BIRD-HABITAT RELATIONSHIPS IN THE
KLAMATH/SISKIYOU MOUNTAINS
By
JOHN DOTY ALEXANDER
A thesis submitted to the Department of Biology
And the Graduate School of Southern Oregon University
In partial fulfillment of the requirements
For the degree of
MASTER OF SCIENCE
In
BIOLOGY
Ashland, Oregon
1999
Copyright John Doty Alexander 1999
APPROVAL PAGE
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ABSTRACT OF THESIS
BIRD-HABITAT RELATIONSHIPS IN
THE KLAMATHWSISKIYOU MOUNTAINS
By John D. Alexander
The Klamath/Siskiyou Region is a globally significant center for biodiversity and
although it is recognized as an important area for avian diversity it has received little
ornithological attention. Research in this field is critical for developing adequate
conservation strategies for the region.
Landbird abundance and environmental-vegetation data were collected across the
Klamath National Forest's five west-side ranger districts. Analyses were conducted on
various subsets of the bird census and habitat data in order to identify bird-habitat
relationships. In this paper, bird and habitat relationships resulting from several
analytical approaches are used to build confidence in conclusions about bird-habitat
associations.
Bird associations with high elevation conifer, mixed conifer/hardwood and
riparian habitats are explored. In addition, the influence of forest structure on the
distribution of old growth associated bird species is examined.
iii
"All I know is she sang a little while and then flew on...
If you hear that same sweet song again, will you know why?
Anyone who sings a song so sweet is passing by,
Laugh in the sunshine, sing, cry in the dark,
Fly through the night."
Hunter/Garcia
To my Grandmothers, Mary Jones and Edith Alexander; together they taught me to
always strive for learning, whether it be in a classroom, barefoot on the river, or
anywhere else we go.
iv
ACKNOWLEDGMENTS
The author wishes to acknowledge the Forest Service Pacific Southwest Region's
Partners In Flight Steering Committee for its support of this monitoring research. Special
thanks to the Klamath National Forest, Sam Cuenca, Kathy Granillo and Bill Maynard
for helping to build the Forest-wide Landbird Monitoring Program. Thanks to the
Redwood Sciences Laboratory, and CJ and Carol Ralph for their continued support.
Also, thanks to Steve Herman and fellow Evergreen Students, Sue Sniado, Thomas
Mohagan, Lisa Renan, John Munari, Glenn Johnson, Jonus Majerski, Tara Chestnut, and
Chrissy Apodaka. In addition I would like to thank Brian Helsaple, Lisa Greenberg,
George Livingston and the Oak Knoll Fire Crew. My appreciation is extended to John
Menke, Stewart Janes, my thesis committee, SOU's School of Sciences and the
Department of Biology.
Finally, my deepest gratitude to my wife Taylor Alexander, who assisted in all aspects of
this project while providing encouragement and support; and to our daughter Natalie for
her additional inspiration.
v
TABLE OF CONTENTS
CHAPTER
PAGE
I.
INTRODUCTION AND APPROACH
Bird Conservation and Ecosystem Management
Bird-habitat Relationships
Objectives
Approach
Study Area
Landbird Census and Environmental-vegetation Data
Analysis Methods
I
1
3
4
5
7
9
19
II.
ANALYSIS OF BIRD-HABITAT RELATIONSHIPS
AT A LANDSCAPE LEVEL USING THE 500 STATION
DATASET
Cluster Analysis of 500 Station Dataset
Canonical Correspondence Analysis (CCA)
of 500 Stations
24
24
III.
IV.
ANALYSIS OF BIRD-HABITAT RELATIONSHIPS AT A
WATERSHED LEVEL USING TEN STUDY AREAS FROM
THE 500 STATION DATASET
Study Areas
Canonical Correspondence Analysis (CCA) of Ten
Study Areas
Correlation Analysis of Ten Study Areas
ANALYSIS OF BIRD-HABITAT RELATIONSHIPS
WITHIN LATE-SERAL MIXED-CONIFER FORESTS
Canonical Correspondence Analysis (CCA) of
Intensive Point Counts
Correlation Analysis of Intensive Point Counts
vi
33
44
44
47
52
55
55
57
V.
DISCUSSION
Methods
Distribution Of Birds Across Klamath/Siskiyou
Habitat Types .
Conclusion
LITERATURE CITED
Appendix A
Appendix B
61
61
63
74
76
Common and scientific names for bird species
included in the 500 Station Dataset and Late-seral
Dataset
81
Environmental Variables from 500 Station Dataset
and additional variables collected for Late-seral
Dataset
84
vii
LIST OF TABLES
PAGE
Table 1.1.
Approaches used to analyze bird-habitat relationships
.
11
Table 1.2
Fifty-seven bird species from 500 Station Dataset
.
13
Table 2.1.
Description of environmental characteristics across habitat
types derived from cluster analysis of 500 Station Dataset
.
25
.
26
.
29
Table 2.2.
Constancy of plant species in vegetation sublayers across
habitat types derived from cluster analysis of 500 Station
Dataset
Table 2.3.
.
.
.
.
.
.
.
.
..
.
34
.
.
.
38
.
39
Three bird assemblages derived from CCA polygons in
analysis of 500 Station Dataset
Table 2.7.
.
Environmental variables contained within vegetation
community polygons, based on ordination of 57
environmental variables from 500 Station Dataset
Table 2.6.
.
CCA X and Y axis eigenvalues and variance explained by
first two CCA axes in the analysis of the 500 Station dataset;
environmental variables which had the furthest distance between
their mean spatial location and the origin of the CCA with X
and Y axis scores
Table 2.5.
.
.
Average number of individuals and species per station,
and constancy and percent of total individual bird species
detected within 7 vegetation series from the 500 Station
Dataset
Table 2.4.
.
.
.
.
Percent of bird species within each assemblage which are:
classified as at risk, within three migration categories,
considered old growth associates, and members of feeding and
nesting guilds
.
.
.
viii
.
.
.
40
Table 2.8.
CCA X and Y axis scores for bird species from the 500
.
.
.
Stations Dataset
.
.
.
42
Table 3.1.
500 Station Dataset study areas
.
45
Table 3.2
X and Y axis eigenvalues, and the percent of variance
explained by each axis in the CCAs .
.
.
.
47
Environmental variables which had CCA X or Y axis
correlations of >0.4 or <-0.4 in five or more study areas
.
49
Bird species which had CCA X or Y axis correlations
.
> 0.91 or < -0.91 in three or more study areas
.
51
Number of study areas where bird variables were
significantly correlated with one or more environmental
.
53
Weighted correlations of environmental variables and bird
species with CCA X and Y axes using 61 late-seral forest
bird-habitat census stations .
.
.
.
.
56
Highest correlations between bird species and environmental
.
variables from 61 late-seral forest bird-habitat stations.
59
Table 3.3
Table 3.4.
Table 3.5.
Table 4.1.
Table 4.2.
ix
.
.
.
LIST OF FIGURES
PAGE
Figure 1.1.
Figure 2.1.
Figure 2.2.
Northwestern California and The Klamath National
Forest's west-side in Siskiyou County.
.
.
.
8
Vectors representing the influence of 13 environmental
variables defined by the CCA ordination of 57 environmental
variables
.
.
.
.
.
.
.
35
CCA ordination of 57 bird species classified into 3 bird
assemblages (clear polygons) from the 500 Station Dataset .
37
x
CHAPTER I: INTRODUCTION AND APPROACH
Bird Conservation and Ecosystem Management
The Klamath/Siskiyou Region is a globally significant center for biodiversity and
although it is recognized as an important area for avian diversity, it has received little
ornithological attention (Trail et al. 1997). Because of the Region's patchwork of
habitats and its complex mix of breeding bird species there is a unique opportunity to
study bird-habitat relationships in the Siskiyou Mountains; this research is critical for
developing adequate conservation strategies (Trail et al. 1997). With the development of
ecosystem management programs in public land management agencies and recent
concerns about declining landbird populations, investigation of landbird-habitat
relationships has become a priority for the USDA Forest Service (USDA and USDI 1994,
USDA 1994 and USDA 1996) and many other agencies.
Under the President's Northwest Forest Plan the Klamath/Siskiyou Mountains
will not only be influenced by management strategies which focus on the conservation of
old growth habitats and their associated wildlife, it will continue to be affected by timber
harvest and cattle grazing (USDA et al. 1993, USDA and USDI 1994). While
implementing the Ecosystem Management Plan land management agencies are under
direction to monitor management effects on the ecosystem (USDA and USDI 1994).
Standardized techniques for monitoring bird abundance and habitat composition have
1
2
been developed and can be used to determine bird-habitat relationships (Ralph et al.
1993).
An understanding of bird-habitat relationships can provide insight into how
environmental characteristics influence bird distribution. This thesis presents results that
will provide land managers with precise lists of birds likely to be affected in local
environments. Bird relationships with habitat-types are determined to provide
information on which birds are likely to breed in specific habitat types and within broad
ecological zones. I also investigate how forest characteristics influence bird species
distribution.
With insight into the relationship of bird community composition with habitats
and forest conditions, bird population distribution may be used as an index for predicting
changes brought about by land management activities. With increased knowledge of
local bird-habitat relationships, predictions of how bird community composition will
change as forest characteristics are manipulated may be made and, in turn, used to
describe a desired condition. The effectiveness of management practices can be assessed
by monitoring changing bird communities (USDA and USDI 1994). In addition,
increased information about bird-habitat relationships allows conservation biologists to
assess how well the Klamath/Siskiyou Mountain avifauna will be conserved under
current land management plans. Management and conservation implications are
especially relevant as old growth forests in the Klarnath/Siskiyou Region continue to be
impacted under Late Successional Reserve (LSR) management (USDA and USDI 1994,
USDA 1998). As bird monitoring becomes integrated into federal land management
3
plans and the ecosystem management process the influence of bird conservation on land
management policies in the United States will grow.
Bird-habitat Relationships
Bird-habitat relationships have been the focus of much research. Species
composition of the vegetation has been shown to be important to habitat selection by
birds. Frequencies of occurrence of the major tree species are important aspects of bird
community habitat selection (Rice et al. 1983). By studying the effects of plant species
on the foraging behavior of birds, Robinson and Holmes (1984) concluded that the
presence of different plant species causes variation in the foliage distribution and
arthropod availability and therefore influence a bird's success at exploiting particular
habitats. MacArthur and MacArthur (1961) determined that structural diversity of
habitats has more influence on bird species diversity than does plant species diversity.
Forest seral-stage and stand structure have been found to influence the distribution of
birds across Douglas-fir forests of Northwestern California (Marcot 1984). In addition
Marcot (1984) showed forest overstory to be a major component influencing bird
composition. Dellasala et al. (1996) also found relationships between breeding birds and
conifer forest seral stages in Southeast Alaska. By studying differences in bird
distribution between cut forests and uncut forests, management treatments have been
shown to be important in determining the distribution of bird communities (Szaro and
Russell 1986). Raphael et al. (1985) determined that 14 northwestern bird species will
4
decline by 50% as mature Douglas-fir forests are harvested and replaced with younger
stands.
Objectives
The objectives of this research are to investigate bird-habitat relationships and to
identify environmental characteristics that influence the distribution of birds in the
Klamath/Siskiyou Mountains. By studying patterns of bird community composition in
relation to environmental variables, the effects of various land management practices on
bird distribution can be inferred. This research is designed to explore the effects of land
management on bird distribution by asking questions that demonstrate how landbird
monitoring can be used in the ecosystem management process:
a) How are birds distributed across Klamath/Siskiyou Mountain habitat types
(Jimerson et al. 1997) at the landscape level?
b) What forest characteristics (e.g., seral stage, fuels accumulation, canopy cover)
are correlated bird distribution within specific habitats?
c) Which habitats or habitat conditions are important for priority bird species (e.g.,
landbird species associated with late-successional forests; USDA 1998)?
d) Which bird species or groups of species indicate current and desired conditions
(e.g. forests characterized by fuels accumulation and open late-seral forests
respectively) on managed lands?
My hypothesis is that bird species composition is driven, in part, by measurable
environmental characteristics, or groups of characteristics, that change over time under
A
r
5
forest management practices. Continued analysis of the relationships between birds and
habitat characteristics will allow us to better predict the effects of land management on
bird diversity, as well as provide us with a tool for monitoring the effectiveness of
ecosystem management (USDA and USDI 1994).
Approach
As a part of the Partners In Flight International Landbird Conservation Program,
the Klamath Demographic Monitoring Network (KDMN; Hollinger and Ralph 1995) has
been collecting data across the Klamath National Forest. I contributed to the KDMN by
collecting data on 562 stations across nearly two million acres using extensive point
count breeding bird censuses and releve' habitat/vegetation assessment methods outlined
in Ralph et al. (1993). To build confidence in conclusions about bird-habitat
relationships, McGarigal and McComb (1995) suggest that consistencies in results among
several analytical approaches be used. Descriptive, bivariate and multivariate statistics
were used to examine three bird and habitat census datasets and subsets. I use several
approaches to examine various datasets for identifying explainable relationships between
environmental variables and bird species abundance, species richness and species
diversity.
Chapter II of this thesis focuses on analyzing my extensive 500 point count
station dataset (500 Station Dataset) at a landscape level. At this scale I examine the
associations of birds with habitat-types and environmental characteristics. In the first
three approaches the stations were grouped and classified into habitat-types using a
6
cluster analysis. The distribution of bird detections among the habitat-types was then
examined. Further investigation of bird-habitat relationships was conducted using
Canonical Correspondence Analysis (CCA), a multivariate ordination technique.
Chapter III of the thesis focuses on bird-habitat relationships within
geographically-based subsets of the 500 Station Dataset (Study Areas). I examined birdhabitat relationships across various study areas using several analyses. These included
examining the abundant birds and habitat-types in each Study Area, conducting CCAs on
each Study Area dataset, and looking at correlations between bird and environmental
variables in each Study Area.
In Chapter IV I used an intensive point count dataset (Late-seral Dataset ; Ralph
et al. 1993) to test the influence of canopy cover on the distribution of birds in late-seral
mixed conifer habitats. I conducted CCA and correlation analysis to examine the
difference between the distribution of old growth associated species (USDA et al. 1993)
in open and closed-canopy old growth habitats.
Bird-habitat relationships that result from more than one of the ten approaches are
discussed. I use California bird risk rankings (Manley and Davidson 1993), migratory
habits, nesting characteristics, and foraging techniques (Ehrlich et al. 1988) to better
understand the biological influences associated with observed bird-habitat associations. I
compare my results with similar studies.
7
Study Area
The Klamath/Siskiyou Mountains
The study was conducted on the west side of the Klamath National Forest (KNF),
in Siskiyou County, California, which is located in the Klamath Siskiyou Province
(Figure 1.1). According to the Hierarchical Framework of Ecological Units (Bailey
1995) this area is in the Klamath Mountains section of the Mediterranean Regime
Mountains division of the Humid Temperate Domain within the Pacific Southwest
Region (Jimerson et al. 1996). The climate of the area is an inland expression of a
maritime climatic regime, with an average rainfall of 75-100 cm. The Klamath
Mountains are a group of ranges with moderate to high relief in predominantly
metamorphic rocks having diverse and complex structure (Jimerson et al. 1996).
Drainage tends to be dendritic and large landslide complexes are widespread. Ranges of
shallow to deep soils are formed from serpentinized peridotite, phyllite, gabbro/diabase,
greenstone, semischist, schist and sandstone (Jimerson et al. 1996). These physiographic
features have led to very complex vegetation structure and composition at the landscape
level.
Vegetation consists of mixed-conifer hardwood forests dominated by conifer
species: Douglas-fir (Pseudotsugamenziesii), with ponderosa pine (Pinusponderosa),
sugar pine (P. lambertiana),incense cedar (Calocedrusdecurrens), white fir (Abies
concolor), and California red fir (A. magnifica) at higher elevations. The tree layer also
includes a component of hardwoods including Pacific madrone (Arbutus menziesii),
canyon live oak (Quercus chrysolepis), chinquapin (Castanopsischrysophylla), tanoak
8
f
Figure 1.1. Northwestern California and The Klamath National Forest's westside in
Siskiyou County.
(Lithocarpusdensiflorus), big-leaf maple (Acer macrophyllum), black oak (Q. kelloggii),
Pacific dogwood (Cornus nuttallii), and Oregon white oak (Q. garryana), with red alder
(Alnus rubra), mountain alder (A. tenuffolia), and willow (Salix spp.) in riparian areas.
