Northwest Laboratories)
The conclusion of all was that the average 24-hour ambient concentration of
S02 was below detectable levels before the Colstrip power plants went on-line.
The OPC data we utilized during 1976 and 1977, in juxtaposition with the data
obtained from our ZAPS studies, are important in understanding the potential
impact of S02 at the concentrations being received by the flora and fauna on
the A treatment plots.
The last major problem encountered during the four years of ZAPS
studies is the real possibility that our study designs, which evolved before
and after the ZAPS investigations, are potentially incapable of quantifying
the long-term impacts of ambient S02 at any realistic annual concentration
(0.5 to 1.0 pphm) when applied to a short-term fumigation study (4 years vs.
80 years). These concentrations could and probably will occur during the
next 40 years if the Fort "Union Basin becomes industrialized because of its
vast coal deposits. Our primary concern is that potential long-term conse-
quences of chronic air pollution to the grassland and ponderosa pine eco-
systems cannot be easily or quickly ascertained. For instance, until the
viability and germination studies on the 1976 seed crop of several species
from the ZAPS sites were completed, analyzed, and studied during 1977, we
did not realize that: (1) There was an impact on these processes by S02, and
(2) this type of impact study has rarely been utilized in field or controlled
fumigation studies. Also, our work on the mycorrhizal association of western
wheatgrass during 1977 and the winter of 1978 disclosed that there is a
disruption and/or change in this association in vegetation fumigated with
569
-------
different levels of SOo. It has not been determined whether this disruption
and/or change is caused directly or indirectly by the S02 fumigation of host
species, but it is known and fairly well accepted that this reciprocal symbi-
otic relationship between fungi and root tissues probably occurs in all
higher plant species and is beneficial to their health and growth (Zak, 1964).
The mycorrhizal association of the other numerous grass and forb species on
the ZAPS sites has neither been identified nor studied. If the effects of
S02 on possible mycorrhizal associations of these other species are to be
determined, a study period of several years would be required.
This unique field S02 fumigation study was initiated to better understand
the potential impact threshold levels of ambient S02 upon a grassland eco-
system. Thus far, the ZAPS study has demonstrated that these impacts are
probably more subtle and evolve more slowly than any of the investigators
originally believed. If there is a quantifiable ambient S02 threshold, below
which no important biological and/or economic damage will occur, it has not
been established at this time.
Sulfur accumulation in the foliage of the grass and forb species
collected at the ZAPS sites during 1976 demonstrated that vegetation analyses
can be utilized in pristine areas to determine the presence of chronic levels
of S02. The limitations of this technique, however, may become apparent
after two or three years of continuous, chronic fumigation because it
appears that residual sulfur in the root tissues or biologically available in
the soil solutions may mask much of the ambient sulfur taken in by foliage
during any single year at chronic S02 levels (0.5 to 2 pphm) . Cronan e~b al.
(1978) have documented the large contribution (76%) of sulfate anion to the
electrical charge balance in the soil water solution of chronically-polluted
ecosystems of New Hampshire. Sulfur levels in western wheatgrass roots
collected at the two Anaconda sites during 1977 at three different periods
during the growing season adequately demonstrate the presence of residual
sulfur in these plant parts in chronically- and acutely-polluted areas.
Probably the most important aspects of sulfur accumulation studies on
the ZAPS studies thus far are that:
(1) Sulfur accumulation is a continuous phenomenon in the foliage of
most species on the ZAPS being tested. If this continuous increase
in live foliage of the plant sample cannot be detected, the analysis
of current year's dead tissue will more effectively demonstrate
the phenomenon.
(2) Sulfur accumulation in foliage collected from the ZAPS sites can be
used to distinguish the higher S02 dosage areas from lower dosage
areas within each plot (see Tables 14.3 and -14.4).
(3) Plants with higher sulfur levels in foliage across treatment plots
generally manifest earlier leaf senescence and greater reductions
in seed viability, percent seed germination, speed of germination,
and mycorrhizal association. Tests for significant correlations
between these quantifiable changes and the sulfur levels in the
foliage have been undertaken only for mycorrhizal associations at
570
-------
this time. Of the grass and forb species collected during the
1977 season, only western wheatgrass has been analyzed for sulfur
content. Thus we believed it too early to test for other possible
correlations prior to finishing all studies on the 1977 foliage and
seed collections.
Simulated "rainfall event" and "overwintering" experiments on foliage
from the D plot demonstrate that a portion of the sulfur on and possibly in
the foliage from the ZAPS sites can be removed. Because sulfur can be reduced
in such a manner, the use of such accumulation in foliage to determine chronic
ambient S02 fumigations will probably have to take into consideration the
amounts and durations of rainfall in the study area.
In the TIR we reported that species of grasses and forbs common on the
ZAPS sites would be grown on Anaconda soils brought to the Botany gardens in
Missoula to determine the specific contribution of the soil to residual
sulfur levels. These species were established on soil collected from the
DHES Highway Junction and Pumphouse air monitoring sites in Anaconda. Data
on the influence of 80 years of S02 pollution on these soils in relationship
to potential excessive sulfur uptake is being gathered and will be reported
in the Fifth Interim Report.
Analysis of western wheatgrass samples collected during 1977 from the
two Anaconda air monitoring sites (Table 14.6) show that after years of low
and high level SO2 fumigation, the sulfur content of root tissue exceeds that
accumulated by the foliage during the growing season. Portions of the excess
sulfur undoubtedly end up in the rhizosphere of S02-impacted plants. Unfor-
tunately, very few air pollution studies have included research to ascertain
the potential indirect impacts of sulfur accumulation in the soils on the
microflora and microfauna.
Lack of time during 1977 allowed only a limited preliminary study on the
population or presence of mycorrhizal association in the root tissues of the
Anaconda samples. This study disclosed that mycorrhizal fungi were not
present in root tissues from the DHES Highway Junction site. This cannot be
attributed singularly to the S02 or sulfur levels in the ambient air or plant
tissues because areas of the Deerlodge Valley affected by the Anaconda copper
smelter emissions also are seriously impacted by heavy metals which have
eliminated a large portion of the soil fungal populations (Hartman, 1975).
The ZAPS sites, however, unlike the Anaconda area, are being impacted by
only one phytotoxic gas, and studies on the potential impacts of any excessive
rhizosphere sulfur levels should be explored. The indirect effects of S02
fumigation upon ecosystems may be the most serious and long-lasting impact
caused by the emissions of coal-fired power plants, which release relatively
small amounts of toxic trace metals in comparison to nonferrous smelters.
The germination and viability studies carried out in 1976 on seed
collections from the ZAPS sites were essentially a pioneering effort to deter-
mine the impacts of S02 fumigation upon ecosystems. While earlier air
pollution investigations (Katz et al. , 1939) have included viability tests on
seeds from S02-impacted trees, we know of no investigation in which seeds
571
-------
from plants fumigated with known and different concentrations of S02 were
tested for viability, percent germination, and rate of germination. Because
the 1976 seed collections were our first attempt to ascertain the potential
impacts of different S02 levels at the ZAPS sites on seed viability and
percent germination, it is probably premature for us to discuss the possible
consequences of seed damage from S02 fumigation until we have completed these
same studies on the 1977 seed collections.
However, there are three assumptions which are suggested at this time by
the results of these seed studies. First, there have been numerous articles
in the air pollution literature discussing the possible existence of invisible
injury to plants caused by phytotoxic gases. If one accepts that visible
injury is damage to any portion of the plant structure which can be determined
by careful visual examination or by weighing or counting the plant structures,
seed viability and percent germination rate affected by phytotoxic gases
should be considered an invisible injury. The numerous investigators who
have fumigated various plant species with various levels of S02 to determine
the effects on anatomical structure or metabolic pathways of the plant species
have not tested the seed viability and percent germination of these species.
Any damage remained invisible to the investigators and was not reported in
the literature.
The second point is the reduction in seed weight across the treatment
plots which, in general, paralleled the reduction observed in viability,
percent germination, and rate of germination. This loss of seed weight in
the grass species has some serious implications, not only to these species
but very possibly to the yields of agricultural grain species grown through-
out the Fort Union Basin.
The third point deals with the implications of the results obtained from
the germination studies of the seeds of Tragopogon dub-ius, an introduced
species to the Fort Union Basin and an unwanted forb. The data obtained thus
far from the seed germination studies on T. dubius suggest that S02 fumi-
gations may indirectly enhance both percent germination and rate of germi-
nation. If this is true, the impacts of increased colonization of both
grazing lands and reclaimed strip mined lands by this forb species could
cause a loss of carrying capacity and a reduction in the success of recla-
mation efforts in southeastern Montana.
A normal rate of seed viability of the indigenous plant species of this
grassland ecosystem of southeastern Montana is an extremely important part of
the continuing health and growth of this agricultural area. Long-term impacts
could be serious if S02 fumigations at low chronic or high acute concentra-
tions reduce seed viability or change the rate of germination by extending
the time needed for seeds to germinate and establish their roots in the soils
of this semi-arid area. Because of the importance of seed viability and the
results thus far obtained in tests on our 1976 seed collections, we have
continued these studies on 1977 seeds and will also be collecting them during
1978 for future studies.
We conducted vegetative phenology studies of western wheatgrass during
the past two growing season (1976-77). During 1977, we expanded the number
572
-------
of tagged plants by increasing the number of subplots used in the study. It
is important to understand the rate of leaf senescence across the treatment
plots of the two ZAPS sites. This became apparent when we realized that
senescence is the only clear visible response of western wheatgrass to S02
dosages, not the necrotic leaf lesions or the tan/ivory chlorosis obtained in
controlled, acute fumigation chamber studies (Tingey et at. , 1978; Hill et at.
1974). Early leaf senescence is the visible manifestation of this grass
species to chronic levels of S02 fumigation and is quantified only after
careful comparison of senescence rates on different treatment plots over the
entire growing season. Therefore, it appears that the data in the literature
on the impacts of short-term, acute S02 fumigations are of relatively little
use in preparing or establishing ambient SOo standards.
Data on the rate of leaf senescence (or percent necrotic) of western
wheatgrass (Tables 14.10a and 14.10b) show that while there are significant
differences between some of the treatment plots on both ZAPS sites, these are
not necessarily related to each dosage level. There was never more than 15%
difference in the number of necrotic leaves between any of the treatment
plots, including the OPC, at any given study period. If leaf necrosis is the
criteria used for damage on the ZAPS sites, it seems that either there are
few or no consequential impacts from the chronic S02 fumigations, or leaf
necrosis is not an adequate indication of air pollution impacts on grassland
ecosystems. In Section 5, Gordon et at. discuss the fact that air pollution
damage to pine foliage can mimic those normal damage symptoms which occur on
foliage collected from pristine areas. This discussion of data on conifer
foliage pathologies suggests that no single damage manifestation can be
utilized to determine the differences between health/growth/disease character-
istics of foliage collected from chronically-polluted and pristine areas. If
one compares the percent necrotic leaves of western wheatgrass from the OPC
to' those from the ZAPS sites (Tables 14.10a and 14.10b), one should under-
stand that if an entire western wheatgrass ecosystem was exposed to ambient
air S02 levels of 1 to 5 pphm for varying durations during the growing season,
field investigators would not be able to detect the potential impacts by
visually inspecting the foliage.
Although by no means conclusive, the results of this investigation indi-
cate that certain levels of S02 fumigation, such as those on the ZAPS C and
D plots, have a definite detrimental impact on mycorrhizal populations which
inhabit Agropyron smifhli. Besides data generated from the 1977 collection
period, photographed morphological evidence substantiates the finding of
impairment of the symbiotic state by S02 (Figures 14.57 and 14.58).
Statistically significant were the findings that: (1) Spectrophotometer
absorbance readings are related to and potentially predictive of percent
mycorrhizal infection; (2) mycorrhizal levels were negatively correlated with
sulfur concentrations in the leaves of A. smithii from the same collection
period; (3) mycorrhizal levels were not correlated with sulfur levels in
roots, and (4) theoretical S02 dosage was inversely related to mycorrhizal
infection levels on ZAPS II in the fall collection.
Taking into considerations heterogeneity of biological response within
naturally-varying populations, several additional trends or patterns emerged
573
-------
from this study. For example, roots from C and D plots consisted of a greater
number of thinner, senescent roots, whereas roots from the OPC tended to be
thicker, less senescent, and with a fatter and possibly more persistent
cortex. The following high probability trends or patterns also emerged from
this study: (1) High levels of infection and exterior vesicle formation were
associated with low S02 dosage plots; (2) populations generally declined or
fewer roots were infected on the higher (C and D) dosage plots; (3) abnormal,
swollen interior vesicles, similar to those formed as a result of a lack of
nitrogen, were found on the IB plot, and (4) a trend towards less variability
of infection levels was associated with increasing fumigation levels.
The fact that EDM exist within an enormous variety of plant species and
flourish under an extremely wide range of environmental conditions suggests;
that these are organisms of widely adaptable behavior and tolerance. The
depressions in their population seen on the ZAPS plots, which are edaphically
far more similar than dissimilar, are thus most likely an indirect result of
unusual modifications in the health state of the host plant, rather than a
direct result of S02 fumigation. Explanations of the manner in which myqor-
rhizae are impacted by alterations in host plant metabolism are a matter
worthy of consideration, further experimentation, and future investigation.
At this point in time, explanations of this sort would be highly speculative.
However, by utilizing information garnered from S02 impact studies on other
obligate parasites or symbiotic states, one can obtain a greater understanding
of the trends elicited in this study.
Occurrence of an unusually large number of exterior vesicles on roots
from IIB, when compared to any of the other plots, might be interpreted in
the following manner: Either the fungus has entered into its sporulating
stage as part of a repetitive infectious process due to the very high suit-
ability of the habitat, or the fungus is undergoing a typical reaction to
harsh, extreme, or otherwise adverse environmental conditions. This and
observations of very swollen interior vesicles on the IB plot lead to the
conclusion that the habitat is quite unsuitable. Although such a change
could perhaps also be wrought by stress induced as a consequence of sudden
alterations in the host plant's competitive ability, the condition is, never-
theless, abnormal.
With respect to the impact of S02 on other aspects of plant metabolism,
Dodd et al. (see Section 13) noted a tendency towards a decrease in rhizome
biomass across the plots, which coincides with the experimenter's observation
of a similar decrease in root size. A surplus of carbohydrates in roots is
thought by some to be the main fungal attractant, utilization of such by
EDM preventing the attraction of more serious pathogens. If S02 fumigation
caused either a decrease in proper photoassimilates transported to the roots
due to an overall decrease in root carbohydrates, or an increase of tissue
leakage within the roots, suitable mycorrhizal nutritional requirements
might not be maintained.
A well-established theory of plant pathogenicity associates tissue
leakage or quantities of cellular materials released by exosmosis with
disease-induced stress (Wheeler and Hanchey, 1968). That mycorrhizae do not
increase tissue leakage is evidenced by their induction within a host of
574
-------
increased cortical and cytoplasmic volume, increased mineral uptake, and an
overall increase in vigor. Plasmolysis and consequent tissue leakage,
however, are characteristic of S02 damage (Ziegler, 1975). Leakage of
vascular cylinder contents to root exteriors would most likely be deleterious
to EDM because it is within the phloem and endodermis that phenols and poten-
tially fungitoxic quinones exist in greatest concentration. It is thought
that only in the more successful pathogens, those which cause a systemic
infection or otherwise penetrate the endodermis and enter the vascular
cylinder, does there exist the capability of oxidizing the phenols and
quinones to non-toxic insoluble pigments (Miles, 1968). Less successful
pathogens are considered incapable of extensive quinone oxidation. Although
the relationship between such fungitoxic phenols and EDM is unknown, the fact
that EDM do not penetrate the endodermis and vascular cylinder is suggestive
of a chemical barrier within these tissues, which would be deleterious to EDM
if it leaked, as might happen under conditions of unusual stress.
Once again, it must be stated that the physiological relationship, in
terms of metabolic pathways, has been virtually unexplored in the case of EDM,
due to the lack of technique for culturing the endophyte separately from the
host. In view of the delicate metabolic balance exhibited in any symbiotic
state and the potential for disruption of this state in EDM by S02, theories
concerning such at this point in time, however speculative, are nonetheless
pertinent.
In conclusion, it is suggested that in response to S(>2 fumigation, the
root system of Agropypon smi-th'ii- on the ZAPS sites is undergoing modification
resulting in either exclusion or lessening of the mycorrhizal habit.
CONCLUSIONS
The 1977 studies on vegetation collected on and/or studied in situ at
the ZAPS sites demonstrate that there are significant impacts to selected
species fumigated by various S02 concentrations. Levels of S02 between and
within treatment plots are variable and, in general, substantially lower in
the vicinity of most of the foliage of the plant species than reported in
earlier publications. The studies conducted and completed during 1976 and
1977 indicate that seed viability and germination studies across treatment
plots and the continuation and expansion of mycorrhizal association studies
of western wheatgrass would be the most productive investigations during the
1978 season. Both of these studies are unique to controlled fumigation, and
grass mycorrhizal studies have never previously been reported in field investi-
gations of air pollution impacts.
Our 1978 studies will attempt to verify the results obtained in these
two studies during the last interim report period. To adequately test the
results, we will increase the mycorrhizal collections from each treatment
plot and utilize collections from earlier portions of the growing season
(June) as well as at the end of the seasons. Also, another OPC will be
established in the Port Howes district of the Custer National Forest during
the spring of 1978 so that adequate sample sizes can be utilized to contrast
collections from the ZAPS treatment plots.
575
-------
From the studies completed during the last three years on the ZAPS sites,
it has become totally evident that seasonal low-level S02 fumigation impacts
upon grassland ecosystems are subtle and difficult or impossible to quantify
by examining foliage for S02-caused necrotic lesions or typical discoloration.
It also has become apparent that S02 causes impacts directly or indirectly to
plant functions (seeds and mycorrhizal association) which have remained invi-
sible to both field and fumigation chamber investigators.
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583
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APPENDIX TABLE 14.1. EFFECTS OF REMOVING OUTLYING SULFUR OBSERVATIONS
ON MEAN VALUES AND 95% CONFIDENCE INTERVALS* FOR
TOTAL SULFUR AT THE OFF PLOT CONTROL (OPC) AND
ZAPS IA ON SEPTEMBER 11, 1977.
Sample
1
2
3
4
5
6
7
8
9
10*
OPC
ppm S
750
800
900
950
800
850
900
850
800
2,150
IA
Sample
8NW
8SE
9NE
10NE1
12SE
14NW
17SE
19NE
12NW
20SE
ppm S
1,050
950
1,350
1,950
900
950
1,000
800
1,150
1,000
Mean Values* and 95% Confidence Intervals
OPC including sample 10
x = 922
X + t^^r =
x - ts_ = 746
IA including sample 10NE
¥ = 1,069
x + tg- = 1,268
x - tg- = 901
OPC excluding sample 10
x = 842
x - ts- = 795
IA excluding sample 1QNE
x = 1,006
x 4- ts- = 1,128
x - tg- - 897
*x ±
i These values were statistical outliers according to Dixon's Criteria at
the 95% significance level after: Grubbs, Frank E. 1969. Procedures
for Detecting Outlying Observations in Samples. Technometrics , 2(1).
^Statistics shown are based on Iog10 transformations of the raw data.
584
-------
50001
4000-
3000
2000
QL
U_
_J
1000
2: TOO
EARLY SEPT. OUTLIERS (COLLECTION 29)
I
I
OPC IA IB 1C
TREATMENT PLOT
ID
Appendix Figure 14.1. Means and 95% confidence limits (log-j^) of total
sulfur in A. sirrithii; outliers removed are indi-
cated by + .
585
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APPENDIX TABLE 14.2a. SUtFUR (PPM) IN LIVE AND DEAD PLANT MATERIAL COLLECTED FROM ZAPS I, TREATMENT A, IN 1976.
Collection
Date
April 6
May 13
June 1
June 18
July 4
August 2
August 16
Sept 1
Sept 17
Oct 16
Julian
Date
97
134
153
170
186
215
229
245
261
290
A. snrithii
Live Dead
1,300 500
700 ns
850 as
1,000 ns
700 500
1,000 900
850 750
1,275 1,225
745 800
(731) (790)
850 750
K. cristata
Live Dead
1,675 600
700 ns
550 ns
900 ns
650 550
800 500
700 550
875 750
575 590
(568) (581)
800 800
P. sandbergii
Live Dead
ns ns
500 ns
550 ns
550 ns
ns 400
ns ns
ns ns
ns ns
ns ns
ns ns
A, longiseta
Live Dead
ns 400
ns ns
ns ns
ns ns
1,000 ns
750 700
950 850
900 600
800 650
ns 650
A. mills fo tiun
Live Dead
800 700
600 ns
550 ns
850 ns
550 550
550 650
750 600
900 800
650 650
650 600
A. frigida
Live Dead
1,100 1,100
1,250 ns
— na
1,550 ns
1,300 na
1,250 ns
1,300 1,300
1,550 1,300
1,300 950
1,350 1,150
ns » not sampled
- missing sample
( ) - antilog log x
APPENDIX TABLE 14.2b. SULFUR (PPM) IN LIVE AND DEAD PLANT MATERIAL COLLECTED FROM ZAPS II, TREATMENT A, IN 1976.
Collection
Date
April 10
May 8
May 31
June 18
July 6
August 3
August 15
Sept 1
Sept 19
Julian
Date
101
128
152
170
188-
216
228
245
263
A. snrithii.
Live Dead
1,716 350
800 ns
850 ns
1,050 ns
1,050 ns
800 800
950 850
800 850
745 830
(735) (814)
K. aristata
Live Dead
1,575 500
650 ns
750 ns
900 ns
500 ns
650 550
650 700
850 650
800 519
(790) (502)
P. sandbergii
Live Dead
ns ns
650 ns
600 ns
700 ns
ns 450
ns ns
ns ns
ns ns
ns ns
S. in.zn.du.la
Live Dead
ns 550
800 ns
800 ns
1,100 ns
950 ns
1,150 950
1,000 750
1,100 850
1,050 800
A. millefolium
Live Dead
1,175 550
850 ns
700 ns
950 ns
650 650
600 700
850 700
750 600
900 1,000
A. frigida
Live Dead
1,600 750
1,550 na
913 na
1,350 ns
1,133 ns
1,250 na
1,350 1,050
1,550 750
1,550 1,200
ns • not sampled
( ) " antilog log x
586
-------
APPENDIX TABLE 14.2c. SULFUR (PPM) IN LIVE AND DEAD PLANT MATERIAL COLLECTED FROM ZAPS I, TREATMENT B, IN 1976.
Collection
Date
April 7
May 13
June 1
June 16
July 5
August 2
August 16
Sept 2
Sept 17
Oct 16
Julian
Date
98
134
153
168
187
215
229
246
261
290
A. smithii
Live Dead
1,400 600
1,050 ns
1,050 ns
1,350 ns
1,450 850
1,500 1,400
1,700 1,650
1,650 2,000
1,565 1,605
(1,538) (1,549)
1,200 1,450
K. eristata
Live Dead
1,575 500
900 ns
900 ns
1,425 ns
1,200 1,050
1,850 1,400
1,550 1,550
1,800 1,600
1,585 1,311
(1,525) (1,286)
1,250 1,250
P. eandbevffii
Live Dead
ns ns
950 ns
783 ns
850 ns
ns 500
ns ns
ns ns
ns ns
ns ns
ns ns
A. lontjiaeta
Live Dead
ns 725
ns ns
ns ns
ns ns
850 ns
1,050 1,050
1,200 1,050
1,300 1,150
1,000 1,000
ns 950
A. millefoHwn
Live Dead
1,275 —
800 ns
800 ns
1.200 ns
700 1,050
1.200 1,350
1,150 1,400
950 1,225
1,000 1,250
1,300 1,300
A. frigida.
Live Dead
1,700 1,150
1,950 ns
1,450 ns
1,850 ns
1,750 ns
1,933 ns
1,600 1,600
1,500 1,900
1,500 1,600
1,950 1,650
ns " not sampled
— » missing sample
( ) • antilog log z
APPENDIX TABLE 14.2d. SULFUR (PPM) IN LIVE AND DEAD PLANT MATERIAL COLLECTED FROM ZAPS II, TREATMENT B, IN 1976.
Collection
Date
April 10
May 11
June 1
June 21
July 7
August 3
August 15
Sept 2
Sept 18
Julian
Date
101
132
153
173
189
216
228
246
262
A, smithii
Live Dead
1,250 600
1,110 ns
1,300 ns
1,450 ns
1,600 ns
1,550 1,900
1,250 1,500
1,450 1,950
1,170 1,445
(1,122) (1,429)
K. apietata
Live Dead
1,050 550
800 ns
1,100 ns
850 ns
1,300 ns
1,550 1,350
1,050 1,250
1,350 1,300
1,069 912
(1,044) (903)
P. sandbergii
Live Dead
ns ns
975 ns
800 ns
950 ns
ns 850
ns ns
ns ns
ns ns
ns ns
S. vi.ridu.la
Live Dead
ns
1,275 ns
950 ns
1,350 ns
1,600 ns
1,300 1,200
1,100 1,350
1,600 1,500
1,300 1,600
A. millefoliwn
Live Dead
850 700
1,050 ns
1,050 ns
1,800 ns
1,100 1,400
1,300 1,550
775 1,300
1,350 1,350
1,100 1,150
A, frigida
Live Dead
2,125 1,050
1,350 ns
1,050 ns
1,900 ns
1,950 ns
1,750 ns
1,550 1,350
1,800 1,500
2,150 750
ns • not sampled
— • missing sample
( ) - antilog log x
587
-------
APPENDIX TABLE 14.2e. SULFUR (PPM) IN LIVE AND DEAD PLANT MATERIAL COLLECTED FROM ZAPS I. TREATMENT C, IN 1976.
Collection
Date
April 7
May 13
June 1
June 16
July 5
August 2
August 16
Sept 2
Sept 17
Oct 16
Julian
Date
98
134
153
168
187
215
229
246
261
290
A. amithii
Live Dead
1 ,300 800
1,350 ns
1,500 ns
2,050 ns
1,750 1,200
2,550 2,750
2,550 2,950
2,225 2,800
2,235 1,990
(2,143) (1,961)
1,950 1,800
K. crietata
Live Dead
1,200 850
1,200 ns
1 , 600 ns
2,250 ns
2,100 1,250
2,350 2,200
2,400 2,000
2,600 1,800
1,585 1,260
(1,554)(1,244)
2,050 1,550
P. aandbergii
Live Dead
ns ns
1,150 ns
1,450 ns
988 ns
ns 900
ns ns
ns ns
ns ns
ns ns
ns ns
A. longiseta
Live Dead
ns 750
ns ns
ns ns
ns ns
1,450 ns
1,250 1,400
1,750 1,700
1,275 1,500
1,550 1,250
ns 1,150
A. milte folium
Live Dead
900 1,050
1,150 ns
1,450 ns
1,650 ns
2,000 2,700
2,200 2,850
1,850 2,150
2,150 2,350
2,000 1,950
2,500 1,950
A> frigida
Live Dead
2,700 1,100
2,050 ns
2,050 ns
ns
3,100 ns
2,700 ns
2,350 2,325
3,150 2,100
3,200 1,350
3,100 2,800
ns » not sampled
— • missing sample
( ) " antilog log
APPENDIX TABLE 14.2f. SULFUR (PPM) IN LIVE AND DEAD PLANT MATERIAL COLLECTED FROM ZAPS II, TREATMENT C, IN 1976.
Collection
Date
April 9
May 11
May 31
June 21
July 7
August 3
August 15
Sept 2
Sept 18
Julian
Date
100
132
152
"5
189
216
228
246
262
A. smithii
Live Dead
1,100 400
1 , 150 ns
1,700 ns
2,200 ns
2,150 ns
2,616 2,850
2,200 3,400
2,450 3,200
1,925 2,630
(1,820) (2,505
K. aristata
Live Dead
1,675 550
1,550 ns
1,300 ns
2,250 ns
2,450 ns
2,650 2,250
2,250 1,950
2,550 2,050
1,775 2,094
(1,731)(1,956)
P. sandbergii
Live Dead
ns ns
1,450 ns
1,250 ns
1,250 ns
ns 1,100
ns ns
ns ns
ns ns
ns ns
S. viridula
Live Dead
ns 450
2,500 ns
1 , 600 ns
2,250 ns
2,600 ns
2,100 2,500
2,250 2,250
2,950 2,800
2,000 2,450
A. nrillefolimft
Live Dead
550 500
1,400 ns
1,200 ns
2,550 ns
2,200 2,450
2,350 3,750
2,150 2,800
1,800 2,250
2,725 2,100
A. frigida
Live Dead
1,250 800
1.650 ns
1,750 ns
— ns
2,325 ns
3,150 ns
3,050 3,350
3,950 2,800
2,550 2,725
n> • not sampled
— • missing sample
( ) « antilog log x
588
-------
APPENDIX TABLE 14.2g. SULFUR (PPM) IN LIVE AND DEAD PLANT MATERIAL COLLECTED FROM ZAPS I, TREATMENT D, IN 1976.
Collection
Date
April 8
Kay 13
June 1
June 16
July 4
August 2
August 16
Sept 2
Sept 17
Oct 16
Julian
Date
99
134
153
168
186
215
229
246
261
290
A. smithii
Live Dead
1,500 1,000
1,750 ns
1,950 ns
2,400 ns
2,600 1,519
3,175 4,725
3,450 3,200
3,800 4,100
3,105 2,700
(3,059) (2,639)
3,750 2,700
K. crietata
Live Dead
1,200 1,050
1,650 ns
2,017 ns
3,350 ns
3i850 2,100
4,275 2,850
3,400 2,350
3,400 2,650
3,210 2,145
(3,150)(2,115)
2,700 2,100
P. eandbergii
Live Dead
ns ns
1,550 ns
1,500 ns
1,900 ns
ns 2,350
ns ns
ns ns
ns ns
ns ns
ns ns
A. longiaeta
Live Dead
ns 800
ns ns
ns ns
ns ns
1,850 ns
2,100 1,700
2,350 1,800
2,400 2,100
2,050 1,950
ns 1,900
A. millefolium
Live Dead
1,350 1,600
1,300 ns
2,750 ns
3,600 ns
3,725 5,750
3,900 5,250
4,400 6,367
5,325 4,750
4,450 4,350
4,750 2,700
A. frigida
Live Dead
2,650 2,725
3,300 ns
3,400 ns
ns
5,150 ns
5,450 ns
4,250 4,200
5,550 3,850
5,800 3,400
5,250 4,300
ns - not sampled
—• • missing sample
( ) » antilog log x
APPENDIX TABLE 14.2h. SULFUR (PPM) IN LIVE AND DEAD PLANT MATERIAL COLLECTED FROM ZAPS II, TREATMENT D, IN 1976.
Collection
Date
April 9
Hay 13
May 31
June 21
July 7
August 3
August 15
Sept 2
Sept 18
Julian
Date
100
134
152
173
189
216
228
246
262
A. smithii
Live Dead
1,400 450
1,850 ns
3,250 ns
4,350 ns
4,200 ns
4,150 5,675
3,100 3,950
3,950 4,450
2,618 4,135
(3,150) (4,068)
K. avietata
Live Dead
1,625 600
1,300 ns
1,550 ns
3,750 ns
4,183 ns
3,550 3,250
3,550 3,800
3,950 2,900
3,223 2,511
(3,101)(2,467)
P. eandbergii
Live Dead
ns n&
1,400 ns
1,900 ns
2,400 ns
ns 1,800
ns ns
ns ns
ns ns
ns ns
5. viridula
Live Dead
ns 500
3,250 ns
2,150 ns
4,650 ns
4,850 ns
3,600 3,000
4,150 3,800
4,250 4,000
3,425 3,250
A. millefoliim
Live Dead
500 550
2,600 ns
2,800 ns
4,983 ns
3,875 4,750
4,100 5,400
4,950 5,500
6,000 4,550
4,150 2,850
A. frigida
Live Dead
1,450 850
2,700 ns
3,550 ns
ns
4,850 ns
5,150 ns
5,450 5,925
5,100 4,350
4,800 5,650
ns * not sampled
missing sample
( ) « antilog log x
589
-------
APPENDIX TABLE 14.3. SULFUR LEVELS (PPM) IN AiSKOPYKON SMlTHIt DURING 1977.
Collection No.
and Date
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
late April
mid-May
late May
mid- June
early July
mid- July
early August
late August
early Sept
late Sept
late Oct
Julian Day
JC
n
lt
h
Julian Day
X
n
li
i2
Julian Day
lc
n
lv
h
Julian Day
JC
n
l!
12
Julian Day
JC
n
ll
12
Julian Day
jT
n
ll
!2
Julian Day
JC
n
ll
12
Julian Day
JC
n
h
*2
Julian Day
x
n
ll
12
Julian Day
X
n
ll
X2
Julian Day
JC
n
ll
12
OPC
114
1,198
10
1,082
1,328
134
871
10
786
965
149
1,132
10
974
1,314
168
1,197
10
1,057
1,355
185
1,073
7
905
1,273
201
1,129
10
965
1,321
216
883
8
763
1,022
236
1,197
10
1,071
1,338
254
842
9
795
892
278
1,066
10
948
1,199
299
1,917
3
IA
112
1,448
9
1,248
1,680
132
1,081
9
981
1,191
148
1,172
10
1,116
1,231
166
1,050
10
981
1,124
183
1,011
10
796
1,285
200
1,202
10
1,068
1,352
217
880
10
817
949
234
1,200
10
1,019
1,414
253
1,006
9
897
1,128
272
1,276
10
1,060
1,536
300
1,643
5
1,279
2,111
IIA
112
1,466
10
1,295
1,659
130
1,538
9
1,435
1,649
148
1,212
10
1,112
1,319
166
1,209
10
1,126
1.299
182
1,184
10
1,098
1,275
199
1,037
10
979
1,097
215
1,224
10
1,142
1,312
233
1,038
10
892
1,208
251
905
10
810
1,010
269
840
10
732
965
290
1,675
2
IB
113
1,620
10
1,419
1,850
133
1,285
9
1,169
1,413
148
1,421
10
1,345
1,501
167
1,359
10
1,215
1,521
184
1,282
9
1,122
1,465
200
1,443
10
1,345
1,549
217
1,288
10
1,161
1,428
235
1,510
10
1,360
1,677
253
1,382
10
1,193
1,602
276
1,332
10
1,124
1,578
300
1,325
2
IIB
112
1,580
8
1,406
1,776
131
1,810
10
1,712
1,904
147
1,517
10
1,425
1,614
166
1,548
10
1,443
1,660
182
1,536
10
1,366
1,726
199
1,440
10
1,294
1,602
216
1,434
9
1,303
1,579
233
1,508
10
1,379
1,650
252
1,293
10
1,169
1,431
270
1,362
10
1,235
1,503
291
1,469
10
1,308
1,650
1C
113
1,590
8
1,404
1,802
133
2,081
10
1,986
2,179
148
1,617
10
1,447
1,807
167
2,031
10
1,819
2,267
184
1,972
10
1,716
2,266
201
2,013
10
1,778
2,278
218
2,251
10
1,998
2,536
235
2,441
10
2,083
2,860
253
2,234
10
2,045
2,441
276
2,149
10
1,842
2,508
299
2,275
2
IIC
111
1,596
10
1,424
1,789
131
1,912
10
1,758
2,080
147
1,917
10
1,829
2,121
165
2,139
10
2,027
2,257
182
2,403
10
2,059
2,805
199
2,166
10
1,980
2,371
216
2,304
10
2,035
2,607
233
2,396
10
2,140
2,681
252
2,222
10
1,921
2,571
270
2,243
10
2,021
2,489
291
1,930
7
1,722
2,163
ID
113
1,893
10
1,689
2,123
133
1,937
6
1,700
2,207
148
2,142
10
1,945
2,360
167
2,590
10
2,308
2,906
184
2,993
10
2,617
3,424
201
2,832
10
2,590
3,098
218
3,315
10
2,913
3,772
236
3,559
10
3,113
4,068
254
3,480
10
3,253
3,724
276
3,322
10
2,989
3,692
299
2,275
2
IID
111
2,073
9
1,854
2,319
132
2,351
9
2,053
2,693
147
2,815
10
2,550
3,107
165
3,198
10
2,903
3,523
183
3,916
10
3,548
4,322
200
3,376
10
3,050
3,738
215
3,466
10
3,090
3,887
234
3,572
10
3,205
3,982
252
3,253
10
2,680
3,948
271
3,288
10
2,813
3,842
292
3,132
9
268
3,648
NOTE: Limits are the 952 level; log1Q transformation applied when n > 5.
590
-------
APPENDIX TABLE 14.4a. PERCENT MYCORKIUZAL INFECTION (% M) AND MEAN ABSORBANCE (ABS)
FOR COLLECTION 26 DURING MID-JULY, 1977.
Plots
V
OPC
X M
ABS
IA
Z M
ABS
IB
Z M
ABS
1C
Z M
ABS
ID
Z M
ABS
IIA
Z M
ABS
IIB
Z M
ABS
IIC
~~Z M
ABS
IID
Z M
ABS
1
7NW
62.16
.380
50.00
.205
42.25
.245
78.57
.280
40.62
.230
52.94
.435
48.57
.290
29.41
.435
34.62
.400
APPENDIX
Plots
4-
OPC
Z M •
ABS
IIA
Z M
ABS
IIB
Z M
ABS
IIC
Z M
ABS
IID
Z M
ABS
1
SE
57.70
.425
76.66
.285
52.42
.275
42.37
.308
19.23
.245
2 .
8NE
56.25
.305
.275
72.41
.190
57.14
.255
60.00
.230
57.78
.680
57.90
.450
29.41
.440
60.87
.375
TABLE 14
2
8NW
61.11
.330
63.93
.290
41.97
.235
13.95
.200
3
9SW
62.50
.290
70.83
.205
69.56
.210
50.00
.255
53.66
.275
46.15
.360
57.14
.355
26.53
.185
63.33
.310
4
9NW
.450
63.64
.295
70.83
.190
54.29
.260
62.96
.350
56.41
.440
78.57
.380
54.54
56.52
.250
*• Subplots •*
5 6
10NW 12SW
46.88 75.00
.300 .330
62.50 53.85
.205 .260
50.82 68.18
.235 .190
59.46 52.17
.260 .235
65.71 72.41
.230 .265
56.25 45.45
.385 .370
64.86 33.33
.390 .365
43.75 28.89
.390 .405
35.90 61.54
.325 .350
7
14NE
56.76
.315
58.62
.190
78.57
.225
52.63
.300
58.62
.230
68.18
.385
47.83
38.78
.365
54.17
.435
.4b. PERCENT MYCORRHIZAL INFECTION (% M) AND MEAN
FOR COLLECTION 29 DURING MID-SEPTEMBER, 1977
3
9NE
47.06
.230
68.00
.320
44.83
.290
19.12
.248
4
10NE
45.83
.275
56.76
.240
55.55
.235
.235
40.00
.235
*• Subplots •*
5 6
12SE 14NW
50.00 26.67
.320 .235
69.51
.290
51.67 43.64
.355 .265
47.37 42.59
.330 .290
19.56 25.46
.245 .225
7
17SE
25.00
.200
69.56
.268
56.60
.335
39.47
.295
8
17NW
79.17
.335
51.62
.200
65.22
.260
50.00
.230
72.84
.275
58.82
.325
69.44
.305
51.26
27.50
.315
ABSORBANCE
8
19NW
30.00
.230
48.28
.272
.285
42.22
.285
17.65
.205
9
18SE
80.00
.550
53.06
.300
68.75
.225
61.11
.305
75.00
.225
66.67
.370
67.50
.380
23.07
.395
51.61
.315
(ABS)
9
19NE
41.02
.318
40.86
.268
52.63
.330
39.39
.225
.260
10
19SW
78.57
.320
57.14
.190
62.50
.225
43.33
.305
59.46
.225
67.65
51.85
.400
23.91
.375
37.50
.270
10
20SE
20.83
.220
66.66
.300
56.25
.315
26.19
.210
591
-------
SECTION 15
RESPONSE OF SELECTED SMALL GRAINS, RANGE GRASSES
AND ALFALFA TO SULFUR DIOXIDE
R. G. Wilhour, G. E. Neely, D. E. Weber and L. C. Grothaus
ABSTRACT
Experiments were conducted to determine the
effects of various sulfur dioxide (S02) treatments on
yield of small grains (spring wheat, Tvitiow aestivw
'Olaf; Durum wheat, Trit-icum tivgidwn 'Ward'; barley,
Hordeum vulgare 'Hector') and alfalfa (Medioago sativa
'Ladak-65') growing in a field environment. The
experiments were: 1) chronic exposure experiment to
determine the effects of weekly exposure to S02
treatments of 0, 3, 5, 10 or 15 pphm for 72 continuous
hr; 2) multiple exposure experiment to determine the
effects of varying the frequency of exposure to S02
treatments of 0, 25, 40, 80 or 120 pphm for 3 hr; and
3) a growth stage experiment to determine if phenolog-
ical stages exist during which plants are most sensi-
tive to a single S02 treatment of 0, 25, 40, 80 or 120
pphm for 3 hr. Another study was included to deter-
mine the effects of 3 hr treatments to 0, 25, 40, 80
or 120 pphm S02 repeated at two-week intervals on the
yields of range grasses (crested wheatgrass, Agyopyvon
desertorwn 'Nordan1; western wheatgrass, Agvopyvon
smit/iii; Russian wild ryegrass, Elymus junoeusi blue
grama grass, Bouteloua gvaoi1is\ needle and thread
grass, Stipa oomata) and alfalfa grown in containers.
The yields of Durum wheat and barley treated
weekly with 15 pphm S02 for 72 continuous hr were 42
and 44% of the controls, respectively. These results
were not significant at the 95% probability level, but
the data suggested that weekly, 72-hr exposures to S02
concentrations as low as 10-15 pphm could suppress
yields. The yield of spring wheat was not affected by
a similar treatment. Varying the frequency of 3-hr
exposures to S02 concentrations up to 120 pphm from as
often as once every week to as infrequently as once
every 5 weeks had no effect on yields of the small
grains and alfalfa. No growth stage was identified
592
-------
during which the small grains or alfalfa were most
sensitive to a single 3-hr exposure to S02 concentra-
tions up to 120 pphm. The growth of tops and roots of
range grasses and alfalfa were not affected by 3-hr
exposures to concentrations of S02 up to 120 pphm
repeated at 14-day intervals during September and
October.
INTRODUCTION
The increased reliance of the United States on energy produced by coal-
fired power plants will result in elevated concentrations of S02 in areas
sharing airsheds with electrical generating stations. The Poplar River Valley
of Montana, due to the current and planned construction of coal-fired power
plants in neighboring states and Canada, will experience increased S02 concen-
trations. This study was initiated due to the concern of EPA Region VIII in
Denver, Colorado regarding the potential detrimental effects of elevated S02
concentrations on agricultural crops important to the economy of the Poplar
River Valley.
Several studies have described injury symptoms (Lamb, 1972; Hill et al.9
1974; Tingey et al.9 1978), changes in various plant processes (Bennett and
Hill, 1973; Rabe and Kreeb, 1976; Neely et al., 1977; Dodd, Section 13 of this
report) and yield effects (Davis et al., 1966; Booth et al., 1976; Brough and
Parry, 1976; Heitschmidt, 1977; Neely et al., 1977; Dodd, Section 13 of this
report) of S02 on plants similar to those economically important in the Poplar
River Valley. Although these studies demonstrated probable response charac-
teristics of several plant species to S02 and provided some dose/response
data, knowledge remained incomplete for a reasonable assessment of the effects
of increased S02 levels on the agricultural economy of the Poplar River
Valley.
A research program was planned to broaden the knowledge concerning the
response of important plant species grown in the Poplar River Valley to S02.
Two studies were conducted utilizing different species and emphasizing differ-
ent objectives. Small grains and alfalfa were included in a study which had
three objectives: 1) to determine if more frequent exposure to given concen-
trations of S02 resulted in greater yield reductions; 2) to assess the effects
of a range of S02 concentrations on yield; and 3) to determine if periods of
time exist during which a species is more sensitive to S02. Another study
utilized native range grasses and alfalfa and was designed to assess the
effects of a range of S02 concentrations on yield.
MATERIALS AND METHODS
The experimental S02 exposures were conducted at the Schmidt research
farm which is located approximately 5 miles east of Corvallis, Oregon. The
farm is owned and operated by Oregon State University.
593
-------
Field Exposure Study
Three distinctive experiments were included in this study. A chronic
exposure experiment was conducted to determine the effects on yield of small
grains (spring wheat, Tritiewn aestivum 'Olaf; Durum wheat, Triticwn turgidum
'Ward'; and barley, Hordewn vulgare 'Hector') and alfalfa (Medioago sativa
'Ladak-65') from repeated, lengthy exposures to low concentrations of S02.
Treatments in this experiment were ambient air (never covered by an exposure
chamber), 0 (ambient air filtered by activated charcoal), 3, 5, 10, or 15 pphm
S02 (ambient air filtered by activated charcoal amended with desired S02
concentrations) . The duration of the S02 treatments was 72 hr (Friday noon
until Monday noon) and the treatments were repeated each week for 12 weeks
beginning May 6, 1977.
The objectives of the multiple exposure experiment were to correlate
yields of small grains and alfalfa with 1) S02 concentrations in the range of
0-120 pphm and 2) frequency of exposure to these S02 concentrations. The
effects of all combinations of five S02 concentrations (0, 25, 40, 80 or 120
pphm) and seven exposure frequencies (ranging from once per week to once every
five weeks*) were examined as they affect plant yields. The S02 treatments
lasted 3 hr beginning at 8 a.m. The experiment was continued for 12 weeks,
beginning May 11.
A growth stag e experiment was conducted to determine if phenological
stages of development exist during which a single exposure to S02 concentra-
tions of 0, 25, 40, 80 or 120 pphm most affects yield of small grains or
alfalfa. Treatments representing all combinations of five S02 concentrations
(0, 25, 40, 80 or 120 pphm) and six growth stages (two-week intervals) were
used in this experiment. The S02 treatments were 3 hr in duration (8-11 a.m.)
and an experimental plot was treated only once during the experiment. A
different group of five experimental plots (one for each S02 concentration)
was treated at 2-week intervals, beginning May 17.
The soil at the Schmidt research farm is a Willamette silt loam. The
surface layer is a well drained, very dark brown silt loam, about 60 cm thick
over a silty clay loam subsoil. A chemical analysis of the soil prior to
seeding identified the following chemical concentrations: nitrate (6.6 ppm),
phosphorus (45 ppm), potassium (252 ppm), sulfur (6.2 ppm) and boron (.42
ppm). The soil had a pH of 5.8, cation exchange capacity of 18.35 milliequiv-
alents per 100 grams and an organic matter content of 3.29%. The following
amendments were applied and incorporated into the soil prior to seeding: 16-
20-0-14 (N-P-K-S) and 0-0-52-17 at rates of 337 and 129 kg/ha, respectively,
boron (14.3%) at 3 kg/ha and agriculture limestone at 8980 kg/ha. The amend-
ments and rates were selected to provide an average growing condition capable
of adequately sustaining nutrient demands for the test plants.
Eight experimental blocks (2.7 by 60 m) were established in an east-west
direction. Within each block 16 plant rows were oriented lengthwise. North-
south divisions were made to divide each block into 20 plots which became the
* The once-every-four-weeks treatment was repeated three times using slightly
different starting dates.
594
-------
experimental units. An entire plot was covered by an exposure chamber during
treatment. Treatment plots measuring 2.4 x 2.4 m were selected within blocks
on the basis of uniform plant size and distribution. Treatments were assigned
to plots to minimize the possibility that a response trend would appear due to
variability asociated with location. This was achieved within an experiment
by assigning treatments with a common S02 concentration to the same block
whenever possible and/or by assigning treatments which differed most to
adjacent plots.
The blocks were drilled on April 11, 1977 with wheat and barley at a rate
of 100 kg seed/ha, alfalfa at 11 kg/ha, and crested wheatgrass at 9 kg/ha.
All rows were drilled 18 cm apart. Sparse and spotty emergence of alfalfa
required replanting of this test species on May 10, 1977. Poor development of
crested wheatgrass resulting in its deletion from the field studies. One day
after the second planting of alfalfa, experimental plots were sprayed with
2,4-DB amine (.6 kg/ha) to control broadleaf weeds. The herbicide was not
applied to the alfalfa. Poor weed control resulted and weeding by hand was
necessary. No additional cultural practices (e.g. irrigation) were performed.
Sulfur dioxide exposures were conducted in exposure chambers similar to
those previously described by Heagle et ai. (1972). The S02 was dispensed
into exposure chambers and concentrations controlled as previously described
(Heagle et aZ-., 1974). The portable exposure chambers covered the experi-
mental plots only during actual S02 treatments. Ambient temperature (therm-
istors), humidity (Hygrodynamic Model 15-7012 Sensor), and sunlight (Solar-a-
Meter Mark I-G100) measurements were made during the study period. Ambient
S02 concentrations during the experimental period were always less than 1
pphm. Pollutant concentrations were continuously monitored during fumigations
by drawing air from exposure chambers through Teflon sample lines to Meloy
Labs sulfur analyzers (Model SA 285). The S02 analyzers were checked monthly
for accuracy with a Monitor Labs Model 8500 Calibrator.
Visible injury to the foliage of the grain species was estimated three
days after each fumigation and terminated in July due to the appearance of
natural chlorosis and necrosis.
The grain crops were harvested on August 15. The 180 cm center sections
of the two test rows per species were divided into two equal, 90 cm sections,
providing 4 samples per treatment per species. The number of plants and seed
heads per sample were counted. Grain heads were removed from each sample
area, bagged, air dried and threshed with a Vogel wheat-head thresher. Ker-
nels were oven dried at 50°C and weighed. Yields were expressed as gm of
grain per plant.
Alfalfa was harvested on July 29, 1977 when at approximately 10% bloom.
Sample areas were assigned as described for the grain species. Plants were
clipped at soil level, oven dried at 70°C and weighed. Yield values were
expressed as weight (gins) per plant.
595
-------
Range Grass and Alfalfa Study
The objective of this study was to determine the effects of repeated S02
exposures during the vegetative stage of growth on the yield of alfalfa, M.
sativa 'Ladak-651; crested wheatgrass, Agropyron desertorwn 'Nordan1; western
wheatgrass, Agropyron svrithii', Russian wild ryegrass, Elymus junceus; blue
grama grass, Bouteloua gvaoilis and needle and thread grass, Stipa comata.
Ladak-65 alfalfa, Nordan crested wheatgrass and Russian wild ryegrass were
seeded and the remaining species were transplanted from cuttings on July 5,
1977. The growing medium was a mixture of three parts soil (sandy clay loam)
to one part Jiffy-Mix-Plus. This mixture was amended with 2.3 kg of 11-33-11-
5 (N, P, K, S) and 1.2 kg of hydrated lime per cubic meter of soil. Grasses
were grown in 10 cm dia. by 30 cm high pots and alfalfa in 20 cm dia. by 18 cm
high pots. Plants were thinned to one grass or two alfalfa plants per pot.
Treatments were 0, 25, 40, 80, or 120 pphm S02 repeated every 14 days
between the hours of 8 and 11 a.m. The treatment plots were randomly arranged
in an east-west direction and within plots, test species were grouped in rows
oriented in an east-west direction. There were 13 to 14 pots per treatment of
each grass species and 6 pots of alfalfa per treatment. All plots received
five 862 exposures, separated by two weeks, beginning August 25- Test plants
were covered by exposure chambers only during treatment with S02- Plants were
watered as necessary to prevent moisture stress. Ambient environmental condi-
tions and S02 concentrations were monitored as described in the earlier study.
All plants were harvested November 3 while in the vegetative growth stage.
Plant tops were clipped at soil level and roots were washed. Tops and roots
were oven dried at 70°C and weighed.
Data Analysis
Preliminary examination of the data from the field exposure study indi-
cated that a large block-to-block variation occurred, independent of treatment
differences. Because of this variation, treatment comparisons were limited to
those appearing in the same block. The effect of this limitation is variable
and will be discussed with the analysis of the results for each experiment in
the field exposure study.
The statistical treatment of the data involved analyses of variance and
calculation of LSD's by Tukey's multiple comparison procedure (Snedecor and
Cochran, 1967). The one exception was that in the multiple exposure experi-
ment Bonferroni's multiple comparison method (Neter and Waserman, 1974) was
used to compute significant t-values. The assumption inherent in the t-test
and analysis of variance that the data be normally distributed with variances
which do not increase with treatment means (Snedecor and Cochran, 1967) was
tested and found to be true. Therefore, no corrective data transformations,
such as the logarithmic transformation, were needed and the only modification
of the data was to express yield on a weight per plant basis to adjust for
differences in the number of plants between samples.
596
-------
RESULTS
Average temperature, relative humidity, solar insolation and rainfall
which occurred during the experimental periods are summarized in Table 15.1.
Comparisons of desired and actual S02 concentrations for all experiments are
presented in Table 15.2.
Field Exposure Study
Chronic Exposure Experiment
Comparatively severe limitations were imposed on this experiment by the
large block-to-block variability which prevented comparisons of treatments
located in different blocks. Two analyses were completed comparing 0 pphm, 3
pphm and 15 pphm treatments or the 5 and 10 pphm treatments. The block-by-
block comparisons of; the mean yields between S02 treatments are given in Table
15.3. The yields of Durum wheat and barley were suppressed 42 and 44%, re-
spectively, comparing the mean at 0 to that at 15 pphm, and about 15% when
comparing the mean yield at 5 pphm to the mean yield at 10 pphm. The differ-
ences, however, were not statistically significant at the 95% level of confi-
dence. In the above comparisons, the mean yield at the highest S02 concentra-
tion was always the lowest, suggesting that the yield of Durum wheat and
barley can be reduced by weekly, 72-hr exposures to S02 concentrations as low
as 10 to 15 pphm.
Spring wheat seemed more resistant to the chronic S02 exposures. The
mean of the 15 pphm treatment was actually greater by 7% than the 0 pphm
treatment mean (control). Further, only a 5% yield difference occurred be-
tween the 5 pphm and 10 pphm treatments.
Foliar injury was observed on all species of small grains exposed to S02
in the field experiments. Symptoms of S02 injury appeared as chlorosis and
necrosis on the leaf tips and margins. No similar injury was observed on
plants not treated with S02. Foliar injury on small grains in the chronic
exposure experiment was no greater than 15% at S02 concentrations of 3, 5, or
10 pphm (Table 15.4). At 15 pphm, the highest concentration used in this
experiment, average injury values ranged from 25 to 50%.
Multiple Exposure Experiment
The block-to-block variability discussed earlier restricted comparisons
of exposure frequencies to S02 concentrations completely contained within a
block (25, 80 or 120 pphm).
Analyses of variance for Durum wheat, spring wheat, barley and alfalfa
showed that 1) the pattern of differences in mean yields between exposure
frequencies did not vary with S02 concentration (no significant exposure
frequency by S02 concentration interaction) and 2) there were no significant
differences in mean yields between different exposure frequencies at either
25, 80 or 120 pphm (Table 15.5 gives means and LSD's). Thus, varying the
frequency of 3-hour exposures to S02 concentrations up to 120 pphm from as
597
-------
Ui
\£>
00
TABLE 15.1. AVERAGE WEEKLY AMBIENT TEMPERATURE, HUMIDITY AND SOLAR INSOLATION OCCURRING DURING THE WEEKS
OF EXPOSURE
Average Ambient Environmental Conditions
Temperature (°C)
*/
Week Max.—
5/6-5/12
5/13-5/19
5/20-5/26
5/27-6/2
6/3-6/9
6/10-6/16
6/17-6/23
6/24-6/30
7/1-7/7
7/8-7/14
7/15-7/21
7/22-7/28
7/29-8/4
8/5-8/11
8/12-8/18
8/19-8/25
8/26-9/1
9/2-9/8
9/9-9/15
9/16-9/22
9/23-9/29
9/30-10/6
10/7-10/13
10/14-10/20
10/21-10/27
18.1
17.1
19.0
17.8
25.1
24.8
26.3
29.7
24.1
25.8
28.2
30.3
35.6
37.2
35.9
24.5
24.8
25.0
26.2
18.1
17.3
17.9
19.3
19.2
16.8
*/
Min.-'
-.4
2.2
2.0
3.2
9.0
5.2
6.8
7.6
6.8
5.8
7.0
9.6
11.0
11.9
8.7
10.9
10.2
10.3
5.5
6.9
5.7
3.8
3.7
2.7
3.2
Day±/
Avg.
13.4
13.1
14.8
14.4
20.8
19.6
21.2
24.0
20.0
21.6
22.6
24.6
30.0
30.5
28.6
20.0
20.0
20.4
20.1
13.6
13.0
12.5
13.4
12.3
11.7
Relative Humidity (%)
Night-?- Solar Insolation— ^,
Avg. (cal. /cm2/min) Max.—
3.8
4.5
6.0
5.6
11.9
9.1
11.0
12.0
10.4
10.2
11.3
13.7
16.0
17.7
16.4
13.3
12.4
13.3
10.8
9.3
8.0
7.4
7.2
6.7
6.3
.74
.62
.68
.64
.73
.79
.70
.89
.73
.74
.78
.73
.83
.79
.70
.43
.58
.54
.56
.39
.36
.43
.43
.38
.32
95
96
97
96
95
95
97
89
88
93
92
85
79
72
83
92
93
90
91
96
92
79
88
93
97
*/
Min.-
39
42
37
45
41
32
36
22
24
26
20
20
11
11
8
33
22
24
14
36
42
30
31
34
51
Da^
Avg.
58
58
56
63
59
52
56
34
36
39
37
37
24
25
31
54
43
44
35
64
67
54
54
62
73
Night4-
Avg.
85
87
87
91
87
86
84
73
68
76
74
67
58
52
60
80
83
78
69
87
85
66
76
77
91
Rainfall (cm)
March 12.9
April 2.6
May 8 . 7
June 2 . 9
July . 3
August 4.8
September 9.1
October 6.5
*/
x/Average of seven daily maximum hourly values.
x/Weekly average of hourly values between 7 am and 8 pm.
•^Weekly average of hourly values between 8 pm and 7 am.
-------
TABLE 15.2.
COMPARISONS OF ACTUAL AND DESIRED S02 CONCENTRATIONS FOR ALL
EXPERIMENTS
Actual Concentration, pphm
No. Desired
Study Obs. Cone. Min. Avg.
% of time — stated value*
Max.
10 50 90
(Median)
95
Multiple
192
192
192
192
25
40
80
120
9
0
29
25
24.0
39.4
74.6
114.9
80
130
110
160
14
26
46
84
17
32
56
90
25
38
78
120
27
45
83
130
30
51
84
135
Growth
36
36
36
36
25
40
80
120
5
0
33
25
25.1
36.5
77.1
112.8
33
47
87
135
16
0
45
25
18
30
55
85
26
38
80
123
30
44
84
130
31
44
84
130
Range
Grass
Chronic
30
30
30
30
864
864
864
864
25
40
80
120
3
5
10
15
18
27
38
120
0
1.4
0
0
25.2
36.4
86.1
111.1
3.0
5.1
9.7
15.0
35
45
120
125
9
12
20
53
.0
.0
.0
.0
19
28
45
100
1.8
3.3
6.6
9.0
22
30
46
100
2.0
3.6
7.5
10.0
25
37
90
110
2.7
4.8
9.5
14.5
27
40
105
120
4.0
6.8
12.0
21.0
28
41
120
125
5.6
8.0
14.0
23.0
* For example, the first line indicates that 5% of the time the concentration
was no more than 14 pphm, 10% of the time it was no more than 17 pphm, half
the time it was no more than 25 pphm, 90% of the time it was no more than 27
pphm, 95% of the time it was no more than 30 pphm.
often as once every week to as infrequently as once every 5 weeks had no
effect on yields of the test species.
A secondary objective of the multiple exposure experiment was to evaluate
the effect of various S02 concentrations on yield. The lack of a significant
effect on plant yield by varying the frequency of exposure was discussed
above. Therefore, all plots which received the same S02 exposure concentra-
tion can be considered equivalent and pooled to assess the effect on yield of
varying S02 concentrations. The results of pooling plots treated with a
common S02 concentration and located in the same block are given in Table
15.6. No differences significant at the 95% level of confidence were found
between S02 concentrations indicating the yields of Durum wheat, spring wheat,
barley and alfalfa were independent of S02 concentration for these 3-hr dura-
tion exposures.
599
-------
TABLE 15.3. YIELD RESPONSE OF SELECTED SMALL GRAINS TO WEEKLY, 72-HOUR EXPO-
SURES TO LOW S02 CONCENTRATIONS
BLOCK 1
MEANS
SPECIES 0 pphm
Durum wheat 1 . 68
Spring wheat 1.34
Barley 1.49
3
1
1
1
*/
(gm/plant)—
pphm 15
.52
.81
.64
0.
1.
0.
pphm
97
44
83
%
0.
-0.
0.
[Q -
71
10
66
Xl5
t/
(42%)^-'
(7%)
(44%)
LS
1.
1.
.1.
ID#
28
67
35
BLOCK 2
MEANS
Durum wheat
Spring wheat
Barley
5
2
1
3
pphm
.71
.85
.10
*/
(gm/plant)—
10
2.
1,
2.
Pphm
28
76
66
X 5 - Xl 0 U^
0.
0.
0.
43
09
44
(16%)^
(5%)
(14%)
1.
1.
1.
04
36
10
*/
— Means based on a sample size of four.
— Represents change relative to the smaller of the means,
4- Least significant difference (LSD) based on Tukey's studentized rang© pro-
cedure using error mean squares of .452 (Durum wheat), .760 (spring wheat)
and .502 (barley) with 11 degrees of freedom.
TABLE 15.4. ESTIMATED PERCENT FOLIAR INJURY FOR SMALL GRAINS IN THB CHRONIC
EXPOSURE EXPERIMENT
Sulfur Dioxide concentration, pphm
Species
Durum wheat
Spring wheat
Barley
3
*/
57-'
5
15
5
10%
15
10
10
15%
15
15
15
25%
50
35
*/
— Percent foliar injury readings made on June 30, 1977.
The foliar injury data are given in Table 15.7. No trends exist which
would suggest that greater foliar injury occurred with more frequent SOa
exposures; however, it is apparent that a positive correlation existed between
foliar injury and SOz concentration. Averaged across species and frequency of
exposure, foliar injury ranged from about 5% at 25 pphm S02 to about 35% at
120 pphm.
600
-------
TABLE 15.5. EFFECTS OF VARYING FREQUENCY OF 3-HOUR S02 EXPOSURES ON YIELD OF
SMALL GRAINS AND ALFALFA
S02
(pphm)
25
80
120
25
80
120
1.
3.8
2.2
2.0
2.7
3.0
Wks between repeated exposures
*/
4a-'
(gm) (gm)
DURUM WHEAT
1.1
3.8
2.2
1.4
3.1
2.5
1.3
2.5
2.2
1.8
2.2
2.1
1.2
3.5
1.9
1.4
3.8
2.2
SPRING WHEAT
1.8
2.5
2.2
1.2
3.0
2.0
1.1
2.6
2.7
1.6
3.1
2.1
(gm)
1.3
3.6
1.6
1.8
3.4
2.3
BARLEY
m
0.5
0.3
1.1
0.8
1.2
1.0
LS
D*'
1.7
1.7
1.7
2.2
2.2
2.2
25
80
120
25
80
120
1.9
2.4
1.8
0.64
0.39
0.67
2.0
3.8
2.5
0.38
1.01
0.51
1.8
2.4
2.7
0.44
0.82
0.55
1.9 1.9
3.7 2.7
2.2 2.2
ALFALFA
0.71 0.42
0.80 0.80
0.54 0.38
1.8
3.1
2.8
0.57
0.98
0.58
2.3
2.5
1.9
0.22
0.76
0.65
0.5
1.4
1.0
0.49
0.53
0.29
1.8
1.8
1.8
1.2
1.2
1.2
— Experiments started on different dates (May 13, May 19 or June 2).
— Maximum mean minus minimum mean.
•T- LSD based on Tukey's studentized range procedure using error mean squares of
.452 (Durum wheat), .760 (spring wheat), .520 (barley), and .225 (alfalfa)
with 11 degrees of freedom.
Means based on a sample size of four; means given in gm per plant
Growth Stage Experiment
The block-to-block variability already discussed limited the analysis to
comparisons of growth stages at S02 concentrations completely contained within
one block (40, 80 and 120 pphm). Analyses of variance for Durum wheat, bar-
ley, spring wheat and alfalfa showed that 1) the pattern of differences in
mean yields between growth stages did not vary with S02 concentration ^ (no
significant growth stage by S02 concentration) and 2) there were no signific-
ant differences in mean yield between growth stages at either 40, 80 or 120
pphm (see Table 15.8 for means and LSDs) . Thus, when yields were averaged
across the three S02 concentrations, the growth stage mean yields typically
were within a range of plus or minus one standard error, indicating that the
sensitivity of the test plants to S02 was not different with regard to growth
stage.
601
-------
TABLE 15.6. YIELD RESPONSE OF SELECTED SMALL GRAINS AND ALFALFA EXPOSED TO S02 FUMIGATIONS IN THE
MULTIPLE EXPOSURE EXPERIMENT
Durum wheat
Spring wheat
Barley
Alfalfa
Durum wheat
Spring wheat
Barley
Alfalfa
Durum wheat
Spring wheat
Barley
Alfalfa
S02 (pphm)
0 120
1.96^ 2.12
2.41 2.31
2.17 2.29
0.44 0.55
*
S02 (pphm)
0 40 80
3.37 2.99 3.37
2.28 2.39 2.86
3.29 3.92 2.95
0.39 0.96 0.77
S02 (pphm)
25 40
1.30 1.92
1.64 2.02
1.92 2.07
0.48 0.41
BLOCK 3
X120~X0
0.16
-0.10
0.12
0.11
BLOCK 4
(8%)ty
(4%)
(6%)
(25%)
Max rlin
0.38
0.58
0.33
0.37
BLOCK 5
X40
0.62
0.38
0.15
-0.07
(13%)
(25%)
(11%)
(63%)
-x25
(48%)
(23%)
(8%)
(17%)
«- i §/§§
t-value
0.76
-0.37
0.53
0.74
t-values
40-0 80-0
-1.38 0.0
0.31 1.57
0.88 0.29
1.91 1.10
t-value
2.94
1.39
0.67
-0.10
/
80-40
1.64
1.93
-1.34
-1.16
*/
— No t-values significant at the 95% level of confidence.
— Average plant yield (grams dry weight of grain and foliage of small grains and alfalfa, respectively) .
Means were grouped over frequencies of exposures based on the following sample sizes: Block 3 (0 pphm-
16; 120 pphm-28); Block 4 (0, 40 pphm-12; 80 pphm-28), Block 5 (25 pphm-28; 40 pphm-16).
i'
§/.
Represents change relative to smaller of the means.
— Significance levels controlled simultaneously for group of 5 comparisons made per species.
§§/
—Based on error mean squares of .452 (Durum wheat), .760 (spring wheat), .520 (barley) and .225
(alfalfa) with 11 degrees of freedom.
-------
TABLE 15.7. ESTIMATED PERCENT FOLIAR INJURY FOR SELECTED SMALL GRAINS IN THE
MULTIPLE EXPOSURE EXPERIMENT
Species
Durum wheat
Spring wheat
Barley
Desired
Concentration
(pphm)
25
40
80
120
25
40
80
120
25
40
80
120
Days Between Exposures
7
t/
5%-7
5
10
20
5
5
15
25
1
10
25
35
14
5%
15
25
30
0
15
15
30
1
20
15
35
21
5%
15
30
40
1
1
25
35
5
1
30
80
*/
28-;
15%
5
25
45
15
15
20
30
10
25
40
50
35
5%
10
20
30
1
10
15
40
1
5
20
35
*/
— Average of three 4th week regimes.
—Percent foliar injury readings made on or about July 1, 1977.
Range Grass and Alfalfa Study
The analyses of variance indicated that significant differences existed
only for western wheatgrass roots and alfalfa tops (Table 15.9). However, the
significance in each case was due to a single mean being greatly different
than the others. For western wheatgrass, the 80 pphm mean was low, for alf-
alfa the 25 pphm mean was high. No systematic variation appeared among the
S02 treatment means for any of the test species. The 25, 40, 80 and 120 pphm
treatment means tended to vary haphazardly about the control (Figure J-5-1)-
Among these four means, the minimum was typically less than 10% below the
control and the maximum no more than 25% above.
Species by species comparison of the four treatment means to the control
(Table 15.9) showed that 13 times the S02 means were less than the <;°n«°\
means and 35 times they were greater. None of these differences were "8
cant at the 95% level. Since standard errors were typically less than UU o
the means, the lack of systematic response to S02 oo uld «* have f™ ^he
excessive sampling variability. The results clearly indicate that under the
conditions of biweekly, 3-hr exposures, S02 concentrations of up to 120 ppto
had no effect on the growth of either the roots or tops of these six species
of
603
-------
TABLE 15.8. YIELD RESPONSE OF SELECTED SMALL GRAINS AND ALFALFA AT SEVERAL
GROWTH STAGES TO S02 FUMIGATIONS
Growth stage (biweekly) increments
S02
I-/ 2 3 4
5
6
TT TT
Max Mi
n LSD?-'
DURUM WHEAT
40 pphm 1.7 gm 1.3 gm 1.6 gm 1.4 gm 1.9 gm 2.5 gm 1.2 1.7
80 1.2 1.6 2.0 1.4 1.5 1.7 0.4 1.7
120 2.2 2.5 2.0 2.9 2.5 2.3 0.9 1.7
SPRING WHEAT
40 1.8 1.5 1.7 1.4 1.3 1.2 0.7 2.2
80 1.4 2.0 2.1 1.5 1.6 1.8 0.7 2.2
120 2.1 2.4 1.4 1.9 1.4 2.3 1.0 2.2
BARLEY
40 2.8 2.6 2.3 2.4 3.1 2.0 1.1 1.8
80 1.2 1.7 1.8 1.6 1.3 1.1 0.7 1.8
120 3.4 4.9 3.5 2.2 3.2 3.7 2.7* 1.8
ALFALFA
40
80
120
0.36
0.49
0.57
0.77
0.40
1.34
0.57
0.52
0.61
0.50
0.51
0.98
0.45
1.14
0.52
0.86
0.36
0.64
0.50
0.78
0.82
1.2
1.2
1.2
^Significant at 95% level of confidence.
— Average plant yield in (grams dry weight of grain and foliage of small
grains and alfalfa, respectively) based on a sample size of four.
-r LSD based on Tukey's studentized range procedure using error mean squares of
.452 (Durum wheat), .760 (spring wheat), .520 (barley) and .225 (alfalfa)
with 11 degrees of freedom.
DISCUSSION
Weekly exposure of Durum wheat and barley for 72 hr at an S02 concentra-
tion of 15 pphm suppressed average grain yields 42 and 44%, respectively,
compared with the 0 pphm treatment. This suppressive effect was also observed
as the S02 concentration increased from 5 to 10 pphm, but the effect was
considerably less. Though these yields differences were not significant at
the 95% level of confidence, it is probably that the lack of statistical
significance between the treatment means for Durum wheat and barley was due to
1) the small sample size which was related to experiment limitations (prevent-
ing treatment replication) or 2) the inability to make block-to-block compari-
sons .
A similar yield suppression was not observed with spring wheat indicating
that this species was more resistant. Compared to Durum wheat and barley, the
604
-------
TABLE 15.9. YIELD RESPONSE OF RANGE GRASS SPECIES AND ALFALFA TO S02 FUMIGATIONS.
o
TREATMENT MEANS-
SPECIES
Crested
Western
Russian
wheatgrass
Tops
Roots
wheatgrass
Tops
Roots
wildrye
Tops
Roots
0 pphm
9.1 gm
7.7
-
3.7
7.5
5.9
4.3
25 pphm
9.1 gm
7.4
4.6
7.3
7.7
5.7
40 pphm
9.6 gm
7.9
4.2
7.7
6.3
4.4
f 80 pphm
9.7 gm
8.6
4.2
6.5
5.8
4.0
120 pphm
9.7 gm
8.7
4.0
8.0
6.4
4.8
+ /
v -vSJ
A. -~"A 1
M m
0.6
1.3
0.9
1.5*
1.9
1.7
LSD
2.1
1.8
1.1
1.2
2.0
1.8
SE§/
olL
0.53
0.46
0.28
0.31
0.49
0.43
F
0.38
1.62
1.40
3.30*
2.42
2.24
Blue grama grass
Tops
Roots
0.58
0.34
0.63
0.30
0.58
0.31
0.39
0.23
0.69
0.40
0.30
0.17
0.48
0.31
0.12
0.08
0.86
0.68
Needle & Thread Grass
Alfalfa
Tops
Roots
Tops
Roots
2.4
1.2
5.4
7.7
3.0
1.6
7.5
8.8
2.2
1.3
6.5
8.9
3.1
1.7
5.0
7.9
3.0
1.4
5.5
8.2
0.9
0.5
2.5*
1.2
1.3
0.7
2.1
3.5
0.33
0.17
0.50
0.85
1.50
0.46
3.88*
0.40
*Signifleant at 95% confidence level.
— Means based on sample sizes of 14 (crested wheatgrass, western wheatgrass), 13 (Russian wildrye, blue
grama grass, needle and thread grass) and 6 (alfalfa); grams per plant.
•$• Maximum mean minus minimum mean.
§/
—Standard error.
-------
TOPS
ROOTS
I0r
E 8
o>
H
CL
•—
h-
X
LJ
. Crested
Wheotgross
,. Russian
Wildrye
Alfalfa
]7 Western
J" Wheatgrass
L_ Needle 8
J_ Thread Grass
10
£ 8
a>
£ 2-
_L
_L
T, Blue Grama
~Grass
Crested
. Wheatgrass
^— Alfofa
^Western
Wheatgrass
Russian
Wildrye
T_ Needle 8
iThread Grass
Blue Grama
Gross
25
50 75
50? (pphml
100
125
25
50
75
100
125
S02 (pphm)
^
Each bar equals 2 standard errors.
Each bar equals 2 standard errors.
Figure 15.1. Yield response of tops and growth response of roots of range
grass species and alfalfa to various S02 concentrations.
foliage of spring wheat was severely injured, but the yield of this species
appeared to be less affected by the S02 treatments. This, along with results
of associated studies discussed below, suggests that within the environmental
conditions of this research, small grain species can sustain significant
foliar injury without accompanying yield suppression. Based on these observa-
tions, foliar injury is not a reliable predictor for estimating grain yield
losses.
There was no stage of growth during which the yield of Durum wheat,
spring wheat, barley or alfalfa was affected most by a single, 3-hr exposure
to S02 concentrations up to 120 pphm. These treatments repeated as frequently
as once a week also failed to affect yields. The average foliar injury to the
small grain species exposed to 120 pphm was approximately 35%. Apparently,
sufficient intervals of time were present between repeated exposures to allow
physiological recovery and a decrease in yields did not occur. This recovery
phenomenon was described by Zahn (1963), when he observed that plant yields
were less affected by S02 as the period of time between successive exposures
was increased.
The small grain species and alfalfa were tolerant of the relatively
short, 3-hr S02 exposures when treated under the environmental conditions
which occurred during this investigation. This tolerance to S02 could be
related to the low rainfall levels which occurred in June and July (Table
15.1). Although soil moisture was not measured within the experimental plots,
the presence of low moisture values can be inferred from the low levels of
precipitation during these months. It was also during this period of time
that grain heads were developing. Wells (1915), van Haut (1961) and van Haut
and Stratmann (1970), found that the heading-out stage is one of the critical
phases of growth during which exposure of grain crops to S02 would be most
likely to suppress yields. Therefore, the absence of adequate soil moisture
606
-------
may have increased the tolerance of the crops to S02 during this critical
growth stage. This aspect of the experimental studies can be related to
expected effects on non-irrigated land within the Poplar River Valley of
Montana, since average moisture conditions are typically low in this region
during the time when grain heads are developing. This ambient condition could
increase the tolerance of plants to S02, similar to that suspected in this
research. The yields of small grains in this study were similar to average
yields for grain grown in non-irrigated areas of northeastern Montana (Bowman
and Shaw, 1976, 1977) which typically experience low rainfalll during the
later growth stages.
Biweekly exposures (every 14 days) of five range grasses and alfalfa for
periods of 3 hr at concentrations of up to 120 pphm S02 did not affect the
growth of roots or yield of tops. The range grasses failed to develop in
field plot studies, and cuttings transplanted from greenhouse cultures devel-
oped slowly. As a result, exposures to S02 were not started until late summer
and were, therefore, associated with cool temperatures (Table 15.1). The
exact cause of the lack of response of the range grasses and alfalfa to the
S02 treatments is difficult to assess, but two possibilities are apparent:
(1) low temperatures during treatment and (2) inherent resistance to S02.
Cool temperatures which prevailed during this study tend to reduce plant
response to S02 (Heck et ol.9 1965; Guderian, 1977). Other investigators
found that the injury (Tingey et aZ., 1978) and growth (Dodd, Section 13 of
this report) responses of several plant species used in this study were not
significantly affected by a single S02 exposure to 100 pphm for 4 hours or by
seasonal median S02 concentrations up to 6.8 pphm (concentrations were lognor-
mally distributed with a standard geometric deviation of approximately 2.5),
respectively. A reasonable analysis of the response of the range grasses and
alfalfa used in this study is that they appear to be relatively tolerant
(based on foliar injury and growth response) to S02 exposures. A similar
analysis, however, apparently does not exist with regard to another response
parameter—nutritive quality. An analysis of the nutritive quality of western
wheatgrass and prairie June grass demonstrated that seasonal median S02
concentrations up to 6.8 pphm during two growing seasons reduced crude protein
content and digestibility of western wheatgrass (Schwartz et aZ., 1978).
CONCLUSIONS
The yields of Durum wheat and barley treated weekly with 15 pphm S02 for
72 continuous hr were 42 and 44% of the control, respectively. These results
were not significant at the 95% probability level, but the data suggested that
weekly, 72-hr exposures to S02 concentrations as low as 10-15 pphm could
suppress yields. The yield of spring wheat was not affected by a similar
treatment. Varying the frequency of 3-hr exposure to S02 concentrations up to
120 pphm from as often as once every week to as infrequently as once every 5
weeks had no effect on yields of the small grains or alfalfa. No growth stage
was identified during which the small grains or alfalfa were most sensitive to
a single 3-hr exposure to S02 concentrations up to 120 pphm. The growth of
tops and roots of range grasses and alfalfa were not affected by 3-hr expo-
sures to concentrations of S02 up to 120 pphm repeated at 14-day intervals
during September and October.
