EPA-600/3-77-104
September 1977
PHOTOCHEMICAL OXIDANT AIR POLLUTANT EFFECTS ON A
MIXED CONIFER FOREST ECOSYSTEM
A Progress Report
1976
Scientific Editor
Paul R. Miller
Technical Editor
Michael J. Elderman
Principal Authors:
Paul R. Miller, Ronald N. Kickert, 0. Clifton
Taylor, Rodney J. Arkley, Fields W. Cobb, Jr.,
Donald L. Dahlsten, Paul J. Gersper, Robert F.
Luck, Joe R. McBride, J. Richard Parmeter, Jr.,
John M. Wenz, Marshall White and W. Wayne Wilcox
University of California
Riverside, California 92521 and
Berkeley, California 94720
Contract No's. 68-03-0273 and 68-03-2442
Project Officer
R. G. Wilhour
Terrestrial Ecology Branch
Corvallis Environmental Research Laboratory
Corvallis, Oregon 97330
This study was conducted under the direction of
0. Clifton Taylor, Troject Principal Investigator and Associate Director
Statewide Air Pollution Research Center
University of California
Riverside, California 92521
CORVALLIS ENVIRONMENTAL RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
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 publi-
cation. Approval does not signify that the contents necessarily reflect
the views and policies of the U.S. Environmental Protection Agency, nor
does mention of trade names or commercial products constitute endorsement
or recommendation for use.
11
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FOREWORD
Air pollutionincluding ozone (Oo), nitrous oxides (NO, N02)» and
particularly peroxyacetyl nitrate (PAN)is placing more and more stress
on plant and animal life in southern California. One ecozone affected more
strenuously than others is the mixed conifer ecosystem of the San Bernar-
dino National Forest (SBNF), where losses of ponderosa and Jeffrey pines
have increased dramatically as pollutant levels in the area have risen.
Scientists at the University of California, Berkeley and Riverside, have
studied air pollutant effects on 18 plots in the SBNF where data was
collected to establish a group of linked models. These models are needed
to describe pollutant effects on various subsystems of the ecozone, but
also may be used to project conditions and responses in other similar
ecosystems, including the Sierra Nevada in northern California and the
Wasatch in Utah and the eastern slope of the Rocky Mountains in Colorado.
The future importance of the model's description of soils, climate, and
vegetation lies in three areas: (1) its predictive capacity; (2) its
expected reliability in defining conditions under which stress will be more
evident; and (3) its ability to provide researchers with the means to
counteract these stresses.
As it now stands, this project has yielded significant data which
will allow for further development and refinement of the model. Environ-
mental occurrences during the next two-year period of this grant should
help either corroborate or negate projections already generated by the
models or inferred by the participating scientists. By enabling scientists
to project such future environmental stresses and responses, the models
will ultimately enable resource management agencies to move towards con-
trolling those stresses, and to preserving the ecosystems now affected
by them.
iii
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ABSTRACT
Since 1972, twelve scientists representing several research disciplines
systems ecology, soils, plant nutrition, forest ecology, forest pathology,
wildlife ecology, air pollution technology, and meteorology have collabo-
rated in integrated studies to determine the chronic effects of photochem-
ical oxidant air pollutants on a western mixed conifer forest ecosystem. An
enormous amount of data has been collected, describing present and past
natural conditions of twelve subsystems comprising the conifer forest eco-
systems of the San Bernardino Mountains in southern California.
A computer data bank is being developed to allow efficient storage and
retrieval of these numerous data sets. The systems simulation modeling
process was begun early in 1975. Goals were redefined, a flow paradigm with
time-space resolution was developed, and existing simulation models for
separate subsystems were considered and adapted when applicable. The basic
unit for modeling purposes was defined as the forest stand, which may be
comprised of from 10 to 200 trees with equivalent land areas of from 100
to 25,000 m . Time resolution varies according to the subsystem in question
and may be hourly, daily, biweekly, monthly, seasonal, annual, or multi-
annual.
The subsystems receiving attention at the stand level are defined as:
tree population dynamics, oxidant flux canopy response, stand-tree growth,
stand moisture dynamics and microclimate, stand mortality responses related
to bark beetles and root disease, tree seedling establishment, cone and
seed production, litter production, litter decomposition, and small mammal
population dynamics. Both a flow diagram and a preliminary word model have
been prepared to describe the behavior of these linked subsystems.
The most important steps for the immediate future are to make the data
management system completely operational, and continue model development
and collection of essential data for each subsystem. As the work continues,
questions about reversibility or irreversibility of the effects of chronic
oxidant exposure and the utility of the output of this research for resource
management purposes will be evaluated constantly.
This report was submitted in partial fulfillment of contract numbers
68-03-0273 and 68-03-2442 by the University of California-Riverside under the
sponsorship of the U.S. Environmental Protection Agency. This report covers
project progress from July 1976 through June 1977. This is a continuing long
term study initiated in 1972 with an expected termination date of July 1980.
iv
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CONTENTS
Page
Disclaimer Notice ii
Foreword iii
Abstract iv
Contents v
Figures vii
Tables xii
Abbreviations and Symbols xvii
Acknowledgements xviii
1. Introduction 1
2. Conclusions 5
3. Recommendations 14
4. General Description of Ecosystem Properties
A. Soils 19
B. Vegetation 29
C. Climate 39
D. Temporal and Spatial Trends of Oxidant Air Pollutant
Concentrations 46
5. Definition of the Conifer Forest Ecosystem as a Group of
Coupled Ecological Models 71
6. Tree Population Dynamics Subsystem 106
7. Oxidant Flux-Canopy Response Subsystem 122
8. Stand-Tree Growth Subsystem 139
9. Stand Moisture Dynamics and Microclimate Subsystems 151
10. Western Pine Bark Beetle Population Dynamics - Stand Mortality
Response Subsystem 159
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Page
11. Root Pathogen Dynamics and Stand Mortality Subsystem 177
12. Tree Seedling Establishment Subsystem 186
13. Cone and Seed Production Subsystem 191
14. Litter Production Subsystem 204
15. Foliage Litter Decomposition Subsystem:
A. Microbial Activity and Nutrient Recycling 220
B. Microarthropod Activity 226
16. Woody Litter Decomposition Subsystem 233
17. Small Mammal Population Dynamics Subsystem 238
References 251
Appendices 264
Glossary 329
vi
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FIGURES
Number Page
1 Location of study plots in the San Bernardino National Forest . . 3
2 Three representative soil profiles of particle size
distribution 23
3 Average particle size distribution of soils of study plots ... 26
4 Representative soil bulk density profiles on study plots .... 27
5 Vegetation zones of the San Bernardino Mountains 30
6 Overstory vegetation type map of the San Bernardino Mountains . . 31
7 East-west distribution of vegetation types in the San Bernardino
Mountains 33
H
8 Tree species composition of five permanent plots 36
9 Long-term Weather Bureau records for monthly means of temperature
and precipitation at Lake Arrowhead and Big Bear Dam 40
10 Locations of San Bernardino County Flood Control District
precipitation stations in the San Bernardino Mountains in
relation to major vegetation study plots and air monitoring
stations 43
11 Sequences of five distinct meteorological patterns or day classes
in the San Bernardino Mountains, 1974-1975 51
12 Biweekly and seasonal cumulative ozone dose at Sky Forest,
1974-1975 54
13 The frequencies of occurrence of each meteorological pattern
on consecutive days, and the daily average ozone concentrations
on consecutive days of each pattern at Sky Forest, 1974-1975 57
14 Surface wind fields generated from a computer model for 1300 hr
PST, August 31, 1974, for a limited portion of the study area
(see caption in next figure) 60
vii
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Number Page
15 Wind direction and speed at selected surface stations at 1300
hr PST, August 31, 1974, compared with the concentration of
total oxidants at 1200, 1300, and 1400 hours PST 61
16 Topographic projection of the San Bernardino Mountains showing
monthly summation, June through October 1974, of total oxidant
dose at seven monitoring stations 63
17 Topographic projection of the San Bernardino Mountains with
a comparison of total daylight and night hours during August,
September, and October 1974, when total oxidant concentra-
tions were greater than, or equal to, 157 yg/m^ (0.08 ppm)
at seven air monitoring stations 65
18 Comparative daily maximum hourly averages for ozone, total
oxidant, PAN, and N0£ at Sky Forest, August 1974 66
19 Comparative hourly concentrations of total oxidant, PAN, and
N02 at Sky Forest, November 18, 19, 1973, and total oxidant
at Big Bear Ranger Station and Barton Flats 67
20 Number of hours of total oxidant, July through September,
greater than or equal to 392 Ug/m^ (0.20 ppm) at the down-
town San Bernardino County Air Pollution Control District
Station, 1963-1974, and Rim Forest/Sky Forest, 1968-1974 ... 69
21 Monthly summation, June through September, 1968-1976 of total
oxidant dose at Rim Forest/Sky Forest 70
22 Objectives for the study of effects of ambient oxidant pollu-
tants on mixed conifer forest ecosystems 72
23 The system simulation modeling process 80
24 Basic design philosophy of 'Master Control' 82
25 The San Bernardino Data Management System 83
26 Hierarchical structure of problem objectives for simulation
modeling. Black dot indicates problem is covered by a
subproject 86
27 Guide to subsystems 89
28 Coniferous forest stand ecosystem flow chart 90
29 Differences of 18 permanent vegetation plots when compared as
the percent species composition of oxidant air pollutant
sensitive tree species (ponderosa and Jeffrey pines and white
fir as a group) versus percent shrub cover 94
viii
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Number
30 Example of PUTCUR graphic display for exploratory data analysis ,
31 Example of PRTPLT graphic display for output of system model
behavior 101
32 The arthropod data capture system 103
33 Alternative field data entry system 105
34 Layout of sampling locations on a 30 m section of a permanent
plot and a plot used to study forest succession following
fire 108
35 Plot map of 0-30 m section of U.C. Conference ground plot .... 112
36 Stand age distribution curve for U.C. Conference ground plot . . 113
37 Stand age distribution curves for fire plot P-38 121
38 Chlorotic mottle, necrosis caused by an experimental ozone fumi-
gation, and superficial necrotic flecks not associated with
oxidant injury but rather winter weather 123
39 Development of oxidant injury symptoms on current, and current
plus one year old, needles of ponderosa pine saplings, in
relation to stage of current year needle growth and time
during the summer season and in relation to total dose of
oxidant 125
40 Relationship of oxidant doses at several monitoring stations
expressed as a ratio of that received at Sky Forest with the
average oxidant injury scores of ponderosa and Jeffrey pines
at the plots nearest each station 130
41 Topographic projection of the San Bernardino Mountains, showing
a comparison of oxidant injury to black oaks at major study
sites, August 31, 1974 with accumulated total oxidant dose,
June-August, measured at nearby monitoring stations 131
42 Topographic projection, San Bernardino Mountains, showing how
ponderosa and Jeffrey pines, in major study sites, are
distributed in six injury classes in relation to seasonal
dose of total oxidant 132
43 Injury score of current plus one-year needles, 1968-1973, from
ponderosa pine saplings maintained in filtered (FAH), or
unfiltered air greenhouse (AAH), and an outside ambient air
treatment (AAO) 141
44 Average dry weight of all needle fascicles per internode in
IX
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Number Page
filtered (FAR), or unfiltered air greenhouse (AAH), and an
outside ambient air treatment (AAO) 142
45 Annual growth of the terminal shoot and first order branches in
upper half of sapling from ponderosa pine maintained in
filtered (FAH), or unfiltered air greenhouse (AAH), and an
outside ambient air treatment (AAO) 144
46 Relationship of precipitation, oxidant dose and foliar injury to
radial and vertical growth of ponderosa pine saplings before
and after treatments in filtered (FAH), or unfiltered air
greenhouse (AAH), and an outside ambient air treatment (AAO) . 145
47 Calculated average cross-sections of two 30-year-old ponderosa
pines at breast height grown in polluted air and in non-
polluted air based on radial growth samples from 1941-1971
and 1910-1940 147
48 Calculated average growth of 30-year-old ponderosa pines in
polluted and non-polluted air based on radial growth samples
from 1941-1971 and 1910-1940 148
49 Soil moisture and temperature regime 1973-74 at Dogwood plot . . 153
50 Time intervals during which the soil at various depths contained
moisture available for plants during spring and summer 1974 . . 154
51 Ponderosa and Jeffrey pine predawn xylem water potential at three
plots in 1975 in relation to daily temperature maximums and
relative humidity minimums 157
52 Ponderosa and Jeffrey pine predawn xylem water potential at three
plots in 1976 in relation to daily temperature maximums and
relative humidity minimums 158
53 Graphic summary of the population sampling procedures used for
the western pine beetle, showing data sets and the type of in-
formation included for the San Bernardino study 176
54 Conceptual model of oxidant effects on the Fomes annosus root
disease 178
55 Conifer seed production subsystem ..... ..... 192
56 Examples of Keen's tree age and growth vigor classes for east
side Sierra Nevada and southern California ponderosa pine
(Keen, 1936) 193
57 Mass of ponderosa pine needle litter-fall compared to oxidant
injury score, 1974; for Camp Paivika plot to Camp Oongo plot . 208
x
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Number Page
58 Ponderosa and Jeffrey pine needle-fall compared to oxidant
injury score, September-December, 1973 and 1974 209
59 Crown drip cation concentration in relation to distance from
ponderosa pine tree trunk 212
60 Crown drip cation concentration in relation to oxidant injury
score of ponderosa pine 213
61 Precipitation and crown drip collected under 24 trees expressing
various degrees of air pollutant injury. (Low score = high
injury) 214
62 Cation content of crown drip water related to air pollutant
score. (Low score = high injury) 215
63 Relationshio of potassium (k) content of soils to the air
pollutant injury score on adjacent trees. (Low score =
high injury) 216
64 Relationship of calcium (Ca) content of soil to the air pollutant
injury score on adjacent trees (Low score = high injury) . . . 217
65 Relationship of magnesium (Mg) content of soil to the air
pollutant injury score on adjacent trees (Low score = high
injury) 218
66 Source and destination (tree tag-1976 oxidant score) of 960
decomposition study envelopes. Each arrow represents 30
envelopes and points from their source to their destination . . 222
67 Source and destination (tree tag-1976 oxidant score) of 160
decomposition study envelopes. Each arrow represents 5
envelopes and points from their source to their destination . . 223
68 Total microarthropods per sample (organic horizon) collected
under 6 trees from 1973 to 1975, San Bernardino National
Forest 231
69 Number of small mammals caught per year per plot 242
70 A comparison of the species composition of the small mammal
catch on the study plots with the catch in three other forests
in California 243
71 Comparison of cone utilization by gray squirrels in 1973 and
1974 by plot 248
72 Extremes of weekly cone utilization by gray squirrels in 1974 . . 250
xi
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TABLES
Number Page
1 Tree Layer Data from Plots Representative of Each Vegeta-
tion Type Dominated by Ponderosa or Jeffrey Pine in the
San Bernardino Mountains 34
2 Comparison of Measured and Projected Mean Annual Precipitation
from San Bernardino County Flood Control District Stations
Nearby the Permanent Vegetation Study Plots 42
3 Comparative Elevations of 18 Permanent Vegetation Plots with
Precipitation Collectors and San Bernardino County Flood
Control District Precipitation Stations 44
4 Winter Precipitation, 1973-1974, and 1974-1975 at Each Major
Vegetation Study Plot, Determined by Snow Storage Gauges,
September 15 to May 1 45
5 Descriptions of Meteorologic Patterns for Five Classes of
Spring an Summer Days in Southern California 47
6 The Most Frequent (Mode) Wind Direction (WD) and Associated
Average Wind Speeds (WS) at Selected Hours During Five
Meteorologic Patterns 52
7 Percent of Time During Five Classes of Meteorological Patterns
That Specified Ozone Concentrations were Equaled or Exceeded
at Three San Bernardino Mountain Monitoring Stations from
May Through October, 1975-1975 55
8 Frequency of the Most Common Transitional Combinations of Day
Classes or Meteorological Patterns and Resultant Ozone
Dose 56
9 Comparisons of Hourly Averages for Wind Direction (WD), Wind
Speed (WS) and Ozone (DASIBI) at a) Barton Flats, b) Camp
Paivika, and c) Sky Forest During May Through October, 1975 . . 58
10 Potential Couplings Between Stressed Ecosystem Responses and
Socio-Politico-Economic Systems Under Various Forest Land
Use Policies 79
xii
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Number
Page
11 Vegetation Data for the U.C. Conference Ground Plot Ill
12 Stand Age Distribution for the U.C. Conference Center Plot . . . 114
13 Percentage Species Composition on Plots Established to Study the
Relationship Between Topography and Tree Mortality in a Zone
of High Concentration of Oxidant Pollutants 115
14 Mean Numbers for Each Size Class in 22 Aspect Plots 117
15 Vegetation Data on Fire Plot P-38 120
16 Comparison of Oxidant Injury to Ponderosa and Jeffrey Pines and
Black Oak in 1974 and 1975 127
17 Regression of all Matching Hourly Average Oxidant Concentrations
at Paired Stations in 1975 Using Sky Forest as a Baseline for
Comparing Each of Ten Other Stations 128
18 Regression of all Matching Hourly Average Oxidant Concentrations
During 1974 and 1975 at Five Oxidant Stations Each Paired with
Sky Forest 128
19a Changes in Annual Injury Scores and Mortality Rates of Ponderosa
and Jeffrey Pines at Major Vegetation Plots, 1973-1975 .... 134
19b Changes in Annual Injury Scores and Mortality Rates of Ponderosa
and Jeffrey Pines at Major Vegetation Plots, 1973-1975 .... 135
19c Changes in Annual Injury Scores and Mortality Rates of Ponderosa
and Jeffrey Pines at Major Vegetation Plots, 1973-1975 .... 136
20 Oxidant Injury Scores of White Firs, Incense Cedars, and Sugar
Pines at 18 Major Study Plots, 1973-1974 137
21 Average Annual Radial Growth of 19 Ponderosa Pine Trees in Two
Levels of Oxidant Air Pollutants 146
22 Correlations Between Ponderosa Pine Radial Growth (Y) in
Centimeters and Oxidant Injury Score (X) . 149
23 Changes of Timber Volume and Percentage of Total Jeffrey Pines
in Four Bark Beetle Risk Classes at Two Control Plots Excluded
from Sanitation Salvage Logging Between 1952 and 1972 at
Barton Flats in the San Bernardino National Forest 150
24 Western Pine Beetle-Infested Ponderosa Pines Ranked by Oxidant
Damage Classes and Beetle Generations, 1973-1975 167
xlii
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Number Page
25 Western Pine Beetle Egg Dissection Data Grouped by Generation
and Oxidant Injury Class. EPA, San Bernardino Air Pollutant
Study, 1973-1974 168
26 Preliminary Analysis of Number of Attacks and Gallery Length
for the Mountain Pine Beetle from Varying Bark Sample Sizes
(Data Converted to 1000 cm.2 for Comparison). EPA, San Bernar-
dino Air Pollutant Study, 1974 169
27 Preliminary Analysis of Number of Attacks and Gallery Length
for the Jeffrey Pine Beetle from Varying Bark Sample Sizes
(Data Converted to 1000 cm2 for Comparison). EPA, San
Bernardino Air Pollutant Study, 1974 170
28 Total Arthropods Reared from Ponderosa Pine Bolts from Three
Heights Infested with Mountain Pine Beetle in 1974, San
Bernardino 171
29 Total Arthropods Reared from Jeffrey Pine Bolts from Three
Heights Infested with Jeffrey Pine Beetle in 1974, San Ber-
nardino 173
30 Preliminary Summary of Final Smog Damage Ratings for Pines
Killed by Insects on Established Vegetation Plots, 1973-1975 . 175
31 Infection and Colonization by Fomes annosus of Oxidant Injured
Jeffrey and Ponderosa Pine Trees in Natural Stands 181
32 Infection of Ozone Fumigated and Unfumigated Jeffrey and
Ponderosa Pine Seedlings by Fomes annosus 182
33 Relationship of Chronic Ozone Injury of Ponderosa and Jeffrey
Pine Seedlings to Colonization of Root Crown Tissue by
Fomes annosus 183
34 Stump Inoculation Results 185
35 Number of Seeds With and Without the Natural Organic Layers
(400 Seeds Planted in Each Treatment) 189
36 Seed Status 30 Days After Planting 190
37 Description of Crown Class Characteristics 195
38a Influence of Crown Class on the Number of Trees Which Produced
Cones and the Number of Cones Produced by Ponderosa Pine
in 1973 and 1974 in 18 Plots 196
38b Influence of Crown Class on the Number of Trees Which Produced
Cones and the Number Cones Produced by Ponderosa Pine
xiv
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Number Page
in 1975 and 1976 in 18 Plots 197
39a Influence of Crown Class on the Number of Trees Which Produced
Cones and the Number Cones Produced by Jeffrey Pine in 1973
and 1974 in 18 Plots 198
39b Influence of Crown Class on the Number of Trees Which Produced
Cones and the Number Cones Produced by Jeffrey Pine in 1975
and 1976 in 18 Plots 199
40 Estimates of the Number of Expanded Seeds Per Cone and Total
Seed Crop Per Plot For the 1975 Cone Crop 201
41 Identified Insect Species Reared From Jeffrey and Ponderosa
Pine Cones 202
42 Mass and Thickness of the Forest Floor on Major Study Plots . . . 207
43 Content of Nutrient Elements in Needle Fall Collected in
Autumn, 1973 210
44 Nutrient Content and Loss in Nutrient Due to Leaching of Needle-
Fall From Pine Trees 210
45 Sample Dates for Soil Microarthropods Beneath Trees on
Established Vegetation Plots. San Bernardino National
Forest, 1973-1975 229
46 Mean Microarthropods per Decimeter of Soil Core for All Layers
on Four Plots for Two Sample Dates, Fall, 1974, San Bernardino
National Forest 232
47 Results of Soil-Block Test on Wood Grown Under Various Oxidant
Exposures 236
48 Description of Sample Trees 237
49 Composition of the Total Small Mammal Catch on the Study Plots,
1972-1974 240
50 Comparison of Percent Trapping Success of Small Mammals in
1972, 1973, 1974 244
51 Comparison of Percent Trapping Success of Small Mammals on
Four Forests in California 245
52 Comparisons of Species Diversity of Small Mammals Trapped on
Plots with Four Levels of Vegetation Injury from Air
Pollution 245
xv
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Number Page
53 Preliminary Sex and Age Ratios of the Total Small Mammal Catch
on the Study Plots, 1972-1974 247
xvi
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LIST OF ABBREVIATIONS AND SYMBOLS
ABBREVIATIONS
SCAB
SBNF
CP
BP
TUN 2
DWA
DWB
SF
UCC
COO
GVC
NEGV
SV
BL
SC
HV
CA
SCR
BF
CAO
HB
STANDCMP
TREEGROW
SEED
ROOTS
BEETLE
CANOPY
WATER
MICROCLI
SEEDLING
LITTER
LITDECAY
WOODECAY
RODENT
PP
JP
dbh
ppra
South Coast Air Basin
San Bernardino National Forest
Camp Paivika vegetation plot
Breezy Point vegetation plot
Tunnel 2 vegetation plot
Dogwood A vegetation plot
Dogwood B vegetation plot
Sky Forest vegetation plot
University Conference Center vegetation plot
Camp 0-Ongo vegetation plot
Green Valley Creek vegetation plot
Northeast Green Valley vegetation plot
Snow Valley vegetation plot
Bluff Lake vegetation plot
Sand Canyon vegetation plot
Holcomb Valley vegetation plot
Camp Angeles vegetation plot
Schneider Creek vegetation plot
Barton Flats vegetation plot
Camp Osceola vegetation plot
Heart Bar vegetation plot
Tree Population Dynamics Computer Routine
Tree Growth Computer Routine
Cone and Seed Production Computer Routine
Root Pathogen Dynamics Computer Routine
Pine Bark Beetle Population Dynamis Computer Routine
Oxidant Air Pollutant Flux-Canopy Response Computer Routine
Stand Moisture Dynamics Computer Routine
Microclimate Computer Routine
Seedling Establishment Computer Routine
Litter Production Computer Routine
Fine Litter Decay Computer Routine
Woody Litter Decay Computer Routine
Small Mammal Population Dynamics Computer Routine
ponderosa pine
Jeffrey pine
diameter at breast height
parts per million
SYMBOLS
microgram
03
ozone
xvii
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ACKNOWLEDGEMENTS
Administrative services for the Project are coordinated by 0. Clifton
Taylor, Associate Director, Statewide Air Pollution Research Center,
University of California, Riverside, CA
Portions of this report were contributed by the following authors:
Pages Author Section
iii Michael J. Elderman Foreword
Editor, College of Natural
and Agricultural Sciences
University of California
Riverside, CA
iv Paul R. Miller Abstract
Plant Pathologist,
U.S.D.A., Forest Service
Pacific Southwest
Forest and Range
Experiment Station (PSW)
Fire Laboratory,
Riverside and
Research Associate
Statewide Air Pollution
Research Center
University of California
Riverside, CA
1 0. Clifton Taylor Introduction
Professor of Plant
Sciences, Horticulturist
Department of Plant Sciences
University of California
Riverside, CA
19 Rodney J. Arkeley General Descrip-
Lecturer in Soils tion of Ecosystem
and Plant Nutrition Properties: Soils
and Soil Morphologist
Agricultural Experiment
Station
xviii
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Pages Author Section
Paul J. Gersper
Associate Professor
of Pedology
and
Rudolph Glauser
Staff Research Associate
Department of Soils
and Plant Nutrition
University of California
Berkeley, CA
29 Joe R. McBride General Description
Associate Professor of Ecosystem Proper-
ties; Vegetation
Assisted by
Diana Jacobs
Richard Laven
Vaivia Semion
Department of Forestry
and Conservation
University of California
Berkeley, CA
39 Rodney J. Arkeley General Description
of Ecosystem Proper-
Assisted by ties; Climate
John N. Zorich
Statewide Air Pollution
Research Center
University of California
Riverside, CA
and
Robert E. Thomson
Department of Forestry
and Conservation
University of California
Berkeley, CA
46 Paul R. Miller and General Description
Bill C. Ryan of Ecosystem Proper-
ties: Temporal and
Assisted by Spatial Trends of
H. P. Milligan (deceased) Oxidant Air Pollutant
and Concentrations
Robert E. Van Doren
U.S. Forest Service, PSW
and Maureen A. Thomas
xix
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Pages Author Section
John N. Zorich
James O'Connor
Statewide Air Pollution
Research Center
University of California
Riverside, CA
71 Ronald N. Kickert Definition of the
ADP, Senior Systems Conifer Forest Eco-
Analyst system as a Group
Department of Forestry of Coupled Ecological
and Conservation Models
University of California
Berkeley, CA
Assisted by
James Barbieri, formerly
"G"-Division
Lawrence Livermore Laboratory
Livermore, CA
106 Joe R. McBride Tree Population
and Dynamics Subsystem
Paul R. Miller
Assisted by
Diana Jacobs
Rick Laven
122 Paul R. Miller Oxidant Flux
Canopy Response
Assisted by Subsystem
Maureen A. Thomas
John N. Zorich
Joanne Leung
139 Joe R. McBride Stand-Tree Growth
Vaivia Semion Subsystem
and
Paul R. Miller
Assisted by
John N. Zorich
Joanne Leung
Diana Jacobs
Richard Laven
151 Rodney J. Arkeley Stand Moisture
and Dynamics and Micro-
xx
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Pages Author Section
Paul R. Miller climate Subsystem
Assisted by
John N. Zorich and
Peter G. Rowlands
Statewide Air Pollution
Research Center
University of California
Riverside, CA
159 D. L. Dahlsten Western Pine Bark
Professor of Entomology Beetle Population
Dynamics-Stand
R. J. Swift Mortality Response
Staff Research Assistant Subsystem
W. A. Copper
Staff Research Associate
and
James Barbieri
Assisted by
Katherine A. Sheehan
Patricia A. Felch
Edith Reisner
Nancy X. Norick
Division of Biological Control
University of California
Berkeley, CA
177 Robert L. James Root Pathogen
Research Assistant Dynamics and Stand
Mortality Subsystem
Fields W. Cobb, Jr.
Associate Professor of
Plant Pathology
J. Richard Parmeter, Jr.
Professor of Plant Pathology
and
Paul R. Miller
Assisted by
G. Nick McKibben
Department of Plant
Pathology
University of California
Berkeley, CA
xxi
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Pages Author Section
186 Fields W. Cobb, Jr. Seedling Establish-
ment Subsystem
Nancy L. Bruhn
Staff Research Associate
David L. Rowney
and
J. Richard Parmeter, Jr.
Assisted by
G. Nick McKibbin
Isabel Alvarez
A. R. Weinhold
Department of Plant
Pathology
University of California
Berkeley, CA
and
S. K. Sweetwood
and Joe R. McBride
191 R. F. Luck Cone and Seed Pro-
Assistant Professor of duction Subsystem
Entomology
and Assistant Entomologist
Assisted by
John Harper
Glenn Scriven
Marcella Waggoner
Division of Biological
Control
University of California
Riverside, CA
204 Rodney J. Arkley Litter Production
Paul J. Gersper Subsystem
and
Rudolph Glauser
Assisted by
John N. Zorich
220 J. N. Bruhn Foliage Litter
Research Assistant Decomposition
and Subsystem: Microbial
J. Richard Parmeter, Jr. Activity and Nutrient
Recycling
xxii
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Pages Author Section
Department of Plant
Pathology
University of California
Berkeley, CA
226 John M. Wenz Foliage Litter
Forest Entomologist Decomposition
U.S.D.A., Forest Service Subsystem: Micro
State and Private Forestry arthropod Activity
Forest Insect and Disease
Management
630 Sansome St.
San Francisco, CA 94111
Donald L. Dahlsten
and
D. L. Rowney
Staf Research Assistant
Division of Biological
Control
University of California
Berkeley, CA
Assisted by
James Barbieri
233 W. Wayne Wilcox Woody Litter
Associate Forest Decomposition
Products Pathologist Subsystem
Associate Professor
of Forestry
and
Nancy D. Oldham
Staff Research Associate
Forest Products Laboratory
University of California
Richmond, CA
238 Marshall White Small Mammal
Associate Research Biologist Population Dynamics
and Subsystem
Steven K. Sweetwood
Bibliographer
Department of Forestry
and Conservation
University of California
Berkeley, CA
xxiii
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Particular thanks is extended to the District Rangers and staffs
of the Arrowhead, Big Bear, and San Gorgonio Districts of the San Bernardino
National Forest for their interest and cooperation in regard to field
study activities. Appreciation is expressed to Dave Nichols, Geography
Department, UC Riverside for use of the figure described as a topographic
projection of the San Bernardino Mountains and to the former San Bernardino
County Air Pollution Control District for oxidant concentration data at
Lake Gregory and Big Bear Lake.
The location of bark beetle infested trees was helped by the constant
surveillance of both State Department of Forestry and U.S. Forest Service
crews.
A special expression of gratitude is extended to Donna M. Shaw for
typing the manuscript and to Maureen A. Thomas for drafting and proofing.
xxiv
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INTRODUCTION
This final report is submitted to the Corvallis Environmental Research
Laboratory of the United States Environmental Protection Agency in partial
fulfillment of the requirements of EPA Contract number 68-03-0273. The
purpose of this report is to describe the forest ecosystem and air pollutant
conditions under study and to present research results where they are avail-
able. The contract was renewed for each of three successive years from
June 15, 1973 through June 15, 1976.
This is a continuing-long term study initiated in 1972 with an expected
termination date of July, 1980. The disciplines selected for the investi-
gation were those judged to be the ecosystem components most likely to
respond directly to successive pollutant exposures or show secondary
response in the complex interacting system. A modeling section was included
in the study for the purpose of adapting existing models to the study of
pollutant impact on a forest ecosystem and possibly to add a predictive
capability to the research.
The San Bernardino National Forest (SBNF) is located at the east end of
the 80-mile-long South Coast Air Basin where the last four decades of
extensive urban and industrial development have created a severe air pollu-
tion problem. Hydrocarbons and oxides of nitrogen generated during
combustion of petroleum fuels provided the precursors for ozone and other
oxidants. These oxidants, carried by the marine air flow, undoubtedly
invaded the forest either when vegetation injury was first recognized in
the early 1940's near the coast, or shortly after. Intensity of the
pollutant problem and expansion of the affected area has increased markedly
as population growth has continued in the basin. Sensitive species in the
local National Forest such as ponderosa pine began showing unmistakable
injury in the early 1950's.
Green vegetation, including the dominant tree species such as ponderosa
pine, are essential elements in the biological community because they are
the sole converters of solar energy for use by herbivores, decomposers,
and carnivores. Any significant change in the "producer" segment of the
ecosystem should be reflected by changes in one or more of the dependent
components of that system. An understanding of changes in plant communities
suffering from acute, chronic, or insidious air pollutant injury is
critical if one is to predict the fate of the ecosystem.
Vegetation in the San Bernardino Mountains is composed about equally
of chaparral and forest types. This study has focused on ecosystems in
the coniferous forest zones which range from 1200 to 1981 meters on
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north-facing slopes and from 1524 to 2286 meters on south-facing slopes.
Dominant tree species in these areas include ponderosa and Jeffrey pine and
white fir. At lower elevations, and particularly on the south slope of the
San Bernardino Mountains, the vegetation is largely chaparral. This area
is exposed directly to oxidant air pollutants but was excluded from the
study not only because its physical and vegetation characteristics were so
different from those of the coniferous forest, but also because it is less
important for human use.
Eighteen major study plots were selected along an east-to-west gradient
of air pollutants (Fig. 1). The highest dosage of air pollutants occurs
at the west end near the Cajon pass; the smallest dosage occurs near the
eastern border of the National Forest. Smaller plots for specific types of
studies were established throughout this area. Uniformity of tree species,
soil characteristics, and other physical conditions were important factors
considered in locating the major plots.
Soils in the SBNF were generally derived from decomposed granite but
texture and depth varied considerably, largely due to the very uneven
terrain. Shallow, coarse-textured soils were usually found on the steeper
slopes while finer sediments collected in the valleys. Water-holding
capacity was generally high and nutrient levels appeared to be adequate for
good tree growth. This might be expected since an important criterion for
site selection was the presence of a dominant population of ponderosa or
Jeffrey pine in areas where ponderosa was not the dominant species.
Forest stand age, structure, and species composition in such a eco-
system are constantly changing and many environmental factors can be
expected to accelerate the rate of such change. Since many forest species
are susceptible to ozone injury, it is inevitable that heavy dosages of
oxidant air pollutants will affect both the rate and direction of plant
succession. By developing conceptual models of plant succession and
measuring selected vegetation parameters, it may be possible to predict
successional patterns when certain environmental variables are known and
pollutant conditions have been described. Historical information on
vegetation succession following major fires in the past will provide
valuable information for such models. Such studies identify variables
which influenced the rate and direction of plant succession prior to
serious air pollutant conditions and during the decades when oxidant
pollutants were increasing rapidly.
Climate is one of the most important factors influencing an eco-
system's essential processes. Climate in the San Bernardino Mountains is
distinquished by its Mediterranean character: maximum precipitation
(primarily snow) occurs during the cold months, and the summers are warm
and dry. Long term weather records available for several sites in the
mountains provide valuable data for observing ecological changes induced
by periods of unusual weather conditions. Records from each of the
major study plots can be compared with historical data from the same
general region to assist interpretations of possible pollutant impact.
Since the pollutant problem was identified in the early 1940's,
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penetration of oxidants eastward through the South Coast Air Basin has been
documented by numerous reports of air movement, vegetation injury, and two
to three decades of pollutant monitoring by established stations. Intensive
studies with airborne instrumentation have verified the penetration of
heavily polluted air into this forest. Monitoring stations have been
established at selected sites along the pollutant concentration transect
to provide accurate information of pollutant exposure for the major study
plots.
Oxidant pollutant stress, whether direct or indirect, is expected to
have different degrees of effect on the linked subsystems or units com-
prising the coniferous forest ecosystem. Several investigators selected
units of this ecosystem to study a process which may be affected either
by the introduction of air pollutants or by significant changes in pollu-
tant dosage. The objective of these various studies focused on ways of
applying systems analysis and computer modeling in order to (1) forecast
ecological effects of photochemical oxidants in the southern California
coniferous forest ecosystem; (2) evaluate the consequences of oxidant
pollutants in forest ecosystems on human welfare; and (3) evaluate the adapt-
ability of systems models to other pollutants and other forest types.
Process studies of the various ecosystem units are essential to identify
and quantify direct oxidant effect and to differentiate between these and
biological responses induced by disease, insects, and climate.
A native forest ecosystem is a very complex unit comprised of many
interdependent components. Time and funds were not available to study
the system in its totality; therefore, various subsystems were selected
for study by forest scientists to represent those areas where, in their
best judgment, any effect of long-term oxidant air pollutant exposure might
be detected and measured. These subsystems included: tree population
dynamics, oxidant flux canopy response, stand-tree growth, stand moisture
dynamics and microclimate, stand mortality responses related to bark
beetles and root disease, tree seedling establishment, cone and seed pro-
duction, litter production, litter decomposition, and small mammal popula-
tion dynamics. These have been investigated in relation to such factors
as climate (temperature and precipitation), natural topography, and soil
types and characteristics. The investigations have led to the collection
and storage of a significant amount of data during the four-year period
of this EPA grant.
One could hypothesize that an air pollutant's effect on one segment
of an ecosystem may be transferred to one or more of the other associated
subsystems; in addition, compensatory adjustments may be made within an
ecosystem to protect against changes too rapid for the system to handle.
With the exception of measurable injury to certain tree and shrub species,
the effects of oxidant air pollutants are not obvious, and the subtle
effects which could result in major ecological changes over time may
ultimately be difficult or impossible to measure completely.
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CONCLUSIONS
GENERAL ECOSYSTEM PROPERTIES
Soils
The soil classification is adequate for comparisons of the impact
of a range of oxidant air pollutants on vegetation growing on essentially
similar sets of soils.
Physical analyses of the soil show that most soils are relatively uni-
form and low in clay content above the level of contact with decomposed
granite substrata. This simplifies the possible comparison of the effect
of soils on the relative air pollutant injury to the vegetation. Two
soil areas which have more clay in the subsoil have similar soil tempera-
tures but widely differing intensity of air pollutants, so these two
are suitable for comparison.
Chemical analyses have shown that the soils over the study area gener-
ally contain adequate mineral soil nutrients for plant growth, especially
calcium (which is often very low in more humid forested soils). Also,
the soils generally contain reasonably high amounts of organic matter and,
with few exceptions, contain adequate nitrogen for forest growth. However,
only preliminary conclusions can be made about the general relationships
between soil nutrient content and oxidant injury to pines.
Vegetation
More variation in forest composition exists than was recognized when
the study was initiated. As a result of this variation, comparisons of
the impact of oxidant pollutants on forest stands of dissimilar composition
may limit the predictive capability of a simple stand succession model.
Climate
An examination of the historical records for precipitation for 24
mountain locations shows large year to year variation and also suggests
the strong influence of topography in controlling precipitation. The
comparison of the long term precipitation record, now available on computer,
with the precipitation record at permanent vegetation plots will be
necessary to help separate the effects of moisture and oxidant stresses
on stand succession.
Oxidant Air Pollutant Trends
Two of the five meteorological classes describing summer days in the
San Bernardino Mountains are most responsible for the highest daily doses
of oxidant. These classes include warm-moist and hot-moist days, respec-
tively, and occur more frequently than the remaining classes which include
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hot-dry, very hot-dry and cool-moist days.
The geometric means for classes 1-5 were 0.03, 0.09, 0.10, 0.09 and
0.06 ppm ozone, respectively for 361 days sampled at Sky Forest in 1974 and
1975.
The wind direction and speed during the hot, dry (Santa Ana wind) day
class is the only distinct pattern because winds are from the north and
blow toward the source of pollutants. The remaining four day classes are
all characterized by winds with a westerly to southerly source, namely,
from the origin of photochemical pollutants.
Both large (canyons) and small (hillslope configuration) terrain
features influence surface flow patterns and hence the penetration and
duration of injurious oxidant doses.
Both increasing elevation of the terrain and dilution during trans-
port were associated with a 68% decrease in the total oxidant dose for June
through October between extreme ends of a 37 km, west to east transect
in the San Bernardino Mountains in 1974.
Comparison of the hourly and daily average concentrations of ozone,
nitrogen dioxide and peroxyacetyl nitrate (PAN) at Sky Forest showed that
PAN was frequently present at concentrations injurious to herbaceous plants
but nitrogen dioxide was present at concentrations too low to be injurious
to plants.
The June through September seasonal oxidant doses from 1968 to 1975
at Rim Forest/Sky Forest have shown large year to year fluctuations caused
mainly by the weather of each season. However, the three year moving
average has become gradually larger each year since 1972.
SUBSYSTEMS
Definition of the Conifer Forest Ecosystem as a Group of Coupled Ecological
Models
Model Development
Construction of a single flow diagram, incorporating the conceptual
models for the various subsystems being investigated, has been a useful
step in planning the structure and logic of the computer programs represent-
ing each of the subsystems.
With minor changes, it appears very feasible to adapt three simulation
models developed in the International Biological Program, Coniferous Forest
Biome, to our entire set of models being developed for the study of air
pollution effects in the SBNF. Those that we have concluded are readily
adaptable include a transpiration simulator, a stand tree growth simulator,
and a stand-level hydrology simulator.
Data analysis
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There is an urgent need to implement an easily accessible computer
system to store and analyze the various data being acquired within the
total research program.
A reliable, computer-based, forecasting procedure for identifying
future ecological effects of air pollutants is more likely to be obtained
from an explanatory analysis of data on dynamic ecological processes,
rather than from data of a descriptive, index-monitoring nature. Therefore,
analysis of effects due to oxidant-induced tree crown degradation should
reference actual tree crown and foliage properties, rather than a single
aggregated smog-injury index.
Model design activity has identified that data needed to be col-
lected on tree growth properties and death rates and their causes, for
mature tree communities, tree seedlings, and seeds, so that quantitative
relations can be established for computer models.
In order to choose natural aggregations of vegetation plot data for
analysis, data need to be obtained on the spatial variation of soil types
and hillslope characteristics.
For comparing computer model behavior to the real forests, there is
a critical need to evaluate the existence of useable long-term historical
data which might already exist in government agency files for the SBNF.
Model Applications and Scope
With regard to future applications and limits of the simulation models
being developed, based on the kinds of data which have already been collected,
the models are intended primarily for exploring possible consequences of
alternative future air quality levels. This idea is aimed at discovering
the effects of controlling an input to the forest ecosystem.
For ecosystem response categories in forest resource-potentials
management and hazards management, which are of major concern to the
production-oriented land and wildlife management agencies, the basic
structure of this set of models is suited for application in recreation
management and timber management under various air pollution conditions.
Resource potentials which are not expected to be very directly
addressable by these models involve watershed management, forage-livestock
management, and wildlife management questions.
In terms of hazards management, the set of models will be address-
able to fire, insect pest, and forest disease management questions on a
limited scale under air pollution conditions.
Tree Population Dynamics
Fire frequency has been significantly reduced since 1905 in the San
Bernardino Mountains. Much of the forest age structure reflects a fire
frequency which will no longer influence stand development. Development
of the succession model must recognize this change in fire frequency.
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The distribution of diameter classes on the permanent plots is
skewed toward larger diameter trees. An inadequate number of trees in the
10 to 30 cm DBH size range are available for observation of air pollution
in j ury.
Oxidant Flux - Canopy Response
Conifer Injury/Dose Relationship
A preliminary oxidant dose - visible needle injury relationship was
obtained for current year and one-year old needles of ponderosa pine sap-
lings. Chlorotic mottle symptoms appeared on current needles before they
were fully grown and following an accumulated dose ranging between 1.0
and 2.0 x 10^ Ug/m^ hrs ozone (excluding background). A more quantitative
measure of needle injury effect of different dose sequences and associ-
ated weather conditions needs to be incorporated.
The west to east gradient of decreasing chronic injury to ponderosa
and Jeffrey pines at 18 vegetation plots corresponds closely with the
decreasing oxidant doses measured at 10 air monitoring stations located as
close as possible to these plots. The mathematical heterogeneity of the
present oxidant injury score system makes it impossible to formulate a
valid dose-injury equation.
The oxidant injury score system for ponderosa and Jeffrey pines has
provided a useful means for comparing each tree with its former condition
at the end of the previous growing season. Among the 18 permanent plots,
along the gradient of decreasing oxidant dose the results for 1973 to 1975
indicate that 7 pine populations declined in score (5 significant at p =
.05, 2 not significant), 5 remained about the same, and 6 increased in
score (3 significant at p = .05 and 3 not significant). The declining,
lower scores (greater injury) were at plot locations receiving the largest
seasonal oxidant doses.
Accumulated ponderosa and Jeffrey pine mortality at the 18 plots
ranged from 0 to 8.9% between 1973 and 1975. In our score system, where
1 to 36 describes injury ranging from very severe to no visible injury,
the mortality greater than 1% occurred in the 12 to 25 segment (severe
to slight injury) and involved mainly ponderosa pine.
Mortality that can be related to chronic oxidant injury was not
observed among white fir, incense cedar and sugar pine at the 18 plots.
White fir was present at 14 of the 18 plots and its scores reflected a
gradient of chronic oxidant injury. Incense cedar and sugar pine did not
offer a sufficient number of observation locations since they were present
at only 5 and 6 plots respectively.
Deciduous Trees
Black oak was a very useful indicator of the rate of injury develop-
ment during the season. Because it is present in 13 of the 18 plots,
it has helped to characterize the oxidant dose gradient.
Shrubs and Herbs
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Oxidant injury symptoms have been observed on one shrub species and
11 herbaceous species. Injury to herbs may be less severe for those which
complete their vegetative and reproductive growth in spring and early
summer before the most severe episodes of oxidant pollutants occur.
Stand Tree Growth
Ponderosa Pine Saplings
The needle, shoot and main stem growth of ponderosa pine saplings
maintained in a carbon-filtered air greenhouse compared to an unfiltered
greenhouse and ambient outside treatments was dramatically greater follow-
ing an exposure period lasting from 1968 to 1973. Removal of oxidant
stress will allow rapid recovery of ponderosa pine.
Pole-Size Ponderosa Pine
Oxidant air pollution in the forests of the San Bernardino Mountains
reduces the average annual diameter growth of ponderosa pine by approxi-
mately 40% in trees under 30 years of age. Merchantable volume growth
of trees 30 years of age is reduced by 83% in the zones of highest ozone
dose. This reduction in growth, along with air pollutant caused tree
mortality, combine to limit production of timber in the San Bernardino
Mountains.
Saw Timber-Size Ponderosa Pines
Annual ring widths of increment cores taken from 160 ponderosa pines,
each 30 cm or larger dbh, correlated weakly (r = 0.51) with the oxidant
injury score of each tree. Other crown characters, e.g. some estimate of
foliage surface area, may be a more desirable measure of injury.
The increase of timber volume from low to high risk categories was
very large at two Forest Service plots between 1952 and 1972. This is an
indirect measure of the consequences of chronic oxidant injury. High
risk trees are removed and this procedure may be considered an oxidant-
related mortality factor.
Stand Mositure Dynamics and Microclimate
Soil Moisture and Soil Temperature
The soil moisture regime has been documented for 23 sites beginning
in the summer of 1973 to the present and measurements are continuing. Soil
moisture depletion is most rapid during June, and the upper 1.5 m of soil
is depleted of soil moisture available for plants by about mid-July.
However, some moisture at depths up to 2.7 m (9 ft) is used by plants into
August. The period of dynamic growth appears to be form May to August, and
it appears that air pollutant injury to plants coincides with this period.
The total storage capacity of soil moisture available to pine trees in
this system is generally considerably higher than the 15 cm often assumed
in water balance studies.
Soil temperature regimes at 23 sites have been recorded since mid-
summer, 1973. Preliminary analysis of the data suggest that mean annual
soil temperatures range from about 4.5 C to 11.5 C in the general study
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area, with even higher soil temperatures on south facing aspects. Warm
and cold sites, dependent upon aspect and slope, can be found throughout
the range of air pollutant concentration.
Predawn Xylem Water Potentials
The seasonal trend in predawn xylem water potential of ponderosa
and Jeffrey pines was measured at biweekly intervals at six representative
plots. The decrease in water potential (-Bars) varied from plot to plot
but generally paralled the soil moisture depletion curves. Some of the
shorter interval variation appears to be related to the daily temperature
maximum. These data will be used for an existing transpiration model.
Western Pine Beetle Population Dynamics and Stand Mortality Response
Tree killing beetles pay an important role in the dynamics of a
forest community affected by photochemical oxidants. The hastening of
tree mortality changes the successional sequences in a plant community and
this, in turn, affects many other organisms, some of which have been con-
sidered by other investigators in this research program.
Trees in various states of decline due to photochemical oxidants
affect various biological attributes of the bark beetle populations.
Attack rates and eggs per centimeter of gallery length are reduced by
survivorship is greater in diseased trees.
Since there is some evidence that diseased trees have an influence
on the dynamics of bark beetle populations, it follows that the rate of
tree mortality can be affected and therefore the dynamics of the forest
community will be influenced. This is a critical relationship and must
be taken into consideration in the development of models of forest
communities stressed by photochemical oxidants.
Root Pathogen Infection and Spread-Stand Mortality Response
Observations show that oxidant air pollutants reduce resistance of
stumps and tree roots to infection and colonization by the fungus Fomes
annosus. Therefore, increased destruction by _F. annosus in the San
Bernardino Mountains is quite possible, and additional consideration
of control measures is recommended.
Tree Seedling Establishment
Influence of Fungi
Overall populations of soil fungi vary substantially among plots, but
differences do not appear to be related to levels of photochemical air
pollution.
The traditional damping-off fungi, Rhizoctonia and Pythuim spp,
were absent or very rare in the forest soils of the San Bernardino Moun-
tains, but the seeding studies showed that damping-off of seedlings
especially in the presence of litter was very common.
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Influence of Vertebrates
Predation by vertebrates appears to account for the greatest loss of
seeds, but fungi are responsible for most of the mortality in surviving
seeds.
Cone and Seed Production
A greater percentage of ponderosa and Jeffrey pine in the dominant
crown class produce cones; codominant ones are the next most frequent
bearers. Dominant ponderosa pines represent 33% of the individuals of
this species present on the plots, but they account for 63% of the cone-
bearing individuals and produce 68% of the cones born by this specie.
Similarly, dominant Jeffrey pines comprise only 28% of the individuals of
this specie on the plots but account for 58% of the cone bearing indivi-
duals and produce 85% of the cones born by this specie.
Litter Production
Variability at Different Study Sites
The thickness and mass of the forest floor (mainly pine needle litter)
was shown to be greater at lower elevations, i.e., the Lake Arrowhead
vicinity and at Camp Angelus in the lower Santa Ana Canyon, than at higher
elevations. However, forest floor thickness and mass varied even greater
between disturbed and undisturbed locations. It was found that thickness
of the litter layer was generally markedly reduced where there had been
activity such as recreation or logging.
After selective felling of beetle-infested trees of repeated sanita-
tion salvage logging, particularly in the ponderosa pine and ponderosa pine-
white fir forest types, the accumulation of heavy fuels from the slash
represents a serious wildfire risk which would result in hotter than
normal fires.
Pine needles fall, collected on screens under trees during the Fall of
1974, especially in the vicinity of Lake Arrowhead, resulted in compara-
tively small accumulations under trees that were healthy or only slightly
injured by oxidant air pollutants, markedly greater amounts under trees
of moderate injury, and levels similar to those of healthy trees under those
of severe injury. The latter case reflects the scarcity and small size of
needles which remain on the severely injured trees.