Dominant shrub species include ceanothus (Ceanothus spp.), manzanita
(Arctostaphylos spp.), western hazel (Colylus cornuta), ocean spray (Holodiscus
discolor), Pacific serviceberry (Amelanchier alnifolia), snowberry (Symphoricarpos
albus), currant (Ribes spp.), and poison oak (Toxicodendron diversilobum). The herb
layer consists of various grasses, forbs and bryophytes, and mosses and lichens cover
various ground and vegetation surfaces.
-I
9
Landbird Census and Environmental-vegetation Data
Landbird abundance and environmental-vegetation data were collected from 500
stations located between 360 and 2,153 m in elevation across the KNF's five west-side
ranger districts. The stations included stands ranging in age from late-seral through
recently logged forests, and those characterized by heavy fuel accumulation and white fir
encroachment due to past fire exclusion. I analyze a 500 Station Dataset, described
below, in Chapters II and III, and a 61 station Late-Seral Dataset in Chapter IV (Table
1.1).
Extensive Point Counts (500 Station Dataset)
During 1992-1995, with the help of Bill Maynard and Thomas Mohagan, I
collected bird census data using a standardized extensive point-count protocol (Ralph et
al. 1993) during the May and June breeding season. Using low resolution maps of major
land cover types and the existing road network, routes were followed in the five ranger
districts. We surveyed 500 stations, 25-30 per day, along secondary and tertiary roads at
half-mile intervals (quarter-mile intervals in riparian areas). We conducted one fiveminute bird count between sunrise and 1100 PDT on each station recording all landbird
species seen and heard. Detections were separated into three categories: birds detected
within 50 m, birds detected beyond 50 m, and birds detected flying overhead. Bird
species abundance and diversity data included all detected birds excluding flyovers. In
my analyses I combined Rufous and Allen's Hummingbirds because they are difficult to
separate in the field.
F
10
Conservation biologists and ecologists commonly employ species richness and
species diversity indices to examine relationships between the environment and animal
populations (Meffe et. al. 1997). Total numbers of individual birds at stations and total
number of bird species at stations are analyzed. A Shannon-Weiner, index which
considers relative abundance in addition to species number (Ludwig and Reynolds 1988),
was calculated for each station.
The US Forest Service and other land management agencies have identified bird
species associated with late-seral forest habitats (USDA et al. 1993). I refer to fourteen
of these species (Table 1.2), which are included in the dataset, as FEMAT birds. FEMAT
is a pneumonic for the Forest Ecosystem Management Assessment Team which is the
group that classified the old-growth associated bird species (USDA et al. 1993). Under
the President's Northwest Forest Plan, lands are to be managed to benefit these species
(USDI et al. 1995). In my analyses I examine variables representing total number of
individual FEMAT birds at stations, total number of FEMAT bird species at stations, and
Shannon-Weiner diversity indices for FEMAT birds.
Environmental Data
With the assistance of a three field technicians I collected vegetation data at each
station between May and September of 1993-1995. We visually estimated total cover
and range in height for the tree layer (>5 m), shrub layer (> 0.5 m and < 5 m), and herb
layer (< 0.5 m) and determined the number of sublayers within each of these three
structural categories. We visually estimated the maximum and minimum DBH of trees in
Table 1.1. Approaches used to analyze bird-habitat relationships with questions each approach is designed to dataset associated with
each approach (.5° = 500 Station Dataset, SA = Study Area Dataset, LS = Late-seral Dataset).
Approach Analyses (Chapter)
1
Analysis of habitat types. (Chapter II)
Questions
What is the distribution of 500 bird census stations?
Does bird abundance and species richness vary between
habitat types?
Dataset
500
2
Constancy of bird species in 7 habitat types
(Chapter II)
How are bird species distributed across 7 habitat types?
500
3
Percent of all bird detections in 7 habitat types.
(Chapter II)
What bird species occur in specific habitat-types?
500
4
Analysis of CCA-derived polygons defining bird What environmental characteristics are correlated with the
groups and associated environmental variables. distribution of birds?
What groups of birds are associated with habitat types?
(Chapter II)
5
Analysis of CCA axis associated birds and
environmental variables. (Chapter II)
500
What environmental characteristics are correlated with the
500
distribution of birds?
What is the association between environmental characteristics
and bird species distribution?
Table 1.1. (Continued)
Approach Analyses (Chapter)
6
Identification of watershed based study area
subsets of 500 Station Dataset. (Chapter III)
L
Number
What bird species occur in the 10 study areas ?
Dataset
SA
7
Analysis of CCA axis associated birds and
environmental variables in 10 study areas.
(Chapter III)
What environmental characteristics are correlated with the
distribution of birds in several study areas?
SA
8
Correlation analysis of birds and environmental
variables by 10 study areas. (Chapter III)
What bird and habitat relationships occur in several study
areas ?
SA
9
Analysis of CCA axis associated birds and
environmental variables in late-seral forests.
(Chapter III)
What environmental characteristics are correlated with the
distribution of birds in late-seral forests?
LS
10
Correlation analysis of birds and environmental
variables in late-seral forests. (Chapter III)
What bird and habitat relationships occur in late seral forests ? LS
-
Table 1.2. Fifty-seven bird species from 500 Station Dataset with total number of individuals detected and number of stations on
which individuals were detected in that dataset. California risk ranking (Calrank), diet, foraging technique, migratory status and
nesting substrate for bird species. FEMAT birds are indicated by bold print (USDA and USDI 1994, Manley and Davidson 1993,
Ehrlich et al. 1988).
Bird Species
Code
Blue Grouse
BLGR
Calrank Diet
-9
Omnivore
MOQU
Mountain Quail
-9
MODO
Mourning Dove
4.04
Seeds, bulbs,
greens, Insects
Seeds, grain
SELA
Selasphorus spp.
5.45
Nectar, insects
ACWO
Acorn Woodpecker
-9
RBSA
Red-breasted
Sapsucker
Downy Woodpecker
Hairy Woodpecker
Northern Flicker
3.49
DOWO
HAWO
NOFL
PIWO
OSFL
Pileated
Woodpecker
Olive-sided
Flycatcher
Omnivore
Insects, tree sap,
fruit
Insects
Insects
Insects
Foraging Technique
Foliage browse, ground
glean
Ground glean
Migration Nest Substrate
Resident Ground
Resident Ground
Ground glean, foliage glear Short
distant
Long
Hover glean, hawks
distant
Bark glean, bark drill,
hawks
Bark glean
vine
Resident Snag
-9
Insects
Short
distant
Bark glean
Resident
Bark glean
Resident
Ground glean, hawks, bark Short
distant
glean
Resident
Bark glean
6.21
Insects
Hawks
-9
-9
3.09
Deciduous tree,
conifer tree
Deciduous tree,
conifer tree, shrub,
Long
distant
Deciduous tree,
snag
Snag
Conifer tree, snag
Snag
Snag
Conifer tree
Table 1.2. (Continued)
Code
Bird Species
DUFL
Dusky Flycatcher
HAFL
Calrank Diet
3.8
Insects
Miaration
Hawks, hover glean
Long
distant
Hawk
Long
distant
Hawk, hover glean
Long
distant
Ground glean, foliage glear Resident
Ground glean, foliage glear Resident
Ground glean
Resident
Foliage glean, bark glean Resident
F:oragina Technique
Nest Substrate
Shrub, tree
Hammond's
Flycatcher
Pacific-slope
Flycatcher
Gray Jay
Steller's Jay
Common Raven
Mountain
Chickadee
Chestnut-backed
Chickadee
Common Bushtit
2.8
Insect
3.8
Insect
-9
-9
-9
-9
-9
Omnivore
Omnivore
Omnivore
Insects, conifer
seeds
Insects, seeds, fruit Foliage glean, bark glean
-9
Insects, seeds, fruit Foliage glean, bark glean
-9
Insects
Bark glean, hawks
-9
Insects
Bark glean
Resident Deciduous tree
BRCR
Red-breasted
Nuthatch
White-breasted
Nuthatch
Brown Creeper
Resident Deciduous tree,
shrub
Resident Conifer tree
3.23
Insects, nuts, seeds Bark glean, hawks
HOWR
House Wren
2.12
WIWR
Winter Wren
-9
Insects,
invertebrates
Insects
WEFL
GRJA
STJA
CORA
MOCH
CBCH
COBU
RBNU
WBNU
Conifer tree,
deciduous tree
Deciduous tree, cliff,
ground
Deciduous tree
Conifer
Cliff
Conifer tree, snag
Resident Snags, trees
Short
distant
Ground glean, foliage glean Long
distant
Ground glean, foliage glean Resident
Conifer tree,
deciduous tree
Deciduous tree,
snag
Snag
Table 1.2. (Continued)
SWTH
Calrank Diet
Bird Species
3.18 Insects, tree sap,
Golden-crowned
Kinglet
fruit
3.74 Insects, fruit
Townsend's
Solitaire
4.49 Insects, fruit
Swainson's Thrush
HETH
Hermit Thrush
1.42
Insects, fruit
AMRO
American Robin
4.03
Insects, fruit
VATH
Varied Thrush
-9
Insects, Fruit
SOVI
Cassin's Vireo
1.45
Insects
WAVI
Warbling Vireo
3.23
Insects, berries
OCWA
3.52
NAWA
Orange-crowned
Warbler
Nashville Warbler
2.65
Insects, fruit,
nectar, tree sap
Insects
YWAR
Yellow Warbler
3.52
Insects
BTYW
Black-throated Gray
Warbler
Hermit Warbler
2.65
Insects
3.63
Insects
Code
GCKI
TOSO
HEWA
Migration
Foraginq Technique
Foliage glean, hover glean, Resident
hawks
Short
Hawks, foliage glean,
distant
ground glean
Foliage glean, hawks, hover Long
glean
distant
Long
Ground glean, foliage
glean, hover glean
distant
Ground glean, foliage glean Short
distant
Ground glean, foliage glean Short
distant
Foliage glean, hawks, bark Long
glean
distant
Foliage glean, hover glean Long
distant
Foliage glean
Long
distant
Foliage glean, ground
Long
distant
glean, hover glean
Foliage glean, bark glean, Long
hawks, hover glean
distant
Foliage glean, hover glean, Long
distant
hawks
glean,
hover
glean,
Foliage
Long
hawks
distant
Nest Substrate
Conifer tree
Ground, snag
Shrub, conifer tree
Ground, tree
Deciduous tree,
conifer tree
Conifer tree
Conifer tree,
deciduous tree
Deciduous tree,
shrub
Ground
Ground
Shrub, tree
Conifer tree,
deciduous tree
Conifer tree
en
Table 1.2. (Continued)
Bird SDecies
Code
MGWA MacGillivray's
Warbler
WIWA
Wilson's Warbler
AUWA
3.75
Yellow-rumped
Warbler
Yellow-breasted
Chat
Western Tanager
2.34
Black-headed
Grosbeak
Lazuli Bunting
3.33
3.35
SPTO
CHSP
Green-tailed
Towhee
Spotted Towhee
Chipping Sparrow
FOSP
Fox Sparrow
2.14
SOSP
Song Sparrow
3.32
LISP
Lincoln's sparrow
3.62
YBCH
WETA
BHGR
LAZB
GTTO
Migration
Foraging Technique
Foliage glean, bark glean, Long
distant
ground glean
Foliage glean, hover glean, Long
Insects, Fruit
distant
hawks, bark glean
Foliage glean, hawks, hover Long
Insects, berries
distant
glean
Foliage glean
Long
Insects, Fruit
distant
Foliage glean, hawks
Long
Insect, fruit
distant
Long
Insects, seeds, fruit Foliage glean
distant
Ground glean, foliage glean Long
Insects, seeds
distant
Ground glean
Insects, seeds,
Long
berries
distant
glean
glean,
foliage
fruit
Ground
Insects, seeds,
Resident
Insects, seeds
Ground glean, foliage
Long
glean, hawks
distant
Gound glean
Insects, seeds,
Short
distant
berries
Ground glean, foliage glean Short
Insects, seeds
distant
Ground glean
Long
Insects, seeds
distant
Calrank Diet
3.54 Insects
3.47
3.39
3.40
3.98
5.02
Nest Substrate
Shrub, ground
Ground, vine, tangle
Conifer tree
Shrub
Conifer trees
Deciduous tree,
shrub
Shrub, tangle
Shrub, ground
Ground, shrub
Conifer tree,
deciduous trees
Ground, shrub
Ground, shrub
Ground
Table 1.2. (Continued)
Bird Species
Code
Dark-eyed Junco
DEJU
Calrank Diet
4.17
Seeds, insects
3.1
Insects, seeds
BUOR
Brown-headed
Cowbird
Bullock's Oriole
4.24
PUFI
Purple Finch
3.23
Insects, fruits,
Foliage
nectar
Seeds, insects, frui t Ground
CAFI
Cassin's Finch
3.12
PISI
Pine Siskin
LEGO
Lesser Goldfinch
BHCO
Migration Nest Substrate
Short
Ground, bank
distant
Resident Deciduous tree,
glean
shrub, ground
Long
Deciduous tre me
glean, hawks
distant
Conifer tree,
glean, foliage glean Short
distant
deciduous tref
Conifer tree
glean, foliage glean Short
distant
Conifer tree,
glean, ground glean Short
distant
deciduous tref
glean
Short
Deciduous treme,
distant
shrub, forb
ForaoingTechn iue
Ground glean, hawks
Ground
Ground
5.1
Seeds, Insects,
buds, berries
Seeds, insects
3.47
Seeds, insects
Foliage
Foliage
r
18
the tree layer. We visually estimated the cover of plant species within each sub-layer
using eight classes (0, < 1, 1-5, 5-25, 25-50, 50-75, 75-100%) and noted if permanent
standing or running water occurred within the 50 m. The vegetation sublayer, plant
species composition, and station elevation information included 171 environmental
variables recorded at each census station (Appendix B). I entered bird abundance and
environmental data into a database program (Borland International 1995) to calculate
means and develop categorical queries for presenting tabular information, and formatting
input data for statistical analysis programs.
Intensive Point Counts (61 Station Late-seral Dataset)
In 1998 I established 61 targeted census stations in late-seral mixed conifer
habitats. I used the Klamath National Forest's Land Management Plan Timber Type GIS
layer (USDA 1976), which provides information about tree size class and canopy cover,
to locate potential sites. I located sites that were large enough to contain an array of
census points located at least 100 meters from any road using GIS polygons queried to
identify forest stands between 730 and 1,450 m which contained trees that were greater
than 63 cm in diameter. The high and low elevation limits were established to avoid
forests dominated by true fir or hardwood tree species. Four census routes accessed by
off-road hiking routes or ATV accessible skid trails were established following a
modified version of Ralph (1998). Points placed at least 250 meters apart along transects
made up each route.
r
19
I collected bird census and environmental data using the same standardized pointcount protocol (Ralph et al. 1993) used for the 500 Station Dataset, however, I gathered
additional vegetation data (Appendix B). These include total cover values for each shrub
and tree sublayer and total cover values for the plant species at a station. The number of
trees within 5 DBH classes (2-14, 15-27, 28-63, 64-101, and >101 cm) was counted; I
estimated these counts using variable radius plots in order to estimate density without
counting every tree within 50 m. In densely stocked stands stems were counted within a
5 m radius and in the most open stands within a 20 m radius circular plot. I also
classified each station into standardized timber type categories (USDA 1976).
Analysis Methods
Cluster Analysis
In Chapter II of this thesis I conducted a cluster analysis of vegetation cover data using
TWINSPAN (Micro Computer Power 1987) to classify groups of census stations into
habitat types (Table 1.1) which I used to detect relationships between bird communities
and the environment (Jongman et al. 1987). I used a subset of the environmental data (48
variables), which included total cover values for the dominant trees and shrubs, along
with herbs, lichen and moss cover values for the cluster analysis. The cluster analysis
divided the dataset into groups representing habitat-types based on the dominant tree
species found on the stations. I associated each habitat-type with one of seven vegetation
subseries described Jimerson et al. (1996). The distribution of 57 bird species among the
seven habitat types was then examined.
20
Canonical Correspondence Analysis (CCA)
I conducted multivariate analysis of bird species abundance and environmental
variables using canonical correspondence analysis (CCA) in CANOCO (ter Braak 1991).
