EPA-600/3-76-013
February 1976
Ecological Research Series
THE BIOENVIRONMENTAL IMPACT OF
COAL-FIRED POWER PLANT
Second Interim Report
Colstrip, Montana - June 1975
Environmental Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Corvallis, Oregon 97330
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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 five series. These five broad
categories were established to facilitate further development and application of
environmental technology. Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface in related fields.
The five series are:
1. Environmental Health Effects Research
2. Environmental Protection Technology
3. Ecological Research
4. Environmental Monitoring
5. Socioeconomic Environmental Studies
This report has been assigned to the ECOLOGICAL RESEARCH series. This series
describes research on the effects of pollution on humans, plant and animal
species, and materials. Problems are assessed for their long- and short-term
influences. Investigations include formation, transport, and pathway studies to
determine 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-600/3-76-013
February 1976
THE BIOENVIRONMENTAL IMPACT
OF A COAL-FIRED POWER PLANT
Second Interim Report, Col strip, Montana
June 1975
Edited by
Robert A. Lewis, Norman R. Glass and Allen S. Lefohn
Ecological Effects Research Division
Corvallis Environmental Research Laboratory
Corvallis, Oregon 97330
U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF RESEARCH AND DEVELOPMENT
CORVALLIS ENVIRONMENTAL RESEARCH LABORATORY
CORVALLIS, OREGON 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 publication. Mention of trade names or commercial
products does not constitute endorsement or recommendation for
use.
ii
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ABSTRACT
This document describes the progress of an investigation that
attempts to characterize the impact of air pollutants on a total (grass-
land) ecosystem. More importantly, it is the first to attempt to generate
methods to predict bioenvironmental effects of air pollution before
damage is sustained. We expect to observe complex changes in ecosystem
dynamics as a function of relatively long term, chronic pollution challenge.
By studying a rather broad range of interacting variables, we hope to
isolate some as sensitive and reliable measures of air pollution impact.
The approach employed requires (1) the use of reasonably comprehensive
models of component populations of the ecosystem; (2) the use of appro-
priately structured field and laboratory experiments; and (3) evaluation
of physiological and biochemical functions that may serve as specific
indicators of air pollution stress. The study will establish one part
of the cost/benefit matrix that will provide for the normalization of
environmental impact information.
Included in the study are the characterization of the effects of
coal-fired power plant emissions upon plant and animal community structure;
primary production, invertebrate animal consumers, and decomposers;
plant and animal diseases; both beneficial and harmful insects; indicators
and predictors of pollution (e.g., lichens and honeybees); physiological
responses of plants and vertebrate animals; insect behavior (mainly of
honeybees) and production; the behavior, reproduction and development,
population biology, health and condition of vertebrate animals.
Supportive and integrative components include field experimental
studies; mathematical modeling; remote sensing; micrometeorological
investigation; chemical analyses (e.g., sulfur, fluoride) of biological
specimens; and air quality monitoring that includes integrated aerosol
characterization.
m
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ACKNOWLEDGEMENTS
In addition to the authors and their respective institutions,
many individuals have contributed to the development of the Col strip,
Montana Coal-fired Power Plant Project and to the preparation of this
document. We would like to express our sincere appreciation to all.
Personnel of the Custer National Forest and the Office of the Lieutenant
Governor, State of Montana have been particularly helpful.
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. Editorial assistance was provided by Ms. Karen
Manthe; the help of Ms. Patty Wilkison, Ms. Cathy Alava and others in
the preparation of this document is much appreciated.
IV
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CONTENTS
Abstract iii
Acknowledgements iv
List of Figures vii
List of Tables Y_.
/\ I
Appendices • xv
Sections
I Introduction to the Col strip, Montana, Coal -Fired Power 1
Plant Project
Robert A. Lewis, Allen S. Lefohn, Norman R. Glass
II Monitoring Plant Community Changes Due to Emissions from 14
Fossil Fuel Power Plants in Eastern Montana
J. E. Taylor, W. C. Leininger, R. J. Fuchs
III Effects of SCL and other Coal -Fired Power Plant Emissions 41
on Producer, invertebrate Consumer, and Decomposer
Structure and Function in a Southeastern Montana Grass-
land
J. L. Dodd, R. G. Woodmansee, W. K. Lauenroth,
R. K. Heitschmidt, J. W. Leetham
IV Investigations of the Impact of Coal -Fired Power Plant 61
Emissions upon Plant Disease and upon Plant-fungus and
Plant-insect Systems
C. C. Gordon
V Lichens as Predictors and Indicators of Air Pollution from 91
Coal -Fired Power Plant Emissions
Sharon Eversman
VI Physiological Responses of Vegetation to Coal -Fired Power 100
Plant Emissions
David T. Tingey, Richard W. Field, Lucia Bard
VII Investigations of the Effects of Coal -Fired Power Plant 112
Emissions upon Insects, Report of Progress
Jerry J. Bromenshenk
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CONTENTS (continued)
VIII The Effects of Coal-Fired Power Plant Emissions on 130
Vertebrate Animals in Southeastern Montana
Robert A. Lewis, Martin L. Morton, Susan C. Jones
IX The Field Experimental Component: Evaluation of the 178
Zonal Air Pollution System
Jeffrey J. Lee, Robert A. Lewis, Denis E. Body
X A Remote Sensing Study of the Bioenvironmental Effects of 193
Stack Emissions from the Colstrip, Montana, Power Plant
Thomas R. Osberg, Robert A. Lewis, John E. Taylor
XI Air Monitoring Characterization at the Hay Coulee Site, 203
Colstrip, Montana
James R. Miller, T. Cail, Allen S. Lefohn
XII Integrated Aerosol Characterization Monitoring 222
Vernon E. Derr, G. T. McNice, Allen S. Lefohn
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FIGURES
No. Page
1-1 Operational Plan and Flow Diagram 8
II-l Location of Principal Study Sites 16
II-2 Panoramic View of Taylor Creek Site 17
II-3 Ordination of Intensive Sites 29
II-4 Cluster Dendrogram of Intensive Sites 30
II-5 Sample Stereogram 34
II-6 Stereoscopic Photo Plot Setup 36
II-7 Detail of Camera, Mount and Command Unit 37
IV-1 Vegetation Collection Sites 63
IV-2 Recovery Efficiency of the Combustion lodometric Method 78
for the Analysis of Total Sulfur
V-l Lichen Respiration Rates 95
VI-1 Western Wheat Grass Exposed to 1.5 ppm S02 for 4 Hours 105
VI-2 Western Wheat Grass Exposed to 1.5 ppm S02 for 4 Hours 106
VI-3 Needle and Thread Grass Exposed to 2 ppm S02 for 4 Hours 107
vii
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FIGURES (continued)
VI-4 Fringed Sage Wort Exposed to Ippm SCL for 4 Hours 108
VII-1 Honeybee Collection Sites 114
VII-2 Laboratory Population of Malanoplus bivittatus 121
VII-3 Laboratory Colonies of Various Pine Pests 122
VII-4 Glass-walled Observation Hive 124
VII-5 Accumulation of Fluorides in Tissues of Adult Honeybees 129
near Industrial Areas
VII-6 Pollen Trap 130
VIII-1 Map of Rosebud - Colstrip Roadside Census Route 152
VI11-2 Seasonal Changes in Species Composition of Rodents 160
Captured Near Colstrip
VIII-3 Sex and Age Distribution of Peromyscus man iculatus 162
Captured Near Colstrip
VIII-4 Seasonal Change in Body Weight of Peromyscus maniculatus 163
Trapped in the Colstrip Area
VIII-5 Seasonal Change in Testicular Weight of Adult Peromyscus 168
maniculatus Captured Near Colstrip
VIII-6 Seasonal Change in Seminal Vesicle Weight of Adult 169
Peromyscus maniculatus
VIII-7 Daily Variation in the Weight of Adult Male Mourning 171
Dove Crop Contents
viii
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FIGURES (continued)
VIII-8 Body Weights of Adult Male Mourning Doves as a Function 172
of Molt Stage
VIII-9 Seasonal Progression of Juvenile Western Meadowlark Body 174
Weights
VIII-10 Body Weights of Juvenile Western Meadow!arks as a Function 175
of Molt Stage
VIII-11 Progression of Postjuvenal NoIt of Western Meadowlarks 176
VIII-12 Dried Integument Weight of Juvenile Western Meadowlarks 177
VIII-13 Dry Carcass Weight (less plumage and skin) of Juvenile 178
Western Meadowlarks
VIII-14 Dry Carcass Weight (less plumage and skin) of Juvenile 179
Western Meadowlarks as a Function of Molt Stage
VIII-15 Gizzard Weight of Juvenile Western Meadowlarks as a 180
Function of Molt Stage
VIII-16 Weight of the Bursa of Fabricius (relative to body weight) 182
of Juvenile Western Meadowlarks
VIII-17 Map of Sites Employed to Study Corrosiveness of the 183
Atmosphere
IX-1 Distribution of Concentrations on the Prototype 192
ix
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FIGURES (continued)
IX-2 Time-series of Concentrations on the Prototype 195
X-l Coal Reserves in the Col strip Power Plant Area 208
X-2 Aerial Photograph of the Area Immediately to the East and 209
South of the Col strip Mines
X-3 Field Study Sites in the Vicinity of the Fort Howes Ranger 210
Station
XI-1 Comparison of Hourly Averages of Ozone, Nitric Oxide, 220
Temperature and Solar Radiation
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TABLES
NOji. Page
1-1 Outline of the Research Plan for the Montana Coal- 9
Fired Power Plant Project
II-l Characterization of Study Sites 18
II-2 Comparison of Various Indices of Diversity, based on 23
Plant numbers
1 1-3 Spearman Rank Correlation Coefficients, based on plant 24
numbers
II-4 Pearson's Product of Moments Correlation Coefficients, 25
based on plant numbers
I I -5 F Ratios (based on variances) comparing the First vs. 26
Second Sampling Periods for Each Index for each site
II -6 Test of Equality of means of Two Samples, Variances Unequal 26
(a comparison of the first year vs. second year sampling
period means of each index for each site)
II-7 Phenology code 32
III-l Nitrogen and Phosphorus chemical analysis of Aboveground 44
Old Dead Material
111-2 Nitrogen and Phosphorus Chemical Analysis of Aboveground 45
Standing Live Material
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TABLES (continued)
III-3 Nitrogen and Phosphorus Chemical Analysis of Aboveground 46
Recent Dead Material
III-4 Nitrogen and Phosphorus Chemical Analysis of Aboveground 47
Live and Dead Material
111-5 Site AG Macroarthropod Data Summary. Treatment E. 49
III-6 Site AG Macroarthropod Data Summary. Treatment.F. 50
II1-7 Site AG Macroarthropod Data Summary. Treatment G. 51
III-8 Site AG Macroarthropod Data Summary. Treatment H. 52
II1-9 Site Soil Macroarthropod Data Summary. Treatment E. 53
I11-10 Site Soil Macroarthropod Data Summary. Treatment F. 54
III-ll Site Soil Macroarthropod Data Summary. Treatment G. 55
111-12 Site Soil Macroarthropod Data Summary. Treatment H. 57
IV-1 Vegetation Collection Sites in the Vicinity of Colstrip, 54
Montana
IV-2 Fungal Checklists of Identified Cultures 66
IV-3 Results of Analyses of Potassium Aluminum Sulfate 74
(KA1(S)J2) as the Source of Sulfur for S02 Generation
IV-4 Results of Analyses of Synthetic Plant Standards Prepared 75
by A:h,orbing Thiorurea on Pure Cellulose
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TABLES (continued)
IV-5 Results of Sulfur Recovery from Synthetic Plant Standards 76
Ponderosa Pine Mixtures
IV-6a Sulfur Data from Vegetation Samples 80
IV-6b Fluoride concentration in Vegetation from Colstrip EPA 82
Study Area Exclosures
IV-7a Mean, High, and Low F~ Concentrations in EPA Enclosures 85
IV-7b Mean, High, and Low S concentrations in EPA Exclosures 86
IV-8 Colstrip Samples- Rainwater, Fall 1974 87
V-l Lichens collected, summer 1974 93
V-2 Nitrogen and Sulfur Contents (%dry weight) of 1974 samples 96
of Parmelia chlorochroa and Usnea hirta
VI-1 The Effect of Sulfur Dioxide on the Foliar Injury of Native 101
Plant Species
VI-2 The Effect of Sulfur Dioxide on the Foliar Injury of Native 102
Grasses of Montana
VI-3 Sulfur Dioxide Induced Foliar Injury of Native Plant Species 103
VII-1 Insect Damage to Ponderosa Pines at 13 Sites - Tree Damage and 115
Cone Damage
xm
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TABLES (continued)
VI1-2 Insect Species Selected for Study 119
VI1-3 Chemical Analyses of Adult Honeybees 127
VII-4 Honeybee Samples Containing Residues of Organochlorine- 133
type Pesticides
VII-5 Weights of Adult Worker Honeybees (Apis Mellifera) 134
VIII-1 Bird Species Banded in 1974 150
VIII-2 Road-side Census 153
VIII-3 Numbers of Mice Captured on Grids and Traplines in Colstrip Area 159
IX-1 Geometric Means and Standard Geometric Deviations for Urban Areas 189
IX-2 Expected S02 Concentrations on the Field Experimental Plots 197
X-l High Altitude Photography of Southeastern Montana 207
XI-1 Ambient Air Quality Data 216
XI-2 Wind Directional Frequencies 218
XII-1 Aerosol Characterization Measurement 224
xiv
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APPENDICES
A Biomass Dynamics and Primary Production in Mixed Prairie 217
Grasslands in Southeastern Montana: Baseline Data for Air
Pollution Studies
W. K. Lauenroth, J. L. Dodd, R. K. Heitschmidt,
R. G. Woodmansee
B Col strip Samples - Vegetation - Fluoride, Sulfur 246
C Air Pollution - Insect Pollination, Pertinent Literature 277
Jerry J. Bromenshenk
D Biological Impact of Air Pollution on Insects 286
Jerry J. Bromenshenk
E Dissection Worksheet for Whole Carcass Analysis 304
xv
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SECTION I
INTRODUCTION TO THE COLSTRIP, MONTANA, COAL-FIRED POWER
PLANT PROJECT
by
Robert A. Lewi s
Allen S. Lefohn
Norman R. Glass
INTRODUCTION
The United States presently faces a series of problems concerning
the production, distribution and consumption of fossil fuel energy.
Because this fuel resource is abundant at relatively low cost, the
Administration's desire to attain energy self-sufficiency by 1985, and
other factors, it ,is clear that the United States is moving toward an
economy based on coal as the primary fossil fuel. This rush toward
energy self-sufficiency is creating new pressures on the environment.
The decisions that will ultimately resolve the environmental and economic
issues we face must be made with full knowledge of the constraints
imposed by the need to minimize environmental impacts associated with
energy production and utilization.
Currently, over 95 percent (Council on Environmental Quality, 1974)
of the primary energy in the United States is produced through the
combustion of fossil fuels (the remainder is derived from hydro power
and nuclear energy). By the year 2000, the fossil fuel contribution to
the total energy economy is expected to be approximately 70 percent, but
total use of fossil fuels will probably increase by more than 100 percent.
During the same period, nuclear energy production is expected to grow
ten-fold.
There is a clear relationship between research conducted on energy-
related problems and research which has been carried out to set or
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revise air and water quality standards that are designed to maintain
environmental quality. This is due to the fact that environmental
research designed to determine the effects on biota and ecological
processes is concerned with the same types of pollutants or residuals
for standard setting purposes as for identifying the effects of energy
extraction, conversion, or generation. For example, ambient air quality
standards have been established under the Clean Air Act Amendments of
1970 for the major, but not all, pollutants generated by fossil fuels.
National Ambient Air Quality Standards (NAAQS) have been established for
sulfur oxides (SO ), particulates, carbon monoxide (CO), nitrogen
A
oxides (NO ), hydrocarbons, and oxidants. These standards were based
/\
upon the best information available at the time of their promulgation.
New source performance standards (NSPS) have been established for
several industries, including electric utilities. These new standards
restrict the emissions of SO , NO , particulates, and other pollutants
A A
and apply to the operation of fossil fueled generating plants constructed
or modified after August 1971.
In general, progress is being made toward attaining higher ambient
air quality levels nationwide. However, certain air quality control
regions may not meet statutory deadlines for reaching suitable air
quality levels. Considering all 247 air quality control regions of the
country, it is anticipated that 60 will not meet the statutory deadlines
for particulates (TSP), and 42 will not meet the deadline for sulfur
dioxide (S02). About the same number of air quality control regions
will not meet the deadline for oxidants, NO , and CO. For areas with
/\
high ambient S02 levels generally, the cause is emissions from an
uncontrolled point source such as a smelter or power plant. While most
air quality control regions can anticipate that rigorous enforcement of
existing regulations will be adequate to meet S0? standards, future
problems may arise because of inadequate supplies of low sulfur fuel or
installations and application of flue gas desulfurization equipment.
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The Clean Air Act states that "...air quality criteria for an air
pollutant shall accurately reflect the latest scientific knowledge
useful in indicating the kind and extent of all identifiable effects on
public health or welfare which may be expected from the presence of such
pollutants in the ambient air, in varying quantities" [section 108(a)].
The Act further states that national primary ambient air quality standards
are regulations which "...in the judgment of the administrator, based on
such criteria, and allowing for an adequate margin of safety, are requisite
to protect the public health" [section 109(b)]. Air quality criteria,
then reflect scientific knowledge, while primary air quality standards
involve a judgement as to how this knowledge must be used in a regulatory
action to protect public health. The secondary air quality standards
determine the level of air quality required to protect the public welfare.
Public welfare as defined in the Clean Air Act "...includes, but is not
limited to, effects on soils, water, crops, vegetation, manmade materials,
animals, wildlife, weather, visibility, and climate...[section 302(h)]."
These considerations also apply and become focal points for energy
related environmental research. It is clear that the research experience
gained in meeting requirements of the Clean Air Act is valuable in
pursuing energy related research. In fact, the objectives of each set
of research programs are so similar that precise separation is not
possible.
The major categories of air pollutants emanating from fossil fuel
energy systems are sulfur oxides, nitrogen oxides and particulate matter.
Energy systems also contribute, to a lesser degree, to carbon monoxide
and oxidant burdens. Primary ambient air standards, based on health
effects have been established for these pollutants. Secondary standards
have been established for sulfur dioxide, particulates, carbon monoxide,
oxidants, hydrocarbons, and nitrogen dioxide. These standards were
based on the best scientific information available at the time of their
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creation. However, when they were established, significant knowledge
gaps existed; even now major gaps in knowledge still exist for each
pollutant. Therefore, under the Clean Air Act, EPA is required to
continually examine and update the criteria for these standards. In
addition to the above pollutants, numerous trace metals (such as copper,
cadmium, zinc, lead, arsenic, mercury, and others), are emitted from
fossil-fueled power generating plants. Numerous other trace contaminants
in the form of hydrocarbons and various aerosols are also emitted from
power plants. In general, trace metals are emitted as particles adsorbed
to fly ash and/or other particulate matter coming from the stack of the
coal-fired power plant.
The following discussion represents an overview of the National
Ecological Research Laboratory's recently initiated coal-fired power
plant project. The broad objective of this program is to develop a set
of guidelines which planners can use in predicting the impact of power
plants on a grassland ecosystem. This study is concerned not only with
the stability of ecosystem organization in relation to ambient conditions,
but also with the predictability and reproducability of changes that do
occur. Insight into the mechanisms of dynamic-structural responses of
ecosystem components to air pollution challenge is also sought. Identi-
fication of subsystem functions that contribute to ecosystem regulation
and the mechanisms whereby such regulation is effected is of special
concern.
This investigation represents an effort to characterize the impact
of air pollutants on a total ecosystem. It is the first attempt to
generate methods that can predict bioenvironmental effects of air pollution
before damage is sustained. Historically, most terrestrial air pollution
field research has dealt almost exclusively with direct, usually acute,
effects on vegetation. We expect to observe complex changes in ecosystem
dynamics as a function of relatively long term, chronic pollution challenge.
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By studying a rather broad range of interacting variables, we hope to
isolate some of these as sensitive and reliable measures of air pollution
impact.
The approach employed requires (1) the use of reasonably compre-
hensive models of component populations of ecosystems; (2) the use of
appropriately structured field and laboratory experiments; and (3) an
evaluation of physiological and biochemical functions that may serve as
specific indicators or predictors of air pollution stress.
Even in a comprehensive investigation, extensive studies of a large
array of species or processes is not possible. Considerable research is
required to identify the specific parameters that will give an adequate,
sensitive measure o.f air pollution to a grassland ecosystem and/or its
components. Broad categories of important functions under investigation
include (1) productivity or biomass of ecosystem compartments; (2),
life-cycle and population dynamic functions of "key" taxa; (3) community
structure or diversity; (4) nutrient cycling; (5) sublethal biochemical
or physiological changes in individuals or compartments; (6) behavior of
mobile organisms; and (7) reproductive patterns and breeding success of
terrestrial vertebrates.
If we are to assess and interpret the effects of air quality upon
natural ecosystems, it is essential to understand the wide range of
abiotic factors,(e.g., weather, geography, insolation, hydrology, etc.)
that influence the dynamics of the living components of the ecosystem.
Optimum production, the maintenance of stability and diversity, and
other desirable properties of ecosystems all depend upon a variety of
these abiotic factors. Thus, appropriate micrometeorological and air
quality support is provided to this study.
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RATIONALE
In addition to the "simple" direct effects of air pollutants that
•
have been reported from experimental studies of natural systems\ we may
expect to observe complex changes in ecosystem dynamics as a function of
pollution challenge. We know that insults to the environment from
rather diverse sources (toxic substances, pesticides, radiation, disease,
and adverse climate) produce a similar array of effects at the community
level in spite of very different effects on individual organisms studied
under experimental conditions. The response mechanisms may vary, but
results are often similar: (1) a "reversal" of succession or simplification
of ecosystem structure; (2) a reduction in the ratio of photosynthesis
to respiration; and (3) a reduction in species diversity at more than
one trophic level, which may include the elimination of certain species
(e.g., in grassland, usually rare, but characteristic species). Effects
may be temporary and reversible (i.e., the system adapts) or chronic and
cumulative. In any case, if a coal-fired power plant has a measurable
impact on the environment, there is every reason to believe that it will
be registered as an alteration of community structure.
Both plant and animal diversity and energy transfer between and
within trophic levels are measures of community structure. Also, these
functions may be regarded as important ecosystem resources. We hypothesize
that the immediate population-level effects from environmental stress
may result from differential impairment of competitive ability. At the
relatively low pollution levels anticipated in the investigation, we may
expect to find predisposing and subclinical effects that will be impossible
to detect in the absence of appropriate population dynamic, biochemical
and physiologic information.
Effects need not be mediated by alterations in food chains or
energy flow. Certainly food chains and mass and energy flow patterns
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will be affected (although possibly secondarily) whenever population
adjustments occur. For example, a pollutant may alter the physiology or
behavior of the individuals that comprise a population. These alter-
ations are ultimately reflected in altered survival, reproduction
and/or emigration rates. Such effects may be subtle and difficult to
relate to the specific stressor. In the real world, numerous stressors
are operating in complex ways with various lag times; these tend to
confound the results of any field evaluation of a single stressor. The
end result of the community response to a continued environmental stress
is a readjustment of the component populations (plant and animal) at a
new state of dynamic equilibrium. It is not possible to predict with
any confidence either the adjustments and mechanisms most critically
involved or the final population levels that will be reached. By studying
a rather broad range of interacting variables and, in particular, by an
intensive study of certain populations, some may be isolated as sensitive
and reliable measures of air pollution. Table 1-1 outlines the existing
research plan.
Figure 1-1 summarizes the operational plan of the project. The
four major components (field and laboratory experiments, field validation,
and modeling) form an integrated approach; information generated by each
component is used to guide the course of the other components. The goal
is to generate information on both short-term and longer-term responses
and, with appropriate models, to integrate and relate these data to
generate procedures for impact assessment that are truly predictive.
The recruitment of a new field experimental system each year for three
years will allow us to evaluate both within-year and between-year sources
of variance. This temporal structure of the field experimental system
will further allow us to conduct new experiments during the third year
of the study to test hypotheses generated by our field experience and
modeling efforts during the first two years of the study.
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^_
Figure 1-1 Operational Plan and Flow Diagram. Numbers represent
the project year. See accompanying text.
MET DATA
DESIGN
•i
t
M
RETROSPECTIVE
STUDY
MODELLING
EFFORT
FIELD
XPER
LAB
XPER
FIELD
VALID.
128
SHORT-TERM
(organ,
organismal)
131
7"
V
ECOSYSTEM
LEVEL EFFECTS
:TS
t
ISECOND (3ENERATIONI
IFIELP EXPERIMEISITSl
V
MODEL (PREDICTIVE) "PROGRAM
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Table 1-1. OUTLINE OF THE RESEARCH PLANT FOR THE MONTANA
COAL-FIRED POWER PLANT PROJECT
I. Field Investigation
A. Temporal and spatial quantitative inventory of components of
the study area, with particular focus on the annual cycle
phenomena of key species.
B. Meteorological measurements to support the modeling and experimental
air pollution research efforts.
C. Development of remote sensing as a tool for detecting effects
of air pollutant challenge on the ecosystem.
D. Measurement of loss of inventory attributed to strip mining, power
lines, human activity, water use, and other potentially confounding
influences, e.g., pesticides, disease, population cycling.
i
II. Air Pollution Experiments
A. Experimentally controlled air pollution of spatial segments of
an ecosystem.
B. Detailed measurement of biological structure and function,
including energy flow, nutrient cycling and species condition,
composition and diversity during and following air pollution stress.
III. Laboratory Experiments
A. Measurement and evaluation of physiologic, biochemical and
behavioral mechanisms of response to air pollution challenge.
B. Precise measurement of parameters that support dynamic models.
C. Experiments designed to test whether changes observed in
experimental study plots can be attributed to air pollutant
stress.
D. Secondary stresser experiments (e.g., disease, temperature
stress, water stress, non-specific stress).
E. Experiments designed to test field-generated hypotheses.
IV. Modeling
A. Use of an ecosystem level model to describe and predict effects
of air pollutant challenge.
B. Use of models to help design experiments.
C. Use of models to help disentangle pollutant effects from
natural variation and system dynamics.
D. Meteorological and dispersion modeling to describe the
mode of entry of pollutant into the ecosystem and its
time and space distribution and concentration.
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BASIS FOR SITING THE INVESTIGATION IN SOUTHEASTERN MONTANA
The identification and selection of an appropriate study area was
essential to structuring the entire investigation. Col strip was selected
on the basis of our initial literature review and several field trips to
Montana and Wyoming. The principal criteria used to select the study
area are detailed below:
1. The region is climatically and ecologically representative of
a relatively large portion of the North Central Great Plains.
2. The Colstrip area of the Fort Union Basin is a relatively
pristine pine savanna area which has never been subjected to [toxic]
gaseous or particulate emissions from a stationary source. Thus the
vegetation and non-migratory animals in the area, although stressed by
various environmental factors such as drought, adverse temperatures,
nutrient deficiencies, etc., have never experienced the added stress of
air pollutants. Previous air pollution studies around power plants
(e.g., the Environmental Protection Agency's Mount Storm studies; the
Tennessee Valley Authority's pre- and post-operational studies; Large
Power Plant Effluent Study (LAPPES) [APTD 70-2, 0589, and 0735] and
others([EPA 660/3-74-011]) have generally occurred after the power
plants are on line, or in areas that have suffered substantial pollution
prior to operation of the power plant. Thus, it has been impossible to
assess adequately the first introduction of toxic power plant emissions
into plants to an essentially pristine ecosystem.
3. Montana laws favor rational resource development.
4. Current assessments indicate that Montana contains nearly a
third of the strippable coal reserves in the North Central Great Plains.
It is possible that some 120,000 acres will be stripped during the next
two decades.
10
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5. Southeastern Montana is a rich rangeland resource.
6. Existing data, although scarce, indicate that air quality in
Eastern Montana is well above the national average.
7. Local-regional emission sources (see Regional Profile Report
on Atmospheric Aspects, Northern Great Plains Resource Program, April
1974 [draft copy]) other than the coal-fired power plant at Col strip are
unlikely to contribute significantly to the air pollution burden of the
Rosebud Creek Watershed during the period of investigation.
8. The projected sites and schedules of strip-mining and power
plant development are known.
9. The history of human disturbance is reasonably well-documented.
10. We expect human disturbance (except that associated with coal
mining and coal-conversion) to be relatively minimal throughout the
investigation period. We feel reasonably assured that sample sites,
including buffer zones and reference sites, will remain substantially
free of confounding disturbance.
11. Other investigations underway at Colstrip complement this
investigation; thus, this research will broaden and extend an existing
data base.
SCOPE AND PURPOSE
Following one year of intensive preparation, the overall investi-
gation is planned as a three-year field effort. A fourth year will be
allowed for data analyses and evaluation. Most of the field activities
during each sampling year will occur from April through October, although
some components will continue throughout the entire annual cycle. We
11
-------
expect the evaluation and synthesis of our results to generate a protocol
that will permit planners to assess the impact of energy conversion
activities on grasslands in the Northern Great Plains prior to the
initiation of site selection activities. Achievement of this objective
would favor valid siting and regulatory decisions. Full realization of
this objective within the projected time frame will require a synthesis
of the National Ecological Research Laboratory's effects research data
and coordination with the results of socio-economic and transport/fate
research projects. This will be difficult to accomplish, but the
rewards are potentially great.
-------
REFERENCES
1. Council on Environmental Quality. 1974. DCS Oil and Gas—An
Environmental Assessment: A Report to the President. Vol. 2. p.
3.
13
-------
SECTION II
MONITORING PLANT COMMUNITY CHANGES DUE TO EMISSIONS FROM FOSSIL FUEL
POWER PLANTS IN EASTERN MONTANA
by
J. E. Taylor, W. C. Leini.nger, and R. J. Fuchs
This component of the Montana Coal-Fired Power Plant Project was
initiated on 15 July 1974.
Specific tasks are to:
1. Document pre-treatment native plant communities in areas
likely to be affected by the power plants under investigation
and on areas to be stressed artificially with pollutants.
2. Develop measurement techniques and monitor changes in plant
community structure, diversity, phenology, and speciation
following air pollution stress.
3. Develop detailed vegetation maps of the study areas.
4. Provide data for simulation models to predict bioenvironmental
changes resulting from fossil fuel power generation in other
areas.
Due to the late starting date some objectives were not realized the
first summer. When the field work was initiated, many of the ephemeral
plants were dry and were either impossible to identify or absent from
the sites. The late date also hampered the color infrared photography
14
-------
work and seed and plant collections. The main first year accomplishment
was the development of specialized techniques.
The 1974 work concentrated on the project's experimental areas,
including the proposed stressing site at Ash Creek (where grassland was
to be artifically fumigated) and the validation sites near Colstrip.
Additional Colstrip sites were located on three adjacent, relatively
undisturbed knolls, referred to as relict knolls A, B, and C (Figure
II-l).
Project activities to date may be classified into these categories:
Description and Characterization of Study Areas
Analysis of Plant Community Structure
Photographic Monitoring
Description and Characterization of Study Areas
Each study site was described in detail (Taylor, Leininger, and
Fuchs, 1975). Data were recorded on exact location, topography, soils,
and vegetational composition (Table II-l).
The Zonal Air Pollution System operation has been moved from Ash
Creek to Taylor Creek (Lee, Lewis and Body, 1975) (Figure II-2). This
new site is about 7.5 miles (12 km) SSE of the Ash Creek site in Fort
Howes District of the Custer National Forest.
The Taylor Creek site lies about 54 miles (86 km) southeast of
Ashland in W 1/2 S9 T7S R47E, MPM. The exclosure lies on a 6 to 8
15
-------
Figure II-l Locations of Principal Study Sites (l=Hay Coulee,
2=Cow Creek, 3=North Pasture, 4=School Section,
5=Relict Knolls, 6=Ash Creek).
CUSTER
COUNTY
ROSEBUD
COUNTY
16
-------
B
Figure II-2 Panoramic View of Taylor Creek Site, 17 March 1975.
-------
Table II-l. CHARACTERIZATION OF STUDY SITES
Distance (km) &
Direction fr/
00
Name
Ash Creek
Hay Coulee
Cow Creek
North Pasture
School Section
Col strip
74.8 SE
11.6 SE
11.6 ESE
14.7 E
18.3 ESE
Pristine Knolls A 13.8 SE
Elevation
(meters)
1173
927
917
902
904
908
902
908
Slope &
Exposure
Plant Aspect-/
4-5% NE AGSM, KOCR, BRJA
4% NNE AGSM, ARTR, KOCR, BRJA
6% N STCO, AGSM, BRJA, BRTE
5% NE STCO, ARFR, AGSM, BRJA
3 1/2% NE AGSM, BRTE, BRJA, ARFR
2% ESE CALO, SCSC, AGSP
4 1/2% NW AGSP, STCO, ARTR
6 1/2% SE STCO, CAFI, AGSM
Soil
Characterization
Residual silt loam
Colluvial clay loams
Colluvial sandy loams
Colluvial sandy loams
Residual and colluvial
clay loams
Colluvial and residual
sandy loams
Colluvial and residual
loams
Colluvial and residual
sandy loams
]_/ AGSM = Western wheatgrass (Agropyron sirnthii)
ARCA = Silver sage (Artemisia cana)
BRJA = Japanese brome (Bromus japonicus)
ARTR = Big sagebrush (Artemisia tridentata)
AGSP = Bluebunch wheatgrass (Agropyron spicatum)
CAFI = Thread!eaf sedge (Carex filifolia)
KOCR = Junegrass (Koeleria cristata)
STCO = Need!e-and-thread (Stipa comata)
BRTE = Cheatgrass (Bromus tectorum)
ARFR = Fringed sagewort (Artemisia frigida)
SCSC = Little bluestem (Schizachyriutn scoparium)
CALO = Prairie sandreed (Calamovilfa longifolia)
-------
percent southwest facing slope, and the elevation is about 1220 meters.
Soils are loams, derived from colluviurn and parent materials weathered
in place. The site is considered in good range condition; dominant
vegetation is western wheatgrass (Agropyron smithii). Sandberg bluegrass
(Poa secunda), and junegrass (Koeleria cr istata). Major plant associates
are needle-and-thread grass (Stipa comata), common dandelion (Taraxacum
officinale), and western yarrow (Achillea lanulosa).
Further sites have been examined for possible future use, including
areas east of Colstrip and several sites on the Ashland Division, Custer
National Forest.
Plant Community Structure
Canopy cover estimates were made on all intensively-studied locations
and on all three relict knolls. The technique used was that of Dauben-
mire (1959), i.e., a 2 X 5 dm plot frame in which each species canopy
cover is classified into one of six categories. At each site, 50
frames were examined on each sampling date.
Diversity Studies. Numerical data for index of diversity studies
(species and individuals per species) were recorded for each Daubenmire
plot concurrently with canopy cover. Diversity indices used were:
1. Shannon-Weaver Function
S
H1 = Z Pi log Pi
19
-------
Where H' = the index of diversity
S = the number of species present
Pi = the number of individuals per species divided
by the total number of individuals sampled.
H1 is an estimation of Brillouin's H, the true population
diversity. At large sample sizes the value for H1 is almost
exactly that for H. In addition, since log Pi is used,
rarer species aren't discriminated against (Pielou, 1966;
Shannon and Weaver, 1963).
2. Simpson's D
S 2
D = i - x p-r
Where D = the index of diversity
S = the number of species present
Pi = the number of individuals per species divided
by the total number of individuals sampled.
While values for D agree closely with values for H1, the
o
expression Pi used in the formula discriminates against
the rarer species (Simpson, 1949).
3. Redundancy
R = (H'max-H'KH'max-H'min)
Where R = redundancy
H1 = Shannon's H1
20
-------
H'max+H'min are the maximum and minimum possible values,
respectively, for H1 based on the species and
total number of individuals recorded.
Redundancy is a measure of evenness or equitafaility which
relates the observed H1 to the maximum and minimum possible
values of H1 given the number of species and total number of
individuals present (Hamilton, 1974).
4. Probability of Interspecific Encounter (P.I.E.)
A 1 • [ A] 1- *., "2 ' < fPT '"
Where A , = the probability of interspecific encounter
(P.I.E.)
D = Simpson's D
N = the total number of individuals sampled.
P.I.E. is an index of diversity based on Simpson's D. It
is the probability an individual has of encountering
an individual of another species (Hurlbert, 1971).
5. Probability of Intraspecific Encounter (Pa)
Pa = 1 - AI
Where Pa = the probability of intraspecific encounters
21
-------
AI = P.I.E.
Pa is the complement to P.I.E. (Hurlburt, 1971). It measures
the probability an individual has of encountering another
individual of the same species in the population sampled.
6. P.I.E. Transformation (Ag)
S 2
A- = V £ pr
6 i=l
Where A3 = P.I.E. transformation
S o
I Pi = the expression from Simpson's D.
i=l
The P.I.E. transformation is used to increase the spread
between values for Simpson's D at the upper portion of its
range (Hurlbert, 1971).
7. Fisher's a
a = N(l-X). N = n,.
a X ' N 1-X
Where a = the index of diversity
N = the total number of individuals sampled
n, = number of species with just one individual.
Fisher's a is based on the number of species in the sample
containing only one individual (Fisher, Corbett, and Williams,
1943).
22
-------
Table II-2. COMPARISON OF VARIOUS INDICES OF DIVERSITY, BASED ON PLANT NUMBERS
Site Fisher's a Simpson's D Hj_ Redundancy P.I.E. Pa
North
Pasture 3.0382 .8765 1.0506
Hay
Coulee 5.0052 .8585 .9804
Cow
Creek 5.0053 .8433 .9464
Ash
Creek 2.0010 .8423 1.0590
School
Section 6.0112 .8194 .8886
.2808
.3275
.3516
.3547
.3948
.8768
.8587
.8435
.8425
.8196
.1232
.1413
.1565
.1575
.1804
8.0972
7.0671
6.3816
6.3412
5.5371
-------
Table II-3. SPEARMAN RANK CORRELATION COEFFICIENTS, BASED ON PLANT NUMBERS
D H' R P.I.E. Pa A3
D - 0.4 -,1.0 1.0 -1.0 .1.0
H' 0.4 - -0.4 0.4 -0.4 0.4
R -0.1 -0.4 - -1.0 1.0 -1.0
P.I.E. 1.0 0.4 -1.0 - -1.0 1.0
Pa -1.0 -0.4 1.0 -1.0 - -1.0
3 1.0 0.4 -1.0 1.0 -1.0
24
-------
Table II-4. PEARSON'S PRODUCT OF MOMENTS
CORRELATION COEFFICIENTS, BASED ON PLANT NUMBERS
D
H1
R
P.I
Pa
A3
D
-
0.4
-1.0
.E.1.0
-1.0
1.0
H'
8.4
-
-0.4
0.4
-0.4
0.4
R
-1.0
-0.4
-
-1.0
1.0
-1.0
P. I.E.
1.0
0.4
-1.0
-
-1.0
1.0
Pa
-1.0
-0.4
1.0
-1.0
-
-1.0
A3
1.0
0.4
-1.0
1.0
-1.0
_
25
-------
Table II-5. F RATIOS (BASED ON VARIANCES) COMPARING THE
FIRST VS. SECOND SAMPLING PERIODS FOR EACH INDEX FOR EACH SITE
Shannon-Weaver
Function
Site
Hay Coulee
Pasture North
Cow Creek
School Section
* = significant at the .05 confidence level
** = significant at the .01 confidence level
*** = significant at the .001 confidence level
Simpson's D
Redundancy
1.70*
2.12**
1.73*
1.53
3.19***
5.47***
"2.10**
2.64***
1.23
1.24
2.13**
2.06**
Table II-6'. TEST OF EQUALITY OF MEANS OF TWO SAMPLES,
VARIANCES UNEQUAL (A COMPARISON OF THE FIRST VS. SECOND
SAMPLING PERIOD MEANS OF EACH INDEX FOR EACH SITE)
Site
Hay Coulee
North Pasture
Cow Creek
School Section
Shannon-Weaver
Function
7.82***
4.31***
7.26***
6.70***
Simpson's D
6.84***
3.02**
4.12***
5.80***
*
**
A**
= significant at the 0.5 confidence level
= significant at the .01 confidence level
= significant at the .001 confidence level
Redundancy
0.41
0.63
0.49
2.50*
26
-------
A comparison of the various indices is given in Table 11-2.
Statistical tests of correlation appear in Tables II-3 and II-4. Note
that all indices were calculated on a site-by-site, not frame-by-frame
basis. Standard errors are thus not presented.
The various indices correlate quite closely except for Fisher's a
(Tables II-2, II-3, and II-4). The high value for H1 for the Ash Creek
site is probably due to a greater number of forbs, reflecting a more
favorable plant habitat.
Using the random line placement technique, additional statistical
tests were performed on data from the primary sites during the first and
second sampling periods.
Tests were run on each of three primary indices of diversity: the
Shannon-Weaver function (HP), Simpson's D (D2), and redundancy (BR)
(Tables II-5 and II-6).
2
Bartlett's test for homogeneity of variances gave a x value of
23.76 for HP, 65.14 for D2, and 14.44 for BR. The first two are signi-
ficant at the .001 confidence level; the third is significant at .05.
These results permitted testing for equality of means with heterogeneous
variances. Results produced Fg values of 44.98 for HP, 3770.01 for D2,
and 1.73 for BR. The first two were significant at the .001 confidence
level while BR was not significant. Significant differences show that
the samples were taken from populations with unequal means.
Table II-5 presents results of an F test based on variances.
Again, significant differences demonstrate that the samples were drawn
from populations with unequal means. These results allow use of a test
for equality of means of two samples with unequal variances (Table II-
6).
27
-------
The results thus far have been highly encouraging, especially those
documented in Table II-6 which compare the means of the first and second
sampling period for each site. Both the Shannon-Weaver function and
Simpson's D yield significant differences at the .01 to .001 confidence
levels. This demonstrates that these indices can record changes in a
natural rangeland ecosystem as the growing season progresses. Since
these changes may be viewed, in part, as the ecosystem's response to
climatic stress, we may infer that the tests also are sensitive enough
to monitor changes created by pollution or other types of stress on a
rangeland ecosystem.
Redundancy has not yielded comparable results. Dr. Martin Hamilton,
biostatistician in the Mathematics Department, Montana State University,
is devising a redundancy index based on Simpson's D rather than on the
Shannon-Weaver function. He is also developing statistical tests of
significance that should be specifically applicable to indices of
diversity. Thus, project staff will not be dependent on generalized
tests of significance. These techniques will be tested and applied to
the 1975 data.
Site Similarity Comparisons. Frequency data from all sites were used to
pu
construct a similarity matrix, using the relationship I = |^-. , where I =
Index of Similarity, W = the sum of frequency in common between two
stands (sites), a = the sum of frequencies of the first stand and b =
the sum of frequencies of the second stand (Sorenson, 1948).
The similarity matrix was the basis for a two-dimensional ordination
(Bray and Curtis, 1957) and a cluster dendrogram (Sorenson, 1948). The
ordination (Figure II-3) and the dendrogram (Figure II-4) show a reasonably
high degree of similarity among all sites. The sites fall into three
major groupings: Ash Creek and Hay Coulee; Cow Creek, North Pasture,
and School Section; and the three relict knolls. The overall I-value of
28
-------
Figure II-3
Ordination of Intensive Sites, Based on Indices of
Similarity (frequency). l=Hay Coulee; 2=Cow Creek;
3=North Pasture; 4=School Section; 5=Relict Knolls;
6=Ash Creek
29
-------
Figure II-4
Cluster Dendrogram of Intensive Sites. See Figure
I1-3 for definition of symbols.
o
o
o .
CO
o .
CO 9 -
o _
CM
6) (0 (2) (3) (4) (5«) (5b) (5c
30
-------
52.5 indicates a reasonable level of comparability among the study
sites.
Phenology. Initial observations were made to test a phenological
scorecard developed for this project. The lateness of the season
precluded the development of an annual phenologic profile for the study
areas, but this system should be useful in subsequent seasons. The
phenological stages recognized are shown in Table II-7.
Considerable interest has been shown among grassland researchers in
the project's plant phenology techniques. Because of this, we have
reviewed the literature on the design and use of phenology indices, and
are preparing a manuscript on the subject. We have provided copies of
the phenology scale to several correspondents.
Plant Collection. The field crew collected all plant species on each
study site as they came into flower. This year only late flowering
species were obtained. Future collections will include specimens of the
early flora. This material will provide a reference herbarium for local
consultation. Specimens also will be submitted to the Montana State
University Herbarium for taxonomic verification and voucher purposes.
Seed Collection. Seeds of common plant species were collected. This
material will be used by the vertebrate animal research personnel in
examining food habits of the populations under study. This work will
continue in future years.
Photographic Monitoring
Permanent Ground Photo Plots. Initial photo plots were established and
photographed at all locations. At Ash Creek, two plots were placed in
each of the proposed stress sites. At Hay Coulee, Cow Creek, North
31
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TableII-7 Phenology Code
Code Stages
1 Cotyledon (newly germinated)
2 Seedling
3 Basal Rosette
4 Early greenup, veg. buds swelling
5 Vegetative growth, twig elongation
6 Boot stage, flower buds appearing
7 Shooting seed stalk, floral buds opening
8 Flowering, anthesis
9 Late flowering
10 Fruit formed
11 Seed shatter, dehiscence
12 Vegetative maturity, summer dormancy, leaf drop
13 Fall greenup
14 Winter dormancy
15 Dead
32
-------
Pasture, and School Section, two photo plots were established in each
exclosure; one photo plot was placed on each of the three relict knolls.
The photo plots were 3x3 feet and marked for relocation. Each was
photographed in color from a high oblique angle (25° from vertical).
Stereoscopic photography was used to facilitate plant identification.
Most plots were also photographed with infrared color film. After the
oblique photographs were made, the camera was tilted up so that the
field of view included the horizon, and an aspect picture was taken. At
the same time that the plot photography occurred, a rough chart was
prepared to show locations and identifications of the various species.
This will help in the photograph interpretative work. An example
stereogram is shown in Figure II-5.
Enlargements (8"xlO") of permanent plot photographs are being
interpreted by preparing species overlays. These will constitute base-
line maps of the monitoring stations, and will be used to follow changes
in species composition and cover.
Using a computer plotting procedure, some of the photographs are
being charted in three dimensions. Researchers will evaluate the
effectiveness of this technique in plant monitoring activities.
Procedures for ground level photo plots will be changed for this
field season. Instead of the oblique photographs made in 1974, vertical
stereoscopic photo pairs will be taken of all permanent photo plots.
These will be replicated with color, infrared color, and black-and-
white. This should permit equally good photographic interpretation of
the plant communities being sampled and allow quantification of vegetation
parameters such as density, number, cover, and individual plant location.
The stereoscopic coverage will enable the researchers to make volume and
33
-------
Figure II-5 . Sample Sterogram
-------
height estimates using the principle of stereoscopic parallax.
The 1975 photographic plot setup is shown in Figures II-6 and II-7.
Studies of optimum film/filter combinations and exposure standardization
will be made.
Aerial Photography. On September 24 and 25, initial aerial photography
of the study areas was conducted by Aerial Survey, Inc. of Miles City.
This activity was designed to obtain imagery in various emulsion types
and at different scales to be evaluated for future operations. Color,
infrared color, and black-and-white imagery was obtained in 35 mm and 70
mm formats. Flying elevations ranged from 500 to 7200 feet above ground
level, yielding image scales from 1:3000 to 1:44,500. To aid in future
aerial photography work, black-and-white index mosaics were prepared for
each study area. The color imagery will be examined for use as a
monitoring technique.
Enlargements of Hay Coulee 70 mm aerial photographs show that
conventional color at a negative scale of 1:3000 will yield prints of
1:500 with sufficient resolution to map plant communities and conspicuous
species. These photographs also show impacts of travel and sampling in
the exclosure area.