The mass and length of individual needle fascicles in litter fall
decreases linearly with increasing air pollutant injury to the tree.
Nutrient Input to the Litter in Crown Drip
The relationship between chemical composition of crown-drip and air
pollutant impact on the trees is obscured by variability of crown (foliar)
density over the range of impact damage and by variability due to differences
in path of intercepted water moving from needles to twigs to large limbs
before falling to the ground surface.
The concentration of cations in crown-drip near the trunk of trees
11
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averages about 5 times higher than concentrations in precipitation. How-
ever, no clear differences in crown-drip concentration obtained between
trees varying in air pollutant damage.
Soil Surface Nutrients Under Pines With a Range of Oxidant Injury
In surface soils with moderate to low organic carbon content there was
a trend toward increasing levels of exchangeable calcium, potassium and
magnesium under trees as the amount of chronic oxidant injury to pines
increased. Further analysis is required to determine the actual correla-
tions of Ca, K, and Mg with organic carbon and nitrogen in surface soils.
Foliage Litter Decomposition-Microbial
Ponderosa pine litter decomposed significantly (a = .001) faster
than did Jeffrey pine litter. Within each species, decomposition was
faster on the site receiving the greatest oxidant air pollution dosage.
Available data suggest that air pollution increased the rate of
litter decomposition, but other side influences have not yet been eliminated.
Foliage Litter Decomposition-Microarthropods
Our data gives evidence, although not statistically conclusive, that
microarthropod populations decrease under the direct or indirect influence
of oxidant air pollution.
Between-plot variations in microarthropod populations tend to be more
significant than between tree variations within plots.
Highs of microarthropod density tend to occur in November, coinciding
with cooler temperatures and higher moisture.
Species composition appears to be similar to that found in other
California forests that have been sampled.
Woody Litter Decomposition
It is probable that wood formed by ponderosa and Jeffrey pines during
chronic oxidant exposure does not differ in decay susceptibility since no
meaningful differences from wood formed in the absence of pollutants was
found in laboratory decay tests.
Small Mammal Population Dynamics
The mixed conifer forest of the San Bernardino Mountains have a well
developed fauna of small mammals. This fauna may exert a measurable effect
upon the succession of the forests through its collective feeding on seeds
and fruits. This effect may be increased indirectly by photochemical air
pollution.
Population densities of small mammals appear to be lower on these
study sites, particularly on the plots with higher air pollution, than on
12
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similar areas in northern California.
Deer mice represent a larger component of the small mammal fauna, and
chipmunks and golden-mantled ground squirrels make up a smaller proportion,
than is found on similar areas in northern California. The dominance of
deer mice results in dramatic fluctuations in the total numbers of small
mammals from year to year.
There is much variation in the occurrence of small mammals from plot
to plot. Those plots with lower levels of photochemical air pollution
generally have a larger and more diverse small mammal fauna. The distri-
bution and abundance of small mammals on the study areas probably correlates
most closely with the occurrence and quality of key habitat requirements for
vegetation and soil. If these key habitat elements are being affected
and/or have, been affected by photochemical air pollution, then, in turn,
this air pollution will affect indirectly the small mammal populations
through this habitat alteration.
The western grey squirrel is abundant and widespread in these study
areas. It may have an important effect upon forest succession because
of its heavy feeding upon pine and oak seeds.
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RECOMMENDATIONS
FOR GUIDANCE OF FUTURE PROJECT ACTIVITIES
Data Collection and Analysis
Soils
A few more soils will need to be analyzed for chemical and physical
properties in order to establish plot parameters. Moreover, considerably
more chemical analyses of surface soils will be needed to relate soil
nutrient levels to individual trees variously affected by air pollutants.
Due to the natural heterogeneity within many of the 18 permanent
vegetation plots, it is recommended that boundaries of soil types, hill-
slope gradient classes, and hillslope aspect classes be determined in order
to allow stratification of plot data for analysis.
Vegetation
The project should consider a redirection of effort through a focus
on a single forest type within the mixed conifer zone. The selection of
this type is suggested to be on the basis of the quantity and quality
of data already collected and the occurrence of the type relative to the
oxidant dose gradient. The final recommendations developed by this project
for management prescriptions relating to oxidant-injured stands must be
forest type specific.
It is suggested that action be taken to eliminate or resolve the taxo-
nomic discrepancies for ponderosa pine, Jeffrey pine, and Coulter pine trees
among several data sets from the 18 permanent plots before tree-related
data analysis proceeds.
Climate
Precipitation should be measured at all 18 permanent plots and three
complete telemetering stations should be operated for the full term of
the project in order to have a sufficient sample of driving variable
data needed for most subsystem models.
Trends in the Annual Oxidant Dose
Seasonal oxidant doses measured at three permanent stations must be
complemented by intermittent measurements at each of the 18 vegetation plots,
This will enable more careful estimation of the dose-injury relationship
for important tree species.
Measurement of the year to year oxidant dose at the three permanent
14
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monitoring stations should be continued for the full term of the project in
order to document the variation and the trend in the San Bernardino mountains
since 1968 relative to annual climate.
Tree Population Dynamics
The project research design should be expanded to include determination
of tree mortality rates, and the proportion between various causes, on a
spatial scale larger than the permanent vegetation plots. This is so the
root pathogen and bark beetle submodels can be linked to other models for
the forest stand.
The project research design should be expanded to include determination
of proportional causes of tree seed and seedling mortality so that a stand
regeneration submodel can be quantified and submodels dealing with litter
production, decomposition, cone production, and nutrient flows can be
integrated with the forest stand modeling program.
A determination must be made of the dynamic importance of various
quantities of non-arboreal plant life-forms with regard to the regeneration
and growth of various tree species found on the 18 permanent plots.
Investigators in the project should establish several historical data
'sets. A fire history data file for the 18 permanent vegetation plots should
be provided. A determination should be made from various agency files of
the availability and reliability of historical data on meteorology, pest-
tree damage, stump production, and cone crop production for areas of the
SBNF in the vincinity of the 18 permanent plots.
Oxidant Flux-Canopy Response
A process-oriented analysis should examine the sequence of oxidant
concentration exposure in relation to foliar uptake of oxidants controlled
by the transpiration process, and the resulting responses of individual
properties of foliar injury. This is so we can quantify the tree foliar
response to chronic photochemical air pollutant exposure, rather than
aggregate all oxidant-sensitive foliar properties into a single numerical
value.
The within season development of injury to foliage should be measured
biweekly on selected ponderosa pines, Jeffrey pines and black oaks at 6
of the 18 vegetation plots where biweekly measurements of predawn water
potential are made.
Stand-Tree Growth
It is recommended that tree growth data under various levels of oxidant
air pollution be collected and analyzed for tuning and validating the tree
growth simulator being developed.
Stand-Moisture Dynamics and Microclimate
It is recommended that soil water characteristics curves be determined
at 10°C and 20°C for each soil type in which moisture blocks are being used
to monitor seasonal changes in soil water content.
15
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It is recommended that quantitative relations be defined between tree
root zone soil water potential and tree xylem water potential. Continuous
measurements of temperature and relative humidity must be made at selected
vegetation plots in order to provide data to drive the transpiration model.
Western Bark Beetle Population Dynamics and Stand Mortality Response
Sampling of bark beetle populations should be intensified and should
include at least three species of bark beetles and one flatheaded borer.
The interaction of variously diseased trees with bark beetle and
wood borer populations should be studied more extensively, noting effects
on various phases of the life cycles of the beetles; and also effects on
the natural enemies and associates of these tree-killing beetles.
Beetle population data must be linked in some manner to the data
on tree mortality from the Forest Service pest damage inventory study.
This will help define the apparently critical interaction of smog-damaged
trees and tree-killing beetle populations.
Root Pathogen Dynamics and Stand Mortality Response
Air pollution effects on the epidemiology of other important forest
diseases, such as dwarf mistletoe, Armillaria mallea and Elytroderma
deformans needle cast, should be investigated.
The influence of pollutants on mycorrhizae could also be significant
and should be investigated.
Tree Seedling Establishment
The factors affecting soil fungus populations are very complex. De-
tailed studies are necessary to better understand the role of photochemical
air pollution on these organisms.
Litter Production
It is recommended that field data collection on leaf litter production
be expanded to include sample trees of all six major tree species found on
the 18 permanent plots.
Analysis of the nutrient status of needles falling from trees should,
and is, being continued to determine the effect of air pollutants on the
needles and, consequently, on the forest floor over time. Nutrient analyses
of the foliage will link the litter analyses with the crown-drip studies.
Litter Decomposition
In order to evaluate trends in fungal populations, fumigation experiments
to determine growth rate, spore production and spore germinability should be
continued with isolates of common litter decomposing fungi.
One more year of data is required to clarify our current picture of
microfloral succession in pine needle decomposition. This will involve
sampling of needles on trees prior to litter fall as well as sampling needles
separated annually by nylon mesh squares on the forest floor.
16
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Data previously collected should be analyzed further to detect all
significant trends. The analysis should attempt to locate changes in
species composition of microarthropod populations that may accompany air
pollution effects.
Small Mammal Population Dynamics
Further study of the effects of the collective feeding of mammals on
seeds and fruits upon forest succession is needed.
The possible effects of photochemical air pollution upon these feeding
and succession relationships, and upon key habitat elements, also need to
be investigated.
FOR DESIGN AND MANAGEMENT OF ECOSYSTEM MODELING STUDIES
It is necessary to recognize that some recommendations which arise
during the duration of a time-limited research project pertain to conditions
which are likely to be more valuable for other subsequent, similar research
programs starting anew. The following recommendations fall into that
category.
For any full-time research personnel employed under an extramural re-
search grant, the project director should insure that adequate office work
space is available so that the personnel can perform the functions for which
they were hired.
In any extramural research endeavor like this which involves a number
of disciplines, a smaller staff (4 or 5) of full-time senior scientists
should be employed, rather than a larger staff of senior scientists who
may only be able to devote 5 to 15% of their time. This is especially
advisable where the senior scientist's value system forces him to require
assistants whose function does not involve interpretation of a scientific
data as the research effort approaches its climax.
Any research effort conceived to involve systems analysis and modeling
for forecasting purposes should be funded and programmed only in a sequence
which involves the systems modeler immediately. A small staff of subject-
matter specialists should draw upon a larger pool of professionals on a
consultant basis, for the purpose of clearly defining the research problem,
identifying the possible kinds of information outputs expectable, the
possible users and ways for using the information, and synthesizing the
state-of-the knowledge information content from the professional literature
into usable computer models. Data weaknesses should thereby be revealed
and results of sensitivity analyses on the computer models should be the
required justification for prioritizing possible new additional data
collection programs.
In any research endeavor where computer technology is planned to be
used for data storage, data analysis, and modeling, it is urgently recom-
mended that all of these activities take place from the beginning on the
same computer system.
17
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For rapid processing of data not collected by electronic sensing, it is
recommended that the use of hand calculators for temporary data storage be
evaluated for feasibility and cost-effectiveness.
Where field plots are established to study the effects of an environ-
mental stress, it is strongly suggested that the project director assure that
a considerable proportion of the effort and funds be devoted to establishing
control plots.
FOR INTERESTED, COOPERATING AGENCIES
The funding agency should recognize and act upon the need of the system
modeler to have as clear a definition as possible of the ways in which the
funding agency intends to use the information being sought from the research
project. It is recommended that the project systems modeler, agency project
officer, and other informed agency personnel obtain a conceptual information
flow model describing how the environmental information resulting from this
research is to be used by administrators and legislators in evaluating
secondary standards for photochemical air pollutants.
For efficient execution of research activities, it is recommended that
the contract anniversary date be arranged to fall outside of the field data
collection season.
The variation in injury scores within each specie on any one plot
suggests the possibility of genetically controlled resistance to air pollu-
tion injury. The U.S. Forest Service should begin an investigation aimed
at the production of air pollution-resistant strains of ponderosa pine from
San Bernardino stock.
The U.S. Forest Service should curtail further reforestation efforts
with ponderosa pine, Jeffrey pine, or white fir in zone of high oxidant
concentration. Programs aimed at utilizing Incense cedar and sugar pine
should be developed for these areas.
The EPA should recognize the impact of ozone on plant communities
rather than single species when setting secondary air quality standards for
forested landscapes.
Studies should be initiated jointly between the U.S. Forest Service
and the EPA to investigate the relationship between various silvicultural
practices and air pollution injury.
Slash resulting from sanitation salvage logging should be disposed of,
possibly by controlled burns. Prescription burning should be incorporated
as a part of the sanitation operation. This would reduce the wildfire
hazard and should also result in a healthier, more productive ecosystem; air-
pollution damage notwithstanding.
Where Fomes annosus is present and has potential to cause significant
damage, such as in the San Bernardino mountains, control should be initiated
through stump protection using substances such as sodium borate.
18
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GENERAL DESCRIPTION OF ECOSYSTEM PROPERTIES: SOILS
Introduction
Geology and Soil Formation in the San Bernardino Mountains
Soils have formed in the San Bernardino Mountains through the influence
of climate, relief, vegetation, parent materials, and time. Climate in this
area varies from semi-arid to humid depending on altitude. Parent materials
vary from recent alluvium to weathering products of Pre-Cambrian rocks.
Igneous, sedimentary, and metamorphic rocks, are the sources of such parent
material as well as of alluvium derived from these sources. The types of
parent material have influenced the texture, depth, and other properties
of the soil found in this area.
The area is composed mainly of gneisses, schists, plutonic rocks,
sediments, and recent alluvium. The Cactus granite formation (Miller,
1946), primarily a light-colored quartz monzonite of Mesozoic age, is
exposed over a large portion of the mountain area; this esposure is found
primarily on the subdued upland surface. Metoamorphosed sedimentary rocks
of Paleozoic age are abundant in the area, and numerous intrusions of
metoamorphosed rocks are found in both the Cactus formation and other
plutonic bodies. Sedimentary rocks of Pliocene and Pleistocene age are
also found in the area along with recent alluvium.
The texture of the rocks varies from fine textured volcanics to
gravels which contain boulders several feet in diameter. Rocks which have
been fractured and broken to a great extent are found in much of the moun-
tain area, especially near faults and in fault zones. In some areas,
only normal jointing and fracturing are exhibited by the rocks; the
presence or absence of joints and fractures is important to the area's
hydrologic characteristics.
The various geologic materials in the San Bernardino Mountains have
weathered by physical and chemical processes to form parent materials
which have differentiated into soil profiles by the processes of additions,
removals, transfers, and transformation. Differences in the rates of these
four processes have resulted in the formation of different soil type.
Relief has been an important factor in soil formation in this area.
Slopes vary from nearly level to nearly vertical. Soils found on steeply
sloping land are generally shallow due to erosion processes during soil
formation. Deeper soils are found on more stable landscapes. Most of
the soils are coarse textured, well drained, and have a low water-holding
capacity. These properties are primarily the result of relief and parent
materials.
19
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Relationship of Soils Studies to the Overall Project
At the organism level, soil moisture and temperature studies have been
coordinated with the climate and air pollution monitoring subproject by
using identical sites. Litter production, forest-floor measurements, soil
sampling and analysis for soil characteristics have been coordinated with
sampling sites under specific trees variously impacted by air pollution.
These trees were also studied by subprojects dealing with soil and litter
arthropords, pathogenic and nonpathogenic fungi, and litter decomposers,
plant communities, and the impact of pollutants on vegetation and indivi-
dual plants.
At the community level, a number of plots are being subjected to in-
tensive study. The pattern of soils and their morphological character-
istics are being described, so that they can be related to plant communities,
stand composition and growth, and to populations and distributions of
small mammals, arthropords, fungi, and other pathogens. Data have been
collected on thickness measurements and core mass by which the amount of
organic matter (litter) on the forest floor can be estimated over entire
plots; however areas disturbed by logging activities have to be separated
from essentially undisturbed areas.
At the level of plant succession, we hypothesize that the principal
variables affected by oxidant air pollution are: the organic matter con-
tent of the soil; the amount, kind, and compositon of litter; and, to a
lesser degree, nutrient cycling. Differences in these properties measured
at the community and organism level can be applied directly to considera-
tions of plant succession, particularly in relation to seedling germination
and survival.
Research Objectives
The research objectives fall under three categories: soils, litter and
surface soils, and climate and soil climate.
1) SoilsTo analyze the nature and pattern of soil in relation to
vegetation patterns and the impact of pollutants on the nature
and vigor of that vegetation, especially the western yellow pine
trees.
2) Litter and surface soilsTo analyze the effects of air pollutants on
the litter production, the thickness and nature of the forest floor,
and the surface soil below in relation to arthropod and microbial
activity and to the suitability of the soil and forest floor as a
medium for seedling germination and survival.
3) Climate and soil climateTo analyze the relationship of soil proper-
ties, soil moisture and temperature regime, and climate to the
susceptibility of vegetation to damage by oxidant air pollutants.
Materials and Methods
Nature and Pattern of Soils
20
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In relation to the first objective, soils were sampled and described at
a number of sites on each of the major vegetation plots and their patterns
were identified to give a highly detailed map of each plot. Because of the
variability across individual plots, it was necessary to develop the re-
lationships among soil, topography, and vegetation characteristics. Using
observed properties of soil color, texture, structure, and reaction (pH),
soils on the various plots were classified according to "Soil Taxonomy"
(Soil Survey Staff, USDA) and according to soil series names established by
the National Cooperative Soil Survey of California. See Appendix A. The
soils have been characterized with respect to their chemical and physical
properties in order to find relationships between soil properties and the
susceptibility of vegetation to air pollutant damage.
Soil properties measuredParticle size distribution (soil texture) was
measured because of its importance as an indicator of the soils' ability to
store water and nutrients for plant use. Bulk density was measured because
of its effect upon root penetration and distribution, and its relationship to
soil porosity and permeability to water and air. Exchangeable and soluble
cations and soil pH were measured as they relate to the mineral nutrient
status of the soils; soil organic matter likewise affects the structure,
water retention, and porosity of the surface soil. It is a source of nitro-
gen for plants and of energy for microorganisms, including pathogens. The
water storage capacity of the soil is particularly important in this area
because of the long, dry, warm summer during which plants are almost
entirely dependent upon stored soil moisture for their survival. Finally,
the amount of organic litter (needles and woody material) on the forest
floor is related to forest vigor and the production of litter in relation to
its decomposition rate. It also directly affects seed germination and
seedling survival, as well as soil temperature, moisture, and humus content.
Specific analytical proceduresExchangeable cations were extracted
from soil with ammonium acetate according to Black (1965). Cations from
litter samples were prepared using the digestion process recommended by
Johnson and Ulrich (1959). Atomic absorption was used to measure the con-
centration of individual cations. Nitrogen was measured with a modified
Kjeldahl analysis from Black (1965), and phosphorus was determined by a
colorimetric method (Jackson, 1960). Carbon was determined by a combustion
method modified from Black (1965).
Exchangeable and Soluble Cations
Exchangeable and soluble cations were determined on 22 soils through-
out their total depths on the vegetation plots (omitting Camp Angelus, and
including two other sites at S22 and NE13) making a total of 251 samples.
Soluble cations were determined on a 1:1 water extract of the soil, and
exchangeable cations on a neutral 1.0 normal ammonium acetate extract.
Results and Discussion
Soil Classification for the 18 Permanent Study Plots
Soils were examined at a number of sites in each of 18 plots. The
parent material of the soils is partially weathered or decomposed granitic
rock on all of these plots except for three which also include alluvial
21
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or colluvial material. Sand Canyon (SC) plot is on granitic rock at its
eastern end, but the bulk of the plot is colluvium including some marble
fragments derived from metamorphic rocks. It is located southeast of Big
Bear Lake. Heart Bar plot (HB) is primarily mixed alluvium derived from
granitic and metamorphic rocks, and is located in the upper end of Santa
Ana Canyon. Camp Angelus plot (CA) is mainly stony granitic colluvium,
although the southern end of the plot is formed directly on granitic rock.
Granitic rock weathers first to decomposed granite gruss, then to
coarse sand, loamy coarse sand, coarse sandy loam, and eventually to
sandy clay loam or clay textured soils if the weathering is sufficiently
intense and of long duration. Above about 1800 m (6,000 ft) the mean
annual soil temperature is low (less than 8 C) with reduced weathering
intensity, so that the soils are mainly coarse sandy loams, or loamy
coarse sands without marked accumulation of clay in the subsoil. At lower
elevations, soils in moist sites show some degree of clay accumulation
in the subsoil. Only on the warmest sites on the desert (north) side of
the crest are continuous areas of soils with a sandy clay loam subsoil
texture encountered. These plots are Tunnel Two, U.C. Conference Center,
C.UCC) and Holcomb Valley (HV).
Soils in the Lake Arrowhead region are dominantly of the Shaver series
which is dark in color to a depth of greater than 50 cm (Pachic), slightly
acid in the surface (Mollic), increasingly acid with depth (Ultic) and with
no significant clay accumulation in the subsoil (Haplic). The texture of
the subsoil is coarse sandy loam, classified as "coarse loamy"; the clay
mineralogy for granitic soils is a mixture of kaolinite, mica, illite,
and vermiculite. The mean annual soil temperature is between 8 and 15
C (Mesic)t and soils are continuously dry in the upper part for 90 days
in summer CXeric).
Thus, the complete classification of the Shaver soil series is:
Order: Mollisol
Suborder: Xeroll
Great group: Haploxeroll
Subgroup: Pachic Ultic Haploxeroll
Family: Coarse, loamy, mixed, mesic
Soil series: Shaver.
Due to more intense and prolonged weathering on the Tunnel Two and UCC
plots soils with distinct subsoil clay accumulation differ in that on Tunnel
Two, the surface is dark to a depth of less than 25 cm, while on the other
plot it is dark between 25 and 50 cm in depth. Consequently, the Stump
Springs soil on Tunnel Two is an Ultic Haploxeralf, while that at the UCC
plot is an unnamed soil classified as an Ultic Argixeroll. At HV, north
22
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of Big Bear Lake, there are Typic Argixeroll soils of the Domingo Series,
similar to those at the UCC, but not increasingly acid with depth.
The remaining soils are either coarse sandy loam ("coarse loamy"),
or loamy coarse sand ("sandy") throughout the entire soil depth, except
for the Cahto variant soil at CA which is stony, coarse, sandy loam. Some
are shallow (lithic) while others are sandy (Psamments). Some have dark,
acid surface soils and slightly bleached layers below (Umbrepts) or are
not dark (Orthents and Ochrepts). Although Appendix Table A shows that
there are some 23 soils represented on these plots, many are quite similar,
making it possible to compare the effects of air pollutants of varying
concentration on vegetation growing on nearly identical soils in a number
of cases.
Chemical and Physical Soil Morphology
In addition to the soil samples collected at 23 sites, morphological
descriptions of soils at 62 sites were obtained on 18 plots. Information
included horizon designation, texture, color, pH, and surface structure.
Physical and chemical measurements also were made of 23 soils at the soil
moisture sensor sites. These included particle size distribution, bulk
density, gravel and stone content, pH, exchangeable and soluble cations,
and nitrogen and organic carbon content. Only partially complete informa-
tion could be obtained from the plots at CA, BF, and CO because the stony
nature of the soils there essentially precluded volumetric sampling. A
total of 246 samples were analyzed in this way. These data provide the
basic information for relating the nature of the soil to the kind and
amount of vegetation and its susceptibility to air pollution injury.
Particle Size Distribution
The content of sand, silt, clay, fine gravel, and coarse gravel of
selected soil samples from 17 study plots is shown in Appendix B. All
values are given in percent of fine soil material, i.e. grams per 100
grams of soil material finer than 2.0 mm in effective diameter. The samples
reported include those from the surface soil, a subsoil sample showing the
maximum clay content, and a deeper sample of minimum clay content at or
near the base of the soil where it grades into decomposed granite.
The variation in particle size distribution with depth for 3
representative soils is shown in Figure 2. The soil labeled "Unnamed-
2" has a distinct maximum in clay content at a depth of 70 to 100 cm.
Similar soils are found at Tunnel Two and at HV. The Shaver soil found
on a number of plots in the Lake Arrowhead area between Camp Paivika and
Sky Forest contains less clay and shows only a small and gradual decrease
in clay content from the surface downward. The Crouch variant soil at
Schneider Creek is representative of the sandier soils at Green Valley
Creek, N.E. GV, HB, and SC which contain little clay and considerable fine
gravel. The soil at BL is also sandy but contains little fine gravel.
As in most soils formed from granitic rock, these soils generally
contain considerable fine gravel (2 to 12 mm in diameter) and, as a
consequence, would technically be classified as "gravelly." However,
most of the fine gravel is about 2 to 4 mm in diameter and behaves much
24
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like very coarse sand in the soil; thus, the "gravelly" designation is
omitted from the "coarse sandy loam" and loamy coarse sand" textural class-
ifications (Fig. 3).
Bulk Density of Soils
The bulk density of volume weight of soils (I>b) was determined in con-
nection with the moisture sampling. The variation of bulk density with
depth is shown for eight representative soils in Figure 4. A complete set
of data are given in Appendix C.
Of the surface soils, the one at Breezy Point (BP) is the least dense
(0.74 gin/cm-^) and very rich in organic matter. The soils with the most
dense surface soils are at HV and the UCC with bulk densities of more than
1.4 gm/cm^, which are soils also having clayey subsoils and are in the
warmer north side of the general transects. Most of the soils have surface
bulk densities of 1.1 to 1.3 gm/cm^, and are thus very porous and of good
granular or crumb structure.
Subsoil densities are generally from 1.5 to 1.7 gm/cm , which is
very common for soils of sandy textures. The higher bulk densities are
associated with loose sandy soils which tend to crumble into the sampling
hole so that those greater than 1.8 gm/cm may well be due to sampling
error. Notice that again, BP soil has a low density to considerable depth;
this soil also has the highest available water storage capacity as indicated
in Appendix C.
Exchangeable and Soluble Cations in Soils
Results for surface soils are shown in Appendix D. The dominant
exchangeable cation is calcium (Ca), with magnesium (Mg), potassium (K),
and sodium (Na) decreasing in that order. The values obtained are quite
typical of surface soils formed on granitic rocks elsewhere in California
(Soil Survey Staff USDA, unpublished document). For example the common
range for exchangeable calcium is from 5.0 to 10.0 meg/100 g. Thus, the
soils at site 3 on the Dogwood plot (DW-3) and at BL are low in calcium,
due to their cold, humid climates. At SC, surface soil is rich in Ca,
probably due to its proximity to the ridge above, which contains some
marble. Exchangeable potassium content is quite low.
Soluble cations in the surface soil are dominated likewise by Ca
followed by K, Mg, and Na in that order. These again are in concentrations
often found in granitic soils. All except Sand Canyon site 1 (SC-1)
appear to contain adequate supplies of these elements for plant growth.
Exchangeable and soluble cations for representative subsoil layers
from the same soils are shown in Appendix E. Again, the soils at DW-3 and
BL are low in cations, especially at BL. High values of exchangeable Ca
are shown for HV and UCC, both of which have pronounced clay accumulations
in the subsoil. A number of the values for exchangeable and soluble K are
low (less than 0.1 and less than 0.005 meg/100 gm) respectively. However,
the complete data indicate that soluble K is low throughout the entire depth
of soil only in Bluff Lake (BL), Sand Canyon site 1 (SC-1), and GVC.
25
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Sandy Clay Loam
Sand %
Figure 3. Average particle size distribution of soils of study plots.
26
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Soil Bulk Density-gm/cc
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27
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Soil Organic Matter
Organic carbon and nitrogen were determined on samples from major plots
to a depth of 50 or 60 cm. The results for the upper 25 cm of soil only
are shown in Appendix F. The soils with the most organic matter are shown
to be at DW-3, BL, and BF, with organic carbon values of 2.99 g/100 g or
more. Soils with the least organic matter are SC-1, GVC, and HB, all of
which have relatively thin needle-litter layers on the soil. The highest
value for N was found at Camp 0-Ongo, but the unusually low ratio of C
to N suggests possible contamination, perhaps from riding horses from the
nearby summer camp. Other sites with high N levels are at BL, BF, DW-3
and BP. C/N ratios generally range from 20 to 30, which are common under
mixed conifer forests.
Soil Water Available for Vegetation Growth
In order to quantify the soil moisture regimes in terms of total
quantities of water, the soils at the 23 sites were sampled volumetrieally
for gravimetric measurement of total water content both in April when
fully wet, and in October, when they were at minimum moisture content.
The difference appears to be the amount of water available to the plants,
assuming that the organic litter layer on the surface limits air movement
and thus limits direct evaporation from the soil to very low levels.
The values obtained by this procedure are shown in Appendix G. Plots
included are only those in which soils were sufficiently low in stone
and gravel content to permit volumetric sampling. The first 3 columns of
data show the volumetric percent and the total calculated depth of avail-
able water in April to a uniform depth of 152 cm (5 ft). The last two
columns show the total soil depth and the total available water storage.
The most significant fact shown by these data is that the available soil
moisture storage values within the root zone of the pine forest is very
high, about 30 cm,(12 in.or more), compared to the values commonly used
in water balance studies of this kind (10 or 15 cm). The low values found
for the last five plots listed, may underestimate the water available to
the trees, which may be obtaining water from the firm weathered granite
below the depth of sampling; perhaps from cracks and joints in the rock.
28
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GENERAL DESCRIPTION OF ECOSYSTEM PROPERTIES: VEGETATION
Introduction
Development of a Conceptual Model for Succession of the Vegetation
Continued high levels of oxidant air pollutants in the San Bernardino
Mountains will affect both the rate and direction of plant succession.
Those working with the tree population dynamics subsystem are developing a
model of plant succession that can be used to predict species composition
and the structure of forest stands subjected to different levels of air
pollution. This model will require the cooperation of many of the in-
vestigators collecting data on other components of the ecosystem. The
first contribution to the development of this model involves the develop-
ment of (1) a conceptual (non-mathematical) model of plant succession
and (2) the field measurement of certain vegetation parameters needed
to "run" the mathematical model. The following sections describe some of
the important state variables and driving variables of this model.
Vegetation Zones
The vegetation of the San Bernardino Mountains is composed about
equally of chaparral and forest types with important minor elements of
woodland, sagebrush, and grassland. Horton (1960) and Minnich et al.
(1969) have undertaken major treatments of this vegetation. Horton (1960)
recognized six vegetation zones on the basis of plant physiognomy and
environmental conditions (Fig. 5): chamise-chaparral, woodland-chaparral,
desert chaparral, pinyon-juniper woodland, timberland chaparral, and
coniferous forest. One or more of these vegetation types occur within
each zone. Twenty of these types were defined by Horton (1960) on the
basis of field reconnaissance. Using infrared color imagery on aerial
photographs, Minnich et^ al. (1969), mapped 28 vegetation types in the
San Bernardino Mountains.
Vegetation Types
Our study focused on the Coniferous Forest Zone, which ranges in
elevation from 154 m to 1981 m on north-facing slopes, and 1524 m to 2286
m on south-facing slopes upward to the highest peaks (San Gorgonio, 3,505
m). Four coniferous forest vegetation types were recognized by Horton
(1960) in this zone, two of which Pine Forest and Ponderosa Pine-
White Fir Forest were the central concern of this study. An improved
map based on a U.S. Forest Service (1973) type map, has been prepared to
show the distribution of these types (Fig. 6 ) Our work indicated that
these two general types may be subdivided further into five vegetation
types on the basis of species dominance. These types are as follows:
Ponderosa Pine Forest, Ponderosa Pine-White Fir Forest, Ponderosa Pine-
Jeffrey Pine Forest, Jeffrey Pine Forest, and Jeffrey Pine-White Fir.
29
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10 O
I"
lev)
JlO
Q
Z
LJ
CD
LJ
LJ
Z
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LJ
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U. LJ
li. Q.
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60
H
ft*
33
-------
TABLE 1 . TREE LAYER DATA FROM PLOTS REPRESENTATIVE OF EACH VEGETATION
TYPE DOMINATED BY PONDEROSA OR JEFFREY PINE IN THE SAN
BERNARDINO MOUNTAINS.
Characteristics
Mixed conifer
forest types
Ponderosa Pine
(N.W. Paivika)
PP
SP
1C
WF
JP
BO
QW
DW
Total
Ponderosa Pine -
White Fir
(Sky Forest)
PP
SP
1C
WF
JP
BO
QW
DW
Total
Ponderosa Pine -
Jeffrey Pine
(Barton Flats)
PP
SP
1C
WF
JP
BO
QW
DW
Total
No. of
trees
98
1
.
70
169
104
15
25
67
7
4
222
139
86
16
8
249
spp.j
comp.
57.9
0.5
41.6
100
46.9
6.8
11.2
30.2
*
3.1
1.8
100
55.9
34.5
6.4
3,2
100
Density^
217.8
2.2
155.6
375.6
144,4
20,8
34.7
93,1
9.7
-
5,6
308.3
200.1
T-
123.8
23.0
11,6
358.5
Basal
area'
24.11
0,03
_
-
6.32
30,46
28.38
0,60
4.10
3.85
-._
2,21
__
39,14
16,87
10,21
5.99
0.56
33.63
34
-------
TABLE 1. TREE LAYER DATA FROM PLOTS REPRESENTATIVE OF EACH VEGETATION
TYPE DOMINATED BY PONDEROSA OR JEFFREY PINE IN THE SAN
BERNARDINO MOUNTAINS. (CONTINUED)
Characteristics
Mixed conifer
forest types*
Jeffrey Pine -
White Fir
(Green Valley Cr.)
PP
SP
1C
WF
JP
BO
QW
DW
Total
Jeffrey Pine
(Snow Valley)
PP
SP
1C
WF
JP
BO
QW
DW
Total
No. of
trees+
11
10
62
39
82
1
205
3
99
1
103
Spp. £
comp.
5.4
4.9
30.3
19.0
40.0
0.4
100
2.9
96.2
0.9
100
Density
12.2
11.1
68.9
43.3
91.1
1.1
227.7
3.9
129.4
1.3
134.6
Basal
area"
2.93
1.63
4.94
12.20
4.70
0.02
26.42
1.30
21.56
0.16
23.02
TABLE LEGEND:
^Symbol
PP
SP
1C
WF
JP
BO
QW
DW
Common Name
ponderosa pine
sugar pine
incense cedar
white fir
Jeffrey pine
black oak
interior live oak
dogwood
Scientific Name
Pinus ponderosa
Pinus lambertiana
Libocedrus decurrens
Abies concolor
Pinus jeffreyii
Quercus kelloggii
Quercus wislizenii
Cornus nuttallii
Number of trees on the plot
Percent of species composition on the basis of number of trees
Number of trees/hectare
if
Basal area in square meters/hectare
35
-------
r
i
r
i
i
fc
UJUJQ
>zS r
HEo rl-
9 or v ui '
yoLft l
igffs 1
«; £u.ti
o guz
Q B ->
UJ U- O X r
1
s 4-
* iu 1
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y^^t i
9 = m * 7
|
< CO O Q
1 1 1 1 1
O O O O O
O CO (0 ^ CM
O
U
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U.
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CD
0
X
CD
U.
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0
111
U
X
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CAMP SKY BARTON GREEN VALLEY SNOW
WVIVttA FOREST FLATS CREEK VALLEY
CO
§
Q.
OT
4^1
O
B
0)
CO
B
V-i
0)
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CO
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01
d.
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CD
oo
60
(%) NOIllSOdWOO S3l03dS
36
-------
in terms of the characteristics of the shrub and herb layers. The plots
occurring in forest types dominated by ponderosa pine have an average
shrub cover of 3.8%, while those plots occurring in forest types dominated
by Jeffrey pine average 26% shrub cover. Arctostaphylos pringlei and Ribes
roezlu are typical of the shrub layer in ponderosa pine-dominated types.
Ceanothus cordulatus, Arctostaphylos patula, and Artemisia tridentata are
common shrubs in forest types dominated by Jeffrey pine (See Fig. 29).
Heterogeneity of the Ponderosa Pine-White Fir Type on Adjacent Sites with
Different Aspects
Fire historyA meaningful conceptual model of forest succession requires
a study of plant succession following fire in the ponderosa- and Jeffrey pine-
dominated forest types in the San Bernardino Mountains. This study identi-
fies variables which have influenced the rate and direction of plant suc-
cession in the past. In the summer of 1974, eighty-three plots were estab-
lished in this study (Fig. 1). Analysis of the field data suggests that
a stratification of fire succession plots according to physiographic units
is necessary before meaningful successional patterns can be determined.
General observations made during the previous field seasons suggest that
fire has been a selective factor in forests of mixed species composition.
White fir and incense cedar are more vulnerable to wildfire than are pine
species. Similar observations have been made in other parts of California
(Biswell, 1977) and the southwest (Weaver, 1964). Other mortality factors
operating in the San Bernardino Mountains, including air pollution, are also
selective. Any model of plant succession must take into account the rate at
which these mortality factors remove trees from a forest stand. Since
mortality rates differ according to the age of plants, it is necessary to
know the age structure of the stand. With knowledge of (1) the initial age
structure, (2) expected mortality rates from various factors (insects, path-
ogens, air pollutants, fire, herbivores), and (3) reproductive rates (seed
production and establishment), one could approach the modeling of plant
succession using a modification of the life table method introduced by Leak
(1970). With this approach in mind, we included a study of age structure of
stands in the San Bernardino Mountains as one of our research objectives.
Initially, the age structure of the 18 permanent plots was determined using
ring counts on cores taken with increment borers. Tree age was also determined
on the 83 fire-succession plots. These data, along with additional samples
to be taken in the next field season, will build an important data source
for use in the modeling of plant succession.
Four patterns of forest regeneration have been identified from the age
structure curves of the 18 permanent plots. In order of increasing occur-
rence, these are:
1. No significant tree regeneration over the last 20 years;
2. Regeneration of Ponderosa or Jeffrey Pine;
3. Regeneration of more tolerant conifers;
4. Invasion of Black oak.
37
-------
The occurrence of any pattern is independent of. air pollution gradients
in the forest; however, the selective impact of air pollution on tree mor-
tality, combined with certain of the above patterns of regeneration, may
have serious consequences for the continued dominance of pine in certain parts
of the San Bernardino Mountains.
Multiple Uses of Vegetation Composition Data
The descriptive information developed by the vegetation subcommittee has
been used by other investigators for the selection of sampling locations,
general habitat descriptions, and as a basis for comparison with auxiliary
plots. Several auxiliary plots were established to study bark beetle popu-
lation dynamics; these plots were surveyed by the vegetation subcommittee
using the same procedures used on the permanent plots. This type of survey
allows certain comparisons with other data collected on the permanent plots.
38
-------
GENERAL DESCRIPTION OF ECOSYSTEM PROPERTIES: CLIMATE
Introduction
Temporal and Spatial Trends of Temperature and Precipitation
The climate of the San Bernardino Mountains is distinguished by its
Mediterranean character, with maximum precipitation during the cold months
(November to April) and minimum precipitation during the warm summer
months (June, July and August). Only 1% of the world (and no other part
of the United States) has this particular climate. Deep snow may cover the
mountain peaks during the winter but only rarely does any remnant of snow
cover persist on higher peaks through the summer. A peculiar feature of
the precipitation is the occurrence in July and August of sporadic thunder-
storms which originate over the desert and reach their maximum develop-
ment mainly over the eastern one third of the mountains. Precipitation
ranges from light to heavy over short distances and usually for short
periods during the afternoon hours.
The annual fluctuations of temperature and precipitation exercise
strong controls over most ecosystem processes under study by this project.
The objectives of this section are to:
1. Examine the long term temperature and precipitation record
at representative sites.
2. Compare the short term precipitation record at the permanent
vegetation plots with long established precipitation stations.
Materials and Methods
Long term records for temperature and precipitation were obtained
from the National Weather Service and the San Bernardino County Flood Con-
trol District. Winter precipitation was collected at vegetation plots
using Sacramento type storage gauges precharged with antifreeze and a
small amount of transmission fluid. Changes from the initial fluid depth
in each gauge were measured with a dip stick at the end of each month.
Summer precipitation was collected with small plastic rain gauges with a
9 inch capacity.
Results and Discussion
Long Term Temperature and Precipitation at Lake Arrowhead and Big Bear
Lake Dam
The relationship between mean monthly precipitation and temperature
is illustrated in Figure 9 using long-term Weather Bureau records for
39
-------
LAKE ARROWHEAD, LONG-TERM MEANS.
20
15
s
iS
10
200
150?
BO
50 i
J F MAMJJ ASOND
MONTH
BIG BEAR LAKE DAM, LONG-TERM MEANS.
200
JFMAMJJASOND
Figure 9. Long-term Weather Bureau records for monthly means of
temperature and precipitation at Lake Arrowhead and
Big Bear Lake Dam,
40
-------
Lake Arrowhead and Big Bear Lake Dam. Although Big Bear Lake is higher
(Elev. 2,078 m) and colder (mean annual air temperature, 6.43 C) than Lake
Arrowhead (Elev. 1,587 m and mean annual air temperature, 11.05 C), it
receives less average annual precipitation (934 mm) than Lake Arrowhead
(1063 mm).
Precipitation Record Comparisons Showing Trends Relating to Topography
The mean annual precipitation measured or projected for a number of
stations maintained by the San Bernardino Flood Control District is shown
in Table 2 in relation to nearby study plots and their elevations. In
Appendix H, these tables give the monthly and annual means, standard de-
viations, standard errors of the means, and coefficients of variation for
each of 24 precipitation stations in the San Bernardino Mountains. These
stations are in close proximity to the 18 permanent vegetation plots shown
in Figure 10.
A comparison of the elevations of the precipitation stations to the
elevations of the permanent vegetation plots is shown in Table 3. The
mean annual precipitation does not increase uniformly with elevation in the
area because of the configuration of the mountains and its effect upon the
movement of air masses and subsequent occurrence of rain showers. The
long-term precipitation estimates indicate that the plots near Lake Arrow-
head (DWA, UCC, and SF) receive the greatest precipitation, while those
at the eastern end of the study area receive the least (HB and SC). How-
ever, two years of data collected with snow storage gauges at each plot
(Table 4) indicate that Holcomb Valley north of Big Bear Lake receives low
precipitation, while the Bluff Lake north of Big Bear Lake on a high
plateau area receives more precipitation than any other plot. The long-
term means shown in Table 2 may be compared with 1973-1974, and 1974-1975
precipitation measured at each vegetation plot (Table 4). An improved
precipitation map for the SBNF can now be constructed from these data.
Precipitation variability across the transect of study plots might
have implications for the degree of oxidant injury to vegetation. Analysis
of this possible interaction is reported in the Stand Moisture Subsystem
section.
41
-------
TABLE 2. COMPARISON OF MEASURED AND PROJECTED MEAN ANNUAL PRECIPITATION
FROM SAN BERNARDINO COUNTY FLOOD CONTROL DISTRICT STATIONS
NEARBY THE PERMANENT VEGETATION STUDY PLOTS.
Station
Cedar Pines Park
Job's Peak
Blue Jay Co.
Yard
Lake Arrowhead
Arrowhead RS
Running Springs
Green Valley Lake
Big Bear Lake Dam
Big Bear Lake
Fire Station
Big Bear City
Green Canyon
Springs
Heart Bar
Camp Angelus
Elev.
1448
1573
1646
1587
1705
1854
2098
2078
2056
2073
2134
2039
1762
Nearest
major
vege-
tation
plots
CP
BP
DWA
UCC
SF
COO
NEGV
GVC
BL
HV
SC
SC
HB
CA
Direction
and
distance
(km)
of station
from major
vegetation
plot
1.6 N
1.5 W
1.0 NNW
1.6 S
0
3.2 SE
1.6 WSW
2.4 ENE
2.4 N
5.2 S
6.4 N
2.4 E
0
0
Mean
annual
precip.
(mm)
579*'
*/
707-'
*/
1073-'
1063
*/
1112-
960
829^
934
570
SOI-''
+ .
331-
3S9-7
750^
Years
of
record
6
7
4
35
13
21
6
33
24
13
10
7
5
Long term mean projected from Lake Arrowhead by linear regression
Long term mean projected from Running Springs by linear regression
Long term mean projected from Big Bear Lake Fire Station by linear
regression
Correlation coefficients for linear regression are highly significant
with values at least 0.92, where 1.0 represents a perfect correlation.
-------
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-------
TABLE 3- COMPARATIVE ELEVATIONS OF 18 PERMANENT VEGETATION PLOTS WITH
PRECIPITATION COLLECTORS AND THE SAN BERNARDINO COUNTY FLOOD
CONTROL DISTRICT PRECIPITATION STATIONS.
Elevation
meters
(above m.s.l.)
1120
1150
1385
1450
1485
1500
1525
1545
1550
1555
1595
1600
1610
1650
1655
1705
1720
1725
1730
1787
1830
1853
1855
1900
District station name
and length of record
Plot name (years)
Pilot Rock Conserv. Camp (16)
Panorama Point (17)
Lake Gregory (16)
Cedar Pines Park (6)*
Crestline Fire #2 (10)
Crestline County Yard (14)
Breezy Point
Job's Peak (6)*
Crestline SE (20)
Lake Arrowhead FD 4 (6)
Squirrel Inn #1 (73)*
Camp Paivika Lake Arrowhead Fire (84)
Univ. Calif. Conference Cen.
Blue Jay County Yard (4)*
Tunnel Two Ridge
Arrowhead Ranger Station (17)
Sky Forest
Dogwood
Squirrel Inn #2 (46)
Camp Angelus Spencer (9)
Camp Angelus
Schneider Creek
Running Springs (21)*
Camp O'Ongo
1950
2040
2055
2075
2080
2100
2135
2160
2170
2225
2320
2365
Deer Lick
Barton Flats
Green Valley Creek
Camp Osceola
Heart Bar
N.E. Green Valley
Holcomb Valley
Bluff Lake
Sand Canyon
Heart Bar State Park (10)
Big Bear Lake Fire (26)
Big Bear City (21)
Big Bear Lake Dam (93)
Green Valley Lake (16)
Green Canyon Springs (13)
*Record not continuing
44
-------
TABLE 4. WINTER PRECIPITATION, 1973-1974, AND 1974-1975, AT EACH MAJOR
VEGETATION PLOT, SAN BERNARDINO NATIONAL FOREST, DETERMINED
BY SNOW STORAGE GAUGES, SEPTEMBER 15 TO MAY 1.
Plot
CP
BP
TUN 2
UCC
DWA
SF
COO
GVC
NEGV
SV
DL
HV
BL
SC
CA
SCR
BF
CAO
HB
Precipitation*
(cm)
1973- 1974-
1974 1975
45.6
99.0
85.6
80.8
106.9
81.1
71.8
73.3
77.0
39.7
134. 8+
35.1
38.6
39.5
40.1
43.1
37.8
48.5
76.9
64.1
49.4
83.6
79.5
68.5
59.3
54.8
78.2
30.8
68.9
31.1
61.6
47.2
40.9
35.1
32.9
Precipitation*
(inches)
1973- 1974-
1974 1975
18.0
39.0
33.7
31.8
42.1
31.9
28.3
28.9
30.3
15.6
53. 1+
13.8
15.2
15.6
15.8
17.0
14.9
19.1
30.3
25.2
19.4
32.9
31.3
27.0
23.3
21.5
30.8
12.1
27.1
12.2
24.2
18.6
16.1
13.8
12.6
All data calculated by formula using individual snow gauge dimensions.
Apparently much too large, snow probably drifted over the snow gauge.
45
-------
GENERAL DESCRIPTION OF ECOSYSTEM PROPERTIES: TEMPORAL AND SPATIAL TRENDS
OF OXIDANT AIR POLLUTANT CONCENTRATIONS
Introduction
Climate and Oxidant Concentrations
The National Primary and Secondary Air Quality Standards for Photo-
chemical Oxidants (California Air Resources Board, 1974), Appendix I,
provides the basis for evaluating the trends of pollutant concentrations
in the area under study. Penetration of photochemical oxidant pollution
eastward from the Los Angeles metropolitan area to the inland valleys and
mountains has been recorded for many years at surface stations operated by
both the California Air Resources Board and various county agencies. Data
back to 1963 are available from the downtown San Bernardino station
operated by the County Air Pollution Control District (APCD). The
accuracy of the long-term records has been examined by Pitts, j^t _al. (1976)
The mechanisms of oxidant transport have been described for sample days
by simultaneous use of surface and air borne oxidant sensors (Blumenthal,
et^ _al. , 1974; Edinger, j± _al.. , 1972). The dependency of ozone concentra-
tion on the elements of the regional climate is illustrated by the simple
models of Tiao, ^t al. (1976), and Zeldin (1975), which are used to pre-
dict maximum ozone concentrations for the following day. McCutchan and
Schroeder (1973) have used a stepwise discriminant analysis of eight
meteorological variables to classify days from May through September in
southern California, specifically around the San Bernardino mountains. A
description of the five resultant day-classes appears in Table 5; three
of these classes (2, 3, and 4) are associated with elevated ozone concen-
trations.
This study of the chronic effects of oxidant air pollutants on the
mixed conifer forest requires a means of documenting the daily oxidant
dose and associated meteorological conditions. The within-season
distribution or occurrence of these five meteorological patterns is
superimposed on two other factors: (1) the declining availability of
typical soil moisture as the summer season passes in a Mediterranean
climate, and (2) the state of plant growth or phenological develop-
ment. A given distribution of meteorological patterns associated with
high oxidant concentrations occurring within a growing season is ex-
pected to result in variable amounts of injury to individual species in
the forest community. The most important use of this method for classi-
fying meteorological patterns in our pollutant effects study is to provide
a means for comparing both prevailing day-to-day patterns within a
summer season and those between summer seasons. Later, these comparisons
include the ozone doses associated with each day class or most frequent
sequences of day classes. Then it will be possible to obtain better
46
-------
TABLE 5. DESCRIPTIONS OF METEOROLOGIC PATTERNS FOR FIVE CLASSES OF
SPRING AND SUMMER DAYS IN SOUTHERN CALIFORNIA.*
Class
General weather
Associated synoptic pattern
Surface
500 mg
Hot, dry continental air
throughout the day
(Santa Ana)
Relatively dry forenoon;
modified marine air in
afternoon; very hot (heat
wave)
Moist, modified marine
air; hot in afternoon
Moist, modified marine
air; warm in afternoon
Cool moist, deep marine
air throughout the day
Large high pressure
over Great Basin
High pressure over
Great Basin and
thermal trough over
desert
Thermal trough over
desert
Thermal trough over
desert
Synoptic low over
desert
Strong northerly
sinds over area
with trough east
of the area
Subtropical closed
high over area
Ridge over area
Trough over area
Deep trough or
closed low over
area
*Source: McCutchan and Schroeder (1973).
47
-------
resolution of the dose-environment interactions which characterize each
season, and to compare this characterization with the amount of injury
to forest vegetation both during and after the season.
Research Objective
The objectives of this program of air monitoring and measuring meteoro-
logical variables are:
1) To examine the relationship of cumulative seasonal ozone dose to
meteorological patterns at three telemetering stations;
2) To examine the relationship of surface wind flow to pollutant
transport;
3) To define the gradient of oxidant across the study area in terms of
cumulative seasonal dose at six stations complementing the three
telemetering stations;
4) To compare the simultaneous concentratons of ozone, total oxidant,
PAN, and N02 on an hourly and daily basis;
5) To examine the historical trends of seasonal oxidant doses.