This ordination technique was designed to detect patterns of variation in a set of response
variables (bird species abundance) that can be explained by patterns of variation in a set
of predictor variables (habitat data). The resulting ordination diagrams express not only
the pattern of variation in species composition, but also the main relations between the
bird species and each environmental variable (Jongman et al. 1987). Biplots of
environmental variables and birds on ordination diagrams allow habitat correspondences
to be made.
CCA analysis selects the linear combination of environmental variables that
maximizes the dispersion of species scores. CCA chooses the best weights for the
environmental variables and represents them as the first CCA axis. Here lies the primary
advantage of canonical analyses in that we consider the combination of environmental
variables from the beginning. There are no restrictions to the number of variables (both
species or environmental) used (Palmer 1995).
CCA contrasts with indirect ordinations where theoretical environmental variables
are constructed to maximize species dispersion, which are then explained by comparing
this latent variable with combinations of environmental variables. The importance of the
species' associations with environmental variables is expressed by CCA axis eigenvalues,
which measure how much variation in the species data is explained by each axis and,
hence, by the environmental variables (Jongman et al. 1987). The sum of the first two
21
CCA axis eigenvalues divided by the sum of all eigenvalues results in the fraction of
variance accounted for by a CCA diagram (Jongman et al. 1987).
Following the standard CCA procedure (Jongman et al. 1987) 1 logl 0 -transformed
environmental variables prior to all CCA analyses. Ordination diagrams were drawn
using Delta-Graph (Delta Point 1996). In Chapter II the 171 environmental variables
from the 500 Station Dataset were split into 6 groups and run separately, due to size
limitations of my version of CANOCO. Fifty-seven environmental variables where
chosen for a final run based on the following criteria. When variables had high
autocorrelations, the ones that had greater X or Y-axis correlations, and the ones that had
a greater frequency of occurrences across each habitat type, were included.
Vectors connecting the origin of the X-Y coordinate system of the ordination
diagram with the mean spatial location of each environmental variable show the strength
and direction of each environmental variable's influence on bird abundance (Jongman et
al. 1987). The longer the vector the more the influence; the ordination of birds along
vegetation-related vectors estimate the influence of specific habitat characteristics on bird
abundance. Vegetation community-types and related bird assemblages were identified by
polygons hand-drawn around groups of related environmental and bird species variables
on the ordination diagrams. The correspondence of CCA-derived environmental variable
groups and bird assemblages in ordination space can be used to hypothesize habitat
relationships (Alexander and Menke 1997).
In all the analyses the first two CCA axes were used to identify bird-habitat
relationships. These explain the majority of the variation, and because the CCA uses all
22
species and environmental data at once, diagramming ordinations beyond two dimensions
is extremely complex. Each CCA axis represents a gradient that can be described by the
environmental variables that have the highest positive and negative correlation
coefficients with the axis. The CCA X and Y-axes are correlated with influential
environmental variables and bird species. By examining the birds and environmental
variables that are correlated with the same end of a CCA axis habitat relationships can be
inferred.
Correlation Analysis
Correlation analysis is a bivariate statistical technique for measuring the amount
of association between two variables. Pearson correlation assumes that the two variables
are measured on at least interval scales. Correlation analysis is also based on the
assumption that each of the two variables is normally distributed, although with larger
datasets (n >100), such as the one analyzed here, this becomes less important (Jongman et
al. 1987). The correlation coefficient represents the linear relationship between two
variables. If the correlation coefficient is squared, then the resulting value will represent
the proportion of common variation in the two variables. The significance level that is
calculated for each correlation determines the reliability of the correlation (Jongman et al.
1987).
In Chapter II autocorrelations were conducted on environmental variables to
identify redundant variables. In Chapters III and IV investigations of bird-habitat
relationships was done by examining bird and environmental variable correlations.
23
Pearson correlation matrixes were derived to investigate bird associations with habitat
types, as well as with environmental variables, using the Study Area subsets of the 500
Station Dataset. The objective of this was to identify statistically significant bird and
habitat associations that reoccur in several geographically based study areas. In an
additional analysis, correlation matrices were derived for bird and environmental
variables from the Late-seral Dataset to examine bird-habitat relationships in old growth
mixed-conifer habitats.
CHAPTER II: ANALYSIS OF BIRD-HABITAT RELATIONSHIPS
AT A LANDSCAPE LEVEL USING THE 500 STATION DATASET
Cluster Analysis of 500 Station Dataset
Habitat Types
Using a cluster analysis, I classified 500 bird-habitat survey stations from the
Klamath National Forest's five west-side ranger districts into one of seven habitat types,
which dominate the Klamath/Siskiyou Mountains. These habitat types include true fir
(TF), Douglas-fir/true fir (DF/TF), Douglas-fir/incense cedar (DF/IC), Douglas-fir/tanoak
(DF/TO), Douglas-fir/big-leaf maple (DF/BLM), Douglas-fir/mixed-oak (DF/OW) and
Douglas-fir/alder (DF/AL - Table 2.1).
When 48 plant species cover variables were entered into TWINSPAN, the
program processed eight splits resulting in 42 groups containing fewer than 25 stations
each. I analyzed the average cover of the dominant tree species on stations within each
group and labeled each group of stations with corresponding habitat types (Table 2.1).
True firs were the most common dominant species in the upper tree layer (T I) across the
TF and DF/TF habitat-types (Table 2.2). In the second tree layer (T2) tanoak and Pacific
madrone were the most common hardwoods in the DF/TO habitat-type, Big-leaf Maple,
deciduous oaks (Quercus garryanaand Q. kelloggii), and Pacific madrone in the
DF/BLM type, deciduous oaks in the DF/OW type, and alder and big-leaf maple in the
DF/AL type.
24
jjjjjp
- -
Table 2.1. Description of environmental characteristics across habitat types derived from cluster analysis of 500 Station Dataset.
(Habitat-type codes: TF=True Fir, DF/TF=Douglas-fir/True Fir, DF/IC=Douglas-fir/Incense Cedar, DF/TO=Douglas-fir/tanoak,
DF/BLM=Douglas-fir/Big-leafed Maple, DF/OW=Douglas-fir/Oak Woodland, DF/AL=Douglas-fir/Alder).
TF
DF/TF
DF/IC
DF/TO (n=80)
DF/BLM
DF/OW
DF/AL
(n=108
(n=44)
(n=72)
(n=108
(n=29)
(n=59)
Portion of dataset:
22%
9%
14%
16%
19%
22%
6%
Elevation:
1098-2153m
(mean: 1767m)
540-2086m
(1586m)
610-1830m
(1336m)
360-1543m
(821m)
341-1391m
(752m)
403-1641m
(993m)
403-1780m
(mean: 776m)
22%
57%
32%
29%
56%
19%
100%
Total tree cover:
-3-88%
(mean:45%)
3-88%
(34%)
15-88%
(52%)
0-88%
(58%)
15-88%
(64%)
15-88%
(54%)
3-88%
(55%)
Height of tree
layer:
6-55m
(mean:33m)
10-50m (30m)
6-60m
(37m)
0-60m
(41m)
3-68m
(34m)
6-60m
(30m)
10-50m
(24m)
Maximum tree
DBH:
25-163cm
(mean: 79cm)
38-190cm
(92cm)
25-175cm
(85cm)
0-200cm
(102cm)
35-155cm
(80cm)
23-138cm
(69cm)
25-86cm
(53cm)
Minimum tree
DBH:
5-38cm
(mean: 18cm)
8-88cm
(24cm)
3-30cm
(14cm)
0-78cm
(13cm)
3-28cm (11 cm)
3-20cm
(12cm)
5-20cm
(9cm)
Stations with
water:
111w
-.-
-___-__
Table 2.2. Constancy of plant species in vegetation sublayers across habitat types derived from cluster analysis of 500 Station
Dataset. (Constancy = Number of stations within a habitat typewhere a plant occurs . number of stations within that habitat; Habitattype codes: TF=True Fir, DF/TF=Douglas-fir/True Fir, DF/IC=Douglas-fir/Incense Cedar, DF/TO=Douglas-fir/tanoak,
DF/BLM=Douglas-fir/Big-leafed Maple, DF/OW=Douglas-fir/Oak Woodland, DF/AL=Douglas-fir/Alder).
ABIETI
PSMET 1
CADETI
PILATI
PINUTI
Tree layers
First layer (Ti1
True fir
Douglas fir
Incense cedar
Sugar pine
Ponderosa pine
ABIET2
PSMET2
CADET2
PILAT2
PINUT2
ACMAT2
LIDET2
ARMET2
QUEDT2
ALNUT2
Second layer (T2)
True Fir
Douglas Fir
Incense Cedar
Sugar Pine
Ponderosa Pine
Big-leaf Maple
Tanoak
Pacific madrone
Deciduous oak
Alder
TF
DF/TF
Constancy Constancy
DF/IC
DF/TO
DF/BLM
DF/OW
DF/AL
Constancy Constancy Constancy Constancy Constancy
97
15
15
12
6
86
77
34
30
18
50
88
46
49
58
5
99
6
28
20
1
99
23
22
38
12
90
22
31
86
10
72
24
14
48
78
13
68
71
41
18
32
61
90
67
17
74
0
21
0
0
2
2
I
6
15
14
4
73
4
4
21
40
69
56
21
14
1
82
22
6
31
73
18
56
58
46
14
80
22
8
59
24
3
34
56
12
3
52
24
7
21
66
0
28
52
90
19
3
8
0
1
0
5
0
o0i
-I
27
Six of these habitat-types, excluding TF, correspond to subseries described in
Jimmerson et al. (1996): DF/TF habitat-type with Douglas-fir-red fir Subseries, FF/IC
with Douglas-fir-incense cedar Subseries, DF/TO with Douglas-fir-tanoak Subseries,
DF/BLM with Douglas-fir-Maple Subseries, DF/OW with Douglas-fir-Black Oak and
Douglas-fir-white oak Subseries, and DV/AL with the Douglas-fir-red alder Subseries.
I examined the distribution of stations across habitat types, the distribution of
habitat types across the landscape and general characteristics of the habitat-types to better
understand their various attributes. The majority of the stations were classified as
Douglas-fir/big-leaf maple in contrast to the Douglas-fir/alder stations of which there
were less than 30 (Table 2.1). Over half of the stations were classified into high elevation
types (True fir, Douglas-fir/true fir and Douglas-fir/incense cedar), the others classified
as hardwood habitat types (Table 2.1).
The True Fir (TF), Douglas-fir/true fir (DF/TF), and Douglas-fir/incense cedar
(DF/IC) habitat-types are concentrated at higher elevations (mean elevation > 1,300 m)
and the Douglas-fir/tanoak (DF/TO), Douglas-fir/big-leafed Maple (DF/BLM), and
Douglas-fir/oak woodland (DF/OW) types typically occur at lower elevations (mean
elevation < 1,000 m - Table 2.1). The DF/TF and Douglas-fir/alder (DF/AL) covered the
greatest range of elevations (1,546 and 1,377 m elevation range respectively) and the TF,
DF/IC, DF/TO, DF/BLM, and DF/OW covered a range of elevations less than 1,250 m.
The 29 riparian stations (DF/AL) stations had water present, greater than 50% of
the Douglas-fir/true fir (DF/TF) and Douglas-fir/big-leafed maple (DF/BLM) stations had
28
water, fewer of the True fir (TF), Douglas-fir/incense cedar (DF/IC) and Douglasfir/tanoak (DF/TO) had water, and only 19 % of the Douglas-fir/oak woodland (DF/OW)
had water within the plot (Table 2.1). All of the habitat-types had a wide range of total
canopy cover, the canopy cover on DF/BLM stations averaging the highest (64% mean).
All habitat-types were made up of stations with a wide range of maximum canopy
heights, maximum and minimum DBH values, and total shrub covers. The DF/TO type
had the highest mean canopy height (41 m), the greatest mean DBH (102 cm) and the
greatest mean shrub cover (50%). The DF/TF type had the highest minimum DBH (24
cm), followed by the TF type (18 cm) in contrast with the DF/AL type (9 cm - Table
2.1).
TF and DF/TF habitat-types represent varying habitats within high elevation
conifer ecosystems of the Klamath Mountains, DT/TO and DF/OW represent habitats
within mixed-conifer/hardwood ecosystems, and DF/AL represents habitats within
riparian ecosystems. DF/IC represents the transition between high elevation conifer and
mixed-conifer/hardwood ecosystems, and DF/BLM the transition between mixedconifer/hardwood and riparian ecosystems of the Klamath Mountains.
Birds and Habitat-types
Overall numbers of individual birds and number of bird species detected on
stations within different habitat types differed. Average number of individual birds per
station and average number of species per station were highest on Douglas-fir/incense
cedar (DF/IC) and Douglas-fir/oak woodland (DF/OW) stations (Table 2.3). Average
Emery
-
Table 2.3. Average number of individuals and species per station, and constancy and percent of total individual bird species detected
within 7 vegetation series from the 500 Station Dataset. (Constancy = number of stations where species occurred total number of
stations)
Indivs.:
Species:
Selasphorus Spp.
Acorn Woodpecker
Red-breasted Sapsucker
Downy Woodpecker
Hairy Woodpecker
Northern Flicker
Pileated Woodpecker
Olive-sided Flycatcher
Western Wood-pewee
Hammond's Flycatcher
Dusky Flycatcher
Pacific-slope Flycatcher
Steller's Jay
Common Raven
Mountain Chickadee
TF
(n=108)
8.7
6.4
Con.
5.6
1.9
0.9
0.0
3.7
14.8
0.9
15.7
4.6
1.9
47.2
0.0
27.8
3.7
21.3
DF/TF
(n=44)
8
5.8
%
44.4
28.6
14.3
0.0
23.8
27.9
3.5
32.7
8.1
16.7
55.2
0.0
13.5
13.8
33.3
Con.
0.0
0.0
2.3
2.3
2.3
9.1
9.1
11.4
15.9
4.6
22.7
0.0
25.0
0.0
25.0
DF/IC
(n=72)
9.6
6.9
%
0.0
0.0
28.6
25.0
4.8
6.6
17.2
11.5
14.9
16.7
7.6
0.0
7.7
0.0
23.3
Con.
1.4
0.0
1.4
0.0
6.9
12.5
6.9
15.3
13.9
4.2
27.8
1.4
31.9
1.4
19.4
DF/TO
(n=80)
8.6
6.5
%
5.6
0.0
14.3
0.0
23.8
16.4
17.2
21.2
17.6
33.3
17.2
1.4
13.9
3.5
18.9
Con.
6.3
5.0
0.0
0.0
2.5
16.3
6.3
17.5
5.0
2.5
11.3
31.3
57.5
10.0
6.3
DF/BLM
(n=108)
7.1
5.6
%
27.8
57.1
0.0
0.0
9.5
21.3
17.2
32.7
6.8
16.7
8.3
40.0
27.7
31.0
8.9
Con.
1.9
0.0
2.8
4.6
2.8
7.4
9.3
0.0
11.1
0.0
2.8
26.9
43.5
5.6
1.9
DF/OW
(n=59)
10.2
7.4
%
11.1
0.0
42.9
62.5
14.3
16.4
34.5
0.0
17.6
0.0
2.1
50.0
23.5
27.6
2.2
Con.
3.4
1.7
0.0
0.0
8.5
10.2
5.1
1.7
22.0
3.4
15.3
8.5
33.9
3.4
17.0
DF/AL
(n=29)
7.3
4.9
%
11.1
14.3
0.0
0.0
23.8
11.5
10.3
1.9
29.7
16.7
9.0
7.1
11.5
6.9
13.3
Con.