607
-------
ACKNOWLEDGEMENT S
The authors acknowledge the capable assistance of the following Oregon
State University Crop Science Department technical personnel in the conduct of
research described in this report: Alex March, Sharon Newton, Milton Plocher
and Rick Voelkel. The excellent supervision of employees and coordination of
research activities by Mr. Shelton Perrigan was greatly appreciated. The
skill of Nancy Lanpheare, the typist, greatly facilitated the preparation of
this manuscript.
This research was funded jointly by EPA Region VIII and the Corvallis
Environmental Research Laboratory. George Bolter, the Region VIII coordinator
for this project, assisted in the design of the experiment.
REFERENCES
Bennett, J. H. and A. C. Hill. 197.3. Inhibition of Apparent Photosynthesis
by Air Pollutants. J. of Envir. Quality, 2(4):526-530.
Booth, J. A., G. 0. Thorneberry and M. Lujan. 1976. Crop Reactions to
Sulfur Dioxide in New Mexico. University Park, New Mexico State Univ.
Agric. Experiment Sta. Bull. 645, 27 pp.
Bowman, H. and A. F. Shaw. 1977. Performance Summary, Barley. Bull. 1094.
Cooperative Extension Service, Montana State University, Bozeman. 21 pp,
Bowman, H. and A. F. Shaw. 1976. Performance Summary, Spring Wheat Varie-
ties. Bull. 1098. Cooperative Extension Service, Montana State Univer-
sity, Bozeman. 30 pp.
Brough, A. and M. A. Parry. 1976. Effects of Aerial Pollutants on Cereal
Growth. Rothamsted Exp. Sta. Report for 1975, Part 1:41-42.
Davis, C. R., D. R. Howell and G. W. Morgan. 1966. Sulfur Dioxide Fumiga-
tions of Range Grasses Native to Southeastern Arizona. J. Range Manage-
ment, 19(2):60-64.
Guderian, R. 1977. Air pollution. Springer Verlag, Berlin. 127 pp.
Heagle, A. S., D. E. Body and E. K. Pounds. 1972. Effect of Ozone on Yield
of Sweet Corn. Phytopathology, 62:683-687.
Heagle, A. S., D.E. Body and G. E. Neely. 1974. Injury and Yield Responses
of Soybean to Chronic Doses of Ozone and Sulfur Dioxide in the Field.
Phytopathology, 64:132-136.
Heck, W. W., J. A. Dunning, and I. J. Hindawi. 1965. Interactions of En-
vironmental Factors on the Sensitivity of Plants to Air Pollution. J.
Air Pollut. Cont. Assoc.,15:511-515.
608
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Heitschmidt, R. K. 1977. Chronic Effects of S02 Western Wheatgrass in a
Montana Grassland. Ph.D. Thesis. Colorado State Univ., Fort Collins,
Colorado. 100 pp.
Hill, A. C., S. Hill, C. Lamb and T. W. Barret. 1974. Sensitivity of Native
Desert Vegetation to S02 and to S02 and N02 Combined. J. Air Pollut.
Control. Assoc., 24:153-157.
Lamb, C. 1972. Sensitivity to Sulfur Dioxide Injury of Plant Species Native
to the Southwest Desert Region. M.S. Thesis. Dept. of Biology, Univer-
sity of Utah, Salt Lake City. 62 pp.
Neely, G. E., D. T. Tingey, and R. G. Wilhour. 1977. "Effects of Ozone and
Sulfur Dioxide Singly and in Combination on Yield, Quality and N-Fixation
of Alfalfa," Proceedings of Internatinal Conference on Photochemical
Oxidant Pollution and Its Control, EPA-600/3-77-001b, 2:663-673.
Neter, J. and W. Wasserman. 1974. Applied Linear Statistical Models. Rich-
ard D. Irwin, Inc., Homewood, Illinois. 842 pp.
Rabe, R. and Kreeb, K. 1976. Bioindikation bei Luftverunreinigungen Durch
Messung der Aktivitat Verschiedener Enzyme von Testpflanze. (Bioindica-
tion of Air Pollution by Measuring the Activity of Various Enzymes of
Test Plants.) Vortr Tag Umweltforsch Univ Honenheim 1976:73-78.
Schwartz, C. C., W. W. Lauenroth, R. K. Heitschmidt and L. L. Dodd. Manu-
script has been submitted to and accepted, pending minor revision, by
Journal of Applied Ecology for publication in fall, 1978.
Snedecor, G. W. and W. G. Cochran. 1967. Statistical Methods, 6th ed. Iowa
State University Press, Ames, Iowa. 592 pp.
Tingey, D. T., L. Bard and R. W. Field. 1978. The Relative Sensitivity of
Selected Plant Species to Several Pollutants Singly and in Combination.
In: The Bioenvironmental Impact of a Coal-Fired Power Plant, Third
Interim Report, Colstrip, Montana, December, 1977, E. M. Preston and R.
A. Lewis, eds. EPA-600/3-78-02, U.S. Environmental Protection Agency,
Corvallis, Oregon, pp. 508-513.
van Haut, H. 1961. Die Analyse von Schwefeldioxidwirkungen auf Pflanzen im
Laboratoriumversuch. Staub. 21:52-56.
van Haut, H. and H. Stratmann. 1970. Farbtafelatlas uber Schwefeldioxid-
wirkugen an Pflanzen. Essen, W. Germany Verlag W. Giradet. 206 pp.
Wells, A. E. 1915. Fumigation Experiments to Determine the Effect of Highly
Diluted Sulfur Dioxide on a Growing Grain Crop. Bull. 98. U.S. Bur.
Mines (Rep. Selby Smelter Comm.):213-307.
Zahn, R. 1963. Ueber den Einfluss Verschiedener Unweltfaktoren auf die
Pflanzenempfindlichkeit Gegeneuber Schwefeldioxyd. Z. Pflanzenkr.
Pflanzekesch. 70:81-95.
609
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SECTION 16
PLANT COMMUNITY CHANGES DUE TO
LOW LEVEL S00 EXPOSURE
2
J. E. Taylor and W. C. Leininger
ABSTRACT
Changes in plant community structure due to
artificial air pollution stressing were monitored by
studying canopy cover, species diversity and phenology,
In addition, aerial and ground photography was accom-
plished at periodic intervals during the growing
season. Vegetation on the two ZAPS sites is respond-
ing differently to S09 fumigation. This is shown in
differential responses of individual species and of
graminoids versus forbs. These changes are partly
confounded with inherent site differences between
and within the study areas. Species diversity is
not decreasing with SO- fumigation, whether based
on canopy cover or number. Evenness and species
richness are about equally influential on both ZAPS
sites. Number-based diversity values are more
variable than indices derived from cover because of
the strong influence on evenness of sporadic flushes
of high-number, low-cover annual species. Phenology
data have not reflected treatment differences.
Significant changes in lichen cover have occurred
over the years. Though never abundant, lichen
cover has been strikingly depressed by SO fumi-
gation. This is more strongly observed on ZAPS II,
where growing conditions are less favorable and
fumigation is more intense. Preliminary stereo-
scopic analysis of ground photo plots suggests
this procedure can yield accurate estimates of
cover and number, but some problems remain to be
resolved.
610
-------
INTRODUCTION
The background and objectives of our overall project are given in the
Introduction to Section 3. Research on the Zonal Air Pollution Study (ZAPS)
site near Ft. Howes, is discussed in this section. This research consists of
two interrelated but functionally independent parts: ground studies and
aerial photography. The division is somewhat arbitrary because part of the
data from ground studies is used as ground truth for the aerial photography.
Thus, a portion of the data discussed here also is used in connection with
aerial monitoring in Section 24.
The research to be discussed in this section includes studies of canopy
coverage, species diversity, plant phenology, and ground-level photography.
These are organized in the two general topics, Plant Community Analysis and
Photographic Monitoring.
MATERIALS AND METHODS
Methodological details are presented in Section 3. The following
discussion is restricted to the modification of those details on the ZAPS
sites.
Plant Community Analysis
Canopy Coverage
Data were collected on the ZAPS sites at four times during the 1977
growing season: 21-22 May, 26-27 June, 26-27 July, and 4-5 September.
These dates approximated the stages of early growth, peak of cool-season
green, peak of warm-season green, and summer dormancy, respectively.
Each of the ZAPS plots was arbitrarily subdivided for sampling, with
equal observations collected from the upper (north) and lower (south) half.
These were handled as "replicates" in the statistical analyses, although
they were not randomly designated; the lower area was always termed the first
replicate, and the upper the second.
Two restrictions were imposed on sample plot positioning. Microtopo-
graphic depressions (run-in moisture areas) were avoided and no plots were
placed less than one meter from a gas delivery pipe.
Diversity
As at the Colstrip locations, both density and cover data were collected
concurrently at every sampling date. Diversity, evenness, and species rich-
ness were calculated from each data type. Species encountered in the samples,
as well as others observed on the sites, are given in Appendix 16.1.
611
-------
In several analyses, linear regression procedures were used to illustrate
relationships between S02 levels and plant responses. The fumigation rates
used were the theoretical ones of 0, 2, 5, and lOpphm for control, low,
medium, and high, respectively. The actual values varied slightly (Sections
9 and 10).
Phenology
The phenological stages of all recognizable species were codea at each
of six observation dates in 1977.
Lichens
During the 1977 cover sampling we noticed the striking absence of
lichens from the plots receiving the higher rates of S02. Eversman (1977)
reported similar findings with lichens which she had transplanted into the
ZAPS plots. This prompted us to review our data from previous years to see
if temporal changes had indeed occurred. Because of the low initial abun-
dance of lichens in the area and their characteristically clumped distri-
bution patterns, we analyzed lichen cover over all samples within years. As
in other canopy data, we used five contiguous frames as one sampling unit.
All these techniques served to reduce sample variability. Lichen numbers
were not estimated because of the difficulty in distinguishing individual
plant units i.n situ.
Photographic Monitoring
We used our standard ground and aerial photography procedures as
described in Section 3 and 24. Aerial photo missions were timed to coincide
with ground samples.
RESULTS AND DISCUSSION
Plant Community Analysis
Canopy Coverage
A summary of coverage data for ZAPS I and II is given in Tables 16.1.
and 16.2., respectively. Means of vegetational categories are presented in
Figure 16.1.
The treatment responses on the two ZAPS sites are difficult to compare
because of pretreatment differences in species composition. Variations in
soils, climate, and recent grazing histories all contribute to these differ-
ences .
In ZAPS I there is a tendency for a decrease in grasses and a corres-
ponding increase in forbs with increasing fumigation. Total vegetation shows
no consistent pattern. Lichens show a general decrease across treatments.
Reverse trends are observed in ZAPS II, at least for grasses and forbs.
Lichens, while never abundant, are essentially absent on the higher treat-
ments of S02«
612
-------
TABLE 16.1. CANOPY COVERAGE (PERCENTAGE) FOR ZAPS I, 1977.
ON
SPECIES CONT .
21 MAY
LOW MED.
HIGH
26 JUNE
CONT . LOW MED .
HIGH
26-27
CONT. LOW
JULY
MED. HIGH
4 SEPT
CONT. LOW MED. HIGH
GRAMINOIDS
Agropyron smithii 21.
Aristida longiseta
Bouteloua graoilis
Bromus sp. 2.
B, japoniaus
Calamagrostis montanensis 1*
Carex pennsylvaniaa
Danthonia unispiaata
Festuaa idahoensis
Junaus interior
Koeleria aristata 16.
Muhlenbergia auspidata
Poa pratensis 4.
P. sandbergii 3.
Sohedonnardus paniaulatus
Sporobolus aryptandrus
Stipa aomata 3.
5. viridula 2.
FORBS
Aahillea millefolium 8,
Agoseris glauaa
Ambrosia psilostaohya
Androsaae ooaidentalis
Antennaria sp.
A. neglecta
A. rosea
Arnica sororia
Aster falcatus
Astragalus sp.
A. crassiaarpus
A. purshii
Bahia oppositifolia
Cerastium arvense
Conyza oanadensis
Erigeron divergens
Gaura coacinea
Grindelia squarrosa
81
81
44
00
06
38
19
06
31
44
,19
.31
.25
.44
10.75
4.50
2.94
.75
.25
12.50
2.13
4.50
10.63
2.00
.25
.13
2.00
.38
.06
13.81
1.13
.38
1.88
.31
.38
.38
11.50
2.94
4.25
3.75
.06
8.88
.06
.94
.50
1.60
.38
17.81
2.94
.06
1.31
.44
9.06
.25
4.69
.81
.38
16.31
.69
.44
.75
.38
.38
26.75 15.88
4.25 4.13
.38
4.25 1.06
.56 .31
2.00
.06
22.31 19.81
1.75
5.44 2.88
11.50
2.69
15.38 2.25
.56 2.31
1.31
.06
.38 2.00
.06 .06
.75
14.19
.75
.38
1.56
.50
23.75
3.94
2.25
3.75
5.75
5.75
.44
1.19
19.69
2.38
.38
1.13
.38
8.06
.13
5.63
.44
2.00
.38
20.19
2.25
.06
2.56
19.94 20.88
2.13 6.00
1.00
3.50 .69
.06 .13
17.00 12.50
.63
6.06 5.81
1.31
6.94 15.81
.50
9.13 1.06
.50
.06
.94
.06
.38
.06 .38
.06
.13
.44 2.81
.38
17.44 19.38
2,56 7.63
1.38 .38
1.31 .94
.44
18.66 9.88
1.25 1.38
7.44 4.31
6.94 .06
.06
8.63 15.63
3.25 1.31
.38
2.06
.38
19.20 15.15
1.45 5.85
.05
5 . 80 .50
.05
15.65 17.60
1.05 .70
3.50 1.85
.35 4.30
2.55
7.45 1.46
3.50 4.65
.05
1.96
.30
16.15 24.90
4.25 2.25
.05 1.60
1.00 1.90
.90
21.85 9.15
.40 .65
2.30 6.15
.05
7.35 .05
.05
3.85 15.95
.05
2.80 1.50
.65
1.25 2.40
.30
* Includes B. japonicus and B. tectonm which were indistinguishable early in the season.
-------
TABLE 16.1. (continued)
SPECIES
CONT.
21 MAY
LOW MED.
HIGH CONT.
26 JUNE
LOW MED.
HIGH CONT.
26-27 JULY
LOW MED. HIGH
CONT.
4 SEPT
LOW MED.
HIGH
FORBS (continued)
Hedeoma hispida
Lepidiwn densiflorum
Leucoarinum montanum
Lomatium sp.
Lup-inus sp.
Mammi'l'iax'ia missouriensis
Melilotus offieinalis
Opuntia fragilis
Orthooarpus luteus
Petalostemon pwcpwcewn
Phlox hoodii
Plantago sp.*
P. patagonioa
P. spinulosa
Polygonum viviparwn
Psoralea argophylla
Solidago missouriensis
Sphaeralcea oooainea
Taraxacum officinale
Tragopogon dubius
Vioia americana
Zygadenus venenosus
Misc. forbs
.13
.13
.06 .31
.50
.38
.20
.10
.25
.05
.05
.38
.75
.31
.75
9.88
7.94
.44
.50
.38
.88 .63
.38 .25
1.25 12.56
5.69 6.94
.06 .63
.12
.38
.50
1.50
12.69
7.56
.06
.13
.32
.50
.25
.44
.25
1.75
10.00
10.19
.88
.06
.75
.44
1.44
4.25
11.50
.44
.50
.56 6.56
.69 .31
.44
.25
.44
6.06 4.63
13.19 12.63
10.81 9.00
.25
.44
.06
1.50
3.31
9.25
.19
.94
.81
.06
.13
.56
4.13
6.44
.13
.06
1.19
.06
.38
.19
4.81
12.00
8.00
.06
3.75
.44
.13
.44
.06
1.69
8.13
8.88
1.31
.05
.15
.35
2.35
.80
1.35
1.85
4.20
.25
.05
.70
.05
.45
2.80
1.45
7.60
.50
.20
.10
.05
1.10
4.05
9.15
3.05
.55
.20
.05
.35
.75
5.45
4.60
HALF-SHRUBS AND SHRUBS
Artemisia frigida
A. tridentata
.38
1.38
.88
.06
.06 1.50
.13 1.25
.30 1.35
OTHERS
Bare ground
Lichen
Moss
Litter
Rock
TOTAL VEGETATION
TOTAL GRAMINOIDS
TOTAL FORBS
TOTAL SHRUBS
2.94
4.88
3.25
60.63
94.39
55.69
30.19
.38
3.75
1.50
11.50
59.50
.06
74.90
48.94
13.00
8.69
1.50
2.25
67.56
79.38
40.75
33.50
1.38
3.38
1.25
1.00
74.56
83.44
37.31
42.63
1.25
4.38
6.75
3.75
72.38
.13
122.31
68.69
43.06
.06
3.19 3.63 4.25
1.94 8.44 5.56
5.50 3.50 7.06
77.50 67.19 61.06
.19
90.25 107.50 114.87
57.31 51.06 40.56
25.50 44.44 60.19
.06 1.50
5.25
4.94
4.69
74.06
.19
90.95
56.13
25.25
5.56
3.19
9.44
73.88
.25
96.69
64.75
19.31
5.63
5.25
.88
76.44
.06
101.57
56.38
38.94
.13
4.00
1.69
1.13
81.56
92.76
44.44
44.25
1.25
5.30
11.80
4.55
70.40
88.80
49.55
22.90
6.35
4.00
10.30
71.10
91.95
56.05
21.60
5.20
2.35
.30
81.85
78.95
53.40
22.60
.30
4.00
1.15
2.45
80.30
.05
88.45
47.60
,35 . 90
1.35
Includes both P. Patagonia and P. spinulosa which were indistinguishable early in the
season.
-------
TABLE 16.2. CANOPY COVERAGE (PERCENTAGE FOR ZAPS II, 1977.)
Ul
SPECIES
GRAMINOIDS
Agropyron smithii
Aristida longiseta
Bouteloua gracilis
Bromus sp.
B. japonicus
B. tectorum
Car ex f Hi folia
Koeleria cristata
Muhlenbergia auspidata
Poa pratensis
P. sandbergii
Sohedonnardus pani au lotus
Stipa comata
S. viridula
FORBS
Aohillea millefolium
Androsaoe oacidentalis
Antennaria negleota
Astragalus sp.
A . drummondii
A. purshii
Bahia oppositi folia
Camelina miarocarpa
Conyza canadensis
fJrigeron divergens
Hedeoma hispida
Heterotheaa villosa
Lappula echinata
Lepidium densiflorum
Leuoocrinum montanun
Lomatium sp.
CONT.
34.94
9.94
.50
10.56
.06
2.00
.69
.06
.06
.06
.44
.06
10.94
.31
22 MAY
LOW MED .
30.75
3.56
.06
.50
11.81
.06
.94
2.25
.31
.13
.06
.06
1.31
.06
Mammillaria missouriensis
Melilotus officinalis
Opuntia fragilis
0. polyacantha
Orthocarpus luteus
.38
.13
.06
17.19
.13
7.69
11.13
1.75
7.50
13.00
.38
.06
.38
.75
.06
.06
1.81
.06
HIGH
14.19
.50
1.81
29.50
.69
5.13
10.94
.06
.25
2.25
.38
.81
.06
.13
.06
CONT.
40.31
.06
9.00
.44
9.81
.75
8.88
.63
2.06
3.50
.19
.13
6.44
.06
.06
27 JUNE
LOW MED .
41.00 25.69
4.25
5.56 12.25
.31
.13 11.63
6.56 6.25
10.06 5.75
.88 .19
2.81 22.81
3.88 1.31
.06
2.75
.38 .13
.63
1.35 3.31
.06 .38
HIGH CONT .
37.63 34.19
.06
4.81 12.81
.25 .06
.94
23.25 7.38
.13 .94
6.50 8.44
.38 .88
1.25
19.94
.06 2.25
.19 .13
5.31 1.63
.25 .31
3.31 4.75
.06
.44
27-28
LOW
41.31
.94
6.75
.44
5.19
6.25
.13
2.19
2.44
.06
.06
.38
1.50
.06
.50
JULY
MED.
25.88
1.94
9.19
9.88
.38
9.56
5.06
.25
.75
16.06
3.81
.50
1.75
.38
1.50
.06
HIGH CONT .
32.81 36.85
.38
2.69 .10
8.81 9.75
.06 .10
16.06 1.35
.10
5.25 6.05
.06 .55
1.69
14.19
.44 .30
.19
3.31
.31 .25
4.75 10.75
5 SEPT
LOW MED.
42.95 29.30
1.70 3.35
7.10 7.10
.30
.05 11.00
1.65 2.75
5.20 3.30
.10
.05
.40 6.85
2.20 .95
2.00
.10
.05
.85 1.10
.30 .30
1.70
HIGH
31.30
4.75
15.45
.05
2.55
.15
.95
10.30
.05
1.15
.05
1.80
* Includes B. japonicus and B. teotorwn, which were indistinguishable early in the season.
-------
TABLE 16.2. (continued)
SPECIES
CONT.
22 MAY
LOW MED.
HIGH CONT.
27 JUNE
LOW MED.
HIGH CONT.
27-28 JULY
LOW MED.
HIGH CONT.
5 SEPT
LOW MED.
HIGH
ON
FORBS (continued)
Phlox hoodii
Plantago sp.*
P. patagoniaa
P. spinulosa
Polygonum viviparum
Sphaeralaea aoaainea
Taraxacum offioinale
Tragopogon dubius
Viaia amevicana
Viola nuttallii
Misc. forbs
HALF-SHRUBS AND SHRUBS
Artemisia aana
A. frigida
A. tridentata
Ceratoides lanata
OTHERS
Bare ground
Lichen
Moss
Litter
Rock
TOTAL VEGETATION
TOTAL GRAMINOIDS
TOTAL FORBS
TOTAL SHRUBS
1.94
.31
.63
13.19
1.69
2.13
.50
.13
1.06
29.00
2.31
1.44
.13
.19
1.25 1.63 2.44
.06
.06 3.06 2.00 4.19
1.94 2.56 2.25
.75 2.40 1.60
.88
1.44
.25
2.13
.13
.63
.31
.81
.69
.19
.06
.13
.13
1.31
.06
.63
.35
.10
.05
.25
.35
.05
.10
.25
.05
.75
.88
14.81 2.81 20.38 43.88 9.94 2.38 8.38 26.88 16.75 3.44 5.85 1.75 5.80
4.56 1.69 6.38 7.31 6.25 5.75 2.38 1.44 5.06 2.31 2.70 1.90 1.90
5.13 5.56
.81 3.56 9.25 7.63
.25
.13
.25
.06
.06 3.56
.88
.10
.05
.50
.06
.30
.75
.15
.06
8.38
2.63
3.31
65.56
97.00
56.00
35.00
.06
9.88
2.25
1.69
62.19
90.63
47.69
39.00
.69
5.75
.06
.31
61.38
89.87
58.38
30.44
.69
.06
.88
9.88
57.06
79.56
62.75
15.88
.94
.94
8.44
3.94
3.06
65.50
123.13
71.94
43.25
.94
4.19
1.94
1.56
77.60
133.81
67.31
63.00
1.50
6.81
.75
.13
77.13
130.89
88.81
39.81
1.50
3.75
13.88
.19
70.25
.50
122.13
90.13
28.06
3.75
1.44
8.00
4.69
.19
79.81
.13
96.63
64.69
25.63
1.44
.38
4.63
1.50
.25
83.31
98.88
63.19
33.56
.38
1.00
8.19
.31
.25
81.00
.06
117.25
78.94
36.75
1.00
1.63
1.63
5.94
83.31
.06
104.19
82.00
18.88
3.31
2.85
6.95
2.55
.05
78.95
.10
92.90
64.85
22.60
2.85
.40
5.40
1.40
.20
82.10
.10
90.65
59.15
29.50
.40
1.60
10.90
.50
.10
75.30
.15
82.35
63.00
17.15
1.60
.40
1.30
8.15
.15
80.30
.10
74.00
65.50
6.65
1.70
* Includes P. patagoniaa and R, spinulosa3 which were indistinguishable early in the season.
-------
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There are no strong response patterns in individual grass species on
ZAPS I. Stipa viridula may be decreasing, but is present in such small
amount that trends are difficult to see. The increase in forbs is primarily
due to Taraxacum officinale. Other species, notably Achillea millefoliwn,,
appear to respond differently to different treatment rates. This suggests a
gradient of interspecific competition across the plots as species are
alternatively less and more tolerant than other species to different levels
of S09 fumigation.
On ZAPS II, the species which are decreasing most strongly are Agropyvon
smifhli- and Poa sandbergii. On the other hand, Koeleri-a cr-istata is in-
creasing, as is Stipa viridula. The latter species is probably responding
more to the higher amount of run-in moisture on the high S0_ plot than to
any negative influence of the fumigation. Many of the forbs are present in
such low amounts that their treatment responses are obscure. Two species
which do show SO effects are Achillea mi11efo1i.im and Taraxacum officinale.
Both decrease with treatment, although T. offic-inaie appears to be slightly
enhanced at very low levels of fumigation.
Additional evidence of the fundamental differences between ZAPS I and
II is given in Figure 16.2., which shows the numbers of species observed in
each sample. On each ZAPS site there are similar seasonal trends in plant
numbers. ZAPS I tends to show a depression in species richness at inter-
mediate treatment levels, while ZAPS II responds inversely.
UJ
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30-
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21-
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• • MAY
x x JUNE
a A JULY
•• • SEPTEMBER
CONTROL LOW MEDIUM HIGH CONTROL LOW MEDIUM HIGH
ZAPS I ZAPS H
Figure 16.2. Total number of species encountered in ZAPS
I & II during four sample dates, 1977.
618
-------
Diversity
Diversity, evenness, and species richness based on canopy cover are
shown in Figure 16.3. The close agreement in diversity trends among dates
indicates that diversity can indicate changes in plant community structure.
ZAPS I is more diverse than ZAPS II. Both areas show a dip in diversity at
the low S02 rate. The two components of diversity, evenness and species rich-
ness, seem to be about equally influential on both ZAPS areas. Species rich-
ness is more variable with season, which is reflected in diversity trends.
Evenness is very uniform through seasons, especially on ZAPS II. This
suggests that our sampling procedures are very precise, and that interplot
differences are real, not sampling artifacts.
When based on plant numbers, very similar trends are seen in diversity
and species richness (Figure 16.4., A and C). Evenness is much more variable,
which is to be expected because of the high numbers of annuals and Agropyron
smithii in some of the plots (Figure 16.4., B). The greater overall vari-
ability in number-based data is due to the disproportionate influence of
species which may be present in high numbers but low coverage or biomass.
Statistical summaries of diversity based on canopy and number are
presented in Tables 16.3. and 16,4., respectively. These tables illustrate
the greater variation among treatments on ZAPS II and the similar statistical
sensitivities of cover- and number-based diversity data.
Table 16.5. compares diversity means based on cover and numbers. The
low diversity on the low fumigation level is significant on both ZAPS, but
more so on ZAPS II.
A very highly significant correlation exists between diversity based on
cover and on number (Figure 16.5.). Further testing may show that either is
sufficient to characterize diversity changes due to pollution stress. If
only one kind of data wereT collected, canopy probably would be preferred
because it is more closely related to ecological importance (Daubenmire,
1959), is easier to obtain, and is less influenced by periodic flushes of
annuals.
We looked at ecosystem stability by comparing standard errors as per-
cents of mean diversity. Values were averaged over all observations within
treatments and ZAPS sites. The results are shown in Figure 16.6. There is
a tendency for increasing variation with increased stress application on
ZAPS II. This may reflect incipient ecosystem instability.
We are convinced that diversity values are showing plant community
changes due to air pollution stress. Additional refinements in data col-
lection and analysis will be made in the coming field season. The results
will be incorporated in the Power Plant Siting Protocol.
619
-------
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z
lz«-
• • MAY
x x JUNE
A A JULY
• • SEPTEMBER
.90-,
.82-
- ,7B-\
in
5 .74-
>
LJ
• • MAY
X X JUNE
O- a JULY
• • SEPTEMBER
CONTROL LOW MEDIUM HIGH CONTROL LOW MEDIUM HIGH
ZAPS i ZAPS n
CONTROL LOW MEDIUM HIGH CONTROL LOW MEDIUM HIGH
ZAPS I ZAPS H
(/)'•*"
LiJ
•z.
I
o
IT 13-
(fl
• • MAY
x x JUNE
A a JULY
• ' •• SEPTEMBER
I X±S=
10-
Figure 16.3.
A=Diversity Index (H1),
B=Evenness (J'), and
C=Species Richness (S)
based on canopy cover-
age, ZAPS I & II, 1977.
9-
''
CONTROL LOW MEDIUM HIGH CONTROL LOW MEDIUM HIGH
ZAPS I ZAPS I
620
-------
29 T
2.7-
g
(3 2.3-
UJ
15
• • MAY
x x JUNE
a a JULY
• • SEPTEMBER
UJ .54-
>
LU
« • MAY
X X JUNE
a- a JULY
• • SEPTEMBER
CONTROL LOW MEDIUM HIGH CONTROL LOW MEDIUM HIGH
ZAPS I ZAPS I
CONTROL LOW MEDIUM HIGH CONTROL LOW MEDIUM HIGH
ZAPS I ZAPS H
16-1
15-
05 13-
(f)
CO
UJ
10-
9-
• • MAY
x x JUNE
a- a JULY
• • SEPTEMBER
X± S,
Figure 16.4.
A=Diversity Index (HT),
B=Evenness (J'), and
C=Species Richness (S)
based on numbers, ZAPS
I & II, 1977.
CONTROL LOW MEDIUM HIGH CONTROL LOW MEDIUM HIGH
ZAPS I ZAPS IE
621
-------
TABLE 16.3. ANALYSIS OF VARIANCE OF CANOPY COVER BASED DIVERSITY, ZAPS I&II, 1977.
ZAPS I
ZAPS II
ho
DATE
21 MAY
26 JUNE
26-27 JULY
4 SEPT
SOURCE OF
VARIATION
REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
DEGREES
FREEDOM
1
3
3
3
3
9
9
31
1
3
3
3
3
9
9
31
1
3
3
3
3
9
9
31
1
3
4
3
4
12
12
39
MEAN
SQUARE
1.0593
.0396
.0241
.1451
.0172
.0123
.0299
.0683
.0000
.1110
.0383
.1259
.0235
.0112
.0289
.0405
.0955
.0921
.0571
.0402
.0296
.0226
.0293
.0393
.2699
.1872
.0974
.1348
.1027
.0575
.0354
.0808
F
35.5**
1.3
.8
4.9*
.6
.4
0.0
3.8*
1.3
4.4*
.8
.4
3.3
3.1
1.9
1.4
1.0
.8
7.6*
5.3*
2.7
3.8*
2.9
1.6
SOURCE OF
DATE VARIATION
22 MAY REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
27 JUNE REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
27-28 JULY REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
5 SEPT REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
DEGREES
FREEDOM
1
3
3
3
3
9
9
31
1
3
3
3
3
9
9
31
1
3
3
3
3
9
9
31
1
3
4
3
4
12
12
39
MEAN
SQUARE
.1272
.1854
.0303
.0442
.0278
.0851
.0877
.0821
.5422
.5184
.0934
.0218
.0388
.0234
.0857
.1142
.4291
.5001
.0373
.2348
.0385
.0551
.1029
.1382
.7020
.3955
.2032
.0603
.0566
.0699
.0288
.1101
F
1.5
2.1
.3
.5
.3
1.0
6.3*
6.0*
1.1
.3
.5
.3
4.2
4.9*
.4
2.3
.4
.5
24.3**
13.7**
7.0**
2.1
2.0
2.4
* Significant at P.05
** Significant at P.01
-------
TABLE 16.4. ANALYSIS OF VARIANCE OF NUMBERS BASED DIVERSITY, ZAPS I & II, 1977.
ZAPS I
ZAPS II
SOURCE OF
DATE VARIATION
21 MAY REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
26 JUNE REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
26-27 JULY REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
4 SEPT REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
DEGREES
FREEDOM
1
3
3
3
3
9
9
31
1
3
3
3
3
9
9
31
1
3
3
3
3
9
9
31
1
3
4
3
4
12
12
39
MEAN
SQUARE
.5102
.2487
.0619
.4701
.1456
.0345
.0445
.1290
.0341
.0671
.1010
.1076
.0376
.0420
.0879
.0691
.3116
.3409
.1353
.0996
.1605
.0682
.1172
.1351
.1865
.1102
.1653
.4603
.0252
.1394
.0974
.1411
F
11.5**
5.6*
1.4
10.6**
3.3
.8
.4
.8
1.1
1.2
.4
.5
2.7
2.9
1.2
.9
1.4
.6
1.9
1.1
1.7
4.7*
.3
1.4
SOURCE OF
DATE VARIATION
22 MAY REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
27 JUNE REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
27-28 JULY REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
5 SEPT REPLICATIONS
TREATMENTS
GROUPS
REP X TRMT
REP X GROUP
TRMT X GROUP
ERROR
TOTAL
DEGREES
FREEDOM
1
3
3
3
3
9
9
31
1
3
3
3
3
9
9
31
1
3
3
3
3
9
9
31
1
3
4
3
4
12
12
39
MEAN
SQUARE
.6457
.4138
.0343
.0433
.1063
.0192
.0962
.1122
.7532
.4132
.0346
.1052
.0825
.0197
.0160
.0961
.8511
.4145
.0354
.3807
.0352
.0458
.0804
.1479
.5068
.4342
.0271
.1298
.0321
.1349
.0253
.1117
F
6.7*
4.3*
.4
.5
1.1
.2
47.2**
25.9**
2.2
6.6*
5.2*
1.2
10.6**
5.2*
.4
4.7*
.4
.6
20.1**
17.2**
1.1
5.1*
1.3
5.3**
* Significant at P.05
** Significant at P.01
-------
TABLE 16.5. MEAN VALUES OF DIVERSITY (H1) BASED ON CANOPY COVERAGE AND NUMBERS, ZAPS I & II, 1977.
ZAPS I
ZAPS II
DATE
21 MAY
26 JUNE
26-27 JULY
4 SEPT
TREATMENT
CONTROL
LOW
MEDIUM
HIGH
CONTROL
LOW
MEDIUM
HIGH
CONTROL
LOW
MEDIUM
HIGH
CONTROL
LOW
MEDIUM
HIGH
CANOPY
MEAN
3.1899
3.0514
3.1898
3.1962
3.2367 ab
3.0659 a
3.1435 ab
3.3385 b
3.0929
2.9924
3.2249
3.2023
3.1324 a
2.8681 b
2.8429 b
3.0270 ab
NUMBERS
MEAN
2.6659 a1
2.3632 b
2.6525 a
2.7757 a
2.6044
2.4786
2.6968
2.5536
2.2427
2.1527
2.5528
2.5463
2.1961
2.2044
2.1733
1.9830
DATE TREATMENT
22 MAY CONTROL
LOW
MEDIUM
HIGH
27 JUNE CONTROL
LOW
MEDIUM
HIGH
27-28 JULY CONTROL
LOW
MEDIUM
HIGH
5 SEPT CONTROL
LOW
MEDIUM
HIGH
CANOPY
MEAN
2.7921
2.4542
2.7365
2.5894
2.9137 a
2.5217 b
3.1373 a
2.8419 ab
2.7459 a
2.2854 b
2.8334 a
2.7593 a
2.4781 a
2.1031 b
2.5468 a
2.2980 c
NUMBERS
MEAN
2.1617 ab
1.8835 a
2.3691 b
2.3585 b
2.4003 a
1.9777 b
2.4910 a
2.3704 a
2.0095 ab
1.7558 a
2.3104 b
2.0663 ab
1.8741 a
1.4341 b
1.8352 a
1.5908 c
Any two means within dates and columns not followed by the same letter are significantly different
at the .05 level.
-------
2.8-,
2.6 -\
CO
(T
UJ
992.4
02.2-1
O
UJ
CO
00
2.0 H
t 1.8
CO
(T
UJ
>
Q 1.6-
I.2H
• X
• MAY
X JUNE
A JULY
• SEPTEMBER
2.0
2.2
2.4
2.6
2.8
3.0
3.2
DIVERSITY (H1) BASED ON % CANOPY COVERAGE
3.4
Figure 16.5.
The regression of diversity based on numbers onto diversity
based on canopy coverage, ZAPS I and II, 1977.
** P < .01.
625
-------
7-
6-
5-
LJ
o
<
z
LJ
o
LT
LJ
CL
% CANOPY COVERAGE
NUMBERS
I- *±Sx
!x
J - X±S3
UJ
LU
O
cr
6-
5-
4-
r2 = .004
2-
% CANOPY COVERAGE
NUMBERS
1= x±s.
M
S02
M
S02
Figure 16.6. Standard errors expressed as percentages of mean diversity over
four observations, ZAPS I (left) and ZAPS II (right), 1977.
Phenology
Phenological data from the ZAPS sites are presented in Appendices 16.2
and 16.3. No conspicuous trends are shown. These data are contributions to
the long-term phenologic baseline records of the sites.
Lichens
Although lichens usually are ignored in grassland research, they may be
important on pollution studies because they are more sensitive than other
plant groups. (LeBlanc and Rao, 1975).
We have traced lichen canopy cover since our first data collections on
ZAPS I in 1975, and ZAPS II in 1976 (Figures 16.7. and 16.8.). The graphs
are based on averages among sample dates in each year. The principal lichen
is Parme'li-a dnlovochpoa on both ZAPS sites. Our earlier data may include
small amounts of blue-green algae, but not in sufficient quantities to
influence conclusions.
In 1975, the first year of stress on ZAPS I, lichens were not depressed
by S0_ fumigation. The low treatment plot had a significantly lower lichen
cover than the other three plots, probably because of inherent site dif-
ferences. In the second year, a significant depression in lichens was
626
-------
UJ
OL
LU
>
O
o
a.
o
o
10-
9-
8-
7-
6-
5-
4-
3-
2-
Figure 16.7.
M
H
L M
S02
1977
1976
- 1975
M
H
Mean lichen coverage (canopy) for ZAPS I, 1977,, 76, and 75
-"-Means within years followed by the same letter are not
significantly different at the p.05 level.
1977
1976
—i-
L
—r—
M
H
S02
Figure 16.8.
Mean lichen coverage (canopy) for ZAPS II, 1977 and 1976.
^eans within years followed by the same letter are not
significantly different at the p.05 level.
** P < .01
627
-------
observed with increasing stress. The overall reduction in cover is ascribed
to the dry growing conditions in 1976. By 1977, which was a more normal
moisture year, the cover of lichens was significantly lower on all levels of
SO compared with the control. The lower inherent lichen cover on the low
treatment plot greatly decreases the linearity of the regression.
The situation on ZAPS II is different. This may be due to a later first
sample date, more intense and earlier fumigation, and the less favorable
growing conditions in 1976. The highly significant linear regression shows
the depression of lichen cover in the first year of fumigation. In 1977,
the second year of treatment stress, lichen cover was significantly depressed
at all SO levels. The data points would be better fit by an exponential
curve, which is typical of biological functions.
In an attempt to eliminate annual climatic effects, we normalized the
data by expressing treatment coverages as percents of controls (Figure 16.9.),
The increasing depression in lichen cover with years is clearly illustrated,
as is the consistently low lichen cover on the 2pphm SO treatment.
The ZAPS II curves reflect the more severe lichen losses in both years.
They also more clearly show the overall loss the second year.
120
o HO-
OT
2 100
O
" ^
O
.o 80
70
?
<
< 60H
UJ
< 50-
§ 40-
O
O
>_ 30-
0.
0
20-
10-
• -1977
--I976
1975
M
S02
1977
1976
Figure 16.9.
Lichen cover in four treatments expressed as a percentage of
the control (0 pphm S0?), ZAPS I (A) and ZAPS II (B).
** P < .01
628
-------
r
Both ZAPS I and II have lost very substantial portions of
SeV6re °ature of the stress being applied
exposure level has reduced lichens to about
the original cover on both sites.
Summaries of analysis of variance for lichen data are given in Table
16.6. In every case, treatment effects become more significant with ad-
ditional seasons of stress.
LU
LJ
O
IT
120 -j
110-
100-
90-
80-
70-
60-
50-
40-
30-
20-
10-
l.
1977 as a % of 1975
1977 as a % of 1976
V..
L M
ZAPS I
H
S02
L M
ZAPS H
Figure 16.10. Lichen cover expressed as a percentage
of the first year coverage.
CONCLUSIONS
Species composition, based on both canopy cover and number, varies
among SO rates and sites. On ZAPS I graminoids are being replaced by forbs
at higher fumigation levels. The opposite response is occurring on ZAPS II.
The relative importance of treatments and inherent site variability is
still unclear.
Species diversity is sensitive in monitoring seasonal plant community
changes. Low standard errors and large differences in sample means suggests
that the treatment plots are different. Evenness and species richness is
much more variable among sample dates.
629
-------
TABLE 16.6. ANALYSIS OF VARIANCE FOR LICHEN COVER, ZAPS I & II
ZAPS I
ZAPS II
U>
O
SOURCE
YEAR VARIATION
1977 REPLICATIONS
TREATMENTS
GROUPS
OBSERVATIONS
TRMT X OBSERV
TRMT X REP
TRMT X GROUPS
OBSERV X REP
OBSERV X GROUPS
REP X GROUPS
ERROR
TOTAL
1976 REPLICATIONS
TREATMENTS
GROUPS
OBSERVATIONS
TRMT X OBSERV
TRMT X REP
TRMT X GROUPS
OBSERV X REP
OBSERV X GROUPS
REP X GROUPS
ERROR
TOTAL
1975 REPLICATIONS
TREATMENTS
GROUPS
OBSERVATIONS
TRMT X OBSERV
TRMT X REP
TRMT X GROUPS
OBSERV X REP
OBSERV X GROUPS
REP X GROUPS
ERROR
TOTAL
DEGREES
FREEDOM
1
3
4
3
9
3
12
3
9
4
84
135
1
3
3
1
3
3
9
1
3
3
33
63
1
3
4
2
6
3
12
2
8
4
74
119
MEAN
SQUARE
128.1177
177.3382
58.5180
61.6302
26.8055
14.3382
35.7682
42.0678
8.8924
40.3179
22.0610
31.7832
1 .0000
27.1823
4.5677
31.6406
23.2240
11.6042
2.6788
16.0000
9.6719
14.0729
6.6746
8.9521
7.7521
81.7354
1.3042
49.3188
99.6687
25.9799
19.1694
25.9522
22.8994
27.0854
26.0416
29.6917
F
5.8*
8.0**
2.7*
2.8*
1.2
.7
1.6
1.9
.4
1.8
.2
4.1*
.7
4.7*
3.5*
1.7
.4
2.4
1.4
2.1
.3
3.1*
.1
1.9
3.8**
1.0
.7
1.0
.9
1.0
SOURCE OF DEGREES
YEAR VARIATION FREEDOM
1977 REPLICATIONS
TREATMENTS
GROUPS
OBSERVATIONS
TRMT X OBSERV
TRMT X REP
TRMT X GROUPS
OBSERV X REP
OBSERV X GROUPS
REP X GROUPS
ERROR
TOTAL
1976 REPLICATIONS
TREATMENTS
GROUPS
OBSERVATIONS
TRMT X OBSERV
TRMT X REP
TRMT X GROUPS
OBSERV X REP
OBSERV X GROUPS
REP X GROUPS
ERROR
TOTAL
1
3
4
3
9
3
12
3
9
4
84
135
1
3
3
1
3
3
9
1
3
3
33
63
MEAN
SQUAK£
.0000
77.1520
.3630
2.0755
2.6797
2.9167
.6285
5.9192
1.6050
1.0191
1.7968
3.4847
3.0625
21.0052
1.6406
66.0156
3.5469
9.4271
3.6719
1.5625
3.5156
6.3750
5.0420
6.4540
*
F
.0
42.9**
.2
1.2
1.5
1.6
.4
3.3*
.9
.6
.6
4.2*
.3
13.1**
.7
1.9
.7
.3
.7
1.3
Significant at P.05.
** Significant at P.01.
-------
Differences in phenology among treatment plots were not seen, either
because phenology is not affected or because of the masking influence of
climate, sites, and grazing history. Long-term baseline records are
necessary for phenologic comparisons.
Lichen cover is decreasing with increasing SO rates, and this effect
is cumulative with years.
REFERENCES
Daubenmire, R.F. 1959. A Canopy-Covered Method of Vegetational Analysis.
Northw. Sci., 33(l):43-64.
Eversman, S. 1978. Effects of Low-Level S0~ Stress on Two Lichen Species
In: The Bioenvironmental Impact of a Coal-Fired Power Plant, Third
Interim Report, CoIstrip, Montana. E.M. Preston and R.A. Lewis, eds.
EPA-600/3-78-021, U.S. Environmental Protection Agency, Corvallis,
Oregon, pp. 385-398.
LeBlanc, F. and D.N. Rao, 1975. Effects of Air Pollutants on Lichens and
Bryophytes. In_ Mudd, J.B. and T.T. Kozlowski (Eds). Responses of
Plants to Air Pollution. Academic Press, New York. pp. 237-272.
631
-------
APPENDIX 16.1.
SPECIES ENCOUNTERED ON THE TWO ZAP SITES
ZAPS I
SYMBOL SPECIES
AGSM
AGSP
ARLO
BOGR
BRJA
BRTE
BUDA
CAMO
CAFI
CAPE
DAUN
FEID
JUIN
KOCR
MUCU
PHPR
POPR
POSA
SCPA
SPCR
STCO
STVI
VUOC
ACMI
AGGL
ALTE
AMPS
ANOC
ANTEN
ANNE
ANRO
ARHO
ARSO
ARLU
ASPUM
ASTER
GRAMINOIDS
Agropyron smithii
A. spioatwn
Aristida longiseta
Bouteloua graoilis
Brooms japonicus
B. teotorwn
Buohloe daotyloides
Calamagrostis montanensis
Car ex f Hi folia
C. pennsylvanioa
Danfhonia unispioata
Festuoa idahoensis
Juncus interior
Koeieria cristata
Muhienbergia ouspidata
Phleym pratense
Poa pratensis
P. sandbergii
Schedonnardus paniculatus
Sporobolus oryptandrus
Stipa oomata
S. viridula
Vuipia octoflora
FORBS
Aohiliea miliefoiiim
Agoseris glauea
Alliiwi textile
Ambrosia psilostachya
Androsaoe oooidentalis
Antennaria species
A. neglecta
A. rosea
Arabis hoiboeilii
Arnica sororia
Artemisia lijdoviciana
Asotepias pwniia
Aster species
Cont.
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Low
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Med.
X
X
X
X
X '
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
High
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
ZAPS
Cont.
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Low
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
II
Med.
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
High
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
632
-------
APPENDIX 16.1. (continued)
SPECIES ENCOUNTERED ON THE TWO ZAP SITES
SYMBOL
ASFA
ASTRA
ASCR
ASDA
ASGI
ASPU
BAOP
BEWY
CAMI
CANU
GEAR
CHAL
CHTE
CIUN
COLI
COCA
CREPI
DEBI
DESCU
DRABA
ECPA
ERDI
ERPU
ERAS
GACO
GETR
GRSQ
HASP
HEHI
HEVI
LASE
LAEC
LEDE
LEMO
LIIN
LIRU
LOMAT
LOOR
LUPIN
LUSE
KAMI
SPECIES
A. faloatus
Astragalus species
A . crassiearpus
A. drummondii
A. gilviflorus
A. purshii
Bahia oppositi folia
Besseya wyomingensis
Camelina miorocarpa
Calochortus nuttallii
Cerastium arvense
Chenopodium album
Chorispora tenella
Cirsium undulatum
Collomia linearis
Conyza oanadensis
Crepis species
Delphinium bicolor
Descurainia species
Draba species
Echinacea pallida
Erigeron divergens
E. pumilus
Erysimum asperum
Gaura coccinea
Geum triflorum
Grindelia squarrosa
Eaplopappus spinulosus
Eedeoma hispida
Heterotheca villosa
Lactuca serriola
Lappula enchinata
Lepidium densiflorum
Leucocrinum montanum
Litho sperrrwon incisum
L. ruderale
Lomatium species
L. orientate
Lupinus species
L. sericeus
Mammillaria missouriensis
Cont.
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
ZAPS
I
Low Med.
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Y
A
X
x
X
ZAPS II
High
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
x
x*.
Cont.
X
X
X
X
X
X
X
X
X
Y
A
Y
*\.
X
x
X
Low Med.
X X
X
X
X
X
X X
X X
X
X X
X X
X
X X
x
J.\.
XV
A
.A.
XV
A
x x
v x
A A
x x
4x •**•
x
x x
X
x x
X X
-tV *»•
High
X
X
X
X
X
x
X
X
X
x
633
-------
APPENDIX 16.1. (continued)
SPECIES ENCOUNTERED ON THE TWO ZAP SITES
ZAPS I
SYMBOL
MESA
MEAL
MEOF
MERTE
MEOB
MOFI
OPFR
OPPO
ORLU
OXSE
PENST
PEN I
PEPU
PHHO
PLPA
PLSP
POVI
PSAR
PSES
RAGL
RACO
SENEC
SIAN
SOLID
SOMI
SPCO
TAOF
THAR
TRDU
VIAM
VINU
ZYVE
SPECIES
Medicago sativa
Melilotus alba
M. officinalis
Mertensia species
M. oblongifolia
Monavda fistulosa
Opuntia fragilis
0. polyacantha
Orthooarpus luteus
Oxytropis sevicea
Penstoman species
P. nitidus
Petalos-bemon puppurewn
Phlox hoodii
Plan-bago patagonioa
P. spinulosa
Polygomm viviparwn
Psoralea avgophylla
P. esculenta
Ranunculus glabewimus
Ratibida colwmifez>a
Senecio species
Sisyvinchium angustifoliim
Solidago species
S. missoupiensis
Sphaeralcea coccinea
Taraxacum off-icinale
Thlaspi arvense
Tragopogon dubius
Vicia americana
Viola nuttallii
Zygadenus venenosus
Cont.
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Low
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Med.
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
High
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
ZAPS
Cont.
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Low
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
II
Med.
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
High
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
HALF-SHRUBS AND SHRUBS
ARCA
ARDR
ARFR
ARTR
ATNU
CELA
XASA
Artemisia cana
A. dracunculus
A. frigida
A. tpidentata
Atviplex nut-ballii
Ceratoides lanata
XanthocepHalwn sarothrae
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
634
-------
ON
APPENDIX 16.2.
PHENOLOGICAL PROFILE FOR ZAPS I, 197?!/
HIGH
SPECIES 4-13
GRAMINOIDS
Agropyron 1
smithii
A . spieatum
Aristida
longiseta 12
Boute loua
gracilis 12
Brorms
japonicus 1
B. tectorwn 1
Buchloe
dactyloides
Ca lamagros tis
montanensis 2
Carex filifolia
C. pennsylvaniaa
Danthonia
unispicata
Festuaa iddhoensis
Junaus interior
Koeleria cristata 2
Muh lenbergia
Guspidata
Poa pratensis 3
P. sandbergii 3
Sporobo lus
aryptandrus 12
Stipa Gomata 1
S. viridula
Vulpia octoflora
4-26
2
1
2
2
4
3
3
3
1
2
3
6-2
3-4
3
7
8
7
6
7-8
8
8
5
5
6-26
7
6
7
9
10
10
9
8
10
10
10
11
10
7-19
4
11
8
11
11
12
11
11
11
11
6
11
12
9-4
10
12
12
11-12
12
12&3
12
12
12
12
12
12
12
12
4-13
1
12
12
2
2
2
2
3
3
12
1
4-26
2
1
1
3
3
2
3
3
3
3
1
2
2
6-2
3
3
3
7
4
7
7-8
8
8
3
4
6-26
4
7
7
10
11
4
12
9
10
10
10
3
10
7-19
8
9
9
11
11
12
12
11
11
11
5
11
11
9-4
10
12
12
11-12
11-12
12
12
12
12
12
12
12
12
12
4-13 4-26
1 3
3
12 1
12 12
1 2
3
2 8
2
2 3
3 3
3 3
2
1 3
6-2
3
6
3
6
11
4
8-9
8
8
5
6
6-26
3
some
8
9
6
7
10
3
12
11
10
11
9
9
3
10
11
7-19
8
11
11
11
12
12
11
8
11
11
5
11
12
9-4
9
12
11
11
12
12
3
12
12
11
11
12
11
12
3
4-13 4-26 6-2 6-26
2 2 3 4&7
12 1 3 6
12 12 3 7
269
6 10
3 9
4
11
7
8-9 11
3 3 8 10
3 3 9 11
11
3 6 10
7-19
4&9
11
8
11
11
10
12&3
11
12
11
11
9-4
4&10
12
11
12
12
12
3
12
12
12
12
11
12
12
3
FORBS
Aahillea
millefolium
Agoseris glauca
Allium textile
Ambrosia
psilostachya
Androsace
oaaidentalis
3689 11-12 1
12
8
12
9 12&3 1399 10 32399 11 12&3
2
10
12
10
—Codes are given on p 110.
-------
APPENDIX 16.2. (continued)
SPECIES
CONTROL LOW
4-13 4-26 6-2 6-26 7-19 9-4 4-13 4-26 6-2 6-26 7-19 9-4
MEDIUM HIGH
4-13 4-26 6-2 6-26 7-19 9-4 4-13 4-26 6-2 6-26 7-19 9-4
FORBS (continued)
Antennaria sp. 1 4 9 12 12 12 1 5 9 12 12
Arabis hoiboellii 11
Arnica sororia 2 2 8 12 12 12 2 8 12 12 12
Artemisia
ludovioiana 12 3358 12 23358
Asalepias pumila
Aster faleatus 13499
Astragalus sp.
A. erassioarpus 1 9 11 12
A . drurmondii
A. gilviflorus
A. purshii 11
Besseya
wyomingensis 6 9
Cerastiwn arvense 1 3 9 12 12 12 9 12 12
Chenopodium album
(-^ Cirsium undulatum 1
u> Collomia linearis R
CT* -F
Conyza eanadens^s 5 12 5 12
Crepis sp. 11
Z?e Iphinium
bioolor
Desaurainia sp. 4 12 2 4 12
Echinaaea pallida
Erigeron
divergens 389 8-11 12&3 2389 9-11 12
Erysimum asperum 2 12 9
Gaura oooainea
Grinde lia
squarrosa 12 3 3 4 5 9-10 4 5 6 11
Hapiopappus
spinulosus
Hedeoma hispida 7 12 9 12
Heterotheaa
villosa 2 4 8 9 11
Laetuoa serriola
Lepidium
densiflorum 12
Leueoarinum
montanum 12 3 10 12 12
Li thospermum
ineisum
£,oma.tium sp.
1 4 11 12 12 12 1 10 11-12 12 12
12
2 8 12 12 12
12 23344 2 348
3 4
12
1 3 9 9 11 12 3 9 9 11 12
9 9
1 4
9 11 12
8 9 12 12 12 6 9 12 12 12
239 12 12 9 12 12
8 12
12 433 11&3 3 4 11&3
7
3 3
6 8-9 11 12
2 3 9 9 9&1 10&3 3289 7-12 8-12&3
9 10
5
2 4 7 9&3
569
2 7 489
2 12
9
2 4 11 12 12 12 4 11 12 12 12
10
9 12 12 4 7 12 12 12 12
-------
APPENDIX 16.2. (continued)
SPECIES
CONTROL LOW MEDIUM
HIGH
FORBS (continued)
L. orientale 8
Lupinus sp .
L. serioeus
Mammilaria
missouriensis
Medioago sativa
Meli lotus 1
officinale
Monarda fistulosa
Opuntia fragilis 1
0. polyaeantha I 1
Orthooarpus
luteus 12 12
Oxytropis seriaea
Petalostemon
purpureum
Phlox hoodii 8
Plantago
patagonioa 12 12
P. spinulosa 12
viviparum
Psoralea
argophylla
Ranunculus
glaberrimus 6 8
Ratibida
oolwrtnifeva 12
Seneoio sp .
Sis yrinchium
angus tifo Hum
Solidago sp.
S. missouriensis
Sphaeraloea
aooainea 1
Taraxaeum
officinale 1 5
Thlaspi arvense
Tragopogon
dubius 1 3
Viaia amerieana 3
12
6 8 11
4 5 12
3 8
12
688
8 8
9 11
5 9 10
6 8
8
5 10 10
12 12 12
8 11 12&3
9 11 12
12
12
3
12
12
12
12
12 12
12 12
12
12
11 12
12
12&3 1
12&3 1
12
6 8 11 12
8 12
1 11 12
3 6 8&1 11 11-12 12 6 8 11 11
3
1 12 12 1 4 4 12 12
12
8 8-11 12 12 48 8-11 12
11 12
11
12 3 8 12 12 12 12
6 8 8 12 12 9 12
12 12 8 12
10 12
5 9 9 11 12 4 9 10 12
1 5 6 9 12 12 5 6 9 11
9 10
12 468
5 9 11 12 1 5 10 11 12
5 12 12&1 12&3 12&3 2 5 12 12 12 12&3
9
3 8 12&3 12&3 12&3 238 11&3 12 12&3
9 11 12 12
8 9 11
12 1 6 8&1 11 11&3
1 12 12
4 8 9 12
12 6 8 9 12
12 6 8 9 12
10
6 9 10 12
5 8
12 5 6 8 .11
8
12 3 3 6 9
13569
5 10 11 12
2 5 12 12&1 12 12&3
1 11&3 12 12&3
venenosus
12
9 12 12 12
9 11 12 12
9 12 12
12
-------
APPENDIX 16.2. (continued)
SPECIES
CONTROL
4-13 4-26 6-2 6-26 7-19 9-4
4-13 4-26
LOW
6-2 6-26 7-19 9-4
MEDIUM HIGH
4-13 4-26 6-2 6-26 7-19 9-4 4-13 4-26 6-2 6-26 7-19 9-4
HALF SHRUBS AND
SHRUBS
Artemisia aana
A . dracunou IMS
A . frigida
A . tridentata
Xanthooephalum
sarothrae
1
1
1
1
2
2
3
3
3
3
3
3
3
3
4
5
5
5
10
10
10
10
1
1
3
1
1
3
2
3 3 4 10
3
3 3 5 10
3 3 5 10
9
1
1
1
1
3
2
3
3
3
3
3
3
3
3
4
4
4
9
8
9
8
1
1
1
3
1 3
3 3
1
3
3
3
3
5
5
5
4
8
9
9
9
00
-------
APPENDIX 16.3.
PHENOLOGICAL PROFILE FOR ZAPS II, 197?1/
SPECIES 4-13 4-26
GRAMINOIDS
Agropyron
smithii I 3
A . spioatum
Aristida
longiseta
Bouteloua
graailis 1
Bromus
japonious
B. teatorum
Carex fili folia
Koeleria oristata 2 4
Muhlenbergia
ouspidata
Poa pratensis 3 3
P. sandbergii 3 3
Schedonnardus
paniaulatus
Sporobolus
oryptandrus
Stipa oomata I 3
5. viridula 1 3
FORBS
Aahillea
millefolium I 3
Allium textile
Androsaae
ooaidentalis 11
Antennaria sp.
Arniaa sororia 3
Artemisia
ludovioiana
Aster faleatus
Astragalus orassioarpus
A . drumnondii
A. purshii
Bahia
oppositifolia
Besseya
wyomingensis 8
Cerastium arvense i
5-26 6-26
3 7
3
9
10
6 9
6
6 10
10-11
4 10-11
5 8-9
8 12
9 12
4
8 12
5
12
8
3 8
10 12
7-26
9
10
11
11
11
11
11
7
11
12
12
12
12
12
12
5
12
11
12
9-5 4-13 4-26
10 1 3
11
12 1 3
12
12 3 4
11-12 3 3
12 3 4
12
12
12 1 3
12 1 3
12
12
12
12 3
12
12
12
5-26
3
3
5
6
6
6
4
5
8
10
8
10
8
6-26
4&7
9
11
10
10
10-11
6
3
10-11
8-9
12
12
4
8
12
7-28
9
11
11
12
11
11
11
12
12
11
12
12
12
11
12
12
9-5
10
11
12
12
12
11&3
12
12
12
12
12
12
12
8
12
12
4-13 4-26 5-26
133
12 1 3
12 1 3
135
11
346
336
3 3-4 6
3
134
135
8
10
8
2-3 8
5
3
8 10
8
6-26
some
8
6
8
9
11
12
9
10
10
11
10
8-9
12
12
12
4-5
9
12
7-28
9
11
10
11
12
11
8
11
11
4
12
12
11
12
12
12
5
12
12
11
12
12
9-5
10&3
11
11
12
12
12
11&3
12
12
3
12
12
12
12
7
9
12
12
12
12
12
4-13 4-26 5-26 6-26 7-28
1 2 3 4&7 10
8 11
13 10
1 3 5 9 10
11 12
12 12
3 3-4 7 10 11
10 11
337 11
8
1
3 11 12
1 3 4 10 12
1 3 5 8 11
8 12 12
10 12 12
8 12
3
3 8 11
8 11 12 12
9-5
10-11
&3
12
11
12
12
12
3
3
12
12
12
3
12
12
12
12
12
12
-•L/Codes are given on p. 110.
-------
APPENDIX 16.3. (continued)
SPECIES
CONTROL
4-13 4-26 5-26 6-26 7-26 9-5
LOW MEDIUM HIGH
4-13 4-26 5-26 6-26 7-28 9-5 4-13 4-26 5-26 6-26 7-28 9-5 4-13 4-26 5-26 6-26 7-28 9-5
FORBS (continued)
Camelina 9
mioroaarpa
Chenopodiwn
album
Chorispora
tenella 89 11 12
Crepis sp.
Deseurainia sp. 9
Erigeron
divergens 9 9-10 12
Gaura ooooinea
Grindelia
squ.arrosa 559
Hedeoma
hispida 12 12
Laatuoa
serriola 12
Lepidium
densiflomm 2 3 6-9 11 12 12
LeuGoorinum
montanum
Lithospermun rudevale 3 4
Lomatium sp. 4 8 9 12 12 12
L. orientale
Mammilaria
missouriensis 6 12 12
Mertensia
oblongifolia
Opuntia fragilis 12 1 5 12 12 12
0. polyaoantha
Orthooavpus
luteus
Penstemon nitidus 8 12 12
Phlox hoodii 4 8 8 12 12 12
Plant ago
patagonioa 8 12 12
P. spinulosa 12 12
Polygonum
viviparum
Psoralea
argophylla
P. esaulenta 9
Ranunculus
glaberrimus
3 7 8 10 57
11
5
10
13 9 8-12 12 2 99
8
5 6 10 56
10 9
10 11 12 12 10 11 12
11 12 12
48 12 12 3 8 11 12 12
36 12 12
7
12 3 5 12 12 12 58 12
12 2 3 9 11
8 12 12 12
38 12 12 12 8-9 9 12 12
11 12 12
11
9 11
5 12
34 12 12 12
11
12
9 1
10
12
12
12
4
12
12 12
12
12
12
12
12
11
9 10 11
9 10 12
3 569
12
5
10 11 12 12
8 10 12 12
15 12 12
1 5 8 12 12
12 12
12
-------
APPENDIX 16.3. (continued)
SPECIES
CONTROL
4-13 4-26 5-26 6-26 7-26 9-5
LOW
4-13 4-26 5-26 6-26 7-28 9-5
MEDIUM HIGH
4-13 4-26 5-26 6-26 7-28 9-5 4-13 4-26 5-26 6-26 7-28 9-5
FORBS (continued)
Ratibida
oolumnifera
Solidago
missouriensis
Sphaeraloea
ooooinea
Taraxacum
offieinale 1
Tragopogon
dubius 1
Vioia
americana
Viola nuttallii
Zygadenus
venenosus
HALF- SHRUBS AND
SHRUBS
Artemisia oana
A . frigida 1
A. tridentata 1
Atriplex nuttallii
Ceratoides lanata 1
4-5
5 11
3 4
3 8
7
3 3
3 3
4
3 6
10
12
8&
12&3
12
12
3
3
8
11
12
12&3
12
12
5
5
9
9
12
12
12
12
12
8
9
10
10
10 11 11
9 12 12
1 5 11 12&3 12 12
135 11&3 12&3 12
10 12 12
3 3
133358
3 358
4
1 11
135
8
11
8
3
2 3
133
12 2 5
9
9
12
11
10
12
12
3
3
3
8
10
7
12
12
12&3
12
12
12
5
5
5
11
11
9
12
12 .1
12&3
12
12
12
8 1
8 1
8 1
12
11 12
3
2
3
3
3
2
3
4
5
8
8
3
3
5
6
9
12&3
10
12
12
3
3
3
6
8
9
12
12&3
12
12
5
5
5
9
11
12
12&3
12
12
12
7
8
6
10
11
XanthoaephaIwn
sarothrae
-------
•SECTION 17
EFFECTS OF LOW-LEVEL S02 ON
TWO NATIVE LICHEN SPECIES
S. Eversman
ABSTRACT
The objective of this portion of the lichen
project has been to determine dose-response curves
for lichens subjected to S0?. Usnea hirta (L.) Wigg.
and Paimel'ia chlovoehToa Tuck, samples showed a sta-
tistically significant increase in percentage of plas-
molyzed algal cells when exposed to medium and high
levels of SO- on the ZAPS sites, and a significant
decrease in respiration rates at high levels of S0~.
Responses of the lichens to S0~ at low and medium
SO dosages were generally more erratic in 1977 than
in 1975 and 1976. Sulfation rates were greater at
50 cm above ground than at 10 cm or 100 cm in plots
B, C, and D. The lichen samples at 50 cm exhibited
more marked effects from SO,., than the lichen samples
collected from 10 cm and 100 cm.
INTRODUCTION
Summary of 1975-1976 Activities on the ZAPS Sites
The primary objective of this portion of the lichen project has been to
determine anatomical and physiological effects of low-level S09 on two native
lichen species, Usnea h-ivta (L.) Wigg. and PaTmelia chloTOchvoa Tuck. A
secondary objective has been to attempt comparison of the sensitivity of
lichens with that of associated vascular plants, particularly grasses.
I transplanted samples of the two lichen species onto fenceposts in
ZAPS Site I in 1975, and in ZAPS Site I and II in 1976. The samples were
collected monthly and returned to the laboratory for determination of res-
piration rate and percentage of plasmolyzed algal cells. Simultaneous
collections of the grasses Agvopyron smithii and Koeler-ia cristata in June,
1975, and June, July, and August, 1976 were made and the respiration rates
642
-------
of the leaves determined.
Significant differences in respiration rates of Agropyron smUhii samples
from plots A and D occur in 1 of 4 readings from ZAPS I, and 1 of 3 readings
from ZAPS II, but there is no obvious relationship to length of S02 treatment
(Appendix .17.1). In 5 of 7 respiration rate determinations of KoeLeria
cvistata samples, specimens from plots C and D have a higher (not significant)
respiration rate than do samples from plot A, the control. I feel that an
effect of S02 may be present, but if so, it is subtle.
In 1975 and 1976, the respiration rates of U. hirta samples, all col-
lected from about 50 cm above the ground, decreased very significantly
(p < .01) within 31 days of S02 treatment in test plots C and D, ZAPS I and
II. The respiration rates of those samples remained significantly lower than
those of control samples throughout the test periods (Appendix 17.2). The
respiration rates of U. hivta samples from plot B decreased, but were not
significantly lower than those of control samples until after at least 72
days of treatment (1976, ZAPS I). The rate did not remain statistically
lower consistently throughout the test period on plot B, ZAPS II, 1976.
Direct visual microscopic observations of U. h-ivta (i.e., counting
plasmolyzed algal cells) appeared to be a sensitive method of detecting
adverse S02 effects and gave reliable results (Appendix 17.3). A very
significant (P <.01) increase in number of plasmolyzed bleached algal cells
appeared within 31 days in U. Ivivta samples from plots B, C, and D, and
remained significantly higher than the controls throughout the test periods.
More than 90% of the algal cells were plasmolyzed in the U. Trip-to, samples
from plots C and D within 30 days of exposure; samples from plots C and D
were nearly identical in percentage of plasmolyzed cells. During 156 days
of SOz treatment in 1976, the percentages of bleached, plasmolyzed algal
cells from U. hivta samples from ZAPS I and II, plots B, remained signifi-
cantly higher than those of samples from plot A and lower than those of
samples from plots C and D.
PaYmel-ia chloTochroa which was transplanted to the base of fenceposts
on the sulfation treatment plots in 1975 appeared to be much less sensitive
to SOa than Usnea hivta. The respiration rates of samples collected in
1975 did not vary significantly during 110 days of S02 treatments (Appendix
17.4), and the plasmolysis rates increased significantly only on plots C
and D after 60 days of S02 exposure (Appendix 17.5).
More than species differences, the vertical position of the samples on
the fenceposts in the plots may have been responsible for the different
responses of U. hirta and P. chloroohvoa. Elevating P. chloroo'kroa, by
tying thalli on empty ponderosa pine branches which were then wired onto the
posts adjacent the U. hirta, gave the results tabulated in Appendix 17.4.
Elevated samples from Plot D had respiration rates significantly less
(P <.01 level) than those of control samples at 23 and 60 days. By 60 days,
elevated P. chlorochroa samples from B and C also had significantly lower
respiration rates than control samples, and the algal cell plasmolysis in-
creased significantly (Appendix 17.5).
643
-------
The results led to experiments designed to investigate vertical differ-
ences in SO- on the ZAPS I test plots, and to attempt to more closely corre-
late SO dosage with lichen responses.
1977 Activities on ZAPS Sites
The S09 monitoring system on the ZAPS plots had samplers 35 cm above
ground level. The lichen samples that showed the most obvious, and sta-
tistically significant, responses to S02 were about 50 cm above ground.
P. ohloTOchToa samples on the ground were not exhibiting SO^ damage as
convincingly as anticipated. It appeared from the lichen information from
1975 and 1976 that either less SO was reaching lichens on the ground or
that lichens on the ground were less susceptible to SO-. Sulfation plates,
U. hivta samples, and P. ohlovoohToa samples were placed adjacent each other
at different heights to obtain more precise dose-response data in 1977.
METHODS AND MATERIALS
I obtained sulfation plates from the Air Quality Bureau, Montana
Department of Health, Helena. Their methods of preparing and analyzing
these plates are presented in Appendix 17.6.
The locations of fenceposts on each ZAPS I and II test plot are shown
in Figure 17.1. Sulfation plates were wired on poles 1, 3, and 4, at 100,
50, and 10 cm above the ground (9 plates/plot). The plates faced north or
northeast in each case because of the ridges on the fence posts. The
dates of exposure of each set of plates were: 1) June 22-July 6, 2) July 6-
July 19, 3) July 19-August 3, 4) August 3-August 17. Ponderosa pine
branches containing U. In-ivta or P. chlorochroa samples were wired adjacent
the sulfation plates. U. hivta from ZAPS I was collected with each change
of sulfation plates (every two weeks). U. hirta from ZAPS II and P.
ohloTOohpoa were collected monthly. Collection dates from 1977 (also 1975
and 1976) are in Appendix 17.7.
Respiration rate was measured in a Gilson respirometer for 250 mg of
sample material for 1 hour at 20°C.
To determine percentage of plasmolyzed algal cells, I scraped pieces
of several thalli into 3 separate water drops on a microscope slide, then
counted 100 algal cells in each drop, recording the number of plasmolyzed
algal cells.
Changes in chlorophyll absorption were determined by making two or three
3-ml extractions with boiling methanol from 300 mg lichen samples, then
adding methanol to make 10 ml. Absorbance was read at 665 nm on a
Beckman DU Spectrophotometer.
RESULTS AND DISCUSSION
Individual sulfation plate results appear in Table 17.1. The results
from the Montana Department of Health Laboratory were reported as
644
-------
Ui
73m
00
01
3
5
"x
A
3
HHH
x
4 +
D
B
5
X
4
1 X
3X
D
D
Figure 17,1. Locations of fenceposts on ZAPS I and II sites. + = ZAPS I fenceposts;
x = ZAPS II fenceposts.
-------
TABLE 17.1
SULFATION, PPHM SO BY INDIVIDUAL LOCATION, 1977 (24 JUNE
17 AUGUST)
Sample Identification Code:
A,
1,
a,
1,
B, C, D =
2, 3
b, c
2, 3, 4 =
Sample
Identification
Alal
A3al
A4al
Ala 2
A3a2
A4a2
Ala3
A3a3
A4a3
Ala4
A3a4
A4a4
Blal
B3al
B4al
Bla2
B3a2
B4a2
Bla3
B3a3
B4a3
Bla4
B3a4
B4a4
Clal
C3al
C4al
Cla2
C3a2
C4a2
ZAP I plot
fence post
height : a
collection
S02
pphm
0.315
0.175
0,210
0.105
0.000
0.105
0.700
0.700
0.150
0.525
0.140
0.105
1.365
1.330
0.875
1.925
1.680
1.155
2.520
1.960
1.785
2.135
1.785
1.750
2.100
3.640
2.980
3.200
2.400
= 100 cm, b = 50 cm
date: 1 = 7-3-77,
4 = 8-17-77
Sample
Identification
Albl
A3bl
A4bl
Alb2
A3b2
A4b2
Alb3
A3b3
A4b3
Alb4
A3b4
A4b4
Blbl
B3bl
B4bl
Blb2
E3b2
B4b2
Blb3
B3b3
B4b3
Blb4
B3b4
B4b4
Clbl
C3bl
C4bl
Clb2
C3b2
C4b2
, c - 10
2 « 7-19-
S02
pphm
0.280
0.035
0.105
0,000
0.000
0.000
0.420
0.490
0.525
0.058
0.140
0,350
1.540
2.100
0.450
2.065
2,065
1.400
3.010
2,800
1,400
1,575
1.750
1.225
1.720
1,960
3.96Q
3.610
4. 170
2.730
cm
-77, 3 = 8-3-77,
Sample
Identification
Alcl
A3cl
A4cl
Ale 2
A3c2
A4c2
Alc3
A3c3
A4c3
Ale4
A3c4
A4c4
Blcl
B3cl
B4cl
Blc2
B3c2
B4c2
Ble3
B3c3
B4e3
Blc4
B3c4
B4c4
Clel
C3cl
C4cl
Clc2
C3c2
C4c2
SOa
pphm
0.035
0.000
0.070
0.000
0.035
0,000
0.380
0.070
0.420
0.000
0.035
0,140
0.630
1,015
|||I1HH|^
0.805
0,735
mw**
1.190
1.155
0.980
1.225
1.085
1.050
2 . 065
0.805
0.805
1.680
1.610
1.400
646
-------
TABLE 17.1 (Cont.)
Sample S02
Identification pphm
Cla3
C3a3
C4a3
Cla4
C3a4
C4a4
Dial
D3al
D4al
Dla2
D3a2
D4a2
Dla3
D3a3
D4a3
Dla4
D3a4
D4a4
3.200
2.800
3.590
3.500
2.800
3.360
7.245
5.250
6.510
5.390
5.150
4.170
5.530
5.220
3.400
5.360
6.760
4.800
Sample S02 Sample S02
Identification pphm Identification pphm
Clb3
C3b3
C4b3
Clb4
C3b4
C4b4
Dlbl
D3bl
D4bl
Dlb2
D3b2
D4b2
Dlb3
D3b3
D4b3
Dlb4
D3b4
D4b4
4.400
2.500
3.290
3.300
3.500
3.850
10.325
14.210
5.635
6.650
12.950
5.640
7.210
13.370
3.610
10.610
17.780
4.450
Clc3
C3c3
C4c3
Clc4
C3c4
C4c4
Dlcl
D3cl
D4cl
Dlc2
D3c2
D4c2
Dlc3
D3c3
D4c3
Dlc4
D3c4
D4c4
2.275
1.960
1.295
1.110
1.860
1.190
7.00
3.920
5.530
2.170
3.190
4.130
2.170
3.750
3.640
3.540
647
-------
mg SOa/lOO cm2/day. I used a conversion factor of. 035 to convert those
units to ppm (Corning Laboratories), then multiplied by 100 for pphm.
Table 17.2 gives the means of S02 in pphm, by heights, 100, 50, and 10 cm,
for June 22-August 17, 1977, and results of one-way analysis of variance.
Only ZAPS I, plot A showed no significant differences between the three
heights surveyed.
On plots B, C, and D, the amounts of S02 received by the sulfation
plates at 10 cm above the ground were significantly less than the SOa
amounts received by the higher plates. In plots B, C, and D, the greatest
amounts of SO 2 occurred at the 50 cm height.
There were no significant differences in sulfation rate means (4
collections, each about 14 days of exposure) at the 50 cm heights between
plots A and B, and B and C; and at the 100 cm height on plots B and C, for
the 56 days of monitoring with the sulfation plates.
Some of the lichen observations reflect these results, U.
samples from plot D generally had significantly lower respiration rates
than samples from other plots (Figures 17*2^5, Table 17.3). However, the
respiration rates of U. kipta samples from plots B and C fluctuated con*
siderably, especially in relation to samples from plot A*
Determination of absorbance spectra of chlorophyll extracts of £/»
samples (Table 17.4) gave relative results similar to those of respiration
rate determination.
The results obtained from cell plasmolysis counts of t/, hivta are in
Table 17.5. Again, the results are less clear-cut than those obtained
previously, but are consistently significant between samples from plot A
and plots C and D. An expected significant difference between £/, hipta
samples from plots A and B did not appear in 56 days, finished sets of
plasmo lysis readings for U. hivta and P. ehloPoohpQa for 1977 are not yet
complete .
Fairly consistent significant differences in respiration rate of
elevated P. ohlOTOehpoa samples occurred between samples from plot A, and
from plots C and D (Figures 17.2-5, Table 17.6). Significant differences
did not occur between samples from plots A and B. Only samples from plot
D exhibited consistent significantly lower absorbance by chlorophyll
extracts after 84 days of treatment (Table 17.7).