Medium scale (1:10,000) aerial photography was viewed stereoscop-
ically to aid in exact placement of exclosure sites on U. S. Geological
Survey topographic maps. This imagery proved useful as a guide to
interpretation of smaller scale photography acquired elsewhere.
35
-------
Figure II-6 Stereoscopic Photo Plot Setup. Two EL/M Hasselblad
cameras are operated simultaneously with the remote
command unit.
36
-------
Figure II-7 Detail of Camera, Mount and Command Unit.
37
-------
Future Plans
Methodology and field techniques for 1975 will be essentially the
same, with a few modifications. Use of the fixed or random line place-
ment method, rather than both, is a possible modification in field
techniques. A first line analysis of last year's data using the fixed
line placement method is complete. If statistical tests show no signi-
ficant differences between the two line placement methods, then only one
type would be needed. This would represent a reduction of 50 percent in
the number of Daubenmire frames needed, a considerable savings in time,
energy and money.
38
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REFERENCES
1. Bray, J. R. and J. T. Curtis. 1957. An ordination of the upland
forest communities of southern Wisconsin. Ecol. Monog. 27:325-349.
2. Daubenmire, R. F. 1959. A canopy-coverage method of vegetational
analysis. Northw. Sci. 33:43-64-
3. Fisher, R. A., A. S. Corbet, and C. B. Williams. 1943. The
relation between the number of species and the number of individuals
in a random sample of an animal population. J. Anim. Ecol. 12:42-
58.
4. Hamilton, Martin A. 1974. Indexes of diversity and redundancy.
Unpubl. paper, Dept. of Mathematics, Mont. State Univ., Bozeman.
5. Hurlbert, S. H. 1971. The nonconcept of species diversity: a
critique and alternative parameters. Ecol. 52:577-586.
6. Lee, J., R. A. Lewis, and D. Body. 1975. (In this report).
7. Pielou, E. C. 1966. The use of information theory in the study of
the diversity of biological populations. Fifth Berkeley Symposium
on Mathematical Statistics and Probability.
8. Shannon, C. E. and W. Weaver. 1963. The mathematical theory of
communication. Univ. Illinois Press, Urbana. 117 p.
9. Simpson, E. H. 1949. Measurement of diversity. Nature 163:688.
10. Sorenson, T. 1948. A method of establishing groups of equal
amplitude in plant society based on similarity of species content.
K. Danske Vidensk. 5:1-34-
39
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11. Taylor, J. E., U. C. Leininger, and R. J. Fuchs. 1975. 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 and A. S. Lefohn, eds.)
Ecological Research Series, U. S. Environmental Protection Agency.
Corvallis, Oregon. In press, pp. 11-39.
40
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SECTION III
EFFECTS OF S02 AND OTHER COAL-FIRED POWER PLANT EMISSIONS
ON PRODUCER, INVERTEBRATE CONSUMER, AND DECOMPOSER
STRUCTURE AND FUNCTION IN A SOUTHEASTERN MONTANA GRASSLAND
by
J. L. Dodd, R. G. Woodmansee, W. K. Lauenroth,
R. K. Heitschmidt and J. W. Leetham
INTRODUCTION
The primary objective of this research is to determine the effects
of coal-fired power plant emissions on the structure and function of a
Southeastern Montana grassland ecosystem, to replicate these effects in
a total system simulation model, and to integrate these results with
those of other program elements to satisfy overall project goals (see
previous chapter of this report, by Lewis, Lefohn, and Glass).
One set of objectives relates to baseline monitoring of four
grassland study sites, near the coal-fired power plant at Col strip
Montana (Hay Coulee, Cow Creek, North Pasture, and School Section) (Taylor,
Leininger, and Fuchs, 1975). After the plant is completed (fall, 1975)
these sites are expected to experience different intensities of atmospheric
pollution. Project objectives for 1974 were designed to characterize
seasonal biomass dynamics of the producer and invertebrate consumer
components of each of these sites in the season prior to first exposure
to power plant emissions. Objectives for 1975 are to determine the
effects of the anticipated atmospheric pollution on these and other
selected ecosystem attributes.
A second series of objectives relates to the experimental field study
located near the Fort Howes Ranger Station in the Custer National Forest.
On this site we will attempt to determine the effects of three levels of
41
-------
S02» a major component of power plant emissions, on the seasonal biomass
dynamics of the producers and invertebrate consumers and on decomposition
rates.
A final set of objectives pertains to the adaptation of the Natural
Resource Ecology Laboratory's ecosystem level simulation model to the
grassland type discussed in previous objectives. The objectives for
1974 were to secure the field information necessary to prepare the model
for simulation of control conditions. Future activities (1975, 1976)
will consist of modifications of the model that will allow simulation of
the dynamics of the Montana grassland under challenge from atmospheric
pollution.
1974 FIELD SEASON PROGRESS
I. Primary Producer Biomass
A. Seasonal biomass dynamics and primary productivity estimates.
This work was completed and is discussed in Appendix A.
B. Phenology
No phenology data were collected in 1974 due to a late starting
date.
C. Species lists
Species lists compiled in 1974 included only those species
occurring in the 0.5 m2 quadrats clipped for aboveground
biomass and were presented in the first interim report.
42
-------
D. Chemical analyses
Tables III-l through III-4 summarize the chemical analyses for
the major herbage components. In addition, all aboveground
plant material is being saved for future analyses. Analyses
for ash content are complete but not summarized; analyses for
total sulfur are in process.
II. Soil Respiration
No soil respiration data were collected in 1974 due to a late
starting date.
III. Decomposition Bags
A. Litter
No litter bag samples were collected in 1974 due to a late starting
date.
B. Cellulose
Sixteen cellulose bags were placed in the field per treatment
(exclosure) in the spring, 1974. Three collections of four bags
per treatment (exclosure) were completed in 1974. These data are
not yet summarized.
IV. Invertebrates
A. Aboveground invertebrates
Samples were collected in conjunction with plant biomass samples.
43
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Table III-l. NITROGEN (N) AND PHOSPHORUS (P) CHEMICAL ANALYSIS OF ABOVERROUND OLD DEAD MATERIAL EXPRESSED IN WEIGHT PERCENTAGE.
TREATMENT-/
ANALYSIS
REPLICATION
Agropyron smithii
MAY
JUN
OUL
AUG
SEP
Stlpa comata
MAY
JUN
JUL
AUG
SEP
J P
2 T
1 ?
~P N .._ P
.600 .057 .585^ .062 .580 .057 .635 .047 .675 .061
.595 .574 .060 .051 .709 .532 .047 .042 .589 .558 .057 .059 .440 .046
.640 .630 .083 .063 .590 .630 .071 .063 .545 .505 .062 .057 .490 .520 .059 .068 .515 .054 .725 .595 .075 .056
548 564 .077 .198 .505 .620 .047 .048 .703 .703 .058 .057
.640 .071
.886
^/Treatment: A, B, C, D, original fumigation plots at Ash Creek; E, Hay Coulee; F, Cow Creek; 6, North Pasture; H, School Section
— Composite sample of replications 1 and 2.
-------
Table III-2. NITROGEN (N) AND PHOSPHORUS (P) CHEMICAL ANALYSIS OF ABOVEGROUND STANDING LIVE MATERIAL EXPRESSED IN WEIGHT PERCENTAGE
TREATMENT-' A B
ANALYSIS N P N P
REPLICATION T 2" T 2" T 2~ T 2~
Agropyron smithil
MAY 1.680 .251
JUN 1.737 .225 2.201 1.675 .239 .231
(1.305) (.2)
JUL 1.385 1.3 .219 .202 1.25 1.34 .177 .204
AUG
SEP
Bromus japonicus
MAY 1.654 .308
JUN 1.466 .284 1.852 .267
JUL
AUG
SEP
Stipa comata
MAY
JUN
OUL 1.24 1.59
AUG
SEP
Koelerla cristate
MAY
JUN
OUL 1.335 1.35 .255 .219
AJG
SEP
C D E f G H
N P N P N P N P N P N P
2.035^ .286 2.435 .253 2.065 .266 2.135 .239
1.633 1.873 .274 .246 1.617 1.325 .235 .176 1.262 1.231 .194 .173 1.09 1.351 .18 .144
1.38 1.295 .201 .188 1.225 1.485 .189 .19 1.16 1.355 .125 .1541.2051.32.168.16
.896 .806 .127 .103 .86 .099 .85 .984 .101 .093 .955 .945.099 .095
1.755 .313 1.420 .255 1.600 .274
1.502 .279 1.367 1.299 .264 .219
1.915 .232 1.820 .235
1.153 1.216 .199 .149
1.2 .16 1.3 1.155 .156 .185 1.215 .177
1.1431.467 .174 .172 1.151 1.102 .162 .157
1 .252 .201
1.236 .174
a/ and b/See notes Table III-l
-------
TREATMENT-'
ANALYSIS
REPLICATION
Stipa comata
HAY
JUNE
JUL
AUG
SEP
Bromus japonicus
MAY
JUN
JUL
; AUG
SEP
Koelarla aristata
MAY
JUN
JUL
AUG
SEP
Bouteloua gracilis
MAY
JUN
JUL
AUG
SEP
.475 .465
.11 .09
Table III-3. NITROGEN (N) AND PHOSPHORUS (P) CHEMICAL ANALYSIS OF ABOVEGROUND RECENT DEAD MATERIAL EXPRESSED IN WEIGHT PERCENTAGE
B C 0 I f
N
N
.,
1.1954'
.132
.533 .53 .079 .078 .685 .783 .102 .113
.855 .897 .174 .173 .746 .736 .157 .139
.870
.597 .618 .089 .074 .497 .476 .067 .065 .677
.592 .068
.59
.546
.088
.069
1.254 .229
1.195
.216 1.179
.173
.100
.978 .081
.77
1.522
.636
.14
.173
.200 1.280 .128
and
-------
Table III-4. NITROGEN (N) AND PHOSPHORUS (P) CHEMICAL ANALYSIS OF ABOVEGROUND LIVE AND DEAD MATERIAL EXPRESSED IN WEIGHT PERCENTAGE.
TREATMENT5/ A
ANALYSIS N P
REPLICATION 1 2 1 2
Bouteloua gracills
MAY
JUN
JUL
AUS
SEP
B C D E
N P N P N P N
1.165^
1.080 1.226
i nfiQ cm
P
.145
.164 .166
•jm n Q
F G
N P N P
1.380 .164 1.145 .137
1.195 .195
1.056 1.150 .183 .219
fl7Q
H
N P
1.105 .155
.955 .127
a/ and b/ See Table III-l
-------
Six sample dates were completed for the Col strip sites and two for
the fumigation system at Fort Howes. Each sample date included 10
o
0.5 m samples per treatment. Laboratory processing is complete.
Preliminary statistical analysis and interpretation of the data are
incomplete. A summary of the data is presented in Tables III-5
through III-8.
B. Belowground invertebrates
/
1. Macroarthropods. Ten soil cores per treatment (exclosure)
were collected on each of the aboveground invertebrate
sample dates. Processing and statistical analysis status
are the same for aboveground macroarthropods. A summary
of the data is presented in Tables III-9 through 111-12.
2. Microarthropods. At this writing (May 1975) all 1974
soil microarthropod samples from both the Col strip
(Treatments E, F, G, H) and the fumigation system (Treat-
ments A, B, C, D) sites have been sorted, identified and
counted. These samples represent five sample dates from
Col strip and three sample dates from the fumigation
system. Project staff have analyzed 320 soil core samples,
5 cm diameter by 10 cm deep (two 5 cm sections/sample).
Data collected on one sample date from Col strip (14 May
1974) have been summarized. Analysis of data from the
remaining sample dates from both Col strip and the fumigation
system sites will be completed soon. With summary infor-
mation from only one sample date available it is impossible
to document soil microarthropod populations at the various
sites for the season. However, the estimated total
microarthropod population numbers and biomass at the four
Col strip sites on 14 May 1974 are: Hay Coulee (Tr. E) —
48
-------
SD
UD
SD
110574
250674
50774
10874
180874
120974
MEAN
T Weight
Mean
UNKNOWN
NO/SQM
110574
250674
50774
10874
180874
120974
MEAN
T Weight
Mean
1.800
2.000
3.000
1.000
5.600
6.000
3.233
2.848
G/SQM
.00133
.00050
.00208
.00004
.00030
.00011
PARASITE
NO/SQM
.400
.800
0.000
0.000
1.000
1.200
.567
.540
.00044
.00109
0.00000
0.00000
.00017
.00070
.00040
Table III-5. SITE AG MACROARTHROPOD DATA SUMMARY
SAMPLE TYPE COL. TREATMENT E
FOR THE YEAR 1974
NUMBERS AND BIOMASS FOR TROPHIC
DEPTH - CM
PLANT TISSUE
NO/SQM G/SQM
400
600
15.400
2.000
4.000
18.600
.00073 8.333
.00073 7.245
800
400
22.200
2.800
.200
2.600
6.333
.02288
.01595
.02231
.01149
.01026
.02192
.11747
.12587
OMNIVORE
G/SQM NO/SQM
.00042 4.964
G/SQM
.00039
.00040
.00497
.00021
.00001
.00065
.00110
.00101
PLANT SAP
NO/SQM G/SQM
4,
21
600
200
38.200
3.000
49.800
4.000
20.133
20.605
NO/SQM
000
600
000
800
600
600
2.100
2.090
.00187
.00858
.01154
.00224
.00851
.00235
.00585
.00604
SCAVENGER
G/SQM
.00687
.00086
.00160
.00717
.00236
.00058
.00324
.00341
PLANT POLLEN
NO/SQM G/SQM
0.000
.600
.600
0.000
0.000
0.000
.200
.223
0.00000
.00062
.00227
0.00000
0.00000
0.00000
.00048
.00048
PREDATOR
NO/SQM G/SQM
2.200
10.400
13.000
2.600
3.800
8.600
6.767
6.617
.00375
.00752
.01346
.00220
.00303
.00229
.00537
.00549
-------
SD
140574
250674
70774
40874
180874
130974
MEAN
SD
140574
250674
70774
40874
180874
130974
MEAN
T WEIGHT
MEAN
Table III-6. SITE AG MACROARTHROPOD DATA SUMMARY
SAMPLE TYPE COL. TREATMENT F
FOR THE YEAR 1974
NUMBERS AND BIOMASS FOR TROPHIC
DEPTH - CM
NO/SQM
2.000
2.400
.200
.600
.600
3.000
1.467
UNKNOWN PLANT TISSUE
G/SQM NO/SQM G/SQM
T WEIGHT
MEAN 1.430
.00046
.00068
0.00000
.00004
.00001
.00007
.00021
.00025
5.200
8.000
4.400
1.800
5.600
8.200
5.533
5.489
PARASITE
NO/SQM
.600
.600
.600
.200
.200
.400
.433
.444
.00030
.00073
.00020
.00015
.00015
0.00000
1.23385
.07199
.06110
.01063
.02063
.02279
.23183
.24105
OMNIVORE
G/SQM NO/SQM
26.000
.600
.800
0.000
.000
.000
0.
2.
.00025 4.900
.00030 4.952
G/SQM
.00527
.00015
.00006
0.00000
0.00000
0.00000
.00091
.00095
PLANT SAP
NO/SQM G/SQM
14.000
23.400
10.400
11.600
20.200
9.400
14.833
.01084
.00876
.00559
.00455
.00368
.00755
.00683
15.603 .00691
SCAVENGER
N)/SQM
2.600
11.000
4.600
1.400
10.000
3.400
5.500
5.879
G/SQM
.00716
.04016
.00678
.00014
.00506
.01175
.01184
.01334
PLANT POLLEN
NO/SQM G/SQM
0.000
2.000
.200
0.000
.200
0.000
.400
0.00000
.00470
.00046
0.00000
.00007
0.00000
.00087
.508
.00113
NONFEEDING
NO/SQM
.200
0.000
0.000
.200
.200
.200
.133
.123
G/SQM
.00004
0.00000
0.00000
.00012
.00012
.00012
.00007
.00006
PREDATOR
NO/SQM G/SQM
800
,000
,400
800
,800
,600
5.233
5.389
.00227
.00754
.01118
.00184
.00269
.00526
.00513
.00521
-------
SD
UNKNOWN
NO/SQM
150574
230674
70774
50874
200874
200974
MEAN
T WEIGHT
MEAN
4.800
3.800
1.200
.600
.600
2.200
2.200
2.197
SD
150574
230674
70774
50874
200874
200974
MEAN
T WEIGHT
MEAN
G/SQM
.00226
.00070
.00031
.00002
.00002
.00009
.00056
PARASITE
NO/SQM
1.400
1.600
.400
.200
0.000
1.400
.833
.816
.00022
.00458
.00193
.00007
0.00000
.00056
Table III-7. SITE AG MACROARTHROPOD DATA SUMMARY
SAMPLE TYPE COL. TREATMENT G
FOR THE YEAR 1974
NUMBERS AND BIOMASS FOR TROPHIC
DEPTH - CM
PLANT TISSUE
NO/SQM G/SQM
13.000
37.000
7.800
3.800
000
12.000
.00057 13.100
1.86301
.04209
.03044
.04112
.02175
.02311
.33692
13.955
.31142
OMNIVORE
G/SQM NO/SQM
45.800
57.800
1.000
.400
2.000
9.000
.00123 19.333
.00139 20.630
G/SQM
.00935
.01008
.00059
.00004
.00107
.00086
.00366
.00391
PLANT SAP
NO/SQM G/SQM
95.800
108.400
11.400
18.200
6.400
26.400
44.433
.02299
.03706
.00866
.00417
.00355
.00488
.01355
46.427 .01458
SCAVENGER
NO/SQM
400
200
200
400
000
200
3.233
3.342
G/SQM
.00782
.01022
.00306
.00033
.00342
.00427
.00485
.00501
PLANT POLLEN
NO/SQM G/SQM
0.000
.400
.200
.200
0.000
.200
.167
0.00000
.00012
.00007
.00007
0.00000
.00007
.00005
.175 .00006
NONFEEDING
NO/SQM
0.000
.200
0.000
.200
0.000
0.000
.067
.076
G/SQM
0.00000
.00007
0.00000
.00012
0.00000
0.00000
.00003
.00004
PREDATOR
NO/SQM G/SQM
13.600
14.600
6.000
4.000
5.000
9.600
8.800
8.851
.00734
.01387
.01037
.00229
.00259
.00870
.00753
.00764
-------
UNKNOWN
SD
110574
230674
50774
30874
200874
130974
MEAN
T WEIGHT
MEAN
SD
110574
230674
50774
30874
200874
130974
MEAN
T Weight
MEAN
NO/SQM
2
9,
11,
2
2,
600
400
000
200
600
6.800
5.767
5.803
G/SQM
.00273
.00736
.00126
.00007
.00004
.00019
PARASITE
NO/SQM
.600
.600
.800
.600
.800
.400
.633
.646
.00011
.00134
.00187
.00019
.00004
.00048
Table III-8. SITE AG MACROARTHROPOD DATA SUMMARY
SAMPLE TYPE COL. TREATMENT H
FOR THE YEAR 1974
NUMBERS AND BIOMASS FOR TROPHIC
DEPTH - CM
PLANT TISSUE
NO/SQM G/SQM
6.600
12.400
15.600
.600
.600
2.
2.
2.200
.00194 7.000
.94378
.02576
.04508
.00931
.02025
.00336
.17459
.00233 7.538
.18075
OMNIVORE
G/SQM NO/SQM
2.000
27.000
2.400
.200
.600
4.200
.00067 6.067
.00071
7.216
G/SQM
.00123
.00494
.00118
.00014
.00032
.00241
.00170
.00180
PLANT SAP
NO/SQM G/SQM
7.200
45.600
11.200
.000
.600
4.
1.
8.800
13.067
.00227
.01711
.00495
.00170
.00052
.00228
.00480
14.950
.00558
SCAVENGER
NO/SQM
,800
.400
,600
,200
,800
,200
4.833
4.295
G/SQM
.00308
.00435
.00833
.00014
.00370
.00131
.00348
.00361
PLANT POLLEN
NO/SQM G/SQM
0.000
.400
0.000
0.000
.200
0.000
.100
0.00000
.00016
0.00000
0.00000
.00009
0.00000
.00004
.121
.00005
NONFEEDING
NO/SQM
.200
0.000
.200
.200
0.000
0.000
.100
.104
G/SQM
.00007
0.00000
.00004
.00012
0.00000
0.00000
.00004
.00004
PREDATOR
NO/SQM G/SQM
4.000
16.200
10.600
.200
.800
.200
3.
2.
6.
7.167
7.634
.00476
.00678
.00362
.00341
.00383
.00655
.00482
.00479
-------
SD
Da Mo Yr
120574
230674
190774
30874
190874
110974
MEAN
T WEIGHT^-7
MEAN
120574
230674
190774
30874
190874
110974
MEAN
T WEIGHT-7
MEAN
UNKNOWN
NO/SQM
24.390
0.000
0.000
8.130
0.000
0.000
5.420
5.231
0.000
8.130
0.000
0.000
0.000
8.130
2.710
3.032
G/SQM
.00463
0.00000
0.00000
.00008
0.00000
0.00000
.00078
.00081
SCAVENGER
0.00000
.00780
0.00000
0.00000
0.00000
.00780
.00260
.00291
Table 111-12. SITE SOIL MACROARTHROPOD DATA SUMMARY
SAMPLE TYPE COL. TREATMENT H
FOR THE YEAR 1974
NUMBERS AND BIOMASS FOR TROPIC
DEPTH 0-15 CM
PLANT TISSUE
NO/SQM G/SQM
32.520
8.130
0.000
8.130
8.130
56.911
18.970
.01935
.00683
0.00000
.00423
.19073
.00472
.03674
15.561 .03670
NONFEEDING
8.130
0.000
0.000
0.000
0.000
105.691
18.970
11.362
.00293
0.00000
0.00000
0.00000
0.00000
.06211
.01084
.00636
PLANT SAP
NO/SQM G/SQM
0.000
0.000
0.000
000
000
8.130
1.355
.776
.00610
.00345
OMNIVORE
NO/SQM G/SQM
0.00000
0.00000
0.00000
0.00000
0.00000
.03659
32.520
0.000
8.130
0.000
0.000
0.000
6.775
6.964
.00813
0.00000
0.00000
.00000
.00000
0.
0.
0.00000
.00136
.00140
— Time weighted mean
-------
Table 111-10. SITE SOIL MACROARTHROPOD DATA SUMMARY
SAMPLE TYPE COL. TREATMENT F
FOR THE YEAR 1974
NUMBERS AND BIOMASS FOR TROPHIC
DEPTH 0-15 CM
SD
Da Mo Yr
120574
230674
190774
70874
190874
110974
UNKNOWN
NO/SQM 6/SQM
PLANT TISSUE
NO/SQM G/SQM
0.000
0.000
0.000
24.390
0.000
8.130
0.00000
0.00000
0.00000
.07569
0.00000
.06333
8.130
16.260
0.000
0.000-
0.000
16.260
MEAN
T WE
MEAN
T WEIGHT-''
SD
120574
230674
190774
70874
190874
110974
MEAN
5.420
3.865
NO/SQM
.02317 6.775
.01559 7.464
OMNIVORE SCAVENGER
40.650
0.000
.000
,000
56.911
113.821
0.
0.
G/SQM
.01333
0.00000
0.00000
0.00000
.01699
.02211
NO/SQI
16.260
0.000
0.000
8.130
8.130
8.130
35.230
T WEIGHT^
MEAN
25.890
.00874 6.775
.00682 5.764
.00683
.01951
0.00000
0.00000
0.00000
.21919
.04092
.02727
G/SQM
.00951
0.00000
0.00000
.00780
.00780
.00780
.00548
.00448
PLANT SAP
NO/SQM G/SQM
PREDATOR
8.130
0.000
0.000
0.000
0.000
0.000
1.355
.00098
0.00000
0.00000
0.00000
0.00000
0.00000
.00016
1.399
.00017
NONFEEDING
NO/SQM
8.130
0.000
0.000
8.130
0.000
0.000
2.710
2.432
G/SQM
.00163
0.00000
O.OOQOO
.02537
0.00000
0.00000
.00450
.00350
NO/SQM
8.130
0.000
0.000
0.000
0.000
0.000
1.355
1.399
G/SQM
.00016
0.00000
0.00000
0.00000
0.00000
0.00000
.00003
.00003
PARASITE
NO/SQM G/SQM
0.000
0.000
8.130
8.130
0.000
0.000
2.710
2:532
0.00000
0.00000
.04341
.00081
0.00000
0.00000
.00737
.00811
—'Time weighted mean
-------
Table III-ll. SITE SOIL MACROARTHROPOD DATA SUMMARY
SAMPLE TYPE COL. TREATMENT G
FOR THE YEAR 1974
NUMBERS AND BIOMASS FOR TROPHIC
DEPTH 0 - 15 CM
UNKNOWN
SD
Da Mo Yr
120574
230674
190774
70874
190874
110974
MEAN
NO/S.QM
0.000
8.130
32.520
0.000
0.000
16.260
9.485
T WEIGHT-/
MEAN 9.796
SD
1 20574
230674
190774
70874
190874
110974
MEAN
PLANT
NO/SQM
0.000
8.130
0.000
0.000
0.000
0.000
1.355
G/SQM
0.00000
.06333
.00033
0.00000
0.00000
.06951
.02219
.02426
SAP
G/SQM
0.00000
.00130
0.00000
0.00000
0.00000
0.00000
.00022
T WEIGHT-7
MEAN 2.266
ROOT TISSUE
NO/SQM G/SQM
0.000
0.000
0.000
16.260
0.000
0.000
2.710
0.00000
0.00000
0.00000
.15935
0.00000
0.00000
.02656
2.066
.00036
NO/SQM
24.390
8.130
8.130
0.000
8.130
8.130
9.485
9.896
.02025
PREDATOR
G/SQM
.00593
.00033
0.00000
0.00000
.00195
.00439
.00210
.00181
ROOT SAP
NO/SQM G/SQM
0.000
0.000
0.000
8.130
0.000
0.000
1.355
1.033
0.000
0.000
0.000
8.130
0.000
0.000
1.355
1.033
0.00000
0.00000
0.00000
.01033
0.00000
0.00000
0.000
8.130
0.000
16.260
0.000
0.000
.00172
.00131
PARASITE
NO/SQM G/SQM
0.00000
0.00000
0.00000
.03837
0.00000
0.00000
.00639
.00487
PLANT TISSUE
NO/SQM G/SQM
0.00000
.01480
0.00000
.04488
0.00000
0.00000
.00995
.00983
4.065
4.332
OMNIVORE
NO/SQM G/SQM
65.041
0.000
16.260
32.520
16.260
32.520
27.100
23.724
.01577
0.00000
.00154
.01154
.00293
.00618
.00633
.00547
SCAVENGER
NO/SQM G/SQM
8.130
0.000
0.000
0.000
0.000
16.260
4.065
2.932
.00780
0.00000
.00000
.00000
.00000
.01561
0.
0.
0.
.00390
.00281
-------
Table III-ll. (Continued)
NONFEEDING
SD NO/SQM G/SQM
0.00000
.00163
0.00000
0.00000
0.00000
.09577
.01623
.00948
120574
230674
190774
70874
1 90874
110974
MEAN
0.000
8.130
0.000
0.000
0.000
164.472
27.100
T WEIGHT^
MEAN
16.827
— Time weighted mean
-------
SD NO/SQM
Da Mo Yr
140574
230674
190774
120874
190874
110974
MEAN
32.520
24.390
16.260
16.260
8.130
24.390
20.325
T WEIGHT^
MEAN
CJl
SD
20.969
NO/SQM
140574
230574
190774
120874
190874
110974
MEAN
T WEIGHT-''
MEAN
0.000
0.000
0.000
8.130
0.000
8.130
2.710
1.829
UNKNOWN
G/SQM
.12764
.09878
.06358
.06951
.06333
.12667
.09158
.09071
NONFEEDING
G/SQM
0.00000
0.00000
0.00000
.07805
0.00000
.00163
.01328
.01024
Table III-9. SITE SOIL MACRQARTHROPOD DATA SUMMARY
SAMPLE TYPE COL. TREATMENT E
FOR THE YEAR 1974
NUMBERS AND BIOMASS FOR TROPHIC
DEPTH 0-15 CM
PLANT TISSUE
NO/SQM G/SQM
8.130
0.000
0.000
8.130
8.130
24.390
8.130
5.759
.00691
0.00000
0.00000
.00423
.00992
.20919
.03837
.02299
PREDATOR
NO/SQM G/SQM
8.130
0.000
8.130
24.390
0.000
0.000
6.775
6.199
.04065
0.00000
.00244
.12195
0.00000
0.00000
.02751
.02304
OMNIVORE
NO/SQM G/SQM
8.130
0.000
8.130
0.000
0.000
0.000
2.710
3.049
.00691
0.00000
.00203
0.00000
0.00000
0.00000
.00149
.00157
I'Tirne weighted mean
-------
131,026.5/m2 for 82.2 mg/m2; Cow Creek (Tr. F)--151,473.5/m2
for 78.4 mg/m2; North Pasture (Tr. G)-110,082.2/m2 for
46.7 mg/m2; School Section (Tr. H)—128,705.5/m2 for 81.2
mg/m2. These populations are much greater than those for
a shortgrass prairie. A similar sampling on 5 May 1972
at the Pawnee Site in Colorado (a shortgrass prairie)
2
gave an estimated population density of 52,499.0/m (19.7
mg/m2) and 39,180.9/m2 (13.0 mg/m ) in ungrazed and heavy
grazed situations, respectively. With the exception of
the North Pasture site, it appears that the Col strip
sites are quite comparable in soil microarthropod popu-
lations. Further comments on the data will be deferred
until all summaries are complete.
V. Soil Description
This work is in progress; completion is scheduled for summer, 1975.
PLANS AND PROGRESS FOR THE 1975 FIELD SEASON
Plans for 1975 field work specify that seasonal biomass dynamics of
primary producers and invertebrate consumers will be measured on six
sample dates (17 April, 16 May, 10 June, 1 July, 1 August and 15 September)
for each of the four Col strip sites and for the four treatments of the
S02 fumigation study near Fort Howes. Methods and procedures will be
the same as for 1974. In addition to the previously mentioned work
(biomass dynamics work, modeling and chemical analysis), soil water,
plant phenology, decomposition, and soils description studies will be
conducted as outlined in the continuation proposal for the 1975-1976
budget year.
58
-------
Field work for 1975 has been initiated. Producer and invertebrate
consumer biomass dynamics measurements are complete for two sample dates
on all eight study sites. The project staff has aided in the establishment
of several weather monitoring stations and the Zonal Air Pollution
System (see subsequent chapter of this report, by Lee, Lewis, and Body).
Summaries and initial interpretation of all 1974 data should be
complete by fall, 1975. Analysis and interpretation of most of the 1975
data from the fumigation study should be available by January, 1976.
59
-------
REFERENCES
1. Taylor, John E., Wayne Leininger, and Ronald Fuchs. 1975. Site
descriptions and effects of coal-fired power plant emissions on
plant community structure. In: The Bioenvironmental Impact of a
Coal-Fired Power Plant. (R. A. Lewis and A. S. Lefohn, eds.).
Ecological Research Series, U.S. Environmental Protection Agency.
Corvallis, Oregon. In press.
60
-------
SECTION IV
INVESTIGATIONS OF THE IMPACT OF COAL-FIRED POWER PLANT EMISSIONS
UPON PLANT DISEASE AND UPON PLANT-FUNGUS AND PLANT-INSECT
SYSTEMS
by
C.C. Gordon
INTRODUCTION
Research on this component of the Montana Coal-Fired Power Plant
Project began August 1, 1974. This report covers the work accomplished
to date on our five main objectives and includes a discussion of the
methodology used in the field and laboratory studies.
The major objective of our project component is to conduct extensive
studies on species of flora and fauna surrounding Colstrip, Montana,
prior to and after two 350-megawatt coal-fired power plants become
operational. The work is to be conducted in such a way that predictive
models can be generated and the results of our investigations can be
integrated with those of the component investigations so that a predictive
impacts assessment protocol can be generated. The first plant is scheduled
to begin boiler testing in August, 1975; commercial generation should
begin in October. Using baseline data gathered by the project investi-
gators and the data collected after the power plants begin operating,
project staff feel that a methodology can be developed that will predict
the impact of coal-fired power plant emissions upon similar terrestrial
ecosystems.
The University of Montana Environmental Studies Laboratory (ESL)
portion of this project is designed to establish the baseline levels
61
-------
of (1) fungal populations (both beneficial and pathogenic), (2) insect
populations (both beneficial and destructive), (3) the sulfur and
fluoride concentrations within selected species of indigenous vegetation
of the Colstrip area, (4) the chemistry of the area's precipitation, and
(5) the growth of the predominant coniferous species, ponderosa pine.
These studies are being conducted on the six primary sites (Figure
II-l) and 14 secondary sites (Figure IV-1; Table IV-1). The 14 additional
sites were established in 1973 for a study the Environmental Studies
Laboratory conducted for the Montana State Department of Natural Resources
and Conservation. Five of the primary sites, located within 10 nautical
miles of Colstrip, are in grasslands that are commonly dominated by
western wheatgrass, needle and thread grass and sagebrush. The other
sites, located within 20 nautical miles of Colstrip, are ponderosa pine
plots in which common associates are skunkbush sumac (Rhus), bluebunch
wheatgrass and ponderosa pine. The primary sites are located at lower
elevations in the Colstrip area; the remaining sites are on ridgetops.
The insect survey and field and laboratory studies are presented in
a separate section of this report by J. Bromenshank.
OBJECTIVE #1
A SURVEY STUDY OF THE INSECTS AND FUNGAL POPULATIONS, INFESTATION,
AND DAMAGE TO INDIGENOUS PLANT SPECIES AT THE STUDY SITES
OUTSIDE AND INSIDE THE IMPACT AREA
As indicated in the introduction, we are using the primary sites
and 14 others in the preliminary survey studies of the fungal and insect
populations. During the last nine months, surveys and collections were
made at: Ash Creek, Hay Coulee, Cow Creek, North Pasture, School Section,
and the relict knolls (A, B, and C).
62
-------
Co
r
ROSEBUD
COUNTY
n
J
YELLOWSTONE %
COUNTY
I
CARTER
Figure IV-1 Vegetation Collection Sites
-------
Table IV-1. VEGETATION COLLECTION SITES IN THE VICINITY OF
COLSTRIP, MONTANA. Also see Figure IV-1.
Site No.
North #4
Northeast #1
Northeast #3
Northeast #4
East #1
East #3
East #4
East #5
Southeast #1
Southeast #3
West #3
West #4
Northwest #3
Northwest #4
Location
Sec.
Sec.
Sec.
Sec.
Sec.
Sec.
Sec.
Sec.
Sec.
Sec.
Sec.
Sec.
Sec.
Sec.
36,
16,
10,
17,
29,
27,
36,
18,
16,
17,
36,
8,
16,
2,
T8N
T2N
T4N
T6N
T2N
T2N
T2N
T2s
TIN
T2S
T2N
T2N
T4N
T5N
9
9
9
9
9
9
9
9
9
9
9
9
9
9
R40E
R42E
R43E
R46E
R42E
R44E
R47E
R55E
R42E
R44E
R37E
R35E
R39E
R36E
64
-------
Vegetation samples from each of these sites were collected three
times since August 1, 1974. A herbarium sample has been prepared for
each plant species collected; those species thus far collected are on
deposit and appropriately labeled at the University of Montana Botanical
Herbarium.
Identification of the insect fauna present on the vegetation
collected from the sampling sites is by Jerry Bromenshenk, entomologist.
C. C. Gordon, plant pathologist and mycologist, is identifying the
fungal species.
The identification of fungi and insects is done almost entirely in
the laboratory. Plant samples with symptoms of fungal disease are
treated as follows:
A temporary microscope slide is prepared of the plant
tissue manifesting the tissue necrosis caused by the
fungus. If the fungus is not an obligate parasite
(a rust or smut), an attempt is made to isolate the
organism by culturing on nutrient media.
To date, using this method 46 cultures of fungal isolates have been
obtained (Table IV-2). Culturing of these fungi and new isolates will
continue throughout the 1975 spring and summer until an adequately
diverse group of fungi is obtained.
Samples of both obligate and saprophytic fungi have been prepared
for histological studies, using the normal procedures of fixing in a
solution of 95 percent ethanol: glacial acetic acid: formal in:water
(126:10:10:54), dehydrating in the tertiary butyl alcohol series, and
mounting in paraffin. Thus far, 54 fungi damaged or infected specimens
have been prepared for microtoming. Sectioning of the materials is
65
-------
Table IV-2. FUNGAL CHECKLISTS OF IDENTIFIED CULTURES
Number
Fungus
Hosts obtained from:
2
3
4
5
8
9
10
n
12
Septoria avenae
Ascohyta agropyrina
Hendersonia sp.
Fusarium sol am'
Penicillium spp.
Aspergillus spp.
Leptosphaeria artemisiae
Phyllosticta sp.
Tubercularia vulgaris
Alternaria sp.
Cladosporium sp.
Verticillium sp.
Agropyron smithii
A. splcatum
Agropyron smithii
Stipa comata
Koeleria cristata
Stipa comata
Agropyron spicatum
Melilotus alba
Agropyron spicatum
A. smithii
Koeleria cristata
etc.
Artemisia cana
A. tridentata
A. tridentata
Symphoricarpos occidental is
Rhus trilobata
Chrysothamnus viscidiflorus
Petalostemon purpureum
Artemisia frigida
66
-------
completed and photomicrographs have been taken of most specimens.
Special emphasis for histological studies has been given to the fungi
parasitizing the grass species since at the NERL stress site, grasses
are the most abundant species.
OBJECTIVE #2
ANALYSIS AND SELECTION OF INDIGENOUS PLANT SPECIES WHICH HAVE
A DIVERSIFIED BUT UNDERSTANDABLE INTERRELATIONSHIP
WITH THE INSECT AND FUNGAL POPULATIONS AT THE STUDY SITE
Histological studies of vegetation collected from the study sites
being parasitized or decomposed by fungal saprophytes were conducted
during the 1974 fall and winter. The studies were not continued in
detail from January to June, 1975 since the scientist who performs this
work was on a six-month sabbatical leave.
In these studies on host-parasite and host-saprophyte relationships
using histological methods, the major concern is to make sure that some
fungi are selected which have exogenous growth habits and some with
endogenous growth habits on their respective host species. While the
available literature regarding the identification of fungal species is
adequate to identify both cultured and sectioned specimens, there is
little discussion in the literature of the host-parasite relationship of
those fungi that we have thus far studied.
During the 1975 summer and fall considerable time will be spent on
inoculation studies with the fungal cultures thus far obtained, and with
the host species grown in the field and at selected collecting sites in
the Col strip area.
67
-------
OBJECTIVE #3
SELECTION^ AND PRETESTING FOR EASE OF IN-VITRO GROWTH AND INOCULATION
STUDIES OF DISEASE- AND INJURY-CAUSING FUNGAL AND INSECT SPECIES
TO BE UTILIZED AT STUDY SITES INSIDE AND OUTSIDE THE IMPACT AREA
Of those fungi species isolated into pure culture and identified so
far, there is a predominance of Moniliales and Sphaeropsidales which
belong to the class Fungi Imperfect! (Deuteromycetes). The species of
Moniliales, especially the isolates of Fusarium, Penicillin! and
Aspergillus, are not known to be strongly parasitic to any of the host
plants from which they were isolated. They are, in fact, likely to be
soil contaminants of the plant. However, several of these Moniliales
isolates are being maintained for inoculation studies this winter.
Species of the Spaheropsidales isolated to date are known pathogens or
saprogens of the hosts from which they were isolated. Three of the
general isolated (Septoria avenae, Phyllosticta sp. and Hendersonia)
have been cited as common saprophytes and/or parasites of indigenous
grasses of the Colstrip area. The isolation, culturing, identification,
and inoculation pretesting of fungi will be a major effort this summer.
OBJECTIVE #4
SELECTION AND PRETESTING OF BENEFICIAL FUNGAL AND INSECT SPECIES
TO BE UTILIZED AT STUDY SITES INSIDE AND OUTSIDE THE IMPACT AREA
See studies of insects.
Fungal studies were not conducted during the last quarter since the
lead researcher was on sabbatical. See discussion of Objectives 1, 2,
and 3 for description of work completed in first two quarters.
68
-------
OBJECTIVE #5
CHEMICAL ANALYSIS OF INDIGENOUS PLANTS, INSECTS AND FUNGI WHICH ARE
SELECTED FOR INTENSIVE INVESTIGATION
DURING SECOND AND THIRD YEARS OF PROPOSED STUDY
I. METHODS
Types and Methods of Vegetation Collection
Each of 14 sampling sites was divided into four subsections for
sample collection. In each subsection, ponderosa pines were identified
as the primary indicator species for air pollution impact; the grasses,
shrubs and/or other vegetation were collected in the immediate
vicinity. Each pine selected at each site was permanently marked with
an aluminum tag containing the sample number. At the NERL sampling
plots where no pines grow, only grasses, shrubs and other vegetation
were collected.
Branches of ponderosa pine (with foliage) were collected from
the top third of the tree on the side of the crown facing Colstrip. The
branches were removed from the tree by shooting them down with a
shotgun.
Grass foliage was clipped at least one inch above ground level.
Shrub foliage was collected by removing those branches holding foliage.
Yucca samples were obtained in the same manner as grasses, and juniper
the same as shrubs.
Immediately after collection, each sample was placed in an
individual plastic sack with a card identifying the sample, collection
date, plot location, and sample number. This information was recorded
in the field diary with other pertinent information. When collection at
69
-------
a given plot was complete, samples were placed in a duffle bag for
transportation to the University of Montana.
As soon as possible after collection, the samples were transported
to the University of Montana. In no case did more than seven days lapse
between collection time and delivery. The average time from field
collection to laboratory was four days. Upon arrival at the University
of Montana, samples were stored in a walk-in cooler.
Preparation of Vegetation for Chemical Analysis
As soon as practical after receipt at the laboratory, the foliage
of each sample was removed according to year of growth in the case of
pines, or as a composite in the case of other plants. Samples were
placed in a paper sack containing the sample number and foliage year, if
appropriate. The samples were either transferred to a forced draft oven
or stored in boxes until oven room was available. After drying under
forced draft for at least three days at 90°F., the samples were ground
in a Wiley mill to pass 40 mesh, placed in a 30 dram vial with an
identifying label, and stored in a plastic sack by site until analyzed.
Each step in the analysis procedure was recorded on a permanent
sample log sheet. This sheet contained the sample number, date
collected, species, collector's name, site, with space for other
observations. Also, the sample type, year of foliage or composite, and
dates dried, ground, and analyzed were recorded on the log. Finally,
the results of all analyses were entered.
Fluoride Analysis of Vegetation
The method of fluoride (F~) analysis of vegetation used in this
study was developed in 1970 at the University of Montana Environmental
70
-------
Studies Laboratory. It incorporates the Orion fluoride specific ion
electrode as the fluoride sensor. The method is precise and rapid, and
the results of comparative studies using other techniques show good
agreement.
Precisely 0.50 g of dried, ground plant material was placed in a 35
ml. nickel crucible with 0.05 g of low fluorine calcium oxide and
slurried with distilled water. The slurry was dried and then charred by
infrared radiation, transferred to a muffle furnace, and ashed overnight
at 600°C. The crucibles were covered during ashing.
When the crucibles were cool, the ash was moistened with distilled
water, dissolved in a minimum of 30 percent perchloric acid, increased
to 100 ml. with 50 percent TISAB, transferred to a plastic beaker,
placed on a magnetic stirrer, and the electrodes inserted into the
stirred solution. The solution was insulated from the heat of the
stirrer with a half inch of sponge and the millivolt (MV) reading was
recorded after the electrodes had equilibrated.
Immediately prior to sample analysis, the electrodes were
calibrated with standard solutions of the following fluoride
concentrations: 0.05, 0.10, 0.50, 1.0, 5.0, 10.0, and 19.0 ppm. A
calibration curve was prepared by plotting millivolt reading as a
function of fluoride concentration on semi logarithmic graph paper, and
the fluoride content of unknowns was determined by interpolation from
the graph and the following calculation:
>1 ., x
Wt. in G.
Samples with fluoride concentrations falling below the useful range
of the calibration curve were treated by adding sufficient fluoride to
bring them into millivolt range. For most plant materials, 1 ml. of a
71
-------
5.0 ppm F" solution was sufficient. Reagent blanks were carried through
the entire procedure with each series of samples.
As an alternative to the manual determination of fluoride concen-
tration of unknowns, the preparation of the calibration curve, the
interpolation and the calculation of the flouride concentration of
unknown samples may be computerized according to the BASIC program.
Sulfur Analysis of Vegetation
The total sulfur (S) content of vegetation was determined by a
combustion iodometric procedure employing a Leco induction furnace to
generate S02 and titration of the S02 with potassium iodate (Laboratory
Equipment Corporation, undated). An aliquot of dried, ground plant
material was weighed into a crucible, tin and iron metal catalysts were
added, and the crucible was placed into the furnace induction field.
The sample was combusted in an oxygen atmosphere to generate S02 which
was bubbled through a solution of iodine and starch. Sulfur dioxide
generated in the furnace bleaches the solution of starch and free iodine
by the following reaction:
S02 + I2 + H20 -* H2S04 = 2HI
The blue color was maintained by titrating the starch solution with
potassium iodate:
KI03 + SKI + 6HCL + 6KC1 + 3I2
The titration continued until S02 generation was complete, as
evidenced by the maintenance of blue color in the starch solution
without adding KI03 (Laboratory Equipment Corporation, undated).
72
-------
Recovery Studies
To determine recovery efficiency of the combustion iodometric
method for the analysis of total sulfur in plant material, three separate
experiments were performed. First, aliquots of potassium aluminum
sulfate were analyzed (Table IV-3). Second, known amounts of thiourea
(NH2CSNH2) were adsorbed onto cellulose to give varying concentrations
of sulfur in cellulose, and these standards were then analyzed (Table
IV-4). Finally, cellulose standards and plant samples were mixed to
determine the effect of plant material on the recovery of sulfur from
the standards (Table IV-5). Sample aliquots of 0.1 g were used to
obtain the data presented Tables IV-4 and IV-5. Preliminary work indicated
that such aliquots of plant material resulted in good combustion without
violence and ready conversion to percent sulfur in the sample. The data
in Table IV-5 show that the lowest recoveries were obtained with the
largest volume of plant material and the smallest volume of cellulose-
thiourea.
The average sulfur content of Pinus foliage collected away from
areas subjected to sulfurous air pollution has been previously reported.
Katz and McCallum (1939) report average total sulfur concentrations of
.09 to .13 percent. Thomas, Hendricks, and Hill (1950) report average
sulfur content in different years' conifer foliage ranging from .10 to
.11 percent. They indicate that organic sulfur in conifers normally is
about .1 percent. The data of Kieley and Lambert (1972) indicate that
sulfate-sulfur in the foliage of Pinus radiata averages less than .025
percent.