Materials and Methods
Equipment and Calibration Methods
MeteorologicalThe remote stations at Camp Paivika, Sky Forest, and
Barton Flats, all of which were part of a Forest Fire Meteorology Research
Network (McCutchan, 1975), measure temperature at 0.5 m and 1.2 m, relative
humidity at 1.2 m, wind speed and wind direction at 9.2 m, and net radiation
at 0.2 m above the ground. The stations accept hourly interrogations from
the master station, convert analogue measurements to digital form, and
transmit data either directly or through a. repeater back to the master
station.
Each remote station consists of: (1) a modular field data system
(Ball Brothers Research Corporation Model 700); (2) a 4.5-watt two channel
VHP band radio transceiver which is manually switchable (General Electric
Model PR-36-RCC-66) with attenna (Phelps Dodge Model 130-509); (3) a 12-
VDC rechargeable battery; (4) RAMOS hat-type radiation shields for tempera-
ture and relative humidity sensors; and C5) meteorological sensors and
signal conditioners.
The master stations consists of: (1) a minicomputer (Data General
Noval 1200) with 24 K core memory, real time clock, power fail option, and
auto program load option; (2) an ASR 33 teletype; (3) a nine track tape
transport (Wangco); a station clock registering days, hours, and minutes
(Chrono-Log); (4) a modem (Intertel Model 2026); and (5) a remote control
for voice transmission to remote stations (General Electric Model 549-AISI).
48
-------
Sensors were calibrated over their entire range in 10% increments.
Supplementary wind data was obtained with a portable station (Meteoro-
logical Research Incorporated Model 1072-2); additional temperature and
relative humidity data was obtained with hygrothermographs (Weather Measure
Model H302). Meteorological data is stored on magnetic tape or punch cards
and has been summarized monthly on an hourly basis (see Appendix J)
Air pollutionAt the telemetering stations at Camp Paivika, Sky
Forest, and Barton Flats, ozone was measured with ultraviolet photometers
(DASIBI Model 1003AH). Strip chart recorders were used to back up data
stored on magnetic tape. Total oxidant was measured at all other stations
by the Mast Model 724-2 and data was recorded on strip charts. The strip
chart records from both DASIBI and Mast instruments were key punched and
summarized by the hour for each month. Nitrogen dioxide and peroxyacetyl
nitrate (PAN) were measured at Sky Forest only. Nitrogen dioxide was
measured continuously, using Saltzman's reagent, with an Air Monitor IV
(Technicon Instrument Corporation). PAN was measured at 15 min intervals
by an automated Panalyzer 681 (Varian) with an electron capture detector.
Total oxidant data gathered prior to June, 1975, was based on the
former primary standard calibration procedure using buffered potassium
iodide. A recent revision (California ir Resources Board, DeMore Committee,
1974) for calibration of ozone sensing instruments suggested that a cor-
rection of all hourly ozone concentration data could be made by a multipli-
cation factor of 0.80. The former primary standard calibration procedure,
using buffered potassium iodide, was found to be 20% higher than ultra-
violet photometry, which has now been accepted as a valid primary (transfer)
standard in California. Thus, when total oxidant and ozone data for 1973
and 1974 appears separately all values should be approximately 20% less
than indicated. However, where total oxidant records for all years between
1968 and 1976 are compared, they have all been corrected to correspond
to the new calibration standard. The altitude correction factor was
calculated by dividing the larger pressure height (mb) at the calibration
laboratory by the smaller pressure height at each mountain station.
The N02 monitor was calibrated by the California Air Resources
Laboratory at El Monte and the Panalyzer was calibrated against a standard
available at the Statewide Air Pollution Research Center, Riverside (SAPRC).
Ozone and total oxidant concentrations are expressed as parts per million
by volume (ppm) and micrograms per cubic meter (yg/m^). The conversion is:
1 ppm = 1960 Ug/m3. Correspondence between ozone and total oxidant was com-
pared at Sky Forest. PAN and N02 are expressed as ppm only.
Location of Monitoring Stations
The biggest constraint in locating the monitoring stations was to
find a source of electricity near the 18 permanent vegetation plots. The
distribution of stations maintained from May through October (triangles,
Fig. 1) conforms to the general downwind air flow from the urban basin,
so that the gradient of oxidant concentration can be measured. Other
locations where total oxidant (Mast) was measured for periods shorter
than the May-October season include: UCC, CA, and HB (Fig. 1).
49
-------
Appendix J lists the inventory of air monitoring data.
Classification of Meteorological Patterns in Relation to Pollutant
Concentrations
The ozone data for this study were analysed using the time-averaging
method recommended by Larsen (1976). Daily average concentrations were
used. The 361 sample days from the May-October periods of 1974 and 1975
were classified using the predictors and discriminant analysis method
described by McCutchan and Schroeder (1973).
Surface windflow model designTo integrate the complexities of
terrain effects on surface flow, a mathematical wind model was formulated
by the Fire Meteorology Project (Ryan, 1974). The need for such a model
was intensified by the lack of meteorological observations in mountainous
areas. Thus, the model was designed to predict winds at remote locations
if only sky condition, 850-mb data, and terrain height were available for
input. If other data are available, the model is designed to incorporate
them.
The model design is based on the premise that mountain winds are
a result of the vectorial sum of component winds generated by several
different mechanisms and factors. These factors included valley-mountain
wind, slope wind, sea breeze, larger scale winds induced by pressure
gradient and the sheltering and diverting effect of the terrain.
Results and Discussion
Within Season Meteorological Patterns and Ozone Dose
Details describing the five meteorological patternsAn overview of
the 1974, 1975 summer seasons (Fig. 11) shows two common characteristics
relating to the distribution of the five classes of meteorological patterns,
First, both seasons began and ended with a high marine air throughout the
day. On such days, fog limited visibility to less than 20 m along moun-
tain ridges between 1600 and 2100 m elevation msl. The temperature
maximum on such days averaged 16 C and, there was considerable moisture
condensation on conifer tree foliage. Second, there was a higher fre-
quency of class 1 days from mid-September to late October. Class 1 days
are typified by the presence of hot, dry, continental air throughout the
day. The sky is usually cloudless and the strong Santa Ana winds often
persist throughout the day. The daily temperature maximum averages 26 C.
Class 2, 3, and 4 days dominate the period from early June through mid-
September. The specific differences of these types of summarized in
Table 5. Average daily temperature maxima for these days are 29, 26,
and 22 C, respectively. These days differ mainly in the degree to which
the moist marine air is modified as it flows inland and up the mountain
slopes.
The most frequent wind direction (mode) and accompanying wind
speed for each class of day is shown in Table 6. Camp Paivika and Barton
Flats are better sited stations than Sky Forest for wind measurements.
Winds during these 5 day classes have many common features; the only
distinct type is class I.
50
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Cumulative ozone dosesAt the Sky Forest monitoring station (1715 m,
msl), the end-of-season dose in 1974 was more severe than that in 1975
(Fig. 12). The bars show biweekly dose increments and also demonstrate
that the diminished dose of 1975 was fairly evenly distributed through all
of the biweekly intervals. Further evidence suggests that a substantial
difference in the frequency of the class 3 and 4 days throughout these
seasons can be postulated as the cause of the difference in cumulative
seasonal dose. The relationship between day class and concentration
(daily average) equaled or exceeded 50% of the time (geometric mean) at
Sky Forest is indicated in Table 7 . The geometric means for classes 1-
5 were 0.03, 0.09, 0.10, 0.09 and 0.06 ppm ozone, respectively, for the 361
days sampled at Sky Forest in 1974 and 1975.
Sequence of meteorological patterns and associated dosesA second way
to compare the effect of day-classes on ozone concentrations is to consider
the influence of all possible sequences of day-class changes, 25 combina-
tions in all. In Table 8, 13 of the possible 25 are included; the other
12 which occurred less than 1% of the time for the 361 sample days were
omitted from Table 8. Altogether, the 12 combinations omitted accounted
for only 6.8% of the total. The last column of Table 8 is the cumula-
tive ozone dose for the 24 hr of the second day of the combination. The
"3-3" combination, which was more prevalent in 1974 than in 1975, resulted
in one of the highest doses (2.09 ppm-hr). It appears that the "4-4"
and "3-3" combinations were key ones which regulated the cumulative sea-
sonal doses in 1974 and 1975 (Figs. 11, and 12). There were 22 more "4-
4" classes in 1975 than in 1974; but in 1974, there were 36 more "3-3"
classes than in 1975, resulting in higher 1974 cumulative dose.
Oxidant concentration trends during consecutive days of each pattern
A third way to evaluate the effect of transitional combinations is to
examine the number of consecutive days a single-day-class persisted and to
observe the trend of the 24-hr ozone average for each successive day of the
sequence (Fig. 13). Again, the class 3 and 4 days are prominent because
they did persist up to 10 days in each case, and the average daily ozone
concentration remained around 0.10 ppm during these sequences. Class 5
days persisted up to 9 days, but there was a certain decline in the ozone
concentration of each successive day. Class 1 and 2 days persisted up to
6 and 5 days, respectively, and both showed a downtrend in ozone concentra-
tions; there is some suggestion that the second and third days in a class
2 sequence may result in slightly higher daily ozone averages.
Pollutant Transport
Surface wind flow and oxidant concentrations during May through
October at three stationsThe averages of wind direction (expressed as
one of 16 compass points) and wind speed (km/hr) for selected daylight
hours is shown in Tables 9a, 9b> and 9C. In these tables, all meteoro-
logical patterns are combined. Before 1000 hr and after 1800 hr, oxidant
concentrations were always lower; thus, this 8 hr period represents the
worst case conditions. At all stations and in all months, the maximum
hourly average oxidant concentration occurred at around 1600 hr. This
was preceded at 1400 hr or was coincident with the highest average wind
speed for the day. At Camp Paivika the source of flow was S or SSE;
53
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TABLE 8 . FREQUENCY OF THE MOST COMMON TRANSITIONAL COMBINATIONS OF DAY
CLASSES OR METEOROLOGICAL PATTERNS AND RESULTANT OZONE DOSE.*
Transitional
combinations
4
3
5
2
3
4
4
5
1
2
3
2
4
4
3
5
2
4
5
3
4
1
3
2
4
2
1974
32
53
22
8
11
9
8
9
6
6
4
1
2
1975
54
17
22
16
8
9
8
7
9
6
6
4
2
Total
84
70
44
24
19
18
16
16
15
12
10
5
4
Percent Dose, second day
of of combination
total ppm-hrs = 0.03 ppm
23.
19.
12.
6.
5.
5.
4.
4.
4.
3.
2.
1.
1.
2
4
2
6
2
0
4
4
2
3
8
4
1
1.
2.
0.
1.
1.
1.
1.
1.
0.
2.
1.
1.
2.
76
09
78
88
90
50
77
42
38
10
80
31
20
*
The 12 remaining combinations of the possible 25 were excluded because
individually they occurred less than one percent of the time.
56
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Sky Forest was SSW or SWS; and Barton Flats was generally W. The effect
of terrain on flow is evident from the general configuration of ridges
and drainages shown in Figure 10, and as described below.
Pollutant penetration during days representing different meteoro-
logical classesContinuous ozone measurements for 1974 and 1975 from two
additional mountain stations (Snow Valley and Barton Flats) were compared
with those of Sky Forest (Fig. 10). Snow Valley is 12 km east and 346 m
higher than Sky Forest; the terrain resembles a shallow basin tilted slightly
to the west-southwest. The Sky Forest station is located on a south-
facing slope just below the crest of a smooth ridge top. Barton Flats
is 24 km east and 231 m higher than Sky Forest; it is situated on a north-
facing slope at 1946 m overlooking a prominent canyon which opens to the
west. The canyon bottom is about 230 m below and directly north. The
question of interest is whether certain meteorological patterns aid deeper
penetration of polluted air farther eastward and up to higher elevations in
the mountains.
A comparison of concentrations in the 50% column for the three stations
(i.e., the geometric means; see Table 7) showed that classes 2, 3, and 4
were equally effective at Snow Valley and that class 3 and 4 days were
most conducive to pollutant transport to Barton Flats. Station comparisons
in the 10% column showed that pollutant transport was most effective during
class 2 days at Barton Flats. Since class 2 days are the hottest, it is
possible that the up-canyon flow was much stronger on these days; thus,
higher concentrations of ozone penetrated farther eastward. The high
concentrations on class 4 days (10% column) may not be related to the late
afternoon surge of air flow but rather to the fact that the inversion base
is relatively high in the morning (approximately 1067 m) and oxidant
concentrations approaching 0.20 ppm can be detected by 0900 PST in lamina
above the inversion base (Edinger et al., 1974). The westerly wind com-
ponent soon delivers this polluted air to the forested mountains because
the elevation differential has been considerably diminished by this re-
latively high inversion base.
Modeling of surface wind flow and pollutant penetration on a class
4 dayThe detailed terrain effects on wind flow (Fig. 14) were computed
for a limited area (see Box, Fig. 15) by Ryan's model for 1300 PST on August
31, 1974. Detailed terrain effects on wind flow for the entire area
(Fig. 15) are not modeled because of lack of both terrain and wind data at
the present time.
The synoptic conditions on August 31 resemble a class 4 day with
generally high air pollution potential (McCutchan and Schroeder, 1973).
A surface thermal trough was over the desert, and a weak 500 mb trough was
just off the coast of southern California. Flow aloft was southwesterly,
and the sea breeze was strong from the southwest. The combined effect
produced a prevailing surface wind from the southwest with speeds near 6.7
m/sec (15 mph).
Sheltering of the fairly strong southwest flow resulting from the
59
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SURFACE ,/,,/,,/,,,, ///////////////////// . . -
WINDS AT ////-///;//////////////////////// -^/
1300 HRS 8/31
1974
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 9 17 25 33 41 49 57 65 73 81
GRID INTERVALS (X)
= 1.77 mm = 30mph = I3m/sec.
= x 20
DIRECTION OF FLOW
Figure 14. Surface wind fields generated from a computer model for
1300 hr PST, August 31, 1974, for a limited portion of the
study area (see caption in next figure).
60
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effects of terrain can be seen in several areas such as around grid point
X = 31, T = 61 and around X = 46, Y = 36. In these areas, the strong flow
is blocked by higher terrain up-wind. In contrast to these sheltered areas,
channels through which strong winds are allowed to flow are evident, such
as near grid point X = 16, Y = 66. Examples of directional change caused
by terrain effects are also displayed, e.g., at gridpoint X = 21, Y = 61.
Changes in wind direction are the result of three different terrain effects:
mechanical diversion, wind component produced by differential heating on
slopes, and wind component produced by differential heating in valleys.
Observed prevailing surface winds were south-to-southwest over the
entire area (Fig. 15). Variation from the prevailing direction owing to
terrain influence is evident at Converse. The east-west orientation of
Santa Ana Canyon is responsible for the west wind at Converse.
The hourly average of total oxidant concentrations at 1200, 1300, and
1400 hr (the hours before, during, and after wind observations) are indi-
cated in Figure 15, where monitoring stations were present. For example,
concentrations at Sky Forest were 235, 235, 353 yg/m^ for the three con-
secutive hours. The expected increases of concentrations to a daily
maximum sometime after 1400 (Tables 9a, 9b, and 9c) are evident at all six
monitoring stations. If detailed wind fields can be obtained with the
model for the whole mountain area, it will be possible to evaluate the
relationships of flow patterns and pollutant dispersion in relation to
forest vegetation injury.
Definition of the Oxidant Dose Gradient in the San Bernardino Mountains
Characterization of the west-to-east gradient of seasonal oxidant
dosesSeven ground stations were maintained from June through October,
1974, along a west-to-east transect. These stations can be located by
intersection on the scales superimposed above the topographic projection
of the San Bernardino Mountains (Fig. 16). The cumulative monthly doses
presented in Figure do not include data from every hour possible during
each month because of intermittent instrument failure. On the average,
at least 90% of the data are available. Since 1974 was one of the most
severe air pollution years on record (Fig. ), these data probably
represent an overestimate of the average doses along this gradient in
previous years.
As we have suggested from data in Figures 14, and 15, terrain is the
likely cause of the rapid decline in dose between Sky Forest (SF) and
Snow Valley (SV) because the elevation gradually increases from 1661 m
(5,450 ft) to 2052 m (6,750 ft). The slight dose increase at Big Bear
Dam (BED) occurs because the monitoring station is in a notch which
channels air flow at the top of a major canyon leading up from the basin.
The terrain along the interval between BBD and the Big Bear Air Pollution
Control District (BBAPCD) is primarily lake surface. Barton Flats (BF)
monitoring station is located on the forested north slope of the Santa
Ana River drainage and is exposed to the unimpeded afternoon up-canyon
flow of polluted air. The information in Figure 16 does not adequately
represent the complete eastward extent of pollutant transport in the mixed
conifer forest which is necessary to fully define the dose gradient. Also,
62
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the western part of the transect generally overlooks the basin, and additional
data must be otained by placing stations in a south-to-north configuration.
> o
In Figure 17, the total hours with oxidant concentration - 157 Hg/m , the
Federal Standard, are separated into day and night-time hours for August,
September, and October, 1974. It is readily apparent that the western, lower
elevation monitoring stations receive more night-time hours when oxidant
concentrations exceeded 157 yg/m , especially at Camp Paivika. The greater
oxidant concentration at night may be associated with the nocturnal position
of the inversion layer which acts as a reservoir for oxidant (Edinger, 1973).
The west-to-east gradient of decreasing oxidant dose is plainly evident in
this analysis, as well as in Figure 16.
The time averaging analysis (Larsen, 1973) was also used to compare
these stations in 1974. The geometric means were as follows: CP = 0.075;
SF = 0.068; RS = 0.049; SV = 0.045; BED = 0.055; BBAPCD = 0.034; BF =
0.045. These numbers should be rounded off to two decimal places.
Comparative daily maximum hourly averages for ozone, total oxidant,
PAN, and N07 at Sky Forest, August 1974Daily concentrations of ozone and
total oxidant for August 1974 closely mimic one another (Fig. 18). Except
for one day (August 8) data from the DASIBI ultraviolet spectrophotometer,
which measures ozone specifically, were always lower than the Mast KI
instrument, which responds to other oxidants. It is important to observe
that ozone is a good surrogate for total oxidant measurement; in addition,
it is the most important pollutant causing injury to conifers. Because
August is usually one of the more severe months for pollution, this record
probably displays one of the highest frequencies of air pollution episodes
to be expected in the mountain area, especially in 1974, (See Fig. 16).
PAN concentrations were sufficient to cause injury to common herbaceous
plants frequently used in laboratory studies, but PAN symptoms were not
distinguished from ozone symptoms on nearby herb layer plant species.
Nitrogen dioxide remained at low, probably nonphytotoxic, concentrations
compared to the other oxidants.
Comparative hourly concentrations of total oxidant, NC^ and PANA
comparison of total oxidant at SF, BB, and BF, with winds at SF and Big Bear
Ranger Station during two days in October, 1973 (Fig. 19), shows that total
oxidants may peak out later at more distant stations (October 18) or nearly
simultaneously (October 19). The stronger winds on the 19th may have
caused the more uniform peaking time. At SF, PAN peaks later than total
oxidant. Nitrogen dioxide has a very small peak around 0800 hr and a
slightly larger one at from 2000 to 2100 hr PST.
Air Quality Standards and Historical Trends in Oxidant Concentrations and
Seasonal Doses
One acceptable way of identifying trends in air pollution doses is to
compare the number of days or total hours each year when concentrations
exceed some threshold higher than the Federal Standard (160 ]Jg/m ). At the
selected threshold, human health and welfare is imperiled, especially because
the daily peak oxidant concentration on these days can reach up to 1176
^ (0.60 ppm). Local communities and both State and Federal agencies have
64
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65
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45
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I 0-
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-TOTAL OXIDANT (pphm ),KI,MAST
OZONE(pphm) UV, DASIBI
TELEMETRY, ONCE HOURLY
PAN (ppb) G.C..ELECTRON
VV CAPVURE
SALTZMAN
N02 (pphm)TECHNlCON IV
24 68 10 12 14 16 18 20 22 24 26 28 30
DAYS
Figure 18. Comparative daily maximum hourly averages for ozone, total
oxidant, PAN and N02 at Sky Forest, August 1974. (For
absolute values, oxidant concentrations might be multiplied
by 0.8 to comply with a new calibration procedure, Pitts,
_et al., 1976)
adopted different threshold values to signify adverse effects. The State
of California employs several descriptive thresholds, one being 392 yg/m3
(0.20 ppm), to identify the frequency of air pollution episodes or periods of
sustained high concentrations of atmospheric pollutants.
Concentrations at San Bernardino and Rim Forest/Sky ForestData from
the mountain station at RF/SF were compared with published data from the
San Bernardino County APCD in terms of the number of hours during which total
oxidant concentration exceeded 392 yg/m3 (0.20 ppm) during July, August,
and September from 1968 to 1974, when both stations operated. From 1963
to 1967, data are available only from the San Bernardino APCD station Air
Resources Board (1973). A large part of the year-to-year differences at
the same station and between stations can be attributed to differences in
1972, 1973, and 1974, at RF/SF (Fig. 20) are associated with 6, 16, and 46
days, respectively, when a persistent 500 mb high pressure system (class
66
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3 and 4 type days, Table 5) occurred over the southwest, particularly
over southern California. The difference between stations in the same year
is probably influenced most by inversion height. Lower inversion heights
would partially restrain transport upslope to shorter periods daily.
Higher inversions mean longer periods of upslope flow and, in addition, allow
a greater air volume below to dilute oxidants. The index for comparison
chosen in Figure 20, i.e., hours with total oxidant concentration ^ 392
yg/m^, should be largely determined by inversion height. The three-year
moving averages for each station tend to remove some of the variation due
to higher frequency fluctuations. In terms of hours with total oxidant
concentration (^ 392 Hg/m^) , the moving average between 1970 and 1973 at SF/
RF increased from 175 to 290 hr. This trend is the reverse of that in
upwind, urban Los Angeles County, where increased emissions of NO (nitric
oxide in fresh auto exhaust) tend to shift the chemical equilibrium to the
left towards the ozone precursors in the chemical reaction which produces
ozone.
Seasonal dose at Rim Forest/Sky Forest 1968-1976A second method of
documenting trends of oxidant levels during the 1968 to mid-1976 period at
RF/SF expresses the accumulated dose (ug/m^-hr) including concentrations
for June through September (Fig. 21). This period represents the main part
of the growing season; however, doses during the remaining months of the
year are also being measured at this station. These doses exclude hourly
concentrations = the background concentration of 59 Ug/m^ (0.03 ppm) ,
as reported by Gloria e_t al. (1974) . The percent of valid data recovered
is also indicated. The absence of some data, up to as much as 18% in 1970,
but averaging 8.3% during the seven years, persents a margin of error that
cannot presently be adjusted with any certainty. Future analysis of past
meteorological data may permit some adjustments to be made. The percent
of the total possible hours for which data could be obtained for each month
during the June through September period is also indicated.
The most recent predictions suggest that oxidant doses will either
increase annually or oscillate around the mean of present high levels in
the foreseeable future at these distant locations unless dramatic improve-
ments are made in control strategies (Corn e_t al. , 1975; Blumenthal et al. ,
1974).
68
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DEFINITION OF THE CONIFER FOREST ECOSYSTEM AS A GROUP OF COUPLED ECOLOGICAL
MODELS
Introduction
Background and Project Objectives
Ecosystems are defined as units dependent upon (1) energy and moisture
flowing through them and (2) minerals cycling within them; as a result (3)
vegetation reproduces, grows, and dies, supporting (4) a diversity of
animal life, some of which feeds on vegetation and some of which feeds on
other animals. In ecosystems, (5) dead organic matter accumulates and (6)
organisms decompose it to make minerals and space available for the next
generation (Odum, 1971). At any given time, some organisms are more
dominant than others in the ecosystem processes listed above as (3), (4),
(5), and (6).
As time passes, these patterns of dominance go through a gradual change;
in fact, the subject of ecological succession has received considerable
study (Knapp, 1974). After a disturbance occurs in an ecosystem, time is
set back, and the sequential patterns of dominance begin to occur again.
In some cases, the nature of the disturbance may lead to a different
sequential pattern of dominant plants and animals than the sequence pre-
vailing before the disturbance. For example, an alteration of the natural
accumulation, and/or decomposition, rates of dead organic matter may con-
tribute to changes in the dominance patterns of vegetation and wildlife
communities.
Several investigators are studying selected problems within this
variety of processes in the laboratory and field as the first step in the
hierarchy of project objectives (Fig. 22, bottom). These objectives center
on applying methods of systems analysis and computer simulation modeling
in the following areas: (1) developing models for forecasting ecological
effects of photochemical air pollutants in southern California mixed conifer
forest ecosystems; (2) evaluating the adaptability of these systems models
to other pollutant and forest types; and (3) evaluating the predicted
consequences of photochemical air pollutants in forest ecosystems on
human welfare.
Studies of the processes carried out by components of ecosystems are
necessary to determine and quantify direct oxidant effects as well as
biological effects resulting from simultaneous occurrence of oxidants,
drought, and insects and plant diseases. These analyses are necessary to
assemble our understanding of various processes into a set of quantitative
computer models. With such models, we plan to forecast the various possible
alternative futures for the ecosystems in the San Bernardino National
71
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Evaluate the effect of ambient photochemical
oxidant air pollution on a complex mixed
conifer forest ecosystem
Evaluate predicted consequences
of photochemical oxidants on
the forest ecosystems in terms
of human welfare effects*
1
Develop systems models for
prediction of future conditions
Evaluate adaptability of
systems models to other
pollutant types and other
forest types
I
Evaluate direct impacts
of photochemical oxidants
on major components of a
forest ecosystem
LJ
1
Assess interactive
effects
Ecosystem component
process studies
". . .includes, but is not limited to, effects on soils, water, crops,
vegetation, man-made vaterials, animals, wildlife, weather, visibility,
and climate, damage to and deterioration of property, and hazards to
transportation, as well as effects on economic values and on personal
comfort and well-being."
Source: Clean Air Act 1970, Section 302 (h).
Figure 22. Objectives for the study of effects of ambient oxidant
pollutants on mixed conifer forest ecosystems.
72
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Forest (SBNF) (Fig. 22, middle). Scientists do not expect to be able to
make absolute predictions since too many qualifying conditions (e.g., the
future use rate of the internal combustion engine, and its possible
technological modifications; future weather conditions) cannot be predicted
with certainty. Instead, we can forecast various possible alternative
futures for the forest ecosystems by postulating sets of alternative, hypo-
thetical qualifying conditions, and seeing how the set of computer simula-
tion models responds to them.
For example, one set of possible future conditions might assume twice
the 1974 annual oxidant dose with a three- or four-year wet-weather
pattern of either 1 1/2 times or 1/2 the normal rainfall. We would then
determine how the simulated forest system behaves on the computer. Of
course, there is no guarantee that real forests will respond as computer
models do, but given the options of using informal, intuitive guesswork
on the part of individual specialists, or a synthesis of current scientific
understanding of the processes which control whatever future forest con-
ditions actually will occur, we prefer the latter.
Purposes for Building Computer Simulation Models of Ecosystem Level
Response to Photochemical Air Pollutants
Anticipating effects of possible futuresThe types of ecosystem
forecasts sought from using the computer models must evaluate likely con-
sequences in terms of "human welfare effects" (Fig. 22, top). This is
a vague expression from a systems analysis viewpoint, but it is defined
in section 302(h) of the Clean Air Act, (Environmental Protection Agency,
1970):
"All language referring to effects on welfare includes, but is not
limited to, effects on soils, water, crops, vegetation, man-made
materials, animals, wildlife, weather, visibility, and climate,
damage to and deterioration of property, and hazards to transpor-
tation, as well as effects on economic values and on personal com-
fort and well-being."
We expect losses in the form of vegetative production decreases and
(2) shifts in the balance of species abundance in forest ecosystems under
oxidant air pollution stress. Nevertheless, one of the ultimate questions
to "ask" forest ecosystem simulation models in order to evaluate conse-
quences in terms of human welfare effects concerns ecosystem irreversi-
bility. Is there some level of oxidant air pollution, in some time and
space definition, at which irreversibility in forest stand succession
patterns occurs? Further can oxidant air pollutants affect the resilience
limits of terrestrial ecosystems? In particular, is the detection of such
irreversibility possible within one human lifetime (e.g., between 1950,
when photochemical air pollution is believed to have begun its chronic
rise above natural background levels in the South Coast Air Basin, to
2000)?
In terms of the possible range of air quality conditions from now
to the year 2000, one possibility could be a worsening of air quality in
the SBNF by some factor 2, 3, or 4 times that at present. Under such an
73
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extreme, we might expect changes in the life forms of dominant vegetation
to occur; as this was suggested by Woodwell's (1970) studies on the effects
of gamma radiation. The other theoretical extreme, however, is that the
present air pollution trend could be reduced by virtually 100% at some time
within the next 25 years. The question of irreversibility asks (1) if this
reduction occurs through political and technological procedures, and (2) if
air pollution stress on forest ecosystems is removed (at inevitably high
costs), might these ecosystems re-establish their pre-stress species
composition after a period of readjustment? In other words, can oxidant
air pollutants affect the renewability of mixed conifer forest ecosystems?
General assumptions being examinedThe exploration and evaluation of
two assumptions are the goals of this investigation. The first is to
construct an ecosystem-level interpretation for stress induced by oxidant
air pollution; the second is to apply analysis and forecasting methods.
Ecological systems under stressCombinations of non-biological stresses
lead to changes in the natural frequency of periodic biological stresses
such as insect epidemics and disease epidemics. These non-biological
stresses include, increases in ground-level concentration of photochemical
oxidants, changes in natural fire frequency distribution, changes in the
frequency and intensity of timber removal, and various intensities of
meteorological drought. As a result of these stresses, sequences of
ecologically dominant vegetation undergo changes not likely to reverse
naturally, even after the removal of any single non-biological stress.
Benefits of systems analysis approachTo conduct this study, we feel
that a systems analysis and simulation modeling approach will provide
participating scientists with a means of: (1) clarifying their concept
definitions and explicitly exposing their assumptions which ordinarily
would remain hidden; (2) clarifying relationships between system components;
(3) collating a number of different scientists' data sets; (4) considering
a larger set of interrelated ecological variables than any single investi-
gator can observe in the field; and (5) comparing similarly structured
systems, e.g. from different field plots, having different rates of
change.
Simulation models can provide government agencies responsible for
air quality and forest resources management with means of: (1) fore-
casting some likely responses of ecosystem properties (species composition,
timber yield, community stability, or resilience) to possible air quality
trends, forest resource harvesting methods, and other environmental
stresses; (2) extending the range of relevance of a set of field investi-
gations to other sites and other years (see Fig. 22, middle); (3)
educating resource management personnel about possible consequences of
alternative air quality and forest-management strategies through simulation-
gaming. The usefulness of simulation-gaming for resource management
personnel was treated by Rolling and Chambers (1973) and Biswas (1975) .
Literature Review
Evidence Supporting the Ecosystem Stress Interpretation
74
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Koenig and Tummala (1972) defined a concept involving three eco-
system states based on relative pollutant levels. The first of these is
nonpollution. This state exists when pollutants do not affect the ecosystem
state's capacity to meet the. criteria of an "environmental quality region."
We define an "environmental quality region" as a concept defined in terms
of ecological state space, where "locations" define the region's capability
for a set of resource uses by man. Woodwell (1975) refuted the existence
of an ecosystem's assimilative capacity, even though Smith (1974) also
advanced the concept.
A second state is reversible pollution. This occurs when the input rate
of pollutant stress causes the ecosystem's temporary failure to meet the
criteria which define an environmental quality region. However, when the
stress is removed or neutralized by another counteractive stress, the eco-
system reverts to its original quality.
The third state is nonreversible pollution. In this state, pollutant
stress causes the ecosystem's complete failure to meet the criteria which
define an environmental quality region. In this case, the system remains
at this inferior level even after subsequent reduction of pollutant
stimuli.
Deficiencies in present terrestrial ecosystem stress-response theory
Woodwell (1970) defined the general sequence of the elimination of vegeta-
tive life forms from an eastern oak-pine forest. He utilized a spatial
gradient of increasing exposure to gamma radiation, which first affected
trees, then shrubs, herbs and, finally, low-growing cushion plants. He
concluded that this sequence was the typical pattern to be expected from
chronic exposures to serious environmental stresses. Woodwell's general-
ization, however, may not apply to either this project's aims or to the
nature of California mixed conifer forests under oxidant air pollutant
stress. This is because certain discrepancies become apparent regarding
the perturbation inputs to the system and the system's stress response.
Relation between effects and chronic vs. acute exposureThe differences
between chronic and acute exposure and effect, may relate to the source
of stress. Woodwell claims that the pattern of vegetation response was
evident after only six months' exposure to gamma radiation; compared to
other environmental perturbations, the immediacy of this system response
could be categorized as acute.
Effect of possible receptor feedback controlBoth gamma radiation
injury and air pollutant injury to plants are controlled by internal
physiological mechanisms which vary with stage of plant development and
associated environmental stresses. The mechanisms governing sensitivity
to these stresses are different. The dose of gamma radiation was constant
in Woodwell's (1970) experiment, but air pollutant dose in nature varies
greatly with time. In adlition, the mechanism controlling pollutant
sensitivity, i.e., transpiration (Mukammal, 1965), may be coupled more
strongly to environment than that controlling radiation sensitivity, i.e.,
rate of cell division. The daily regulation of transpiration and varying
oxidant air pollutant doses lead one to expect longer time lags between
75
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episodes of pollutant absorption by vegetation and the detectability of
resultant injury compared to Woodwell's (1970) gamma radiation study. The
dose-response behavior characteristic of pollutant-injured plants suggests
that a feed back control mechanism may be operative in SBNF vegetation. We
need to know how much pollutant, for a given time, will cause various degrees
of growth reduction by age class. We also need this data between, as well
as within, species of a plant community.
Ecosystem response under multiple stressesA longer time lag may allow
additional perturbation inputs to arise in the system. During the study
period reported by Woodwell in the gamma-radiated forest, no other physical
or biological mortality agents were reported to have been imposed on the
forest ecosystem. This may be cause, in the forest, gamma radiation is a
more direct mortality agent than oxidant air pollutants, which reduce
growth rate and overall vigor, enabling other mortality agents to become
active among larger tree size classes. Woodwell does not suggest that the
causes of observed mortality zones were triggered by another mortality
agent during increased weakening of the various life forms by gamma radia-
tion; thus, we must assume that his mortality sequence was simply gamma
radiation which killed vegetation.
Under these circumstances, it is questionable that results from the
gamma radiation study are similar to responses expected from other forest
ecosystems under different types of stresses. In this study of the SBNF,
we looked at possible effects from meteorological drought, plant disease,
insect outbreaks, fire, and timber harvesting practices concurrent with the
stress induced from oxidant air pollution. Levin (1975) stated that " . .
.if stability is measured relative to the set of perturbations to which
the system is normally exposed (a variable criterion by which different
systems are compared with respect to different perturbation sets), then
such systems show up as more stable" (Italics and parentheses are Levin's).
Rank of species sensitivity and type of stressWoodwell (1970) does not
deal with evidence that ranking inter-species sensitivities to one stress-
inducing agent (e.g., oxidant air pollutants) (Miller, 1973) is often
different from that species' order of sensitivity to other stress agents
(e.g., plant diseases, herbivorous insects, or fire) (Wellner, 1970;
Kilgore, 1973).
Response after stress removalWoodwell's reports (1970, 1975) say
nothing about the degree of reversibility (see above, p 75) after the stress
agent has been removed. It seems more than fair to challenge Woodwell's
claim, based only on his experience with gamma radiation, for the general
applicability of his prognosis for ecosystem response to pollutants. The
kind of responses and their permanence in conifer forests chronically
exposed to oxidant pollutants are yet to be defined.
Empirical Evidence
Ecological literature is comprised of both descriptive natural history
and theoretical analyses whose applicability to real world ecosystems is
questionable. Documentary evidence is not available on the irreversibility
hypothesis, although one finds the question raised frequently in the
76
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research literature (Koenig and Tumala, 1972; Holling, 1974; Edmonds and
Sollins, 1974). Bryson and Wendland (1970) claimed that India's arid lands
resulted from defoliation and elimination of vegetation which in turn induced
local climatic changes not conducive to re-establishing the original vege-
tation. Charney et al. (1975) provided evidence for a similar positive
feedback for the Sahara. Glendening (1952) has shown that defoliation stress
due to grazing intensity, which then enables tree establishment, will not
allow the ecosystem to revert to its previous condition even after stress
removal. Holling (1974) discussed evidence of aquatic ecosystems which
fail to rejuvenate when stresses are removed. Habeck and Mutch (1973)
discussed the likelihood that forest fuel accumulations are so great now
because the natural fire frequency has been lowered through fire protection
programs, that if these ecosystems were subjected to uncontrolled fire, the
heat intensity would be far greater than that to which the systems are
evolutionarily adapted. La Chapelle (1967) reported on management attempts
to reverse the otherwise irreversible changes in Austrian sub-alpine
timberline forest equilibrium resulting from previous logging and grazing
activity; these activities have caused a higher frequency of snow avalanche
perturbations in this forest ecosystem.
Evidence Supporting the Usefulness and Necessity of Computer Modeling of
Ecological Systems
Conceptual and developmental usefulness for project participantsInnis
(1973) defines three stages of usefulness in applying systems modeling
methods to environmental research. Conceptual utility is derived from the
integrated frame of reference provided by an explicity model, or a set of
interconnected submodels. Developmental utility is the usefulness of the
ideas acquired by the team of modeler and field biologists when they assemble
the various functional hypotheses comprising a simulation model. A large
amount of the published literature on ecological systems simulation is
methodology that describes in detail how parts of the system model were con-
structed, but not what was done with the model after construction.
Experimental reports are rare which explain the discoveries made by using
the simulator at the ecosystem level. The discoveries, themselves, are
accompanied by evidence in the form of displays of simulation experiment
results. Both the National Academy of Science (1974) and the National
Science Board (1972) provided some evidence of the conceptual and develop-
mental utility of computer simulation modeling in ecosystem research. An
interesting discussion of the value to scientists and non-scientists of
explicitly exposing assumptions used to construct a simulator appeared
in Yorke's discussion in Boling and Van Sickle (1975). Wiegert (1975)
demonstrated the clarification of relationship among system components
which occurs when working with a simulator. The fact is that using the
simulator offers the ability to consider a larger set of ecological
variables than any single investigator can observe, and allows collation
of various specialists' data sets. A comparison of the team interdisci-
plinary report by Van Dyne (1972) with the very disciplinary papers in
Fries (1974) reveals the difference in levels of system component inte-
gration.
Usefulness exported to non-participantsOutput utility is the set of
data from the computer model performance which is somewhat useful to people
77
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not directly involved in the model development. Innis attributed the current
relative sparsity of published evidence for output usefulness of ecological
simulators to their dependence on a more limited data base than comparable
quantitative relations in the physical sciences. Biswas (1975) also presented
some reasons and remedies for system simulators' not being used more fre-
quently for environmental management decision-making. An example of one
type of output utility forecasting of ecosystem responses to trends in
environmental stresses is found in Giese et al. (1975) ; this type is
central to the objectives of this study (Fig. 22).
Another output utility extending the range of relevance of investi-
gations to other locations and/or other years was discussed by Goodall
(1972). This purpose is shown in the hierarchy of project objectives
(Fig. 22), and may be a crucial one. To the extent that system simulators
developed for the SBNF can be applied to coniferous forests elsewhere in
the western states for making comparative projectives on a geographic scale,
we may be able to avoid having this study treated by others simply as an
isolated case study for one particular location.
Methods of the System Model Design and Development Process
To design computer simulation models which mimic each subsystem, the
project investigators progressed through a sequence of stages for planning,
development, and application of systems models (Fig. 23).
After the field monitoring design was established, the investigators
explored conceptual models describing the ecosystems (Taylor, 1974), In
January, 1975, a system ecologist was added to the project to organize and
coordinate the systems modeling effort.
The process of model construction is planned to evolve into a modified
form of the "model-oriented, computer-assisted conferencing system" (Kupper-
man, Wilcox, and Smith, 1975). Two of the principal investigators are
located at the University of California, Riverside, and nine are at the
University of California, Berkeley. During modeling sessions, a portable
computer terminal is carried around for on-line access to a computer center
time-sharing system.
Defining Goals for the Eventual Use of System Simulators
With respect to the stages of modeling (Fig. 23), definition of fore-
casting goals for the overriding project problem is a critical starting
point (Giles, 1972). Two of the objectives (Fig. 22) are to evaluate (1)
"the adaptability of these systems models to other pollutant and forest
types," and (2) the "consequences of photochemical air pollutants in forest
ecosystems on human welfare" (see above p. 72). Thus, we must ascertain
that the simulators developed are not customized too exclusively for fore-
casting conditions unique to the SBNF; they must also be applicable to other
similar forest types in the Sierras and elsewhere. Table 10 indicates
how various land-use policies for other forests may affect the kind of
forest conditions for which we might want forecasts, based on possible
future air quality environments.
78
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Model Planning
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GOAL DEFINITIONS ]
INTERACTION
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Model
FLOW PARADIGM
TIME-SPACE
RESOLUTION
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SENSITIVITY
ANALYSIS
Figure 23. The system simulation modeling process.
80
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We needed to know what kinds of questions the set of system simulation
models would be expected to provide answers for, regarding possible future
forest conditions. Knowing these would allow examination of the ecosystem-
irreversibility question discussed above (pp.73,75). Our immediate question
was what might be the effects of various changes in photochemical oxidant
air pollutant trends over the next 50 to 100 years, as expressed by (1)
number of dead trees per hectare; (2) rate of change in tree species
composition for ponderosa and Jeffrey pine. In addition, as a consequence
of these two items, we needed to know what vegetation (trees, shrubs,
grasses) was likely to maintain or establish an ecologically dominant role
in various plant communities now recognized within the California mixed
conifer forest type.
Organizaing Subject-Matter Specialists' Ideas into Models
Our next step (Fig. 23) was to construct interaction tables showing
which variables were involved in the various subsystems and decide whether
the interaction between any two variables was positive or negative, with
an accelerating or decelerating effect. A previous Task D Report (Taylor,
1974) containing various types of interaction diagrams was helpful here.
Next (Fig. 23), we had to select the appropriate paradigm for the
substances flowing through the various subsystems: a discussion of various
paradigms appeared in Noy-Meir (1973). Possible flows are energy, water,
mineral nutrients, biomass, population densities, number of taxonomic
species, and area occupied per biotic unit, among others.
Ecosystems can be defined at various spatial scales and for various
time scales. In this project, ecosystem simulators are planned for the
forest stand-community level. The stand-community ecosystem model may
simulate a time period of 50 to 100 years at annual intervals.
Published simulation models (Fig. 23) for ecological systems were
reviewed and evaluated to expand upon others' work wherever possible. We
used the University of California Center for Information Services (CIS)
continually for literature searches in the Cataloging and Indexing System
(CAIN) for agriculture; in addition, we used Biological Abstracts (BA) and
the Bio-Research Index. Some existing models which we modified for sub-
system simulation are indicated below. Flow charts graphic represen-
tations of subsystem model structures were defined, and are being
translated into computer code.
Model Quantification and Evaluation Activities Dependent on Availability
of a Computerized Data Management System
Any thorough attempt to study a particular ecosystem will generate
large amounts of diverse and highly structured data which need to be
collected and stored efficiently. In general the data depend on both the
intrinsic properties of the process being measured and the sampling
technique employed. A computer processing procedure seemed advisable
to handle the large volume of field data we expected to collect.
The types of field data we are collecting can be subdivided into six
broad study information classes: meteorological-pollutant dose; vegetation;
81
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arthropods; soils; pathogens; and wildlife. Each of these can be subdivided
further into the particular type of data being collected; for example,
vegetation information is composed of six different data types. Thus, the
data's hierarchical structure mimics that of the SBNF itself.
To process the volume of extremely varied data for the SBNF study, a
three year interagency agreement between the Environmental Protection Agency
and the Lawrence Livermore Laboratory was initiated on January 1, 1974, for
designing and implementing a data management system. The purpose of this
system was to collect, store, and process data efficiently and then use it
in various subsystem models (Fig. 23). The system ultimately designed for
this study is divided into three general sections: data capture, data
banking, and data manipulation.
Data captureData capture is a collection of techniques used to
convert field data into a format suitable for computer storage. Because of
the variability in the types of field data being collected, no single data
capture scheme can satisfy all field researchers. Therefore, the data cap-
ture system should be general enough to accept diverse types of data,
which then assumes the dominant role in establishing formats required for
entry into the computer system. Once the data are in an acceptable form,
they will be stored in a data bank.
The data bankThe data banking system used was designed for the
Lawrence Livermore Laboratory, and is called "Master Control" (Hampel and
Ramus, 1975). This program was designed to unify storage, and to manipu-
late, reorganize, retrieve, and display data from dissimilar data bases. It
is open-end and user-oriented. Some of its characteristics include:
packed memory allocation; hierarchical ordering; using pointers for random
access; a telegram-like command language; and options to interrogate and
BASIC DESIGN PHILOSOPHY OF MASTER CONTROL
UNDEFINED
BASIC
PROGRAM
DEFINITION
OF ARRAYS
LISTER.ETC
-USER
DEFINITION
OF ARRAYS
LISTER.ETC.
Figure 24. Basic design philosophy of "Master Control'
82
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METEOROLOGY
VEGETATION
ARTHROPODS
SOILS
PATHOGENS
WILDLIFE
DATA
CAPTURE
DATA
CAPTURE
DATA
CAPTURE
DATA
CAPTURE
DATA
CAPTURE
DATA
CAPTURE
/
v -
MASTER
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MET
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7
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'
^ /
^ /
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Figure 25. The San Bernardino Data Management System.
manipulate data bases in both batch or time-share modes. Master Control
allows progressive adaptation of data bases to contemporary needs (Fig. 24)
Initially each of the six main field data classes will have its own
data bank created by Master Control. Processed field data received from
the data capture routines will be stored in each of these banks. Using
general command language, we can construct Master Control's new data banks
which will reflect user needs (Fig. 25). The command language itself
consists of ten general operations: (1) define, (2) initialization,
(3) generation, (4) construction, (5) file transfer, (6) alter, (7) edit,
(8) search, (9) numerical operations, and (10) macro-operations. Work
on applying Master Control to the SBNF study began in April, 1975.
To use the data banking system effectively, it is necessary to pro-
vide the user (the modeler(s) or subsystem investigators) with a library
of numerical, statistical, and graphical techniques.
Data manipulationThe data manipulation facility of this system
83
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contains a library of operational programs which can be used to analyze
parts of the data in any given data bank. This facility will reflect
the desires indicated by modeling activity, and along with the commands
available in Master Control, will provide modeling activity with a method
of obtaining data for input into various model development activities.
There are a variety of approaches to designing ecological system models
(Jeffers, 1973; Mar, 1974). As a consequence of the diversity in the
state-of-the-art, and since field data for this project are being collected
on four different classes of observations (nominal, ordinal, interval, and
ratio scale), the specific data manipulation procedures have not yet been
defined. In general, they will comprise three separate categories of
computer programs (Bridges, 1974): (1) graphic display procedures to
visually examine graphic plots, spatial maps, response surfaces, and
tabularization of observations from field sites and computer model be-
havior; (2) statistical procedures for use in model design and sub-
sequent model evaluation against the actual landscape ecosystems; and (3)
ecological subject data procedures which transcend conventional statistical
methods and provide computer analysis capability for analyzing climate,
population, biological community, and for calculating ecosystem indices
such as species diversity.
Results and Discussion
Progress for this project is described according to the sequence of
steps in the simulation modeling process (Fig. 23). Results of this
research consist primarily of numerous decisions made while pursuing the
three general objectives mentioned above (see "Introduction"). It is still
too early to treat results of actual computer experiments using the
forest system simulation models.
Progress in the development of this project's simulation modeling
process has been governed by several constraints. The principal problem
is that a systems modeler was added to the project in January, 1975,
whereas the study design and data collection were initiated in 1973. This
reverses the most advantageous sequence of events for this type of study;
thus it was necessary to attempt to accommodate pre-existing activities to
a workable modeling strategy. Specific attention to this task was limited
further by a delay in employing a qualified assistant and by limited
available office space in which two people could not work efficiently
simultaneously. A reliable solution to the office space problem is being
sought. Finally, the prime editorial responsibilities for the 1974-75
annual progress report consumed several months. From June through
December, 1975, groups of investigators from nine subprojects met for
modeling discussions. These meetings helped determine which environmental
variables and relationships could be used to structure a model for the
various observational and experimental studies being conducted within the
entire project. The period from January 1976 to June 1976 was spent
synthesizing the information obtained during the previous six months into
flow charts for different model subsystems corresponding to the various
subprojects. In addition, missing conceptual links between subprojects
were corrected as they were revealed in the model discussion sessions.
84
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Hierarchy of Research Problems as Motivating Goals for the Development of
Subsystem Simulators
Relations among problems being explored by systems modelingFrom a
system viewpoint, some research questions exist above the level of any indi-
vidual subproject. Such overriding problems must be defined and resolved
operationally into a hierarchy of sub-level problems. These, in turn, must
correspond to the individual subprojects and their specific objectives.
Figure 26 shows the hierarchical structure of problems for the entire
project.
In a model such as the one we are developing, the solution of high-
level problems depends on the solution of lower-level component problems.
This can be interpreted in at least two ways. Any given problem in Figure
can be explored through systems simulation only if the next lower level
problem is also explored. In addition, any process can be simulated on
the computer only if the indicated next lower-level process is simulated.
Logical dependency (strategy) is seen from the top down, while tactical
operations for time scheduling of research proceed from the bottom up.
This explains why the overriding air pollution effects problem cannot be
interpreted until after the component subordinate problems have been solved.
Problem Goals, System Model Complexity, and Three Properties of all
Simulation Models
If the overriding problems above all other individual subprojects
are to be evaluated (general objective number 3 of the Simulation Modeling
subproject), the submodels for all subprojects should be planned at the
outset to be dynamically linkable during execution on the computer. It
is assumed that this entire project evolved by the conscious direction of
the participating research investigators into eleven subprojects. Some of
these include investigations so diverse that they actually cover more
phenomena than can reasonably be identified as a single subsystem. Such
a linking of submodels, in terms of computer programs developed to represent
each submodel, becomes a necessary condition for the modeling approach.
We are not attempting to define such a complete, comprehensive, large-
scale ecosystem model as many of the biome programs of the U.S. portion
of the International Biological Program tried (Mitchell _et_ al^. , 1976;
Boffey, 1976). Rather, our approach emphasizes selected components or
processes of the ecosystem which biological specialists define as the
most critical to analyzing the transfer of air pollution effects through
the forest system. Our model structure is oriented neither toward trophic
levels nor energy flow, but is rather a selected food-web structure based
on population dynamics paradigms. We use a compartment model approach,
where each compartment is usually a population density except in four
cases: the water budget subsystem; the litter subsystem (biomass, and
percent substrate colonized by fungi); the tree growth subsystem (biomass);
and the pathogenic fungi subsystems (percent substrate colonized). Flows
between compartments are controlled deterministically by processes, except
in the cone production, seedling establishment, and bark beetle subsystem.
Part of the end product will be a set of smaller-scale component models
of the forest system which are linkable on the computer.
85
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Although we have considered three other alternative model development
strategies, they are unacceptable for the following reasons. The first
alternative is to develop "stand-alone" models, one for each subproject,
none of which could be dynamically linked during a computer simulation
run. In this case, the overall research program would lose its integrative
nature and more importantly, computer models could not be used directly to
address the higher-level research problems (Fig. 26) which transcend all
individual subprojects. At the beginning of the entire project (1972-1973),
data collection designs were constructed so that a component subproject
model would sometimes require driving data input from one, or several,
different component models of the other subprojects; consequently, linkages
were very strongly inherent in the data collection designs of some of
the subprojects even before initiation of formal system modeling work in
January, 1975.