0.0
0.0
0.0
3.5
0.0
0.0
0.0
0.0
10.3
0.0
3.5
3.5
20.7
13.8
0.0
%
0.0
0.0
0.0
12.5
0.0
0.0
0.0
0.0
5.4
0.0
0.7
1.4
2.3
17.2
0.0
Table 2.3. (Continued)
Chestnut-backed Chickadee
Common Bushtit
Red-breasted Nuthatch
Brown Creeper
House Wren
Winter Wren
Golden-crowned Kinglet
Townsend's Solitaire
Swainson's Thrush
Hermit Thrush
American Robin
Warbling Vireo
Cassin's Vireo
White-breasted Nuthatch
Orange-crowned Warbler
Nashville Warbler
Yellow Warbler
Black-Throated Gray
Warbler
Hermit Warbler
MacGillivray's Warbler
Wilson's Warbler
Yellow-rumped Warbler
TF
0.9
2.8
48.2
3.7
5.6
0.0
34.3
3.7
3.7
28.7
21.3
6.5
3.7
0.9
3.7
25.0
0.0
11.1
4.2
11.8
35.7
6.7
17.1
0.0
44.2
18.2
36.4
30.8
31.5
12.7
2.8
20.0
30.8
15.2
0.0
6.0
DF/TF
0.0
0.0
20.5
9.1
6.8
2.3
25.0
9.1
2.3
20.5
15.9
31.8
11.4
0.0
4.6
50.0
0.0
20.5
0.0
0.0
5.5
8.3
11.4
6.3
13.5
27.3
9.1
8.3
9.8
26.8
3.5
0.0
15.4
10.8
0.0
4.3
DF/IC
4.2
5.6
44.4
16.7
2.8
1.4
20.8
12.5
0.0
29.2
12.5
6.9
27.8
1.4
0.0
52.8
2.8
25.0
16.7
19.6
22.0
30.0
5.7
6.3
18.3
40.9
0.0
20.8
9.8
9.9
15.4
20.0
0.0
23.8
11.1
10.2
DF/TO
2.5
8.8
28.8
11.3
3.8
2.5
3.8
2.5
6.3
28.8
3.8
1.3
20.0
1.3
1.3
47.5
0.0
32.5
27.8
13.9
9.3
58.3
21.8
10.6
28.9
43.2
27.3
4.6
2.3
36.4
8.3
1.4
2.2
9.2
44.4
18.1
5.6
44.4
26.4
12.0
8.9
21.0
27.5
33.8
11.3
21.3
12.5
25.5
14.8
18.3
8.6
18.8
3.9
9.1
45.5
22.5
3.3
1.4
13.3
20.0
7.7
20.1
0.0
18.7
DF/BLM
4.6
1.9
14.8
10.2
3.7
10.2
8.3
0.0
0.9
5.6
17.6
14.8
39.8
0.9
1.9
25.0
1.9
62.0
19.2
29.6
26.7
8.7
10.2
26.9
6.5
12.0
37.5
21.6
8.8
21.7
17.1
68.8
9.6
0.0
9.1
5.0
22.8
22.5
38.5
20.0
15.4
13.8
16.7
37.0
DF/OW
6.8
8.5
35.6
13.6
11.9
0.0
11.9
1.7
0.0
20.3
8.5
10.2
40.7
1.7
3.4
49.2
8.5
42.4
25.0
17.7
13.2
15.0
28.6
0.0
8.7
4.6
0.0
12.5
10.9
8.5
18.9
20.0
15.4
13.8
33.3
19.2
6.7
23.2
20.0
7.9
30.5
25.4
6.8
23.7
17.6
16.9
11.1
9.2
DFMAL
3.5
4.2
3.5
3.9
0.0
0.0
0.0
0.0
10.3
11.4
0.0
0.0
6.9
1.9
0.0
0.0
0.0
0.0
0.0
0.0
24.1
12.0
24.1
18.3
34.5
7.7
0.0
0.0
6.9
15.4
17.2
2.6
17.2 38.9
27.6
4.7
0.0
27.6
3.5
6.9
0.0
6.3
2.2
0.9
0
-
-
-
Table 2.3. (Continued)
Yellow-breasted Chat
Western Tanager
Brown-headed Cowbird
Lazuli Bunting
Green-tailed Towhee
Spotted Towhee
Chipping Sparrow
Fox Sparrow
Song Sparrow
Lincoln's Sparrow
Dark-Eyed Junco
Black-headed Grosbeak
Bullock's Oriole
Purple Finch
Cassin's Finch
Pine Siskin
Lesser Goldfinch
TF
0.0
9.3
6.5
13.9
8.3
1.9
15.7
21.3
0.0
11.1
50.9
0.0
0.0
2.8
6.5
11.1
0.0
0.0
5.5
3.1
36.4
58.8
2.0
45.8
73.2
0.0
88.2
33.1
0.0
0.0
12.0
34.6
41.5
0.0
DF/BLM
DF/TO
DF/OW
DF/TF
DF/IC
0.0
0.0
2.8
12.5
8.5
0.0.
2.3
4.2
0.0
13.9
38.9
28.4
52.5
15.9
4.0
38.9 17.9 27.5
57.4
37.6
42.4
6.6
50.0 23.0
4.6
1.3
15.3
10.9
17.0
3.6
0.0
0.0
4.6
9.1
9.1
2.8
0.0
23.5
2.5
11.8
0.0
0.0
2.3
5.9
5.6
23.2
31.0
33.9
6.0
23.8 22.0
4.6
3.0
8.3
6.8
7.4
15.3
13.6
5.1
3.8
11.4
10.2 4.2
1.7
9.8
6.3
14.6
0.0
0.0
0.0
0.0
5.6
0.0
0.0
0.0
0.9
12.5
0.0
4.6
25.0
0.0
0.0
0.0
0.0
0.0
5.9
0.0
2.3
5.9
1.4
10.3
19.4
9.3
33.9
68.2 16.4 43.1 18.9 27.5
0.0
0.0
0.0
1.9
33.3
5.1
0.0
0.0
0.0
0.0
0.0
0.0
0.9
8.3
10.2
0.0
0.0
0.0
20.0
8.8
32.0
1.9
8.0
5.1
6.8
16.0
6.9
38.5
0.0
0.0
0.0
0.0
1.7
13.6 23.1
9.7
3.8
2.5
0.9
1.7
0.0
6.8
3.4
13.9 33.9
0.0
0.0
0.0
0.0
0.0
6.8
0.0
0.0
0.0
29.2
20.9
17.3
29.1
0.0
27.0
17.0
2.4
0.0
0.0
10.0
66.7
58.3
12.0
3.9
0.0
71.4
DF/AL
24.1
51.7
58.6
13.8
0.0
27.6
0.0
0.0
10.3
0.0
13.8
0.0
6.9
0.0
0.0
3.5
3.5
54.2
9.5
11.1
10.9
0.0
9.0
0.0
0.0
62.5
0.0
2.1
0.0
33.3
0.0
0.0
17.0
28.6
_____-4
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32
individuals per station was lowest on Douglas-fir/big-leafed maple (DF/BLM), and
average number of species per station was lowest on Douglas-fir/alder (DF/AL) stations
(Table 2.3).
Bird species were not distributed evenly across habitat types and several species
were more abundant in or primarily occurred in specific habitat types or related habitat
types. The following species were associated with high elevation habitat types. The
majority of the Lincoln's Sparrow, Fox Sparrow, Dusky Flycatcher, Green-tailed
Towhee, Chipping Sparrow and SelasphorusHummingbird spp. detections were in the
True fir (TF) habitat-type (Table 2.3); this habitat made up 22% of stations in the dataset.
Dark-eyed Juncos were common on TF and Douglas-fir/true fir (DF/TF) stations.
Yellow-rumped Warblers were common on the TF and the majority of their total
detections occurred on TF, DF/TF, and Douglas-fir/incense cedar (DF/IC) stations, which
comprise 45% of the dataset. The majority of the Pine Siskin, Golden-crowned Kinglet,
and Mountain Chickadee detections were on TF, DF/TF and DF/IC stations (45% of the
dataset, Table 2.3). Red-breasted Nuthatches and Hermit Warblers had the majority of
their detections on TF and DF/IC stations which comprise 36% of the dataset and
Nashville Warblers were common on DF/TF and DF/IC stations (Table 2.3).
In contrast with high elevation habitat associates, several bird species were
associated with hardwood habitats. The majority of Swainson's Thrush, Acorn
Woodpecker, and Blue Grouse detections were on Douglas-fir/tanoak (DF/TO) stations
which comprise 16% of the dataset (Table 2.3). DF/TO and Douglas-fir/big-leafed maple
(DF/BLM) stations (38% of the dataset) had the majority of Steller's Jay and Pacific-
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33
slope Flycatcher detections. The majority of Brown-headed Cowbird detections were on
DF/TO and DF/BLM stations where they were also common. Winter Wren, Downy
Woodpecker, and Red-breasted Sapsucker had the majority of their detections on
DF/BLM stations, which comprise 22% of the dataset (Table 2.3).
The majority of Bullock's Oriole, Lesser Goldfinch, Mourning Dove, and Blackheaded Grosbeak detections were on Douglas-fir/oak woodland (DF/OW) stations, which
comprise 19% of the data set. Nashville Warblers and Western Tanagers were common
on DF/OW stations (Table 2.3). Brown-headed Cowbirds and Western Tanagers were
common on Douglas-fir/alder (DFIAL) stations. Finally, the majority of Yellow-breasted
Chats, Yellow Warblers, and Song Sparrows occurred on DF/AL stations, which
comprise 6 % of the dataset (Table 2.3).
Canonical Correspondence Analysis (CCA) of 500 Station Dataset
Environmental Variables
The Canonical Correspondence Analysis eigenvalues showed that 71% of the
variance of bird and environmental variable distribution was described by the CCA
ordination, 42% by the first axis, and 28% by the second (Table 2.4). The CCA showed
the mean spatial location of 13 out of the 57 environmental variables to be farthest from
the origin of the axis, and therefore most influenced the ordination (Table 2.4).
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34
Table 2.4. CCA X and Y axis eigenvalues and variance explained by first two CCA axes
in the analysis of the 500 Station dataset; environmental variables which had the furthest
distance between their mean spatial location and the origin of the CCA with X and Y
axis scores.
X-axis
Y-axis
Eigenvalue
0.1430
0.0950
Variance Explained
42%
28%
Code
ELEV
TRECOV
TREUPR
ABIET1
ABIET2
ABIES1
PSMET1
PSMET2
SALIS1
ALNUT1
ACMAT2
ARMET2
QUCHT2
Variable
X-axis Score Y-axis Score
Elevation
-0.8326
0.3191
Total tree cover
0.2595
-0.4456
Canopy height
-0.1147
-0.5034
Cover of true fir in first tree
-0.6306
0.2779
layer
Cover of true fir in second tree
-0.5063
0.1792
layer
Cover of true fir in first shrub
-0.5672
0.3437
layer
Cover of Douglas-fir in first
0.2852
-0.5401
tree layer
Cover of Douglas-fir in second
0.2064
-0.4960
tree layer
Cover of willow. in first shrub
0.1175
0.5064
layer
Cover of alder spp. in first
0.3486
0.3526
tree layer
Cover of big-leaf maple in
0.4620
-0.3348
second tree layer
Cover of Pacific madrone in
0.3506
-0.4195
second tree layer
Cover of live Oak in second
0.4055
-0.3233
tree layer
I subjectively choose the top 13 variables (as opposed to top ten or top 15
variables) as a cut off because these describe the majority of the environmental variability
across the landscape, which the inclusion of additional variables would not increase.
Vectors connecting these variables to the axis origins illustrate the magnitude and
direction of their influences on bird distribution (Figure 2.1). Elevation and true fir in TI,
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35
T2, and S2 show their influence on bird distribution by pulling the ordinated location of
associated birds towards in the upper-left quadrant of the ordination space. Alder in TI
and willows in SI pull associated birds towards the upper-right quadrant. Douglas-fir in
T 1, big-leaf maple, Pacific madrone, live oak and Douglas-fir in T2, and canopy height
influence the ordination by pulling the centroid of associated birds towards the bottom
right quadrant of the ordination space (Figure 2.1).
Figure 2.1.Vectors representing the influence of 13 environmental variables defined by
the CCA ordination of 57 environmental variables from the 500 station bird point-count
dataset. The longer the vector the greater the influence.
I
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36
Bird Assemblages and Vegetation Community-types
CCA ordination of bird species variables and environmental variables on the X
and Y axes formed groups (see hand-drawn polygons in Figure 2.2, and Tables 2.4 and
2.5), which identify bird assemblages and three vegetation community-types.
Environmental variables that were located closer to the origin of the CCA axis were
included in the polygon that contained associated forest characteristics. For example,
cover of sugar pine was contained in the polygon with high elevation tree species and
cover of horsetail (Equisetum spp.) was grouped with the riparian species. The proximity
of bird assemblages to community-types indicates bird-habitat associations, although
spatial spread of bird variables is broader in the ordination diagram (Figure 2.2).
I drew polygons around the three main clusters of environmental variables as
plotted in the CCA ordination (Figure 2.2). Environmental variables which were located
toward the outskirts of the clusters were included with the clusters which contained the
most related variables. I labeled each polygon by examining most influential
environmental variables (Table 2.5) based on their distance from the origin of the CCA
axis, which are contained in each respective polygon (high elevation conifer, riparian,
and mixed-conifer hardwood; Figure 2.2). I also drew polygons around three bird species
groups formed by the CCA ordination. As with the environmental variables, bird
species' centroids that were located toward the outskirts of the clusters were included
with the clusters that contained related bird species. These three groups of bird species
were labeled with the name of the overlapping vegetation community-type polygon
(Figure 2.2).
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37
3.
2 5-
2-
tRIponan
15.
H4ghElwAuon Coeet
1
bA
0 5-
VI<\\M\\'I%
-1
. J o
_i 5
-I
-0 5
a
0.5
lle~~~Mod-ontlr/Hardwood
1
I 5
2
2.5
Figure 2.2. CCA ordination of 57 bird species classified into 3 bird assemblages (clear
polygons) from the 500 Station Dataset. Assemblages were associated with 3 vegetation
community types (shaded polygons) based on their proximity to and overlap with the
vegetation community polygons. See Table 2.5 for bird species and Table 2.6 for
environmental variable grouped into respective polygons.
The high elevation conifer assemblage had 20 bird species, the riparian had 16,
I
and the mixed-conifer hardwood had 21 (Table 2.6 and Table 2.7). Each bird assemblage
I
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I
included species with a variety of California risk rankings, migratory statuses, FEMAT
bird statuses, diets, foraging techniques and nesting characteristics (Tables 2.1, 2.6, and
I
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2.7). The high elevation assemblage contained the highest percentage of species of
concern in California (Calrank > 3.50 - Table 2.7). Long distant migrants make up
-
Table 2.5. Environmental variables contained within vegetation community polygons, based on ordination of 57 environmental
variables from 500 Station Dataset.
Mixed-conifer/Hardwood
High Elevation Conifer
Riparian
Douglas fir in 1" tree layer
True fir in 1st tree layer
Willow in 1st shrub layer
Douglas fir in 2nd tree layer
True fir in 1st shrub layer
Alder in 1st tree layer
Big-leafed maple in 2nd tree layer Alder in 2nd tree layer
True fir in 2nd tree layer
Pacific madrone in 2nd tree layer
Manzanita in 2nd shrub layer
Hardwood spp. in 2nd tree layer
Live oak in 2nd tree layer
Groundcover
Forb
Deciduous oak in 2nd tree layer
Poison oak in 2nd shrub layer
Fern in 2nd shrub layer
Incense cedar in 1st shrub layer tanoak in 2nd tree layer
Grass
tanoak in 1st shrub layer
Currant in 2nd shrub layer
Willow in 2nd tree layer
Douglas fir in 1" shrub layer
Buckthorn in 2nd shrub layer
Herb cover
Sugar pine in 2nd tree layer
Moss
Willow in 2nd shrub layer
Incense cedar in 2nd tree layer
Big-leafed maple in 1st shrub layer Rubus spp. in 1st shrub layer
Pacific madrone in 1st shrub layer
Sugar pine in 1st shrub layer
Live oak in 1st shrub layer
Alder in 1st shrub layer
Deciduous oak in I st shrub layer
Alder in 2nd shrub layer
Ceanothus in 2 nd shrub layer
Poplar in 1st tree layer
Lichen
ponderosa pine in 1st tree layer
Western hazel in 2nd shrub layer
Horsetail in 2nd shrub layer
Currant in 2nd shrub layer
Wood rose in 2nd shrub layer
Pacific dogwood in 2nd shrub layer
x
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39
Table 2.6. Three bird assemblages derived from CCA polygons in analysis of 500
Station Dataset.