These previous studies appear to indicate that species of Pinus
found away from sources of sulfurous air pollution may contain most of
their sulfur as organic sulfur and possibly less than 250 ppm of their
total sulfur as inorganic sulfur. Therefore, the efficiency of recovery
73
-------
Table IV-3. RESULTS OF ANALYSES OF POTASSIUM ALUMINUM SULFATE (KA1(S)4)2)
AS THE SOURCE OF SULFUR FOR S02 GENERATION
Grams S x TO"5 Added Grams S x IP"5 Recovered
46.5 43
46.5 43
46.5 47
36.4 33
30 29
30.3 29
24.8 22
24.2 21
24.6 13
17.8 16
18.2 16
13.5 13
10.7 11
9.4 9
10 9
74
-------
Table IV-4. RESULTS OF ANALYSES OF SYNTHETIC PLANT STANDARDS
PREPARED BY ADSORBING THIOUREA ON PURE CELLULOSE
Ppm S Concentration
Ppm S Concentration in Cellulose-Thiourea
in Cellulose-Tlriourea Recovered by Analysis Average
10000
5000
3000
2500
1500
1000
500
0
9200
4700
4600
4700
2800
2800
3000
2300
2400
2300
1500
1500
1300
900
1000
900
500
500
600
0
0
0
9200
4666
2866
2333
1433
933
533
0
75
-------
Table IV-5. RESULTS OF SULFUR RECOVERY FROM SYNTHETIC PLANT STANDARDS
PONDEROSA PINE MIXTURES
Ppm S in Weight (g)
Cellulose Cellulose
2500 .025
.025
2500 .05
.05
.05
1500 .05
.05
.05
1000 .01
.01
.01
500 .05
.05
Weight (g)
P. Ponderosa
.075
.075
.05
.05
.05
.05
.05
.05
.09
.09
.09
.05
.05
Ppm S
Recovered
2000
2400
2700
2500
2100
1500
1400
1200
800
700
600
500
500
Average
2200
2433
1366
700
500
76
-------
for the combustion iodometric method used in this study was based upon
the results of recovery studies employing cellulose-thiourea standard
and plant sample mixtures.
Because the lowest recoveries were obtained with the largest amount
of plant material relative to the cellulose standard (Table IV-4), a
graph was prepared (Figure IV-2) from which a given analysis of plant
material could be increased by an amount of sulfur reflecting the low
recovery. The recovery results of 2200 ppm S for a 2500 ppm concentration,
and 700 ppm S for a 1000 ppm concentration were used to prepare Figure
IV-2. Thus if a given analysis of plant material resulted in a concen-
tration of 1500 ppm S (X-axis, Figure IV-2), the result to be reported
is 1800 ppm s (Y-axis, Figure IV-2).
Method of Sulfur Analysis
The following method is used in the sulfur analysis process:
Weigh 0.10 g of dried, ground plant material into a combustion
crucible, add 1 scoop of iron and 2 scoops of tin metal. Add
starch and HC1 to the titration vessel, and titrate KI03 until the
endpoint blue color is reached. Record the burette reading. Cover
the crucible and place in the induction furnace. Titrate with KI03
to keep the endpoint blue color until the solution is no longer
bleached. Record the resultant burette reading. Determine the
total sulfur content by use of Equations I and II (below). Report
the results as ppm S.
Equation I:
Percent S = (Final Burette Reading - Initial Burette Reading) - Blank
77
-------
Figure IV-2
Recovery Efficiency of the Combustion lodometric
Method for the Analysis of Total Sulfur. See
accompanying text.
o
o
m
CM
o
o
o
CN|
o
o
0)
H
P4
W
13
0)
O
-------
Equation II:
Ppm S = (Percent S) (10 ) + Increase from Figure IV-2.
II. RESULTS
Four to five separate samples of each species of trees, shrubs,
forbs, and grasses collected from each of the 14 ESL field sites during
the 1974 fall and winter were analyzed for sulfur and fluoride. Over
1100 fluoride and sulfur analyses have been completed since the Second
Quarterly Report on more than 540 samples of vegetation. A tabular
listing of each sample from each site is included in Appendix B. The
fluoride and sulfur analyses completed on Bromenshenk's plant and insect
speciments are reported in another section of this report.
Statistical analysis of the fluoride data accumulated this winter
has been started; new results have not been compared to collections from
previous years at these same sites. However, examination of the 1974
data shows that the mean for any given species will not exceed 4 ppm of
fluoride and that none of the pine samples will exceed 3 ppm of fluoride.
Table IV-6a shows the sulfur data obtained from analyzing vegetation
samples collected at the five primary sites and the Ash Creek site. The
fluoride data for these 40 vegetation samples were reported in the
Second Quarterly Report. However, the sulfur analyses had not been
completed at that time. They are presented in this report in Table IV-
6b.
Comparison and statistical analysis of the sulfur data accumulated
this winter with data from other year's studies are not completed;
results will be reported in the Fourth Quarterly Report.
79
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Table IV-6a.
Sulfur Data from Vegetation Samples Collected
at the Primary Sites and Ash Creek Site.
F#
241 3-A
241 4-A
241 5-A
241 6-A
241 7-A
241 8-A
241 9-A
2420-A
2421 -A
2422-A
2423-A
2424-A
2425-A
2426-A
2427-A
2428-A
2429-A
2430-A
2431 -A
2432-A
2433-A
2434-A
2435-A
2436-A
2437-A
2438-A
2439-A
2440-A
Species
Artemisia ludoviciana
C. viscidiflorus
Artemisia cana
Aristidalongiseta
C. viscidiflorus
Artemisia cana
Aristida longiseta
C. viscidiflorus
A. ludoviciana
Aristida longiseta
Artemisia cana
C. viscidiflorus
Aristida longiseta
Artemisia cana
Artemisia cana
Bromus tectorum
Chrysothamnus viscidiflorus
A. tridentata
Artemisia cana
Bromus tectorum
Andropogon scoparius
Stipa comata
Artemisia cana
Stipa comata
Artemisia cana
Aristida longiseta
Artemisia cana
Aristida longiseta
Location
Ash Creek - 1 acre
Same
Same
Same
Ash Creek - 25 acre
Same
Same
Same
Same
Same
Same
Same
Same
Same
Hay Coulee - 1 acre
Same
Same
Same
Same
Same
Same - 50 yd. North
ii n n n
School Section
Same
Same
School Section
Same
Same
Ppm S
1100
2200
2000
900/1000
1300
1600
700
1400
700
700
2400/2400
1300
700
2400/2500
1800
500
1500
1100
1700
500/500
400/300
600
1600
700
2200
600
2200
700
80
-------
Table IV-6a (Continued)
fi
2441 -A
2442-A
2443-A
2444-A
2445-A
2446-A
2447 -A
2448-A
2449-A
2450-A
2451 -A
2452-A
2453-A
2454-A
2455-A
2456-A
Species
Andropogon scoparius
Artemisia cana
Chrysothamnus viscidiflorus
Second growth medicago
Aristida longiseta
Bromus tectorum
Aristida longiseta
Bromus tectorum
A. frigida
Stipa comata
Bromus tectorum
Aristida longiseta
Bromus tectorum
Aristida longiseta
Bromus tectorum
Aristida longiseta
Location
Relict Knolls
Same
Same
Same
North Pasture
Same
Same
Same
Same
Same
Cow Creek
Same
Same
Same
Same
Same
Ppm S
400
2000
1200
2500/2000
550
500
600/600
800
800
700
400
400
700
600
300
700
81
-------
Table IV-6b. FLUORIDE CONCENTRATIONS IN VEGETATION
FROM COLSTRIP EPA STUDY AREA EXCLOSURES
F£ Species Location Ppm F"
2413-A Artemisia ludoviciana Ash Creek - 1 acre - 5.7
2414-A Chrysothamnus viscidiflorus " " 5.9
2415-A Artemisia cana " " 4.7
2416-A Aristida longiseta " " 2.8
2417-A Chyrsothamnus viscidiflorus Ash Creek - 25 acre 3.6
2418-A Artemisia cana " " 1.7
2419-A Aristida longiseta " " 2.8
2420-A Chrysothamnus viscidiflorus " " 1.7
2421-A Artemisia ludoviciana " " 3.8
2422-A Aristida longiseta " " 3.2
2433-A Artemisia cana " " 4.1
2424-A Chrysothamnus viscidiflorus " " 3.0
2425-A Aristida longiseta " " 1.4
2426-A Artemisia cana " " 3.3
2427-A " " Hay Coulee - 1 acre 4.3
2428-A Bromus tectorum " " 2.6
2429-A Chrysothamnus viscidiflorus " " 3.2
2430-A Artemisia cana " " 3.6
2431-A Artemisia cana " " 3.8
2432-A Bromus tectorum " " 3.1
2433-A Andropogon scoparius " " 2.6
2434-A Stipa comata " " 2.5
2435-A Artemisia cana School Section 2.8
2436-A Stipa comata " " 3.4
2437-A Artemisia longiseta " " 2.5
2438-A Aristida longiseta " " 1.6
2439-A Artemisia cana " " 3.4
82
-------
Table IV-6b (Continued)
F£ Species
2440-A Aristida longiseta
2441-A Andropogon scoparius
2442-A Artemisia cana
2443-A Chrysothamnus viscidiflorus
2444-A Medicago sativa
2445-A Aristida longiseta
2446-A Bromus tectorum
2447-A Aristida longiseta
2448-A Bromus tectorum
2449-A Artemisia frigida
2450-A Stipa comata
2451-A Bromus tectorum
2452-A Aristida longiseta
2453-A Bromus tectorum
2454-A Aristida longiseta
2455-A Bromus tectorum
2456-A Aristida longiseta
Location
School Section
Relict Knolls
North Pasture
Cow Creek
Ppm F"
3.4
1.5
2.5
6.1
1.7
2.7
2.4
3.3
3.9
3.0
2.8
2.1
1.7
1.7
4.6
3.6
2.6
83
-------
Tables IV-7a and IV-7b show the mean average results of sulfur and
fluoride concentrations (as well as highest and lowest values) found in
the various species of vegetation from all sites.
OTHER OBJECTIVES
I. PRECIPITATION CHEMISTRY
Five new automated Wong precipitation collectors were received in
February, 1975. These collectors, however, were not put into operation
until May because of needed modifications. Winter collections for 1974
were not made from the 14 bulk precipitation and 2 Wong collectors
already located in the field. We are now collecting the winter precipi-
tation samples and selected chemical and physical parameters of the
winter samples will be carried out CpH, SO." concentration, fluoride,
and conductivity). While much of the chemistry of the long-term bulk
samples will be totally inconsistent with long-term wet and dry collectors
such as the Wongs, pH, S0»~ concentration and conductivity vary considerably
less than other parameters such as trace metal content (Galloway and
Likens, in preparation). We expect some useful information to emerge
from these analyses. Table IV-8 contains data on pH of rainwater
samples collected during November, 1974.
An ancillary study to determine the measureable pH changes of small
amounts (3/10 ml) of various acid solutions (H,,S04 and HNOJ under
differing humidities and temperatures is underway. This study was
initiated because of the acid deposition-caused damage now occurring on
the basal tissues of ponderosa pine needles at several sampling sites.
A report of this experiment will be included in the next progress report
since this study is short-term (two months) and will be completed soon.
84
-------
Table IV-7a. MEAN, HIGH, AND LOW F" CONCENTRATIONS IN EPA ENCLOSURES
Species
A. ludoviciana
A. cana
A. tridentata
A. frigIda
A. longiseta
C. viscidiflorus
B. tectorum
S. comata
2nd growth medicago
P. ponderosa
J. scopulorum
A. scoparius
A. s pica turn
C. longifolia
R. trilobate
A. tridentata
A. cana
Y. glauca
C. viscidiflorus
C. nauseosus
A. longiseta
S. comata
0. hymenoides
N
2
10
1
1
11
6
7
3
1
'71 65
'72 65
'73 65
'74 65
46
57
68
11
10
16
36
5
6
2
6
10
4
Mean
4.7
3.3
3.6
3.0
2.7
3.9
2.7
2.9
1.7
COLSTRIP SITES
2.6
2.2
2.1
1.6
2.3
2.1
2.2
1.4
1.7
3.6
2.4
1.7
2.8
2.3
1.5
2.5
2.5
High
5.7
4.7
4.6
6.1
3.9
3.4
9.9
5.2
3.7
3.3
4.7
7.2
6.8
2.0
2.6
5.6
6.7
3.1
3.7
2.9
2.9
4.5
4.2
Low
3.8
1.7
1.4
1.7
1.7
2.5
0.8
0.4
0.4
0.2
0.1
0.1
0.2
0.7
1.4
1.8
0.4
0.8
1.7
1.8
1.1
1.3
1.2
85
-------
Table IV-7b. MEAN, HIGH, AND LOW S CONCENTRATIONS IN EPA EXCLOSURES
Species N. Mean High Low
A.
t -----
longiseta
A. cana
A.
A.
A.
C.
B.
S.
A.
2nd
P.
A.
J.
A.
A.
C.
R.
A.
A.
Y.
S.
C.
C.
0.
tridenta
ludoviciana
frigida
vlscidiflorus
tectorum
comata
scoparius
growth medicago
ponderosa ' 71
'72
'73
'74
canas
scopulorum
scoparius
spicatum
longi folia
trilobata
tridentata
longiseta
glauca
comata
nauseosus
viscidiflorus
hymenoides
11
10
1
2
1
6
7
3
2
1
65
65
65
65
36
46
59
67
11
10
16
6
5
12
5
5
4
673
2066
1100
900
800
1483
525
366
366
2250
COLSTRIP SITES
655
677
723
676
2372
641
353
501
609
725
1196
621
941
441
1683
1725
660
.I. m
1000
2500
1100
2200
800
400
400
1000
900
1100
1000
3400
900
800
800
900
1100
1750
850
1400
600
3300
2800
800
400
1600
700
1200
300
300
300
450
400
400
400
1700
400
200
200
400
500
700
400
700
250
500
1000
500
86
-------
Table IV-8. COLSTRIP SAMPLES - RAINWATER*
FALL, 1974
f£ Location jjH.
2458-A Hay Coulee 5.41
2459-A Kluver Home (Wong) 5.46
2460-A School Section 5.06
2461-A McRae Home (Wong) 5.33
2462-A North Pasture 7.06
*Sulfate, conductivity and fluorides have not been tabulated
yet.
87
-------
Because of the strong possibility of more Federal funding (Energy
Research and Development Administration) to this laboratory for precipi-
tation chemistry studies in the Colstrip area, a full-time field collector
will be assigned to the area during the coming year to secure rain
samples. This collector will also obtain rain samples from the NERL
sites and our other EPA-designated sites (see list in First Quarterly
Report). More data on precipitation chemistry will be generated and
recorded in the next NERL progress report.
II. ANNUAL GROWTH INCREMENT, AND NEEDLE AND STEM GROWTH OF PONDEROSA
PINE
During the last winter increment, boring was completed at four of
the primary study sites. Increment boring of ponderosa pine trees at
other sites was not completed because of adverse weather conditions (-
20°F) causing increment bores to break during the sample boring process.
At the four sites, 12 trees were selected and the circumference (at
breast height) and height of each tree was measured. Since the dendro-
chronometer owned by the U. S. Forest Service, was in constant use by
Forest Service personnel during this last winter, no analyses of the
increment bores have been completed. However, the Forest Service assures
us that the instrument will be available this summer and measurements
will be conducted in the near future. Boring will continue this fall on
six more ponderosa pine sites. Stem and needle growth studies will be
carried out this spring and summer on the four sites bored this past
wi nter.
SUMMARY
It is apparent that my staff has placed heavier emphasis on establishing
baseline levels of accumulative phytotoxic substances (sulfur and fluoride)
emitted by coal-fired power plants than on other phases of the study.
-------
We believe that it is important to determine the baseline levels of
these two elements in vegetation, insects and rainwater prior to the
fire-up of Colstrip Unit #1. Then, if and when an impact of emissions
does occur on one or more of our study sites, it might be reflected in
altered chemical content of some components of the ecosystem.
During the 1975 spring and summer, we plan to have one or two more
full-time field collectors to gather samples and data from the Colstrip
sites. It is important to collect as much material as possible prior to
the fire-up of Unit #1 boiler; this effort will have highest priority in
the coming study quarter.
89
-------
REFERENCES
1. Galloway, J. and G. E. Likens. In preparation. Calibration of
collection procedures for determination of precipitation chemistry.
Abstract only. Draft of paper on file at Environmental Sciences
Laboratory, University of Montana, Missoula.
2. Laboratory Equipment Corporation. Undated. Instruction Manual for
Operation of Leco Sulfur Determinators. Form No. 133A. Saint
Joseph, Michigan.
3. Katz, M. and A. W. McCallum. 1939. Effect of Sulfur Dioxide on
Vegetation. National Research Council of Canada, Ottawa.
4. Kieley, J. and Marcia J. Lambert. 1972. Plant and Soil 27(2):233.
5. Thomas, M. D., R. H. Hendricks, and G. R. Hill. 1950. Soil Science
70:9.
90
-------
SECTION V
LICHENS AS PREDICTORS AND INDICATORS OF AIR
POLLUTION FROM COAL-FIRED POWER PLANT EMISSIONS
by
Sharon Eversman
INTRODUCTION AND OBJECTIVES
Two lichen species, a terricolous foliose (Parmelia chlorochroa)
and a corticolous fruticose (Usnea hirta), are undergoing intensive
investigation in this component of the Montana Coal-Fired Power Plant
Project. These two lichen species are those most likely to serve as
indicators of SOp pollution in Southeastern Montana. They are the only
species that are abundant enough for use in the evaluation of the physio-
logical and anatomical functions that might signal pollution stress.
Principal objectives are to: (1) establish secure field and
laboratory baseline information on these two lichens (Parmelia chlorochroa
and Usnea hirta) so that effects of chronic SOp challenge may be determined;
(2) compare relative sensitivities of lichens, native grasses and ponderosa
pine (Pinus ponderosa); and, (3) assess changes in population or community
structure that may result from the power plant emissions. Control data
were recorded during the summer of 1974 and will continue during the
spring of 1975.
To simulate S0? pollution similar to that generated by fossil-fuel
burning facilities, a Zonal Air Pollution (ZAP) System will regulate
sulfur dioxide concentrations on grassland study plots in Southeastern
Montana. Responses of plants and animals to this fumigation will be
assayed to determine the effects of chronic S02 challenge. Then before
and after comparisons can be made between their existing condition and
91
-------
conditions after exposure to the fumigation system and power plant
emissions. Effects of S02 on lichens are expected to serve as sensitive
gauges of SCL pollution.
The lichen study is designed to detect changes resulting from coal-
burning emissions in two major categories—community structure and
sublethal biochemical or physiological changes. Data from the lichen
study will be correlated with information from the pine forest and
grassland communities.
Field Activities
During the late summer of 1974 and spring of 1975, collections were
made of lichen species for identification and preparation of a species
list from Rosebud and Powder River Counties, Montana. The preliminary
list, arranged according to substrate and study area site, is presented
in Table V-l. Using the 2x5 dm Daubenmire plots (Taylor, Leininger, and
Fuchs, 1974) the researchers attempted to establish the canopy coverage
percentage for each species on each grassland study site. Staff estimates
were consistently low when compared with Taylor's estimates. During the
1975 field season the activity will be repeated using a camera.
Adequate growth of Parmelia chlorochroa and Usnea hirta is not
indigenous to the Taylor Creek site, so lichen specimens were transplanted
to the area. Parmelia was collected from a pasture near the site and
placed on the bare ground in each of the four fumigation plots. Ponderosa
pine branches containing Usnea were collected from the divide between
Ashland and Lame Deer, Rosebud County; five branches have been wired
onto steel fence posts, less than one-half meter above the ground, on
each plot. Project staff evaluate the transplants for visible injury,
as well as anatomical and physiological changes caused by exposure to
92
-------
Terricolous
Parmelia chlorochroa
Cladonia s
00
Flugensia fulgens
Buellia epigaea
Collema tenax
Dermatocarpon 1achneum
Squamarina lentigera
LeeIdea decipiens
Toninla coeruleonigrleans
Acarospora schleicheri
Peltigera cam'na
Cornicularia muricata
Lignicolous
Caloplaca aurantiaca
Cyphelium notarsil
Corticolous
Usnea hirta
Hypogymnia physodes
Parmelia subolivacea
P^_ i nf umata
P^ sulcata
P^ ulophyllodes
Alectora sp.
Cetraria pinastri
Saxicolous or muscicolous
Parmelia subdecipiens
Physcia caesia
Hay
Coulee
Table V-l. LICHENS COLLECTED SUMMER, 1974
Harvey
x
x
x
x
x
x
x
x
x
x
Relict
Knolls
Cow
Creek
North
Pasture
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Ash
Creek
x
x
x
x
x
x
x
x
x
x
x
x
Fort
Howes
x
x
School
Section
x
x
x
x
x
x
x
x
-------
the S02 (see subsequent chapter of this report, by Lee, Lewis, and
Body).
Laboratory Procedures
The samples of Parmelia and Usnea are washed with distilled water
and air-dried for at least 48 hours. The thalli are weighed; some are
soaked in acetone for two hours, then reweighed to detect possible
deposition of acetone-soluble compounds (Rao and LeBlanc, 1973).
Respiration rates are determined in a Gilson Differential Respiro-
meter; 250-mg samples of entire lichen thalli are moistened for one hour
with 1 ml of distilled water. The respiration flask, containing 0.5 cc
of 20 percent KOH with a 1.5 x 1.5 cm filter paper wick in the center
well, is wrapped in aluminum foil to obtain the dark respiration rate
for 2 to 3 hours at 20°C. Figure V-l shows results from 11 samples from
one site. Timing for this procedure has been determined; but many
samples are not yet duplicated.
The Analytical Chemistry Laboratory at Montana State University
determined the total nitrogen content of one-gram thai!us samples, using
the Kjeldahl method (Table V-2). Samples from 1975 have not been
analyzed. The Soils Testing Laboratory measured total sulfate sulfur
content of 1974 (Table V-2).
The chlorophyll absorption spectrum was determined for 1974 samples
using the Rao and LeBlanc method (1966). However, this method does not
separate chlorophylls a_ and b^, and pheophytins as precisely as desired.
A 90 percent acetone extraction method, used in algal chlorophyll
analyses, will be employed this year (Strickland and Parsons, 1972).
After grinding in 90 percent acetone, the thallus material is centrifuged
and the supernatant is sampled in a Beckman DU spectrophotometer.
94.
-------
Figure V-l Lichen Respiration Rates
OJ
O
30
60 90
TIME (min)
120
95
-------
Table V-2. NITROGEN AND SULFUR CONTENTS (%DRY WEIGHT) OF 1974 SAMPLES OF
PARMELIA CHLOROCHROA AND USNEA HIRTA
01 01
% lo
Nitrogen Sulfur
Parmelia chlorochroa
Hay Coulee A 0.72% 0.274
B 0.73 0.248
Cow Creek A 0.82 0.224
B 0.75 0.210
North Pasture 0.73 0.199
School Section 0.77 0.255
Ash Creek A 0.227
Harvey A 0.230
Usnea hirta
Ash Creek trees 1.52
Ashland-Lame Deer Divide 1.70 0.442
96
-------
Project staff feel that these five characteristics—thai!us weights,
respiration rates, total nitrogen content, total sulfur content, and
chlorophyll analyses—along with the field photographs and micro-
photographs should provide valid bases for comparisons between the
unexposed Parmelia and Usnea, and those samples subjected to the SO^ on
the ZAPS site and in study areas that will be affected by the power plant
emissions.
97
-------
Future Activities
In addition to Usnea and Parmelia collection and laboratory tests,
two native grasses and needles from Pinus ponderosa will undergo the
same battery of laboratory analyses to determine relative sensitivities
of the lichens and the plants in the same plant communities as the
Parmelia (grasses) and Usnea (ponderosa pine). If enough specimens of
other epiphytic lichens are available, they will be included in the same
series of analyses.
Identification of collected species is continuing for characterization
of the various lichen communities in the area.
98
-------
REFERENCES
1. Rao, D. N. and F. LeBlanc. 1966. Effects on the lichen algae of
sulfur dioxide with special reference to chlorophyll. Bryologist
69:69-75.
2. Rao, D. N. and F. LeBlanc. 1973. Effects of sulfur dioxide on
lichen and moss transplants. Ecology 54(3):612-617.
3. Strickland, J. D. H. and T. R. Parsons. 1972. A Practical Handbook
of Seawater Analysis. Fisheries Research Board of Canada. Ottawa.
pp. 186-196.
4. Taylor, J. E., W. Leininger, and R. Fuchs. 1975. Site descriptions
and effects of coal-fired power plant emissions on plant community
structure. In: The Bioenvironmental Impact of a Coal-Fired Power
Plant. (R. A. Lewis and A. S. Lefohn, eds.). Ecological Research
Series, U. S. Environmental Protection Agency. Corvallis, Oregon.
In press.
99
-------
SECTION VI
PHYSIOLOGICAL RESPONSES OF VEGETATION
TO COAL-FIRED POWER PLANT EMISSIONS
by
David T. Tingey, Richard W. Field and Lucia Bard
INTRODUCTION
The objective of this aspect of the research was to conduct pre-
liminary exposures of native plants from Southeastern Montana to sulfur
dioxide.
METHODOLOGY
The plants described in Table VI-1 were grown during January 1975
with day/night temperatures of 24/18°C on a photoperiod of 12 hr of light
and 12 hr of dark (12L 12D). Maximum light intensity was 200 micro-
-2 -1
einsteins m~ sec" at 400-700 nm (1 microeinstein is equal to 6.023 x
10 photons). The grasses were propagated by division and the Fringed
Sage Wort by cuttings. These were planted in 225 ml styrofoam cups
containing a 2:1 (v:v) mixture of perlite: Jiffy Mix. Plants for all
studies were grown in greenhouses, watered daily with a modified Hoagland
solution, and periodically leached with water. Tables VI-2 and VI-3
contain data from plants grown during March and April at day temperatures
ranging from 24-30°C, night temperature 18°C, a daily photoperiod of 16L
2 1
8D, and light ranging between 350 and 500 microeinsteins m sec .
100
-------
Table VI-1. THE EFFECT OF SULFUR DIOXIDE ON THE FOLIAR
INJURY OF NATIVE PLANT SPECIES-7
Species SO^ Concentration (ppm)
1.0 1.5 2.0
Western Wheat Grass 555
Agropryon smithii
Idaho Fescue 0 4 13
Festuca idahoensis
Prairie June Grass 038
Koeleria cristata
Needle and Thread Grass 0 4 18
Stipa comata
Fringed Sage Wort 6 31 50
Artemisia frigida
— Plants were exposed for 4 hr; foliar injury was assessed 96 hr
following exposure. The injury was assessed as the percentage of the
leaf area showing S02 injury. Each mean was based on 6 observations,
S- = 2. Exposure conditions were: Temp. = 24°C; light = 200 micro-
-2 -1
einsteins m sec .
101
-------
Table VI-2. THE EFFECT OF SULFUR DIOXIDE ON THE FOLIAR
INJURY OF NATIVE GRASSES OF MONTANA^
Species
Western Wheat Grass
Idaho Fescue
Prairie June Grass
Needle and Thread Grass
S02 Concentration
0.5
0
0
0
0
0.75
0
0
0
0
1.0
0
0
3
5
(ppm)
1.5
19
33
16
17
— Plants were exposed for 4 hr and foliar injury was assessed 96 hr
after exposure. The injury was measured as the percentage the
leaf area showing SOp injury. Each mean was the average of three
observations. S- = 3. Exposure conditions were: Temp. = 26°C;
21
light = 475 microeinstein m sec .
102
-------
Table VI-3. SULFUR DIOXIDE INDUCED FOLIAR
INJURY OF NATIVE PLANT SPECIES-/
Species
Western Wheat Grass
Idaho Fescue
Prairie June Grass
Needle and Thread Grass
SOp Concentration
0.75 1.0
0 0
0 0
0 0
0 0
(ppm)
1.25 1.5
1 1
0 3
0 0
0 0
* ' DT a *!+•*• i.fs\v-»s\ s\\sr\e ,f f\A -P/"\v* A Inv* 9 nsJ -ff\ "1 T a v» n«"4iiv*\/ i.o c* ^e-fr\cte't*tr\ Q(\ hv»
after exposure. The injury was assessed as the percentage of
the leaf area showing S02 injury. Each mean was based on four observations,
S- = 2. Exposure conditions were: Temp. = 24°C; Light = 360
-1 -1
microeinsteins m sec .
103
-------
Sulfur dioxide exposures were conducted in single pass exposure
chambers (Heck, Dunning, and Johnson, 1968). Sulfur dioxide diluted in
nitrogen was metered into the exposure chambers at a rate sufficient to
maintain the gas phase concentration. The sulfur dioxide was measured
with a Melpar photometric sulfur dioxide analyzer. Prior to each
exposure the analyzer was calibrated with a Monitor Lab's dynamic
calibrater containing an S02 permeation tube. The plants were exposed
to sulfur dioxide about four weeks after transplanting. Leaf injury was
assessed 96 hr following exposure as the percentage of leaf area showing
sulfur dioxide injury. The standard error for leaf injury was calculated;
visual estimates of injury do not permit further statisical analysis.
RESULTS
Description of injury (Figures VI-1, VI-2, VI-3). For Western
Wheat Grass, Idaho Fescue, Prairie June Grass and Needle and Thread
Grass, the sulfur dioxide injury was similar. Injury on young leaves
developed at the leaf tip, on older leaves injury usually occurred at
the bend of the leaf. Injury frequently occurred as small bifacial
lesions. As severity increased the lesions coalesced and spread down
the leaf or out from the bend of the leaf. Interval streaks of necrotic
tissue were frequent. Lesion color ranged from light tan to ivory. On
Fringed Sage Wort the injury appeared to occur on the middle-aged leaf
tissue as a bifacial collapse of the tissue, killing both veins and
interveinal areas (Figure VI-4).
Relative Sensitivity. The data shown in Table VI-1 for the five
species were for plants grown under conditions of low light intensity
and relatively cool temperatures. Data in Tables VI-2 and VI-3 were
obtained from plants grown under a light regime of 16L 8D—a higher light
intensity. This procedure could account for some of the observed
differences in sensitivity. Only the Western Wheat Grass and Fringed
104
-------
Figure VI-1 Western Wheat Grass Exposed to l.Sppm S02 for 4 Hours.
The injury is characterized at nectrotic leaf tips and
bifacial necrotic lesions at the bend of the leaf.
105
-------
Figure VI-2
Western Wheat Grass Exposed to 1.5ppm S02 for 4 Hours.
The injury is shown as "bifacial" necrotic lesion
between the veins. In places the lesions have coalesced.
106
-------
Figure VI-3
Needle and Thread Grass Exoosed to 2Dnm SCL for
4 Hours. The injury symotoms are similar to
Figure VI-2.
107
-------
Figure VI-4
Fringed Sage Wort Exposed to Ippm SCL for
4 Hours. The injury is bifacial necrosis of
the lower and middle aaed leaves of the plant.
The injury appears as the lightest color leaf
tissue in the photograph.
108
-------
Sage Wort exhibited injury below 1.5 ppm S02 for 4 hr. Data presented
in Tables VI-2 and VI-3 indicate there was no injury below 1 ppm for 4
hr. The injury threshold for Western Wheat Grass appeared to range
between 1 and 1.25 ppm SCL• For Idaho Fescue the threshold was approxi-
mately 1.5 ppm; for Prairie June Grass and Needle and Thread grass the
injury threshold appeared to be between 1 and 1.5 ppm. Based on limited
data, the threshold for Fringed Sage Wort was approximately 1 to 1.25
ppm.
In general, available data suggest that Western Wheat Grass and
Fringed Sage Wort are somewhat more sensitive than the other three
species tested.
DISCUSSION
The injury observed on the native species was similar to that
previously described (Barrett and Benedict 1970; Hill, Hill, Lamb, and
Barrett, 1974). Injury thresholds suggested for the species tested in
our experiments do not take into account the effect of soil water potential
on plant sensitivity. Low soil water potential could reduce plant
sensitivity.
Davis, Howell, and Morgan (1966) reported that levels of sulfur
dioxide that might be expected around Phelps Dodge smelters in Arizona,
and which would defoliate cocklebur, did not injure blue gramma. Hill
et al. (1974), working with established native plants in the field,
showed that species of Agropyron cam'nun and A_._ desertorum required
between 6 and 10 ppm S02 for 2 hr to cause visual injury. This suggests
that these two species of Wheat Grass are more tolerant of S02 than
Western Wheat Grass. Hill watered the plants for a month prior to
exposure to ensure that they were in a stage of rapid growth and thus
highly sensitive. He also reported that Stipa occidental is required 10
109
-------
ppm SCL for 2 hr to induce visual injury. This suggests that Stipa
occidental is is more tolerant than Stipa comata which showed injury of
both 1.5 and 2 ppm SCL for 4 hr.
110
-------
REFERENCES
1. Barrett, T. W. and H. M. Benedict. 1970. Sulfur dioxide. C1-C17
In: Recognition of Air Pollution Injury to Vegetation. A Pictoral
Atlas. (J. S. Jacobson and A. C. Hill, eds.). Air Pollution Control
Association. Pittsburgh, PA.
2. Davis, C. R., D. R. Howell and G. W. Morgan. 1966. Sulphur dioxide
fumigations of range grasses native to southeastern Arizona.
Journal of Range Management 19:60-64.
3. Heck, W. W., J. A. Dunning and H. Johnson. 1968. Design of a
single plant exposure chamber. DHEW, National Center for Air
Pollution Control, Publication APTD-68-6. Cincinnati, OH. 24 pp.
f
4. Hill, A. C., S. Hill, C. Lamb and T. W. Barrett. 1974. Sensitivity
of native desert vegetation to S02 and to SOp and N02 combined.
Journal Air Pollution Control Association 24:153-157.
Ill
-------
SECTION VII
INVESTIGATION OF THE EFFECTS OF COAL-FIRED POWER PLANT EMISSIONS
UPON INSECTS, REPORT OF PROGRESS
by
Jerry J. Bromenshenk
INTRODUCTION
/
This section discusses the progress on the insect studies subsequent
to the First Interim Report of December, 1974 (National Ecological
Research Laboratory, 1975). The objectives referred to below correspond
to those elaborated by C. C. Gordon in a preceding chapter of this
report.
OBJECTIVE #1
Field surveys of insect populations, infestations, and damage to
indigenous plant species at the study sites were initiated on August 1,
1974. They were terminated in late October, 1974, and resumed in mid-
May, 1975. Initiation of the 1975 field work coincided with the appearance
of those insect species considered to be most important, both to the
goals of this study and to the ecosystems of Eastern Montana. Selection
of species for individual study was based on (1) insect surveys performed
in 1974; (2) plant samples that were collected during this same period
and subsequently examined for insects and damage; and (3) an intensive
review of the literature concerning insects and air pollution relations.
Handling of plant and insect samples, survey methods and analyses are
discussed in an earlier report (Gordon, 1975).
112
-------
This phase of the project utilizes all of the principal study
sites, together with the 14 sites described in an earlier chapter of
this report by C. C. Gordon as well as 15 apiaries (Figure VII-1). Four
additional apiaries are being sampled: one near the town of Rosebud to
the north, one near Broadus to the east, one at Fort Howes Ranger Station
to the south, and one near Biddle to the southeast. Since the Colorado
State University research group is sampling vegetation and insects on
the NERL sites, this phase is concentrating on the other sites to avoid
redundancy. However, I have examined the primary sites and am monitoring
population trends of the western harvester ant, Pogonomyrmex spp.
Honeybees will be used in experiments at the field experimental site on
Taylor Creek (see the chapter of this report by Lee, Lewis and Body).
Insect pests of ponderosa pine constitute a major insect-plant
system of ecologic and economic importance to the Col strip area.
Population and damage studies begun in August, 1974, revealed several
types of insect damage to needles, cones, and woody portions of the
pines. Statistical analyses of the damage sustained by foliage are
based on samples of 100 needles per tree for each year of growth. Cone
damage is computed as the percent total cones damaged per tree as
indicated by the cones on the branch samples. The materials and methods
for this work follow those of Carlson, Bousfield and McGregor, (1974).
Insect damage to most of the trees was slight or low. At some
sites, many or all of the cones were damaged by larvae of cone beetles
(Conophthorus spp.) and cone moths (Laspeyresia spp. and Dioryctria
spp.). Tree vigor (damage) ratings and cone injury data are presented
in Table VII-1. Insects that attack cones reduce or destroy seed crops
but usually do not seriously harm the trees. High variability of the
cone injury data indicated that the sample size was probably not adequate
for establishing baseline damage levels. Similar difficulties with
variability occurred with evaluations of damage by other species of
113
-------
Figure VII-1 Honeybee Collection Sites.
APIS MIUIKRA
(HONtYBIE)
COILECTION SITIS
N I Spr«fv* cr«*k
114
-------
Table VII-1. INSECT DAMAGE TO PONDEROSA PINES AT 13 SITES
TREE DAMAGE AND CONE DAMAGE
(Preliminary data, subject to revision and possible enlargement
of data base before 1975 growth)
Tree #
F1495
F1490
F1485
F1480
F1475
F1050
F1055
F1060
F1065
F1070
F1770
F1765
F1760
F1755
F1750
F1200
F1205
F1210
F1215
F1220
F1300
F1305
F1310
F1315
F1320
Site
SE-1
Tree Damage
(0 low - 4 high)
Per Cent Total Cones Damaged
(Cone beetles
and Cone Meths)
SE-3
W-3
W-4
N-4
X = .08
SD = .27
0
0
0
0
0
0
-
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
X = 33.35
SD = 30.65
61
40
88
68
0
6
0
27
0
0
50
57
40
43
8
0
14
11
22
5
5
0
46
7
33
115
-------
Table VII-1 (Continued)
Tree #
Site
Tree Damage
(0 low - 4 high)
F1575
F1580
F1585
F1590
F1595
F1850
F1855
F1860
F1865
F1870
F1825
F1830
F1835
F1840
F1845
F1275
F1280
F1285
F1290
F1295
F1250
F1255
F1260
F1265
F1270
F1225
F1230
F1235
NE-3
n
n
n
n
NE-1
n
n
n
n
E-l
n
n
n
n
E-3
n
n
n
it
E-4
n
n
n
M
M
M
n
Per Cent Total Cones Damaged
(Cone beetles)
and Cone Moths)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
40
83
0
0
43
19
19
78
8
24
8
56
64
46
17
21
0
100
16
—
n
0
0
6
0
—
6
26
116
-------
Table VII-1 (Continued)
Per Cent Total Cones Damaged
Tree Damage (Cone beetles
Tree # Site (0 low - 4 high) and Cone Moths)
F1240 NW-3 0 87
F1780 " 0 79
F1785 " 0 92
F1790 " 0 75
F1795 " 0 42
F1350 NW-4 1 83
F1355 " 1 50
F1360 " 1 46
F1365 " 1
F1370 " 0 100
117
-------
insects such as weevils that attack the needles, although to a lesser
extent. However, for most insect damage, such as that incurred from
scale insects, needle and sheath miners, defoliators, and bark beetles,
and for the tree vigor (damage) evaluations, the sample size appeared to
be adequate.
Many types of injury are characteristic of a particular species or
at least a family of insects. Since the samples were obtained in the
fall of 1974, many of the damaging insects were no longer visible on the
plants. Confirmation of the identification of the specific insects
responsible for the damage must be made at the time insects are feeding.
Completion of the baseline insect populations and damage of ponderosa
pines relies on surveys and collections to be conducted this spring and
summer. This work started in May. The number of treees sampled per
site has been doubled to minimize variability due to sampling error.
The sites will be visited several times during the field season to
observe the insect populations while injury is occurring, and preliminary
analyses of injury will be conducted at the sites rather than in the
laboratory to avoid damaged artifacts such as chlorosis of needles
caused by storage.
OBJECTIVE #2
Plant-insect systems which have a diversified but understandable
interrelationship were selected on the basis of the survey work and
literature review described in Objective #1. The systems selected for
more intensive investigations are listed in Table VII-2. These are
concerned primarily with pests of ponderosa pines and with beneficial
insects, mainly pollinators.
Damage syndromes caused by insects such as some scales, aphids,
weevils, needle midges, and "mites" may resemble that of air pollution
118
-------
Table VII-2. INSECT SPECIES SELECTED FOR STUDY
Pollinators
Apis mellifera L,
Bombus spp.
Nomia melanderi
Osmia spp.
Honeybee
Bumblebee
Alkali bee
Leaf-cutter bee
Forest Pests
Neophasia menapia Felder & Felder
Phaeoura mexicanara (Grote)
Ips pini (Say)
Ips calligraphus (Germar)
Dendroctonous valens Lectone
- Dendroctonous ponderosae Hopk.
Eucosma spp.
Rhyacionia spp.
Cicididae
Buprestidae
Itonididae
Cerambycidae
Dioryctria spp.
Laspeyrsia spp.
Phenacaspis pinifoliae (Fitch)
Conophthorus Hopk.
Curculionidae
Pine butterfly
Pine looper
Pine engraver
Pine engraver
Red turpentine beetle
Mountain pine beetle
Pine-shoot borer
Shoot and tip moths
Cicadas
Flatheaded borers
Gall midges
Roundheaded borers
Coneworm
Cone or nut moth
Pine-needle sacle
Cone beetles
Weevils
Miscellaneous insects
Melanoplus spp.
Pogonomyrmex spp.
Grasshoppers
Harvester ant
119
-------
but can be differentiated by dissection and histological examinations
(Anderson, 1970). Specimens of insect damage to pine needles have been
prepared for histological sectioning using formaldehyde-ethanol-acetic
acid fixation as described in an earlier section of this report by C. C.
Gordon. Histological investigations are in progress and should help us
to distinguish insect damage from other types of damage such as that
produced by pollution or fungi. C. C. Gordon is conducting histological
studies of fungal parasites and host plant species. Previously he
conducted histological studies of several types of air pollution damage
to pine needles.
OBJECTIVE #3
Selection and pre-testing of insects for inoculation studies of
injury-causing insect species were conducted during the winter. A
laboratory population of Malanoplus bivittatus, a grasshopper species,
was established (Figure VI1-2). Methods of rearing various pine pests
in the laboratory were investigated and tested. In general, rearing of
pine insects depends on providing the insect with its preferred food
such as boughs of foliage for needle damaging insects and bolts of wood
for bark beetles. Use of synthetic diets was considered unrealistic in
terms of the objectives of the present study. We are currently rearing
several species of pine pests in the laboratory, including the pine
needle scale, Phenacaspis pinifoliae (Fitch); weevils, Pissodes spp.;
needle midges, Contarinia spp.; and bark beetles Ips spp. and Dendroctonus
spp. (Figure VII-3). These insect populations will be used in laboratory
fumigation experiments as soon as adequate numbers have been established-
sometime this summer. I shall continue to collect insects for laboratory
rearing.
120
-------
Figure VII-2 Laboratory Population of Malanoplus bivittatus,
121
-------
10
ro
Figure VII-3 Laboratory Colonies of Various Pine Pests,
-------
OBJECTIVE #4
The selection and pretesting of beneficial insect species to be
used at study sites and in the laboratory has primarily involved honeybees.
Approximately 3,000 honeybee colonies are maintained in the Fort Union
Basin. Each October 1,000 colonies are transported to California to
pollinate orchard crops; the colonies are returned in May. The bees and
bee products from this region, at a conservative estimate, comprise a
$240,000 to $300,000 enterprise. According to Floyd Moeller, research
leader of the North Central States Bee Laboratory, the actual value of
honeybees as pollinators may be more than twenty times that of the honey
product. This means that the honeybees in Southeastern Montana may be
worth $4.5 million as pollinators of rangelands and agricultural lands
and an additional $500,000 to $1 million as pollinators of California
crops. (Data based on marketable honey yields from 1,200 colonies in
the Fort Union Basin, confidential report.) In addition to honeybees,
native bees are plentiful and may be capable of meeting the pollination
needs of the Fort Union area. However, evidence indicates that the
native bees, especially the physically smaller species, may be much more
susceptible to pollutant toxicosis than honeybees (Johansen, 1971).
Manageability and the numbers of honeybees in the study area make
them an excellent subject for study. Hopefully, they will be indicative
of the population trends of other pollinators. Native bees such as
leaf-cutter bees, wild honeybees and bumblebees will be used for compar-
ative studies.
Field experiments are now in progress to evaluate physiological and
behavioral responses of honeybees to controlled exposures of sulfur
dioxide (see Lee, Lewis and Body, present report). Two colonies (50-
100,000 bees per colony) have been established near the SO,, stressing
plots. In addition, two observation hives (Figure VII-4) will be used
123
-------
ro
-P*
feeding hole
comb
frame t
secure glass
protective cover
entrance
entrance funnel
Figure VII-4 Glass-walled Observation Hive.
-------
to monitor the activities of bees within hives. I am particularly
interested in dance patterns which may be altered by sublethal exposures
to pollutants. The glass-walled observation hives are readily movable
and may be used in a variety of positions such as up, down or cross-wind
directions; near or far from the plots; and possibly on the plots.
Feeding stations will be established on the plots, primarily to determine
if differing visitation patterns occur in response to the S02 emissions.
A ferrous-metal tag capture-recapture technique (Gary, 1971) will
be applied where appropriate for distribution, movement and flight range
studies of bees. Coded metal tags are glued to the bee's abdomen.
Later, these labels are retrieved using magnets at strategic locations.
The system was tested this spring and appears to work well. For example,
tags from honeybees marked at feeding stations could be retrieved at
hive entrances. If bees are tagged as they leave the hive, the tags
will be retrieved at the first collection point visited by the foraging
bees. Total counts of bees visiting specific locations may be estimated
by this method. However, either direct observations or some means of
mechanically counting bees such as by a photo-cell must be utilized for
inclusive counts. The proposed budget for the next fiscal year has
requested funds to construct some photo-cell counters. For the current
season, direct observation and counts that can be made by walking a
transect will be used.
A possible source of physiological and behavioral variability is
the genetic composition of the bee populations that are under investigation.
To minimize data variations resulting from genetic differences, the
colonies at the ZAP plots will be stocked with queens of similar genetic
constitution. These queens will convert the colonies to the "same"
genetic composition. Queens have been received from the U. S. Department
of Agriculture Bee Breeding and Stock Center of Baton Rouge, Louisiana.
Two-way sister hybrid queens artificially inseminated with sperm from
125
-------
drones of a single inbred line were obtained in mid-May, 1974, and
introduced into eight colonies near Broadus, Montana. These colonies
will be used to stock the hives at the ZAP plots as soon as the queens
have become well established and the colony has reached a healthy,
vigorous condition.
OBJECTIVE #5
Chemical analyses of indigenous plants and insects which were
selected for investigation and sampled in the fall of 1974 were completed
during the winter, 1974. Dr. Gordon has reported methods and results of
the vegetation analyses in a preceding chapter. Honeybees were sampled
in October and again in mid-May and will be sampled twice this season
for chemical analyses.
Adult honeybees were collected with an electric vacuum apparatus
from 11 apiaries in October and from three apiaries in mid-May (most of
the colonies were too weak from overwintering to test until June).
Three one-pound honey jars filled with bees were obtained from each
apiary. Each sample contained specimens from at least four colonies and
held from 500 to 15,000 bees. The specimens collected in October were
analyzed for fluoride and sulfur; the results are presented in Table
VII-3. The assays demonstrated a mean fluoride (F~) content of 7.4 ppm
dry weight and a standard deviation of 3.1 (Table VII-3). Concern has
been expressed by other investigators that the levels of F" in the bees
varied three-fold among the sites; however, the content of F~ in the
honeybees from the Fort Union Basin appears reasonable as a baseline
figure. Carlson and Dewey (1971) reported 10.5 ppm F~ in bees from a
control "clean" area in Northwestern Montana, while bees collected near
an aluminum reduction facility at Columbia Falls, Montana, contained 221
ppm F".
126
-------
Table VII-3
CHEMICAL ANALYSES OF ADULT HONEYBEES
(APIS MELLIFERA)--AUTUMN, 1974
Distance (Miles)
& Direction
From Col strip
ppm Fluoride
(dry weight)
6
17
15
14
11
- 8
ro
4
4
8
8
10
12
.8
.0
.0
.5
.4
.8
.2
.2
.8
.0
.0
.0
N
NE
NE
NE
E
SE
S
S
S
S
S
SW
X = 7.4
SD = 3.1
4
7
5
15
6
10
5
5
11
5
6
5
.8,
.8,
.5,
.5,
.4,
.1,
.2,
.8,
.2,
.9,
.7,
.5,
5.
6.
5.
15
5.
8.
5.
7.
10
6.
7.
5.
6
6
5
.