Counts of plasmolyzed algal cells in P. ehloPoclwoa showed no
significant differences in samples from all plots after 27 days of S02
treatment (Table 17.8). After 56 days of exposure, iumples from plot D
have a significantly higher percentage of plasmolyzed algal cells than
samples from plot A. Samples from plots B and C are intermediate.
648
-------
TABLE 17.2. STATISTICAL COMPARISONS OF S02 RATES OBTAINED FROM SULFATION
PLATES ON POLES 1, 3, 4; ZAPS I, 1977
Plot
A
B
C
D
Height
cm
100
50
10
100
50
10
100
50
10
100
50
10
X *
pphm
0.27
0.17
0.09
1.69
1.78
0.99
2.96
3.25
1.60
5.40
9.37
3.90
CI
.95
0.15
0.13
0.08
0.29
0.44
0.14
0.32
0.55
0.32
0.68
2.86
1.04
ANOVA F
A100cmA50cmA10cm 2.37
B50B100B10 7'88
C50C100C10 22'60
D50D100D10 10'98
AIOOBIOOCIOODIOO 136'54
A50B50C50D50 36'05
AIOBIOCIODIO 50'10
Mean pphm S0? from 12 samples with ±.95 confidence interval, 24 June -
17 August 1977.
Results of one-way analysis of variance. Locations with significantly
different sulfation rates (P < .05) do not share the same underline.
649
-------
ex
O.
O
W
O
Ul
ID
V)
O
ow
1.0
0.5
O
UJ
o
o
CM
O
800
600
600
400
200
1 1 1 1
ZAPS I A
Sulfation, 1977
— -— 50 cm
— | 0 cm
Respiration Rate
Usneo hirta
— 100 em, 1977
__„_ 50 cm
10 cm
Parmgliq chlorqchrpq
100 cm., 1977
„___» 50 cm
• 10 cm
15 30 45 60 75 90 105
DAYS of S02 TREATMENT
120 135 150 165
Figure 17.2,
Sulfation rate (pphm S02) 22 June - 17
August, 1977j respiration rates of Usn&a
htota and Pamglia QhloTooh^oa^ 1976
and 1977j ZAPS I A.
650
-------
2.5
2.0
o. 1.5
Q.
CM
£ i.o
0.5
1200
1000
•= 800
Q
uj 600
CO
O ^OO
o
M
° 200
'o. 600
O
UJ
400
O
O 200
M
O
ZAPS I B
Sulfation, 1977
100 cm
50 cm
10 cm
Respiration Rate
Usnea hirta
100 cm, 1977
50 cm
10 cm
~ 1976
Parmelia chlorochroa
100 cm, 1977
50 cm
10 cm
Ground, 1976
15 30 45 6O 75 90 105 120
DAYS of SO2 TREATMENT
135 ISO 165
Figure 17,3. Sulfation rate (pphm S02) 22 June - 17 August,
19775 respiration rates of Usnea kirta and
Parmelia chlorocfooa, 1976 and 1977; ZAPS I B.
651
-------
4.0
3.5
3.0
2.5
2.0
E
"I
M
o
1.0
0.5
ZAPS I C
Sulfotion, 1977
100 cm
50 cm
——— 10 cm
^
800
geoo
2
to
Z400
O
M
0 200
Respiration Rate
Usnea hirta
100 cm, 1977
50 cm
10 cm
1976
'o.600
O
HI
2
en
400
8 200
M
O
Pormelio chlorochroo
100 cm, 1977
50 cm
10 cm
Ground, 1976
15 30 , 45 60 75 90 105 120
DAYS of S02 TREATMENT
135 ISO 165
Figure 17.4. Sulfation rate (pphm S02) 22 June - 17 August,
19775 respiration rates of Z/snea hirta and
Parmelia chloroohroa, 1976 and 1977; ZAPS I C,
652
-------
11.0
10.0
9.0
8.0
7.0
E
"Q- 6.0
Q.
CM
o
CO 5.0
4.0
3.0
..g?
CONSUMED
•& O)
0 0
o o
CM
0 200
a.
£.
\ £ f\n
o> 6OO
0
UJ
§ 400
W
z
o
0 200
CM
a.
f ZAPS 1 D
/ Sulfation, 1977
/ 100 cm
^ /
\ / 50 cm
\ / 10 cm
* /
. w
• \
I
- V— ./
\
\ ^
^ Respiration Rate
^T ^^^>_ Usnea hirta
\\\ N. 100 cm, 1977
\ \|^N N. .^* 50 cm
\ i«^ TT^ 10 cm
^ w^fc — «— gQ cm. 1976
V "v, ,A._
""•*•''
i i i i i i i i i i i
Parmelia chlorochroa
\f\f\ — i^-»-»
^^^^^^ luu cm,iyf f
50 cm
^^^ 10 cm
_\^><^ Ground, 1976
i i i i i i i i i i i
15 30 45 60 75 90 105 120 135 ISO 165
DAYS of S02 TREATMENT
Figure 17.5.
Sulfation rate (pphm SOa) 22 June - 17 August,
1977; respiration rates of Usnea hirta and
Parmelia chloroohroa* 1976 and J.977^ ZAPS I D,
653
-------
TABLE 17.3 RESPIRATION RATES OF USNEA HIRTA COLLECTED FROM ZAPS I AND ZAPS II, 1977
Collection Date,
Sample Location
100 cm
7-06-77 ZAPS I A
B
C
D
7-19-77 ZAPS I A
B
C
D
8-03-77 ZAPS I A
B
C
D
8-17-77 ZAPS I A
B
C
D
-9-14-77 ZAPS I A
B
C
D
Days
S02
14
27
42
56
84
*
? CI
704 49
607 48
696 56
704 89
887 146
636 97
775 45
623 51
786 12.1
724 73
753 67
602 123
788 111
666 64
736 46
481 96
791 183
1089 S18
715 36
530 117
ANOVAt F
ADCB 4 . 26
ACBD 9.46
ACBD 4.32
ACBD 17.32
—
BACD 3.78
Collection Date,
Sample Location
100 cm
no collection
7-19-77 ZAPS II A
B
C
D
no collection
8-17-77 ZAPS II A
1
C
D
9-14-77 ZAPS II A
B
C
D
Days
S02
27
56
84
*
5 CI
819 191
863 413
787 87
646 293
748 27
637 176
795 95
419 67
919 70
802 65
195 1154
315 703
ANOVAf F
BACD 2.16
CABD 39,09
ABDC 75.79
-------
TABLE 17.3 (Cont.)
Collection Date,
Sample Location
50 cm
7-06-77 ZAPS I A
B
C
D
7-19-77 ZAPS I A
B
C
D
8-03-77 ZAPS I A
B
C
D
8-17-77 ZAPS I A
B
C
D
9-14-77 ZAPS I A
B
C
D
Days
S02
14
27
42
56
84
X ci
602 58
698 91
686 103
312 217
704 43
790 50
649 148
191 90
757 93
788 84
544 184
202 135
738 71
855 122
537 116
148 155
684 38
1112 291
414 351
159 166
t F
ANOVA
BCAD 12.86
BACD 98 . 91
BACD 28,37
BACD 41.17
BACD 38.36
Collection Date,
Sample Location
50 cm
no collection
7-19-77 ZAPS II A
B
C
D
no collection
8-17-77 ZAPS II A
B
C
D
9-14-77 ZAPS II A
B
C
D
Days
S02
27
56
84
-T* ,
X CI
720 80
737 219
740 194
184 85
737 55
624 84
612 199
106 89
852 582
878 105
627 275
97 72
ANOVAt F
CBAD 56.20
ABCD 100.49
BACD 15 . 61
Oi
Ui
-------
TABLE 17.3 (Cont.)
Collection Date,
Sample Location
10 cm
7-06-77 ZAPS I A
B
C
D
7-19-77 ZAPS I A
B
C
D
8-03-77 ZAPS I A
B
C
D
8-17-77 ZAPS I A
B
C
D
9-14-77 ZAPS I A
B
C
D
Pays
S02
14
27
42
56
84
r*
% CI
693 109
663 37
680 105
461 152
782 441
694 66
729 130
363 251
832 31
729 50
668 71
255 165
870 67
805 82
734 113
215 136
756 1253
844 477
— —
136 47
ANOVAf £
ACBD 7 . 12
ACBD 9.06
ABCD 29.87
ABCD 71,99
BAD 22.88
Collection Date,
Sample Location
10 cm
no collection
7-19-77 ZAPS II A
B
C
D
no collection
8-17-77 ZAPS 11 A
B
C
D
9-14-77 ZAPS II A
B
C
D
Days
S02
27
56
84
_'*
X Cl
591 109
729 120
739 95
212 164
628 189
801 191
681 102
145 142
836 127
774 207
449 839
132 902
ANOVA F
CBAD 24.66
BCAD 60.12
ABCD 61.06
Ul
—
Respiration rates are expressed as yl oxygen consumed g-hr , means of 2-6 samples with ±.95 con-
fidence interval (CI).
tResults of one-way analysis of variance. Locations with significantly different respiration rates
(P < .05) do not share the same underline.
-------
TABLE 17.4. RELATIVE ABSORBANCE AT 665 ran LIGHT OF CHLOROPHYLL EXTRACTS FROM
USNEA HIRTA COLLECTED FROM ZAPS I AND THE TRANSPLANT SOURCE (EOC:
EAST OTTER CREEK), 1977
Collection date,
Sample Location
4-27-77 EOC
transplant source
ZAPS I
(overwintering)
7-19-77
100 cm
50 cm
10 cm
8-17-77
100 cm
50 cm
10 cm
6-23-77 ZAPS II
8-16-77 EOC
9-17-77 ZAPS II
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
A
C
D
A
B
D
A
D
A
A100
A50
A10
Days
S02
0
(1976)
27
27
27
56
56
(1976)
84
84
84
X
.225
.147
.039
.014
.014
.168
.217
.202
.183
.266
.174
.202
.038
.175
.217
.140
.236
.119
.049
.200
.209
.044
.331
.027
.163
.211
.188
.195
.130
CI
.95
.120
.090
.034
.013
.004
.116
.004
.017
.026
.267
.009
.017
.004
.202
.026
.034
.013
.191
.114
.1025
.140
.089
1.436
.076
ANOVAt F
ABCD 32.73
BCDA 0.71
ACBD 9.42
BAG 1.95
9.63
A 10 A100 B50 A50 C100 °100 D50 D10
.129
.086
.077
.065
.026
* Means of relative absorbance readings of 3 extracts with ± .95 confidence
interval.
t Results of one-way analysis of variance. Locations with significantly
different absorption means do not share the same underline.
Usnea hirta sample from 10 cm height, treatment plot A; etc.
657
-------
TABLE 17.5.
PERCENTAGE OF PLASMOLYSIS OF ALGAL CELLS OF USNEA_ HIPTA
COLLECTED FROM ZAPS I AND ZAPS II AND THE TRANSPLANT SOURCES
(EOC: EAST OTTER CREEK), 1977
Collection
Date
3-26-77
7-19-77
8-17-77
Sample
Location
EOC
ZAPS I A50
B50 •
C50
D50
ZAPS I A100
B100
B100
B50
BIO
C100
CIO
D10
C50
D50
Days
S02
0
27
56
_*
X
3.0
3.7
30.0
67.0
99.3
13.3
16.3
24.3
24.7
30.7
41.3
62.0
85.3
97.7
98.3
C1.95
6.5
1.3
24.5
2.6
3.01
9.9
12.5
19.9
19.9
27.3
54.7
5.0
14.9
7.5
7.5
ANOVA F
ABCD 211.49
A100 B100 B100 B50 B10 C100 C10 D10 C50 D50
88.75
* Means of counts of 3 samples with ± .95 confidence interval.
t
Results of one-way analysis of variance. Locations with significantly
different plasmolysis determinations do not share the same underline.
A50 = Usnea samples collected from 50 cm height, treatment plot A, etc.
658
-------
TABLE 17.6. STATISTICAL ANALYSIS OF RESPIRATION RATES OF PARHELIA
CHLOROCHROA COLLECTED FROM ZAPS I AND THE TRANSPLANT
SOURCE (KLUVER WEST), 1977
Collection Date
Sample Location
6-20-77
7-19-77
100 cm ZAPS
50 cm ZAPS
10 cm ZAPS
8-17-77
100 cm ZAPS
50 cm ZAPS
10 cm ZAPS
KLW
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
Days
S02
0
27
56
_*
X
460
390
368
585
321
408
424
240
114
461
359
475
119
403
419
407
163
439
430
167
100
297
412
335
165
CI
122
51
60
137
75
115
67
148
7
197
126
126
85
110
49
22
95
33
48
42
44
37
62
165
36
ANOVA1" F
-
CABD 17.82
BACD 30.32
CABD 13.70
BCAD 25.75
ABCD 103 . 01
BCAD 13 . 24
-1
means
* Respiration rates are expressed as yl oxygen consumed g-hr
of 2-6 samples with ±.95 confidence interval (Cl).
Results of one-way analysis of variance. Locations with significantly
different respiration rates (P < .05) do not share the same underline.
659
-------
TABLE 17.7 RELATIVE ABSORBANCE AT 655 run LIGHT OF CHLOROPHYLL EXTRACTS FROM
PARHELIA CHLOROCHROA COLLECTED FROM ZAPS I, 1977
Collection Date
Sample Location
8-17-77
100 cm
50 cm
10 cm
9-14-77
A
B
C
D
A
B
C
D
A
B
C
D
A
native
_*
X
.118
.091
.142
.007
.065
.084
.060
.031
.118
.116
.006
.034
.039
CI
.065
.004
.056
.039
.003
.017
.013
0
.065
.003
.017
.004
.025
t F
ANOVA
CABD 6.90
BACD 64 . 68
ABCD 29.32
* Means of relative absorbance readings of 3 extracts with ± .95 confidence
interval (CI).
Results of one-way analysis of variance. Locations with significantly
different (P < .05) absorbance means do not share the same underline.
660
-------
TABLE 17.8.
PERCENTAGE OF PLASMOLYSIS OF ALGAL CELLS OF PARHELIA CHLOROCHROA
COLLECTED FROM ZAPS I, 1977
Collection Date
Sample Location
7-19-77
8-17-77
A100
B50
BIO
C50
D10
D50
A100
A10
B50
C100
C50
D100
D10
Days
S02
27
56
_*
X
9.0
34.7
12.7
8.0
41.7
53.0
12.0
8.0
24.7
13.0
44.3
52.0
51.0
CI
12.5
33.1
19.9
21.5
109.4
19.8
5.0
5.0
49.7
12.5
29.8
42.3
69.6
ANOVA1" F
DBCA 2.79
4.80
D100 D10 C50 B50 C100 A100 A10
*Means of counts of 3 samples with ± .95 confidence interval (CI).
tResults of one-way analysis of variance. Locations with significantly
different plasmolysis determinations do not share the same underline.
= Parmel'ia samples collected from 100 cm height, plot A; etc.
As in 1975 and 1976, we collected samples of U. hii'ta and P.
from many field sites to compare with samples from the ZAPS A plots. Analy-
sis of variance of respiration rate data of U. hivta from 1977 have shown no
significant differences in respiration rate from collection date 1 (July 6)
to collection date 5 (September 14); these rates are not significantly
different from the rates of simultaneously collected samples from the trans-
plant source (East Otter Creek)and other ponderosa pine sites at any time.
Analyses of variance have also consistently indicated no differences in
P. cKlovoohPoa samples between ZAPS and field sites. Therefore, I have
used samples from ZAPS A plot as controls.
Analysis of variance of respiration rate of U. hirta samples collected
from zAPS I plot B from June through September, 1977 indicates a gradual
significant increase (P <, .01) on all heights from the first to the last
collection; the rise in rate is progessive by date. An interpretation of
this phenomenon appears below. The analysis of variance of samples from
plots C and D shows a significant decrease, compared with control samples,
661
-------
within 14 days, then no significant respiration rate decrease from July 3
to September 14. Damage by SO2 at the levels of plots C and D, as
measured by respiration rate and plasmolysls of algal cells, is acute and
immediate in U. hivta.
Some of the lichen samples in 1977 and the grass samples in 1976
from plots B, C, and D exhibited increases in respiration rates compared
with samples from plot A. This behavior was different from the patterns
established in 1975 and 1976. I have interpreted this phenomenon as an
effect of low-level S02 stress, previously described by Baddeley &t at,
(1971) and Puckett
-------
CONCLUSIONS
Usnea hirta seems to be slightly more sensitive to 862 than P. chlovo-
clfwoa. The respiration rates of U. hirta decrease more consistently
and the plasmolysis percentage increases more rapidly and to a greater
degree than those of P. ohloTochToa. U. hirta3 normally located on
tree trunks and branches, is more exposed to airborne 862 than P. ohloTO-
clwoa and may be more useful as an air quality indicator.
Direct microscopic observation of P. chlorochroa is the most reliable
method of determining S02 effects on this species. Not only can one
determine plasmolysis rate, but the behavior of the bacterial populations,
and the general thallus condition can also be observed.
REFERENCES
Baddeley, M. S., B. W. Ferry, and E. J. Finegan. 1971. The Effects of
Sulphur Dioxide on Lichen Respiration. Lichenologist, 5:283-291.
Malhotra, S.S. and D. Hocking, 1976, Biochemical and Cytological
Effects of Sulphur Dioxide on Plant Metabolism. New Phytologist,
76:227-237.
Puckett,K. J., E. Nieboer, W. P. Flora, and D. H. S. Richardson, 1973.
Sulphur Dioxide: Its Effects on Photosynthetic llfC Fixation in Lichens
and Suggested Mechanisms of Phototoxicity. New Phytologist, 72:
141-154,
Puckett, K. J., D, H. S. Richardson, W. P. Flora, and E. Nieboer, 1974.
Photosynthetic aitC Fixation by the Lichen Urribi,l'ieari,a nruhlenbeTgii
(Ach), Tuck, Following Short Exposure to Aqueous Sulphur Dioxide.
New Phytologist, 73:1183-1192.
663
-------
APPENDIX 17.1 RESPIRATION RATES OF GRASSES AGROPYRON SMITHII AND KOELERIA
CRISTATA COLLECTED FROM ZAPS I AND ZAPS II, 1975-76
Agropyron smithii
Collection Date,
Sample Location
6-26-75 ZAPS I
6-23-76 ZAPS I
ZAPS II
7-17-76 ZAPS I
ZAPS II
8-9-76 ZAPS I
•
ZAPS II
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
\
Days
S02
33
72 .
93
119
_*
X
936
761
858
805
646
736
520
610
579
699
551
349
355
231
197
212
335
328
366
249
145
177
239
197
312
107
394
530
CI
59
89
55
147
470
431
263
584
74
174
83
85
159
224
159
526
94
297
405
136
32
40
72
168
94
80
125
211
ANOVA1" F
ACDB 6 . 63
-i — —
ABCD 0,73
BACD 31.55
ABDC 2.19
CABD 0*65
CDSA 3.12
DCAB 20,63
•
664
-------
APPENDIX 17.1 ( Cont.)
Koeleria ei*istata
Collection Date,
Sample Location
6-26-75 ZAPS I
6-23-76 ZAPS I
ZAPS II
7-17-76 ZAPS I
ZAPS II
8-9-76 ZAPS I
ZAPS II
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
Days
SO
33
72
96
119
_*
X
554
637
732
635
702
706
893
1045
728
617
563
759
506
587
560
827
247
411
430
525
127
164
146
108
147
226
375
332
CI
279
149
196
386
126
255
260
104
6
334
298
284
9
324
178
282
22
187
79
256
87
48
72
78
63
112
103
115
ANOVA F
CBDA 0.67
DCBA 12.76
DABC 2 . 01
DBCA 6.92
DCBA 9-28
BCAD 2 . 08
DCBA 19.75
t
Respiration rates are expressed as yl oxygen consumed g-hr , means of 3
samples with ±.95 confidence interval (CI).
Results of one-way analysis of variance. Locations with significantly
different respiration rates (P < .05) do not share the same underline.
665
-------
APPENDIX 17.2 RESPIRATION RATES OF USNEA HIRTA COLLECTED FROM ZAPS I AND
ZAPS II, 1975-1976
Collection Date
Sample Location
5-13-75 Transplant
Source
6-25-75 ZAPS I
7-10-75 ZAPS I
9-11-75 ZAPS I
5-13-76 ZAPS I
6-23-76 ZAPS I
7-17-76 ZAPS I
8-9-76 ZAPS I
9-15-76 ZAPS I
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D.
A
B
C
D
Days
S02
0
33
47
110
31
72
96
119
156
X
719
817
746
472
54
I
686
599
336
66
709
499
355
4
711*
618
290
325
704
359
236
115
670
473
323
244
721
556
298
150
631
487
340
142
CI
37
45
12
353
56
96
93
220
95
137
159
170
16
116
175
192
247
176
194
206
166
256
97
97
229
' 45
209
182
72
52
107
t
ANOVA F
•
ABCD 35.82
ABCD 16.13
ABCD 22.38
ABDC 9.96
—
ABCD 34.62
ABCD 19.33
.
ABCD 58.14
ABCD 61.81
99 !
169 1
1
666
-------
APPENDIX 17.2 (Cont.)
Collection Date,
Sample Location
5-13-76 ZAPS II
6-23-76 ZAPS II
7-17-76 ZAPS II
8-9-76 ZAPS II
9-15-76 ZAPS II
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
Days
S02
31
72
96
119
156
_*
X
800
755
438
264
555
476
263
169
643
479
264
98
618
509
282
118
506
456
298
112
CI
154
92
278
114
85
191
119
95
95
214
120
52
125
163
211
39
151
90
211
116
ANOVA F
ABCD 23.61
ABCD 35.87
ABCD 59.24
ABCD 42.77
ABCD 26.45
t
Respiration rates are expressed as yl oxygen consumed g-hr 1, means of
3-5 samples with ±.95 confidence interval (CI).
Results of one-way analysis of variance. Locations with significantly
different respiration rates (P < .05) do not share the same underline.
667
-------
APPENDIX 17.3 PERCENTAGE OF PLAMOLYSIS OF ALGAL CELLS OF USNEA EIRTA
COLLECTED FROM ZAPS I AND ZAPS II, 1975-1976
Collection Date,
Sample Location
6-25-75 ZAPS I
7-10-75 ZAPS I
9-11-75 ZAPS I
5-13-76 ZAPS I
6-23-76 ZAPS I
9-15-76 ZAPS I
5-13-76 ZAPS II
6-23-76 ZAPS II
7-17-76 ZAPS II
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
Days
S02
53
47
110
31
72
156
31
72
96
_*
X
6.0
65.3
99.7
100.0
9.0
54.3
99.0
100.0
15.3
76.7
98.0
100.0
6.0
34.8
94.0
94.3
4.0
77.7
99.7
100.0
7.3
82.3
99.7
100.0
4.3
36.7
98.7
100.0
3.7
58.3
99.3
100.0
3.3
65.7
98.7
100.0
* Means of counts of 3 samples with ±.95
t Results of one-way analysis of variance
different plasmolysis determinations do
CI
9.9
85.1
1.3
0
6.5
48.6
2.6
0
7.7
40.0
8.6
0
2.6
39.1
21.5
22.4
5.2
3.9
1.3
0
3.9
32.3
1.3
0
6.5
95.5
3.9
0
1.3
51.2
3.0
0
3.9
43.9
3.9
0
ANOVAf F
ABCD 17 . 02
ABCD 60 . 15
ABCD 66.39
ABCD 29,36
ABCD
ABCD 58 . 18
confidence interval
. Locations with significantly
not share the same underline.
668
-------
APPENDIX 17.4 RESPIRATION RATES OF PARMELIA CHLOROCHEOA COLLECTED FROM
ZAPS I, 1975-1976
Collection Date,
Sample Location
5-1-75 Pasture
Field *
6-26-75 ZAPS I A
B
C
D
7-10-75 ZAPS I A
B
C
D
9-11-75 ZAPS I A
B
C
D
7-14-76 Kluver East *
8-9-76 ZAPS I A
ground B
C
D
8-9-76 ZAPS I A
elevated B
C
D
9-15-76 ZAPS I A
ground B
C
D
9-15-76 ZAPS I A
elevated B
C
D
Days
S02
0
0
33
47
110
0
23
23
60
60
_*
X
337
223
319
330
344
296
345
404
317
294
362
271
353
340
322
292
314
309
396
366
311
197
79
305
270
322
396
345
174
45
43
CI
110
48
55
45
26
42
62
50
42
29
86
25
64
34
65
120
62
65
60
65
82
134
37
109
82
95
32
22
117
25
85
ANOVAf F
BACD 1.99
BACD 5.35
" ~"
ACDB 3.56
DBCA 13.31
ABCD 39.80
DCAB 7.39
ABCD 69.29
* Respiration rates are expressed as yl oxygen consumed g-hr"1 , means of 3
samples with ±.95 confidence interval (CI) .
t Results of one-way analysis of variance. Locations with significantly
different respiration rates (P<.05) do not share the same underline.
$ Transplant sources.
669
-------
APPENDIX 17.5 PERCENTAGE OF PLASMOLYSIS OF ALGAL CELLS OF PABMELIA
CHLOPOCHROA COLLECTED FROM ZAPS I, 1975-1976
Collection Date,
Sample Location
6-26-75 ZAPS I
ground
9-11-75 ZAPS I
ground
9-15-76 ZAPS I
ground
ZAPS
elevated
A
B
C
D
A
B
C
D
A
B
C
D
A
B
C
D
Days
S02
33
110
60
60
_*
X
1.7
9.0
9.8
13.3
10.3
-
4.3
43.3
22.3
7.3
30.3
29.8
—
42.7
72.0
89.8
CI
1.7
9.9
6.7
26.1
18.9
-
10.0
85.5
6.2
7.7
21.9
13.9
_
76.5
63.6
14.6
ANOVA F
ABCD 2.04
DAC 3.17
ABCD 2.62
BCD 12.62
t
Means of counts of 3 samples with ±.95 confidence interval.
Results of one-way analysis of variance. Locations with significantly
different plasmolysis determinations do not share the same underline.
670
-------
APPENDIX 17,6. METHOD USED BY AIR QUALITY BUREAU LABORATORY, MONTANA
DEPARTMENT OF HEALTH, HELENA, FOR PREPARATION AND ANALYSIS
OF SULFATION PLATES
Sulfation Plates
AQ - P50 - 1 (Written 1975)
The sulfation plate for determining S0~ concentrations is made by
attaching a 4.8 centimeter diameter Gelman A fiberglass filter to a 4.8
centimeter diameter petri dish with three drops of acetone. The lead
dioxide solution to coat the petri dish is made in the following manner:
112 grams of lead dioxide is blended in a blender with 700 milliliters of
water, 0.7 grams of gum tragacanth, and 7 grams of fiberglass filter ground
on a Wiley mill to pass 20 mesh. Ten milliliters of this material is trans-
ferred into each petri dish. The coated dish is dried in an oven at low
temperature (60°C) and sealed with a lid.
To expose a sulfation plate, the lid is removed and the plate is placed
in a bracket that will secure the sulfation plate upside-down. The petri
dish serves as the shelter, shipping container, and lead dioxide support.
The sulfation plate is exposed for approximately 30 days.
After exposure, the lead dioxide is removed from the petri dish with
a little water. The insoluble lead sulfate is converted to soluble sodium
sulfate with the aid of 20 ml of sodium carbonate solution (50 grams/liter)
and heated in a water bath for - 30 minutes. The excess insoluble lead dioxide
is removed by filtration using a Whatman 42 filter. The solution is acidified
with hydrochloric acid to bring the pH of the filtrate between 2 and 3. The
acidified filtrate is diluted to 50 ml or any other convenient volume with
water. Take a portion of this solution (up to 25 ml) and dilute to 25 ml
with water. To this, 0.1 gram of sulfaver powder is added, mixed, and let
stand 20 minutes. The resulting turbidity is measured in a spectrophoto-
meter at 450 millimicrons.
The results are reported as mg SOa/lOO cm2/day.
2
Sulfation rate (mg S03/100 cm/day) =
A x 1<
3
B
- C
4.6 -f D.
A = yg SOit from standard curve x 10 3 to convert yg of SOi* to mg of
B = Fractioh of filtrate used to produce turbidity ( -rrr = -ypr if 5 ml of
filtrate used)
C = Blank
D = Exposure time in days
The 4.6 conversion factor is derived as follows:
671
-------
APPENDIX 17.6 (cont).
Inside diameter of sulfation plate « 4.8 cm
Radius = 2.4 cm
Area of plate - TTR2 = Tr(2.4)2 » 18,1 cm2
For a 100 cm2 would = 1?g =5.52
lo. 1
SO 3 80
n "SOT = "96 * °'833 (because you want ^rig S03)
Therefore, 5.52 x 0,833 - 4.6 (the conversion factor)
APPENDIX 17.7 LICHEN COLLECTION DATES AND DAYS OF S02 TREATMENT, 1975-77
Date Days
so2
1975 May 24 0
June 26 33
July 10 47
August 11 79
September 11 110
1976 April 12 0
May 13 31
June 23 72
July 17 96
August 9 H9
September 14 156
1977 June 22 Q
/
July 6 14
July 19 27
August 3 42
August 17 56
September 14 84
672
-------
SECTION 18
RESPONSES OE GROUND-DWELLING INSECTS TO SULFUR DIOXIDE
J. J. Bromenshenk
ABSTRACT
Population studies of ground-dwelling beetles and
other insects were conducted using pitfall trapping
at the EPA Zonal Air Pollution System (ZAPS). The
studies were initiated to examine responses to in situ
low level sulfur dioxide fumigation and to establish an
information base for evaluation of the long-term poten-
tial for resource depletion.
The most prevalent beetles, as indicated by pit-
fall captures, represented three families including
saprophagous, necrophagous, and predacious forms. In
more than 80 percent of the trappings, more beetles
were captured on the control plots than on any of the
treatment plots. However, the changes in abundance as
related to sulfur dioxide treatment level were most
pronounced and consistent for the Scarabaeid Canfhons
mostly laevis. Throughout most of the 1976 and 1977
trapping periods, the number of Canthon beetles captured
by pitfalls was significantly lower on all of the sulfur
dioxide treatment plots than on the control plots at
each of the two ZAPS sites.
The decomposer beetles appear to be more important
to the steady turnover of nutrients in grasslands than
heretofore suspected. Observations are discussed which
support this hypothesis as well as possible adverse
effects of low level sulfur dioxide fumigation on other
insects. Several lines of evidence are presented in
support of the use of terrestrial insects as indicators
of environmental quality.
673
-------
INTRODUCTION
The species diversity, biomass, and abundance of insects in cool-season
grasslands often surprises the initiate. More than 1,300 species of above~"
ground arthropods inhabit Montana rangelands; of these, approximately 1,200
are insects (Rees and Hewitt, 1977). The very abundance of insects is an
indication of ecologic and economic importance.
Entomological studies have made a considerable contribution to the
development of ecological concepts because insects are abundant in species
and numbers, have short life spans, are small in size, easy to study, and
important to ecosystems (Price, 1975).
In previous reports I have shown that specific insect systems appear to
be sensitive and useful indicators or estimators of environmental quality
(Bromenshenk, 1976, 1978). In these reports, I reviewed more than 200
references indicating that: (1) Air pollution has significant effects on
entomological systems; (2) pollution impacts on insect systems may occur at
all levels of organization from the biochemical to the ecosystem; (3) pollu-
tion may act directly on insects, as in the case of zootoxins, or indirectly,
as in the case of phytotoxins that alter food and habitat resources; (4) the
effects of anthropogenic contaminants on insect-plant interfaces may demon-
strate reciprocity, acting on the insect through the plant or on the plant
through the insect, and (5) pollution-caused changes in insect systems may
induce modifications in fundamental ecosystem components and processes.
Frietag et al. (1973), Kulman (1974), Thiele (1977), Cornaby (1977) and
others reported that terrestrial arthropods, particularly predatory and
saprophagous species, demonstrated considerable potential as indicators of
environmental quality. Several of these studies dealt specifically with
ground-dwelling beetles, although the emphasis for the most part was on the
Carabids.
Pursuing the objective to identify indicators which would best serve as
progenitors of pollution-induced effects on critical rangeland resources
(including processes and functions of the ecosystem), I continued monitoring
the population responses of ground-dwelling beetles to in situ low level S02
fumigation at the ZAPS sites during the 1977 growing season. Data collected
in 1975 by entomologists from the Natural Resources Ecology Laboratory,
Colorado State University (Dodd et at. , 1978), indicated that the total
numbers and biomass of beetles (the Coleoptera) were substantially reduced
on the high treatment plot at ZAPS I during the first year of fumigation.
Since the Colorado investigators decided to concentrate their efforts on
soil arthropods, I decided (Bromenshenk, 1978) to evaluate population
responses of beetles to S02, and at the ZAPS in 1976, I observed significant
decreases in the relative abundance of several species of saprophagous
beetles with respect to increasing S02 fumigation treatment levels.
Saprophagous and necrophagous beetles breakdown and fragment organic
material such as carrion, feces, and vegetative matter. They consume large
quantities of these materials and distribute them through carrying and
burying activities (Milne and Milne, 1976; Ritcher, 1958). Thus, they
directly affect the allocation and partitioning of resources in soil/litter
subsystems (Cornaby, 1975, 1977; Rainio, 1966).
674
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I believe that saprophagous beetles have been underestimated as regards
their contribution to nutrient cycling and food chains in grassland ecosysems,
and in this report I shall present data in support of this hypothesis.
Obviously, beetles are not the "sole agents" of nutrient cycling. Other
soil fauna, such as mites, collembolans, and millepedes, are abundant and act
as comminutors of organic matter, while microbes act more directly as decom-
posers and as chemical deteriorators (Crossley, 1970; Dickinson and Pugh,
1974; Whitkamp, 1971). However, exclusion or depression of the abundance of
litter arthropods results in lowered decomposition rates (Strojan, 1978;
Whitkamp and Crossley, 1966; Payne, 1965; Edwards and Heath, 1963; Kurcheva,
1960).
In addition, litter arthropods may aid in the dispersal of soil micro-
flora and microfauna, compete with less desirable insects such as hornflies,
fleshflies, and intestinal parasites for food resources, carry mites which
attack the eggs of flies and parasites, and serve as food for other insects
and higher animals (MacQueen, 1975; McKinney and Morley, 1975; Price, 1975;
Durie, 1975; Lodha, 1974; Bryan, 1973; Ritcher, 1958). Other benefits
more directly related to their burying and comminuting activities include
regulation of rates of release of nutrients, less waste of fouled herbage by
grazers, better infiltration by rainfall and greater moisture holding capacity
of soil, less surface runoff and loss of nutrients due to runoff, leaching,
and volatilization, greater surface storage of nutrients, and better returns
of phosphorus and nitrogen to the soil (McKinney and Morley, 1975; Gillard,
1967).
Although I concentrated on the effects of the S02 fumigation on ground-
dwelling beetles, I also examined the influence of this gas on other insects,
including pollinators and seed-infesting insects. Data concerning this
aspect was not processed completely at the time of this report (May, 1978).
I shall only briefly describe the progress here and shall include this infor-
mation in the next interim report.
MATERIALS AND METHODS
In order to monitor the population responses of ground-dwelling beetles
to the S02 fumigation treatments, I continued to use pitfall traps arranged
in grid arrays across the treatment plots. Each trap consisted of a cone-
shaped disposable coffee cup set into a 14-ounce disposable cold-drink cup
(Olsen, Elliot, and Associates, 1976; Bromenshenk, 1978) and sunk into the
soil so that the mouth was level with the soil surface. An inch of water in
the bottom of each trap drowned captured beetles and prevented predacious
species from devouring each other and other captured insects. All traps were
baited with five grams of meat, which appeared to increase the trapping yield
of Scarabaeids and Silphids and to resolve an overtrapping problem introduced
when traps containing a few beetles acted as attractants.
In 1976, 24 traps were placed in a grid pattern within each treatment
plot. Each trap was located 152 cm from a S0£ delivery pipe, measured
diagonally from each pipe to the ground. In 1977, I (Bromenshenk, 1978)
added a trap line around the perimeter of each plot, forming a 7 x 7 Latin
675
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Square grid pattern containing 25 traps within and 24 traps outside of the
gas delivery lines (Figure 18.1). The perimeter lines improved our ability
to monitor beetle movements. The pitfall traps were opened for intervals of
ten days during the first half of each month from May through September during
1976 and during May, late June, and September of 1977.
CONTROL
LOW
MEDIUM
HIGH
Figure 18.1. Pitfall trapping grid pattern at each ZAPS site. Boxes
represent perimeters of gas delivery systems; dots
represent traps.
Southwood (1975) reviewed the use of pitfall traps. He suggested that
they are useful for studies of relative abundance (in similar vegetation),
movements, spatial patterns of distribution, seasonal incidence, species
diversity, and diurnal activity patterns (if the traps are examined
frequently). However, this type of trap is difficult to use for estimates of
absolute population density since animals may be attracted to the traps from
a distance, and different species may vary in susceptibility to capture.
Also, comparisons of captures in dissimilar vegetation types such as forest
to grassland may be inaccurate because the vegetation may impede movements.
The pitfall method continues to be used because, as Kulman (1974) pointed
out, other sampling methods such as mark-recapture, total population per unit
area, and direct quadrant counts also create problems and are more difficult
to use. Southwood (1975) concluded that the method is useful for many
studies, if used with reasonable caution and if the captures are not consid-
ered to represent absolute population numbers.
Thomas and Sleeper (1977) demonstrated that the method is more suited to
some species than others; as might be expected, the vagility of the population
676
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appeared to be an important factor. They listed sources of variation associ-
ated with the method, indicated methods of overcoming these problems, and
reviewed mathematical models of stochastic processes. Roff (1973) disparaged
the use of trapping schemes which cannot provide coefficients of variance of
less than 10 percent. However, as Thomas and Sleeper (1977) explained, it is
unrealistic to expect an estimate this precise for invertebrate populations;
they advised acceptance of coefficients of variation as great as 100 percent.
All my statistical evaluations were performed on a Hewlett-Packard 65
calculator or a Dec-20 computer and utilized standard statistical programs,
including mean, standard deviation, standard error, chi-square (goodness of
fit) and linear regressions. Statistical tests and mathematical models
followed the ecological methods designed for use with insect populations by
Southwood (1975) and the biometrics of Sokal and Rohlf (1969) and Conover (1971)
In December, 1977, EPA released data on the S0£ fumigation treatment
levels and meteorology in the ZAPS sites area. I have incorporated mathe-
matical evaluations testing correlations of beetle captures to S02 treatment
and weather effects in this report and anticipate a more complete analysis
for the next interim report. Also, for this report I have used only non-
transformed raw data in my computations, but I intend to test for Poisson,
geometric, binomial, and non-parametric distributions. If warranted, I will
incorporate data transformations and appropriate statistical tests. There is
a pronounced tendency towards clumping in the raw data which indicates that
the populations are highly contagious. Southwood (1975) and Thomas and
Sleeper (1977) demonstrated that mathematical models of distribution such as
coefficients of dispersion provide important population information, and I
intend to examine these processes. Currently, this trapping data is being
incorporated into a Dec-20 computer program so that these more complex and
lengthy statistical tests can be utilized.
The following assumptions are inherent in this study:
(1) Habitat preference is not assumed to be a major factor influencing
results. Terrain and habitat features are similar on all plots at
both ZAPS, although similarity does not imply identical conditions.
For example, in terms of canopy cover and species diversity, the
ZAPS II site is less diverse than the ZAPS I, based on 1975 and 1976
data. However, in 1976, overall vegetation similarity within sites
was 0.78 on ZAPS I and 0.71 on ZAPS II (Taylor and Leininger, 1978).
Other data collected at the ZAPS sites by each of the investigative
teams of the CFPP project provides an extensive data base so that
many confounding influences can be identified and separated.
(2) The chances that a beetle may occur on or traverse a plot or be
trapped within any plot are assumed to be equal for all plots.
The null hypothesis is that relative abundance and species diversity of
ground-dwelling beetles on any ZAPS plot is independent of S0£ treatment.
The corollary is that if a beetle species is sensitive to S02, responses to
gas emitted at different concentrations across the series of treatment plots
should be reflected in corresponding population changes.
677
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Functionally, the grid trapping system should monitor resident and
transient adult beetles, providing data concerning movements (dispersal,
recruitment, emigration, immigration, drift) spatial patterns of distribution,
seasonal incidence, species diversity, and relative abundance. These may
reflect mortality factors, which were not differentiated from behavioral
responses in this study.
Several terms and names used throughout this paper are rather specialized
and require a brief explanation:
(1) Perimeter trap—any trap outside of the area of a treatment plot
enclosed by the SC>2 gas delivery lines; in other words, any trap in
the outermost rows and columns of the 7x7 Latin Square grid.
(2) Interior trap—any trap within the area of a treatment plot enclosed
by the S02 gas delivery lines; any trap in the central (5 x 5)
portion of the 7x7 Latin Square grid.
(3) Canthon—beetles, mostly of the species C. laevis (Drury), which are
members of the subfamily Coprinae and which feed upon decaying
substances such as carrion, vegetative matter, and dung (Ritcher,
1958). Since some species of Canthon can be segregated only by
characteristics of the male genetalia, a process which would neces-
sitate extremely time-consuming dissections, species have not been
differentiated in the counts. However, samples which I did dissect
indicated that 95 percent of the Canthon beetles were of the species
laevis.
(4) Saprophagous—feeding on decaying organic matter.
(5) Coprophagous—feeding on dung.
(6) Necrophagous—feeding on carrion or dead bodies.
(7) Nidification—nest building or provision for the progeny by adults
such as the dung balls rolled by Canthon.
(8) Scarabaeidae—the family of lamellicorn beetles composed mainly of
stout-bodied, saprophagous or phytophagous beetles.
(9) Silphidae—the family of clavicorn beetles comprised of the burying
beetles, carrion beetles, and related forms.
RESULTS
Pitfall trapping results for the 1976 season were published previously
(Bromenshenk, 1978; Bromenshenk and Gordon, 1978) and will only be summarized
here. Trapping results for the 1977 season have been completed for all three
trapping periods. In May, 1976, I observed significant decreases on the treat-
ment plots in the numbers of five species of beetles representing three
families: Scarabaeidae, Silphidae, and Carabidae. The decreases were nega-
tively correlated with fumigation levels. Depressions in abundance were most
678
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pronounced and consistent through the season for Canfhon laevis. In general,
the population levels of the other species declined and remained low across
the plots (including control) throughout the summer and autumn. Captures of
Canfhon sp. in August, 1977, displayed the same pattern as early season
captures (Figure 18.2).
£ 900 n
-------
2000
o
* 1000,
UJ
Ul
CD
ZAPS I, 1977
SO- TREATMENTS
2
°
ct
t—
o
.1000
LU
LU
CD
ZAPS II, 1977
SO- TREATMENTS
MAY
JULY
SEPT.
MAY
JULY
SEPT.
Figure 18.3. Seasonal summary of captures of Canthon sp. beetles by
traps both interior and exterior to the plots.
550.
400.
^ 200
Ul
ZAPS I, 1977
S02 TREATMENTS
X^X V\
^^ 'X \
^-» *X» ^iSJy N \
• ^ ^k ^
^^^ 1 ^
—. JSs
MAY
JULY
SEPT.
550
b)
O
CL.
400
o
(TV
200
CO
<*>
ZAPS II, 1977
S02 TREATMENTS
MAY
JULY
SEPT.
Figure 18.4. Seasonal summary of captures of Canthon sp. beetles by
traps on the interior of the plots.
680
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interior traps. Unlike Canthon, not all of these other groups of beetles
reached maximum population size by mid-summer. Scarabaeids of the species
Onthophagus hecate Panz. (small, saprophagous and necrophagous beetles) were
captured most frequently in May as were weevils of the family Curculionidae.
Skin, feather, and dung-feeding beetles of the genus Trox, subfamily Troginae,
were most common in September. Carrion feeders of the genus NiepophoTUS
(Silphidae) were caught at about the same rate throughout the growing season.
Carabids of the predacious species Pasimaohus elongatus LeConte were most
abundant during May and June-July, while predatory tiger beetles of the genus
Cicindela (Cicindelidae) often were caught in May and September, but none were
captured in June-July. Miscellaneous species of beetles which were captured
infrequently were grouped in a category designated "other beetles." They were
most numerous in May, common in June-July, and greatly reduced in number by
September.
Because of the in-line placement of the ZAPS treatment plots, the B and C
plots bordered two 61-meter intervening buffer zones, while the A and D plots
bordered only one buffer zone. The north and south portion of the plots inter-
faced with the surrounding rangeland. More beetles should have inhabited the
surrounding grasslands, which extended for kilometers in all directions, than
inhabited the 61 x 35 m buffer zones. If all species of beetles had very
limited home ranges, this would not be important. But some of the decomposer
beetles have extensive home ranges. For example, Milne and Milne (1976)
described experiments by F. Petruska in which carrion beetles that were
carried as far as four kilometers from a carcass returned within 24 hours.
But, Shubeck (1968) concluded that NioTophoTUS sp. seemed to utilize random
wandering to carrion and were not very efficient in locating carrion even
from distances as close as five meters, although he postulated that there may
be species and even population differences in patterns of foraging behavior.
My own field observations indicated that although both Canfhon and Nicrophorus
beetles often were seen moving about on the ground, they are strong fliers.
I have seen them traverse the length of a treatment plot quickly, sometimes
traveling back and forth across one or two plots several times before disap-
pearing from my visual range.
If the relative abundance and species diversity of ground-dwelling
beetles were not affected by S0£ treatment, then one would expect an equal
probability of capture on each of the plots for those beetles that have a
limited home range, that is, areas smaller than the buffer zones. However,
for beetles that can and do move distances greater than the width of the
buffer zones during the ten-day trapping interval, an equal probability of
capture was hypothesized for plots bordered on three sides by rangeland
(A and D plots) and for plots bordered on two sides by rangeland (B and C
plots) with a greater rate of capture on the former compared to the latter.
This phenomenon is termed edge effect. As an alternative scenario, it was
hypothesized that capture rates would not be equal on each of the plots
because of SC>2 treatment effects and that the plots receiving the least
amount of S02 would display the highest capture success, since the 1976
trapping data demonstrated inverse correlations between beetles and SC>2
levels.
681
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These hypotheses were tested by pairing the trapping data for all generic
groups captured on at least some of the plots during all three trapping
periods. Then the non-parametric signs test was applied. This is based on
the hypothesis that the number of positive and negative signs among differences
(omitting all differences of zero) occurred in equal frequencies.
For limited beetle movement and home range, the following hypotheses
were tested :
(1) HQ : P(A < B) _> 1/2
El : P(A < B) < 1/2
(2) H0 : P(B < C) _> 1/2
H : P(B < C) < 1/2
(3) HQ : P(C < D) _> 1/2
H : P(C < D) < 1/2
But if beetle movements and home range were large, edge effects would be
important and only homologous pairs could be tested, i.e., AD or BC. The
hypotheses applicable in this instance were:
(1) H0 : P(A < D) >_ 1/2
El : P(A < D) < 1/2
(2) H0 : P(B < C) _> 1/2
Hx : P(B < C) < 1/2
The results of the sign tests are presented in Table 18.1.
Based on the sign test analysis for perimeter traps, I accepted the
hypothesis of an edge effect; i.e., A > B (P = .09) and D > C (P = .03). For
the interior traps, I rejected the hypotheses of equal captures. The data
indicated that capture success followed the trend A > B > C = D, the differ-
ences significant at the P < .001 level for A > B, at the P < . 10 level for
B > C, but not significant for C > D. This supports the hypothesis of a
treatment effect which demonstrated, after an initial effect, a pattern of
diminishing effects with increasing 862 • Other statistical tests will be
applied, but these were not complete at the time of this draft.
682
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TABLE 18.1 SIGN TEST OF BEETLE CAPTURES FOR THE FIVE MOST PREVALENT
GENERA AND FOR ALL TRAPPING PERIODS, ZAPS I AND II, 1977
Incidence of Property Exact Probability
Interior Traps Perimeter Traps Number Percentage (one-tailed test)
A > B 24
A < B 4
B > C 18
B < C 9
C > D 13
C < D 10
A > D 23
A < D 4
A > B 18
A < B 10
B > C 15
B < C 13
C > D 8
C < D 19
A > D 13
A < D 16
85.7
14.3
66.7
33.3
56.5
43.5
85.0
15.0
64.3
35.7
46.4
53.6
70.4
29.6
44.8
55.2
.9999
.0001
.939
.061
.661
.339
.998
.0002
.908
.092
.425
.575
.974
.026
.355
.645
Sulfation plate studies (Section 10) indicated that in the buffer zones,
sulfur fumigation levels at 35 cm above the ground averaged 53 percent of the
nearest sample points inside the treatment plots. The perimeter beetle traps
and the buffer zone sulfation plates were located at approximately the same
distance from the edge of the plots. Decreased sulfur fumigation at the peri-
meters of the plots, as compared to the interiors, could account for the
difference in the capture rate between perimeter traps and interior traps.
In my data analyses of beetle capture relative to S02 treatment level, I
used the EPA sulfation plate data (Section 10). This provided the largest
amount of information on horizontal and vertical spatial distributions.
Unless otherwise indicated, only data from the 35 cm height was used, the
lowest height for which information was available for all trapping periods.
It was assumed that ground level concentrations would have the greatest
effects on the responses of ground-dwelling beetles, although this may not be
true; long range movements appeared to be mainly by flying.
683
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ZAPS I
ZAPS II
N
Figure 18.5. Wind roses for 24-hour periods during the pitfall trapping
of beetles at the ZAPS; length of line indicates frequency,
684
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ZAPS I
ZAPS II
30%
SEPTEMBER
2.SI/' 2.23 X7.79
Figure 18.6.
Wind roses for night periods during the pitfall trapping
of beetles at the ZAPS; numbers indicate wind speed and
length of line indicates frequency.
685
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Wind plays an important role in the orientation of movements by many
insects (Fraenkel and Gunn, 1961). Observations of captures by the pitfall
traps indicated that many of the ground-dwelling beetles being studied were
most active at night, i.e., nocturnal. Therefore, wind patterns for the 24-
hour and night periods were examined and are summarized by wind roses in
Figures 18.5 and 18.6. Winds blew frequently from the SC^ treatment plots
towards the controls, especially at night, at both ZAPS. This supports data
(Section 10) which indicated that S02 reached the control plots. Comparison
of Figures 18.5 and 18.6 (wind roses) with Figure 18.7 (perimeter captures of
Canfhon sp.) indicates that there is a tendency for the greatest capture rates
to occur on the side of the plots upwind of the more prevalent air flows.
These trends have not been mathematically analyzed.
ZAPS I SEASONAL TOTALS
1977
636
528 401
404
A
400
B
386
388
435 897
261
514
798
717
383
493
578
100 METERS
ZAPS II SEASONAL TOTALS
1977
650
759 950
488
725
905
288
B
273
321
101
488
859
319
274
231
195
100 METERS
PERIMETER CAPTURES OF CANTBON SP.
Figure 18.7. Seasonal totals of perimeter captures of Canfhon sp.
at ZAPS.
Statistical analyses of wind and sulfur interactions with beetle captures
were in progress at the time of this report. Linear regression analysis of
the seasonal capture of Canthon sp. against the reciprocal of the sulfation
concentrations was performed. The reciprocal transformation produced a signi-
ficant r2 value (F = 23.847, df = 1,6). The captures of Carrfhon sp. were
inversely correlated to sulfate concentration (Figure 18.8).
686
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3
a.
Q.
to
1
I
UJ
cc
ID
a.
<
o
UJ
UJ
270^
170
70
Y=87029I + II54I.5/X
r2 = 0.765
F = 23.847, df=|,6
50
250 450 650
|jg SULFATE
850
1000
Figure 18.8. Linear regression of seasonal capture of Canthon sp.
against the reciprocal of sulfation concentrations.
I continued to maintain hives of honeybees at ZAPS II in 1978. One hive
was located north of each of the plots 35 meters from the last delivery pipe.
It was hoped that a line could be extended to the hives to insure S02 fumi-
gation, but this was not done. The hives were not located on the plots because
of concern expressed by other investigators about the possibility of being
stung by bees while working on the plots. As in previous years, bees
continued to abscond from hives above the higher treatment plots. This may be
coincidental, but Hillmann (1972) had a similar problem when he fumigated bees
with S02 at levels up to 5 ppm.
Seed germination of Koeleria oristata (Section 14) revealed that thrips
frequently infest seeds but that the percent infestation changes across the
treatment plots. At ZAPS I in 1977, thrips were found in 5, 3, 3, and 1
percent of 100 seeds examined from A to D, respectively.
Another S02 effect on insect feeding was a preference for unfumigated
versus fumigated grass by grasshoppers (Section 19).
Thus, insects at the ZAPS during 1977 demonstrated significant and
varied responses to the S02 treatments.
687
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DISCUSSION
Based on the trends of preliminary statistical analyses, population
abundance relative to S0£ treatments clearly demonstrated that chronic low
levels of S02 affected Canthon beetle populations. The data indicated that
more of these beetles were captured within the control plots than on any of
the fumigated plots. Either beetles moved farther into the interior
of the control plots or there was a larger resident population in the interior
of these plots. It appeared that S02 often caused a significant reduction in
abundance even at the lowest (B) fumigation levels and that increased fumi-
gation (C and D plots) demonstrated only a slightly greater reduction in
abundance. This suggests that whatever the threshold for this response might
be, it occurs at or below the lowest fumigation concentration.
Trapping success of Canthon greatly increased by mid-summer and decreased
in the autumn. Both seasonal changes of abundance and treatment related
changes in abundance were more or less parallel at ZAPS I and ZAPS II,
although the responses were more consistent and displayed- a steeper gradient
of decrease on ZAPS II. Data on sulfur uptake by vegetation (Section 14)
showed a steeper gradient of sulfur uptake on ZAPS II, while capture-mark-
release studies of deer mice (Peromyseus man-ioulatus) carried out by Chilgren
(1978 and Section 20) yielded results which were very similar to those of my
beetle trapping. Based on trapping data from 1977 and 1976, the number of
mice that he captured on all fumigated plots decreased relative to the control
plots on both ZAPS. The effect became most pronounced at mid-season, continued
through the autumn, and was more clearly demonstrated on ZAPS II than on ZAPS I.
Chilgren pointed out that the two most important findings of his work
were that: (1) Sampling must be carried out over extended periods of time
before effects become interpretable and (2) similar results occurred when the
same experiment was replicated in space (ZAPS I and II) and time (1976, 1977,
and within season). I concur with his interpretation of his results, and
these statements also apply to my data.
Canthon laevis may be more sensitive or susceptible to S02 pollution
than other grassland, ground-dwelling beetles, but other beetles, including
saprophagic and predatory forms, have been shown to respond in a similar
manner to sulfur compounds in the ambient air (Bromenshenk, 1978; Dodd et at. ,
1978; Frietag et al., 1973). The sensitivity of other species of insects and
their usefulness in studies of sulfur oxide pollution have not been deter-
mined. Preliminary data have shown a trend towards decreased seed infestation
of prairie Junegrass by thrips (Section 14) and significant preferences by a
grasshopper, Aulooara ell-iotti (Section 19), for non-fumigated western wheat-
grass over that from the highest fumigation plot. Hillmann (1972) reported
increases of aphids and decreases of predatory and parasitic wasps (Hymen-
optera) near a 615 MW coal-fired power plant in Pennsylvania.
Most previous studies of the impacts of pollutants on terrestrial insects
systems have consisted of the formulation of species lists and other types of
unfocused but extensive information or the collection of data which is by
nature so variable as to be unusable in evaluating chronic effects. It is the
functioning of components and processes of ecosystems which is of interest to
688
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ecologists, policy makers, and managers, and this functioning needs to be
understood in order to provide the information necessary for environmental
problem solving. Because of this, I believe that studies of pollution
impacts on terrestrial insects should concentrate on critical (key) or sensi-
tive insect systems rather than on broad spectrum sampling. In addition, the
ability to delineate effects is dependent to a great degree on the utilization
of appropriate methods of investigation. For example, D-Vac sampling of
aboveground arthropods provided some leads towards identifying sensitive
species, but the variability of the data made the investigators hesitant to
attribute any observed changes to treatment effects (Dodd et al. , 1978).
D-Vac techniques are poorly suited to examinations of many ground-dwelling
beetles which tend to hide under objects during the day and to be most active
at night, while pitfalls are effective both day and night.
At this point, some difficult questions have been raised. Given the
large number of insect species present in grassland ecosystems, do other
important insects (other than the ones identified) respond to SC>2? Has the
inability to identify other susceptible insects been due to inadequate
approaches, lack of concentration on the specific group, or insufficient time
for a response to become evident? In view of the bioaccumulation of fluorides
and arsenic near power plants and smelters and the toxic effects of these
substances on bees (Bromenshenk, 1978; Section 6), what are the effects of
other pollutants such as cadmium, mercury, polycyclic hydrocarbons, fluorides,
and arsenics, alone or in synergism with sulfur oxides, on insect systems?
The ZAPS studies have provided a means of finding sensitive, preliminary
indicators. Now there is a need to know what changes in fundamental ecosystem
components and processes should be anticipated as a consequence of responses
by insect systems.
The depressed abundance of Canfhon beetles on the fumigation plots may
reflect some type of disorientation or avoidance movement, mortality of a
resident population, or some combination of mortality and behavioral factors.
The mechanisms involved will be the focus of my 1978 investigations.
A hypothesis has been advanced that if the reduced abundances observed
during this study were a result of alterations in movements or distributional
habitat choices, there would be no changes in the abundance of these beetle
populations in S02~polluted areas. The rationale for this hypothesis is that
the beetles in this study were avoiding a very localized SC^ fumigation but
would not have the opportunity to do so if large areas were involved. Also,
if extensive geographical areas were inundated by SC^, the question arises as
to whether insects could adapt (or develop resistant populations, if mortal-
ity is a factor) to SO?? If this occurred, there may be no long-term effects
on the grassland ecosystem once the system essentially adjusts itself to the
prevailing conditions.
On the other hand, avoidance or distributional habitat choices may convey
protection from toxic effects by SC^, while disorientation could impair the
efficiency and success of finding of food resources. Movements could proceed
from areas of higher concentration of SC^ to lower. Thus, even if beetles
were not capable of "escaping" S0£ stress by an extended emigration, this
might occur over several generations or over long periods of time by a series
689
-------
of shorter incremental movements. Small rodent studies by Chilgren (Section
20) indicated that mice may avoid S02- Because carrion is an important food
resource to many of these beetles, they might follow small rodent movements.
If resistance were to become a factor in the response of these beetles
to S02 stress, one would expect that S0£ dosages would have to be high enough
to kill a segment of the population. Stress avoidance could negate this
possibility. Also, Brown (1968) pointed out that there is no "single
doctrinaeire answer" to resistance phenomena.
Frietag &t al. (1973) found depressed abundance of several species of
ground-dwelling beetles in the plume path of a Kraft mill, and Hillmann (1972)
observed reductions of predatory Hymenoptera downwind from a coal-fired power
plant complex 14 years after the plant began operations. These indicate that
reductions in insect population abundance have occurred and may persist for
several years, although different mechanisms of action may be involved.
Regardless of the mechanisms involved, a continued depression of the abundance
of these beetles could have long-term effects on grassland ecosystems.
The trophic relations of coprophagous and necrophagous beetles have been
described (Milne and Milne, 1976; Ritcher, 1958; Price, 1975), and personnel
of the Environmental Studies Laboratory are obtaining data on the relationship
of these beetles to mice and voles, both as food to these rodents and as
consumers of them. This should provide data concerning food web effects.
I am particularly interested in the role that these insects play in soil
nutrient cycles. Necrophagous and coprophagous beetles appear to occur in
greater numbers in eastern Montana grasslands than in western Montana forests,
based on comparisons of our data with that of the USDA Region I Forest Service
which is trapping beetles in pitfalls in timber stands (personal communication,
D. Fellin, USDA Entomologist). If this finding is typical, studies of soil
nutrient cycles in forest systems would not consider these beetles to be of
much importance due to low population numbers. However, in the grasslands,
as many as 1,000 beetles of a single species have been captured on a 1%-acre
plot over a ten-day period. In addition, 20 percent of the mice caught in
snap traps near Colstrip by our personnel during the 1977 growing season were
attacked, partially devoured, and often buried by carrion beetles during the
same night that they were caught. F. Munshower (MSU) and J. Chilgren (EPA)
(personal communications) reported that mice, voles, and ground squirrels in
their traps were badly mutilated and sometimes the smaller animals completely
stripped of flesh by beetles within as short a period as 24 hours. These
were animals that had been inadvertently captured or overlooked so that they
had not been more quickly removed from the traps. Milne and Milne (1976)
reported that adult burying beetles transport and bury bodies of birds and
small animals as large as 100 gm, or the size of a rat or large robin, and
that they may inter larger animals, birds, or snakes. They credit these
beetles with the removal of the majority of dead carcasses of small animals
and birds. Thus, it appears that decomposer beetles (saprophages and necro-
phages) are important to the rapid turnover of the organic materials in
grassland ecosystems.
690
-------
CONCLUSIONS
As in any field study, innumerable variables could not be controlled,
although the employment of support data such as meteorology, vegetation maps,
S02 fumigation, and uptake (vegetation, sulfation plates) in the data analyses
should g-eatly improve the ability to partition sources of variance.
However, based on the capture of 17,159 Canfhon sp. beetles at ZAPS I
and II in 1977, during these trapping periods (May thru September), the data
strongly indicate that chronic low levels of S0£ affect highly mobile popula-
tions of these beetles. I am currently examining sulfur accumulation in the
body tissues of beetles, but these analyses were not available for incorpo-
ration into this report. Thus, at present, I have no physiological data on
S02~fumigated beetles and no data concerning life table factors such as age
structure, natality, mortality, life expectancy, and reproductive processes.
Analysis of temporal and spatial capture patterns of Canthon sp. indi-
cated that:
(1) Total captures, with the exception of the May trapping period on
ZAPS I, were significantly greater (x2 analyses) on the controls
than for any of the fumigated plots.
(2) Population size, as reflected by total capture, was greatest in
mid-summer and smallest by mid-September.
(3) The effects of S02 fumigation demonstrated a noticeable time-lag as
reflected by beetle capture; -I.e., early season trapping for the
most part showed no or little S02 effect on the population abundance.
(4) Temporal and treatment-related changes were more or less parallel
on ZAPS I and II, although decreased relative abundance as compared
to increased S02 treatment on ZAPS II tended to be more consistent
and pronounced.
(5) Perimeter capture exceeded interior captures in all cases, indi-
cating recruitment or movement onto the plots. Assuming that peri-
meter traps should be the first to be occupied by immigrants and
nearby residents and should contain a larger portion of the capture,
one would expect that the interior traps would fill at equal rates
with residents and those beetles which successfully eluded "the
filter effect" of the perimeter traps, providing S02 does not
affect the populations.
(6) Capture rates within plots demonstrated higher levels of difference
in beetle abundance across the treatment plots than total captures,
especially for the controls. Either there is a larger resident
population or movements are less restricted at the control plots.
^
(7) Although demonstrating a trend towards an inverse correlation of
numbers compared to fumigation level, changes in abundance within
the fumigated plots were variable.
691
-------
(8) The data indicate that S02, even at the lowest fumigation level,
affected free ranging populations of Canthon.
(9) The results for 1977 at the ZAPS are consistent with the results
obtained in 1976.
Thus, although I do not know how a beetle such as Canthon responds to
S02, the results of these tests indicate that S02 significantly affects the
relative abundance of beetles in grasslands, causing depressed abundance.
Generic differences in sensitivity of ground-dwelling beetles to S02^air-
pollution may occur, although results from 1976 (Bromenshenk, 1978) indicate
that several different species and families respond to S02.
Saprophagous, including coprophagous and necrophagous, beetles as well
as predatory beetles contribute to the vigor of grassland ecosystems. Damage
to decomposers or nutrient pools may constitute a potential source of insta-
bility to the entire ecosystem (Harte and Levy, 1975; Dudzik et al. , 1975).
Cornaby (1977) presented three resource problems of international importance
to which saprophagous animals may provide a key to the solution and an under-
standing of ecosystem processes. He concluded that saprophagous animals do
or can contribute to: (1) Assessments of environmental quality (biological
indicators); (2) acceleration of the regeneration of spent or reclaimed land,
and (3) deactivation of pathological materials.
The long-term consequences of reduced abundance of saprophagous and
predatory beetles are unclear, but a potential of important changes in
ecosystem functioning seems likely.
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Plant Emissions Upon Insects, Report of Progress. In: The Bioenviron-
mental Impact of a Coal-Fired Power Plant, Second Interim Report,
Colstrip, Montana, June, 1975, R.A. Lewis, N.R. Glass, and A.S. Lefohn,
eds. EPA-600/3-76-013, U.S. Environmental Protection Agency, Corvallis,
Oregon, pp. 112-129 and 286-312.
. 1978. Investigations of the Impact of Coal-Fired Power
Plant Emissions Upon Insects. I. Entomological Studies in the Vicinity
of Colstrip, Montana. II. Entomological Studies at the Zonal Air
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Power Plant, Third Interim Report, Colstrip, Montana, December, 1977,
E.M. Preston and R.A. Lewis, eds. EPA-600/3-78-021, U.S. Environmental
Protection Agency, Corvallis, Oregon, pp. 146-312 and 473-507.
, and C.C. Gordon. 1978. Terrestrial Insects Sense Air
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American Chemical Society, Washington, D.C. pp. 66-70.
Brown, A.W.A. 1968. Insecticide Resistance Comes of Age. Bull. Entomol.
Soc. Am., 14:3-9.
692
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Bryan, R.P. 1973. The Effects of Dung Beetle Activity on the Numbers of
Gastro-Intestinal Helminth Larvae Recovered from Pasture Samples.
Aust. J. Agric. Res., 24(1):161-168.
Chilgren, J.D. 1978. Responses of Prairie Deer Mice to a Field S02 Gradient.
In: Proceedings of the Fourth Joint Conference on Sensing of Environ-
mental Pollutants, November 6-11, 1977, New Orleans, Louisiana. American
Chemical Society, Washington, D.C. pp. 61-65.
Conover, W.J. 1971. Practical Nonparametric Statistics. John Wiley & Sons,
Inc., New York. 462 pp.
Cornaby, B.W. 1975. Soil Arthropods as Indicators of Environmental Quality.
In: Organisms and Biological Communities as Indicators of Environmental
Quality—A Symposium, C.C. King and L.E. Elfner, eds. The Ohio State
University, Columbus, Ohio. pp. 23-25.
. 1977. Saprophagous Organisms and Problems in Applied Resource
Partitioning. In: The Role of Arthropods in Forest Ecosystems, W.V.
Mattson, ed. Springer-Verlag, New York. pp. 96-101.
Crossley, D.A., Jr. 1970. Roles of Microflora and Fauna in Soil Systems.
In: Pesticides in the Soil: Ecology, Degradation, and Movement.
International Symposium on Pesticides in the Soil. Michigan State
University, East Lansing, Michigan, pp. 30-35.
Dickinson, C.H., and G.J.F. Pugh, eds. 1974. Biology of Plant Litter
Decomposition, Volumes 1 and 2. Academic Press, New York. 146 pp. and
175 pp.
Dodd, J.L., W.K. Laurenroth, R.K. Heitschmidt, and J.W. Leetham. 1978.
First-Year Effects of Controlled Sulfur Dioxide Fumigation on a Mixed
Grass Prairie Ecosystem. In: The Bioenvironmental Impact of a Coal-
Fired Power Plant, Third Interim Report, Colstrip, Montana, December,
1977, E.M. Preston and R.A. Lewis, eds. EPA-600/3-78-021. U.S. Environ-
mental Protection Agency, Corvallis, Oregon, pp. 345-375.
Dudzik, M., J. Harte, D. Levy, and J. Sandusky. 1975. Stability Indicators
for Nutrient Cycles in Ecosystems. Lawrence Berkeley Laboratory Report
LBL-3264. University of California, Berkeley, California. 59 pp.
Durie, P. 1975. Some Possible Effects of Dung Beetle Activity on the
Infestations of Pastures by Intestinal Worm Larvae of Cattle. J. Appl.
Ecol., 12(3):827-831.
Edwards, C.A., and G.W. Heath. 1963. The Role of Soil Animals in Breakdown
of Leaf Material. In: Soil Organisms, J. Doeksen and J. van der Drift,
eds. North-Holland Publishing Company, Amsterdam, pp. 76-84.
Fraenkel, G., and D.L. Gunn. 1961. The Orientation of Animals, Kineses,
Taxes, and Compass Reactions. Dover Publications, Inc., New York.
376 pp.
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Frietag, K., L. Hastings, W.R. Mercer, and A. Smith. 1973. Ground Beetle
Populations Near a Kraft Mill. Can. Entomol., 105(2):299-310.
Gillard, P. 1967. Coprophagous Beetles in Pasture Ecosystems. J. Aust.
Inst. Agric. Sci., 33(l):30-34.
Harte, J., and D. Levy. 1975. On the Vulnerability of Ecosystems Disturbed
by Man. In: Unifying Concepts in Ecology, W.H. van Dobben and R.H. Lowe-
McConnell, eds. Junk Publications, The Hague, Netherlands. pp. 208-223.
Hillmann, R.C. 1972. Biological Effects of Air Pollution on Insects,
Emphasizing the Reactions of the Honey Bee (Apis melUfera L.) to Sulfur
Dioxide. Ph.D. Thesis, The Pennsylvania State University, University
Park, Pennsylvania. 159 pp.
Kulman, H.M. 1974. Comparative Ecology of North American Carabidae with
Special Reference to Biological Control. Entomophaga Mem. H.S., 7:61-70.
Kurcheva, G.F. 1960. Role of Invertebrates in the Decomposition of Oak Leaf
Litter. Povcvovedenie, 4:16-23.
Lodha, B.C. 1974. Decomposition of Digested Litter. In: Biology of Plant
Litter Decomposition, Volume 1, C.H. Dickinson and G.F. Pugh, eds.
Academic Press, New York. pp. 213-238.
MacQueen, A. 1975. Dung as an Insect Food Source: Dung Beetles as
Competitors of Other Coprophagous Fauna and as Targets for Predators.
J. Appl. Ecol., 12(3):821-827.
McKinney, G.T., and F.H.W. Morley. 1975. The Agronomic Role of Introduced
Dung Beetles in Grazing Systems. J. Appl. Ecol., 12(3):831-837.
Milne, L.J., and M. Milne. 1976. The Social Behavior of Burying Beetles.
Sci. Am., 235(2):84-89.
Olson, Elliott, and Associates. 1976. Effects of Spruce Budworm Control on
Pollinating Insects. USDA Forest Service, Region 1, Missoula, Montana.
56 pp.
Payne, J.A. 1965. A Summer Carrion Study of the Baby Pig Sus sorofa
Linnaeus. Ecology, 46(5):592-602.
Price, P.W. 1975. Insect Ecology. Wiley-Interscience, New York. 514 pp.
Rainio, M. 1966. Abundance and Phenology of Some Coprophagus Beetles in
Different Kinds of Dung. Ann. Zool. Fennici., 3(l):88-98.
Rees, N.E., and G.B. Hewitt. 1977. Effects of Specific Cultural Practices
on Immediate Rangeland Arthropod Populations. Bulletin 695. Montana
Agricultural Experiment Station, Montana State University, Bozeman,
Montana. Ill pp.
694
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Ritcher, P.O. 1958. Biology of Scarabaeidae. Ann. Rev. Entomol., 3:311-335.
Roft, D.A. 1973. On the Accuracy of Some Mark-Recapture Estimators.
Oecologia (Berl.), 12(1):15-34.
Shubeck, P.P. 1968. Orientation of Carrion Beetles to Carrion: Random or
Non-random? J. N.Y. Ent. Soc., 76(4):253-265.
Sokal, R.R., and F.J. Rohlf. 1969. Biometry. The Principles and Practice of
Statistics in Biological Research. W.H. Freeman & Company, San Francisco,
California. 776 pp.
Southwood, T.R.E. 1975. Ecological Methods with Particular Reference to the
Study of Insect Populations. Chapman and Hall Ltd., London. 391 pp.
Strojan, C.L. 1978. The Impact of Zinc Smelter Emissions on Forest Litter
Arthropods. Oikois (in press).
Taylor, J.E., and W.C. Leininger. 1978. Monitoring Plant Community Changes
Due to S02 Exposure. In: The Bioenvironmental Impact of a Coal-Fired
Power Plant, Third Interim Report, Colstrip, Montana, December, 1977,
E.M. Preston and R.A. Lewis, eds. EPA-600/3-78-021. U.S. Environmental
Protection Agency, Corvallis, Oregon, pp. 376-384.
Thiele, H.-U. 1977. Carabid Beetles in Their Environments. A Study in the
Habitat Selection by Adaptations in Physiology and Behavior. Springer-
Verlag, Berlin, Fed. Rep. Germany. 369 pp.
Thomas, D.B., Jr., and E.L. Sleeper. 1977. The Use of Pit-Fall Traps for
Estimating the Abundance of Arthropods, with Special Reference to the
Tenebrionidae (Coleoptera). Ann. Entomol. Soc. Am., 70(2):242-248.
Whitkamp, M. 1971. Soils as Components of Ecosystems. Ann. Rev. Ecol. Sys.,
2:85-110.
, and D.A. Crossley, Jr. 1966. The Role of Arthropods and Microflora
in Breakdown of White Oak Litter. Pedobiologia, 6:293-303.
695
-------
APPENDIX TABLE 18.1. 7X7 LATIN SQUARE GRID CAPTURE OF CANTHON SP. AT EPA ZAPS, 1977
ZAPS I
ZAPS I
PLOT A (Control)
May 9-19, 1977
PLOT C (Medium)
May 9-19, 1977
Total Traps
01
n
#3
04
05
06
07
PLOT
(49)
I - 854
X - 17
S - 21
I
178
5
35
108
161
117
250
B (Low)
.5
.8
Rows
X
25.4
0.7
5.0
15.4
23.0
16.7
35.7
Total Traps
(49)
Perimeter Traps
(24)
I - 606
X - 25
S - 24
S
21.8
1.3
4.0
24.7
22.5
26.6
21.6
Perimeter
(24)
.3
.9
01
02
03
#4
05
06
07
Traps
Interior Traps
(25)
E - 248
X~ - 9.9
S - 15.3
Columns
E X
220 31.4
129 18.4
125 17.9
79 11.3
134 19.1
66 9.4
101 14.4
May 9-19,
Interior Traps
(25)
S
34.5
23.9
19.5
14.5
20.7
11.8
22.6
1977
01
02
03
04
05
06
07
Total Traps
(49)
E = 642
X - 13.1
S = 16.5
E
134
55
68
66
39
147
133
Rows
X
19.1
7.9
9.7
9.4
5.6
21.0
19.0
Perimeter Traps
(24)
E - 468
X •= 19.5
S = 19.5
S
18.4
15.2
12.5
14.1
5.32
12.1
28.1
01
02
03
04
05
06
07
Interior Traps
(25)
E
X
. s
E
165
55
142
90
56
49
85
«= 174
= 7.0
9.9
Columns
X
23.6
7.9
20.3
12.9
8.0
7.0
12.1
S
17.8
14.2
20.0
22.5
8.4
13.3
14.0
Total
Traps
(49)
01
02
03
04
05
06
07
Plot
E -
x -
s -
E
106
22
81
10
97
109
206
631
12.9
16.8
Rows
X
15.1
3.1
11.6
1.4
13.9
15.6
29.4
Perimeter Traps
Interior Traps
(24)
r -
JC -
s -
s
17.1
3.9
13.0
1.5
14.3
17.8
25.6
467
19.5
20.6
01
02
03
04
05
06
07
E
X
S
E
89
95
90
5
38
145
169
D (High)
Total Traps
Perimeter Traps
(49)
01
02
03
04
05
06
07
E -
X -
S -
E
162
59
11
97
249
118
212
908
18.5
28.1
Rows
X
23.1
8.4
1.6
13.9
35.6
16.9
30.3
E
X
S
S
28.3
11.2
1.8
18.0
49.4
28.0
29.2
(24)
- 643
- 26.8
- 34.8
01
02
03
04
05
06
07
(25)
- 164
- 6.6
- 8.5
Columns
X
12.7
13.6
12.9
0.7
5.4
20.7
24.1
May 9-19,
S
16.3
15.7
11.0
1.3
5.1
26.7
20.7
1977
Interior Traps
E
77
135
138
114
62
56
326
(25)
E - 265
X - 10.6
S - 17.1
Columns
X
11.0
19.3
19.7
16.3
8.9
8.0
46.6
S
21.4
23.1
31.0
24.2
8.9
10.1
48.9
-------
APPENDIX TABLE 18.1. CANTHON SP. (continued)
ZAPS II
ZAPS II
PLOT A (Control)
May 10-20, 1977
01
02
03
04
05
06
07
PLOT
01
02
03
04
05
06
07
Total Traps
(49)
£ - 757
X - 15.5
S • 18.3
Rows
£ X
101 14.4
129 18.4
67 9.6
35 5.0
70 10.0
110 15.7
245 35.0
B (Low)
Total Traps
(49)
£ - 845
X - 17.3
S - 28.1
Rows
£ X
55 7.9
114 16.3
16 2.3
20 2.9
17 2.4
198 28.3
425 60.7
Perimeter Traps
(24)
£ " 531
X- 22.2
X - 23.1
S
15.3 01
26.5 02
6.8 03
6.8 04
8.3 05
10.2 06
28.9 07
Perimeter Traps
(24)
E - 709
X - 29.5
X - 34.9
S
7.6 01
20.9 02
3.7 03
2.1 04
2.4 05
43.1 06
27.1 07
Interior Traps
(25)
£ - 226
)C - 9.0
X - 8.6
Columns
E X
168 24.0
170 24.3
117 16.7
64 9.1
89 12.7
45 6.4
104 14.9
May 10-20,
Interior Traps
(25)
£ - 136
X - 5.4
X - 10.7
Columns
£ X
284 40.6
52 7.4
130 18.6
78 11.1
125 17.9
41 5.9
135 19.3
S
26.7
28.3
19.5
10.5
13.9
6.5
10.9
1977
S
50.3
14.2
27.2
19.3
29.6
8.8
24.1
PLOT C (Medium)
May 10-20, 1977
Total Traps
Perimeter Traps
(49)
£ -
X -
s -
643
13.1
16.3
(24)
E - 492
X- 20.5
S - 19.4
Interior Traps
£
X
S
Rows
01
#2
03
04
05
#6
#7
E
123
A3
40
47
86
82
222
X
17
6
5
6
12
11
31
.6
.1
.7
.7
.3
.7
.7
S
14.