Mixed-conifer Hardwood
Riparian
High Elevation Conifer
Bird Species
Bird Species
Bird Species
Winter Wren
Bullock's Oriole
Pine Siskin
Pacific-slope Flycatcher
Mourning Dove
Lincoln's Sparrow
Black-headed Grosbeak
American
Robin
Green-tailed Towhee
Chestnut-backed
Yellow Warbler
Fox Sparrow
Chickadee
Spotted Towhee
Dusky Flycatcher
Yellow-breasted Chat
Common Raven
Cassin's Finch
Song Sparrow
Cassin's Vireo
Townsend's Solitaire
Lesser Goldfinch
Black-throated Gray
Brown-headed Cowbird
Golden-crowned
Warbler
Kinglet
Western Tanager
House Wren
Mountain Chickadee
MacGillivray's Warbler
Mountain Quail
Blue Grouse
White-breasted Nuthatch
Lazuli Bunting
Red-breasted Nuthatch
Common Bushtit
Orange-crowned Warbler
Hermit Thrush
Purple finch
Yellow-rumped Warbler
Hairy Woodpecker
Western
Wood-pewee
Steller's Jay
Olive-sided Flycatcher
Brown Creeper
Chipping Sparrow
Warbling Vireo
Northern Flicker
Dark-eyed Junco
Downy Woodpecker
Pileated Woodpecker
Hermit Warbler
Nashville Warbler
Hammond's Flycatcher
Swainson's Thrush
Red-breasted Sapsucker
Wilson's Warbler
Selasphorus spp.
Acorn Woodpecker
majorities in all three assemblages (Table 2.7). The riparian assemblage had the fewest
FEMAT Birds. The majorities in all assemblages were insectivores, but the high
elevation assemblage had a higher proportion of seed eaters (Table 2.7). The majority of
high elevation species were ground gleaners in comparison with the riparian and mixed
conifer species which were primarily foliage gleaners.
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40
Table 2.7. Percent of bird species within each assemblage which are: classified as at risk
(Calrank > 3.5 - Manley and Davidson 1993 ), within three migration categories,
considered old growth associates (FEMAT birds - USDA and USDI 1994), and members
of feeding and nesting guilds (Ehrlich et al. 1988).
High Elevation Conifer
(n=20)
45.0%
Riparian (n= 16)
Migratory Status
Long distant
Short distant
Resident
50.0%
30.0%
20.0%
50.0%
25.0%
25.0%
42.9%
14.3%
42.9%
FEMAT birds
25.0%
12.5%
33.3%
Prey
Insect
Seed
Nectar
Omnivore
75.0%
20.0%
5.0%
0.0%
81.3%
12.5%
0.0%
6.3%
81.0%
4.8%
0.0%
14.3%
Feeding behavior
Foliage glean
Ground glean
Hawk
Bark glean
25.0%
40.0%
20.0%
10.0%
43.8%
37.5%
6.3%
12.5%
47.6%
28.6%
4.8%
19.0%
Nesting substrate
Snag
Ground
Conifer tree
Deciduous tree
Shrub
0.0%
30.0%
50.0%
10.0%
10.0%
6.3%
12.5%
12.5%
12.5%
18.8%
19.0%
9.5%
23.8%
19.0%
9.5%
Calrank > 3.5
25.0%
Mixed-conifer
Hardwood (n=2 1)
14.3%
41
Bird species that use a variety of substrates as primary nest locations made up
each bird assemblage (Table 2.6 and Table 2.7). The mixed-conifer/hardwood
assemblage had the highest proportion of snag and deciduous tree nesters in contrast to
the high elevation assemblage, which had higher percentages of ground and conifer
nesters (Table 2.7). The riparian assemblage had the highest percentage of shrub nesters
(Table 2.7).
Analysis of CCA Axes
The first canonical axis (X-axis), which is the first habitat gradient derived by the
CCA analysis, was most strongly associated at the negative end with elevation and true
firs (Table 2.4) representing high elevation associated birds such as Pine Siskin, Lincoln's
Sparrow and Fox Sparrow (Table 2.8). The positive end of the X-axis was associated
with alders, deciduous oaks and Big-leaf Maples in TI (Table 2.4) representing birds
found in lower elevation hardwood forests (Table 2.8).
The Y-axis is the second habitat gradient derived by the CCA and represents
forest structure. The negative end of the Y-axis was associated with older mixed-conifer
hardwood forests represented by tall canopies, trees with larger DBHs, high tree cover,
Douglas-firs in TI and T2, and Pacific madrone and tanoak in T2 (Table 2.4). Birds
associated with this end of the Y-axis include Chestnut-backed Chickadee, Pacific-slope
Flycatcher and Winter Wren (Table 2.8). The positive end of the Y-axis was associated
with riparian habitat represented by willows in SI (Table 2.4). These habitats
A
Table 2.8. CCA X and Y axis scores for bird species from the 500 Stations Dataset. See Table 2.1 for bird species codes.
Negative Y-axis
Bird Species X-axis Score
PISI
-1.1070
LISP
-0.9316
FOSP
-0.8768
DUFL
-0.8179
GTTO
-0.8041
CAFI
-0.7087
TOSO
-0.6513
GCKI
-0.6090
MOQU
-0.5850
MOCH
-0.5829
HETH
-0.5587
RBNU
-0.5322
AUWA
-0.5084
OSFL
-0.4836
DEJU
-0.4426
HEWA
-0.4192
HAFL
-0.3975
CHSP
-0.3884
Positive X-axis
Bird Species
X-axis Score
BUOR
2.7329
MODO
2.6483
YBCH
2.6296
SOSP
2.5764
YWAR
2.5500
DOWO
1.7932
LEGO
1.5387
BHCO
1.1391
WIWR
0.7813
BHGR
0.7657
HIOWR
0.7504
SPTO
0.7077
WEFL
0.6542
0.6109
BLGR
CORA
0.5809
SOVI
0.5565
WETA
0.5564
BTYW
0.4375
Negative Y-axis
Bird Species
Y-axis Score
CBCH
-0.8587
WEFL
-0.8180
WIWR
-0.7398
WBNU
-0.4987
BTYW
-0.4918
COBU
-0.4330
STJA
-0.4089
MGWA
-0.3967
BRCR
-0.3928
CORA
-0.3810
BHGR
-0.3400
PIWO
-0.3148
SOVI
-0.2967
NOFL
-0.2679
PUFI
-0.2388
-0.2225
NAWA
WETA
-0.2031
SWTH
-0.1526
Positive Y-axis
Bird Species Y-axis Score
BUOR
3.0791
MODO
2.6539
YWAR
2.4454
YBCH
2.2237
SOSP
1.9699
LEGO
1.1959
1.1595
LISP
PISI
1.0444
0.8977
LAZB
GTTO
0.8890
0.8743
BLGR
0.8677
HOWR
0.7863
OCWA
0.6919
DOWO
AMRO
0.6787
0.5182
FOSP
CAFI
0.4693
0.3909
DUFL
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43
have low canopies, small DBHs and are dominated by a well-developed shrub layer.
Birds ordinated toward the positive end of the Y-axis, including Bullock's Oriole,
Mourning Dove, Yellow Warbler, Yellow-breasted Chat, Song Sparrow (Table 2.8) are
related to willow shrubs.
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CHAPTER III: ANALYSIS OF BIRD-HABITAT RELATIONSHIPS
AT A WATERSHED LEVEL
USING TEN STUDY AREAS FROM THE 500 STATION DATASET
Study Areas
To further investigate bird-habitat relationships in the Klamath Mountains I
divided the 500 Station Dataset into ten study areas based on Forest Service watershed
analysis boundaries (Table 3.1). The number of stations within each study area ranged
from 25 to 114 stations (Table 3.1). Elevations within each area ranged from 725 meters
to 1,703 meters.
Stations in the Lower Beaver Creek study area had the lowest mean maximum
DBH (58 cm) and stations in the Callahan study area had the highest (116 cm). The
Douglas-fir/big-leafed maple (DF/BLM) vegetation series was the primary habitat type in
six of the ten study areas. True fir (TF) or Douglas-fir/true fir (DF/TF) were the primary
habitat types in four study areas, and Douglas-fir/incense cedar (DF/IC) and Douglasfir/Oak Woodlands (DF/OW) in three of the ten study areas (Table 3.1). The TF habitat
type was among the primary types in the two study areas with mean elevations above
1600 m and the DF/BLM type was among the primary types in the three areas with mean
elevations below 1,000 m. The Douglas-fir/Alder (DF/AL) habitat type was the least
prevalent and only occurred as a primary type in the East Scott River area (Table 3. 1).
44
Table 3.1. 500 Station Dataset study areas, number of stations within each study area, top 3 detected birds on stations in each study
area (See Table 2.1 for bird species codes), average number of FEMAT birds (USDA et al. 1993) per station in each area, primary
habitats types occurring on stations (TF= True fir, DF/TF= Douglas-fir/true fir, DF/IC= Douglas-fir/Incense Cedar, DF/BLM=
Douglas-fir Big-leafed Maple, DF/TO= Douglas-fir/tanoak, and DF/OW= Douglas-fir/oak woodland), average elevation of stations
within each area, average maximum DBH, canopy height, number of tree sublayers, minimum DBH on stations within each area.
Average
Average Average
Average
# of
Average
Maximum Canopy # of Tree Minimum
Primary
FEMAT
Top 3
# of
Study
Elevation (mi DBH (cm) Height (m) Sublayers DBH (cm)
Habitats
Abundant Birds
Birds
Stations
Areas
Upper
Beaver
Lower
Beaver
E. Scott
74
AUWA, PISI, DEJU
2.08
TF, DF/IC
1691
70.54
33.34
1.89
15.86
49
0.61
58.08
25.14
2.18
9.20
893
58.13
19.38
2.06
10.10
28
1231
94.39
39.29
2.14
13.29
S. Seiad
25
2.12
DF/BLM,
DF/OW
DF/AL,
DF/BLM
DF/IC,
DF/BLM
DF/OW, DF/IC
725
W. Scott
1255
90.04
41.40
1.64
18.68
N. Seiad
25
2.08
DF/BLM, TF
1143
75.20
29.00
2.48
12.68
Happy
Camp
Orleans
114
1.83
DF/TO, TF
1009
85.65
41.14
1.94
14.90
1.56
115.76
43.05
2.11
12.53
27
1035
87.33
34.44
2.00
16.04
Callahan
55
DF/TO,
DF/BLM
DF/BLM,
DF/OW
DF/TF, TF
911
Cecilville
BTYW, BHGR,
WETA
BHGR, WETA,
WEWP
BTYW, AUWA,
NAWA
HEWA, DEJU,
AUWA
DUFL, BTYW,
RBNU
BTYW, MGWA,
NAWA
NAWA, STJA,
BTYW
STJA, BHGR,
BTYW
DEJU, AUWA,
NAWA
1705
91.25
29.97
2.04
21.38
48
55
0.69
2.07
1.04
1.96
40l
-I
'I
46
I examined the relationship of bird species abundance and diversity with
environmental variables within the study areas, allowing me to determine if the birdhabitat relationships identified at a larger landscape level are consistent when examined
at a more restricted watershed scale. To begin looking at bird and habitat relationships at
the watershed scale I associated most common birds in each study area with the general
characteristics of the area (Table 3.1).
Black-throated Gray Warblers and Black-headed Grosbeaks were strongly
associated with Douglas-fir/big-leafed maple habitats (DF/BLM) and were among the
three most abundant birds in study areas where this habitat type was abundant (Table
3.1). Nashville Warblers were frequently detected in study areas where the hardwood
associated habitat types, DF/BLM or Douglas-fir/tanoak (DF/TO), were abundant.
Yellow-rumped Warblers were frequently detected in study areas where high elevation
habitat types were abundant (Table 3. 1). These types include true fir (TF), Douglasfir/true fir (DF/TF), and Douglas-fir/incense cedar (DE/IC). Dark-eyed Juncos were
among the abundant birds in the four study areas thathad the highest elevations (Table
3.1)
The average number of FEMAT birds detected on point count stations within each
study area ranged from 0.7 to 2.1 (Table 3.1). The five study areas with the highest
average number of FEMAT birds per station were the areas with the highest mean
elevations. The two study areas with the lowest mean maximum DBHs at their stations
also had the lowest average number of FEMAT birds (Table 3.1).
47
Canonical Correspondence Analysis (CCA) of Ten Study Areas
As in Chapter II, I conducted multivariate analysis of bird species abundance and
environmental variables from the ten study areas using canonical correspondence analysis
(CCA). CCA axis eigenvalues showed that the percent of variance in bird and
environmental data explained by the first two axes ranged from 30% in the CCA analysis
of The Upper Creek Study Area to 89% in the analysis of The North Seiad Study Area.
Table 3.2. X and Y axis eigenvalues, and the percent of variance explained by each axis
in the CCAs of bird and environmental variables from ten Study Areas.
Y-axis
X-axis
Variance
Variance
Y-axis
Eiaenvalue Explained Eiaenvalue Explained
Study
Areas
X-axis
Upper Beaver
Lower Beaver
E. Scott
W. Scott
S. Seiad
N. Seiad
Happy Camp
Orleans
Cecilville
Callahan
0.172
0.203
0.208
0.186
0.138
0.232
0.164
0.115
0.146
0.220
37.7%
35.7%
28.7%
38.1%
30.3%
33.0%
39.0%
29.0%
31.2%
42.9%
0.121
0.131
0.193
0.123
0.114
0.190
0.104
0.105
0.117
0.114
26.5%
23.0%
26.7%
25.2%
25.1%
27.1%
24.7%
26.4%
25.0%
22.2%
Environmental Variables and Associated Bird Species
Environmental variables which had X or Y-axis correlations that were > 0.4 or
<-Q.4 in three or more study areas were examined (Table 3.3). I subjectively choose 0.4
as a cut off to limit the number of variables examined in each study area. The First CCA
axes represented an elevation gradient in seven of ten study areas, and in the other three
the second axis represented this gradient. These axes were associated, at their opposite
48
ends, with the cover of true firs which dominate higher elevation forests, and the cover of
Douglas-firs which are the dominant tree at middle and lower elevations.
Elevation was strongly correlated with CCA axes in six study areas and Chestnutbacked Chickadee, Pileated Woodpecker, Brown Creeper, Golden-crowned Kinglet and
Pacific-slope Flycatcher were correlated with the upper end of this elevation gradient in
several of them (Table 3.3). All of the high elevation associates are FEMAT birds except
Pacific-slope Flycatcher (Table 1.2). Cover values for true fir were correlated with CCA
axes in seven study areas and Golden-crowned Kinglet, Hermit Thrush, Chipping
Sparrow, Dark-eyed Junco, Dusky Flycatcher, Fox Sparrow, Lazuli Bunting, Hermit
Warbler, Mountain Chickadee and Red-breasted Nuthatch were correlated with the same
end of the axis in several areas (Table 3.3). Four of these true fir associates are FEMAT
birds (Table 1.2).
The cover values of Douglas-fir were correlated with CCA axes in eight study
areas (Table 3.3). Chestnut-backed Chickadee, Golden-crowned Kinglet, Red-breasted
Nuthatch, Fox Sparrows, Hermit Thrush and Hermit Warbler were correlated with the
same axis as Douglas-fir in multiple study areas (Table 3.3). All of these Douglas-fir
associates except Fox Sparrow are FEMAT birds (Table 1.2).
An additional gradient represented by one of the first two axes in several study
areas was a forest structure gradient. This was gradient is described by variables which
showed correlations with the CCA axes and which measure total canopy cover and the
number of canopy sublayers. The number of tree sublayers was correlated with CCA
I
49
Table 3.3 . Environmental variables which had CCA X or Y axis correlations of >0.4 or
<-0.4 in five or more study areas (with canopy cover variable in addition) and the number
of study areas where bird species were correlated with the same axis.
Cover of Cover of
Douglas-fir True Firs Elevation
(n=8)
(n=7)
(n=6)
Number of
Canopy
Sublayers
(N=5)
Brown Creeper
I
0
3
2
I
Chestnut-backed Chickadee
5
2
4
I
2
Chipping Sparrow
2
3
0
I
1
Dark-eyed Junco
2
3
2
0
I
Dusky Flycatcher
2
I
0
0
I
Fox Sparrow
4
3
0
0
1
Golden-crowned Kinglet
5
4
3
1
4
Hermit Thrush
3
4
2
0
2
Hermit Warbler
3
3
2
0
2
Lazuli Bunting
2
3
1
2
0
Mountain Chickadee
1
3
1
0
1
Pileated Woodpecker
2
0
4
1
3
Red-breasted Nuthatch
5
3
1
1
1
Song Sparrow
0
0
1
3
0
Cassin's Vireo
1
0
2
3
1
Pacific-slope Flycatcher
2
0
3
2
1
Western Tanager
1
0
2
3
0
Bird Species
I
I
1
1
Canopy
Cover
(n=3)
-I
50
axes in five study areas, and Cassin's Vireo, Song Sparrow and Western Tanager were
correlated with the same end of that gradient in three of the five areas. Total canopy
cover was correlated with CCA axes in four study areas. Golden-crowned Kinglet,
Hermit Warbler and Pileated Woodpecker were correlated with the end of the gradient
where greater canopy covers occur in several study areas (Table 3.3). All of the closed
canopy associates are insectivorous FEMAT birds (Table 1.2).