5
0
0
5
•
2
2
0
8
8
CHEMICAL ANALYSES OF ADULT HONEYBEES
(APIS MELL IF ERA)—AUTUMN, 1974
Distance (Miles)
& Direction
From Col strip
6.8 N
17.0 NE
15.0 NE
14.5 NE
11.4 E
8.8 SE
4.2 S
4.2 S (C)
8.8 S
8.0 S
10.0 S
12.0 SW
X = 4392
SD = 286
ppm Sulfur
(Dry Weight)
4400, 4800
4600, 4800
4000, 3800
4200, 4400
4000, 4400
4800, 4600
4400, 4800
4400, 4400
4600, 4600
4200, 4400
4400, 4400
4000, 4000
-------
The literature indicates that honeybees rapidly accumulate fluoride
(Figure VII-5). Maurixio (1955-56) found that dead honeybees obtained
from apiaries near industrial areas contained 50-1120 ppm F", while
control bees contained 040 ppm F". Dreher (1965) suggested 10 yg per
bee as the average threshold of toxicity. Note that the baseline levels
of F" in plants reported earlier in this report indicate that a three-
fold difference within and between species of vegetation is not uncommon.
Bees also must obtain water for drinking. Thus, because of their
mobility, utilization of different plant species, and possible contact
with fluoride in water as well as respiratory intake, bees from different
locations would be expected to have differing fluoride levels. However,
the F~ content of bees from Eastern Montana should be relatively low in
comparison to that of bees in polluted areas. At present the Fort Union
area is relatively free of air pollution.
Fluoride uptake in honeybees may occur through (a) pollen, (b)
water, (c) nectar, (d) honeydew, (e) bee products (honey and wax), and
possibly (f) respiration. Water does not appear to be a major source of
fluoride in the study area. Well and surface waters in the Col strip
vicinity contain 0-0.5 ppm F", with a mean of approximately 0.2 ppm F"
(unpublished data, Bureau of Mines and Geology, personal communication
by Robert B. Hedges). Pollen, honey, live bees, and dead bees will be
collected and chemically analyzed to monitor the environmental routes of
F~ transport into bees. While nectar and honeydew may be sources of F",
efficient methods of collecting these materials have not been identified,
although it is possible to analyze entire flowers. Pollen will be
collected this summer using pollen traps—wire grids placed in front of
hive entrances. Bees must enter the hive by squeezing through the wires
which brush pollen from the "pollen baskets" into jars or trays below
the grids (Figure VII-6).
128
-------
cu
-------
Figure VII-6 Pollen Trap.
A Entrance-exit
(opened when pollen-trap
is not being used)
B Pollen-trap
(removable)
C Pollen-collector
D Dead-bee-collectors
E Ventilation opening
F Normal hive entrance
cm
130
-------
An electric vacuum has proven to be the most effective method of
collecting live bees, while a dead-bee trap (Figure VII-6) will be used
to capture "abnormal" or dead bees. An open-ended box is fitted over
the hive entrance. Honeybees entering or leaving the hive are forced to
walk across the floor of this box. Two 9" funnels attached to pint jars
are set flush into the floor of the apparatus. Housecleaning bees
remove debris or dead or abnormal bees from hives. Light debris is
carried away by flight and dropped at a distance away from the hive.
The funnels of the dead-bee-trap are an impassable barrier. Either the
housecleaning bee will drop its burden into the funnel, or the bee and
its load will slide down the funnel into the jars, whereupon the live
bee flies back out. The smooth surface of the funnels and the jars
prevent the housecleaning bees from emptying the bottles. Bees that die
away from the hive cannot be collected with the dead-bee-trap, but data
for studies such as quantitative mortality chemical analyses, and
disease investigations may be obtained with a minimum expenditure of
time and labor by the researcher.
Bee products such as honey and wax are easily obtained from the
hives for analyses. These products may be an important source of re-
introduction of contaminants since the stored food reserves are ingested.
Honeybees from the Col strip Area are transported to California each
winter and returned to Montana in the spring. The stored reserves of
these colonies may contain any number of pollutants. For this reason,
36 hives will be left at six sites in Eastern Montana for sampling
purposes.
Sulfur analyses (Table VI1-3) demonstrated a mean of 4,392 ppm dry
weight and a standard deviation of 286. Sulfur occurs as a natural
portion of animal tissue and there appears to be a question of whether
or not it accumulates, although exposure to S02 at 8.2 ppm for three
weeks increased the sulfate in honeybee haemolymph by a significant
131
-------
amount (Gunnison, 1970). Currently, the information contained in the
literature about sulfur in bees is inadequate and conflicting. Sulfur
analyses will be conducted on bees, bee products and forage materials as
indicated above for fluorides. Sulfur may affect acetylcholinesterase
levels in bees. Therefore, Robert A. Lewis, animal physiologist,
intends to conduct acetylcholinesterase analyses on bee tissue. One of
the three samples from each apiary has been sent to Robert A. Lewis.
This work is not yet complete.
Last summer, 700-800 bee colonies died from pesticide poisoning in
the Fort Union Basin. Pesticides may be a serious, confounding factor.
In cooperation with this project, Ronald Thomas of the EPA Biological
Investigations Laboratory is conducting pesticide analyses of bees. The
third sample taken from each apiary is sent to him. The results of the
pesticide analyses of the bees collected in October are presented in
Table VII-4. Bees from seven sites contained residues of organochlorine-
type pesticides, although no carbamates or organophosphate pesticides
were found in any of the samples. The levels of pesticides detected
were low. The analytical methodology used in the analyses of these
samples were those outlined in the FDA Analytical Manual for chlorinated
insecticides (e.g., DDT, DDE), phosphate pesticides (e.g., malathion,
parathion), and carbamate pesticides (e.g., sevin, carbofuran). All of
the methods used were sensitive to approximately 0.01 ppm. Screening
procedures utilized gas chromatography, thin layer chromatography, and
gas chromatography in conjunction with mass spectrometry.
Studies of the toxicity of industrial pollutants to bees often
present contaminant content as a unit of mass or weight per one bee
rather than per unit of mass or weight of bee tissue. Therefore, wet
and dry weights of bees obtained from Colstrip are presented in Table
VII-5 so that a comparison can be made to other reports.
132
-------
Table VII-4. HONEYBEE SAMPLES CONTAINING RESIDUES OF ORGANOCHLORINE-
TYPE PESTICIDES*
BSE-1 0.02 ppm DDE
A-l
BNE-3 Trace DDE (<0.01 ppm)
A-l
SE-1 0.02 ppm DDE/ODD
A-1C
BE-1 Trace DDE (<0.01 ppm)
A-l
BS-1 0.02 ppm DDE
A-l
BSW-1 0.025 ppm DDE
A-l
BNE-5 0.01 ppm DDE
A-l
*Source: U. S. EPA, TSD-Chemical and Biological Investigations Laboratory,
Beltsville, Maryland
133
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Table VII-5. WEIGHTS OF ADULT WORKER HONEYBEES (APIS MELLIFERA)
gm dry
gm wet weight/ grin wet weight/ gm dry weight/ weight/
F# 500 frozen bees bee 500 oven-dried bees bee
2403-A
2404-A
2405 -A
2406 -A
2407 -A
2408-A
2409-A
241 0-A
2411 -A
241 2-A
45.253
43.434
42.856
46.065
48.609
48.582
47.291
45.903
46.589
46.275
0.091
0.087
0.086
0.092
0.097
0.097
0.095
0.092
0.093
0.093
14.999
14.029
14.037
16.263
15.351
17.544
15.290
14.273
15.665
15.061
0.030
0.028
0.028
0.033
0.031
0.035
0.031
0.029
0.031
0.030
X = 0.092 X = 0.031
S = 0.004 S = 0.002
134
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Emphasis of this aspect of the Montana project will continue to be
placed on baseline levels of accumulative toxic substances (sulfur and
fluorides) in vegetation and insects prior to the shake-down operations
of the Col strip power plants. Also, efforts have been made to establish
baseline levels of insect damage to ponderosa pine, one of the more
susceptible plants to phytotoxic air pollutants, and for which there is
evidence that insect infestations may correlate with physiological
weakening of the trees due to air pollution (Carlson, Bousfield and
McGregor, 1974). It is also possible that predators and parasites of
these pine pests may be reduced in numbers or eliminated by toxicosis.
Finally, emphasis has been placed on work with honeybees, an insect that
because of its morphological and behavioral specialization for foraging
widely and collecting pollen and other particulates, may be one of the
insects most sensitive to pollution effects.
During the spring and summer of 1975, the high priority objectives
will be to collect as much baseline data as possible from the Colstrip
sites before the power plants begin operation.
The insect studies should contribute to an understanding of the
plant-insect-fungal relations of both the grassland and forest ecosystems
of Southeastern Montana. The information about responses of pollinators
to air pollution stress should be invaluable to the other studies being
conducted on plant diversity, plant productivity, and energy flow relations.
The Colorado research group has concentrated on inventories of the
insect and other arthropod fauna and on consumer, producer, and decomposer
relations. This study contributes information about insect population
trends, behavior, and physiology, as well as following pathways of air
pollutants through an insect system: honeybees. In addition, our work
with the pine forest ecosystems contributes to an area not being invest-
igated by any of the other research groups, yet is a prominent component
of the Eastern Montana ecosystems.
135
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While conducting research and development activities during the
winter months, 1974-75, it became apparent that insect systems are very
sensitive to pollution stress and respond in diverse ways. For example,
some insect populations increase while others decrease or disappear.
Insects appear to be valuable indicators of environmental quality.
Economically and ecologically, insects have a great impact on a region.
Pollinators, primarily because of pesticide poisoning, but also because
of other toxic pollutants, are in short supply in many areas of the
United States. This affects not only the natural ecosystems, but also
vital food supplies. California orchard and produce growers import bees
from Montana and North Dakota to meet their minimum pollination require-
ments. Yet honeybees cannot replace native pollinators. For example,
37 species of native insects are capable of pollinating onions, but
honeybees are not very effective (telephone conversation, March 14,
1975, Dr. Frank D. Parker, USDA, Bee Biology and Systematics Laboratory,
Logan, Utah). Approximately one-third of the total United States diet
is derived, directly or indirectly from insect pollinated crops (McGregor,
1973).
At workshop sessions of the Western Institute of Forest Insect and
Disease held in Monterey, California, March, 1975, interactions of air
pollution, insects, and disease on forest ecosystems repeatedly were
discussed, particuarly regarding problems in California and Northwestern
Montana. Unfortunately, adequate information concerning these problems
is lacking.
Telephone interviews conducted during the winter indicate the
research projects concerning insects and pollution in the United States
except for the NERL project are almost non-existent. Studies must be
initiated to clarify the relationships of insects and air pollution. A
bibliography of the literature concerning air pollution and insect
pollinators has been included for use by other investigators (see
136
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Appendix C). A more inclusive discussion of the relations of insects
and air pollution appear in a paper delivered at the Fort Union Coal
Field Symposium in Billings, Montana, April, 1975. This paper appears
as Appendix D of this report.
137
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REFERENCES
1. Anderson, R. F. 1970. Relation of Insects and Mites to the Abnormal
Growth of Christmas Trees in the Mt. Storm, West Virginia—Gorman,
Maryland, Vicinity. Report for the U.S. EPA Air Pollution Control
Office, Division of Abatement, Durham N.C.
2. Carlson, C. E., W. E. Bousfield, and M. D. McGregor. 1974. The
Relationship of an Insect Infestation of Lodgepole Pine to Fluorides
Emitted from a Nearby Aluminum Plant in Montana. U.S. Forest
Service, Division of State and Private Forestry, Northern Region.
Report No. 72-203. 1-21.
3. Carlson, C. E. and J. E. Dewey. 1971. Environmental Pollution by
Fluorides in Flathead National Forest and Glacier National Park.
U. S. Forest Service, Division of State and Private Forestry,
Northern Region. Report No. 72-203. 1-57.
4. Dreher, K. 1965. Fluorvergifteungen bei bienen. Bull. Apic. Inf.
Docum. Scient. Tech. 8(2)-.119-128.
5. Gary, N. E. 1971. Magnetic retrieval of ferrous labels in a
capture-recapture system for honeybees and other insects. J. Econ.
Entomol. 64:961-5.
6. Gordon, C. C. 1975. Effects of coal-fired power plant emissions
on plant disease and on plant-fungus and plant-insect systems. In:
The Bioenvironmental Impact of a Coal-Fired Power Plant. (R. A.
Lewis and A. S. Lefohn, eds.) Ecological Research Series, U. S.
Environmental Protection Agency. Corvallis, Oregon. In press.
138
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7. Guilhon, J. 1961. Atmospheric pollution by sublimated fluorines.
Origin. Revue Ass. Prev. Pollution Atmospherique. 3(4):260-272.
8. Gunnison, A. F. 1970. Biological effects of sulfur dioxide on
animals, emphasizing the interaction of sulfite with the noncellular
fraction of the blood. Ph.D. Thesis, The Penn. State University,
Pennsylvania. 151 pp.
9. Johansen, C. A. 1971. Toxicity of field-weathered insecticide
residues to four kinds of bees. Env. Ent. 1(3):393-394.
10. Maurixio, A. 1955. Plant disinfectants and industrial waste
gases, the cause of bee poisonings. Schweiz. Landwirtschaftliche
Monatshefte 33:159-166.
11. Maurixio, A. 1956. Bee Poisoning in Switzerland by Industrial
Waste Gases Containing Fluorine (Bienen-vergiftungen mit Fluorhaltigen
Industrieabgasen in der Schweiz). XVI Int. Beekeep. Congr.
Prelim. Sci. Meet.
12. McGregor, S. E. 1973. Insect pollination—significance and research
needs. Am. Bee Jour. 113(7):249, (8):249-295, (9):330-331.
13. National Ecological Research Laboratory. 1975. The Bioenviron-
mental Impact of a Coal-Fired Power Plant: First Interim Report,
Col strip, Montana—December 1974. (R. A. Lewis and A. S. Lefoh,
eds.}. Ecological Research Series, U. S. Environmental Protection
Agency, Corvallis, Oregon. In press.
139
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SECTION VIII
THE EFFECTS OF COAL-FIRED POWER PLANT EMISSIONS ON
VERTEBRATE ANIMALS IN SOUTHEASTERN MONTANA
(A REPORT OF PROGRESS)
by
Robert A. Lewis, Martin L. Morton and Susan C. Jones
INTRODUCTION
To address the overall goals of the Montana Coal-Fired Power Plant
Project (Lewis, Lefohn and Glass, 1975) we are attempting to identify:
(a) those populations (or taxa) of birds and mammals in the study area
that are most sensitive to air pollution; (b) those species, systems,
and functions that may serve as specific, "noise-free" indicators of
pollution (e.g., physiologic control systems); (c) population components
that may serve as a measure of impact in the sense that they themselves
are ecosystem resources or are coupled to ecosystem resources. We shall
attempt to relate, if possible, functions of types (b) and (c) to evolve
extrapolative or predictive models. We hope to determine the extent of
pollution-related effects on small mammal and bird populations in the
study area, and if possible, to distinguish between direct and indirect
air pollution effects and effects of other human activities that might
tend to confound our results (e.g., effects of coal-mining, water use,
increased human population density, use of herbicides and pesticides,
etc.).
Major objectives of the vertebrate animal investigation are to:
1. Measure and predict change in population structure and/or dynamics
of selected species of birds and mammals as a function of air
pollution, endogenous and exogenous cycles, and other environmental
information including relevant biotic interactions and physical
factors.
140
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2. Evaluate physical and biotic factors that influence the dynamic-
structural processes under investigation.
3. Identify, if possible, specific pollution effects on animal popu-
lations or systems.
4. Identify physiologic and population functions that contribute to
the regulation of selected populations and evaluate the mechanisms
whereby such regulation is effected, so that we may better interpret
the causes of changes. We may thus increase our understanding of
pollution-related effects and the confidence in our output.
5. Evaluate certain physiological, biochemical, and behavioral functions
that may have potential for sensitive assay of pollution challenge.
We hope to identify low levels of pollution stress before serious
or irreversible effects occur.
Animal response to air pollution challenge varies seasonally, as a
function of resource availability, as a function of sex and age, and in
response to secondary stress from diverse sources (e.g., high population
density, disease, competing or interacting populations, other pollutants).
Consequently, this work relies heavily upon baseline evaluation of
annual cycle and life cycle phenomena and the mechanisms that regulate
such functions. We hope that appropriate analysis of the temporospatial
relationships of observed changes in animal function can be related to
those of other ecosystem components that are under investigation (e.g.,
plant community structure) so that predictive relationships can be
established.
141
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Based on our interpretation of the literature of environmental
physiology, toxicology, and to a lesser extent upon health related studies
of air pollution effects, we anticipate that power plant emissions may
affect almost all levels of animal organization, However, we do not
know the "threshold" exposure rates that might be expected to produce
various biological effects. This naivete" (coupled with the low pollution
levels anticipated from the facility under investigation) has strongly
conditioned our approach. Thus, the investigation is based more upon
the application of what we believe to be sound biological principles
than upon the application of the results of air pollution science or of
health effects studies.
The very limited literature (to be reviewed in a later publication)
that deals with the effects of low levels of pollutants from coal-fired
power plants on animals is, nevertheless, encouraging and suggests that:
1. Some birds may be especially susceptible to gaseous emissions
from coal-fired power plants.
2. Dispersion of animals about a stationary source, in response
to air pollution, may change within a very short time.
3. At low levels of pollution, transient effects are likely to
occur.
4. Birds are especially sensitive during the breeding season; the
longer the breeding season, the greater the damage sustained.
5. Changes in organ weights occur in response to ambient pollution
levels that are well below present standards. For example, in
one study, increased weights of liver, kidneys, spleen and
adrenal glands occurred (starting at 30 days) in white rats
142
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exposed to polluted air containing S09, SO, mist, and airborne
C. O
dusts at very low concentrations (i.e., 0.034-0.077 ppm, 6.7-
9.5 yg/tn and 0.076-0.128 mg/m3, respectively). Clean room
controls did not exhibit these changes. The increase in liver
weight was transient.
6. Protein metabolism is altered at very low pollution levels in
some animals; a negative nitrogen balance may be induced. For
example, in one study, flue gas (mixed with air) with an S00
3
concentration of 1 mg/m produced a decrease in liver protein
of guinea pigs.
7. Lung damage occurs in some birds at low pollutant levels.
This is apparently due in part to the poor filtering ability
of the nasal passage. Doves in polluted areas (Japan) sustain
far greater lung damage than humans.
8. Chronic low levels of NO impair lipid metabolism of guinea
J\
pigs and may exert an arteriosclerotic effect.
9. Acetylcholinesterase (blood and liver), ascorbic acid (liver,
lung, and perhaps other organs), spleen dehydrase, and carbo-
hydrase concentrations may provide sensitive measures of air
pollution in terrestrial vertebrates.
10. Species of vertebrates vary widely in their responses and
sensitivities to air pollution. The standard laboratory
animals maintained under good conditions of housing and
nutrition are possibly much less sensitive to pollutant-
induced stress than some of the more sensitive feral animals.
143
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The scope of work is such that not all components can receive the
same intensity of effort. Components are listed below in order of
decreasing priority:
I. Reproductive and developmental biology.
II. Measures of condition, physiologic stress, homeostasis, and
adaption.
III. Population biology.
IV. Histological cycles of organ-systems of potential or probable
concern.
V. Niche selection and resource utilization.
VI. Experiments.
Briefly, the reproductive and developmental portion of the study
focuses on the description of the annual reproductive cycles of a small
set of indigenous species together with the growth and development of
young to include information on bioenergetics, productivity, and the
regulation of reproductive processes and of postnuptial molt (birds).
The species of primary concern are the Mourning Dove (Zenaldura macroura),
Western Meadowlark (Sturnella neglecta), Lark Bunting (Calamospiza
melanocorys), Vesper Sparrow (Pooecetes gramineus), Lark Sparrow (Chondestes
grammacus). Deer Mouse (Peromyscus maniculatus), and Prairie Vole (Microtus
ochrogaster). The second or physiological component treats a number of
types of functions, notably those that reflect condition and vigor of
the animals and their stress responses. The third phase of the investi-
gation treats population processes and some of the mechanisms that
effect population adjustments (e.g., fecundity, mobility). The fourth
phase, the evaluation of histological cycles, is designed to
144
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support the other components. Since it is impossible to fully anticipate
which tissues or organ systems may be most affected by chronic pollution
challenge, we are maintaining a tissue bank of the major organs that
might be expected to show involvement.
Laboratory experiments will be conducted to test field-generated or
model-generated hypotheses and/or to identify specific pollution effects
suggested by observed field responses.
REPRODUCTION AND DEVELOPMENT
The reproduction component of this investigation overlaps and
supports the population component. The reproductive and life cycles are
of special and independent concern. We feel that significant impairment
of animals at the population level will be reflected in altered repro-
ductive performance and/or developmental patterns.
The reproductive cycle of North Temperate Zone vertebrates is, in
general, the best characterized of the annual subcycles. Furthermore,
regulatory mechanisms are fairly well known (Farner and Lewis, 1971;
Lewis and Orcutt, 1971; and Sadlier, 1969). We are thus in an excellent
position to assess the effects of air pollution on reproductive functions.
Lowered maturation rates to the time of nest departure of altricial
birds and rodents, by whatever agency (e.g. air pollution), would
increase the period of time that the young remain in the nest and their
period of dependence upon parental care. They would thus be exposed to
relatively high predation rates for a longer than normal period and also
both the parents and the young might suffer a competitive disadvantage
during and immediately following departure from the nest.
145
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Immature mammals and birds may be especially sensitive to pollution.
Furthermore, rates of growth and development can be easily related to
several functions under study in other components of the Montana Coal-
Fired Power Plant Project (see the introductory chapter of this report
by Lewis, Lefohn, and Glass). Our study of development is restricted to
a few indigenous bird and mammal species and treats the following:
1. Growth and maturation rates and phenology.
2. Biometry of growth.
3. Growth and development in relation to:
a. Plant community structure and change.
b. Climate
c. Nutritional environment.
d. Pollution concentrations.
e. Molt progress and intensity.
4. Caloric and nitrogen balance as indicators of condition and
/
ability to obtain and utilize nutritional resources.
5. Covariance of the above functions with physical environmental
factors and air pollution gradients.
CONDITION, STRESS, ADAPTATION AND DISEASE
This phase of the vertebrate research deals with a number of
functions and systems that may be expected to reflect the health and
condition of the animals under investigation. Of particular interest
are the following:
146
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1. Bioenergetics (to include body weights, body composition
[water, lipid, etc.], growth rates) and nutritional biology.
2. Adrenocortical system and responses to stress (e.g., general
adaptation syndrome of mammals).
3. Immunobiologic responses (e.g., blood and reticuloendothelial
system responses).
4. Disease and histopathology.
5. Behavior patterns (e.g., mobility, territorial behavior, niche
utilization, etc.).
The measures of condition that we employ are regulated functions.
That is, they tend to be maintained within relatively narrow limits at
any given stage of the annual cycle. Such functions are, of course,
frequently age- and sex-dependent. We expect some of these to provide
relatively stable frames of reference against which environmental
impacts can be measured.
To the extent that time and resources permit, food habits (mammals
and birds) will be evaluated in order to establish whether observed
effects are mediated by the nutritional environment. To this end, we
are collecting seeds in the study area. Our seed collection to date
consists of specimens of 17 species provided by John E. Taylor (Montana
State University). This reference collection will be extended by us
during the coming season.
POPULATION BIOLOGY
In this component we are attempting to assess changes in population
147
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size and structure of several indigenous species as a function of
mortality, recruitment rates and life cycle functions. Ultimately, we
would like to be able to predict changes in any or all of these as a
function of pollution intensity. Also, we would like to determine the
growth potential of the populations of concern. That is, we would like
to establish the capacity of these populations to tolerate, or to
recover from, challenge (especially from air pollutants) or perturbations
that alter life functions and thereby tend to reduce the population or
alter its composition.
/
Because of the relatively low signal-to-noise ratio in many population
dynamic functions, we may expect the short-term chronic effects of air
pollutants on population parameters to be small relative to natural
and/or random variation. Appropriate sensitive analysis requires: (a)
a pollution gradient across study sites (mammals and perhaps birds); (b)
employment of reference sites that will allow us to estimate variations
both between and within years (birds and mammals); (c) investigation and
characterization of responses that may be pollution specific (birds and
mammals); (d) investigation of associated functions that may represent
deviations from the normal pattern or the phase-shifting or uncoupling
of normally coupled phenomena; (e) evaluation of changes in population
structure rooted in a study of annual cycle and life cycle components
(e.g., time-based changes in sex and age structure, breeding success,
etc.).
HISTOLOGICAL CYCLES OF ORGAN-SYSTEMS OF POTENTIAL OR PROBABLE CONCERN
A system of tissue banking has been initiated; several tissues and
organs of the animals collected in the field are fixed and routinely
embedded. As pollution-sensitive species and tissues are identified,
appropriate specimens will be stained and examined histologically.
Organ-systems of probable importance include the respiratory system,
148
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blood, adrenocortical system, reticuloendothelial system, liver, and the
reproductive system.
NICHE SELECTION AND RESOURCE UTILIZATION
We have undertaken a quantification of major niche (habitat)
dimensions on the mammal trapping grids. Prairie voles and deer mice
occur together on all grids (i.e., are captured at the same trapping
stations). Our analysis will include food habits (analysis of fecal
pellets); shrub density; foliage profile diversity; extent of "aboreal"
habitat and depth of the perennial grass mat.
Ground data will be augmented by high resolution (color or color-
infrared aerial photography and the identification and mapping of the
vegetation.
PROGRESS TO DATE
Collections of small mammals and birds using standard mark and
release methods were initiated at five stations situated from 8-24 km
from the plant.
Birds were trapped at fixed stations (1974) by the use of four 12
meter mist nets that are set at dawn and usually operated until noon.
Birds captured were banded with U.S. Fish and Wildlife Service numbered
bands, weighed, examined for sex, breeding condition (degree of development
of the brood patch; cloacal protuberance) molt, ectoparasites, and then
released at the site of capture. A total of 318 birds, representing 33
species, were banded and released. Of these, only 6 percent (two species)
occurred at all of the netting stations and only 30 percent were present
at more than one site (Table VIII-1). Because of personal limitations
and the relatively high cost/benefit ratio, this component of the animal
investigation has been discontinued.
149
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Table VIII-1.
BIRD SPECIES BANDED AND RELEASED
Species Number % Total
1. Vesper Sparrow 80 25.3
2. Lark Sparrow 78 24.7
3. Western Meadow!ark 22 7.0
4. American Robin 20 6.3
5. Red Crossbill 19 6.0
6. Yellow Warbler 17 5.4
7. Savannah Sparrow 14 4.5
8. Catbird 10 3.2
9. American Redstart 7 2.2
10. American Goldfinch 6 1.9
11. Red-winged blackbird 5 1.6
12. Mourning Dove 4 1.3
13. Eastern Kingbird 4 1.3
14. Lark Bunting 4 1.3
15. Red-shafted flicker 3 1.0
16. House Wren 3 1.0
17. Downy Woodpecker 2 0.6
18. Starling 2 0.6
19. Black-headed Grosbeak 2 0.6
20. Yellow-brested chat 2 0.6
21. Brewer's blackbird 2 0.6
22. Brown-headed Cowbird 1 0.3
23. Roufous-sided Towhee 1 0.3
24. Red-eyed Vireo 1 0.3
25. Brown Thrasher 1 0.3
26. Audubons Warbler 1 0.3
27. Loggerhead Shrike 1 0.3
28. Red-headed Woodpecker 1 0.3
29. Black-capped Chickadee 1 0.3
30. Bullocks Oriole 1 0.3
31. Western Flycatcher 1 0.3
32. Winter Wren 1 0.3
33. Ovenbird (1 unhanded) 1 0.3
TOTAL: 318 individuals, 33 species
150
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A standard roadside census of birds, conducted from April through
September at semimonthly intervals, continues. This census is patterned
after the widely employed North American Breeding Bird Survey (Robbins
and Van Velzen, 1970). The census route is depicted in Figure VIII-1.
We expect this census to provide fairly sensitive data on changes in
species diversity; changes in relative and absolute abundance; changes
in dispersion in relation to the coal-fired power plant at Colstrip; and
supplemental information on sex and age ratios, productivity and the
annual calendar of some species. Based upon the combined results of
netting and censusing, the most abundant and widely-distributed grassland
bird species that breed in the study area are the Western Meadowlark,
Vesper Sparrow and Lark Sparrow (Tables VIII-1 and VIII-2).
In addition, bird specimens are collected via shotgun at various
locations both within the study area (but never closer than one mile
from the sites where live animals are studied) and in reference areas in
Rosebud and Powder River counties.
Bird specimens collected by shooting are used for carcass analysis
and histological study. Five species are specifically sought: the
Vesper Sparrow, Lark Sparrow, Western Meadowlark, Mourning Dove, and
Lark Bunting. Immediately following collection, organs or tissues that
are to be assessed histologically are removed (in the field) and placed
in the appropriate fixative. The carcass is then placed in a sealed
plastic bag and retained in an ice chest for no more than a few hours.
Upon return to the field laboratory, the carcass is immediately weighed
on a O'haus dial 0-gram balance with an accuracy of +. 0.05 g and placed
in five nested plastic bags and retained in a freezer at -5°C until
shipment via air freight in dry ice to the Corvallis laboratory where
the specimens are processed as soon as possible. The bird collections
are generally made twice weekly.
151
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Figure VIII-1. Map of the Rosebud-Col strip roadside census route (birds).
I06°45'
T. 2 N.
T. 2 N.
I06°45
R. 41 E.
0 2
R. 42 E.
6 I06°30
R. 43 E.
MILES
152
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Table VIII-2 Road-Side Census Rosebud-Colstrip
6 May, 1975, 0532-1215 hr
-SPECIES-
-STATIONS-
Sparrow Hawk
Red-tailed Hawk
Marsh Hawk
Rouqh-1 egged Hawk
Rinq-necked Pheasant
Sharp-tailed Grouse
Mourning Dove
Poor-will
Common Nighthawk .
Red-shafted Flicker
Red-headed Woodpecker
Western Kingbird
Eastern Kingbird
Cassin's Kingbird
Say's Phoebe
Barn Swallow
Black-billed Magpie
Common Crow
Black-capped Chickadee
Robin
Audubon's Warbler
Yellow Warbler
Brewer's Blackbird
Red-winged Blackbird
Common Crackle
Western Meadow! ark
American Goldfinch
Rufous-sided Towhee
Vesper Sparrow
Lark Sparrow
Savannah Sparrow
OtherJ>pecies
Starling
Owl?
Woodpecker?
Buteo
_ Common Snipe
Kill deer
1 2
4
2
4
1
1
1
7
3 4 5 6 7 8 9 10 11 12 13 14 15
1
1
2
5
1
2
1
1
5
1
10
1
10
fi
"
8
2
1
1
3
5
4
c
3
5
3
3
3
2
13?
1
5
2
6
1
5
1
1
8
6
153
-------
-SPECIES-
Table VIII-2 (continued)
-STATIONS-
Sparrow Hawk
Red- tailed Hawk
Marsh Hawk
Rough-legged Hawk
Ring-necked Pheasant
Sharp-tailed Grouse
Mourning Dove
Poor-will
Common Niqhthawk
Red-shafted Flicker
Red-headed Woodpecker
.Western Kingbird
Eastern Kingbird
Cassin's Kingbird
Say's Phoebe
Barn Swallow
Black-billed Magpie
Common Crow
Black-capped Chickadee
Robin
Audubon's Warbler
Yellow Warbler
Brewer's Blackbird
Red-winged Blackbird
Common Crackle
Western Meadowlark
American Goldfinch
Rufous-sided Towhee
Vesper Sparrow
Lark Sparrow
Savannah Sparrow
Other Species
Yellow-throat
Siskin-sized bird
Loggerhead Shrike
Woodpecker
Buteo
16 17 18 19 20 21 22 23
3
3
?
2
-
4
2
14
__
1
1
3
6
1
1
20
4
8
2
2
1
3
4
24 25
2
3
26 27 28 29 30
1
1
9
3
1
1
1
2
2
4
1
2
2
3
3
1
1
2
10
10
3
1
2
4
4
154
-------
-SPECIES-
Table VIII-2 (Continued)
-STATIONS-
Sparrow Hawk
Red-tailed Hawk
Marsh 'Hawk
Rouqh-1 egged Hawk
Rinq-necked Pheasant
Sharp-tailed Grouse
Mourning Dove
Poor-will
Common Niqhthawk
Red-shafted Flicker
Red-headed Woodpecker
Western Kingbird
Eastern Kingbird
Cassin's Kingbird
Say's Phoebe
Barn Swallow
Black-billed Magpie
Common Crow
Black-capped Chickadee
Robi n
Audubon's Warbler
Yellow Warbler
Brewer's Blackbird
Red-winqed Blackbird
Common Crackle
Western Meadowlark
American Goldfinch
Rufous -sided Towhee
Vesper Sparrow
Lark Sparrow
Savannah Sparrow
Other Species
Loggerhead Shrike
Unidentified Sparrow
_. Long-eared Owl
31
5
32 33
2
10
2
20
2
1
1
1
9
34 35 36
1
1
2
5
1
2
1
2
4
37 38 39 40 41 42 43 44 4S
1
4
6
1
3
2
4
7
3
2
2
1
1
6
*
5
3
1
•3
1
1
6
1
.
2
3
1
5
75
1
155
-------
-SPECIES-
Table VIII-2 (Continued)
-STATIONS-
Sparrow Hawk
Red-tailed Hawk
Marsh Hawk
Rough-legged Hawk
Ring-necked Pheasant
Sharp-tailed Grouse
Mourning Dove
Poor-will
Common Nighthawk
Red-shafted Flicker
Red-headed Woodpecker
Western Kingbird
Eastern Kingbird
Cassin's Kingbird
Say's Phoebe
Barn Swallow
Black-billed Magpie
Common Crow
Black-capped Chickadee
Robin
Audubon's Warbler
Yellow Warbler
Brewer's Blackbird
Red-winged Blackbird
Common Grackle
Western Meadow! ark
American Goldfinch
Rufous-sided Towhee
Vesper Sparrow
Lark Sparrow
Savannah Sparrow
Other Species
Mallard
Golden Eagle
White-crowned Sparrow
46 47 48 49 50 51 52 53 54
1
7
1
1
5
8
5
6
17
1
9
3
3
2
10
1
4
1
2
3
, 2
1
1
4
2
3
1
55
2
2
3
4
56 57 58 59 60
2
2
4
1
3
O
3
3
1
2
'
3
2
6
2
156
-------
Mammals are collected with two trapping systems, one for the
collection of specimens for necropsy and another for mark-release data.
Live traps are used in both systems.
1. Collections. Rodents are livetrapped one day per week and returned
to the field laboratory for processing. Body weight and length
measurements (body, ear, hindfoot and tail) are taken. Following
ether anesthesia, blood is taken from the orbital sinus in a capillary
tube. From this is determined hematocrit (via centrifugation) and
plasma protein concentration (via diffraction meter). Heart,
lungs, kidneys, adrenals, spleen, liver, gonads and oviducts are
preserved in Bouins fixative, weighed after one week, and transferred
to 70 percent ethanol for subsequent embedding. The frozen carcasses
are saved for analysis of components. More than 200 small mammal
specimens have been collected thus far. Femurs from 80 animals
have been frozen and mailed to C. C. Gordon (University of Montana)
for determination of fluoride content.
2. Mark-release. Grids with outside dimensions of 150 m x 150 m have
been established at five locations. Trapping stations within each
grid are 15 m apart; there are 121 stations/grid. Two traps are
set at each station; a total of 242 traps/grid. The grids are
trapped in regular rotation following three or four nights of
prebaiting with rolled oats.
All rodents trapped are toe-clipped according to a standard numerical
scheme, weighed, measured, and examined for external signs of sexual
activity and other factors such as ectoparasites and pelage changes.
Releases are made at the station of capture. By midwinter 313 individuals
had been marked and released.
157
-------
A total of 305 recaptures have occurred. The species captured, in
ascending order of frequency, are the Grasshopper Mouse (Onchomys
leucogaster). Harvest Mouse (Reithrodontomys megalotis), Olive-backed
Pocket Mouse (Perognathus fasciatus), Prairie Vole (Microtus ochrogaster).
and Deer Mouse (Peromyscus maniculatus) (Table VIII-3).
The percentage of each species comprising our catch on the five
grids varies seasonally (Figure VII1-2). Numerous interacting factors
account for this variation and these undoubtedly vary among species. In
the case of Onychomys leucogaster, for example, none were captured until
the grasshopper population experienced a sharp decline in August.
Beyond October nei ther £._ 1eucogaster nor Perognathus fasciatus were
captured and both species are presumed to have entered hibernation.
Nearly all specimens of P. fasciatus were captured on two nights when
traps were left open during rainstorms.
Peromyscus maniculatus comprised from 52 to 79 percent of the total
catch during every month. Microtus ochrogaster also made up a fairly
consistent portion of the catch, 13 to 33 percent, although they were
not taken at every trapping session as was the case for P. maniculatus.
Traps that are set within a network of M_._ ochrogaster runways will
often take more P. maniculatus than M. ochrogaster. And at grid stations
where animals have been captured, P. maniculatus only have been taken at
80 percent of the stations, M. ochrogaster only at eight percent of the
stations, and both have been taken at 12 percent of the stations. On
three occasions members of each species have been taken during the same
night at the same station. Thus P. maniculatus and M. ochrogaster are
locally sympatric in the Col strip area. This is unexpected since
distributional and behavioral studies indicate that these groups are
usually allopatric or only geographically sympatric and that differential
habitat utilization occurs because of interspecific competition (Pearson,
158
-------
Table VIII-3. NUMBERS OF MICE CAPTURED ON GRIDS AND TRAPLINES
IN COLSTRIP AREA. JULY 1974-April 1975
GRID
No.
Species Captures
Onychomys leucogaster 7
Reithrodontomys megalotis
Perognathus fasciatus
Microtus ochrogaster
Peromyscus maniculatus
Totals
12
21
75
260
*375
No.
Recaptures
6
1
8
56
290
361
Trapline
Captures
1
12
6
44
262
325
Total
Captures
14
25
35
175
812
1061
1.3
2.4
3.3
16.5
76.5
*indicates number of individuals that were marked and released.
159
-------
Figure VIII-2. Seasonal changes in species composition of rodents captured
on grids near Colstrip, Montana, in terms of trapping frequency. Note
tnat Onychomys and Perognathus are hibernators.
10
0
10
0
20
10
0
x
O 40
< 30
O
. 20
Onychomys leucogaster
r
Reithrodontomys megalotis
1
9 • M m m Bl
:•:•:•:•:-
i • • • • i
• m m m m
m*
V.'.V.
Perognathus fasciatus
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July Aug Sept Oct Nov Dec Jan
160
-------
1959; Wirtz and Pearson, 1960; Shure, 1970; Murie, 1971). We are aware
of only one previous case of local sympatry in these groups, that in a
wet prairie environment in Southern Ontario (M'Closkey and Fieldwick,
1975).
This is not to say that interspecific competition is absent when
these species occur together. Members of these groups are not distributed
randomly in Col strip populations and they undoubtedly occupy separate
niches, however subtly structured.
We expect our analysis of niche dimensions involved in the ecological
separation of Peromyscus and Microtus in relatively arid shortgrass
prairie to be important for comparative purposes and for testing the
applicability of models such as those that deal with utilization of
space by small mammals (Calhoun, 1963; Myton, 1974).
Our routine trapping of grids is yielding demographic information,
particularly on P^ maniculatus. The proportion of adults in our samples
decreased in autumn (Figure VIII-3). Reproduction ceased in December
and the proportion of adults increased through the winter as young
animals continued to attain adult size and pelage. Males formed a
remarkably constant proportion of the catch, about 60 percent in all
months (Figure VIII-3). The sex ratio observed in 621 captures of P_^
maniculatus was 1.52:1. This is an unbalanced sex ratio that deviates
significantly from 1:1 (P < 0.005) according to a chi-square test.
Body weights of P. maniculatus showed considerable seasonal variation
(Figure VIII-4). This variability is expected in immatures because of
growth and constant recruitment and in adult females because of varying
reproductive status. Adult males show much less variation; however, a
slight but regular increase in mean body weight occurred from July
through January. Our analysis of whole body composition should reveal
the basis for this increase (e.g., pelage growth or fattening).
161
-------
Figure VIII-3. Sex and age distribution of Peromyscus maniculatus
captured near Col strip, Montana, 1974-75. Numbers in parentheses
indicate total catch.
80
60
O
< 40
20
0
20
40
o
cr
60
Peromyscus maniculatus
MALES
ADULTS
IMMATURES
i • • • •
tiv.v,
• * • • •
VIV
FEMALES
July Aug Sept Oct Nov Dec Jan
(64) (141) (137) (130) (63) (55) (31)
162
-------
Figure VIII-4. Seasonal change in body weight of Peromyscus maniculatus
trapped in the Col strip, Montana, area.
r-
UJ
Q
O
QQ
28
26
24
22
20
18
6
14
Peromyscus maniculatus
15
II
J L
1
J I I L
July Aug Sept Oct Nov Dec Jan
163
-------
Laboratory activities center about five sets of protocols.
1. Carcass analysis - birds
2. Carcass analysis - mammals
3. Histology - birds
4. Histology - mammals
5. Experiments
This work deals principally with four species of indigenous birds
and two species of mammals.
Mourning Dove, Zenaidura macroura
Western Meadowlark, Sturnella neglecta
Vesper Sparrow, Pooecetes gramineus
Lark Sparrow, Chondestes grammacus
Prairie Vole, Microtus ochrogaster
Deer Mouse, Peromyscus maniculatus
Standard biometric methods and whole carcass and organ analyses of
the rodents and birds are employed to evaluate composition and biometric
changes as a function of age, sex, season, and physiologic state in
relation to the physical and biotic environment. The main purpose of
this type of analysis is to better assess condition, vigor, nutritional
state, metabolic state, and net energy balance as a function of air
quality and other environmental factors.
Major body and organ components to be measured and evaluated
include wet body weight, dry body weight, fat-free dry weight, lipids,
allometry of feather growth (birds) and of related functions, stomach
and crop (birds) contents and weights, caloric density of the diet,
parasite burdens (e.g., of intestinal tract arid perhaps of blood).
164
-------
Dietary and tissue (liver, muscle, contents of lower intestinal tract)
protein levels are assayed by gas chromatography.
A copy of the "Dissection Worksheet for Whole Carcass Analysis,"
for birds is included as Appendix E, and a description of the procedures
for carcass analysis of birds follows. The protocol for mammals (not
included in this report) is similar to that of birds, except that most
functions must be referred to dry weight and the organs of interest
differ somewhat.
Carcass Analysis Procedure (Birds): Mammal and bird carcasses are
shipped frozen to the Con/all is laboratory and stored in five nested
plastic bags in freezers kept at -5°C. A designated number of carcasses
are selected one day prior to dissection, the specimen numbers are noted
and they are returned to the freezer until the morning of the dissection.
Dissection containers are prepared in advance for each specimen. The
containers are marked with specimen number and tissue; labels with the
same information are inserted into the corresponding vials, the proper
amount of 10 percent neutral formalin or saline (to maintain state of
hydration) is added to the vials and the fat sample container is preweighed.
All containers for each bird are kept together and stored in a dry dust
free place.
On the morning of dissection, all the designated specimens are
moved to the refrigerator; each bird is allowed to partially thaw just
prior to its dissection. Three people are essential to the procedure,
with an optional fourth person offering general assistance and taking
wet weights of tissues periodically throughout the day. The dissection
procedure closely follows the outline of the dissection worksheet (Appendix
E). Standard methods are employed and will be described, as appropriate,
in later reports. Organs and tissue samples of 10 mg or less are weighed
on a Cahn Model 4100 electrobalance. Larger samples are weighed on a
165
-------
Sartorius analytical balance, model 2462 (200 gr. cap., 0.1 mg sens.).
Tissues are then either returned to the carcass (including the Bursa of
Fabricius, adrenals, kidney, empty crop, empty gizzard, ovary, oviduct,
testes and spleen) or are processed in some other manner. Prior to
return to the carcass, the ovary is examined for measurement of pre- and
postovulatory follicles and the oviduct is examined for the presence of
ova. To obtain the dry weight of the carcass or other tissues, the
samples, already in petri dishes, are placed, uncovered, in a Fisher
Isotemp Vacuum oven, Model 201 at 40°C, 20" Hg. until a constant weight
is reached. Time required will vary with sample size. Dry weights are
recorded and the tissues are ready for further treatment. The remaining
tissues that complete the analysis as part of the carcass are now
returned to it, including the ventral apterium, integument, heart and
lungs.
The carcass and all remaining samples (including pectoral is, fat,
crop contents, and liver) are now individually ground in a Model 4-E
Quaker City Laboratory Mill so the material will pass through a 35 mesh
sieve. At this point, one or more random samples are taken from each
tissue sample and formed into pellets, using the Parr 1/2" Pellet Press,
Model 2811. These pellets are weighed and burned in a Parr model 12141
adiabatic bomb calorimeter to determine the dry weight calorie content.
The remainder of the fat sample is put in a tissue bank for possible
future pesticide scan or trace elements analysis. The remainder of the
crop contents sample as well as the dried intestinal contents are analyzed
for carbon and nitrogen contents by a gas chromatographic method.
The remaining carcass, pectoral is and liver samples are now prepared
for lipid extraction. Milled samples are wrapped in filter paper packets
or cellulose extraction thimbles and processed in a soxhlet apparatus
using 1,2-dichlorethane (Lewis, unpublished). The samples are dried at
166
-------
65°C in a Thelco convection oven and the fat-free dry weights are recorded.
Tissue samples are also taken for nitrogen analysis to be determined by
gas chromatograph method. Following fat extraction, three homogenized
random samples of the whole dry fat-free carcass or of a specific organ
are burned in a Parr model 12141 adiabatic oxygen bomb calorimeter. A
weighed fat-free dry sample of the carcass is also analyzed for ash
content. This is determined by combustion in a muffle furnace at 600°C
until a residue of constant weight is obtained.
Examples of preliminary results on growth, condition, and nutrition
follow. These data illustrate the pronounced seasonal and diurnal
changes that occur in many functions. These types of variation are
pervasive in living systems and of concern in the study of pollution
effects for at least two major reasons: (a) both experimental design
and field sampling protocols must be structured to control or describe
these kinds of variations, and (b) the sensitivities and exposure rates
of animals to air pollutants and to other sources of stress vary both as
a function of the time of day (Aschoff, 1965; Hal berg, Jacobsen, Wards-
worth, Bittner, 1958; Hal berg, Johnson, Brown, and Bittner, 1960; Haus
and Halberg, 1959) and time of year (Fretwell, 1972; Tashiro, Namie,
Takemota, and Misazumi, 1974).
Figures VII1-5 and VII1-6 illustrate the enormous changes in the
size and internal organization of reproductive tissues that may occur in
periodically breeding vertebrates. In 1974, for example, testicular
size decreased in P. maniculatus near Col strip during September and
October (Figure VIII-5). The testes remained at near minimum size
during winter and did not become substantially enlarged until March (no
males were collected in February). Parallel changes in functional
capacity in these structures are demonstrated also by the annual cycle
in seminal vesicle size, a measure of androgen release (Figure VIII-6).
The first pregnant female of the new season was collected on March 25.
167
-------
400
300
UJ
I-
co
LJ
200
100
0
A S 0 N D
1974
F M
1975
A
Figure VIII-5 Seasonal change in testicular weight of adult Peromyscus maniculatus
captured near Col strip, Montana. Means 1 S.E. are shown. Down arrow-indicates last
pregnant female captured in 1974 and up arrow indicates first pregnant female captured
in 1975. Numerals in parantheses indicate sample size.
-------
Figure VIII-6. Seasonal change in seminal vesicle weight of adult
Peromyscus maniculatus captured near Colstrip, Montana. Means
j^S.E. are shown.Numerals in parentheses indicate sample size.