8.
6.
5.
23.
12.
22.
3
4
3
9
0
6
3
01
02
03
04
05
06
07
£
107
101
68
29
81
74
183
(25)
- 151
6
- 8
.0
.1
Columns
X
15.
14.
9.
4.
11.
10.
26.
3
4
7
1
6
6
1
S
13.
26.
12.
4.
9.
13.
22.
3
2
5
I
5
0
6
PLOT D (High)
May 10-20, 1977
01
02
03
04
05
06
07
Total Traps
(49)
£ -
X =
S -
I
47
116
95
69
102
106
431
966
19.7
32.5
Rows
X
6.7
16.6
13.6
9.9
14.6
15.1
61.6
Perimeter Traps
(24)
£ - 803
X- 33.5
S » 41.5
S
7.3
32.6
24.5
9.7
16.1
24.5
57.6
01
02
03
04
05
06
07
Interior Traps
£
X
S
£
53
24
62
95
179
100
453
(25)
- 163
- 6.5
9.7
Columns
X
7.6
3.4
8.9
13.6
25.6
14.3
65.0
S
6.7
3.7
8.7
26.2
40.1
21.8
49.5
-------
APPENDIX TABLE 18.1. CANTHON SP. (continued)
ZAPS I
ZAPS I
PLOT A (Control)
June 22-July 2, 1977
PLOT C (Medium)
June 22-July 2, 1977
00
Total
Trnpa
Perimeter Traps
(49)
01
02
03
04
05
06
07
PLOT
£ - 1
5( -
S -
£
520
103
271
243
210
310
270
B (Low)
Total
,927
39.3
45.7
Rows
X
74.3
14.7
38.7
34.7
30.0
44.3
38.6
Traps
£
X
S
S
49.2
18.6
49.4
54.3
29.3
55.7
48.2
(24)
- 1,397
58.2
48.4
01
02
03
04
05
06
07
Perimeter Traps
(49)
01
12
#3
04
#5
16
#7
£ -
31 -
S -
£
237
232
196
52
103
127
263
1,210
24.7
31.7
Rows
X
33.9
33.1
28.0
7.4
14.7
18.1
35.6
£
X
S
S
47.8
40.7
21.8
12.8
18.4
25.3
39.6
(24)
- 817
- 34.0
« 38.2
#1
02
13
04
15
06
*7
Interior Traps
£
"X
S
£
597
215
408
194
167
52
294
June
(25)
- 530
- 21.2
- 35.2
Columns
X
85.3
30.7
58.3
27.7
23.9
7.4
42.0
22-July 2,
S
44.6
43.7
65.2
32.5
38.5 '
6.0
37.5
1977
Interior Traps
£
X
S
£
230
139
240
174
66
66
295
(25)
- 393
- 15.7
- 20.9
Columns
X
32.9
19.9
34.3
24.9
9.4
9.4
42.1
J
S
36.5
31.2
38.8
33.9
8.8
16.0
47.9
Total Traps
(49)
£ - 1,296
11
02
S3
#4
05
#6
#7
PLOT
X -
X -
£
385
289
87
17
117
182
219
D (High)
26.4
36.7
Rows
X
55.0
41.3
12.4
2.4
16.7
26.0
31.3
Total Traps
#1
#2
#3
14
95
f6
tl
(49)
S - 1.
X -
S -
E
413
54
106
156
139
106
670
644
33.5
46.8
Rows
X
59.0
7.7
15.1
22.3
19.9
15.1
95.7
Perimeter
(24)
Traps
£ - 1,011
X •
S -
S
51.1
43.3
14.2
2.3
28.8
43.1
34.2
Perimeter
(24)
£ - 1,
X -
S -
S
46.9
10.5
36.5
34.8
46.0
37.0
44.2
42.1
41.0
#1
92
S3
#4
05
96
til
Traps
556
64.8
50.1
#1
*2
#3
#4
15
96
17
Interior Traps
£
)C
S
£
297
151
230
15
70
192
341
June
(25)
" 285
- 11.4
- 24.5
Columns
X
42.4
21.6
32.9
2.1
10.0
27.4
48.7
22-July 2,
S
50.9
38.0
41.9
4.0
10.6
41.7
34.2
1977
Interior Traps
£
200
140
261
115
270
207
451
(25)
£ - 88
X - 3.5
S - 7.0
Columns
X
28.6
20.0
37.3
16.4
38.6
29.6
64.4
S
40.5
41.4
58.2
39.1
54.1
43.5
51.6
-------
APPENDIX TABLE 18.1. CANTHON SP. (continued)
ZAPS II
ZAPS II
PLOT A (Control)
June 23-July 3, 1977
PLOT C (Medium)
June 23-July 3, 1977
Total
Traps
(49)
01
02
03
04
05
*6
07
PLOT
E - 1
X -
X -
E
195
186
190
166
215
102
484
B (Low)
Total
,538
31.4
36.4
Rows
X
27.9
26.6
27.1
23.7
30.7
14.6
69.1
Traps
(49)
01
02
03
04
05
06
07
E »
X -
S *
E
216
67
39
57
31
56
490
956
19.5
31.7
Rows
X
30.9
9.6
5.6
8.1
4.4
8.0
70.0
Perimeter Traps
(24)
E - 1,037
)C - 43.2
S - 37.2
S
20.1 01
41.4 02
45.0 03
40.1 04
33.1 05
11.7 06
39.1 07
Perimeter Traps
(24)
E - 858
X - 35.8
S - 39.0
S
47.2 01
20.1 02
8.2 03
7.7 04
8.0 05
8.5 06
32.9 07
Interior Traps
E
X
S
E
419
495
191
114
106
41
172
June
(25)
- 501
- 20.0
- 32.6
Columns
X
59.9
70.7
27.3
16.3
15.1
5.9
24.6
23-July 3,
S
32.4
48.7
30.0
12.3
3'!.1
7.7
28.2
1977
Interior Traps
E
5c
s
E
273
83
83
93
101
137
186
(25)
- 98
- 3.9
- 5.4
Columns
X
39.0
11.9
11.9
13.3
14.4
19.6
26.6
S
35.8
22.3
18.5
28.4
23.0
42.6
45.1
Total Traps
(49)
E - 895
01
02
03
04
05
06
07
PLOT
X -
S -
E
95
125
35
18
51
118
453
18.3
31.9
Rows
X
13.6
17.9
5.0
2.6
7.3
16.9
64.7
Perimeter Traps
(24)
E
X
S
s
29.4
42.1
8.6
3.5
14.9
20.5
40.0
- 837
- 34.9
- 39.3
01
02
03
04
05
06
07
D (High)
Total
Traps
Perimeter Traps
(49)
01
02
03
04
05
06
07
E -
X -
S -
E
138
24
39
27
154
93
429
904
18.5
34.6
Rows
X
19.7
3.4
5.6
3.9
22.0
13.3
61.3
E
X
S
s
31.8
3.8
8.3
5.7
44.0
23.8
55.1
(24)
- 812
- 33.8
- 44.5
01
02
03
04
05
06
07
Interior Traps
(25)
E
X
S
E
160
122
126
17
86
92
292
June
• 58
• 2.3
• 4.0
Columns
X
22.9
17.4
18.0
2.4
12.3
13.1
41.7
23-July 3,
S
31.2
36.1
42.4
3.0
27.8
30.0
36.8
1977
Interior Traps
E
X
S
E
41
39
42
71
206
121
384
(25)
- 92
- 3.7
- 5.7
Columns
X
5.9
5.6
6.0
10.1
29.4
17.3
54.9
S
7.0
5.6
8.6
24.7
48.5
43.1
47.6
-------
APPENDIX TABLE 18.1. CANTHON SP. (continued)
ZAPS I
ZAPS I
PLOT A (Control)
September 11-21, 1977
PLOT C (Medium)
September 11-21. 1977
O
O
Total Traps
(49)
01
02
13
04
15
06
#7
PLOT
E - 75
X - 1.
S - 2.
E
19
4
7
11
15
11
8
B (Low)
5
6
Rows
X
2.7
0.6
1.0
1.6
2.1
1.6
1.2
Perimeter
(24)
E - 63
X - 2.
S - 3.
S
2.3
0.8
2.7
2.1
3.9
3.7
2.2
Traps
6
3
01
12
03
04
15
06
17
Interior Traps
(25)
E <
X •
S <
E
39
2
3
8
16
2
5
- 12
• 0.5
- 1.1
Columns
X
5.6
0.3
0.4
1.1
2.3
0.3
0.7
September 11-21,
Total Traps
11
12
03
04
#5
06
#7
(49)
E - 31
X - 0
S - 1
E
12
3
4
1
4
2
5
.6
.0
Rows
X
1.7
0.4
0.6
0.1
0.6
0.3
0.7
Perimeter
(24)
E - 28
X - 1
S - 1
S
1.5
0.5
0.8
0.4
1.5
0.8
1.0
Traps
.2
.3
11
#2
13
04
#5
96
07
S
4.0
0.5
0.8
2.2
2.6
0.5
1.0
1977
Interior Traps
E
X
S
E
9
3
3
6
0
2
8
(25)
- 3
- 0.1
- 0.3
Columns
X
1.3
0.4
0.4
0.9
0.0
0.3
1.1
S
1.4
0.8
0.8
1.6
0.0
0.5
1.2
Total Traps
11
12
13
14
15
16
*7
PLOT D
(49)
1 - 19
X - 0.4
S - 1.5
£
2
3
1
1
1
1
10
(High)
Rows
X
0.3
0.4
0.1
0.1
o.i
0.1
1.4
Total Traps
(49)
1-49
X - 1.0
11
*2
93
tit
15
06
17
S - 3.
E
3
5
1
2
1
22
15
1
Rows
X
0.4
0.7
0.1
0.3
0.1
3.1
2.1
Perimeter Traps
(24)
E - 16
X - 0.7
S - 2.0
S
0.5
0.8
0.4
0.4
0.4
0.4
3.8
11
12
13
04
15
06
17
Perimeter Traps
(24)
1-43
X - 1.8
S - 4.3
S
0.5
1.3
0.4
0.8
0.4
7.5
3.2
01
02
13
14
05
#6
#7
Interior Traps
(25)
E - 3
X - 0.1
S - 0.3
Columns
E X
0 0.0
1 0.1
10 1.4
0 0.0
1 0.1
3 0.4
4 0.6
September 11-21,
Interior Traps
(25)
E - 6.0
X - 0.2
S - 0.7
Columns
E X
14 2.0
3 0.4
0 0.0
3 0.4
7 1.0
1 0.1
21 3.0
S
0.0
0.4
3.8
0.0
0.4
0.5
0.8
1977
S
3.2
0.5
0.0
0.8
1.4
0.4
7.5
-------
APPENDIX TABLE 18.1. CANTHON SP. (continued)
ZAPS II
ZAPS II
PLOT A (Control)
September 10-20, 1977
PLOT C (Medium)
September 10-20, 1977
Total Traps
(49)
E - 135
tl
02
13
04
05
16
#7
PLOT B
X -
s -
E
23
19
21
16
14
12
30
(Low)
Total
2.7
3.6
Rows
X
3.3
2.7
3.0
2.3
2.0
1.7
4.3
Perimeter Traps
(24)
E - 107
X - 4.5
S - 4.1
S
3.3 SI
5.1 02
3.7 03
4.8 #4
3.6 #5
1.4 06
2.5 91
Interior Traps
(25)
E
X
S
E
63
30
11
2
4
13
12
- 28
• 1.1
- 1.8
Columns
X
9.0
4.3
1.6
0.3
0.6
1.9
1.7
September 10-20,
Traps
(49)
#1
02
03
04
05
#6
#7
I -
X -
S -
E
3
8
2
5
10
8
35
71
1.5
2.5
Rows
X
0.4
1.1
0.3
0.7
1.4
1.1
5-0
Perimeter Traps
(24)
E - 45
X - 1.9
S - 3.1
S
0-5 tl
1.9 #2
0.8- 03
0.8 04
2.1 05
1.8 06
4.1 07
S
3.6
3.5
1.7
0.5
1.1
1.6
1.8
1977
Interior Traps
E
10
13
14
3
17
14
0
(25)
E - 26
X - 1.0
S - 1.5
Columns
X
1.4
1.9
2.0
0.4
2.4
2.0
0.0
S
1.9
3.2
3.2
0.5
3.4
2.5
0.0
Total Traps
(49)
01
02
03
04
05
06
07
PLOT
E - 88
X - 1.
S - 2.
E
13
4
2
6
4
9
50
D (High)
8
8
Rows
X
1.9
0.6
0.3
0.9
0.6
1.3
7.14
Perimeter
(24)
E - 72
X - 3.
S - 3.
S
2.7
0.8
0.5
1.2
0.8
1.6
3.1
Traps
0
.6
01
02
03
04
05
06
07
Interior Traps
(25)
E
Ic
S
E
6
15
18
5
11
20
13
- 16
- 0.6
- 0.9
Columns
X
0.9
2.1
2.6
0.7
1.6
2.9
1.9
September 10-20,
Total Traps
01
02
03
04
05
06
0.7
(49)
E - 75
X - 1
S - 2
E
10
2
2
2
9*
5
45
.5
.9
Rows
X
1.4
0.3
0.3
0.3
1.3
0.7
6.4
Perimeter
(24)
E - 70
X - 2
S - 3
S
1.4
0.5
0.5
0.8
2.6
1.3
4.6
Traps
.9
.6
01
02
03
04
05
06
07
S
1.9
4.0
4.0
1.5
2.2
3.6
1.7
1977
Interior Traps
E
a
s
E
7
13
11
14
6
2
22
(25)
- 5
- 0.2
- 0.7
Columns
X
1.0
1.9
1.6
2.0
0.9
0.3
3.1
S
1.1
4.1
1.6
5.3
1.9
0.5
2.9
-------
APPENDIX TABLE 18.1. CANTHON SP. (continued)
HAY COULEE
o
NJ
if 2
#3
tf4
#5
ilk
in
Total Traps
(28)
Z =
X -
s -
I
57
11
50
6
7
44
20
195
6.9
10.0
Rows
X
14.2
2.8
12.5
1.5
1.8
11.0
5.0
Perimeter Traps
(18)
E - 114
X = 6.3
S » 7.9
S
11.4 #1
2.8 92
21.7 #3
1.3 #4
2.4
5.0
5.6
Interior Traps
(10)
I = 81
X = 8.1
S = 13.6
Columns
E X
28 4.0
39 5.6
69 9.9
59 8.5
S
6.2
4.7
15.9
10.9
-------
APPENDIX TABLE 18.2. 7X7 LATIN SQUARE GRID CAPTURE OF ONTHOPHAGUS HECATE AT EPA ZAPS, 1977
ZAPS I
PLOT A (Control)
Total Traps Perimeter Traps
(49) (24)
1 - 216 Z - 144
X - 4.4 X - 6
S - 4.8 S - 5.7
PLOT B (Low)
Total Traps Perimeter Traps
(49) (24)
£ - 172 Z - 110
X - 3.5 X - 4.6
S - 4.4 S - 5
PLOT C (Medium)
Total Traps Perimeter Traps
(49) (24)
Z - 143 Z - 78
X - 2.9 X - 3.3
S - 3.3 S - 3.4
PLOT D (High)
Total Traps Perimeter Traps
(49) (24)
Z - 189 I - 117
X" - 3.8 X- 4.9
S - 4.9 S - 5.7
May 9-19, 1977
Interior Traps
(25)
£ - 72
X - 2.9
S - 3.1
May 9-19, 1977
Interior Traps
(25)
Z - 62
X - 2.5
S - 3.6
May 9-19, 1977
Interior Traps
(25)
Z - 65
X - 2.6
S - 3.2
May 9-19, 1977
Interior Traps
(25)
Z - 72
X • 2.9
S - 3.8
PLOT A (Control)
Total Traps
(49)
Z • 94
X - 1.9
S • 2.2
PLOT B (Low)
Total Traps
(49)
Z - 61
X - 1.2
S - 2.0
PLOT C (Medium)
Total Traps
(49)
Z - 84
X - 1.7
S « 1.8
PLOT D (High)
Total Traps
(49)
Z - 156
X - 3.2
S - 5.5
ZAPS II
Perimeter Traps
(24)
Z " 44
X - 1.8
S • 1.9
Perimeter Traps
(24)
Z - 41
X - 1.7
S - 2.1
Perimeter Traps
(24)
Z • 57
X - 2.4
S - 2.1
Perimeter Traps
(24)
Z - 129
X - 5.4
S - 7
May 10-20,
Interior Traps
(25)
Z " 50
X - 2.1
S - 2.6
May 10-20,
Interior Traps
(25)
Z - 20
X • .8
S - 1.7
May 10-20,
Interior Traps
(25)
Z - 27
X - 1.1
S - 1.2
May 10-20,
Interior Traps
(25)
Z - 27
X - 1.8
S - 1.6
1977
1977
1977
1977
-------
APPENDIX TABLE 18.2. ONTHOPHAGUS HECATE (continued)
PLOT A
PLOT B
PLOT C
PLOT D
(Control)
Total Traps
(49)
E - 65
X - 1.3
S • 2.2
(Low)
Total Traps
(49)
1-40
X - .8
S - 1.5
(Medium)
Total Traps
(49)
Z - 60
X - 1.2
S - 2.3
(High)
Total Traps
(49)
E- 25
X - .5
S - 1.1
ZAPS I
Perimeter Traps
(24)
E - 52
X - 2.2
S - 2.9
Perimeter Traps
(24)
E - 30
X - 1.3
S - 2.1
Perimeter Traps
(24)
I - 41
X - 1.7
S - 1.8
Perimeter Traps
(24)
Z - 25
X - 1
S - 1.5
June 22- July 2, 1977
Interior Traps
(25)
1 - 13
X • .5
S - .9
June 22-July 2. 1977
Interior Traps
(25)
E • 10
X - .4
S - .5
June 22-July 2, 1977
Interior Traps
(25)
E - 19
X « .8
S - 2.7
June 22-July 2, 1977
Interior Traps
(25)
E - 0
X~ - 0
S - 0
PLOT A (Control)
Total Traps
(49)
Z - 27
X - .6
S - 1.3
PLOT B (Low)
Total Traps
(49)
E - 6
X - .1
S - .4
PLOT C (Medium)
Total Traps
(49)
Z - 12
X - .2
S - .6
PLOT D (High)
Total Traps
(49)
Z - 4
X - .08
S - .3
ZAPS II
June 23-July 3,
Perimeter Traps Interior Traps
(24) (25)
Z . 21 Z - 6
X - .9 X • .2
S - 1.7 S - .4
June 23-July 3 ,
Perimeter Traps Interior Traps
(24) (25)
Z - 5 Z - 1
X~ - .2 X - 0
S - .5 S » .2
June 23-July 3 ,
Perimeter Traps Interior Traps
(24) (25)
Z - 10 Z - 2
X - .4 1- .1
S - .8 S - .3
June 23 -July 3 ,
Perimeter Traps Interior Trape
(24) (25)
Z " 2 E - 2
1 - .1 X - .1
S - .4 S » .3
1977
1977
1977
1977
-------
APPENDIX TABLE 18.2. ONTHOPHAGUS HECATE (continued)
o
Ui
PLOT A (Control)
Total Traps
(A9)
I - 3
X - .06
S - .2
PLOT B (Low)
Total Traps
(49)
Z - 4
X - .08
S - .3
PLOT C (Medium)
Total Traps
(49)
1 - 4
X - .08
S - .3
PLOT D (High)
Total Traps
(49)
z - 11
X - .2
S - .6
ZAPS I
September 11-21, 1977
Perimeter Traps Interior Traps
(24) (25)
Z • 2 I - 1
X - .1 X • 0
S • .3 S - .2
September 11-21, 1977
Perimeter Traps Interior Traps
(24) (25)
r - 2 z - 2
X - .1 X - .1
S - .3 S - .3
September 11-21, 1977
Perimeter Traps Interior Traps
(24) (25)
Z - 2 1-2
X - .1 X - .1
S - .3 S - .3
September 11-21, 1977
Perimeter Traps Interior Traps
(24) (25)
Z - 9 Z - 2
X » .4 X - .1
S - .8 S - .3
-
PLOT A (Control)
Total Traps
(49)
Z • 19
X - .4
S - .6
PLOT B (Low)
Total Traps
(49)
1-17
X - .4
S - .8
PLOT C (Medium)
Total Traps
(49)
Z - 17
X - .4
S = .7
PLOT D (High)
Total Traps
(49)
Z = 15
X - .3
S - .6
ZAPS II
Perimeter Traps
(24)
I - 10
X - .4
S - .6
Perimeter Traps
(24)
Z - 11
X - .5
S - .8
Perimeter Traps
(24)
Z - 12
X - .5
S - .8
Perimeter Traps
(24)
Z = 12
X = .5
S = .7
September 10-20,
Interior Traps
(25)
E - 9
X - .4
S - .6
September 10-20,
Interior Traps
(25)
E - 6
X - .2
S - .7
September 10-20,
Interior Traps
(25)
E - 5
X - .2
S - .4
September 10-20,
Interior Traps
(25)
E - 3
X - .12
S - .33
1977
1977
1977
1977
-------
APPENDIX TABLE 18.3. 7X7 LATIN SQUARE GRID CAPTURE OF NICPOPHORUS SP. AT EPA ZAPS, 1977
PLOT A
PLOT B
PLOT C
PLOT D
(Control)
Total Traps
(49)
1-60
X - 1.2
S - 1.7
(Low)
Total Traps
(A9)
E - 34
X - .7
S - 1.3
(Medium)
Total Traps
(49)
E - 43
X - .9
S - 1.2
(High)
Total Traps
(49)
E - 53
X • l.l
3 • 1.8
ZAPS I
Perimeter Traps
(24)
£ - 36
X" • 1.5
S - 2
Perimeter Traps
(24)
E - 19
X - .8
S - 1.2
Perimeter Traps
(24)
E - 23
X - 1
S - 1.1
Perimeter Traps
(24)
E - 38
X - 1.6
S - 2.3
May 9-19, 1977
Interior Traps
(25)
E - 24
X - 1
S - 1.5
May 9-19, 1977
Interior Traps
(25)
E - IS
X - .6
S - 1.3
May 9-19, 1977
Interior Traps
(25)
E - 20
X - .8
S - 1.2
May 9-19, 1977
Interior Traps
(25)
E - 15
X - .6
S - .9
PLOT A (Control)
Total Traps
(49)
E - 39
X - .8
S - 1.3
PLOT & (Low)
Total Traps
(49)
E • 55
X - 1.1
S " 2.6
PLOT C (Medium)
Total Traps
(49)
E - 29
X - .6
S - .8
PLOT D (High)
Total Traps
(49)
E - 74
X - 1.5
S - 3
ZAPS II
Perimeter Traps
(24)
E - 25
X - 1
S - 1.3
Perimeter Traps
(24)
E - 44
X - 1.8
S - 3.5
Perimeter Traps
(24)
E - 20
X - .8
S - .8
Perimeter Traps
(24)
E - 66
X - 2.8
S - 3.9
May 10-20,
Interior Traps
(25)
E - 14
X - .6
S - 1.2
May 10-20,
Interior Traps
(25)
E " 11
X - .4
S - .9
May 10-20,
Interior Traps
(25)
E - 9
X - .4
S - .6
May 10-20,
Interior Traps
(25)
1 - 8
X - .3
S - .6
1977
1977
1977
1977
-------
APPENDIX TABLE 18.3. NICROPHORUS SP. (continued)
PLOT A (Control)
Total Traps
(49)
Z - 65
X • 1.3
S - 1.9
PLOT B (Low)
Total Traps
(49)
Z - 32
X - .7
S - 1
PLOT C (Medium)
Total Traps
(49)
Z - 35
X - .7
S - 1.4
PLOT D (High)
Total Traps
(49)
Z • 35
X - .7
S - "l.l
ZAPS I
Perimeter Traps
(24)
Z - 51
X - 2.1
S - 2.4
Perimeter Traps
(24)
Z - 22
X - .9
S - 1.1
Perimeter Traps
(24)
Z - 29
X - 1.2
S - 1.8
Perimeter Traps
(24)
Z - 29
X - 1.2
S - 1.4
June 22-July 2, 1977
Interior Traps
(25)
Z - 14
X - 1.6
S - 1
June 22-July 2, 1977
Interior Traps
(25)
Z » 10
X - .4
S - .8
June 22-July 2, 1977
Interior Traps
(25)
Z - 6
I « .2
S - .7
June 22-July 2, 1977
Interior Traps
(25)
Z - 6
X - .1
S - .4
PLOT A (Control)
Total Traps
(49)
Z " 66
X - 1.4
S - 1.9
PLOT B (Low)
Total Traps
(49)
Z - 39
X - .8
S - 1.6
PLOT C (Medium)
Total Traps
(49)
Z - 39
X - .8
S • 1.2
PLOT D (High)
Total Traps
(49)
Z - 144
X - 2.9
S - 4.4
ZAPS II
Perimeter Traps
(24)
Z - 45
X - 1.9
S - 1.9
Perimeter Traps
(24)
Z " 21
X - .9
S - 1.3
Perimeter Traps
(24)
Z - 31
X - 1.3
S - 1.3
Perimeter Traps
(24)
Z - 110
X - 4.6
S - 5.3
June 23-July 3, 1977
Interior Traps
(25)
Z - 21
X - 1.8
S - 1.8
June 23-July 3, 1977
Interior Traps
(25)
Z - 18
X - .7
S - 1.8
June 23-July 3, 1977
Interior Traps
(25)
Z - 8
X - .3
S - .8
June 23-July 3, 1977
Interior Traps
(25)
Z - 34
X - 1.4
S - 2.6
-------
APPENDIX TABLE 18.3. NICROPHORUS SP. (continued)
o
oo
PLOT A (Control)
Total Traps
(49)
Z - 37
X - .8
S - .5
PLOT B (Low)
Total Traps
(49)
1-24
X - .5
S - 1.2
PLOT C (Medium)
Total Traps
(49)
1-43
X - .9
S - 1.3
PLOT D (High)
Total Traps
(49)
1-33
X - .7
S - 1
ZAPS X
Perimeter Trapa
(24)
E - 31
X - 1.3
S - 1.4
Perimeter Traps
(24)
1-20
X - .8
S - 1.6
Perimeter Traps
(24)
E - 30
X - 1.3
S - 1.6
Perimeter Traps
(24)
E - 28
X - 1.2
S - 1.1
September 11-21. 1977
Interior Traps
(25)
E - 6
X - .2
S - .5
September 11-21, 1977
Interior Traps
(25)
E - 4
X - .2
S - .4
September 11-21, 1977
Interior Traps
(25)
E - 13
X - .5
S - .9
September 11-21, 1977
Interior Traps
(25)
E - 5
X - .2
S - .5
PLOT A (Control)
Total Traps
(49)
E - 76
X - 1.6
S - 2.6
PLOT B (Low)
Total Traps
(49)
E - 41
X - .8
S - 1.2
PLOT C (Medium)
Total Traps
(49)
E - 38
X - .8
S - 1.4
PLOT D (High)
Total Traps
(49)
E - 69
X - 1.4
S - 2.2
ZAPS II
Perimeter Traps
(24)
E - 54
X - 2.3
S - 3.3
Perimeter Traps
(24)
E - 26
X - 1.1
S • 1.4
Perimeter Traps
(24)
E - 31
X - 1.3
S - 1.8
Perimeter Traps
(24)
E - 53
X - 2.2
S - 2.8
September 10-20,
Interior Trapa
(25)
E - 22
X - .9
S - 1.3
September 10-20,
Interior Traps
(25)
E - 15
X - .6
S - .9
September 10-20,
Interior Traps
(25)
E - 7
X - .3
S - .5
September 10-20,
Interior Traps
(25)
E - 16
X - .6
S - .9
1977
1977
1977
1977
-------
APPENDIX TABLE 18.4. 7X7 LATIN SQUARE GRID CAPTURE OF TROX SP. AT EPA ZAPS, 1977
o
VO
PLOT A (Control)
Total Traps
(49)
z - 7
X - .1
S - .4
PLOT B (Low)
Total Traps
(49)
I - B
X - .2
S - .4
PLOT C (Medium)
Total Traps
(49)
Z - 6
X - .1
S - .3
PLOT D (High)
Total Traps
(49)
Z - 5
X - .1
S - .3
ZAPS I
May 9-19, 1977
Perimeter Traps Interior Traps
(24) (25)
Z - 3 1-4
X" - .1 X - .2
S - .3 S • .4
May 9-19, 1977
Perimeter Traps Interior Traps
(24) (25)
Z - 4 Z - 4
X - .2 X - .2
S - .4 S - .5
May 9-19, 1977
Perimeter Traps Interior Traps
(24) (25)
1-3 1-3
X - .1 X - .1
S - .3 S - .3
May 9-19, 1977
Perimeter Traps Interior Traps
(24) (25)
1 - 2 1-3
X- .1 X- .1
S - .3 S - .3
PLOT A (Control)
Total Traps
(49)
Z - 10
X - .2
S - .5
PLOT B (Low)
Total Traps
(49)
Z - 20
X - .4
S - .8
PLOT C (Medium)
Total Traps
(49)
Z - 9
X - .2
S - .5
PLOT D (High)
Total Traps
(49)
Z - 25
X = .5
S « 1.3
ZAPS IX
Perimeter Traps
(24)
Z - 2
X - .1
S - .4
Perimeter Traps
(24)
Z - 9
X - .4
S - .7
Perimeter Traps
(24)
Z - 9
X - .4
S - .7
Perimeter Traps
(24)
Z - 22
X - .9
S - 1.7
May 10-20,
Interior Traps
(25)
Z * 8
X - .3
S - .6
May 10-20,
Interior Traps
(25)
Z - 11
X - .4
S - .9
May 10-20,
Interior Traps
(25)
Z - 0
X - 0
S - 0
May 10-20,
Interior Traps
(25)
Z - 3
X - .1
S - .3
1977
1977
1977
1977
-------
APPENDIX TABLE 18.4. TROX SP. (continued)
PLOT A
PLOT B
PLOT C
PLOT D
(Control)
Total Traps
(49)
E - 4
X - .1
S - .3
(Low)
Total Traps
(49)
£ - 20
X - .4
S - 2.4
(Medium)
Total Traps
(49)
E - 1
X - .02
S - .1
(High)
Total Traps
(49)
1 - 2
X • .04
S » .2
ZAPS I
Perimeter Traps
(24)
E - 2
X - .1
S - .3
Perimeter Traps
(24)
1 - 20
X - .8
S - 3.5
Perimeter Traps
(24)
I - 1
X - .1
S - .2
Perimeter Traps
(24)
E - 2
X - .1
S - .3
June 22- July 2, 1977
laterior Traps
(25)
E - 2
X - .1
S - .3
June 22- July 2, 1977
Interior Traps
(25)
E - 0
!"- 0
S - 0
June 22-July 2, 1977
Interior Traps
(25)
£ - 0
X - 0
S - 0
June 22-July 2, 1977
Interior Traps
(25)
E - 0
X - 0
S - 0
PLOT A (Control)
Total Traps
(49)
E - 8
X - .2
S - .9
PLOT B (Low)
Total Traps
(49)
E - 3
X • .06
S - .3
PLOT C (Medium)
Total Traps
(49)
Z - 2
X - .04
S - .2
PLOT D (High)
Total Traps
(49)
E - 6
X - .1
S - .7
ZAPS II
June 23- July 3,
Perimeter Traps Interior Traps
(24) (25)
E - 1 E - 7
X • .1 X - .3
S - .2 S - 1.2
June 23- July 3,
Perimeter Traps Interior Traps
(24) (25)
E - 0 E - 3
X - 0 I - .1
S - 0 S - .5
June 23- July 3,
Perimeter Traps Interior Traps
(24) (25)
E - 1 E - 1
X - .1 X - .1
S - .2 S - .2
June 23- July 3,
1977
1977
1977
1977
Perimeter Traps Interior Traps
(24) (25)
E - 5 E - 1
¥ - .2 ¥ - .1
S - .1 S - .2
-------
APPENDIX TABLE 18.4. TPOX SP. (continued)
PLOT
PLOT
PLOT
PLOT
A (Control)
Total Traps
(49)
Z - 58
X • 1.2
S - 1.9
B (Low)
Total Traps
(49)
Z - 21
X - .4
S - 1.1
C (Medium)
Total Traps
(49)
Z - 21
X - .4
S - .9
D (High)
Total Traps
(49)
1-36
X - .7
S - 1.2
ZAPS I
Perimeter Traps
(24)
E - 47
X - 2
S - 2.3
Perimeter Traps
(24)
S - 15
X » .6
S - 1.4
Perimeter Traps
(24)
I - 19
X - .8
S - 1.1
Perimeter Traps
(24)
1 - 27
X - 1.1
S - 1.5
September 11-21, 1977
Interior Traps
(25)
1 - 11
X - .4
S - 1.1
September 11-21, 1977
Interior Traps
(25)
1 - 6
X • .2
S - .8
September 11-21, 1977
Interior • Traps
(25)
1-2
X - .1
S - .3
September 11-21, 1977
Interior Traps
(25)
I « 9
X - .4
S - .8
PLOT A (Control)
Total Traps
(49)
S - 58
X - 1.2
S - 1.6
PLOT B (Low)
Total Traps
(49)
Z - 22
X - .5
S - 1.0
PLOT C (Medium)
Total Traps
(49)
Z - 16
X - .3
S - .7
PLOT D (High)
Total Traps
(49)
Z - 44
X - .9
S - 1.6
ZAPS II
Perimeter Traps
(24)
Z - 39
X - 1.6
S - 1.7
Perimeter Traps
(24)
Z - 12
X - .5
S - 1.3
Perimeter Traps
(24)
Z - 9
X - .4
S - .8
Perimeter Traps
(24)
Z - 31
X - 1.3
S - 2
September 10-20,
Interior Traps
(25)
Z - 19
X - .8
S - 1.7
September 10-20,
Interior Traps
(25)
Z - 10
X - .4
S - .7
September 10-20,
Interior Traps
(25)
Z - 7
X - .3
S - .6
September 10-20,
Interior Traps
(25)
Z - 13
X - .5
S - 1
1977
1977
1977
1977
-------
APPENDIX TABLE 18.5. 7X7 LATIN SQUARE GRID CAPTURE OF PASIMACHUS ELONGATUS AT EPA ZAPS, 1977
10
PLOT A
PLOT B
PLOT C
PLOT D
(Control)
Total Traps
(49)
I ' 4
X - .08
S - .3
(Low)
Total Traps
(49)
E - 28
X - .6
S - 1
(Medium)
Total Traps
(49)
E - 17
X - .4
S - .7
(High)
Total Traps
(49)
E - 19
X - .4
S - .8
ZAPS I
Perimeter Traps
(24)
E - 4
X - .2
S - .4
Perimeter Traps
(24)
E - 16
X - .7
S - 1.2
Perimeter Traps
(24)
E - 8
X - .3
S - .7
Perimeter Traps
(24)
E - 6
X - .3
S - .6
Hay 10-20, 1977
Interior Traps
(25)
E - 0
X • 0
S - 0
May 10-20, 1977
Interior Traps
(25)
E - 12
X - .5
S - .7
May 10-20, 1977
Interior Traps
(25)
E - 9
X - .4
S - .8
May 10-20, 1977
Interior Traps
(25)
E - 13
X - .5
S - .9
PLOT A (Control)
Total Traps
(49)
E - 7
X - .1
S - .4
PLOT B (Low)
Total Traps
(49)
E - 13
X - .3
S - .6
PLOT C (Medium)
Total Traps
(49)
E - 11
X - .2
S - .6
PLOT D (High)
Total Traps
(49)
Z - 10
X - .2
S « .6
ZAPS II
Perimeter Traps
(24)
E - 4
X - .2
S - .4
Perimeter Traps
(24)
E - 12
X - .5
S - .8
Perimeter Traps
(24)
E - 8
X - .3
S - .7
Perimeter Traps
(24)
E - 10
X - .4
S - .8
May 11-21,
Interior Traps
(25)
E - 3
X - .1
S - .5
May 11-21,
Interior Traps
(25)
E - 1
X - .04
S - .2
May 11-21,
Interior Traps
(25)
E • 3
X - .1
S - .33
May 11-21,
Interior Traps
(25)
E - 0
X - 0
S - 0
197;
1977
1977
1977
-------
APPENDIX TABLE 18.5. PASIMACHUS ELONGATUS (continued)
OJ
PLOT
PLOT
PLOT
PLOT
A (Control)
Total Traps
(49)
E - 23
X - .5
S - .9
B (Low)
Total Traps
(49)
E - 7
X - .1
S - .4
C (Medium)
Total Traps
(49)
E - 15
X - .3
S - .6
D (High)
Total Traps
(49)
E - 12
X - .2
S = .5
ZAPS I
June 22-July 2, 1977
Perimeter Traps Interior Traps
(24) (25)
E - 12 E - 11
X- .5 X- .4
S - 1 S - .7
June 22-July 2, 1977
Perimeter Traps Interior Traps
(24) (25)
E - 4 E - 3
X - .2 X - .1
S - .4 S - .3
June 22-July 2, 1977
Perimeter Traps Interior Traps
(24) (25)
E - 10 E - 5
X - .4 X - .2
S • .8 S - .4
June 22-July 2, 1977
Perimeter Traps Interior Traps
(24) (25)
E = 9 E - 3
X - .4 X - .1
S - .7 S = .3
PLOT A (Control)
Total Traps
(49)
E - 11
X - .2
S • .6
PLOT B (Low)
-Total -Traps
(49)
E • 18
X - .4
S - .8
PLOT C (Medium)
Total Traps
(49)
E - 13
X - .3
S - .5
PLOT D (High)
Total Traps
(49)
E - 17
X = .4
S = .9
ZAPS II
Perimeter Traps
(24)
E - 5
X - .2
S - .5
Perimeter Traps
(24)
E • 13
X - .5
S - 1
Perimeter Traps
(24)
E = 10
X - .4
S - .6
Perimeter Traps
(24)
E - 13
X » .5
S - 1.2
June 23- July 3,
Interior Traps
(25)
E - 6
X - .2
S - .7
June 23- July 3,
Interior Traps
(25)
E - 5
X - .2
S - .5
June 2 3- July 3,
Interior Traps
(25)
E - 3
X - .1
S - .3
June 2 3- July 3,
Interior Traps
(25)
E - 4
X - .2
S - .5
1977
1977
1977
1977
-------
APPENDIX TABLE 18.5. PASIMACHUS ELONGATUS (continued)
PLOT A (Control)
Total Traps
(49)
Z - 2
X - .04
S - .2
PLOT B (Low)
Total Traps
(49)
Z - 2
X • .04
S - .2
PLOT C (Medium)
Total Traps
(49)
Z - 2
X - .04
S - .2
PLOT D (High)
Total Traps
(49)
Z - 3
X - .06
S - .2
ZAPS I
Perimeter Traps
(24)
Z - 1
X - .04
S - .2
Perimeter Traps
(24)
Z - 1
X - .04
S • .2
Perimeter Traps
(24)
Z - 2
X - .08
S - .3
Perimeter Traps
(24)
Z " 2
X - .08
S - .3
September 11-21, 1977
Interior Traps
(25)
Z - 1
X - .04
S - .2
September 11-21, 1977
Interior Traps
(25)
Z - 1
X - .04
S - .2
September 11-21, 1977
Interior Traps
(25)
Z - 0
X - 0
S - 0
September 11-21, 1977
Interior Traps
(25)
Z - 1
X - .04
S - .2
PLOT A (Control)
Total Traps
(49)
Z - 2
X" - .04
S - .2
PLOT B (Low)
Total Traps
(49)
Z - 15
X - .3
S - .8
PLOT C (Medium)
Total Traps
(49)
Z - 5
X - .1
S - .4
PLOT D (High)
Total Traps
(49)
Z - 7
X - .1
S - .4
ZAPS II
September 10-20,
Perimeter Traps Interior Traps
(24) ' (25)
Z - 0 £ - 2
X • 0 X" - .08
S - 0 S - .3
September 10-20,
Perimeter Traps Interior Traps
(24) (25)
Z - 7 Z - 8
X - .3 X - .3
S - .9 S - .7
September 10-20,
Perimeter Traps Interior Traps
(24) (25)
Z - 1 Z - 4
X - .04 X - .2
S - .2 S - .5
September 10-20,
Perimeter Traps Interior Traps
(24) (25)
Z - 5 Z - 2
X - .2 X - .08
S - .5 S - .3
1977
1977
1977
1977
-------
APPENDIX TABLE 18.6. 7X7 LATIN SQUARE GRID CAPTURE OF CURCULIONIDAE (WEEVIL) AT EPA ZAPS, 1977
PLOT A (Control)
Total Traps
(49)
E - 0
X - 0
S - 0
PLOT B (Low)
Total Traps
(49)
r - 3
X - .06
S - .2
PLOT C (Medium)
Total Traps
(49)
E - 4
X - .08
S - .3
PLOT D (High)
Total Traps
(49)
E - 0
X - 0
S - 0
ZAPS I
Perimeter Traps
(24)
E - 0
X - 0
S - 0
Perimeter Traps
(24)
E - 2
X - .08
S - .3
Perimeter Traps
(24)
E - 4
X - .2
S - .4
Perimeter Traps
(24)
E •= 0
X - 0
S » 0
May 10-11, 1977
Interior Traps
(25)
E - 0
X • 0
S - 0
May 10-11, 1977
Interior Traps
(25)
E - 1
X - .04
S - .2
May 10-11, 1977
Interior Traps
(25)
E - 0
X - 0
S - 0
May 10-11, 1977
Interior Traps
(25)
E - 0
X - 0
S - 0
PLOT A (Control)
Total Traps
(49)
E - 18
X - .4
S - .8
PLOT B (Low)
Total Traps
(49)
E - 4
X • .08
S - .3
PLOT C (Medium)
Total Traps
(49)
E - 8
X - .2
S - .6
PLOT D (High)
Total Traps
(49)
E - 13
X - .3
S - .7
ZAPS II
Perimeter Traps
(24)
E - 15
X - .6
S - 1
Perimeter Traps
(24)
E - 3
x: - .1
S - .3
Perimeter Traps
(24)
E - 6
X - .3
S - .7
Perimeter Traps
(24)
I • 8
X - .3
S - .8
May 11-21,
Interior Traps
(25)
E - 3
X - .1
S - .3
May 11-21,
Interior Traps
(25)
E - 1
X - .04
S - .2
May 11-21,
Interior Traps
(25)
E - 2
X - .08
S - .3
May 11-21,
Interior Traps
(25)
E - 5
X - .2
S - .6
1977
1977
1977
1977
-------
APPENDIX TABLE 18.6. CURCULIONIDAE (WEEVIL) (continued)
ON
PLOT A (Control)
Total Traps
(«9)
NO CAPTURES; ZAPS I, June 22- July 2, 1977
— i . o
ZAPS 11, June 23-July 3, 1977 X - 0
S - 0
7 APS TTt Sopt-emHar lft-20, 1977
PLOT B (Low)
Total Traps
(49)
I - 0
X - 0
S - 0
PLOT C (Medium)
Total Traps
(49)
I - 0
X - 0
S - 0
PLOT D (High)
Total Traps
(49)
E - 1
X - .02
S - .14
ZAPS I
Perimeter Traps
(24)
r - o
¥ - 0
S - 0
Perimeter Traps
(24)
I - 0
X - 0
S - 0
Perimeter Traps
(24)
I - 0
X - 0
S - 0
Perimeter Traps
(24)
I - 0
X - 0
S - 0
September Il-2f,
Interior Traps
(25)
I - 0
X - 0
S - 0
September 11-21,
Interior Traps
(25)
I - 0
X - 0
S - 0
September 11-21,
Interior Traps
(25)
E - 0
X - 0
S - 0
f
September 11-21,
Interior Traps
(25)
E - 1
X - .04
S - .2
1977
1977
1977
1977
-------
APPENDIX TABLE 18.7. 7X7 LATIN SQUARE GRID CAPTURE OF CICINDELA SP. AT EPA ZAPS, 1977
PLOT A (Control)
Total Traps
(49)
E " 9
X - .18
S » .91
PLOT B (Low)
Total Traps
(49)
E - 19
X - .4
S - 1.1
PLOT C (Medium)
Total Traps
(49)
E - 6
X - .1
S - .4
PLOT D (High)
Total Trapa
(49)
£ - 6
X - .1
S - .4
ZAPS I
May 9-19, 1977
Perimeter Traps Interior Traps
(24) (25)
E - 7 1 - 2
X - .3 X - .08
S - 1.2 S - .4
May 9-19, 1977
Perimeter Traps Interior Traps
(24) (25)
E - 15 £ - 4
X - .63 X - .2
S - 1.6 S - .5
May 9-19, 1977
Perimeter Traps Interior Traps
(24) (25)
I - 4 E -,2
X - .2 X - .08
S - .5 S - .3
May 9-19, 1977
Perimeter Traps Interior Traps
(24) (25)
E - 1 E • 5
X" - .04 X - . 2
S - .2 S - .4
PLOT A (Control)
Total Traps
(49)
E - 6
X - .1
S - .4
PLOT B (Low)
Total Traps
(49)
E - 2
X - .04
S - .2
PLOT C (Medium)
Total Traps
(49)
E - 8
X • .2
S - .5
PLOT D (High)
Total Traps
(49)
E • 5
X - .1
S - .3
ZAPS II
Perimeter Traps
(24)
E - 3
X - .1
S - .3
Perimeter Traps
(24)
E - 2
X - .1
S - .3
Perimeter Traps
(24)
E - 5
X - .2
S - .5
Perimeter Traps
(24)
E - 3
X - .1
S - .3
May 10-20,
Interior Traps
(25)
E - 3
X - .1
S - .3
May 10-20,
Interior Traps
(25)
£ - 0
X - 0
S - 0
May 10-20,
Interior Traps
(25)
E - 3
X - .1
S - .4
May 10-20,
Interior Traps
(25)
E - 2
X - .04
S - .3
1977
1977
1977
1977
-------
APPENDIX TABLE 18.7. CICINDELA SP. (continued)
00
PLOT A
PLOT B
PLOT C
NO CAPTURES:
(Control)
Total Traps
(49)
Z - 2
X - .04
S - .2
(Low)
Total Traps
(49)
Z - 2
X - .04
S - .2
(Medium)
Total Traps
(49)
Z - 2
X - i04
S - .2
PLOT D (High)
Total Traps
(49)
1-2
X - .04
S - .2
ZAPS I and II, June 22-July 3, 1977
ZAPS I
September 11-21, 1977
Perimeter Traps Interior Traps
(24) (25)
Z - 2 I " 0
X - .04 X - 0
S - .3 S - 0
September 11-21, 1977
Perimeter Traps Interior Traps
(24) <25)
Z - 2 Z - Q
X - .08 X - 0
S - .4 S - 0
September 11-21, 1977
Perimeter Traps Interior Traps
(24) (25)
Z - 1 £ - 1
X - .04 X - .04
S - .2 S - .2
September 11-21, 1977
Perimeter Traps Interior Traps
(24) <25)
Z - 0 £ - 2
X - 0 X - .08
S - 0 S - .3
PLOT A (Control)
Total Traps
(49)
E - 1
X - .04
S - .2
PLOT B (Low)
Total Traps
(49)
Z • 3
Y - .06
S - .2
PLOT C (Medium)
Total Traps
(49)
Z - 3
X - .06
S - .2
PLOT D (High)
Total Traps
(49)
Z - 5
X - ,1
S - .3
ZAPS II
September 10-20,
Perimeter Traps Interior Traps
(24) (25)
Z - 1 Z - 0
X - .04 X - 0
S - .2 X • 0
Septmeber 10-20,
Perimeter Traps Interior Traps
(24) (25)
Z - 2 Z - 1
X - .08 X - .04
S - .3 S - .2
September 1O-20,
Perimeter Traps Interior Traps
(24) (25)
Z - 3 Z - 0
X - .1 X - 0
S - .3 S - 0
September 1O-20,
Perimeter Traps Interior Traps
(24) (25)
Z - 4 Z - 1
X - .2 X - .04
S - .8 S - .2
1977
1977
1977
1977
-------
APPENDIX TABLE 18.8. 7X7 LATIN SQUARE GRID CAPTURE OF OTHER BEETLES AT EPA ZAPS, 1977
PLOT A (Control)
Total Traps
(49)
Z - 62
H - 1.3
S - 1.9
PLOT B (Low)
Total Traps
(49)
Z - 132
I - 2.7
S - 2.4
PLOT C (Medium)
Total Traps
(49)
1 - 146
X - 2.98
S - 3.34
PLOT D (High)
Total Traps
(49)
Z - 102
X - 2
S - 2.5
ZAPS I
Perimeter Traps
(24)
1 - 25
X" - 1.04
S - 1.8
Perimeter Traps
(24)
1-69
X - 2.9
S - 2.4
Perimeter Traps
(24)
Z - 75
X - 3.8
S - 3.4
Perimeter Traps
(24)
Z - 53
X = 2.2
S - 3.2
May 9-19, 1977
Interior Traps
(25)
Z - 37
X" - 1.5
S - 2.0
May 9-19, 1977
Interior Traps
(25)
Z - 63
X - 2.5
S - 2.6
May 9-19, 1977
Interior Traps
(25)
Z - 71
X - 2.8
S - 2.9
May 9-19, 1977
Interior Traps
(25)
Z - 49
X - 2.0
S - 1.7
PLOT A (Control)
Total Traps
(49)
Z - 287
X - 5.9
S - 7.6
PLOT B (Low)
Total Traps
(49)
Z - 37
X - .7
S - 1.4
PLOT C (Medium)
Total Traps
(49)
Z - 95
X- 1.94
S - 1.78
PLOT D (High)
Total Traps
(49)
Z - 222
X - 4.53
S • 4.76
ZAPS II
Perimeter Traps
(24)
Z - 184
X - 7.4
S - 9.1
Perimeter Traps
(24)
Z - 19
X - .8
S - 1.4
Perimeter Traps
(24)
Z - 54
X - 2.3
S • 2
Perimeter Traps
(24)
Z - 147
X - 6.1
S - 5.8
May 10-20,
Interior Traps
(25)
Z " 103
X - 4.1
S - 5.2
May 10-20,
Interior Traps
(25)
Z - 18
X - .7
S - 1.3
May 10-20,
Interior Traps
(25)
Z - 41
X - 1.6
S - 1.5
May 10-20,
Interior Traps
(25)
Z - 75
X - 3
S - 2.9
1977
1977
1977
1977
-------
APPENDIX TABLE 18,8. OTHER BEETLES (continued)
PLOT
PLOT
PLOT
PLOT
A (Control)
Total Traps
(49)
t - 17
X " .35
S " ,69
B (Low)
Total Traps
(49)
Z - 44
I- .9
S - 1,2
C (Medium)
Total Traps
(49)
Z- 45
X - ,9
S - 1,1
P (High)
Total Traps
(49)
1 * 19
f * ,4
S * ,9
ZAPS I
Jun* 22- July 2. 1977
Perimeter Traps Interior Traps
(24) (25)
E " 10 1 - 7
I- ,4 X . ,3
S - .8 8 - .6
June 22- July 2. 1977
Perimeter Traps Interior Traps
(24) (25)
1 •> 19 ? * 25
X» ,8 X* 1
9 - J,l S - J,3
June 22-Jwiy 2. 1977
Perimeter Traps Interior Traps
(24) (25)
1 * 11 Z * 34
I* ,5 !«• 1,4
S - ,6 S * 1,2
June 2- July 2, 1977
Perimeter Tr*PS Interior fraps
(24) (25)
I * 15 2-3
X - .$ X * -12
S * 1,2 S * ,3
PLOT A (Control)
Total Traps
(49)
I " 21
5- ,4
S - 1.1
PLOT B (Low)
Total Traps
(49^
I i- 1
X - .14
S f .35
PLOT C 0te4iwii)
Total Traps
(49)
I ~ 17
f » .35
S * ,75
PLOT 5 (gigb)
Total Traps
(49)
I ' 1,*
S * 2,2
ZAPS II
June 2 3- July 3.
Perimeter Traps Interior Traps
(24) (25)
E - 7 I - 14
X - ,3 X- .56
S » ,5 S - 1,5
June 23-July 3,
Perimeter Traps Interior Traps
(24) (25)
E - 4 1 - 3
X • .2 X- .12
S * .4 S - .3
June 23- July 3, .
Perimeter Traps Interior Traps
(24) (25)
£ * $ ? i- 9
1 * .3 X - .4
S «• .7 5 - .8
June 2 3- July 3,
Perimeter Traps Interior Traps
(24) (25)
£ - 47 I - 31
f " 2 X* 1.2
S « 2.05 S « 2-4
1977
1977
1977
1977
-------
APPENDIX TABLE 18.8. OTHER BEETLES (continued)
PLOT
PLOT
PLOT
PLOT
A (Control)
Total Traps
(49)
Z - 3
X - .06
S - .2
B (Low)
Total Traps
(49)
Z - 6
X - .1
S - .3
C (Medium)
Total Traps
(49)
Z - 8
X - .2
S - .4
D (High)
Total Traps
(49)
Z - 9
X - .2
S = .4
ZAPS I
Perimeter Traps
(24)
Z - 1
X - .04
S - .2
Perimeter Traps
(24)
E - 5
X - .2
S - .4
Perimeter Traps
(24)
1-4
X - .2
S = .4
Perimeter Traps
(24)
I » 5
X - .2
S - .4
September 11-21, 1977
Interior Traps
(25)
Z - 2
X - .08
S - .3
September 11-21, 1977
Interior Traps
(25)
Z - 1
X - .04
S - .2
September 11-21, 1977
Interior Traps
(25)
1 - 4
X - .2
S - .4
September 11-21, 1977
Interior Traps
(25)
Z - 4
X> .2
S - .4
PLOT A (Control)
Total Traps
(49)
. z - 10
X - .2
S - .5
PLOT B (Low)
Total Traps
(49)
Z - 7
X - .1
S - .4
PLOT C (Medium)
Total Traps
(49)
Z - 8
X - .2
S - .5
PLOT D (High)
Total Traps
(49)
Z - 2
X = .04
S - .2
ZAiS 11
Perimeter Traps
(24)
Z - 7
X • .3
S - .6
Perimeter Traps
(24)
Z - 4
X - .2
S - .5
Perimeter Traps
(24)
Z - 3
X - .1
S - .5
Perimeter Traps
(24)
Z - 0
X - 0
S - 0
September 10-20,
Interior Traps
(25)
Z - 3
X - .1
S - .3
September 10-20,
Interior Traps
(25)
Z - 3
X - .1
S - .3
September 10-20,
Interior Traps
(25)
Z - 5
X - .2
S - .6
September 10-20,
Interior Traps
(25)
Z - 2
X - .08
S = .3
1977
1977
1977
1977
-------
APPENDIX TABLE 18.9. CHI-SQUARE GOODNESS OF FIT FOR PITFALL CAPTURE OF CANTHON SP. AT ZAPS, 1977
to
to
ZAPS I
N.S.
ABCD
AB
A C
A D 1.66
BC 0.10
B D
CD
ZAPS II
ABCD
AB
A C
A D
BC
B D
CD
ZAPS I
M.S.
ABCD
AB
A C
A D
BC 2.95
B D
CD
ZAPS II
ABCD
AB
A C
A D
BC 2.01
B D 1.45
CD 0.05
MAY
Total X2
P <0.05 P <0.005 N.S.
80.79
30.04
33.48
0.56
0.30
45.65
49.86
70.67
5.54
8.37
26.92
27.42 0.78
8.08 2.44
64.84 0.46
JUNE- JULY
Total X2
P <0.05 P <0.005 N.S.
215.43
163.88
123.54
22.43
66.00
41.19
270.36
135.82
169.93
164.60
0.19
Interior X2
P <0.05 P <0.005
36.90
12.98
17.13
18.86
23.78
24.13
19.82
12.83
8.48
9
Interior X
P <0.05 P <0.005
322.27
20.33
73.65
316.12
17.20
193.40
104.05
705.92
271.13
351.07
282.09
10.26
7.71
SEPTEMBER
ZAPS I Total X2 Interior X2
N.S, P <0.05 P <0.005 U.S. P <0.05 P <0.005
ABCD 40.90 9.00
AB 18.26 5.4
A C 33.40 5.4
A D 5.45 2.00
BC 2.88 0.00
B D 4.05 1.00
CD 3.57 1.00
ZAPS II
ABCD 28.13 17.85
AB 19.88 0.07
A C 9.91 3.27
A D 17.14 14.67
BC 1.82 2.38
B D 0.11 14.23
CD 1.04 5.76
-------
SECTION 19
EFFECTS OF CONTROLLED LEVELS OF S02
ON INVERTEBRATE CONSUMERS
J. W. Leetham, T. J. McNary and J. L. Dodd
ABSTRACT
Presented in this section are summarizations to
date of the various studies of the effects of chronic,
low level S02 exposure on the invertebrate consumers
in the ZAPS plots. Included are season summaries for
the 1975 and 1976 field censusing for aboveground
arthropods, soil macroarthropods and microarthropods,
results of the single mid-season samplings for soil
microarthropods (1977), nematodes (1976, 1977),
tardigrades (1977) and rotifers (1977), and summary of
the intensified studies on grasshoppers. A majority
of the groups discussed failed to show substantial
population level treatment responses. However, popu-
lation reductions with increasing S02 were noted in
the Coleoptera families, Curculionidae and Carabidae,
and the Lepidoptera family, Pyralidae (larvae), and
grasshopper adults (Acrididae). Also, population
reductions were noted in the high treatment plots in
both ZAPS for both the tardigrades and rotifers. The
soil microarthropods showed highest populations in the
medium and low treatment plots with the lowest popula-
tions under the pipe orifaces of the high treatment
(1977 data only). Controlled feeding trials in
laboratory cages showed two grasshopper species,
Aulooopa elllotti, and Agenotettix deovumy selectively
rejected western wheatgrass (Agvopyvon smitkii) that
had been previously exposed to S02 on the high ZAPS
treatment.
723
-------
BIOMASS AND POPULATION DYNAMICS
OF INVERTEBRATE FAUNA
The total arthropod fauna on the control and all treatments of both ZAPS
sites was censused during the 1975 and 1976 growing seasons (1976 only for
ZAPS II). The sampling techniques used were the same as those used at the
Colstrip sites during 1974 and 1975 (Section 2).
Six samplings for each of the aboveground arthropods, soil macroarthro-
pods, and microarthropods were taken in each of the two growing seasons, 1975
and 1976. Only the last four samplings for the soil macroarthropods were
used in 1975 because of previously described sampling problems (see Colstrip
section). Also, one intensified sampling was made for soil microarthropods
in 1977. In that sampling, the number of samples per replicate was doubled
to 10 per replicate from that in previous years samplings. An additional set
of samples was taken beneath the pipe orifaces on the high concentration
treatments on both ZAPS I and II.
The purpose of sampling the arthropod fauna was to attempt-to detect
major population or community-level changes in the fauna on the field plots
as a result of exposure to the various S02 concentrations. These changes
could be the result of direct toxicity of the S02, repellent effect of the
S02, or indirect effects arising from changes in other ecosystem components.
Emphasis here is placed on effects on the trophic structure of the arthropods,
The data have not been statistically analyzed for significant population
changes.
Aboveground Arthropods
Results of the sampling are presented for 1975 (Table 19.1) and 1976
(Table 19.2). The trophic groups do not show any indication of a treatment
response with the possible exception of plant tissue feeders on ZAPS I in
1975. However, the same trend is lacking in 1976 on both ZAPS I and ZAPS II.
The higher populations on ZAPS I in 1975 appear to be an artifact of the high
variability of the data.
Soil Macroarthropods
Of the three arthropod groups censused on the ZAPS sites, the most
apparent treatment responses were recorded among the soil macroarthropods.
Although total numbers and biomass did not reflect major treatment response
(Figure 19.1) definite population declines were noted for some constituent
families and one trophic group. Most of the major trophic categories failed
to show treatment responses (Tables 19.3 and 19.4); however, a sharp decline
in the number of predators with increasing S02 concentration was noted for
ZAPS I in 1975 and both ZAPS I and II in 1976, although the declines in ZAPS
II were not as sharp as in ZAPS I. The decline in total predators was
primarily a result of a similar decline in the largely predatory carabid
beetles (Coleoptera-Carabidae) represented by Harpalus desertus (primarily),
Axinopalpus biplagiatus, and Berribidion nitidum (Figure 19.2, Table 19.5). A
724
-------
TABLE 19.1. ABOVEGROUND ARTHROPODS ON ZAPS I FOR 1975'
Sample
date
Control
Low
Medium
High
Unknown
20 April
17 May
12 June
10 July
4 August
17 September
Mean
20 April
17 May
12 June
10 July
4 August
17 September
Mean
20 April
17 May
12 June
10 July
4 August
17 September
Mean
20 April
17 May
12 June
10 July
4 August
17 September
Mean
0.4
0.4
0.9
0.3
6.0
0.0
1.3
115.4
124.6
59.8
87.0
334.5
39.3
130.1
1.9
2.8
37.3
30.7
16.1
23.3
18.7
3.1
0.7
1.6
9.2
6.8
1.7
3.8
0.3
2.6
0.2
0.3
0.6
0.0
0.7
Plant Tissue Feeders
45.8
41.9
45.2
64.9
97.7
53.7
58.2
Plant Sap Feeders
4.5
4.8
43.2
23.0
7.6
9.4
15.4
Plant Pollen Feeders
1.5
0.2
0.6
16.2
5.8
0.6
4.2
1.9
1.0
0.3
1.1
2.6
1.2
68.7
91.1
70.2
97.5
44.8
76.5
74.8
6.8
5.8
57
22
10.0
3.6
1
,5
17.6
1.9
0.6
1.0
12.8
0.1
1.2
2.9
0.2
0.5
1.6
:0.1
1.3
0.0
0.6
56.8
84.9
63.5
157.4
65,
79,
84.5
11.4
5.2
59.7
36.2
16.9
3.0
22.1
1.3
0.6
0.5
16.2
0.0
1.6
3.4
725
-------
TABLE 19.1. CONTINUED
Sample
date
20 April
17 May
12 June
10 July
4 August
17 September
Mean
20 April
17 May
12 June
10 July
4 August
17 September
Mean
20 April
17 May
12 June
10 July
4 August
17 September
Mean
20 April
17 May
12 June
10 July
4 August
17 September
Mean
Control
7.1
5.5
5.1
17.5
2.6
0.8
6.4
5.6
12,9
35.3
22.5
8.9
15.1
16.7
5,3
15.3
9.4
2.4
1.5
13.1
7.8
0.0
0.0
60.5
0.6
0.0
0.0
10.2
Low
Predators
11.7
4.2
3.6
14.0
22.3
0.7
9.4
Omnivores
6.0
20.4
35.6
17.5
10.5
18.2
18.0
Scavengers
8.2
28,1
7.7
13.0
4.1
0.8
10,3
Nonfeeding
0,0
0,0
158.5
3.7
0.0
0,0
27.0
Medium
6.5
15.2
6.6
19.3
21,7
2.5
12.0
0,6
34.1
17.6
5.8
0.5
4.0
10,4
10,2
8.5
5,2
3.8
1-6
8.0
6.2
0,0
0,0
59.9
0.6
0,0
0.0
10.1
High
8.7
5.4
3.2
24.2
2.0
5.7
8.2
2.2
25*2
70.5
8.8
36.6
2,0
24.2
5.4
18.3
8.5
4.8
0.3
8.5
7.6
0.0
0.0
69.3
0.0
0.0
0.0
11.5
Biomass (mg • m"2) data are given by sample date and
season mean.
726
-------
TABLE 19.2. ABOVEGROUND ARTHROPODS ON ZAPS I AND ZAPS II FOR 1976*
Sample
ZAPS I
date Control
Low
Medium
High
Sample
date Control
ZAPS II
Low
Medium
High
Plant Tissue Feeders
22 March
17 May
15 June
10 July
9 August
6 September
Mean
22 March
17 May
15 June
10 July
9 August
6 September
Mean
22 March
17 May
15 June
10 July
9 August
6 September
Mean
53.5
45.1
52.7
44.1
62.3
41.2
49.8
2.7
14.3
22.4
53.0
29.3
6.9
21.4
0.6
1.7
22.0
1.7
9.7
0.3
6.0
59.
36.
37.
53.
45.
66.
49.
3.
16.
16.
25.
25.
4.
15.
0.
0.
1.
3.
0.
0.
1.
4
6
8
6
1
5
9
7
4
9
3
7
8
5
2
9
5
0
6
3
1
70.4
32.4
43.2
48.1
77.7
25.9
49.6
3.3
20.6
13.7
18.8
14.2
3.7
12.4
0.2
0.6
0.4
4.2
1.8
0.3
1.3
110.5
22.4
63.7
48.1
49.6
71.9
61.0
Plant
2.7
18.9
18.2
33.9
19.8
4.0
16.3
Plant
0.5
0.9
21.5
15.0
2.7
<0.1
6.8
24
21
20
14
13
11
March 142.4
May
June
July
August
September
51.2
33.2
48.9
74.8
93.2
74.0
117.4
73.4
61.7
53.3
87.4
69.2
77.1
124.7
44.5
55.5
79.4
109.1
63.2
79.4
80.3
27.4
32.2
62.1
45.2
88.3
55.9
Sap Feeders
24
21
20
14
13
11
March
May
June
July
August
September
1.6
8.2
12.8
19.8
13.3
12.8
11.4
1.8
19.2
17.0
12.5
22.6
6.8
13.3
2.2
6.4
14.3
8.3
11.5
6.1
8.1
0.7
9.5
10.2
15.0
17.6
7.0
10.0
Pollen Feeders
24
21
20
14
13
11
March
May
June
July
August
September
0.6
0.4
0.8
2.1
9.2
0.6
2.3
0.6
0.9
2.1
5.0
8.9
0.2
3.0
1.1
0.6
1.3
0.2
1.8
1.2
1.0
0.2
1.3
2.3
14.6
3.0
<0.1
3.6
-------
TABLE 19.2. CONTINUED
00
Sample
ZAPS I
date Control
22 March
17 May
15 June
10 July
9 August
6 September
Mean
22 March
17 May
15 June
10 July
9 August
6 September
Mean
22 March
17 May
15 June
10 July
9 August
6 September
Mean
9.1
7.2
10.7
20.3
17.9
4.6
11.6
0.3
21.1
36.4
26.3
2.6
0.0
14.5
21.6
1.9
3.4
2.7
3.4
0.2
5.5
Low
7.0
10.6
12.9
8.6
12.6
1.9
8.9
0.1
18.9
32.4
22.8
0.9
2.3
12.9
2.0
2.0
2.4
1.0
2.4
4.7
2.4
Medium
20.2
11.3
17.4
13.6
15.7
2.3
13.4
0.5
52.5
22.2
20.5
8.9
0.0
17.4
4.2
4.4
6.7
1.5
4.2
0.8
3.6
High
21
5
25
16
11
3
14
0
26
39
9
2
0
12
15
0
0
3
1
<0
3
Predators
.1
.7
.8
.9
.0
.3
.0
Omnivores
.0
.2
.0
.6
.4
.0
.9
Scavengers
.9
.8
.0
.1
.6
•1
.6
Sample
date Control
24
21
20
14
13
11
24
21
20
14
13
11
24
21
20
14
13
11
March
May
June
July
August
September
March
May
June
July
August
September
March
May
June
July
August
September
7.3
19.8
11.4
11.3
7.2
4.7
10.3
0.3
10.0
20.9
20.1
5.6
0.0
9.5
8.5
2.3
7.8
2.8
6.4
2.8
5.1
ZAPS
Low
5.8
29.4
11.0
10.7
14.3
2.8
12.3
1.1
36.8
36.6
12.5
9.5
0.0
16.1
21.3
8.2
22.8
6.6
12.5
8.5
13.3
II
Medium
16.4
19.9
13.6
5.2
12.2
2.3
11.6
0.4
32.7
42.5
5.3
5.3
0.9
14.5
51.9
18.1
4.5
3.3
14.7
3.7
16.0
High
5.1
14.3
5.2
26.6
8.0
2.2
10.2
0.1
13.3
16.7
42.3
4.5
0.0
12.8
8.7
4.1
3.2
3.2
2.8
7.0
4.8
Biomass (mg • m~~2) data are given by sample date and season mean.
-------
second beetle family, Curculionidae, though not predatory, also showed a
decline in biomass with increased S02 exposure in both ZAPS I and II in 1976
(Table 19.6). The family was represented primarily by Hypexodes witt-LooHis-
and H. grypidioides; and secondarily by Smievonyx sp., Api-on sp., and
Epioaerus. A similar decline was noted in ZAPS I in 1975, i.e., 120, 50, 80,
and 40 mg • m~2 for control, low, medium, and high treatments, respectively.
The aforementioned declines in Carabidae and Curculionidae were responsible,
in large part, for a decline in total Coleoptera biomass with increasing S02
exposure (Figure 19.2, Table 19.5).
In 1975, grasshopper (Orthoptera-Acrididae) egg biomass was substan-
tially reduced in all S02 treated plots of ZAPS I (Figure 19.3). This was
originally interpreted as indicative of decreased oviposition on the treated
plots.
However, the 1976 data (not given) for both ZAPS I and II failed to
substantiate this. Grasshopper population studies were intensified in 1976,
and those results are detailed in the section entitled The Effect of Chronic
S02 Air Pollution on Acrididae (Grasshoppers) Population Dynamics and
Behavior.
4-1
Numbers
|""l Biomass
CM
E
CJ* "2 __
>_x O
O
CD 2-
oT°
g
X
^ \-
1
JUMBERS,
O
i
fi^m^^m
: : ;
rrr
• • •
^^
^^•^^
; ; !
• • •
Control Low Medium High
TREATMENTS
Figure 19.1. Total soil microarthropod numbers and biomass on four S02
fumigation treatments on the ZAPS I site for 1975 (based on
time-weighted means of the four post treatment samplings).
729
-------
TABLE 19.3. SOIL MACROARTHROPODS ON ZAPS I FOR 1975
Sample
date
13 June
23 July
6 August
17 September
Mean
13 June
23 July
6 August
17 September
Mean
13 June
23 July
6 August
17 September
Mean
13 June
23 July
6 August
17 September
Mean
13 June
23 July
6 August
17 September
Mean
Control
60.5
363.0
400.3
619.4
360.8
0.0
746.9
35.4
70.7
213.3
121.6
0.0
40.7
142.3
76.2
74.5
235.7
258.1
10.9
144.8
20.7
65.0
356.4
23.1
116.3
_ i
Low Medium
Root Tissue Feeders
269.0
7,299.5
423.9
970.3
2,240.7
Root Sap Feeders
0.0
0.0
21.2
28.3
12.4
Plant Tissue Feeders
106.9
0.0
0.0
149.0
64.0
Predators
122.4
0.0
242.5
79.1
111.0
Omnivores
23.1
6.6
17.2
0.0
11.7
184.0
669.4
558.4
654.3
516.8
0.0
0.0
106.1
99.0
51.3
30.4
0.0
10.7
148.1
47.3
66.4
55.7
161.2
140.6
106.0
131.1
0.0
362.0
0.0
123.3
High
451.6
192.8
338.9
1,080.7
516.0
241.9
49.5
56.6
169.8
129.4
99.1
0.0
7.9
28.5
33.9
56.1
115.8
20.8
57.2
62.5
244.4
0.0
12.0
0.0
64.1
730
-------
TABLE 19.3. CONTINUED
Sample
date Control Low Medium
High
Nonfeeding
13 June
23 July
6 August
17 September
Mean
301.1
423.5
68.9
0.0
198.9
201.5
380.1
633.1
r- 97.4
328.0
331.4
741.9
348.8
0.0
355.5
246.6
263.1
58.8
114.2
170.7
it
Biomass (mg • m~2) data are given by sample date and season
mean.
One other macroarthropod group appeared to decline under S02 exposure in
1976. The plant-chewing Crambus sp. (Lepidoptera-Pyralidae) generally had
lower populations in the treated areas in both ZAPS except for the high
treatment of ZAPS I. The data for ZAPS II appear to be in strong support of
the hypothesis that the S02 is causing population reductions in this and
other arthropod groups.
The data for all the aforementioned groups include both adults and
immatures. Therefore, the mechanism by which the S02 caused the population
declines could be one or more of the following: (1) The S02 could act as a
noxious repellent to the active adults, causing them to leave the treated
areas and keeping others from entering. (2) In the case of predatory types,
the prey items could be repelled as in (1). (3) Plant-feeding adults might
be repelled by vegetation contaminated by deposited sulfur salts. (4) The
S02 could be directly toxic to the insects. (5) The S02 could be indirectly
detrimental to immature development through such mechanisms as reduced forage
quality. Future studies will address these various possibilities.
Soil Microarthropods
From a qualitative evaluation of the data for both years and both ZAPS
areas, no obvious treatment response has been observed for any trophic or
taxonomic group although most all family-level data are yet to be evaluated.
A slight treatment result was thought to be observed in the changing percent
composition by major suborders of the total acarines on ZAPS I in 1975
(Figure 19.4). There was a decrease in Prostigmata with a corresponding
increase in Cryptostigmata with increased S02 concentration. However, this
trend was not observed for either ZAPS I or II in 1976 (Tables 19.7 and
19.8). There do not appear to be any major changes in intraseasonal dynamics
of the soil microarthropods as exemplified in Figures 19.5 to 19.13. Further
731
-------
TABLE 19.4. SOIL MACROARTHROPODS ON ZAPS I AND II FOR 1976
(jO
Sample
date
Control
ZAPS
Low
I
Medium
Sample
High
date
Control
ZAPS II
Low
Medium
High
Root Tissue Feeders
21 March
17 May
15 June
10 July
9 August
7 September
Mean
21 March
17 May
15 June
10 July
9 August
7 September
Mean
21 March
17 May
15 June
10 July
9 August
7 September
Mean
0.0
681.8
1030.6
841.7
792.6
160.9
584.6
0.0
0.0
0.0
28.3
0.0
84.9
18.9
56.9
0.0
9.9
0.0
125.5
24.7
36.2
137.7
1062.4
468.9
250.4
181.2
610.0
451.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
56.9
0.0
104.2
229.6
550.7
138.9
180.0
344.9
634.3
1169.7
461.2
178.8
80.5
478.2
0.0
0.0
0.0
42.4
0.0
0.0
7.1
28.5
0.0
0.0
0.0
56.3
229.6
52.4
1097
1436
553
292
296
114
631
Root
0
0
0
70
725
0
132
Plant
22
133
0
124
116
0
66
.6
.1
.1
.3
.9
.5
.8
Sap
.0
.5
.0
.7
.7
.0
.8
23
21
20
14
13
11
Feeders
23
21
20
14
18
11
March
May
June
July
August
September
March
May
June
July
August
September
389.6
563.6
600.2
310.4
354.6
19.4
373.0
0.0
0.0
0.0
0.0
141.5
0.0
23.6
0.8
890.8
590.2
108.8
487.0
25.6
350.4
0.0
0.0
0.0
99.0
84.9
0.0
30.6
403.2
433.5
328.5
222.5
17.1
17.1
237.0
0.0
0.0
0.0
113.2
70.7
0.0
30.6
387.0
247.2
383.5
201.4
17.1
6.0
206.0
0.0
0.0
0.0
0.0
28.3
0.0
4.7
Tissue Feeders
.8
.6
.0
.1
.9
.0
.2
23
21
20
14
13
11
March
May
June
July
August
September
298.0
0.0
1052.0
574.0
1291.2
400.3
602.6
515.5
229.6
358.6
803.6
803.6
142.3
475.5
491.2
344.4
344.4
344.4
230.0
344.4
349.8
286.8
0.0
0.0
230.0
0.0
516.1
172.2
-------
TABLE 19.4. CONTINUED
U)
Sample
date
Control
ZAPS
Low
I
Medium
High
Sample
date
ZAPS II
Control
Low
Medium
High
Predators
21 March
17 May
15 June
10 July
9 August
7 September
Mean
260.0
506.7
633.3
263.1
83.2
483.2
371.7
105.0
316.7
268.9
126.8
4.8
166.5
164.8
0.0
41.6
0.0
380.0
124.9
334.8
146.9
0.
0.
0.
41.
0.
41.
13.
0
0
0
6
0
6
9
23
21
20
14
13
11
March
May
June
July
August
September
126.7
1244.9
380.0
570.0
778.1
503.1
600.5
194.8
484.9
190.0
506.7
190.0
336.6
317.2
378.7
273.2
321.1
168.3
273.2
126.7
256.9
363.5
443.3
253.3
743.1
253.3
63.3
353.3
Omnivores
21 March
17 May
15 June
10 July
9 August
7 September
Mean
0.0
12.8
32.9
1310.2
3.1
0.0
226.5
551.7
0.0
239.6
50.7
0.0
0.0
140.3
702.4
1592.8
164.9
22.0
0.0
0.0
413.7
0.
0.
9.
41.
0.
0.
8.
0
0
5
2
0
0
45
23
21
20
14
13
U
March
May
June
July
August
September
0.0
0.0
120.8
18.7
0.0
0.0
23.2
0.0
244.1
3.2
98.8
0.0
0.0
57.7
0.0
0.0
0.0
117.2
0.0
0.0
19.5
0.0
0.0
9.5
0.0
0.0
0.0
1.6
Scavengers
21 March
17 May
15 June
10 July
9 August
7 September
Mean
0.0
69.1
152.7
149.9
0.0
0.0
62.0
69.1
138.2
0.0
0.0
0.0
0.0
34.6
0.0
' 236.3
0.0
5.8
0.0
0.0
40.4
0.
0.
0.
29.
0.
0.
4.
0
0
0
3
0
0
9
23
21
20
14
13
11
March
May
June
July
August
September
69.1
36.2
7.2
51.6
0.0
0.0
27.4
138.2
145.4
83.6
0.0
17.6
0.0
64.1
169.5
14.5
0.0
5.8
0.0
0.0
31.6
276.4
0.0
0.0
7.2
5.8
0.0
48.2
Biomass (mg • m"~2) data are given by sample date and season mean.