Bird Species and Associated Environmental Variables
Bird species which had CCA X or Y axis scores > 0.91 or < -0.91 in three or more
study areas were examined (Table 3.4). Again I choose 0.91 as a cut off arbitrarily in
order to find consistencies amongst study areas. The distribution of these birds is more
strongly influenced by the gradient represented by the associated CCA axis.
Table 3.4 shows the number of study areas in which an environmental variable
was correlated to an axis that a bird species had high axis scores, inferring an association.
Elevation, the cover of Douglas-fir in the first and second tree sublayers, and the height
of the tree canopy were correlated Chestnut-backed Chickadee associated axes (Table
3.4). This chickadee is a FEMAT bird (Table 1.2). The cover of ponderosa pine in the
second tree sublayer was correlated with the same axis as Common Bushtit in three of the
four study areas where it had high axis scores.
51
Table 3.4. Bird species which had CCA X or Y axis correlations > 0.91 or < -0.91 in
three or more study areas, and the number of study areas where environmental variable
were correlated with the same axis.
Elevation
Water
Canopy Height
Minimum DBH
Cover of Douglas-fir
Cover of ponderosa
Pine
Cover of Incense Cedar
Cover of True Firs
Cover of Riparian Spp.
CBCH COBU FOSP GCKI PISI SOSP TOSO WEWP
3
0
3
3
4
0
3
2
1
3
I
3
0
0
1
1
2
3
2
1
3
0
1
0
3
0
2
2
3
1
3
2
0
3
0
0
1
0
1
1
1
2
1
0
1
1
4
2
2
2
1
1
0
2
2
3
3
2
3
1
1
3
3
1
0
3
2
2
3
3
0
4
The cover of true firs, elevation, presence of water, minimum tree DBH and cover
of alder were correlated with the same axis as Pine Siskin in several study areas (Table
3.4). The cover of riparian plant species (alder and willow), the cover of Douglas-fir, and
the cover of smaller incense cedars were correlated with axis for which Western Woodpewee had high axis scores in several study areas (Table 3.4). Fox Sparrow had high
scores for axes associated with elevation, minimum DBH, cover of true fir and cover of
willow in three study areas (Table 3.4). Golden-crowned Kinglet, a FEMAT bird, had
high scores for axes associated with elevation, height of the tree canopy and cover of true
firs in several areas. Song Sparrow high scores for axes associated with riparian plant
species (alder or willow) and the presence of water. Townsend's Solitaire was correlated
with the axes associated with elevation and riparian plant species (Table 3.4).
-I
52
Correlation Analysis of Ten Study Areas
Pearson correlation matrixes were created to examine the associations of 56 bird
species, total number if individuals, the total number of FEMAT bird individuals, and the
Shannon-Weiner diversity indices for all bird species and FEMAT bird species with
seven habitat types within ten study areas. Red-breasted Nuthatch, a FEMAT bird, was
correlated with the Douglas-fir/incense cedar (DF/IC) or true fir (TF) habitat types in five
areas. Dusky Flycatcher, Fox Sparrow, Dark-eyed Junco, House Wren, and Goldencrowned Kinglet were associated with true fir habitats (DF/TF and TF) in 2 areas. These
true fir associates include I FEMAT bird (Golden-crowned Kinglet).
TF was negatively correlated with Bird Species Diversity. Total Individuals,
Total Number of Species, FEMAT Bird Richness, and FEMAT Bird Diversity were
positively correlated with Douglas-fir/oak woodland (DF/OW) habitats in three study
areas. Black-throated Gray Warbler, Chipping Sparrow and Western Wood-pewee were
correlated with the DF/OW habitat type in two areas. Cassin's Vireo was associated
with the Douglas-fir/big-leaf maple (DF/BLM) habitat type in 4 areas, and Chipping
Sparrow was negatively correlated with DF/BLM in two areas, as was the variable
representing total bird richness.
Birds and Associated Environmental Variables
Eleven bird species, plus two bird species richness and diversity variables,
showed significant Pearson correlation coefficients (P<0.05, r>0.35 or r<-0.35) with one
or more environmental variables in eight or more study areas, and showed a consistent
4-
Table 3.5. Number of study areas where bird variables were significantly correlated with one or more environmental variables and
number of study areas where bird variable and environmental variables had significant Pearson correlation coefficients (P<0.05,
r>O.35 or r<-O.3 5). Negative correlations indicated with negative numbers. Cover of willow, alder and Populous spp. represented by
riparian plant species, and cover of Ocean spray, Pacific dogwood and western hazel represented by forest shrub species.
Elevation Water Minimum Cover Cover of Cover of Cover of Cover Cover Cover of Cover of Cover of
# of
DBH
of
true fir Douglas ponderosa of big- of live deciduous Riparian Forest
Study
Areas
moss
-fir
pine
leafed oak
oak
Spp.
Shrub
maple
Spp.
9
1
o
o
0
1
AMRO
1
3
1
1
0
1
2
0
1
1
0
9
1,-1
BRCR
1
2
1
2
2
4
2
1
1
9
-2
0
-2
3
-1
I
BTYW
1
2
3
4
0
9
1
-1
2
0
1
1
CHSP
0
0
0
1
1
o
o
0
1
9
0
PIWO
1
4
2
7
2
1
3
CBCH
8
0
0
-1
2
1
2
0
3
0
0
3
3
8
3
-1
1
0
2
1, -1
0
DEJU
0
0
0
1
0
8
2
0
0
1
2
GCKI
3
0
0
0
0
1
2
8
1,-1
o
o
0
0
MGWA
2
2
0
1
1
1
1
-1
1
0
3
MOCH
8
1
0
2
1
2
0
3
0
-1
0
1
1
PUFI
8
0
0
4
1
3
1
1
1
-1
2
0
3
RBNU
8
3
1
2
1, -1
0
0
1
0
WEWP
8
0
-1
1
0
1
0
1
4
1
0
0
0
-4
0
1
1,-1
Richness
1,-1
-1
0
1
1,-2
-1
-2
-1
Diversity
1, -1
-3
0
0
1,-1
0
0
-2
1
-2
0
-1
LA
54
relationships with at least one environmental variable in three or more of the areas (Table
3.5). American Robin was associated with the cover of ponderosa pine in several study
areas (Table 3.5). Brown Creeper, a FEMAT bird, had a positive correlation with
riparian plant species, and Black-throated Gray Warbler was associated with moss cover,
the cover of riparian plants and the cover of forest shrub species in multiple study areas
(Table 3.5). Pileated Woodpecker, a FEMAT bird, was associated with ponderosa pines
and live oak in three areas and with riparian plant species in several areas (Table 3.5).
Chestnut-backed Chickadee showed significant correlation's with the cover of big-leaf
maples, riparian plants and forest shrubs, Dark-eyed Junco was associated with high
elevations, and Golden-crowned Kinglet was correlated with the cover of Douglas-fir in
the upper canopy in three study areas (Table 3.5). Mountain Chickadees showed an
association with the cover of true firs and riparian species, and Purple Finch was
associated with the cover of ponderosa pine and live oak (Table 3.5). Red-breasted
Nuthatch, a FEMAT bird, was correlated with high elevations and true firs, and Western
Wood-pewee was associated with deciduous oaks in several study areas (Table 3.5).
Species richness and species diversity were negatively correlated with water in four and
three study areas respectively.
-I
CHAPTER IV: ANALYSIS OF BIRD-HABITAT RELATIONSHIPS
WITHIN LATE-SERAL MIXED-CONIFER FORESTS
Canonical Correspondence Analysis (CCA) of Intensive Point Counts
I conducted a canonical correspondence analyses (CCA) on bird species and
related richness and diversity variables along with environmental variables from the 61
Station Late-seral dataset. The first two CCA axes explained 57% of the variance in bird
and environmental data.
Bird Species and Associated Environmental Variables
An examination of the bird species and environmental variables which were most
correlated with the CCA axis allowed bird and habitat associations to be inferred. Bird
species which had highest negative X-axis scores (X-axis scores < -1.0) were Greentailed Towhee, Olive-sided Flycatcher, Red-breasted Sapsucker, Chipping Sparrow,
Townsend's Solitaire and American Robin (Table 4.1). These birds are associated with
the environmental variables which had the greatest correlations with negative end of the
X-axis (X-axis correlation < -0.3). They include the cover of grass, the cover of
ponderosa pines in the first tree layer, and forest stands with less than 40% total canopy
cover (Table 4.1). Bird species with the greatest positive X-axis scores (> 0.5) include:
Gray Jay, Pacific-slope Flycatcher, Winter Wren, Purple Finch and Hermit Thrush (Table
55
Table 4.1. Weighted correlations of environmental variables and bird species with CCA X and Y axes using 61 late-seral forest birdhabitat census stations.
X-axis eigenvalue: 0.067Variance explained: 29.9%
Negative X-axis
Positive X-axis
Environmental Variables
Bird Species
Environmental Variables
Bird Species
(Corr. < -0.3)
(Corr. < -1.0)
(Corr. > 0.3)
(Corr. > 0.5
Cover of grass spp.
GTTO
Total tree cover
GRJA
Total Canopy Cover < %40
OSFL
Cover of Pacific Dogwood WEFL
Cover of ponderosa pine
RBSA
Total Canopy Cover > %40 WIWR
in 1st tree sublayer
CHSP
Cover of 1st Tree Sublayer PUFI
TOSO
Cover of 2nd Tree Sublayer HETH
AMRO
Y-axis eigenvalue: 0.060 Variance explained: 26.7%
Negative Y-axis
Positive Y-axis
Bird Species
Environmental Variables
Environmental Variables
Bird Species
(Corr. <-0.75)
(Corr. <-0.3)
(Corr. < 0.3)
(Corr. < -1.)
HAFL
Density of trees with DBHs
Elevation
CAFI
CHSP
Between 25 and 40 In.
Cover of Incense Cedar
GRJA
WEFL
Density of trees with DBHs
in 2nd tree sublayer
SPTO
SOVI
> .40 In
Cover of ponderosa Pine
PUFI
TOSO
Cover of deciduous oak spp.
in 2nd tree sublayer
BHGR
BRCR
Minimum DBH
Cover of Incense Cedar
Cover of Pacific madrone
in 1st shrub sublayer
Cover of Pacific Dogwood
Cover of true fir spp.
in 1st tree sublayer
.
..
.
0oA
57
4.1). These birds, three of which are FEMAT birds (Table 1.2), are associated with total
tree layer cover, cover of Pacific Dogwood, forest stands with greater than 40% total
canopy cover, and the cover of the first and second tree sublayers (Table 4.1).
Bird species with the highest negative Y-axis scores (< -0.75) include Hammond's
Flycatcher, Chipping Sparrow, Pacific-slope Flycatcher, Cassin's Vireo, Townsend's
Solitaire and Brown Creeper (Table 4.1). These birds, three of which being FEMAT
birds (Table 1.2) are associated with the density of trees with DBHs greater than 25
inches, the cover of deciduous oaks, higher maximum DBHs, and the cover of Pacific
madrone and Pacific dogwood (Table 4.1). Bird species with the highest positive Y-axis
correlations (> 1.0) include Cassin's Finch, Gray Jay, Spotted Towhee, Purple Finch and
Black-headed Grosbeak (Table 4.1). These birds are associated with positive Y-axis
correlated environmental variables (Y-axis correlation > 0.25). These include elevation,
the cover of incense cedar in the second tree sublayer and first shrub sublayer, the cover
of ponderosa pine in the second tree layer, end the cover of true fir in the first tree
sublayer. (Table 4.1).
Correlation Analysis of Intensive Point Counts
I conducted a Pearson correlation analysis to examine the associations of bird
species and related richness and diversity variables with environmental variables from the
61 Station Late-seral Dataset. Twenty-two bird variables and 21 environmental variables
showed significant correlations (P > 0.03 or P < -0.03, and r < 0.01)
58
Bird Species and Associated Environmental Variables
Three bird species, Yellow-rumped Warbler, Red-breasted Nuthatch and Northern
Flicker, showed significant correlations with elevation (Table 4.2). Red-breasted
Nuthatch and Northern Flicker are FEMAT birds (Table 1.2). Dark-eyed Junco was
correlated with stations that have
<
40% total canopy cover and negatively correlated
with higher cover in the first tree sublayer (TI) and the cover of Douglas-fir in the second
tree sublayer (T2). Green-tailed Towhee was correlated with incense cedar in T I,
ponderosa pine in T2, Ribes spp., and grass species (Table 4.2).
Hammond's Flycatcher, a FEMAT bird, was correlated with higher densities of
64 to 102 cm trees and with canopy covers over 40% (Table 4.2). Hairy Woodpecker, a
FEMAT bird, was correlated with higher densities of 64 to 102 cm trees and with Ribes
spp. Cassin's Vireo was correlated with the density of trees with DBHs above 64 cm
(Table 4.2). Warbling Vireo, a FEMAT bird, was correlated with Pacific madrone and
Pacific-slope Flycatcher, a FEMAT bird, was correlated with Pacific dogwood and
Western Hazel (Table 4.2). Western Tanager was correlated with the density of trees
with DBHs above 102 cm and stands with canopy covers over 40% (Table 4.2).
Variables representing bird abundance, species richness and species diversity
were correlated with elevation, the density of trees with DBHs below 6 inches, and stands
with canopy covers below 40%. Species richness and species diversity were correlated
with total canopy cover and species richness was correlated with cover of TI (Table 4.2).
59
Table 4.2. Highest correlations between bird species and environmental variables
from 61 late-seral forest bird-habitat stations (See Table 2.1 for bird species codes,
END=total individual birds at a station, SPP= total bird species at a station, SW=Shannonweiner diversity index for birds on a station).
AUWA Elevation BHGR Pine spp. Ceanothus CHSP Ocean spray
in SI
spp.
0.41
0.86
0.64
0.39
(0.001)
(0.0001)
(0.0001)
(0.002)
DEJU <40% tree cover T2 cover E)ouglasfir in T2
0.37
-0.47
-().42
(0.004)
(0.0001) (().0007)
GTTO Pine spp.
in T2
0.31
(0.01)
Ribes
spp.
0.57
(0.0001)
0.6
(0.0001)
>102 cm tree
density
0.79
(0.0001)
HEWA Incense
NOFL Elevation
cedar in TI
0.38
0.31
(0.02)
(0.002)
OSFL Incense
Ribes
cedar in T I W.
0.43
0.43
RBNU Elevation
0.53
0.43
(0.0001) (0.0005)
Ribes
Grass HAFL 64-102 cm tree
spp.
density
0.43
0.38
0.57
(0.0005) (0.002)
(0.0001)
HAWO 64-102 cm tree
density
0.57
(0.0001)
(0.0005)
GRJA T2 height Ribes
Grass PUFI Tree cover
spp.
0.38
0.36
(0.0005) (0.002)
(0.004)
SOVI 64-102 cm tree
density
0.43
(0.0006)
Pine spp.
in T2
0.49
(0.0001)
102 cm tree
density
0.42
(0.0009)
SPTO Ceanothus
0.42
(0.0008)
60
Table 4.2. (Continued)
TOSO Pine spp. WAVI
in Ti
0.37
(0.003)
WETA >102 cm ttree
density
0.4
(0.001)
Pacific
WEFL
Madrone
0.43
(0.0005)
IND Elevation
0.4
(0.002)
Pacific
Viestern Hazel
Dogwood
0.4
0 .3
(0.001)
(().017)
<15 cm tree
<40% tree cover
density
-0.3
0.35
(0.02)
(0.005)
SPP Elevation <15 cm tree
density
0.42
0.32
(0.0007) (0.01)
Tree cover <40% tree cover T I cover
SW Elevation <15 cm tree
density
0.42
-0.33
(0.0009) (0.01)
Tree cover <40% tree cover
-0.33
(0.009)
-0.33
(0.01)
0.42
(0.0008)
0.42
(0.0007)
-0.31
(0.01)
-I
CHAPTER V: DISCUSSION
Methods
In developing a study design for this project a high priority was to spread as many
survey stations as possible across the landscape in order to gather baseline information
about the distribution of bird species across the Klamath National Forest's landscape. In
order to sample the widest variety of habitats, many of the stations were only visited
once, allowing a greater coverage of the landscape to be achieved. Because most stations
were visited only once, I used data from one visit in the analyses for stations that were
visited more than once.