200
UJ
_J
o
CO
UJ
CO
60
20
80
40
0
8
\
II
8
\
A S 0 N
1974
D
F M A
1975
169
-------
The reproductive cycle of M. ochrogaster is similar to that of P. mani-
culatus (Morton and Lewis, unpublished data). Experiments are planned
whereby the environmental factors that regulate the annual sexual cycle
of certain of the birds and/or mammals will be quantitatively assessed.
Such studies are needed if we are to sensitively determine the effects
of air pollutants on reproductive performance.
During the hot, sunny days of summer, Mourning Doves, Zenaidura
macroura, feed intensively during the first few daylight hours and again
late in the day. This activity cycle is reflected in the amount of food
in the crop, a storage organ (Figure VIII-7). Clearly, the activity
patterns and feeding rates of these wide ranging birds may influence
both the rate of exposure and susceptibility to air pollutants. Conse-
quently pollution effects may be a function of both the magnitude of the
peak pollutant concentrations and the time of their occurrence. Interest-
ingly, daily maxima in air pollution concentration from coal-burning
processes frequently show strong diurnal cycles; see the chapter of this
report written by Lee, Lewis and Body.
The body weight of adult male Mourning Doves does not appear to
increase substantially during the early stages of postnuptial molt
(Figure VIII-8). However, body weight rapidly increases following
replacement of the fourth primary remex. Interestingly, in a number of
specimens, we have found the molt to be arrested for an as yet undetermined
length of time (probably about one week). Data thus far reveal no clear
seasonal trend in body weight (Lewis and Morton, unpublished data); the
lowest body weights on any given date occur in birds (male and female)
with arrested molt. Furthermore, birds at molt stages six through
eleven almost invariably weigh more than birds at stages zero through
five.
These early data suggest that the earlier stages of molt in the
Mourning Dove may be bioenergetically more costly than later stages.
The brief cessation of molt may favor restoration of a favorable nutri-
tional balance. The data further suggest that this species could be
especially susceptible to environmental stressors during the period of
molt.
170
-------
Figure VIII-7. Daily variation in the weight of the crop contents of
adult male Mourning Doves, Zenaidura macroura, September 9-10,
1974, near Col strip, Montana.
20
10
if)
H
Z
UJ
(-
z
o
o
Q_
O
E
o
1,1,1,1,1 • !__, I
I
0500 0700 0900 1100 1300 1500 1700 1900 2100
TIME OF DAY (MDT)
171
-------
ro
00
h-
LU
O
U
CL
O
a:
o
oo
oo
UJ
140
35
130
125
120
15
I
O
"0
0 105
O
CD
100
1
1
1
I
0
4567
WING MOLT STATUS
8
10
II
Figure VIII-8. Body weights of adult male Mourning Dove, Zenaidura macroura
as a function of molt stage. Stage A represents interrupted molt; stage 0
is prior to onset of postnuptial molt; stages 1 through 10 represents the
highest primary feather that is growing; and stage 11 treats birds in which
molt is complete. Molt proceeds sequentially from 1 through 10.
-------
The seasonal pattern of growth and development of male and female
Western Meadowlarks, Sturnella neglecta (Figure VIII-9, VIII-10) that we
observed in Rosebud and Powder River countries in 1974, differed substan-
tially. The 1974 specimens are not yet fully processed, and sex has not
been established for all birds. Nevertheless, data thus far evaluated
suggest that the juvenile females may have a more limited capacity
(in 1974) to convert nutritional resources into new tissue. Juvenile
females may thus offer a useful system for evaluating the additional
stress of air pollution. Body weight both as a function of season
(Figure VIII-9) and developmental (i.e., molt) status (Figure VIII-10)
differs in males and females. The differences in body weight appear to
reflect differences in nutritional or energetic balance (Lewis and Morton,
unpublished).
The molt schedule (Figure VIII-11) and the rate of growth of new
plumage (Figure VIII-12) are similar in both sexes of juvenile Western
Meadowlarks. However, while the body mass of the males as a group
increases throughout the period of feather growth, most females appear
to replace plumage at the expense of other body compartments (Figures
VIII-13, VIII-14, VIII-15, Lewis and Morton, unpublished data). Support-
ing data on tissue calories and nitrogen will be available in a few weeks.
The postnuptial molt of Meadowlarks is a major molt during which
all plumage is replaced. This molt results in a very considerable increase
in the weight of the integument (Figure VIII-12) and, presumably, a corres-
ponding decrease in thermal conductance. The bioenergetic demands and
the environmental control mechanisms of postjuvenal and postnuptial
molts have not been fully explored. Nevertheless, photoperiod, food,
and microclimate all play a role in regulating molt (Payne, 1972).
The gizzard, or muscular stomach, of birds is an organ that acts,
in part, as an organ of mechanical digestion. Because muscles typically
hypertrophy with increased loading, we would expect the mass of the
173
-------
130
120
I 10
UJ
100
Q
O
DO
o
Q>
90
8
o
o
o
80
o
o
o
o
8
'^5
29
10
14 18 20 26 30
15 19 23 27
31
July August September
Figure VII1-9. Seasonal progression of body weights of juvenile Western Meadow!arks, Sturnella
neglecta in southeastern Montana, 1974. Specimens cluster into two groups on the basis of body
weight. Ninety percent of the birds represented by the closed circles are males; ninety percent
of the birds represented by the open circles are females. Closed triangles represent birds that
were unassigned to either set. See accompanying text.
-------
CXI
WING MOLT STATUS
Figure VIII-10. Body weights of juvenile Western Meadowlarks, Sturnella neglecta. as a function of
molt stage. Stage 0 is prior to onset of postjuvenal molt; stages 1 through 9 represent the highest
primary feather that is growing; and stage 10 represents birds in which the molt is complete. Molt
proceeds sequentially from 1 through 9. Specimens cluster into two groups on the basis of body
weight. Ninety percent of the birds represented by the closed circles are males; ninety percent of
the birds represented by the open circles are females. Closed triangles represent birds that were
unassigned to either set. See accompanying text.
-------
Figure VIIJ-11. Progression of postjuvenal molt of Western Meadowlarks,
Sturnella neglecta in southeastern Montana, 1974. See Figure VIII-10
for definition of molt stages. Closed circles represent males; open
circles, females.
0
July 29-
Aug 3
4-10
11-17 18-24 25-31 ^PT 8-14 15-21 22-28
176
-------
Figure VIII-12. Weight of the dried integument (plumage and skin) of
juvenile Western Meadowlarks, Sturnella neglecta, during the period of
postjuvenal molt (see accompanying text). Closed circles represent males;
open circles, females.
10
LJ
^
ID
CD
LJ
26
July
13 19
August
25
31
12 18 24
September
177
30
-------
Figure VIII-13. Weight of the dry carcass (less plumage and skin) of
juvenile Western Meadowlarks, Sturnel1 a neglecta, during the period of
postjuvenal molt. Closed circles represent males; open circles, females.
3<
ol
LU
2
§
CO 23
CO
LU
CO 22
CO
CL
Q
20
19
18
17
16
26
July
13 19
August
25 31
12 18 24
September
30
178
-------
Figure VIII-14. Weight of the dry carcass (less plumage and skin) of juvenile
Western Meadowlarks, Sturnella neglecta, as a function of molt stage. See
Figure VIII-10 for definition of molt stage. Closed circles represent males;
open circles, females.
30
29
28
27
26
LJ
25
24
LU
I-
? 23
CO
22 .
CO
o
01
O 20
tK
Q 19
18
17
16
456
WING MOLT STATUS
10
179
-------
Figure VIII-15. Weight of the gizzard of juvenile Western Meadowlarks,
SturneTla neglecta, as a function of molt stage. See Figure VIII-10 for
definition of molt stage. Closed circles represent males;' open circles,
females.
456
WING MOLT STATUS
10
180
-------
gizzard to increase during periods of increased food intake. Our analy-
sis is complicated because the Meadowlarks under consideration are growing
and because we have not yet analyzed the stomach contents of these birds
(i.e., harder food as well as increased rate of intake might produce
hypertrophy). Nevertheless, gizzard weight increased substantially in
males during the course of molt and development, but ndt in females
(Figure VIII-15). There was a corresponding increase in the bulk of the
stomach contents of males. This presently incomplete data set indicate
that food resources (1974) are utilized differently by males and females
during the period of postjuvenal molt; they are perhaps less efficiently
exploited or processed by the females.
Both the thymus and the bursa of Fabricus (Figure VIII-16) of the
Western Meadowlark, Sturnella neglecta, persist for an as yet undefined
period following the assumption of the winter plumage. This allows us
to easily distinguish adult birds and birds of the year at least through-
out the fall. We are thus, for example, hoping to determine when birds
of the year reach adult size and condition. Some observations indicate
that the thymus is still evident in adult females (but not males) during
the early part of at least their first breeding season.
Both the thymus and bursa of Fabricus are of special concern to us
because some air pollutants act as immunosuppressive agents; such effects
might be reflected in the development and activity of these glands.
Ancillary to the vertebrate animal research and as an aid to the
establishment of pollution gradients, we are studying the corrosive
effects of the atmosphere at the 18 sites depicted in Figure VIII-17.
Four 4x3 inch steel plates are suspended by plastic ties from fences at
each of these sites. The plates are made of low carbon (200-400 ppm),
low copper (300-500 ppm) steel, Armco enameling iron DO plate. Each
set of plates is exposed for a period of three months. The plates are
1ST
-------
2-6
c»
ro
July August September
Figure VIII-16. Weight of the Bursa of Fabricius (relative to body
weight) of juvenile Western Meadowlarks, Sturnella neglecta, during the
period of postjuvenal molt. The data for males and females are grouped.
-------
Figure VIII-17. Map of sites employed to study corrosiveness of the
atmosphere.
I06°45'
106° 30'
46°00' —
45»45' —
— 46°00'
— 45°45'
I06"45'
MILES
183
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cleaned by a standard method before exposure, and are dried and weighed
to the nearest milligram on the day prior to exposure. Following exposure,
the plates are again carefully cleaned and reweighed. Corrosion rate is
expressed as the number of milligrams lost per day per square decimeter
of exposed surface. It is too early to evaluate the results of this
study on a site-by-site basis. During the autumn quarter of 1974, mean
o
rate of corrosion was 0.49 (S.E.M. = 0.03) mg/day-cm and during the
winter quarter, the corresponding values were 0.59 (-.03).
ACKNOWLEDGEMENTS
Technical assistance for this study is provided by a large number
of people, all of whom have our thanks. We would like especially to
thank Larry Doe for major technical contributions.
184
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REFERENCES
1. Aschoff, J. 1965. Circadian rhythms in man. Science 148:1427-
1423.
2. Calhoun, J. B. 1963. The social use of space. In: Physiological
Mammalogy I. (W. V. Mayer and R. 6. Van Gilder, Eds.}. New York:
Academic Press, pp. 1-187.
3. Farner, D. S. and R. A. Lewis. 1971. Photoperiodism and reproductive
cycles in birds. In: Photophysiology: Current Topic in Photo-
chemistry and Photobiology (A. C. Giese, ed.). New York: Academic
Press 6:325-370.
4. Fretwell, S. D. 1972. Populations in a seasonal environment.
New Jersey: Princeton University Press. 217 pp.
5. Halberg, F., E. Jacobson, G. Wardsworth, and J. J. Bittner. 1958.
Abnormal audiogenic response spectrum in mice. Science 128:657-
658.
6. Halberg, F., E. A. Johnson, B. W. Brown and J. J. Bittner. 1960.
Susceptibility rhythm to E. Coli endotoxin and bioassay. In:
Proc. Soc. Exp. Biol. New York. 103:142-144.
7. Haus, E., and F. Halberg. 1959. 24-hour rhythm in susceptibility
of c. mice to a toxic dose of ethanol. J. Appl. Physio!. 14:878-
880.
185
-------
8. Lewis, R. A., A. S. Lefohn, and N. R. Glass. 1975. An investigation
of the bioenvironmental effects of air pollution from a coal-fired
power plant. In: The Fort Union Coal Field Symposium. Vol. IV.
Terrestrial Ecosystems (W. F. Clark, ed.).
9. Lewis, R. A. and F. S. Orcutt, Jr. 1971. Social behavior and
avian sexual cycles. Scientia 106:447-472.
10. M'Closkey, R. T. and B. Fieldwick. 1975. Ecological separation of
sympatric rodents (Peromyscus and Microtus). J. Mammal 56:119-129.
11. Murie, J. 0. 1971. Dominance relations between Peromyscus and
Microtus in captivity. Amer. Midland Nat. 86:229-230.
12. Myton, B. 1974. Utilization of space by Peromyscus leucopus and
other small mammals. Ecology 55:277-290.
13. Payne, R. B. 1972. Mechanisms and control of molt. In: Avian
Biology II. (D. S. Farner and J. R. King, eds.). New York: Academic
Press, pp. 103-155.
14. Pearson, P. G. 1959. Small mammals and old field succession on
the Piedmont of New Jersey. Ecology. 40:249-255.
15. 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.). Swedish Natural
Science Research Council. Redaktionstjansten.
16. Sadlier, R.M.F.S. 1969. The Ecology of Reproduction in Wild and
Domestic Animals. London: Methesen.
186
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17. Shure, D. J. 1970. Ecological relationships of small mammals in a
New Jersey barrier beach habitat. J. Mammal. 51:267-278.
18. Tashiro, K., K. Namie, K. Takemota, and E. Misazumi. 1974.
Effects of air pollution on the respiratory system of animals in a
zoological garden (Dobutsuen Shiiku Dobutsu No Kokuki-kei Taisuru
Taiki Osen No Eikyo (2)). Nippon Eiseigaku Zasshi 29:107.
19. Wirtz, W. 0., II, and P. G. Pearson. 1960. A preliminary analysis
of habitat orientation in Microtus and Peromyscus. Amer. Midland
Nat. 63:131-142.
187
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SECTION IX
THE FIELD EXPERIMENTAL COMPONENT: EVALUATION OF THE ZONAL
AIR POLLUTION SYSTEM
by
Jeffrey 0. Lee, Robert A. Lewis, and Dem's E. Body
INTRODUCTION
The field experimental component of this investigation is sited on
a grassland park in Custer National Forest in Southeastern Montana.
Experimental challenge of four one-acre plots with sulfur dioxide was
initiated in May, 1975. The plots are situated within a 27-acre exclosure
to protect livestock from injury and to protect equipment from livestock
damage.
These experiments are designed to test the effects of SOp upon
plant and animal (arthropods) biomass dynamics; plant community structure;
insect and fungal diseases of plants; pollination systems; lichens; and
upon a number of physiological and biochemical functions. Dominant
plants on the study plots are Western wheatgrass (Agropyron smithii),
prairie junegrass (Koelaria cristata), and Sandberg bluegrass (Poa
secunda).
The system was designed to allow us to maintain a different constant
30-day median concentration on each plot during the growing season (ca.
1 April-30 September). Continuous monitoring of gas concentrations will
ensure that the desired levels are maintained. Application of a Gaussian
dispersion model (Turney, 1969) indicates that, under unfavorable
dissipation conditions, concentrations about 200 feet from a 40 pphm
plot will remain below 5 pphm. Thus, at the concentrations employed
(Table IX-2), the effects on surrounding areas will be minimal and
188
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Table IX-1. GEOMETRIC MEANS (GM) AND STANDARD GEOMETRIC DEVIATIONS (SGD)
OF ATMOSPHERIC S02 (PARTS PER HUNDRED MILLION) FOR URBAN AREAS. FIVE
MINUTE AVERAGES. (HOLZWORTH, 1973. PP. 162-67).
City GM SGD
mmmmrml^ftjf'im **^^^ ^^^»^^^H
Chicago 10.4 2.2
Cincinnati 1.6 2.9
Denver 1.3 2.1
Los Angeles 1.3 2.3
Philadephia 5.5 2.4
St. Louis 2.8 2.8
San Francisco 0.5 2.9
Washington 3.9 2.2
189
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significant levels will not occur outside the study enclosure. A log-
normal distribution of concentrations about the mean is both expected
and desired since this distribution pattern is typical of gaseous indus-
trial pollutants. Preliminary testing of a prototype system during
September 1974 indicated the feasibility of this type of control.
DESIGN REQUIREMENTS
The ultimate design goal was to provide a system for well-defined
assessment of the sulfur dioxide impact on otherwise undisturbed grassland
ecosystems. We have approached this ideal by establishing realistic
ecological and physical criteria.
Disturbance of biota and of micro-climates by the gas delivery
system must be minimized. Effects on incident radiation, prey refuges,
ground level obstructions and pathways, temperature, humidity, wind, and
other features of the micro-habitats must be kept as small as possible.
The area to be gassed must be large, on the spatial scales of the
populations to be sampled, to reduce edge effects and to assure adequate
population and sample sizes. Areas chosen for comparisons (i.e.,
treatments and control) should be as uniform as possible in habitat,
edaphic and terrain features.
The distribution of pollutants must meet certain spatial and
temporal constraints. Concentration should follow a log-normal distribution
similar to those which occur in polluted areas (Holzworth, 1973). The
distribution should be spatially uniform or nearly so, at least on a
time average basis. Specifically, there should not be any "hot" or
"dead" spots and concentrations must be controllable for a range of
selected averages. Finally, dost, maintenance and operation must be
reasonable.
190
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The system that we have designed meets these criteria. Each study
plot has a 1 1/4 acre network of one-inch pipe supported above ground
level by pipe stakes. The centers of the plots are located along a
line, with buffer zones between plots wide enough to prevent inter-
ference. A dilute mixture of air and SO,, flows through the lines and
is released at numerous points over the grid.
The only ground-level obstructions within the plots are the supports.
These should present minimum interference with animal movements while
the pipe network should cause minimum impact on m-icro-climate. The
relatively small size of the plots will exclude the study of large
animals. However, insects and other arthropods will be included. In
addition, the areas between plots can be studied, although under less
easily evaluated conditions, permitting a limited study, perhaps, of
small rodents. The contiguity of the plots allows for nearly uniform
habitat conditions.
By utilizing many small, elevated point sources, adequate dilution
of SQy at ground level is ensured and, in effect, an area source is
created. This prevents step-function changes in concentrations in time
and space. Testing of the system confirmed our expectations regarding
the nature of the distribution.
PROTOTYPE TESTING
A full scale prototype of the Zonal Air Pollution Systems (ZAPS)
was constructed and employed to test the feasibility of this approach
(Lee and Lewis, 1975). Analysis of the data obtained from the prototype
and the progress made toward application of the multiple plot system are
discussed in the following sections.
191
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40
ro
Q.
Q.
-------
PROTOTYPE: DATA COLLECTION
Sulfur dioxide was monitored by recording the output of a sulfur
analyzer in the logrythmic mode. Eight sample lines fed into a time-
share device so that each line was sampled for 10 of every 80 minutes.
The ends of four of the lines were moved to various positions within the
plot, while one line always sampled the center of the plot. The remaining
three lines were placed adjacent to the plot near the equipment shed.
All sample points were located approximately one foot above ground
level.
Wind speed and direction were recorded frequently each day. The
weather was generally clear and mild during the test period (October,
1974). Daily highs were in the 70's (Farenheit) with lows in the 40's.
PROTOTYPE DATA: TEMPORAL VARIATION
Data on the temporal variation of concentrations were obtained
mainly from the central sampling point. In models of pollutant dispersion,
source strength appears as a normalization constant with the patterns of
distribution determined by meteorological conditions (HEW, 1970). The
frequency distribution of concentrations of the central point was obtained
by pooling all data from this point, after normalizing to the most
common source strength (i.e., SO^ flow rate). The results (Figure IX-1)
clearly demonstrate that the concentrations were log-normally distributed
with a geometric mean (GM) of 5.2 pphm, a standard geometric deviation
(SGD) of 2.1, and an arithmetic mean of 6.5 pphm. Typical values for 5-
minute averaging times of GM and SGD (Gilbert, 1970) are given in Table
IX-1. Note the relatively low variability of SGD over a range'of geometric
means, reflecting the independence of SGD and source strength. The
values obtained by the prototype are consistent with these data.
193
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The main point is not that the system simulated a particular place
(i.e., Philadelphia, 1962-1967, Table IX-1) but rather that the concen-
trations across the plots are adequately controlled at the low levels
desired. Conditions within the plot mimic either locations subject to
area sources or locations some miles down wind from point sources.
Changes in average concentrations associated with changes in wind direction
from a point source can be simulated simply by adjusting the S02 flow
rate.
Typical time series for the central and two other sampling points,
located near opposite corners of the plot, are shown in Figure IX-2,
which contains only un-normalized data. The main features are the two
peaks, one near sunrise, and the other after sunset. The three sample
points generally track one another although some phase differences are
evident.
Diurnal patterns of pollutant SO- concentration from both stationary
point sources and in urban environments are frequently similar to that
produced by our system (Holzworth, 1973; Le Quinio, 1973; Raynor, Smith
and Singer, 1974; Smith, 1968; Saito and Mizoguchi, 1973). Such variation
in air pollutant concentrations are due to (a) variations in source
strengths that, in turn, may result from daily cycles in human activity
(Garnett, 1973; Holzworth, 1973); (b) transport wind speeds and directions,
atmospheric diffusion, and interactions (Cormier, 1974; Fukuoka, 1973;
Garnett, 1973; Holzworth, 1973; Lomaya and Tsintsadze, 1974; Martin,
1974; Smith, 1968). All of these vary as a function of weather and
season (Balabuyev, Lomaya, and Tsintsadze, 1973; Druilhet and Fontan,
1973; Fukuoka, 1973; Sandig and Saendig, 1973). Atmospheric dilution is
frequently greatest during the day and least at night. This may result
in one or more daytime minima and a nocturnal maximum in pollutant
concentrations (Holzworth, 1973).
194
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Figure IX-2. Time-series of concentrations on proto-type, October 12, 1974.
Points are center ( ), generally upwind ( ), and generally
downwind ( ). Latter two were nearer the lines than the central
point.
E
a
a
c
g
"•o
E
-E 10
0
o
h-
a:
i-
z
LlJ
O
z
o
o
CVI
Ol
1
-------
PROTOTYPE DATA: SPATIAL VARIATION
Concentrations varied systematically and smoothly over the plot.
Regions near the delivery Tines tended to exhibit values up to three
times higher than regions midway between the lines (Figure IX-2), although
there did not seem to be any "hot spots" associated with the release
points. Concentrations generally increased in the direction of the
prevailing wind and decreased at a moderate rate outside the plot proper
so that concentrations 20 to 50 feet beyond the plot border were compar-
able to those within the plot.
PROGRESS TOWARD APPLICATON OF THE SYSTEM
At this writing, the first set of Zonal Air Pollution Systems
employing the modified delivery geometry (Lee and Lewis, 1975) and
treatments have begun. We expect to deliver S02 continuously throughout
the remainder of the growing season. Ideally, treatments should begin
in the spring when the 10-day running average of air temperature exceeds
5.0°C and terminate when the 10-day running average falls to 5.0°C.
The reason for this criterion is based on observations in the literature
that plants with the C3 Calvin-Benson pathway of C02 fixation can be
quite active at 5°C. The dominant plants on the fumigation site are C3
species. The rationale behind the 10-day moving average is simply to
ensure that we will be neither beginning nor ending fumigation in
response to brief periods of unseasonal weather. In a typical year, we
expect to fumigate from about mid-April through October.
Based upon our estimates of the daily and seasonal variation in S02
concentrations to be expected from ZAPS and best guesses on the effects
of peaks-biota interactions, we propose to maintain the median concen-
trations indicated in Table IX-2. Preliminary data from this spring
indicate that the expected daily peak-median ratios are being attained.
196
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Table IX-2. EXPECTED S02 CONCENTRATIONS (PPHM) ON THE FIELD EXPERIMENTAL
PLOTS
Probable
Plot
1
2
3
4
5-Minute
Median
0
2
5
10
Daily
3-hour
Peak
0
8-10
20-25
40-50
Growing
Season
Peak
0
15-20
40-50
100-200
Possible
Seasonal
Peak
0-2
90-100
100-200
400
197
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With this design, we anticipate measurable, identifiable SOg
effects on the plot with the highest concentration. S02 levels on this
plot will frequently approach or exceed the present secondary standard
of 0.50 ppm (1300 yg/m ). This is the maximum 3-hour concentration that
is not to be exceeded more than once each year. We feel reasonably
confident that biological effects will occur at the 5 pphm median level
(Elfimova and Guser, 1969; Gilbert, 1970; Palm, Nick, Arnold and Platy,
1973; Shalambergidye and Tseretli, 1971), and liminal effects might be
seen as low as 2 pphm.
FUTURE APPLICATIONS
Construction of a second set of four ZAPS at the same site is
planned. Procurement of the necesary materials is under way. Based on
the experience gained thus far in ZAPS construction, we anticipate no
problems in getting the second set operational by the start of the 1976
growing season.
ACKNOWLEDGEMENTS
Technical assistance in the operation of the prototype system was
provided by Mr. Larry Doe.
198
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REFERENCES
1. Balabuyev, A. G,, 0. V. Lomaya, and D. G. Tsintsadze. 1973.
Annual and diurnal course of the concentration of atmospheric solid
aerosols over a city (Godovoy I sutochnyy Khod Kontsentratsii
Atmosfernykh Aerozoley V Gorodkikh Usloviyakh). Soobshch. Akad.
Nauk Gruz. SSR, 69(3):585-589.
2. Cormier, Rene V. 1974. The nature and variability of integrated
boundary layer winds. Presented at the Conference on Weather
Forecasting and Analysis, 5th, St. Louis, March 4-7, 1974. Preprint,
American Meteorological Society, pp. 244-249.
3. Druilhet, A. and 0. Fontan. 1973. Determination of the vertical
diffusion coefficients between 0 and 100 m by using radon and THB.
(Determination des Coefficients de Diffusion Verticale Entre 0 et
100 M a le Aide du Radon Et due THB). Boundary-layer Meteorol.,
3:468-498.
4. Elfimova, E. V. and M. I. Guser. 1969. Health effects of low
sulfur dioxide concentrations in air (Gigienicheskaya kharakteristika
deistviya malykh kontsentratsii sernistogo angidride V atmosfernom
vosdukhe na organism). Gig. I. Sanit., 34:161-166.
5. Fukuoka, Yoshitaka. 1973. Meteorological study of air pollution.
(1) The general and specific cycles for air pollution (Fukushima
daigaku kyoikugakubu rika hokoku). Sci. Rep. Fac. Educ. Fukushima
Univ. 23: 51-64.
6. Garnett, Alice. 1973. Emissions, air pollution and the atmospheric
environment. J. Inst. Fuel 46:39-45.
199
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REFERENCES
1. Balabuyev, A. G., 0. V. Lomaya, and D. G. Tsintsadze. 1973.
Godovoy I sutochnyy Khod Kontsentratsii Atmosfernykft Aerozoley
V Gorodkikh Usloviyakh. Soobshch. Akad. Nauk Gruz. SSR, 69(3):
585-589.
2. Cormier, Rene V. 1974. The nature and variability of integrated
boundary layer winds. Presented at the Conference on Weather
Forecasting and Analysis, 5th, St. Louis, March 4-7, 1974. Preprint,
American Meteorological Society, pp. 244-249.
3. Druilhet, A. and J. Fontan. 1973. Determination des Coefficients
de Diffusion Verticale Entre 0 et 100 M a le Aide du Radon Et due
THB. Boundary-layer Meteorol., 3:468-498.
4. Elfimova, E. V. and M., I. Guser. 1969. Gigienicheskaya kharak-
teristika deistviya malykh kontsentratsii sernistogo angidride V
atmosfernom vosdukhe na organism. Gig. I. Sanit., 34:161-166.
5. Fukuoka, Yoshitaka. 1973. Meteorological study of air pollution.
(1) The general and specific cycles for air pollution (Fukushima
daigaku kyoikugakubu rika hokoku). Sci. Rep. Fac. Educ. Fukushima
Univ. 23: 51-64.
6. Garnett, Alice. 1973. Emissions, air pollution and the atmospheric
environment. J. Inst. Fuel 46:39-45.
7. Gilbert, 0. L. 1970. A biological scale for the estimation of
sulphur dioxide pollution. New Phytol. 69:629-634.
200
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8. Health, Education and Welfare, Department of. 1970. Air quality
criteria for sulfur oxides. Washington, D.C.: U.S. Gov. Printing
Office. 178 pp.
9. Holzworth, George C. 1973. Variations of meteorology, pollutant
emissions, and air quality. In: Proceedings from the 2nd Joint
Conference, Sensing Environmental Pollution. American Chemical
Society, American Inst. of Aeronautics and Astronautics, American
Meteorological Society, U.S. Dept. of Transportation, U.S. Environ-
mental Protection Agency, Inst. of Electrical and Electronic
Engineers, Instrument Society of America, National Aeronautics
and Space Administration, and National Oceanographic and Atmos-
pheric Administration. Washington, D.C. pp. 247-255.
10. Lee, Jeffrey and Robert A. Lewis. 1975. Field experimental com-
ponent: bioenvironmental effects of sulphur dioxide. In: The
Bioenvironmental Impact of a Coal-Fired Power Plant. (R. A. Lewis
and A. S. Lefohn, eds.). Ecological Research Series, U.S. Environ-
mental Protection Agency. Corvallis, Oregon. In press, pp. 96-102.
11. Le Quinio, R. 1973. Concentrations sur une Heure de pollutants a
des emissions ponctuelles pres due sol-presentation probabiliste.
Atmos. Environ. 7(4):423-428.
12. Lomaya, 0. V. and D. G. Tsintsadze. 1974. Analize sutochnogo khoda
zagryazneniya Vozdukha. Soobsch. Adad. Navk. Gruz. SSR. 73:329-332.
13. Martin, D. E. 1974. Some air pollution climatologies of the St.
Louis Urban complex. Presented at the conference on Weather Fore-
casting and Analysis, 5th, St. Louis, MO., March 4-7, 1974. Preprint,
American Meteorological Society, pp. 180-182.
201
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14. Palm, P. E., M. S. Nick, E. P. Arnold, and B. B. Platy. 1973.
Effects of low concentrations of sulfur dioxide on vascular plants.
Biology Data Book Vol. II, 2nd edn. (P. L. Altman and D. S. Dittmer,
eds.). Bethesda: Fed. Amer. Soc. Exper. Biol. pp. 996-1015.
15. Raynor, G. S., M. E. Smith and I. A. Singer. 1974. Temporal and
spatial variation in sulfur dioxide concentrations on suburbia Hong
Island, New York. J. Air Poll. Contr. Assoc. 24:586-590.
16. Shalambergidye, 0. P., and N. T. Tseretli. 1971. Vliyanie malykh
Kontsentratsii sernistogo gaza i dvuokisi ayota na estralnyi tsikl
i detorodnuya funcktsiyo v eksperimente na zhivotsnykh. Gig. i
Sanit. 36:178-183.
17. Saito, Kazuo and Tokihiko Mizoguchi. 1973. Taikiosen jido sokutei
kirokukei ni yoru iosankabutsu oyobi fuyu bijin no sokutei ni tsuite.
Nara-ken eisei kenkyusho nenpo 6:145-147.
18. Sa'ndig, R. and R. Sa'ndig. 1973. ZUr edv-gestutzten bestimmung der
schwefeldioxid-immissionen an einer stationaeren messstelle im
stadtzentrum von Zwickau. Z. Ges. Hyg. Grenzgebite Berlin, 19:890-896.
19. Smith, M. E. 1968. The influence of atmospheric dispersion on the
exposure of plants to airborne pollutants. Phytopath. 58:1018-
1088.
20. Turner, D. B. 1969. Workbook of Atmospheric Dispersion Estimates.
Washington, D.C.: U.S. Dept. of Health, Education and Welfare. 84 pp.
202
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SECTION X
A REMOTE SENSING STUDY OF THE BIOENVIRONMENTAL
EFFECTS OF STACK EMISSIONS FROM THE COLSTRIP, MONTANA, POWER PLANT
by
Thomas R. Osberg, Robert A. Lewis, and John E. Taylor
INTRODUCTION
As a key integrative element of the Montana Coal-Fired Power Plant
Project, we are developing and applying remote sensing as a tool to (a)
detect biological effects of air pollutant challenge; (b) measure inventory
loss that results from strip mining, installation of power lines, increased
human activity, water use and other potentially confounding influences
such as pesticides, disease, and population cycling; and (c) aid in the
development of predictive models.
We expect this remote sensing task to provide data that confirm and
extend the information gained from ground-based studies. High resolution
camera systems installed in both high performance, high-altitude aircraft
and in low-flying craft should provide an excellent permanent temporal
record of the study areas. Repetitive coverage of a particular ground
area or target is an established technique (Colwell, 1968) for detecting
changes in both natural and man-made features (Genderen, 1974; Pollan-
schuetz, 1968; Zealear, Heller, Norick, and Wilkes, 1971) and has been
applied in some instances to the evaluation and management of grassland
203
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resources (Carneggie and Reppert, 1969; Carneggie, 1970; Poulton, 1970)
and in the assessment of terrestrial effects of air pollution from coal-
conversion facilities (Genderen, 1974; Pollanschuetz, 1968; Zealear,
Heller, Norick, and Wilkes, 1971). In at least some instances color
infrared photography detects plant injury from air pollutants prior to
visual registration (Bravo, 1972) or reveals non-visible injury that may
be associated with decreased growth and yields (Pollanschuetz, 1968).
Thus, remote sensing as applied to this study offers a predictive potential,
We are evaluating several photographic processes (color, color IR,
and monochrome) at varying scales (1:2000 to ERTS) as tools for the
assessment of air pollution impact from the power plant at Colstrip,
Montana, and the effects of SOp on our field experimental plots on
Custer National Forest in Southeastern Montana. Work thus far has shown
that 70 mm color at a negative scale of 1:3000 yields sufficient resolution
for most vegetation work. During 1974, project work was primarily
developmental; now we are prepared to apply the most appropriate procedures
to biological effects monitoring (Taylor, Leininger, and Fuchs, 1975).
The high-altitude photography ranged in scale from 1:35,000 to
scales in excess of 1:80,000. High-altitude photography provides
synoptic coverage and is most suitable for analysis of natural features
in large areas, as well as for mapping purposes. Conversely, low
altitude flights yield imagery with scales to 1:500. This photography
is essential in obtaining detailed information of selected small targets
on the ground.
A series of three to six low level flights is planned for 1975.
These will be timed to coincide with key periods of the growing cycle.
Color and color infrared emulsions will be used. The sensor system,
consisting of two Hasselblad cameras, yields a frame format of 70
millimeters. Although this is relatively small, we expect to acquire
204
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photography at scales as large as 1:2000. We believe that sufficient
detail can be seen in this imagery to enable us to trace and describe
pollution stress patterns that develop in grasses and other types of
vegetation discernible in the imagery. This large-scale imagery will be
used for repetitive coverage of the field sites. Information from this
source, in conjunction with ground data obtained in the field, should
aid the overall program in assessing microclimatic and air pollution
patterns and effects.
The high-level photography will provide baseline data for vegetation
and landform mapping, including a seasonal record of vegetational community
composition. Information on microclimates and moisture gradients is
also desired, including records of subirrigated and run-in moisture
areas, erosion (if any), snow melt patterns, and drainage patterns. We
hope also to record infrared signatures of individual plant species and
plant communities. These photographs will provide information on grazing
patterns, winter game use, and the number and dispersion of large game.
The low-level (500 feet) photography, with more detailed information
on specified sites, should bridge the gap between high-level and ground-
level records. Early in the program we acquired imagery of the Col strip
area from four high-altitude missions. All photographs from these
missions, taken during summers of 1972, 1973 and 1974, are color infrared.
Combined, they cover more than 10,000 square miles around Colstrip.
This photography represents an important source of baseline information
prior to operation of the power plant. The photography was loaned to
EPA; the photolab at the Environmental Photographic Interpretation
Center (EPIC) duplicated the films. Table X-l summarizes the coverage
information.
In 1975, the National Aeronautics and Space Administration will
make two high-altitude flights. Both color and color infrared films
205
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with nine-inch frame format will be used. Coverage is planned for a one
degree cell: 46 to 47 degrees north by 106 to 107 degrees west (Figure
X-l). It includes the power plant and mines at Colstrip and the sites
located east and southeast of Colstrip. The missions are scheduled for
early May and mid-summer to coincide with critical periods of the
growing season. A nominal scale of 1:40,000 is expected from this high
altitude photography.
Field study sites for the program have been established at two
general locations near Colstrip. Some six study sites are situated
within a 20 kilometer (12 miles) arc to the east and south of the power
plant (Figure X-2). A group of three sites is situated near Fort Howes
Ranger Station, about 75 kilometers (47 miles) from Colstrip (Figure X-
3). Experimental fumigation of grassland communities will be conducted
on the three sites (about 25 acres each). A major goal of the remote
sensing work is to record stress patterns that occur at the field
experimental sites over a protracted period.
ACKNOWLEDGEMENTS
Photographs from the four high-altitude overflights of the Colstrip
region were acquired within the past three years by other Federal
agencies based in Billings. We want to acknowledge the efforts of the
people responsible for loaning this invaluable imagery. Fred Batson and
Ed Zaidlicz, U. S. Bureau of Land Management, Montana office, provided
coverage of two BLM resource areas Rosebud-Coalwood and Birney-Decker.
Paul Kipp and Keith Beartusk, Bureau of Indian Affairs, Billings and
Lame Deer, made available photos of Indian lands near Colstrip; and the
U.S. Forest Service in Billings furnished photographs of the Custer
National Forest.
206
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Table X-l HIGH ALTITUDE PHOTOGRAPHY OF SOUTHEASTERN MONTANA
Area of Coverage
Date
Scale
Originating Agency
Rosebud-Coalwood
Planning Unit
28 June 1974
1/80,000
Bureau of Land Management, U.S.
Department of Interior
Decker-Birney
Planning Unit
1 June 1972
1/40,000
Bureau of Land Management, U.S.
Department of Interior
ro
o
Northern Cheyenne
Eastern One-Third
of the Crow Indian
Reservations
Custer National Forest
Ashland/Fort Howes
District
4-5 July 1973
28 August 1973
1/40,000
1/36,000
Bureau of Indian Affairs, U.S.
Department of Interior
U.S. Forest Service, U.S.
Department of Agriculture
TOTAL AREA: Over 10,000 square miles or 2,590,000 hectares
-------
Figure X-l. The Colstrip Power Plant is Based on an Extensive Supply
of Coal Reserves in the Fort Union Deposit of the Great Plains. Over
10,000 square miles of area surrounding the plant Kas been photographed
by high altitude camera systems since 1972. Map sca|e_1/500,000
ham.
-------
Figure X-2. Aerial Photograph of the Area Immediately to the East and
South of the Col strip Mines. A portion of the Mines is visible as white
tone at the left margin. Stream valleys appear as dark-toned meandering
features. Field study sites lie between the mine and Rosebud Creek, seen
flowing from southeast to north through the center of the photo. Original
scale 1/80,000. Acquired by US Bureau of Land Management 28, June 1974.
209
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Figure X-3. Field Study Sites in the Vicinity of the Fort Howes
Ranger Station are some 75 Kilometers South-Southeast of the Power
Plant at Colstrip. Fort Howes is a small cluster of buildings north
of the road intersection at the center of the photograph. Photography
by US Forest Service, August 1973. Original scale 1/36,000.
210
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REFERENCES
1. Bravo, A. Humberto. 1972. The use of color infrared photography
in the detection of non-visible injury to vegetation by ozone. In:
Proceedings of the International Clean Air Conference, May 15-18.
Melbourne: Clean Air Society of Australia and New Zealand, pp.
268-273. 13 Refs.
2. Carneggie, D. M. 1970. Remote sensing: review of principles and
research in range and wildlife management. In: Rangeland and
Wildlife Habitat Evaluation-A Research Symposium. Washington,
D.C.: U.S.D.A. Misc. Publ. No. 1147.
3. Carneggie, D. M. and J. N. Reppert. 1969. Large scale 70-mm
aerial color photography. Photogrammetric Engrg. 35:249-257.
4. Colwell, R. N. 1968. Remote sensing of natural resources.
Scientific American. 218:54.
5. Gendereri, J. L. Van. 1974. Remote sensing of environmental
pollution of Teesside. Environ. Poll. 6(3):221-234. 41 Refs.
6. Pollanschuetz, Josef. 1968. Erste Ergengnisse Ueber Die
• • * •
Verwendung Eines Infrarot-Farbfilmes in Oesterriech Fuer Die
* 9
Azweke der Rachschadenfestellung. Centralblatt Fur Das Gesamte
Forstwesen. 85(2):65-79.
7. Poulton, C. E. 1970. Practical application of remote sensing in
range resources development and management. In: Range and Wildlife
Habitat Evaluation—A Research Symposium. Washington, D.C.:
U.S.D.A. Misc. Publ. No. 1147, pp. 179-189.
211
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8. Taylor, J. E., W. C. Leininger, and R. J. Fuchs. 1975. Baseline
vegetational studies near Colstrip. In: The Fort Union Coal Field
Symposium, Terrestrial Ecosystems. Vol. IV. (W. F. Clark, ed.).
9. Zealear, Kristina A., Robert C. Heller, Nancy X. Norick, and
Marilyn Wilkes. 1971. The feasibility of using color aerial
photography to detect and evaluate sulphur dioxide injury to timber
stands. Forest Service, Berkeley, Calif. Pacific Southwest Forest
and Range Experiment Station. 5 Refs. NTIS: PB 205-279: U. S.
Government Printing Office, Washington, D.C.
212
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SECTION XI
AIR MONITORING CHARACTERIZATION AT THE HAY COULEE SITE,
COLSTRIP, MONTANA
by
James R. Miller, T. Cail, Allen S. Lefohn
INTRODUCTION
The air monitoring characterization work is an integral component
of the Montana Coal-Fired Power Plant Project designed to determine the
effects of emissions from coal-fired power plants on the surrounding
environment. A mobile laboratory was installed at Hay Coulee, about
seven miles southeast of the Colstrip plant location. Measurements and
tests were conducted during August, September and October, 1974.
EXPERIMENTAL
The mobile laboratory is equipped with the following instruments
that measure various parameters of the ambient air. The outputs of the
instruments described in points 1 through 4, below, are connected to a
data acquisition system. This system uses a mini-computer that scans
the instruments every five minutes and prints the data in engineering
units as hourly and daily (24 hr) averages. The data are stored on
magnetic tape.
1. Carbon monoxide (CO), methane (CH4), and reactive hydrocarbons
(total hydrocarbons less methane) are measured by a Beckman 6800 Air
Quality chromatograph that uses a flame ionization detector to measure
concentration as the compounds are eluted following separation by gas
chromatography. CO is converted to methane prior to detection.
213
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2. Nitric oxide (NO), nitrogen dioxide (N02), and total oxide of
nitrogen (NO ) levels are measured by a chemiluminescent analyzer.
A
Ambient air is drawn into the analyzer where the NO reacts with ozone in
the detector cell. Light generated by this reaction is measured by a
photomuliplier tube. The resultant signal is transferred to a memory
circuit. After the sample passes thrdugh a converter that changes the
NO into NO, the signal is subtracted from the NOV signal. The difference
A V\
represents the N0« level. The three signals are then channeled into a
recording device.
3. Ozone (O.J and total sulfur (SO ) are measured by photomultiplier
•5 X
tubes that detect the light generated by reactions in the detection cell
of the instrument. In the 03 analyzer, the light is generated by a
chemiluminescent reaction between Oo and ethylene. Light is generated
in the SO instrument by burning sulfur-bearing compounds in a hydrogen-
A
rich flame.
4. Wind speed and direction are measured with a high frequency
tachometer and a 0-540° potentiometer. In addition solar radiation is
determined by a silicon photovoltaic cell in a solar meter.
5. Particulates are measured on a 24 hour basis by a standard Hi-
Vol sampler.
6. S02 and NOg permeation tubes and a cold cathode mercury vapor
lamp that measures 03 concentration are used to calibrate the appropriate
instruments. The calibrations are verified by wet chemical analysis as
described in the Federal Register (1971). A standard mixture of CO and
methane is used to calibrate the Beckman instrument. The mobile laboratory
also contains a gas chromatograph equipped with a data reduction system.
This unit is used to identify hydrocarbons in the ambient air. The
method is similar to that described by Rasmussen and Holdren (1972).
214
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RESULTS AND DISCUSSION
Table XI-1 summarizes data obtained during the 1974 August-October
sampling period. Of the 43 days that nitrogen oxide data were collected,
there were 5 days where the daily concentration of NO averaged 20 yg/m3 (2
pphm) or more; 5 days when the N02 daily concentration averaged 9 yg/m3
(0.5 pphm) or more; and 2 days when the average for NOX was 60 yg/m3 (3
pphm) or over. The highest daily averages were 34 yg/m3 (2.8 pphm) for
NO, 13 yg/m3 (0.7 pphm) for N0?, and 62 yg/m3 (3.3 pphm) for NOV. The
t* 'j\
highest individual hourly average recorded for both NO and NO occurred
September 8 at 2300 hours when the NO value was 60 yg/m3 (5.15 pphm) and
the NOV value was 100 yg/m (5.50 pphm). For N00 the highest hourly
A « &
average value of 35 yg/m (1.75 pphm) was recorded October 2 at 2100
hours.
Ozone data were collected for 51 days. The daily average exceeded
98 yg/m (5 pphm) on a single day only. That occurred on September 19
when the value was 109 yg/m (5.57 pphm). The highest individual hourly
average recorded was 135 yg/m3 (6.90 pphm) at 1800 hours September 18.
During the 42-day survey period, the highest average daily concen-
tration of SOX (17 yg/m3) was recorded on September 11. The daily
average equaled or exceeded 13 yg/m3 (0.5 pphm) only on three days the
O
daily average was equal to or greater than 3 yg/m (0.1 pphm) on 12
days.
The highest individual hourly average (52 yg/m3 = 2.0 pphm) occurred
on September 17 at 0900 hours.
Methane, carbon monoxide and reactive hydrocarbon data were collected
for 25 days.
215
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Ambient Air Quality Data
Table XI-1. Number of Days Daily Average Equal to or Greater Than Indicated Values
ro
Parameter
NO
N02
N0x
°3
S0x
CH4
CO
THC
Less
Hi-Vol
Particulate
>5pphm
0
0
0
1
0
>_ 2.00 ppm
1
0
0
>. 125 vg/m3
0
>, 4 pphm
0
0
0
10
0
>. 1 . 5 ppm
19
0
0
2^ 1 00 yg/m
0
>3 pphm
0
0
2
35
0
^ 1 . 0 ppm
23
0
2
>_ 75 yg/m3
1
>2 pphm
5
0
8
47
0
> 0.5 ppm
24
0
4
3
> 50 yg/m
7
>1 pphm
18
0
25
51
0
>_ 0.1 ppm
25
15
11
i 25 yg/m3
34
>^ .5 pphm
32
5
41
51
3
> 0.5 ppm
25
22
16
>. 10 yg/m
58
>.. 1 pphm
42
42
43
51
12
> -.01 ppm
25
24
21
3 > 5 yg/m3
60
Total
Days
43
43
43
51
42
25
25
25
61
"Highest
Value-Date
2.8 pphm
Aug. 28 - Sept.
.7 pphm
Sept. 26
3.3 pphm
Aug. 28
5.57 pphm
Sept. 19
.66 pphm
Sept. 11
2.08 ppm
Sept. 5
0.46 ppm
Oct. 5
1.25 ppm
Sept. 26
93.2 yg/m3
Sept. 26
Primary
Standard
1
5 pphm
100 pg/M3
8 pphm
14 pphm
--
9 ppm
35 ppm
0.24 ppm
75yg/m3
260ug/nr
Secondary
Std.
—
5 pphm
100 yg/M3
8 pphm
10 pphn
50 pphm
—
9 ppm
35 ppm
0.24 ppm
60yg/m33
-------
The highest average daily concentration of methane (1362 yg/m3 =
2.1 ppm) occurred on September 5; only 1 day of the 25 exceeded 1310
O
vig/m (2.0 ppm). The methane background is approximately 980 yg/m3 (1.5
ppm) since 19 days had an average equal to or greater than that value.