-------
CD Predators
El Coleoptera-Carabidae
D Coleoptera (total)
100-
NUMBERS/mz
£88
i i i
20-
•••
5
^
•••
*
Control
—
• •
v^
^
"
0.5-
^
^0.4-
E
^ 0.3-
CO
p < 02-
o
CD 0.1-
:rs
i • -i^ s\
'• '•
^
^
'• '•
__ _
~r
\
\
TV
* "
^
\
Ijjb
Low Medium High u Control Low Medium Hig
TREATMENTS
h
Figure 19.2.
Numbers and biomass of predators, Coleoptera-Carabidae, and
total Coleoptera on four S02 fumigation treatments on the ZAPS I
site for 1975 (based on time-weighted means of the four post
treatment samplings).
734
-------
TABLE 19.5. BIOMASS (MG • M~2) OF TOTAL COLEOPTERA AND FAMILY CARABIDAE (COLEOPTERA) FOR 1976
Go
Ln
Sample
date
ZAPS I
Control
Low
Medium
High
Sample
date
ZAPS II
Control
Low
Medium
High
Order Coleoptera
21 March
17 May
15 June
10 July
9 August
7 September
Mean
21 March
17 May
15 June
10 July
9 August
7. September
Mean
316
506
1176
526
138
384
508
259
506
633
194
—
316
318
.4
.7
.9
.6
.9
.1
.3
.5
.7
.3
.8
.7
.5
258.0
492.0
534.3
446.8
618.5
164.5
419.0
63.3
316.7
253.3
356.3
464.0
—
242.3
95.4
85.4
1096.8
497.8
64.8
364.8
367.5
_ _
—
— —
380.0
—
356.3
122.7
153.7
446.3
45.4
138.3
125.4
17.1
154.4
Family
__
114.8
— —
114.8
—
—
38.3
23
21
20
14
13
11
March
May
June
July
August
September
424.6
1336.0
1816.7
1423.7
1861.2
673.1
1255.9
710.3
687.1
749.2
419.0
993.6
421.2
830.1
1052.4
967.9
899.4
621.1
436.7
488.1
744.3
603.5
680.2
636.8
1111.6
270.4
579.4
647.0
Carabidae
23
21
20
14
13
11
March
May
June
July
August
September
241.5
1203.3
1413.2
1144.0
1832.8
482.9
1053.0
654.0
672.9
534.4
1310.2
993.6
253.3
736.4
780.6
534.4
694.9
471.1
419.6
471.1
562.0
546.3
443.3
253.3
931.1
253.3
522.5
491.6
-------
TABLE 19.6. BIOMASS (MG • M~2) DATA FOR COLEOPTERA AND LEPIDOPTERA, ZAPS I AND II IN 1976
U)
Sample
date
ZAPS I
Control
Low
Medium
High
Sample
ZAPS II
date Control
Low
Medium
High
Order Coleoptera (Family Curculionidae)
21 March
17 May
15 June
10 July
9 August
7 September
Mean
56.
—
31.
248.
90.
—
71.
9
2
5
2
1
56.9
—
15.6
62.1
88.6
28.5
42.0
28.5
—
—
46.7
28.5
—
17.3
15.9
18.8
31.2
—
113.8
—
30.0
23
21
20
14
13
11
March
May
June
July
August
September
—
—
80.9
248.5
28.5
170.7
88.1
56.3
—
186.3
108.8
—
142.3
82.3
__
—
62.1
93.2
—
—
25.9
25.2
—
46.7
62.1
—
56.9
31.8
Order Lepidoptera (Family Pyralidae)
21 March
17 May
15 June
10 July
9 August
7 September
Mean
584.
681.
487.
584.
779.
97.
535.
4
8
0
4
2
4
7
389.6
876.6
292.2
97.4
97.4
584.4
389.6
194.8
487.0
—
—
97.4
—
129.9
1168.8
1071.4
487.0
194.8
194.8
97.4
535.7
23
21
20
14
13
11
March
May
June
July
August
September
389.6
389.6
194.8
—
292.2
— —
211.0
39.5
876.6
389.6
—
487.0
—
298.8
194.8
—
97.4
—
—
—
48.7
487.0
—
—
—
—
—
81.2
-------
data analyses, including statistical analyses, may reveal some treatment
responses not yet noted.
The data for 1977 again fail to show substantial population changes in
either ZAPS system (Tables 19.9 and 19.10). However, in both plots, the
highest total populations were observed in the medium concentration plots of
both ZAPS with the low in ZAPS I and low and high concentrations in ZAPS II
showing populatibns higher than the controls. The populations in the extra
high treated areas were at or below control levels. It is difficult to
ascribe these changes to S02 exposure since the general acarine population
(which makes up 90% and over of the total) remains proportionately the same
for each suborder with the possible exception of ZAPS I where the percent of
Prostigmata declined in the high and extra high treatments along with
increases in the Mesostigmata and Cryptostigmata. The trophic structure is
essentially constant across the treatments. The proportionate structure (by
suborder) of the acarines is also the same as those given for 1976 (Tables
19.7 and 19.8). The soil microarthropods are definitely responding very
slowly, if at all, to the S02 treatments.
Cn
en
<
o
GO
ro
O
X
CM
cr
LU
oo
0.02-
°-0'-
03 Numbers
D Biomass
f. Low Med. High
TREATMENTS
Figure 19.3. Numbers and biomass of grasshopper eggs on four S02 fumigation
treatments on the ZAPS I site for 1975 (based on time-weighted
means of the four post treatment samplings) .
737
-------
THE EFFECT OF CHRONIC S02 AIR POLLUTION
ON ACRIDIDAE (GRASSHOPPERS) POPULATION
DYNAMICS AND BEHAVIOR
During the 1977 field season, grasshopper reactions to the S02
on the ZAPS site were observed in three separate experiments, ine
experiment was a censusing of the grasshoppers on each treatment. The secona
experiment, or feeding preference test, was performed to determine the effect
of sulfur compounds in and on plants exposed to S02 on feeding by seiectea i
species of grasshoppers. A third experiment was conducted to determine tna
effect of S02 on fecundity and survival in Aulooara *llu>tto, (Thomas) (big-
headed grasshopper) by establishing caged test populations on the control and
high treatments of ZAPS I. The latter two experiments were designed to help
explain treatment effects observed in the grasshopper census.
100-
80-
co 60-
(T
LU
m
| 40-
2:
20-
O-
in
\
\
\
\
\
•MM
F
\
\
\
_
fs
\
-
•«•
-
—
"^
\
\
\
\
CO "
CO
2
O -
CD
•M
QMesostigmata
QCryptostigmata
DProstigmata
•
H5
:\
:\
:\
:\
: \
:\
:\
MM
J
***•"
^
r\
::\
::N
_
(T1
\
\
\
\
\
\
-
f^
r" \
:\
;\
:\
:\
:\
:\
Control Low Medium High Control Low Medium High
TREATMENTS
Figure 19.4.
Composition, by suborders of total soil Acarina using numbers
and biomass on four S02 fumigation treatments on ZAPS I site in
1975 (based on season time-weighted means). Total numbers of
soil Acarina/m2 for control, low, medium, and high treatments
were 86,081.5, 82,194.8, 73,315.5, and 73,254.3, respectively.
Total biomass for control, low, medium, and high treatments were
36.0, 28.7, 27.5, and 33.6 mg • m"2, respectively.
738
-------
TABLE 19.7. TIME WEIGHTED SEASONAL MEANS AND PERCENT COMPOSITION FOR SOIL MICROARTHROPODS'
Co
Season mean
(number • m~2)
Group
Total Acarina
Astigmata
Cryptostigmata
Prostigmata
Me so stigmata
Total
microarthropods
Acarina (% of
total)
% Astigmata
% Cryptostigmata
% Prostigmata
% Mesostigmata
Trophic groups
Fungivores
Unknown
Plant sap feeders
Predators
Scavengers
Nonfeeding stage
A
112,329
515
18,047
87,900
5,867
144,557
77.7
0.4
16.1
79.2
5.2
57,809
33,656
39,939
19,176
304
24
B
119,482
908
11,736
100,875
5,963
139,476
85.7
0.8
9.8
84.4
5.0
39,600
27,322
54,668
22,111
571
39
C
155,239
1,454
20,974
126,378
6,433
177,914
87.2
0.9
13.5
81.4
4.1
55,933
32,725
70,334
23,569
313
71
D
123,568
698
11,784
104,358
6,728
144,341
85.6
0.6
9.5
84.4
5.4
49,822
45,655
42,085
18,543
195
146
A
46.50
0.39
12.55
19.83
13.73
81.73
56.9
0.8
27.0
42.6
29.5
42.46
577.91
10.54
22.50
0.01
0.01
Season mean
(mg • m~2)
B
38.04
0.68
5.80
21.88
9.68
62.81
60.6
1.8
15.2
57.5
25.4
23.59
400.32
10.15
24.22
0.02
0.01
C
49.25
1.09
12.36
27.17
8.63
78.15
63.0
2.2
25.1
55.2
17.5
32.05
459.24
15.19
24.47
0.01
0.02
D
42.69
0.47
6.63
22.08
13.51
68.01
62.8
1.1
15.5
51.7
31.6
26.73
1096.78
9.63
24.32
0.01
0.04
t
ZAPS I, 1976 (A = Control, B = Low, C = Medium, D = High).
Suborders are % of total Acarina.
-------
TABLE 19.8. TIME WEIGHTED SEASONAL MEANS AND PERCENT COMPOSITION FOR SOIL MICROARTHROPODS'
Season mean
(number • m~2)
Group
Total Acarina
Astigmata
Crypto stigmata
Prostigmata
Me so stigmata
Total
microarthropods
Acarina (% of
total)
% Astigmata
% Crypt os tigmata
% Prostigmata
% Me so stigmata
Trophic groups
Fungivores
Unknown
Plant sap feeders
Predators
Scavengers
Nonfeeding stage
A
118,256
1,428
16,988
94,605
5,235
143,998
82.1
1.2
14.4
80.0
4.4
56,942
15,058
55,806
19,733
200
48
B
103,657
589
5,866
81,749
5,453
134,401
77.1
0.6
15.3
78.9
5.3
57,995
12,758
47,485
19,052
654
18
C
155,583
1,207
25,168
122,800
6,408
182,217
85.4
0.8
16.2
78.9
4.1
73,462
15,854
73,370
24,279
590
14
D
129,200
1,367
21,318
101,211
5,304
160,908
80.3
1.0
16.5
78.3
4.1
63,593
13,465
70,543
20,035
357
53
A
44.96
1.08
14.09
21.04
8.75
70.69
63.6
2.4
31.3
46.8
19.5
37.33
344.38
12.86
17.31
0.01
0.01
Season mean
(mg • m~2)
B
38.18
0.45
9.30
17.97
10.46
69.26
55.1
1.2
24.4
47.1
27.4
35.58
322.86
12.58
18.74
0.03
0.01
C
54.27
0.93
18.72
26.02
8.60
82.98
65.4
1.7
35.5
47.9
15.8
43.69
484.50
15.92
20.63
0.02
>0.00
D
45.98
1.03
16.26
22.01
6.68
83.77
54.9
2.2
35.4
47.9
14.5
40.90
644.72
22.58
18.12
0.01
0.02
ZAPS II, 1976 (A = Control, B = Low, C - Medium, D = High).
Suborders are % of total Acarina.
-------
CM
i
o
OD
to
O
CM
^
CO
cr
UJ
en
[^Initiation of S02 Fumigation
Control
Low
Medium
High
18 Apr 16 May ISJun 17 Jul IIAug 19 Sep
SAMPLING DATES
Figure 19.5. Total soil microarthropod biomass and numbers on four S02
fumigation treatments on the ZAPS I site for 1975 (six sample
dates).
741
-------
CM
00
00
o
00
75
50
25
CM
250,000
200,000
150,000
100,000
50,000
Control
Low
Medium
High
Mar Apr May Jun Jul Aug Sep
Figure 19-6. Seasonal dynamics of soil Acarina on ZAPS I, 1976,
742
-------
OJ
75
50
V)
<
s
O
CD
Control
Low
Medium
250,000
cv. 200,000
cr
W 150,000
100,000
5QOOO
•\\\\
Mar Apr May Jun Jul Aug Sep
Figure 19.7. Seasonal dynamics of soil Acarina on ZAPS II, 1976,
743
-------
50
CM
O>
CO
CO
<
2
g
GO
25
0
100
- 75
10
O
C\J
^
CO
LJ
oo
50
I 25
of S02 Fumigation
Control
Low
Medium
High
18 Apr 16 May !5Jun !7Jul IIAug 19 Sep
SAMPLING DATES
Figure 19.8,
Biomass and numbers of the soil microarthropod trophic group,
fungivore, on four S02 fumigation treatments on the ZAPS I site
for 1975 (six sample dates).
744
-------
100
-------
100 r
04
C/)
<
s
g
GO
50
Control
Low
Medium
—High
« 100,000
6
cr
Ul
CD
50,000
Mar Apr May Jun Jul Aug Sep
Figure 19.10. Seasonal dynamics of soil microarthropod fungivores on ZAPS II,
1976.
746
-------
50
CJ
o>
25
o
GO
0
30
ro
O
20
en
UJ
m
10
0
Initiation of SOg Fumigation
Control
— Low
Medium
High
/ /s-
I
18 Apr ISMay 15 Jun ITJul
SAMPLING DATES
I I Aug 19 Sep
Figure 19.11.
Biomass and numbers of the soil microarthropod trophic group,
predator, on four S02 fumigation treatments on the ZAPS I site
in 1975 (six sample dates).
747
-------
I
0)
o
QD
40
30
20
10
Control
• — Low
Medium
High
CSI
UJ
CD
40,000
30,000
20,000
10,000
Mar Apr May Jun Jul Aug Sep
Figure 19.12. Seasonal dynamics of soil microarthropod predators on ZAPS I,
1976.
748
-------
CO
<
s
o
CD
30
20
10
tr
UJ
CD
40,000
30,000
20,000
10,000
Control
— • — Low
Medium
High
Mar
Apr May
Jun
Jul
Aug Sep
Figure 19.13. Seasonal dynamics of soil microarthropods on ZAPS II, 1976
749
-------
TABLE 19.9. TAXONOMIC AND TROPHIC STRUCTURE OF THE SOIL MICROARTHROPODS ON ZAPS I ON 10 JULY 1977'
Ul
o
Numbers * m~2
Group
Total Acarina
Astigmata
Cryptostigmata
Prostigmata
Mesostigmata
Collembola
Total
microarthropods
Acarina (% of
total)
% Astigmata
% Cryptostigmata
% Prostigmata
% Mesostigmata
Trophic groups
Fungivores
Herbivores
Predators
Scavengers
A
119,615
995
13,705
99,665
5,250
2,321
124,008
96.0
0.8
11.5
83.3
4.4
22,492
71,951
22,132
28
140
2
15
116
5
2
145
24
93
17
B
,090
,432
,501
,272
,885
,404
,091
96.6
1.7
11.1
83.0
4.2
,509
,061
,712
28
C
177,033
2,017
23,873
143,018
8,124
2,653
182,504
97.0
1.1
13.5
80.8
4.6
32,080
119,394
24,094
83
D
89,939
276
13,042
68,525
8,096
2,432
94,111
95.6
0.3
14.5
76.2
9.0
22,713
43,022
22,713
166
E
122,406
1,326
20,530
87,038
13,512
3,813
128,733
95.1
1.1
16.8
71.1
11.0
29,455
57,721
30,560
884
A
46.5
0.8
9.9
21.6
14.2
2.2
52.0
89.4
1.7
21.3
46.6
30.5
14.0
14.2
21.7
<0.0
Mg - m'2
B
44.7
1.9
7.4
22.8
12.7
2.0
50.7
88.2
4.3
16.6
51.0
28.4
12.0
18.0
18.9
<0.0
C
64.9
1.5
16.8
31.3
15.3
1.8
71.0
91.4
2.3
25.9
48.2
23.6
20.8
24.4
24.0
<0.0
D
42.1
0.2
10.4
16.2
15.2
2.3
46.5
90.5
0.5
24.7
38.5
36.1
14.2
8.7
21.9
<0.0
E
55.8
0.6
14.1
20.4
20.7
3.0
61.0
91.5
1.1
25.3
36.6
37.1
18.3
10.1
29.5
<0.0
t
A = Control, B = Low, C = Medium, D =* High, E = Extra High,
Suborders are % of total Acarina.
-------
TABLE 19.10. TAXONOMIC AND TROPHIC STRUCTURE OF THE SOIL MICRO ARTHROPODS ON ZAPS II ON 7 AUGUST 1977'
Numbers • m 2
Group
Total Acarina
Astigmata
Cryptostigmata
Prostigmata
Mesostigmata
Collembola
Total
microarthropods
Acarina (% of
total)
% Astigmata
% Cryptostigmata
% Prostigmata
% Mesostigmata
Trophic groups
Fungivores
Herbivores
Predators
Scavengers
A
95,907
304
10,555
80,738
4,310
1,768
101,738
94.3
0.3
11.0
84.2
4.5
22,961
57,970
13,650
28
B
128,015
414
16,192
105,523
5,885
3,067
133,844
95.6
0.3
12.7
82.4
4.6
25,200
79,108
15,888
— •«.
C
170,594
332
20,585
141,112
8,566
7,571
203,309
83.9
0.2
12.1
82.7
5.0
37,247
138,707
22,796
" '
148
1
20
118
8
11
163
37
94
24
D
,710
,050
,309
,952
,400
,495
,824
90.8
0.7
13.7
80.0
5.7
,689
,830
,371
*"~™~
E
80,931
442
13,069
63,828
3,592
13,788
97,152
83.3
0.6
16.2
78.9
4.4
31,831
45,453
15,280
332
A
31.4
0.2
8.9
17.5
4.9
1.6
39.1
80.3
0.6
28.3
55.7
15.6
12.8
14.3
8.9
<0.0
Mg • m~2
B
46.6
0.3
14.4
22.5
9.3
2.3
53.3
87.3
0.6
30.9
48.3
20.0
18.2
15.9
14.0
™
C
63.5
0.3
17.0
28.0
18.2
5.5
108.5
58.5
0.5
26.8
44.1
28.7
24.7
57.2
24.6
__*
D
55.8
0.8
16.4
26.1
12.6
10.5
72.6
76.9
1.4
29.4
46.8
22.6
28.6
20.5
20.2
—
E
26.9
0.3
7.9
14.1
4.6
8.7
41.5
64.8
1.1
29.4
52.4
17.1
17.8
8.5
13.3
0.01
t
A = Control, B = Low, C = Medium, D = High, E = Extra High.
Suborders are % of total Acarina.
-------
Grasshopper Census
A census of the grasshopper populations was made on each treatment of
both ZAPS sites, starting in early May and continuing through August. The
census method used was one employed by the USDA-Plant Protection and Quaran-
tine Division to census outbreaks and make control recommendations for the
grasslands of eastern Colorado. This census method involved walking a
predetermined transect (see Figure 19.14) on each replicate and along this
line, 25 one-ft2 areas were observed for grasshoppers. Most identifications
were made to the species level with estimate of the instars observed. These
data have been converted to number per m2 by age of species (instar), species,
sub-family, and total count. The censuses were made in the morning, usually
between 9:00 a.m. and noon, on clear days when the wind was not excessive.
Censusing was done before other investigators had disturbed the treatments.
A census was made eight times on each ZAPS sites. The census dates were:
Position 25 J>
/
r(
7
/
/
(___
V
\
/
/
/
/
/
/
/
/
\
\
1
/
/
/
Position
13
/
[f, Position 1
° Position 25
\
\
\
\
/
/
I
V
\
\
^[
Position
13
jx - —
\
\
\
i
/
/
v ..
\
\
\
\
Position 1 Q
VJU5
Mixina
Figure 19.14. Route of transect used for the grasshopper census within a
given treatment plot.
752
-------
ZAP I ZAP II
10 May 1977 10 May 1977
24 May 1977 24 May 1977
7 June 1977 7 June 1977
15 June 1977 15 June 1977
24 June 1977 24 June 1977
7 July 1977 7 July 1977
22 July 1977 22 July 1977
3 August 1977 12 August 1977
Melanoplus sanquinvpes (Fab) was by far the most common grasshopper observed.
See Table 19.11 for the relative numbers of grasshoppers counted in the
census. Other species observed on the ZAPS sites that were not included in
the counts were M. biwitattus (Say), Dissostevia oarolina (Linnaeus), Metator
pardalinus (Saussare), and Spharagemon eollare (Scudder).
Statistical analysis has not yet been performed on the data, but the
trend is for decreasing numbers of grasshoppers with increasing S02 concentra-
tions (see Figure 19.15). Because the sample data have a non-normal distribu-
tion, they were pooled by replicate and the mean and standard error for a
treatment is based on a sample size of two. The greatest differences between
treatments were in the latter half of the season so it was thought that this
might be due to the adults (more mobile than nymphs) leaving the higher
concentration treatments, thereby decreasing the mean instar of the remaining
population; This was not observed (Figure 19.16). Thus, the differences
between treatments were either present before the beginning of the 1977
season or are the result of population decreases independent of age of
grasshoppers. Most likely the later season differences occur because of
differential oviposition during the previous years of fumigation as these
differences do not appear until the time of hatching. This is supported by
biomass sampling of grasshopper eggs in 1975 (Dodd et al. > 1977). Although
data are not yet compiled from the survival study, they should provide
further evidence for the support or rejection of this hypothesis. A second
hypothesis for explaining the trend toward fewer grasshoppers with increased
S02 is emigration from the fumigated treatments because of a decrease in food
quality or selectivity against S02-exposed food. The feeding preference
experiment lends some support to this.
Feeding Preference Test
This experiment was designed to test for an effect of chemical deriva-
tives of S02 deposited in and on plants on the feeding of grasshoppers.
There have been many studies on the food preference of grasshoppers, most
dealing with determining a preference for different species of plant as food,
A few have dealt with the influence of plant chemicals on food selection.
Thorsteinson and Nayar (1963) found that certain phospholipids in wheat
stimulated feeding by grasshoppers. In a later study, Harley and
Thorsteinson (1967) tested the reaction of Melanoplus bivittatus to 20
secondary plant chemicals. They found that the rejection of certain plant
chemicals may have been due to the chemical's form, with most salts being
rejected. This is important to this experiment because S02 is dissolved in
753
-------
TABLE 19.11. RELATIVE NUMBERS OF ACRIDIDAE OBSERVED ON THE
ZAPS SITES, SUMMER 1977
Acrididae species Number
Acridinae
Aevopedellus clavatus (Thomas) °
Ageneotettix deovwn (Scudder) ^
Amp'h'itornus oolovadus (McNeill) 2
Auloeapa elliott-i (Thomas) 2
Drepanoptevna femoratum (Scudder) 2
Eritettix simplex (Scudder) 34
Opeia dbscwpci (Thomas) 21
Total observed 152
Cyrtacanthacridinae
Melanoplus confusus (Scudder) 8
Melanoplus infantilis (Scudder) 1
Melanoplus paokcofdii (Scudder) 8
Melanoplus sanquinipes (Fabricius) 434
Phoetaliates nebvascensis (Thomas) 9
*
Total observed 473
Oedipodinae
Avphia pseudonietana (Thomas) 5
Spharaagemon equate (Say) 8
Traehyrhaehys kiowa (Thomas) 2
Xanthippus eovallipes (Haldeman) 1
*
Total observed 21
*
Total Acrididae observed 646
*
Totals include grasshoppers not identified to a species,
754
-------
CM
o:
iij
DO
I
0
8
Control
Low
Medium
High
ZAPS-I
0
ZAPS-H
May Jun Jul
1977
Aug
Figure 19.15. Seasonal dynamics of total Acrididae population by treatment
±1 SE.
755
-------
0
6
Control
Low
Medium
ZAPS-I
<
LU
ZAPS-IE
May
Jun Jul
1977
Aug
Figure 19.16. Seasonal dynamics of mean instar for Acrididae by treatment,
756
-------
the leaf to form sulfite S03 and then slowly oxidizes to form sulfate SOI?
(Ziegler, 1975).
Two species of grasshoppers were used in the feeding trial, Aulooava
elliotti and Ageneotettix deovim. AuloGava elHotti was chosen for the
trials to complement information obtained from the survival and fecundity
study. Toward the middle of the summer it was realized that this species was
not going to be common enough on the ZAPS for collection there and the
species used was changed to Ageneotettix deorwn. These two species are
closely related and have similar feeding habits (Anderson and Wright, 1952).
Both feed heavily on grasses, especially Agropyron snrithii which is the
dominant grass on the ZAPS. A. smithii was chosen as the grass used for the
feeding trial because it is the preferred grass of the two grasshopper species
and much information is known about it and its reaction to S02 from auxiliary
studies on the ZAPS sites.
Late instar nymphs and adult Aulooara elliotti were collected from an
outbreak area near Springdale, Montana on 20 June 1977. The population there
was estimated at 10 to 15 per m2. The vegetation was similar to the ZAPS but
was heavily grazed and Stipa spp. grasses were more prevalent. Approximately
400 individuals were collected by sweep net. Some were used in the second
attempt to establish the survival and fecundity study, but 50 were kept at
the lab for use in the feeding trials. At the laboratory they were separated
by sex, placed in cages and fed Agvopyron cristatum* A. smithii, and other
grasses collected in the vicinity of the laboratory.
Each feeding trial consisted of placing a number of grasshoppers (usually
five or six) in a cage where there was a choice of A. smitkii from the
control and high S0£ treatment. The food was presented "cafeteria style."
A leaf of A. smithii was placed in each of ten vials spaced 2.5 cm apart and
alternated between leaves from the control and high concentration treatment.
Leaves from the control were in positions 1, 3, 5, 7, and 9 and leaves from
the high treatment were in positions 2, 4, 6, 8, and 10. Testing was done to
determine the length of time grasshoppers should be left in the cage, which
was found to be 6 to 8 hours depending on the number of grasshoppers, the
temperature, and the time of day. The amount eaten was determined by making
a blueprint of each leaf, a method used by Langford (1930), before and after
being fed on. The outlines were then cut out and weighed to determine area
eaten per grasshopper per hour of each type of grass. A total of eight
feeding trials were done with A. elliotti, five with just male grasshoppers
in the cage and three with just females. Thirteen trials were done with A.
deovum, eight with grasshoppers collected from the high treatment, five with
grasshoppers from the control. One trial was done with Melanoplus
sanquinipes while looking for a new species to use after finding out popula-
tions of A. elliotti were too sparse to be collectible on the ZAPS. The data
are now undergoing statistical analysis, but preliminary analysis shows a
strong rejection of the S02-exposed grass in both species of grasshopper
(Table 19.12).
757
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TABLE 19.12. WESTERN WHEATGRASS EATEN PER GRASSHOPPER PER HOUR
Feeding trials Control Hiffh treatment—
involving Mean N SE Mean N SE
Male Aulooara elliotti 2.7 5 0.5 1.5 5 0.7
Female 4. elliotti 3.5 3 0.7 2.2 3 0.2
All trials using
A. elliotti 3.0 8 0.4 1.8 8 0.5
Ageneotettix deorwn
collected from the
control 1.6 5 0.2 1.2 5 0.3
A. deovum collected
from the
All trials
high
using
treatment
A. deoxnm
1.
1.
7
7
8
13
0.
0.
3
2
1.
1.
1
2
8
13
0.3
0.2
* 9
Area (mm^) from control and high treatments of ZAPS I.
Effects of S02 on Survival and Fecundity
Because grasshoppers exhibit considerable trivial movement over an area,
a cage study was initiated to insure that certain grasshoppers were exposed
to S02 over a period of time. The cage design was from Pfadt et at. (1970)
and measured 20 cm x 20 cm x 51 cm and was made from wood and 32 mesh/inch
saran screen. A removable dirt floor was attached to the bottom and served
as an oviposition site for adult females and also weighted the cage down to
prevent it from blowing over.
In mid-May, 25 first and second instar nymphs were placed in each of
four cages on each replicate of the control and high treatment. Within a
week all grasshoppers were dead. This could be attributed to many things
including overcrowding, higher temperature inside the cage, traumatic shock
from movement, and change of diet and other factors.
A second attempt was made during the first week of July when four adults
(two males and two females) were placed in each cage. About 25% died within
the first week and then the last one died the last week of August. Ovi-
position was noted and the removable dirt floor was left in the field until
23 September 1977.
The analyses for fecundity and oviposition success are not complete at
this time. Preliminary analyses indicate no treatment effects on survival
and are too incomplete to indicate anything about the effect of S02 on
fecundity.
758
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TABLE 19.13. NEMATODE POPULATIONS ON ZAPS SITES, 24 AUGUST 1976'
ZAPS I
ZAPS II
Nematodes Control Low Medium High Control Low Medium High
Herbaceous 2338 2406
Predaceous 1950 1938
Saprophagous
726 1546
Total 5014 5890
2967
1971
1142
6080
4017
1772
934
6723
1527
2080
1455
5063
1796
1821
1528
1670
1917
1055
5145 4642
930
1688
1645
4263
3C
Individuals • 17.8 cm"2 in surface 15 cm of soil.
NEMATODE POPULATIONS
Nematodes have been shown to be important components of native grassland
ecosystems (Smolik, 1974). Their importance stems from their large numbers
and subsequent impact on nutrient cycles and energy flow in the belowground
part of the system. Smolik (1974) has estimated that nematodes consume as
much plant material in northern Great Plains grasslands as do cattle at
proper stocking rates.
On 24 August 1976 we estimated the population level of nematodes on the
controls and all treatments of both ZAPS sites to determine if there had been
a response to the controlled S02 exposures (Table 19.13). The population was
estimated by taking four randomly located soil cores per treatment. The
cores were 4.8 cm in diameter and were taken to a depth of 15 cm.
Preliminary statistical analysis indicates no significant effects by
treatment (P = 0.76), site x year (P = 0.105), feeding type x treatment (P =
0.71), or in the feeding type x site x treatment interaction (P = 0.14).
However, significant differences were found between feeding types (P <
0.001) and in the feeding type x site interaction (P = 0.001).
In 1977 we intensified the nematode sampling to clarify the trends seen
in 1976. One sampling was done on 14 July 1977 wherein 10 soil core samples
were taken per treatment (five per replicate) on both ZAPS systems. Each
core was 4.8 cm diameter as in 1976; however, the depth was increased to
20 cm. Each core was divided into 0-10 cm and 10-20 cm increments and each
section was extracted separately. Extraction was by the Baermann funnel
technique (Thorne, 1961). Extraction time was 48 h and efficiency tests were
made on a subset of samples. The total nematodes from each core segment were
preserved in 50 ml of a 1% Formalin solution. Counting and identification
was done by taking three 1.0 ml subsamples and averaging the counts from each
then projecting back to the 50. ml total. We categorized the nematodes as
stylet bearers (plant feeders), nonstylet bearers (saprophagous), and preda-
tors of the genus Mononehus. Some of the larger stylet bearers probablv were
759
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TABLE 19.14. NEMATODE POPULATIONS ON ZAPS I, 14 JULY 1977*
Nematodes
Stylet bearers
Non-stylet bearers
Total stylet and
non-stylet bearers
Stylet /non-stylet
ratio
Predators
Depth
(cm)
0-10
10-20
Total
0-10
10-20
Total
0-10
10-20
Total
0-10
10-20
Total
Total
Control
2069
1280
3348(283)
2690
464
3154(476)
4758
1745
6502(663)
0.92
2.36
1.19(0.11)
24.70(7.15)
Low
2207
1698
3905(776)
2436
572
3008(365)
4642
2270
Medium
4458
1831
6289(682)
2492
633
3125(465)
6950
2465
6912(1015) 9414(1098)
0.87
3.64
1.31(0.22)
10.80(1.85)
1.84
3.78
2.14(0.17)
8.00(3.13)
High
2397
2008
4404(809)
1450
236
1686(221)
3847
2243
6090(872)
1.99
8.88
2.93(0.57)
12.50(3.68)
Figures are given per core segment or core total; for totals, the standard
errors are included in parentheses; the number
m
-2 _
(X)(552.6).
predatory but we could not readily distinguish them, hence the total grouping.
Certainly a large majority of the stylet bearers are plant feeders for most
of their life cycle.
The total number of predatory nematodes of the genus Mononahus per soil
core was very low in comparison to the other two categories. Nearly all the
specimens of Mononehus were found in the 10-20 cm segment of each sample.
The data indicate reduced populations of Mononehus in the S02-treated plots
of both ZAPS systems (Tables 19.14 and 19.15); however, the data for ZAPS II
are more discrete than ZAPS I. The relatively low counts and high variabil-
ity may negate a test of significance. The difference in counts of predators
from 1976 to 1977 is most likely a result of the difference in expertise of
the authors and Dr. James Smolik, a recognized nematologist, who did the
extractions and identifications in 1976.
For a majority of the nematodes, the trends, observed in 1976, especially
on ZAPS I, were not repeated in 1977. In 1976 there was a substantial
increase in plant feeding nematodes with increased S0£ exposure on ZAPS I
(Table 19-13). A similar increase was not noted in 1977. There was a
760
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TABLE 19.15. NEMATODE POPULATIONS ON ZAPS II, 14 JULY 1977'
Nematodes
Depth
(cm)
Control
Low
Medium
High
Stylet bearers
Predators
0-10
10-20
Total
Non-stylet bearers 0-10
10-20
Total
Total stylet and 0-10
non-stylet bearers 10-20
Stylet/non-stylet 0-10
ratio 10-20
3886
2086
•••••••••• •
5971(863)
3975
709
3271 3604 3722
2879 2005 2446
6146(712) 5609(635) 6168(442)
2526 2283 3091
695 735 589
4684(677)
7860
2795
3220(321) 3017(425) 3680(289)
5796 5886 6812
3574 2740 3036
Total 11,445(1,253) 10,367(921) 8836(917) 9922(653)
1.04
3.53
1.51 1.78
4.35 3.43
1.24
4.52
Total 1.41(0.19)
2.14(0.33) 2.01(0.22) 1.71(0.13)
Total 15.80(5.67) 20.00(3.49) 4.20(2.26) 1.5(1.4)
Figures are given per core segment or core total; for totals, the standard
errors are included in parentheses; the number • m~2 = (X)(552.6).
decrease in the saprophagic nematodes on the high treatment of ZAPS I, but at
the same time an unusually high number of stylet bearers on the medium
treatment of the same ZAPS probably accounts for the trend of increasing
stylet bearer/nonstylet bearer ratio. The increase in this ratio on ZAPS I
seems valid because it appears in both the 0-10 cm and 10-20 cm levels as
well as the total. However, the stylet bearer/nonstylet bearer ratio on ZAPS
II did not show as large an increase with increased S02 as on ZAPS I, though
an increase was noted. The implications for a change in the ratio of the two
nematode groups is not clear, but most probably is due to an indirect effect
of S02 through the vegetation and not through direct exposure to the atmos-
pheric S02. These trends, if indeed they are trends, should magnify over
time and additional sampling will help clarify them.
TARDIGRADE AND ROTIFER POPULATIONS
The tardigrades and rotifers are microscopic organisms that are con-
sidered members of the soilwater fauna, i.e., those organisms living within
761
-------
the thin water films of soil particles (Wallwork, 1970). Very little is
known of the biology and ecological relationships of these tiny organisms
even though their populations can be very high. Wallwork (1970) indicates
the rotifers are vortex feeders, i.e., creating water currents with their
cilia and taking in organic material of both plant and animal origin.
Tardigrades are thought to feed on a variety of material including organic
debris, bacteria, fungi, algae, nematodes, and rotifers. Hallas and Yeates
(1972) describe most species of the Tardigrade genus Hypsibius as feeding on
bacterial films; however, some are considered predatory. The tardigrades
collected on the ZAPS sites have been tentatively identified as Hypsifrius sp.
using keys by Schuster and Grigarick (1965). Both the tardigrades and
rotifers have the ability to encyst in a state of anabiosis during drought
conditions.
The population counts of both tardigrades and rotifers presented here
are derived from the same soil samples used for the nematode censusing
discussed in the previous section. The Baermann funnel extraction technique
has been shown to be efficient for these groups (Hallas and Yeates, 1972);
The tardigrades were counted in total for each sample extracted while the
rotifers in each sample were estimated by the subsample technique used for
nematodes. Generally low counts with high sample variability make it diffi-
cult to draw conclusions from the data (a statistical analysis is yet to be
run). However, our counts for the 14 July 1977 collection (Table 19.16) show
substantial reductions in the populations of both groups in the high treatment
plots for both ZAPS. The tardigrades show reduced populations in all but one
S02-treated plot while the rotifers show population reductions in only the
high concentration plots. The mechanism by which these possible reductions
are brought about and the significance of the reductions are very difficult
to interpret considering the lack of biological information on the two
groups. Since both groups are said to be members of the soilwater fauna, the
mechanism of S02 effect may be by way of the soil microwaterway and not
indirectly through the plants. As with the population trends observed for
the nematodes and arthropods, the observed trends in the rotifer and
tardigrade populations should magnify over time and be clarified with
additional censusing.
TABLE 19.16. TARDIGRADE AND ROTIFER POPULATIONS ON ZAPS I AND II ON 14 JULY 197?'
ZAPS I
ZAPS II
Fauna Control
Low
Medium
High
Control
Low
Medium
High
Tardigrade 6.80(2.53) 2.10(0.73) 2.90(0.93) 0.30(0.22) 6.80(3.34) 2.30(1.48) 7.20(4.36) 1.40(0.91)
Rotifers 97(34) 90(21) 95(23) 68(26) 174(35) 177(55) 167(42) 130(23)
Figures are given per core total. The number • m~2 = (X)(552.6). Standard errors are in parentheses.
762
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REFERENCES
Anderson, N, L., and J. C, Wright, 1952, Grasshopper Investigations on
Montana Rangeland, Bull. No. 486, Mont. Agric. Exp. Stn., Bozeman,
46 pp.
Dodd, J. L., W. K. Lauenroth, R. K. Heitschmidt, and J. W. Leetham. 1977.
First-year Effects of Controlled Sulfur Dioxide Fumigation on a
Mixed-grass Prairie Ecosystem. In: The Bioenvironmental Impact of a
Coal-fired Power Plant, E. M. Preston and R. A. Lewis, eds. 3rd Interim
Rep., EPA-600/3-78-021, U.S. Environmental Protection Agency, Corvallis,
Oregon, pp. 345-375.
Hallas, T. E., and G. W- Yeates. 1972. Tardigrade of the Soil and Litter
of a Danish Beech Forest. Pedobiologia, 12(4):287-304.
Harley, K. L. S., and A. J. Thorsteinson. 1967. The Influence of Plant
Chemicals on the Feeding Behavior, Development and Survival of the Two-
stripped Grasshopper, Melanoplus bivittatus (Say), Acrididae: Orthoptera.
Can. J. Zool., 45(3):305-319.
Langford, G. S. 1930. Some Factors Relating to the Feeding Habits of
Grasshoppers with Special Reference to Melanoplus bivittatus• Tech,
Bull, No, 354. Colo. Agric. Exp. Stn., Fort Collins. 53 pp.
Pfadt, R. E., J. E. Lloyd, M. Ali, and G. Sharafi. 1970. Manner of Pickup
of ULV Malathion by Grasshoppers from Aerially Sprayed Rangelands. J.
Econ. Entomol., 63(4):1210-1214.
Schuster, A. 0., and A. A. Grigarick. 1965. Tardigrada from Western North
America with Emphasis on the Fauna of California. Univ. California
Publ. Zool., 76:1-67.
Smoli^ J. D. 1974. Nematode Studies at the Cottonwood Site. US/IBP
Grassland Biome Tech. Rep. No. 251. Colorado State University,
Fort Collins, Colorado. 80 pp.
Thorne, G. 1961. Principles of Nematology. McGraw-Hill Book Co., Inc.,
New York. 551 pp.
Thorsteinson, A. J., and J. K. Nayar. 1963. Plant Phospholipids as Feeding
Stimulants for Grasshoppers. Can. J. Zool., 41(6):931-935.
Wallwork, J. A. 1970. Ecology of Soil Animals. McGraw-Hill Publishing Co.,
Ltd., London. 283 pp.
Ziegler, I. 1975. The Effects of S02 Pollution on Plant Metabolism.
Residue Reviews, 56:79-105.
763
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SECTION 20
SMALL MAMMAL INVESTIGATIONS AT ZAPS: DEMOGRAPHIC STUDIES AND
RESPONSES TO GRADIENT LEVELS OF S02
J. D. Chilgren
ABSTRACT
A capture-mark-release study of deer mice (Pero-
mysous manioulatus) and prairie voles (Mi,orotus oohro-
gaster) was conducted on two grassland Zonal Air
Pollution Systems (ZAPS) at monthly intervals from
April to September 1976. Small mammal population
structure, biomass, and other functional population
attributes were studied in addition to an analysis of
the behavioral responses of deer mice to S02 at each
ZAPS site. Most voles were distributed in a way that
precluded a comparable analysis. Animal composition
was similar on both ZAPS, although population density
and changes were greater or more variable on ZAPS II
compared to ZAPS I. In the response analysis, three
functional groups of mice were recognized: resident
adults and juveniles (group 1); transient adults and
juveniles (group 2); and resident and transient adults
(group 3). Temporal displacement and numerical re-
placement of group 1 was directed toward areas of lower
S02 concentration. Members of group 2, especially
juveniles, were trapped more frequently on the control
and low SOa plots on ZAPS II, but transient juveniles
were virtually absent from ZAPS I. Recruitment of
group 3 onto the control plots at both ZAPS occurred
more rapidly than onto other plots in late summer.
Throughout most of the trapping period, the number of
occupied traps on all fumigated plots decreased rela-
tive to control plots on both ZAPS, and remained rela-
tively higher on control plots from mid-season to the
end of all trapping.
INTRODUCTION
In recent years the massive research effort directed toward evaluation of
air pollutant effects in vertebrates has emphasized chamber fumigations em-
764
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ploying a variety of pollutants that result in acute injury within a short
period of time (e.g., hours to days). Many of these studies cannot be applied
to ecological models for several reasons. First, exposure rates are fre-
quently too high and therefore unrealistic. These pollutant levels achieved
under laboratory conditions are probably seldom attained in nature, with
certain exceptions that might, for instance, involve temperature inversions in
or near large industrial areas. Secondly, organisms may have inadequate
periods of time to adapt to the induced pollutant stress. The homeostatic
capability of stressed animals is briefly overcome, thus preventing observa-
tions of processes and patterns of individual responses that may result in
continued survival or some level of sustained resistance. Thirdly, laboratory
animals are normally subjected to optimum living conditions, which maximizes
their ability to withstand pollution stress experiments. On the other hand,
wild animals are continually exposed to a variety of stressors, each of which
presents a challenge to survival. The permutations of the search for food,
competition, aggressive interactions, disease, predation, and the vicissitudes
of weather and other variables all subvert the animal's ability to counteract
additional stresses. Lastly, extrapolations are often made from laboratory
test animals to those species whose lives are being tested in nature. Perhaps
just as often, no interpretations of laboratory results are given, and the
ecological setting that would give them additional meaning is not addressed.
These criticisms are not meant to undermine the value and necessity of labora-
tory experimentation. Controlled laboratory experiments, for example, cannot
be valid unless the test populations are of uniform physiological composition.
Laboratory tests form the basis from which animal models of pollution-health
effects are constructed. Formulation of new hypotheses and testable ideas
requires some forecasting from laboratory data. But now that acute exposure
data are available, field work should be expected to assume a more distinct
role in order to amplify and render more useful the studies now available.
The study reported herein is but one step forward in evaluating small
mammal responses to sulfur dioxide (SOz) over a period of several months in
1976 and 1ST77. The ZAPS sites provided ideal study areas for these investiga-
tions. In addition, this field study was an attempt to bridge the hiatus
between acute exposure experiments and quantitative inventories of vertebrates
in pollution-impacted areas. Knowledge of subtle changes in population struc-
ture may be more helpful in predicting chronic pollution injury or stress than
would large population fluctuations related to natural cyclic variation, which
may mask those population variables affected by various emissions. Herein
lies the difficulty in relating pollutant impact to population dynamics,
especially in microtine rodents. Alterations in population levels are gov-
erned by a host of variables, several of which cannot be said to exert primary
control over these levels. Because non-microtine rodents exhibit fewer ampli-
tude fluctuations than do microtine rodents, their study becomes more signifi-
cant for the Colstrip project even though the element of population predicta-
bility is less well defined than in microtines. Many non-microtine species
are widely-distributed and abundant in SE Montana. Both of these factors
recommend them for intensive study.
The objectives of this research were to (1) gather population data that
would assist in the characterization of small mammal populations in grassland
communities, (2) ascertain trends in animal movements within the ZAPS gradient
765
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and (3) to determine capture and recapture frequencies at each plot within
each ZAPS. Mechanisms by which S02 affects grassland rodents may be proposed
if deviations in trapping expectancies that may occur at either site are
interpreted in the light of current knowledge of S02 effects and sensitivity
in mammals.
MATERIALS AND METHODS
Trapping Procedure
Both treatment and interval plots were trapped over a six month period in
1976 (Table 20.1). Twenty-five Sherman live traps were placed within each
TABLE 20.1. 1976 TRAPPING PERIODS
1.
2.
3.
4.
5.
6.
7.
CMR Period*
9-11 April (prefumigation)
13-15 April (postfumigation)
12-14 May "
23-25 June "
28-30 July "
25-27 August "
15-17 September "
Day
1
4
33
75
110
138
159
*Capture-mark-release.
test and control plot in a 5 x 5 pattern with a 15.2 x 17 meter spacing be-
tween traps, with 20 traps in each interval plot (plots ii, i2, is) in a 5 x 4
pattern with distances of 15.2 and 12.2 meters between traps. Plots are
graphically represented in Figure 20.1. Traps were prebaited with rolled oats
A
ii
i
Figure 20.1. A schematic of designated trapping grids at ZAPS I and II.
for two days followed by three days of capture-mark-release (CMR). Prebaiting
allows free entry into and exit from a baited trap, thus enhancing familiarity
to a known food source. Trapped animals were marked by toe clipping and
released later at the precise point of capture. Body weight, length, sex,
age, reproductive status, pelage color, molt phase, and ectoparasite burden
were recorded each time an individual was caught. Age was determined by
766
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combined use of weight and length, pelage color, and appearance of the exter-
nal genitalia. Animals not classed as adults were termed juveniles (see
beyond for definitions).
Individually marked traps were opened between 1800 and 2000 hr and
checked the following morning on days of CMR. Traps remained open all day
during prebaiting periods. Records of both trap number and animal number (as
identified by clipped toes) made possible the determination of areas of cap-
ture, movement patterns of resident animals, and visitations to individual
traps.
After the last day of CMR, live trapping continued for three days (here-
after referred to as trap-out or T.O.). Animals trapped within this period
were taken to the laboratory and sacrificed. Blood samples and dissection of
major organs were followed by freezing the carcasses for future analysis.
These data will be presented elsewhere.
During the 1977 field season, live-trapping of small mammals was con-
ducted on fumigated plots only, and was limited to three trapping periods at
three week intervals (27-29 July; 16-18 August; and 6-8 September). One extra
day (3 August) of live trapping was conducted to compensate for the low catch
during the first trapping period. Blood samples for biochemical analysis were
taken from each animal but not exceeding one sample per animal each trapping
period. The results from these tests will also be reported elsewhere.
Home Range Estimates
Estimates of home range for mammals captured several times was accom-
plished by employing the minimum area technique, in which lines joining the
outermost points of capture are drawn a map and the area enclosed calculated
(Delaney, 1975). Only adults captured at least four times in at least two
different months were included in this analysis.
Definitions
Several terms used throughout this section require a brief definition:
1. Adult—a sexually immature animal characterized by adult features in-
cluding body weight (ca. 14 g) and length minimums, developed sexual or
lactating organs, and adult pelage color.
2. Juvenile—a sexually immature animal, not fulfilling the definition of an
adult.
3. Resident—an adult or juvenile trapped in successive trapping periods,
not necessarily sequential.
4. Transient—an animal trapped only once during a trapping period, and at
no time thereafter.
5. Trapping period—two days of prebaiting followed by three of CMR.
767
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6. Activity—the total number of animals trapped, including recaptures,
during any trapping period.
RESULTS AND DISCUSSION
Species Composition and Description
The most commonly encountered species were the deer mouse (Peromyscus
maniculatus) and prairie vole (MicTotus ochvogastev), both predominantly noc-
turnal in summer, and the 13-lined ground squirrel (Spewnophilus tridecemline-
atus}, a common diurnal rodent. Squirrels were commonly encountered in the
spring when traps were opened early or were not checked within three hours
after sunrise.
The numbers and proportions of mice and voles trapped at both ZAPS sites
over 6720 trap-nights in 1976 were similar (Table 20.2), despite greater
TABLE 20.2. SPECIES COMPOSITION AT TRAPPING SITES*
Site P. maniculatus M. oehrogaster Other Total
ZAPS 1
ZAPS 2
86 (76.8%)
101 (71.1%)
26 (23.2%)
38 (26.8%)
0
3t
112
142
^Numbers exclude squirrels; numbers in parentheses
are percent of total.
tlncludes one ReithTodontomys megalot-ls, one Pero-
gnathus fasciatus, and one Thomomys talpoides.
canopy coverage and more precipitation at ZAPS I and higher S02 levels at ZAPS
II (Taylor and Leininger, 1978). Similar to these proportions of animals are
the results obtained at Hay Coulee during the 1976 grid trapping study (Chil-
gren, unpublished data). If the Wyoming pocket mouse (Perognathus fasoiatus)
is ignored for the moment, the catch at Hay Coulee was 75% for P. manioulatus
and 25% for M. ochvogaster. The presence of P. fasoiatus in reasonable num-
bers at Hay Coulee (14 of 66) reduced the actual composition of P. maniculatus
and M. ochvogaster to 58% and 20% respectively. Because M. oehrogaster pre-
fers denser grass habitats than does P. maniQulatus (Eadie, 1953) the ungrazed
vegetation at ZAPS I and II provided an enriched habitat for M. oahrogasteT.
The latter is found throughout all areas of Powder River and Rosebud Counties
where adequate cover and grass exist. Heavily grazed areas appeared to be
consistently low in vole numbers.
Sex and Age Composition
The distribution of sex and age classes of P. manioulatus at ZAPS I and
II is shown in Figure 20.2. The sex classes throughout the trapping season
are shown for M. oehrogaster (Figure 20.3). Only two juvenile deer mice were
trapped at ZAPS I for the period April-August 1976,Awhile 17 were caught at
ZAPS II during this time. Further division of sex classes of voles into age
768
-------
25
20
0) l5
_i
<
5
^ 10
^
U-
o
(E 5
UJ
m
2
^
z O
v
5
IO
•"•"•"••••••••••••••I
•••M
Adult P.maniculatus
M
\
Xl— I"*"
tf&
M itv
R
^~
K
K\
Cs
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^
f
?
1— 2 J L-2 j|
_ A A
P P
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s s
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i
LJ
Juvenile
1
-
mm
i
i
I
^H
—
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/>
y
y
•v
\
\
V
^
V
\
\
v
A
V
\
\
\
\
^
Cx
•y
f/
//
1
/.
/.
/.
'',
I
^^
'/
••1
P. maniculatus
—
I
X
/
x
^
s
£
V1
•y
2
h^hal
^
!
y.
/
/
/
\
V
y
y
%
—
£.U
Apr
May
Jun
Jul
Aug
Sep
Figure 20.2. Sex and age composition of P. manieulatus at ZAPS I and II on
all plots from April to September 1976.
classes seems unnecessary here because the response of voles to the ZAPS SO2
gradient appeared to be undeterminable. Nearly all voles ostensibly inhabited
plot B and its adjacent interval plots (see Figure 20.A). No voles were
caught in Plot A and very few in plot D. The reasons for this clumped distri-
bution of voles on both ZAPS sites are unknown. Although voles form colonies
of seasonally changing densities, the remarkable and fortuitous similarity in
colony location appears for the present to be only coincidental. For example,
a vole colony was found at plot D on ZAPS II in 1977, and hence I assume that
there was nothing peculiar to plot B at both sites that attracted them. The
existence of vole colonies on plot B did facilitate intersite comparison and
was a prominent factor in establishing experimentally one site as a spatial
replication of the other. The nonuniform distribution of voles, however, did
not permit any correlation between S02 level and vole behavior. The extent to
which voles may have interferred with deer mouse emigration is not known.
However, few mice were ever trapped in areas containing large vole colonies.
This apparent exclusion occurred mainly on the north end of plot B of ZAPS II
in 1976, and was tested statistically using a 2 x 2 frequency analysis for
both ZAPS sites. In each analysis, a negative association between Peromyseus
and Miorotus was detected, being stronger on ZAPS I (P < 0.001) than on ZAPS
769
-------
30
25
CO
u
o
u.
O 15
UJ
CD
10
0
Microtus ochrogaster
HM^
rr
F
— I*
A
P
S
1
//
—
1
^J
5
^ r^
1 F
n
\\
^
•z-
A
P
S
II
O
V V
S
^
7
1
!
25
7
I
^
\
\
\
\
S
_
18
6
I
\\
\
—
—
5
Fk~
i
Apr May
Jun
Jul
Aug
Sep Sep(T.O.)
Figure 20.3. Sex composition of M.' odhrogaster on ZAPS I and II on all plots
from April to September 1976. T.O. indicates trap-out: animals
removed after the last date of CMR.
II (P < 0.025). Hence, these species were not distributed independently of
each other.
Population Characteristics
It was not critical among the objectives of this experiment to character-
ize the population levels at ZAPS. First, trap distances were not conducive
to population analysis and no removal trapping was conducted. Nevertheless,
it is possible to characterize the population in general terms and to make
some specific statements as to the degree of similarity in population struc-
ture at both ZAPS. Sex and/or age composition of Peromyseus and Mi,crotus has
already been shown (Figures 20.2 and 20.3). Populations levels of P. maniGu-
tatus varied throughout the season, reaching zenith levels at both ZAPS in the
period from mid-summer to fall. This late peak was correlated with the ap-
pearance of juveniles in the existing population. Because the S02 appeared to
be a strong factor in organizing the distribution of P. manieulatus, it is
inappropriate to attempt an accurate population estimate. Generally speaking,
however, population levels at ZAPS I were more uniform, varying at the most
770
-------
ZAPS
II
ZAPS
/
Sep
Aug
Jul
Jun
May
Apr
Sep
Aug
Jul
Jun
May
Apr
Plot
A
•*•*•*•
• •
*
• •
• ••
L
• •••
• ••
*
..
• *•
• ••
• ••
• ••
•
B
-PLOT
• ••••
• •
•
**
.
•
•
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1
INTER
• •
c
VALS-
•
...
• ••
•
t
• •
D
Figure 20.4. Distribution of M. oehrogaster at ZAPS I and II from April to
September. A dot indicates one individual.
during the summer by a factor of about 1.8, whereas at ZAPS II, this factor
was about 2.7. Refined and elaborate techniques of population density esti-
mates were not employed because density analysis was not central to the study
objectives. Furthermore, mark- re capture methods suffer the weakness of equal
trappability assumptions, the fallacy of which cannot be detected or compen-
sated for statistically. Removal techniques are superior and, as mentioned
above, were not conducted under the experimental design of the ZAPS small
mammal study.
Table 20.3 summarizes the recapture data at both ZAPS sites. The mean
recaptures per individual are 3.2 and 2.8 for Peromyscus and 2.6 and 1.5 for
MoTotus at ZAPS I and ZAPS II, respectively. The values for Peromysous are
about 30% higher than those obtained at trapping grids near Cols trip (Morton
and Chilgren, in press), although they are not without bias. On both ZAPS
.there were two mice caught 21 times and two voles caught seven and 16 times.
Obviously animals caught early in the season had a chance of being trapped
much more often than those trapped later, say in July.
Transient animals often form a large fraction of trapped
(Terman, 1968). Transient P. maniculatus accounted for 38X and
at ZAPS
771
-------
TABLE 20.3. RECAPTURE SUMMARIES AT ZAPS SITES*
P. manieulatus M. oahrogaster
Number Total times Number Total times
1 e caught recaptured caught recaptured
ZAPS I 76 242 21 54
ZAPS II 93 260 35 53
*Excludes trap-out individuals.
I and II, respectively. Animals captured in September could not be considered
as transients or residents, since no trapping occurred in later months to
verify the status of a September individual. The transient population ap-
peared to be affected by the S02 levels (see page 777). A transient individual
by definition could have been trapped one to three times during a trapping
period but could not be caught at any other trapping period. This definition
has limitations since a trap-shy resident trapped only once would be errone-
ously called a transient.
Survival
Because the population could not be determined accurately, it is not
possible to determine mortality rates of mice. However, one can compute a
probability curve defining appearance and disappearance rates without knowing
specific population numbers. The data used as a basis for this curve are
shown in Table 20.4. The "Total Animals" column summarizes the number of
TABLE 20.4. PROBABILITY OF APPEARANCE DATA FOR ZAPS I AND II*
Site Month
1
2
ZAPS I 3
4
5
1
2
ZAPS II 3
4
5
Total Animals
31
16
9
5
4
34
21
13
4
3
Chances
31
24
18
14
10
34
27
25
15
13
Probability
1.00
0.67
0.50
0.36
0.40
1.00
0.78
0.52
0.27
0.23
*See text for explanation.
772
-------
animals known to be alive each month since their initial release month (April
to August) and excludes animals that died in traps or that suffered some
trauma during the capture and marking process. Because mice caught later in
the season do not have an equal chance of being captured as do mice caught
early in the season, the chances of capture for all individuals is summarized
under Chances, and the ratio of animals captured to the chances of capture
(Probability of Appearance) defines the proportion of recaptured mice known to
be alive for a subsequent month. The month of initial release is month 0 and
subsequent months are numbered 1 to 5. For an animal trapped in August for
the first time, there would be only one subsequent month (September). The
probability values are then plotted on semilog paper and a logarithmic func-
tion is calculated to define the curve (Davis, 1964). The last month values
can distort the curve since the number of animals appearing may not decline as
fast as the chances of capture. Hence, the last month for ZAPS I has been
omitted so that a more reliable probability curve could be drawn. The expres-
sions for these functions on each site are as follows:
(1) ZAPS I: log y = 0.136 - 0.147x (r2 = 0.996)
(2) ZAPS II: log y = 0.218 - 0.179x (r2 = 0.968)
where y is the Probability of Appearance (the number that appear divided by
the initial population) and x is the month of capture after marking the ini-
tial population. The annual probability of appearance can be calculated by
substituting 12 for x and computing y. For ZAPS I y is 0.023 and for ZAPS II
y equals 0.012. The probability of disappearance is 1 - y. Hence, the proba-
bility of disappearance is 0.977 and 0.988 for ZAPS I and II respectively.
These values indicate that the chance of recapture after one year are compara-
bly small at both sites, which is not unexpected for Cricetid rodents (French
et al.t 1975). These numbers might be liberally interpreted to indicate that
the survival rate is rather low, and that the lifespan of a mouse is not
likely to exceed one year at this particular locality. The extent to which
SOa may have affected these calculations cannot be determined. It should be
mentioned here that five P. maniaulatus trapped in April were at ZAPS I and
four at ZAPS II in April were also trapped in September. Hence, the known
lifespan of some mice in this region is at least 7-8 months (six months seen
in trapping and one to two months for maturity and development) .
Home Range
The home range is the area over which a small mammal will travel in the
course of its normal or routine activities. Home ranges were calculated only
for adults and those mice that were captured four or more times in at least
two different trapping periods. Animals captured in successive months and
that appeared to have shifted their apparent home range (Brown, 1966; Stickel,
1968) were also not included. Because of the fumigation, animals may not have
lived on the grids, but merely may have been attracted to the oat bait^in^the
traps. However, since home range calculations are estimates at best, it is
reasonable to compare these data with existing data to determine the overall
reliability of the estimates. Table 20.5 shows home range estimates for both
P. manioulatus and M. odhvogastev-
773
-------
TABLE 20.5. HOME RANGE ESTIMATES FOR RODENTS IN CUSTER NATIONAL FOREST*
Site
Male
P. maniQulatus
N Ct Female
N C
M. oohrogaster
Both sexes N C
0.22 ± 0.09- 14 9 0.12 ± 0.07 15 6 0.11 ± 0.07 7 7
(0.54 ± 0.22)
(0.29 ± 0.18)
(0.27 ± 0.17)
0.14 ± 0.05 12 8 0.12 ± 0.05 18 8 0.05 ± 0.12 10 5
(0.33 ± 0.13)
(0.30 ± 0.14)
(0.14 ± 0.04)
*Mean area (hectares) ± S.D.; acres in parentheses; N = number of
animals.
tAverage number of captures per individual.
The existing literature on Peromyscus reveals that the home range size of
most species of adult males is larger than that of females. Stickel (1968)
has summarized home range sizes for several subspecies of P. maniQulatus and
indicates than in six of these, the male home ranges are larger than in fe-
males, and>in two subspecies the sizes are equivalent. Because I believe that
osgoodi is the subspecies at ZAPS, there are no comparable data, but even so
the data in Table 20.5 are somewhat confounding. Male maniQulatus home ranges
were significantly larger (P < 0.005) than that of females at ZAPS I as well
as that of males at ZAPS II (P < 0.01). Female home range estimates were
comparable at both sites. Nevertheless, the estimates for Peromyscus in Table
20.5 are well within prior estimates for other species and subspecies of
Peromyscus (see Table 1 in Stickel, 1968). These estimates appear to be less
than those calculated by Metzgar (1973), however, for P. manioulatus near
Missoula, Montana. He used a much larger (3.2 ha) grid and calculated home
range size for both feeding and exploratory activity. Measured from the
animal's center of activity, the mean distances for feeding and exploratory
activity were 30.6 and 31 m, respectively. If transformed into circular
areas, his home range data exceed those of male mice in Table 20.5 by 30-50%.
Since grid areas and methods of measurement were different in both studies,
and the data in Table 20.5 exhibit some deficiencies (e.g. , low averages of
captures per animal), these differences do not seem incompatible. Further-
more, Metzgar may have been experimenting with a different subspecies whose
habitat was quite dissimilar from that of the ZAPS sites.
Although the home range estimates for M. ochrogaster appear to be differ-
ent the 95% confidence limits calculated for means at each site overlap (ZAPS
I: 0.052-0.164; ZAPS II: 0.044-0.066) and are therefore not significantly
different. Using a modified minimum area technique that reduces the magnitude
of the original technique, Harvey and Barbour (1965) estimated the home range
of six M. ochvogaster to be 0.09 acre, or about 43% that of the unmodified
technique. Assuming the true home range of M. ochrogaster to be overestimated
by the technique I employed and by applying a correction factor derived from
Harvey and Barbour, the average home range for 17 voles at both ZAPS is com-
puted to be 0.06 acre at ZAPS II and 0.11 acre at ZAPS I. These values agree
774
-------
with those of Harvey and Barbour, and are compatible with an average value of
0.075 acre for M. pennsylvanicus obtained with an isotope technique (Ambrose,
_L-/ O 3/ / •
Home Range and Biomass; Relationships to Population Density
Home range can be expected to change in response to physical factors
(season and weather), population factors (population density), ecological
factors (habitat and food supply) and an individual's biology (sex, age, and
behavioral patterns). Because home range estimates were made at the same time
of year and under conditions of similar habitat and weather, the only conspic-
uous factor named above that differed extensively at ZAPS I and II was popula-
tion density. Juveniles were virtually absent from ZAPS I until August unlike
ZAPS II, on which several juveniles were trapped from June until the end of
the trapping period in September. Expressed in terms of biomass (grams per
hectare) or the total mouse and vole weight per unit land area, the population
density at ZAPS II peaked in June owing ostensibly to juveniles entering the
population from within (recruitment) as well as adults and juveniles entering
from peripheral areas (emmigration) (Figure 20.5). No comparable change was
observed at ZAPS I. The magnitude of the differences in biomass is expressed
in Table 20.6 as a ratio for each month of trapping. Thus, both the rate of
population increase as well as the population at peak level may be correlated
with the lower estimate of male home range at ZAPS II, since population dens-
ity and home range size are often inversely related (Stickel, 1960). Although
I have no evidence that other variables may not have been operative, the data
suggest that population density may be one feature regulating home range since
a similar pattern was observed in M. oohvogasteT (Figure 20.5). These data
indicate that vole biomass increased dramatically at ZAPS II but was much less
variable at ZAPS I. The mean home range estimate for M. oohrogastev was more
than halved, although the high standard deviation at ZAPS II reduced the level
at which confidence intervals are nonoverlapping to less than 90%. Neverthe-
less, there is a clear trend expressing the relationship between population
density and home range estimates. This discussion takes no note of the possi-
bility that unknown differences in species trappability may have adversely
affected the above analysis. One has to make this assumption in order to
evaluate the available data. I also cannot explain why female home ranges did
not vary if population density is affecting home range of both sexes.
Experimental Effects
Assumptions and Hypotheses
The following assumptions were made in the interpretation of these re-
sults. First, terrain and habitat features are similar on all plots at both
ZAPS so that habitat preference is assumed to not influence the results.
Second, the chances that an animal may traverse a plot or be trapped within
any one plot are assumed to be equal for all plots.
The null hypothesis is that immigration or recruitment onto any portion
of the ZAPS proceeds unimpeded as if no S02 were present. On the contrary, if
a mouse or vole is sensitive to S02 at these concentrations, its response to
test plots should be different in space and time from that of control plots.
775
-------
o>
200
150
100
50
P. maniculatus
o ZAPS I
• ZAPS n
J I
200
50
100
o>
- M. ochrogaster
Figure 20.5. Biomass changes from April to September 1976 in two common
rodent species in SE Montana.
TABLE 20.6. RELATIVE BIOMASS DIFFERENCES OF MICE AND VOLES*
Species
Apr May Jun Jul Aug
Sep
P. manioulatus 0.73 0.94 2.44 1.00 1.32 0.87
M. ochrogaster 0.27 0.00 0.20 2.82 2.54 1.84
Both species 0.54 0.61 1.60 1.49 1.83 1.17
*The quotient of ZAPS I biomass/ZAPS 2 biomass.
776
-------
Categories of Experimental Animal Groups
Three functional groups of mice were recognized: resident adults and
juveniles (residents), transient adults and juveniles (transients), and resi-
dent and transient adults (adults), a group created by necessity because of
the low incidence of juveniles on ZAPS I. As juveniles are often dispersing
to find new territories, a category of resident and transient juveniles as a
separate entity did not exist and I found no evidence that juveniles as a
group took up residence at either site. These groups of mice form the basis
of the subsequent discussion. Voles have been excluded from discussion,
except where their presence affected mouse populations, for reasons given
previously.
Capture Patterns of Resident Mice
Because the burrow sites of resident mice were not determined, a mouse
that lived within a fumigated plot could not be distinguished from one that
lived outside the plot but returned to the trap for food. As no trapping was
conducted beyond the borders of test or interval plots, no movement of resi-
dent mice other than that parallel to and within the gradient could be as-
certained. The criteria for movement within this zone were (1) capture at
least twice in the area of initial capture followed by successive captures in
another interval or plot at least 45 m away; and (2) capture in the new area
at least once in a future trapping period.
At ZAPS I, 16% (eight mice) of all mice trapped (26% of all residents)
fulfilled these criteria, and at ZAPS II these figures were 5.3% (four mice)
of all mice trapped (11.1% of all residents). Of these 12 mice, seven moved
down and five up the gradient. Six of the seven moving down were initially
trapped on plot D and one of the adjacent intervals. Of the five moving up
the gradient, three originated at plot A, one at plot B, and one at plot C.
None of these moved into plot D. At least two explanations are possible.
First, if the burrows of permanent residents were not within the ZAPS, these
mice may not be affected by exposure to S02 while entrapped. The lure of
plentiful food then outweighed any discomfort a mouse experienced during its
stay within test plots. It is equally possible that those residents showing
movement may have had their burrows on the ZAPS and moved accordingly in
response to S02. Second, if most residents had burrows within the ZAPS, they
may not have been sufficiently repulsed by S02 to emmigrate on a large scale.
In addition, the number of residents having burrows within the ZAPS that
emigrated shortly after exposure to S02 in April cannot be determined. If
captured only once, these mice are by definition transients. Any number of
mice that were so misclassif ied would tend to weaken the argument that only a
small percentage of residents moved out of the S02 field.
Temporal Capture Patterns of Resident and Transient Adults
The temporal changes in adult mice trapped on each ZAPS site (recaptures
excluded to minimize bias associated with trap-shyness or trap-addiction) are
depicted in Figure 20.6. Juvenile mice have been omitted because of the pro-
found discrepancy between numbers of juveniles trapped on ZAPS I and on ZAPS
II. Their omission facilitates a more equitable comparison of mice of all age
777
-------
12
10
8
o Plot A (control)
A Plot B
• Plot C
n Plot D
33 75 HO 138 159
DAYS OF EXPOSURE
Figure 20.6. Temporal changes in numbers of adult P. mcm/iculatus on test
plots at ZAPS I (top) and II (bottom).
groups. These graphs show that while mice on plots C and D are relatively
stable and low, control plots show enhanced recruitment throughout the season,
especially at ZAPS I. The low numbers of mice observed on plot B can be
attributed to the presence of voles. It can also be shown that totals of
adult mice summed May to September differ significantly on plots A, C, and D,
with plot B excluded for the reason just given (Table 20.7). April is not
included because of the three days between initial and postfumigation CMR
periods were thought to be insufficient for S02 to achieve a noticeable effect
778
-------
TABLE 20.7. X2 ANALYSIS OF SEASON TOTALS OF ADULT MICE (MAY TO SEPTEMBER)
Plot A Plot C Plot D
Observed Expected Observed Expected Observed Expected X'
ZAPS I
ZAPS II
31
41
14.4
18.9
13
21
18.6
21.6
22
15
14.4
16.9
24.6*
34.8*
*P < 0.001.
on animal populations, although data collected in April at ZAPS II indicate
that effects may have been felt within this period of time (see page 782) .
Capture Patterns of Transient Mice
The ZAPS S02 gradient should exert no effect upon the transient popula-
tion if the assumptions mentioned above are valid. One may expect, therefore,
approximately equal numbers of transients on all plots, although there may be
unbalanced numbers in both sex and age classes (Terman, 1968). Because fewer
transients were trapped on ZAPS I, the following analysis has been simplified
by treating the control and low plots and interval ii as one section (AiiB)
and plots C and D and interval i3 as another (Ci3D) . Animals in the middle
interval were assigned to one unit or another, depending on proximity of
capture to either unit.
Several hypotheses were tested in this analysis.
1. The numbers of adult and juvenile transients trapped in section AiiB
should equal approximately those trapped in section Ci3D.
2. The numbers of adult transients should be comparable on plots A and D.
3. The numbers of juvenile transients should be comparable on plots A and D.
4. Juvenile transients should be evenly distributed across each ZAPS.
5. Adult transients should be evenly distributed across each ZAPS.
The results of this analysis are summarized in Table 20.8.
i. ,,c,I«, C1.D .« ZAPS I. ..r,
779
-------
TABLE 20.8. TRANSIENT MOVEMENT AND DISTRIBUTION
Hypothesis
number Site Data X2, P Hypothesis supported
1 ZAPS I 9, 10 0.11, 0.26 Yes
ZAPS II 29, 12 7.07, 0.99 No
2 ZAPS I 7, 5 0.42, 0.48 Yes
ZAPS II 13, 7 1.85, 0.83 Yes
3 ZAPS I insufficient data
ZAPS II 12, 0 10.1, 0.95 No
4 ZAPS I insufficient data
ZAPS II 19, 8 3.70, 0.95 No
5 ZAPS I 13, 12 0.08, 0.22 Yes
ZAPS II 15, 13 0.18, 0.33 Yes
based upon independent observations in time. In this foregoing analysis, the
presence of voles has been ignored, but their presence on plots B, ii, and 12
serves to accent the difference observed with regard to hypotheses 1, 3, 4,
and to some extent 2 because of the presumed increase in mice trapped at plot
B in the absence of voles.
Capture Patterns at Individual Plots
For each plot, animal activity (see definitions, page 767)was summed
throughout all trapping periods for both peripheral and interior portions of
each fumigated plot as well as for each interval. Peripheral portions were
the 16 traps forming the boundary of each plot, and the remaining nine traps
forming the interior portions. Two hypotheses were tested. First, peripheral
activity of all plots should be comparable, and second, interior activity of
all plots should be comparable as well. Both of these hypotheses assume that
a large number of mice live outside each ZAPS and are attracted to the bait.
If each ZAPS is regarded for the moment as a large rectangular grid, the
boundary of this grid is the boundary of traps around each ZAPS. Table 20.9
shows that an edge effect was present and that these hypotheses are most
likely valid. This table shows that the total activity in the peripheral
boundary of the entire ZAPS (which contained 44% of the total traps) was
significantly greater than that of the interior portion (containing 56% of all
traps). It also suggests that each plot might show a similar tendency, and if
both hypotheses are valid, boundary traps can be expected to "filter" immi-
grants or trap visitors and should fill at a more rapid rate than interior
traps. Then, if S02 does not affect foraging behavior, the interior traps at
each plot should also fill at equivalent rates. The data pertaining to activ-
ity at the peripheral and interior regions of each plot are shown in Table
20.10.
780
-------
TABLE 20.9. ANALYSIS OF THE EDGE EFFECT FOR DEER MICE*
Site Total activity % Of total activity
Peripheral Interiort Peripheral Interior
ZAPS I
ZAPS II
179
202
110
124
61.9
62.0
38.1
38.0
*Summed throughout all trapping periods; excludes mice
known to have died during a CMR session.
tSee text.
TABLE 20.10. REGIONAL ACTIVITY SUMMARIES AT EACH ZAPS PLOT
Plot and region
Site
ZAPS I
ZAPS II
A B C D
PIPIPIPI
40 30 35 7 33 14 42 24
55 28 48 11 48 14 48 7
There was no statistically significant difference in peripheral activity
among plots (X2 = 5.95, P > 0.10 for ZAPS I, and X2 = 0.74, P = > 0.60 for
ZAPS II). Plot B was eliminated in these goodness-of-fit tests for interior
activity because of the apparent inhibitory effect of voles on deer mouse
distribution. While peripheral activity was shown to be similar among all
plots, interior activity was reduced on plots C and D of ZAPS II (X2 = 15.22,
P < 0.01) but not on ZAPS I (X2 = 5.96, P > 0.10) owing to results at plot D.
When the effect of time is considered, however, it can be shown that 42% of
the interior activity on ZAPS I occurred during the first three days of fumi-
gation in April. If the April figures are not included, the values for I in
Table 20.10 then become 27, 6, 8, and 16 for the respective plots of A, B, C,
and D (X2 = 27.4; P < 0.01).
Temporal Changes in Relative Activity
Figure 20.7 illustrates the seasonal changes in numbers of transient and
resident adult and juvenile activity within each experimental plot relative to
the control plots. At both ZAPS sites, there was a downward trend on all
three experimental plots after the initial surge of activity, which might be
explained by the initial exposure of each ZAPS to S02. The relatively low
levels of activity in plot B can probably be attributed to the presence of
voles. Because this pattern is duplicated spatially, it is unlikely that
variables other than S02 could exist simultaneously at both sites and elicit
the same pattern. These data then provide some of the strongest evidence for
the effects of chronic low levels of S02 upon animal behavior.
781
-------
5UU
2001
I
rV
1 1 1 - 1 II
A
I X
kX»
• A -•&-._
j^i — • *^^ *•>*» "•n»--..
o
Q.
o
o
700
600
500
O 400
300
200
A Plot B
• Plot C
n Plot D
*•
) \\
f \\
\\
\\
\\
1001
04
33 75 110
DAYS OF EXPOSURE
1
1
138 159
Figure 20.7. Temporal changes in relative activy of P. manicutatus on test
plots at ZAPS I (top) and II (bottom).
Correlation Between Activity and SO2 Levels
Hourly means of SOz (pphm) were averaged over 12 hr periods (1800 to
0600) on nights of CMR. Averages for all three nights of each trapping period
were computed and examined against the activity of deer mice. No correlations
were apparent. These results are expected for several reasons. First, SOa
levels often varied substantially throughout each 12 hr period. Averaging SOa
levels obscures real differences between hours or blocks of hours that might
have correlated with activity if the times of capture were known. Second, any
correlation would imply an immediate behavioral response to SOa. Although it
is not known how P. manioulatus initially responds to SOz inhalation at the
levels experienced in the field, the results of this experiment show that some
mice may tolerate S02 levels for long periods. For example, some mice at both
ZAPS were trapped each month or nearly every month. Hence, it would appear
that in addition to any direct effect of S02 on an animal, there may be in-
direct effects as well operating through various pathways, e.g., food and
water quality or abundance, or habitat characteristics. Lastly, the ground
782
-------
id SM ^i by nocturnal ground-dwelling
id Probably did not resemble the seasonal mean
/heiant°ndecrte ^ ^ Section 10) indi<=ate
ever, inversion conditions in i~hp n-ro c • «*'•'•** ucj_ow it. n.ow~
common pattern according to S02 levels^oni ^n-r^^J^^^8 t0 have been a
allowed S02 levels to increase bv In or^f eachjnl§ht- ^^ situation
between activity and S02 levfl is expiated ' ^ °f C°rrelation
Field Operations in 1977
At ZAPS I, six adult male and six female (four adult, two juvenile) P
ruLLatus WPT-P marked alnno tr-ft-h <-^v«« ^ 7 j. , juveuj.xe; r.
maricea aiong with three M. oehrogaster (one adult male two
At" 7AP^ TT o-io-v,*- «J i i. c -i -i /- . «-v*v»
".i. ^nr o a.i, eignt aauit remale and five male (three adult
two juvenile) P. manioulatus were marked. The catch for M. ochrogaster was
eight males (four adults, four juveniles) and eight females (five adults,
three juveniles). The respective distribution and activity of both species at
each site are summarized in Tables 20.11 and 20.12. These data do not differ
TABLE 20.11. TRAPPING RESULTS FOR P. maniculatus IN 1977
Plot
Site Variable
ZAPS I T°tal animals
Activity
ZAPS II Total animals
Activity
A
6
17
7
19
B
2
10
1
5
C
0
0
2
6
D
4
8
3
6
TABLE 20.12. TRAPPING RESULTS
FOR
M.
oehrogaster IN 1977
Plot
Site Variable
ZAPS I T°tal animals
- Activity
ZAPS II T°tal animalS
Activity
A
2
4
3
3
B
1
1
4
6
C
0
0
3
9
D
0
0
6
10
in substance from that described for the 1976 experiment. It is evident that
activity is more prominent on plots A and B. Assuming homogeneity of sam-
783
-------
pling, activity at ZAPS I for P. manioulatus is significantly greater on plots
A and B compared to plots C and D (X2 - 0.26; P < 0.005), but not on ZAPS II
(X2 = 3.36; 0.10 > P > 0.05) owing ostensibly to insufficient numbers of
trapped animals.