The second alternative is to link some (but not all) subprojects
models as an operating unit. However, this strategy cannot be used when
the project has only one investigator responsible for computer model
development: some subprojects ineivitably would be ignored by the modeling
effort for their irrelevance to the particular system model designed for
the "select" subprojects. Decisions like these would probably be in direct
proportion to the modeler's background in the subject matter disciplines
of the various subprojects. Also, it should raise the issue of why the
E. P. A. would support certain subprojects without any attempt to syn-
thesize their research results into computer models with forecast capa-
bility. Results of the 1976 Environmental Modeling and Simulation
Conference (Ott, 1976) suggest that the E. P. A.'s expectation from modeling
is a complete simulation of the systems under investigation.
The third alternative is to include all subproject results within a
single integrative set of ecological models defined so that each subproject
scientist could use only 2 or 3 variables to describe his biological
processes in the project-wide simulation model. It is likely, however, that
to force this unilateral constraint on the subject matter specialists would
place both the scientist's and the model's credibility in jeopardy. The
specialists and the systems ecologist would have to agree on the level of
biological realism necessary to define the critical components of the system
being studied.
All quantitative models possess different degrees of the three follow-
ing general properties: realism, generality, and precision. However, no
single model can maximize all three properties (Levins, 1966). This sub-
project's priorities for these model properties are:
1) realism. It is important to structure the model components as
subject matter specialists presently conceive of them.
2) generality. There must be sufficient similarity to other forest
ecosystems which could be subject to oxidant pollutant injury at
some future date. Examples include the western slope of the
Wasatch mountains, the eastern slope of the Rocky mountains, and
the western slope of the Sierra Nevada mountains.
87
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3) precision. Only limited levels of precision are possible because
of the limitations of the present state of knowledge; on the other
hand, models must try for the highest level of biological reality
without becoming unmanageable.
Description and Flow Chart of Forest System Model
Dependence between subsystemsCorrespondences may be see among the
subsystem models being developed as a linked set of simulation models (Fig.
27) and the hierarchy of research problems shown in Figure 26. Figure 27
may be used as a guide to find a particular subsystem defined in greater
graphic detail in Figure 28. Figure 28 shows how the investigators have
conceptualized the various component subsystems which they think are
critical to studying the ecological effects of oxidant air pollutants in
the forest. In addition, observable variables used to define entities in
each subsystem are shown. Although we will eventually publish a task- or
procedure-oriented flow chart as part of the description of the algorithmic
logic currently being developed to simulate this system structure, Figure
28 is a flow chart of how the system is conceived of as being dynamically
structured. It is different from the task- or procedure-oriented chart.
At the base of this set of ecological systems models is a population
dynamics accounting for live trees in the forest stand by species. The
reason for the circles in Figure 28, labeled "Source" and "Sink" is that we
are not conceptualizing a biomass cyclical system; this would be necessary
in a carbon or nutrient cycle model. Rather, we are often invoking a
population dynamics approach in which population increases come from an
undefined source and are eventually sent to an undefined sink. Both terms
are modeling abstractions. The rates at which entities flow from a
source, or alternatively into a sink, are controlled by other tangible
biological and environmental variables or site parameters. All of the
subsystems contribute to defining the calculation of new trees added to the
stand, by species, or the number of living trees killed in the stand.
Word model of the linked subsystemsOnly a word model will be
described for the intersubsystem level (Fig. 27). Detailed word model
descriptions, mathematical documentation, and computer programs for the
logic within each of the subsystem models (Fig. 28) will be presented in
subsequent reports. This is because the detailed logic at the level of
Figure 28 is presently being evaluated using data and results from the
various subprojects.
In the order that the various subsystem models will be described, the
following names are being used for the respective computer routines:
STANDCMP (Tree Population Dynamics); TREEGROW (Tree Growth); SEED (Cone
and Seed Production); ROOTS (Root Pathogen Dynamics); BEETLE (Pine Bark
Beetle Population Dynamics); CANOPY (Oxidant Air Pollutant Flux-Canopy
Response); WATER (Stand Moisture Dynamics); MICROCLI (Microclimate);
SEEDLING (Seedling establishment); LITTER (Litter Production); LITDECAY
(Fine Litter Decay); WOODECAY (Woody Litter Decay); and RODENT (Small
Mammal Population Dynamics).
Both stand regeneration and mortality are partially controlled by tree
88
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population density by species (STANDCMP) and rates of tree growth (TREEGROW).
The latter subsystem simulates the diameter and height growth distribu-
tions for trees in the stand and provides dynamic regulation on how large
the cone crop may be for potential regeneration of new trees in the (SEED).
Tree population density and tree growth rate also regulate how likely trees
are to be: (1) cut down, either to provide stumps for root-disease
development or to regulate tree-to-tree spread of the established root
pathogen through the live standing trees (ROOTS); and (2) attacked and
killed by bark beetles (BEETLE). As trees are killed by these processes,
they are removed from the system state which describes how many live trees
of a given species are present at a given time interval. STANDGROW is
controlled primarily by the CANOPY, WATER, and very simplified MICROCLI
which simulates light and heat available for tree growth. CANOPY simulates
various crown injury symptoms as a consequence of the uptake of oxidants
from the air into the foliage. This process is controlled by the rate
of flow of water through the system as simulated by WATER.
Brief mention has been made of regeneration for mature tree population
dynamics as controlled by (SEED) which is partly regulated by rates of
tree growth and the degree of air pollution-induced crown injury. Re-
generation is further simulated with a population dynamics model for
seedlings (SEEDLING). Input is simulated seedfall from SEED, and loss is due
to seed and seedling mortality which, in terms of other subsystems shown
in Figure 28, are controlled by (1) the amount of organic litter lying
above mineral soil (LITTER), (2) herbivory by small mammals (RODENT), and
(3) the surface soil moisture (WATER). The first of these is simulated as a
balance between (LITTER) providing the input, and (LITDECAY) and (WOO-
DECAY) simulating the reduction of organic litter on the ground. The
principal crown symptom of oxidant injury is an increase in the rate of
fall of foliage from the crowns of sensitive conifer species. Three inter-
subsystem controls have important regulatory influences. The first is
the behavior of the CANOPY Subsystem that regulates the LITTER Subsystem.
The second, herbivory, is controlled by a subsystem simulation of small
mammal population dynamics (RODENT). The third intersubsystem control
is through linkage with the WATER Subsystem already mentioned in con-
junction with the TREEGROW Subsystem above.
Two of these submodels will not originate with this project, but
will be modifications of simulators developed elsewhere. There include
the Stand Tree Growth Simulator (Reed, 1976; Reed and Clark, 1976), a
transpiration simulator (Reed and Waring, 1974), and the Stand Moisture
Dynamics Simulator (Sollins, 1974).
An overview of these linked subsystem models reveals certain inputs
that any potential user will be expected to provide and there are certain
primary outputs which are of central interest to air quality effects
analysts and the control-policy decision-makers whom they serve. The
primary inputs are:
1) oxidant/ozone concentration
2) precipitation
91
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3) net radiation
4) air temperature
5) relative humidity
Primary outputs are:
1) number of live trees (by species and age)
2) number of standing dead trees (by species)
3) number of tree seedlings (by species) surviving 3 years
4) number of trees (by species) killed by root disease
5) number of trees (by species) killed by bark beetles
6) distribution of tree basal diameters in the stand (by species)
7) distribution of tree heights in the stand (by species)
8) distribution of breast-height diameters of trees in the stand
9) mass of foliage litter on the ground
Future Application and Limitations
The models are designed primarily to explore possible consequences of
alternative environmental quality control strategies, particular of air
quality. This concept centers on controlling an input to the forest eco-
system. The ecosystem response categories of forest resource production
management and forest protection management are of central concern to the
production-oriented land and wildlife management agencies. It is our view
that the basic structure of this set of models is applicable in forest
recreation management and timber management.
Resource potentials which are not expected to be considered by this
set of models for air pollution effects question involve three areas:
watershed management, forage-livestock management, and wildlife management.
The first of these limitations exists because we are modeling a forest
system at the stand level, and not at the watershed level. Consequently,
the stream is treated as a sink into which we route the stand's soil and
ground water. We focus on the depletion of soil water, rather than on
stream flow. We are not using a daily water budget simulation. This
implies that the WATER subsystem will not provide any output on the timing,
quantity, and quality of stream water, information that would be needed
to answer watershed management questions.
The second limitation exists because of our current inability to
simulate understory vegetation dynamics. This is due to the lack of
appropriate data. The third limitation, however, is only partially valid.
Management of wildlife in a forest under air pollutant stress may be
92
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served indirectly by information on a given animal's habitat, namely, live
and dead tree species composition and abundance, and seed abundance. The
only wildlife planned for explicity modeling in this system are small
mammals.
In terms of forest protection management, the set of models will be
addressable on a limited scale to fire management, insect pest management,
and forest disease management under conditions of air pollutant stress.
Spatial Aspects of Submodels Compared to Field Plot Data
Forest stand levelIt is possible to define a forest ecological
system model at a number of different spatial scales. An early progress
report (Taylor, 1974) indicated that several different scales were being
used informally as a frame of reference for various subprojects. We
argued, however, that one modeler could not efficiently coordinate the
various subprojects to design forest models at several spatial scales
simultaneously. The E. P. A. project officer suggested that E. P. A.'s
needs would be served better by a forest-stand-level model. For simula-
tion purposes, we interpret a stand as comprising anywhere from 10 to
200 trees, primarily conifers; the equivalent land area may range from
about 100 m^ to about 25,000 m2.
Field Plot Biological Complexity versus Model Structure
Eighteen vegetation plots had been established in the SBNF between
1968 and 1974, before the beginning of formal systems analysis and modeling.
The decision to design a forest-stand-level simulation model had to be
reviewed for certain pre-existing conditions, which were determined by
the site suitability and vegetation cover at the 18 plots. The central
question was whether data already collected from these plots could be
used to quantify a stand-level simulation model. The plots ranged in
size from 0.21 ha (UCC) to 1.80 ha (SCR and GVC) and, with the assumption
that a plot could be treated as a forest stand, we discovered a wide range
in percent species composition of oxidant-sensitive tree species and in
percent shrub cover on the plots (Fig. 29) (this was subsequently found to
be untenable). The assumption is that the lower the number of oxidant
sensitive trees, the greater expectation of biological competition for
resources by relatively oxidant-tolerant tree species (incense cedar,
sugar pine, black oak). The higher the shrub cover, the greater the
biological competition exerted by the shrub layer on trees in the
community.
Four of the 18 plots (BF, UCC, CAO and CA) offered the greatest
simplicity of stand ecosystem model structure. They may be suitable for
either model development or model application for a stand model dealing
with the population dynamics of only one tree species and do not require
any shrub dynamics (Fig. 29, upper left).
The next level of complexity for 11 of the 18 plots (SF, TUN2, DW,
SCR, CP, BP, DL, GVC, BL, COO, and SC) required a model structure dealing
with more than one tree species. It especially required one dealing with
differing tolerances to oxidant air pollutants, but with no shrub layer
within the simulated stand (Fig. 29, lower left). This presents some
93
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problems for quantification since a number of biological process studies in
various subprojects have been confined to variables involving ponderosa and
Jeffrey pines only. These include bark beetles and root pathogen in
stand mortality, and seedling establishment, litter production and litter
decomposition with regard to stand regeneration.
The complexity rises another level when we see from Figure 29 (right)
that 6 (HB, HV, NEGV, BL, SC, and COO) of the 18 plots have greater than
15% shrub cover. This implies that, besides being able to quantify and
simulate the dynamics of more than one tree species simultaneously, we
must also model the dynamics of the shrub component of the forest stand.
The present data on shrubs is too meager to permit this. We cannot assume
effects on trees are not influenced by shrub competition, especially
on a plot having 36% shrub cover (NEGV, Fig. 29). We have omitted from
this discussion that other understory life forms such as herbage and
ferns are present. If effects of these understory components were
included in the system structure, then it would be necessary to prescribe
the increases and decreases occurring in the herb layer over time.
The Use of Different Field Plots for Mortality and Regeneration for Model
Building and Model Validation
The 18 permanent vegetation plots were not selected at random. The
first criterion was the presence of at least 50 ponderosa or Jeffrey pines
in size classes larger than 30 cm dbh. The next most important factors
were slope, aspect, and soil type. There was no conscious effort to
avoid any of the physical disturbances, such as logging, or locations where
biological pest complexes were active on any overstory species. The
tremendous diversity which is now a problem when modeling is attempted is
simply a reflection of existing conditions. The absence of some biological
agents responsible for the death of mature trees is to be expected because
they are very spatially discontinuous. If one used the 18 plots alone,
the activity of pests would be seriously underestimated because of the
small plot size. For this reason, the data from 18 permanent vegetation
plots are being used mainly for those biological subsystem models per-
taining to tree growth, canopy response, and litter regeneration. This
partially excludes the two subsystems which directly control mature tree
mortality: the root disease subsystem and the bark beetle subsystem.
These two will be developed and subsequently validated on the basis of
data collected from "mortality centers." These are plots defined around
recently killed and/or extremely injured trees, as determined from a
combination of recent air photo interpretation and ground measurement of
stand-, oxidant injury-, bark beetle-, and disease-related variables
(McBride j± _al., 1976). The 18 permanent plots and the mortality centers
are, therefore, two separate sets of plots, and are used for separate,
although linked subsystem models in the total simulation modeling effort.
Within each of these two sets of plots, one stratification which
must be made for systems modeling purposes at the outset is to define (1)
which plot areas shall be used to develop and quantify subsystem models,
and (2) which plot areas shall be "reserved" for validating the subsystem
models against the real world. It is a commonly accepted principle among
ecological modelers that data which have been used to construct a computer
95
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simulation model cannot, and should not, be subsequently used (Fig. 23) to
compare how well the model performs with respect to the real world. While
it is too early to decide how a group of mortality centers will be reserved
for validating the two mature-tree mortality-related submodels, we will
reserve 30 m^ sections of each of the 18 permanent vegetation plots to
validate the non-mortality subsystem models, but with a particular caveat.
At least 4 of these plots show signs of genetic cross-breeding resulting
in hybridization between ponderosa and Jeffrey pine, and between ponderosa
and Coulter pine. Since other mixed conifer forests (for example, in the
Sierra Nevada) do not produce the same degree of hybridization (Luck,
personal communication), and since one of our objectives is to produce
models which can be used outside the SBNF for assessing ecological effects
of air pollution, we have decided that certain plots (CAO, BF, GVC, and
maybe TUN2) must be regarded very suspiciously with respect to data analysis
for modeling.
Aside from the two sets of field study plots mentioned, some research
has been done on three additional distinct sets of plots: 24 sapling plots,
85 fire plots, and 22 aspect plots. Since the status of data entry into
the computerized data management system for these plots is delayed, we
have not made any plans to immediately use such data for modeling purposes.
This information will be requested from the relevant project investigators
in the near future.
The next decision we faced was how to establish the conceptual
spatial boundaries of a forest stand ecosystem with regard to the spatial
properties of subsystem components. To avoid excessive complexity in
model structure, we are treating the effect of spatial heterogeneity in
terms of areal densities for the stand area as a unit, rather than distance-
dependence relations within the stand area. We realize we depart from
reality in doing this since mature tree mortality and natural tree
seedling establishment do not occur homogeneously or continuously in
horizontal space across the forest. Rather, spatial clumping is evident
especially on those plots where either oxidant-sensitive tree species
composition is lower, or shrub cover is higher (Fig. 29).
Treatment of Time in Submodels Compared to Field Data Collection
The time span to be simulated on the computer by running the set of
models ranges from 20 to 50 years as a user-selectable option. Since most
of the quantitative data collection effort which will establish the para-
meters of transfer functions in the models is based upon annual observa-
tions, most of the subsystems will simulate on a yearly time step. However,
there are a few exceptions. Biweekly time steps are planned for the
following subsystem models: MICROCLI, WATER, and CANOPY. The BEETLE
submodel is planned to cycle at 4-month increments. For the remaining
submodels SEED, SEEDLING, LITTER, LITDECAY, WOODECAY, RODENT, TREE-
GROW, ROOTS, and STANDCMP it is assumed that inter-seasonal and/or
intraseasonal changes which can occur are unimportant for estimating
forest ecosystem response under oxidant air pollutant stress over the
medium-term (20 to 50 year simulation time span). The same conclusion is
assumed for all submodels for time frequencies greater than biweekly (i.e.,
weekly, diurnally, hourly).
96
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Proportional Causes and Rates of Mature Tree Mortality Under Varying Air
Pollutant Stress
While the biological details of a root pathogen and several bark beetle
species were being studied, it became evident that we would not be able to
link the information for either of these possible mortality causes to the
population dynamics of trees at a forest-stand-level. We did not have
data on the variable degree of importance of different possible mortality
agents for mature trees. Both the small area size and the locations of the
18 permanent vegetation plots became suspect in terms of providing
data on stand mortality rates and relative importance of different causes
of mortality. Analysis of data from forest-wide mortality centers will
correct this problem.
Proportional Causes of Tree Seed and Seedling Mortality in Stands Receiving
Varying Air Pollutant Stress
Different subprojects examined various processes controlling the
establishment of tree seedlings, such as seedling growth with respect to
air pollution levels, changes in needle litter and duff depths, abundance
and dietary patterns of herbivorous small mammals, activity of damping-
off fungi, and seasonal soil moisture depletion. To simulate the regenera-
tion of new trees into the stand population, however, we needed to know
what proportion of potential tree seedling establishement is prevented by
various mortality agents. The above data gathering activities have been
consolidated by Cobb (see the above seedling establishment section).
Data for Tree Growth Submodel for Stands Receiving Varying Air Pollutant
Stress
Several of the subsystems required input to other subsystems on
various tree biomass or yield properties under varying air pollutant stress.
Some of the subsystems requiring this information are those for cone
production, root pathogen infection and spread, and pine bark beetle
population dynamics. Through June, 1976, there was insufficient program-
ming of tree growth data collection (and analysis) to allow stand growth
modeling which would provide the needed inputs to these other subsystems.
Preparation of Historical Data Sets for Eventual Computer Model Validation
Analysis
Before a simulator is applied to some need, it should have its
behavior on the computer compared to the behavior of that portion of the
real world that it represents. This step has often been labeled "valida-
tion," although the question of whether any model can be considered
"valid" at all (Wiegert, 1975) has recently become a controversial issue
among systems ecologists. If we can initially set the ecosystem simula-
tor for ca. 1940 and run it up through 1974, we should be able to compare
the tree species composition resulting on the computer with that observed
by McBride (1973), as a form of "validation." In addition, historical
data on physical processes are needed to construct stochastic driving
variable generators for the exogenous inputs to the subsystem models.
Such historical data which could be very useful include meteorological
data from agency files, fire history data (especially on the 18 permanent
vegetation plots), insect-pest tree damage records, and possibly certain
timber-harvesting records for determining annual stump production as
97
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possible root pathogen infection centers. There is also a need to establish
techniques whereby earlier trends in oxidant air pollution concentrations can
be established.
Process-Oriented Foliar Injury Modeling
In an attempt to quantify the responses of various foliage properties
to photochemical air pollution conditions, a "Smog injury index" has been
developed and has gone through several stages of evolution (Stark et al.,
1968; Miller, 1973; Miller, 1974). During mid-1975, we recognized that the
ordinal-scale mathematical definition of the index, while relatively simple
operationally, was inappropriate (Batschelet, 1971) to subsequent quanti-
tative analysis techniques (e.g., statistical regression) which requires
data on interval or ratio-scale-defined variables. The index may be useful
for purely descriptive purposes for forest managers, but it is not defensi-
ble for purposes of ecological functional analysis.
Within Plot Heterogeneity and Data Analysis Noise
In June, 1976, we became aware of the extent of ground cover-soil-
physiography spatial heterogeneity on 12 of the 18 permanent vegetation
plots. Plot data analyzed for model building on a per-unit-area basis
would contain a great deal of noise for such plots unless within-plot areal
stratification could be done on a natural basis. Data on the spatial
variation of soil types, hillslope gradient and aspect are needed within
plots.
Remote Terminal Graphic Display Procedure
Computer centers have numerous library programs which may be used to
display data graphically. Often, these are formated for line-printer line
widths but are not easily reduced to accommodate narrower dimensions for
output on Teletype-like remote terminals. In order to have such on-line
graphing procedures immediately available as we move into that phase of
model development where we resume frequent modeling sessions with various
subject-matter specialists, we have modified a number of graphing routines
originally developed in the U.S. International Biological ProgramThe
Desert Biome.
PUTCUR is a graphing routine that accepts data as input and produces
output as graphs. The user controls the format of the output, sets limits
for X and Y, and either (1) designates the computer file from which data
are taken, or (2) enters the data from the terminal keyboard. He controls
these functions by his responses to questions displayed at the terminal.
The first option can be used when an investigator is retrieving data from
the data bank.
PUTCUR prints a graph fifty print positions wide by twenty-five
print lines high. The plotting symbol is "+" for each data coordinate
pair.
For Scatter Charts (Fig. 30), the Multiple-Occurrence option plots
"f" for a single occurrence, "A" for two occurrences, "B" for three, and
so on to "Z" for twenty-seven or more occurrences.
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NUMBER OF VALUES TO BE PLOTTED = 50
.5000E+04
0.
0.
++
+ +
A +
+BAA
+A+
ADAA +
MULTIPLE OCCURANCE INDICATION
"+" = 1 Occurance, "A" = 2, "B" = 3,
JANUARY RAINFALL 1931-1975
X = Squirrel Inn #2
Y = Lake Arrowhead Fire
.5000E+04
, Z = 27 or more
Figure 30. Example of PUTCUR graphic data display for exploratory data
analysis.
99
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For Line Graphs, the Asterisk Interpolation option adds "*" symbols
between plotted points.
For uniform scale, maximum and minimum can be set for X and Y using the
Set X, Set Y option. If an X, Y pair has either or both values outside
the set limits, it will be ignored. If no limits are set, the X and Y
limits will be determined by the minimum and maximum X and Y values entered.
Data can be entered from the keyboard as integers, with or without an
explicit decimal, will be in scientific notation, and may be either posi-
tive or negative. If the data are entered from a computer file, a
retrieval program is required to assemble them into an array which is
passed to the PUTCUR program.
PRTPLT is an output data diaplay subroutine for graphing simulation
model behavior on the terminal along the length of the paper (Fig. 31).
Therefore, it is only limited theoretically by the length of paper on the
roll.
Progress and Problems in Data Management Procedures
In contrast to all of the other subprojects, the ecosystem simula-
tion modeling subproject does not collect any laboratory or field data.
As Figure 23 indicates, the ecological systems modeling process is very
dependent upon the degree of user-oriented efficiency of a computerized
data management system.
Both the rate at which data collected from the various subprojects are
entered into the data management system, and the subsequent ease with
which we can gain access to those data determine the rate at which
system simulation models can be quantified, and the rate at which we can
move toward model validation analysis, reliability test, or other com-
parison of the computer model performance with real world behavior
(Fig. 23).
Data capture developmentFor the SBNF project, a fieldfree format
input was developed in which field data were not required to appear in
specific columns on a data sheet. By allowing the field researcher to
design his own data sheets, we hoped that the amount of error in handling
data would be minimized. The data capture system designed for the SBNF
study notes inconsistencies and then ignores them: such data are simply
not processed. Therefore, instead of rejecting whole data sets because
of an error in any one of them, the data capture system records the
error and then processes what is acceptable.
The data capture system itself is divided into three types of com-
puter routines: (1) executive and library routines, (2) operational
routines, and (3) decoding routines. The executive routines contain not
only all of the general logic for determining the type of data being
entered but also a library of all names and mnemonics used by any of the
operational routines. The decoding routines are responsible for de-
coding and classifying actual data into integers, floating point numbers,
alphabetic character(s), and/or special symbols. The operational routines
100
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GRAPH OF CFB WATER MODEL BEHAVIOR
SYMBOL MINIMUM
P
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4
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7
8
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12
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16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
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32
3 2
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3 2
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3 2
Figure 31. Example of PRTPLT graphic data display for output of system
model behavior.
101
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determine whether the data is in an acceptable format and then stores it
into given locations for future use. A schematic diagram for the arthropod
data capture system is given in Figure 32. Presently, the data capture
system is capable of accepting twenty different field data types.
Each operational subroutine will have the capability to summarize
and statistically analyze the incoming field data. These capabilities are
determined by the requirements of the user. At present, there are eight
summation routines coded.
Inefficient accessibility to the LLL computerWhile computer imple-
mentation of the various subsystem models (Fig. 27) discussed previously
were planned to be accomplished by June, 1977, in many cases this had to
be done by using hypothetical data. There are frequent problems in using
the Lawrence Livermore Laboratory computer from a dial-up remote location,
and initial data capture of datasets involves a time delay due to keypunching
of card decks.
From June, 1975 to June, 1976, the ecosystem simulation subproject
has used the Burroughs 6700 computer via the CANDE time-sharing system by
telephone from Berkeley to the U.C. San Diego Computer Center. The reasons
for our having to use such a distant computer were: (1) absence of an
academic-based computer center in the San Francisco Bay Area having remote,
conversational time-sharing capability with interactive programming option;
and (2) at the U.C. Davis campus computer center the lack of abundant soft-
ware compared to that UCSD. In spring 1976, we began trying to access the
LLL computer center by telephone in order to process certain data sets for
model-building purposes. Remote-terminal telecommunication was discovered
to be more cumbersome, transmission rate was 3 times slower (10 cps),
unanticipated time-delays were far more prevalent, and time-sharing
command logic was far less conversational on the LLL computer system than
they were on the U.C.S.D. computer. This created insurmountable problems
in terms of ease (and, therefore, rate) of data processing ability by this
and many of the other subprojects. Experience has shown that after one has
learned the fundamentals of computer operation, one knows he is on the wrong
computer system when he finds himself waiting for the computer instead of
finding the computer waiting for him, as occurs on a user-efficient time-
sharing system. In recognition of this, an attempt will be made to export
the computerized data management system to the new 1MB 370/145 computer at
the U.C. San Francisco Medical Center Computer Center, in the latter half of
1976. This computer system supports a time-sharing system called Conver-
sational Monitor System (CMS), and appears able to provide the kind of
computer resources needed by the entire project to link the Simulation
Modeling subproject and the Data Management System subproject on the same
computer system. Also needed is simple and easy, direct, on-line access
for any project investigators to the data management system, as a daily,
routine procedure. If modeling activity progress is to be achieved,
it is imperative that the data management system become completely opera-
tional for all data sets through the "data manipulation phase" by January,
1977, at the latest.
Inefficient methods of field data entry into computer readable
102
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Figure 32. The arthropod data capture system.
103
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storage mediaAnother problem which seems to create a considerable time-
lag between the time when observations are made in the field and the time
when "data analysis" and "report writing" can be done, is the data entry
system used for all observations made by non-electronic methods. "Field" in
this context refers to any location out-of-doors, although the same com-
parisons which are made also apply to non-electronically collected laboratory
data.
Figure 33 shows four possible different data entry systems. From
left to right, each system requires less time between initial observations
as input, and "data analysis" as output, provided that the problem discussed
in the previous section is solved. Most of the collected data in the SBNF
currently pass through system #1. At least one study in the U. S. Forest
Service (Byler, Hart, and Wood, 1975) uses system #2. Systems #3 and 4
would cut down the time-lag tremendously but require (1) an extra piece of
hardware not currently available in this project, and (2) carefully
trained and screened field technicians, especially for system #4. The
latter system, in fact, is not known to be used yet in any environmental
research program. The field-unit on which data are entered is a portable,
handheld microprocessor-equipped terminal, with solid state memory packs
capable of storing 8000 characters at one time. It looks similar to an
ordinary handheld calculator. This data entry device is coming into greater
use for commercial inventory purposes in stores and appears equally suitable,
with minor modifications, for forest, insect, and other environmental
inventories. Technical documentation on the device can be found in the
June, 1976 issue of Datamation (Anonymous, 1976). The sensor on the device
can "read" item identification information from bar code labels designed
in the Universal Product Code, so it seems possible that trees and other
fixed sites for environmental research could be tagged with bar code labels
for ease of field data recording on-site. After returning from the
field, one could immediately connect the memory pack to a computer via
telephone and modem in order to list the data for investigator's verifica-
tion purposes and other computerized processing which he/she may wish to
perform.
104
-------
LMake Observation 1
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105
-------
TREE POPULATION DYNAMICS SUBSYSTEM
Introduction
The vegetation subsystem is focused on (1) plant communities within
the mixed conifer forest type in the San Bernardino Mountains and (2) the
impact of oxidant air pollution on successional changes in these communi-
ties. Initially, it was necessary to characterize these communities and
develop an understanding of their natural successional tendencies.
Research Objectives
Specific objectives of the Vegetation Sub-Committee were as follows:
1) To summarize field data collected in the past two years concern-
ing vegetation of the San Bernardino Mountains. This summary
will provide the following information for the field plots used in
the study:
a) Tree layer species
1. Basal Area
2. Percent composition
3. Map of location
4. Age distribution
b) Shrub layer species
1. Percent cover
2. Frequency
3. Percent composition
4. Density
c) Herbaceous species
1. Level of importance
2. Density
3. Cover
4. Frequency
2) To summarize field data concerning forest succession following fire
in the San Bernardino Mountains. This summary will identity
specific additional data, in terms of both forest type and decade of
fire needed to complete the fire succession study.
3) To establish a series of plots, in a zone of high oxidant concen-
tration, in order to observe the relationship between topography and
tree mortality. Observation of mortality will be made on the plots
in 1978.
106
-------
Literature Review
Variation in forest composition in the San Bernardino Mountains has
been discussed by Horton (1960) and Minnich et al. (1969). Their work was
reviewed by Miller and McBride (1973) in the light of this project's over-
all objectives. The review concluded that a more detailed analysis of the
vegetation was necessary to initially understand its characteristics and
air pollution damage (McBride, 1973).
Forest succession in the San Bernardino Mountains had not been reported
on prior to this project. A general review of the important variables in
forest succession and the anticipated successional patterns in the study
area was presented in the Task B report (Miller and McBride, 1973). Many
of these conclusions concerning succession following fire were based on the
observations Biswell (1967) and Weaver (1964) made in other parts of
California and the West. Their work indicates a succession toward more
tolerant species such as White Fir and Incense Cedar in the absence of
fire. Fire plays a significant role in renewing pine through seedbed
preparation, and furthermore, often eliminates competing species. The
importance of fire to stand structure on 6 of the permanent plots was
discussed by McBride (1973); on four of these plots, the age structure of
ponderosa pine and Jeffrey pine can be explained on the basis of wildfire
which occurred in the nineteenth century.
Materials and Methods
Field Sampling Technique
Eighteen permanent plots were established in 1972 and 1973 to study air
pollution injury to coniferous forest species in the San Bernardino Mountains.
Plots were selected on the basis of relativity homogeneity of tree cover and
the presence of 50 Pinus ponderosa or _P. jeffreyi trees over 10 cm DBH (Fig.34)
(Taylor, Task C Report, 1973).
Eighty-three temporary plots were established in 1974 to investigate
forest condition as a function of time since the most recent fire. Fire-
scarred trees were selected during a field reconnaissance on the basis of
their occurrence in areas known to have burned at various times in the past.
The fire history of the area was based on the work of Miller and McBride
(1973). Each tree selected was sampled to determine the date of the most
recent fire of sufficient intensity to scar the tree. A new method, in-
volving cutting a thin wooden segment from the tree, was developed for
this sampling (McBride and Laven, 1976). Plots (10m x 30m) were then
established around a subsample of the selected trees to provide a chrono-
logical sequence of plots based on years since the most recent fire(Fig.34).
Twenty-two permanent plots were established in 1973 in a zone of high
concentration of oxidant pollutants near Blue Jay, California. The plots
were located according to aspect and topographic position as follows:
107
-------
1 A
i ? 1
CD CD
I 1
1 1
Q CD
1 1
Q CO
1 1
CD Q
1 I
1 1
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D Herb
.. . . Shrub
1
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CD
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layer
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.
1
1
1
U 10m 3d
Figure 34. Layout of sampling locations on a 30 m section of a permanent
plot and a plot used to study forest succession following fire.
108
-------
Topographic position Number of plots
Slope 7
Slope 4
Slope 4
Slope 2
Ridge top 2
Drainage bottom 4
Each plot was 20 x 100 m and was oriented with the long axis parallel to
the contour.
Characteristics of the tree layer and herb layer vegetation were sampled
on the 18 permanent plots and 83 temporary plots by using the quadrat method
(Clements, 1905). Only tree layer species were sampled on the 22 plots
established to study the relationship between topography and tree mortality.
The entire plot served as the quadrat for measuring the characteristics of
the tree layer. Quadrats measuring 0.1 x 0.1 m were used to sample herb
layer vegetation. These were established along five lines parallel to the
long axis of the plot and 7.5 m apart. The herb layer subplots were located
at intervals of 3 m along each of the five lines. Only 10 such herb layer
plots were used to sample the plots established to investigate forest con-
dition as a function of time since the last fire.
Characteristics of shrub layer vegetation were sampled using the line-
intercept method (Canfield, 1941). Five lines running parallel to the long
axis of the plot were used to sample the 18 permanent plots, and two lines
were used to sample the 83 plots established to investigate forest condi-
tions as a function of time since the last fire. The locations of these
lines as well as of herb plots on the two types of plots is shown in Figure
Laboratory Analysis Procedures
Field data of tree layer, shrub layer, and herb layer vegetation were
to be summarized to provide levels of importance (Curtis and Mclntosh,
1951) using a computer program developed by McBride and Stone (1976).
Problems with access to the data at Livermore prevented the use of this
program and as a result, tree layer and shrub layer data were summarized
with hand calculators. No numerical summary of herb layer data was under-
taken; however, species lists were prepared.
The cover data produced from this summary were compared by plotting
change in cover over time (Hanes, 1971). Age distribution data were plotted
using the methods developed by McBride (1974) and analyzed for curve type
using the approach of Meyer and Stevenson (1943).
Dating of fire scars was accomplished by using a 10-power dissecting
109
-------
microscope to count annual rings between fire scars.
Results and Discussion
Summary of Field Data on Vegetation
Field data collected previously was summarized for tree layers on each
of the 18 permanent plots. An example of this data which shows basal area,
percent composition, and tree density is given in Table 11. Tree location
maps showing tree number, dbh, and 1973 smog injury score were also prepared,
and were drawn for 30 x 30 m segments of each transect (Fig. 35). Age
distribution tables were prepared for each of the 18 permanent plots and
the age distribution curves drawn (Table 12; Fig. 36).
The percentage species composition of each of the 22 plots established
to study the relationship between topography and tree mortality in a zone
of high concentration of oxidant pollutants is shown in Table 13. This
data indicates that a higher percentage of ponderosa pine occurs on south
facing slopes and ridge top positions. North facing slopes and drainage
bottoms exhibit a higher percentage of white fir. The diameter class distri-
bution of trees according to topographic position and slope is shown in
Table 14. Smaller diameter classes of ponderosa pine and white fir were
well represented on northerly facing slopes and ridgetops. Smaller diameter
incense cedar were common in the drainages, while the south facing slopes
exhibited few smaller diameter trees. This presence of smaller size classes
may reflect the general capacity for various species to become established
on different physiographic sites.
Shrub layer data were summarized to present information on percent cover,
frequency, percent composition, and density on each of the 18 permanent plots
(Table 11).
A list of herbaceous species on each plot and a summary list (McBride
et _al., 1975) for the Montane forest zone in the San Bernardino Mountains were
prepared. Table 11 illustrated the type of data summary which will be avail-
able for herbaceous data once access to the data banking system is established.
Complete data summaries of tree layer and shrub layer vegetation, as well
as herb layer species lists, are available from the Department of Forestry
and Conservation, University of California, Berkeley, CA 94720.
Observations at the forest community levelA review of the summarized
data suggests that the two general coniferous forest types defined by Horton
(1960) Pine Forest and Ponderosa Pine-White Fir Forest should be further
subdivided into five types as follows: Ponderosa Pine Forest; Ponderosa Pine-
White Fir Forest; Ponderosa Pine-Jeffrey Pine Forest; Jeffrey Pine-White Fir
Forest. A description of typical examples of each of these types was presented
above in the "Description of Subsystem Properties and Processes."
Future work in modeling the impact of oxidant air pollutants on the
forest must consider the variation in forest types identified by this
study. The breakdown used previously between ponderosa and Jeffrey pine
types may not be adequate if we are to understand the impact of air
110
-------
TABLE 11. VEGETATION DATA FOR THE U.C. CONFERENCE GROUND PLOT.
Tree layer:
Species
Pinus ponderosa
Quercus kelloggii
Shrub layer:
Species
Arctostaphylos pringlei
Herb layer:
Species
Bloomeria crocea
Bromus carinatus
Bromus tectorum
Convulvulus fulcratus
Corethrogyne filaginifolia
var. brevicula
Cryptantha simulans
Elymus glaucus
Erigeron f oliosus
Gayophytum nuttallii
Gnaphalium chilense
Iris hartwegii
var. australis
Koeleria cristata
Lathyrus laetif lorus
Linanthus breviculus
Lotus argophyllus
var. decorus
Monardella linoides
No. oj
trees
65
13
% Frequency
40
Relative
frequency
%
3
9
9
9
8
6
3
4
1
1
24
8
1
8
% Species + g
composition Density Basal area"
83
16
309.5
61.9
Density/100 m
0.57
44.76
1.08
% Cover
1.24
Relative
density
%
1
4
42
6
7
2
1
1
1
2
8
3
0
17
Relative
dominance
%
2
5
14
15
10
1
1
4
1
3
25
4
3
5
§
Number of trees on the plot over 10 cm dbh.
Percent species composition on the basis of number of trees.
Number of trees/a
Basal area in m^/ha
I.V.
6
18
65
30
25
9
5
9
3
6
57
15
4
30
spp. stricta
Sitanion hystrix
Vicia californica
1
3
1
3
1
0
1
3
1
5
7
2
111
-------
542 558
48.2 «R 16.2
538Q35 546 f|g 15
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it. *** if i ^>j . __ w^J^J
529 19 ^ O54I l9 54-8
J9
if 5
<
61.5 ^.* 552
o
O Q534 19.2
44 I
19 50.0 ^
011 Ooo
11 45.5
20
Aia
536
H.8 559
12 547 213
528 ^43 9 ' f
O30.6 U 20
13
o
i i c 553 556
11 "5 47.9 70.2
^35.7 13 13
O 21 n53l O
548
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J>R43 O530 O33.7 !f;|
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NA 26'' l9 O
3 554
550 5,3
532 540 545 O
53.9 43.5 41.2
29 2 551
o 00° 565
533 O 544 548 O19
24.6 w 30,9 36.3
II 24 r>27
563 r
25,3V.
I4Q
o f
10.8
O l7
560
28.4
21
561
47.3
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564
61.2
27O
Om 30m
Figure 35. Plot map of 0-30 m section of U.C. Conference ground plot.
112
-------
to
w /
LU
UJ
o:
h-
u_
O
or
Ul
GO
s
=>
z
120-
110-
100-
90-
80-
70-
60-
50-
40-
30-
20-
10-
C
/,
/
/I
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/ »
/ \ Pini
/ \ On/-
/ » UU6
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) 10 20 30 40 50 60
X X X N \ S N
9 19 29 39 49 59 69
Pinus ponderosa
AGE CLASS (Years)
Figure 36. Stand age distribution curve for U.C. Conference ground
plot.
113
-------
TABLE 12. STAND AGE DISTRIBUTION FOR THE U.C. CONFERENCE GROUND PLOT.
Age
0
10
20
30
40
50
60
70
80
90
100
class (yr)
- - 9
- 19
- 29
- 39
- 49
- 59
- 69
- 79
- 89
- 99
- 109
Number of
Pinus conderosa
0
0
0
0
2
7
14
19
10
0
2
individual trees
Quercus kelloggii
57
121
25
32
8
8
2
2
0
0
0
pollution over these mountains.
A summary of tree, shrub, and herb layer data leads to the identifica-
tion of three species not previously reported for the San Bernardino mountains,
This type of information is valued by taxonomists and plant ecologists con-
cerned with the distribution of plant species.
A review of stand age distribution data suggests four general patterns
of age structure significant to future successional changes on the 18 per-
manent plots. In order of increasing occurrence, these patterns are as
follows:
1. No significant regeneration over the last 20 years;
2. Regeneration of pine,
3. Regeneration of more tolerant conifers;
4. Invasion by Black oak.
The occurrence of any particular pattern is independent of the gradient
114
-------
TABLE 13. PERCENTAGE SPECIES COMPOSITION ON PLOTS ESTABLISHED TO STUDY
THE RELATIONSHIP BETWEEN TOPOGRAPHY AND TREE MORTALITY IN A
ZONE OF HIGH CONCENTRATION OF OXIDANT POLLUTANTS.
Species
Plot
name
North plot
IN
6N
2N
4N
5N
19N
20N
Percent of
total
Ridge plots
17R
18R
Percent of
total
Northwest plots
9NW
10NW
11NW
12NW
Percent of
total
Ponderosa
pine
26
27
15
11
29
7.8
26
26
66
52
49
43
30
47
27
37
White
fire
% of
34
39
73
74
38
50
24
24
1.9
14
14
15
31
2.2
44
23
Incense
cedar
total no.
9.4
13
0.69
5.3
9.5
11
7.0
23
9.1
16
1.5
23
42
21
22
Sugar
pine
of trees
9.4
8.1
0.69
11
9.5
13
24
11
3.8
5.7
4.8
3.0
11
2.2
1.4
4.4
Black Dog-
oak wood
per plot
21
13
9.1 0.69
9.5 4.8
19
26
16 2.7
1.9
6.8
4.4
37
5
5.5
6.8
1.4
Other
species
0.69
0.69
3.8
3.8
1.1
1.1
115
-------
TABLE 13. CONTINUED.
Species
Plot
name
Northeast plots
13NE
14NE
15NE
16NE
Percent of
total
Drainage plots
3D
4D
7D
8D
Percent of
total
South plots
21S
22S
Percent of
total
Ponderosa
pine
11
32
32
25
29
5.8
35
5.2
19
56
50
53
White Incense
fir cedar
% of total no.
39 13
32 23
35 21
35 19
21 31
30 10
43 2.5
6.2 73
25 29
12
42
27
Sugar Black Dog-
pine oak wood
of trees per plot
24 11 2.6
8.5 3.8 0.9
1.3 9.3 1.3
11 8.0 1.6
10
5.8 28 20
7.5 12.5
4.1 10
6.7 13.7 15
32
8.3 --
20
Other
species
8.6
1.0
4.8
116
-------
TABLE 14. MEAN NUMBERS FOR EACH SIZE CLASS OF 5 SPECIES IN THE 22 ASPECT
PLOTS,
Diameter
class (cm)
Ponderosa
pine
White
fir
Incense
cedar
Sugar
pine
Black
oak
Ridge-top plots (2)
10.0 -
30.0 -
60.0 -
90.0 +
29.9
59.9
89.9
15
17.
8
+
5±
+
0
*
1.96
0.98
7,84
22
1
1
± 0
0
± 0
± 0
8 ± 0
3+0
3+0
0
2
1
1
±1.9
+ 0
+0
0
5
1
1
+ 0
+ 0
0
±0
South facing plots (2)
10.0 -
30.0 -
60.0 -
90.0 +
29.9
59.9
89.9
4.
6.
4.
0±
5+
0±
0
0
8.8
0.0
0
0
0
0
Northwest
10.0 -
30.0 -
60.0 -
90.0 +
29.9
59.9
89.9
21
6
1.
1.
±15.4
+
5±
3+
3.4
1.0
0.9
16.
1.
1
8 ±23.7
75± 2.5
0
± 0
Northeast
10.0 -
30.0 -
60.0 -
90.0 +
10.0 -
30.0 -
60.0 -
90.0 +
29.9
59.9
89.9
29.9
59.9
89.9
14.
6.
2
1
5.
2.
2.
1.
7+18.4
5±
+
+
7+
6±
5+
6+
2.9
0
0
8.6
2.1
1.9
1.6
19
1.
6
1
28.
5.
1.
1.
±19.4
7 ± 0.9
± 0
± 0
North
4 ±53
0 ± 6.4
8 ± 1.6
3 ± 0.9
1.5± 0.9
2.0± 1.9
1.0+0
0
facing plots
20.3±12.9
1.0± 0
1.7± 1.8
1.0± 0
facing plots
8.3+ 9.1
4.3+ 4.0
2.5+ 2.9
1+0
facing plots
3.7± 6.1
1.7± 1.9
2.0± 1.6
1.0+ 0
(4)
3.
1.
1.
1.
(4)
2.
3.
1.
(7)
2.
2.
1.
0
0
0
0
7+6.1
5±1.0
0+0
0+0
7±4.6
0±3.9
5+1.0
0
3+3.6
8+1.9
0+0
0
1.
3.
4.
7.
1.
1.
3.
1.
1
7.
1.
1.
1.
0+0
5+4.9
0±0
0
5±2.0
5+1.4
3±0.9
0
5+2.9
5+0.9
0
+ 0
1+6.9
0±
5+1.0
0±0
117
-------
TABLE 14. CONTINUED.
Diameter
class (cm)
Ponderosa
pine
White
fir
Incense
cedar
Sugar
pine
Black
oak
Drainage or swale plots (4)
10.0 - 29.9 1 ±0 8.5+10.1 16 ±33 3 ±0 7.3±10.7
30.0 - 59.9 3.5±4.0 3.8± 6.1 9.3±16 1.5+1 3.0± 3.9
60.0-89.9 10.5+6.9 1.8± 1.6 5 ± 6.5 1 ±0 1.3± 0.9
90.0 + 1.5+1.7 1.5± 1 1 ± 0 0 0
*
95 percent confidence limits
118
-------
of air pollution over the forest. The 18 plots, however, represent an in-
adequate sample to establish the relationship between air pollution injury
and successional change.
Summary of Field Data Concerning Forest Succession Following Fire
Data collected during the previous field season (1974) in a study of
forest succession following fire was summarized during 1975-76. An example
of vegetation data is shown in Table 15, and a typical stand age analysis
curve is shown in Figure 37.
In the analysis of this data, the frequencies of wildfires in the San
Bernardino mountains were shown to be as follows: before 1905, the intervals
between fires for ponderosa pine and Jeffrey pine were 10 and 12 years,
respectively; after 1905, the intervals were 22 and 29 years, respectively.
The significant change after 1905 is due to an increase in fire control
methods in the San Bernardino mountains which occurred as a result of state
and federal legislation in that year.
Evaluation of fire plot data indicated the necessity of a new approach
to our study of succession following fire. Close examination of wood speci-
mens showing fire scars indicated quite different units of the mosaic of
forest stands. Recognition of the scope of this variation dictates that
future work on fire succession focus on a limited number of physiographic
sites within one forest type. The overall approach originally proposed
now appears unmanageable because of the enormous sample size required. As
a result of this data summary, the study of forest succession following
fire has been redirected to identify various physiographic units within the
montane forest zone of the San Bernardino mountains and to establish
successional patterns following fire for each of these units. This will
provide baseline data which must be understood about forest succession be-
fore the impact of oxidant air pollutants on succession can be predicted.
119
-------
TABLE 15. VEGETATION DATA ON FIRE PLOT P-38.
Tree layer:
Species
Pinus ponderosa
Quercus kelloggii
Shrub layer :
Species
Arctostaphylos pringlei
Ceanothus cordulatus
Herb layer:
Species
Cryptantha simulans
Iris hartweigii
var. australis
Poa fenderliana
No. of % Species +
trees composition"1" Density Basal area
5 38 1665 298.7
8 62 3330 76.3
% Frequency Density/100 m % Cover
50 3.3 1.85
100 10.0 13.08
Relative Relative Relative
frequency density dominance
(%) (%) (%) I.V.
50 50 36 136
25 44 36 105
25 6 28 59
Number of trees on the plot over 10 cm dbh.
Percent species composition on the basis of number of trees.
Number of trees/ha.
120
-------
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121
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-OXIDANT FLUX-CANOPY RESPONSE SUBSYSTEM
Introduction
Pollutant Doses/Vegetation Injury Response
Chronic injury to vegetation in the San Bernardino Mountains is being
inflicted upon a complex mosaic of forest types which exist along gradients
of increasing elevation and decreasing rainfall in a west-to-east direction.
Oxidant air pollutants at adverse concentrations and durations also decrease
from west to east. Differences in such common environmental variables as
soil-moisture availability, air temperature, relative humidity, and wind
have an important influence on degree of plant sensitivity to oxidant
pollutants. An integral part of this task is to gain an understanding of
the importance of other environmental variables in influencing plant sensi-
tivity; the role of other stresses acting in concert with chronic oxidant
injury to cause mortality is also of special interest.
Ozone is of particular interest because it is primarily responsible for
injury to conifers. Needle symptoms observed under natural conditions can
be duplicated by fumigation with ozone (Miller et _al., 1963). The role of
other oxidants, e.g., PAN and N02, may assume more importance with broad-
leaf trees, shrubs, and with herbaceous understory plants. Injurious
effects from N02 are probably negligible.
Research Objectives
Two time scales are useful in describing oxidant dose/tree injury
responses, namely, the within season effects on foliage and the accumulated
effect of injury in consecutive years. The measurement of injury to selected
species is based primarily on visual description for the within-season
interval and only partially on visual description of needle and tree crown
characteristics for the consecutive year time scale. In the latter scale,
measurements of diameter and height growth are also helpful. Growth
effects are described in the "Stand Tree-Growth Subsystem" section of this
report. The specific objectives of this section are to:
1) Record the occurrence of injury to ponderosa pine needles at in-
tervals during the growing season.
2) Record the amount of injury to all tree species in the 18 vegeta-
tion plots at the end of each growing season in terms of an
injury score, and record mortality rates.
3) Compare the doses of oxidant recorded at monitoring stations
near the 18 vegetation plots. Injury to ponderosa and Jeffrey
pines and black oak in order to obtain a firest approximation of
122
-------
the within-season dose response.
4) Recognize oxidant injury symptoms on shrub and herb layer species.
Materials and Methods
Scoring Oxidant Injury to Needles and Whole Tree Crowns
Two injury rating systems have been employed to provide an index of
the amount of oxidant injury. The first system is employed with container-
grown seedlings and with saplings less than 10 cm dbh, where the trees
are usually small enough so that needle complements can be reached and
inspected from the ground. Needles are inspected closely to determine
the amount of chlorotic mottle, necrosis, and abscission (Fig. 38). Each
of the three symptoms are rated as: none = 0, very slight = 1, slight = 2,
Figure 38. Chlorotic mottle (top), necrosis caused by an experimental
ozone fumigation (middle), and superficial necrotic flecks
not associated with oxidant injury but rather winter weather
(lower).
moderate = 3, and severe = 4. The worst possible score for a single needle
complement is 12 and comparisons of complements of the same age from tree to
tree form the basis for evaluation of injury differences. Following chronic
injury, the current year and one-year-old needle complements are the only
ones remaining. With the seedling-sapling injury evaluation, the higher
scores mean greater injury.
The second system is employed for whole crowns of ponderosa and Jeffrey
pines 10 cm dbh and larger in the field. It was originally contrived as a
123
-------
"penalty score or index" system useful to forest managers in marking trees
for removal during sanitation salvage. Most of the elements making up this
score must be determined by binocular inspection of each tree. With this
system, the higher scores mean less injury for both pines (Miller, 1973) and
associated species (Taylor, 1974). Black oak is examined in late August and
conifer observations begin in mid-September each year.