\
The highest daily average of CO was recorded October 5, 0.53 mg/m3
(0.46 ppm). Of the 25 days sampled, 15 had a daily average of at least
0.12 mg/m (0.1 ppm). The highest hourly average value, 0.92 mg/m3 (0.8
ppm), occurred October 5 at 0400 hours.
The daily average of the reactive hydrocarbon (total hydrocarbon
q
less methane) exceeded or was equal to 655 yg/m (1 ppm) 2 days out of
o
the 25. The highest daily average, 820 yg/m (1.25 ppm), was recorded
September 26. The highest hourly average occurred on October 16 at
0900, 1700 yg/m3 (2.6 ppm).
Particulate matter collected by the Hi-Vol sampler was recorded for
•i
61 days. The highest value, 93.2 yg/m , was recorded September 26.
3
Average value for the sampling period was 30.6 yg/m .
From August 22 through October 15, 1253 hourly averages of wind
speed and direction were recorded (Table XI-2). Wind was predominantly
from the west and northwest. Wind speeds of less than 1 mph are termed
"calm" and usually occurred during early morning. The average wind
speed ranged from 5 to 8 mph with gusts up to 30 mph. The highest
hourly value recorded was 26 mph.
Temperature was measured for the 60-day period from August 22
through October 20, 1974. The highest hourly average was 99°F, recorded
October 2 at 1700 hours. The lowest average was 21°F, recorded September
21 at 0600.
217
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WIND DIRECTIONAL FREQUENCIES1
Table XI-2
Calm N.NWWSWS_S£E_NE_
19% 12% 16% 19% 8% 9% 4% 9% 4%
Values are presented as percent of time that wind flows from each of
eight compass points.
218
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Hourly averages of incident solar radiation ranged from 0 to 1.56
calories per square centimeter per minute; the highest value was recorded
on August 23 at 1300 hours.
Relative humidity was measured for 18 days from October 3, through
October 20. The hourly average ranged from 15 to 86 percent. The
highest value was recorded October 4; the low of 15 percent was recorded
on 12 of the 18 days.
Average hourly concentrations of ozone, and nitric oxide, together
with mean temperature and solar radiation for the period of August 22
through September 26 are presented in Figure XI-1.
Future Activities
Ambient air quality characterization work will continue throughout
the 1975 growing season. Project staff anticipate that these data will
be available by December, 1975.
219
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8-1
ro
ro
o
Temperature
\ Solar
\ Radiation
02 04 06 08 10 12 14 16 18 20 22
HOUR OF DAY
rr
=>
rr
LJ
o_
^
LJ
0
24
Figure XI-1. Comparision of Hourly Averages of Ozone, Nitric Oxide,
Temperature and Solar Radiation.
-------
References
1. Federal Register. 1971. Vol. 36, No. 84, Friday, April 30.
2. Rasmussen, R. A. and M. W. Holdren. 1972. Support-coated open
tubular columns for trace analysis of air pollutants. Chromatography
Newsletter. 1(2).
221
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SECTION XII
INTEGRATED AEROSOL CHARACTERIZATION MONITORING
by
Vernon E. Derr, G. T. McNice and Allen S. Lefohn
INTRODUCTION
The National Oceanic and Atmospheric Administration (NOAA) recently
joined the National Ecological Research Laboratory's (NERL) research
team on the Coal-Fired Power Plant Project at Colstrip, Montana. NOAA
will provide integrated aerosol characterization monitoring of the area
surrounding the Hay Coulee site. These data will be combined with the
NERL air quality data to yield an Integrated characterization assessment
of the Colstrip site.
Assessment of particulate pollution requires measurements of aerosols,
radiation, and meteorological conditions;
1. Particulates. Concentrations of particulates categorized by
size, shape, and chemical constitution will be determined. Their effects
on radiation and precipitation requires classification of condensation,
ice, or Aitken nuclei (less than 1 y). All measurements will be taken
on the ground; some will be taken at heights great enough to observe the
quantity of emitted material. The measurements will be collected by a
combination of in-situ ground sampling, aircraft sampling, and lidar
backscatter (ground based). To observe the geographical extent of stack
plumes, aircraft lidar will be utilized.
222
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A detailed description of the aerosol characterization facility
and the lidar system is presented in Table XII-1.
2. Radiation Effects. Two radiation measurements are important.
First, the rate at which solar energy reaches the earth as a function of
wavelength will be measured (baseline) while the power plant is still
inoperable. The changes registered during succeeding measurements while
the plant is operating will be correlated with the particulate loading
and changes in cloud cover. Also, by using aircraft and ground-based
instruments, the earth's net heat loss will be determined with an
infrared radiometer by measuring the upward and downward radiation.
Infrared (IR) fluxes within and outside the plumes will be measured.
3. Meteorological Conditions. Meteorological variables will be
measured by standard instruments. However, the meteorological conditions
that tend to trap pollutants below temperature inversions are best
measured by an acoustic sounder (Table XII-1).
An instrumented cloud physics trailer will be located on site.
This trailer is equipped to take continuous measurements of Aitken
nuclei (active at 300 percent supersaturation), cloud condensation
nuclei (active at 0.1 percent supersaturation), aerosol light scattering,
and standard meteorological parameters such as wind speed and direction,
temperature, and humidity.
The in-situ elemental composition of individual aerosol
particles will be derived from the real time output of a C02 laser
spectrochemical analyzer. It operates by (1) decomposing the aerosol in
the focal point of 50 watt 10.6 radiation; (2) exciting the atoms
223
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Tafele XII-1
Aerosol Characterization Measurement
Proposed Measurements
Aerosols
Concentration
Size
Elemental Composition
Cloud-condensation nuclei
(effective at <1% super-
saturation)
Ice nuclei (effective at
-20°C water saturation)
Aitken nuclei (effective
at >100% supersaturation)
Aerosol visible light
scatter
Insolation rates
Infrared radiation (down-
ward)
Infrared radiation (upward)
Meteorological variables
Temperature
Humidity
Wind
Cloud cover
Temperature inhomogeneities, Acoustic
inversion, stability of Sounder
the atmosphere
Turbidity
Abbreviations
Instruments
Lidar
ABL
ABA, ACF
ABA
ACF
ACF
ACF
ACF
ABA
ACF
ACF
Spectral
pyrheliometer
Pyranometer
IR radiometer
Airborne IR
radiometer
Standard IS
Instruments
Range
H
US
SS.ISS
SS
IS
IS
IS
IS
SS.IS
IS
IS
IS
IS
IS
US
Meteorological
Effects
Radiation
Precipitation
Radiation-Clouds
Radiation-Clouds
Clouds-
precipitation
Clouds-
precipitation
Clouds-
precipitation
Clouds-
precipitation
Solar Energy
flux
Radiation
balance
Radiation
balance
Lidar*
Integrating
Nephelometer
Volz turbidity
meter
HA
H
IS
Pollution
Trapping
Visibility
1.
2.
3.
ACF
ABL
ABA
4. H
In-situ aerosol characterization facility (NOAA)
Airborne lidar (EPA-NERC-Las Vegas)
Airborne aerosol measurements (small aircraft, primarily
spot sampling near Col strip)
Over the hemisphere whose radius is the lidar range
(10-20 km)
5. IS - In-situ ground sampling
6. SS - Spot sampling
7. US - Wide area, less detailed sampling
8. HA To height within the range of the acoustic sounder (up to 5000 ft.)
*Approximately, but over large volumes
224
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released from the particles; and (3) spectrophotometric detection of
atomic and molecular emissions with subsequent analysis in a multichannel
analyzer.
Nuclepore membrane filters are exposed to the airstream of
predetermined time intervals. The samples will be returned to NOAA's
Wave Propagation Laboratory at Boulder, Colorado, for size distribution
and elemental composition analysis of single particles by scanning
electronmicroscopy and x-ray energy spectrometry.
Ground measurements will be verified by those from an instru-
mented light aircraft. The equipment consists of an isokinetic filter
sampling probe used to collect samples for elemental and size distribu-
tion analyses; a Gardner fine particle counter; and an infrared radiometer
for the in-situ measurement of the IR absorption coefficient. With this
equipment the researchers will determine the vertical profile of Aitken
nuclei concentrations, aerosol size distributions, and aerosol chemical
composition. The radiometer data will be inverted into IR extinction
coefficients, and the aerosol absorption index will be determined by a
comparison of the measured and calculated extinction based on size
distributions of the particles. These data permit conclusions regarding
the effects of aerosols on radiometric measurements in the 8 to 12 ym atmospheric
window.
The filter samples taken on the ground and in the air will be
analyzed by a system using a scanning electron microscope (SEM) and an
x-ray energy dispersive spectrometer (XES). This instrument classifies
the low-volatile portion of the atmospheric aerosol by particle size,
shape and elemental composition. The data from these instruments are
correlated to the cloud physics parameters. This procedure will reveal
the origins of atmospheric nuclei and their residence times and sinks.
225
-------
The remote sensing lidar system will consist of multiple
wavelength laser transmitters and receivers with polarization-sensitive
detectors, a microwave radar, and a radiometer. Using these lidar
techniques, the researchers intend to obtain data on the characteristics
of atmospheric particulate matter over large areas of the atmosphere.
SCHEDULE
Generally, observations of aerosols will be confined to the growing
season (April to October).
To establish baselines, observations will be made from 15 May to 15
June and 15 August to 15 September of 1975 while the power plant is not
operating. Projections for future work are:
1976 May, August
1977 May, August
1978 May, August
\
Through the cooperation of NOAA and other laboratories joining with
NERL, it will be possible to maintain a coordinated effort resulting in
a more precise characterization of the Col strip environment, both before
and after the power plant goes into operation. The data collected in
this phase will be available to the biologists so that biological
effects observed on the ground can be correlated with recorded changes
in air quality.
226
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APPENDIX A
BIOMASS DYNAMICS AND PRIMARY PRODUCTION IN MIXED PRAIRIE GRASSLANDS
IN SOUTHEASTERN MONTANA: BASELINE DATA FOR AIR
POLLUTION STUDIES
by
W. K. Lauenroth
J. L. Dodd
R. K. Heitschmidt
and
R. G. Woodmansee
INTRODUCTION
The extensive grasslands of southeastern Montana have been, until
recently, the single most valuable resource in the region. Now with the
crisis in energy supplies coal, another important resource in the region,
is assuming increased importance, thus raising questions concerning the
conflict between the two resource uses. This paper reports on primary
producer biomass dynamics and productivity for four sites witin 20 km of
an emission source, and for another site located at a distance of 60 km.
The data for this report, from 1974, represent an estimate of baseline
conditions for the sites from the year previous to the year of activation
of the first of two and possibly four generating plants at Colstrip.
Our project is part of a large total system study described by Lewis et
al. (10). The research reported here is concerned with the character-
ization of the mixed-grass prairie in southeastern Montana. This charac-
terization is the first phase of studies which are intended to assess
the effects of atmospheric emissions from a large coal-burning electrical
plant on the mixed-grass prairie.
227
-------
Our long-term study plan is to determine the effect of the emissions
on primary producer biomass dynamics and productivity by comparing pre-
emission measurements (ecosystem characterization) with similar measure-
ments taken for two or more years following activation of a nearby coal-
fired generating plant complex. The four study sites have been established
that, according to unpublished diffusion model predictions (Allen Lefohn
and Robert Lewis, personal communication), will be exposed to a gradient
of atmospheric pollution from the generating plants located at Col strip,
Montana. The sites are located at varying distances southeast of the
generating plant. The direction of the prevailing winds are from the
northwest.
Measurements of producer biomass dynamics and net production have
not been previously reported for the mixed prairie in southeastern
Montana. Several studies in this region have described structural
characteristics (11, 19) and responses to various grazing treatments (5,
6). Net primary production and intraseasonal biomass dynamics have been
reported for the mixed prairie in North Dakota (8) and South Dakota (3,
9).
Understanding the intraseasonal dynamics of primary producer and
the net production of the grassland will be an important link in under-
standing the effects of power plant emissions on the mixed prairie
ecosystem.
SITE DESCRIPTION
The study areas are located within the mixed prairie region of
southeastern Montana. Four sites are near Col strip in Rosebud County
(Hay Coulee, Kluver West, and Kluver North, and Kluver East) while the
remaining site is approximately 64 km southeast in the Fort Howes Division
of Custer National Forest in Powder River County (Table 1). All five
228
-------
sites were fenced to exclude livestock prior to the 1974 grazing season.
Taylor et al. (14) estimated the range condition of the sites as good to
low good according to the method utilized by the Soil Conservation
Service (13).
The mixed prairie has been characterized as a mixture of mid- and
shortgrasses (17). Dominant grass species in the southeastern Montana
region include western wheatgrass, (Agropyron smithii), needle-and-
thread-grass (Stipa comata), green needlegrass (Stipa viridula). prairie
June grass (Koeleria cristata), and Sandburg blue grass (Poa secunda).
Other characteristic species include Japanese brome (Bromus japonicus),
needleleaf sedge (Carex eleocharis), blue grama (Bouteloua gracilis),
Hood's phlox (Phlox hoodii), common salsify (Tragopogon dubi'us). and
fringed sagewort (Artemisia frigida).
The topography of the study region consists of steep rising buttes,
and broad gently sloping valleys. The steeper buttes support Pinus
ponderosa-Juniperus scopulorum communities whereas the hillsides and
valleys are dominated by grasslands. The grassland soils were derived
from parent material deposited as outwash from the surrounding buttes.
Each site's geographical location, slope, aspect, elevation, soil texture
and dominant species are presented in Table 1.
The Northern Plains climate is characterized as semiarid, continental
and extremely variable (15). Long-term climatological records (T.
Weaver, personal communication) from near Colstrip reveal a mean annual
precipitation of 396 mm with approximately 50% falling during the spring
growing months of April, May, and June. The mean monthly maximum temper-
ature ranges from 32°C in July to 1°C in January with mean minimum
temperatures approximately 17°C less. The average frostfree period is
approximately 130 days beginning in mid-May (4).
229
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METHODS
Above- and belowground plant biomass was sampled by the harvest
method on six dates at the Colstrip sites (10 May, T5 June, 1 July, 24
July, 12 August, and 26 September) and two dates at the Ash Creek site
(3 June and 10 July). On each date five circular 0.5-m quadrats were
clipped on each of two replicates at the Colstrip sites and on each of
the eight replicates at the Ash Creek site. All aboveground biomass was
separated by species and into the following categories: current live,
recent dead (current year's production), old dead (previous year's
production), and perennial live. Species or categories estimated to
make up less than 1 g in any quadrat were not harvested. All harvested
material was oven-dried at 60°C to a constant weight.
Litter biomass was collected with a vacuum cleaner after the standing
biomass was removed. These samples were later rinsed with water, oven-
dried, weighed, and ashed. All litter weights are expressed on an ash-
free basis.
Belowground biomass was sampled from each harvested quadrat by
means of three soil cores, 7.5 cm in diameter x 10 cm deep on each
sample date. In addition to this on 27 July 10 cores 5 cm in diameter x
60 cm deep were taken on each site to assess the vertical distribution
of belowground biomass. These soil cores were separted into 10-cm
increments. Roots were removed from the soil cores by the method of
Lauenroth and Whitman (7). The samples were then oven-dried, weighed,
and ashed. Belowground biomass is reported on an ash-free basis.
RESULTS
Aboveground Biomass
/
Seasonal dynamics of total current live (CL), recent dead (RD), and
230
-------
old dead (OD) for the Colstrip sites are presented in Figure 1. Dynamics
of the three categories was similar across sites. The peak in CL occurred
on 15 June for all sites and all peaks were approximately 100 g/m2.
Differences among the sites in CL biomass were evident following the
peak. Current live biomass declined steadily on the Hay Coulee and
Kluver West sites until the last sample date. For Kluver East and
Kluver North CL remained at a high level until mid-August.
Recent dead biomass increased throughout the season on all sites.
The sites with a faster decline in CL also had a faster increase in RD.
In all cases, RD peaked on the final date. Old dead which represents
biomass carried over from previous growing seasons showed a peak early
in the season and declined subsequently.
An overview of the dynamics of total biomass by categories indicates
a high degree of similarity among sites. The seasonality of all sites
is similar to other northern mixed prairie sites for which data are
available (3, 8, 9).
Analysis of primary producer biomass dynamics by individual species
should maximize the amount of information conveyed to the reader.
However, the variability associated with estimates of individual biomass
limits discussions to the most abundant species. For this reason we
have placed emphasis on discussion of biomass dynamics by phenologically
similar growth form groups (viz. cool season grass, warm season grasses,
cool season forbs, warm season forbs, half-shrubs). Cool season species
make the largest portion of their growth in spring and early summer, and
warm season species make their maximum growth in summer and early fall.
An additional reason for combining the data into groups is that cool
season species have been found in general to have the C3 Calvin-Benson
pathway of C02 fixation while warm season species have the C4 dicarboxylic
acid pathway (18). The significance of this for the mixed prairie is
231
-------
that C- plants have a lower temperature optimum for photosynthesis than
C. species (18) and hence their maximum growth is during the cooler
portion of the growing season. This implies that this method of grouping
approximates functional groups.
Cool season grasses are the most important group occurring on the
sites. Figure 2 represents the dynamics of current season production
(CL + RD) for cool season grasses and the three most important species
comprising this group. Peaks in cool season grass production occurred
during June and July in 1974 and ranged from 100 g/m for the Kluver
West site to 55 g/m2 for Kluver North (Fig. 2a). The differences in
cool season grass production among the sites are primarily attributable
to differences in production of Stipa comata (Fig. 2b). Peak production
2
for S. comata ranged from zero to more than 50 g/m . The sites separated
into two groups on the basis of Agropyron smithii biomass (Fig. 2c).
Hay Coulee and Kluver East had peaks in current season production of
2
approximately 40 g/m and remaining-sites had peaks of approximately 20
2
g/m . The annual grass Bromus japonicus was most abundant on the Kluver
West site (Fig. 2d).
Half-shrubs were the second most productive group occurring on the
sites except for Kluver West where there were few half-shrubs. The
dynamics of current season production was bimodal for all three sites
(Fig. 3a). The early peak occurred in June and the second peak in
August and September. Artemisia frigida contributed more than 80% of
the current production in the half-shrub group on all three sites.
Warm season grasses (Fig. 3b) occurred on all four sites. Peak
2
production ranged from 4 to 16 g/m . The peaks were not as distinct as
in the previously mentioned groups largely because of the tendency of
the major species Bouteloua gracilis to grow in patches. Standard
errors for peak current season production estimates were typically
232
-------
greater than 25% of the mean for B. gracilis to grow in patches. Standard
errors for peak current season production estimates were typically
greater than 25% of the mean for B^ gracilis compared to estimates of
the same value for A. smithii which had standard errors of less than 25%
of the mean. The sites with the greatest production of warm season
grasses, Hay Coulee and Kluver North, had peaks in August.
Of the 24 species comprising the cool season forb group only one
species, Tragopogon dubius, was found in amounts of 1 g or more on all
sites. Peaks in cool season forb production occurred in June and July
2
and ranged from 10 to 16 g/m (Fig. 3c). The August peak measured on
the Hay Coulee site was attributable to a dense patch of Phlox hoodii
that occurred in one of the quadrats. We do not feel that the sample
was a valid estimate of P. hoodii production for the entire site.
Warm season forbs was the least productive group with no one species
occurring in amounts of 1 g or more on all sites. Peak production
2
ranged from 0.14 to 3.5 g/m . No figure is presented for this group
since measurable biomass was not encountered on all sites for several of
the sample dates.
Since the Ash Creek site was sampled only twice during the 1974
season, no figures of these data are presented. Judging from the results
from the other sites, we assume that the two samples were very close to
the peak biomass of the majority of the species. Peak current season
production of the various groups were similar to the Colstrip sites
except that there were essentially no warm season grasses. Peak production
2
for cool season grasses and cool season forbs was 73 and 21 g/m ,
respectively. Half-shrub production was 20 g/m and warm season forbs
2
contributed 2 g/m to total production.
233
-------
Litter Biomass
2
Estimates of litter standing crop ranged from less than 150 g/m to
P
more than 200 g/m and exhibited few if any definite trends in seasonal
dynamics (Fig. 4). It appears that a net decline may have occurred over
the course of the growing season. Consistent differences in litter
standing crop do not exist among the Colstrip sites. The Ash Creek site
appears to have lower amounts of litter than the Colstrip sites, at
n O
least during early June (153 g/m ) and early July (154 g/m ).
Belowground Biomass
Since sampling was not initiated until 15 May, we gained an incomplete
picture of the intraseasonal dynamics of root biomass in 1974. Although
there were no dramatic changes in root biomass during the sampling
period on the Colstrip sites, a net decline in root mass took place
between May and September (Fig. 5)* Since the sampling method used to
determine root biomass does not partition the material into live and
dead components, it is impossible to ascertain from these data the
dynamics of each of these components (live and dead). Other studies (3,
9) have shown that there is often a decrease in root biomass very early
in the season that is succeeded by an increase following more complete
development of the photosynthetic tissue. We suspect that such a decrease
occurred well before our first sampling date.
The vertical distribution of roots was examined on one date for
each of the five study sites. Differences in the vertical distribution
of root biomass did not exist among the Colstrip sites. However, the
Ash Creek site had a higher proportion of the total root biomass in the
0-10 cm level than the Colstrip sites (Fig. 6). This may be the result
of differences in botanical composition, soil characteristics, or grazing
history. Differences between the areas do not exist when the 0-30 cm
234
-------
level proportions of total root biomass are compared for the Col strip
and Ash Creek (77% and 79%, respectively).
Net Primary Production
Many methods have been used to estimate net aerial production from
harvest data (12) although it is difficult to determine a "best" method.
We have selected two methods: The first involves summing the peak
amounts of current production (live + recent dead) for each functional
group, and the second method entails summing the peak production estimates
of each species. The first method has the advantage of smaller standard
errors associated with the estimates of current growth. The second
method considers that the phenology of each species is distinct and that
peak growth within the groups is not necessarily attained at the same
time.
Net aerial primary production for the five sites estimated by the
2
first method ranged from 106 to 123 g/m (Fig. 7). Estimates by the
second method were higher as expected and ranged from 117 to 149 g/m
(Table 2).
Dahlman and Kucera (2) have shown that minimal estimates of the
portion of net primary production translocated belowground can be made
by examining belowground biomass dynamics -and considering significant
increases within the season as belowground primary production. Only one
site (Kluver West) exhibited a significant increase (about 120 g/m ).
DISCUSSION
The suitability of the study sites to meet our objectives of assessing
the effects of atmospheric emissions from a large coal-burning electrical
power plant on the vegetation of the northern mixed prairie requires
235
-------
that they meet two general criteria. The first is that the sites are
"typical" northern mixed prairie sites enabling us to generalize our
results to a larger area; the second is that the sites are homogenous
enough so that treatment effects can be separated from site differences.
From the point of view of vegetation structure our sites appear to
be "typical" of many northern mixed prairie sites. Weaver and Clements
(17) list the most widespread dominants of the mixed prairie as Stipa
comata, Sporobolus cryptandrus, Agropyron smithii, Koeleria cristata,
Bouteloua gracilis, and Buchloe dactyloides. Agropyron smithii is one
of the dominants on all of our sites, sharing dominance with Bouteloua
gracilis on the Hay Coulee site, Stipa comata on Kluver West, Sti pa
comata and Artemisia frigida on both the Kluver North and Kluver East
sites, and Koeleria cristata on the Ash Creek site. Coupland (1) described
the distribution of A. smithii as extending from southern Canada to
Texas, and Weaver and Albertson (16) described A. smithii as one of four
dominant grasses that occur throughout the extent of the mixed prairie.
Singh et al. (12) investigated the range of values obtained by 31
methods of calculating aboveground net primary production in grasslands
from harvest data. They report 64 estimates of aboveground production
for a northern mixed prairie site in North Dakota and 186 estimates for
a similar site in South Dakota. The range of estimates for both grazed
and ungrazed grasslands in North Dakota was 119 to 471 g/m . Estimates
by the two techniques that we used in this paper were 351 g/m2 by summing
peak current production by species and 208 by summing peaks of functional
groups for the ungrazed area and 208 by summing peaks of functional
groups for the ungrazed area and 302 and 206 g/m for the grazed area.
In comparison our sites are less productive. The difference in production
was mainly attributable to the greater productivity of Stipa comata
on the North Dakota site.
236
-------
Aerial net primary productivity estimates for the South Dakota site
over 3 years of measurement ranged from 173 to 973 g/m2 for the ungrazed
treatment and 129 to 619j g/m for the grazed (12). Estimates by summing
species peaks ranged frbm 248 to 365 g/m2 for the ungrazed grassland and
2
163 to 220 g/m for the grazed. Summing peak production by groups
yielded a range of 193 to 235 g/m2 for the ungrazed and 139 to 249 g/m2
for the grazed treamtent. Again the Montana sites were less productive
than the South Dakota grassland, but the estimates overlap at the lower
end of the range. Rainfall at the sites reported by Singh et al. (12)
was above average during the years that harvest data were reported.
Precipitation data from Colstrip, Montana, approximately 15 km from the
sites indicate that April and May of 1974 were wetter than normal, but
June, the month in which cool season grass peak production was measured,
was 57 mm below average.
Analysis of variance of aerial net primary production by species
groups (Table 3) indicates that there were no differences in average net
primary production among the Colstrip sites in 1974, but that there was
a significant (P < 0.001) site x functional group interaction. Evaluation
of the site x group interaction revealed that the significant response
was attributable to the data from the Kluver West site. The almost
complete lack of half-shrubs on this site (Fig. 3) was compensated for
by a 40% increase in the net production of cool season grasses (Fig. 2).
Repeating the analysis without the Kluver West data (Table 4) resulted
in a nonsignificant site x group interaction indicating that the contri-
bution of species groups to net primary production was not different
among the three remaining sites. On this basis we can conclude that
three of our sites are similar enough to separate any effects of air
pollution from site differences. These results do not mean that the
Kluver West site will be of no use to our study because many of our
future analyses will be concerned with the changes in individual sites
as a function of time of exposure to power plant emissions. The dominant
237
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species on Kluver West site Stipa comata is well represented in other
mixed prairie communities and the fact that we have two community types
represented in our study may increase the generality of our results.
ACKNOWLEDGEMENTS
This paper reports on work supported in part by Environmental
Protection Agency Grant R 803176-01.
238
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REFERENCES
i
1. Coup!and, R. T. 1950. Ecology of mixed prairie in Canada. Ecol.
Monogr. 20:271-315.
2. Dahlman, R. C., and C. L. Kucera. 1965. Root productivity and
turnover in native prairie. Ecology 46:84-89.
3. Dodd, J. L., J. K. Lewis, H. L. Hutcheson, and C. L. Hanson. 1974.
Abiotic and herbage dynamics studies at Cottonwood. 1971. US/IBP
Grassland Biome Tech. Rep. No. 250. Colorado State Univ., Fort
Collins, 195 p.
4. Energy Planning Division, Montana State Department of Natural
Resources and Conservation. 1974. Draft environmental impact
statement on Colstrip electric generating units 3 and 4, 500 kilowatt
transmission lines and associated facilities. Helena, Montana.
5. Houston, W. R. 1963. Plains prickly pear, weather, and grazing in
the Northern Great Plains. Ecology 44:569-574.
6. Houston, W. R., and R. R. Woodward. 1966. Effects of stocking
rates on range vegetation and beef cattle production in the Northern
Great Plains. USDA Tech. Bull. No. 1357. 58 p.
7. Lauenroth, W. K.s and W. C. Whitman. 1971. A rapid method for
washing roots. J. Range Manage. 24:308-309.
8. Lauenroth, W. K., and W. C. Whitman. 1975. Dynamics of dry-matter
production in a mixed-grass prairie in western North Dakota.
(Submitted to Ecology).
239
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9. Lewis, J. K., J. L. Dodd, H. L. Hutcheson, and C. L. Hanson. 1971.
Abiotic and herbage dynamics studies on the Cottonwood Site, 1970.
US/IBP Grassland Biome Tech. Rep. No. 111. Colorado State Univ.,
Fort Collins. 147 p.
10. Lewis, R. A., A. S. Lefohn, and N. R. Glass. 1975. The Montana
coal-fired power plant project: Introduction and perspectives.
Proceedings of the Fort Union Coal Field Symposium, Billings,
Montana, 25-26 April. (This symposium).
11. Morris, M. W. 1946. An ecological basis for the classification of
Montana grasslands. Proc. Mont. Acad. Sci. 6:41.
12. Singh, J. S., W. K. Lauenroth, and R. K. Steinhorst. 1975. Review
and assessment of various techniques for estimating net aerial
primary production in grassland from harvest data. Bot. Rev. (in
press).
13. Soil Conservation Service, USDA. 1971. Technician's guide to
range sites, condition classes and recommended stocking rates in
soil conservation districts of the sedimentary plains of Monatana;
10-14 and 15-19 inch precipitation zones.
14. Taylor, J. E., W. Leininger, and R. Fuchs. 1974. Site descriptions
and effects of coal-fired power plant emissions on plant community
structure. First Interim report, Col strip, Montana. National
Ecological Research Laboratory, Con/all is, Oregon.
15. Thornthwaite, C. W. 1941. Atlas of climatic types in the United
States 1900-1939. U.S. Dep. Agric. Misc. Pub. No. 421.
240
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16. Weaver, J. E., and F. W. Albertson. 1956. Grasslands of the Great
Plains: Their nature and use. Johnsen Pub. Co., Lincoln. Neb.
395. p.
17. Weaver, J. E., and F. E. Clements. 1938. Plant ecology, 2nd ed.,
McGraw-Hill Book Co., New York.
18. Williams, G. J., Ill, and J. L. Markley. 1973. The photosynthetic
pathway type of North American shortgrass prairie species and some
ecological implications. Photosynthetica 7(3):262-270.
19. Wright, J. C., and E. A. Wright. 1948. Grassland types of south-
central Montana. Ecology 29:448-460.
241
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Table 1. LOCATION, SLOPE AND ASPECT, ELEVATION, SOIL TYPE, AND DOMINANT PLANT SPECIES FOR FIVE MIXED
PRAIRIE SITES IN SOUTHEASTERN MONTANA'
Sites Location Slope and Aspect Elevation
Hay Coulee 12 km south- 4% North 930 m
east of
Col strip
Kluver West 12 km east- 6% North 920 m
southeast of
Col strip
£ Kluver North 15 km 5% Northeast 900 m
east-southeast
of Col strip
Kluver East 19 km east- 3 1/2% Northeast 900 m
southeast of
Col strip
Ash Creek 64 km southeast 4-5% Northeast 1170 m
of Ashland
2
Soils Dominant Species
Clay loam Agropvron smithii
Bromus .iaponicus
Bouteloua gracilis
Artemisia frigida
Traqopoqon dubius
Sandy loam Stipa comata
Bromus .iaponicus
Agropyron smithii
Sandy loam Artemisia friqida
Stipa comata
Aqropvron smi thi i
Bromus .iaponicus
Tragopogon dubius
Bouteloua gracilis
Clay loam Agropyron smithii
Artemisia frigida
Bromus japonicus
Stipa comata
Silt loam Agropyron smithii
Koeleria cristata
Calamagrostis montanensis
Bromus .iaponicus
Artemisia cana
description after Taylor et al. (14).
o
Based on harvest data in 1974
-------
Table 2. PEAK CURRENT SEASON PRODUCTION (G/M2), STANDARD ERROR OF ESTIMATE, AND THE DATE (DAY/MO), WHEN THE
PEAK OCCURRED, BY SPECIES, FOR FIVE MIXED PRAIRIE SITES IN SOUTHEASTERN MONTANA IN 1974.
Species
COOL SEASON GRASSES
Agropyron cristatutn
Agropyron smithii
Bromus japom'cus
Calamagrostis montanensis
Carex eleocharis
Carex filifolia
Carex pennsylvanica
Festuca octoflora
Koeleria cristata
Poa secunda
[NiStipa comata
""WARM SEASON GRASSES
Aristida longiseta
Bouteloua gracilis
Schedonnardus paniculatus
Sporobolus cryptandrus
Hay Coulee
Mean
43.00
23.00
0.16
5.00
2.00
0.14
16.00
0.02
0.02
Std.
Error
3.00
4.00
0.06
3.00
0.50
0.14
4.00
0.02
0.02
Date
11/6
29/6
29/6
29/6
11/5
11/5
16/8
29/6
26/9
Kluver West
Mean
17.00
31.00
5.00
0.18
0.53
0.77
57.00
0.04
4.00
Std.
Error
5.00
3.00
1.00
0.02
0.45
0.33
5.00
0.04
2.00
Date
30/6
20/6
15/5
24/7
24/7
15/5
30/6
22/8
20/6
Kluver North
Mean
24.00
19.00
4.00
0.04
1.00
1.00
32.00
3.00
11.00
Std.
Error
6.00
5.00
3.00
0.03
0.67
0.39
8.00
2.00
4.00
Date
25/7
12/6
1/7
12/6
1/7
12/5
28/9
12/8
12/8
Kluver East
Mean
12.00
39.00
9.00
0.02
0.04
0.84
7.00
6.00
0.48
Std.
Error
3.00
5.00
2.00
0.02
0.03
0.41
3.00
3.00
0.46
Date
2/7
18/6
2/7
2/7
12/5
12/5
2/7
2/7
12/5
Ash Creek
Mean
23.00
14.00
9.00
0.40
0.43
0.21
25.00
9.00
0.58
Std.
Error
4.80
6.50
2.30
0.32
1.20
0.24
2.80
2.00
0.68
Date
10/7
10/7
10/7
10/7
3/6
3/6
3/6
3/6
10/7
WARM SEASON FORBS
Antennaria neglecta
Arnica fulgens
^ircium undulatum
Conyza canadensis
Conyza
Erigen
Erigeron spp.
Gaura coccinea
0.06 0.02
0.02 0.02
11/5
11/5
0.10 0.03 15/5
0.02 0.02
0.06 0.04
0.02 0.02 30/6 0.08 0.05
12/6
12/8
25/7
0.02 0.02
2/7
0.30
0.12
0.32
0.71
0.47
0.46
25
00
0.04 0.04 23/7 0.31 0.29
3/6
3/6
10/7
10/7
10/7
-------
Table 2. Continued
ro
Species
Grindelia squarrosa
Lygodesmia .iuncea
Orthocarpus lutea
Polvgala alba
Psoralea argophylla
Psora lea tenui flora
Ratibida column if era
Senecio spp.
Solidago rigida
Hay Coulee Kluver West
Std. Std.
Mean Error Date Mean Error
1.00 0.82
0.08 0.06 16/8
2.00 1.00
0.08 0.05
Kluver North Kluver East Ash Creek
Date
30/6
30/6
24/7
Std.
Mean Error
0.47 0.47
0.55 0.53
0.27 0.27
Std.
Date Mean Error
1/7
0.04 0.04
12/6 0.04 0.04
1/7
Date Mean
0.72
26/9
2.00
23/7 2.00
0.008
0.13
Std.
Error
0.49
1.00
2.00
0.008
5.00
Date
10/7
10/7
10/7
3/6
10/7
COOL SEASON FORBS
Achillea mi 11efoliurn
Androsace occidental is
Astragalus spp..
Cvmqpterus acaulis
Descurainia SPP.
Draba reptans
Ervsimum asperum
Hedeoma hispida
Lappula redowskii
Lepidium densiflorum
Leucocrinuin montanum
Lithospermum incisum
Li'num riqidum
Lomatium orientale
Penstemon spp.
Plantago patagonia
Phlox hoodii
Selaginella densa
Sphaeralcea coccinea
0.02
0.06
0.02
0.02
0.02 0.02
0.50 0.26
0.12 0.03
0.42
0.06
0.36
6.00
0.29
0.02
0.03
5.00
0.04 0.02
11/5
11/6
11/5
29/6
11/6
16/8
11/5
29/6
16/8
11/5
0.06
0.04
0.02
0.12
1.00
0.28
0.08
0.77
0.02
0.04
0.02
0.03
1.00
0.06
0.03
0.35
0.04 0.02
3.00
2.00
1.00
2.00
1.04 0.93
15/5
24/7
28/9
15/5
30/6
30/6
20/6
15/5
15/5
30/6
15/5
20/6
0.04
0.15
0.02
1.00
0.20
0.16
0.47
0.02
0.02
0.28
0.02
0.13
0.02
0.91
0.07
0.06
0.16
0.02
0.02
0.06
1.00 1.00
12/6
12/5
12/5
1/7
1/7
1/7
12/5
12/5
28/9
1/7
25/7
15.00 5.00
0.08 0.02
0.06 0.15
0.001 0.005
0.63
0.10
0.02
0.10
0.16
3.00
0.58
0.03
0.02
0.10
0.06
3.00
2/7
23/7
2/7
18/6
2/7
13/8
0.12
0.07
0.07
0.22
0.03
0.29
0.07
0.24
0.02 0.02
0.62 0.50
3.00 3.00
0.003 0.01
0.46 0.26
10/7
10/7
10/7
10/7
10/7
3/6
3/6
3/6
3/6
3/6
3/6
10/7
3/6
-------
Table 2. Continued
Species
Taraxicum officinale
Tragapogon dubius
Vicia americana
Z.ygadenus elegans
Misc.
HALF-SHRUBS
Artemisia cana
Artemisia dracunculoides
Artemisia frigida
Artemisia ludoviciana
Artemisia tridentata
Eurotia lanata
Gutierrezia sarothrae
Rosa arkansana
Hay Coulee
Mean
3.00
9.00
0.10
0.04
11.00
0.08
2.00
0.45
Std.
Error
0.85
2.00
0.03
0.04
4.00
0.06
2.00
0.45
Kluver West
Std.
Date Mean Error Date
11/5 0.41 0.28 20/6
29/6 5.00 0.59 20/6
11/5 0.17 0.17 30/6
26/7
29/6 0.27 0.23 30/6
16/8
11/5
26/9
Kluver North Kluver East
Std.
Mean Error
0.17 0.13
12.00 1.00
0.02 0.02
0.02 0.02
37.00 5.00
Std.
Date Mean Error Date
12/5 0.24 0.07 2/7
1/7 6.00 1.00 2/7
12/5
1/7 0.04 0.04 23/7
12/8 29.00 6.00 18/6
Ash Creek
Mean
3.00
2.00
0.002
0.07
0.42
0.25
0.01
12.00
2.00
5.00
0.001
Std.
Error
1.00
1.00
0.01
0.09
0.47
0.41
0.05
4.00
2.00
3.00
0.005
Date
3/6
10/7
10/7
3/6
3/6
3/6
10/7
10/7
10/7
10/7
10/7
OTHERS
Parmelia chlorochroa
Mammilaria spp.
Opuntia polvacantha
Opuntia fragilis
Echinocereus viridiflorus
0.04
0.04
0.02
0.04
29/6
26/7
0.02
0.08
0.04
0.41
0.02
0.06
0.03
0.29
15/5
24/7
30/6
20/6
0.02 0.02
0.04 0.04
0.08 0.06
0.08 0.06
12/6
25/7
25/7
25/7
0.57
0.04
0.57
0.04
18/6
23/7
TOTAL NET PRODUCTION
123
134
149
114
133
-------
Table 3. Analysis of variance for the response of aerial net primary
production to the four Col strip sites and five primary
producer groups.
Source
d.f.
Sum of
Squares
Mean
Square
Sites 3
Groups 4
Site x Group 12
Error 20
92.26
22749.10
7649.99
1345.83
31.09
5687.28
637.50
67.29
0.46
84.52
9.47
0.713
<0.0001
<0.0001
246
-------
Table 4. Analysis of variance for the response of aerial net primary
production to the Kluver North, Kluver East and Hay Coulee
sites and five primary producer groups.
Source
Sites
Groups
Site x Group
Error
d.f.
2
4
8
15
Sum of
Squares
74.81
13864.85
776.16
1295.08
Mean
Square
37.40
3466.21
97.02
86.34
F
0.43
40.15
1.12
P
0.658
<0.0001
0.404
247
-------
FIGURE TITLES
Fig. 1 Seasonal dynamics of current live, recent dead, and old dead
biotnass for the four Colstrip sites in 1974: (a) Hay Coulee
(b) Kluver North, (c) Kluver East, and (d) Kluver West.
Fig. 2 Seasonal dynamics of current production (current live + recent
dead) of (a) cool season grasses, (b) Stipa cpmata, (c) Agro-
pyron smithii, and (d) Bromus japom'cus for the four Colstrip
sites in 1974.
Fig. 3 Seasonal dynamics of current production (current live + recent
dead) of (a) half-shrubs, (b) warm season grasses, and (c)
cool season forbs for the four Colstrip sites in 1974.
Fig. 4 Seasonal dynamics of litter biomass for the four Colstrip
sites in 1974.
Fig. 5 Seasonal dynamics of root biomass for the four Colstrip sites
in 1974.
Fig. 6 Comparison of the vertical distribution of root biomass between
the mean of the four Colstrip sites and the Ash Creek site.
Fig. 7 Functional group composition of total net aerial production
and standard errors for the five mixed prairie sites in south-
eastern Montana in 1974.
248
-------
ISOr
.. 'oo-
50
ISOr
„ 100-
50-
Moy I JuriI Jui1 Aug T
•Old Dead
• Recent Dead
Current Live
Sep
May 1 Jun 1 Jul 1 Aug 1 Sep
ISOr
~ 100-
50-
I50r
„ 100-
May 1 Jun 1 Jul 1 Aug 1 Sep
May 1 Jun 1 Jul 1 Aug 1 Sip
Fig. 1 Seasonal dynamics of current live, recent dead, and old dead
biomass for the four Colstrip sites in 1974: (a) Hay Coulee
(b) Kluver North, (c) Kluver East, and (d) Kluver West.
249
-------
lOOr
A
I/ N
A
Hay Coulee
Kluver North
Kluver West
Kluver East
100
OJ
<0
to
O
O
m
-4----} ~~
50
-------
lOOi-
IOO
^^^
"e
in
(0
o
_o
m
50
E
>^
a>
O
E
o
CD
50
May I Jun I Jul T Aug I Sep
Hay Coulee
Kluver North
Kluver West
Kluver East
May
Sep
ro
en
lOOr
N
E
S
-------
250
CVJ
tfl
CO
O
O
CD
0)
200
150
i
\
Hay Coulee
Kluver North
Kluver West
Kluver East
0
May I Jun
Jul
Aug I Sep
Fig. 4 Seasonal dynamics of litter biomass for the four Col strip
sites in 1974.
252
-------
600
500
o>
(0
o
E
p
5
o
400
Hay Coulee
Kluver North
Kluver West
Kluver East
0
May
Jun
Jul
Aug I Sep
Fig. 5 Seasonal dynamics of root biomass for the four Col strip sites
in 1974.
253
-------
0-IO
10-20
_ 20- 30
E
o
30-40
o
CO
40-50
50-60
Colstrip
Ash Creek
10 20 30 40 50
Percentage of Total Root Biomass
60
Fig. 6 Comparison of the vertical distribution of root biomass between
the mean of the four Colstrip sites and the Ash Creek site.
254
-------
ro
en
on
c
o
0>
<
tt)
120
100
80
u
3
•o
2 60
a.
40
20
[I Cool Season Grasses
Warm Season Grasses
Cool Season Forbs
I
Warm Season Forbs
Half Shrubs
i
Hay Coulee Kluver West Kluver North Kluver East Ash Creek
Fig. 7 Functional group composition of total net aerial production and standard errors for the
five mixed prairie sites in southeastern Montana in 1974.