M. ochrogaster, like P. manioulatus, appeared in insignificant numbers on
ZAPS I to withstand any critical evaluation. Voles were found on all plots at
ZAPS II, and there appeared to be three distinct areas where they could be
found. These were the upper zone of plot B, lower end of plot C, and the
eastern half of plot A. On the basis of the previous years work, vole colo-
nies appear to have been established in new areas. Based on trapping efforts
their virtual absence from ZAPS I in 1977 is not readily explained, however.
Species Differences and Problems in Field Studies
Several lines of evidence presented in this report indicate that chronic
low levels of S02 influence the abundance and activity of free ranging popula-
tions of deer mice. This study produced insufficient evidence that the
prairie vole may be similarly affected. It is now known that M. oohrogaster
is especially resistant to pesticide toxicity compared to other vole species
(J. Gillett, pers. comm.). Furthermore, another species, M. pennsylvanious,
has been shown to be resistant to the long term toxicological effects of the
pesticide endrin at levels where P. manioulatus populations never recover
(Morris 1970). The deer mouse may therefore be a better candidate for assess-
ing low-level air pollution than the vole, a judgment felt appropriate in view
of the wide distribution of this species throughout the United States.
The modes of application of these small mammal studies to air pollution
impact assessment are not readily obvious. Although changes in behavior are
indicated as a bona fide response to SO?, the effect was not correlated with
the median S02 levels and was complicated by the presence of vole colonies on
plot B. Furthermore, there are multiple factors that influence the severity
of exposure (see beyond). These observations point out two problems associa-
ted with large-scale application of these results. First, a pollution gradi-
ent analysis of animal population structure may not demonstrate the presumed
effect of a pollutant or pollutants unless the gradient is steep (large dif-
ference in pollution levels at discrete distances from a point-source).
Secondly, the results may be confounded by the presence of other mammals that
may compete for the same resources required by the test population or species.
Furthermore, demonstrable changes may require long periods of trapping, a
factor that may not be compatible with available manpower and economic re-
sources in wide-area studies. These problems are likely to constrain field
research efforts unless accuracy and definitive results are sought.
Indirect Impact of Sulfur Dioxide at Different Trophic Levels
The interface between atmospheric gaseous pollutants and air-breathing
vertebrates is the respiratory tract comprising nasal passageways, trachea,
bronchi, and finally terminal bronchioles, alveolar sacs, and alveoli of Hi*
lungs. As bC>2 is probably the most toxic o± the gaseous emissions from coal-
fired power plants (other emission forms include particulates and flyash), its
effect on lung tissue and subsequent animal health before and after atmospheric
trans-
784
-------
1^ C°nS^derable interest to students of ecological impact
studies. The sulfur in coal is oxidized and released into the atmosphere.
The majority of this sulfur is in the form of sulfur dioxide and the remainder
(ca 2%) is predominantly sulfuric acid (Rail, 1974). All S02 is not neces-
sarily harmful. Sulfur is an essential growth element for plants, and sulfur
deficient soils (as in the coast range of California) must be supplied with
it. In high concentrations, the effects of S02 become noxious as decades of
research and observations have shown. The sulfate radical is not toxic but
sulfuric acid (or ammonium sulfate) can, in excess, build up soil acidity,
with resultant loss of cations such as calcium which secondarily affects
plant-forest productivity (Ovington, 1962). Indirectly, this deficiency could
reduce the forage quality for both primary and secondary consumers in areas
where cation stores are limited. Specific soil changes are complex and escape
generalization since they are linked to soil acidity, total exchangable cat-
ions, soil differentiation, etc. (Tamm, 1977). Furthermore, all chemical
changes may not be necessarily detrimental (Wood and Bormann, 1977).
Physiological Impact of Sulfur Dioxide on Vertebrates
Sulfur dioxide is highly soluble in the aqueous surface layer of the
respiratory tree, and is consequently rapidly removed from the upper respir-
atory passages. In low concentrations, it is a mild respiratory irritant
(Stokinger and Coffin, 1968). Characteristic signs of S02 injury include
bronchial narrowing or constriction, arrested or altered ciliary beat, and
inflammation of the mucous membranes (Frank and Speizer, 1965; Nadal, 1968;
Talmage, 1977). Functionally, these adverse symptoms denote increased airway
resistance, decreased effectiveness of lung clearance mechanisms, and epi-
thelial cell and submucosal tissue damage. The extra-pulmonary effects of 862
are virtually unknown. Ocular and nasal irritations also occur in higher
concentrations (10 ppm or greater) (Giddins and Fairchild, 1972). Deeper
penetration of sulfur dioxide does not occur unless it is in particulate form,
as for example the absorption of S02 of S0i+ onto the surface of an aerosol
(e.g., fog), which is 20 ym or less in diameter. Particulates 3 ym or less
are especially effective, because at this size about 80% of the particulates
entering the human lung are deposited in the alveolar ducts and sacs (Sam-
field, 1977). It is only when S02 penetrates to these terminal respiratory
surfaces that lung function is affected (Rail, 1974). Irritation in tracheo-
bronchial areas may produce discomfort but not necessarily lung pathologies or
respiratory dysfunction. Guinea pigs exposed for 12 months to S02 concentra-
tions up to-5.72 ppm showed no alterations in pulmonary function in several
standard tests (Alarie et at. , 1970). Similarly, female beagles exposed to
sulfur oxides demonstrated no changes in several hematological variables,
while sulfuric acid applied at levels of about 900 yg/m produced significant
changes in several pulmonary characteristics, including lung volume and carbon
monoxide diffusion capacity in addition to altered lung and heart weights
(Lewis et al., 1973). These results imply that sulfuric acid is far more
toxic to pulmonary function than is S02 gas. Of particular interest at this
point are the results of Amdur and Underhill (1970) who showed that open-
hearth dust at concentrations of 2.45 ppm or iron oxide (1.0 to 23 mg/m ),
both in aerosol form (< 0.3 ym diam), produced no detectable response in
guinea pig respiration or when combined with several levels (1.5 to 26 ppm) of
S02. These observations as well as those of others indicate that the S02 even
785
-------
in the presence of particulates may exert no detectable effects unless the S02
can be oxidized to sulfuric acid. Soluble metallic salts (e.g., manganese,
ferrous iron, vanadium,) can potentiate the effects of S02 by catalyzing the
oxidation of S02, whereas flyash or carbon particulates have no such poten-
tiating effect (Amdur and Underbill, 1968). Thus, sulfur dioxide per se may
not be an acute pulmonary health hazard until it is transformed into a more
toxic form or is in sufficiently high levels to produce its irritating ef-
fects. These and other findings are discussed in depth in a recent document
(Subcommittee, 1977).
Proposed Effects of S02 Upon ZAPS Small Mammals
Based upon the above brief discussion, one can examine the results of the
ZAPS study in the light of two theoretical viewpoints. Firstly, deer mice may
respond to S02 because of its irritant nature; it may produce multiple dis-
comforts without affecting pulmonary function. Depletion of deer mice from a
polluted area may result from avoidance behavior accentuated by the presence
of particulates of appropriate size, density, shape and chemical composition,
and which are capable of oxidizing S02.
Secondly, while the irritation produced by S02 (inter alia) may not
constitute a direct health problem for mice at the relatively low concentra-
tions produced by some power plants, it may nevertheless place a susceptible
animal at a competitive disadvantage if an animal's survival depends on its
frequent ability to maintain silence uninterrupted by coughing or sneezing and
thereby alerting a nearby predator. A similar case may be developed for a
pregnant animal that aborts when irritating fumes produce strong sensations to
the olfactory receptors. More generally, the effect of a sublethal pollutant
can be effective if it produces reactive behaviors in an animal that jeopar-
dize its survival or that of its progeny or indirectly modifies steady-state
processes for a sufficient period to elicit declines in animal performance.
What seems clear from these ideas is that to accurately assess the impact
of a candidate pollutant requires more than the knowledge of its concentration
and fraction of it reaching the organism. Depth of penetration, clearance
mechanisms, and interaction with other pollutants or particulate emissions are
critical in establishing the severity of inhalation exposure to power plant
emissions. Gaps in our knowledge of these processes have been voiced recently
in detail (Stuart, 1976).
Biological Contributions of Small Mammals
Small mammals (mice, voles, shrews, squirrels, etc.) are widely distri-
buted across the North American continent, and affect the soil, vegetation,
and the predators who eat them. These interactions are exceedingly complex.
Heavy grazing (as in a population high) may impair not only the standing crop
but eliminate a plant species as well. If less severe, grazing may stimulate
new growth (Goszcynska and Goszcynski, 1977). Plant consumption helps to
short circuit the mineralization process of organic material by virtue of the
high rate of energy transformation in small mammals (Golley et al. , 1975).
Seed consumption may favor seed dispersal. Surface activity, especially the
establishment of microtine trails, can be extensive, allowing the growth of
786
-------
exotic specxes and producing a vegetational mosaic (Batzli, 1975). Burrows
favor soil water retention and excretory products may contribute to soil
fertility. In the Cols trip area, deer mice are the most abundant of the small
mammals.^ Their populations are relatively stable and exert little grazing
effects in this area dominated by grazing cattle, which probably affect the
vegetational quality and distribution more than all small rodents combined.
Deer mice are facultatively insectivorous and may exert some degree (probably
small) of insect control. In brief, small mammals of the grasslands are
valuable resources and probably do no harm to the landscape.
CONCLUSIONS
Overnight live trapping of ZAPS plots in 1976 and 1977 showed AUcAO&iA
OdhSiOgoAteSi and PeAomuAccM maniculcutuA as the most abundant small mammals,
about 74% of them P. maniCLuZatuA. Greater numbers of both species existed
at ZAPS II, although animal biomass increased throughout late summer at both
ZAPS plots. The colony-forming voles showed non-uniform distributions that did
not appear to change with time. No conclusions could be drawn as to their
sensitivity to S02- On the other hand, the ubiquitous deer mouse showed sev-
eral distinct patterns of movement or trapping indicating S02 sensitivity.
These patterns included larger numbers of adult mice on control plots, espec-
ially in mid to late summer; larger numbers of juvenile transients on plots A
and B, compared to plots C and D, especially at ZAPS II; and substantially
greater animal activity within control plot A, compared to plots B, C, and D.
Despite these observations, the population effects of exposure to ceal-fired
power plant emissions cannot yet be fully evaluated. However, this study in-
dicates that small mammal populations may be affected by long term exposure to
relatively low S02 levels.
ACKNOWLEDGEMENT S
I am indebted to several individuals who patiently assisted me in the
collection of animal data: T. Gullett, J. Rothermel, J. M. Chilgren, J.
Unwin, and A. McPherson. In addition I have appreciated the encouragement
afforded by R» A. Lewis, M. L. Morton, and E. Preston.
REFERENCES
Alarie, Y., C. E. Ulrich, W. M. Busey, H. E. Swann, Jr., and H. N. McFarland.
1970. Long-Term Continuous Exposure of Guinea Pigs to Sulfur Dioxide.
Arch. Environ. Health, 21(6):769-777.
Ambrose, H. W. 1969. A Comparison of MioTotus pennsylvanieus Home Ranges as
Determined by Isotope and Live Trap Methods. Amer. Midi. Nat., 81:535-
555.
Amdur, M. 0. and D. W. Underbill. 1968. The Effect of Various Aerosols on
the Response of Guinea Pigs to Sulfur Dioxide. Arch. Environ. Health,
16:460-468.
Amdur, M. 0. and D. W. Underbill. 1970. Response of Guinea Pigs to a Combi-
nation of Sulfur Dioxide and Open Hearth Dust. J. Amer. Poll. Cont.
Assoc., 20:31-34.
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Batzli, G. 0. 1975. The Role of Small Mammals in Arctic Ecosystems. In:
Small Mammals: Their Productivity and Population Dynamics, F. B. Golley,
K. Petrusewicz, and L. Ryszkowski, eds. Cambridge University Press, N.Y.
pp. 243-268.
Brown, L. E. 1966. Home Range and Movement of Small Mammals. Proc. Zool.
Soc. London, 18:111-142.
Davis, D. E. 1964. Manual for Analysis of Rodent Populations. University
Microfilms, Ann Arbor, Michigan. 82 pp.
Delaney, M. J. 1975. The Ecology of Small Mammals. Crane, Russak & Co.,
N.Y. 60 pp.
Eadie, W. R. 1953. Response of Microtus to Vegetative Cover. J. Mammal.,
34:263-264.
Frank, N. R. and F. E. Speizer. 1965. S02 Effects on the Respiratory System
in Dogs: Changes in Mechanical Behavior at Different Levels of the
Respiratory System During Acute Exposure to the Gas. Arch. Environ.
Health, 11:624-634.
French, N. R., D. M. Stoddart, and B. Bobek. 1975. Patterns of Demography in
Small Mammal Populations. In: Small Mammals: Their Productivity and
Population Dynamics, F. B. Golley, K. Petrusewicz, and L. Ryszkowski,
eds. Cambridge University Press, N.Y. pp. 73-102.
Giddens, W. E. and G. A. Fairchild. 1972. Effects of Sulfur Dioxide on the
Nasal Mucosa of Mice. Arch. Environ. Health, 25:166-173.
Golley, F. B., L. Ryszkowski, and J. T. Sokur. 1975. The Role of Small
Mammals in Temperate Forests, Grasslands and Cultivated Fields. In:
Small Mammals: Their Productivity and Population Dynamics, F. B. Golley,
K. Petrusewicz, and L. Ryszkowski, eds. Cambridge University Press, N.Y.
pp. 223-242.
Goszczynska, W. and J. Goszczynski. 1977. Effect of the Burrowing Activities
of the Common Vole and the Mole on the Soil and Vegetation of the Bio-
cenoses of Cultivated Fields. Acta Theriol., 22:181-190.
Harvey, M. J. and R. W. Barbour. 1965. Home Range of Microtus oohrogastev as
Determined by a Modified Minimum Area Method. J. Mammal., 46:398-405.
Lewis, T. R.,W. J. Moorman, W. F. Ludmann, and K. I. Campbell. 1973. Toxic-
ity of Long-Term Exposure to Oxides of Sulfur. Arch. Environ. Health,
26:16-21.
Metzgar, L. H. 1973. Exploratory and Feeding Home Ranges in Peromysous. J.
Mammal., 54(3):760-763.
Morris, R. D. 1970. The Effects of Endrin on M-icrotus and PeromysGUS. I.
Unenclosed Field Populations. Can. J. Zool,, 28:695-708.
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Nadal, J. A. 1968. Mechanisms of Airway Response to Inhaled Substances.
Arch. Environ. Health, 16:171-174.
Ovington, J. D. 1962. Quantitative Ecology and the Woodland Ecosystem Con-
cept. Adv. Ecol. Res., 1:103-192.
Rail, D. P. 1974. Review of the Health Effects of Sulfur Dioxide. Environ.
Health Perspect., 8:97-121.
Samfield, M. 1977. Hazardous and Toxic Air Pollutants. Energy Sources,
Stickel, L. F. 1960. Peromysous Ranges at High and Low Population Densities.
J. Mammal., 41:433-441.
Stickel, L. F. 1968. Home Range. In: Biology of Peromysous (Rodent ia ), J.
A. King, ed. Sp. Publ. No. 2. Amer. Soc. Mammalogists. pp. 373-411.
Stokinger, N. E. and D. L. Coffin. 1968. Biologic Effects of Air Pollution.
In: Air Pollution, A. C. Stem, ed. Academic Press, N.Y. pp. 445-546.
Stuart, B. 0. 1976. Deposition and Clearance of Inhaled Particles. Environ.
Health Perspect. , 16:41-53.
Subcommittee on Airborne Particles, Committee on Medical and Biologic Effects
of Environmental Pollutants. National Research Council, NAS. 1977.
Airborne Particles. EPA-600/1-77-053. Research Triangle Park, North
Carolina. 555 pp.
Talmage, S. S. 1977. Humans: Metabolism and Biological Effects. In: En-
vironmental, Health, and Control Aspects of Coal Conversion: An Infor-
mation Overview, H. M. Baaunstein, E. D. Copenhaver, and H. A. Pfuderer,
eds. ORNL/EIS-95, Oak Ridge National Laboratory, Oak Ridge, Tennessee.
Ch. 10, Vol. 2, 99 pp.
Tamm, C. 0. 1977. Acid Precipitation and Forest Soils. Water, Air, and Soil
Pollution, 7:367-370.
Taylor, J. E. and W. C. Leininger. 1978. Monitoring Plant Community Changes
Due to S02 Exposure. In: The Bioenvironmental Impact of a Coal-fired
Power Plant, E. M. Preston and R. A. Lewis, eds. 3rd Interim Report,
Colstrip, Montana. EPA-600/3-78-021. Environmental Protection Agency,
Corvallis, Oregon, pp. 376-384.
Terman, C. R. 1968. Population Dynamics. In: Biology of Peromyseus (Ro-
dentia), J. A. King, ed. Sp. Publ. No. 2. Amer. Soc. Mammalogists. pp.
412-449.
Wood, T. and F. H. Bormann. 1977. Short-term Effects of a Simulated Acid
Rain Upon the Growth and Nutrient Relations of Pinus strobus , L. Water,
Air, and Soil Pollution, 7:479-488.
789
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AN EXPERIMENTAL EVALUATION OF THE FATE AND IMPACT OF SELECTED TRACE
ELEMENT STACK EMISSIONS IN THE SOIL-PLANT ENVIRONMENT
791
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SECTION 21
THE FATE AND BIO ENVIRONMENTAL IMPACT OF MERCURY IN SOILS
E. R. Landa
ABSTRACT
Five surface soils from southeastern Montana
were utilized in these studies. The volatile loss
of mercury applied to these soils as mercuric nitrate
and methylmercury chloride was stimulated by elevated
temperatures and repressed by excessive moisture or
dryness. The addition of glucose stimulated the vo-
latile loss of mercury in the case of mercuric nitrate,
but repressed it in the case of methylmercury chloride.
Mercury sorbed by soils previously exposed to elemen-
tal mercury vapor was shown to volatilize at 100-200 C,
and to probably exist as a soil organo-complex. Short-
term respiration studies involving soil amendment with
mercuric chloride showed mercury levels greater than
40 yg/g were required to inhibit carbon mineralization.
Longer-term respiration studies showed inhibition at
levels from 0.1 to greater than 100 yg Hg/g depending
on the soil type. Western wheatgrass seedlings grown
on soils amended with mercuric nitrate showed aerial
tissue concentration factors of 0.01 to 0.12.
INTRODUCTION
With the development of the energy resources of the western United
States have come concerns regarding the environmental impact of the emissions
associated with power-generation on the grassland biome. While coal from
the Powder River Basin of northeastern Wyoming and southeastern Montana
contains an average of only 0.09 ppm Hg (Swanson et at. , 1974), the scrubbers
and electrostatic precipitators used to control air pollution from coal-
fired power plants are ineffective in the removal of Hg, and about 90% of
that in the coal is released to the environment (Billings and Matson, 1972;
Montana State Department of Natural Resources and Conservation, 1974). In
addition to the vast coal resources of the western states, there exists
numerous sites for the potential development of geothermally-powered electric
generating plants. Mercury present in such geothermal reservoirs can be
792
-------
released to the surface environment with the live stream during drilling and
venting, and from the spent steam in condensate ponds (U.S. Dept. of Interior
1973; Siegel and Siegel, 1975).
The toxicity of mercury to man has been recognized since the 16th cen-
tury (D'ltri, 1972). When operating at full capacity, the stacks of Colstrip
Units 3 and 4 (700 MW each) will each emit an estimated 55 grams of mercury
per hour (Montana State Department of Natural Resources and Conservation,
1974).Q The chemical nature of the mercury emitted has not been determined,
but Hg and Hg2+ appear to be likely candidates. In the environment, either
of these forms is subject to a variety of transformations, including methyla-
tion (D'ltri, 1972).
The major foci of the soils research on this project have been study
of:
(1) the volatile loss of soil-applied inorganic and organic mercury,
(2) the retention of metallic mercury vapor by soils,
(3) the uptake from soil of divalent inorganic mercury by plants,
(4) the effect of divalent inorganic mercury on soil microbial respira-
tion.
The Volatile Loss of Soil-Applied Inorganic Divalent Mercury
Mercury is an environmentally mobile element, cycling through the
lithosphere, atmosphere and hydrosphere. The volatile loss of applied
inorganic divalent mercury from soils was first reported by Zimmerman and
Crocker (1933, 1934) who observed foliar damage in plants grown near soils
treated with either mercuric bromide, chloride, cyanide, iodide, nitrate,
oxide or sulfate. The damage was similar to that seen with exposure to
metallic mercury vapor, and indeed the presence of this species was demon-
strated in the atmosphere above soil treated with HgCl2. Several recent
investigations (Gracey and Stewart, 1974; Johnson and Braman, 1974) have
quantified the loss of mercury from soils amended with inorganic mercuric
salts.
Alberts et al. (1974) showed that the loss of Hg from Hg(N03)2 -humic
acid suspensions was as metallic mercury, Hg , and that the process was
probably abiotic. DeFilippis and Pallaghy (1975) showed ethylene and ace-
tylene capable of non-enzymatically reducing mercuric-Hg, in aqueous solution
as HgCl2, to a volatile form, presumably Hg . However, volatilization of Hg
by a variety of microorganisms in vitro has also been demonstrated. Thayer
(1976), and Ben-Bassat and Mayer (1975) reported the loss of Hg from HgCl2-
amended cultures of the alga Euglena gTaeilisis and ChloTella pyvenoidosa
respectively. Brunker and Bott (1974) showed a yeast of the genus Cryptoeoc-
cus capable of reducing Hg(II) to its elemental state. Sayler et at.
(1975) isolated a species of Pseudomonas from Chesapeake Bay sediments
capable of reducing Hg(II) to volatile Hg .
Frear and Dills (1967), using mortality in insect eggs exposed to the
atmosphere above an Hg(II)-amended Hagerstown silt loam as an index of vola-
tile mercury loss, found losses to increase with temperature from 1 to 25 C,
and with soil moisture from 1 to 18%.
793
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The Volatile Loss of Mercury From Soils Amended With Methylmercury Chloride
Due to the ability of methylmercury to cross the blood-brain barrier
and cause irreversible brain damage in mammals (i.e. Minamata disease), its
formation in soils and aquatic sediments subject to mercury amendment by
industrial discharges or the agricultural usage of mercurials has been an
area of considerable concern and investigation.
In studies on methylmercury synthesis, several investigators have
reported the apparent loss of this compound from sediment and soil systems.
Laboratory studies of aerated lake sediment-water systems by Spangler et al.
(1973a) showed a build-up in methylmercury during the first 50 days of
incubation with mercuric chloride, followed by a rapid decrease in the
quantity of methylmercury in the system. River sediments treated with
mercuric chloride (Jacobs and Keeney, 1974; Van Fraasen, 1975; Olson and
Cooper, 1976) or phenylmercuric acetate (Jacobs and Keeney, 1974), and soils
treated with mercuric nitrate (Rogers, 1976) showed an apparent decrease in
methylmercury concentration with time. Kimura and Miller (1964) showed
mercury losses of 6-14% to occur over a period of 35 days from a moist
Puyallup sandy loam soil amended to about 80 ppm Hg applied as methylmercury
dicyandiamide or methylmercury chloride.
The work reported here focuses on the roles of microbial activity,
temperature and moisture on the volatile loss of mercury from soils amended
with methylmercury chloride.
The Retention of Metallic Mercury Vapor by Soils
The sorption of metallic mercury vapor (Hg ) by soils is of interest to
geochemists concerned with the genesis of mercury ore bodies and with the
environmental fate of atmospheric pollutants. Mercury may be introduced
into the atmosphere from natural sources including zones of active volcanism
and mercury mineralization, and by a range of human activities including ore
refining and coal combustion.
The maximum mercury concentration measured by the U.S. Geological
Survey (McCarthy et al., 1970) in the air over unmineralized, non-industrial
areas of the western United States ranged from 0.003 to 0.009 yg/m3. A
survey by Jepsen (1973) of elemental mercury vapor concentrations in the air
of selected U.S. urban areas showed levels up to 4 yg Hg /in3. The mercury
vapor concentration of the air above fumaroles in Hawaii has been reported
to be about 22 yg/m3 (Eshleman et al.3 1971), while concentrations as high
as 2000 yg/m3 have been reported for the air in mercury mines (McCarthy et
aZ.j 1970). Mercury vapor concentrations of 2 to 31 yg/m3 have been measured
in flue-gas resulting from the combustion of coals containing 0.15 to
0.3 ppm Hg (Billings and Matson, 1972; Diehl et al.,, 1972). The threshold
limit value for occupational exposure to mercury vapor in air has been set
at 10 and 100 yg/m3 in the U.S.S.R. and the U.S.A. respectively (Schroeder,
1970).
Metallic mercury vapor (Hg ) was reported as thet dominant Hg species in
the near-ground atmosphere of the Tampa Bay, Florida area (Johnson and
794
-------
Braman, 1974), and in the incoming steam and gaseous effluents at two geo-
thermal power plants in California and Mexico (Robertson et al.3 1977)
Piperno (1975) reported mercury to occur principally in the elemental form
in coal combustion emissions.
The retention of Hg vapor by clays and organic matter (Koksoy and
Bradshaw, 1969) has been postulated as causative factors in the occurrence
of mercury anomalies ("haloes") surrounding ore bodies. Trost and Bisque
(1972) examined the sorption of Hg by soil components, and found much
greater sorption (per unit weight) by organic materials as compared to clay
minerals. The objective of the work reported here was to examine the sorption
of Hg by a range of surface soils.
The Effect of Mercuric Chloride on Carbon Mineralization in Soils*
The fungicidal and bactericidal properties of mercurial compounds has
long been recognized and utilized in agriculture and medicine. However,
little attention has focused upon the quantitative assessment of the impact
of inorganic mercuric compounds on soil microorganisms in situ.
Mercuric ion toxicity presumably is a consequence of the displacement
of the normal suite of catalytic metal ions from their binding sites on a
protein, particularly the sulfhydryl groups, and the resultant impairment of
enzyme function (Hughes, 1972). Two common soil fungi, Aspergittus niger and
Peni-eitlium notation^ were found to grow normally in liquid medium containing
up to 10 ppm Hg as HgCl2 (Hardcastle and Mavichakana, 1974). Oxygen-
consumption by baker's yeast (Saooharomyoes oerevisi,ae) grown in liquid
culture was severely limited at 100 ppm HgCl2 (Kokke, 1974). Tonomura et
at. (1968) reported on a mercury-resistant, soil-isolated Pseudomonas
whose growth was uninhibited at HgCl2 levels in solution culture of below
450 ppm. Van Faassen (1973) showed 100 ppm HgCl2 amendment of two soils
(one of which had a history of treatment with mercurial fungicides) to have
little effect on the number of microbes plated, but to reduce carbon and
nitrogen mineralization and dehydrogenese activity. Peterson (1962) showed
that moistening of a silty clay loam soil to 87 percent of its water holding
capacity with either 0.001 or 0.01 M HgCl2 reduced its oxygen consumption in
50 hours by 24 or 80%, respectively.
This study was designed to assess the short- and long-term effects of
mercuric chloride amendments to a variety of soils on CO2-evolution from
glucose and native soil carbon substrates.
The Uptake From Soils of Inorganic Divalent Mercury by Plants
With the release of mercury to the grassland ecosystem of the Northern
Great Plains by coal combustion and geothermal energy exploitation comes the
potential for bioaccumulation of mercury. Western wheatgrass (Agropyron
smUhii) is a widely distributed range species in the western United States
and Canada, and is often the dominant species in the Northern Great Plains
(Martin, 1969). Little is known regarding its uptake of heavy metals, a
Work done jointly with S. C. Fang.
795
-------
computerized search of Biological Abstracts since 1972 revealing only a
single study (Munshower and Behan, 1971). The uptake of mercury from soils
by western wheatgrass was therefore studied in a greenhouse experiment.
MATERIALS AND METHODS
The five surface soils (0-20 cm depth) utilized in these studies were
collected in May, 1976 from uncultivated sites in Treasure and Powder River
Counties, Montana. The soils were air-dried and ground to pass a 2 mm
sieve. The soil pH (1:2 soil:water), calcium carbonate equivalent, organic
carbon (Walkley-Black titration), total Kjeldahl nitrogen, extractable P
(0.5 M sodium bicarbonate, pH 8.5), total soluble salts (saturation extract
electrical conductivity), extractable potassium and sodium, and cation
exchange capacity (IN ammonium acetate, pH 7) were determined (Kauffman and
Gardner, 1976). Native soil mercury levels were determined by flameless
atomic absorption spectrometry following digestion of the soil with aqua
regia. Particle size analysis was by the pipette method (Day, 1965). The
1/3-bar and saturation moisture percentages was determined by the method of
the U.S. Salinity Laboratory Staff (1954). The results of these analyses
are presented in Tables 21.1 and 21.2.
The Volatile Loss of Soil-Applied Inorganic Divalent Mercury
Microbial Aspects of the Volatile Loss of Soil Applied Inorganic Hg (II)
Prior to Hg(II) amendment, the soils were either untreated, autoclaved
at 121 C for 1 hour, incorporated with glucose at a 1% (w/w) rate, or incor-
porated with glucose (1% w/w) and KN03 (0.3% w/w).
Three replicate samples of each soil, 70 g (oven-dry basis) were amended
to 1 yg Hg/g soil using 203Hg-Hg(N03)2 applied with sufficient water to
reach the 1/3-bar moisture content. The amended soils, contained in 150 ml
plastic cups, were covered with 40 g of coarse quartz sand, watered every
other day to the 1/3-bar moisture level and maintained at room temperature
(18-25 C) in a forced-draft fume hood.
The loss of Hg from the soils was monitored by radioassay of the entire
soil mass using a small animal, whole-body, liquid scintillation spectrometer
system (Armac model 446, Packard Instrument Co.). A special sample holder
established a reproducible counting geometry in the sample well. The samples
were counted, using the 0.28 MeV y-radiation emitted by 203Hg, immediately
after soil amendment, every other day for the first 10 days, and at weekly
intervals for the next 4 weeks.
To determine if any Hg volatilization process might be reactivated after
38 days, the autoclaved soils were irrigated with an inoculum solution
(supernatant of an incubated and settled 2% w/w soilrwater slurry) to
reintroduce the indigenous microflora. The glucose-, and glucose plus KNOs-
treated soils were irrigated with 1% solutions of the respective substrates.
The moisture content of these samples was maintained at the 1/3-bar level
using the inoculum, glucose or glucose plus KN03 solutions rather than di-
stilled water. These samples were monitored for an additional 2 weeks.
796
-------
TABLE 21.1. PHYSICAL PROPERTIES OF SELECTED EASTERN MONTANA SOILS
Soil
Series
Classification
Sand Silt Clay Water Holding
Capacity. Z
'' /° % 1/3-bar Saturation
Arvada Ustollic Natrargid, 35 25 40 31
fine, montmoril-
lonitic, mesic
Campspass Typic Eutroboralf 19 55 25
fine, montmoril-
lonitic
Heldt Usteric Camborthid, 27 48 25
fine, taontmoril-
lonitic, mesic
Bainville Ustic Torriorthent, 29 42 29
fine, silty, mixed
(calcareous), mesic
Terry Ustollic Haplargid, 74 14 12
coarse-loamy, mixed,
mesic
33
21
21
10
54
80
52
45
37
TABLE 21.2. CHEMICAL PROPERTIES OF SELECTED EASTERN MONTANA SOILS
Soil
Series
Arvada
Campspass
Heldt
Bainville
Terry
PH
8.1
6.6
8.3
7.5
8.3
CaC03
equiv.
%
0.08
—
3.92
0.04
0.20
Organic
c,
%
1.6
6.7
1.7
1.0
0.9
Total
N,
%
0.10
0.27
0.12
0.08
0.10
Extractable
P
ppm
3
5
1
2
1
K
ppm
526
203
186
231
84
Na
meq/lOOg
0.87
0.07
0.08
0.07
0.07
Total
Soluble Salts
mmho/ctn
0.43
0.35
0.35
0.28
0.31
Cation
Exchange
Capacity
meq/lOOg
22.2
25.5
11.4
15.8
8.4
Total
Hg
Mg/kg
<60
130
183
73
<60
797
-------
Soil Water Content and Soil Temperature as Factors in the Volatile Loss
of Soil-Applied Inorganic Hg (II)
The soils, in 70 g (oven-dry basis) portions, were amended to 1 yg Hg/g
soil using 203Hg-Hg(N03)2 applied with sufficient water to reach the 1/3-bar
or 80% saturation moisture content. The amended soils, contained in 150 ml
plastic cups, were covered with 40 g of coarse quartz sand, and watered
every other day to maintain the desired moisture level. The moisture con-
tents maintained at room temperature (18-25 C) were 80% saturated or 1/3-
bar. A third set of samples was initially moistened to the 1/3-bar level,
then allowed to air-dry; after 25 days the soils were re-moistened to the
1/3-bar level. The temperature studies were run at room temperature, 10 or
35 C, the latter two temperatures controlled by immersion of the cups in a
water bath, and involved samples maintained at the 1/3-bar moisture content.
There were 3 replicates per soil in each experiment and all samples were
stored in a forced-draft fume hood.
The loss of Hg from the soils was monitored by radioassay of the entire
soil mass as described above. After 38 days, the samples equilibrating at
10 C were brought to room temperature and monitored for an additional 2 weeks
The Volatile Loss of Mercury From Soils Amended with Methylmercury Chloride
In order to examine the role of the microbial population in the volati-
lization process, the soils were either untreated, autoclaved at 121 C for
1 hour, or supplemented with glucose (1% w/w) and KNOs (0.3% w/w) prior to
mercury amendment. Three replicate samples of each soil (70 g, oven-dry
basis) were amended to 1.0 yg Hg/g soil using methylmercury chloride, 203Hg-
CHsHgCl, applied with sufficient water to reach the 1/3-bar moisture content.
The amended soils, contained in 150 ml plastic cups, were covered with 40 g
of coarse quartz sand, watered every other day to the 1/3-bar moisture level
and maintained at room temperature (20-27 C) in a forced-draft fume hood.
In order to examine the influence of soil moisture content and tempera-
ture on the volatilization process, soils in 70 g portions were similarly-
amended to i.O yg Hg/g soil with methylmercury chloride applied with suffi-
cient water to reach either the 1/3-bar or 80% of saturation moisture con-
tent, and were maintained at room temperature at these respective moisture
contents by alternate-day distilled water additions. A third set of samples
was initially moistened to the 1/3-bar level, then allowed to air-dry; after
28 days these soils were re-moistened to the 1/3-bar level. The temperature
studies were run at room temperature (20-27 C), or controlled at 16 or 35 C
by immersion of the cups in a water bath. Samples were maintained at the
1/3-bar moisture content, replicated 3 times and were kept in a forced-draft
fume hood.
The loss of Hg from the soils was monitored by radioassay of the entire
soil mass as described above. The samples were counted using the 0.28 MeV
y-radiation of the 203Hg immediately after soil amendment, every-other day
for the first 12-18 days and at weekly intervals for the next 5-6 weeks.
798
-------
The Retention of Metallic Mercury Vapor by Soils
Forty gram (oven-dry basis) portions of air-dried soil were placed in
100 mm diameter polystyrene petri dishes and stacked in a 23 liter glass
bell jar (Figure 21.1). There were 3 exposure runs and 10 plates of each of
the 5 S™\S Per rUn (200° S °f S0il per run)' MercurY vapor was generated
from a UcSHg-labelled metallic mercury source having an initial specific
activity of 60 mCi/g which was contained in a thermoregulated water bath to
control vapor concentration. Air was passed over this metallic mercury and
down a glass inlet tube to the bottom of the bell jar which contained the
soil samples. The petri dishes of each soil were arranged randomly in a 13-
tier support rack within the bell jar. The air exited near the top of the
bell jar with the flow rate maintained at 200 ml/min. A magnetically-driven
fan at the base inside the bell jar mixed the air within the jar such that
the outlet vapor concentration of Hg was assumed to be the ambient concentra-
tion (Slatyer, 1971) . The internal surfaces of the bell jar and the petri
dish support rack were lightly coated with petroleum jelly to minimize the
sorption of mercury vapor.
Air exiting the bell jar passed through a series of traps containing
Hopcalite, a granular copper-manganese oxide material (Magos, 1966), to trap
the mercury vapor. The traps were radioassayed on alternate days using a
Nal y~scintillation detector. The soils were exposed to air containing an
average outlet concentration of 14.3 yg Hg/m3 for 10 days and then purged
for 2 days with room air. During the exposure and purging periods, the
soils were at room temperature (22-34 C).
At the end of each purge period, the plates of each of the five soils
were radioassayed using a small animal, whole-body, liquid scintillation
spectrometer system (Armac model 446, Packard Instrument Co.) and then the
individual soils were bulked and mixed.
To assess the volatile loss of the retained mercury vapor from these
soils, 60 g (oven-dry basis) samples of soil covered with 40 g of coarse
quartz sand and maintained at room temperature either air-dry or at the 1/3-
bar moisture content (by alternate day additions of distilled water) in
small plastic cups kept in a forced draft fume hood, were monitored for
16 days using the Armac system.
To assess the heat lability of the retained mercury, 1.5 g samples of
soil contained in 2 ml shell vials were heated in an oven for 2 days to
temperatures ranging from 80 to 450 C. A fresh sample was used for each
temperature, and there were 3 replicates per soil per temperature. The
fraction of the initially-retained mercury remaining following the heat
treatment was determined by radioassay of the vials using a Nal y-scintilla-
tion spectrometer (Packard Auto-Gamma Spectrometer Model 5230).
To assess the extractability of the mercury by various chemical agents,
10 g (oven dry basis) of each soil in triplicate were extracted by overnight
shaking at room temperature with 20 ml of the following solutions:
(a) distilled water
(b) W KC1
799
-------
Hg° VAPOR
BY-PASS
TRAPS
REGULATED
FLOWMETER
t
AIR m
MERCURY
VAPOR
GENERATOR
WATER BATH
Hg° (203Hg) SOURCE
VAPOR
TRAPS
MAGNETIC
FAN DRIVE
BELL JAR
Figure 21.1. Schematic representation of system used to expose
soils to metallic mercury vapor.
800
-------
(c) IN CaCl2
(d) IN HC1
(e) W NaOH
(f) 0.5M acetylacetone (2, 4-pentanedione)
(g) Q.5M cupferron (the NH4-salt of tf-nitrosophenylhydroxylamine)
(h) 0.5^ Cu (C2H302)2
(i) .005M DTPA (diethylenetriamine pentaacetic acid): 0.01M triethano-
lamine: 0.1M CaCl2; pH 7.3 solution.
(j) 0.1M cysteine (extraction run at 4 C to inhibit microbial activity)
(k) benzene
(1) methanol
After shaking, the tubes were centrifuged at 27,000 x G for 10 minutes, and
4 ml aliquots of the supernatant were sampled for radioassay using the Nal
spectrometer.
The Effect of Mercuric Chloride on Carbon Mineralization in Soils
Short-term radiorespirometric studies utilized uniformly-labelled 14C-
glucose. Five grams of soil was transferred to each reaction flask contain-
ing 10 ml of water, or HgCl2 solution (1 x 10~4 M to 1 x 10~3 A?) spiked with
0.5 yCi (0.43 yg) of 14C-glucose. The samples were maintained at 25 C for 6
hours and continually flushed with C02-free air. Respired 14C02 was trapped
in 0.5 N NaOH, precipitated as BaCOs, transferred to a weighed glass fiber
filter disc and assayed with a windowless gas flow proportional counter.
Correction was made for self-absorption by the BaCOa filter cake. Each
treatment was replicated four times.
Long-term studies utilized no added carbon substrate. Bulk soil samples
were moistened to 50% of the 1/3-bar moisture holding capacity with distilled
water and incubated for one week at 25 C. The soils were amended to 0, 0.1,
1.0, 10, or 100 yg Hg (as HgCl2)/g soil with sufficient water to bring them
to the 1/3-bar moisture level. Twenty-five gram samples (oven-dry basis) of
treated soil were placed in 1 quart mason jars containing a flask with 10 ml
of dilute standardized NaOH. The jars were sealed, maintained at 25 C, and,
at weekly intervals for a month, opened for reaeration and sampling of the
NaOH traps. Carbonates were precipitated as BaCOs and the remaining alkali
titrated with HC1 as outlined by Stozky (1965). Each treatment was repli-
cated three times.
The Uptake from Soils of Inorganic Divalent Mercury by Plants
The soils, in 70 g (oven-dry basis) portions were amended with 1.0 yg
Hg/g soil using 203Hg-Hg(N03)2 applied with sufficient water to reach the
1/3-bar content, and contained in plastic cups without drainage holes.
There were 3 replicates per soil per treatment. After a 24 hour equilibration
period, twenty seeds of "Rosana" western wheatgrass were applied to the
surface of the soil and covered with 40 g of moist sand. The plants were
grown in a chemical fume hood located in a greenhouse. Distilled water was
added on alternate days to make up for evapotranspiration losses and bring
the soils back to the 1/3-bar moisture content. No fertility amendments
were made to the soil either initially nor during the course of the experi-
ment. Natural illumination was supplemented by incandescent lights (G.E.
801
-------
Gro-Sho; 16 hour day length) whose heat was dissipated by a flowing-water
filter cell. Twenty-two days after planting, the above-ground tissue was
harvested, radioassayed using an Nal y-scintillation spectrometer (Packard
model 5230) and dried at 80 C. Tissue Hg concentrations were calculated
from the specific activity of the added Hg assuming no dilution by the
endogenous soil mercury pool.
In order to assess the extent of volatile loss of the added Hg from the
soils during the course of plant growth, soil 203Hg content was monitored by
radioassay of the entire soil mass using a small animal, whole-body, liquid
scintillation spectrometer system (Armac model 446, Packard Instrument Co.).
A special sample holder established a reproducible counting geometry in the
sample well. The samples were counted using the 0.28 MeV y-radiation of the
203Hg after soil amendment, and again after tissue harvest.
RESULTS AND DISCUSSION
The Volatile Loss of Soil-Applied Inorganic Divalent Mercury
Microbial Aspects of the Volatile Loss of Soil-Applied Inorganic Hg (II)
Figure 21.2 shows the effects of the treatments to suppress and to
stimulate microbial activity on the volatilization of Hg f»rom the soils
examined. In general, autoclaving reduced the total loss, while glucose
additions increased the initial loss rate of the applied Hg(II) from these
soils. After 38 days, neither the addition of a microbial inoculum to the
autoclaved soils, nor fresh additions of C or C + N substrate to the glucose-
or glucose plus KNO3-supplemented, non-sterile soils provide for any further
Hg losses. With the exception of the Bainville soil, the addition of a
nitrogen source to the glucose had little effect on the losses observed,
suggesting that a C:N ratio imbalance was not, in general, involved in the
termination of Hg loss. The coefficient of variation for these experiments
averaged 1.3%.
As it was not possible to suppress microbial growth in the autoclaved
soils after the start of the experiment, the Hg losses seen here may be the
result of an abiotic volatilization process and/or a biologically-mediated
process associated with the recolonization of the autoclaved soil (Baker,
1962). Other workers have reported soil sterilization to decrease the loss
of Hg from soils amended with HgCl2 (Rissanen, 1973), phenylmercurie acetate
(PMA) and ethylmercuric acetate (Kimura and Miller, 1964), although in the
case of PMA, the rate of loss after the first 2 weeks was in excess of that
observed in non-sterile systems. Frear and Dills (1967) attribute the pro-
gressive decrease in the quantity of Hg evolution they observed with HgCl2
amendments above 300 yg Hg/g soil to mass action effects. However, in the
300 to 2400 yg Hg/g soil range they examined, inhibition of microbial activi-
ty by Hg toxicity must certainly be considered a possible causal factor.
The marked acceleration of the Hg loss rate accompanying glucose incor-
poration, seen particularly in the Heldt and Terry soils, together with the
suppression of loss associated with autoclaving, suggests a major role for
the soil biota. Brunker and Bott (1974) showed the mercury content of an
802
-------
ARVADA
a
UJ
_i
CL
0.
<
u.
O
o
b
<
{£
U.
CAMPSPASS
HELDT
-o..
I
Non-Autocloved
Autocloved
Non-Autocloved;
Glucose
Non-Autoclaved;
GlucoM + KNQj
1.00
0.90
0.80
0.70
0.60-
11 • . ' ' ' iii OOQI 1.1 it I i
10 20 30 40 50 60 0 10 20 30 40 50 60 ' 0 10 20 30 40 50 60
BAINVILLE
TERRY
10 20 30 40 50 60
10 20 30 40 50 60
DAYS
Figure 21.2. Effect of autoclaving, glucose, and glucose + KN03 on
He loss from mercuric nitrate-amended soils. Vertical
arrow at day 38 indicates initiation of irrigation with
inoculum suspension or metabolic substrate solution.
HgClo-amended, sterile microbial medium containing 1% glucose to remain
unchanged ove^ a period of 17 days, suggesting that the Presence of glucose
in the absence of microorganisms does not promote the volatile loss of
rapid early losses observed. Microbial respiration b
803
-------
substrates. The pattern is similar to that observed with the volatile loss
of selenium from soils incorporated with readily-available metabolic sub-
strates (Abu-Erreish et al.3 1968; Doran and Alexander, 1977).
Zimmerman and Crocker (1933) found more severe mercury vapor injury to
roses grown in soils treated with both a high organic matter tankage fertili-
zer and HgCl2> as compared to those grown on soils receiving HgCl2 alone.
This effect could be attributed to either a humic acid-mediated abiotic
process such as shown by Alberts et at. (1974) or a microbial stimulation as
demonstrated in this study. Van Faassen (1973) found that the addition of
glucose to an HgCl2-amended soil speeded the recovery of dehydrogenase acti-
vity. This enhanced restoration of microbial activity was perhaps associated
with an accelerated removal of mercury from the soil catalyzed by the addi-
tion of glucose.
While the forms of mercury being lost from the soil were not identified,
Hg seems likely to be the major species. Rogers (1975) showed Hg to be
the predominant form lost from an Hg(NOs) 2""am^nded calcareous fine sandy
loam desert soil, with' lesser amounts of methyl-, mercuric- and dimethyl-
species being detected in the atmosphere above the soil. Johnson and Braman
(1974) showed similar results for HgCl2-amendment of a Florida turf soil.
Van Faassen (1975) and Rogers (1976) found little methylation of applied
Hg(II) in soils.
After 2-24 days, depending upon soil and treatment, little or no further
Hg losses were observed. The remaining Hg appeared to have "stabilized"
after losses of from 5-40% of the initial amendment. In general, for the
non-autoclaved soils, the amount of Hg-loss followed the order:
Terry>Heldt>Bainville, Arvada>Campspass
Frear and Dills (1967) found a similar decrease in mercury volatilization
after 10-16 days from Hagerstown silt loam amended to 5-19 ppm Hg as HgCl£*
The failure of reinoculation with microorganisms, or resupply with glucose
or glucose plus KNOs to restimulate further Hg losses suggests that the
stabilized Hg is no longer available for biological mobilization to a vola-
tile form.
These soils show a high affinity for mercury. In excess of 97% of the
Hg applied at 1 yg Hg/g soil was removed from aqueous solution by all of the
soils in 24 hour equilibration studies. Thus, the adsorption of Hg(II) on a
soil surface would not appear to prevent volatilization. The process by
which the added Hg(II) is eventually stabilized may involve incorporation
with the sulfhydryl groups of soil organic matter or precipitation as HgS.
The reason why the Campspass soils offers greater protection from vola-
tile loss as compared to the Terry soil and others is not known. The high
organic matter content of the Campspass (Table 21.2) is the most obvious
factor, as organic matter tends to bind both Hg(II) and Hg° strongly (Trost
and Bisque, 1972; Gjessing, 1976). However, the nature of the microflora
may also be a factor. It is interesting to note that the Terry soil shows
greater resistance to inhibition of microbial respiration by Hg(II) amendment
804
-------
than the Campspass soil (see pages 818-820), and that microbial resistance
to mercurials is often associated with ability of the organisms to detoxify
their environment by volatilization of mercury (Vaituzis et al.3 1975).
Mercury loss also appears to increase with increasing soil pH (Table 21.2).
Frear and Dills (1967) showed the volatile loss of mercury from a series of
limed Hagerstown silt loams amended with HgCl2 to increase as soil pH in-
creased from 5.3 to 6.4.
Soil Water Content and Soil Temperature as Factors in the Volatile Loss
of Soil-Applied Inorganic Hg (II)
Volatilization of Hg was retarded at both very low and very high mois-
ture contents (Figure 21.3). In the case of the drying soils, the loss
process was reactivated to varying extents by rewetting the soils on day 25,
ARVADA
CAMPSPASS
HELDT
"-O- Q >__^_ _*
WT ^**^**^_._j^-j^' ~~
- ^*»»^ ^_o-o-o
* — — , ^
-
*
1 1 1 1 1
1.00
0.90
050
0.70
0.60
'i
0.00
iii'1
L
Wsctr-i ^_^
\ i*^~^-^— IA • • A _
\
-------
As shielding of the y-radiation by the water added at this time reduced the
count rate by less than 1%, the rapid loss of Hg observed was judged not to
be an artifact of the analytical method.
Figure 21.4 shows that at 35 C, the initial Hg loss rate was accelerated,
but except in the case of the Heldt soil, the total loss was the same as
that seen from samples equilibrated at the room temperature samples. At
10 C, the Hg loss rate and, in all but the Heldt soil, the total loss of Hg,
was reduced with respect to the room temperature samples. Removal of these
samples from the 10 C water bath after 5 1/2 weeks and subsequent storage at
room temperature for 2 weeks appeared to stimulate further losses. The
coefficient of variation in these experiments averaged 0.9%.
Mercury lost from the system is a composite of the Hg converted to a
volatile form, minus that portion of the volatile Hg thus produced which is
subsequently sorbed by the soil. Metallic mercury vapor (Hg ) appears to be
the predominant volatile species from Hg(II)-amended soils (Johnson and
Braman, 1974; Rogers, 1975). The Bainville and Campspass soils have been
shown (see Table 21,3) to sorb about twice as much Hg from air as the Heldt
soil, and about four-times as much as the Arvada and Terry soils. Thus, the
high losses of Hg observed in the Hg(II)-amended Terry soil may be the
result of both a low degree of retention of Hg , as well as a high degree of
conversion of Hg(II) to Hg . Similarly, the low losses of Hg seen here for
the Campspass and Bainville soils are probably due, at least in part, to a
high degree of soil retention of the Hg produced.
Earlier studies (see pages 802-805) which showed a stimulation of
Hg-loss upon the addition of glucose to the soils, and a suppression of loss
following autoclaving of the soils, suggest a major role for microorganisms
in the volatile loss of applied Hg(II) from soils. A soil moisture content
of 50 to 75% of field capacity is optimal for aerobic microbial activity
(Alexander, 1962). The diminished Hg losses, with respect to those samples
moistened to the 1/3-bar moisture content, seen in the air-dried and the 80%
saturated soils (Figure 21.3) suggests that the activity of aerobic soil
microorganisms is involved in the volatilization process, as a purely chemical
reduction of Hg(II) to Hg would presumably be favored by high water con-
tents. A water content - Hg volatilization relationship similar to that
observed here was reported for the loss of Hg from a phenylmercuric acetate-
amended sandy loam (Kimura and Miller, 1964).
Most soil microorganisms are mesophiles, with a temperature optimum of
25-37 C. Maximal respiratory activity in soils, as judged by the breakdown
of carbonaceous materials, generally occurs in the 30-40 C range. At 10 C,
below the growth range of most mesophiles, soil microbial activity will be
considerably reduced (Alexander, 1962). Thus, the temperature-Hg loss rela-
tionships (Figure 21.4) also are consistent with a microbial action hypothesis,
although vapor pressure and reaction kinetic considerations would also
predict increasing loss rates with increasing temperature. The lower losses
of Hg seen at 10 C may also reflect the higher degree of sorption of Hg° (or
other gaseous species) by the soils expected at lower temperatures.
806
-------
ARVADA
CAMPSPASS
HELDT
1.00
o a90
%^
z
Z 030
S °-7°
cr
> (X60
^ <
S cwx)7!
1 1 1 1 1
^ 1
[vv^^ 1
•tfifr^aA^ "m^"'0^ — °
-
- •— -• Room Temperature
_ — •* 35° C
J, o— — 0 10° C
i i i i i
1.00
0.90
0.80
0.70
aeo
fi
0.00
II...
DcVv-._ ""
^•fa»jt^*'^—^^j«'»^^^— ~*O"***~ ^^^— ~O.
^-«^-y- ^ H-J— m "~-o
-
_ _
^
i i i i i
UJ
O
UJ
s!
u_
O
10 20 30 40 50 60
1.00
0.90
0.80
0.70
0.60
\
0.00
10 20 30 40 50 60 0
10 20 30 40 50 60
BAINVILLE
TERRY
£
1.00
030
0.80
0.70
0:60
4
aoo
10 20 30 40 50 60
1.00
0.90
050
0.70
0.60
k
000
10 20 30 40 50 60
DAYS
Figure 21.4.
Effect of temperature on Hg loss from mercuric nitrate-
amended soils. Vertical arrow at day 38 indicates time
of initiation of room-temperature storage for samples
previously equilibrated at 10 C.
807
-------
The magnitude of mercury loss seen here is not unreasonable in light of
other reports. Wimmer (1974) observed Hg losses of up to 40% in 12 weeks
from soils amended to 0.2 ppm Hg by surface application of mercuric acetate.
Gracey and Stewart (1974) and Hogg (1976) found 10-20% losses in 20-25 weeks
in soils amended to 10 ppm Hg as HgCl2. While several Hg loss studies have
demonstrated first order kinetics over periods ranging from of 1 day to
27 months (Bothner and Carpenter, 1973; Alberts et al. 3 1974), the rapid
approach to equilibrium reported here and in earlier work (Frear and Dills,
1967) suggests the dubious validity of extrapolating short-term loss data on
the assumption of first order behavior. For example, a semi-logarithmic
plot of residual Hg vs. time for the first 10 days of data from the room
temperature, 1/3-bar, Terry soil samples predicts an erroneous soil residence
half-life of 30 days for the applied Hg.
The Volatile Loss of Mercury from Soils Amended with Methylmercury Chloride
Glucose and nitrate supplementation of the soils generally repressed
volatile losses of mercury (Figure 21.5). Autoclaving of the soils supressed
losses from the Arvada and Heldt soils but resulted in slightly increased
losses from the Campspass and Bainville soils. Total losses from the auto-
claved and non-autoclaved Terry soils were similar, although in the case of
the non-autoclaved soil, most of the loss came in the period from 0 to
16 days after amendment, while in the case of the autoclaved soil, the major
losses occurred in the period from 14 to 34 days after amendment, suggesting
the recolonialization of the soil by microorganisms following autoclaving as
a possible causative agent in the delayed volatile loss response.
Volatilization of mercury was retarded at both very low and very high
moisture contents (Figure 21.6). Soils maintained at 80% saturation lost
from 3 to 17% of their initial mercury amendment as compared to 7 to 44% for
those maintained at the 1/3-bar moisture content. Air-drying of soils
resulted in a termination of mercury loss after the first 6-8 days. Rewetting
of the soils on day 28 to the 1/3-bar moisture content resulted in a renewed
loss of mercury, with total losses over the two-month monitoring period
approaching those of the soils maintained throughout this period at the 1/3-
bar moisture content.
The magnitude of mercury loss increased with soil temperature over the
16 to 35 C range examined, with losses of up to 60% observed on the Terry
soil at 35 C (Figure 21.7). In all cases (Figures 21.5, 21.6, 21.7),
highest losses were observed in the strongly alkaline soils - Terry, Heldt
and Arvada.
Work by Spangler et al. (1973 b) suggests that bacteria capable of
degrading and volatilizing methylmercury (by reductive demethylation) under
aerobic and/or anaerobic conditions are prevalent in the aquatic environment.
Floyd and Sommers (1974) found that the addition of glucose, and to a lesser
extent acetate, methanol or ethanol, to lake sediments increased the degrada-
tion of methylmercury chloride.
808
-------
ARVADA
CAMPSPASS
HELDT
1.00
0.90
0.80
0.70
Q60
0.50
a:
CL
3
o
DC
Ul
2
o
UJ
fc
u_
o
z
o
0.40
0.00'
Non-Autocloved
\- a—a Autoclaved
Non-Autoclaved;
Glucose tKN03
1.00
0.90
0.80
0.70
0.60
O50
0.40
0 10 20 30 40 50 60
000
*
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.00'
0 10 20 30 40 50 60
0 10 20 30 40 50 60
BAINVILLE
TERRY
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.00
1.00
0.90
0.80
0.70
0.60
0.50
040
0.00
0 10 20 30 40 50 60 0 10 20 30 40 50 60
DAYS
Figure 21.5. Effect of autoclaving and glucose + KNOs on Hg loss
from soils amended with methylmercury chloride.
809
-------
ARVADA
CAMPSPASS
HELDT
z
z
LU
o:
cc
r>
o
tc
Ul
Q
UJ
Q.
Q.
U.
O
O
1.00
0.90
0.80
0.70
0.60
Q50
0.40
0.00
1/3-Bar
80% Saturation
h a—-a Air'drying
0 10 20 30 40 50 60
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.00*1
0 10 20 30 40 50 60
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.00*
0 10 20 30 40 50 6O
BAINVILLE
TERRY
1.00
0.90
0.80
0.70
0.60
0.50
0.40
aoo'1
0 10 20 30 40 50 60
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.00*
0 10 20 30 40 50 60
DAYS
Figure 21.6.
Effect of soil water content on Hg loss from soils
amended with methylmercury chloride. Vertical arrow
at day 28 indicates time of rewetting of air-dried
soils.
810
-------
ARVADA
CAMPSPASS
HELDT
RoomTempi(20-270C) -
35°C
1.00
0.90
0.80
0.70
0.60
050
040
cool
1.00
0.90
OBO
0.70
0.60
0.50
040
—Q
o
(T
UJ
O
UJ
Q.
O.
u.
O
O
I
0 10 20 30 40 50 60 0 10 20 30 40 50 60 0 10 20 30 40 50 60
BAINVILLE
TERRY
1.00
0.90
0.80
0.70
Q60
050
0.40
0.00
1.00
0.90
0.80
0.70
0.60
050
0.40
0 10 20 30 40 50 60
OOO
0 10 20 30 40 50 60
DAYS
Figure 21.7. Effect of temperature on Hg loss from soils
amended with methylmercury chloride.
811
-------
In work reported earlier (see pages 802-805) we found glucose and
glucose & nitrate supplementation to increase the volatilization of mercury
from soils treated with mercuric nitrate. On the basis of the literature
and our earlier experience with Hg2+-amended soils, the finding here of
suppressed mercury losses upon addition of glucose & nitrate to methylinercury-
amended soils was surprising, as these metabolic substrates would be expected
to stimulate the activity of microorganisms which could promote the volatile
loss of mercury through either the reductive demethylation of methylmercury
to methane and volatile metallic mercury, Hg , or the synthesis of volatile
dimethyImercury.
The diminished losses observed here upon addition of glucose & nitrate
may be the result of the stimulation of a biologically-mediated transforma-
tion of the methylmercury to a form (e.g. Hg2^", or incorporated into micro-
bial tissue) less subject to, but certainly not immune from, volatile loss
processes. Billen et at. (1974) showed methylmercury to be stable in sterile
river water, while after 90 hours in non-sterile water, only 10 to 20% of
the initially-present Hg remained as methylmercury. Of the portion of the
methylmercury which was transformed, from 50 to 80% was converted to dis-
solved (presumably Hg2+) mineral mercury, with the remainder being lost from
solution as volatile metallic mercury. Bache et at. (1973) found that at
the end of a cropping experiment, 90% or more of the mercury present in
mineral soils treated with methylmercury dicyandiamide was present as Hg2
or some form other than intact methylmercury. This transformation was
apparently not to Hg or ((^3)2 Hg, as no detectable volatile loss of
mercury from the soils was observed. Experiments by Spanis et at. (1962)
with autoclaved- and non-autoclaved soils showed the transformation of
methylmercury dicyandiamide to a form of lesser fungicidal activity to be
rapid (only 20% of the initial activity remaining after 4 days) and largely
microb ially-mediated.
As also seen with Hg2+-amendment of these same soils (see pages ),
volatile losses of mercury following methylmercury-amendment were lower when
soils were maintained at high moisture contents (80% saturation) or allowed
to air-dry, as compared to those maintained at the 1/3-bar moisture content
(Figure 21.6). The differences observed here between the air-dry and 1/3-
bar conditions are in agreement with the observation by Rogers (1976) that
methylmercury losses during the period 1 to 3 weeks after Hg2+-amendment of
a loam and clay soil increased as the soil moisture content increased from
25 to 75% of the moisture holding capacity.
Rowland et al. (1977) found that hydrogen sulfide stimulated the volatile
loss from solution of methylmercury chloride, presumably as a sulfur-deriv-
ative of methylmercury. In soils at high moisture contents, H2S might be
produced in anaerobic microsites, thereby stimulating the volatile loss of
mercury via such a mechanism. However the present data (Figure 21.6) do
not support this view. Rogers (1976) showed that four times as much methyl-
mercury was present in a water-saturated loam (amended with mercuric nitrate)
as in the same soil at 75% of the moisture holding capacity. As the quantity
of methylmercury present at any given time is the net result of production
812
-------
and loss, it is not clear if this observation is the result of greater
methylmercury synthesis and/or less methylmercury loss at high moisture
conditions.
Floyd and Sommers (1974) and Rogers (1976) found methylmercury loss
from soils and sediments to increase with increasing temperature from 4 to
36 C. Figure 21.7 shows a similar response over the 15 to 35 C range studied
here.
The pattern of mercury loss from these five soils following methylmer-
cury-amendment shows some differences from that observed earlier with Hg2+-
amendment:
(1) Mercury loss from Hg2+-amended soils generally ceased after about 2 weeks,
while following methylmercury amendment, mercury loss was sustained for
periods in excess of 7 weeks.
(2) While the same relative ordering of the soils with respect to volatile
loss generally holds for both Hg2 - and methylmercury-amendment (Terry >
Heldt > Arvada > Bainville > Campspass), losses from the Arvada soil relative
to the Terry and Heldt soils are much higher in the methylmercury case.
(3) As discussed earlier, glucose & nitrate supplementation of soils stimu-
lated mercury loss from Hg2+-amended soils, but suppressed it in methylmer-
cury-amended soils.
(4) Volatile loss of mercury from methylmercury-amended soils showed a more
pronounced response to higher temperature and the rewetting of air-dried
soils than their Hg2+-amended counterparts. At 35 C, as compared to room
temperature, there was an increase in total mercury loss from methylmercury-
treated soils, while with Hg2+-treated soils, the initial rate of loss was
increased, but the total quantity of mercury lost was unaffected, by increa-
sing temperature.
These results indicate that methylmercury present in soils as a result
of either direct contamination or in-situ synthesis may be subject to rapid
and extensive losses to the atmosphere. Such environmental mobility should
be recognized in any considerations of mercury cycling and persistence in
soil systems.
The Retention of Metallic Mercury Vapor by Soils
Radioassay of the individual petri dishes of soil removed from the bell
jar exposure system showed the coefficients of variation for the measured Hg
uptakes of the 10 dishes of each soil type to be 4% or less, indicating that
well-mixed conditions did indeed exist within the bell jar, and that the
assumption of an ambient vapor concentration equal to that measured at the
outlet is valid. The relative order of mercury sorption by the soils
(Table 21.3) was:
Bainville>Campspass>Heldt>Arvada>Terry
The 2000 g of soil contained in the bell jar removed an average of 56% of
the entering mercury vapor.
813
-------
TABLE 21.3. UPTAKE OF MERCURY BY SOILS FOLLOWING 10 £AY EXPOSURE TO
AIR STREAM CONTAINING 14.3 yg Hg°/m3 AIR
SOIL yig Hg/kg soil
Arvada 10.5 + 1.7
Campspass 40.8 +1.0
Heldt 23.7+2.4
Bainville 45.6 + 2.7
Terry 9.5 + 1.0
Values shown are means of 3 replicates + 1 standard error.
No loss of the sorbed mercury from the soils maintained at air-dryness
was observed over the 16 day monitoring period. Soils maintained at the
1/3-bar moisture tension showed maximal losses of about 5% of the total
sorbed mercury. While such losses are quite small, they suggest that micro-
bial activity stimulated by the addition of water to the soils may promote
the biotransformation of the sorbed mercury to a more volatile species.
The majority of the sorbed mercury was liberated at temperatures between
100 and 200 C (Figure 21.8). Similar steep, S-shaped Hg-loss vs. temperature
curves have been reported for several mercury compounds alone (Koksoy et al. ,
1967), or mixed with soil (Koksoy and Bradshaw, 1969). Elemental mercury
showed losses of 30-35% at 70-80 C, while mercurous and mercuric chloride
showed losses of only 1-6% in this temperature range. All three compounds
showed complete mercury volatilization below 250 C. In contrast, mercuric
sulfide and oxide did not show any Hg-loss until the samples were heated to
210-270 C, with complete Hg-liberation at 340 and 535 C, respectively (Koksoy
et al,3 1967). On the basis of this literature evidence, HgS and HgO appear
to be unlikely candidates for the sorbed mercury species observed in the
studies reported here.
Major volatile losses of Hg from the soils studied here occurred at a
somewhat lower temperature range (100-200 C) than demonstrated by Koksoy and
Bradshaw (1969) for soil samples taken from sites surrounding a cinnabar
deposit in Turkey. Based on field evidence, these investigators postulated
the gaseous dispersion of metallic mercury vapor away from the zone of
mineralization, and its subsequent sorption by soil organic matter as an
important mechanism for the Hg enrichment patterns observed in the soils of
the secondary environment. These soils showed maximal Hg losses in the
200-300 C range.
Sodium hydroxide, hydrochloric acid and benzene removed the most sorbed
mercury (Table 21.4). Little or no mercury was extractable by water, potassium
814
-------
ARVADA
CAMPSFttSS
HELDT
• • BAINVILLE
TERRY
Figure 21.8. Volatile loss of sorbed mercury from soils as a
function of temperature.
815
-------
or calcium chloride, cupric acetate, methanol or DTPA, while cysteine,
acetylacetone and cupferron showed limited extraction abilities.
TABLE 21.4.
REMOVAL OF SORBED MERCURY VAPOR FROM SOILS BY VARIOUS
CHEMICAL EXTRACTANTS*
Hg Extracted
Extractant
Soil Arvada Campspass Heldt Bainville Terry
(a) distilled water
(b) 1 N KC1
(c) 1 N CaCl2
(d) 1 N HC1
(e) 1 N NaOH
(f) 0.5 M acetylacetone
(g) 0.5 M cupferron
(h) 0.5 N Cu (C2H302)2
(i) DTPA:TEA:CaCl2
(j) 0.1 M cysteine
(k) benzene
(1) methanol
0.1
0.1
0.2
71.1
91.7
2.6
2.7
0.6
0.2
4.0
9.3
1.1
0.2
0.0
0.1
15.8
74.3
0.9
8.7
0.3
0.4
3.7
5.1
0.4
0.4
0.0
0.2
1.2*
89.3
2.8
4.7
0.0
0.5
5.3
11.9
0.3
0.3
0.0
0.0
68.0
82.7
2.5
3.2
0.3
0.5
3.1
14.7
0.1
0.4
0.2
0.2
79.6
92.3
3.7
2.5
1.2
0.1
2.9
12.8
0.7
1.4 N HC1 extracted 49.6%
•%
Values shown are means of 3 replicates.
While water soluble mercury compounds such as HgCl2 have been identified
in mineralized rock zones (Koksoy and Bradshaw, 1969), the failure of dis-
tilled water to extract the sorbed mercury (Table 21.4) makes such compounds
unlikely candidates for the sorbed species observed here. The failure of
KC1 or CaCl2 to remove the sorbed mercury indicates that no significant
amount exists as a species which is readily available to ion exchange.
Hydrochloric acid extracted from 1 to 80% of the total sorbed mercury.
The low Hg extraction from the Heldt soil is undoubtedly due to the reduction
in the effective H+ concentration resulting from reaction with the free lime
nrSci SO^V^1 (T^ 21'2)' ^ the H6ldt S0il Was extracted with
\L 1 Q77 f £ the sorbed mercury was released. Sodium hydroxide extracted
74 to 92% of the sorbed mercury from the soils. While both HC1 and NaOH are
rather non-selective extractants which can solubilize portions of both the
mineral- and the organic- soil colloids, the uniformly high yield of sorbed
mercury seen with the NaOH extractions suggests the association of the
sorbed mercury species with the soil organs matter. Acidification of the
NaOH extract (Stevenson, 1965) shows a large portion of the Hg thus removed
from^the soil to be associated (as a sorbed or coprecipitated species) with
the insoluble, humic acid (Table 21.5). Whether the Hg present in the
solution phase of the acidified NaOH extract exists as a species soluble in
both acid and alkali, as a fulvic acid complex, or as a species which has
816
-------
been acid-leached from the humic acid is not clear. Only a limited portion
(0.5-4%) of the Hg extractable by IN HC1 (or 1.4217 HC1 for the Heldt soil)
partitioned into benzene upon shaking with the HC1 extracts. Trost and
Bisque (1972) have shown soil organic matter analogs, e.g. peat, humic acid,
pine mull, etc. to have high Hg sorption capacities.
TABLE 21.5. GROSS CHEMICAL FRACTIONATION OF SORBED Hg EXTRACTED
FROM SOILS BY IN NaOH
Soil % of sorbed Hg in acidified NaOH extract
associated with humic acid fraction
Arvada 46
Campspass 86
Heldt 58
Bainville 66
Terry 52
Due to their ability to chelate metals, aqueous solutions of acetylace-
tone and cupferron have proven to be good extractants of organic matter from
podzolic B horizons (Martin and Reeve, 1957). Both of these reagents, in
particular the cupferron with the Campspass soil, extracted a small portion
of the sorbed mercury, lending further support to the existence of the
mercury as an organo-mercury complex. However no sorbed Hg was extracted
with cupric acetate, even though copper forms very stable complexes with
organic matter (Stevenson and Ardakani, 1972).
The DTPA solution tested here has been used as a soil extractant for
several trace elements including zinc, iron, manganese and copper (Follet
and Lindsay, 1971). This chelate however was ineffectual as an extractant
for the sorbed mercury. Cysteine, a monothiol amino acid, was selected for
use because of the known affinity of mercury to form complexes with sulf-
hydryl groups. The 0.1 M cysteine solution extracted from 3-5% of the total
sorbed mercury indicating that at least a portion of the sorbed mercury is
available for complexation.
The selective extraction of organomercurials into organic solvents has
long been used as the method for partitioning the total mercury content of
biological materials into organic vs. inorganic mercury components Caller
et aZ 1958- Gage, 1961). The higher removals of sorbed mercury obtained
wUh benzene as compared to methanol suggests the occurrence of at least a
portion of the sorbed Hg as, or in association with, an organic compound with
an affinity for non-polar as compared to polar organic solvents.
817
-------
Work reported in section 22 (pages 856-861) showed the same relative
order of Hg° sorption for these same five soils. Using a technique developed
by Clarkson and Greenwood (1970) for the selective determination of inorganic
mercury in the presence of organomercurial compounds in urine, blood, and
animal tissues, 20-27% of the sorbed mercury in the Arvada, Heldt and Terry
soils, and 10% and 2% of the sorbed mercury in the Bainville and Campspass
soils, respectively, was ascribed to an inorganic species. This evidence
further supports the existence of a large portion of the sorbed mercury as an
organo-complex. j
The retention of Hg° by soils as demonstrated here offers an explanation
for the enrichment in Hg seen in the soils around a coal-fired power plant
(Klein and Russell, 1973). In predictions of ground level air concentrations
of mercury vapor used in evaluating power plant sitings, the effects of
mercury vapor removal mechanisms have generally been neglected (Lyon, 1977).
The data presented here indicate that the sorption of Hg by surface soils
offers one such significant atmospheric removal mechanism. Such processes
diminish the inhalation hazards associated with metallic mercury vapor to
organisms downwind from the source. However, more information is needed
regarding the abiotic and biotic cycling of this soil-sorbed mercury in order
to fully assess its environmental impact.
The Effect of Mercuric Chloride on Carbon Mineralization in Soils
Table 21.6 shows the results of the short-term radiorespirometry trials.
In all of the soils, amendments greater than 40 yg Hg/g soil were required to
yield significant reductions in C02~evolution from glucose. The 200 yg Hg/g
soil amendment reduced C02-production in the Arvada and Bainville soils, and
400 yg Hg/g soil was sufficient to depress glucose metabolism in all soils
examined.
Several patterns of effect are seen in Table 21.7, showing the results
of the month-long examination of (^-evolution from the HgCl2 amended soils.
The Terry soil shows essentially no inhibition of C02~production during the
monitoring period. In the Arvada soil, inhibition of CO2-production is
evident during the first week at 1 ppm Hg and above; however, in succeeding
weeks only the 100 ppm Hg amendment continues to show any depression. In
contrast, the Campspass soil shows depressed C02~production at the 0.1 ppm
Hg amendment and above for all but week 2. The Heldt soil shows no treatment
effect during the first week, but marked inhibition at all levels of amend-
ment for the succeeding 3 weeks; here the 1 ppm Hg treatment shows greater
C02~production than the 0.1 ppm Hg treatment. The Bainville soil is unique
in exhibiting increased CO2 production with respect to the control at the
1 ppm Hg amendment during the first week; in succeeding weeks inhibition is
seen only at progressively higher levels.
It is clear that exposure time and/or substrate type are important
considerations in assessing the respiratory impact of mercuric chloride in
these soils. All of the soils except the Terry showed suppressed C02~
production throughout the month-long monitoring period at 100 ppm Hg, while
only the Arvada and Bainville soils showed any such effect of 200 ppm Hg in
the short-term exposure studies. Jeffries and Butler (1975) observed such
818
-------
TABLE 21.6.
SHORT-TERM EFFECTS OF MERCURIC CHLORIDE AMENDMENTS ON
THE EVOLUTION OF C02 FROM GLUCOSE IN SOIL-WATER
SUSPENSIONS
M
HgCl2 concentration
yg Hg/g soil
ng CO^/g soil/6 hours
2.
Arvada
Campspaas
Heldt
Bainville
Terry
0
1 x 10~4
5 x 10~4
1 x 10~3
0
40
200
400
18.9 a
16.3 a
12.6 b
4.8 c
18.0 a
15.2 a
10.6 ab
5.9 b
9.9 a
9.7 a
6.2 ab
3.9 b
19.2 ab
21.2 a
16.1 b
8.4 c
11.2 a
12.8 a
11.0 a
3.5 b
*Means (4 replicates) in same column followed by same letter are not significantly different at
the 5% level by Duncan's multiple range test.
TABLE 21.7.
Soil
Arvada
Camp spass
Heldt
Bainville
Terry
LONG-TERM EFFECTS OF MERCURIC CHLORIDE AMENDMENT ON
CO2 EVOLUTION FROM MOIST SOILS
pg Hg/g soil
0
0.1
1.0
10
100
0
0.1
1.0
10
100
0
0.1
1.0
10
100
0
0.1
1.0
10
100
0
0.1
1.0
10
100
Week:
rag CO^/g soil/ week"
1
0.65 a
0.62 ab
0.56 be
0.52 c
0.43 d
1.60 a
1.45 b
1.48 b
1.40 b
1.26 c
0.33 a
0.32 a
0.34 a
0.34 a
0.36 a
0.40 b
0.36 c
0.46 a
0.36 c
0.32 c
0.19 ab
0.20 a
0.22 a
0.21 a
0.18 b
2
0.41 a
0.35 a
0.34 a
0.32 a
0.26 b
1.24 a
1.22 a
1.28 a
1.24 a
0.98 b
0.47 a
0.16 c
0.28 b
0.17 c
0.18 c
0.36 ab
0.39 a
0.44 a
0.30 be
0.23 c
0.21 a
0.18 a
0.22 a
0.23 a
0.18 a
3
0.47 a
0.33 a
0.35 a
0.32 a
0.22 b
1.28 a
1.13 b
1.12 b
1.00 c
0.85 d
0.33 a
0.07 b
0.30 a
0.08 b
0.10 b
0.43 ab
0.48 a
0.52 a
0.44 ab
0.38 b
0.16 a
0.21 a
0.19 a
0.20 a
0.16 a
4
0.31 a
0.25 ab
0.34 a
0.25 ab
0.17 b
0.95 a
0.85 b
0.84 b
0.80 b
0.68 c
0.45 a
0.06 c
0.18 b
0.06 c
0.06 c
0.44 a
0.42 a
0.42 a
0.31 a
0.40 a
0.16 a
0.16 a
0.20 a
0. 19 a
0.17 a
* Means (3 replicates) in same column (for each soil) followed by same letter are not significantly
different at the 5% level by Duncan's multiple range test.
819
-------
an acute vs. chronic exposure dichotomy with the growth of the photosynthetic
bacterium Rhodopseudomonas oapsulata, where exposure in liquid medium for
20-80 minutes to levels of methylmercury acetate that were bacteriostatic
for chronic (300 hour) exposures, stimulated growth.