From 1968 to 1973, three nearby groups of 10 ponderosa pine saplings
averaging 18 years of age were subjected to different treatments: (1)
activated charcoal-filtered air in a greenhouse, (2) unfiltered ambient
air polluted with oxidants in a second greenhouse, and (3) polluted ambient
air outside of the greenhouses. The abbreviations FAH, AAH, and AAO represent
each treatment in the order named above. The differences in growth, needle
biomass retained, and needle injury symptoms among these three treatments
are described in the "Oxidant Effects on Tree Growth" section.
The AAO treatment in this experiment offered the opportunity to
observe the rate of symptom development on current and one-year-old needles
in relation to total oxidant dose. In addition, the rate of current year
needle growth (cm) was measured (40 needles per tree monthly) to determine
(1) the relationships of season to inception and completion of needle
elongation; (2) the time of appearance and intensity of needle symptoms; and
(3) the accumulated oxidant dose associated with needle injury.
Results and Discussion
Injury to Foliage of Ponderosa Pine Saplings in Ambient Polluted Air During
Three Seasons
In Figure 39, the data for three years, 1969, 1970, and 1971, with
complete records are combined. Trees growing outside greenhouses began to
show slight injury to current year needles before needle elongation was
completed (between Julian days 200-225, July 19 to August 13). Injury
continued to increase on current year needles for the duration of the summer
observation period.
In Figure 39 (left), an average of the three years shows that by
Julian day 250 (September 7), the current year needles has a score of
2.2, indicating slight chlorotic mottle; there was usually no necrosis and
almost always no abscission of current year needles. On the same date,
the combined score of the current and one-year-old needles was about 9,
suggesting a combination of mottle, necrosis, and abscission scores for
one-year-old needles totaling about 7, with current year needles having a
score of about 2. The worst score a single needle complement could have
is 12. Two-year-old needle complements were rarely present on this group
of injured saplings because the abscission of older needles is the most
characteristic result of chronic injury. The trees in the filtered air
house nearby usually retained at least 4 needle complements.
The accumulated oxidant dose (yg/m^-hr) since June 1, which is
associated with the current year, or one-year-old needle injury expressed
in Figure 39 (left), can be estimated by transferring the injury score
to Figure 39 (right). For example, the current year needle score of 2.2
124
-------
SYMPTOMS COMPARED TO DATE AND
STAGE OF NEW NEEDLE GROWTH;
JUNE THRU SEPTEMBER 1969, 1970, 197
INCREASE OF VISIBLE NEEDLE SYMPTOMS
COMPARED WITH TOTAL OXIDANT DOSE
PONDEROSA PINE SAPLINGS
RIM FOREST, CA
JUNE-SEPTEMBER
1969,1970, 1971
130 175 200 225 250 2TS 3OO
(MAY30) (JULtt (SEP?) {OCT 27)
JULIAN DATE
0'5 I'D l'5 ZO 25 JO S'5 4'0
ACCUMULATED DOSE «g/m5- hrs , |08 - 59«g/m5
(BACKGROUND)
Figure 39. Development of oxidant injury symptoms on current, and current
plus one-year-old, needles of ponderosa pine saplings, in re-
lation to stage of current year needle growth and time during
the summer season (left) and in relation to total dose of oxidant
(right). (For approximate absolute values, oxidant dose might
be multiplied by 0.8 to comply with a new, oxidant calibration
standard.)
on September 7 is associated with a dose of 2.75 X 10-> yg/m^-hrs total
oxidant. The 95% confidence limits indicated in both parts of Figure
may not encompass all of the variation because they assume that 100% of
the air monitoring data were available; on the average, about 90% was
available.
Other precautions must be introduced when interpreting the dose
response in Figure 39. The frequency of pollution episodes is random so
the accumulated dose is a composite of high, moderate, and low dose days.
The relative injury-inducing effect of different dose sequences and associated
weather conditions is unknown. The three years of data which comprise
Figure 39 are not sufficient to sample the variation involved. It is also
assumed that visible injury increases by equal intervals or units from
125
-------
the first visible symptoms to the most severe.
Another example of the usefulness of injury to current year needles or
broad leaves as an indicator of dose response is shown (Table 16) for pines
and black oaks (for all plots in which oaks are present) during 1974 and
1975. At Barton Flats, Sky Forest, and Camp Paivika, the 1975 dose (June-
October) was 65, 68, and 67%, respectively, which was as great as in 1974.
The injury to current year needles of pines in all plots was also less
56% of that observed in 1974. Injury to oaks was about the same in both
years. Climatic influences are not considered here. Further investigations
will determine the true form of the dose-injury curve for current year
foliage. These investigations must also evaluate the controlling in-
fluences of soil moisture availability, plant water stress, and other
important microclimatic variables on the development of injury. The steps
which have been taken to understand environmental interactions are described
in the "Stand Moisture Dynamics and Microclimate Subsystem" section.
Injury to Major Overstory Species Along a Gradient of Decreasing Oxidant
Dose
Identification of the oxidant gradient with monitoring station com-
parisons in 1974 and 1975A regression of all hourly oxidant averages at
Sky Forest against corresponding hourly averages at each of 10 other stations
in 1975, as located in Figure 1, has provided a very useful index to com-
pare the seasonal doses. In Table 17 stations are listed in order of
decreasing dose according to their regression coefficients; the corresponding
correlation coefficients are not lower than 0.83, lending good confidence
to these paired comparisons.
The order of listing of the stations in Table 17 agrees quite well
with the west-to-east or south-to-north sequence of increasing distance from
the source as indicated in Figure 16. The most notable exception is Lake
Gregory APCD which appears too low. It is most closely located to Camp
Paivika which has the highest hourly average oxidant concentrations of all
stations compared. The latter is located on a ridge heavily influenced
by the upslope flow while Lake Gregory is screened from such direct flow by
higher upwind terrain; this may account for some of the difference. Analysis
of surface air flow in this area did show much lighter winds at Lake Gregory
(see section: "General Description of Ecosystem Properties: Temporal and
Spatial Trends of Oxidant Air Pollutant Concentrations").
In Table 18, five stations are compared with Sky Forest in consecu-
tive years. Regression coefficients for 1974 and 1975 at Camp Paivika,
Running Springs, and Snow Valley are quite close, but the comparisons between
years at Barton Flats and Big Bear APCD are not as similar, however only
the May through July period is compared at Big Bear in 1975.
Relative seasonal doses, mean injury score and mortality rates of
ponderosa and Jeffrey pines at ten selected monitoring stations-vegetation
plot parisAn approximation of the relationship between seasonal oxidant
dose and the amount of chronic injury to overstory species at the end of
the 1975 season is shown in Figure 40. The relative seasonal oxidant doses
at ten stations are expressed as the regression coefficients from Table 16.
126
-------
TABLE 16. COMPARISON OF OXIDANT INJURY TO PONDEROSA AND JEFFREY PINES AND
BLACK OAK IN 1974 AND 1975.
Total pines in each
plot with chlorotic mottle
on current year needles
Plot name
COO
BP
CP
SF
DWA
UCC
TUN2
DL
GVC
BL
NEGV
SC
HV
SCR
CA
BF(PP)
BF(JP)
CAO
HB
SV1 + SV2
Means
*Score ranges from 8
ND = no data
Percent
1974 1975
68
36
36
60
40
36
38
ND±/
16
4
0
0
0
87
31
30
24
28
1
ND
30
(no injury)
28
28
40
45
28
21
28
15
0
0
0
0
0
33
17
24
8
0
0
ND
17
to 1 (severe injury)
Injury to leaves of
black oak in early
September'
Injury
1974
5
5
5
5
5
7
7
ND
7
NP^7
NP
NP
8
6
6
8
ND
8
NP
8
6
score
1975
5
5
5
5
5
7
6
5
6
NP
NP
NP
8
5
6
7
ND
8
NP
8
6
NP = oaks not present in the plot
127
-------
TABLE 17. REGRESSION OF ALL MATCHING HOURLY AVERAGE OXIDANT CONCENTRATIONS
AT PAIRED STATIONS IN 1975 USING SKY FOREST AS A BASELINE FOR
COMPARING EACH OF TEN OTHER STATIONS.
Station compared
with Sky Forest
Camp Paivika
University Conference
Center
Camp Angeles
Barton Flats
Running Springs
Lake Gregory APCD
Rock Camp
Snow Valley
Heart Bar
Big Bear APCD
Time period
May-Oct 1974
July-Oct 1975
Aug-Oct 1975
May-Oct 1975
May-Oct 1975
May-Aug 1975
July-Aug 1975
May-Oct 1975
July-Oct 1975
May- July 1975
Total
hours
3744
2979
1521
3749
3258
2031
597
3615
1706
1971
Regression
coefficient
1.058
0.977
0.803
0.720
0.701
0.674
0.592
0.578
0.552
0.296
Correlation
coefficient
0.911
0.961
0.914
0.897
0.940
0.964
0.926
0.894
0.832
0.884
TABLE 18. REGRESSION OF ALL MATCHING HOURLY AVERAGE OXIDANT CONCENTRATIONS
DURING 1974 AND 1975 OF FIVE OXIDANT STATIONS EACH PAIRED WITH
SKY FOREST.
Station
Sky Forest vs
Sky Forest vs
Sky Forest vs
Sky Forest vs
Sky Forest vs
comparison
Camp Paivika
Running Springs
Snow Valley
Barton Flats
Big Bear APCD
Time period
May-Oct 1974
May-Oct 1975
May-Oct 1974
May-Oct 1975
May-Oct 1974
May-Oct 1975
May-Oct 1974
May-Oct 1975
May-Oct 1974
May- July 1975
Regression
coefficient
1.028
1.058
0.677
0.701
0.579
0.578
0.597
0.720
0.478
0.296
Correlation
coefficient
0.944
0.911
0.951
0.940
0.910
0.894
0.911
0.897
0.886
0.884
128
-------
The longest record of seasonal oxidant (1968-1976) at Sky Forest and one
of the longest records of ponderosa pine injury at the nearby Dogwood
plot (see Miller, 1973) provide a baseline describing the worst case con-
ditions to be expected. The procedure of matching the remaining nine
regression numbers with the mean oxidant injury score of pines in the
vegetation plot nearest each monitoring station provides a display of
points helpful in understanding the dose requirement for different amounts
of chronic injury. It is important to emphasize that Figure 40 does
not deal with mathematical terms that would allow a best fit line to be
added to these points which could then be used as a dose-response curve.
Future work plans will include improved air monitoring data at each
vegetation plot and improved, more quantitative, tree injury data. The
solid triangles in Figure 40 show the accumulated mortality in these
10 selected plots between 1973 and 1975. The lower mortality in the higher
dose regions may be related to a lower residual population of oxidant
susceptible individuals. More complete mortality records are shown for
all 18 plots in Tables 19a,b,c.
Observations of the end-of~season injury to ponderosa and Jeffrey
pines and black oak in 1974 and seasonal dose shown with respect to
topographyIn September, October, and early November, 1974 all tree
species at 18 major study sites or plots were scored individually by
binocular inspection. The data from conifers could be obtained this late
in the season; however, the single most important deciduous species, black
oak, was also evaluated during 3 days (August 28-31) to distinguish between
oxidant injury symptoms and natural autumn senescence of leaves.
The injury to black oak as of August 31, 1974, at several repre-
sentative study sites, along with the June through August accumulated
dose at nearby monitoring stations, is shown in relation to the topo-
graphic projection of the San Bernardino Mountains (Fig. 41). The
darkened portion of the bar representing oak injury is for leaf chlorotic
mottle and interveinal necrosis. A score of 8 means no injury. The
remaining portion of the score is the sum of scores for leaf complement,
leaf size, and twig mortality, not shown separately. These data suggest
that oak shows no injury symptoms when the accumulated June through
August dose does not exceed about 2.0 X 10^ jjg/m-^-hr, or in other words
from around Snow Valley eastward. It is also interesting to note that
a frost in late May killed all the emerging foliage east of a point
midway between Camp 0-ongo and Snow Valley. Frost damage increased with
elevation. The frost-killed leaves were quickly replaced by new foliage;
it is difficult to assess how this may influence subsequent levels of
oxidant injury to oak.
The distribution of ponderosa and Jeffrey pines into various injury
classes with respect to the distance of the study site along the gradient
of oxidant dose (June through September) is illustrated above the topo-
graphic projection in Figure 42. It is important to realize that the 1974
distribution into injury classes is also a product of earlier years when
the oxidant levels were not always as high as in 1974. The trend towards
greater numbers in the "very slight" (29-35) category is quite evident in
the eastern plots receiving lower doses, e.g., Holcomb Valley (HV).
129
-------
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Figure 40. Relationship of oxidant doses at several monitoring stations
expressed as a ratio of that received at Sky Forest with the
average oxidant injury scores of ponderosa and Jeffrey pines
at the plots nearest each station.
130
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The assumption has been made that ponderosa and Jeffrey pine respond
similarly to oxidant stresses. Ponderosa pine is replaced by Jeffrey
pine in the natural stands east of Camp 0-ongo (COO) and at Barton Flats
(BF). The validity of this assumption can be verified partially by
examining the distributions of the two species where they intermix at Barton
Flats (BF - Fig. 42). These data indicate reasonable similarity at a
common site, but the influence of other environmental variables which change
continuously along the oxidant gradient, e.g., soil moisture availability,
air temperature, and humidity, must be examined more intensively to under-
stand how they influence oxidant susceptibility over long term responses
of trees.
The influences of topography on pollutant transport have been dis-
cussed elsewhere in this report. Figure 41 and 42 are helpful in forming
a conceptualization of the interrelationships between distance from
pollutant source, seasonal oxidant dose and the accumulated chronic injury
to overstory vegetation.
Trends in oxidant injury scores and mortality of ponderosa and Jeffrey
pines in 18 major study plots from 1973 - 1975The evaluation of injury
to pines in the major vegetation plots in 1973, 1974, and 1975 is shown
in Tables 19a, b, and c. The paired t test was used to compare each
living tree with itself between years. The highest seasonal dose yet
observed in 1974 was associated with a general decline in tree score
(increase in chronic injury) compared with 1973. Among the 11 plots which
had significantly different mean scores (with a probability that 95 times
out of 100 the difference is not due to chance) seven decreased and four
increased. In 1975, there were seven mean scores significantly different.
Among these, six decreased and one increased the significant differences are
marked by asterisks in Tables 19a, b, and c.
The numbers of trees killed by chronic oxidant injury and associated
pest complexes (including selective removal prior to pest-caused death) are
shown for each year; the accumulated percentage of the original tree
population killed by 1975 is also summarized (Table 19a, b, and c). The
high incidence mortality at some plots with lower scores (severe injury)
could be due to the earlier elimination of the individual trees most
susceptible to the oxidant injury-pest syndrome. The relative incidence
of different bark beetle species as causes of mortality and the relation-
ship of injury score to bark beetle-caused mortality are discussed in the
"Western Pine Bark Beetle Population DynamicsStand Mortality Response
Subsystem" section.
Injury to white fir, incense cedar and sugar pine from 1973 to 1975
The evaluation of injury to white fir, incense cedar and sugar pine is
shown in Table 20 for the 18 vegetation plots. White fir injury scores
show no consistent trends from 1973 to 1975, but there are definite
between-plot differences which may be due mainly to differences in oxidant
dose. For example, DWA shows low score and high injury while HV shows
high score and low injury. The records for incense cedar and sugar pine
at five plots where each are present show generally unchanging scores
from year to year with only a few examples of both increasing and decreasing
133
-------
TABLE 19, a. CHANGES IN ANNUAL INJURY SCORES AND ANNUAL MORTALITY RATES
OF PONDEROSA AND JEFFREY PINES AT MAJOR VEGETATION PLOTS,
1973 TO 1975.
Number
of living trees
Plot
COO
BP
CP
SF
DWA
UCC
TUN 2
DL+
GVC
BL
NEGV
SC
HV
SCR
CA
BF(PP)
BF(JP)
CAO
HB
Start
60
72
98
120
85
65
73
-
66
137
65
62
168
50
68
168
58
124
112
End
60
70
98
119
85
65
73
-
66
137
65
62
168
50
67
163
56
123
112
1973
Number of
mortalities
Oxidant
related
0
2
0
1
0
0
0
-
0
0
0
0
0
0
1
5
1
1
0
Mechanical
damage
0
0
0
0
0
0
0
-
0
0
0
0
0
0
0
0
1
0
0
Year end scores
of living trees
Plus oxidant
related
Only mortalities
15.1
16.8
17.0
13.4
20.2
15.5
19.5
-
21.7
29.4
33.1
41.3
46.3
12.4
25.6
22.5
21.3
24.0
44.0
15.1
16.3
17.0
13.3
20.2
15.5
19.5
-
21.7
29.4
33.1
41.3
46.3
12.4
25.3
20.1
20.9
24.0
44.0
Plot established in 1974 to replace the Snow Valley II plot badly infested
with Jeffrey pine needle miner.
134
-------
TABLE 19, b. CHANGES IN ANNUAL INJURY SCORES AND ANNUAL MORTALITY RATES OF
PONDEROSA AND JEFFREY PINES AT MAJOR VEGETATION PLOTS, 1973
TO 1975.
Number
of living trees
Plot
COO
BP
CP
SF
DWA
UCC
TUN 2
DL
GVC
BL
NEGV
SC
HV
SCR
CA
BF(PP)
BF(JP)
CAO
HB
Start
60
70
98
119
85
65
73
65
65
137
65
62
168
50
67
163
56
123
112
End
60
67
92
117
85
64
71
66
64
137
65
62
166
50
65
157
54
114
111
1974
Number of
mortalities
Oxidant
related
0
2
2
1
0
1
1
0
0
0
0
0
0
0
2
5
2
9
1
Mechanical
damage
0
1
4
1
0
0
1
0
2
0
0
0
2
0
0
1
0
0
0
Year end scores
of living trees
Plus oxidant
related
Only mortalities
12.9*
16.5
16.7
13.8
16.5*
15.9
17.0*
18.6
20.1
31.8
32.1
47.3*
47.7
11.7
17.4*
19.3*
20.4
24.6
39.6*
12.9
16.0
16.4
13.7
16.5
15.6
16.7
18.6
20.1
31.8
32.1
47.3
47.7
11.7
16.8
18.7
19.7
22.8
39.2
Significant 95 times out of 100.
135
-------
TABLE 19, c. CHANGES IN ANNUAL INJURY SCORES AND ANNUAL MORTALITY RATES OF
PONDEROSA OR JEFFREY PINES AT MAJOR VEGETATION PLOTS, 1973 TO
1975.
Number
of living
trees
Numb er
1975
of
mortalities
Year
end scores
of living trees
Oxidant Mechanical
Plot
COO
BP
CP
SF
DWA
UCC
TUN 2
DL
GVC
BL
NEGV
SC
HV
SCR
CA
BF(PP)
BF(JP)
CAO
HB
Start
60
67
92
117
85
64
71
66
64
137
65
62
166
50
65
157
54
114
111
End
56
66
92
113
83
64
70
65
64
136
64
62
166
49
64
155
53
113
111
related
4
1
0
2
2
0
1
1
0
1
1
0
0
1
1
2
1
1
0
damage
0
0
1
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Only
12.5*
14.5*
14.7*
15.3*
16.0
16.3
17.0
19.2
23.1*
30.5*
40.6*
44.5*
44.6*
12.5
17.9
20.5*
21.5
25.7
33.9*
Plus
oxidant
related
mortalities
11.6
14.2
14.7
15.0
15.7
16.3
16.8
18.9
23.1
30.3
40.0
44.5
44.6
12.3
17.6
20.2
21.1
25.5
33.9
Accumulated
oxidant
related
mortality
1973-1975
(%)
6.6
6.9
2.0
3.3
2.4
1.5
2.7
1.5
0
0.7
1.5
0
0
2.0
5.9
7.1
6.9
8.9
0.8
136
-------
TABLE 20. OXIDANT INJURY SCORES OF WHITE FIRS, INCENSE CEDARS, AND SUGAR
PINES AT 18 MAJOR STUDY PLOTS, 1973-1975.
White Fir
average injury
Plot
POP)
SF
UCC
RP
DWA
TUN2
CA
TIT7
sv
DL
GVC
CAO
BL
NEGV
HB
SC
HV
1973
S7 Q
LI 7
40.7
37.9
49.3
55.6
52.7
ND
53.6
48.6
58.0
66.6
48.7
62.3
63.7
score
1974
S9 1
L~l 9
42.5
37.1
51.5
54.8
54.0
55.6
52.0
42.7
56.4*
64.5
51.5
59.2
61.8
1975
CJO -1
/.q 9
46.6+
39.8
55.5
52.9
ND
56.8
52.5
48.6+
58.8+
65.6
49.7
59. b
60.2
Incense Cedar Sugar Pine
average injury average injury
score score
1973 1974 1975 1973 1974 1975
*
10 "\ ?Q 7 9Q 7
24.4 25.2 27.2+ 35.5 34.6 40.2+
77 L 77 1 78 7* -
20.7 24.2* 25. 1+ 60.0 44.7 41.0+
37.6 38.0 35.2
39.0 27.8 28.8
ND 39.3 42.5+
29.2 27.6+ 28.2 36.0 30.7+ 33.7
Blank means that the species is not present.
Significant, 95 times out of 100.
ND = No data.
137
-------
scores.
We- do not have meaningful verbal descriptions (e.g., slight, moderate,
severe) which can be applied to the score ranges of these species. No
incidents of death of these three species which can be related to oxidant
injury have been observed. Oxidant injury to white fir and incense cedar
foliage is simply more difficult to estimate visually since the chlorotic
mottle pattern is not very distinct. Chlorotic mottle is the element of
the score which is weighted most heavily. Efforts are under way to improve
the methodology for describing oxidant injury to conifers other than pines.
Oxidant Injury to Associated Vegetation
WoodyBoth shrub and tree species were inspected throughout the
summer and autumn. Skunk bush (Amorpha californica) was the only shrub
layer species which showed ozone-like injury. Among the trees, the oaks
(Quercus crysolepis and (j>. wizlizenii) and dogwood (Cornus nutallii)
displayed no definite symptoms, but black oak (Quercus Kellogii) began
to show chlorotic mottle in 1974 with some interveinal necrosis as early
in the growing season as August 9, 1974 in the western section of the
study area.
HerbaceousDuring the spring and summer, 1974, all 18 vegetation
plots and adjacent areas were routinely inspected as new plants emerged
and flowered. Ozone or PAN symptoms were observed on 11 species: Bromus
orcuttianus, Elymus glauca, Osmorhiza chilense, Gallium aparine, Erigerpn
breweri, Potentilla glandulosa, Solidago sp., Vicia californica, Artemisia
douglasiana, Silene verecunda, and Collomis grandifolora. Seeds were
collected from six of the above species which occur in the greatest
abundance. Ozone and PAN injury symptoms must eventually be confirmed
by fumigation experiments on young plants grown in the greenhouse from
this seed.
138
-------
STAND TREE GROWTH SUBSYSTEM
Introduction
An understanding of the impact of oxidant air pollutants on mixed
conifer forest ecosystems depends on knowledge of the growth, composition,
and succession of the vegetation. First, we need to know how air pollutants
affect growth of vegetation because this also affects the ability of
different plant species to complete with one another for the resources they
require (ecosystem dynamics). As a result of this competition, particular
species compositional patterns occur (ecosystem structure). Over time,
these compositional patterns change and result in vegetational succession
(ecosystem behavior).
Research Objectives
Several objectives were selected which would help to understand the
effects of chronic oxidant injury on the growth and productivity of
ponderosa and Jeffrey pines. These included:
1) Determine the growth differences of ponderosa pine saplings
maintained in carbon-filtered and oxidant-polluted atmospheres;
2) Compare the radial and vertical growth of two groups of polesize
ponderosa pines between 20 and 39 years old for the periods
1910 to 1940 and 1941 to 1971, before and after the influence
of oxidant injury;
3) Compare radial growth of sawtimber sized ponderosa pines with
amount of chronic injury to the crown expressed as an oxidant
injury score;
4) Examine Forest Service estimates of timber volume loss at two
plots over a 20-year span from 1952 to 1972.
Materials and Methods
Growth in Oxidant Polluted and Unpolluted Atmospheres
Ponderosa pine saplings inside and outside of greenhousesIn August,
1968, two greenhouses were erected over natually established ponderosa
pine saplings near Rim of the World High School (0.4 km east of Rim Forest).
Each greenhouse was approximately 3.7 x 3.7 m at the base and 4.0 m high.
From mid-April to mid-November during each year from 1969 to 1973, the
greenhouse frames were covered with Mylar or Kreen plastic film. During
the winter months, when the panels were removed, the oxidant dose was
139
-------
usually not greater than background (0.03 ppm) and the saplings received
normal precipitation; summer precipitation was usually negligible. A group
of 10 saplings near the greenhouses were used as an ambient air outside
(AAO) treatment. Study methods and results of observations of needle
symptom development on the AAO group have been included in the preceding
section (Oxidant Flux-Canopy Response Subsystem). During the summer of
each year, greenhouses were force ventilated continuously; one received
unfiltered ambient air (AAH) and the other received carbon-filtered air
(FAR). Oxidant concentrations in the FAR treatment never exceeded about
10% of the ambient concentration. Occasional applications of malathion
were needed to control aphid populations. Injury to current and one-
year-old needles of trees in each treatment was measured at the end of each
season. At the end of the 1973 growing season, all but three saplings
from each treatment were harvested to compare (1) needle biomass for
internodes -of the same age, (2) length of annual growth of the terminal
shoot and (3) first order branches, and radial growth response. The latter
was done by measuring annual ring widths on a section cut from all inter-
nodes dating as far back as 1956. A nearby monitoring station at Rim
Forest documented the oxidant dose during June through September each
year (Fig. 2l)
Radial and vertical growth of polesize ponderosa pines before and
after inception of oxidant injuryTwo tree populations near the Dogwood
(DWA) plot were used in the study. As of 1972, one population ranged in
age from 52 to 71 years old and the other from 20 to 39 years old. Nine-
teen dominant trees were selected from each population and an increment
core sample was removed from the south side of each tree. Ring widths
were measured on these cores to the nearest 0.01 mm with a dendrochrono-
graph. An average ring width was calculated for the 52 - 71 year-old
population for rings produced from 1910 to 1940. This period was character-
ized by low oxidant concentrations in the San Bernardino Mountains. During
this period, the trees in the 52 - 71 year-old population became established
and produced 20 to 39 annual rings.
An average annual ring width was calculated for the 20 - 39 year-old
population for rings produced from 1941 to 1971. This period was character-
ized by high oxidant concentrations in the San Bernardino Mountains.
During this period, the trees in the 20 - 39 year-old population became
established and produced 20 to 30 annual rings. Rainfall data for these
two periods was also obtained for a nearby station so that the contribution
of precipitation to growth could be evaluated during each period.
Relationship of Oxidant Injury Scores of Co-dominant and Dominant Ponderosa
Pines to Radial Growth
Increment cores were taken from the south side of 102 dominant and
co-dominant ponderosa pine trees near the DWA plot; these trees were in a
plot designated DWB. Annual ring width was measured to the nearest 0.01
mm on the cores with a dendrochronograph. The correlations between current
(1974) annual ring width and current oxidant injury score, and current
(1974) annual ring width and average oxidant injury score (1969-74) was
determined using a regression analysis based on the method of least squares.
140
-------
Q
UJ
Z
Q
O
UJ
UJI2
z
O
(C
10
o
LJ 6
CC
O
O
or
-D
Z 2
,FAH
1968
1969 1970 1971
YEARS
1973
Figure 43. Injury score of current plus one-year needles, 1968-1973,
from ponderosa pine saplings maintained in filtered (FAH)
or unfiltered air greenhouse (AAH), and an outside ambient
air treatment (AAO).
Changes of Timber Volume Assigned to Four Insect Risk Categories in Two
Jeffrey Pine Stands Between 1952 and 1972
Two 5 acre control plots were established by the Forest Service in the
Barton Flats (BF) area in 1952 to evaluate a four-category bark beetle risk
rating procedure. These plots are in the Jeffrey pine-white fir subtype
and are now considered to be in an area of moderate oxidant injury (our
CAO plot is nested within control plot 2). All Jeffrey pines, with a
diameter breast height (dbh) of 12 in (30.5 cm) and larger were measured
and their vigor was described by judging the risk or the probability that
they would be susceptible to attack and kill by bark beetles (Dendroctonus
spp). Risk classes 1 and 2 indicate low-risk trees that would definitely
be preserved if trees were being marked for a timber sale. Class 3 and
4 are high-risk trees that would be marked for removal in a timber sale.
The trees which remained were observed by the Forest Service again in
1963 and 1972 and were reassigned to the appropriate risk category. The
tree characteristics used for the risk rating procedure and oxidant
injury scoring are generally analogous, so these observations can be used
as indicators of the chronic effects of oxidant injury.
Results and Discussion
141
-------
Growth in Oxidant Polluted and Unpolluted Atmospheres
Ponderosa pine saplings inside and outside of greenhousesAt the
outset of the experiment in August, 1968, most trees retained only 1967
and 1968 annual needle complements with severe oxidant injury symptoms,
namely chlorotic mottle, necrosis, and premature abscission of needles
shorter than normal. In the following years, the new needles growing in
the FAH treatment failed to develop injury symptoms and were distinguished
by their longer length, healthy green color, and lower oxidant injury
scores compared to the AAH and AAO treatments (Fig. 43). The slightly
lower level of needle injury to AAH than to AAO suggests that enclosure
in a force-ventilated greenhouse without air filtration had some positive
benefit compared to AAO saplings growing outside and adjacent to the
greenhouses.
At the end of the 1973 growing season after saplings were harvested,
needle biomass was compared for internodes of the same age. Increases
of needle biomass in the FAH treatment for the one-year-old (1973)
needle complement compared to AAH and AAO trees (Fig. 44) became signifi-
cantly greater (95 times out of 100 by 1973. Needles in internodes older
than 2 years were completely absent in the AAH and AAO treatments.
180-
170-
m |50-
0,40-
£] 130-
2 120-
a.
w I0°"
S-;
2 70-
? 60-
< 50-
UJ 40-
U.
o 20_
I '0-
MASS OF NEEDLES RETAINED PER INTERNODE BY -,
PONDEROSA PINE SAPLINGS W 1973
1. AMBIENT AIR OUTSIDE
2.AMBIENT AIR HOUSE
3. FILTERED AIR HOUSE
I
$ 123 123 12
3
1969 1970 1971
,1
1 2 3
1972
-
2 3
1973
YEAR INTERNOOE AND NEEDLES WERE PRODUCED
Figure 44. Average dry weight of all needle fascicles per internode in
filtered (FAH), or unfiltered air greenhouse (AAH), and an
outside ambient air treatment (AAO).
142
-------
The dramatic decrease in needle leaf biomass in the AAO and AAH
treatments represents severe reductions of photosynthetic capacity.
Conversely, as more leaf biomass was produced in the FAH treatment,
more carbohydrates could be produced and used for the growth of woody
tissue. After a long lag period, lengths of the terminal shoots (Fig. 45,
upper) and first order branches (Fig. 45, lower) of the upper half of
tree crowns in the FAH treatment increased significantly (95 cases out
of 100). Terminal and branch growth of trees in the AAH and AAO treat-
ments remained the same or lower. The general relationships of terminal
and radial growth to precipitation and oxidant dose are presented in
Figure 46. During the period 1956 to 1968, the annual ring width of all
saplings destined to be included in the FAH, AAH, and AAO treatments
declined gradually.
Each data point is the average of the ring width of all internodes
in each year; this offers a more reliable estimate of radial growth
trend (Duff and Nolan, 1954). From 1968 to 1972, radial growth in the
FAA treatment is remarkably larger than in either the AAH or AAO treat-
ments. The improved radial growth in the AAH treatment suggests that some
greenhouse effect is helpful in reducing injury to foliage (Fig. 46)
and subsequent radial growth. The reduction of growth during 1963 in
both the FAH and AAH treatments may be related to increased competition
for water as the trees grew larger, in combination with an uncontrolled
aphid infestation.
Terminal shoot growth appears to have a light upward trend from 1956
to 1972. In the FAH treatment, there was a time lag of 3 years before
the terminal growth reflected a significant response to the carbon-filtered
air. The terminal growth response in the AAH treatment also showed some
benefit from enclosure in the greenhouse with polluted air.
The expected correlation between rainfall and both types of growth
can be identified throughout the 1956 to 1972 period, but a multivar-
iate analysis is needed to further quantify the effects of precipitation,
temperature, and oxidant dose on growth. Between 1964 and 1973, growth
responses in the AAO treatment track the precipitation trend quite well.
It was difficult to judge the relative effects of decreasing oxidant dose
and increasing precipitation on the gradual terminal and radial growth
increases in the AAO treatment between 1970 and 1973. The over-riding
conclusion from this study is that the FAH treatment resulted in dramatic
increases in needle biomass retained on the trees and subsequent increases
in both radial and terminal growth. Finally, the year-to-year trend
of injury to current year needles follows the seasonal oxidant dose
trend in the lower right corner of Figure 46. The small number of repli-
cates in this study limits extrapolation of these results to other saplings.
But terminal growth of 20 - 30 ponderosa and Jeffrey pine sapli-ngs will
be measured non-destructively in each of 12 plots near certain of the
18 vegetation plots.
Radial and Vertical Growth of Polesize Ponderosa Pines Before and After
the Inception of Oxidant Injury
Table 21 shows a comparison of the radial growth of ponderosa pine in
143
-------
32-
30-
28-
26-
24-
§ 22-
I 20-
1-
O 18-
Z
UJ 16-
14-
12-
IOJ
-
4-
TERMINAL SHOOT GROWTH
1 AMBIENT
2 AMBIENT
AIR OUTSIDE
AIR HOUSE
3 FILTER ED AIR HOUSE
-
2 3
1969
ff
1
2 3
1970
2 3
1971
-
r
2 3
1972
2 3
1973
2
3
1969
2
3
1970
2 3
i
1971
2 3 1
1972
2 3
973
YEAR
32-
30-
28-
26-
24-
E 22-
o
x20-
0 1 8~
g 16-
1
~J
1 4H
1 2-
1 0-
8-
6-
4-
FIRST ORDER BRANCH GROWTH
1. AMBIENT AIR OUTSIDE
2. AMBIENT AIR HOUSE
3.
FILTERED AIR HOUSE
2
3
r
1969
-r
2
3
r
1970
2 3
1971
I
T
r
2 3 1
1972
-
2 3
1973
YEAR
Figure 45. Annual growth of terminal shoot (upper) and first order
branches (lower) in upper half of sapling from ponderosa
pine maintained in filtered (FAR), or unfiltered air green-
house (AAH) , and an outside ambient air treatment (AAO) .
144
-------
200 -
56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73
YEAR
Figure 46. Relationship of precipitation, oxidant dose and foliar injury
to radial and vertical growth of ponderosa pine saplings before
and after treatments in filtered (FAH), or unfiltered air
greenhouse (AAH), and an outside ambient air treatment (AAO).
145
-------
TABLE 21. AVERAGE ANNUAL RADIAL GROWTH OF 19 PONDEROSA PINE TREES IN
TWO LEVELS OF OXIDANT AIR POLLUTANTS.
Age*
(years)
20
21
29
22
25
35
27
28
35
22
39
35
29
33
35
35
36
36
34
High Pollution
Average
radial growth (cm)
1941-1971
0.20
0.33
0.22
0.33
0.30
0.23
0.29
0.31
0.26
0.43
0.21
0.34
0.37
0.37
0.34
0.37
0.35
0.33
0.36
Age*
(years)
60
55
55
57
64
63
60
65
60
71
63
71
66
63
60
70
61
62
59
Low Pollution
Average annual
radial growth (cm)
1910-1940
0.52
0.49
0.61
0.34
0.40
0.55
0.44
0.46
0.75
0.67
0.71
0.65
0.78
0.53
0.33
0.38
0.32
0.37
0.37
*Age at 1.4 m above ground in 1971.
146
-------
19.0cm
30.4cm-
OXIDANT POLLUTED AIR
NON-POL LUTED AIR
Figure 47. Calculated average cross-sections of two 30-year-old ponderosa
pines at breast height grown in polluted air (left) and in
non-polluted air (right) based on radial growth samples from
1941-1971 and 1910-1940.
environments characterized by low air pollution (1910-1941) and high air
pollution (1941-1971).
The average annual rainfall between 1910 and 1940 was 110.9 cm per
year, and from 1941 to 1971 was 117.4 cm. A difference of 0.20 mm in
average annual growth occurred between the two periods. Average 30-year-
old trees grown in the two periods would have diameters of 30.5 cm and
19.0 cm (Fig. 47). The difference in these diameters is attributed to the
influence of air pollutants during the period 1941 to 1971. This informa-
tion, along with the height growth data from the saplings in greenhouses can
be combined to approximate the reduction in volume growth in ponderosa
pine trees near the Dogwood plot. An average 30-year-old tree grown
under the present air pollution conditions would be 7.0 m tall, 19.0 cm
in diameter at breast height, and could produce one log 1.8 m long with
a volume of 0.047 m3 (Fig. 48). An average 30-year-old tree grown in the
absence of oxidant air pollutants (i.e., 1910-1940) would be 9.1 m tall,
30.5 cm in diameter and could produce one log 4.9 m long with a volume
of 0.286 m3 (Fig. 48).
Relationship of Oxidant Injury Scores of Co-dominant and Dominant Ponderosa
Pines to Radial Growth
147
-------
lO-i
5-
co
QC
UJ
fc
I
05
UJ
I
OXIDANT POLLUTED NON-POLLUTED AIR
AIR
*WOOD VOLUME IN LOG WITH 15cm TOP(MIN. MERCHANTABLE DIAMETER)
Figure 48. Calculated average growth of 30-year-old 15 cm ponderosa
pines in polluted and non-polluted air based on radial
growth samples from 1941-1971 and 1910-1940.
148
-------
This study of radial growth has attempted to correlate ring width with
the oxidant injury score of individual trees in the Crest Park area at the
DWB plot. The low r-values (Table 22) obtained in both tests indicate that
crown characteristics assessed by oxidant injury scoring (Miller, 1974) are
not closely correlated with radial growth. This result is difficult to
understand in view of the general correlation between photosynthetic
area and radial growth in forest trees as discussed by Kramer and Kozlowski
(1960). The oxidant injury scoring method used may involve the measurement
of characteristics which have little impact on radial growth, but which
contribute significantly to the calculated oxidant injury score. The
influence of each score component should be tested separately, e.g. needle
retention and needle condition. A preliminary attempt at correlating
precipitation and oxidant level with ring width was inconclusive (McBride,
1974). A larger sample of tree cores has been collected and the annual
ring widths are being measured. Variations in temperature, precipitation,
and oxidant level will be used in a principal component analysis (Fritts,
1974) to determine their respective effects on radial growth.
TABLE 22. CORRELATIONS BETWEEN PONDEROSA PINE RADIAL GROWTH (Y) IN
CENTIMETERS AND OXIDANT INJURY SCORE (X).
Independent variable Regression equations r
Current year oxidant injury score (1974) Y=0.12 + 0.06X 0.51
Average oxidant injury score (1969-74) Y=0.10 + 0.06X 0.51
Changes of Timber Volume Assigned to Four Insect Risk Categories in Two
Jeffrey Pine Stands Between 1952 and 1972
This is the longest observational record of tree decline available,
although it was not designed initially to evaluate chronic oxidant injury.
In Table 23, the changes in merchantable volume in board feet (bd ft) in
all four classes are recorded for two control plots in 1952, 1963, and 1972.
The increases in volume of high-risk trees since 1952 are remarkable;
decreases in volume of low-risk trees and total volume in the plots are
very large. The total volume decrease is related (1) to one-by-one
removal of bark-beetle-killed trees inside the plots indicated for certain
by the increase in snags and current stumps, and (2) possibly to suppressed
radial growth. The 1973-1975 accumulated mortality at our Camp Osceola
(CO) plot nested within control plot 2 has remained high (8.9%) even
though the average oxidant injury score was 25.7 (slight) in 1975.
149
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STAND MOISTURE DYNAMICS AND MICROCLIMATE SUBSYSTEMS
Introduction
Within Season Trends of Soil Moisture Availability and Soil Temperature
We set out to examine the interaction of climate with soil and
possible drought-stress which can occur simultaneously with the impact
of oxidant air pollution on the ecosystem. The first step was to document
the macroclimate in terms of precipitation and temperature and the micro-
climate in terms of soil moisture and soil temperature regimes, and the
system's consequent water balance.
Within Season Microclimate and the Trend of Predawn Xylem Water Potential
We hypothesize that one of the most important factors controlling the
amount of ozone injury to conifer foliage in a single growing season is
the pattern of stomatal behavior. A transpiration model developed by Reed
and Waring (1974) provides a method of simulating transpiration by
using the inputs of seasonal trends in predawn xylem water potential, a
submodel of stomatal function, and daily records of temperature and re-
lative humidity. Bennett and Hill (1975) reviewed the literature sup-
porting the hypothesis that increased transpiration results in increased
pollutant uptake. Our seasonal data will provide a means of quantifying
the "effectiveness" of an ozone dose during different times of the growing
season and will be important input to 'the "Oxidant Flux-Canopy Response
Subsystem."
Materials and Methods
Soil Moisture and Temperature Measurements
Soil moisture-temperature sensors (fiberglas moisture blocks) were
installed in auger holes at depths of 15, 30, 61, 92, 152, 214, and 274
cm (6, 12, 24, 36, 60, 84, and 108 in). The holes were repacked with
the same soil to as close to its original thickness and density as
possible. Readings were taken every 1 to 3 weeks since the spring and
summer of 1973 depending upon the rate of change of the soil moisture.
Soil taken from the cores was used to calibrate the moisture sensor
readings with water content. In spring and fall, soil cores were collected
at 23 sites either to the depth of hard bedrock or to a depth of 2.75 m
(9 ft), for measurement of maximum and minimum water holding content, and
for physical and chemical analysis. Water content was determined by weight
differences in oven-dried samples, and the total volumetric water content
was calculated for the entire soil core as corrected for gravel or stones.
These data provide a true estimate of the storage capacity of soil water
which is usable by plants.
Predawn Xylem Water Potential Measurement
151
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Monthly during July, August, and September, 1975, predawn xylem water
potential was measured on two ponderosa or Jeffrey pines at each of three
plots: Camp Angelus, Camp Oceola, and Heart Bar. In 1976, the same measure-
ments were made bi-weekly at the same plots and at three others: Tunnel 2,
Dogwood, and Deerlick. Continuous temperature and relative humidity data
were measured using hygrothermographs and an electric psychrometer at
adjacent stations in both years and at the time of water potential measure-
ments. A bomb patterned after that used by Scholander, &t_ a^> (1965) was
used to measure the water potential of branch tips excised with a pole
pruner from heights between 3 to 5 m above ground. At the same time,
stomatal infiltration pressure was determined using an infiltration poro-
meter (Fry and Walker, 1967) for both current and one-year-old needles of
each excised branch tip. The trees selected for sampling had slight or
no injury (their scores were larger than 21).
Results and Discussion
Trends of Soil Moisture Availability and Soil Temperature
Soil moistureAn example of results obtained at one site from the
fiberglas moisture-temperature sensors installed at 23 sites throughout
the study area is shown in Figure 49. Moisture curves were obtained by a
comparison of field readings (conductivity converted to resistance and
corrected for temperature by computer) with soil samples from the same
site at varying moisture contents. Moisture curves for 3 depths show the
drying period from March to October for 1973 and 1974. In both years,
the effect of light rains wetting the upper 15 cm of soil during April
and May is evident, while rain in May affected the sensor at 91 cm (36
in) only in 1973. The toal amount of rain which produced these effects
was only 20 mm (0.79 in) in 1973, recorded 1.5 km away at Lake Arrowhead.
In May, 1974, rain amounting to only 7.0 mm (0.28 in) produced the rise in
the curve in late May. The sensitivity of the method is quite evident.
The curves show clearly that the maximum rate of water use by vegeta-
tion occurs during June and early July, and that after mid-July, the soil
dries very slowly. From mid-July to late fall the upper 150 cm of soil
is at or near permanent wilting point. At another site, sensors placed
to a depth of 275 cm (9 ft) showed that moisture extraction continued slowly
into September; this suggests that the forest survives the summer drought
by extracting moisture from deep in the decomposed granite substratum. The
drastically reduced rate of water use after mid-August indicates that the
forest is essentially dormant at least until after the first precipitation
in autumn. Future comparisons of soil moisture availability and transpira-
tion determined by the Reed and Waring (1974) simulator will further re-
fine the interpretations of vegetation response.
The spring period during which soils contain available soil moisture
in 1974 is shown by black bars in Figure 50. These data were also ob-
tained from the sensors and indicate that essentially all available soil
moisture was exhausted from the soil in 11 plots before mid-August. The
date was determined by examining the computed resistance of the moisture
sensors; the first date at which the sensor was found to have a resistance
of 100,000 ohms was taken to represent the date after which soil moisture
152
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Depth
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1974 DAY 150 200 250 300
MONTH MAY! JUNE I JULY I AUGUST I SEPT I
Figure 50. Time intervals during which the soil at various depths con-
tained moisture available for plants during spring and
summer 1974.
154
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depletion was at a minimum rate. Three of the sites Heart Bar (HB),
Sand Canyon (5C1), and Camp Osceola (CAO) were wet by summer thunder-
storms in late July and early August. This rain probably had little
effect at HB as only the upper 30 cm (1 ft) was moistened. However, SCR and
CAO were wet to a depth of about 1 m at a time when the deep soil moisture
was nearly exhausted. Thus, the period of active growth may be prolonged
by summer thunderstorms, which occur mainly in the eastern portion of the
San Bernardino Mountains near Big Bear Lake and in Santa Ana Canyon. August
precipitation exceeding 25 mm at Big Bear Lake Dam occurs with a frequency
of about 23%, while at Lake Arrowhead it is about 14%.
The significance of these data in relation to air pollutant impact
is that the most dynamic growing period for conifers and vegetation is
from early May, when soil temperatures begin to rise, through August, when
soil moisture is often exhausted. Thus, one could expect the most severe
damage to the plants by air pollutants to take place during this period.
Soil temperatureSoil temperature measurements at the Dogwood plot
obtained with the soil moisture-temperature sensors are also shown for 3
soil depths in Figure 49, which is representative of the Lake Arrowhead
area. The curves show that soils were colder in April, 1973 than they were
in April, 1974. Soil temperature during 1973 rose smoothly to a maximum
in August, whereas in 1974, they were held down by a cold period in May,
followed by a sharp rise in surface temperature with the maximum (below
the surface layer) delayed into September. A marked soil temperature
difference due to aspect is shown by the fact that in September, 1974,
soil temperature in the upper part ofrthe soil was 7.7 C higher at plot
S22 than at the Dogwood plot. Plot S22 is near Dogwood, but has a south-
facing slope.
Preliminary inspection of the data indicates that in September, at
the Bluff Lake plot, located high above Big Bear Lake at an elevation of
2260 m (7400 ft), the soil temperature was 3.6 C lower than at Dogwood;
at Holcomb Valley, on the desert side of Big Bear Lake, it was about 3.8
C higher; Camp Angelus in the Santa Ana Canyon, which is at about the
same elevation as Dogwood, was about 2.4 C higher. Detailed compari-
sons of the soil temperature regimes at all plots will be completed soon.
Soil Moisture and Temperature Data Collected in 1975 and 1976
Soil moisture and temperature readings continued to be made at 23
sites including the major vegetation plots. It was hoped that by this
time, all data might have been computer processed so that the soil mois-
ture and temperature regimes and their relationships to climate and air
pollutant impacts might be shown. However, the arrangement for data
processing with the Lawrence Livermore Laboratory has been less than
satisfactory. As a result, these data collected since 1973 have been
processed preliminarily, but virtually all have been stored in the com-
puter in the requested form. As a consequence, excellent data have been
collected, but their application for the purposes of the project await
effective final data processing. The amount of data awaiting computer
processing is on the order of 10,000 sensor readings.
155
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Predawn Xylem Water Potential of Ponderosa and Jeffrey Pines at Selected
Sites
Xylem water potential trends, 1975 and 1976The data from 1975 and
1976 in Figures 51 and 52 show the increases of air pressure (bars) required
to force water from excised branch tips as the season progressed and soil
moisture availability diminished. The higher values in the early 1976
season cannot be explained with certainty at this time. The predawn period
provides an opportunity to observe the highest water potential (lowest
scale value in bars) for the 24 hr period. The general relationship of
lower water potentials (higher scale values) and the gradual raising of the
daily temperature maxima as the season progresses can be observed in the
1976 data (Fig. 52).
Data inputs to a transpiration modelThe stomatal infiltration data
gathered during predawn periods and also for all daylight hours on several
other sample days is required for the submodel of stomatal behavior (Reed
and Waring, 1974). Stomatal infiltration data can be converted with some
uncertainty to stomatal resistance. A diffusion porometer is a better in-
strument (Slavik, 1974) and one has just become available to our subproject.
We will use it to calibrate existing data from the infiltration porometer
and to obtain the additional data needed to plot a regression between pre-
dawn xylem water potential and the minimum daily stomatal resistance for
corresponding days. Infiltration data will not be reported here, but
several comparisons have been made, including: different heights in trees,
sunny and shaded sides, different tree sizes, different annual needle
whorls, and different levels of oxidant injury.
156
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WESTERN PINE BARK BEETLE POPULATION DYNAMICS-
STAND TREE MORTALITY SUBSYSTEM
Introduction
General Importance of Bark Beetles
Bark beetles are one of the most important groups of forest insects in
the United States. Although tree mortality due to these beetles varies
considerably from year to year, the fact remains that these insects have
tremendoua potential for destruction. A breakdown of timber loss due to
insects for 1952 showed bark beetles to be responsible for almost 90%
of the total sawtimber mortality nationally (Graham and Knight, 1965). In
California, bark beetles are considered to be the most important forest
insect pests. The three most important species are the western pine beetle
(Dendroctonus brevicomis Le Conte), the mountain pine beetle (_D. ponderosae
Hopkins), and the Jeffrey pine beetle (I), jeffreyi Hopkins). These beetles,
along with the California flatheaded borer (Melanophila californica Van
Dyke) and several other bark beetles, were responsible for a loss of 1676
million board feet of timber, valued at $23,235,000, in California in
1967.*
Literature Review
Bark beetles are not necessarily primary attackers except during
epidemics. They can usually be considered as secondaries or as symptoms
of some other stress experienced by the tree. Stresses that predispose
trees to attack by bark beetles include flooding, drought, lightning
strikes, root disease, and photochemical air pollutants. Cobb et al.
(1968) discuss the relationship of oxidant injury as well as other diseases
to bark beetle infestations on ponderosa pine. It has been shown previously
in the SBNF that as the severity of oxidant injury to ponderosa pine in-
creased, the incidence of western pine beetle and mountain pine beetle
infestation increased (Stark e_t _a_l., 1968). Oxidant injury, therefore, is
an important agent predisposing pines to bark beetles attack, and can be
considered in the same way as the other predisposing agents. This was
further subatantiated by an historical analysis of tree loss in one area
in the SBNF (Lake Arrowhead) where there have been substantial increases
in tree mortality due to bark beetles since 1951 (Wood, 1971). These
tree mortality records will be used along with a pest damage inventory
to evaluate the overall impact of bark beetles on a forest community stressed
by oxidants. The effects of oxidant-weakened trees on the populations
of bark beetles or flatheaded borers have not been studied previously.