In Chapters II and III standardized habitat sampling methods were used. When
collecting the Late-seral dataset analyzed in Chapter IV additional variables were
collected. I collected total cover values for each vegetation sublayer, in addition to total
tree and shrub cover values, and stem counts for a variety of tree size classes. This
allowed me to conduct a better investigation into how bird distribution is related to
specific forest structure characteristics.
One problem I faced with having a large, complex vegetation dataset, was
classifying each station into a habitat type. The cluster analysis split the stations into
small of similar stations in order to classify each into respective habitat types. This
61
62
was essential to the investigation of bird distribution at a landscape level because it
allowed me to efficiently classify each of the 500 stations as one of seven habitat types.
Of the 57 plant species used by TWINSPAN to separate the stations, only the
dominant tree species were used to classify each cluster group. Though most these
groups sorted together in the analysis, a few of them had spurious locations. This was
caused by TWINSPAN's use of plant species to separate the stations which were not used
classify the groups. When these spurious groups were lumped back with groups of
similar classification and analyzed by the habitat as a whole they did not negatively effect
the success of this classification system.
Because Canonical Correspondence Analysis (CCA) looks at all of the
environmental and species abundance data together it is an ideal method for generating
hypotheses. The CCA identified elevation and riparian associated plants, and forest
structure measurements as influential in the distribution of birds. The first two gradients
explain the majority of the of environmental and bird abundance variables. By
investigating groups of variables, insight into community level relationships is gained.
Groups of birds that occur in similar habitats are associated with groups of related
environmental variables. By studying the linear relationship between specific
environmental variables and bird species abundance further hypotheses about how
management actions which change the environmental variables can be developed.
When looking at 57 bird species across a vast landscape, I needed to develop a
strategy to allow me to sift through the data in order to narrow down and focus on
important bird-habitat relationships. My approach of looking at bird-habitat relationships
63
at a landscape level and a watershed level helped me to find consistencies and identify
questions that deserve more study. Additional research was started to focus on such
questions which include how does canopy cover influence the distribution of old growth
associated birds in late-seral forests. The preliminary results examined in the Late-seral
Dataset were analyzed in Chapter IV.
Distribution Of Birds Across Klamath/Siskiyou Habitat Types
Habitat Types
With the diversity of habitat-types across Klamath/Siskiyou Mountains it was
important to classify census stations based on environmental data collected on the
ground. In the analyses of the 500 Station Dataset plant species cover values for true fir,
big-leafed maple, Pacific madrone, alder and willow were used to define the seven
habitat types. These variables were also identified in the canonical correspondence
analysis as influential in the distribution of birds across the landscape. When examined
at the watershed scale, true firs were important in the CCAs of seven study areas. In
addition to true firs, big-leafed maple, deciduous oaks and riparian trees were
significantly correlated with the abundance of bird species in several study areas. These
consistencies support a conclusion bird distribution across the Siskiyou/Klamath
Mountain landscape is, in part, influenced by dominant habitat types that are determined
by dominant tree species.
Six of the seven habitat types are distributed along an elevation gradient with the
true fir and incense cedar types at higher elevations and the hardwood types at lower
"U~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~M-
64
elevations. Elevation was the most important variable for describing the distributing
birds across the landscape and across study areas, as defined by CCAs. Consistently,
higher elevation study areas were dominated by true fir habitats and lower areas by
hardwood habitats. This adds to the complexity of the relationship between birds and
habitat types. The presence of bird species is partially dependent on the resources
provided by the vegetation and associated food supplies and nesting locations. Therefore,
elevation indirectly influences the distribution of bird species by directly influencing the
habitats available.
The alder habitat was different than the other five types in that it was the least
abundant across the landscape, did not dominate any study areas and occurred across a
wide range of elevations. This is typical of riparian habitats in steep mountain ranges, as
they occur in strips, following water from the snow packs of the mountain tops, down to
the rivers. Riparian areas provide unique, limited habitats, which support a unique
community if riparian associated bird species across the elevation gradient and within
each major habitat type.
To further consider the distribution of birds across the Klamath/Siskiyou
landscape I examine consistencies between the results from the habitat type analysis and
the analysis of bird distribution across three broad ecological zones: high elevation
conifer, mixed conifer hardwood, and riparian. As the cover of the major plant species
separated the 500 Station Dataset into three similar vegetation complexes in the CCA, the
habitats types which were defined by these same variables, can logically be placed into
these same ecological zones. The results of this research lead toward a better
65
understanding of the distribution of birds across these ecological zones and they can be
used to summarize the distribution of birds across the Klamath/Siskiyou landscape.
High Elevation Conifer
The high elevation conifer ecological zone is one of the more protected areas in
the Klamath/Siskiyou Mountains and it is where most of the roadless areas, wilderness
areas and late successional reserves are located. It is important to know which birds are
associated with this zone in order to understand the importance of these areas to the
conservation of bird species as a whole.
Nine bird species were associated with high elevation conifer zones at both the
landscape and watershed scale. Golden-crowned Kinglet, Red-breasted Nuthatch, and
Dark-eyed Junco either were abundant in, or preferred, high elevation habitats and were
also included in the high elevation complex. At the watershed level, these species
showed significant correlations with habitat variables that are associated with high
elevations. Fox Sparrow, Chipping Sparrow, Pine Siskin, Yellow-rumped Warbler,
Mountain Chickadee and Hermit Warbler also were associated with high elevation
habitat types and complexes. They also were associated with the same axis as the high
elevation related environmental variables in the CCAs of several study areas.
Four of the high elevation conifer associates, Golden-crowned Kinglet,
Hammond's Flycatcher and Hermit Warbler, are considered old-growth related species
(FEMAT birds) under the Northwest Forest Plan (USDA and USDI 1994). These
habitats make up the majority of the protected areas in the Klamath/Siskiyou Region.
66
These areas should remain protected and the protection of additional high elevation old
growth forests should be sought, however, this should provide a warning that directs our
attention towards learning more about late-seral forests and associated birds at the lower
elevations. Our current network of protected areas underrepresented these lower
elevation areas.
In addition, two of the high elevation associates, Pine Siskin and Chipping
Sparrow, have Calranks above 5.0 (Manley and Davidson 1993). These birds are
considered at risk in California because of a combination of extent of range, extent of
suitable habitat and population trend. Three of the high elevation associates, Yellowrumped Warbler, Chipping Sparrow and Hermit Warbler, are long distance migrant birds.
These species are at risk and populations need to be watched as they face many more
threats and are dependent on many additional habitats.
Gains (1977) found that Golden-crowned Kinglets are most abundant in deep
Red Fir forests and in Northern California were positively correlated with high elevation
(Raphael and Barret 1985). Temperature preferences and the presence of fir have been
identified as reasons for this habitat preference (Airola 1980). Higher elevation conifer
forests with closed canopies tend to have cooler micro-climates. Golden-crowned
Kinglets foliage glean for insects (Ehrlich et al. 1988) and Franzreb (1984) showed that
spruce and fir trees were their preferred foraging substrate.
Red fir is an optimal breeding and feeding habitat for habitat for Red-breasted
Nuthatches (Verner and Boss 1980). High elevation fir trees generally have dense
foliage. Golden-crowned Kinglets nest in conifer trees (Ehrlich et al. 1988).
67
Dark-eyed Juncos, Fox Sparrows, Chipping Sparrows, Yellow-rumped Warbler,
Mountain Chickadee and Pine Siskins occur in a variety of habitats (Verner and Boss
1980), though they showed an association for the high elevation habitats in this study.
Verner and Boss (1980) classify red fir zones as optimal for the breeding and foraging of
the first five of these species, and as suitable for the later. Timossi (1990) identified firs
as preferred for Hermit Warbler reproduction and red fir zones are optimal for foraging
(Verner and Boss 1980).
Mixed-Conifer Hardwood
The Mixed-Conifer Hardwood ecological zone, found at lower elevations, has
fewer intact pieces currently under protected in the Klamath/Siskiyou Mountains. Many
of these habitats including oak woodlands are severely fragmented and continue to be
threatened by development, fire exclusion and other human impacts. As these areas
receive more attention from the conservation community it is important to understand the
importance of these lands to bird conservation. A base for this understanding must be
knowledge of the birds occurring in the associated habitats.
Black-headed Grosbeak and Black-throated Gray Warbler were associated with
hardwood habitats and related variables at both the landscape and watershed scales. In
addition, Cassin's Vireo, Swainson's Thrush, Pacific-slope Flycatcher, Winter Wren,
Nashville Warbler, and Western Tanager were associated with mixed conifer hardwood
habitat types and were included in the mixed conifer hardwood assemblage.
68
Two of these species, Winter Wren and Pacific-slope Flycatcher, are FEMAT
birds (USDA and USDI 1994). Swainson's Thrush has one of the highest Calranks (4.5 Manley and Davidson 1993). All of the mixed-conifer/hardwood associates, except
Winter Wren, are long distance migrants, showing that these habitats are important for
this suite of birds.
It is important to note that as part of the hardwood complex, the Douglas-fir/oak
woodland stations supported the highest abundance and diversity of birds. Excluding the
riparian habitats, oak woodlands are of the most unique and under sampled in the 500
Station Dataset. They are not as much a part of the mosaic of the other mixed conifer
habitats in that they occur independently in the valleys and at the edges of the region. In
the Klamath Siskiyou Region these valley habitats are highly threatened. In addition
their natural processes have been altered by fire exclusion. As well, the habitats receive
little protection under the Northwest Forest Plan that focuses more on land producing
commercial timber.
Black-headed Grosbeaks nest in hardwoods preferring willows and live oaks; they
also nest where water and other deciduous oaks are present (Weston 1947). In the 500
Station Dataset live oaks, willows and deciduous oaks were components of the hardwood
habitats and of these habitat types the big-leafed maple was where both water and Blackheaded Grosbeaks were common. Timossi (1990) also considered hardwood habitats and
associated tree layer complexity as important for Black-headed Grosbeak reproduction.
Black-throated Gray Warbler commonly breed in hardwood habitats in California
(Zeiner et al. 1990). These birds often occur in oak dominated habitats (Morrison 1982).
-I
69
Deciduous trees are of the preferred nesting substrates for this species (Ehrlich et al.
1988). Swainson's Thrush breeding habitats also include hardwood forests and they
prefer dense under-stories (Timossi 1990) which are characteristic of Klamath/Siskiyou
mixed conifer hardwood habitats though they are also found in conifer forests.
Airola and Barret (1985) observed that Cassin's Vireos preferred black oak and
tanoak and avoided incense cedar and white fir when foraging. They often nest in
deciduous trees (Ehrlich et al. 1988) including understory trees such as oaks and alder
(Burleigh 1930, Hammersin and Lapin 1980).
In California Pacific-slope Flycatchers are most common in low elevation
deciduous forests (Zeiner et al 1990), and Timossi (1990) identifies hardwoods as a
preferred habitat element. These birds prefer dense canopies and the hardwood habitats
in this study had the greatest average canopy covers. They forage from lower perches
(Verbeek 1975), which are provided in the complex structures of the hardwood canopies.
Deciduous trees are the preferred nesting substrate for Pacific-slope Flycatchers (Ehrlich
et al. 1988).
In contrast with the results of this research Ehrlich et al. (1988) found that Winter
Wrens as rare breeders in deciduous forest. However they mention that these wrens nest
near water where the understory is dense; in the 500 Station Dataset the hardwood
habitats had greater percent of there stations near water, and greater average shrub
covers. Nashville Warblers prefer oak woodlands for nesting and preferentially forage in
black oaks (Airola 1979, Airola and Barrett 1985). They prefer dense under-stories as
V
70
well (Kilgore 1971). During the breeding season in California, Western Tanagers prefer
open conifer forests with associated hardwoods (USDA 1994).
Riparian
Riparian habitats are the most heavily impacted of those considered in this study.
Over 90% of these habitats have been destroyed in California. Riparian habitats are
extremely important to many species for breeding, dispersing, and migration. A better
understanding of the bird species that breed in Siskiyou/Klamath Mountain riparian
habitats will provide better information for the appropriate management for these areas.
Knowledge of what species should be carefully monitored to assure they do not face
increasing threat of expiration is key for the conservation of birds in this region.
Two FEMAT birds, Pileated Woodpecker and Brown Creeper, were included in
the Riparian bird complex and were significantly correlated with riparian plant species in
several study areas. Yellow-breasted Chat, Yellow Warbler, Song Sparrow and Brownheaded Cowbird were also included in the riparian vegetation complex and were
associated with the Douglas-fir/Alder habitat types at the landscape level.
One objective of the Northwest Forest Plan is to manage for healthy relationships
between riparian areas and surrounding forests by using stream buffers (USDA and USDI
1994). Further study into the relationships between the two riparian associated FEMAT
birds and stream buffer size might provide insight into the adequacy of current suggested
buffers as they indicate a combination of healthy late-seral and riparian habitats.
71
Yellow-breasted Chat, Yellow Warbler, Song Sparrow are receiving special status
under the California Riparian Joint Venture and are considered important indicators for
healthy riparian habitats. In addition, the chat and Yellow Warbler are long distant
migrants. Many authors have documented Yellow Warbler's preference for riparian
habitats (Stauffer and Best 1980, Verner and Boss 1980, Ehrlich et al. 1988, Zeiner et al.
1990, USDA 1994).
These species, which are not necessarily tied to old-growth forests, indicate
healthy riverine riparian habitats at a wider scale and under Ecosystem Management they
can be used to help set riparian conservation goals. These species and habitats linearly
distribution across all habitats and their management must be driven by intensive
conservation policies.
Late-seral Habitats
Late-seral habitats have recently received much attention by the conservation
community and the land managers in the Pacific Northwest (USDA et al 1993). Much of
this attention focuses on single species management. To understand the dynamics of lateseral habitats in the Klamath/Siskiyou Mountains, an increased knowledge of how the
distribution of a whole suite of species is influenced by old-growth associated forest
characteristics is necessary.
As mentioned above, three of the high elevation conifer associates are considered
old-growth related species (FEMAT birds) under the Northwest Forest Plan (USDA and
USDI 1994). These habitats make up the majority of the protected areas in the
72,
Klamath/Siskiyou Region. These areas should remain protected and the protection of
additional high elevation old growth forests should be sought. In Addition, our attention
should also turn towards learning more about late-seral forests and associated birds at the
lower elevations. Our current network of protected areas under-represents these forests
and special efforts should be focussed on changing this trend.
The CCA of the 500 Station Dataset identified two structural variables as being
influential in the distribution of bird species. These include total tree cover and height of
the tree canopy. In Late-successional Reserve (LSR) management, canopy cover is
identified as a management target and under several scenarios will be altered by thinning
and burning under the current land management plan (USDA 1999). Canopy height is
directly related to DBH, which indicates forest stand age, another important component
to LSR management. Additional variables collected in the Late-seral dataset were also
associated with forest structure and provide more insight into the effects of LSR
management on the distribution of bird species with in habitats. These include general
timber type, canopy sublayer cover values and diameter size class tree density measures
and my analyses showed that they were influential on the distribution of birds.
Canopy cover and canopy height were associated with Chestnut-backed
Chickadee on both a landscape and watershed level. Pacific-slope Flycatcher and Winter
Wren showed this relationship at the landscape level and Golden-crowned Kinglet,
Hermit Thrush, Hermit Warbler, and Pileated Woodpecker at the watershed scale.
Golden-crowned Kinglet also was associated with canopy height at the watershed scale.
Three of these bird species, Pacific-slope Flycatcher, Winter Wren, and Hermit Thrush
73
showed similar relationships with canopy cover when studied in the intensive Late-seral
dataset.
Overall bird species richness and diversity is higher on stations where the canopy
cover is less than 40%. This might explain why the old-growth associated species
discussed above are less abundant in these conditions. As canopy covers are reduced and
larger tree thinned from late-seral forests, habitat is opened non old-growth associates
such as Dark-eyed Juncos benefit. These types of species might displace the closedcanopy associated FEMAT birds. The results of this study suggest that reducing lateseral forest canopies below 40% cover might result in the loss of specific FEMAT bird
species even as overall bird species richness and diversity increases.