The reasons for the differences in response of the soils studied are
probably multifaceted. Differences in the binding ability of the soils will
perhaps mitigate the toxic properties of the added mercury. As mercury
tends to bind with the organic fraction of soils (D'ltri, 1972), the apparen-
tly greater sensitivity observed in the long-term study of the Campspass
vs. the Terry soil, is surprising. However, the Campspass soil's much
greater (^-production probably reflects a larger, and perhaps more varied
microflora. As pointed out earlier, microoganisms vary widely in their
sensitivity to mercurials. Strains of many environmentally-common procaryotic
and eucaryotic genera have demonstrated mercury-tolerance, and the existence
of such an array suggests resistance to mercurials may be common and widespread
(Brunker, 1976). A possible genetic link exists between resistance to
antibiotics and to mercury (Richmond and John, 1964). Zajic (1969) reports
work which showed gram-negative bacteria to be more resistant than gram-
positive bacteria to mercury penetration, suggesting that differences in the
cell wall which influence the staining properties may also influence the
uptake and toxicity of mercury. Thus, the nature of the indigenous micro-
flora probably influences the tolerances observed in this study. Also the
ability of the soils to lose by volatilization, presumably of Hg , mercury
added as a mercuric salt by either biotic (Brunker and Bott, 1974) or abiotic
(Alberts et at.3 1974) mechanisms, may influence the response observed to
mercuric chloride amendment.
The Uptake from Soils of Inorganic Divalent Mercury by Plants
Plant/soil concentration factors (CF = yg J?S/,S tlssue) for Hg in the
yg Hg/g soil 6
above ground portion of western wheatgrass seedlings range from 0.01 to 0.1
(Table 21.8). Tissue Hg concentrations were lowest for the Campspass
and Arvada soils, the soils highest in organic matter and clay respectively,
and highest in the high-lime Heldt soil. No toxicity symptoms or yield
reductions with respect to control plants grown on unamended soils were
evident. Tissue yields on the Arvada and Campspass soils were about double
those on the Terry soil, with the Heldt and Bainville yields falling in the
intermediate range.
The volatile loss of Hg, presumably as Hg°, from soils amended with
divalent mercury has been reported by several investigators (Rogers, 1975;
Hogg, 1976). At the end of the 22 day growth period from 9 to 21 % of the
initially-applied mercury had been lost from the soil-plant systems (Table
21.9). As the above-ground portion of the seedlings are exposed to Hg
vapors emanating from the soil, the Hg found in the aerial tissue is probably
the result of both foliar interception of volatilized Hg (see Section 22), as
well as translocation from the roots.
820
-------
TABLE 21.8. UPTAKE OF Hg BY ABOVE-GROUND PORTION OF WESTERN WHEATGRASS
SEEDLINGS GROWN FOR 22-DAYS ON SOILS AMENDED WITH 1.0 yg
Hg/g SOIL*
5011 Series ng Hg/g DM
Arvada 31+2.3
Campspass 12+6.4
Heldt 96 ± 22
Bainville 40+5.8
37+8.3
*
Tissue concentrations shown are means of 3 replicates + Standard
error, and are calculated on a dry matter basis.
TABLE 21.9. PERCENT OF INITIALLY-ADDED Hg REMAINING IN SOIL*
Soil Series
Arvada
Campspass
Heldt
Bainville
Terry
% Hg remaining
90.8 + 0.4
93,4 + 0.2
83.8 + 0.2
90.6 + 0.5
79,4 + 0.6
*
At end of 22 day plant growth period.
Corrected for plant removal.
Values reported are means of 3 replicates + standard error.
The concentration factors reported here are similar to those found for
bromegrass (CF = 0.05-0.06) grown for 49 days on soils amended with 10 yg
Hg (as HgCl2)/g soil (Hogg, 1976), and for wheat and barley (CF = 0.04-0.11)
grown to the heading-out or mature stage on soils amended with 0.5 yg Hg as
Hg(N03)2/g soil (Lee, 1974). Cadmium (Cd) is the Periodic Table neighbor of
Hg in group lib, and Munshower and Behan (1971) report a CF of 0.8 (based on
acid extractable soil Cd) for western wheatgrass growing 20 miles from a
zinc-cadmium smelter in Montana. Cd is generally considered to be more
plant available than Hg (Lagerwerff, 1972).
821
-------
In spite of the potential for both foliar and root uptake, only limited
quantities of Hg were found in the above-ground portion of western wheatgrass
grown on Hg-amended soils. Western wheatgrass would not appear to represent
a source for food chain magnification of environmental mercury.
CONCLUSIONS
The experiments described here suggest that mercury added to the soil as
a result of coal-combustion emissions may be subject to volatilization and
reentry into the atmosphere. Such behavior may explain the mercury enrich-
ment patterns seen in the soil surrounding the coal-fired power plant studied
by Klein and Russell (1973). Soils have also been shown to scavenge metallic
mercury vapor from the air. Thus the soil may act as both a source and a
sink of mercury to and from the atmosphere.
Mercuric-mercury amendments of 0.1 ppm were shown to yield significant
depression of microbial respiration in some of the soils examined. Based on
an assumption of mercury deposition with the combustion particulate emissions,
the Colstrip environmental analysis prepared by Westinghouse (1973) reports
a maximal surface soil enrichment with respect to baseline soil mercury con-
centrations of less than 1%. While such enrichments seem trivial, most of
the mercury probably does not deposit with the particulates and more importan-
tly, the mercury emitted by the combustion of coal may be as a chemical form
of greater toxicity and bioavailability than that present in the native soil.
Future research efforts on trace element emissions from coal-fired power
plants should be aimed at assessing the chemical form as well as total
quantity of the various elements.
The work reported here on western wheatgrass and literature on other
plant species suggests that root uptake of mercury is generally limited.
However, the volatilization of mercury from the soil surface may increase
the bioavailability of this mercury in the terrestrial environment, as
Browne and Fang (Section 22) have shown the aerial tissues of plants to fix
mercury vapor from the atmosphere.
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828
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SECTION 22
UPTAKE OF METALLIC MERCURY VAPOR BY SOILS
AND VARIOUS PLANT SPECIES
C. L. Browne and S. C. Fang
ABSTRACT
Laboratory experiments were conducted to study
(1) the sorption of metallic mercury vapor by dry
soils, minerals and organic materials in relation to
mercury vapor concentration or duration of exposure;
(2) the transformation of the sorbed mercury and avail-
ability for plant uptake; and (3) the foliage uptake
of mercury vapor by various plant species as affected
by a number of environmental factors.
Both organic matter and mineralogical make-up of
the soil appeared to play an important role in the
wide range of mercury vapor sorption observed for the
dry soils. The sorption phenomenon was adequately
described by the Freundlich equation. Only a small
fraction of mercury sorbed was transformed to mercuric
mercury, the form most available for root uptake.
Mercury vapor uptake from the atmosphere by plants
was found to be almost exclusively confined to leaves
and, as such, a simple gaseous exchange model was em-
ployed to describe the phenomenon. The rate of mercury
vapor uptake was dependent on ambient mercury vapor con-
centration, illumination level, and leaf temperature.
Illumination level influenced leaf resistance to mercury
vapor entry, but except in darkness, the effect on rate
of uptake was small compared to that of leaf temperature,
which affected internal biochemical and physical pro-
cesses involved in the conversion of the metal to mer-
curic mercury. In vitTO studies with homogenized leaf
tissue demonstrated that this conversion was to a large
extent enzymatically controlled. Uptake of mercury
vapor was found to differ between plant species, but the
most pronounced difference was that which existed between
plants possessing GS and C4 photosynthetic pathways.
829
-------
INTRODUCTION
Because of abundant resources in the United States at relatively low
cost, coal is being used as the primary fossil fuel for the production of
energy. Although the mean mercury content in coal is small, more than 90%
of mercury escapes into the atmosphere as vapors after burning (Mercury
and the Environment). As mercury pollution of the entire ecosystem continues
to increase through natural and man-made sources, a basic understanding of
the cycling of mercury in the air-soil-vegetation system is urgently needed
to complete the environmental picture. This report describes laboratory ex-
periments designed to study the effect of physical and biochemical factors
on the removal of mercury vapor from the atmosphere by plants and soils.
Ambient temperature, ambient mercury concentration, illumination, and dura-
tion of exposure were studied in relation to their effect on components of a
proposed model for gaseous mercury uptake by whole plants. At the cellular
level, homogenized leaf samples were employed in an in vitro study of possible
biochemical processes involved in the uptake of mercury vapor. Soils of
differing characteristics, clay minerals, and various organic materials were
also examined with respect to their sorption capacity for mercury vapor.
Theory of Mercury Vapor Uptake by Plants
Gas Assimilation Model
The entry of mercury vapor into plants can be expected to follow the
same major transfer pathways as water vapor and carbon dioxide. As such,
the model employed to describe mercury vapor uptake in this work was of
similar form to one commonly used in carbon dioxide assimilation studies
(Bierhuizen and Slatyer, 1964) in that,
U(Hg) = .. '"* . / "* (22.1)
L.Hg M.Hg
_2
where U(Hg) is the rate of mercury uptake per unit leaf surface (g cm
sec); C. is the ambient mercury vapor concentration (g cm"3); CL „ is
the mercury concentration at immobilization sites within the plant and is
assumed to be zero; r is the total leaf resistance to mercury vapor
exchange (sec cm"1) and includes several component resistances, the principal
of which are the stomatal, cuticular, and external boundary layer resi-
stances; r (sec cm"1) is a residual term to account for unexplained
physical and oiochemical resistances to mercury vapor uptake.
A principal step in establishing the model was the determination of
r , which was assumed to be related to total leaf resistance to water
vapo? exchange (r Q) by the relationship,
rL.Hg rL.H20 X — (sec cm l) (22.2)
.o , ^o
h
where D „ 0 and D „ are the free diffusion coefficients for the respective
rioU ng
830
-------
vapors (Jarvis, 1971). A value for D at 25 C of 0.15 cm2 sec"1 was ob-
tained from the results of Mikhailov ana Kochegarova (1967), where experimen-
tal values of D were expressed as a function of temperature. This gives
the ratio D fl Q/D a value of 1.73, where D°H Q at 25 C is 0.26 cm2 sec"1
(Van Haveren and Brown, 1972). This ratio was effectively constant (+1%)
over the range of ambient temperatures examined in our experiments. As
Mikhailov and Kochegarova (1967) observed, there is a substantial difference
between values of D derived experimentally and those which would be
expected on a theoretical basis. Their data, however, corresponds with
other published values for D (Jost, 1952; Spier, 1940).
In using equation 22.2, it was assumed that the diffusion coefficients
were independent of stomatal pore size, and that the boundary layer resis-
tance comprised but a small part of total leaf resistance. This second
assumption is reasonably valid in a well ventilated chamber, such as was
used in these experiments. The first assumption may not be particularly
valid (Cowan and Milthorpe, 1968), and could likely lead to the greatest
errors in estimation of r in instances of narrowest stomatal opening.
Such an assumption was expedient , however, in view of the complex and arbit-
rary alternative of calculating and employing diffusion coefficients appro-
priate to changing stomatal dimensions (Cowan and Milthorpe, 1968; Milthorpe
and Penman, 1967).
Whole Plant Resistance to Gaseous Exchange
Since in this study it was desired to examine mercury uptake and subse-
quent distribution on whole-plant basis, it was necessary to determine leaf
resistance to mercury vapor exchange (r H ), which in turn required the
determination of total leaf resistance to water vapor exchange (r
Li.
equation 22.2). Estimation of r is often confined to single-leaf
chambers, one reason being the theoretical necessity to measure leaf tempera
ture, a difficult entity to characterize accurately. An alternative theory
was therefore sought whereby rT n of whole plants could be estimated in a
L .
plant chamber independently of leaf temperature measurement. Such a theory
was proposed by Jarvis (1971). The approach involves determination of
components of the basic transfer equation,
CT - C
q = -± £ (22.3)
rL.H20
where q is the flux of water vapor per unit of leaf surface (g cm"2 sec"1),
C. is the ambient water vapor concentration (g cm"3), and CL is the water
vapor concentration (g cm"3) at evaporative surfaces within the leaf and is
considered to be saturated at leaf temperature.
Jarvis1 proposal is that by inducing a small change in ambient water
vapor concentration, then
CT' " CA'
t =_J^ £_ (22>4)
rL.H20
831
-------
The assumption is that r A is independent of change in ambient
L . H.2U
humidity. By subtracting equations 22.3 and 22.4,
C.' - C. CT' - CT
r = _k - A _ _L - L (22.5)
L.H20 qv - V % ' V
or
AC. ACT
r = __Ji -- L (22.6)
L.HoO Aq Aq
z ^v ^v
Assuming that the change in leaf temperature is negligible, then the second
term in the above equations can also be considered to be negligible such
that
AC
(22'7)
This assumption concerning leaf temperature becomes more valid when
dimensions of the leaves are small and ventilation is high (Gates, 1968).
Use of equation 22.7, however, would result in some over estimation of r _
Li . n.^J
if ACL /Aq had a finite value. No attempt has been made in these studies
to quantify the value of this term by measurement of change in leaf tempera-
ture. The inherent error has been reduced, however, by the use of small
plants and rapid stirring of air within the chamber. The principal assumption
that rT „. is a constant would also result in error if incorrect. This
L .
possibility is further discussed in the light of results of preliminary
experiments in which the efficacy and versatility of the approach were
examined .
MATERIALS AND METHODS
Plant Chamber
A schematic diagram of the plant chamber and associated equipment is
presented in Figure 22.1. The cylindrical glass chamber was 12 cm in diameter
and 30 cm in height (3.4 liters). The internal surfaces of the chamber and
ancillary glassware were smeared very lightly with petroleum jelly to mini-
mize adsorption of both water and mercury vapor. Air entering the open
system was drawn from laboratory supply lines, dried, and then controllably
mixed with water vapor saturated at chamber temperature to attain a desired
humidity. Prior to entry of air into the chamber, by- pass systems were used
to generate radioactive mercury vapor (203Hg) as well as determine mercury
and water vapor concentrations. Air within the chamber was rapidly mixed by
a fan 7 cm in diameter (c. 800 rpm) so that the outlet vapor concentrations
of water and mercury were assumed to be the ambient concentrations (Slatyer,
1971) . Conditions were sufficiently turbulent so as to produce visible
agitation of the leaves. Air flow rates were controlled by regulated flow-
meters which were of the float-type and were regularly cleaned. Chamber
temperature was controlled (+ 0.02 C) by means of a water jacket serviced by
a temperature-regulated water bath and circulator (Polyscience Corporation) .
832
-------
Hg
VAPOR
TRAP
MANOMETER
OUTLET
PSYCHRO-
MCTER
LAMP
FILTER
CELL
VAPOR
BY-PASS
TRAP
To
CHAMBER
MAGNETIC
FAN DRIVE
TEMPERATURE CONTROLLED
WATER BATH
LAMP
FILTER
CELL
•1 RESULATED
I! FLOWMETER
Figure 22.1. Schematic diagram of the plant chamber for estimation of
whole-plant resistances to water and mercury vapor ex-
change. The plant chamber and water vapor generator were
serviced by the same water bath. The outlet psychrometer,
although indicated separately, was incorporated within
the plant chamber.
Illumination was provided by two banks of one or two reflector-type 150 watt
incandescent lamps (G.E. Plant Light). These were laterally located, and
the light was filtered through flowing water cells 7 cm in width. Illumina-
tion level was measured with a CdS photocell and was controlled by the
number of lamps together with gauze screens.
Psychrometry
Vapor pressure of air entering and exiting the plant chamber was deter-
mined from components of the psychrometric equation,
- e
- PA
(22.8)
w
w
where
e °(T )
w w
w
vapor pressure (mm Hg)
saturated vapor pressure corresponding to TW (mm Hg)
wet bulb temperature (C)
833
-------
T = ambient temperature (C)
P = barometric pressure (mm Hg)
A = psychrometric constant (C~~ )
\V
Psychrometry was simplified by the large chamber size and a high outlet
flow rate. This permitted use within the chamber of wet and dry bulb thermo-
meters with a limit of reading by estimation of 0.05 C. Thermometers were
ventilated and protected from direct radiation by cylindrical foam and
aluminum foil shields; the wet bulb thermometer being located in the outlet
and of a design so as to create high turbulent flow over the wick in the
axial direction. The inlet by-pass psychrometer was of the same design and
all thermometers were matched and calibrated over the range of operative
temperatures.
Air flow through the inlet psychrometer was maintained at a velocity of
3.3m sec"1 so that the psychrometric constant (A inlet) was assumed to be
6.6 x 10"4 (1 + 0.00115 T ) (T1 (Tanner, 1972). A psychrometric constant
(A outlet) was generatedwfor the plant chamber by calibration against A^
inYet for every change in wicks. The relationship between these constants
was unaffected by temperature and illumination, but particularly influenced
by flow rate exiting the chamber (Figure 22.2). An exit flow of 1500 ml
min"1 was therefore maintained in all experiments, this being satisfactory
for adequate wet bulb depression as well as for trapping of mercury vapor.
Figure 22.2.
0 400 800 1200 1600 2000 2400
Chamber Flowrate (ml-min'1 )
Effect of chamber air flow rate on the relationship
between inlet and outlet psychrometric constants (A ).
The value of A (inlet) was 6.6 x 10~4 (1 + 0.00115WT )
c-1.
w
834
-------
Inlet and outlet vapor pressures were converted to units of absolute
humidity (p) using the relationship
p = 2.89 x ICT4 [e/T] (g cm"3) (22.9)
where T was the Kelvin temperature of the chamber (Slatyer, 1967).
203
Hg Vapor Generation
Prior to entry into the plant chamber, part (200 ml min"1) of the total
flow (1700 ml min-1) was passed over a 203Hg labelled mercury source. The
resulting vapor was remixed with the bulk flow and a further 200 ml min"1
then diverted to determine the precise concentration of the mercury vapor
which entered the chamber at a flow rate of 1500 ml min"1. The temperature
of the mercury source, and hence vapor concentration, was controlled by a
thermoregulated water bath. To maintain a constant vapor concentration,
it was also necessary to continuously and gently vibrate the source. Under
this system, a given mercury vapor concentration could be reproduced to
within + 13%. Two sources were used during the course of the experiments,
the first (170 mg) having an initial specific activity of 0.17 mCi/mg, and
the second (33 mg) an initial specific activity of 0.06 mCi/mg.
Mercury vapor exiting the open system, which was located within a
ventilated hood, was collected in traps containing the solid oxidizing agent,
hopcalite (a mixture of copper and manganese oxides; Hopkin and Williams Ltd.,
Chadwell Heath, Essex, England). The mercury content of traps was determined
from the known specific activity of the vapor and by direct measurement of
radioactivity using a y-scintillation detector (Tracerlab). Samples and
background were counted for a period of one hour each such that the counting
error was normally less than 5%.
Leaf Temperature
An estimate of the water vapor concentration within leaves was derived
from equation 22.3, knowing q , C. and r u n. An estimate of average leaf
v A Li. £120
temperature was then derived from saturation vapor density tables by making
the usual assumption that C is saturated at leaf temperature.
±j
Plant Preparation, Exposure and Harvest
The plants for all experiments, which involved several species, were
grown to a height of 15 cm in a glasshouse under natural light. The mean
maximum and minimum daily temperatures were 26 and 19 C. Seeds were sown
into free-draining 150 ml plastic pots containing a peat-loam soil mix.
These were regularly watered with a 0.3% solution of a liquid fertilizer
(10:5:5).
Fifteen hours prior to placement in the chamber, plants were thinned to
a desired number, watered, and the soil surface sealed with petroleum jelly.
Plants were then kept in the dark at room temperature (20 C) and allowed to
drain into sand. Immediately prior to placement in the chamber, the pot was
encased in a second pot which served to seal the base as well as provide the
835
-------
roots with mercury-free air. Plant transpiration and chamber temperature
were then brought to a steady state over a period of 4.5 hours under the
illumination conditions of the experimental run. These were normally of 5
hours duration, in which time 5 to 8 estimates of r were made. After
each exposure period, the chamber and plants were purged for 2 hours with
mercury-free air. Plants were then kept overnight at 3 C and leaf area
determined the following day. This was achieved by comparison of the mass
of photo-copied replicates of the leaves with that of a template of known
area. For harvest, plants were bulked into leaf, stem, and root components,
and the radioactive mercury content determined for fresh and oven-dried
material (24 hours at 80 C) in the same manner as were the traps.
Uptake of Mercury Vapor by Homogenized Leaves
Two grams of fresh leaves from young plants of several species were
homogenized in 50 ml of 0.015 M paosphate buffer, pH 7.0, for one minute with
an Omni-mixer. The container and buffer were pre-chilled to 0 C. Two ml cbf
homogenate were pipetted into a test tube and a stream of air containing a
known concentration of 203Hg vapor was passed through the suspension at a
rate of 15 ml min~l for a period of 15 minutes. The amount of 203Hg uptake
by the leaf homogenate was directly measured, corrected for the blank value
using 2 ml of buffer alone, and calculated as percent conversion from the
total 203Hg bubbling through the system. The experiment was carried out
either in light or darkness. A 75-watt reflector light bulb was used as the
light source, and shined directly under a lucite water bath maintained at
25 C. The test tube was placed in the water bath about 8 cm from the light
source which provided an illumination of 1.5 klux. When the experiment was
carried out in the darkness, the test tube was wrapped with aluminum foil
and the light was turned off. The 203Hg in the homogenate was further analyzed
for mercuric mercury.
Sorption of Mercury Vapor by Soil Materials
The radioactive mercury generator consisted of a 30 x 150 mm test tube
with a sidearm outlet and an inlet tube at the top which extended almost to
the bottom of the test tube. After transfer of the liquid 203Hg (172 mg,
29.5 mCi) into the test tube, the generator was placed into a lead jar of 1-
inch thickness to provide shielding, and the jar was immersed in a thermo-
regulated water bath. Air was pumped into the generator from the inlet tube
at a constant flow rate which was measured by a precision flowmeter. The
203Hg vapor was carried off from the generator and entered a mixing flask in
which a mercury-free air was added to yield a desired concentration. The
203Hg vapor concentration of the atmosphere was controlled by: 1) the
temperature of the water bath; 2) the air flow rate into the generator; and
3) the dilution with mercury-free air. The determination of 203Hg vapor
concentration was achieved by passing a known volume of air through a hopca-
lite trap (a mixture of manganese oxide and copper oxide, Hopkin and Williams
Ltd., Chadwell Heath, Essex, England), measuring the radioactivity in the
trap, and calculating the vapor concentration from the known specific acti-
vity of the mercury. The temperature of water bath used in these experiments
varied from 25 to 40 C.
836
-------
In the experiments described here, a two gram sample of air-dry soil
was placed in a test tube and exposed directly to a controlled atmosphere
containing radioactive mercury vapor (203Hg) for a given period of time and
the uptake of 203Hg vapor was determined by direct measurement of the radio-
activity in the soil with a y-scintillation spectrometer equipped with a 3-
inch Nal well detector (Packard Model 5260 or Technical Associate Model SM-
10) . The background was generally less than 20 cpm for the Packard Model
5260 and 130 cpm for the SM-10, respectively. The 203Hg metal was purchased
commercially with an initial specific activity of 169 mCi/g mercury. The
dry soils were exposed either for various lengths of time, or at different
vapor concentrations. Samples of five soils from southeastern Montana,
several clay minerals, sand, dry straw, humic acid, cellulose powder, peat,
and charcoal were included in this study.
For the exposure of large amounts of soil, four 200 g samples of either
Arvada, Heldt, Bainville or Terry, and 100 g of Campspass soil were spread
individually in 10 cm diameter petri dishes which were randomly arranged in
a sealed bell jar. The top of the bell jar contained an inlet and outlet
9' ft 3
for passing the air containing u°Hg vapor through the bell jar. The inlet
tube was at the upper part of the bell jar with a small orifice and bent
outward, so as to create some mixing action. The outlet tube extended
almost to the bottom of the bell jar. A magnetic fan inside the bell jar
operated continuously to give additional mixing in order to avoid stratifica-
tion of the mercury vapor. The flow-rate was maintained at 100 ml per
minute. The concentration of mercury vapor was measured before and after
entering the bell jar. The difference between these two measurements was
due to the uptake by soil. These soil samples were exposed continuously for
23 days. The vapor concentration was measured daily except on the weekend.
After exposure, the soil samples were removed from the bell jar and the
radioactivity of each was measured using a 2 g sample. The soils were then
subjected to the following examination in order to learn the nature and
characteristics of the radioactive mercury retained by the soil. The treat-
ments were: 1) 24 hours under vacuum (5 mm pressure); 2) 110 C heating for
2 hours; 3) Suspending 2 g soil in 10 ml of tris buffer containing 50 mg
cysteine, bubbling air through the suspension for 30 minutes, and trapping
the vapor (volatile mercury); and 4) Bubbling air through the soil suspension
from (3) after addition of stannous chloride solution and trapping the vapor
(mercuric mercury).
To determine whether or not the sorbed mercury was available for plant
uptake, 50 wheat seeds were sown in each soil (200 g) and allowed to germi-
nate under greenhouse conditions. The soils were maintained moist by adding
water as needed. After 48 and 72 hours, ten seeds or seedlings were care-
fully removed from each soil, washed thoroughly to remove any soil particles
and their radioactivity determined. On the 7th and 10th days, the tops of
ten plants were cut off and counted. Because of the low level of radioactivity
observed, each sample was counted for 60 minutes to ensure the accuracy of
counting. After the wheat cultivation, the soils were allowed to dry at
room temperature, and 2 g aliquots were taken from each sample for the
measurement of total and mercuric mercury as described previously.
837
-------
RESULTS AND DISCUSSION
Estimation of Whole-Plant Resistance to Gaseous Exchange
The efficacy of estimating r on a whole-plant basis by the induction
of small changes in ambient humidity was examined in three initial experiments.
The study was confined to wheat plants (Triticw aestivwn) which were 11 days
of age from sowing.
Magnitude of Humidity Change Versus r n
J_i. n.2»~'
The term r ^ was estimated for a group of 12 wheat plants by decrea-
L. r
sing the relative vapor pressure of incoming air by progressively larger
increments. After each incremental decrease, the inlet relative vapor pres-
sure, or relative humidity, was approximately returned to the initial level
of 0.47. Total leaf surface was 154 cm2, the illumination 6.4 klux, and the
mean chamber temperature 32.90 + 0.05 C.
The relationship between change in inlet and outlet relative vapor
pressures is shown in Figure 22.3. The linearity of the relationship is
indicative of the plants remaining in a stable state during the course of
the experiment, irrespective of the direction or magnitude of change in
humidity. The considerable influence of the plants upon humidity within the
chamber is evident from the slope of the regression equation, and also the
mean ambient relative vapor pressure of 0.79. The slope of the function
would tend towards unity with increases in leaf resistance and chamber flow
rate, or a decrease in leaf surface area. Optimization of the quantity of
plant material placed in the chamber was therefore necessary to ensure that
changes in outlet humidity could be adequately resolved, and at the same
time avoid the creation of excessively high evaporative conditions.
From each change in humidity in Figure 22.3, an estimate of r _ was
L. 112^*
derived using equation 22.7, and these values are presented in Figure 22.4A.
The mean rL (+ SD) was 3.5 + 0.4 sec cm"1. The correlation (r = 0.32)
between magnitude of change in inlet relative vapor pressure and estimated
r n was not significant (P = 0.05). In other words, changes in ambient
L . n^U
or outlet relative vapor pressure ranging from 0.019 to 0.074 (Figure 22.3)
caused no significant change in estimates of r_ TT The implication is
L.ri20
that estimates of r did not substantially differ from the situation
Li. n.2y
where Ae/eQ (inlet) -X) and where errors arising from the assumptions concer-
ning rT and leaf temperature (TT ) would be minimal. This was an
L. rlpU Li
encouraging result since it indicates that Jarvis' approach is applicable
over an operable range of induced humidity changes.
The reason for such a result could not be determined from our data
since our facilities did not permit detection of small changes in leaf
temperature. One possibility is that the theory and assumptions, as
838
-------
• Increase
O Decrease
0.04
O.O8 0.12 0.16
A e/e0(Inlet)
0.20
Figure 22.3. Relationship between induced changes in relative vapor
pressure (e/e ) of air entering and exiting the plant
chamber. The chamber contained a group of 12 wheat
plants at a temperature of 39.2 C and an illumination
of 6.4 klux.
e
o
o
m
O
4
3
2
I
0
35
34
33
32
31
30
A
y = 3.24 + 2.57 x
B
y = 32.90 + 3.34 x
0 0.04 0.08 0.12
Ae/e0(lnlet)
0.16
0.20
Figure 22.4. Relationship between induced changes in relative vapor
pressure (e/e ) of air entering the plant chamber and
estimates of ? (A) total leaf resistance to water
vapor exchange (r ) and (B) leaf temperature (TL).
The chamber contained a group of 12 wheat plants at
a temperature of 32.9 C and an illumination of 6.4 klux.
839
-------
proposed, are correct and that the term ACL/Aqv (equation 22.6) was in fact
small or negligible. The mean value of Aqv (Aqv) in this experiment was
0.44 x 10~6 g cm"2 sec"1. If over the range of changes _in
-------
rL H 0 Were obtained with more substantial changes in humidity and also
higher temperatures (Table 22.2). This was a result of increased wet bulb
depression and hence reduced resolution errors in psychrometry.
TABLE 22.2. TOTAL LEAF RESISTANCE VERSUS CHANGE IN RELATIVE VAPOR
PRESSURE (e/e ) OF AIR ENTERING THE CHAMBER
Temperature (C)
Ae/e Direction 17 25 33 Mean (SE)
0.05
0.05 +
0.10
0.10 +
0.15
0.15 +
Mean
(SE)
2.8
4.0
3.3
2.1
3.2
2.3
3.0
(0.3)
sec cm
2.1
3.0
2.8
2.8
2.9
2.9
2.8
(0.1)
3.2
3.1
2.7
2.9
2.7
2.7
2.9
(0.1)
3.0 (0.3)
2.8 (0.2)
2.8 (0.1)
General
Mean
2.9
The lack of response of leaf resistance to temperature is notable since
these temperatures encompassed most of the range favorable to growth. Appa-
rently humidity levels within the chamber were sufficiently high to eliminate
indirect temperature effects. Slatyer and Bierhuizen (1964) reported no
effect of temperature on stomatal resistance of cotton leaves in the range
from 30 C to 40 C, while Hsiao (1975) concluded from the limited data
available that the slope of stomatal response to temperature curves is
gentle within the range of favorable growing temperatures.
Illumination and Temperature Versus rL H 0
Total leaf resistance values were determined for groups of 15 wheat
plants illuminated at 0, 1.6, 3.2, 6.4, or 12.8 klux at ambient temperatures
of 17, 25, or 33 C. Mean leaf area was 190 + 25 cm2. Five determinations
of r were made during a five-hour period by alternately decreasing and
L .H20
elevating vapor pressure of incoming air by an increment of 0.10. Relative
vapor pressure of air entering the chamber prior to the induced decrease was
0.42.
For convenience of scale, the response to illumination of leaf conduc-
tance (rT „ -1), rather than leaf resistance, is presented in Figure 22.5
L .
. -
Response at each temperature is indicated separately, although a second
order polynomial was fitted to the combined data by regression techniques,
the equation being
Y = (1.8 x 10~3) + (7.2 x 10"2) X - (3.0 x KT3) X2 (22.10)
841
-------
While other forms may have been more appropriate (Osman and Milthrope,
1971), this equation accounted for 94% of variation in leaf conductance, and
indicates negligible temperature effect within the examined ranges, as well
as a maximum value for r
L.H20
of 0.43 at an illumination of 12.0 klux.
o
CD
CO
E
o
0.5
0.4
0.3
0.2
-------
advantages with steady-state diffusion porometers (Campbell, 1975), in addi-
tion to being applicable to whole-plant studies. The method was therefore
adopted for the purposes of this work, although further examination of the
unresolved aspects of the theory appears warranted.
TABLE 22.3. ESTIMATED DIFFERENCE BETWEEN LEAF AND AMBIENT TEMPERATURE
Difference (C)
17
25
33
Total leaf
resistance
-1.9a
(1.7)
0.0
(1.3)
-1.7
(1.3)
82. 9b
(5.1)
9.1
(2.6)
5.9
(1.9)
2.0
(0.4)
16.7
(6.2)
1.1
(1.1)
2.9
(0.9)
1.3
(0.5)
sec cm
5.6
(0.8)
0.8
(0.4)
0.3
(0.2)
0.4
(0.1)
3.0
(0.2)
0.7
(0.4)
-0.4
(0.2)
-0.7
(0.3)
2.4
(0.2)
Aean (SE) of 5 estimates derived over a period of 5 hours.
Mean (SE) for all ambient temperatures.
Factors Influencing the Uptake of Hg Vapor by Wheat
In a second series of experiments, selected environmental parameters
were examined in relation to their effect on components of the proposed
model for mercury vapor uptake (equation 22.1). The study was again confined
to 11 day-old wheat plants and the factors examined were ambient temperature,
ambient mercury vapor concentration, illumination, and duration of exposure.
Illumination and Temperature Versus Hg Uptake
Groups of 15 plants were exposed to a mean mercury vapor concentration
of 16 (+ 2) yg m~3 for a duration of 5 hours at illuminations of 0, 1.6,
3.2, 6.4, or 12.8 klux. Similar exposures were repeated at ambient tempera-
tures of 17, 25, and 33 C. Distribution of mercury accumulated by the
plants is shown in Table 22.4. The incorporated mercury was largely immobile,
as indicated by the almost exclusive confinement to leaves. Oven drying
(80 C) of the leaves released a mean 10% of the mercury, with no detectable
changes in the mercury content of stems and roots.
Both stomatal and biochemical regulation of mercury vapor uptake might
be inferred from the pronounced decrease in dark uptake (Table 22.4). This
can be further appreciated from Figure 22.6, where the effect of both illumi-
nation and ambient temperature on mercury uptake by leaves is depicted.
Maximum uptake at each ambient temperature was attained at the low illumina-
tion level of 3.2 klux.
843
-------
TABLE 22.4. DISTRIBUTION OF MERCURY ACCUMULATED BY WHEAT. PLANTS
EXPOSED TO MERCURY VAPOR (16 yg m~3) FOR 5 HOURS
Illumination (klux)
Site 0 1.6 3.2 6.4 12.8
Leaves
Seems
Roots
9(2)a
0(0)
0(0)
38(6)
KD
1(1)
ng/plant
51(13)
2(1)
2(1)
60(8)
2(2)
2(1)
56(7)
KD
0(0)
uptake (SE) by fresh material at ambient
temperatures of 17, 25, and 33 C.
Conductance and Resistance to Hg Uptake
During each 5 hour exposure period in this experiment, five estimates
of leaf conductance of mercury vapor (rT u -1) were made. The reciprocal of
L.ng
the mean value of r ~ * was then taken as the average value of r for
the same period. This was considered to provide a better estimate of the
value of TT TT since gaseous exchange is a direct function of conductance
rather than resistance. Substitution of this value into equation 22.1,
together with determined values for C. „ and mercury uptake^ then generated
a value for the residual conductance of mercury vapor (rM 1). The effect
rl. rig
of illumination and ambient temperature on rT TT -1 and r., TT ~ 1 is shown in
* L.Hg M.Hg
Figure 22.7. The parameter r ~1, for which stomata represent the major
Li. rig
variable, was highly influenced by illumination level; however, no effect of
temperature on r * was discernible from these results.
L.rig
Since r and r are considered to be in series, it can be appre-
ciated that tne8low valuegof rM ~l (Figure 22_.7) was the predominant
factor limiting mercury uptake." The term r -1 (Figure 22.7) was largely
insensitive to illumination levels other than darkness, and this accounts
for the rapid plateauing of mercury uptake seen in Figure 22.6. The term
r,, H ~1 was influenced by temperature, although this is not obvious in
Figure 22.7. This is apparent in Figure 22.8, however, where r has
been expressed as a linear function of leaf temperature for all illumination
levels other than darkness. The plot of r versus leaf, rather than
ambient, temperature is a recognition of then! io chemical component of rM
Leaf temperature, however, only substantially differed from ambient temperlture
at the low illumination level of 1.6 klux. Thus a linear regression of
rM He versus ambient temperature would have equally accounted for the varia-
tion in rM (r2 = 0.88), with only a slight change in slope (b = -1.9) and
position (a = 111.2). Given a value for r of 11 7. 7-2. Ox (Figure 22.8),
it can be seen that rM ~1 would increase at8an increasing rate with tempera-
ture. Hence, in Figure 22.7, the difference in mercury uptake in light
between 25 and 33 C was greater than that between 17 and 25 C.
844
-------
00
-f>
Ul
Figure 22.7.
0.28
Effect of illumination and ambient
temperature on leaf (rr1!! ) an(* resi~
dual conductances of mercury vapor
(r"1 ) . Each point is the mean for
a groSp of 15 wheat plants exposed to
mercury vapor (16 yg m~3) for a period
of 5 hours.
I7C
25C
33 C
4 6 8 10 12
Illumination (k lux)
14
Figure 22.6.
Effect of illumination and ambient
temperature on mercury uptake by
leaves of wheat plants exposed to
mercury vapor (16 yg m~3) for 5
hours.
0.00
4 6 8 1O
Illumination ( k lux)
-------
90
80
70
o
8 60
50
40
30
y = 117.7-2.0 x
r2 = 0.88
• 1.6 klux
D 3.2 klux
• 6.4 klux
O 12.8 klux
15
20 25 30
Leaf Temperature ( C )
35
Figure 22.8. Effect of leaf temperature on the residual resistance
to mercury vapor uptake (rM ) in light (experiment 4).
The apparent low values of rM l in darkness (Figure 22.7) were in
contrast to those in light, and corresponded to the high r values of
237, 488, and 277 sec cm"1 at ambient temperatures of 17, 25, and 33 C.
These high values may, in part, have been a result of the inappropriate
nature of the assumption that the diffusion coefficients were independent of
stomatal aperture. With incomplete molecular slip, the reduction in diffusion
coefficients could be appreciable in the narrowest regions of stomatal
opening (Milthorpe and Penman, 1967; Cowan and Milthrope, 1968). If the
reduction in DH§ was greater than for DR Q, then TL R as derived from
equation 22.2 would be an underestimate, and hence the residual value of
rM Hg from e
-------
The durations of exposure were 5 hours, in which time 6 to 8 estimates of
~~l were made. Average values of r
' • "§ L. H£
rL He"1 were made> Avera§e values of r which are presented in Table 22.5,
were derived from the mean value of rL H • Analysis of variance revealed
no effect of mercury vapor concentrationgnor ambient temperature on r at
the 5% level of significance. There was no apparent interaction. L'Hg
TABLE 22.5. EFFECT OF AMBIENT Hg VAPOR CONCENTRATION AND AMBIENT
TEMPERATURE ON TOTAL LEAF RESISTANCE TO Hg VAPOR
EXCHANGE (rT „ )*
L.ng
Hg Vapor
Concentration
(wg m~3)
Ambient
17
Temperature (C)
25
33
Mean
rT TT (sec cm )
L.Hg
0
1.6
16
40
Mean
4.9
5.4
4.8
4.1
4.8
4.7
5.6
4.8
5.3
5.1
5.0
6.1
5.8
5.3
5.6
4.9
5.7
5.1
4.9
5.2
Illumination was 6.4 klux.
The r values were determined as in the previous experiment and
these are presented as a function of leaf temperature in Figure 22.9. The
results reaffirm the linearity of the relationship seen in Figure 22.8*
Apart from the obvious effect of temperature, there was no significant
effect of mercury vapor concentration on r H (5% level). This result is
supported by the data in Figure 22.10, where §he rate of mercury uptake by
leaves is depicted as a function of ambient mercury vapor concentration.
The curves for each ambient temperature are essentially linear and pass
through the origin. Given that r „ was effectively constant (Table 22.5),
any deviation of the curves from linearity would have indicated changes in
r« „ or CT „ (equation 22.1). As this was not the case, the assumption
M.Hg L.Hg H
that CT was zero appears to have been justified in these experiments. If
the binding sites for mercury vapor were specific, then this assumption could
become less valid under conditions inducive to high accumulation of mercury.
The mercury vapor concentrations examined in these experiments were
high when compared to normal background levels, which may range from 0.001
to 50 ng nf3 (D'ltri, 1972). High atmospheric concentrations have been
reported, however, such as 18 yg nr3 in an industrialized area of Japan
(Fujimura, 1964) and up to 40 yg m~3 in thermal areas of the Hawaiian Islands
(Siegel and Siegel, 1975).
847
-------
90
80
70
u
i? 60
w* 50
40
30
Figure 22.9.
15
y = 114.9 -2.2x
r2 = 0.85
a
a 1.6 ugrrf3
• 16 ugm~3
O 40 ug m"3
20 25 30
Leaf Temperature ( C)
35
Effect of leaf temperature on the residual resistance
to mercury vapor uptake (r ) at 3 ambient mercury
vapor concentrations. Illumination was 6.4 klux and
the exposure period 5 hours.
M
0»
Q.
0-8 •
0-6 -
0-4 •
00
10 20 30 40
Ambient Hg Vapor (fjq m"3)
5O
Figure 22.10.
Relationship between ambient mercury vapor concentra-
tion and the rate of mercury vapor uptake by wheat
leaves at 3 ambient temperatures and an illumination
of 6.4 klux.
848
-------
Duration of Exposure Versus Hg Uptake
Groups of 15 wheat plants were exposed to a mean mercury vapor concen-
tration of 1.01 (+0.08) yg nT3 for periods of 2, 4, 6, and 8 hours. The
illumination was 6.4 klux and the ambient temperature was 25 C. Mercury
vapor uptake by leaves was determined and was found to be linearly related
to the duration of exposure (Figure 22.11). These results correspond closely
to those of the previous experiment, as demonstrated by the comparison in
Figure 22.11 of actual mercury vapor uptake with that predicted from equation
22.1 knowing C. „ and predicting r_ „ from Table 22.5 and r from
A. rig Li. tig ri. ng
Figure 22.9. The linearity of this relationship and of those in Figure 22.10
indicates that mercury vapor uptake in these experiments did not approach
limiting levels.
500
— 400
CJ
*e
u
o»
°- 300
0
a
o»
X
200
100
O--O Actual
•—• Predicted
2 4 6 8
Exposure Time (hrs)
10
Figure 22.11.
The relationship between duration of exposure and
mercury uptake (actual and predicted) by leaves of
wheat plants exposed to mercury vapor (1.0 yg nT )
at 25 C and an illumination of 6.4 klux.
The close association between r and temperature, which prevailed in
previous experiments is intriguing, ^fifs suggests that r does substan-
tially reflect the rate of biochemical reactions involved in the binding of
mercury vapor. Although the nature of rM at this point remains uncharac-
terized, it can be said that the model was^luccessful in partitioning the
effect on mercury vapor uptake of those parameters which were studied.
849
-------
Differential Uptake of Hg Vapor by Plants
Mercury vapor uptake by six plant species was examined under uniform
conditions. The selected species all belonged to the family Gramimeae since
their growth habit was suited to the determination of resistances to gaseous
exchange using the present theory and plant chamber. The species were oats
(Avena sativa), barley (Hordeum vulgare), wheat (Tvitiown aestivwi), corn ^
(Zeamays), sorghum (Sorghum, vulgare),, and crabgrass (Digi-baria scmguivalis).
Oats, barley and wheat are plants characteristically possessing the GS
photosynthetic carbon fixation pathway, while corn, sorghum, and crabgrass
are C^-pathway plants.
Pots containing several plants of the one species were exposed for a
period of 4 hours to a mercury vapor concentration of 4.4 (+0.3) yg m"~ .
The illumination was 11 klux and the ambient temperature was 25 C. The
experiment was replicated three times and was of a completely randomized
design. The optimum height and leaf surface area of plant material with
regard to the plant chamber was 15 cm and 250 cm2 respectively. The age and
number of plants constituting an exposed group therefore differed between
species. The manner in which these prerequisites was met is presented in
Table 22.6.
TABLE 22.6. PARTICULARS OF PLANT SPECIES EXPOSED TO Hg VAPOR
Species
Oats
Barley
Wheat
Corn
Sorghum
Crabgrass
Plants/pot
20
17
18
6
10
11
Mean leaf Age
surface.area (days from sowing)
(caf)
255
278
231
281
192
267
(16)a
(29)
(23)
(14)
(26)
(13)
8
8
11
12
11
19
^ean (SD)
Mercury vapor uptake by the plants was determined and the results are
presented in Table 22.7. As in previous experiments, mercury vapor in all
species was seen to accumulate predominantly in the leaves. The mercury
uptake by leaves differed between species, but the pronounced difference was
that which existed between C$ and C^-type plants. The reason for this
difference is apparent in Table 22.8, where the calculated values for
components of the model for mercury uptake (equation 22.1) are presented.
The difference in Table 22.8 between r values for GS and C^ plants
would be expected in view of the difference in light saturation characteris-
tics. The effect of r on mercury uptake was small, however, compared to
that of r^ , the values8of which were high in C4 plants. Such differences
cannot be reasonably attributed to leaf age (Table 22.6) nor leaf temperature
850
-------
TABLE 22.7. TOTAL Hg UPTAKE BY PLANTS
Species
Oats
Barley
Wheat
Corn
Sorghum
Crabgrass
SE
F ratio
Significance
level
Leaves
198 (a)*
226 (b)
201 (a)
40 (cd)
25 (d)
54 (c)
7
183
<0.001
Hg untake (ne)
Stems
2.3 (c)
1.4 (c)
5.0 (ab)
3.5 (be)
2.6 (be)
6.5 (a)
0.8
5.4
<0.01
Roots
0.9 (a)
1.6 (b)
0.9 (a)
0.6 (a)
0.3 (a)
0.7 (a)
0.2
4.7
<0.05
Means followed by a common letter do not differ at a
significant level of 5% (DMR test).
TABLE 22.8. A SUMMARY OF RESISTANCES TO Hg VAPOR UPTAKE BY PLANT SPECIES
Species
Oats
Barley
Wheat
Corn
Sorghum
Crabgrass
SE
F ratio
Significance
Level
(sec cm )
4
5
4
14
23
13
1
52
<0
.9
.9
.0
.2
.2
.9
.0
.9
(a)*
(a)
(a)
(b)
(c)
(b)
rM.Hg
(sec cm )
72.
65.
60.
399.
448.
305.
19.
S6.
.001 <0.
0
4
1
4
9
4
4
3
(a)
(a)
(a)
(c)
(d)
(b)
TL
(C)
24.
25.
24.
26.
27.
26.
0.
20.
001 <0.
9
0
8
2
9
2
3
9
(a)
(a)
(a)
(b)
(c)
(b)
001
*
Means followed by a common letter do not differ at a
significance level of 5% (DMR test).
851
-------
(Table 22.8), and must reflect true differences in biochemical and physical
resistances to mercury vapor uptake (r ) between the examined €3 and
species. Mercury is known to inhibit phofosynthetic processes (Horwitz,
1957; Bradeen and Winget, 1974), and this apparent affinity of the vapor for
C3~type plants indicates that the binding sites for the vapor may be specific.
As such, mercury vapor uptake could be a useful tool for photosynthetic
studies.
In. V^t/io Conversion of Elemental Mercury Vapor by Homogenized Leaves
of Various Plant Species
In the experiments with wheat plants so far, the major factor governing
mercury vapor uptake, besides ambient vapor concentration, has been shown to
be leaf temperature. In terms of the model used, the effect of temperature
can be explained by its influence on those internal leaf resistances to
vapor uptake encompassed by the term r . Values of r were found to
decrease with increasirg leaf temperature and, except for'high values in
darkness, the relationship was linear and independent of illumination level
and mercury vapor concentration over the ranges examined.
Differences found in mercury vapor uptake by C$ and Ci+ plant species
under uniform conditions were also largely attributable to differences in
the value of r^ . Since, by definition, biochemical processes contribute
to the value °* rMu2» the following experiments were conducted with homo-
genized leaves with a view to elucidating the possible nature and sites of
the processes involved. Several plant species were examined and these in-
cluded the Cs species - wheat, barley, oats, and water spinach; and the C^
species - corn, sorghum, and crabgrass. Leaf homogenates were prepared and
exposed to mercury vapor as described under Materials and Methods.
Due to the destruction of cellular integrity by the homogenizing pro-
cedure, mercury vapor uptake by the homogenates can be expected to be far
less specific than in the case of the whole plant. There was, however,
notable agreement between results of these experiments and those involving
whole plants in that the conversion of mercury vapor was greater in light
than in darkness for all species except sorghum (Table 22.9). Homogenates
of all C3 plants also exhibited higher percent conversion values than those
of C4 plants, both in light and in darkness (Table 22.9). The rate of
conversion of mercury vapor by the homogenates was linearly related to vapor
concentration (Figures 22.12-22.15), as was also found with whole wheat plants
(Figure 22.10). Higher vapor concentrations resulted in greater mercury
uptake, although the homogenates of younger leaves of wheat and crabgrass
tended to have higher percent conversion values, possibly owing to higher
enzymatic activity.
Boiling the leaf homogenate resulted in a 90 per cent loss of activity.
Enzyme inhibitors such as sodium azide, sodium cyanide, sodium fluoride,
sodium arsenite, and sodium malonate showed various degrees of inhibition
(Table 22.10). The specific photosynthetic inhibitor monuron gave a marked
inhibition of mercury vapor conversion in the case of water spinach. Ami-
trole, an inhibitor of catalase, also gave a high inhibition. Such results
indicate that the conversion and uptake of elemental mercury vapor by plant
852
-------
TABLE 22.9. IN VITRO CONVERSION OF 203Hg° VAPOR BY THE LEAF
HQMOGENATE OF VARIOUS PLANT SPECIES
Species
Water spinach
Wheat
Barley
Oat
Corn
Crabgrass
Sorghum
% Conversion ]
Light
20.6 + 4.4 (12)
11.0 + 6.4 (8)
12.2 + 1.6 (4)
12.3 + 1.5 (4)
3.1 + 0.7 (6)
7.9 + 4.3 (11)
1.1 + 0.3 (4)
Dark
8.6 + 2.8 (12)
5.2 + 3.6 (8)
7.9 + 1.5 (4)
8.6 + 1.2 (4)
2.2 + 0.9 (6)
4.4 + 2.8 (11)
2.2 + 0.2 (4)
Light/ Dark
2.4
2.1
1.5
1.4
1.4
1.8
0.5
2 ml of leaf homogenate (0.08 g fresh leaf) were used In each
experiment. Air containing different Hg vapor concentration
was bubbled through the suspension for 15 minutes at 15 ml per
minute. Percent conversion was calculated from the net uptake
by the leaf homogenate and the total amount of mercury in the
air which passed through the homogenate.
Figure 22.12.
203Hg° Concentration, pg/liter
2.0
In vitro conversion of 2°3Hg vapor by water spinach leaf
homogenate in relation to the vapor coacentra :i*o.
Homogenate used = 0.08 g fresh leaf; time = 15 mm.
853
-------
?IOO
o
"in
o
o
IO
o
CM
• • Light
A A Dark
0
0.5 1-0 1-5
203Hg° Concentration, pg/liter
203i
Figure 22.13. In vitro conversion of 203Hg vapor by wheat leaf
homogenate in relation to the vapor concentration.
Homogenate used = 0.08 g fresh leaf; time = 15 min.
u»
c
c
o
V
^
o
o
X
10
O
(M
10
0.5
1.0
1.5
Hg Concentration, pg /liter
Figure 22.14. In vitro conversion of 203Hg vapor by corn leaf
homogenate in relation to the vapor concentration.
Homogenate used = 0.08 g fresh leaf; time = 15 min,
854
-------
100 -
f
o
U)
Q>
O
O
o
o»
X
10
o
CM
50
Light
Dark
0.5
1.0
1.5
203Hg° Concentration, Mg/liter
Figure 22.15. In vitro conversion of 203Hg vapor by crabgrass leaf
homogenate in relation to the vapor concentration.
Homogenate used = 0.08 g fresh leaf; time = 15 min.
TABLE 22.10. INHIBITION OF 203Hg VAPOR UPTAKE BY LEAF HOMOGENATE
OF SOME C3 AND C4 PLANT SPECIES BY ENZYME INHIBITORS
Inhibitors
NaH
NaF
NaAs02
NaCN
Melonate
Amitrole
Monuron
1
1
1
1
1
1
1
x 10~3M
x 10-3M
x 10" 3M
x 10~3M
x ICT^M
x 10~3M
x 10~5M
Water spinach
Light
82
17
26
18
48
75
76
Dark
91
0
58
0
31
77
92
Wheat
Light
100
36
30
98
18
95
_
Dark
100
39
82
100
50
100
_
Corn
Light
92
47
26
90
35
48
_
Dark
100
57
40
83
30
69
_
Crabgrass
Light
84
25
8
81
9
40
-
Dark
100
25
54
100
28
46
-
855
-------
leaves is an enzymatically controlled process which is in part, at least,
light dependent. A non-specific oxidative enzyme such as catalase may also
be involved in such conversion, since greater than 90 per cent of the mercury
in the leaf homogenates was in the mercuric form in all species examined.
Sorption of Mercury Vapor by Soils
Table 22.11 shows the result of mercury vapor sortition by the soils,
clay minerals, peat, charcoal, sand, and organic materials which were exposed
to an atmosphere containing 75.9 yg metallic 203Hg vapor/m3 for 24 hours at
room temperature. Among the five soil samples, Campspass, which had the
highest organic matter content, had the highest uptake, followed closely by
the Heldt and Bainville soils. The high clay content Arvada and sandy Terry
soils sorbed approximately one-fourth of the amount sorbed by the Campspass
soil. The peat sample sorbed about twice the amount of Hg as the Campspass
soil. Humic acid sorbed slightly more Hg than the peat. Granular charcoal
sorbed about twenty times as much Hg as the peat, while the dry straw and
cellulose powder sorbed very little Hg. Among the clay minerals, illite had
the highest sorbing power (0.308 yg) for elemental mercury vapor, while
kaolinite had the lowest (0.004 yg). Higher sorption of Hg vapor by illite
as compared to montmorillonite and kaolinite was also reported by Trost and
Bisque (1972). The nature of organic matter in the soil was also important,
as humic acid sorbed a great deal more mercury vapor than dry straw or
cellulose powder. The organic-rich A soil horizons studied by Trost and
Bisque (1972) all sorbed more vaporous mercury than did the clay-rich B soil
horizons, and they suggested that the variations in mercury sorbed by the A
horizons may reflect chemical variations in the type of humic matter forming
under different vegetative covers. The wide range of sorption observed here
with these materials leads one to believe that the nature of the assemblage
of minerals and organic residues must play an important role in determining
the sorption capacity of a soil for mercury vapor.
Of the total 500 yg of Hg vapor passed through the bell jar, 353 yg
was adsorbed by soils, 111 yg was collected in the hopcalite traps, and 35
yg was unaccounted for (adsorbed on surfaces of the bell jar, petri dishes,
tubing, etc.). The average Hg vapor uptakes were 8.48 + 0.82 yg, 18.57 +
0.62 yg, 18.06 + 1.51 yg, 36.54+ 2.74 yg and 6.57 + 0.68 yg for the Arvada,
Campsgass, Heldt, Bainville and Terry soils, respectively. The concentration
of Hg vapor was reduced from 75.5 yg/m3 at the inlet, to 16.8 yg/m3 at the
outlet. Three factors would influence the removal of Hg° vapor from the
air, namely: 1) the sorbing power of soil, 2) the surface area, and 3) the
duration of contact. Since the volume of the bell jar was 23 liters and the
air flow rate was 100 ml/min, a complete air change in the bell jar required
230 minutes in which time 78% of the Hg vapor was sorbed. If the rate of
sorption had remained constant, then 99% of mercury vapor could have been in
a 12-hour period, given a stagnant situation.
Mercury Vapor Concentration
Five Montana soils and three clay minerals were exposed for 24 hours to
air containing from 85.16 to 208.67 yg Hg°/m3 of air (Table 22.12). The
sorption of mercury vapor increased with increasing mercury vapor concentrations.
856
-------
TABLE 22.11. 24 HOUR SORPTION OF 203Hg-ELEMENTAL VAPOR BY SOILS,
CLAY MINERALS AND OTHER MATERIALS IN AN ATMOSPHERE
CONTAINING 75.9 yg 203Hg°/m3
203
Soils, Minerals Hg Vapor
and Others Sorbed, ug
Arvada 0.018
Campspass 0.077
Heldt 0.076
Balnville 0.072
Terry 0.015
Sand 0.002
Kaolinite** 0.004
Bentonite** 0.021
Illite #35* 0.308
Montmorlllonite #25* 0.008
Metabentonite #38* 0.059
Cellulose powder 0.004
Dry straw 0.011
Humic acid, technical 0.170
?eat** 0-148
Charcoal 2.943
* Purchased from Ward's Natural Science Establishment, Inc.
** Kindly provided by the Soils Department, Oregon State University.
857
-------
Tliis sorption may be expressed by Freundlich's adsorption equation:
x , n
— = kc
m
where x is the amount of mercury vapor sorbed in yg, C is the concentration
of mercury vapor in yg Hg/m3, m is the mass of adsorbent, n and k are con-
stants. Expressed logarithmically, the equation takes the form:
log — = log k + n log C.
° m
By plotting log— against log C, a straight line was observed (Figure 22.16).
The empirical k and n values are estimated by the least squares method from
the experimental points. A higher k value is an indication of greater
sorption.
Exposure Time
To determine sorption capacities, the minerals and soils were exposed
to air containing an average Hg concentration of 79.2 yg/m3 for 16-17 days.
Sorption measurements were made daily initially and every other day later
during the exposure period by temporarily removing each sample for a 10
minutes radioassay. The sorption of mercury vapor, although decreasing
progressively with time, never reached a saturation state after 17 days of
exposure (Figure 22.17). The average daily sorptions and ranges were 0.017
(.012-.025), 0.059 (.039-.077), 0.030 (.015-.080), 0.047 (.018-.072), and
0.010 (-006-.015) yg Hg per 2 g of the Arvada, Campspass, Heldt, Bainville,
and Terry soils, respectively. These values were slightly less than-the
single day values reported in Table 22.11. The average Kg sorption by montmo-
rillonite //25 was even lower than those of Arvada and Terry, and there was
very little increase of uptake after 12 days. Illite had the highest rate
of Hg sorption; the Hg sorptions of illite and metabentonite per unit time
also decreased progressively with the time of exposure.
Nature of Mercury in Soil After Sorption
There was no loss of radioactivity in these soils after: 1) being
placed in a vacuum dessicator for 24 hours, 2) being heated in an oven at
110 C for 2 hours, or 3) bubbling a stream of air through the suspension to
remove the mercury vapor (Clarkson and Greenwood, 1970). Failure to remove
any radioactivity by these treatments suggested that the sorbed mercury
vapor must be either very tightly bound or transformed into a non-volatile
form. Samples were analyzed by the method of Clarkson and Greenwood (1970),
and only a small fraction of the sorbed mercury vapor was shown to have been
converted to the mercuric form (Table 22.13). Other mercury forms remained
unidentified.
858
-------
TABLE 22.12.
UPTAKE OF 203Hg-ELEMENTAL MERCURY VAPOR BY DRY SOILS AND
CLAY MINERALS AT VARIOUS VAPOR CONCENTRATIONS*
Hg Vapor Concentration, ng/m
Adsorbants
Arvada
Campspass
Heldt
Bainville
Terry
Illite //35
Kaolinite
Bentonite
85.16
Ug/2 g
.016
.045
.037
.052
.016
.383
.005
.017
135.88
.026
.084
.065
.094
.028
.607
.011
.035
185.19
.057
.152
.126
.183
.054
.692
.028
.079
208.67
.080
.191
.147
.217
.062
.948
.020
.105
Adsorption
Characteristics
n
1.79
1.60
1.56
1.63
1.56
.91
1.74
2.07
k
4.89 x
3.52 x
3.40 x
3.54 x
1.50 x
6.71 x
2.28 x
1.56 x
io-6
io-5
io-5
io-5
io-5
io-3
io-6
io-6
Two gram samples were exposed for 24 hours in an atmosphere containing
various 203Hg vapor concentrations.
Figure 22.16. Freundlich's plots of metallic mercury vapor sorption
by dry soils and illite.
859
-------
TABLE 22.13. TOTAL AND MERCURIC 203Hg CONTENT OF MERCURY VAPOR-
EXPOSED SOILS BEFORE AND AFTER CULTIVATION
Total Hg Content
Soils
Arvada
Camp spaas
Heldt
Bainville
Terry
Before
8.25
20.03
19.80
40.05
7.20
After
8.08
22.21
21.75
36.70
4.56
Mercuric Mercury
Before
HE
1.66
0.42
4.44
4.04
1.97
%
20.1
2.1
22.4
10.1
27.4
After
0.44
0.99
3.78
3.78
0.41
%
5.4
4.5
17.4
10.3
8.9
1.0,-
0.0
10
15
20
Time, doys
FIGURE 22.17
Accumulative sorption of metallic mercury vapor by dry
soils and clay minerals. 203Hg vapor concentration
was 79.2 yg/m3. Weight of soil or clay mineral was 2 g
860
-------
Plant Uptake
Fifty seeds were sown and germinated in petri dishes containing soils
exposed to mercury vapor as described above. Beacuse of extremely low radio-
activity in the seeds and leaves, the counting error remained high even though
samples were counted for 60 minutes. Conclusions from the presented data are
therefore limited. It is apparent, however, that the mercuric mercury content
of all soils was low (Tables 22.13 and 22.14) and was not necessarily a
simple function of total mercury content. When the data were pooled for all
sampling dates, there was a linear relationship (P = 0.05) between soil mercuric
mercury content and the mercury content of seeds and leaves (Figure 22.18).
There was no such relationship with total soil mercury.
CONCLUSION
Soils of different characteristics, clay minerals and various organic
materials exhibited various degrees of sorption for mercury vapor. Among the
clay minerals, illite had the highest sorption capacity, while kaolinite had
the lowest. Different types of organic materials were also shown to have a
wide range of sorption capacity; the highest being for humic acid and lowest
for cellulose powder. Both the organic matter and mineralogical make-up
of the soil may play an important role for the wide range of mercury vapor
sorptions observed. The sorption phenomenon for soils was adequately de-
scribed by the Freundlich type equation. The data indicated that the sorp-
tion of mercury vapor did not reach its maxima when the mercury vapor concen-
tration was increased to 209 yg/m3 or the soils were continually exposed for
17 days. Only a small fraction of mercury sorbed was transformed to mercuric
form. The major portion of the mercury sorbed by soils remained unidentified
and a further study of transformation is needed.
For studies into the uptake of mercury vapor by plants, a simple theory
and plant chamber were employed to estimate total leaf resistance of whole
plants to water vapor exchange. The estimates were independent of leaf
temperature. The approach involved the measurement, at steady state conditions,
of the net change in water vapor flux per unit leaf surface (Aqv) in response
to a small change in absolute humidity (AC.). Assuming that total leaf
resistance (rL) was constant and that change in leaf temperature (TL) was
negligible, total leaf resistance was calculated from the following equation
r? = ACA/Aq (sec cm"1)
Evidence is presented which indicates that such assumptions did not signifi-
cantly alter estimates of r from the true values for changes in ambient
relative humidity ranging from 0.011 to 0.074. Total leaf resistance of
whole-plant communities estimated in this manner did not differ for ambient
temperatures of 17, 25 and 35 C. Mean values of r ranged from 83 sec cm
in darkness to 2.4 sec cm"1 at an illumination of T2.8 klux.
Using a whole-plant chamber and 203mercury, a quantitative study was
made of the effect of environmental parameters on the uptake of metallic
mercury vapor by wheat. Factors were examined in relation to their influence
on components of the gas-assimilation model.
861
-------
TABLE 22.14. UPTAKE OF 203Hg BY GERMINATING WHEAT SEEDS FROM SOILS
AFTER EXPOSURE TO 203Hg-ELEMENTAL MERCURY VAPOR
10 Seedlings
Soils
Arvada
Camp spaas
Heldc
Bainville
Terry
Total
203H8
8.25
20.03
19.80
40.05
7.20
Mercuric
!^.
Kg
1.66
0.42
4.44
4.04
1.97
2 days
8.4
6.5
15.0
15.0
7.6
3 days
9.1
9.7
14.6
18.1
6.5
Leaves From
10 Plants
7 days
5.7
2.3
9.8
4.6
2.6
10 days
ng
2.6
1.5
5.1
6.2
1.6
50 r
123
Soil Mercuric Hg Content,
Figure 22.18.
Plant uptake of 203Hg from soils previously exposed to
metallic 203mercury vapor. Mercuric-Hg content of the
dry soil expressed as yg Hg per 200 g soil. 203Mercury
content of wheat tissue expressed as ng Hg per 20
seedlings or leaves from 20 plants.
862
-------
p' _ p'
A C T
U(Hg) = A L
rL.Hg + rM.Hg
where TJ(Hg) is the rate of mercury uptake per unit leaf surface, C' is the
ambient mercury vapor concentration, C' is the mercury concentration at
immobilization sites within the plant (assumed to be zero , r is the
L.Hg
total leaf resistance to mercury vapor exchange, and rM is the residual
term to account for unexplained physical and biochemical resistances to
mercury vapor uptake. rL was particularly influenced by illumination
(o to 12.8 klux), but unaffected by ambient temperature (17 to 33 C) and
mercury vapor concentration (0 to 40 yg m~3. The principal limitation to
mercury vapor uptake was rM , which was linearly related to temperature,
but unaffected by mercury vapSr concentration and illumination, except for
apparent high values in darkness. Knowing C' and estimating r and
rM He from experimental data, mercury vapor uptake by wheat in ligSt was
accurately predicted for several durations of exposure using the above model.
Uptake of mercury vapor was found to differ between plant species, but
the most pronounced difference was that which existed between plants possessing
63 and Ci± photosynthetic pathways. In terms of the model employed, such
differences were largely attributable to differences in the internal bio-
chemical and physical resistances encompassed by the term rM „ .
M. rig
In vitro experiments with homogenized leaves revealed that the uptake
and conversion of elemental mercury vapor to mercuric mercury by the leaves
of various plant species was an enzymatic process. This process was in part
light dependent. A non-specific oxidative enzyme such as catalase may also
be involved, since mercury conversion was impaired by amitrole.
REFERENCES
Aston, M. J. 1976. Variation of Stomatal Diffusive Resistance with Ambient
Humidity in Sunflower (Heli-anthus annuus'). Aust. J. Plant Physiol.,
3:489-501.
Bierhuizen, J. F., and R. 0. Slatyer. 1964. Photosynthesis of Cotton Leaves
Under a Range of Environmental Conditions in Relation to Internal and
External Diffusive Resistance. Aust. J. Biol. Sci., 17:348-359-
Bradeen, D. A., and G. D. Winget. 1974. Site-specific Inhibition of Photo-
phosphorylation in Isolated Spinach Chloroplasts by HgCl2. II.
Evidence for Three Sites of Energy Conservation Associated with Non-
cyclic Electron Transport. Biochim. Biophys. Acta, 333:331-342.
Campbell, G. S. 1975. Steady-state Diffusion Porometers. In: Measurement
of Stomatal and Diffusive Resistance. Bull. 809; College of Agriculture
Research Center, Washington State Univ.; pp. 20-23.
Clarkson, T. W., and M. R. Greenwood. 1970. Selective Determination of
Inorganic Mercury in the Presence of Organomercurial Compounds in
Biological Material. Anal. Biochem., 37:236-243.
863
-------
Cowan, I. R., and F. L. Milthorpe. 1968. Plant Factors Influencing the
Water Status of Plant Tissues. In: Water Deficits and Plant Growth,
vol. 1, T. T. Kozlowski, ed. Academic Press, New York. pp. 137-193.
D'ltri, F.M. 1972. The Environmental Mercury Problem CRC Press, Cleveland
Ohio.
Fujimura, Y. 1964. Studies on the Toxicity of Mercury. Jap. J. Hyg.,
18:10.
Gates, D. M. 1968. Transpiration and Leaf Temperature. Ann. Rev. Plant
Physiol., 19:211-238.
Hall, A. E. , and M. R. Kaufmann. 1975. Stomatal Response to Environment
with Sesamm indicwn L. Plant Physiol., 55:455-459.
Horwitz, L. 1957. Observation on the Effect of Metallic Mercury upon Some
Microorganisms. J. Cell, and Comp. Physiol., 49:437-454.
Hsiao, T. C. 1975. Variables Affecting Stomatal Opening—Complicating
Effects. In: Measurement of Stomatal and Diffusive Resistance.
Bull. No. 809; College of Agriculture Research Center, Washington State
Univ.; pp. 28-31.
Jarvis, P. G. 1971. The Estimation of Resistances to Carbon Dioxide Transfer,
In: Plant Photosynthetic Production. Manual of Methods. Z. Sestak,
J. Catsky, and P. G. Jarvis, ed. Dr. W. Junk, N.V., Publishers. The
Hague, pp. 566-631.
John, M. K. 1972. Mercury Uptake from Soil by Various Plant Species. Bull.
Environ. Contain. Toxicol., 8:77-80.
Jost, W. 1952. Diffusion in Solids, Liquids and Gases. Academic Press,
New York, 413 pp.
Mikhailov, V. K. and M. I. Kochegarova. 1967. Diffusion and Thermal Diffu-
sion of Mercury Vapor in Air. In: Chem. Abstracts, 69:5777.
Milthorpe, F. L. , and H. L. Penman. 1967. The Diffusive Conductivity of the
Stomata of Wheat Leaves. J. Exp. Bot., 18:422-457.
Organization for Economic Cooperation and Development. Paris, 1974.
Mercury Use and Emission. In: Mercury and the Environment, pp. 73-74.
Osman, A. M., and F. L. Milthorpe. 1971. Photosynthesis of Wheat Leaves in
Relation to Age, Illuminance and Nutrient Supply: II. Results.
Photosynthetica, 5:61-70.
Siegel, S. M. , and B. Z. Siegel. 1975. Geothermal Hazards. Mercury Emission,
Environ. Sci. Technol., 9:473-474-
Slatyer, R. 0. 1967. Plant-water Relationships. Academic Press, New York.
p. 14.
864
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Slatyer, R. 0. 1971. Effect of Errors in Measuring Leaf Temperature and
Ambient Gas Concentration on Calculated Resistance to C02 and Water
Vapor Exchange in Plant Leaves. Plant Physiol., 47:269-274.
Slatyer, R. 0., and J. F. Bierhuizen. 1964. Transpiration from Cotton
Leaves Under a Range of Environmental Conditions in Relation to Internal
and External Diffusive Resistances. Aiist. J. Biol. Sci., 17:115-130.
Spier, J. L. 1940. The Determination of the Coefficient of Diffusion of
Mercury Vapor and Cadmium Vapor in Nitrogen. Physica, 7:381-384.
Tanner, C. B. 1972. Psychrometers in Micrometeorology. In: Psychrometry
in Water Relations Research, R. W. Brown and B. P. Van Haveren, eds.
Utah Agric. Exp. Sta., Utah State Univ., pp. 239-247.
Trost, P. B., and R. E. Bisque. 1972. Distribution of Mercury in Residual
Soils. In: Environmental Mercury Contamination, R. Hartung and
B. D. Dinman, eds, Ann Arbor Science Publisher Inc., Ann Arbor, Mich.
pp. 178-196.
Van Haveren, B. P., and R. W. Brown. 1972. The Properties and Behavior of
Water in the Soil-Plant-Atmosphere Continuum. In: Psychrometry in Water
Relations Research, R. W. Brown and B. P. Van Haveren, ed. Utah
Agric. Exp. Sta., Utah State Univ., pp. 1-27.
865
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SECTION 23
EFFECTS OF STACK EMISSIONS UPON PRIMARY ASPECTS OF PHOTOSYNTHESIS
AND PHOTOSYNTHETICALLY-LINKED NITROGEN FIXATION
R. M. Tetley and N. I. Bishop
ABSTRACT
The toxicity of selected trace elements emitted
from coal-fired power plants was determined for several
biological functions in the blue-green algae, Anabaena
oylindrioa. This organism performs the basic biologi-
cal functions of nitrogen fixation, photosynthesis,
respiration, and growth, was easily adaptable to exis-
ting measurement techniques, is of significance in the
grassland biome, and provides an excellent multifunc-
tional organism for testing the effects of emission
contaminants. The elements tested were F, Na, Cl, Br,
Li, K, Sr, Ba, Cr, Mn, Ni, Cu, Zn, Cd, Hg, Pb, and As.
In order of decreasing toxicity Hg, Cu, Cr, Ni, Cd,
and Pb exerted strong inhibition at levels of 1 mM or
below. In assays of biological functions Hg, Cu, Zn,
Cd, and Pb exhibited strong toxicity at 1 mM or lower
levels. Considerably greater sensitivity was seen
with Cr, Ni, Mn, Cu, Sr, and Hg in growth studies than
in physiological assays. The metabolic inhibitors
KCN, DCMU, m-Cl-CCP, and DBMIB, and the interaction of
light and oxygen on nitrogenase activity were studied
and compared to metal toxicity effects. These studies
resulted in the recognition of methodology artifacts
which should be acknowledged in field and laboratory
nitrogen fixation studies. In the strain of Anabaena
used, and under controlled conditions, hydrogen produc-
tion serves as a sensitive measure of nitrogen fixation,
866
-------
INTRODUCTION
In establishing a short-term program capable of surveying the biological
impact of trace elements present in the stack emissions of coal fired power
plants, it was important to choose an appropriate biological system. The
criteria used to select an organism or system for this study were that it
performed several basic biological functions, that it was easily adaptable
to existing measurement and assay techniques, and that it was of significance
in the grassland biome as well as having importance in other environmental
settings. The decision to use blue-green algae for the organism in this
study was made because they fit the previous criteria.
Blue-green algat ,. -„ r«. aived increased attention recently and their
biology is surveyed thoroughly in two relatively new reviews (Carr and
Whitton, 1973; Fogg, et aZ., 1973). Certain blue-green algae are capable of
fixing atmospheric nitrogen gas into biologically usable ammonia as well as
functioning in the role of photosynthetic primary producers. Therefore,
apart from the photosynthetic bacteria, the growth and metabolism of the
blue green algae is unique in that it includes the basic biological functions
of nitrogen fixation, photosynthesis, respiration, and growth. As will be
discussed in the methods portion of this section, it is possible to grow
blue-green algae in a manner suitable to measure these biological functions
with existing instrumentation. Although blue-green algae have a broad
aquatic distribution, including lakes, streams, hot springs, estuaries, salt
marshes, and marine habitats, their importance in soils is becoming more and
more apparent. Blue-green algae are extremely abundant in certain soils and
function to retard erosion, maintain moisture, add organic content, and fix
nitrogen. The terrestrial algae are considered to be most abundant in rich
moist soils, but may be the dominant microflora in arid soils.
Blue-gix algae are also responsible for large inputs of nitrogen into
certain tropical agricultural soils (MacRae and Castro, 1967). However,
high fixation rates have also been observed in pasture and meadow land in
temperate regions (Henriksson, 1971) as well in arid regions of the United
States (Mayland et al.3 1966). In addition, it has been generally esta-
blished that nitrogen fixed by soil blue-green algae eventually becomes
available to other associated organisms such as higher plants.
The vertical distribution of blue-green algae in soil may extend to
more than a meter, but because of their obligate photoautotrophic nature,
they are most abundant near the soil surface. It is reasonable to assume
that deposition of particulate matter containing trace quantities of various
elements would have early effects on the microalgae present in this zone.
It appears, therefore, that nitrogen fixing blue-green algae are not only
superb multifunctional organisms for testing the effects of emission contamin-
ants on biological function, but they are also important organisms which
would be affected by such contaminants in the grassland biome.
For these reasons then, this study was undertaken to investigate the
effects of trace elements on photosynthesis, nitrogen fixation, respiration
and growth in the blue-green algae, Anabaena cylinfoiea and the water ferns
Salvin'ia and Azolla.
867
-------
In addition to the trace elements being tested, several metabolic inhibi-
tors, whose mode of action is well known in other systems, were included to
assist in interpreting the action of active trace elements. The role of ^
oxygen in stimulating and inhibiting hydrogen production (nitrogen fixation)
was also investigated and related to the inhibitor study. As a check of the
sensitive hydrogen production assay used to determine nitrogenase activity,
a series of experiments were conducted using the acetylene reduction assay
for comparison.
MATERIALS AND METHODS
Culturing of blue-green algae
The blue-green algae chosen for assays of trace metal effects was
Andbaena oylindrica Lemm. (B629). This organism has demonstrated an active
nitrogenase activity which may be assayed by measuring hydrogen production
(Jones and Bishop, 1976). Cells were grown on the medium described by
Castenholz (1970) without the addition of nitrate. The nitrogen remaining
in the iron chelator does not inhibit the production of the nitrogenase.
Cells were grown at a density of approximately 3.5 yl packed cell volume
(PCV) per ml of culture medium in a constant density growth apparatus similar
in function and design to that described by Senger and Wolf (1964), but
fitted with overflow and sampling ports on the side of the tube. Cultures
were illuminated at a light intensity of about 8 x 104 ergs/cm2/sec from
mixed fluorescent tubes supplemented with tungsten bulbs. Culture tempera-
ture was maintained at 24 to 27 C and aerated with 2% CO 2 in air. Continuous
cultures were renewed occasionally from batch grown stock cultures which
were subcultured every four to six days.
Assay Procedures
Single samples of algae were prepared for assay by removing 10 to 12 ml
aliquots from the growth tube and concentrating the cells by centrifugation.
PCV values were determined by centrifuging 10 ml of the culture at 1250 x G
for 5 minutes in Constable protein tubes. For analysis cells were resu-
spended in 1.8 to 2.0 ml of culture media and placed in small 10 to 25 ml
Erlenmeyer flasks capped with serum stoppers. The gas over the cell suspen-
sions was removed three times by aspiration and replaced by argon or helium
after each evacuation. The cells were stored anaerobically in the absence
of nitrogen for short periods before assay. Various gas mixtures were
produced by adding measured volumes of gas with syringes to cell samples
that had been evacuated an additional time. The balance of the pressure was
provided with argon or helium. After addition of the cells to the cuvette,
they were treated in the following manner (see Figure 23.1): 1) addition
of 5% of the cuvette volume of test solution and dark incubation for 3 to 5
minutes, 2) irradiation with white light with an intensity of approximately
7.5 x 104 ergs/cm2/sec for three to six minutes until oxygen and hydrogen
production rates were established, and 3) a dark period of three to six
minutes in which respiratory rates were established. If photosynthesis was
inhibited during the light irradiation steps, oxygen was added to the cuvette
to establish a respiratory rate at an oxygen concentration of about 100 yM.