However, a study of ponderosa pine infested with western pine beetle at
*
California Department of Food and Agriculture, 31 July, 1968.
159
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Blodgett Forest in the central Sierra Nevada has shown beetle populations to
be higher in non-diseased trees in all respects (Dahlsten and Rowney, 1974) .
This study was a comparison of non-infected trees and those infected with
the root pathogen, Verticicladiella wagenerii. Results are too preliminary
to draw any conclusions about what this means in terms of either tree
mortality or associated organisms, predators, and parasitoids.
Detailed studies of the population dynamics of the mountain pine
beetle, the Jeffrey pine beetle, and the California flatheaded borer on
ponderosa and Jeffrey pines in California have not been conducted. In
addition, population sampling procedures have not been perfected for
these species. The western pine beetle, however, has been studied in
considerable detail, with early work summarized by Miller and Keen (1960).
Recent studies have concentrated on the population dynamics of the western
pine beetle and the development of population sampling techniques (Dahlsten
et_ al. , 1974; Stark and Dahlsten, 1970).
It is obvious that a forest community under the kind of stress,
represented by high oxidant pollutant levels, will be predisposed to attack
by the tree-killing beetle complex. So far, only trees most sensitive to
pollutants have been studied in relation to the beetles that attack them.
Bark beetles can have a tremendous effect on the age and species composition
of a forest community. The beetles by killing certain tree species,
actually hasten succession and therefore secondarily influence many other
organisms and processes in the community. The removal of trees strongly
influences the vegetation that follows. In addition, there will be changes
in litter fall, soil moisture and structure, small mammal inhabitants, soil
microarthropods, litter decay rates, and regeneration. The rates of change,
however, may be ameliorated by the influence of oxidant-injured trees on
beetle populations. This interaction will have to be characterized in
order to model and eventually predict the influence and rates of change in
forest communities affected by photochemical oxidant air pollutants.
Research Objectives
The main objectives of this subproject are to characterize the role
of tree-killing beetles in stands predisposed by photochemical air pol-
lutants. The relationship of the beetles to other components in the eco-
system is shown in Figure 53. Specific objectives are as follows:
1) To determine the degree of susceptibility of oxidant-injured
ponderosa pine to the western pine beetle and the mountain pine
beetle, and of Jeffrey pine to the Jeffrey pine beetle and the
California flatheaded borer.
2) To investigate the influence of oxidant-injured pine trees on
the success and productivity of broods of the four beetle species
to be studied.
3) To study the direct and indirect influence of photochemical
oxidant pollutants on the biology of the four tree-killing beetles,
160
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with particular reference to insect associates, parasitoids, and
predators.
4) To develop life tables for the four beetles by oxidant injury
categories and, based on these tables, to develop predictive
models of beetle activity with reference to stand type and pine
oxidant-injury level.
5) To determine the biological impact and relative importance of
each of the beetle species in forest communities and what in-
fluence they have on stand change and forest succession.
Methods and Materials
Field Sampling Techniques for Bark Beetles
Western pine beetleSampling procedures used in this study have been
developed within the past ten years (Stark and Dahlsten, 1970; Dahlsten
et^ _al. , 1974). Details of the sampling procedures including laboratory
methods, data forms, and analytical procedures are given by Dahlsten
(1974).
The ideal situation is to locate four infested trees in each oxidant-
injury category for each beetle generation. We used three oxidant-injury
classes as defined by the oxidant-injury rating score of Miller (1973)
(Table 24). Therefore, twelve trees were sampled each generation from
1973-74. This was reduced to six for 1975 (see below). Trees are often
green and have not faded, so beetle-produced frass (boring dust) or pitch
tubes were used to find infested trees. Local personnel of the State
Division of Forestry and the U.S. Forest Service aided in the search for
trees. Once trees were found, they were given an oxidant injury rating,
and other statistics such as height and diameter were recorded. Trees
with mixed broods (more than one species of bark beetle present) were
not selected. The mountain pine beetle and the western pine beetle are
commonly found infesting the same tree.
The various sampling procedures, the data form identification, and
the types of information recorded are shown in Figure 53. The basic
sample unit consisted of paired 88 cm^ discs cut with a gasoline-powered
Drillgine saw. Samples were taken at 1.5 m intervals along the length of
the infestation. A summary of the four procedures follows:
1) Egg discs. Paired discs were cut at 3.0 m intervals, (it is not
necessary to take these discs at 1.5 m intervals, so every other sample
height is skipped). These discs were taken only once per generation and
were used to evaluate attacks, egg density, and egg mortality.
2) X-ray discs. Paired discs were cut at 1.5 m intervals, returned
to the laboratory, x-rayed, and then placed in rearing cartons. During
the first generation, discs were cut twice: the first time occurred when
the beetles reached, at most, the third instar of larval development;
and the second time occurred just prior to, or immediately after, pupa-
tion. The second generation was treated differently since the beetles
161
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overwintered in this generation. Discs were taken three times: once at the
third instar stage, once before winter, and then again in the spring of the
following year. Developed x-rays were interpreted for beetle stage, para-
sitoids, predators, and miscellaneous insects. The abundance of each of
these inclusion types was recorded.
3) Rearing. Each x-ray disc was placed in a separate ice cream
container to which a vial was attached and placed through the lid. All in-
sects were reared from the bark discs, collected, and identified. Approxi-
mately 75 species were reared from these samples. Discs were kep in
rearing nine to twelve months.
4) Sticky carton. The interiors of ice cream containers were lined
with a sticky substance (Stikem Special) to prevent insects from boring out.
The containers were placed on trees in pairs at 1.5 m intervals when the
last x-ray discs were taken. These cartons xrover an area of 88 cm . Car-
tons were put up once during the first generation and removed for analysis
only after it was determined that all insects had emerged from the study
trees. Cartons were put up and removed twice in the second generation,
once before and once after winter. The sticky cartons were used as a
comparison to the laboratory-reared samples, since rearing conditions
influence the western pine beetle as well as a number of the other insects
associated with it.
During the 1975 field season only six ponderosa pine infested with I).
brevicomis were sampled for each of the two annual beetle generations. This
is half the number of trees normally sampled per generation. Phloem
thickness was recorded for each sample tree. In addition, trees were
examined for evidence of root pathogens, but no evidence of disease was
found.
Mountain pine beetle and Jeffrey pine beetleStudies on these two
beetles were initiated in 1974 to develop sampling procedures and to rear
and identify associated insect species.
Infested trees in which broods had completed development were selected
whenever possible. Mixed broods were avoided, but bark beetles (Ips spp.)
or California flatheaded borers were found often in portions of the sample
trees. Six IK jeffreyi-infested Jeffrey pines from the Big Bear and Heart
Bar areas and five J3. ponderosae-infested ponderosa pines from the Lake
Arrowhead area were used to determine sample size, cost, and efficiency.
Bolts were taken from one tree of each species for rearing. Sample bolts
were taken from the top, middle, and bottom of each infested pine species.
Broods in both trees were in the late pupal stage, and all rearing was
done outside at Lake Arrowhead. Emerging insects were trapped in KAAD (a
preservative for insects) and collections were made on a weekly basis from
26 July through 14 November, 1974.
Each tree to be sampled was felled, examined for mixed broods, and
measured for standard tree and infestation characteristics. Paired samples
were taken from points 1.5 m above the base of infestation, 1.5 m below
the top of the infestation, and from the mid-point between the two. The
162
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samples were sections of bark 60 cm long by one half the circumference
of the bole.
Vegetation plot surveysThe 19 permanent vegetation plots were surveyed
in June and November of each year for tree mortality. The Insects responsi-
ble for the death of each tree were recorded.
Laboratory Analysis
Western pine beetleDissection of egg discs, x-ray interpretation,
and collection and identification of all insects from rearing cartons
and sticky cartons was done in the laboratory. The information was .punched
on cards, verified, corrected, and put into the information system (Fig. 53).
Mountain pine beetle and Jeffrey pine beetleAnalysis of eaph sample
consisted of placing an acetate overlay upon which five nested Samples
(rectangles of 1000 cm2, 500 cm2, 250 cm2, 100 cm2, and a circle 100 cm2)
were drawn. Parameters measured included: number of attacks, adult
gallery length, number of larval mines, pupal cells, emergence holes, and in
some cases the number of egg niches and Coeloides (a parasitoid) cocoons.
These data were punched onto cards for analysis, but data from this study
were not put into the larger information system.
Results and Discussion
Preliminary Analyses of Bark Beetle Population
Wester pine beetleOnly the egg data for 1973 and 1974 were available
for summarization (Table 25) . The trends indicated by the egg data, however,
were fairly definite. Other interesting influences of oxidant air pollu-
tants on other aspects of western pine beetle biology are anticipated.
Since populations of western pine beetle have been studied for the past
ten years at Blodgett Experimental Forest (Stark and Dahlsten, 1970;
Dahlsten et al., 1974), there is a base of information available to compare
with the SBNF populations. These comparisons will be interesting, as
many of the ponderosa pines at Blodgett have been stressed by a root
pathogen, Verticicladiella wagenerii; but there is little, if any, oxidant
air pollutant injury to the trees.
In the SBNF, the mean attack rates of beetles were highest in the
first generation in both years (Table 25) A similar trend was noted at
Blodgett Forest, but the differences are greatly exaggerated in the SBNF.
The mean attack rates in the first generation of 1973, (hereafter re-
ferred to 1973-1) were higher (2.57 and 2.49/sample disc) than any of the
previously recorded highs at Blodgett (1.82/sample disc). Not enough
generations have been studied to explain this phenomenon.
Mean attack rates were more variable in the SBNF, which may be an
effect of air pollutants on the trees. Attack rates tended to be higher
in the Class III trees ("slight" to "no visible symptoms") except in the
1973-1 generation. However, if that generation was part of an epidemic
outbreak, it could explain the breakdown of any behavior pattern. For
example, vigorous trees, or trees not predisposed by some other factor,
are often killed by beetles during epidemic outbreaks.
163
-------
Another valuable attribute for evaluating bark beetle populations
(Objective 2) is the mean number of eggs per centimeter of gallery length.
Results were extremely variable, and no consistent trend could be found
(Table ). The values tended to be higher in the second generation in
both years. A similar trend was noted at Blodgett (Dahlsten et^ a^. , 1974).
Again the data from the SBNF is much more variable than that from Blodgett.
The values from five second generations at Blodgett ranged from 1.46 to
1.94 eggs/cm gallery length, and for four first generations from 1.32 to
1.54 eggs/cm gallery length. Values consistently less than 1.0 were
recorded in the SBNF. The highest value, 1.37, was recorded on severely
injured trees in the 1974-2 generation, but results from other genera-
tions were too variable to draw any conclusions.
The percentage of hatched eggs per sample disc can often be used as
an index of egg mortality, which is essential for both estimates of brood
productivity (Objective 2) and development of meaningful life tables
(Objective 4). The egg discs can and must be taken well after oviposition
occurs to insure that all ecolosion (hatching) has occurred. Estimates
of egg mortality at Blodgett vary between 15 and 25 percent. Again, the
data from the SBNF are more variable (Table 25) There was a tendency
for the percentage of eggs hatched to be lower in the less severely
injured trees. Since the percentage of eggs hatched is used as an indi-
cator of egg mortality, there is a possibility that oxidant-injured trees
increase egg mortality primarily or secondarily. Work on this facet of
the egg data will be expanded in the future (Objective 3).
The following is the status of the data capture routines for the
western pine beetle population study:
1) A system for capturing egg data has been developed and is
operational. This system consists of computer routines which capture egg
data (EGG) and which analyze it (EGGSUMS and STATPAK). Field data has
been summarized for 1973 and 1974 (Table 25).
2) A system for capturing x-ray data has been developed and is also
operational. This system consists of computer routines which capture
x-ray data (XRAY) and which analyze it (XRAYSUMS and STATPAK).
3) Computer routines which capture tree data, sticky carton data,
rearing data and tree-bug data (BTREE, STIK, REAR, and TBUG) have been
programmed and debugged but are not fully operational.
Mountain pine beetle and Jeffrey pine beetleSampling procedures were
not available for either the mountain pine beetle or the Jeffrey pine
beetle. The first step was to determine sample size. Preliminary summaries
and statistics for number of attacks and gallery length have been completed
for both species (Tables 26 and 27). Results have been analyzed statis-
tically and the data suggests that a 500 cm^ rectangle would be suitable.
Counts of larval mines and pupal cells of _D. Jeffrey! were compli-
cated by the feeding of the California flatheaded borer which was present
to varying degrees in all samples. Estimates of the proportion of the
164
-------
host sample utilized by the flathead larvae were recorded and will be used
to evaluate interspecific competition. Field observations indicated that
the flatheaded borer may be an important component in the forest communities
of southern California, particularly in Jeffrey pine.
Mountain pine beetle trees were also difficult to locate and broods
were usually mixed with those of the western pine beetle. There was
evidence that ponderosa pines had been killed by mountain pine beetles,
but currently infested trees were rarely located in 1974. This suggested
an important interaction with western pine beetle populations; however, it
appears that the most important factors in extensive pine mortality are
the western pine beetle and the flatheaded borer. Further studies should
concentrate on these beetles, and not the mountain pine beetle or the
Jeffrey pine beetle.
All insects reared from the sample bolts to determine the associates
of the mountain pine beetle and the Jeffrey pine beetle have been preserved,
identified, and counted (Tables 28 and 29). Future analyses of rearings
for both species will include the distributions of each insect through time
and by height on the tree. A knowledge of the associate complex for each
species is necessary for evaluating the effects of oxidant-injured pines
on beetle populations either directly or indirectly through the effects
of parasitoids, predators, and competitors. The species lists compiled
thus far are consistent with the present knowledge of bark beetle associate
complexes (Dahlsten, 1971; Dahlsten and Stephen, 1974).
Vegetation plotsTrees killed by insects on the 18 vegetation plots
are summarized and the mean oxidant injury score is given in Table 30. The
most common cause of mortality in ponderosa pine was the western pine beetle,
followed by mixed populations of western and mountain pine beetles.
The most common cause of Jeffrey pine mortality was the Jeffrey pine
beetle. The mean oxidant injury scores for those trees killed by the
Jeffrey and western pine beetles were the lowest for their respective
host trees. This may explain why these two beetles are the most common
killers of ponderosa and Jeffrey pine in southern California as they are
more successful on the more seriously weakened trees. This is only a
trend, and a more extensive pest damage inventory will need to be under-
taken to resolve this question.
Conclusion
Western Pine Beetle
Based on comparisons with population studies of the western pine
beetle in other regions of California, it appears that oxidant-stressed
trees influence several aspects of western pine beetle biology. There is
a greater difference in attack rates between generations than occurs
in other areas of California, and this indicates that oxidant-stressed
trees are killed by fewer beetles than non-stressed trees. All popula-
tion variables measured are more variable and erratic in southern Califor-
nia, which may indicate that the interaction of smog-weakened trees and
western pine beetles is unique and that this relationship is more direct
165
-------
than previously thought. A survey of the vegetation plots showed the
western pine beetle to be the most common killer of ponderosa pine. In
addition, this beetle appears to attack the more seriously oxidant-damaged
trees.
Mountain Pine Beetle and Jeffrey Pine Beetle
On the basis of a limited sampling study of the mountain pine beetle
in ponderosa pine, and the Jeffrey pine beetle in Jeffrey pine, the most
efficient sample unit was found to be 500 cm . The mountain pine beetle
was not as common in dead ponderosa pine on the vegetation plots as the
western pine beetle. The Jeffrey pine beetle was the most common killer
of Jeffrey pine.
Priorities for Future Research
It appears from the preliminary analysis of these data that population
sampling of the western pine beetle and the Jeffrey pine beetle should be
continued. In addition, an extensive survey of ponderosa and Jeffrey pine
mortality should be undertaken. During the 1976-77 year, emphasis will
be put on the analysis of the population data. In addition tree
mortality records will be examined.
166
-------
TABLE 24. WESTERN PINE BEETLE-INFESTED PONDEROSA PINES RANKED BY OXIDANT
DAMAGE CLASSES AND BEETLE GENERATIONS, 1973-1975.
D. brevicomis
generation
1973-1
1973-2
1974-1
1974-2
1975-1
1975-2
Very severe
(1-8)
0
3
2
5
2
2
Severe
(9-14)
0
3
3
4
2
0
Damage
Moderate
(15-21)
2
4
0
1
0
2
Class
Slight
(22-28)
6
0
7
2
2
0
Very slight
(29-35)
3
0
0
0
0
1
No visible
symptoms
(36 +)
1
2
0
0
0
1
Totals 14 12 9 17
167
-------
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168
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TABLE 26. PRELIMINARY ANALYSIS OF NUMBER OF ATTACKS AND GALLERY LENGTH
FOR THE MOUNTAIN PINE BEETLE FROM VARYING BARK SAMPLE SIZES
(DATA CONVERTED TO 1000 cm2 FOR COMPARISON). EPA, SAN
BERNARDINO AIR POLLUTANT STUDY, 1974.
Number of
Location of
sample
Base of
infestation
Middle of
infestation
Top of
infestation
Sample
size
(cm2)
100
100
250
500
1000
100
100
250
500
1000
100
100
250
500
1000
Number
of
samples
10
10
10
10
10
9
9
9
9
8
10
10
10
8
6
Mean
3.00
4.00
3.60
3.00
3.00
5.56
5.56
4.00
2.89
3.00
0
0
0
1.00
1.50
Attacks
Standard
deviation
6.75
9.66
3.98
3.43
2.71
5.27
5.27
3.46
1.76
2.45
0
0
0
1.51
1.97
Gallery Length
Number
of
samples
10
10
10
10
10
10
10
10
10
9
10
10
10
8
5
Mean
(cm)
246.0
278.0
243.6
230.8
195.5
230.0
266.0
253.2
243.8
216.8
142.0
160.0
141.6
159.8
147.8
Standard
deviation
(cm)
182.9
198.3
155.9
123.5
95.1
114.8
130.8
120.4
87.0
78.2
99.4
113.2
80.8
93.9
129.3
169
-------
TABLE 27. PRELIMINARY ANALYSIS OF NUMBER OF ATTACKS AND GALLERY LENGTH
FOR THE JEFFREY PINE BEETLE FROM VARYING BARK SAMPLE SIZES
(DATA CONVERTED TO 1000 cm2 FOR COMPARISON), EPA, SAN
BERNARDINO AIR POLLUTANT STUDY, 1974.
Number of Attacks
Location of
sample
Base of
infestation
Middle of
infestation
Top of
infestation
Sample
size
(cm2)
100
100
250
500
1000
100
100
250
500
1000
100
100
250
500
1000
Number
of
samples
12
12
12
12
12
12
12
12
12
12
' 12
12
12
12
12
Mean
3.33
3.33
2.00
3.33
2.83
3.33
3.33
2.67
2.83
2.91
2.50
4.17
2.33
2.67
2.42
Standard
deviation
4.92
4.92
2.09
2.31
1.58
6.51
6.51
4.29
3.01
2.57
4.52
5.15
3.17
2.87
2.35
Gallery Length
Number
of
samples
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
Mean Standard
(cm) deviation
146.7
156.7
144.3
144.5
136.7
135.8
141.7
133.3
117.7
112.8
71.67
89.17
82.00
80.00
84.25
(cm)
89.98
96.42
63.04
56.90
52.81
107.7
112.4
78.32
67.30
57.05
59.52
69.86
62.93
59.60
52.47
170
-------
TABLE 28. TOTAL ARTHROPODS REARED FROM PONDEROSA PINE BOLTS INFESTED WITH
MOUNTAIN PINE BEETLE FROM THREE HEIGHTS IN 1974, SAN BERNARDINO.
Arachnida
Araneae 3
Pseudoscorpionida
Chernetidae 68
Insecta
Hemiptera
Anthocoridae
Lyctocoris sp. 2
Species #2 1
Unknown nymphs 8
Neuroptera
Inocelliidae
Inocellia sp. 14
Raphidiidae
Agulla sp. 52
Chrysopidae
Species #1 1
Unknown larvae 2
Coleoptera
Histeridae
Plegaderus sp. 338
Platysoma sp. 10
larva //I 18
larva #2 2
Scaphidiidae
Species #1 1
Staphylinidae
Nudobius sp. 4
Species #2 1
Dermestidae
Species //I 2
Ostomidae
Temnochila sp. 119
Tenebroides sp. 4
Cleridae
Enoclerus sp. 171
Species #4 4
Rhizophagidae
Rhizophagus 2
Cryptophagidae
Salebius sp. 3
Nitidulidae
Species #1 1
Lathridiidae
Corticaria sp. 12
Colydiidae
Lasconotus sp.
Aulonium sp.
Othniidae
Othnius sp.
Tenebrionidae
Corticeus sp.
Melandryidae
Rushia sp.
Bostrichidae
Species #1
Curculionidae
Cossonus sp.
Lechriops sp.
Scolytidae
Dendroctonus
valens Lee.
D. brevicomis
Pityokteines sp.
Gnathotrichus sp.
Unknown larvae
Species #3
Lepidoptera
Unknown species
Diptera
Ceratopogonidae
Species #1
Sciaridae
Species #1
Scatopsidae
Species #1
Cecidomyiidae
Species #1
Stratiomyidae
Zabrachia sp.
Scenopinidae
Belosta sp.
Empididae
Drapetis sp.
Dolichopodidae
Medetera sp.
Species #2
Phoridae
Species //I
10
138
28
38
127
14
293
1
1
11
307
32
256
233
21
1
5
289
27
11
7
2
51
171
-------
TABLE 28. (CONTINUED)
Diptera (continued)
Londraeidae
Species #1 33
Milichiidae
Species #1 22
Drosophilidae
Species #1 8
Sarcophagidae
Species #1 2
Unknown larvae
Species //I 116
Hymenoptera
Braconidae
Species #1 2
Species #2 1
Encyrtidae
Species #1 8
Species #4 2
Species #6 1
Torymidae
Roptrocerus sp. 81
Pteromalidae
Species #1 5
Bethylidae
Species #1 1
Formicidae
Species #2 1
Sphecidae
Pemphredon sp. 1
172
-------
TABLE 29. TOTAL ARTHROPODS REARED FROM JEFFREY PINE BOLTS INFESTED WITH
JEFFREY PINE BEETLE FROM THREE HEIGHTS IN 1974, SAN BERNARDINO.
Arachnida
Araneae
Pseudoscoptionida
Chernetidae
Insecta
Neuroptera
Inocelliidae
Inocellia sp.
Raphidiidae
Agulla sp.
Coleoptera
Scaphidiidae
Species #1
Staphylinidae
Species #1
Species #2
Species #4
larvae
Clambidae
1 species
Dermestidae
Megatoma sp .
larvae #1
Malachiidae
Species #1
Ostomidae
Temnochila sp.
Cleridae
Enoclerus sp.
Species #3
Buprestidae
Larvae #1
Rhizophagidae
Rhizophagus sp.
Crypt ophagidae
Salebius sp.
Nitidulidae
Species #1
Colydiidae
Lasconotus sp.
Aulonium sp.
Othniidae
Othnius sp.
156
31
3
2
1
1
1
1
25
1
1
13
1
44
57
15
12
1
8
2
3
1
21
Tenebrionidae
Larvae #1
Curculionidae
Cossonus sp.
Scolytidae
Ips pini Lanier
Ips latidens (LeC)
Pityokteines
ornatus (Swaine)
Gnathotrichus sp.
Unknown Larvae #1
Lepidoptera
Larva #1
Species #2
Diptera
Ceratopogonidae
Species #1
Mycetophilidae
Species #1
Sciaridae
Species #1
Scatopsldae
Species //I
Cecidomyiidae
Stratiomyidae
Zabrachia sp.
Scenopinidae
Belosta sp.
Empididae
Drapetis sp.
Dolichopodidae
Medetera sp.
Species #2
Phoridae
Species #1
Milichiidae
Species #1
Unknown larvae
Species //I
Species //2
Species #4
26
1
1
2
3
189
1
1
1
2,993
1
40
1
7
28
2
9
7
1
224
23
91
98
27
173
-------
TABLE 29. (CONTINUED)
Hymenoptera
Braconidae
Species #1 12
Encyrtidae
Species #1 10
Species #2 1
Species #3 10
Species #4 2
Species #5 1
Avetienella sp. 3
Eurytomidae
Eurytoma sp. 2
Diapriidae
Species #1 1
Formicidae
Species #1 24
Colletidae
Species #1 1
174
-------
TABLE 30. PRELIMINARY SUMMARY OF FINAL SMOG DAMAGE RATINGS- FOR PINES
KILLED BY INSECTS ON ESTABLISHED VEGETATION PLOTS, 1973-1975.
Tree , Insect,
Species species+7
I/
t/
PP D.b.
PP D.p.
PP Mixed (D.b.
Broods +D.p.)
PP Ips & M.c.
(combined)
JP D.j.
JP Mixed (D.j.
Broods +Ips)
Number Oxidant
of
trees Mean SD
17 9.9 6.3
7 10.4 6.3
8 11.8 8.6
5 15.2 10.0
7 11.6 6.7
4 13.0 8.2
All Scores given by P. Miller except those from 1973.
PP = ponderosa pine; JP = Jeffrey pine
D.b. = Dendroctonus brevicomis; D.p. = D. ponderosa; D
Ips = Ips sj>.; M.c. = Melanophila calif ornica.
injury score
SE Range
1.5 1-21
2.4 6-25
3.0 1-30
4.5 2-32
2.5 3-19
4.1 4-23
.j . = D. Jeffrey!
175
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176
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ROOT PATHOGEN DYNAMICS AND STAND MORTALITY
Introduction
Pathogens have a subtle, but often profound influence on a forest eco-
system. Their activity may affect the rate and even the direction of
successional changes (Baxter, 1952; Smith, 1970), the occurrence of plant
species, and the overall productivity of the plant community. Thus,
fundamental information on the effects of photochemical air pollutants on
the activities of forest pathogens is essential in developing models to
predict long-term effects of pollutants on the forest ecosystem as a whole.
There are many potential pathogens in any forest, including viruses,
bacteria, fungi, and higher plant parasites such as the mistletoes. Some
may infect the whole plant, whereas others may be limited to foliage, the
branches, stems, or roots. Many pathogens may have little effect upon
the forest; however, others may have a devastating effect. To determine
the effects of air pollutants on all forest pathogens is clearly beyond
our practical capabilities. Thus, to limit the scope of the study while
developing an initial estimate of the effects of pollutants, we have chosen
two approaches.
First, we attempted to develop a general overview of the potential
effects of air pollutants on disease incidence and severity through a
disease survey. All trees on 18 permanent study sites established across
the oxidant air pollutant gradients in the SBNF were examined periodically.
Each tree was examined for diseases of roots, stems, branches, and foliage.
Rates of increase or decrease in the occurrence of disease were determined
through periodic examinations (at least once every two years) for the
duration of the study. Data were analyzed to determine the relationship
between disease incidence and oxidant air pollutant levels.
Second, we conducted intensive studies of selected pathogens to
determine the effects of oxidant air pollutants on their occurrence and on
the various stages of their life history. To date, studies have been
initiated on one specific pathogen, Fomes annosus (Fr.) Cke. The selection
of this pathogen was based on (1) the known or potential importance of the
pathogen in the plant community under investigation; (2) the potential
importance of the pathogen in the plant succession model; (3) interactions
with other components of the system being studied; and (4) present knowledge
of the pathogen, the facility with which it can be studied, and potential
application of the results.
J?. annosus is usually considered to be one of the most destructive
root pathogens in conifer forests of California (Bega and Smith, 1966).
177
-------
Hosts include ponderosa and Jeffrey pine, both of which are adversely
affected by oxidant air pollutants. f\ annosus has been found to cause
damage to these species in the San Bernardino Mountains. However, the
effects that oxidant air pollutants may have on susceptibility of ponderosa
and Jeffrey pine to infection and colonization by the fungus are unknown.
Also the ability of the fungus to live, proliferate, and cause disease
in an environment with oxidant air pollution is unknown.
The following model (Fig. 54) indicates areas where oxidant air
pollutants probably have direct and indirect effects on disease development
by the fungus.
GENETIC ADAPTABILITY
OF THE FUNGUS
SPOROPHORE
PRODUCTION
INOCULUM
DISPERSAL
INFECTION OF
FRESHLY-CUT
STUMP SURFACES
SYMPTOM EXPRESSION
AND DEATH
PHOTOCHEMICAL
AIR POLLUTION
COLONIZATION OF
STUMPS AND ROOTS
LIVE TREE
COLONIZATION
LIVE TREE ROOT
INFECTION
Figure 54. Conceptual model of oxidant effects on the Fomes annpsus
root disease.
This study was established primarily to determine the effects of pol-
lutants on the life history of F_. anno s us as outlined above. Field studies
were used as much as possible, since results would be more applicable to
actual conditions in the forest. However, certain controlled-environment
investigations were necessary to monitor ozone concentration and other
environmental factors closely, and to properly establish cause and effect
relationships. Study sites were chosen based on species location and
presence of oxidant air pollutant injury. Ponderosa and Jeffrey pines were
the two tree species used in the study.
178
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Methods and Materials
Rates of Local Spread and Tree Mortality
Naturally occurring ]?. annosus infection centers, primarily in
ponderosa and Jeffrey pines, were plotted and exmained annually to de-
termine the rate at which the fungus apparently moves through roots to
infect adjacent trees, and the rate of tree mortality in these centers.
Wherever feasible, these plots were located along the air pollution
gradient. Data were recorded on the tree species, diameter (BH), height,
crown class, pollution damage, and any symptoms of _F. annosus, insect, or
other pathogen activity.
Susceptibility of Roots of Young Sawtimber Trees
To compare Y_. annosus susceptibility of existing trees showing light
and severe oxidant air pollution injury, inoculation of roots with the
fungus was necessary. The 42 trees (ponderosa and Jeffrey pine) used in
this study were mostly codominant and averaged 38 cm DBH. Two roots of
each tree were inoculated and analyzed for infection and colonization at
the end of 6 and 12 months.
Tree Seedling Susceptibility
A controlled environment experiment was undertaken to determine the
susceptibility to JF. annosus of ponderosa and Jeffrey pine seedlings
fumigated at ozone concentrations of 431.2 and 882.0 yg/m . A suitable
number of noninoculated and nonfumigated controls were included. Seed-
lings used in this experiment were grown initially in activated charcoal-
filtered greenhouses and, therefore, were not exposed to ambient air
pollutants.
Susceptibility of Freshly-Cut Stumps
F_. annosus often spreads to new areas by infecting the surface of
freshly cut stumps. Infection centers are established when the fungus
moves from infected stumps to adjacent live trees through root grafts and
contacts. To investigate this type of infection, ponderosa and Jeffrey
pine trees in each of two groups"none" to "slight," or "severe" to
"very severe" oxidant injurywere cut and their stumps inoculated with
a conidial suspension of the fungus.
Laboratory Decay Studies
JF. annosus generally causes decay of the wood of infected trees. Thus,
studies evaluating the decay capacities of the fungus on wood from air
pollution-injured trees were initiated. Wood from ponderosa pine trees,
cut for the stump inoculations, was used in a standard soil-block decay
test (American Society for Testing and Materials, 1973) to determine decay
rates expressed as weight loss over time. In addition to _F. annosus,
Poria monticola Murr. and Polyporus versicolor (L.) Fr., two standard
decay fungi, were used in this study.
Cultural Studies
Because F_. annosus as well as its hosts is exposed to air pollutants
in the San Bernardino Mountains, studies are being conducted to determine
the direct effects of ozone on the fungus. Effects on growth, production, and
179
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germination of reproductive spores, and genetic adaptability of the fungus
are being studied. This entails fumigating fungus cultures in specially
constructed growth chambers with various levels of ozone.
Miscellaneous Studies
A number of additional studies have been initiated recently. One
is designed to evaluate inoculum concentration of F_. annosus by sampling
the spore load at a number of sites throughout the San Bernardino Mountains.
Such evaluations will help determine the effects of oxidants on sporula-
tion and the relative hazard of _F. annosus at this time.
Also, studies were begun in 1976 to determine by seedling inoculations
whether ozone can influence virulence of F_. annosus. Such an evaluation
is potentially important in assessing overall oxidant effects on the
pathogen.
Results and Discussion
Rates of Local Spread and Tree Mortality
Thus far, ten plots have been established and more (up to 21) were
planned for 1976. These plots will be studied for the duration of the
project. To date, data has been taken twice on the initial plots, but at
least another year will be needed to analyze for trends in rates.
Susceptibility of Roots of Young Sawtimber Trees
All data have now been collected from the first series of inoculations,
and the results are sumarized in Table 31. Regression analyses of pollutant
damage vs. total root colonization indicated no significance at P=0.05
for either ponderosa or Jeffrey pine.
Proximal movement of F_. annosus (toward the tree trunk) is probably
a better indicator of host susceptibility, especially when compared to that
which occurs in severed roots. A regression analysis indicated that the
relationship between pollutant damage and proximal colonization for ponder-
osa pine was significant at P=0.01; for Jeffrey pine, the relationship
was not significant. It should be pointed out, however, that numbers
of Jeffrey pine inoculated were severely restricted, none of the Jeffrey
pine was severely damaged by pollutants, and the test was confounded by
moderate-severe damage by a needle miner.
Another root inoculation trial involving 20 ponderosa pines was
established to confirm the results indicated Table and to test _F. annosus
isolate variability. Also, an additional inoculation trial of 62 trees
was initiated to test variability of different pathogen isolates in an
area where oxidant air pollution is not an influencing factor.
Tree Seedling Susceptibility
The percentage of infection of fumigated seedlings was greater than
that of nonfumigated seedlings (Table 32). A simple comparison between
all ozone and control treatments showed statistically significant
differences in colonization among treatments for ponderosa and Jeffrey pine
180
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TABLE 31. INFECTION AND COLONIZATION BY FOMES ANNOSUS OF OXIDANT INJURED
JEFFREY AND PONDEROSA PINE TREES IN NATURAL STANDS
Tree
species
Jeffrey pine
Jeffrey pine
Jeffrey pine
Ponderosa pine
Ponderosa pine
Ponderosa pine
Pollution
in j ury
None
Slight
Moderate
Slight
Moderate
Severe
Infection
(%)
56.3
53.3
41.7
43.7
75.0
45.0
Average
colonization*
(cm)
36.3
23.1
21.6
14.7
18.2
21.6
^Colonization includes distal and proximal movement by the fungus.
Average values include only those roots which became infected.
at the 5% and 25% levels, respectively.
If the data were considered according to the time of inoculation with
respect to length of ozone fumigation, it was found that the rate of coloniza-
tion of host tissue was also significantly greater at the highest ozone
doses.
For example, in the first inoculation schedule, one-third (8) of all
seedlings in each of eight fumigation cubicles were inoculated on June 21.
Fumigation began several days later and continued until August 23 (day 58),
when these seedlings were removed for confirmation of infection and measure-
ment of the fungal invasion above and below (cm) the inoculation point.
A zero was given when no infection occurred. The total doses were 3.0 and
6.1 X 105 yg/nP -hr, respectively, and were administered at concentrations
of 431 and 882 yg/m , respectively. Two control groups of 8 seedlings,
each of which had been maintained in carbon-filtered air in identical
cubicles, were removed for evaluation at the same time. An analysis of
variance shows that 95 times out of 100 there were no differences in
disease development between control and fumigated seedlings as measured
by movement of the fungus in root crown tissues. The ozone injury scores
at 3.0 X 105 Ug/nr -hrs, determined by the same method as in Fig. 39, were
4.0 and 6.3 for ponderosa, 10.6 and 11.1 for Jeffrey pine.
In the second inoculation schedule, 8 additional seedlings in each
fumigation cubicle were inoculated on August 8, after 37 days of ozone
181
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TABLE 32.INFECTION OF OZONE FUMIGATED AND UNFUMIGATED JEFFREY AND PONDEROSA
PINE SEEDLINGS BY FOMES ANNOSUS
Pine
species
Jeffrey
Jeffrey
Jeffrey
Ponderosa
Ponderosa
Ponderosa
No.
seedlings
32
16
16
32
16
16
Fumigation
cone. (03)
(Pg/m3)
0.
431.2*
882.0
0.
431.2
882.0
Infection
(%)
53.1
75.0
81.0
62.0
81.0
75.0
*Seedlings at each concentration were exposed for a period ranging
between 58 and 87 days.
fumigation or filtered-air treatment. Fumigation was continued for an
additional 50 days at the same concentrations, after which seedlings were
removed and disease development was determined. The total ozone doses were
4.5 and 9.2 X 105 yg/m3-hr. In Table 33, a definite trend toward increased
disease development is indicated at the highest ozone dose. The results
show that 95 times out of 100, the largest total dose resulted in greater
disease development when the combined ponderosa and Jeffrey pine populations
from the 9.2 X 10 Ug/m -hr dose were compared with one control group using
Duncan's multiple range test. Needle injury scores were very similar
at both doses and for both species.
The 8 seedlings remaining in each cubicle were not inoculated. Each
tree was observed periodically to compare ozone injury scores with inocu-
lated seedlings, but no differences were evident. In addition, unfumi-
gated, uninoculated control plants showed no evidence of foliage injury.
Although these results cannot be extrapolated to explain disease
development in natural stands of larger trees, they did show that ozone
treatments cause a higher percentage of infection and a higher coloniza-
tion rate of seedlings by _F. annosus.
Susceptibility of Freshly-Cut Stumps
Results of infection and surface colonization studies indicates that
all inoculated sumps became infected. Results obtained thus far are
182
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TABLE 33. RELATIONSHIP OF CHRONIC OZONE INJURY OF PONDEROSA AND JEFFREY
PINE SEEDLINGS TO COLONIZATION OF ROOT CROWN TISSUE BY FOMES
ANNOSUS.
Ponderosa
Ponderosa
Combined
Treatment
Filtered air, 1
Filtered air, 2
Ozone, 4.5
Ozone, 9.2
Average
oxidant
inj ury
score
0.
0.
16.9
17.5
Fungus
movement
(cm)
0.3A*
1.3A
0.9A
3.4A
Average
oxidant
inj ury
score
0.
0.
13.3
14.9
Fungus
movement
(cm)
0.5A
1.5A
1.5A
3.4A
Fungus
movement
(cm)
0.4AB
1.4ABC
1 . 2ABC
3.4BC
Values followed by the same capital letters are not significantly
different 95 times out of 100.
4. o c
Ozone dose as vig/m-hr x 10 .
summarized in Table 34.
Regression analyses have been completed for "percent surface colonized"
vs. pollutant damage score. The significance levels are as follows: pon-
derosa pine at Barton Flats, P = 0.025; ponderosa pine at Camp Paivika,
P= 0.01; Jeffrey pine at Amphitheatre, P = 0.25.
Analyses for downward colonization after six months showed no
significance at P = 0.05 for either species. The greater rate of downward
colonization in Jeffrey pine may be due to seasonal differences. In
Jeffrey pine, stumps were inoculated in the spring and dissected the next
fall. In ponderosa pine, stumps were inocluated in the fall and dissected
the following spring.
Analyses for average stump volume colonized indicated significance for
Jeffrey pine at P = 0.10, and for ponderosa pine P = 0.25. The inocula-
tions on ponderosa pine at Camp Paivika have not yet been dissected to
determine downward colonization and volume colonized.
From these data, it appears that air pollution injury increases the
susceptibility of pine stumps to colonization by F_. annosus. The
differences between severely and slightly damaged trees indicate an
approximate increase of 100% in surface colonization and about a 50%
increase in the rate of colonization over time.
183
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Laboratory Decay Studies
For the J\ annosus test, differences existed (P = 0.05) showing that
wood from trees slightly damaged by air pollution was more decay-susceptible
than wood from severely damaged trees. However, conclusions are difficult
to reach because of the low percentage (avg. ca 1.5%) weight loss involved.
The test using Poria monticola resulted in greater weight loss
(x = 60.8%) in wood from severely damaged trees than in wood from slightly
damaged trees (x = 59.4%). Differences were significant (P = 0.05). For
Polyporus versicolor, the same relationship held (x = 42.0% - severe;
40.7% - slight); however, no significant difference occurred.
These results with ]>. monticola and J?. versicolor corroborate those
reported in the following section ("Woody Litter Decomposition Subsystem")
where the meaningfulness of very small differences in decay rate is seriously
questioned. The actual quantitative differences are difficult to assess at
the present time, and additional work is necessary to properly evaluate
the differences.
Cultural Studies
These studies have just been initiated. Preliminary work indicates
that ozone may restrict asexual spore formation in culture; as yet, no
quantitative effect on growth rate has been determined.
Miscellaneous Studies
No results from these studies are yet available.
184
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185
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TREE SEEDLING ESTABLISHMENT SUBSYSTEM
Introduction
Factors Affecting Seed and Seedling Survival
The regenerative phase of any forest stand is one of the most important
aspects of that stand's biology. Factors affecting seedling establishment
are numerous. The health of the cone-producing tree affects the number and
quality of cones produced. Weather, disease, insects, avian and mammal pre-
dators, and air pollution further determine how many sound seeds are
produced and how many survive in the cones. After seeds are shed and before
they germinate, they are subject to disease, predation by vertebrates and
invertebrates, and such abiotic factors as adverse temperature or moisture
conditions. When germination begins, the mortality factors include the
same general categories but possibly with different organisms. Similarly,
the seedling that survives this far may be killed by any of these mortality
factors including air pollution.
Research Objectives
Assays for Incidence of Saprophytic and Pathogenic Fungi in Surface Soils
Three subobjectives are included. These objectives are:
1) Determine the effect of photochemical air pollutants on soil fungus
populations;
2) Determine the abundance of traditional damping-off fungi, specifi-
cally Rhizoctonia and Pythium present in soil across the photo-
chemical air pollution gradient;
3) Determine the abundance of damping-off organisms in the organic
horizons compared to those in the mineral soil.
Sampling the Combined Influences of Seed Bed Condition, Fungi, Insects, and
Small Vertebrates on Seed and Seedling Survival in the Field
The three subobjectives are as follows:
1) Determine the individual and joint effects of predators and pathogens
on seeds and seedling establishment, and to investigate the in-
fluence of pollution on these interactions by establishing the study
in stands across an air pollution gradient.
2) Determine the relative importance of pre-emergence damping-off as
opposed to post-emergence damping-off.
3) Determine the interaction between litter (quantity and quality) and
186
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the joint effects of the vertebrates, insects, and pathogens on
seedling establishment.
Materials and Methods
Sampling for Soil Fungi
Comparison of populations by dilution isolationsSoil samples were col-
lected from Breezy Point, Camp Osceola, Camp Congo, Northeast Green Valley,
Sky Forest and Snow Valley by using a 3-in diam. tube sampler. Samples
were maintained at 2° F until analyzed.
Soils were put through a 2 mm sieve. Then 1 g of soil was added to
100 ml sterile water. This was agitated 60 sec before pipetting 1 ml of
the solution to 9 ml sterile water. Agitation and dilution were continued
to the desired dilution ratio. Using a sterile pipette, we dispensed 1
ml of each dilution onto labelled petri dishes. Twelve ml of media at
45°-50° C was poured over each plate and the contents swirled to mix them.
After 4 days at room temperature, the dilution showing at least 15
colonies/plate was counted and selected cultures were made. Five replica-
tions were made for each dilution. The medium used was Potato Dextroxe
Agar with 10,000 ppm streptomycin and 1,000 ppm Tergitol.
Isolation of Rhizoctonia spp. and Pythium spp.Soil samples were
collected from Breezy Point, Camp Osceola, Camp Congo, Holcomb Valley,
Northeast Green Valley, Sky Forest, and Snow Valley by using a 3-in diam.
tube sampler. Samples were maintained at 2° F until analyzed.
To sample for Rhizoctonia spp. each sample of the organic matter in
a known quantity of soil was washed from the soil and distributed sparsely
on melted water agar in large petri plates. The plates were incubated at
24° C and checked at 18, 24, 36, and 96 hr for Rhizoctonia colonies.
Suspect colonies were cultured to confirm identification.
To sample for Pythium spp. each 4-g sample of soil was put through a
.20 mm sieve, then blended for 60 sec with 100 ml sterile water. Four ml
of this suspension were then dropped in .10 ml increments on 3-day-old
water agar plates. Plates were checked for growth 18-24 hr later and
Pythium-like mycelium were cultured as a second check.
Influence of fungi in mineral soil and surface litter on seedling
emergence in the greenhouseFlats of mineral soil and organic material from
heavily and mildly smog-affected sites were collected and planted with
Jeffrey and ponderosa pine seed. The number of emerging seedlings was
noted at frequent intervals and any seedling exhibiting damping-off symptoms
was taken to the laboratory for culture.
Sampling for the Influences of Combined Factors on Seed and Seedling
Survival in the Field
Preliminary study of screened and unscreened seed on surface soil with
and without litterA preliminary field study established in May, 1975
at Barton Flats, Camp Congo, Camp Osceola, and Holcomb Valley followed the
status of 3,136 seeds over a one-month period. Four trees on each of four
187
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sites were selected with 2 of the 4 relatively healthy and 2 unhealthy
with regard to air pollution injury. Four mini-plots were located outside
the crown drip line of each tree. The mini-plots for each tree consisted of
four treatments:
1) screened with the organic horizon removed;
2) screened with the organic horizon intact;
3) unscreened with the organic horizon removed;
4) unscreened with the organic horizon intact.
Seeds collected from the SBNF during the Fall of 1974 were used to
plant the mini-plots.
Comparative survival of screened and unscreened seed on surface soil
with and without litter in different seasonsIn November, 1975, seeds were
collected from healthy Jeffrey pine trees in the SBNF and used in a field
study on Camp Osceola, Barton Flats, Holcomb Valley, and Heart Bar. The
study was designed with the cooperation of Dr. D. Dahlsten, Dr. M. White,
and S. Sweetwood to provide information on the amount and type of seed
predation by small vertebrates and arthropods as well as to determine
whether differences in seedling establishment due to pathogenic fungi were
related to the presence and depth of the organic horizons or to the severity
of oxidant levels.
Twenty-eight mini-plots (36 x 36 x 7 cm wood frames with and without
% in galvanized screen) on each of the four sites were planted with Jeffrey
pine seed. On each site the mini-plots were placed in 4 groups of 6 each
and 1 group of 4. The groups of 6 mini-plots included the following
treatments:
1) 2 mini-plots screened witfy the organic horizons removed;
2) 2 mini-plots screened with the organic horizons intact;
3) 1 mini-plot unscreened with the organic horizons removed;
4) 1 mini-plot unscreened with the organic horizons intact.
The group of 4 mini-plots included one each of the 4 treatments listed
above.
In Februrary, 1976, the group of 4 mini-plots on each site was destruc-
tively sampled to determine the status of seeds after three months in the
field. These plots were then replanted. The sites were visited on May 19,
June 7, and June 25, 1976. Each time observations were made and dead or
dying seedlings were brought back to the laboratory for determination of the
cause of death. Seed collected from the February sampling were x-rayed to
check for lesions, empty seeds, and any other abnormalities that would
indicate an inability to germinate. Abnormal seeds were dissected and
188
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"normal" seeds were germinated under controlled conditions to check the
X-ray interpretations. Seedlings brought back to the laboratory were surface-
sterilized before isolations were made from tissue showing disease symptoms.
Results and Discussion
Assays of Soil Fungi
Population differences at sites experiencing different chronic
oxidant dosesA preliminary analysis of variance of fungal populations
among the six plots sampled showed that a significant difference exists
among the plots at the. .01% level. Further analyses will help determine
whether there are population differences primarily due to air pollution,
but no trends are obvious at this stage of analysis. The factors affecting
soil fungus populations are very complex. Detailed studies are necessary
to better understand the role of photochemical air pollution on these
organisms. No further data collection is planned.
Rhizoctonia spp. and Pythium spp. at sites experiencing different
chronic oxidant dosesSoil assays yielded no Rhizoctonia spp., and
Pythium spp. was isolated only once on each of two sites (Breezy Point and
Sky Forest) which have "moderate-to-severe" air pollution injury. These
sites were characterized by well-developed soils (Shaver series) beneath
mixed conifer stands with ponderosa pines. Subsequent studies on seed
microflora and litter decomposition studies by J. N. Bruhn have indicated
that Pythium and Rhizoctonia may not occur in the humus layer either.
We may conclude that neither Rhizoctonia spp. nor Pythium spp. are among
the important damping-off pathogens in the forest soils examined. No
further work on this study is planned.
Seedling emergence from mineral soil or organic surface litter in
the greenhouseGermination of seeds sown in mineral soil seedbeds was
significantly greater (alpha = .01) than germination in seedbeds retaining
the natural organic layers. Table 35 summarizes seed germination for this
study.
TABLE 35. NUMBER OF SEEDS GERMINATED ON SEEDBEDS WITH AND WITHOUT THE
NATURAL ORGANIC LAYERS (400 SEEDS PLANTED IN EACH TREATMENT)
Vegetation plot Total
Nature Barton Camp Holcomb Camp
of seedbed Flats Oongo Valley Osceola Germ. Planted
(No. of seeds)
With organic
material 65 36 81 117 299 1600
Mineral soil
only 224 243 232 149 848 1600
Totals 289 279 313 266 1147 3200
189
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The organic horizons of the SBNF soil reduce successful germination of
Jeffrey and ponderosa pine seeds. More tests are needed to detail the
complex of biotic and abiotic factors causing these results.
Influences of Combined Factors on Seed and Seedling Survival in the Field
Preliminary studyAfter one month the mini-plots were examined. Table
36 summarizes seed status at the termination of the study. "Intact" refers
to the condition of the seedcoat. An "intact" seedcoat does not necessarily
mean the seed is gerininable.
TABLE 36. SEED STATUS 30 DAYS AFTER PLANTING.
Site
Barton Flats
Camp Osceola
Camp Oongo
Holcomb Valley
Totals
Planted
(No.)
784
784
784
784
3136
Recovered
(No.) (%)
313
201
485
360
1359
40
25
61
45
43
.0
.6
.9
.9
.3
Intact
(No.) (%)
178
154
457
288
1067
22.
19.
58.
36.
34.
7
6
3
7
3
Predated
(No.) (%)
135
47
28
72
282
17.
5.
3.
9.
9.
2
9
6
2
0
Of 3136 seeds planted, predators are known to have removed 9% and are
suspected of having removed a total of 60-66% of the seed. Seed predation,
occurring after seed fall, is one of the major causes of seed loss. Of
the remaining seed, only 0.3% germinated. Fungi are probably the cause of
this low germination rate, but more extensive studies are needed to define
their role. Identification of fungi associated with intact seed remaining
after one month showed seven fungus species occurring most frequently.
Survival in different seasonsOf 274 seeds checked from the February
sampling, 234(85%) germinated. Analysis for the study is in progress.
Periodic observations on the condition of the remaining seedlings will be
made throughout the remainder of the project. The current study design
should be expanded for future work on this problem.
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-CONE AND SEED PRODUCTION FOR DOMINANT CONIFER TREE REPRODUCTION
Introdution
To persist, a forest must reproduce itself. This involves the pro-
cesses of seed production, seed germination, and seedling establishment. In
coniferous forest species, seed production is accomplished by the production
of an annual cone crop whose abundance varies widely each year (Pearson,
1923; Roeser, 1941; Boe, 1954; Fowells and Schubert, 1956; Daubemire, 1960;
Larson and Schubert, 1970). The causes of these annual fluctuations are
unknown, but they are thought to be partially the result of weather
patterns (Maguire, 1956; Daubenmire, 1960; Lowry, 1966; Puritch, 1972).