-------
APPENDIX B - PART I
COLSTRIP SAMPLES - VEGETATION - FLUORIDE
FALL, 1974
F# Site
2001 -A SE #1
(1495)
2002 -A
(1496)
2003-A
(1497)
2004-A
(1498)
2005-A
(1499)
2006 -A
(1490)
2007 -A
(1491)
2008-A
(1492)
2009-A
201 0-A
(1494)
2011 -A
(1485)
201 2-A
(1486)
201 3-A
(1487)
201 4-A
(1488)
201 5 -A
201 6-A
(1480)
201 7 -A
(1481)
2018-A
(1482)
201 9-A
(1483)
2020-A
(1484)
2021 -A
(1475)
2022-A
/ M A ^_ -fc \
(1476)
Species
Scientific Name
Pinus ponderosa
Ouniperous scopulorum
Andropogon scoparius
Agropyron spicatum
Calamovilfa longi folia
Pinus ponderosa
Juniperous scopolorum
Andropogon scoparius
Calamovilfa longi folia
Pinus ponderosa
Juniperous scopulorum
Agropyron spicatum
Andropogon scoparius
Calamovilfa longi folia
Pinus ponderosa
Juniperous scopulorum
Calamovilfa longifolia
Andropogon scoparius
Agropyron spicatum
Pinus ponderosa
Juniperous scopulorum
Species Ppm F
Common Name 71 72
Ponderosa Pine 6.3 3.0
Rocky Mtn. Juniper
Little Bluestem
Bluebunch Wheatgrass
Sandgrass
Ponderosa Pine 2.5 2.6
Rocky Mtn. Juniper
Little Bluestem
Sandgrass
Ponderosa Pine 1.2 2.0
Rocky Mtn. Juniper
Bluebunch Wheatgrass
Little Bluestem
Sandgrass
Ponderosa Pine 1 .7 4.1
Rocky Mtn. Juniper
Sandgrass
Little Bluestem
Bluebunch Wheatgrass
Ponderosa Pine 1.9 3.3
Rocky Mtn. Juniper
(by year)
73 74
3.5 2.6
2.2
2.0
2.7
2.0
2.0 1.7
2.0
1.6
2.0
1.7 2.7
2.6
1.1
2.0
1.7
3.1 2.4
2.8
1.7
2.2
1.7
2.4 1.5
2.4
256
-------
COLSTRIP SAMPLES (Continued)
F#
Site
2023-A SE #1
(1477)
2024-A
(1478)
2025-A
(1479)
2076-A W #4
(1200)
2077-A
(1201)
2078-A
(1202)
2079-A
(1203)
2080-A
(1204)
2081-A
(1205)
2082-A
(1206)
2083-A
(1207)
2084-A
(1208)
2085-A
(1209)
2086-A
1210)
2087-A
(1211)
2088-A
(1212)
2089-A
(1213)
2090-A
(1214)
2091-A
(1215)
2092-A
(1216)
2093-A
(1217)
2094-A
(1218)
2095-A
(1219)
2096-A
(1220)
Species
Scientific Name
Artemisia cana
Andropogon scoparius
Agropyron spicatum
Pinus ponderosa
Rhus trilobata
Artemisia cana
Andropogon scoparius
Agropyron spicatum
Pinus ponderosa
Artemisia cana
Rhus trilobata
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Artemesia cana
Rhus trilobata
Agropyron sp/icatum
Adropogon scoparius
Pinus ponderosa
Rhus trilobata
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Species
Common Name
Silver Sage
Little Bluestem
Bluebunch Wheatgrass
Ponderosa Pine
Skunkbrush
Silver Sage
Little Bluestem
Bluebunch Wheatgrass
Ponderosa Pine
Silver Sage
Skunkbrush
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine :
Silver Sage
Skunkbrush
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine
Skunkbrush
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine
Ppm F"
ZI Zi
i
4.1 2.8
4.3 2.9
3.5 1.4
1.3 2.4
1.9 3.3
(by year)
73 74
0.8
2.9
2.1
3.3 2.4
1.3
3.5
2.2
2.2
1.9 2.4
2.5
2.0
1.9
1.4
2.9 1.1
3.5
1.7
1.0
0.8
1.9 1.3
2.6
2.4
2.2
3.1
2.8 2.3
257
-------
COLSTRIP SAMPLES (Continued)
F#
Site
2097-A W #4
(1221)
2098-A
(1222)
2099-A
(1223)
2100-A
(1224)
2101-A W #3
(1750)
2102-A
(1751)
2103-A
(1752)
2104-A
2105-A
2106-A
(1755)
2107-A
(1756)
2108-A
2109-A
2110-A
2111-A
(1760)
2112-A
(1761)
2113-A
(1762)
2114-A
(1763)
2115-A
2116-A
(1765)
2117-A
(1766)
2118-A
(1767)
2119-A
(1768)
2120-A
Species
Scientific Name
Rhus trilobata
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Yucca glauca
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Aristida longiseta
Pinus ponderosa
Juniperous scopulorum
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperous scopulorum
Yucca glauca
Agropogon spicatum
Andropogon scoparius
Species
Common Name
71
Ppm F
Skunkbrush
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 3.7 3.0
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Yucca
Ponderosa Pine 3.3 2.8
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Red Three Awn
Ponderosa Pine 2.0 1.0
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 1.5 1.1
Rocky Mtn. Juniper
Yucca
Bluebunch Wheatgrass
Little Bluestem
2.3
3.0
(by year)
73 74
1.7
3.3
1.0
1.7
2.7
2.0
3.9
1.5
2.0
1.8
3.0
2.5
1.3
1.2
1.1
1.3
0.8
1.7
1.1
1.0
1.7
0.8
1.6
1.0
1.8
1.3
258
-------
COLSTRIP SAMPLES (Continued)
F£ Site
2121-A W #3
(1770)
2122-A
(1771)
2123-A
(1772)
2124-A
(1773)
2125-A
(1774)
2126-A NW #4
(1350)
2127-A
(1351)
2128-A
(1352)
2129-A
(1353)
2130-A
(1354)
2131-A
(1355)
2132-A
(1356)
2133-A
(1357)
2134-A
(1358)
2135-A
(1359)
2136-A
(1360)
2137-A
(1361)
2138-A
(1362)
2139-A
(1363)
2140-A
(1364)
2141-A
(1365)
2142-A
(1366)
2143-A
(1367)
2144-A
(1368)
Species
Scientific Name
Pinus ponderosa
Juniperous scopulorum
Yucca glauca
Agropyron spicatum
ii ii
Pinus ponderosa
Juniperus scopulorum
Rhus trilobata
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperus scopulorum
Rhus trilobata
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Rhus trilobata
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Rhus trilobata
Juniperus scopulorum
Agropyron spicatum
Species
Common Name
Ppm F"
71 72
(by year)
73 74
Ponderosa Pine 1.3 0.7
Rocky Mtn. Juniper
Yucca
Bluebunch Wheatgrass
n n
Ponderosa Pine 3.6 2.8
Rocky Mtn. Juniper
Skunkbrush
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 3.8 4.0
Rocky Mtn. Juniper
Skunkbrush
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 1.4 1.1
Skunkbrush
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 2.9 2.2
Skunkbrush
Rocky Mtn. Juniper
Bluebunch Wheatgrass
1.3
2.4
2.5
2.1
1.3
1.2
2.0
1.1
1.2
1.2
2.2
2.8
1.7
5.9
2.2
1.7
1.3
1.5
0.9
2.1
1.2
1.4
1.1
5.1
4.3
0.6
1.7
1.5
259
-------
COLSTRIP SAMPLES (Continued)
El
2145-A
(1369)
2146-A
(1370)
2147-A
(1371)
2148-A
(1372)
2149-A
(1373)
2150-A
(1374)
2151-A
(1775)
2152-A
(1776)
2153-A
(1777)
2154-A
(1778)
2155-A
(1779)
2156-A
(1780)
2157-A
(1781)
2158-A
(1782)
2159-A
(1783)
2160-A
(1784)
2161-A
(1785)
2162-A
(1786)
2163-A
(1787)
2164-A
(1788)
2165-A
2166-A
(1790)
2167-A
(1791)
2168-A
(1792)
Species
Site Scientific Name
NW #4 Andropogon scoparius
" Pinus ponderosa
" Rhus trilobata
" Artemisia cana
" Andropogon scoparius
" Calamovilfa longifolia
NW 13 Pinus ponderosa
" Juniperous scopulorum
" Artemisia tridentata
" Agropyron spicatum
H
" Pinus ponderosa
" Artemisia tridentata
" Artemisia cana
" Agropyron spicatum
" Aristida longiseta
" Pinus ponderosa
" Juniperus scopulorum
" Artemisia cana
" Agropyron spicatum
" Andropogon scoparius
" Pinus ponderosa
" Juniperus scopulorum
" Artemisia cana
Species
Common Name
Ppm F"
71 72
(by year)
73 74
Little Bluestem
Ponderosa Pine
Skunkbrush
Silver Sage
Little Bluestem
Sandgrass
Ponderosa Pine
Rocky Mtn. Juniper
Big Sage
Blue Bunch Wheatgrass
1.0 1.7 1.1
3.6 3.2 3.2
3.5 2.0 2.6
Ponderosa Pine
Big Sage
Silver Sage
Bluebunch Wheatgrass
>
Red Three Awn
Ponderosa Pine 2.3 1.5
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 1.7 2.3
Rocky Mtn. Juniper
Silver Sage
1.9
1.6
1.5
0.8
1.5
1.6
1.1
0.7
3.3
2.3
5.0
1.2
1.1
5.3
2.5
3.1
1.2
0.9
2.2
1.2
1.4
1.9
0.9
2.9
2.3
260
-------
COLSTRIP SAMPLES (Continued)
fi
2169-A
(1793)
2170-A
(1794)
2171-A
(1795)
2172-A
(1796)
2173-A
(1797)
2174-A
(1798)
2175-A
(1799)
2176-A
(1575)
2177-A
1576)
2178-A
(1577)
2179-A
(1578)
2180-A
(1579)
2181-A
(1580)
2182-A
(1581)
2183-A
(1582)
2184-A
(1583)
2185-A
(1584)
2186-A
(1585)
2187-A
(1586)
2188-A
(1587)
2189-A
(1588)
2190-A
(1589)
2191-A
(1590)
2192-A
(1591)
Species
Site Scientific Name
NW #3 Agropyron spicatum
" Aristida longiseta
" Pinus ponderosa
" Ouniperus scopulorum
" Artemisia cana
" Agropyron spicatum
Species
Common Name ;
Bluebunch Wheatgrass
Red Three Awn
Ponderosa Pine 1
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Calamovilfa longifolia Sandgrass
NE #3 Pinus ponderosa
" Juniperus scopulorum
11 Artemisia cana
" Agropyron spicatum
11 Andropogon scoparius
" Pinus ponderosa
" Juniperus scopulorum
" Artemisia cana
" Agropyron spicatum
" Adropogon scoparius
" Pinus ponderosa
" Juniperus scopulorum
Ponderosa Pine ;
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 1
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine t
Rocky Mtn. Juniper
Chrysothamnus nauseosus Rubber Rabbitbrush
Agropyron spicatum Bluebunch Wheatgrass
Andropogon scoparius Little Bluestem
Pinus ponderosa Ponderosa Pine :
Juniperus scopulorum Rocky Mtn. Juniper
Ppm F~ (by year)
Z2.Z3.Zi
1.2 1.8
2.2 1.7
1.4 1.9
2.5 1.9
2.5 2.5
1.4
1.3
1.2
1.8
1.9
2.1
1.0
1.8
2.5
2.0
2.3
2.2
1.6
1.8
3.7
4.9
3.9
1.3
1.9
1.8
3.6
7.2
1.6
1.9
261
-------
COLSTRIP SAMPLES (Continued)
F#
2193-A
(1592)
2194-A
(1593)
2195-A
(1594)
2196-A
(1595)
2197-A
(1596)
2198-A
(1597)
2199-A
(1598)
2200-A
(1599)
2201 -A
(1050)
2202 -A
2203-A
2204-A
(1053)
2205-A
(1054)
2206-A
(1055)
2207 -A
2208-A
(1057)
2209-A
(1058)
221 0-A
(1059)
2211 -A
(1060)
221 2-A
221 3-A
(1062),
2214-A
(1063)
221 5-A
(1064)
Species
Site Scientific Name
NE #3 Artemisia tridentata
" Agropyron spicatum
" Andropogon scoparius
11 Pinus ponderosa
11 Juniperus scopulorum
" Artemisia tridentata
" Agropyron spicatum
" Andropogon scoparius
SE #3 Pinus ponderosa
" Yucca glauca
" Andropogon scoparius
" Agropyron spicatum
" Stipa comata
" Pinus ponderosa
" Artemisia cana
Species Ppm F
Common Name 71 72
Big Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 2.0 2.2
Rocky Mtn. Juniper
Big Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 3.3 1.1
Yucca
Little Bluestem
Bluebunch Wheatgrass
Needle and Thread
Ponderosa Pine 2.6 3.6
Silver Sage
" Chrysothamnus viscidiflorus Green Rabbi tbrush
" Agropyron spicatum
" Stipa comata
" Pinus ponderosa
" Andropogon scoparius
Bluebunch Wheatgrass
Needle and Thread
Ponderosa Pine 2.8 3.6
Little Bluestem
" Chrysothamnus viscidiflorus Green Rabbitbrush
" Agropyron spicatum
" Stipa comata
Bluebunch Wheatgrass
Needle and Thread
(by year)
73 74
3.4
2.1
3.3
2.5 2.6
1.9
3.9
3.2
3.9
2.9 2.2
1.5
1.3
2.5
2.4
1.7 1.9
3.2
2.5
3.5
2.2
3.7 1.9
0.9
2.9
2.0
1.3
262
-------
COLSTRIP SAMPLES (Continued)
F£ Site
2216-A SE #3
(1065)
22T7-A
2218-A
(1067)
2219-A
(1068)
2220-A
(1069)
2221-A
(1070)
2222-A
2223-A
2224-A
(1073)
2225-A
(1074)
2226-A E #3
(1275)
2227-A
(1276)
2228-A
2229-A
(1278)
2230-A
(1279)
2231-A
(1280)
2232-A
(1281)
2233-A
2234-A
(1283)
2235-A
(1284)
2236-A
(1285)
2237-A
(1286)
2238-A
2239-A
(1288)
Species
Scientific Name
Species
Common Name
Pinus ponderosa Ponderosa Pine
Andropogon scoparius Little Bluestem
Chrysothamnus viscidiflorus Green Rabbitbrush
Agropyron spicatum Bluebunch Wheatgrass
Stipa comata Needle and Thread
Pinus ponderosa Ponderosa Pine
Chrysothamnus viscidiflorus Green Rabbitbrush
Andropogon scoparius Little Bluestem
Agropyron spicatum
Stipa comata
Pinus ponderosa
Juniperus scopulorum
Stipa comata
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperus scopulorum
Stipa comata
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperus scopulorum
Artemisia tridentata
Andropogon scoparius
Bluebunch Wheatgrass
Needle and Thread
Ponderosa Pine
Rocky Mtn. Juniper
Needle and Thread
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine
Rocky Mtn. Juniper
Needle and Thread
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine
Rocky Mtn. Juniper
Big Sage
Little Bluestem
Ppm F"
Zl 72
2.3 2.7
;h
1.8 1.4
sh
3.9 2.5
1.7 1.3
1.5 1.3
(by year)
Zl Zi
1.2 1.3
1.1
1.7
3.3
1.8
1.8 1.9
3.3
1.1
1.1
1.3
3.0 2.0
^2.7
3.2
1.9
2.6
1.3 1.3
2.3
1.7
1.0
1.1
1.8 1.7
2.8
2.1
1.3
263
-------
COLSTRIP SAMPLES (Continued)
F#
Site
2240-A E #3
(1289)
2241-A
(1290)
2242-A
(1291)
2243-A
2244-A
(1293)
2245-A
(1294)
2246-A
(1295)
2247-A
(1296)
2248-A
2249-A
(1298)
2250-A
(1299)
2251-A E #4
(1250)
2252-A
(1251)
2253-A
(1252)
2254-A
(1253)
2255-A
(1254)
2256-A
(1255)
2257-A
(1256)
2258-A
2259-A
(1258)
2260-A
(1259)
2261-A
(1260)
2262-A
(1261)
2263-A
(1262)
Species
Scientific Name
Agropyron spicatum
Pinus ponderosa
Juniperus scopulorum
Artemisia tridentata
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperus scopulorum
Yucca glauca
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Artemisia tridentata
Chrysothamnus
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Artemisia tridentata
Chrysothamnus
Andropogon scoparius
Agropyron spicatum
Pinus ponderosa
Chrysothamnus
Artemisia tridentatum
Species
Common Name
Bluebunch Wheatgrass
Ponderosa Pine
Rocky Mtn. Juniper
Big Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine
Rocky Mtn. Juniper
Yucca
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine
Big Sage
Rabbitbrush
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine
Big Sage
Rabbitbrush
Little Bluestem
Bluebunch Wheatgrass
Ponderosa Pine
Rabbitbrush
Big Sage
Ppm F" (by year)
71 72 73 74
1.7 1.4 0.7
1.6 1.5 0.7
6.4 5.2 3.4
2.9 2.8 2.7
2.7 2.6 2.1
1.7
0.5
2.0
2.5
0.8
0.8
0.5
4.4
3.1
3.6
0.9
3.2
5.6
3.7
2.4
3.1
3.0
3.2
2.9
1.6
2.6
2.1
3.2
2.9
264
-------
COLSTRIP SAMPLES (Continued)
Ei Site
2264-A E #4
(1263)
2265-A
(1264)
2266-A
(1265)
2267-A
2268-A
(1267)
2269-A
(1268)
2270-A
(1269)
2271-A
(1270)
2272-A
2273-A
(1272)
2274-A
(1273)
2275-A
(1274)
2276-A NE #4
(1175)
2277-A
(1176)
2278-A
0177)
2279-A
(1178)
2280-A
(1179)
2281-A
(1180)
2282-A
(1181)
2283-A
(1182)
2284-A
(1183)
2285-A
(1184)
2286-A
(1185)
2287-A
(1186)
Species
Scientific Name
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Chrysothamnus
Artemisia tridentatum
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Chrysothamnus
Artemisia tridentatum
Agropyron spicatum
Andropogon scoparius
Andropogon scoparius
Artemisia tridentatum
Agropyron spicatum
Artemisia cana
Stipa comata
Agropyron spicatum
Artemisia tridentatum
Andropogon scoparius
Artemisia cana
Stipa comata
Artemisia cana
Andropogon scoparius
Species
Common Name
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine
Rabbitbrush
Big Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine
Rabbitbrush
Big Sage
Bluebunch Wheatgrass
Little Bluestem
Little Bluestem
Big Sage
Bluebunch Wheatgrass
Silver Sage
Needle and Thread
Bluebunch Wheatgrass
Big Sage
Little Bluestem
Silver Sage
Needle and Thread
Silver Sage
Little Bluestem
265
Ppm F"
Zl 72
i
2.1 1.9
2.1 2.7
(by year)
73 74
2.1
3.7
2.0 2.9
3.0
1.8
2.7
3.9
1.9 2.0
2.5
3.2
2.5
2.4
4.5
4.4
6.8
2.0
4.5
2.0
3.8
1.8
2.6
2.4
2.8
2.3
-------
COLSTRIP SAMPLES (Continued)
fi
2288-A
(1187)
2289-A
(1188)
2290-A
(1189)
2291-A
(1190)
2292-A
(1191)
2293-A
(1192)
2294-A
(1193)
2295-A
(1194)
2296-A
(1195)
2297-A
(1196)
2298-A
(1197)
2299-A
(1198)
2300-A
(1199)
2301-A
(1300)
2302-A
(1301)
2303-A
(1302)
2304-A
(1303)
2305-A
(1304)
2306-A
(1305)
2307-A
2308-A
(1307)
2309-A
(1308)
2310-A
2311-A
(1310)
Species
Site Scientific Name
NE #4 Artemisia tridentata
" Agropyron spicatum
" Stipa comata
ii it n
" Artemisia cana
" Andropogon scoparius
" Agropyron spicatum
" Artemisia tridentatum
" Artemisia cana
" Andropogon scoparius
" Stipa comata
: Juniperus scopulorum
11 Artemisia tridentatum
N #4 Pinus ponderosa
" Juniperus scopulorum
" Artemisia cana
11 Agropyron spicatum
" Oryzopsis hymenoides
" Pinus ponderosa
" Juniperus scopulorum
" Artemisia cana
" Agropyron spicatum
" Oryzopsis hymenoides
" Pinus ponderosa
Species
Common Name
Big Sage
Bluebunch Wheatgrass
Needle and Thread
ii n
Silver Sage
Little Bluestem
Bluebunch Wheatgrass
Big Sage
Silver Sage
Little Bluestem
Needle and Thread
Rocky Mtn. Juniper
Big Sage
Ponderosa Pine
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Indian Rice Grass
Ponderosa Pine
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Indian Rice Grass
Ponderosa Pine
266
Ppm F"
Zl TL
3.3 2.1
2.4 2.2
\
3.3 2.3
(by year)
73. 74
4.2
2.0
3.9
2.4
6.7
2.8
3.1
2.9
4.1
3.7
1.9
3.7
4.7
2.5 1.7
3.8
2.0
2.9
2.6
2.1 1.4
3.0
2.3
1.8
2.2
1.7 1.0
-------
COLSTRIP SAMPLES (Continued)
F#
Site
2312-A N #4
2313-A
(1312)
2314-A
(1313)
2315-A
2316-A
(1315)
2317-A
2318-A
(1317)
2319-A
(1318)
2320-A
(1319)
2321-A
(1320)
2322-A
(1321)
2323-A
(1322)
2324-A
(1323)
2325-A
(1324)
232fi-A NE #1
(1850)
23^7-A
(1851)
2328-A
(1852)
2329-A
(1853)
2330-A
(1854)
2331-A
(1855)
2332-A
(1856)
2333-A
(1857)
2334-A
(1858)
2335-A
(1859)
Species
Scientific Name
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Oryzopsis hymenoides
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Oryzopsis hymenoides
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Species
Common Name
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Indian Rice Grass
Ponderosa Pine
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Indian Rice Grass
Ponderosa Pine
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
267
Ppm F"
zi n.
1.3 1.3
2.3 2.1
4.0 3.6
1.1 0.4
(by year)
73. 74
2.5
2.9
2.5
1.8
2.4 1.3
1.3
2.3
1.9
4.2
3.2 2.3
4.7
3.2
3.3
1.2
3.2 2.9
1.3
0.4
0.2
0.1
0.4 0.8
0.1
0.6
0.9
0.8
-------
COLSTRIP SAMPLES (Continued)
E£
2336-A
(1860)
2337-A
(1861)
2338-A
2339-A
(1863)
2340-A
(1864)
2341-A
(1865)
2342-A
(1866)
2343-A
(1867)
2344-A
(1868)
2345-A
(1869)
2346-A
(1870)
2347-A
2348-A
(1872)
2349-A
(1873)
2350-A
(1874)
2351-A
(1825)
2352-A
(1826)
2353-A
2354-A
(1828)
2355-A
2356-A
(1830)
2357-A
(1831)
2358-A
(1832)
2359-A
(1833)
Species
Site Scientific Name
NE #1 Pinus ponderosa
" Juniperus scopulorum
n
" Artemisia cana
" Agropyron spicatum
" Pinus ponderosa
" Juniperus scopulorum
" Artemisia cana
" Agropyron spicatum
" Andropogon scoparius
" Pinus ponderosa
" Juniperus scopulorum
" Artemisia cana
" Agropyron spicatum
" Andropogon scoparius
E #1 Pinus ponderosa
" Juniperus scopulorum
" Agropyron spicatum
" Andropogon scoparius
" Calamovilfa longifolia
" Pinus ponderosa
" Juniperus scopulorum
" Agropyron spicatum
" Andropogon scoparius
Species
Common Name
Ppm F"
71 72
Ponderosa Pine 0.8 0.7
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Ponderosa Pine 1.3 1.1
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 2.4 1.7
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 4.7 2.4
Rocky Mtn. Juniper
Bluebunch Wheatgrass
Little Bluestem
Sandgrass
Ponderosa Pine 1.8 2.1
Rocky Mtn. Juniper
Bluebunch Wheatgrass
Little Bluestem
268
0.7
1.9
(by year)
73 74
0.6 0.6
0.9
0.8
0.6
0.2
1.2
0.7
0.3
1.3
0.6
0.9
1.9
1.4
1.1
1.9
2.7
2.4
2.5
1.5
1.4
4.0
3.3
1.8
1.4
1.7
-------
COLSTRIP SAMPLES (Continued)
F#
Site
2360-A E #1
(1834)
2361-A
(1835)
2362-A
2363-A
(1837)
2364-A
(1838)
2365-A
(1839)
2366-A
(1840)
2367-A
2368-A
(1842)
2369-A
(1843)
2370-A
(1844)
2371-A
(1845)
2372-A
(1846)
2373-A
(1847)
2374-A
(1848)
2375-A
(1849)
2376-A E #5
(1225)
2377-A
(1226)
2378-A
(1227)
2379-A
(1228)
2380-A
(1229)
2381-A
(1230)
2382-A
(1231)
2383-A
(1232)
Species
Scientific Name
Calamovilfa longifolia
Pinus ponderosa
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Calamovilfa longifolia
Pinus ponderosa
Juniperus scopulorum
Agropyron spicatum
Andropogon scoparius
Aristida longiseta
Pinus ponderosa
Juniperus scopulorum
Agropyron spicatum
Andropogon scoparius
Calamovilfa longifolia
Pinus ponderosa
Juniperus scopulorum
Andropogon scoparius
Agropyron spicatum
Aristida longiseta
Pinus ponderosa
Artemisia cana
Juniperus scopulorum
Species
Common Name
Sandgrass
Ponderosa Pine
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Sandgrass
Ponderosa Pine
Rocky Mtn. Juniper
Bluebunch Wheatgrass
Little Bluestem
Red Three Awn
Ponderosa Pine
Rocky Mtn. Juniper
Bluebunch Wheatgrass
Little Bluestem
Sandgrass
Ponderosa Pine
Rocky Mtn. Juniper
Little Bluestem
Bluebunch Wheatgrass
Red Three Awn
Ponderosa Pine
Silver Sage
Rocky Mtn. Juniper
269
Ppm F" (by year)
71 72 73 74
2.5 1.4 1.9
1.6 1.5 2.1
2.7 3.2 2.2
9.9 3.5 3.0
3.6 2.6 3.2
1.0
1.2
3.1
1.8
1.6
1.0
1.6
1.8
0.8
2.0
1.1
1.4
2.1
2.2
3.7
1.5
1.6
4.5
1.5
3.7
1.4
1.4
2.5
2.0
-------
COLSTRIP SAMPLES (Continued)
F#
Site
2384-A E #5
(1233)
2385-A
(1234)
2386-A
(1235)
2387-A
(1236)
2388-A
(1237)
2389-A
(1238)
2390-A
2391-A "
(1240)
2392-A
(1241)
2393-A
2394-A
(1243)
2395-A
(1244)
2396-A
(1245)
2397-A
(1246)
2398-A
2399-A
(1248)
2400-A
(1249)
Species
Scientific Name
Andropogon scoparius
Agropyron spicatum
Pinus ponderosa
Juniperus scopulorum
Andropogon scoparius
Agropyron spicatum
Aristida longiseta
Pinus ponderosa
Juniperus scopulorum
Calamovilfa longifolia
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Species
Common Name
Ppm F" (by year)
71 72 73 74
Little Bluestem 2.7
Bluebunch Wheatgrass 2.3
Ponderosa Pine 2.5 2.6 2.2 1.4
Rocky Mtn. Juniper 3.2
Little Bluestem 1.4
Bluebunch Wheatgrass 2.2
Red Three Awn 2.9
Ponderosa Pine 2.2 3.5 2.4 1.4
Rocky Mtn. Juniper 3.1
Sandgrass 1.3
Bluebunch Wheatgrass 3.8
Little Bluestem 2.0
Ponderosa Pine 2.3 1.5 2.5 1.4
Rocky Mtn. Juniper 1.5
Silver Sage 2.9
Bluebunch Wheatgrass 3.2
Little Bluestem 1.8
270
-------
APPENDIX B - PART II
COLSTRIP SAMPLES - VEGETATION - SULFUR
FALL, 1974
Ei Site
2001-A SE #1
(1495)
2002-A
(1496)
2003-A
(1497)
2004-A
(1498)
2005-A
(1499)
2006-A
(1490)
2007-A
(1491)
2008-A
(1492)
2009-A
2010-A
(1494)
2011-A
(1485)
2012-A
(1486)
2013-A
(1487)
2014-A
(1488)
2015-A
2016-A
(1480)
2017-A
(1481)
2018-A
(1482)
2019-A
(1483)
2020-A
(1484)
2021-A
(1475)
2022-A
(1476)
Species
Scientific Name
Pinus ponderosa
Juniperous scopulorum
Andropogon scoparius
Agropyron spicatum
Calamovilfa longifolta
Pinus ponderosa
Juniperous scopulorum
Andropogon scoparius
Calamovilfa longifolia
Pinus ponderosa
Juniperous scopulorum
Agropyron spicatum
Andropogon scoparius
Calamovilfa longifolia
Pinus ponderosa
Juniperus scopulorum
Calamovilfa longifolia
Andropogon scoparius
Agropyron spicatum
Pinus ponderosa
Juniperus scopulorum
Species
Common Name
Ppm S (by year)
71 72 73 74
Ponderosa Pine 800 700 700 700
Rocky Mtn. Juniper 800
Little Bluestem 300
Bluebunch Wheatgrass 700
Sandgrass 500
Ponderosa Pine 600 650 800 700
Rocky Mtn. Juniper 700
Little Bluestem 400
Sandgrass 600
Ponderosa Pine 700 700 700 700
Rocky Mtn. Juniper 700
Bluebunch Wheatgrass 600
Little Bluestem 400
Sandgrass 500
Ponderosa Pine 700 700 700 700
Rocky Mtn. Juniper 700
Sandgrass 600
Little Bluestem 400
Bluebunch Wheatgrass 700
Ponderosa Pine 700 700 700 700
Rocky Mtn. Juniper 700
271
-------
COLSTRIP SAMPLES (Continued)
Ei
2023-A
(1477)
2024-A
(1478)
2025-A
(1479)
2076-A
(1200)
2077-A
(1201)
2078-A
(1202)
2079-A
(1203)
2080-A
(1204)
2081-A
(1205)
2082-A
(1206)
2083-A
(1207)
2084-A
(1208)
2085-A
(1209)
2086-A
(1210)
2087-A
(1211)
2088-A
(1212)
2089-A
(1213)
2090-A
(1214)
2091-A
(1215)
2092-A
(1216)
2093-A
(1217)
2094-A
(1218)
2095-A
(1219)
2096-A
(1220)
Species
Site Scientific Name
SE #1 Artemisia cana
" Andropogon scoparius
" Agropyron spicatum
W #4 Pinus ponderosa
11 Rhus trilobata
" Artemisia cana
" Andropogon scoparius
" Agropyron spicatum
" Pinus ponderosa
" Artemisia cana
" Rhus trilobata
" Agropyron spicatum
11 Andropogon scoparius
" Pinus ponderosa
" Artemesia cana
Rhus trilobata
" Agropyron spicatum
" Andropogon scoparius
" Pinus ponderosa
Rhus trilobata
" Artemisia cana
" Agropyron spicatum
" Andropogon scoparius
" Pinus ponderosa
Species
Common Name
Ppm S
71 72
Silver Sage
Little Bluestem
Bluebunch Wheatgrass
Ponderosa Pine 800 600
Skunkbrush
Silver Sage
Little Bluestem
Bluebunch Wheatgrass
Ponderosa Pine 500 500
Silver Sage
Skunkbrush
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 800 800
Silver Sage
Skunkbrush
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 600 700
Skunkbrush
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 700 600
272
(by year)
73_ 74
2200/2200*
400
500
700 1000
700
1100
400
400
500 500
2600
500
500
300
900 800
2600
800
600
600
700 700
500/600*
2600/2600*
800/800*
400/300*
600 800
-------
COLSTRIP SAMPLES (Continued)
££
2097-A
(1221)
2098-A
(1222)
2099-A
(1223)
2100-A
(1224)
2101-A
(1750)
2102-A
(1751)
2103-A
(1752)
2104-A
2105-A
2106-A
(1755)
2107-A
(1756)
2108-A
2109-A
2110-A
2111-A
(1760)
2112-A
(1761)
2113-A
(1762)
2114-A
(1763)
2115-A
2116-A
(1765)
2117-A
(1766)
2118-A
(1767)
2119-A
(1768)
2120-A
Species
Site Scientific Name
W #4 Rhus trilobata
" Artemisia cana
" Agropyron spicatum
" Andropogon scoparius
W #3 Pinus ponderosa
" Juniperus scopulorum
" Artemisia cana
" Agropyron spicatum
" Yucca glauca
" Pinus ponderosa
" Juniperus scopulorum
" Artemisia cana
11 Agropyron spicatum
11 Aristida longiseta
" Pinus ponderosa
" Juniperus scopulorum
11 Artemisia cana
" Agropyron spicatum
" Andropogon scoparius
" Pinus ponderosa
" Juniperus scopulorum
" Yucca glauca
" Agropogon spicatum
" Andropogon scoparius
Species
Common Name
Ppm S
71 72
700/ 700
800
Skunkbrush
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Yucca
Ponderosa Pine 900 700
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Red Three Awn
Ponderosa Pine 600 500
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 400 700
Rocky Mtn. Juniper
Yucca
Bluebunch Wheatgrass
Little Bluestem
273
(by year)
73 74
700
2100
300
300
700 700
700
2900/3000
700
800
900 700
700/700
2500
400
600
700 600
800
2000
700/600
400
600 600
400
800
500
400
-------
COLSTRIP SAMPLES (Continued)
Ei
2121-A
(1770)
2122-A
(1771)
2123-A
(1772)
2124-A
(1773)
2125-A
(1774)
2126-A
(1350)
2127-A
(1351)
2128-A
(1352)
2129-A
(1353)
2130-A
(1354)
2131-A
(1355)
2132-A
(1356)
2133-A
(1357)
2134-A
(1358)
2135-A
(1359)
2136-A
(1360)
2137-A
(1361)
2138-A
(1362)
2139-A
(1363)
2140-A
(1364)
2141-A
(1365)
2142-A
(1366)
2143-A
(1367)
2144-A
(1368)
Site
Species
Scientific Name
Species
Common Name
Ppm S
71 72
W #3 Pinus ponderosa
" Juniperus scopulorum
" Yucca glauca
" Agropyron spicatum
H n M
NW #4 Pinus ponderosa
" Juniperus scopulorum
" Rhus trilobata
" Agropyron spicatum
" Andropogon scoparius
" Pinus ponderosa
" Juniperus scopulorum
" Rhus trilobata
" Agropyron spicatum
" Andropogon scoparius
" Pinus ponderosa
11 Rhus trilobata
" Artemisia cana
" Agropyron spicatum
" Andropogon scoparius
" Pinus ponderosa
" Rhus trilobata
" Juniperus scopulorum
" Agropyron spicatum
500 800/
700
Ponderosa Pine 600 700
Rocky Mtn. Juniper
Yucca
Bluebunch Wheatgrass
n ii
Ponderosa Pine 1000/ 600/
900 700
Rocky Mtn. Juniper
Skunkbrush
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine
Rocky Mtn. Juniper
Skunkbrush
Bluebunch Wheatgrass
tittle Bluestem
Ponderosa Pine 600 800
Skunkbrush
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 700 800
Skunkbrush
Rocky Mtn. Juniper
Bluebunch Wheatgrass
274
(by year)
73. 74
600 600
900
700
700
300
900 900
600
700
600
400
800 800
600
1100
800
400
700 700
800/700
2200
600
400
900 800
800
700/600
-------
COLSTRIP SAMPLES (Continued)
Fl Site
2145-A NW #4
(1369)
2146-A
(1370)
21 47 -A
(1371)
2148-A
(1372)
2149-A
(1373)
2150-A
(1374)
21 51 -A NW #3
(1775)
21 52 -A
(1776)
2153-A
(1777)
2154-A
(1778)
2155-A
(1779)
2156-A
(1780)
21 57 -A
(1781)
2158-A
(1782)
2159-A
(1783)
2160-A
(1784)
21 61 -A
(1785)
2162-A
(1786)
2163-A
(1787)
2164-A
(1788)
2165-A
2166-A
(1790)
21 67 -A
(1791)
2168-A
(1792)
Species
Scientific Name
Andropogon scoparius
Pinus ponderosa
Rhus trilobata
Artemisia cana
Andropogon scoparius
Calamovilfa longifolia
Pinus ponderosa
Juniperus scopulorum
Artemisia tridentata
Agropyron spicatum
Pinus ponderosa
Artemisia tridentata
Artemisia cana
Agropyron spicatum
Aristida longiseta
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Species Ppm S
Common Name 71 72
Little Bluestem
Ponderosa Pine 500 800
Skunkbrush
Silver Sage
Little Bluestem
Sandgrass
Ponderosa Pine 900 700
Rocky Mtn. Juniper
Big Sage
Bluebunch Wheatgrass
Ponderosa Pine 650/ 800
750
Big Sage
Silver Sage
Bluebunch Wheatgrass
Red Three Awn
Ponderosa Pine 800 850
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
*
Little Bluestem
Ponderosa Pine 750 500
Rocky Mtn. Juniper
Silver Sage
(by year)
73 74
200
700 700
800
2700
800
600
700 500
800
1500
550
900 800
1100
2500
500
850
550 800
700
2100
600
400
650 600
600/550
2400
275
-------
COLSTRIP SAMPLES (Continued)
Ei
2169-A
(1793)
2170-A
(1794)
2171-A
(1795)
2172-A
(1796)
2173-A
(1797)
2174-A
(1798)
2175-A
(1799)
2176-A
(1575)
2177-A
(1576)
2178-A
(1577)
2179-A
(1578)
2180-A
(1579)
2181-A
(1580)
2182-A
(1581)
2183-A
(1582)
2184-A
(1583)
2185-A
(1584)
2186-A
(1585)
2187-A
(1586)
2188-A
(1587)
2189-A
(1588)
2190-A
(1589)
2191-A
(1590)
2192-A
(1591)
Species
Site Scientific Name
NW #3 Agropyron spicatum
" Aristida longiseta
" Pinus ponderosa
" Juniperus scopulorum
" Artemisia cana
" Agropyron spicatum
" Calamovilfa longifolia
NE #3 Pinus ponderosa
" Juniperus scopulorum
" Artemisia cana
" Agropyron spicatum
" Andropogon scoparius
" Pinus ponderosa
" Juniperus scopulorum
" Artemisia cana
" Agropyron spicatum
" Andropogon scoparius
" Pinus ponderosa
" Juniperus scopulorum
11 Chrysothamnus nauseosus
11 Agropyron spicatum
" Andropogon scoparius
" Pinus ponderosa
" Juniperus scopulorum
Species
Common Name
Ppm S (by year)
71 72 73 74
Bluebunch Wheatgrass
Red Three Awn
Ponderosa Pine
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Sandgrass
Ponderosa Pine 450 550
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 550 550
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 400 400
Rocky Mtn. Juniper
Rubber Rabbitbrush
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 600 600
Rocky Mtn. Juniper
276
400
500/400
600 6°°£50 600 600
600
2200
400
400
500 600
550
2800
400
200/200
700 700
500
2750
200/200
200/200
400 500
600
900
300
400
550 400
400
-------
COLSTRIP SAMPLES (Continued)
F#
Site
2193-A NE #3
(1592)
2194-A
(1593)
2195-A
(1594)
2196-A
(1595)
2197-A
(1596)
2198-A
(1597)
2199-A
(1598)
2200-A
(1599)
2201-A SE #3
(1050)
2202-A
2203-A
2204-A
(1053)
2205-A
(1054)
2206-A
(1055)
2207-A
2208-A
(1057)
2209-A
(1058)
2210-A
(1059)
2211-A
(1060)
2212-A
2213-A
(1062)
2214-A
(1063)
2215-A
(1064)
Species
Scientific Name
Artemisia tridentata
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperus scopulorum
Artemisia tridentata
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Yucca glauca
Andropogon scoparius
Agropyron spicatum
Stipa comata
Pinus ponderosa
Species
Common Name
Ppm S
71 72
Big Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 400 400
Rocky Mtn. Juniper
Big Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 650 650
Yucca
Little Bluestem
Bluebunch Wheatgrass
Needle and Thread
Ponderosa Pine 500 500
Silver Sage
Artemisia cana
Chrysothamnus viscidiflorus Green Rabbitbrush
Agropyron spicatum Bluebunch Wheatgrass
Stipa comata Needle and Thread
Pinus ponderosa Ponderosa Pine 750 600
Andropogon scoparius Little Bluestem
Chrysothamnus viscidiflorus Green Rabbitbrush
Agropyron spicatum Bluebunch Wheatgrass
Stipa comata Needle and Thread
(by year)
73 74
1100
200/300
200/200
600 600
500
900
550
300
550 700
1400
400
400
400
700 700
2700
2800
500
400
700 500
300
2100
650
500
277
-------
COLSTRIP SAMPLES (Continued)
Ei
2216-A
(1065)
2217
2218-A
(1067)
2219-A
(1068)
2220-A
(1069)
2221-A
(1070)
2222-A
2223-A
2224-A
(1073)
2225-A
(1074)
2226-A
(1275)
2227-A
(1276)
2228-A
2229-A
(1278)
2230-A
(1279)
2231-A
(1280)
2232-A
(1281)
2233-A
2234-A
(1283)
2235-A
(1284)
2236-A
(1285)
2237-A
(1286)
2238-A
2239-A
(1288)
Site
SE #3
Species
Scientific Name
Species
Common Name
Ppm S (by year)
71 72 73 74
E #3
Pinus ponderosa Ponderosa Pine
Andropogon scoparius Little Bluestem
Chrysothamnus viscidiflorus Green Rabbitbrush
Agropyron spicatum Bluebunch Wheatgrass
Stipa comata Needle and Thread
Pinus ponderosa Ponderosa Pine
Chrysothamnus viscidiflorus Green Rabbitbrush
Andropogon scoparius Little Bluestem
500 700 700 600
300/350
1000/1000
600
500
600 700/ 750/ 650
700 800
1850
Agropyron spicatum
Stipa comata
Pinus ponderosa
Juniperus scopulorum
Stipa comata
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Ouniperus scopulorum
Stipa comata
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperus scopulorum
Artemisia tridentata
Andropogon scoparius
300
Bluebunch Wheatgrass 500
Needle and Thread 500
Ponderosa Pine 600 750 800 700
Rocky Mtn. Juniper 700
Needle and Thread 400
Bluebunch Wheatgrass 450
Little Bluestem 300
Ponderosa Pine 700 750 800 700
Rocky Mtn. Juniper 600
Needle and Thread 500
Bluebunch Wheatgrass 400
Little Bluestem 300
Ponderosa Pine 700 750 750 750
Rocky Mtn. Juniper 700
Big Sage 1300
Little Bluestem 400
278
-------
COLSTRIP SAMPLES (Continued)
fi
2240-A
(1289)
2241-A
(1290)
2242-A
(1291)
2243-A
2244-A
(1293)
2245-A
(1294)
2246-A
(1295)
2247-A
(1296)
2248-A
2249-A
(1298)
2250-A
(1299)
2251-A
(1250)
2252-A
(1251)
2253-A
(1252)
2254-A
(1253)
2255-A
(1254)
2256-A
(1255)
2257-A
(1256)
2258-A
2259-A
(1258)
2260-A
(1259)
2261-A
(1260)
2262-A
(1261)
2263-A
(1262)
Species
Site• Scientific Name
E #3 Agropyron spicatum
" Pinus ponderosa
" Juniperus scopulorum
" Artemisia tridentata
" Agropryon spicatum
" Andropogon scoparius
" Pinus ponderosa
" Juniperus scopulorum
11 Yucca glauca
" Agropyron spicatum
" Andropogon scoparius
E #4 Pinus ponderosa
" Artemisia tridentata
11 Chrysothamnus
" Agropyron spicatum
11 Andropogon scoparius
" Pinus ponderosa
" Artemisia tridentata
" Chrosothamnus
" Andropogon scoparius
" Agropyron spicatum
" Pinus ponderosa
" Chrysothamnus
Artemisia tridentata
Species
Common Name
Ppm S
71 72
Bluebunch Wheatgrass
Ponderosa Pine 700 950
Rocky Mtn. Juniper
Big Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 700 700
Rocky Mtn. Juniper
Yucca
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 600 900
Big Sage
Rabbitbrush
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 600 600
Big Sage
Rabbitbrush
Little Bluestem
Bluebunch Wheatgrass
Ponderosa Pine 600 700
Rabbitbrush
Big Sage
279
(by year)
73_ 74_
400
1100/ 800
950
650
1400
400
300
900 700
600
1000/950
400
400
900 650
700
1800
200
500
600 600
900
1600
700
300
600 600
600
1400
-------
COLSTRIP SAMPLES (Continued)
El
2264-A
(1263)
2265-A
(1264)
2266-A
(1265)
2267-A
2268-A
(1267)
2269-A
(1268)
2270-A
(1269)
2271-A
(1270)
2272-A
2273-A
(1272)
2274-A
(1273)
2275-A
(1274)
2276-A
(1175)
2277-A
(1176)
2278-A
(1177)
2279-A
(1178)
2280-A
(1179)
2281-A
(1180)
2282-A
(1181)
2283-A
(1182)
2284-A
(1183)
2285-A
(1184)
2286-A
(1185)
2287-A
(1186)
Site
- •! _L III
E #4
Species
Scientific Name
Species
Common Name
Ppm S (by year)
71 72 73 74
Agropyron spicatum
" Andropogon scoparius
" Pinus ponderosa
" Chrysothamnus
" Artemisia tridentata
" Agropyron spicatum
" Andropogon scoparius
11 Pinus ponderosa
" Chrysothamnus
11 Artemisia tridentata
" Agropyron spicatum
11 Andropogon scoparius
NE #4 Andropogon scoparius
" Artemisia tridentata
11 Agropyron spicatum
" Artemisia cana
" Stipa comata
" Agropyron spicatum
" Artemisia tridentata
" Andropogon scoparius
" Artemisia cana
" Stipa comata
" Artemisia cana
" Andropogon scoparius
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine
Rabbi thrush
Big Sage
Bluebunch Wheatgrass
Little Bluestem
Ponderosa Pine 700 600
Rabbitbrush
Big Sage
Bluebunch Wheatgrass
Little Bluestem
Little Bluestem
Big Sage
Bluebunch Wheatgrass
Silver Sage
Needle and Thread
Bluebunch Wheatgrass
Big Sage
Little Bluestem
Silver Sage
Needle and Thread
Silver Sage
Little Bluestem
280
600
200
600 600/ 700 800
550
3300/300
1570
300
300
700 600
500
900
400
300
200
1200
400
3500/3300
350
500
1100
200
1750
25d
2300
250
-------
COLSTRIP SAMPLES (Continued)
F#
2288-A
(1187)
2289-A
(1188)
2290-A
(1189)
2291 -A
(1190)
2292 -A
(1191)
2293-A
(1192)
2294-A
(1193)
2295-A
(1194)
2296-A
(1195)
2297-A
(1196)
2298-A
(1197)
2299-A
(1198)
2300-A
(1199)
2301 -A
(1300)
2302 -A
(1301)
2303-A
(1302)
2304-A
(1303)
2305-A
(1304)
2306-A
(1305)
2307-A
2308-A
(1307)
2309-A
(1308)
231 0-A
2311 -A
(1310)
Site
NE #4
n
n
n
n
n
n
n
n
n
ii
ii
n
N #4
n
ii
M
II
II
II
II
II
II
II
Species
Scientific Name
Artemisia tridentata
Agropyron spicatum
Stipa comata
ii n
Artemisia cana
Andropogon scoparius
Agropyron spicatum
Artemisia tridentata
Artemisia cana
Andropogon scoparius
Stipa comata
Juniperus scopulorum
Artemisia tridentata
Pintus ponderosa
Juniperus scopulorimi
Artemisia cana
Agropyrofl spicatum
Oryzopsis hymenoides
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Oryzopsis hymenoides
Pinus ponderosa
Species Ppm S
Common Name 71_ ]2_
Big Sage
Bluebunch Wheatgrass
Needle and Thread
M II
Silver Sage
Little Bluestem
Bluebunch Wheatgrass
Big Sage
Silver Sage
Little Bluestem
Needle and Thread
Rocky Mtn. Juniper
Big Sage
Ponderosa Pine 700 700
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgrass
Indian Rice Grass
Ponderosa Pine 700 700
Rocky Mtn. Juniper
Silver Sage
Bluebunch Wheatgras
Indian Rice Grass
Ponderosa Pine 700 700
281
(by year)
73 74
1400
500
300
600
3000
400
400
1300
2300
300
600
700
1200
600 700
750
2100
400
700
700 600
600
2600
500
700/600
700 600
-------
COLSTRIP SAMPLES (Continued)
F#
Site
2312-A N #4
2113-A
(1312)
2314-A
(1313)
2315-A
2316-A
(1315)
2317-A
2318-A
(1317)
2319-A
(1318)
2320-A
(1319)
2321-A
(1320)
2322-A
(1321)
2323-A
(1322)
2324-A
(1323)
2325-A
(1324)
2326-A NE #1
(1850)
2327-A
(1851)
2328-A
(1852)
2329-A
(1853)
2330-A
(1854)
2331-A
(1855)
2332-A
(1856)
2333-A
(1857)
2334-A
(1858)
2335-A
(1859)
Species
Scientific Name
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Oryzopsis hymenoides
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropryon spicatum
Oryzopsis hymenoides
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Species
Common Name
Ppm S
71 72
(by year)
73_ 74
Rocky Mtn. Juniper 800
Silver Sage 2400
Bluebunch Wheatgrass 600
Little Bluestem 300
Ponderosa Pine 600 700 700 700
Rocky Mtn. Juniper 400
Silver Sage 1800
Bluebunch Wheatgrass 700
Indian Rice Grass 500
Ponderosa Pine 500 600 700 600
Rocky Mtn. Juniper 700
Silver Sage 2300
Bluebunch Wheatgrass 400
Indian Rice Grass 800
Ponderosa Pine 600 600 700 700
Rocky Mtn. Juniper 700
Silver Sage 2000
Bluebunch Wheatgrass 600
Little Bluestem 300
Ponderosa Pine 700 700 600 600
Rocky Mtn. Juniper 700
Silver Sage 2300
Bluebunch Wheatgrass 400
Little Bluestem 300
282
-------
COLSTRIP SAMPLES (Continued)
F#
Site
2336-A NE #1
(1860)
2337-A
(1861)
2338-A
2339-A
(1863)
2340-A
(1864)
2341-A
(1865)
2342-A
(1866)
2343-A
(1867)
2344-A
(1868)
2345-A
(1869)
2346-A
(1870)
2347-A
2348-A
(1872)
2349-A
(1873)
2350-A
(1874)
2351-A E #1
(1825)
2352-A
(1826)
2353-A
2354-A
(1828)
2355-A
2356-A
(1830)
2357-A
(1831)
2358-A
(1832)
2359-A
(1833)
Species
Scientific Name
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperus scopulorum
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Pinus ponderosa
Juniperus scopulorum
Agropyron spicatum
Andropogon scoparius
Calamovilfa longifolia
Pinus ponderosa
Juniperus/ scopulorum
Agropryon spicatum
Andropogon scoparius
Species
Common Name
Ppm S (by year)
71 72 73 74
Ponderosa Pine 700 700 800 600
Rocky Mtn. Juniper 700
Silver Sage 2200
Bluebunch Wheatgrass 500
Ponderosa Pine 600 800 800 700
Rocky Mtn. Juniper 800
Silver Sage 2800
Bluebunch Wheatgrass 600
Little Bluestem 500
Ponderosa Pine 750 750 900 700
Rocky Mtn. Juniper 600
Silver Sage 3400
Bluebunch Wheatgrass 600
Little Bluestem 400
Ponderosa Pine 700 700 800 650
Rocky Mtn. Juniper 700
Bluebunch Wheatgrass 700
Little Bluestem 300
Sandgrass 600
Ponderosa Pine 800 700 800 800
Rocky Mtn. Juniper 600
Bluebunch Wheatgrass 500
Little Bluestem 500
283
-------
COLSTRIP SAMPLES (Continued)
F#
Site
2360-A E #1
(1834)
2361-A
(1835)
2362-A
2363-A
(1837)
2364-A
(1838)
2365-A
(1839)
2366-A
(1840)
2367-A
2368-A
(1842)
2369-A
(1843)
2370-A
(1844)
2371-A
(1845)
2372-A
(1846)
2373-A
(1847)
2374-A
(1848)
2375-A
(1849)
2376-A E #5
(1225)
2377-A
(1226)
2378-A
(1227)
2379-A
(1228)
2380-A
(1229)
2381-A
(1230)
1382-A
(1231)
2383-A
(1232)
Species
Scientific Name
Calomovilfa longifolia
Pinus ponderosa
Artemisia cana
Agropyron spicatum
Andropogon scoparius
Calamovilfa longifolia
Pinus ponderosa
Juniperus scopulorum
Agropyron spicatum
Andropogon scoparius
Aristida longiseta
Pinus ponderosa
Juniperus scopulorum
Agropyron spicatum
Andropogon scoparius
Calamovilfa longifolia
Pinus ponderosa
Juniperus scopulorum
Andropogon scoparius
Agropyron spicatum
Aristida longiseta
Pinus ponderosa
Artemisia cana
Juniperus scopulorum
284
Species
Common Name
Sandgrass
Ponderosa Pine
Silver Sage
Bluebunch Wheatgrass
Little Bluestem
Sandgrass
Ponderosa Pine
Rocky Mtn. Juniper
Bluebunch Wheatgrass
Little Bluestem
Red Three Awn
Ponderosa Pine
Rocky Mtn. Juniper
Bluebunch Wheatgrass
Little Bluestem
Sandgrass
Ponderosa Pine
Rocky Mtn. Juniper
Little Bluestem
Bluebunch Wheatgrass
Red Three Awn
Ponderosa Pine
Silver Sage
Rocky Mtn. Juniper
Ppm S
zi zi
600 700
700 700
600 600
800 800
600 700
(by year)
73_ 74
700
700 600
1900
500
400
600
800 600
700
550
500
700
800 700
400
400
400
900
700 700
600
300
400
600
700 800
1900
700
-------
COLSTRIP SAMPLES (Continued)
Ei
2384-A
(1233)
2385-A
(1234)
2386-A
(1235)
2387-A
(1236)
2388-A
(1237)
2389-A
Species
Site Scientific Name
E #5 Andropogon scoparius
" Agropyron spicatum
" Pinus ponderosa
" Juniperus scopulorum
" Andropogon scoparius
" Agropyron spicatum
Species
Common Name
Ppm S (by year)
71 72 73 74
Little Bluestem 200
Bluebunch Wheatgrass 500
Ponderosa Pine 600 600 600 600
Rocky Mtn. Juniper 500
Little Bluestem 200
Bluebunch Wheatgrass 500
-------
APPENDIX C
AIR POLLUTION - INSECT POLLINATION
PERTINENT LITERATURE
by
JERRY J. BROMENSHENK
Free, J. B. 1960. Pollination of fruit trees. Bee World. 41:141-151,
169-186.