A second year of data collected in late-seral forests will provide a larger dataset
allowing for aniore powerful analysis of these relationships. As thinning projects are
implemented in Late-successional Reserves (LSR), bird diversity and the presence and
absence of FEMAT birds should be monitored to determine the effects of these practices
on the distribution of high priority species, and the ecosystem as a whole. With a larger
dataset, canopy cover thresholds can be developed to assure management remains
beneficial for these species and associated habitats.
Maximum DBH was associated with the distribution Hammond's Flycatcher,
Cassin's Vireo, Pacific-slope Flycatcher, and Brown Creeper by the CCA of the Lateseral dataset. Hammond's Flycatcher and Cassin's Vireo also were correlated with
higher densities of large trees in the analysis of study areas. Well shaded, dense conifer
forests with moderate to dense canopy closer appear to be required for breeding and
74
foraging Golden-crowned Kinglets (Timossi 1990, Zeiner et al. 1990). Pacific-slope
Flycatchers and Hermit Thrushes also prefer higher canopy closer (Timossi 1990, Zeiner
et al. 1990). In the Northwest Hammond's Flycatchers and Pacific-slope Flycatchers had
a higher occurrence in old-growth forests than in younger forests (Raphael 1984, 1988,
Sakai 1988, Carey et al. 1991, Gilbert and Allwine 1991, Ralph et al. 1991). Though
research is mixed on this point Hermit Warblers have been observed to prefer larger trees
and dense cover (Verner and Boss 1980, Harrison 1984).
Many LSRs in the Klamath/Siskiyou Mountains are currently in young to middle
succession. Management objectives for these stands are to enhance old-growth
conditions. These species should be used as indicators of old-growth conditions. By
monitoring for these, the effectiveness of LSR management can be determined.
Conclusion
This study provides information about the distribution of birds across the variety
of habitats found on the Klamath/Siskiyou Mountains. This provides managers with
more precise lists of birds which must be considered when developing land management
plans. As well, the watershed based datasets can be used to provide managers with more
detailed information about bird and habitat distribution in localized areas.
By looking at specific environmental variables that influence bird distribution, we
can gain insight into the effects of land management activities on these species. The
presence or absence of species associated with forest characteristics that change under
management can be used to indicate current and desired conditions. In addition this
75
information can help managers to develop plans which will provide the needed habitat for
high priority bird species, including old-growth associates.
Finally, this study begins to look closer at the ecosystem management of oldgrowth forests by providing insight into how forest structure is associated with bird
distribution within specific habitats.
76
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USDA. 1998. Forest-wide late successional reserve ecosystem assessment. USDA
Forest Service Klamath National Forest. Yreka, CA. (Draft)
USDA and USDI. 1994. Record of decision (standards and guidelines). USDA Forest
Service and USDI Bureau Of Land Management. Portland, OR
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USDA, USDI, USDC and Environmental Protection Agency. 1993. Forest ecosystem
management: an ecological, economic, and social assessment. USDA Forest Service,
USDI USFWS, USDC National Oceanic and Atmospheric Administration National
Marine Fisheries Service, USDI National Park Service, USDI BLM, Environmental
Protection Agency. Portland, OR
Verbeek, N.A. 1975. Comparative feeding behavior of three coexisting tyrannnis
flycatchers. Wilson Bull. 87:231-240
Verner, J., and A.S. Boss, eds. 1980. California wildlife and their habitats: western
Sierra Nevada. USDA For. Serv. Gen. Tech. Rep. PSW-37, Pac. Southwest For. And
Range Exp. Stn., Berkeley, CA. 439pp.
Weston, H.G. 1947. Breeding behaivior of Black-headed Grosbeak. Condor. 49:54-73
Zeiner, D.C., W. Laudenslayer Jr., K. Mayer, and M. White., eds. 1990. California's
wildlife, Vol. 2, Birds. Calif. Dep. Fish and Game, Sacramento. 732pp.
APPENDIX A
Common and scientific names for bird species included in the 500 Station Dataset and
Late-seral Dataset.
81
82
Appendix A
Common Name
Blue Grouse
Mountain Quail
Mourning Dove
Selasphorus spp.
Acorn Woodpecker
Red-breasted Sapsucker
Downy Woodpecker
Hairy Woodpecker
Northern Flicker
Pileated Woodpecker
Olive-sided Flycatcher
Western Wood-pewee
Hammond's Flycatcher
Dusky Flycatcher
Pacific-slope Flycatcher
Gray Jay
Steller's Jay
Common Raven
Mountain Chickadee
Chestnut-backed Chickadee
Common Bushtit
Red-breasted Nuthatch
White-breasted Nuthatch
Brown Creeper
House Wren
Winter Wren
Golden-crowned Kinglet
Townsend's Solitaire
Swainson's Thrush
Hermit Thrush
American Robin
Varied Thrush
Cassin's Vireo
Warbling Vireo
Orange-crowned Warbler
Nashville Warbler
Yellow Warbler
Black-throated Gray Warbler
Scientific Name
Dendragapus obscurus
Oreortyx pictus
Zenaida macroura
Selasphorus spp.
Melanerpes formicivorus
Sphyrapicus ruber
Picoides pubescens
Picoides villosus
Colaptes auratus
Dryocopus pileatus
Contopus borealis
Contopus sordioulus
Empidonax hammondii
Empidonax oberholseri
Empidonax difficilis
Perisoreus canadensis
Cyanocitta stellen
Corvus corax
Parus gambeli
Parus rufescens
Psaltnparus minimus
Sitta canadensis
Sitta carolinensis
Certhia americana
Troglodytes aedon
Troglodytes troglodytes
Regulus satrapa
Myadestes townsendi
Catharus ustulatus
Catharus guttatus
Turdus migratorius
Ixoreus naevius
Vireo solitarius
Vireo gilvus
Vermivora celata
Vermivora ruficapilla
Dendroica petechia
Dendroica nigrescens
83
Appendix A (Continued)
Common Name
Hermit Warbler
MacGillivray's Warbler
Wilson's Warbler
Yellow-rumped Warbler
Yellow-breasted Chat
Western Tanager
Black-headed Grosbeak
Lazuli Bunting
Green-tailed Towhee
Spotted Towhee
Chipping Sparrow
Fox Sparrow
Song Sparrow
Lincoln's sparrow
Dark-eyed Junco
Brown-headed Cowbird
Bullock's Oriole
Purple Finch
Cassin's Finch
Pine Siskin
Lesser Goldfinch
Scientific Name
Dendroica occidentalis
Oporomis tolmiei
Wilsonia pusilla
Dendroica coronata
Icteria virens
Piranga ludoviciana
Pheucticus melanocephalus
Passenna amoena
Pipilo chlorurus
Pipilo erythrophthalmus
Spizella passenna
Passerella iliaca
Melospiza melodia
Melospiza lincolnhl
Junco hyemalis
Molothrus ater
Icterus galbula
Carpodacus purpureus
Carpodacus cassinii
Carduelis pinus
Carduelis psaltria
APPENDIX B
Environmental Variables from 500 Station Dataset and additional variables collected for
Late-seral Dataset.
84
85
Appendix B
500 Station Dataset
Variable Name
Definition
ELEV
ASPECT
SLOPE
WATER
EAST
NORTH
TRECOV
TREUPR
TREMIN
TREMAX
TRESUB
SHRCOV
SHRSUB
HRBCOV
MOSCOV
Elevation (meters)
Aspect (degrees)
Percent slope
Presence of Water (0-1)
Sin(aspect)
Cos(aspect)
Total tree cover (%)
Canopy height (meters)
Minimum tree DBH (centimeters)
Maximum tree DBH (centimeters)
Number of tree sublayers
Total shrub cover (%)
Number of shrub sublayers
Total herb cover (%)
Total moss cover (%)
The follow variables represent species specific/sublayer specific percent cover values.
Variable Name
Vegetation Species
Vegetation Sublayer
ABIEHI
ABIESI
ABIES2
ABIETI
ABIET2
ABIET3
ACERS 1
ACHIHi
ACMAH1
ACMAS I
ACMAS2
ACMAT1
ACMAT2
True fir
True fir
True fir
True fir
True fir
True fir
Maple spp.
Yarrow
Big-leaf Maple
Big-leaf Maple
Big-leaf Maple
Big-leaf Maple
Big-leaf Maple
Herb layer
First shrub layer
Second shrub layer
First tree layer
Second tree layer
Third tree layer
First shrub layer
Herb layer
Herb layer
First shrub layer
Second shrub layer
First tree layer
Second tree layer
86
Appendix B (Continued)
ACMAT3
ALNUSI
ALNUS2
ALNUTI
ALNUT2
ALNUT3
AMALS2
ARCTHI
ARCTS1
ARCTS2
ARMES1
ARMES2
ARMETI
ARMET2
ARMET3
ARTRS2
BERBS2
CADEHI
CADESI
CADES2
CADETI
CADET2
CADET3
CASTHI
CASTS I
CASTS2
CASTT1
CASTT2
CEANHI
CEANSI
CEANS2
CHRYH1
CHRYSI
CHRYS2
COCOSI
COCOS2
COCOT2
CONUS1
CONUS2
CONUT2
CONUT3
Big-leaf Maple
Alder spp.
Alder spp.
Alder spp.
Alder spp.
Alder spp.
Serviceberry
Manzanita spp.
Manzanita spp.
Manzanita spp.
Pacific Madrone
Pacific Madrone
Pacific Madrone
Pacific Madrone
Pacific Madrone
Sagebrush
Oregon Grape
Incense Cedar
Incense Cedar
Incense Cedar
Incense Cedar
Incense Cedar
Incense Cedar
Chinquapin
Chinquapin
Chinquapin
Chinquapin
Chinquapin
Ceanothus spp.
Ceanothus spp.
Ceanothus spp.
Rabbitbrush
Rabbitbrush
Rabbitbrush
Western Hazel
Western Hazel
Western Hazel
Pacific Dogwood
Pacific Dogwood
Pacific Dogwood
Pacific Dogwood
Third tree layer
First shrub layer
Second shrub layer
First tree layer
Second tree layer
Third tree layer
Second shrub layer
Herb layer
First shrub layer
Second shrub layer
First shrub layer
Second shrub layer
First tree layer
Second tree layer
Third tree layer
Second shrub layer
Second shrub layer
Herb layer
First shrub layer
Second shrub layer
First tree layer
Second tree layer
Third tree layer
Herb layer
First shrub layer
Second tree layer
First tree layer
Second tree layer
Herb layer
First shrub layer
Second shrub layer
Herb layer
First shrub layer
Second shrub layer
First shrub layer
Second shrub layer
Second tree layer
First shrub layer
Second shrub layer
Second tree layer
Third tree layer
87
Appendix B (Continued)
CROPHI
EQUIS2
FERNS2
FORBH1
FRLAT2
GRASHI
GRDCHI
HARDT2
HERBHI
HODISI
HODIS2
HOLLS2
RUCKS2
JUNIS1
JUNIS2
JUNITI
JUNIT2
LEGUHI
LICHM1
LIDESI
LIDES2
LIDETI
LIDET2
LIDET3
LUPIHI
MOSSMI
NETTS2
PHEMS2
PILAS 1
PLLAS2
PILATI
PILAT2
PINUHI
PINUSi
PINUS2
PINUT1
PINUT2
PINUT3
Crop
Giant Horsetail
Fern spp.
Forb spp.
Oregon Ash
Grass spp.
Ground cover
Hardwood spp.
Herb spp.
Ocean Spray
Ocean Spray
Holly
Ribes spp.
Juniper spp.
Juniper spp.
Juniper spp.
Juniper spp.
Legume spp.
Lichen spp.
Tanoak
Tanoak
Tanoak
Tanoak
Tanoak
Lupine spp.
Moss spp.
Nettle
Poison Hemlock
Sugar Pine
Sugar Pine
Sugar Pine
Sugar Pine
Ponderosa Pine
Ponderosa Pine
Ponderosa Pine
Ponderosa Pine
Ponderosa Pine
Ponderosa Pine
Herb layer
Second shrub layer
Second shrub layer
Herb layer
Second tree layer
Herb layer
Herb layer
Second tree layer
Herb layer
First shrub layer
Second shrub layer
Second shrub layer
Second shrub layer
First shrub layer
Second shrub layer
First tree layer
Second tree layer
Herb layer
Moss layer
First shrub layer
Second shrub layer
First tree layer
Second tree layer
Third tree layer
Herb layer
Moss layer
Second shrub layer
Second shrub layer
First shrub layer
Second shrub layer
First tree layer
Second tree layer
Herb layer
First shrub layer
Second shrub layer
First tree layer
Second tree layer
Third tree layer
88
Appendix B (Continued)
POPUHI
POPUSI
POPUS2
POPUT 1
POPUT2
POPUT3
PRUNSI
PRUNS2
PRUNT2
PSMEH1
PSMES1
PSMES2
PSMET1
PSMET2
PSMET3
PUTRS1
PUTRS2
QUCHH1
QUCHS1
QUCHS2
QUCHT1
QUCHT2
QUCHT3
QUEDHI
QUEDS1
QUEDS2
QUEDTI
QUEDT2
QUEDT3
RHAMS1
RHAMS2
RIBESI
RIBES2
ROSASI
ROSAS2
RUBUSI
RUBUS2
RULEHI
RUPAS2
Populus spp.
Populus spp.
Populus spp.
Populus spp.
Populus spp.
Populus spp.
Cherry
Cherry
Cherry
Douglas Fir
Douglas FIR
Douglas Fir
Douglas Fir
Douglas Fir
Douglas Fir
Bitterbrush
Bitterbrush
Live Oak
Live Oak
Live Oak
Live Oak
Live Oak
Live Oak
Deciduous Oak
Deciduous Oak
Deciduous Oak
Deciduous Oak
Deciduous Oak
Deciduous Oak
Buckthorn
Buckthorn
Ribes spp.
Ribes spp.
Rose spp.
Rose spp.
Rubus spp.
Rubus spp.
Raspberry
Salmonberry
Herb layer
First shrub layer
Second shrub layer
First tree layer
Second tree layer
Third tree layer
First shrub layer
Second shrub layer
Second tree layer
Herb layer
First shrub layer
Second shrub layer
First tree layer
Second tree layer
Third tree layer
First shrub layer
Second shrub layer
Herb layer
First shrub layer
Second shrub layer
First tree layer
Second tree layer
Third tree layer
Herb layer
First shrub layer
Second shrub layer
First tree layer
Second tree layer
Third tree layer
First shrub layer
Second shrub layer
First shrub layer
Second shrub layer
First shrub layer
Second shrub layer
First shrub layer
Second shrub layer
Herb layer
Second shrub layer
89
Appendix B (Continued)
SALIHI
SALISI
SALIS2
SALITI
SALIT2
SALIT3
SAMIBSI
SAMBS2
SHRUHl
SHRUSI
SHRUS2
SHRUT2
SYMPHI
SYMPS1
SYMPS2
TODIHI
TODISI
TODIS2
TSUGH1
TSUGS1
TSUGS2
TSUGT1
TSUGT2
VETHS2
VINES2
Willow spp.
Willow spp.
Willow spp.
Willow spp.
Willow spp.
Willow spp.
Elderberry
Elderberry
Shrub spp.
Shrub spp.
Shrub spp.
Shrub spp.
Snowberry
Snowberry
Snowberry
Poison Oak
Poison Oak
Poison Oak
Mountain Hemlock
Mountain Hemlock
Mountain Hemlock
Mountain Hemlock
Mountain Hemlock
Mullen
Vine spp.
Herb layer
First shrub layer
Second shrub layer
First tree layer
Second tree layer
Third tree layer
First shrub layer
Second shrub layer
Herb layer
First shrub layer
Second shrub layer
Second tree layer
Herb layer
First shrub layer
Second shrub layer
Herb layer
First shrub layer
Second shrub layer
Herb layer
First shrub layer
Second shrub layer
First tree layer
Second tree layer
Second shrub layer
Second shrub layer
61 Station Late-seral Dataset
Variable Name
Definition
T1COV
Cover of the first tree sublayer
T2COV
Cover of the second tree sublayer
S1COV
Cover of the first shrub sublayer
S2COV
Cover of the second shrub sublayer
SIZE I
Density of trees with DBHs below 6 inches
SIZE2
Density of trees with DBHs between 6 and 11 inches
SIZE3
Density of trees with DBHs between 11 and 25 inches
SIZE4
Density of trees with DBHs between 25 and 40 inches
SIZE5
Density of trees with DBHs above 40 inches
SP
Station with tree canopy cover below 40%
NG
Station with tree canopy cover above 40%
Total Cover
Total cover values for all plant species