Furthermore, each species differs in the amount and frequency of the cone
crops it produces (Fowells and Schubert, 1956). This difference, coupled
with differing requirements for seed germination, seedling establishment,
and seedling survival by each species determines the rate of change in the
species comprising a stand. Measuring the cone crop patterns of each
species thus becomes important in understanding stand succession.
The mixed conifer forests of the SBNF have had a history of photochem-
ical oxidant air pollution exposure, principally to ozone (Miller and
Millecan, 1971). Of the species comprising this forest type, ponderosa,
Pinus ponderosa Lawson, and Jeffrey pine,'£. jeffreyi Greville and Balfour
are the two most sensitive species (Miller and Millecan, 1971). In these
pines, exposure to ozone reduces the rate of photosynthesis and injures
the needle tissue. Both of these effects lead to premature needle ab-
scission (Miller £t _al., 1969; Evans and Miller, 1972: Miller, unpublished
data).
Ponderosa and Jeffrey pines injured by ozone have crowns which appears
similar to those used to define the low vigor classes employed in rating
pines subjected to higher risks of bark beetle attack (Keen, 1936) and in
evaluating the growth potential of pines following selective logging
(Hornibrook, 1939; Thompson, 1940). Larson and Schubert (1970), using the
vigor classes employed to evaluate growth potential (Thompson, 1940),
found that trees of low vigor (sparse complement of needles within the
crown) produced substantially fewer cones. Therefore, the sparse crown
foliage resulting from abscission of ozone-injured needles, coupled with
reduced photosynthesis in those needles that remain, suggest that oxidant-
sensitive trees may produce fewer and smaller cones, less frequent cone
crops, fewer seeds per cone, and lower seed viability. This subsystem is
indicated in Figure 55.
Research Objectives
There are two primary objectives to this study:
191
-------
1
ISEEDLINGSI*
_ , , ^
SPECIES ,
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X = CONTROL VALVE,
= MATERIAL TRANSFER,
- 'CONTROLLING INFLUENCE
=OXIDANT INFLUENCE
Figure 55. Conifer seed production subsystem.
1) To test the hypothesis that cone crop abundance and frequency
in ponderosa and Jeffrey pines are affected by ozone injury.
2) To describe the probability for a given tree of producing
a cone crop in a given year. A number of factors are known
to affect cone production (Fowells and Schubert, 1956; Larson
and Schubert, 1970); hence, this description will require the
identification of certain tree characteristics, such as species,
age class, vigor class, ozone-injury class, and other variables
such as temperature patterns or soil moisture depletion rates
which are likely to affect that probability. The description
will be used in a submodel of cone production and can be
integrated with a stand succession model.
Materials and Methods
Estimating Cone Crops
Cones within the crowns of all conifers on the 18 established plots
were counted visually with the aid of binoculars. Although these counts
underestimate the actual number of cones within the crown, they reveal the
pattern of annual cone production, identify those trees which produce cones,
and provide an order of magnitude estimate of cone abundance (Roeser, 1941;
Fowells and Schubert, 1956, Daubemire, 1960). Their inaccuracy, however,
suggests the need for a second estimate of cone abundance. This was
192
-------
It
IB
ID
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obtained by counting the cones after they have fallen to the grourd. They
were recorded by assigning them to the trees from which they fel_. In cases
where the crowns of two or more trees were interlaced, cones were parti-
tioned among the trees in proportion to the number of cones counted in each
of their crowns. (This latter point suggests a fourth reason for the need
of visual cone counts.) The cones were collected periodically in the spring
and summer of the year following production of a given cone crop. Very
few cones from the previous year's crop remain in the tree crowns by the
time the next crop is produced (Larson and Schubert, 1970). Counts of cones
on the ground are applicable only to the pines (sugar pine, ponderosa pine,
Jeffrey pine), and possibly to incense cedar, Libocedrus decurrens Torrey.
Cones can be counted on the ground and their year of production determined
(Pearson, 1923; Larson and Schubert, 1970). The cones of white fir, Abies
concolor, disintegrate in the process of seed dispersal.
Cones collected in the 18 plots were used to estimate the incidence
of cone insects, the incidence of predation on cones by squirrels, and the
frequency distribution of seeds produced per cone. The incidence of cone
insects was obtained by placing aborted or unopened cones in individual
containers and rearing out the insects they contain. The specimens which
emerged were identified and their damage characteristics determined. An
estimate of the number of seeds per cone was made by counting the number of
seed niches present in the bracts in fifty cones. These cones were also
cut along the axis and the presence or absence of insect damage noted. In-
cidence of cone predation by squirrels is evidenced as the number of immature
cones on the ground upon which feeding has occurred. The effect of squirrel
predation is being studied in conjunction with investigations on small
mammals.
Additional information was taken from trees on all of the plots. Trees
were classified on the basis of their age, height, crown class (Table 37),
vigor class (Fig. 56), length of live crown and location within a stand (on
the margin or in the interior). All these factors are known to be associated
with cone abundance and cone crop frequency (Powells and Schubert, 1956;
Larson and Schubert, 1970). These additional data have been taken on 8 of
the 18 plots. Additional plot and tree data was obtained from the other
subprojects and this subproject will supply data to them in return. Multi-
variate analysis (multiple regression, stepwise regression or variance-
covariance analysis, for example) will be used to identify the relationship
of cone crop to the independent variables discussed above.
Results and Discussion
Counts of Cone-Bearing Trees and Cone Production
Most of the data presented below is preliminary. The 1974 cone crop
was the first one counted visually in the 18 plots. Only a portion of the
plots were counted in 1973 because plot establishment was not completed
prior to the loss of many of the cones from the trees. Lack of these counts
prevented assigning the fallen cones to the trees from which they came in
those tree groups whose crowns interlaced. Furthermore, cone data for 1973
do not include losses due to insects or squirrels. The 1973 cone data,
194
-------
TABLE 37. DESCRIPTION OF CROWN CLASS CHARACTERISTICS
Crown Class
Description
Dominant
Trees whose crowns extend above the general
crown level.
Codominant
Intermediate
Intermediate open
Intermediate suppressed
Suppressed
Trees whose crowns form the general crown
level.
Trees whose crowns extend into the general
crown level.
Trees substantially smaller in diameter and
height than those that generally character-
ize the stand but are isolated, free to
grow on all sides.
Trees which are of similar diameter as those
which generally characterize the stand but
whose crown lies entirely below the general
crown level.
Trees which are smaller in diameter than
those which generally characterize the stand
and whose crown lies entirely below the
genera,! crown level.
however, provide a reliable estimate of the number of trees which produce a
cone crop. Ground counts of the cone crop began in spring 1975 and these
represent the count of the 1974 cone crop. Cones lost to insects, squirrels,
and unknown sources were incorporated into these counts. It should be noted
that most all of the additional tree and plot data are still being acquired;
thus, the effect of oxidants on cone production in ponderosa and Jeffrey pine
cannot be addressed, since the data are still in various stages of analysis.
Visual counts of annual cone crops (1973-76) born by ponderosa pine are
summarized in Table 38a,b; those for Jeffrey pine are summarized in Table
39a,b. Crown classifications used in Tables 38 and 39 are defined in Table
37. The visual counts for those cone crops are summarized by plot in
Appendix K.
A greater percentage of ponderosa and Jeffrey pine in the dominant
crown class produce cones; codominant ones are the next most frequent bearers
(Tables 38 and 39). Dominant ponderosa pines represent 33% of the indivi-
duals of this species present on the plots, but they account for 63% (60-
66% range) of the cone-bearing individuals and produce 68% (61-73% range) of
the cones born by this species. Similarly, dominant Jeffrey pines comprise
only 28% of the individuals of this species on the plots but account for
195
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58% (51-63% range) of the cone-bearing individuals and produce 85% (80-90%
range) of the cones born by this species. Clearly the dominant crown classes
are the greatest contributors to the cone crop. These findings agree with
those of Pearson (1923), Powells and Schubert (1956), and Larson and Schubert
(1970).
Tentatively, it appears that the type of tree which contributes the
most cones to a given annual crop has a large diameter (larger than 50 cm),
is isolated from its neighbors or on the margin of a stand, has a good com-
plement of needles, and belongs to the dominant crown class.
Seed Production
Twenty-five ground cones from each plot were used to estimate the 1975
seed crop. A sample size of 25 cones was chosen because the standard devia-
tion stabilized at this sample size and it generally provided a standard
error of at least 10% of the mean. The average number of seed impressions
per cone with the associated standard error for those plots which produced
cones (as measured by visual counts) in 1975 is summarized in Table 40.
Also Table 40 provides estimates for the number of seeds produced by each
plot.
There are two major sources of error associated with these estimates.
First, estimates of the number of seeds per cone include all seeds which
swelled enough to leave an impression in the bract. These estimates
include unfilled seeds; thus, they overestimate the number of viable
seeds per plot. Second, the number of cones per plot estimated by visual
cone counts underestimates the size of the cone crop. The smaller cone
crops are more subject to error since they are generally borne as single
cones on a branch. This tendency increases their likelihood of being
obscured by foliage. Larger cone crops are generally borne as clusters
on a branch and are thus more easily seen. Furthermore, the number of
cones per plot has not been corrected for losses due to insects, squirrels,
and unknown causes.
Even with these errors, however, it is clear from Table 40 that five
of the seven plots dominated by Jeffrey pine produced a substantial number
of seeds in 1975. The Snow Valley (SV) and Green Valley Creek (GVC) plots,
both of which produced a light cone crop in 1975, are both lower in eleva-
tion and more exposed to oxidant air pollution. However, inspection of
the cone crop data in 1974 indicates that the trend in the Jeffrey pine
plots was the reverse of that observed in 1975; GVC and SV had a heavier
1974 cone crop while the remaining 5 plots had lighter ones that year
(Appendix K). The increased cone crops on the 5 Jeffrey pine plots in
1,975 perhaps indicate a one year time lag in response.
Agents of Mortality: Insects
Table 41 lists those insect species which have been reared from
ponderosa and Jeffrey pine cones and identified by experts at the U.S.
National Museum. This list is incomplete because the cone moths and
chalcid hymenoptera (parasitoids) have not yet been returned from the
museum. Of those species listed in Table 41, two are generally thought
to damage cones: Conopthorus ponderosae Hopkins and the three species
200
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TABLE 40. ESTIMATES OF THE NUMBER OF EXPANDED SEEDS PER CONE AND
TOTAL SEED CROP PER PLOT FOR THE 1975 CONE CROP.
Plot
X
Seeds/
cone
Estimated
seed crop
Sample size
for seed/cone
estimate
Ponderosa Pine
BP
CAO
COO
CP
DW
SF
TUN 2
ucc
BL
GVC
HB
HV
NEGV
SC
SV
70
105
85
73
78
110
101
111
111
48
115
124
109
42
143
.77
.76
.24
.61
.60
.68
.52
.92
.76
.80
.92
.20
.48
.76
.56
±
±
+
±
±
±
±
±
±
±
±
±
+
±
±
6
3
6
7
9
4
2
6
5
2
8
5
4
3
7
.11
.61
.40
.22
.38
.19
.25
.03
Jeffrey Pine
.55
.38
.51
.51
.65
.33
.70
Mixed
1,332
740
341
1,472
2,206
6,751
812
895
18,216
732
106,762
56,883
30,544
79,747
143
22
25
25
23
10
25
25
25
25
25
25
25
25
50
25
SCR
101.52 ± 7.85
1,624
25
201
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TABLE 41. INDENTIFIED INSECT SPECIES REARED FROM JEFFREY AND PONDEROSA
PINE CONES.
Species observed
Role
Coleoptera
Scolytidae
Conophthorus ponderosa Hopkins
Ptinidae
Ptinus aguatus Fall
Cleridae
Cynatodera ovipennis LeC
Lathridiidae
Microgramme filuir Aube
Corticaria clentigera L.
Dermestidae
Megatomz (prob.) variegata Horn
Anobiidae
Ernobius melanoyentris (or near) Ruckes
Ernobius (prob.) montanus Fall
Ernobius socialist (or near) Fall
Neuroptera
Hemerobiidae
Sympherobius californicus Bks
Raphiidiae
Rhaphidia f lexa Carp
Dipter
Drosophilidae
Drosophila (Dorsilopha) busckii Coquillett
Chloropidae
Hapleginella cornicola Green
Chironomidae
Orthocladiinae
Hymenoptera
Braconidae
Eubazus sp
Apanteles sp
Chelonus (Microchelonus) sp.
Platygasteridae
Platygaster sp
Bethylidae
Cephalonomia hyalinipennis
attacks cones
attacks cones or
is a scavenger
predator
scavenger
s cavenger
scavenger
attacks cones
attacks cones
attacks cones
predator
predator
fungus feeder
scavenger
parasitoid
parasitoid
parasitoid
parasitoid
parasitoid
202
-------
of Ernobius. Cone losses to both the 1974 and 1975 cone crops were not
substantial.
Agents of Mortality: Squirrel
Squirrels accounted for the greatest loss of cones in both the 1974
and 1975 cone crops. This loss occurs in the second summer of cone matura-
tion, but the impact has yet to be assessed quantitatively. Further dis-
cussion of squirrel predation can be found in the section: "Small Mammal
Population Dynamics Subsystem".
203
-------
LITTER PRODUCTION SUBSYSTEM
Introduction
It is clear that air pollutants affect the production of litter from
the fact that the number and size of needles on the trees decline with
increasing air pollutant damage. In order to document the changes, we
measured litter production, mass and thickness of the forest floor, and
size and composition of needles in the litter fall under trees in various
stages of decline due to air pollutants. It was also assumed that changes
in the forest floor caused by change in the kind and amount of litter-
fall affect the upper part of the soil and the forest floor as habitats
for flora and fauna being studied in other subprojects. These changes
may be important to seedling survival and, thus, to the succession of
forest vegetation.
Research Objectives
This project had five research goals along the oxidant injury gradient:
1) To measure needle litter on the forest floor.
2) To measure the rate of needle litter accumulation.
3) To measure the nutrient content of needle litter from trees
with a range of oxidant injury.
4) To measure the effect of tree crown injury on interception of
precipitation and nutrient composition of crown drip.
5) To measure surface soil nutrients under ponderosa and Jeffrey
pines with range of oxidant injury.
Materials and Methods
Measuring Needle Litter on the Forest Floor
In order to document the status of accumulated organic matter (pine
needles, twigs, etc.) on the forest floor of the various study plots in re-
lation to the impact of air pollutants on the pine forest, the thickness of
the litter layer was measured at 2 m intervals along a line transect for
the length of the plots. In addition, core samples of the litter layer
were collected at 135 representative sites, in order to establish the
relationship between mass and thickness (T) of the layer in cm.
Measuring the Rate of Needle Litter Accumulation
204
-------
As a result of injury to vegetation due to oxidant air pollutant and
related pathogenic and bark beetle interactions, dead organic matter accumu-
lates on the forest floor in the form of needle litter and coarse woody
fragments.
Litter fall was collected on 0.209 m^ screens (18 in square) on 6 trees
in the fall of 1973 and under 39 trees in the fall of 1974. Oxidant injury
ratings ranged from 3 (severe injury) to 33 (slight injury) in 1973, and
from 9 (severe injury) to 44 (no injury) in 1974. Needles were separated
from other litter, and the mass per fascicle of needles was determined to
obtain a measure of the size of the needles in the litter fall. Total needle
and other litter weight were also measured. Needle-fall from selected trees
has been analyzed for its content of nitrogen, phosphorus, potassium,
calcium, and magnesium.
The organic forest floor was sampled with a core-cutter at 110 sites
under 52 pine trees variously affected by oxidant air pollutants, and
the mass per unit area was related to thickness. Using these data and
transect measurements of thickness on 12 major plots, we estimated the
total amount of litter on the forest floor. The forest floor was also
measured in radial lines from the trunks of somewhat isolated individual
pine trees and the pattern of needle litter accumulation on the forest
floor was determined.
Measuring the Nutrient Content of Needle Litter from Trees with a Range
of Oxidant Injury
The methods of analysis have been described above in "General
Description of Ecosystem Properties: Soils".
Measuring the Effect of Tree Crown Injury on Interception of Precipita-
tion and Nutrient Composition of Crown Drip
The amount, distribution, and composition of crown drip under pine
trees variously affected by air pollution injury was studied to examine
the effect of air pollution on the forest floor (litter layers) and the
surface soil. Nine ponderosa pine trees were sampled at the Camp Congo
plot, with oxidant injury ratings from 10 (severe) to 34 (slight). Random
radial lines of collector cans were set on stakes at 0.5 m intervals out
from the tree trunk to 1.0 m outside the drip line. Precipitation and
crown drip were collected and the volume measured at 173 sites, an average
of 19 samples around each tree immediately following the first period
of precipitation in the fall which occurred in the last week of October,
1974. Of these samples, 66 (7 or 8 per tree) were selected at random and
analyzed for calcium, magnesium, potassium, sodium, and phosphorus.
Crown drip was collected at 127 sites under 24 trees on the Camp Congo
plot following a single fall rain including a little light snow on October
31, 1975.
Measuring Surface Soil Nutrients Under Ponderosa and Jeffrey Pines with
a Range of Oxidant Injury
Soil samples collected from the surface of the mineral soil to a
depth of 7.5 cm under 40 pine trees (3 or 4 per tree) were analyzed for
the percentage of organic carbon and nitrogen, and exchangeable sodium,
205
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potassium, calcium and magnesium. The methods of analysis were described
above in "General Description of Ecosystem Properties: Soils".
Results and Discussion
Variation of Needle Litter Thickness on the Forest Floor
The relationship of litter thickness (T) to litter mass was calculated
by regression analysis: this showed that
Mass (kg/m2) = 1.249 T + 1.329
The correlation coefficient was 0.902, and the regression line was cal-
culated to be not significantly different from one passing through the
origin (T=0, Mass=0), which gave us the following equation:
Mass = 1.4 T
Using this equation, we calculated the average amount of litter on the
forest floor from the average thickness measured. However, we found that
the litter layer on the forest floor of some plots had been stripped away
by recreational and logging activities. In order to obtain meaningful
averages, these areas were treated separately. Results are shown in Table
42. The thickest forest floor was found on undisturbed areas of Dogwood,
Sky Forest, U.C. Conference Center, Camp Paivika, Breezy Point, and Camp
Angelus. Relatively thin layers were found on undisturbed plots at Snow
Valley, N.E. Green Valley, and Holcomb Valley, but none of these was as
thin as the disturbed areas of Dogwood, Green Valley Creek, Holcomb Valley,
and Camp Osceola. The very marked reduction in thickness of the forest
floor by recreation activities (mainly motorcycles) any by logging (even
scattered sanitation logging removing oxidant-injured or insect-infested
trees) may have important consequences on seed germination, seedling
survival, soil temperature and moisture, animal habitats, and fire be-
havior.
On the other hand, the accumulated needle litter, fallen (unharvested)
trees killed by the oxidant-injury/bark beetle complex, and the accumulated
slash from repeated sanitation salvage logging have resulted in serious
fuel overloads at places like Sky Forest. The implication is that wild-
fires could cause death of even large trees because of sustained high
temperatures.
Effect of Oxidant Injury to Tree Crowns on Rate of Litter Accumulation
One of the most obvious effects of air pollutants on the ponderosa and
Jeffrey pine trees is the decrease in size and number of needles on the
tree. It is clear that as injury to the tree increases, older needles
fall from the tree and increase litter-fall until most of the older needles
are on the ground, and the production of new needles is low. The mass of
needles collected on screens placed under pine trees from September 10 to
December 11, 1974the period of normal needle-fall with minimal effect of
snow breakage of the treeis shown for the Lake Arrowhead region (Camp
Paivika to Camp Oongo) in relation to the oxidant injury score for
individual trees in Figure 57.
206
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TABLE 42. MASS AND THICKNESS OF THE FOREST FLOOR ON MAJOR STUDY PLOTS.
Plot
DWA
(disturbed)
SF
UCC
CP
BP
TUN 2
COO
GVC
(disturbed)
NEGV
SV
HV
(disturbed)
BL
CA
CAO
(disturbed)
Sample
Size
Number
20
(66)
102
32
76
49
81
84
20
(60)
127
138
77
(52)
110
74
62
(24)
Mean
Thickness ,
T
(cm)
12.5
(2.8)
10.7
11.1
10.3
9.4
8.4
7.5
8.4
(3.3)
5.3
4.2
5.2
(1.3)
6.6
9.8
6.6
(2.6)
Standard
Deviation
of T
+ 1.23
(^0. 42)
+0.43
+1.03
+0.48
+0.50
+0.54
+ 0.43
+0.54
(+0.34)
+0.3
+0.39
+0.42
(+0.19)
+_0.39
+0.55
+0.40
(+0.29)
Mass*
(Kg/m2)
17.61
(3.92)
15.11
15.73
14.52
13.23
11.8
10.56
11.81
(4.71)
7.47
5.91
7.32
(1.84)
9.35
13.75
9.27
(3.65)
Standard
Deviation
of mass
+ 1.73
(_+0.59)
+0.61
+1.45
+0.68
+0.71
+0.76
_+0.61
+0.76
(+0.48)
+0.47
+0.55
+0.59
OK). 27)
_+0.55
+0.78
+0.56
(+0.41)
Range
(undisturbed)
4.2/12.5
5.91/17.61
Calculated mass = 1.41 T
207
-------
The oxidant injury scores determined by, another subproject for these
trees ranged from 9 (severe impact) to 34 (very slight impact). It can be
seen readily that needle-fall was low in the relatively healthy trees
(oxidant injury score > 25); but as the injury becomes increasingly severe,
needle-fall increases to a maximum where the average injury score is about
15 and drops again to low values in the severely injured range (oxidant
injury score 9 and 10). Trees with "severe" injury retain only the current
and previous year's needles, which are relatively short in length. The
variation in litter caught on the screens was quite large under those trees
with oxidant injury scores ranging from 14 to 19, but otherwise the data
appear to represent significant changes with time.
The oxidant air pollutants also affect the size of needles in the
needle-drop collected. The lengthor, more properly, the average mass
per cluster of 3 needles (fascicle)is shown in Figure 58 in relation to
the oxidant injury score. The decreased mass as the impact grows more
severe is clearly shown and is highly significant. Each point on Figure 58
represents a single tree.
I
UJ
_J
Q
LU
LU
10 15 20 25 30 35
OXIDANT INJURY SCORE 1974
Figure 57. Mass of ponderosa pine needle litter-fall compared to oxidant
injury score, 1974; for Camp Paivika plot to Camp 0-Ongo plot.
208
-------
26-r-
24--
22--
UJ
_l
o
o
Co 20-
I. .16
SS .16-
-14-
UJ
UJ
z
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Q.
o o
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I
I
Y«0.00306 X + O.BI
x R-.80,n -40,SEY«.020
0 X- 1973 NEEDLE-FALL
0- 1974 NEEDLE-FALL
10 15 20 25 3O
OXIDANT INJURY SCORE (X)
35
40
45
Figure 58. Ponderosa and Jeffrey pine needle-fall compared to oxidant
injury score, Sept. - Dec., 1973 and 1974.
Nutrient Content of Needle Litter from Trees with a Range of Oxidant Injury-
Preliminary results from analysis of needles from 5 selected trees in
1973 are shown in Table 43.
Evidence for an effect of air pollutants on nutrient content of needle-
fall is inconclusive, but it appears that severely affected trees with
oxidant injury scores of 3 to 11 are higher in nitrogen (N) content than
those less affected (oxidant injury scores 21, 33).
The content of N, P, K, Ca, and Mg has been determined on samples
collected on screens under pine trees in spring and late fall from 12/73
to 5/75. Examination of the data reveals no clear relationships between
nutrient content of the needles and the impact of air pollutants. However,
clear evidence of loss of nutrients due to leaching by precipitation,
particularly for potassium and magnesium, is shown by the data in Table 44.
Data from two trees (COO 852 and 856) showed a marked decline in
N, P, K, and Mg content between fresh-fallen needles collected on September
15 before any fall rain and those affected by light autumn precipitation
to those collected in May after heavy winter precipitation and snow melt.
The data in Table 44 are representative of a large volume of data for
samples collected from 40 trees (2 to 4 samples per tree) which is to be
analyzed by computer.
209
-------
TABLE 43. CONTENT OF NUTRIENT ELEMENTS IN NEEDLE FALL COLLECTED IN
AUTUMN, 1973.
Nutrient
Plot
COO
UCC
COO
SF
UCC
Tree
no.
Al-449
Al-448
GO-863
GO-1244
Al-405
Oxidant
in j ury
score
33
21
11
8
3
P
44
50
66
56
48
K
199
246
336
285
242
Ca Mg
(mg/lOOg)
357
417
355
363
173
123
141
103
155
79
N
426
403
444
670
532
C
543
532
521
542
526
TABLE 44. NUTRIENT CONTENT AND LOSS IN NUTRIENTS DUE TO LEACHING OF
NEEDLE-FALL FROM PINE TREES.
No. of
Plot trees
COO 5
COO 9
COO 9
Percent loss
Date
Fresh
9-15-74
11-74
5-75
9-74/5-75
The losses indicated are all
N
786
501
601
245
significant
P
101
64
52
49
(P < .001)
Nutrient
K Ca
(mg/lOOg)
510 359
289
81 445
84
Mg
123
86
30
This loss in nutrients due to leaching does not reflect the total loss
since it is reported on a weight basis. At the same time, the total weight
of needles is declining. The average mass per needle fascicle declined from
fall, 1974 to May, 1975 from 0.179 g to 0.156 g, for a total weight loss of
18 percent. Applying this correction to the data in Table 44, losses of the
original weight were 37, 57, 87, and 43% and an apparent increase of only
2.6% in Ca, indicating only a small weight loss between September and
December, 1974.
The needle-fall was collected under the same trees which other
210
-------
subsections have been studying with respect to micro-arthropods, micro-
organisms, and seedling germination. These changes in nutrient status can
not be integrated into those studies.
Effect of Oxidant Injury to Tree Crowns on Interception of Precipitation
and Crown Drip Nutrient Composition
Interception in 1974An interesting observation is that the crown drip
under trees 1.0 to 3.0 m from the trunk exceeded the precipitation measured
1.0 to 2.0 m outside the crown line of the tree. Precipitation averaged
79.2 mm, while the average crown drip was 90.2 mm. The difference is highly
significant since statistical analysis indicates this difference to be real
in 99 out of 100 cases. Generally, interception of precipitation by
vegetation is thought to decrease the amount of water reaching the ground
surface. However, in these mountain regions, precipitation is generally
accompanied by considerable wind. Apparently, the fact that rain falls at
an angle, rather than vertically, accounts for the fact that less than the
total precipitation reaches the ground between trees. Presumably, the true
precipitation, if it were measured above the forest, would be between the
two values of 90.2 and 79.2 mm.
Crown drip nutrients in 1974Collected crown drip and precipitation
were analyzed for calcium (Ca), magnesium (Mg), potassium (K), sodium (Na),
and phosphorus (P). The most striking feature of the results is the increase
in total cations (Ca, Mg, K, and Na) with decreasing distance from the
trunk, although some high values were found (> 20.0 mg/1) up to 2.0 m from
the trunk. It appears that precipitation drips from ponderosa pine needles
to limbs near the center of the tree-crown before falling to the ground.
The high values appear to be from drip from the limbs, rather than directly
from needles. The general relationship is shown clearly in Figure 59.
This variation apparently obscures any effect that air pollutant injury
may have on the composition of crown drip. The content of total cations in
crown drip is shown in relation to oxidant injury score in Figure 60. The
two lowest values do show up on the trees with the most severe impact
(injury score 10 and 11), but the others do not show a corresponding rela-
tionship.
Interception in 1975Precipitation measured with collectors (99 mm in
diameter) was 19.4 mm. The average amount of crown-drip caught in similar
collectors under 24 trees plotted in relationship to air pollutant injury
rating (I) is shown in Figure 61. There was no evident relationship shown
between (I) and the amount of crown-drip; however, net interception of
precipitation by the tree crown is apparent for only 8 trees, whereas the
crown-drip exceeded the precipitation under 16 trees. This increase was
attributed to the effect of wind in introducing a horizontal component to
the angle of falling raindrops, thus increasing the effective precipita-
tion under the trees and reducing it on their down-wind side. Since the
base line precipitation was measured on an open hilltop, the measurement is
probably accurate.
Crown drip nutrients in 1975The effect of air pollutant injury on
the composition of crown-drip is much more evident than on the amount
211
-------
15
oo
e
M
5 10
u
S5
§
S
H
Y = -3.122 X + 15.1
r = .865
Figure 59.
DISTANCE FROM TRUNK - meters
Crown drip cation concentration in relation to distance from
ponderosa pine tree trunk.
-(Fig. 62). The average amount of total cations (Ca, Mg, K, and Na) in-
creased with the injury score (I) from .014 g/M2 in the precipitation to
about 0.26 g/M for the slightly affected or unaffected trees (I = 30 to
40). Severely affected trees (I = 6 to 12) yielded about 0.1 g/M2. Two
trees yielded very high amounts of cations (> 0.3 g/M ) , but these results
do not fit the general relationship, and the reason has not been explained.
Although one might expect an increase of nutrients leached by crown-
drip from the tree with increased air pollutant injury, the trees are also
being defoliated by the injury; thus, there is less contact between
precipitation and the foliage on severely affected trees, and fewer cations
are being leached. These results need to be related to the crown density
measurements made by the vegetation subproject and to nutrient status of
intact needles.
Variation of Soil Surface Nutrient Content Under Ponderosa and Jeffrey
Pines with a Range of Oxidant Injury
Preliminary inspection of results indicated no evident relationships
from 18 trees in the higher rainfall areas (plots: COO, SFRS, DL, TUN2,
BP, NWCP). However, significant correlations were observed between air
pollutant injury ratings (I), and exchangeable Ca, K, and Mg for trees in
212
-------
TREE NUMBER:
_ 2°-T866 864 863 852 871 868 802 853 449
o>
e
o
_l
<
o
10 II 12 13 21 21 26
OXIDANT INJURY SCORE
1974
34 34
Figure 60. Crown drip cation concentration in relation to oxidant injury
score of ponderosa pine.
the lower rainfall areas of Santa .Ana Canyon (plots: CA, SCR, BF, CAO) and
plots on the north side of the San Bernardino Mountains (UCC, GVC, NEGV, and
HV).
The relationships observed were significant only when soils with
unusually high organic carbon content (> 3.0%) were excluded. The trend
indicated in Figure 63 indicates that soil K increased as the injury score
decreased (indicating increased injury). A similar trend for Ca was
indicated in Figure 64 and the correlation is even more significant. The
trend was about the same also for the Mg as shown in Figure 65.
Since very high soil carbon produced unusually high values for
exchangeable Ca, K, and Mg, the relationship of organic carbon and air
pollutant injury score was also investigated for the same trees, but there
was found to be no direct correlation. The correlation coefficient was
-.114, which is not significant.
Soil N is generally highly correlated with soil organic C and so,
as expected, the correlation of N with air pollutant injury rating was also
found to be non-significant (r = -.184). However, both Ca and K are
significantly correlated with organic C in the soil (r = .645 and .459);
thus, it is likely that some of the trend with respect to air pollutant
impact was a reflection of soil carbon. However, this may not be entirely
true since soil C is not correlated with air pollutant impact. To unravel
these relationships, it will require multivariate analysis, which will be
carried out in the coming year.
213
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Mg = 1.44 - .0159 I
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10 20 30 40
AIR POLLUTANT INJURY SCORE - 1975 (I)
50
Figure 65. Relationship of magnesium (Mg) content of soil to the air
pollutant injury score on adjacent trees (Low score = high
injury).
218
-------
A possible explanation of the apparent increase in exchangeable Ca, K,
and Mg with increasing air pollutant injury may be found in the leaching of
dead foliage on the forest floor resulting from air pollutant injury to the
pine trees. As noted before, needle mortality and needle-fall are important
consequences of air pollutant injury to yellow pines. Dead needles are
subject to rapid loss of cations from leaching by precipitation. Apparently,
these cations are added to the soil and fixed in exchangeable form in the
first few inches of soil by the soils organic material. The excess
cations added by this process would be expected to remain in the surface
soil only temporarily; presumably after the death of the tree and the
cessation of needle fall, excess cations would be leached into the deeper
soil and eventually lost with deep percolation in wet years.
Soil samples were collected from the same trees being studied with
respect to microarthropods, microorganisms, and seedling germination and
establishment. Thus, it will be possible to integrate the soil information
into those studies. In the absence of the integrated results, it is fair
to say that critical nutrient levels have not yet been determined.
219
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FOLIAGE LITTER DECOMPOSITION SUBSYSTEM: MICROBIAL ACTIVITY AND NUTRIENT
CYCLING
Introduction
There is a continual turnover of tree biomass in the forest as old
foliage, branches, and trees die and fall and others grow to replace them.
Litter decomposition and nutrient cycling are the means by which the living
forest recovers much of the nutrition incorporated in this organic matter.
Recovery of these vital nutrients is the function of the vast populations
of litter and soil microflora and microfauna. This portion of the overall
study is directed toward determining the influence of oxidant air pollu-
tion on microfloral populations and leaf litter decomposition (primarily
of ponderosa and Jeffrey pines). Although previous work in this field is
relatively sparse, reviews are available (Dickinson and Pugh, 1974).
Research Objectives
Three major research approaches are being implemented in this sub-
system study. They include the following:
1) To quantify needle litter decomposition in the field. This will
help determine the degree to which oxidant air pollution affects
(a) the quality of needles as substrates for decomposers and as
sources of nutrients for cycling, and (b) the capacity of naturally
occurring populations of litter microorganisms to decompose pine
needle litter.
2) To characterize and quantify microfloral inhabitant populations
of pine needles from needle elongation through decomposition on
the forest floor. This will suggest effects of oxidant air
pollution on decomposer communities and provide the basis for
laboratory fumigation/decomposition experiments.
3) To conduct laboratory fumigation experiments on both fungal
growth and needle decomposition. These are expected to clarify
results obtained from field studies by eliminating such vari-
ables as moisture and temperature from consideration.
Materials and Methods
Needle Litter Decomposition in Natural Stands
For this study, relatively isolated co-dominant and dominant trees
were selected. Two each of the least and most oxidant-injured Jeffrey
pine trees were selected on each of two sites. These sites were Holcomb
Valley ("no" oxidant injury) and Camp Osceola ("moderate" oxidant injury).
220
-------
Similar selections of ponderosa pines were made at Barton Flats ("moderate"
oxidant injury) and Camp Congo ("moderate-heavy" oxidant injury). These
sites represent the range of oxidant injury to each species on the study
plots in the SBNF. During the autumns of 1974-1976, freshly fallen litter
was sampled randomly beneath each selected tree and subsamples of approx-
imately 15 gm were made at random. One random 20-gm subsample from each
tree per year was analyzed by Drs. Gersper and Arkley for nutrient content.
An additional random sample was dried to 30 C, allowing calculation of
a fresh/dry weight ratio for the entire sample. The remaining subsamples
were placed in labeled nylon mesh (3 mm) envelopes (approximately 15 cm x
30 cm) and disbursed as related in Figure 66. Each arrow in Figure 66
represents similar treatments consisting of 5, 10, and 10 envelopes left
in the field for one winter, one year, and two years, respectivley. The
1974 samples comprised the two-year experiment; the 1975 samples comprised
the one-year and first one-winter experiments; and the 1976 samples com-
prised the second one-winter experiment. The first one-winter experiment
was repeated, and the second involved the exchange of ponderosa and Jeffrey
pine litter between their respective sites (Fig. 67). The rationale for
this is explained in the following discussion.
After each treatment was completed, envelopes were, or will be, re-
trieved. The needles will be (1) brushed lightly to remove excessive
inorganic and fungal material; (2) dried to a constant weight at 30 C and
weighed; (3) classified visually into categories of decay type; and (4)
analyzed for percent content of N, P, K, Ca, and Mg. Percent change in
weight and nutrient content are then calculated.
Decomposer Microorganism Populations on Pine Needles in Natural Stands
Experiencing Different Oxidant Doses
Oxidant air pollution may alter the rate of pine needle decomposition
by affecting the composition of microbial populations on senescing and fal-
len needles. To study the succession of litter microorganisms, two lines
of investigation were followed in the field. Microbial succession in
living needles was determined by isolation of fungi from surface-sterilized
needles of various ages, while succession in litter was determined by
isolating fungi from surface-sterilized needles that were on the forest
floor for varying periods of time.
Before litter fall in 1974-1976, one square meter of nylon mesh was
placed approximately two-thirds of the crown radium out from the stem
beneath each of the trees involved in the integrated field needle decom-
position study. In 1974, four trees were tagged at each of two locations
in the Univer.-?'-zy of California Blodgett Experimental Forest, El Dorado
County, California. They were tagged Gr 1-8, and each received a nylon
mesh square prior to litter-fall in 1974 and 1975. In 1975, four Jeffrey
and four ponderosa pines were selected for study and tagged Gr 9-16 on
the Stanislaus National Forest, near Pinecrest, California. Each received
mesh squares prior to litter-fall in 1975. It is felt that pine stands
outside the SBNF must be considered for comparison in terms of air pollu-
tion impact. Having separated annual increments of litter-fall in this
manner, we collected periodic samples of litter from these nets, surface-
sterilized them, and incubated them on water agar in petri dishes. The
221
-------
Pinus Jeffrey!
Holcomb Valley
Camp Osceola
Pinus ponderosa
Camp Congo
Barton Flats
1974 oxidant score (Go868 was killed by bark beetles and replaced in
this study by Si449.)
Figure 66. Source and destination (tree tag-1976 oxidant score) of 960
decomposition study envelopes. Each arrow represents 30
envelopes and points from their source to their destination.
222
-------
Pinus Jeffrey!
Pinus ponderosa
Holcomb Valley
Barton Flats
Camp Osceola
Figure 67. Source and destination (tree tag-1976 oxidant score)
of 160 decomposition study envelopes. Each arrow
represents 5 envelopes and' points from their source
to their destination.
diversity and populations of microorganisms were then recorded.
To determine the succession of microorganisms on living pine needles,
the lowest healthy twigs on the north, south, east, and west sides of the
stem were clipped not only from trees involved in the integrated field
needle decomposition study, but also from trees at Blodgett and Pinecrest.
The annual needle increments on each twig were separated in the field. A
subsample of each increment was surface-sterilized and incubated on water
agar in petri dishes. The diversity and populations of microorganisms
were then recorded and analyzed.
Laboratory Tests of the Effect of Oxidant Dose on Decomposers and Decom-
position
This phase of the project is designed to determine how air pollution
affects (1) growth and reproduction of microbial agents of litter decomposi-
tion, and (2) rates of needle decomposition by major microorganisms.
Two clear and twelve opaque plexiglass fumigation chambers were
constructed and installed inside two walk-in Percival growth chambers on
the Oxford Tract, UCB. These walk-in chambers have been renovated to
permit control of light, temperature, and relative humidity. The plexiglass
223
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chambers were designed to permit control of ozone concentration, and are
currently being calibrated and tested.
Species of fungi isolated from litter samples will be fumigated at a
number of ozone concentrations. The fungus will be inoculated onto sterile
pine needle sections placed on cellophane-covered cellulose agar in petri
dishes (Eggins and Pugh, 1962). The effects of ozone will be quantified
on such factors as (J.) colony growth rate, (2) spore production, (3) spore
germinability, and (4) cellulose decomposition.
Sterile litter from a variety of sources was inoculated by place-
ment on wet humus from a variety of sources and fumigated to determine the
effects of ozone on needle decomposition by natural complexes of decomposer
microorganisms. Such fumigation experiments were designed to separate the
direct effects of ozone on microbes from the effects of ozone on the
suitability of a substrate for decomposition.
Results and Discussion
Needle Litter Decomposition in Natural Stands
Quantification of integrated needle litter decomposition in the field
has progressed. Data sets are complete for weight losses incurred by 160,
320, and 320 mesh litter envelopes over one winter, one year, and two
years, respectively. The 32 treatments involved in each of these three
experiments are diagrammed in Figure 66. Change in nutrient status (per-
cent N, P, K, Ca, Mg) has been determined for a pooled sample from each
of the 32 over-winter treatments. As Dr. Gersper's schedule permits,
similar data on post-harvest chemical analysis will be obtained for the
one- and two-year treatments.
Ponderosa pine litter lost more weight (a=.001) during the first win-
ter and the one- and two-year experiments than did Jeffrey pine litter.
Within each species, available data shows greater weight loss on the site
receiving the greatest oxidant air pollution dosage. Preliminary nutrient
data available to date suggest that during the first over-winter experi-
ment, ponderosa pine needles lost more P and K than did Jeffrey pine
needles. In general, these data also showed a decline of N in Jeffrey pine
needles but an increase of N in ponderosa pine needles. This increased N
and decreased P and K may correspond to the greater fungal activity observed
in ponderosa pine litter.
It is thought that the weight losses experienced over the winter of
1975/1976 were relatively light, probably reflecting the below-normal pre-
cipitation. The overwinter experiment currently in the field may provide
more representative data and substantiate the trends observed to date. The
sparse literature relevant to this point suggests that weight and nutrient
losses by pine needle litter during its first winter on the ground are
relatively great (Stark, 1972, 1973; Millar, 1974).
Because ponderosa pine sites may receive more precipitation than the
Jeffrey pine sites, not only soil moisture data being collected by the
soils group, but also precipitation, air temperature, and approximate
224
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oxidant-dosage estimates for the involved sites, will be used in the
interpretation of data collected. Also, litter of each species has been
disbursed to sites of the opposite species for the winter of 1976/1977.
Weight and nutrient loss data from this experiment will help clarify the
effects of site and litter specie on decomposition.
Decomposer Microorganism Populations on Pine Needles in Natural Stands
Experiencing Different Oxidant Doses
One complete experiment during late summer of 1975 has provided in-
formation on microbial succession in pine foliage in the SBNF, Blodgett
Forest, and the Stanislaus NF. Data from a similar experiment in the
SBNF during spring, 1976, will be analyzed shortly. One additional
complete experiment of this type is planned for early spring, 1977. In
this experiment, it is hoped that nutrient status will be determined by
Dr. Gersper's group for each annual increment of foliage. Results of
the first experiment are tentative, requiring further analysis and con-
firmation. Collection of data on microbial succession in litter continues.
The value of the data increases from each successive sampling; there are
now four annual increments of litter-fall separated (except where nets
have been vandalized) in the SBNF. All data collected from these studies
will be interpreted in the light of existing soil moisture, precipitation,
air temperature, and other site data, as well as from oxidant dosage
information.
Through the study of annual increments of living foliage and strati-
fied litter, successions of microfloral populations are being determined
for individual trees representing plots and regions impacted by varying
amounts of smog. Comparisons among these population successions will help
explain patterns in (1) litter decomposition and (2) the incidence of
fungus-caused damping-off of pine seeds and seedlings (under study by the
seedling establishment investigators). Species of fungi for which popu-
lation data have been collected, to date, include phycomycetes, ascomycetes,
basidiomycetes, and fungi imperfect!. A method for the culture of fungi
on microscope slides has been employed forthe grouping and identification
of important isolates (Riddell, 1950).
Laboratory Tests of the Effect of Oxidant Dose on Decomposers and Decom-
position
The clear plexiglass chambers and ozone detection equipment have only
recently become operational. Though no data are yet available, these
studies are planned and will be underway very shortly.
225
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FOLIAGE LITTER DECOMPOSITION SUBSYSTEM: MICROARTHROPOD ACTIVITY
Introduction
Natural Role of Microarthropods
Litter microarthropods form an important, if rather inconspicuous,
component of the forest ecosystem. Therefore, it is necessary to evaluate
the effects of potentially disruptive environmental contaminants, e.g.,
oxidant air pollutants, on these abundant arthropods. The pine needles,
twigs, and other organic materials that make up the forest floor and the
underlying upper layers of mineral soil contain a complex and diverse
community of small (often less than 2-3 mm) animals. They belong to the
phylum Arthropoda, which includes insects, mites, spiders, centipedes,
and a variety of other less well known animals; taken together, these can
be termed "litter microarthropods." They can occur in very large numbers,
with population estimates in pine forest soils ranging from 102,000/m^ in
Tennessee (Crossley and Bohnsack, 1960), to 200,739/m2 in California
(Price, 1973).
The primary role of litter and soil microarthropods in conjunction
with the soil microflora (fungi, actinomycetes, and bacteria) is to
decompose and reduce plant and animal organic residues which fall to the
forest floor (Edwards _et al., 1970; Millar, 1974). They can contribute
directly to the decomposition process by mechanically breaking down or-
ganic materials such as pine needles into smaller fragments. The activity
and movement of microarthropods help to reduce these fragments further
into humic substances and then to mix them and other breakdown products
with the mineral soil below. These processes make the nutrients contained
in the undecomposed organic material available for use by other plants
and animals in the ecosystem. Furthermore, these disintegrating and
reducing activities can increase the surface area of organic material and
create microhabitats and substrates that are more easily attacked by soil
fungi and bacteria. In turn, these microflora chemically decompose and
change the organic residues, which benefits the microarthropods. Thus,
both directly and indirectly, through decomposition, mechanical mixing,
and by complex interactions with soil microflora, soil microarthropods
affect overall soil fertility and nutrient cycling.
At the same time, species composition and abundance of litter micro-
arthropods can be influenced by various soil and litter properties. These
include the quantity and quality of the organic litter, its accumulation
rate, soil water availability, and the pH of the soil. Litter micro-
arthropods are also affected by the biological components of the soil,
including microflora. Chemicals released by the action of soil fungi may
inhibit or enhance litter microarthropods; some of these arthropods feed
on, and hence are dependent on, certain fungi. From a long-term standpoint,
226
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these complex feedback interrelationships between litter microarthropods
and the physical and biological attributes of the soil can significantly
affect forest succession. They accomplish this through natural seed bed
preparation, seed germination success, seedling survival, and the basic role
of decomposition.
Stable forest ecosystems are generally considered to have a relatively
constant rate of litter production (Burgess, 1967). Any factor that could
affect this balance warrants investigation. Disturbances could involve
not only changes in the rate and amount of litter fall, but also the
quality of the organic matter itself. In addition, other factors are
involved such as the composition and amounts of dissolved organic matter
in rain water passing through the canopy. Such changes could take several
years as ponderosa or Jeffrey pine gradually weaken due to continued
exposure to oxidants or they could be accelerated by disease, bark beetles,
or an interaction of factors. Under natural conditions, the dead trees
themselves ultimately fall to the forest floor and are decomposed.
Research Objectives
The response of litter microarthropods and other components of the
forest floor to these changed conditions may influence the nature of forest
regeneration through nutrient availability. Thus overall objectives
of this study were to determine the (primarily indirect) effects of photo-
chemical air pollution on the litter microarthropod component of the
ecosystem, and to evaluate the effects of this component on the rest of
the system. The specific objectives are as follows:
1) To determine species abundance and diversity in the forest floor
under selected individual trees.
2) To relate these population characteristics to soil and litter
properties.
3) To determine how photochemical air pollutants influence litter
microarthropod populations: through their effect (a) on litter
quantity and quality, and (b) on microbial activity.
4) To relate litter microarthropod populations with soil microbial
populations under selected individual trees: (a) by correlating
microarthropod and microbial species composition and relative den-
sities; and (b) by determining the succession of soil microarth-
ropods and microflora in the decomposition of forest litter and
their effect on gross decomposition rates.
5) To determine and compare characteristics of ecological disrup-
tions of litter microarthropods caused by oxidant air pollutants
at undisturbed (natural) sites and at sites of disruptions
caused by other factors, e.g., pesticides, fire, and logging.
6) To identify specific components of the litter microarthropod
community as indicators of an ecosystem disrupted by oxidant
227
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air pollutants.
Methods and Materials
Field Sampling Technique
Plots and individual sample trees were selected primarily on the basis
of oxidant injury ratings in an attempt to compare them at different oxi-
dant levels. To minimize possible sources of variation, an attempt (largely
unsuccessful) was made to choose trees that were isolated and undisturbed
(other than by oxidant air pollutants), and that were relatively unin-
fluenced by adjacent trees. In addition, an effort was made to work with
trees, at least within plot, that were of similar size and age. Table 45
shows the vegetation plots, trees, and dates on which they were sampled.
Samples were taken at six-week intervals with a rectangular shaped
soil corer 32.26 cm^ (5 sq. in.) in area. Some variation in time occurred
due to snow and other weather conditions. Ten cores per tree were taken
on each sample date and, where appropriate, the different forest floor
layers (litter, fermentation, humus) and the top 0-5 cm of mineral soil
were measured and stored separately for individual extraction. The forest
floor beneath each sample tree was divided into eight quadrants based on
cardinal direction. The exact dimensions depended on crown size, ground
cover, and disturbances of the forest floor. Samples were taken by ran-
domly selecting the quadrant and specific direction from the tree bole;
the location of each individual core was mapped as precisely as possible
using the angle (from N, 0-360) and the distance from the bole. (This
sampling is directly coordinated with the "Litter Decomposition and
Nutrient Cycling" subproject.)
Laboratory Analysis Procedure
All cores taken in the field were stored at low temperatures until
extraction. Microarthropods were extracted from the soil using a high
heat gradient modified Berlese funnel system (Price, 1973). This system
uses a combination of heat, light, and drying action on the individual soil
samples. It drives microarthropods from the soil core through steep-
walled plastic funnels sprayed with a dry silicone lubricant, and then
into alcohol-filled vials where they are preserved for later analysis and
counting. The temperature in the funnel units was controlled by a voltage
regulator and was increased gradually from an initial temperature of 32
C. This was done to avoid excessively rapid heating and drying of the
soil cores, which could result in microarthropods being killed in place,
rather than being driven into the alcohol vial. Each core was extracted
in the system for a minimum of three days.
Data Capture and Analysis
Through June, 1976, all field samples have been extracted, identified,
and counted. All data have been put into the information system, data
capture programs have been run, and data have been verified and corrected.
Programs are being written to combine data for different species into
predator, decomposer, and other groups, and to combine different soil
horizons as needed. Also, programs are being developed to perform the
required statistical analyses and for output of corrected, fixed format
228
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data decks. This work will be completed under the contract for 1976-77.
Results and Discussion
A list of specimens collected during the initial phases of the study is
given in Appendix L. The systematics of many of these groups, especially the
Acarina, are poorly understood, and at this point many groups have not been
identified beyond their family level.
Data analyses have been limited since the effort to date has been
directed primarily toward creation of error-free and complete data files.
However, trends can been seen by examining the mean values of total micro-
arthropods per sample collected under the 6 trees sampled from 1973 to 1975
(plots SV2, NEGV, BP) . Three of these trees were heavily damaged (range 9-
14) by pollutants, while the others were lightly damaged (range 24-29).
Figure 68- plots the comparative means of total microarthropods per sample
in the organic layer of heavily and lightly damaged trees. Considerable
variation by date is evident, but at every date fewer microarthropods were
collected in samples under damaged trees. It appears that populations are
generally lowest during the July-August period of any given year, suggest-
ing that moisture and/or temperature have an effect. Only one sample was
taken during 1975, so it is not possible to tell if the high populations
of August, 1975 were a continuing trend from those shown for November, 1974.
Conclusions can only be tentative because the effect of the plots, sample
depths, and between-sample variation have not yet been analyzed for this
group of samples.