Free, J. B. 1970. Insect pollination of crops. Academic Press, Inc.
Lond. 544 pp.
Griggs, W. H. 1953. Pollination requirements of fruit and nuts.
Calif. Agr. Expt. Sta. Cir. 424, 35 pp.
Hawthorn, L. R. and L. H. Pollard, 1954. Vegetable and Flower Seed
Production. Blakiston, New York.
Levin, M. D. 1967. Pollination. Agr. Handbook 335. U.S. Dept. Agr.
77-85.
Macior, L. W. 1974. Pollination ecology of the front range of the
Colorado Rocky Mountains. Melandria 15:59.
McGregor, S. E. 1973. Insect pollination - significance and research
needs. Am. Bee Jour. 113(7):249, (8):294-295, (9):330-331.
Meeuse, B. J. 1961. The story of pollination. Ronald Press. Co., New
York. 243 pp.
286
-------
Robertson, C. 1924- Flower visits of insects. II. Psyche 31:93-111
Air Pollution and Pollinators
Arsenic
Bartik, M. 1962. Veterinarstvi. 12(2):52-53.
Bartik, M. and I Havassay, 1963. Veterinarstvi 13(10):460-462.
Dolotovskaya, Y. A. 1962. Action of arsenic on bees. Bull. Apic.
Inform. 5(1):9-20.
Ferencik, M. 1961. Industrial poisoning of bees and its diagnosis.
Vet. Casopia 10(4):377-382.
Gunther, 0. and H. Dallmann, 1968. Distribution and action of fumes
toxic to honeybees, especially around arsenical dusts. Garten u.
Kleintierz. Imker 7(4):10-11.
Knowleton, G. F., A. P. Sturtevant and C. J. Suranson. 1950. Adult
honeybee losses in Utah as related to arsenic poisoning. Bull.
Utah Agric. Exp. Sta. No. 340:30 pp.
Muller, B. and M. Worseck. 1970. Injuries to bees from arsenic - and
fluorine-containing industrial gases. Monatsh. f. Veterinarmed.
25:554-556.
Mulsteph, W. 1963. Tharandter Forstl. Jahr. 87(3):239-277.
Prell, H., 1954-55. Smoke damage among the creatures of the forest.
Wiss. Z. Th. Dresden. 453-462.
287
-------
Rousseau, M. and C. Pangaud. 1959. Lethal doses of arsenic and digestion
in the honeybee. Bull. Apic. Inform. 2(2):15-28.
Svoboda, J. 1962. Arsenic poisoning of bees by industrial fumes.
Rostlinna Vyroba 1499-1506.
Svoboda, J. 1960. Industrial poisoning of bee colonies and its control
in the C.S.S.R. Za Sotaialist. Sel's Kokhoz Nauku, ser. A. 9:595-
602.
Yao, T. A., and G. F. Knowlton. 1949. Surface arsenic occurrence on
some plants attractive to bees. Utah State Agrie. Exp. Sta. Mimeo.
Ser. No. 349, 1-8.
Cyanide
Muller, B. and M. Worseck. 1970. Injuries to bees by cyanide-containing
sewage. Montash. f. Veterinarmed. 25:557-558.
Fluoride
Artkins, E. L., Jr., L. D. Anderson and E. A. Greywood, 1970. Pesticide
research techniques and results in California. Am. Bee Jour.
110:287-89, 426-429.
Bourbon, P. 1967. Analytical problems posed by pollution by fluorine
compounds. Air Pollut. Control Assoc. Jour. 17:661-663.
Bredemann, G. and H. Radeloff. 1939. Death of Bees through waste gas
containing fluorine. Deutscher Imkerfuhrer XIII (2):59-61.
288
-------
Caparrini, W. 1957. Fluorine poisoning in domestic animals (cattle)
and bees. Zooprofilass 12:249-250.
Carlson, C. E. and J. E. Dewey. 1971. Environmental pollution by
fluorides. USDA, Forest Service, Missoua, Mt.
Carlson, C. E., W. E. Bousfield and M. D. McGregor, 1974. The relation-
ship of an insect infestation on lodgepole pine to fluoride emitted
from a nearby aluminum plant in Montana. USDA, Forest Service,
Missoula, Mt. Insect and Disease Rpt. 74-14, 7 pp.
Dewey, J. E., 1972. Accumulation of fluorides by insects near an emission
source in western Montana. Environ. Ent. 2(2):179-182.
Dreher, K. 1965. Poisoning of bees by fluorine. Bull Apic. Inf.
Docum. Scient. Techn. 8(2):119-128.
Ferenicik, M. 1961. Industrial poisoning of bees and its diagnosis.
Vet. Casopia 10(4):377-382.
Gerdes, R. A., J. D. Smith and H. G. Applegate. 1971. The effects of
atmospheric hydrogen fluoride upon D. melanogaster-I. Differential
genotypic response. Atm. Environ. 5:113-116.
Gerdes, R. A., J. D. Smith and H. G. Applegate. 1971. The effects of
atmospheric hydrogen fluoride upon D. melanogaster-II. Fecundity,
Hatchability, and Fertility. Atm. Environ. 5:117-122.
Guilhon, J. 1961. Atmospheric pollution by subliminated fluorines of
industrial origin. Revue. Ass. Prev. Pollution Atmospherique
3(4):260-272.
289
-------
Guilhon, J. 1958. Fluorine and beekeeping. XVII Int. Beekeep. Congr.
Guilhon, J., R. Truhant, and J. Bernuchon, 1962. Studies ef variations
in fluorine levels in bees with respect to industrial atmospheric
air pollution in a Pyrenean village. C. R. Seances Acad. Agric.
Fr. 48:607-615.
Himmer, E. 1934. The influence of fumes and waste gases from industrial
plants on bees. Verhandlungen der deutschen Gessellschaft fur
angewandte Entomologies IX:115-129.
Jachimowicz T. 1961. Damage to bees by industrial waste gases containing
fluorine. Dtsch. Bienenw. 12(2):38-40.
Jachimowicz, T., C. Toumanoff, and F. Weiler. 1958. Fluorine in honey-
bees in Haute-Autriche. Rev. franc. Apic. 3(144):165-170.
Jachimowicz, T., R. Truhant and J. Bernuchon. 1962. Acad. d'Agr. de
France Compt. Rend., 48:607-615.
Johansen, C. A. 1971. Toxicity of field-weathered insecticide residues
to four kinds of bees. Envir. Ent. 1(3):393-394.
Lezovic, Jr. 1969. The influence of fluorine compounds on the biological
life near an aluminum factory. Fluoride Q. Rep. 2(l):25-26.
»
Warier, J. R. 1968. Fluoride's. Science 159:1494-5.
Warier, J. R., D. Rose and J. A. Hart. 1969. Environmental Fluoride.
Pollution Task Force Report. Div. Biol. N.R.C., Ottawa.
290
-------
Maurizio, A. 1960. Determination of the lethal dose of some fluorine
compounds for bees. With a contribution to the methods of determining
toxicity in bee research. IV Int. Congr. PI. Prot. 2:1709-1713.
Maurizio, A. 1957. Factors affecting the toxicity of fluorine compounds
to bees. Bee World 38(12):314.
Maurizio. A. 1956. Bee poisoning in Switzerland by industrial waste
gases containing fluorine. XVI Int. Beekeep. Congr. Prelim. Sci.
Meet.
Maurizio, A. 1955. Plant disinfectants and industrial waste gases, the
cause of bee poisonings. Schweiz. Landwirtschalftliche Monatshefte
33:159-166.
Maurizio, A. and M. Staub. 1956. Bee poisoning in Switzerland with
industrial waste gases containing fluorine. Schweiz. Beinenztg.
79(11):276-486.
Mohamed, A. H. 1970. Induced recessive lethals in second chromosomes
of Drosophila melanogaster by hydrogen fluoride. 2nd. Int. Clean
Air Congr. of the Int. Union of Air Poll. Prev. Assoc. 10 pp.
Muller, B. and M. Worseck. 1970. Injuries to bees from arsenic- and
fluorine- containing industrial exhaust gases. Monatsh. f. Veter-
inarmed. 25:554-556.
Outram, I. 1970. Some effects of the fumigant sulphury! fluorides on
the gross metabolism of insect eggs. Fluoride Q. Rpt. 3(2):85-91.
Randeloff, . 1939. Investigation and appraisal of flu-gas damage.
Hamburg. Staat. sist. Angew. Botanik Jahresher 6:126-127.
291
-------
Root, E. R. and M. J. Deyell. 1941. Destruction of bees by smelter
gases. Clean. Bee Culture LXIX (10):638.
Toumanoff, C. 1964. New experiments on the toxicity of fluorine to
honey bees. Ann. Abeille 7(3):207-215.
Toumanoff, C. 1962. Experimental research on the toxicity of fluorine
to honeybees. Ann. 5(3):247-2600.
Trautwein, K., R. Buchner, and C. Kopp. 1968. Laboratory and field
investigations of fluorine effects on bees. Trans, from German.
Franklin Inst. Res. Labs., Phil!., Pa. Sci. Info. Services., Proj.
#C2439. 10 pp.
Yamazoe, Fumio. 1970. Effects of hydrogen fluoride on plants. Kogai
To Taisaka (J. Pollution Control) 6(7):515-520.
Lead
Galob, R. 1958. Poisoning of bees by dust containing lead. Slov. Ceb.
60(3/4):57-60.
Jachimowicz, T. 1955. The effect of lead oxide on bees. Z. Bienenforsch
3(2):29-31.
Nitrous compounds
Ribbands, C. R. 1954. Nitrous oxide anaesthesia does not encourage
reorientation of honeybees. Bee World 35:91-95.
Ribbands, C. R. 1950. Changes in the behavior of honeybees following
their recovery from anaesthesia. Jour. Exp. Biol. 27:302-310.
292
-------
Simpson, J. 1954. Effects of some anaesthetics on honeybees: nitrous
oxide, carbon dioxide, ammonium nitrate, smoke and fumes. Bee
World 35:147-155.
Wells, F. B. 1957. Treatment of bees with nitrous oxide. Am. Bee
Jour. 97(4):149-50.
Radiation
Goolsby, M. 1968. How does nuclear radiation affect honeybees? Am.
Bee Jour. 108(9):352-353.
Svoboda, J. e_t al_. 1968. The occurence of radioactive strontium-90 in
experimental honeybee colonies and in their products. Vedecke
Prace Vyzkumneho Ustavu Vclarskeho v Dole 5:63-75.
Sulfur
Cotton, R. T., 1932. The relation of respiratory metabolism of insects
to their susceptibility to fumigants. J. Econ. Entomol. 25:1088-
1103.
Gough, H. C. 1940. The toxicity of sulfur dioxide to the bed-bug,
Cimex lectularius L. Ann. Appl. Biol. 27:101.
Gunnison, A. F. 1970. Biological effects of sulfur dioxide on animals,
emphasizing the interaction of sulfite with the noncellular fraction
of blood. Ph.D. Thesis. The Penn. State Univ., University Park.
151 p.
Hastings, L. and R. Frietag 1973. Kraft Mill Fallout and Ground Beetle
Populations. Atm. Environ. 7(5):587-88.
293
-------
Hastings, L. R. Frietag, and A. Smith. 1972. Fallout of sodium sulphate
near a Kraft mill. Atm. Environ. 6:241-246.
Hilliam, R. C., 1972. Biological effects of air pollution on insects,
emphasizing the reactions of the honeybee (Apis mellifera L.) to
sulfur dioxide. Ph.D. Thesis. Penn. State. 159 pp.
Kanage, E. E. 1956. An evaluation of the use of sulfur dioxide in
fumigant mixtures for grain treatment. J. Econ. Entomol. 723-9.
Trace elements. Miscellaneous
Atkins, E. L., Jr. 1966. Well, almost: Bees breathe smog with ease.
Am. Bee Jour. 106(10):374.
Ramel, C. 1967. Genetic effects of organic mercury compounds. Oikos
(suppl.) 9:35.
Schricker, B. and W. Stephen. 1970. The effect of sublethal doses of
parathion on honeybee behavior. 1. Oral administration and the
communication dance. Jour. Apic. Res. 9(3):155-164.
Shekiladze, A. V. 1971. Effect of some trace elements (cobalt and
zinc) on the egg-laying capacity of queens and colony productivity.
Research Works of the Georgian Beekeeping Research Station 3:239.
pp.
294
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APPENDIX D
BIOLOGICAL IMPACT OF AIR POLLUTION ON INSECTS
Jerry J. Bromenshenk
Insect populations, which comprise 75 percent of all animal species,
respond significantly to air contaminants. Unfortunately, our under-
standing of insect-pollutant relationships is restricted primarily to
studies of a few benficial and destructive species such as honeybees and
pests of forests. The extant reports consist of historical and geographical
surveys of insects near industrial sources, a few laboratory fumigation
experiments, and disparate biochemical and genetic studies.
Insect populations often increase or decrease in numbers in response
to pollution stress. In areas of Pennsylvania subjected to elevated
levels of sulfur dioxide, significant increases in the number of aphids
(Aphidae) and decreases in the numbers of social bees (Apidae) and
several parasitic wasp (Hymenoptera) families were recorded—the increase
of aphids may have been de to a S02 induced parasite imbalance (15). A
highly significant relationship between an increase in tree damage by
two species of needle miners, Ocnerostoma strobivorum (Zeller) and
Zellaria haimbachi (Busck) and ambient and foliar concentrations of
fluoride in lodgepole pine, Pinus contorta v. latifolia Engelm. was
observed near an aluminum reduction facility at Columbia Falls, Montana.
The data indicated that fluoride disposed the pines to insect injury
(2). A negative correlation between the size of ground beetle populations
and the rate of fallout of sodium sulphate existed near a Kraft mill in
2_
Canada; the change in insect numbers may have been due to S02 or to
other particulates (13). Most ground beetles are predatory, and like
their beetle allies, the ladybugs, attack noxious insects.
295
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Some contaminants accumulate in the tissues of insects. Four major
groups of insects—pollinators, predators, foliage feeders, and cambial
feeders—collected near an aluminum smelter (Montana) and analyzed for
fluoride content contained 58.0 to 585.0 ppm fluoride (dry weight), 6.1
to 170.0 ppm, 21.3 to 255.0 ppm, and 8.5 to 52.5 ppm, respectively.
Control insects had 3.5 to 16.5 ppm of fluoride. "The relatively high
fluoride levels in the 100 percent predatory insects indicate fluorides
are either accumulated by respiration or are passed along the food chain
(5). Other reports indicate that fluorides (see Figure 1), arsenites,
trace elements and fractions of particulates may accumulate in insect
tissue (1, 3, 5, 6, 7, 11, 17, 18, 21, 23, 26, 28). Tissue concentrations
of contaminants (and presumably their effects) vary with different
insects, climate, geography, and pollution factors. Insect species,
activity, age, development, feeding habits; weather patterns, wind,
precipitation; contaminant species, composition and form—all influence
uptake. But, contaminants do not necessarily have to be accumulated to
affect insect populations either directly by toxicosis or indirectly
through chain reactions among dependent organisms.
A fallacy of many field studies of air pollution and insects has
been the use of data that correlates changes in insect populations, such
as mortalities, with ambient air concentrations or tissue concentrations
of a single contaminant to indict the contaminant as the "cause" of
mortality and event to estimate toxicity. Harm by air contaminants is
demonstrated by such surveys, but the data are usually insufficient to
identify a specific causal agent. Air pollution does not consist of
single contaminants, but rather consists of complexes of gases and
particulates that may be physically and chemically transformed during
atmospheric transport. The effects of air pollution results from inter-
actions of many contaminants. Assessments of specific, individual
pollutants is largely a matter of "practical" simplification of the
problem and a lack of understanding of the interactions of contaminants
296
-------
30.0
25.0
20.0 .
o
-------
and other environmental factors. The total impact of pollutants and
environmental stresstors is not simply additive. Not only contaminant
emitting sources, but other sources of evironmental insults must be
examined. For insect studies, a frequent confounding stressor is pesti-
cides.
Toxicosis is usually an obvious manifestation of pollution injury.
Episodic, acute exposures to pollutants may result Jin marked displays of
insect population response such as serious losses of honeybees due to
arsenic or pesticide poisonings. Figure 2 shows some lethal doses of
contaminants to honeybees. But, episodic exposure may not be as important
to a biological system as chronic, low level exposures to air contaminants
over periods of years. Low level of pollutants or low toxicities do not
imply low hazard to insects. Chemicals such as arsenic and the organo-
phosphate insecticide, carbaryl, may have little effect on foraging
bees, but are accumulated in the brood—a situation analagous to control
of ants in which case on seeks a slow acting, low level toxic to increase
effectiveness (Dr. Roy V. Barker, letter dated March 14, 1975, USDA Bee
Research Laboratory, Tucson, Arizona).
Sublethal as well as lethal effects of contaminants are important.
Physiological, biochemical, genetic and behavioral consequences of air
pollution are superficially understood. Some information is available
for honeybees (Hymenoptera), less is available for flies and midges
(Diptera), and practically nothing is known for other insects. The
toxicology of a few contaminants as insecticides (such as arsenic and
carbon disulfide) has been examined although lethal dose determinations
predominate, and the biochemical processes are sketchily understood for
most compounds. For example, sulphuryl flouride in eggs of desert
locusts and yellow mealworms "appears" to act as an inhibitor of several
metabolic processes and may be nonspecific in respect to sites of attack
(22). Genetic studies of pollution effects have been restricted primarily
298
-------
160.0 _
130.0 J
11.0
10.0
9.0 _
8.0 .
a
5
>»
o
c
0
7.0 .
6.0 .
5.0
3.0 _
2.0 _
1.0 .
0.0
T
to
tn
O
ir,
Q
1 Arsenic trioxidc (17) 4 Sodium fluoride (18) 5 Sodium fluoride (11)
Ammonium fluoride
2 Sodium arsenate (26) Ammonium bifluoride 6 Calcium fluoride (11)
Hydrofluoric acid
3 Potassium cyanide (21) 7 Sodium aluminum (18)
fluoride
Fig. 2. Comparative determinations of the lethal doses of pollutants
to honeybees. Numbers in parentheses refer to authors.
299
-------
to Drosophila species (fruit flies). Hydrogen fluoride at 1.3 to 2.9
ppm reduced hatchability and fecundity of D. melanogaster. presumably as
a result of genetic damata (9). Chromosone disjunction has been induced
in Drosophilia by feeding 0.25 mg mercury (methyl mercury hydroxide/kg
substrate) (23). Fumigation treatments of D. melanogaster for 6 to 12
hours of hydrogen fluoride (hydroflouric acid at 2.5 percent concentrations)
produced a trend toward higher frequencies of lethal and sublethal
chromosomes (drastics) with increased treatment duration (20). Pollutant
induced behavior modifications occur. Anaesthesia with carbon dioxide
or nitrous oxide induced permanent changes in the behavior of honeybees--
pollen collecting was reduced or suspended, while brood rearing and wax
secreting were eliminated by young bees because these bees began foraging
at an earlier age (24). Sublethal doses of parathion prevented honeybees
from communicating to other bees by dancing the direction of a food
source (27). Similar doses of parathion changed the singing patterns of
crickets (Acheta domesticus L.) and resulted in prevention of successful
copulation by cricket males, while sublethal doses of Dieldren and Sevin
resulted in complete cessation of singing for 3-6 hours (31).
Although the relationships between insect populations and air
contaminants are obscure, the indirect effects of air pollution on insects
such as vegetation responses to pollutants and subsequent respones by
associated obligative and facultative insects are practically unknown,
except for a few studies of insect infestations on pollutant stressed
forests (2, 3, 4, 29). The observed increases of insect pests on pollution
stressed vegetation may be due to: (1) increased susceptibility of
plants because of weakened physiological condition (2) reduction or
elimination of parasites and predators of the insect pests; (3) movements
of insect populations to or from these areas, or (4) combinations of
these factors and presumably other factors yet to be identified. Air
pollution may affect only a few components of an ecosystem, yet these
may initiate chain reactions among dependent organisms. Adverse impacts
300
-------
of air contaminants on beneficial insects (pollinators) have been frequently
reported, but it is conceivable in some instances that pollinators might
increase in numbers—air pollution stress can increase flowering of some
plants, and pollinators such as the social bees reflect changes in
nutritional supplies through their brood rearing. However, many pollutants
have direct adverse effects on bees and as such exert a limiting influence
on population size.
Pollinators may be one of the insect systems most sensitive to air
pollutant stress. Pollination (entomophily) depends primarily on bees
(Hymentoptera). Flies and midges (Diptera) are second to bees in visiting
thrips (Thysanoptera), beetles (Coleptera), and other orders of insects
contribute in various degrees. Bees are the best pollinators, being
morphologically and behaviorally specialized for pollent transport. The
hairy bodies of solitary and social bees are well adapted for pollen
collection. Unlike insects that collect pollen for their immediate
needs, bees collect pollen not only for their own needs, but also to
provision the nest and brood. This necessitates extensive foraging and
efficient collection and transport of nectar and pollen. The branched
hairs on the bodies of many bees are well suited to the collection and
transport of particulate contaminants. Obviously, the repeated and
often lengthy foraging journeys of bees increase the likelihood of these
insects encountering a pollution source. There is probably more infor-
mation about air pollution and insect response for honeybees than for
any other species of insects, but one still cannot generalize even about
the response of honeybees or of other species of bees to particular
pollutant complexes. For example, susceptibility of four species of
bees to field weathered insecticides occurred as follows: alfalfa
leafcutter bees > alkali bees > honeybees > bumblebees. Susceptibility
appeared to increase as the surface: volume ratio increased (bumblebees
are as much as nine times the mass of leafcutter bees), although factors
such as hairiness and behavior probably contributed (16).
301
-------
Throughout the U.S. many areas already are experiencing lack of
native pollinators. S. E. McGregor says that approximately one-third of
the total U.S. diet is derived, directly or indirectly from insect pollinated
crops. He quotes (14), " there has been an increasing accumulation
of data to indicate that seed fields of insect pollinated crops can be
lower than they need to be, not because of climate, soil, or cultural
practices, but simply because the population of certain insects is low."
Mr. McGregor concludes that there is a need for 5 to 20 times the number
of manageable colonies of bees available—an additional 2.5 to 10 millon
colonies (19). California growers now important honeybees from as far
away as North Dakata to satisfy pollination needs. Yet honeybees cannot
replace native pollinators to meet the pollination requirements of many
plants. Approximately 37 species of native insects are capable of
pollinating onions, but honeybees are not as effective. (Telephone
conversation, March 15, 1975, Dr. Frank D. Parker, USDA Bee Biology and
Systematics Laboratory, Logan Utah. Pesticide poisoning is responsible
for much of the current shortage of pollinators, yet air pollution is
rapidly increasing as a contributing factor. In telephone conversation
(March, 1975) with the major research groups involved with pollination
and pollution research, investigators repeatedly reported observations
of an absence of pollinators, especially bees, in industrial and urban
areas, although hard data is often lacking to support these observations.
But commercial beekeepers often do not or cannot keep honeybees downwind
from industrial developments such as smelters and fossil fuel-burning
power plants. It is reasonable to expect adverse effects of air pollution
on other pollinators.
Obviously, studies should be initiated very soon to clarify the
relationships of insects and air pollution. Again, in our telephone
interviews, we could not find any research projects concerned with
insects and pollution in the U.S. except for those current in progress
under the auspices of the Environmental Protection Agency, Corvallis,
Oregon, in the Fort Union Basin area of Southeast Montana.
302
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The coal-fired power plant development in Southeast Montana affords
a unique opportunity to investigate some of the consequences of air
contaminants on insect systems. Both forest and grassland areas occur
in the vicinity of the power plant complex. A number of insect systems
are available for study. Most importantly is the opportunity to conduct
baseline studies before the power plants begin operation in an area that
is relatively pollution free at the present time and the opportunity to
work with a multi-institution, multi-disciplinary research effort.
Ongoing studies in the Fort Union area include examinations of plant
communities, biomass, fungi, vertebrates, meteorology, lichens, reclamation.
soils, hydrology and socio-economics. The grasslands biome project
(Colorado State University) includes investigations of the invertebrate
consumer components of the grassland ecosystems. Included are identi-
fication and quantification of above and belowground macro-and micro-
invertebrates.
The Environmental Studies Laboratory, University of Montana, under
the Direction of Dr. C. C. Gordon was awarded a grant by the Environmental
Protection Agency on August 1, 1974 to conduct studies on vegetation,
fungi and insect components of the Fort Union area. Although a number
of insect systems are available for study and should be examined, it
would be futile to attempt to look at all of the insects. Specifically,
we selected dominant, indigenous insect-plant populations which have a
diversified, but understandable realtionship. We considered feasibility
biological importance and economic impact. Certain insect populations
are sensitive indicators of pollution stress, and these appeared to have
the greatest potential for supplying useful and understandable information.
Consequently, the insect work has been concentrated on two groups:
pollinators and infestations on Ponderosa pines by pest insects. Both
showed specific respones to air contamination in previous studies,
appear to be very sensitive pollution indicators, are economically
important to the region, and are manageable for research purposes.
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The Fort Union development provides an excellent opportunity for
field experimentation. Unfortunately, since the shakedown operations of
the power plant complex will begin this spring (1975), baseline data
should already have been obtained. In some instances it has. Studies
of insect population response should be oriented towards field invest-
igations. Laboratory studies have value, but laboratory results do not
necessarily correspond to events in the much more complex environment of
an ecosystem. For example exposure to 5,000 rads of gamma or neutron
irradiation reduced by 21 percent the life span of worker honeybees
housed in laboratory cages. Yet, when an entire colony was irradiated
with 5,000 rads and returned to the field, the bees perished (10). Most
researchers are cognizant of the problems associated with conducting
field experiments in complex environments. Oversimplification of the
field environment as a "control" measure, in essence, establishes a
quasi-laboratory condition. Cultivation of non-cultivated plants,
irrigation of plants normally receiving only natural rainfall, elimination
of insect pests, transplantation of plants to areas in which they would
not normally occur, destructive sampling—procedures such as these
simply testing but may invalidate extrapolation of results to the real
world. Field controls ideally consist of natural sites in which confounding
factors are identified and monitored, not eliminated. Hopefully, this
can be accomplished in the Fort Union Basin.
There can be no doubt that air contaminants affect insect populations,
although the exact processes are not understood. It is reasonable to
expect biologic and economic costs of air pollution stress. We need to
know at what level of pollution the economic and biologic consequences
are important as well as to identify the effects. We must assess the
actual significance of insect populations, benficial and destructive, to
the Southeast Montana ecosystems. Ultimately, biologic impact is expressed
in terms of economic impact. Who pays for destructive insect infestations
to forests? What is the cost of replacing or supporting pollination
304
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study (5). The mean sulfur content was 4392 ppm, SD=286. Sulfur occurs
as a natural portion of animal tissue and there appears to be some
question as to whether or not it is accumulated, although exposure to
S02 at 8.2 ppm for three weeks increased sulfate in honeybee haemolymph
by a significant amount (12). Pesticide analyses being conducted in
cooperation with this project by Dr. Ronald Thomas, EPA, Biological
Investigations Laboratory, Beltsville, Maryland, revealed the presence
of low level residues of chlorinated hydrocarbons in bees from four
sites. Some 700-800 colonies of bees were killed in the Fort Union area
in 1974, presumably as a result of pesticide poisonings. Pesticide
poisonings have occurred previously in this area, and therefore, it is
essential to consider this pollutant source with that of the air contam-
inants emitted by the power plants. We shall continue these chemical
analyses over the next 2-3 years, after the power plants have become
operative. We intend to perform analyses for trace elements as well as
to utilize AchE determinations as an index of sulfur interaction.
Our approach to the bees will be as inclusive as possible. We
shall monitor behavioral responses through the use of observation beehives
and a ferrous-metal capture-recapture system. The latter (8) consists
of small metal tags that are affixed to bees and collected at monitoring
points by magnets. This method is particularly useful for monitoring
foraging activities. We shall monitor biopathways of pollutant uptake
through the use of pollen and dead bee collectors and conduct fumigation
experiments at the EPA zonal air pollution delivery system in Southeastern
Montana and in the laboratory. Finally, we shall examine indications of
physiological condition such as brood rearing, colony activity, and
colony size.
Our work with the pest infestations on Ponderosa pine is concerned
with: (1) estimates of the endemic insects and pollution damage being
sustained by the pines, (2) comparisons over the next few years to
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determine if insect damage has appreciably increased, and (3) if this
increase correlates to a significant degree with foliar and precipitation
content of pollutants such as fluorides and sulfurs. The condition of
the ptnes is rated via vigor rating whtch takes Into account factors
such as needle retention, needle necrosis, and other physiological
symptoms of pollution stress. Our data from 1974 indicates that insect
damage in the area was usually very slight, with the exception of fairly
severe loss of seed production because of cone boring insects such as
Conophthorus beetles and Laspeyresia and Dioryctria moths. This type of
damage affects seed production, but does not appreciably injure the tree
itself. Several studies have shown significant correlations in the
relationships of pest damage and foliar and ambient air concentrations
in the relationships of pest damage and foliar and ambient air concen-
trations of air contaminants. However, these studies have always relied
on data obtained after the source of the contaminants have been in
operation for extended periods of time. Therefore, whereas the level of
pollution and the size of the insect populations may correlate, the
total impact or extent of the increase over that of an "undisturbed"
situation is unknown.
Obviously, other insect systems should be investigated in Southeast
Montana. One of the more significant systems is that of the western
harvester ant. Another consists of the grasshopper populations which
periodically have been severe pests of the range!ands. The "Applicant's
Environmental Analysis" (30) recognized the following economically
important insects and arachnids present in the impacted area: Rocky
Mountain ticks, mosquitos, fleas, and deer flies as vectors of human
disease; pine beetles, larch casebearers, spruce budworms, and mountain
pine beetles as forest pests. The applicants made no mention of agri-
culturally important insects such as pollinators and those species
predacious or parasitic on invertebrate pests.
306
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Commercial honeybees are important to the economics of the Col strip,
Montana, area. Approximately 3,000 colonies of honeybees are maintained
i the Fort Union Basin. These colonies provide bee products such as
honey and wax, are valuable pollinators of alfalfa seed crops, and at
least 1,000 colonies are transported annually to California (October
through April) and rented for pollination of crops. At a very conservative
estimate, the honeybee industry comprises a $240,000 to $300,000 enter-
prise (at a value of $80-100 per colony for bees and products). Floyd
Moeller, research leader of the North Central States Bee Laboratory,
Madison, Wisconsin, estimates the actual economic value of honeybees as
pollinators at 20 times their value as honeymakers. This means that the
honeybees in Southeast Montana may be worth $3-4.5 million as pollinators
of rangelands and agricultural lands in Montana and an additional $500,000
to one million dollars as pollinators of California crops. (Data based
on marketable honey yields from 1,200 colonies in the Fort Union Basin,
confidential report.) In addition to honeybees, native bees are plentiful
in the Col strip area as evidenced by my observations in August-October
of 1974. Currently, native bees may be capable of satisfying the pol-
lination needs of most of the vegetation of the Fort Union area. However,
evidence from insecticide problems indicate that the native bees, especially
the physically smaller species, may be much more susceptible to pollutant
toxicosis than honeybees.
The manageability and numbers of honeybees in the study area make
them an excellent tool. We obtained samples of adult honeybees from
thirteen apiaries in October of 1974 for chemical analyses. We have
completed fluoride and sulfur analyses, have obtained partial results
from pesticide analyses, and have a bank of fresh frozen and dried
material for additional chemical analyses. The baseline levels of
contaminants tn this area appear to he low: fluoride averaged 7.4 npm
dry weight, SD=3.1, in adult bees (unpublished data), which compares
favorably with the 10.0 ppm found in control bees for the Columbia Falls
307
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systems by importing the cost of replacing or supporting pollination
systems by importing insects such as now occurs in California? What
are the consequences of a lack of pollinators to plant diversity and
abundance on rangelands and eventual impact on the cattle industry?
What is the impact of increased foliage feeders such as aphids on agri-
cultural crops? These are but a few of the questions that need to be
answered. Unfortunately, we will not answer any or all of these questions
without intensive long-term studies. Evaluations of pollution impact
must be tested by gathering baseline information under "pollution free"
conditions. Areas in which this can be done are becoming increasingly
difficult to find. The Fort Union Basin afforded one such opportunity,
although advance notice was not sufficient to allow long-term baseline
studies. Obviously, we cannot accurately predict the location or intensity
of new pollution sources. Therefore, we need to find undisturbed areas
and conduct baseline studies while such areas are available. S. E.
McGregor, in a recent synopsis of the significance and research needs of
insect pollination, stated: "Many crop varieties grown today, have
been tested under insecticide-free conditions to determine the actual
value of the pollinators unhampered by damaging pesticides" (19).
Considering the worldwide distribution of pesticide use, one must ask if
a totally insecticide-free area exists. The same may soon be true for
pollution-free areas.
308
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REFERENCES
1. Atkins, E. L., Jr., L. D. Anderson and E. A. Greywood. Pesticide
research techniques and results in California. Am. Bee Journal.
Vol. 110:387-89, 426-29. 1970.
2. Carlson, C. E., Wayne E. Bousfield and Mark D. McGregor. The
relationship of a insect infestation on Lodgepole pine to flouride
emitted from a nearby aluminum plant in Montana. USDA, Forest
Service, Northern Region, Missoula, Montana. Insect and disease
report No. 74-14, 21 pp. (1974).
3. Carlson, C. E. and J. E. Dewey. Environmental pollution by fluorides
in Flathead National Forest and Glacier National Park. USDA,
Forest Service, Northern Region, Missoula, Montana. 57 pp. (1971).
4. Carlson, C. E. and W. P. Hammer. Impact of fluorides and insects
on radial growth of Lodgepole pine near an aluminum smelter in
northwestern Montana. USDA, Forest Service, Northern Region,
Missoula, Montana. Report No. 74-25. 14 pp. 1974.
5. Dewey, J. E. Accumulation of fluorides by insects near an emission
source in western Montana. Environ. Ent., Vol. 2, No. 2:179-182.
1972.
6. Dreher, K. Poisoning of bees by fluorine. Bull. Apic. Inf. Docum.
Scient. Tech. Vol. 8, No. 2:119-128. 1965.
7. Frencik, M. Industrial poisoning of bees and its diagnosis. Vet.
Casopia. Vol. 10, No. 4:377-382. 1961.
309
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8. Gary, N. E. Magnetic retrieval of ferrous labels in a capture-
recapture system for honey bees and other insects. Journ. Econ.
Entomol. Vol. 64, No. 4:961-65. 1971.
9. Gerdes, R. A., J. D. Smith, and H. G. Applegate. The effects of
atmospheric Hydrogen Fluoride upon D. melanogaster. II. Fecundity,
hatchability and fertility. Atm. Environ. Vol. 5:117-122. 1971.
10. Goolsby, M. How does nuclear radiation affect honeybees? Am. Bee
Journal. Vol. 108, No. 9:352-353. 1968.
11. Guilhon, J. Atmospheric pollution by sublimated fluorines of
industrial origin. Revue. Ass. Prev. Atmospherique. Vol. 3, No.
4: 260-272. 1961.
12. Gunnison, A. F. Biological effects of sulfur dioxide on animals,
Emphasizing the interaction of sulfate with the noncellular fraction
of blood. Ph.D. Thesis, Pennsylvania State University, PA. 151
pp. 1970.
13. Hastings, L. and R. Frietag. Kraft mill fallout and ground beetle
populations. Atm. Environ. Vol. 7, No. 5:587-88. 1973.
14. Hawthorne, L. R. and L. H. Pollard. Vegetable and flower seed
production. Blakiston, New York (1954).
15. Hillman, R. C. Biological effects of air pollution on insects,
emphasizing the reactions of the honeybee (Apis mellifera L.) to
sulfur dioxide. Ph.D. Thesis, the Pennsylvania State University,
University Park, PA. 159 pp. (1972).
310
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16. Johansen, C. A. Toxicity of field-weathered insecticide residues
to four kinds of bees. Env. Ent. Vol. 1, No. 3:393-394. 1971.
17. Knowlton, G. F., A. P. Sturtevant, and C. J. Suranson. Adult
Honeybee Losses in Utah as related to Arsenic Poisoning. Bull.
Utah Agric. Exp. Sta. No. 340. 30 pp. 1950.
18. Maurizio, A. Factors affecting the toxicity of fluorine compounds
to bees. Bee World. Vol. 38, No. 12:314. 1957.
19. McGregor, S. E. Insect pollinators—significance and research
needs. Am. Bee Journal. Vol. 113, No. 7:249, No. 8:294-295, No.
9:330-331. 1973.
20. Mohamed, A. H. Induced Recessive lethals in second chromosomes of
Drosophila melanogaster by hydrogen fluoride. Second International
Clean Air Congress of the Int. Union of Air Poll. Prev. Assoc. 10
pp. 1970.
21. Muller, B. and M. Worseck. Injuries to bees from arsenic- and
fluorine-containing industrial exhaust gases. Monatsh. f. Veter-
inarmed. Vol. 25:554-556. 1970.
22. Outram, I. Some effects of the fumigant sulphuryl fluorides on the
gross metabolism of insect eggs. Fluoride Q. Rept. Vol. 3, No.
2:85-91. 1970.
23. Ramel, C. Genetic effects of organic mercury compounds. Oikos
(Suppl.) No. 9:35 (1967).
24. Ribbands, C. R. Nitrous oxide anaesthesia does not encourage re-
orientation of honeybees. Bee world. Vol. 35:91-95. 1954.
311
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25. Robertson, C. Flower visits of insects. II. Psyche, Vol. 31:93-
111. 1924.
26. Rosseau, M. and C. Pangand. Lethal doses of arsenic and digestion
in the honeybee. Bull. Apic. Inform. Vol. 2, No. 2:15-28. 1959.
27. Schricker, B. and W. Stephen. The effect of sublethal does of
parathion on honeybee behavior. 1. Oral administration and the
communication dance. Jour. APic. Res. Vol. 9, No. 3:155-164.
1970.
28. Shekiladze, A. V. Effect of some trace elements (cobalt and zinc)
on the egg-laying capacity of queens and colony productivity. Res.
Works of the Georgian Beekeeping Res. Stat. Vol. 3:239 pp. 1971.
29. Stark, R. W. and J. F. Cobb, Jr. Smog injury, root diseases, and
bark beetle damage in ponderosa pine. Calif. Agric. Vol. 23, No.
9:13-15. 1969.
30. Westinghouse Electric Corporation. Col strip generation and trans-
mission project. Applicant's Environmental Analysis. 327 pp.
(1973).
31. Young, C. L. and W. P. Stephen. The acoustical behavior of Acheta
domesticus L. (Orthoptera: Gryllidae) following sublethal doses of
parathion, dieldrin and sevin. Oecologia. Vol. 4:143-162. 1970.
312
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APPENDIX E.
DISSECTION WORKSHEET FOR WHOLE: CARCASS ANALYSIS
Species: Spec_ No_
Capture Site ~Se~ _
Capture Wt gm. Date _
Disposition
Field or Fxper History __
Post-capture Body Weights: Wt _. gm. Date ;
wt gm. Date ; wt gm. Date _;
Date of Dissection ; Age ; Body Irt gm.;
History Immediately Prior to Death
Lesions, Abnormalities & Ectoparasites
Type of Molt ; Plum. Aspect ; Wing mm;
Bill , mm; Tarsomet. mm; Body Molt_
Hi ng molt
Growing Remiges
Outer 1C mm; Penult 1° mm; Tail molt_ ;
Decks mm; Outer Rectrices mm; Tail mm;
Cloaca! Protub: Length . mm; Diameter _,mm;
Shape of Vent____ ; Bursal Orifice (+) __.
Remarks
Vent. Apter. (d,v,o) ; Viet Wt mg.;
Dry Wt mg; Integument Dry Wt. mg;
PFCTORALIS: Wet Wt. mg; Dry Wt-. mg; DW Calorie Sample mg;
DU Cal. ; Fat Free Wt. mg; FF Calorie Sample mg;
FF Cal. ___; N Sample mg; N g/kg; Fat Class :
FURCULAR FAT SAMPLE: Wet Wt. mg; Dry Wt. nig;
Calorie Sample nig; Calories ; WET CROP & CONTENTS mg;
Wet Crop mg; CROP CONTENTS: Dry Cal Sample mg;
Calories ; Dry N Sample mg; N g/kg;
313
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Thyrnus (Gr. lat, diani.)
mm,
; Wet Ovary_
mg; Cicatrix__
Gonacial Sex
Pre-ov Foil, (mm) _
Post-ov Foil., (mm)
Wet Oviduct mg; Ova mm; Ova
Left Testis mm; Right Testis mm;
mg;
mg; Right
mg; Combined
mg; Viet Spleen_
Wet Testes, Left _
Wet Heart mg; Dry Heart mg; Wet Bursa
Wet Adrenals mg; Wet Kidney__
LIVER: Wet „ mg- Dry
OK1 Cal. ; Fat Free Wt
FF Cal.
_; N Sernple_
mg; DW Cal Sample
; FF Cal, Sample
__ mg; H_
mg;
mg;
me;;
mg ;
mg; Empty.
_mg; Intestinal Contents
Wet Gizzard, Full
Dry ing; N g/kg; Trachea ; Lungs, Wet mg; Dry mg;
CARCASS: Dry Wt. mg; DW Cal. Sample mg;
_ . rng;
DW Cal.
; Fat Free Wt.
FF Cal. Sample mg; FF Cal.
N g/kg; Dry Ash Sample mg; Ash
Internal Parasites
; Dry N Sample nit;;
Other Information:
TISSUE
Carcass sarnole
ADDITIONAL PROCESSING
dry; for chem. essay (e.g. }'ast'icide scan)
Code:
DW =
N =»
FF =
foil -
cal -
dry weight
nitrogen
fat free
follicles
calorie
314
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
•W-W/3-76-013
2.
3. RECIPIENT'S ACCESSION-NO.
ITLE AND SUBTITLE
The Bioenvironmental Impact of a Coal-fired Power Plant
Second Interim Report, Colstrip, Montana
June 1975
5. REPORT DATE
June 1975
6. PERFORMING ORGANIZATION CODE
'. AUTHOR(S)
Edited by Robert A. Lewis, Norman R. Glass and
Allen S. Lefohn
8. PERFORMING ORGANIZATION REPORT NO.
. PERFORMING ORGANIZATION NAME AND ADDRESS
National Ecological Research Laboratory
Corvallis Environmental Research Laboratory
Corvallis, Oregon 97330
10. PROGRAM ELEMENT NO.
I/E-AP-77AC
ST/GRANT NO.
EHA541/E-AP-77ACV
11. CONTRACT
12. SPONSORING AGENCY NAME AND ADDRESS
same
13. TYPE OF REPORT AND PERIOD COVERED
Interim Jan - Jun 1975
14. SPONSORING AGENCY CODE
EPA-ORD
15. SUPPLEMENTARY NOTES
16. ABSTRACT xhis document describes the progress of an investigation that attempts to
characterize the impact of air pollutants on a total (grassland) ecosystem. More im-
portantly, it is the first to attempt to generate methods to predict bioenvironmental
effects of air pollution before damage is sustained. We expect to observe complex
changes in ecosystem dynamics as a function of relatively long term, chronic pollution
challenge. By studying a rather broad range of interacting variables, we hope to
isolate some as sensitive and reliable measures of air pollution impact.
The approach employed requires (1) the use of reasonably comprehensive models of
component populations of the ecosystem; (2) the use of appropriately structured field
and laboratory experiments; and (3X evaluation of physiological and biochemical
functions that may serve as specific indicators of air pollution stress. The study
will establish one part of the cost/benefit matrix that will provide for the normal-
ization of environmental impact information.
Included in the study are the characterization of the effects of coal-fired power
plant emissions upon plant and animal community structure; primary production, inver-
tebrate animal consumers, and decomposers; plant and animal diseases; both beneficial
and harmful insects; indicators and predictors of pollution (e.g., lichens and honey-
bees); physiological responses of plants and vertebrate animals; insect behavior
(mainly of honeybees) and production; the behavior, reproduction and development,
population biology, health and condition of vertebrate animals.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
plant ajnd animal response to pollution
coal-fired power plant
air pollutants
grassland ecosystems
mathematical modeling
remote sensing
micr.ometeorological investigation-
b.lDENTIFIERS/OPEN ENDED TERMS
COSATI Field/Group
coal-fired power plant
emissions
air quality monitoring
aerosol characterization
51
8. DISTRIBUTION STATEMENT
release to pyblic
19. SECURITY CLASS (ThisReport)
Unclassified
21. NO. OF PAGES
20. SECURITY CLASS (Thispage)
22. PRICE
EPA Form 2220-1 (9-73)
315
U.S. GOVERNMENT PRINTING OFFICE: 1976-696-807167 REGION 10
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