868
-------
Changes in oxygen and hydrogen concentrations were monitored by an
apparatus similar to that described by Jones and Bishop (1976). Two Yellow
Springs Instrument 4004 Clark type electrodes were fitted to a 1 30 ml
jacketed plexiglass cuvette maintained at 27 C and mixed by a small magnetic
stirrer. Polarization voltages of -0.8 and +0.6 volts were maintained on
the oxygen and hydrogen platinum electrodes respectively. Electrode currents
were amplified and scaled by two Keithley electrometers (Models 601 and 602)
and recorded on a dual pen recorder (Linear Instruments Corp., Model 291).
Illumination was provided by a Tiyoda (Model 7034) variable output lamp.
Argon, helium, and hydrogen were obtained from Airco, Inc. and C. P. Grade
ethylene gas used as an ethylene standard was supplied by Matheson Gas
Products. All trace elements tested were of reagent grade and commonly
available from chemical companies. Test solutions produced by serial dilu-
tion of concentrated stock solutions of trace elements were purged with
argon or helium and stored oxygen and nitrogen free prior to their addition
to the reaction cuvette with small syringes. Oxygen and hydrogen responses
of the electrodes were calibrated with culture media in equilibrium with air
for 20.9% oxygen and 2 or 10% hydrogen and the values used were 247.8, and
15.0 or 74.9 ymolar respectively at 27 C (Dean, 1973; Loomis, 1928). Gas
production and utilization rates were calculated in the units that were used
in the measurements, 'I.e. pico- or nanomoles per microliter PCV per minute.
One yl PCV represents about 0.5 nmoles or ygrams of chlorophyll-a. Respira-
tion, light-induced hydrogen production, and gross photosynthesis (oxygen
production in the light plus oxygen uptake in the dark) rates were plotted
against inhibitor concentration and curves were drawn through the points by
inspection. The criteria for choosing the trace elements tested in this
study were twofold: 1) those that were present in the stack emissions of
coal fired power plants at rates above 15 mg per second (Montana State
Department of Natural Resources and Conservation, 1974) and, 2) those that
have demonstrated toxic effects in other biological systems. Several ele-
ments fitting the first criteria were not tested. The elements were provided
as the soluble anions or cations of either sodium or chloride salts, or as
the acetate salt in the case of lead. Chromium and arsenic were supplied as
NaCr207 and Na2HAsOi+, respectively.
Gas chromatography
Experiments involving the acetylene reduction assay for nitrogenase
activity were carried out by simultaneously running all samples in one
experiment. Cells were concentrated by centrifugation and resuspended in
culture media to a density of 7.5 to 15 yl per ml. Aliquots of 5 ml were
pipetted to 25 ml flasks and capped with serum stoppers. The cells were^
rendered oxygen- and nitrogen-free as in the polarographic assays, but with
the addition of 10% (4.02 mM in solution) acetylene generated from cold
water and reagent grade calcium carbide. Reaction mixtures were incubated
for 5 to 50 minutes on a modified Gilson respirometer shaking bath held at
27 C and supplied with tungsten light providing an intensity of 7.5 x 10
ergs/cm2/second. After the desired reaction time, 0.5 ml samples of the gas
mixtures over the cells were taken with 1.0 ml plastic tuberculin syringes.
Assay of the ethylene present was accomplished on a Hewlett Packard Gas
Chromatograph (Model 5830 A) with flame ionization detection. An Alltech
869
-------
aluminum column (6 ft. x 1/8 in. O.D.) packed with 80-100 mesh Porapak R was
used with an oven temperature of 45 C and a flow rate of approximately 30 ml
per minute. Areas under the peaks were standardized using 1% ethylene gas
in air.
Growth studies
Andbaena cylindrica
The long term effect of trace metals on algal growth was determined by
inoculating culture media containing a series of concentrations of the
element under study with Andbaena oylindrioa. Cells were grown for 48 to 56
hours in 18 x 150 mm Pyrex culture tubes, illuminated with fluorescent
lights at an intensity of 2 x 104 ergs/cm2/sec, and were bubbled with 2%
carbon dioxide in air. After the growth period the total chlorophyll-a
content of each tube was extracted with 10 ml of 80% acetone for at least 24
hours in the dark at room temperature. The chlorophyll-a was quantified by
measuring the absorbance at 665 nm and employing the extinction coefficient
given by Vernon (1960). The increase in chlorophyll content was determined
by subtracting the initial value. The data are plotted as percent increase
in chlorophyll of the untreated growth control. Cell clumping in single
tubes occasionally resulted in high chlorophyll values.
The compounds used to study the effect of trace elements on the selected
vital functions of Andbaena oyllndrioa were NaF, NaCl, NaBr, LiCl, KC1, SrCl2,
BaCl2, Na2Cr207, MnCl2, NiCl2, CuCl2, ZnCl2, CdCl2, HgCl2, Pb(acetate)2, and
Na2HAsOi+.
Salvin-ia and Azolla
Samples of healthy Salvinia or Azolla fronds grown in departmental
greenhouses were surface sterilized with sodium hypochlorite, and washed
thoroughly with water. Uniform sized plants were inoculated into 50 ml
volumes of culture media containing trace elements in 125 ml Erlenmeyer
flasks. The water ferns Were grown under fluorescent lights in growth
chambers with a 16 and 8 hour day-night light regime. Visual and gravimetric
observations were made of the growth over a period of several weeks in which
time trace element toxicity could be determined.
The elements tested were Hg, Cr, Pb, Zn, Cd and Sr, between the concen-
trations of 0.001 and 1 mM.
RESULTS AND DISCUSSION
The Action of Oxygen and Select Metabolic Inhibitors on Photosynthesis,
Respiration and Nitrogen Fixation
Oxygen and Nitrogenase Activity
A sample experimental trace (Figure 23.1), taken from the control data
of the ZnCl2 assays (Figure 23.19) illustrates a commonly observed phenomenon.
After the light stimulated oxygen and hydrogen evolution rates had been
870
-------
§0
••J
U
o
I
CD
Z>
co
CO
LU UJ
O K
0>JM H2
OjuM 02
Figure 23.1 Sample tracing for the determination of respiration,
photosynthesis, and hydrogen evolution in physiologi-
cal assays of Andbaena cy li-Yidfica. Slope values are
given as nmoles/yl PCV/min for oxygen, and pmoles/yl
PCV/min for hydrogen.
871
-------
established, the oxygen levels in the cuvette were of considerable magnitude
(greater than 50 yM). Due to the oxygen accumulation during thxs first
portion of the experimental run, a continued evolution of hydrogen was
observed in the dark. The initial oxygen concentration of these experiments
was purposefully brought to zero to minimize any possible deleterious effect
on the sensitive nitrogenase (Drozd and Postgate, 1970; Haaker and Veeger,
1977). However, it is apparent that oxygen supports the nitrogenase activity
in the dark. In order to determine if the assays performed were optimal for
nitrogenase activity, a series of experiments were conducted, the results of
which are summarized in Figures 23.2 and 23.3. It had previously been
determined (Jones and Bishop, 1976) that the light-driven nitrogenase activity
was well saturated at an intensity of 105 ergs/cm2/second. However, oxygen
addition in the dark may account for as much as 40% of the hydrogen production
activity seen in saturating light (Tetley and Bishop, 1977). Figure 23.2
indicates that the hydrogenase activity due to light and that due to oxygen
are partially additive at light intensities below about 7.5 x 104 ergs/cm /sec,
and at saturating light intensities moderate oxygen concentrations have
little or no effect. However, at high oxygen concentrations, in fact those
c
E
x.
o 800
a.
> 700
600
to
J2
o
~ 500
2 400
i-
o
Q 300
o
tr
°- 200
LU
o 100
o
o:
2 o
LIGHT INTENSITY
(erg / cm2- sec) x I0~4
o 0
2.52
Q 11.40
200 400
OXYGEN -
600
Figure 23.2 The effect of oxygen concentration and light intensity
on hydrogen production in Anabaena cylindrica.
872
-------
c
i
\
o 600
CL
^ 500
Cft
Qj
"o
a 400
2 300
H
o
S 200
cc
UJ
bJ
LU
O
100
0
LIGHT INTENSITY
(ergs / cm2 • sec) x IO"4
200
400
600
OXYGEN -
Figure 23,3 The effect of oxygen concentration and light intensity
on acetylene reduction in Anabaena oylindrica.
at which the algae were grown, strong inhibition of the nitrogenase activity
was seen; but clearly this was not an oxygen inactivation of the enzyme. At
higher oxygen concentrations (i.e. 250 yM and above) an irreversible inhibi-
tion of the nitrogenase is found. It was observed in a similar series of
experiments (Figure 23.3) that the same interaction between light and
oxygen are observed when analyzing the nitrogenase activity with the standard
acetylene reduction assay. From these experiments it is concluded that
maximal hydrogen production is a good indication of acetylene reduction or
nitrogen fixation, and may be obtained in saturating light at oxygen concen-
trations below about 100 yM. Normally the hydrogen evolution showed somewhat
lower values than the acetylene reduction assays though there was considerable
variability from experiment to experiment in both assays on the basis of
packed cell volume. An interesting point was illustrated by the light and
oxygen concentration study that bears directly upon measurement of actual
nitrogen fixation rates during culture growth or natural growth in the
field, as opposed to maximal nitrogenase activity. If the cells are not
873
-------
assayed under exactly the same conditions that they grow naturally, with
respect to light intensity and gas concentrations, then grossly erroneous
estimations of field or culture nitrogen fixation rates may result.
Effects of Select Metabolic Inhibitors
The compounds employed as model metabolic inhibitors were potassium
cyanide, carbonyl cyanide m-chlorophenyl-hydrazone (w-Cl-CCP) , 3-(3,4-
dichlorophenyl)-l,l-dimethylurea (DCMU), and 2,5-dibromo-3-methyl-6-iso-
propyl-p-benzoquinone (DBMIB) . Cyanide is effective in inhibiting oxygen
uptake at the site of cytochrome oxidase in respiring organisms and inhibits
electron transport at the site of plastocyanin in photosynthetic systems
(Webster and Frenkel, 1953; Ouitrakul and Izawa, 1973). At millimolar
levels, cyanide acts as a substrate for nitrogenase (Rivera-Ortiz and Burris,
1975) and therefore it has several potential sites of action in Andbaena.
The action of cyanide on photosynthesis, respiration, and hydrogen production
is illustrated in Figure 23.4. It is clear that 30 yM cyanide maximally
inhibits respiration about 50% at about 100 yM Q£ levels, and completely
eliminates oxygen-dependent hydrogen evolution in the dark. Light- stimulated
hydrogen production is not inhibited to the same extent as the dark process.
600-
O
a.
TO
o
o 400-
O
E
O
O 200
z
UJ
o
o
cc
0.001 O.I
KCN (mM)
JO.O
Figure 23.4.
The effect of cyanide on respiration (•), photosynthesis
(O)> oxygen-stimulated hydrogen production in the dark
(•)> light-driven hydrogen production (Q), and light-
driven hydrogen production in the presence of DCMU
in Anabaena
874
-------
In fact, in the presence of DCMU, which prevents the evolution of oxygen
(Figure 23.6), the inhibition of light-driven hydrogen evolution is seen at
much higher cyanide concentrations. These experiments indicate that it is
the oxygen produced during photosynthesis that is detrimental to light-
driven hydrogen evolution at those cyanide concentrations sufficient to
inhibit respiration. It appears that cyanide prevents the utilization of
oxygen near the site of the nitrogenase, which in turn results in an oxygen-
inactivation of this oxygen sensitive enzyme complex. Therefore, by inhibi-
ting oxygen uptake, the nitrogenase may be affected indirectly by increased
oxygen concentrations and the results could be easily misinterpreted as a
direct effect. This is especially true in nitrogenase assays involving
longer periods of time, such as the acetylene reduction assay. The inhibi-
tion of photosynthetic oxygen production at higher concentrations of cyanide
is clearly a second effect supposedly due to electron transport inhibition
at the level of plastocyanin. In DCMU-inhibited cells, cyanide does not
exert a noticeable inhibition on light-stimulated hydrogen production until
300 yM levels are reached (Figure 23.4), whereas inhibition of photosynthesis,
as judged by gross oxygen production, is affected at 30 yM KCN. If the
inhibition at the plastocyanin level is the cause of the decrease in oxygen
production it would not be expected that hydrogen production would continue
at nearly control rates. This is particularly noticeable at 300 yM cyanide
where photosynthesis is inhibited by over 90%. For these reasons, it is
possible that cyanide inhibits photosynthesis in photosystem II. Alterna-
tively, photosynthesis in heterocysts may be protected from cyanide by
competing for cyanide-binding sites, for cyanide clearly rapidly enters the
heterocysts as evidenced by its effect on oxygen-stimulated hydrogen produc-
tion in the dark.
Carbonyl cyanide m-chlorophenyl hydrazone or ???-Cl-CCP is a potent
poison which uncouples oxidative and photosynthetic electron transport from
phosphorylation (Heytler and Pritchard, 1962; Biggins, 1969). Since the
nitrogenase is dependent upon ATP produced by these processes, uncoupling
should result in a loss of nitrogenase activity. From Figure 23.5 it is
clear that hydrogen production in both the dark and the light is eliminated
by 3 to 10 yM w-Cl-CCP. However, photosynthesis is retarded about 60% and
respiration slightly increased at the same level of inhibitor. Normally
uncouplers cause increases of 50% or more in respiration. In the case of
photosynthetic electron transport (oxygen production) this compound also
shows strong inhibition. Thus the inhibitory effect of light-driven hydrogen
production may be attributed to uncoupling, since electron transport is
reported to be inhibited in photosystem II by m-Cl-CCP (Kimimura, et al. 3
1971). DCMU inhibition of photosynthetic electron transport has been well
documented (Bishop, 1958). Figure 23.6 shows no effect of DCMU on either
respiration or light-stimulated hydrogen production. However, complete
inhibition of oxygen production is observed at about 1 yM levels. Since
gross photosynthesis is calculated as the difference in oxygen production
rate in the light and uptake in the dark in the presence of oxygen, there is
apparent photosynthesis at DCMU levels above 0.5 yM. This is interpreted as
an inhibition of respiration. Since no oxygen is produced in the presence
of DCMU, then complete inhibition of gross photosynthesis is seen when the
photosynthetic activity is assayed in the absence of oxygen. Light inhibi-
tion of respiration has been recognized in blue-green algae for some tune
875
-------
1.0
/7?-C!-CCP
100
Figure 23.5. The effect of ???-Cl-CCP on respiration <•)» photosynthesis
(O)» oxygen-stimulated hydrogen production in the dark
(•)> and light-driven hydrogen production (Q) in
Andba&wa cylincbrica.
(Brown and Webster, 1953). The light inhibition of respiration decreases
with increases in oxygen concentration and appears to involve the cyanide-
sensitive component of oxygen uptake. Therefore, between experimental runs
it is important to measure both respiration and photosynthetic activities at
the same oxygen concentration. Though DCMU is effective in blocking non-
cyclic electron transport, photosystem I driven cyclic photophosphorylation
apparently continues, and sufficient ATP synthesis is maintained, resulting
in no loss of ATP-dependent hydrogen evolution.
The action of DBMIB in photosynthesis has been recognized more recently
(Trebst et at. > 1970). This compound acts at the site of plastiquinone, and
is a strong inhibitor of oxygen production as well as photosynthetic phos-
phorylation. The action of DBMIB on Andbaena is seen in Figure 23.7.
Oxygen production is inhibited about 60% at 10 yM DBMIB, and maximally
inhibited at about 30 yM. A parallel inhibition of light-induced hydrogen
production is also seen and is complete. At 10 yM levels of the inhibitor,
oxygen stimulation of hydrogen production in the dark is not inhibited
876
-------
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E
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Figure 23.6. The effect of DCMU on respiration (•), photosynthesis
(O)» and light-driven hydrogen production (Q) in
Anabaena cyl-indrica.
though higher concentrations of DBMIB are effective. Oxygen uptake is
unaffected by DBMIB up to 100 yM levels. Apparently DBMIB acts as a selective
inhibitor of the light-stimulated nitrogenase activity before influencing
the aerobic dark production of hydrogen at higher concentrations. This
information, taken together with the selective cyanide inhibition data of
aerobic dark hydrogen production indicates that the light and the dark ATP
generating systems necessary for driving the nitrogenase operate independently
of one another.
877
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(Q)» oxygen-stimulated hydrogen production in the dark
(H)> an
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Figure 23.8.
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Figure 23.9.
The effect of Na and Cl as NaCI on
respiration (0), photosynthesis
(O) > light-driven hydrogen produc-
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Figure 23.10.
The effect of Br as NaBr on
respiration (•), photosynthesis
(O)» light-driven hydrogen pro-
duction (Q), and growth (A) in
Anabaena oylind^ioa.
Figure 23.11.
The effect of Li as LiCl on respi-
ration (•)> photosynthesis (O) ,
light-driven hydrogen production
(Q), and growth (A) in Anabaena
oylindrica.
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Figure 23.12.
The effect of K as KC1 on respira-
tion (•), photosynthesis CQ)»
light-driven hydrogen production
(Q), and growth (A) in Anabaena
Figure 23,13. The effect of Sr as SrCl2 on
respiration (•), photosyn-
thesis (O)9 light-driven
hydrogen production OD),
and growth (A) in Andbaena
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The effect of Ba as BaCl2 on respi-
ration (0), photosynthesis (O)>
light-driven hydrogen production
(D)» and growth (A) in Anabaena
cylindrica.
Figure 23.15.
The effect of Cr as Na2Cr207
on respiration (0), photosyn-
thesis (Q)> light-driven hydro-
gen production (Q), and growth
(A) in Anabaena cyl-lndr-ica.
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Figure 23.16.
The effect of Mn as MnCl2 on
respiration (• ), photosynthesis
(Q)» light-driven hydrogen pro-
duction (Q), and growth (A)
in Andbaena cylindrioa.
Figure 23.17.
The effect of Ni as NiCl2 on
respiration (•), photosynthesis
(O)> light-driven hydrogen pro-
duction (Q), and growth (A)
in Anabaena cylindrica.
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Figure 23.18
The effect of Cu as CuCl2 on respi-
ration (•), photosynthesis (O)»
light-driven hydrogen production
(Q ) , and growth (A) in Anobaena
cylindrica.
Figure 23.19.
The effect of Zn as ZnCl2 on
respiration (% ), photosynthesis
(O), light-driven hydrogen pro-
duction (Q), and growth (A)
in Anabaena
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light-driven hydrogen production
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23,21. The effect of Hg as HgCl2 on
respiration (0), photosynthesis
(O)3 light-driven hydrogen pro-
duction (Q), light-driven acety-
lene reduction (^) , and growth
in Andbaena cyl'lndri.ca.
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Figure 23.23.
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was growth less sensitive to a trace element than any of the measured physio-
logical Processes From Figure 23.27 it may be seen that these same elements
cause growth inhibition at generally lower concentrations. Of the elements
tested Cr, Ni, Mn, Cu, Sr, and Hg elicited much greater sensitivity in the
growth assay. Notable is the dramatic difference in sensitivity seen with
Cr which is nearly three hundred times more active in growth studies than in
short-term physiological assays. This difference results in Cr, as dichromate,
being the third most poisonous element tested overall, having a toxicity
similar to copper. Therefore, in decreasing degree of overall toxicity, Hg,
Cu, Cr, Ni, Cd, Zn, and Pb are strongly active at 1 mM levels or below with
Mn, F, and Li showing large growth inhibition below 3 mM levels. Mercury
remains by far the most potent poison tested and inhibited growth by at
least 50% at approximately 1 mM levels. On the other hand, at concentrations
as high as 100 mM, Na, Cl, K, and Br showed little or no effect. Apparently
there is no adverse effect on Andbaena due to high osmolarity of the reaction
mixtures or culture media during physiological assays or growth periods.
Effects of Select Elements on Growth of Salvinia and Azolla
In general, the effects of trace elements on the growth of Salvinia.
and Azolla were the same. Consistent with the growth studies on Anabaena, the
greatest effects were seen in the presence of low concentrations of Hg and Cr,
both of which strongly affected the waterferns at 1 mM levels. Interestingly,
the remaining elements did not show strong inhibition at millimolar levels.
From the growth results with Anabaena, it would be expected that Cd and Pb
would greatly retard growth or kill the plants. The symbiotic relationship
between these waterferns and the blue-green algae they harbor possibly pro-
vides some protection for the algae which are sensitive when cultured indivi-
dually. In fact, as was clearly observed in the case of the zinc studies,
strong inhibition of green algae contaminants was observed at concentrations
above 50 yM, whereas little or no effect was seen on the waterferns.
Inhibition by Select Trace Elements
In general, three types of responses to test trace elements were
observed: non-toxic, toxic, and differentially toxic. In the case of the
majority of the elements relatively little effect was seen at 10 mM levels
and below. Salt concentrations of 0.1 M and more in certain instances are
clearly tolerated by these algae (Figure 23.27). This is consistent with
the knowledge that certain Anabaena species are very tolerant to highly
eutrophic or saline situations (Palmer, 1969). The remainder of the elements
clearly exert toxic effects. In fact, Rabinowitch (1945) has suggested that
compounds that are inhibitory at levels of 10 mM and below were true poisons
since non-specific secondary effects might occur at higher concentrations.
For the purpose of this report, highly toxic elements are considered to be
those acting at 1 mM or lower concentrations. The highly toxic elements
detected in this report were Hg, Cu, Cr, Ni, Cd, Zn, and Pb Two of these,
Hg and Cd, showed clear differential inhibition of photosynthesis ^photo-
synthetic hydrogen production. The remaining elements which show Physiolo-
gical inhibition at 1 mM levels and below are Cu, Zn, and Pb (Figures 23.24
887
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Summary of trace element effects
on photosynthesis of Andbaena
cyls'indpi'CCL. Solid bars repre-
sent concentrations at which 50%
or greater inhibition was observed,
Parentheses indicate the concen-
tration range tested.
Figure 23.25.
Summary of trace element effects
on hydrogen production (nitro-
gen fixation) of Anabaena cylin-
dpi,ca. Solid bars represent
concentrations at which 50% or
greater inhibition was observed.
Parentheses indicate the con-
centration range tested.
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Summary of trace element effects
on respiration of Anabaena cyl'in-
dx"ica. Solid bars represent con-
centrations at which 50% or grea-
ter inhibition was observed.
Parentheses indicate the concen-
tration range tested.
Figure 23.27
Summary of trace element effects
on growth of Anabaena cyl'indT'ica.
Solid bars represent concentra-
tions at which 50% or greater
inhibition was observed. Paren-
theses indicate the concentration
range tested. The X on each
bar indicates the lowest concen-
tration needed to cause 50%
inhibition in any of the three
physiological assays summarized
in Figures 23.24 through 23.26.
-------
to 23.26), and in growth studies Cr and Ni also showed strong toxicity at
these levels (Fig. 23.27). These toxic elements and their effects will be
discussed in the following paragraphs.
Mercury and Cadmium
Both Hg and Cd are potent inhibitors of algal and higher plant systems
(Greenfield, 1942; MacDowal, 1949; Hewitt, 1953; Harriss et al. 3 1970; Kamp-
Nielsen, 1971; Barker,1972; Matsen et al.3 1972; Page et al. * 1972; Bartlett
et al.y 1974; Klass et al. 3 1974; DeFilippis and Pallaghy, 1976; Kayser
1976). In the vegetative cells of blue-green algae complete photosynthesis
occurs, including oxygen production, whereas in heterocysts, the sole site
of nitrogen fixation in Andbaena, only partial photosynthesis occurs and
oxygen evolution is absent (Wolk and Wojciuch, 1971; Donze et al. 3 1972;
Kulasooriya et al. * 1972). It is also observed that photosynthetic oxygen
production is more sensitive to Cd and Hg than photosynthetic hydrogen
production (Figures 23.20 and 23.21). Because of the chemical similarities
of Cd and Hg, it is not surprising that a similar differential action is
seen with both elements. However, Zn, which belongs to the same group of
transition metals (IIB) does not demonstrate the same differential effect
(Figure 23.19).
The specific effects of Cd and Hg on photosynthesis have been investi-
gated (Izawa and Good, 1969; Gould, 1975; Li and Miles, 1975). The most
extensive work has dealt with mercury toxicity. Mercury inhibits photo-
synthetic electron transport at the site of plastocyanin (Kimimura and
Katoh, 1972) but it also causes partial uncoupling of photophosphorylation
(Izawa and Good, 1969), and has been reported to be specific for proposed
site I phosphorylation (Gould, 1975) but not site II phosphorylation asso-
ciated with photosystem II. Electron transport has been found to be less
sensitive to mercury than phosphorylation. Oxygen evolution or photosyn-
thetic electron transport in vegetative cells is strongly affected by
one-tenth the Hg concentration that affects hydrogen evolution from the
heterocysts. If mercury is entering the heterocysts as rapidly as the
vegetative cells, then electron transport and associated phosphorylation
should be inhibited in a manner similar to oxygen production in vegetative
cells, assuming plastocyanin to be the site of electron transport inhibition
in both cell types. Since respiration is strongly inhibited by 30 yM Hg
(Figure 23.21), then the respiratory system of the heterocysts is likely
affected. The data can be best explained by the presence of an insensitive
photophosphorylation system in heterocysts due to nonspecific competitive,
and therefore protective-binding of Hg, or slower transport of mercury to
the site of inhibition across the larger heterocyst cell. In any case, it
is significant that 30 yM Hg completely inhibits oxygen production and
strongly affects respiration, but has little or no effect on hydrogen produc-
tion (Figure 23.21).
Similar differential inhibition is seen with cadmium at relatively
higher concentrations (Figure 23.20). However, it has been reported (Bazzaz
and Govindjee, 1974a; Li and Miles, 1975) that Cd inhibits photosynthesis at
a site remote from those affected by Hg. Inhibition of electron transport
890
-------
associated with photosystem II is consistent with the inhibition results
obtained with both Cd and Hg, whereas the reported sites of Hg inhibition
remain inconsistent with the data without invoking other factors.
The pattern of differential inhibition exhibited by Hg and Cd appears
similar to that caused by cyanide, wherein oxygen evolution is inhibited at
lower concentrations than hydrogen evolution in the absence of oxygen. It
is interesting that both cyanide and Hg are known to inhibit photo synthetic
electron transport at the site of plastocyanin.
It was observed that mercury inhibition of hydrogen production was more
severe in the presence of oxygen. It should be noted that Hg affects oxygen
uptake at concentrations of 3 yM and higher in short-term experiments
(Figure 23.21). As a result of this respiratory inhibition, the levels of
Hg that affect light-stimulated acetylene reduction and light-driven hydrogen
evolution are quite different due to oxygen inhibition of nitrogenase acti-
vity in the long-term (45 minutes) acetylene reduction assays. In fact,
acetylene reduction and respiration exhibited similar inhibition curves
(Figure 23.21) and respiration is also more severely affected by Hg than Cd
with respect to the inhibition of hydrogen evolution (Figure 23.20). Because
of the multiple sites of action of Hg and Cd in biological systems (Passow
et aZ.A 1961; Vallee and Ulmer, 1972), it is not surprising to observe that
growth is inhibited at one-tenth to one-third the concentrations that retard
the most sensitive short-term physiological functions.
Copper
Copper has been used as an algal control chemical since the early
1900's. It inhibits growth at low concentrations, but apparently has a
broad range where it has reversible algistatic properties (Fitzgerald and
Faust, 1963; Steeman-Nielsen et al. 3 1969). Copper inhibits growth, photo-
synthesis, and dark reactions at low concentrations (Greenfield, 1942;
MacDowal, 1949; McBrien and Hassall, 1967; Habermann, 1969; Gross et al. ,
1970; Whitton, 1970; Steeman-Nielsen and Wium-Anderson, 1971; Morris and
Russell, 1973; Bartlett et al. , 1974; Home and Goldman, 1974). In the
present study, Cu showed strong parallel toxicity of photosynthesis, respira-
tion and nitrogen fixation between 0.3 and 1.0 mM levels, whereas growth was
inhibited by nearly 50% at 10 yM Cu (Figure 23.18). An inhibition plateau
for growth is seen between 30 and 300 yM CuCl2, and may represent those
concentrations which exert algistatic rather than algicidal effects (Fitz-
gerald and Faust, 1963; Steeman-Nielsen and Kamp-Nielsen, 1970). The
inhibitory action of Cu in isolated photosynthetic systems has been recog-
nized by MacDowal (1949), wherein 10 yM Cu clearly inhibits light-driven
electron transport by about 50%, and 100 yM levels inhibit the rate between
61 and 93% dependent upon the light intensity. Greenfield's (1942) earlier
conclusion was that Cu also strongly affected dark reactions, and subsequent-
ly it was suggested that inhibition may be dependent upon anaerobiosis
(Hassall, 1962). More recent work on isolated systems has implicated Cu in
the inhibition of chloroplast processes, and showed that inhibition was
reversed by the addition of Mn2+ ions (Habermann, 1969). Later work has
indicated that Cu may interact with photosynthetic pigments, and that these
interactions are prevented by reducing agents, Mn, and anaerobiosis (Gross
891
-------
et, al. > 1970). Interesting in this respect is a recent publication reporting
the existence of a copper-manganese-protein complex associated with photo-
system II (Holdsworth and Arshad, 1977). It appears that no specific site
of inhibition can be assigned to Cu.
Lead
Lead toxicity has been of concern in many biological systems (Hewitt,
1953; Vallee and Ulmer, 1972) and it has been shown to inhibit photosynthesis
in chloroplasts and algae (Whitton, 1970; Miles et al., 1972; Malavchuk and
Gruendling, 1973; Bazzaz and Govindjee, 1974b). In Anabaena (Figure 23.22)
strong Pb toxicity is observed for all parameters measured at concentrations
between 1 and 3 mM. Respiration is an exception though it has been shown
that Pb inhibits mitochondrial function in higher plants (Koeppe and Miller,
1970). Characteristically, Pb inhibition may involve many binding sites in
cells (Vallee and Ulmer, 1972), but inhibition of growth is not seen at
concentrations below those in which physiological processes were attenuated.
It appears that short-term assays of hydrogen evolution are affected slightly
less by 1 mM Pb than is photosynthesis. This is consistent with the reported
site of Pb inhibition (Bazzaz and Govindjee, 1974b), and resembles the
differential inhibition exerted by Cd and Hg.
Chromium, Nickel and Zinc
Chromium, nickel and zinc all exhibited strong toxicity toward Anabaena
(Figures 23.15, 23.17, 23.19 and 23.27). Chromium toxicity has been recognized
in plant systems for some time, and is often an important component in some
barren soils (Robinson et al.3 1935; Hewitt, 1953; Hunter and Vergano, 1953;
DeKock, 1956; Soane and Saunder, 1959). Work has been continued to define
Cr toxicity (Turner and Rust, 1971; Wallace et al., 1976), but relatively
little information appears to be available concerning toxicity in algae
(Leland and Wilkes, 1977). Hexavalent chromium has exhibited greater toxi-
city to plants than trivalent chromium (Hewitt, 1953), and chromium was used
in the dichromate form (Cr2072~) in this study. It can be noted in Figure
23.15 that no toxic effects of dichromate are observed on physiological
processes until 10 mM concentrations are applied. However over 50% inhibi-
tion of growth is observed when Anabaena is supplied with 30 yM dichromate.
Thus it appears to demonstrate toxicity similar to copper. In growth assays
with Azolla and Salvinia, micromolar concentrations of dichromate were also
extremely toxic.
Zinc and nickel are recognized to be toxic to higher plants (Baker,
1972; Hewitt, 1953; Hunter and Vergano, 1953; DeKock, 1956 ) and
algae (Greenfield, 1942; Whitton, 1970; Coleman et al. 3 1971; Bartlett
et al., 1974; Rachlin and Farran, 1974; Greene et al. 3 1975; DeFilippis and
Pallaghy, 1976). In Anabaena, Zn effects were close to maximal at I mM
for all parameters tested including growth which did not show appreciably
greater sensitivity (Figure 23.19). However, Ni toxicity exhibited a much
different pattern. Nickel at I mM had little or no effect on any physiolo-
gical process that was tested, but was completely inhibitory to growth
(Figure 23.17). A slow decrease in the activity of the physiological
892
-------
parameters was seen as Ni concentrations were increased from 1 to 100 mM
levels. As contrasted to the Zn experiments, Ni shows a great differential
in toxicity between growth and short-term physiological processes.
CONCLUSIONS
The effects of selected trace elements emitted from coal-fired power
plants on nitrogen fixation, photosynthesis, respiration and growth were
surveyed in the blue-green algae, Anabaena oyl-indrica. The seventeen ele-
ments tested were F, Na, Cl, Br, Li, K, Sr, Ba, Cr, Mn, Ni, Cu, Zn, Cd, Hg,
Pb, and As. In order of decreasing toxicity, it was found that Hg, Cu, Cr,
Ni, Cd, Zn, and Pb exerted inhibition at levels of 1 mM or below. In
short-term physiological experiments Hg, Cu, Zn, Cd, and Pb exhibited toxi-
city to biological functions at 1 mM or lower levels. The algae showed much
greater sensitivity to Cr, Ni, Mn, Cu, Sr, and Hg in the long-term growth
studies than in the short-term physiological experiments. Inhibition of
Azolla growth was strong at 1 mM Hg and Cr but was insensitive to millimolar
concentrations of Pb, Zn, Cd, and Sr. Chromium is therefore identified as
an extremely toxic element in both systems. In Anabaena, differential
inhibition of nitrogen fixation, photosynthesis, respiration, and growth was
observed with varied concentrations of several elements. The metabolic
inhibitors KCN, DCMU, w-Cl-CCP, and DBMIB were studied, and the interaction
of oxygen and light on nitrogenase activity was determined, with implications
for field and laboratory nitrogen fixation studies. Under certain conditions
hydrogen production serves as a sensitive measure of nitrogen fixation.
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898
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SECTION 24
THE USE OF REMOTE SENSING
IN EVALUATING S02 DAMAGE TO GRASSLANDS
J. p Taylor, W. C. Leininger,
and T. R. Osberg
ABSTRACT
Aerial photography in the vicinity of the EPA's
southeastern Montana grassland research sites has
been collected since 1974. This includes conventional
coverage acquired from several federal agencies and
original large scale imagery flown by the project
investigators. A system using small aircraft and
70mm cameras has been developed and used in periodic
monitoring of the study sites and adjacent locations.
Color, color infrared (CIR) and black-and-white films
are exposed at scales ranging from 1:3700 to 1:30,000
for various purposes. In 1977, four fixed wing flights
and one helicopter photo mission were flown. The resul-
tant imagery was analyzed through visual interpretation,
color standard matching, image enhancement, and densito-
metric analysis. The latter yields numeric data which
can be related to various kinds of ground data by
regression techniques. Highly significant relation-
ships were observed between image densities and S0»
treatment levels on the fumigation plots. Leaf
senecense of western wheatgrass showed similar ten-
dencies. Color infrared taken during the active
growth season gave the best results. ZAPS II shows
poorer relationships than ZAPS I because of its
higher inherent variability in microtopography and
plant community patterns. The influences of grazing
deferment, grasshopper infestations, and annual
climatic fluctuations are discussed in relation to
data interpretation and the necessity for long-term
ecological studies in grasslands. Vegetation maps
have been prepared for the ZAPS sites.
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INTRODUCTION
The background and objectives of our overall project are given in the
Introduction to Section 3. Here, we discuss procedures and results of aerial
and ground photography which we have developed to monitor air pollution
effects in a grassland ecosystem.
MATERIALS AND METHODS
Aerial Photography
Procedures
In our aerial photography we have concentrated on developing procedures
which use standard, readily available equipment, since if a system is to be
applied in a variety of situations it must not necessitate highly specialized,
costly investments.
The aircraft and camera system we use (Cessna 182, Hasselblad EL/M
camera) is described in Section 3. This is essentially an "off-the-shelf"
system, with the exception of a belly port in the aircraft, fitted with a
custom-built camera mount.
We use color positive, color negative, color infrared (CIR), and black-
and-white films for various purposes. Color positive and color infrared
(Kodak 2448 and 2443, respectively) both yield transparencies which can be
viewed on a light table or used to make paper prints. We use the Cibachrome
process for prints because of its sharpness, good color saturation, and re-
sistance to fading. Where we want prints only, we use color negative film,
usually Kodak Vericolor VPS-120. Any of these films can also be used to make
black-and-white prints. However, when we want extremely sharp black-and-
whites for mapping or other purposes requiring high resolution we use H&W VTE
film.
In 1974 and 1975, when we were first working out the details of
procedures, we used both 70mm (120 roll film) and 35mm film formats. The
35mm material was easily processed immediately after each mission so we
could check on exposure and target centering. Also, we could go into the
field the next day and compare ground features with their photographic
images. The exposure was a particularly difficult problem because of the
great sensitivity of color infrared to variations in cloud cover and shadows.
With experience under a variety of light conditions and an accumulation
of ground truth data from the study sites, we have learned to adjust ex-
posure to the situation, and have found that immediate ground checking is
not necessary on familiar targets. For this reason, we now use the 70mm
format most of the time, since it covers almost five times the area per
frame as 35mm at the same photo scale. Also, the 70mm casette allows 70
exposures without changing camera backs, a great advantage in the air.
35mm CIR is readily available only in 20 exposure casettes.
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Our workhorse film type is color infrared. This material has good
sharpness, penetrates light haze very well, and most importantly is
sensitive to subtle differences in plant species' physiological states,
particularly their cell water contents. For any particular growth stage,
infrared reflectance is characteristic of each species, and also is strongly
influenced by stress factors.
We use various photo scales, depending upon the amount of ground detail
(resolution) and the area per frame (coverage) required for different pur-
poses. All of our vertical aerial photography is flown with 60% end lap
so it can be viewed stereoscopically.
Our largest scale is 1:3700, which is obtained by flying at 305 meters
above ground with an 80mm lens. Larger scales are effectively precluded by
the minimum 1/500 second shutter speed of the camera. At 195 km per hour,
an object on the ground moves 10.5 cm (relative to the camera), during ex-
posure. The resultant image motion causes a slight displacement in the
direction of flight. This is negligible at smaller scales, but becomes
noticeable at lower elevations. This phenomenon can be seen in the ZAPS
photos, where the pipes oriented at right angles to the flight direction
appear to be slightly thicker than those parallel to flight.
Even with image displacement, photography at this large scale shows
excellent ground detail, discriminating individuals of many plant species
and even 10 x 15 cm plastic marking flags and the wires supporting them.
When more coverage is desired and ground detail is less critical,
flying altitude is increased or lenses changed to shorter focal lengths.
For instance, to get each ZAPS location in one frame we use a scale of
1:15,000. This still allows good species discrimination and also reveals
more of the surrounding areas for topographic analysis, drift detection, etc.
Our smallest practical scale is about 1:30,000, approximately two inches
per mile. This is obtained by flying about a mile (1609 meters) above the
ground with a 50mm lens. This gives excellent synoptic coverage, shows land
use patterns, generalized vegetation and topography, etc.
With repeated aerial photography throughout the growing season, we
propose to characterize the normal sequence of plant signatures, and then
detect any deviations in this normal pattern which might be brought about
by such stresses as plant disease, drought, insect infestations, or air
pollution.
With color materials of any kind, we have observed variation in color
from one batch to another. This can confound attempts to distinguish species
signatures from normal variation in film. A good share of this problem can
be eliminated by standardizing techniques as much as possible. We buy film
in sufficient quantities so that all the photography from a growing season
has the same emulsion number. Film is kept frozen until it is used, then
cool until processing, which is done as soon as possible after each mission.
901
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Film is processed by a commercial firm which specializes in aerial photo-
graphic work. A density step wedge is printed onto the film end before
processing for density and color calibration.
For optimum discrimination of infrared reflectance, CIR film requires a
minus blue filter, which removes some of the shorter wave length radiation to
which the film is also sensitive. The manufacturer's recommendation is a
yellow (Wratten 12) filter. We prefer a Wratten 15, which is a little more
orange colored, and which cuts off slightly more of the yellow-orange portion
of the spectrum. In our situation, this improves the separation of infrared
reflectances, which are rendered on CIR in tones of red. Also, it produces
ground tones which are less blue than those obtained with the 12 filter,
and we find these more visually pleasing.
Most of our photography is accomplished with lenses of 50 or 80mm, but
we sometimes use 150mm and 250mm lenses for increasing scale without reducing
elevation. For any given scale, the use of a longer lens at higher elevation
decreases the effect of vertical scale displacement because of ground relief.
However, it is harder to accurately sight at higher elevations, so if there
is little margin for tracking error, it is better to fly lower with a
shorter lens.
Analysis of Photography
Visual Observation
The simplest kind of photo interpretation (PI) is identification on the
photography of ground objects. Shape, size, shadows, texture, and proximity
to other objects all are clues to PI, but in color systems, (including CIR)
color is the most conspicuous and useful characteristic in detecting both
temporal and spatial changes.
Our earliest procedure for cataloging colors was to simply assign
subjective names based on the color perception of the observer. This
suffers from the serious disadvantages of being non-quantitative, being
influenced by the colors of adjacent objects and ambient light, and numerous
other problems.
We reduced the subjectivity of color description by employing the
Munsell Color System (Munsell Corporation, 1976). Standard color chips
of known hue, chroma, and value are matched with the photograph under
standard light conditions (Anderson et al., 1977; Anderson, 1978). This
approach has proven to be repeatable among workers, although it is less so
as colors approach grey. Unfortunately, the color designations are not
coded in a way which allows them to be correlated with other quantitative
data.
Color Enhancement
We have analyzed some of our photography with a scanning densitometer.
This device displays the various density levels of the scene on a cathode
ray tube. Each density step can be assigned a color, making subtle
902
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differences in the original photography much more conspicuous. On the ZAPS
plots, this has indicated a trend in decreased density with increased SO
since the first growing season. 2
The output still is subjective because the density ranges are under
the control of the operator, and we have not had access to a calibrated
system. Thus, while revealing interesting features of the scene, as well as
problems in uniformity over the surface of the photography caused by filter
cut-off and vignetting, this color enhancement has not been highly useful in
providing data for further analysis.
Densitometrie Analysis
Our previous limitations in obtaining numerical data from our aerial
photography have been partially resolved with our recent access to a trans-
mission densitometer. We used a Macbeth TD-504 with Status A filtration
belonging to the EPA Environmental Photo Interpretation Center (EPIC) to
examine some of our 1977 coverage from the ZAPS and Colstrip sites. This
instrument measures the density of the red, green, and blue information
content of film, using a 3mm aperture. The optical density of each color
is displayed digitally. These values or ratios between them can be used
to develop correlations with other kinds of digital data from the ground.
We have run correlations with SO- treatment rates, leaf senescence
data for western wheatgrass (Dodd et al, Section 12), and livestock grazing
effects.
Calspan Report
The October, 1975, 1:55,000 CIR was flown over the study sites by NASA.
The portion of this coverage which included ZAPS I and considerable sur-
rounding country was examined by Schott et al. (ND), using a patented
density ratioing procedure developed at Calspan Corporation (Piech et al.,
1974). Their analysis indicated some patterns of SO- drift and accumulation
at several spots some distance from the funigation plots. Our photography
and ground studies have not corroborated these observations, but we are
continuing to monitor the locations, since the Calspan procedure is reported
to be more sensitive to low levels of stress than conventional methods.
It may be that we simply have not detected their patterns yet.
Vegetation Mapping
Using CIR from the active growing season (June), plant communities
and some conspicuous species on both ZAPS plots were delineated on over-
lays. This mapping was done while traversing the area with photo prints
in hand. The mapping units were defined as they were encountered. There
were 104 vegetational units and five others. Plant community names are
based on the predominant species influencing the photo signatures.
903
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RESULTS AND DISCUSSION
Aerial Photography
During 1977, we flew four photo missions over the ZAPS sites and three
in the vicinity of Colstrip. The photography obtained was color infrared
and color, at scales from 1:3700 to 1:30,000. In August we flew a heli-
copter mission around Colstrip at 1:900 to 1:2700. A list of our 1977
aerial photography is given in Appendix 24.1. The smaller scale photography
of the study sites, which is held by EPA/EPIC, is listed in Appendix 24.2.
Analysis of Photography
Visual Observation
Ever since the end of the first growing season in 1974, we have observed
a trend of increased reflectance across the ZAPS plots. This has appeared
in both color and CIR, although it is more pronounced in the latter.
Corroborating ground data have not been forthcoming. Much of the apparent
"pollution" effect appears to have been a bleaching of plant tissues,
particularly western wheatgrass. Production, phenology, or plant species
diversity have not supported the hypothesis that permanent damage was
occur ing with the SO fumigation, at lease for the first few years. This
has been considered By some to be a problem of the remote sensing rather
than reflecting inadequacy in the sensitivity of ground data. In 1977,
supportive data have finally started to appear. This is discussed in detail
in Section 16 and below under "Densitometric Analysis". This suggests that
the aerial imagery can in fact detect early changes in growth patterns of
native grassland species before overt signs of stress are visible on the
ground.
Munsell Color System
The Munsell Color System is used in a MS Thesis (Anderson, 1978). We
have found that color matching is quite feasible, and that differences among
interpreters are relatively slight until color saturations decrease to near-
grey levels. If viewed under constant light conditions, the standard color
chips and colors of objects in aerial photographs can be accurately matched
if the photo colors are isolated from surrounding colors with neutral grey
cards. The main drawback to this kind of color description is the problem
of avoiding color shifts when making paper prints from color transparencies.
(The color chips cannot readily be compared with the original transparencies
because the chips are opaque, so one is faced with the difficulty of
comparing a reflected image with a transmitted one, and color matches are
very hard to make.)
Densitometric Analysis
As previously mentioned, the densitometer we use has a viewing aperture
of 3mm. This makes photo scale very important in density measurements,
since even at our largest scale (1:3700), the area being measured represents
a little over 96 m2. Thus, density readings integrate the reflectance
904
-------
characteristics of various plant species as well as bare ground, rock, litter
and anything else occupying space in the scene. At large scale, subsamples
of image density can be taken within plots the size of ZAPS. At our smaller
scales, each density value represents the sum of reflectances for an entire
plot. The correlations discussed below are all based on subsampled large-
scale photography.
We examined several kinds of ground information as related to the color
densities in both color and color infrared film. May and June exposures were
included. Density ratios were examined, but were consistently unrelated to
ground data, so are not discussed.
The relationship between optical density and ZAPS treatments is shown
in Figure 24.1. There is a general decrease in density with increasing
S02. This relationship is more linear with ZAPS I, especially when based
on CIR imagery. On ZAPS II CIR, the low treatment has a greater than ex-
pected density, particularly green and blue. The reasons are that this plot
has the least bare ground and the greatest vegetational cover of any of the
plots. Further, forbs contribute a higher percentage of the canopy than on
any other treatment. Since CIR is recording active plant tissue, the
observed pattern makes sense.
With the color film, the ZAPS I medium plot also has a displaced density
curve in May. This may be due to the high amount of bare soil on the plot,
which is recorded dark when the soil is moist in early season.
In Figure 24.2. we have regressed density on SO levels using color
infrared film. We used the theoretical values of 0, 2, 5, and lOpphm
for the control, low, medium, and high SO levels, respectively. The actual
fumigation rates deviated slightly from the theoretical levels. Observed
values are discussed in Sections 9 and 10. This shows the close correlation
on ZAPS I between SO rate and color density. In CIR, the red density (which
includes the infrared record) is consistently the most closely related to
stress levels. In June, the month of maximum plant growth, the better curve
fit is observed. The relatively poor relationship on ZAPS II is attributed
to the uneven micro topography. This influences not only plant growth and
vigor, but also species composition and canopy cover. This irregular sub-
strate also is evidenced in diversity data (Section 16).
Color film density is related to SO rates in Figure 24.3. The trends
follow those seen in CIR, except that the relative densities of the colors
are lower. Also, in order of increasing density, the colors rank green,
blue, red compared with red, green, blue in CIR. Green, the dominant color
of actively growing vegetation, is the least variable indicator of pollution
stress.
Leaf senescence of western wheatgrass (Dodd, et al., Section 12), is
related to the optical density of CIR in Figure 24.4. In June, the ZAPS I
relationship is very good (r2 = 0.94 - 0.97). The ZAPS II fit is dis-
appointing, probably because of inter-site variability and possxbly also
due to the strongly fumigated "hot spots". The earlier (May) reflectance
905
-------
2 5
2«
2 3
22
21
20
19
O
14 -
1.3-
I 2-
l.l-
10-
.9-
8-
1
« RED
A GREEN
• BLUE
[• *±S-
I,.
I I I I "< I I I I
CONTROL LOW MEDIUM HIGH CONTROL LOW MEDIUM HIGH
I On
.9-
.8-
Ld
D
.6-
x- x RED
a a GREEN
• • BLUE
ZAPS I
ZAPS n
CONTROL LOW MEDIUM HIGH CONTROL LOW MEDIUM HIGH
ZAPS I ZAPS H
I 2
10
-------
2.4-
2.3-
2.2-
2.1-
2.0-
1,9-
1.8-
> 1-7-
H
CO 1.6-
z
LJ
Q 1.5-
1.4-
1.3-
1.2-
l.l-
1.0-
.9-
.8-
1
RED
GREEN
BLUE
CO
z
LU
2.4
2.3
2.2
2.1
2.0
1.9
1.8
1.7
1.5-
1.4-
1.3-
1.2-
l.l-
1.0-
.9-
.8-
• GREEN D
BLUE b
M
S02
M
S02
1.2
I.I
1.0
.9
.8
CO .6
LJ
Q .5-
.4-
.3-
.2-
Figure 24.2.
Optical density of CIR
photos regressed on levels
of S02. A=ZAPS I, June;
B=ZAPS II, June; C=ZAPS I,
May. **P<,01
S02
907
-------
sample may include previous year's plant material. The higher leaf
senescence observed on the control plot in May is anomalous. It certainly
contributes to a lower coefficient of variability with density data.
1.2-
l.l -
1.0-
.9
.8-
.7-
(f) .6-
Z
UJ .
0 .5-
RED
GREEN
BLUE
M
S02
1.0-
.9-
.8-
>- -7~
CO *6 -
z
LJ
0 .5-
.4
.3-
.2-
.1-
RED
M
S02
Figure 24.3.
Correlation of density of May color photography of ZAPS I
(left) and ZAPS II (right) to levels of S09 stress.
** P < .01
Density shows a similar relationship to May leaf senescence in color
film (Figure 24.5). As before, ZAPS I shows the better correlation. On
ZAPS II the leaf data are highly variable. The combination of color film
and ZAPS II early observations yields the poorest curve fits noted.
We feel that with color infrared film and peak-of-green, large-scale
photography, we are detecting real differences in treatments. We have
ground data to explain the remote sensing indications, and now we have
techniques to relate ground and aerial information. We will extend this
line of research in the coming season and will retrospectively examine
data from previous years. The remote sensing aspect of this project
started small, but it was large enough to record annual data. It appears
now that it will play a key role in the siting and monitoring protocol.
908
-------
2.4-
2.3-
2.2-
2.1-
2.0-
1.9-
1.8-
1.7-
>. 1.6-
55 . _
Z '-5-
UJ
°,.4-
1.3-
1.2-
l.l-
1.0-
.9-
.8-
o o RED
o o GREEN
0 o BLUE
LU
2.4
2.3
2.2
2.1
2.0
1.9-
1.8-
1.7-
. !.6-
! 1.5-
1.4-
1.3-
1.2-
l.l-
1.0-
.9-
.8-
60 70 80 90 100 110 120 130 140
SENESCED AREA (mm2)
110 120 130 140 150 160 170 180 190 200 210 220
SENESCED AREA (mm2)
RED
o -o GREEN
o o BLUE
1.0-
•9H
.8-
CO
I.7
.5-\
Figure 24.4.
Density of CIR photo-
graphy regressed on
senesced leaf area of
western wheatgrass. A=
ZAPS I, June; B=ZAPS II,
June; OZAPS I, May.
* P < .05
1C=Control; L=Low; M=
Medium, H=High S02 treat-
ment
•4H
20 25 30 35 , 40 45
SENESCED AREA (mm2)
909
-------
0-
.9-
.8-
CO
6-
.5-
.4-
o o RED
o o GREEN
o o BLUE
20 25 30 35 40
SENESCED AREA (mm2)
45
1.0-
.9-
GO
2
UJ
.7-\
.6-
.5-
4-
—o RED
--° GREEN
-° BLUE
30
—i—
40
—I—
50
—i—
60
SENESCED AREA (mm2)
N.H
—i—
70
Figure 24.5. Density of May color photography over ZAPS I (left) and
ZAPS II (right) related to senesced leaf area of western
wheatgrass.
C=Control; L=Low; M=Medium; H=High S00 treatment
Vegetation Mapping
Vegetation maps of the ZAPS plots are Figures 24.6. through 24.13.
The index to map units is given in Table 24.1.
General Discussion
All the field elements of the CFPP Project are affected by site factors
which have not been quantified. Perhaps the most serious of these is the
notable increase in plant vigor which has occurred due to grazing deferment
of the study sites. This introduces a potentially serious confounding
factor with any low-level pollution effects.
We studied one of the sites (Kluver West) to see how much photo
density differed between the inside and outside the exclosure (Figure 24,14.)
In all three colors there is a highly significantly greater density
inside. Ground observations show a much more vigorous vegetational cover
inside. If grazing deferment is coupled with low chronic pollution levels,
it is very likely that any pollution effects would be masked by the deferment,
910
-------
TABLE 24.1. INDEX TO MAP UNITS
SYMBOL
COMMUNITY
AA
AB
AC
AD
AE
AF
AG
AH
AI
AJ
AK
AL
AM
AN
AO
AP
AQ
AR
AS
AT
AU
AV
AW
AX
AY
AZ
Aa
Ab
Ac
Ad
Ae
Af
Ag
Ah
Ai
Aj
Ak
Al
Am
An
Ao
Sedges and Rushes
Grasses
Car ex pennsylvanioa/Agropyron smithii
C. pennsylvanioa/A. smithii/Stipa viridula
C. pennsylvanioa/A. smithii/Tragopog on dubius
C. pennsylvanioa/Artemisia ludovioiana
C. pennsylvanioa/Festuoa idahoensis
Junous interior
Carex species
Agropyron oristatum
A. smithii
A. smithii/Koeleria oristata/Poa sandbergii
A. smithii/K. oristata
A. smithii/S. viridula/P. sandbergii/K. oristata
Agvopyvon spioatum/A. smifhii
Aristida longiseta
Bouteloua gvaoil-is
B. graoilis/K. oristata
Bromus japonicus
B. japonieus/A. smithii/Poa
B. japonieus/Buehloe dactyloides
B. japonicus/Cirsium undulatwn
B. japonieus/Stipa oomata
B. japonicus/Taraxacum offioinale/A. smithii
Calamovilfa longifolia
C. longifolia/mixed forbs
C. longifolia/Schizachyriwn seopariwn/A. smithii
F. idahoensis
Eordewn jubatwn
Mixed grasses
Poa pratensis . , ..
P. pratensis/Aehillea millefoliwn/A. s^mth^^
P. pratensis/A. smithii
P. pratensis/A. smithii/K. oristata
P. pratensis/A. spioatwn
P. pratensis/C. pennsylvanioa
P. pratensis/C. pennsylvanioa/A. smithii
P. pratensis/S. viridula
pratensis/S. viridula/A. m^^^efo^^wn/A.
pratensis/S. viridula A. smithii
pratensis/Vioia amerioana
oomata/A. smithii/T. dubius
-oiridula
P.
P.
P.
S.
S.
911
-------
TABLE 24.1. (continued)
SYMBOL
COMMUNITY
Ap
Aq
Ar
As
BA
BB
BC
BD
Be
BE
BF
BG
BH
BI
BJ
BK
BL
BM
BN
BO
BP
BQ
BR
BS
BT
BU
BV
BW
BX
BY
BZ
Ba
Bb
Be
Bd
Bf
Grasses (continued)
Forbs
Bh
S. viridula/A. smifhii
S. viridula/A. smithii/Muhleribergia euspidata
S. viridula/Artemisia frigida/B. japonieus
S. viridula/V. amerieana
A. millefolium
A. mille folium/A. smithii
A. millefolium/T. dubius
Antennaria species
Artemisia ludovieiana
A. ludovieiana/A. smithii/K. eristata
Bahia oppositifolia
Cirsium undulatum
Glyeyrrhiza lepidota
Grindelia squavrosa
G. squarrosa/Psoralea argophylla/P'. pratensis/
A. ludovieiana
Heterotheca villosa
Hyoseyamus niger
Lupinus sevieeus
Melilotus offieinalis
Medieago sativa
M. sativa/A, eristatum
Monarda fistulosa
Orfhoearpus luteus/A. smithii/V. amerieana
0. luteus/C. pennsylvaniea/A. longiseta/F.
idahoensis
0. luteus/P. pvatensis
Oxytropis species
P. argophylla/A. smithii/C. pennsylvaniea
P. argophylla/A. smithii/C. pennsylvaniea/
M. euspidata
P. argophylla/A. smithii/S. eomata
P. argophylla/C. pennsylvaniea
P. argophylla/Lupinus serieeus
P. argophylla/P. pratensis
P. argophylla/S. viridula
Solidago missouriensis
Solidago species
T. offieinale/A. smithii/V. amerieana
T, offieinale/P. pratensis
T. offieinale/Sphaeraleea eoeeinea/A. smithii
912
-------
TABLE 24.1. (continued
SYMBOL COMMUNITY
Forbs (continued)
Bi T. dubius/A. smithii
Bj T. dubius/A. smithii/A. frigida
Shrubs and Half -Shrubs
CA Artemisia cana
CB A. cam/mixed grasses
CC Artemisia dracunoulus
CD A. frigidoL
CE A. fvigida/A. smithii
CF A. frigida/S. oomata/A. smithii
CG A. ludovioiana/C. permsylvanioa/Symphoricarpos/
S. viridula
CH A. ludovioiana/ Artemisia tridentata/A. smithii/
S. viridula
Ci A. tridentata
A. tpidentata/m±xed grasses
A. tridentata A. eana/mixed grasses
Atriplex nuttallii
Ceratoides lanata
C. Zanata/mixed grasses
Juniperus horizontalis
Rhus trilobata
#. trilobata/Iuooa glauca/A. tridentata
j?. trilobata/Lupinus serieeus/Schizacyriwn
scopariim
.Rc>sa woodsii
Symphorioarpos oooidentalis
cu Xanthooephalim sarothrae
cv j. sawt/zpae/A. smithii/P. sardbergii/A.
millefolium
Trees
species
Non-Vegetation Units
Anthills, Bare Ground, or Disturbed Sites
Burn
Grasshopper Cages
Pho topic ts
S0 Collection Plates
?
913
-------
ZAPS I CONfR0|:
Figure 24.6.
Vegetation map, ZAPS I control. Scale = 1:800
(For key to map units see Table 24.1. p. 911-913)
914
-------
Figure 24.7.
Vegetation map, ZAPS I low. Scale = 1:800.
(For key to map units see Table 24.1. p. 911-913)
915
-------
Figure 24.8.
Vegetation map, ZAPS I medium. Scale = 1:800.
(For key to map units see Table 24.1. p. 911-913)
916
-------
Figure 24.9.
Vegetation map, ZAPS I high. Scale = 1:800.
(For key to map units see Table 24.1. p. 911-913)
917
-------
f
AR
3 CONTROL
Figure 24.10.
Vegetation map, ZAPS II control. Scale = 1:800.
(For a key to map units see Table 24.1. p. 911-913)
918
-------
Figure 24.11.
Vegetation map, ZAPS II low. Scale = 1:800.
(For a key to map units see Table 24.1. p. 911-913)
919
-------
ZAPS H MEDIUM
Figure 24.12.
Vegetation map, ZAPS II medium. Scale = 1:800.
(For a key to map units see Table 24.1. p. 911-913)
920
-------
ZAPS II HIGH
Figure 24.13.
Vegetation map, ZAPS II high. Scale = 1:800.
(For a key to map units see Table 24.1. p. 911-913)
921
-------
1.2-
i.o-
.9-
en
LJ _
o .8-
.7-
.6-
1
x x OUTSIDE
• • INSIDE
Figure 24.14.
Optical density com-
parison between inside
and outside the Kluver
West exclosure.
RED
GREEN
BLUE
In the absence of comparable grazed plots, the exclosure data are
highly questionable. This problem is substantially diminished with the
McRae Knoll relict sites along Rosebud Creek. They can be considered base-
line examples of several vegetational types in the general area of Colstrip,
so partially serve as control sites for the exclosure.
Another factor which can affect data is grasshopper infestations.
These occur periodically, and can be severe enough to invalidate sampling
some years. In 1977 the Kluver West site was very severely infested.
Along with annual variations in climate, this emphasizes the importance
of long term studies when dealing with grassland ecosystems.
922
-------
CONCLUSIONS
An aerial photography system has been developed and is being used to
monitor plant communities in southeastern Montana. Large scale growing
season coverage with color infrared film records plant species and communities
at high resolution. This photography has been used to map the study sites at
McRae Knolls and ZAPS.
Visual observation, the Munsell Color System, image enhancement and
densitometric analysis give successively more useful information from the
imagery. Highly significant relationships have been observed between photo-
graphic density and theoretical S02 levels. In addition, the ZAPS I June
photography shows close agreement between photo density and leaf senescence
in western wheatgrass.
REFERENCES
Anderson, J.S. 1978. Large Scale Aerial Photography over Native Range
Transects. M.S. Thesis. Montana State University, Bozeman, 96 p.
Anderson, J.S., J.E. Taylor, and W.C. Leininger. 1977. Large Scale Aerial
Photography of a Native Range Transect. Abstr. Ann. Mtg. Soc. Range
Manage., Portland, Oregon, p. 7.
Munsell Corporation, 1976. Munsell Book of Color. Munsell Color, Macbeth
Div- of Kolmorgen, Inc., Baltimore, Md.
Piech, K.R. et al. 1974. Method for Extracting Photometric Information from
Aerial Photographic Imagery. U.S. Patent #3,849,006.
Schott, J.R., D.W. Gaucher, and J.E. Walker. ND. Aerial Photographic
Technique for Measuring Vegetation Stress from Sulfur Dioxide.
Calspan Corp. Rep. YB-5967-M-1.
923
-------
APPENDIX 24 . 1.
LARGE SCALE AERIAL PHOTOGRAPHY FLOWN IN 1977 OVER EPA STUDY SITES
DATE
22 May
22 June
27 July
9 August
31 August
SITE
ZAPS I & II
McRae Knolls
Kluver West
Kluver North
ZAPS I & II
McRae Knolls
Hay Coulee
Kluver West
Kluver North
Kluver East
-
ZAPS I & II
McRae Knolls
Hay Coulee
Kluver West
Kluver North
Kluver East
ZAPS I & II
McRae Knolls
SCALE
1:15,000
1:15,000
1:3700
1:3700
1:3700
1:3700
1:10,000
1:10,000
1:3700
1:3700
1:3700
1:3700
1:3700
1:3700
1:3700
1:3700
1:3700
1:3700
1:3700
1:3700
1:20,000
1:20,000
1:10,000
1:10,000
1:2700
1:1500
1:1500
1:900
1:2700
1:1500
1:2700
1:1500
1:1500
1:900
1:12,000
1:3700
1:3700
1:3700
1:3700
EMULSION TYPE
2443 (70mm CIR)
2448 (70mm color)
2443
2443
2443
2443
2443
120-VPS
120-VPS
2443
2443
2448
2448
2443
2443
2448
2448
2443
2443
2448
2443
2448
2448
2443
120-VPS
120-VPS
120-VPS
120-VPS
120-VPS
120-VPS
120-VPS
120-VPS
120-VPS
120-VPS
120-VPS
120-VPS
2443
2443
120-VPS
FILTER
Wratten 15
Haze
Wratten 15
Wratten 15
Wratten 15
Wratten 15
Wratten 15
Haze
Wratten 15
Wratten 15
Wratten 15
Wratten 15
Wratten 15
Wratten 15
Wratten 15
Haze
Haze
Wratten 15
Wratten 15
Wratten 15
924
-------
APPENDIX 24.2.
SMALL SCALE PHOTOGRAPHY OF EPA STUDY SITES IN SOUTHEASTERN MONTANA
DATE
COVERAGE
SCALE
EMULSION TYPE
ACQUIRING AGENCY
28 August 1973
ZAPS I & II Sites 1:36,000 Color Infrared U.S. Forest Service,
Custer National Forest, (CIR) U.S. Department of Agriculture
Ashland/Ft.Howes Districts
28 June 1974
Ui
14 May 1975
23 June 1975
Colstrip Mines and
Surrounding Region
(ZAP Site Excluded)
Colstrip Mine Area
North and Eastward to
Rosebud Creek
Colstrip Mine Area
North and Eastward
to Rosebud Creek
1:80,000
1:110,000
1:55,000
CIR
CIR
U.S. Bureau of Land Manage-
ment, U.S. Department of
Interior
National Aeronautics and Space
Administration (NASA)
NASA
16 October 1975 Colstrip Mines and
Environs to Rosebud
Creek; ZAPS I & II
1:55,000 SO 397, Color
2443, CIR
NASA
22 July 1976
ZAPS Sites I & II
1:24,000 2443, CIR
2448, Color
U.S. Environmental
Protection Agency/EPIC
-------
SECTION 25
METHODOLOGY DEVELOPMENT FOR SITING POWER PLANTS
J. L. Dodd, W. K. Lauenroth and W. J. Parton
Within the past year we have structured a research and work plan for the
development of a methodology that can be applied to the northern Great Plains
or other similar regions for the purpose of classifying all parts of the
region according to their anticipated reduction in ecological value resulting
from air pollution impact from coal-fired power plants. The work will be
restricted to air pollution impacts on the major terrestrial ecosystem types
of the area (native and crop systems) . Since the ecosystem types are impor-
tant to society in more than one way, an attempt will be made to rate their
sensitivity to air pollution impact according to several criteria. The major
value systems to be considered are wildlife habitat value, agricultural
productivity, and recreational-aesthetic values.
We are suggesting a two-phase system for evaluating regions for candidate
areas for power plant sites. The system will consist of a low resolution
screening system capable or evaluating all possible sites within a region and
a high resolution system that would be utilized to anticipate specific
impacts on a small number of sites under serious consideration. We will
attempt to develop a low resolution system (LRES) that
1. Can be applied by decision makers with a limited amount of technical
assistance by resource specialists.
2. Is transferrable from one region to another without great changes
in the basic framework of the methodology.
3. Requires a data base that is comparatively easy to secure.
4. Has sufficient flexibility to allow decision makers to easily
specify the relative importance of the various value systems.
5. Can be improved in a straightforward manner by updating with new
information on air pollution effects as data becomes available from
scientific research.
The second syscem will be a high resolution system (HRES) designed to
evaluate a single or a very small set of potential sites. The high resolution
ecological evaluation system will consist of a collection of simulation and
926
-------
regression models that are designed to simulate effects of air pollution on
each cover type that occurs in the region. Basic frameworks for these models
will be existing models where possible. The existing models will be modified
to respond to air pollution stress and to show influence of air pollution
stress on the various value systems.
This effort will differ from the low resolution analysis in many ways.
It will require much more specific information about the cover type's, soils,
and abiotic characteristics of each cover type and will require heavy involve-
ment by modeling and resource specialists. Application of the high resolution
ecological evaluation system will probably require one field season of data
collection to secure information for initializing and tuning the models to an
area chosen as a possible power plant site.
Simulation models for a variety of ecosystems and agricultural crops
have been developed and are just starting to be utilized in environmental
impact analysis. The natural ecosystem models developed by the different
biomes (grassland, desert coniferous forest, and deciduous forest) in the
U.S. International Biological Program have been used to assess the impact of
SST development on natural systems (Cooper et at. 1974) while the ELM grass-
land model (Innis 1978) has been used to simulate the impact of weather
modification (Parton and Smith 1974). A discussion of the problem associated
with utilizing these models in environmental analyses is presented by the
Holcomb Research Institute (1976) and Parton and Wright (1977).
The data base for the two systems will differ considerably. In the
first case (low resolution system) the data base will be based on available
interpretations of remote sensing imagery. In the second case (high resolu-
tion system) the data base will require specific biological and ecological
data collected from each of the potential sites after their preliminary
selection.
The low and high resolution ecological evaluation systems will ultimately
interface with the overall power plant siting process in one of several
possible ways. Since a standard structure for the total power plant siting
process does not exist, we present two alternatives below and indicate how
our proposed ecological evaluation systems would fit into each.
In the first case, separate low resolution analyses for ecological,
socio-economic, and engineering considerations would be conducted in a
parallel fashion (Figure 25.1). All possible sites would be evaluated by
each system and the better sites for power plant siting would be so indicated.
The decision-making body would then select only those sites rated as the
better sites in all three low resolution evaluations. This would substan-
tially reduce the number of sites that need to be evaluated by much more
costly and time-consuming high resolution analyses.
A single candidate site or group of better sites would then be selected
by the decision makers and be subjected to high resolution evaluation
(ecological, socio-economic, and engineering, in parallel). Based upon
results of the high resolution analyses (i.e., projections of consequences of
927
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All Possible Sites
Low
Resolution
Evaluation
Systems
(LRES)
Ecological
Socio-economic
Sites Classified
Best by all LRES's
High
Resolution
Evaluation
Systems
(HRES)
i
Sites Classified
Best by all HRES's
i
Decision Making Body
Engineering
Sites Classified
Unsuitable by
at least one
LRES
1
Ecological
Socio-economic
I
Engin
|
Sites Classified
-Unsuitable by
at least one
HRES
Best
Site
Figure 25.1. Power plant site selection process—Parallel application of
evaluation systems.
siting a power plant at a particular locale), the decision-making body could
then select the best site or reject all sites.
An alternative power plant siting process would consist of the same
elements as in the process discussed previously but would differ in having
the three low resolution and high resolution evaluations applied sequentially
(Figure 25.2). In this configuration of the process one low resolution
evaluation system would be applied to all possible sites; the second low
resolution evaluation would then be applied to only the sites deemed better
by the first LRES and so forth. The three high resolution evaluation systems
would be applied in the same manner. The final step of the process would be
carried out by the decision-making body in the same manner as for the parallel
application of the evaluation systems (Figure 25.1).
928
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Low
Resolution
Evaluation
Systems
(LRES)
High
Resolution
Evaluation
Systems
(HRES)
All Possible Sites
T
Engineering
Socio-economic
I
Ecological
Sites Classified
Best by all LRES's
Engineering
Socio-economic
Ecological
l
Sites Classified
Best by all HRES's
Decision Making Body
Unsuitable
Sites
Unsuitable
Sites
Best Site
Figure 25.2. Power plant site selection processes—Sequential application of
evaluation systems.
929
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A number of advantages and disadvantages exist for both forms of the
siting processes discussed. One problem that may be common to both, as
illustrated in Figures 25.1 and 25.2, is that it may well be necessary to
have middle level resolution evaluation phases in order to reduce the number
of potential sites that have to be subjected to the HRES's.
An obvious advantage of the sequential applications structure is that
the second and third evaluation systems would have to consider fewer possible
sites than the first evaluation (at any level of resolution). This might
effect a reduction in cost of the power plant siting process itself. A
possible disadvantage of the sequential system is that it would not allow the
user to see sites that are classified best by two out of three of the evalu-
ation systems (essentially second best sites) except when the sites were
classified as acceptable by the first two evaluations of the sequence.
At the present time a variety of methodologies are used in the power
plant siting procedure. A common feature of most of these techniques is that
they start by screening large areas and then narrow down the search to a
smaller number of potentially suitable sites. The most widely used technique
for initial screening is the use of map overlays. Maps of the region of
interest are made on transparent film, with each map shaded to represent the
effect of a particular site consideration (darker shading indicates lower
site suitability). Some of the site considerations include: site develop-
ment criteria, such as water supply, land availability, and seismology;
environmental criteria, ranging from water quality to the effect of air
pollution on the environment; and socio-economic criteria. A visual screening
of the maps overlaid upon each other will show the area that appears lightest
and thus is the most acceptable for further site analysis. The siting
procedure starts by determining a number of candidate aveas within the
overall region and then narrowing down to a small number of candidate sites.
This procedure can be quantified by assigning values for each site
criterion on each given point in the region and then using the computer to
generate maps for each criterion or computer maps which combine any subset of
the different criteria and thus show a combined suitability for each given
unit. A variety of different groups [Argonne National Laboratory (Frigeria
et al. 1975), Dames and Moore (Fischer and Ahmed 1974), and EDAW, Inc.
(Bishop 1972)] have been successful at quantifying the power plant siting
procedure utilizing computer mapping, data analysis, and computer simulation
models. A thorough comparison of the methodologies used in power plant
siting is presented in a report by the MITRE Corporation (Graf-Webster
et al. 1974).
Details of our research plan are contained in a research proposal that
has been submitted to the Environmental Protection Agency. Pending approval
of the proposal, work will be initiated in late summer of 1978. We anticipate
completion of the low resolution ecological evaluation system by the end of
1979 and completion of the high resolution system by the end of 1980.
930
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REFERENCES
Bishop, A. B. 1972. Approach to Evaluating Environmental Soil and Economic
Factors. Water Resour. Bull., 8(4):724-734.
Cooper, C. F., T. J. Biasing, H. C. Fritts, Oak Ridge Systems Ecology Group,
F. M. Smith, W. J. Parton, G. F. Schreuder, P. Sollins, J. Zich, and W.
Stoner. 1974. Simulation Models of the Effects of Climatic Change on
Natural Ecosystems. In: Proceedings of the Third Conference on the
Climatic Impact Assessment Program. Transportation Systems Center, U.S.
Dep. Transportation, Cambridge, Mass. pp. 550-562.
Fischer, J. A., and R. Ahmed. 1974. A Systematic Approach to Evaluate Sites
for Nuclear Power Plants. Presented at the Conference on Nuclear Power
Plant Siting, American Nuclear Society, 26-28 August, Portland, Oregon.
Frigeria, N. A., L. J. Habegger, R. F. King, L. J. Hoover, N. A. Clark, and
J. M. Cabian. 1975. Site: A Methodology for Assessment of Energy
Facility Siting Patterns. ANL/AA-2 Argonne National Laboratory,
Argonne, 111. pp. 1-116.
Graf-Webster, E., S. Haus, S. Labore, J. Pfeffer, and J. Watson. 1974.
Resource and Land Investigations (RALI) Program: Methodologies for
Environmental Analysis—Vol. III. Power Plant Siting. Final Report.
Contract 14-08-0001-14715, Report No. USGS-LI-75-005. U.S. Geological
Survey, Reston, Va.
Holcomb Research Institute. 1976. Environmental Modelling and Decision
Making. Praeger Publishers, New York.
Innis, G. S., ed. 1978. Grassland Simulation Model. Ecol. Studies, Vol.
26. Springer-Verlag, Inc., New York. 298 p.
Parton, W. J., and F. M. Smith. 1974. Exploring Some Possible Effects of
Potential SST-Induced Weather Modification in a Shortgrass Prairie
Ecosystem. In: Sixth Conference on Aerospace and Aeronautical Meteo-
rology. American Meteorological Society, Boston, Mass. pp. 255-258.
Parton, W. J., and R. G. Wright. 1977. The Use of Models in the Analysis of
Environmental Impact. In: New Directions in the Analysis of Ecological
Systems, Part 1, G. S. Innis, ed. Simulation Councils, Proc. Ser. Vol.
5, No. 1. The Society for Computer Simulation (Simulation Councils,
Inc.), La Jolla, Calif, pp. 83-92.
931
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT \O.
EPA-600/3-79-044
2.
3. RECIPIENT'S ACCESSION NO.
4 TITLE A\D SUBTITLE
The Bioenvironmental Impact of"a Coal-fired Power
Plant; Fourth Interim Report, Colstrip, Montana
December 1978.
5. REPORT DATE
April 1979 issuing date
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
Edited by Eric M. Preston and Thomas L. Gullett
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
U.S. EPA
Corvallis Environmental Research Laboratory
200 S.W. 35th St.
Corvallis, OR 97330
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
12. SPONSORING AGENCY NAME AND ADDRESS
SAME
13. TYPE OF REPORT AND PERIOD COVERED
Interim 12/75--12/77
14. SPONSORING AGENCY CODE
EPA/600/02
15. SUPPLEMENTARY NOTESjp
002; the 2nd Interim Rept.
is EPA number EPA-600/3-78-021
series, the 1st Interim Rept. is EPA number EPA-600/3-76-
is EPA number EPA-600/3-76-013, and the 3rd Interim Rept.
16. ABSTRACT
The EPA has recognized the need for a rational approach to the incorporation of
ecological impact information into power facility siting decisions in the northern
great plains. Research funded by the Colstrip, Coal-fired Power Plant Project is a
first attempt to generate methods to predict the bioenvironmental effects of air
pollution before damage is sustained. Pre-construction documentation of the en-
vironmental characteristics of the grassland ecosystem in the vicinity of Colstrip,
Montana began in the summer of 1974. Since then, key characteristics of the eco-
system have been monitored regularly to detect possible pollution impacts upon plant
and animal community structure.
In the summer of 1975, field stressing experiments were begun to provide the
data necessary to develop dose-response models for S02 stress on a grassland eco-
system. These experiments involve continuous stressing of one acre grassland plots
with measured doses of S02 during the growing season (usually April through October).
Results of the 1976 & 1977 field seasons' investigations are summarized in this
publication. The six-year project will terminate in 1980 and a final report will
be published after data analyses are complete.
17.
KEY WORDS AND DOCUMENT ANALYSIS
a.
DESCRIPTORS
b.IDENTIFIERS/OPEN ENDED TERMS
c. cos AT I Field/Group
plant and animal response to pollution
coal-fired power plant
air pollutants
grassland ecosystems
mathematical modeling
remote sensing
micrometeorological investigation
coal-fired power plant
emissions
air quality monitoring
aerosol characterization
51
3. DISTRIBUTION STATEMENT
release to public
19. SECURITY CLASS (ThisReport)'
Unclassified
21. NO. OF PAGES
954
20. SECURITY CLASS (Thispage)
Unclassified
22. PRICE
EPA Form 2220-1 (9-73)
932
ft U. S. GOVERNMENT PRINTING OFFICE: I979-699-222 /205 REGION 10
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