An analysis has also been conducted for four plots, each with one
damaged and undamaged tree. The sampling dates were October 1, and November
15, 1974. The variable in this case was mean microarthropod density, and
the means are given in Table 46. Analysis of variance by plot, tree smog-
damaged level, and date showed that microarthropod density was significantly
different between two dates (.005 level) and significantly different among
plots (.05 level). Individual means compared in pairs with Tukey's HSD
test showed that only in one plot (BP) on one date 11/15/74 was micro-
arthropod density significantly greater in the undamaged tree compared to
the damaged one. Among the four plots, three had moderate smog concentra-
tions (BP, CAO, COO) and one had heavy smog concentration (SF). There
were no significant differences in density for all trees on the first date,
and none for heavily damaged trees on the second date. However, on the
second date, the lightly damaged tree in BP had a significantly higher
density (to .05 level) than the lightly damaged trees in COO and SF on
that date.
From the analyses completed up to this point, it appears that date,
plot, smog damage, moisture, and temperature are factors in establishing
microarthropod populations. Much more extensive data collection would be
required to meet all research objectives named. The difficulty of coupling
arthropod data from such small plots with the forest stand succession
modeling strategy on a much larger scale augers against the continuation of
data collection efforts. Further analysis of the data may isolate some
critical factors and determine if some groups of microarthropods are
permanently affected.
230
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232
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WOODY LITTER DECOMPOSITON SUBSYSTEM
Introduction
Rationale for the Study
Trees chronically exposed to oxidant pollutants lose photosynthetic
capacity. One possible effect of this may be an alteration of woody
tissues and a change in the wood's resistance to attack by decay fungi.
Such altered resistance may affect litter accumulation and nutrient
cycling, in addition to having various other effects on the forest floor.
On the other hand, direct exposure of decay fungi on the forest floor
to air pollutants may alter their growth rate or their ability to decay
wood, which would produce similar effects on litter accumulation and
nutrient cycling. Collection sites for this subproject were coordinated
with other projects dealing with soil, litter, and assoicated fungi
and insects. The overall objective of this study was to determine
whether exposure to air pollutants alters wood decay resistance or the
activity of decay fungi.
Research Objectives
The specific objectives for this subproject for the past year were
as follows:
1) To analyze the results of a soil-block test testing the decay
resistance of ponderosa pine wood grown under different levels
of exposure to air pollutants.
2) To determine the effect of exposure to various levels of ozone
on the decay capacity of fungi isolated from the study site
and some standard wood decay fungi.
3) To determine the effect of exposure to various levels of ozone
on the growth rate of fungi isolated from the study site and
some standard wood decay fungi.
This report summarizes the results of attempts to isolate decay fungi
from woody litter on the study site and of experimentation to determine
possible effects of oxidant exposure on the susceptibility of wood
produced under such exposure to attack by wood decay fungi.
Methods and Materials
Identification of the Kinds of Fungus Decomposers of Woody Litter
Pieces of large ponderosa pine wood lying on the ground were collected
233
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during spring, summer, and fall of 1973 from sites representing the full
range of long-term exposures. Isolates were screened for ability to cause
weight loss in wood by exposing wood blocks to actively growing agar cul-
tures. Decay resistance and rate of decay were measured by a standard
soil-block method (American Society for Testing and Materials, 1973). For
the most active decayers of the fungi isolated, decay rate and hyphal growth
rate were measured in the laboratory under conditions of high and low ozone
concentration.
Testing Decay Susceptibility of Sapwood from Trees with Different Amounts
of Oxidant Injury
Four small ponderosa pine trees were felled in May, 1974, in the SBNF
adjacent to Dogwood and Tunnel II, two established study plots rated as
"moderate" and "slight" oxidant exposure sites, respectively. Two trees
representative of both high and low degrees of tree damage from oxidant
exposure were chosen from each site. Several feet of the butt portion of
each stem were collected as sample material. After ring counts and measure-
ments were made, specimens 2.5 x 2.5 x 0.9 cm (in the grain direction) were
machined. These specimen blocks were exposed for 12 weeks to decay fungi
in a soil-block test (American Society for Testing and Materials, 1973)
using the standard test fungi Poria monticola, Lenzitestrabea, and Poly-
porus versicolor, along with two decay fungi isolated from the SBNF sampling
sites. The white-rot fungus, Polyporus versicolor, is not normally used
when testing coniferous woods because white-rot fungi rarely attack
coniferous wood in service. Since both the San Bernardino isolates appeared
to be white-rot fungi, however, 3?. versicolor was used for comparison as
a known, vigorous, white-rotting wood destroyer.
Results and Discussion
Degree of Completion of Research Objectives
Objective 1 was satisfied and the results are reported here. Objec-
tives 2 and 3 were not achieved because of delays in completing modifica-
tions of the ozone exposure chambers necessary to undertake this work;
such modifications are being carried out by one of the other subprojects.
Identification of the Kinds of Fungus Decomposers of Woody Litter
Eleven of the fungi isolated from woody litter have been shown by
general screening to be wood-destroying organisms; microscopic examination
has certified that at least five are definitely decay fungi. Superficial
examination of the decay suggests that all wood-destroying isolates may be
white-rot fungi. This is surprising, since most decomposers of coniferous
wood in soil contact are brown-rot fungi.
Decay Susceptibility of Sapwood from Trees with Different Amounts of
Oxidant Injury
Results of the soil-block test are shown in Table 47: descriptive
data on sample trees are shown in Table 48, which indicate that the majority
of sample material taken consisted of sapwood. Sapwood of all tree species
is considered to have no resistance to decay in service. However, since
oxidant damage to trees in this area dates back no more than approximately
25 years, use of heartwood for the tests would have involved tissue produced
234
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before the onset of oxidant impact, and was therefore not of interest. The
test became one of comparing possible differences in sapwood susceptibility,
instead of one of comparing possible differences in heartwood decay resist-
ance. As shown in Table 47, no meaningful differences in decay suscepti-
bility were found in sapwood produced under various conditions of oxidant
impact for any fungi employed. Weight losses caused by the two San
Bernardino isolates were substantially lower than those produced by any of
the recognized products destroyers. It is not unusual to find that field-
and tree-isolated decay fungi perform poorly in a soil-block test as compared
with decay fungi isolated from decaying wood in service. In our screening
tests, these two San Bernardino isolates have consistently produced the
highest weight losses of any of the decay fungal isolates obtained from the
San Bernardino sites.
One sample tree contained sufficient heartwood to include a small
test of heartwood decay resistance in the experiments. As shown in Table
47, it demonstrated moderate decay resistance (American Society for Testing
and Materials, 1973) to _P. monticola and was highly resistant to the
other fungi. This is considerably greater resistance than that reported
by Clark (1957) in comprehensive tests on a number of western coniferous
heartwoods. He reported average weight losses for ponderosa pine heart-
wood of 53% with _P. monticola and 19% with L,. trabea. However, the
values reported in Table 47 refer to a sample from a single tree and are
within the range of variation reported by Clark. Furthermore, since the
heartwood included in the present work was formed 49 to 55 years before
felling, any variations in data are presumed not to involve effects of
oxidant exposure.
The severity of damage to the tree, as noted by external symptoms,
appears to be recorded in the growth of the tree by progressively decreasing
thickness of annual increments (Table 48).
The difficulty of incorporating the results of these detailed studies
into the forest stand level modeling strategy selected for the project may
lower the priority level of this subsystem as it is now defined.
235
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SMALL MAMMAL POPULATION DYNAMICS SUBSYSTEM
Introduction
Wildlife species form an important component of all forest ecosystems.
As consumers, for example, wildlife may have a major influence on forest
plant succession patterns (Lawrence, 1958; Hooven, 1969). Changes in
wildlife abundance or species mix induced by direct or indirect effects
of oxidant air pollution potentially may affect forest plant succession.
The overall objective of this wildlife study has been to describe
the terrestrial vertebrate community within this mixed conifer forest,
particularly in relation to ponderosa pine, Jeffrey pine, and other forest
vegetation. We have attempted to describe (1) the effects of terrestrial
vertebrates upon this forest and (2) the effects of photochemical air
pollution on the vertebrate community. Neither time nor resources were
available to study all vertebrates in detail. It was decided to emphasize
only the common small mammals and the gray squirrel. Small mammals were
selected for detailed study because they are reported to exert major
effects on the ecology of many conifer forests and because their relatively
limited range of travel makes them more subject to the air pollutant dose
and fluctuation of food supply at any given location.
Literature Review
Small mammals commonly consume a major portion of tree and shrub seed
crops in western forest. In this manner they exert a major influence upon
seedling establishment and, hence, potentially upon forest successional
patterns (Moore, 1940; Smith and Aldous, 1947; Lawrence, 1958; Gashwiler,
1959; and Black, 1969). Additionally, small mammal populations respond
markedly to habitat alteration, particularly to vegetation and soil changes
(Hagar, 1960; Vohs, 1974) . Third, small mammals are one of the least
difficult groups of vertebrates to study, and a modest body of literature
exists on them in conifer forests (see reviews by Black, 1969, 1974).
Materials and Methods
Field work began in the summer of 1972, and was restricted largely to
the summer period. As is the case in most wildlife studies, inventory was
the first step. We prepared preliminary lists of the vertebrates found
in the study area (White and Kolb, 1973) based upon observations and
census, literature review, and consultation with experts.
Census of small mammal populations was conducted in the summers of
1972, 1973, and 1974, using standard mouse and rat snap-trap procedures
(Calhoun, 1959). Trapping in 1972 occurred only on the 6 original plots
(Kolb and White, 1974). In 1973 and 1974 trapping occurred on an expanded
238
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network of 18 plots. A total of 830 small mammals was captured in the
three years.
One objective of these trapping censuses was to determine the species
inhabiting the study plots and to estimate the population density patterns
from plot-to-plot and from year-to-year. Partial results of these efforts
were presented in Kolb and White (1974), Each specimen was initially
preserved by freezing. Later specimens were thawed and dissected, and
data on sex, age, general health, and reproductive conditions were recorded.
Reproductive tracts, stomachs, parasites, and skulls (for age verification)
were preserved for subsequent examination.
The western gray squirrel is too large to be studied by snap-trapping;
nevertheless, gray squirrels were studied because they feed heavily upon
conifer and oak seeds. They represent the largest source of loss of pon-
derosa and Jeffrey pine seed in this forest. The goal of this work has
been to measure the extent of gray squirrel feeding upon ponderosa and
Jeffrey pine seed crops.
Small Mammal Trapping
In the three-year trapping period, a total of 17 species of small
mammals was caught (Table 49). The dominant genus in this small mammal com-
munity was the deer mouse, which made up 54% of the total catch. The white-
footed deer mouse alone represented 43.7% of the total catch, accompanied
by noticeably fewer brush mice, pinyon mice, and California mice. Other
common small mammals on the study plots are the dusky-footed woodrat,
chipmunks (Merriam and lodgepole), the golden-mantled ground squirrel, and
the Botta pocket gopher. Pocket gopher numbers are markedly under repre-
sented in Table 1 because they are not vulnerable to the standard snap-trap,
and minimal efforts were made to sample them in proportion to their occur-
rence. Numbers of western gray squirrel, northern flying squirrel, and
ornate shrew also are under represented for the same reasons.
There was considerable variation in the number of small mammals
captured year-to-year and from one plot to another (Fig. 69). Overall, the
most were captured in 1974, and the fewest were captured in 1973. Much of
the fluctuation can be accounted for by changes in the numbers of deer
mice, whose populations characteristically fluctuate dramatically from
season-to-season and from year-to-year (Hooven, 1969).
The paucity of larger species in 1972, including the dusky-footed
woodrat and golden-mantled ground squirrel, was largely a result of using
only small museum special (mouse) traps during this first trap-year. The
marked increase of both species in 1973 and 1974 is coincident with addi-
tional use of rat traps.
Figure 70 presents a comparison of the proportions of the catch on
the study plots of deer mice, chipmunks, golden-mantled ground squirrels,
and other species, with the results of similar trapping programs on three
other yellow pine forest areas in California. These comparisons are made
because of the lack of control plots in this current study. These three
studies represent the best comparisons for California that exist in the
239
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literature. The small mammal catch on the study plots appears different
from that on these three northern California forests as follows: (1)
deer mice are more dominant; (2) chipmunks and golden-mantled ground
squirrels comprise a smaller portion of the catch; and (3) the "other
species" category is considerably larger. This latter difference is caused
by the dusky-footed woodrats, which were the second most abundant species
on the study plots, comprising 11.6% of the total catch. They do not
occur on the three comparison areas.
Table 50 presents the percentage of trapping success on the study
plots for 1972, 1973, and 1974. We use this percentage as an index of
small mammal population density because of the difficulty of estimating
densities directly from trapping results. The percentage of trapping
success varied from a low of 2.3% in 1973 to a high of 7% in 1974. Major
differences in the abundance of deer mice were the important cause of
this marked change in trapping success. Even after allowing for different
levels of trapping effort each year, there was a 6-fold increase in deer
mice between 1972 levels and 1974 levels (Table 49).
TABLE 50. COMPARISON OF PERCENT TRAPPING SUCCESS OF SMALL MAMMALS IN
1972, 1973, 1974.
Year
1972
1973
1974
Totals
Trap-days
2160
3960
4140
10260
Total catch
83
93
291
467
% trapping success
3.8
2.3
7.0
4.5
The composite percentage of trapping success for the three years on
the study plots was lower than that reported for the three northern
California comparisons areas (Table 51) . The reported percentages of
trapping success ranged from 27.8% in Nevada County (Reichart and White ms)
to 8.8 in Lassen County (McKeever, 1961). Table 51 also presents the marked
differences in the percentage of trapping success found on the study plots
according to smog injury ratings of the vegetation. The percentage of
trapping success was markedly lower on plots with severe and moderate smog
injury ratings.
Species diversity represents another way of describing a small
mammal community. A total of 17 species was caught during this study,
indicating that the small mammal fauna of this mixed conifer forest
was well developed. On a plot-to-plot basis, the species diversity
indices indicated that the small mammal fauna on plots where vegetation
244
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TABLE 51. COMPARISON OF PERCENT TRAPPING SUCCESS OF SMALL MAMMALS ON FOUR
FORESTS IN CALIFORNIA
Study area
Reichart and White (ms)
Nevada County
Storer et al. (1944)
Lake Tahoe
McKeever (1961)
Trap-days
360
1,658
1,920
Total catch
100
195
170
% trapping success
27.8
11.8
8.8
Lassen County
White and Sweetwood (ms)
San Bernardino County
Smog injury rating of vegetation:
Severe
Moderate
Very slight
No visible damage
Composite -
1,035
5,985
720
2,520
10,260
15
163
64
225
467
1.4
2.7
8.9
8.9
4.5
TABLE 52. COMPARISON OF SPECIES DIVERSITY OF SMALL MAMMALS TRAPPED ON PLOTS
WITH FOUR LEVELS OF VEGETATION INJURY FROM AIR POLLUTION.
Smog injury rating
of vegetation
Severe
Moderate
Very slight
No visible symptoms
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number
Number of Species diversity
species caught index*
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} .75
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5 2.5
7 2.3
of species caught
number of plots
245
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exhibits severe and moderate smog injury ratings is only half as abundant
as that on plots with very slight or no symptoms of smog injury to vegetation
(Table 52).
Table 53 presents a preliminary analysis of the sex and age ratios
of the small mammal catch. Species showing a possible surplus of males
include the white-footed deer mouse, golden-mantled ground squirrel, and
brush mouse. The dusky-footed woodrat and Beechey ground squirrel results
suggest a surplus of females in the population. For the remaining species
either the sex ratio appears approximately equal or the sample size was too
small to make an accurate estimate.
From the initial 1972 period throughout the study, we have noted a
larger and more diverse small mammal fauna on study plots with lower levels
of photochemical air pollution. We hypothesize that the distribution and
abundance of small mammals on the study areas probably correlates closely
with the occurrence and quality of key vegetation and soil habitat re-
quirements. Further, if these key habitat elements have been affected
and/or are being affected by air pollution, then, in turn, air pollution
will directly affect small mammal populations through this habitat alter-
ation. A description of these effects and long-term trends is needed.
Western Gray Squirrel Observations
Study of the western gray squirrel began in 1973 and continued through
1975. Abundant throughout the conifer forest, the gray squirrel depends
on the yellow pine-black oak (Pinus ponderosa-Quercus kelloggii) vegetation
mosaic for food, cover, and nest sites. The seed-squirrel relationship
is very important in this forest system. An alteration of the balance
between pine and oak through the agency of oxidant air pollution, or a
change in the squirrel population directly due to oxidants, will affect
the balance of the seed-squirrel relationship and have a significant in-
fluence on the forest, especially on pine and oak reproduction.
Preliminary census results on 43 live-trapped and ear-tagged squirrels
(23 male : 20 female) on six study plots indicate a large, wide-spread
population of gray squirrels, with small areas of unusual density. For
example, on the Sky Forest plot, 18 individuals were tagged in 6 trap-days
on an area of less than 0.2 hectares.
According to our measurements, yellow pine cone production increased
in 1974 over 1973. The number of cones destroyed for seed eating by
gray squirrels also was higher in 1974 than in 1973 (Fig. 71). Squirrels
generally utilized the same trees in both years. Only four trees that
were heavily utilized in 1973 were not used in 1974. All other trees
heavily used in 1973 produced cones and were utilized in 1974. A good
example of this "favored tree" syndrome was Jeffrey pine #1718 on the
Schneider Creek plot: in 1973, 753 cones were cut; in 1974, 2,034 cones
were cut.
In both years, the bulk of the cone utilization occurred on only a
few of the 50 overstory yellow pine trees on each plot. The cones cut
from tree #1718 represent 85% and 90%, respectively, of the total cone
246
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Figure 71. Comparison of cone utilization by gray squirrels in 1973
and 1974 by plot.
248
-------
production for that plot in 1973 and 1974.
Gray squirrels began to cut green cones in June. In 1973, the first
signs of cone-cutting appeared during the last week in June on the west side
of the mountains. In 1974, workers on the west side noticed freshly cut
cones by 10 June. Cone-cutting on the east side started somewhat later
both years, but was underway by early July. Relatively few cones are cut
during this early period through mid-July. From mid-June through mid-
August the greatest amount of cone-cutting occurrs. In Figure 72, we
separate the three plots with the greatest amount of cone utilization from
the four lowest. The salient difference between the two groups was the
sustained plane of high utilization on the three heavily utilized plots
during this peak period. Cone-cutting dropped off in the weeks after mid-
August. One Green Valley Creek and Schneider Creek, cone-cutting ceased in
late August. On all other plots, cone-cutting continued at a low level in
September and October.
A total of 14,844 cones were counted on the seven study plots in 1974;
all of them were cut prior to seed maturity. This large loss of seed prior
to maturity may be a factor acting in concert with oxidant air pollutant
injury to depress the regeneration of yellow pine. In areas unaffected by
oxidants, western gray squirrels are regarded as usually having limited
or moderate effects on the overall regeneration potential of yellow pine
(Moore 1940, Fowells and Schubert 1956, Larson and Schubert, 1970). However,
cone cutting by squirrels in the oxidant-injury areas in the SBNF may be
contributing to a hastening of vegetation change.
Future Activities
Further trapping of small mammals and direct observations of the western
gray squirrel are not planned at this time. The effects of these animals
in the context of the stand succession modeling strategy will be monitored by
the Cone and Seed Production and Seedling Establishement Subsystems.
249
-------
2500 -i
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1500 -
1000 -
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-------
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263
-------
APPENDIX
Appendix Page
A Classification of soils of major plots in the San
Bernardino Mountains 265
B Particle size distribution and pH of representative soil
samples from major study plots 268
C Bulk density of soils of major study plots 270
D Exchangeable and soluble cations of surface soils 271
E Exchangeable and soluble cations of representative
subsoil layers 272
F Organic carbon and nitrogen in the surface soils to a
depth of 25 cm 273
G Available soil water storage capacity of major study plots 274
H Long-term precipitation data for 24 San Bernardino
Mountain stations 275
I National and California air quality standards 299
J Inventory of air monitoring data from 1967-1976 for
the San Bernardino Mountains 300
K The number of cones produced by Jeffrey and ponderosa
pines of different crown classes during 1973, 1974, 1975,
and 1976 (visual counts of cones within the tree crowns) 322
L Taxonomic list of microarthropod specimens collected from
study plots, 1973-1974 326
264
-------
Appendix A. CLASSIFICATION OF SOILS OF MAJOR PLOTS IN THE
SAN BERNARDINO MOUNTAINS.
Plot
Lake Arrowhead Region
Dogwood
Sky Forest
NE13
S22
UC Conf. Cen.
NW Camp
Paivika
Breezy Point
Tunnel Two
Soil Series
Shaver
Unnamed-1
Shaver
Unnamed-1
Shaver
Crouch
Unnaraed-2
Shaver
Shaver
Stump Springs
Classification: Soil
Taxonomy (1973)'
Pachic Ultic Haploxeroll,
coarse loamy, mixed, mesic
See below
See above
Pachic Ultic Argixeroll,
fine loamy, mixed, mesic
See above
Ultic Haploxeroll, coarse
loamy, mixed, mesic
Ultic Argixeroll, fine
loamy, mixed, mesic
See above
See above
Ultic Haploxeralf, fine
loamy, mixed, mesic
East of Lake Arrowhead Region
Camp 0-Ongo
25M, 13 M R.
76M, 7 M R. Unnamed-3
58M, 11 M L.
142M, 2 M R.
Unnamed-4
Unnamed-5
Typic Xerorthent, coarse
loamy, mixed, frigid
Entic Xerumbrept, coarse
loamy, mixed, frigid
Pachic Xerumbrept, coarse
loamy, mixed, frigid
265
-------
Appendix A. CLASSIFICATION OF SOILS OF MAJOR PLOTS IN THE
SAN BERNARDINO MOUNTAINS. (Continued)
Plot
Green Valley Creek
(Valley)
(Hill)
Snow Valley
0-156M
156-249M
NE GREEN VALLEY
0- 60M
60-175M
Soil Series
Unnamed-6
Unnamed-7
Heitz
Chiquito
Corbett
Heitz
Classification: Soil
Taxonomy (19731
Entic Xerumbrept, sandy,
mixed, mesic
Typic Xerorthent, sandy,
mixed, mesic
Lithic Xeropsamment,
mixed, frigid
Entic Xerumbrepts, coarse
loamy, mixed, frigid
Typic Xeropsamment, mixed,
frigid
Lithic Xeropsamment,
mixed, frigid
Big Bear Lake Region
Bluff Lake Gefo Variant
Holcomb Valley
Ducey Variant
Domingo
Unnamed-10
Typic Xerombrupt, sandy,
mixed, frigid
Typic Xerumbrept, coarse
loamy, mixed, frigid
Typic Argixeroll, fine
loamy, mixed, mesic
Typic Haploxeroll, coarse
loamy, mixed, mesic
266
-------
Appendix A. CLASSIFICATION OF SOILS OF MAJOR PLOTS IN THE
SAN BERNARDINO MOUNTAINS. (Continued)
Plot
Sand Canyon
(Granite area)
Soil Series
(Mixed alluvial area)
Heitz
Unnamed-8
Delleker Variant
Unnamed-3
Unnamed-9
Gefo Variant
Classification: Soil
Taxonomy (1973^
Lithic Xeropsamment,
mixed, frigid
Lithic Xerorthent, coarse
loamy, mixed, acid, frigid
Typic Haploxeralf, fine
loamy, mixed, frigid
Typic Xerorthent, coarse
loamy, mixed, frigid
See above
Typic Xerumbrepts, sandy,
mixed, frigid
Santa Ana Canyon Region
Camp Angelus Cahto Variant
Unnamed-10
Schneider Creek
Heart Bar
Crouch Variant
Gear son Variant
Unnamed-11
Pachic Ultic Haplixeroll,
loamy-skeletal, mixed,
mesic
Typic Haploxeroll, coarse
loamy, mixed, mesic
Ultic Haploxeroll, sandy,
mixed, mesic
Typic Haploxeroll, sandy,
mixed, frigid
Typic Xerochrept, sandy,
mixed, frigid
267
-------
Appendix B. PARTICLE SIZE DISTRIBUTION AND pH OF REPRESENTATIVE SOIL
SAMPLES FROM MAJOR STUDY PLOTS.
Plot-site
Dogwood-L
Dogwood-2
Dogwood-3
S 22
NE 13
UC Conf.
Cen.
Sky Forest
R.S.
Breezy
Point
Camp
0-Ongo
Depths Sand
2-. 05
mm
(cm) (%)
0-23
77-99
122-141
0-19
112-126
173-198 .
0-25
29-112
119-140
0-20
41-58
79-99
0-24
109-133
246-272
0-25
71-99
250-268
0-15
91-107
208-231
0-29
102-127
208-231
0-24
72-93
110-128
128-149
71.6
62.7
69.2
72.8
67.7
74.6
69.2
71.4
69.1
74.0
74.2
77.5
74.7
74.2
78.3
69.1
58.3
73.8
71.2
71.9
76.2
69.9
73.0
82.2
67.0
65.0
55.5
56.9
Silt
.05-. 002
mm
(%)
20.3
19.1
19.6
20.7
16.9
20.5
18.2
16.7
14.2
18.1
18.1
14.8
15.8
13.8
15.6
24.9
21.6
19.7
18.5
20.7
18.1
20.6
19.2
12.6
24.8
22.2
28.4
35.0
Clay
<.002
mm
(%)
8.1
18.1
11.2
6.6
15.4
4.8
12.6
12.0
16.7
7.9
7.6
7.7
9.5
12.0
6.1
6.1
20.1
6.5
10.3
7.4
5.7
9.5
7.8
5.1
8.2
12.9
16.1
8.2
Fine
Gravel
2- 12mm
(%)
29.0
62.3
38.3
21.7
51.6
28.0
42.2
42.8
42.3
0.2
7.0
6.9
29.2
36.8
37.1
24.7
41.0
34.2
0.0
6.4
5.2
20.6
25.5
27.9
30.0
50.0
55.2
93.4
Gravel
>12mm
(%)
1.3
0.6
0.4
0.0
2.7
0.3
0.9
1.3
0.6
4.9
5.0
0.6
7.7
0.0
0.4
1.9
0.0
0.0
2.2
2.0
0.3
0.8
0.0
0.0
0.5
4.4
0,5
0.0
PH
5.83
5.73
5.59
6.05
5.53
5.52
5.40
5.70
5.50
6.75
5.80
5.33
6.28
5.50
5.21
5.91
5.58
4.88
5.53
5.80
5.50
5.92
5.68
5.65
5.94
5.63
5.35
5.36
268
-------
Appendix B. PARTICLE SIZE DISTRIBUTION AND pH OF REPRESENTATIVE SOIL
SAMPLES FROM MAJOR STUDY PLOTS. (Continued)
Plot-site
Green
Valley
Creek
NE Green
Valley
Snow
Valley
Bluff Lake
Hoi comb
Valley
Sand
Canyon
Schneider
Creek
Barton
Flat
Heart Bar
Camp
Osceola
Depths
(cm)
0-29
98-121
212-234
0-22
81-104
0-14
33-46
0-28
103-127
189-211
0-13
28-43
94-110
0-25
87-110
0-14
81-104
166-189
0-15
61-76
0-15
91-107
122-137
0-15
61-76
91-107
Sand
2-. 05
mm
76.6
78.7
84.2
82.4
84.7
75.3
74.4
79.4
78.2
82.2
69.4
67.3
70.7
79,9
82.0
79.8
81.7
81.4
71.2
69.5
84.8
81.8
81.4
17.9
67.6
67.5
Silt
.05-. 002
mm
16.1
17.2
13.0
11.5
12.6
16.1
16.1
14.0
15.2
11.2
18.8
16.2
14.8
12.6
14.9
14.1
12.9
13.1
19.4
22.4
9.9
8.1
8.9
21.7
21.0
18.2
Clay
<.002
mm
7.3
4.1
2.8
6.1
2.8
8.6
9.5
6.6
6.6
6.6
11.8
16.5
14.5
7.5
3.2
6.1
5.3
5.6
9.4
8.1
5.3
10.1
9.1
10.4
11.4
14.3
Fine
Gravel
2-12mm
48.8
52.8
28.6
37.6
31.4
28.1
40.0
34.8
44.4
47.0
30.0
71.0
83.1
39.6
34.1
104.2
63.1
58.2
4.2
7.4
5.2
7.3
5.6
5.2
7.4
10.1
Gravel
>12mm
1.9
0.6
0.1
0.8
0.0
0.0
0.0
0.2
0.7
0.0
3.7
0.3
2.3
0.1
0.0
0.9
0.1
0.0
ND
ND
ND
ND
ND
ND
ND
ND
pH
6.05
5.78
5.21
6.00
6.13
5.40
5.00
5.74
5.79
5.89
6.18
6.43
7.70
6.52
6.08
6.51
6.45
6.46
6.15
6.45
6.81
6.11
6.13
5.93
5.98
5.78
269
-------
Appendix C. BULK DENSITY (D^) OF SOILS OF MAJOR STUDY PLOTS
Plot Site Surface Subsoil Substratum
Depth H Depth D, Depth 1^
(cm) (gm/cc) (cm) (gm/cc) (cm) (gm/cc)
DW 1
DW 2
DW 3
NE 13
S 22
SF
UCC
CP
BP
TUNE
COO
GVC
NEGV
SV
HV
BL
SC 1
SCR
0-46
0-43
0-51
0-50
0-20
0-61
0-25
0-27
0-29
0-28
0-51
0-29
0-22
0-14
0-13
0-55
0-25
0-20
1.09
1.13
1.13
1.07
1.20
1.05
1.40
1.12
0.74
1.18
1.15
1.11
1.31
1.24
1.46
1.15
1.30
1.19
41-157
43-147
51-157
50-189
20-145
61-160
25-152
27-80
29-147
28-90
51-149
29-156
22-150
14-55
13-117
55-147
25-110
20-145
1.46
1.64
1.94
1.61
1.53
1.53
1.69
1.65
1.17
1.67
1.68
1.85
2.15
1.56
1.77
1.67
1.80
1.75
147-267 1,57
189-272 1.53
145-290 1.70
160-277 1.47
152-250 1.68
147-284 1.57
150-246 2.10
147-255 1.74
145-234 1.73
270
-------
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272
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Appendix F. ORGANIC CARBON (C) AND NITROGEN (N) IN THE SURFACE SOILS
TO A DEPTH OF 25 cm.
Plot Site
Dogwood 1
Dogwood 2
Dogwood 3
NE 13
S 22
Sky Forest R.S.
U.C. Conference
Center
Camp Paivika
Breezy Point
Tunnel-2
Camp 0-Ongo
Green Valley Creek
N.E. Green Valley
Snow Valley
Holcomb Valley
Bluff Lake
Sand Canyon 1
Sand Canyon 2
Schneider Creek
Barton Flat
Camp Osceola
Heart Bar
C
(g/100g)
2.56
1.88
3.46
2.70
1.70
2.03
1.10
1.78
2.08
1.63
1.72
0.93
1.47
0.83
1.14
3.42
0.65
1.78
2.15
2.99
1.14
0.87
N
(g/100g)
0.094
0.069
0.105
0.097
0.071
0.076
0.040
0.081
0.102
0.051
0.122
0.036
0.061
0.041
0.054
0.118
0.031
0.084
0.092
0.119
0.043
0.034
C/N
27.3
27.2
33.0
27.9
23.9
26.8
27.5
22.0
20.4
32.0
14.1
25.8
24.1
20.4
21.1
29.0
21.0
21.1
23.5
25.1
26.8
25.6
273
-------
Appendix G. AVAILABLE SOIL WATER STORATE CAPACITY OF MAJOR STUDY PLOTS
Plot-Site
Breezy Point
Sky Forest
Green Valley Creek
Bluff Lake
Dogwood-2
Dogwood-1
NE 13
U.C. Conf. Cen.
Dogwood-3
S 22
Schneider Creek
Camp 0-Ongo
Sand Canyon
Tunnel-2
NE Green Valley
Camp Paivika
Holcomb Valley
Snow Valley
Soil
Depth
( cm)
152
152
152
152
152
152
152
152
152
152
152
152
152
Available Water
(Vol.%) (cm)
15.4 23.4
14.3 21.8
14.3 21.7
13.9 21.2
13.5 20.6
13.4 20.4
12.9 19.6
12.4 18.9
12.2 18.5
10.6 16.1
8.9 13.5
8.6 13.1
7.7 11.7
12.5
10.3
8.1
8.4
16.3
Soil Total
Depth Available
Water
(cm) (cm)
256
208
203
223
267
Not
272
269
Not
208
221
152
262
86
121
80
116
61
39.2
30.6
28.9
28.4
29.0
sampled
37.4
27.9
sampled
18.4
28.8
13.1
13.8
10.8
12.4
6.5
9.7
9.9
Range
7.7-15.4 11.7-23.4
6.5-39.2
Mean
11.9
18.5
21.6
274
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Appendix L. TAXONOMIC LIST OF SOIL MICROARTHROPODS COLLECTED FROM THE
BREEZY POINT, SNOW VALLEY AND NEGV STUDY PLOTS, 1973-74.
Insecta
Protura
Campodeidae
Japygidae
Lepismatidae
Collembola
Istornidae
Entomobryidae
Poduridae
Onychiuridae
Sminthuridae
Thysanoptera
Pscocoptera
Hymenoptera
Diptera
Coleoptera
Staphylinidae
Silphidae
Curculionidae
Lathridiidae
Raphidiidae
Myriapoda
Diplopoda
Chilopoda
Geophilidae
Scut igeromorpha
Symphyla
Pauropoda
Arachnid a
Araneida
Chelonethida
Acarina
Prostigmata
Labidostorn idae
Eupodidae
Bdellidae
Nanorchestidae
Stigmaeidae
Cunaxidae
Ragidiidae
Erythraeidae
Anystidae
Neophylobiidae
326
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Appendix L. TAXONOMIC LIST OF SOIL MICROARTHROPODS COLLECTED FROM THE
BREEZY POINT, SNOW VALLEY, AND NEGV STUDY PLOTS, 1973-74
(Continued)
Arachnida (continued)
Tydeidae
Cryptognathidae
Raphignathidae
Cheyletidae
Linotetranidae
Paratydeidae
Trombidiidae
Caeculidae
Me sostigmata
Zerconidae
Trachytidae
Phytoseidae
Ascidae
Hypoaspidae
Pachylaelaptidae
Rhodacaridae
*
Cryptostigmata
Cyranodamaeidae
Jacotella sp.
Gymnodamaeus sp.
**
Damaeidae
Genus 1 sp. 3
Genus 1 sp. 6
Genus 2 sp. 5
Genus 5 sp. 3
Eremaeidae
Eremaeus stiktos Higgins
Eremaeus sp. (two species)
Oribatulidae
Scheloribates sp.
Hemileius sp.
Liacaridae
Liacarus sp. nr.
Charassobatidae
Ametroproctus sp.
Cepheidae
Eupterotegaeus sp.
* Cryptostigmatid identifications by R. A. Norton, State Univ. of
New York, Syracuse Campus
** Genus and species numbers refer to Norton terminology.
327
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Appendix L. TAXONOMID LIST OF SOIL MICROARTHROPODS COLLECTED FROM THE
BREEZY POINT, SNOW VALLEY, AND NEGV STUDY PLOTS, 1973-74
(Continued)
Passalozetidae
Passalozetes sp.
Hermanniellidae
Hermanniella sp,
Palaeacar idae
Palaeacarus sp.
Cosmochthono idea
Cosmochthonius sp.
Aphelacaridae
Aphelacarus sp.
Camisiidae
Camisia sp.
Ceratozetidae
Propelops sp.
Galumnidae
Philogalumna sp.
Tectocephe idae
Tectocepheus sarekensis Tragardh
328
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GLOSSARY
(An underlined word in a definition implies that this word is
defined in another part of this glossary).
AAH - Ambient air house; a greenhouse experiment to evaluate tree
growth in which ambient air was drawn into the house by fans.
AAO - Ambient air outdoors; used in reference to the outdoor control in
an experiment on tree growth.
Abscission - Act or process causing leaves or needles to detach from
the stem and fall to the ground; it occurs following advanced oxidant
injury to leaves.
Accumulated Oxidant Dose - The sum of all the hourly average concentra-
tions of total oxidant for any specified period, e.g., a month or a
growing season, expressed as micrograms per cubic meter -hours (ug/m3
-hrs).
Agar Media - A gelatinous nutrient substrate for growing microorganisms
in the laboratory.
Alluvial - Deposited by running water, as soil material deposited
during a flood.
Ambient Air - Air surrounding a given location; the outside air.
APCD - Air pollution control district, a county agency.
Attack - The point on a tree where the female bark beetle (Dendroctonus
spp.) bores through the bark to feed and begin egg laying.
Available Water Storage Capacity - The total amount of water which a
soil is capable of holding and which the plants can use.
Background Concentration (of ozqnej_ - The world-wide background or
natural concentration of tropospheric ozone injected downward from the
stratosphere or formed by photochemical reactions in the troposphere;
generally considered to be 59yg/m3 (0.03 ppm).
Basal Area - The area of cross section of a tree, expressed in square
meters, and referring to the section at breast height.
Basal Fire Scars - Area of charred wood at the base of a living tree
caused by a wildfire.
329
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Bioindicator - Biological organisms which have specific sensitivity to
a single pollutant and thus are useful as indicators for the presence
of that pollutant.
Biomass - The total quantity at a given time of living organisms of one
or more species per unit of space (species biomass) , or of all the
species in a community (community biomass).
Bole - The trunk or stem of a tree.
Bolt - A relatively small cylindrical section cut from the stem of a
tree.
Branch Order - The arrangement of branches on a tree. The following
terms are used to identify branches according to their order: main
stem is referred to as the leader; any branch growing out of the leader
is a first order branch; any branch growing out of a first order branch
is a second order branch; any branch growing out of a second order
branch is a third order branch, etc.
Cation - An ion which is positively charged in solution; typical, .
cations in soils are potassium, sodium, calcium and magnesium (K , Na ,
Ca4"1", and Mg4"1") .
Chlorotic Mottle - Irregular, diffuse patterns of yellow areas inter-
spersed with normal green tissue.
Climax - Vegetation existing in a relatively stable equilibrium with its
environment and with good reproduction of the dominant plants.
Codominant - Trees that share dominance of the canopy of a forest stand.
Colluvial - Deposited at least in part as a result of gravitational
movement of material; occurs at the base of slopes and is sometimes
stony or rubbly,
Colonization - Spread of a fungus throughout a substrate.
Complement - See leaf complement and needle complement.
Conidial - Of or pertaining to conidia which are asexual spores of many
fungi.
Cores - Cylindrical samples of wood removed from a tree with a tool
known as an increment borer.
Cover - The ground area covered by the individuals of one species.
Crown - The portion of a tree containing limbs, branches and foliage.
330
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Crown Drip - Liquid which falls to the ground under the crown of a tree
or other plant during precipitation or dew-formation onto the crown.
Crumb Structure - Same as granular structure except that the soil
aggregates are relatively porous; common in the surface of forested
soils.
Damping-off - The lethal effect of certain fungi on germinating seeds
or seedlings.
Data Form - A standardized form upon which a certain type of information
is recorded, mostly in the field.
Data Set - An identifiable complete unit of information composed of
several individual entries.
DBH - D_iameter of the trunk of a tree measured at bjreast h_eight above
the ground surface.
Debug (. . .computer program) - The identification and elimination of
problematical errors in a computer program so that the computer may
perform the intended functions.
Density - Number of individuals per unit area.
Dilution Plating - A known weight of humus or mineral soil is suspended
and diluted in sterile distilled water; a portion of the suspension is
swirled in water agar medium; developing fungal colonies are identified
and counted.
Direct Plating - A known weight of litter or fermentation zone material
is distributed evenly over the surface of water agar medium; developing
fungal colonies are identified and counted.
Dose - A measured concentration of a toxicant for a known duration of
time to which vegetation is exposed.
Duff - A collective term that includes the litter layer (fresh or
slightly altered organic matter), fermentation layer (partially decom-
posed organic matter), and humus layer (amorphous organic matter) of
the soil.
EClosion - The emergence of the adult insect from the pupa or the act
or process of hatching from the egg.
Ecosystem - A level of biological organization that includes the total
array of plant and animal life in an environment and also the matter
which cycles through the system and the energy used to power the system
331
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Egg Niche - A small notch chewed by the adult bark beetle in the side of
a gallery into which an egg is deposited.
Epidemiology - The study of spread or increase of disease.
Exchangeable Cation - A cation which is held mainly by the colloidal
portion of the soil (clay and organic matter) which is not soluble in
pure water but is easily exchanged with the cation of a neutral salt
solution.
FAH - Filtered air house; used in reference to the greenhouse treatment
in an experiment on tree growth in which filtered air (ozone removed)
was forced into the house by fans.
Fascicle - A bundle of 1-5 needle leaves all originating from a common
growth point; a characteristic of the foliage of pine trees.
Forest Floor - All dead vegetable matter or organic matter resting on
the surface of the mineral soil, including leaves, branches, needles
and humus not incorporated into the mineral soil; under forest
vegetation.
Frass - A combination of boring dust and excrement or feces produced by
feeding insects.
Gallery (length) - The tunnel created by adult bark beetles as they feed
and deposit eggs in the phloem layer of a tree.
Granular Structure - Soil aggregates generally spheroidal in shape and
less than 10 mm in diameter and relatively nonporous,
Gruss - Any rock that is granulated but not decomposed by weathering.
Partially weathered granitic rocks are often gruss.
Herbaceous - Refers to plants that die back to the ground each year;
for example, grasses and forbs are distinct from shrubs and trees in
this regard.
Host - The plant, or animal, on, or in which a parasite exist
Human Welfare Effects - Includes, but is not limited to, eff .cts on
soils, water, crops, vegetation, man-made materials, animals, wildlife,
weather, visibility, and climate, damage to and deterioration of
property, and hazards to transportation, as well as effects on economic
values and on personal comfort and well-being. (Clean Air Act, 1970).
Hypha - One of many cellular filaments making up the thallus of a
fungus.
Importance Value - A measure of the degree to which a species occurs in
a vegetation type and exerts influence on the microclimate of the type.
332
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Inclusion Type - This refers to images in the x-rays of the bark samples
that are categorized by form and developmental stage of the insect
inclusions. There are six categories used in this study.
Infection - Establishment of a physiological relationship between a
host and pathogen.
Instar - The period or stage between molts in the larva, numbered to
designate the various periods; e.g., the first instar is the stage
between the egg and the first molt, etc.
Internode - The portion of a woody stem produced in a single growing
season,
Isolate - The product of culturing a small portion of a microorganism
to yield a new individual.
Lachrymator - An atmospheric chemical compound which induces tears to
run from the human eyes, and possibly from the eyes of various animals.
Larva - The young individuals in an insect population, which are due to
undergo changes in their structural form.
Larval Mine - The small tunnels created by bark beetle larvae as they
feed in the phloem or bark of a tree, generally perpendicular to the
parent adult gallery.
Leaf Complement - A subjective evaluation of numbers of leaves present
on all living branches of an oak tree as average, or less than average,
for the stand.
Life Table - Similar to the actuarial tables kept by life insurance
companies for humans. As adapted for insects, it is a convenient method
to account for mortality during each developmental stage of an insect,
Line Interception Method - The sampling of vegetation by recording the
plants intercepted by a measured line placed close to the ground, or by
vertical projection on the line.
Loam - A textural class of soil containing 7 to 27 percent clay, 28 to
50 percent silt, and 23 to 52 percent sand,
Main Leader - The central trunk of a tree, usually refers to the
youngest or tip portion,
Metamorphic Rock - Rock formed from pre-existing rock by mineralogical,
chemical and structural alteration due to geologic processes originat-
ing within the earth.
333
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Mesoscale Meteorological Patterns - A scale of observation of meteoro-
logical elements, namely winds and temperatures, which is intermediate
between very local observations such as up-canyon or down-canyon
breezes in a single canyon and the synoptic scale observations describ-
ing conditions over a broad area like the southwestern United States.
The density of observing stations for mesoscale interpretation is
typically 50 miles apart.
Micrograms Per Cubic Meter, yg/m3-A measure of the concentration of a
pollutant in micrograms per cubic meter of air at standard temperature
and pressure.
Minimum Moisture Content - Measured soil water content at the driest
period of the year;corresponds approximately to permanent wilting
point.
Mixed Brood - A situation in bark beetle infested trees in which more
than one species of bark beetle offspring is present in the same tree.
Model - A description of the system which it represents.
Molt - The process of certain organisms shedding their outer covering,
to be succeeded by new growth.
Mortality - A standing tree whose current year buds are dead; a conif-
erous tree may be defoliated without being dead.
Needle Complement - The total number of needle fascicles retained on
each branch internode, which were formed in any one growing season.
Needle Injury Score - The score or index is the sum of individual rat-
ings for chlorotic mottle, necrosis and abscission, each on a scale of
0 to 4. The score, or index, may be as high as 12 for a single annual
needle complement. Scores for current and one-year-old needle comple-
ments are often added together; this scoring procedure is adequate for
seedlings and small saplings only.
Necrosis - An advanced stage of tissue injury indicated by brown, dead
tissue, involving all or parts of a leaf or needle; necrosis develops
following chlorotic mottle, especially in older leaf tissues.
Oviposition - the act of depositing eggs.
Qxidant Air Pollutants - Gas phase molecules and compounds capable of
oxidizing a reference substance, namely the liberation of iodine from
potassium iodide solutions; these include ozone (more than 90 percent)
and smaller amounts of nitrogen dioxide and peroxyacetyl nitrate and its
homologs, e.g., propionyl and butyrl.
Paradigm - The basic pattern underlying the functioning of a system.
334
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Parameter - A characteristic which can be easily quantified.
Parasitoid - An insect, generally a wasp or fly, which lays its own
eggs on the eggs, larvae, or adults of other species of insects (hosts)
so that the larvae may develop by feeding within or upon the body of the
host.
Particle Size Distribution - See soil texture.
Pathogen - Organism capable of causing disease.
Pathogen Type - An organism, not usually considered a pathogen, which
behaves like a pathogen under special circumstances.
Pathophysiology - The altered metabolic state of pathogen infected, or
toxicant injured tissues.
Permanent Wilting Point - The soil moisture content at or below which
plants can absorb water only very slowly or not at all; sunflower used
as a test plant wilts and does not recover over night.
pH (soil) - A measure of the acidity or alkalinity of a soil expressed
as the negative logarithm of the hydrogen-ion activity of the soil.
The general range of soil pH is 4.0 (very strongly acid), 7.0 (neutral),
10.0 (strongly alkaline).
Phenology - The study of the time of appearance of characteristic peri-
odic events in the life cycles of organisms in nature.
Phloem - The complex tissue of higher plants which forms a spongy layer
between the protective outer layer and the inner structurally sup-
portive portion. Its function is to transport food materials.
Photosynthetic Capacity - The ability of a plant to convert inorganic
carton in the air,from carbon dioxide, into organic carbon molecules
in a given environment.
Phytotoxicant - Any chemical agent that causes injury to plants.
Pitch Tube - A small resinous tube projecting from the bark of a tree
as a result of a beetle boring into the tree. A successful attack is
indicated by frass in the resin while an unsuccessful attack produces
a pitch tube without frass.
Plot - An area of land surface within which vegetation, soil, and
animal life is periodically inventoried and studied for determining
dynamic interactions among them. In this study, 18 plots were delin-
eated on the ground during 1972 in the San Bernardino Mountains. The
range of individual plot area sizes runs from 0.2 ha to 1.2 ha.
335
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Pollinator - An organism, usually an insect, which carries pollen from
one flower to another.
ppb - Parts by weight, or volume, of pollutant per billion parts by
volume of air (usually refers to volume of pollutant if not so stated).
pphm - Parts by weight, or volume, of pollutant per hundred million
parts by volume of air (usually refers to volume of pollutant if not so
stated).
ppm - Parts by weight, or volume, of pollutant per million parts by
volume of air; it usually refers to volume of pollutant if not so
stated.
Pupal Cell - A cavity in the bark or phloem created during the final
feeding of the larvae of bark beetles and in which the larvae go into
a non~feeding, and often immobile, transformed stage of development.
Quadrat - A sampling area O.lm square used to sample herbaceous
vegetation.
r-Value - The coefficient of correlation between a dependent and an
independent variable. When there is no association between two vari-
ables, the correlation coefficient is 0; when there is perfect positive
association, the coefficient is +1; and when there is perfect negative
association, the coefficient is -1.
Rearing - Raising insects in the laboratory. This allows insects to
complete their development to the adult stage before being collected
and identified. Immature insects are difficult to identify so this
is an important procedure.
Rearing Carton - A paper ice cream carton with a glass vial attached to
the lid. It is used to capture insects as they emerge from the bark
samples. The insects are attracted to light and fall into the glass
vial.
Ring Count - A method used to determine tree age by counting annual
growth rings of the bole, usually at DBH.
Sanitation Salvage - A forest management technique with the objective
of periodic removal of ponderosa and Jeffrey pines judged to have re-
duced vigor and to be more susceptible to fatal attack by bark
beetles; the selection and cutting process is repeated every 10 years.
Sapling - A tree that is more than one meter in height and less than 10
cm in diameter at breast height.
Saprophyte - An organism utilizing an organic source of food which is
dead.
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Senescence - The combined processes by which leaves or needles on a
tree age, and undergo abscission.
Simulation - The process of using a dynamic model on an electronic
computer to mimic the functioning of a system or process by repeated
step-by-step solution of the equations describing the system.
Soil Bulk Density - The mass of dry soil per unit volume of soil in its
natural state which may be moist at the time the volume is determined.
Soil Core - A cylindrical sample of soil, usually circular in horizontal
cross section.
^oil-dilution Assay - See dilution plating.
Soil Moisture Regime - The variation of soil moisture content through-
out the soil through an entire year.
Soil Texture - A classification of soil material based upon particle
size distribution of the mineral grains in the soil, the relative pro-
portions of sand, silt, clay and gravel.
South Coast Air Basin (SCAB) - One of the five principal airsheds
(atmospheric basins) in the State of California and partially located
within the six counties of Santa Barbara, Ventura, Los Angeles,
San Bernardino, Orange and Riverside.
Species Composition - The relative percentage of the total number of
individuals in a vegetation type represented by a certain species.
Species Dominance - The degree of influence a species exerts over a
vegetation type .
Spore - A reproductive body capable of developing into a new individual
fungus thallus.
Subsoil - A general term for soil material from about 25 to 100 cm
depth below the surface, although these depths may vary considerably.
Succession - The replacement of one vegetation type by another.
Synoptic meteorological patterns - Typically a description o,*
sure patterns at the surface and at higher elevations over ;
area (see mesoscale meteorological patterns) . Synoptic sc-'
are usually more than 100 miles apart, e.g., Los Angeles,.
and Tonapah, Nevada.
System - A set of elements together with relations among
and among their states.
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Systems Ecology - The application of the philosophy and techniques of
systems analysis to ecological problems.
Temperature Inversion - When air temperature decreases from the surface
up at a rate greater than 5.5 F per 1,000 ft. or 1.0 C per 100 m, there
is pronounced vertical mixing. But if the temperature increases with
height, vertical air movements are suppressed. This temperature pro-
file is "inverted" from the normal condition and it is a temperature
inversion. Air pollutants are trapped near the ground by temperature
inversions.
Terminal Shoot - The uppermost section of the main leader of a tree.
Thallus - The vegetative structures comprising body of lower plant
forms,for example, fungi.
Troposphere - The layer of air extending 7 miles above the earth's sur-
face and containing 80 percent of the total atmospheric mass.
Vegetation Type - A plant community of definite floristic composition,
presenting a uniform physiognomy and growing in uniform habitat
conditions.
Volumetric Water Content - The volume water content of soil per unit
volume of soil; expressed as percent by volume,
Water Balance - A complete accounting of the soil moisture regime;
water gains and losses from, and to, the atmosphere, and losses to
runoff and deep percolation into the groundwater system.
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