Assessment of nongame bird habitat using forest survey data

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J States
Uspartment of
Agriculture
Forest Service

Intermountain
Research Station

Research Paper
INT-431

October 1990

ssessment of Nongame
ird Habitat Using Forest
urvey Data

Renee A. O'Brien

THE AUTHOR

RENEE A. O’BRIEN is a range scientist in the Forest
Survey Research Work Unit, Intermountain Research
Station, Ogden, UT. She holds a B.S. degree in bot-
any from Weber State College, Ogden, UT, and B.S.
and M.S. degrees in range science from Utah State
University, Logan. She began her professional career
with the Forest Service in 1981 with the Intermountain
Station.

RESEARCH SUMMARY

Forest Survey data have potential for use in obtain-
ing information on the condition and diversity of the
Nation’s forest resources relevant to wildlife habitat
that is needed for planning and monitoring at State
and regional levels. In this study, Forest Survey data
were used to assess nongame bird habitat potential
based on food and shelter requirements on 24 plots.
These assessments were then evaluated using bird
numbers. Results of the analyses showed some cor-
relation of bird numbers with tree canopy variables,
and iliustrate the potential for using Forest Survey data
for wildlife habitat assessment, for identifying opportu-
nities to improve habitat through management, and for
predicting change in conditions over time.

Assessment of Nongame Bird
Habitat Using Forest Survey Data

Renee A. O’Brien

INTRODUCTION

Recent environmental concern has generated
much public pressure to protect and conserve the
Nation’s renewable natural resources. Necessary
for regionwide decisions is information on current
resource conditions. Wildlife habitat is one resource
of current interest that is an important element in
forest planning and management decisions. Infor-
mation on existing habitat conditions and predictive
capabilities about future conditions on a regionwide
scale is needed to allow evaluation of resource
tradeoffs involved in management decisions. Forest
inventory data may offer opportunity as an efficient
way to streamline the task of wildlife resource
monitoring.

To meet the requirements for National assess-
ments mandated by the Forest and Rangeland Re-
newable Resources Planning Act of 1974 and other
legislation, forest resource inventories are con-
ducted on public and private lands by Forest Sur-
vey, Forest Service, U.S. Department of Agriculture.
Forest Survey projects are located throughout the
continental United States and Alaska and are some
of the most comprehensive, permanent plot invento-
ries in the country. They provide permanent base-
line data for most forested land, including most pri-
vate, State, Bureau of Land Management of the
U.S. Department of the Interior, and Indian lands;
and excluding some National Forest lands in the
West. The inventory procedures for the various
Survey projects produce standardized timber statis-
tics, with some regional differences in the scope and
details of the inventories.

The Forest Survey data base has the potential to
provide information on forest conditions relevant to
wildlife populations and on change in these condi-
tions over time (O’Brien and Van Hooser 1983). At
the regional level at which Forest Survey operates,
some efforts have been made in the area of wildlife
habitat assessment by Brooks (1986) in the North-
east, Flather and others (1989) in the South,
Ohmann (1983) in the Pacific Northwest, Rudis
(1988) in the South, and Sheffield (1981) in the
Southeast. This paper focuses on the ponderosa
pine forests of Arizona.

Forest Survey variables that could be useful for
assessment of potential wildlife habitat are:

Forest type Aspect Evidence of use
Basal area Slope Distance to roads
No. trees per acre Habitat type Fire history

Site index Percent crown cover Logging history

Quadratic mean Species composition Understory cover
diameter Size of condition and height
Stand-size class Vegetation Insect and disease
Tree height concealment evidence
Elevation
THE PROBLEM

Evaluating wildlife habitat is complex. Wildlife
managers have made use of general timber stand
variables such as forest type, stand-size class, age,
canopy cover, and other stand features to predict
potential wildlife use of a site for feeding, breeding,
or resting. Specific habitat suitability models are
being developed for predicting occurrence and quan-
tifying value of potential habitat for some wildlife
species. Most models are designed to provide site-
specific comparisons and are not applicable to exten-
sive forest inventory data. Forest Surveys operate
at a much broader level than most research model-
ing being done for wildlife habitat evaluation.

This paper evaluates Forest Survey plot data for
potential nongame bird habitat. General habitat
criteria on food and shelter from the literature were
used for habitat assessment. These habitat assess-
ments were then evaluated using bird numbers col-
lected on the same plots.

The birds chosen for this study were secondary
cavity-nesting foliage-gleaners and bark-gleaners
(subsequently referred to as cavity-nesting glean-
ers). These birds are important for several reasons.
They are sensitive to timber management practices
because they use old and dying trees for nesting
(Balda 1969, 1975; Cunningham and others 1980;
Diem and Zeveloff 1980; Medin 1985; Owens 1983;
Sturman 1968; Szaro and Balda 1979) and because
they forage in tree canopies. They are conspicuous,
in many places common, and their diets consist of
75 to 90 percent insects (Bent 1946, 1948; Scott and
Patton 1975), making them important for insect

population control (Thomas and others 1979). Five
species of cavity-nesting gleaners found in the study
area are the pygmy nuthatch (Sitta pygmaea),
white-breasted nuthatch (Sitta carolinensis), moun-
tain chickadee (Parus gambeli), house wren (Troglo-
dytes aedon), and brown creeper (Certhia ameri-
cana).

The main food and shelter variables chosen for
evaluating cavity-nesting gleaner habitat are foliage
volume and snag density. Foliage volume is impor-
tant due to its relationship to the food supply. The
relationship between gleaners and foliage volume is
well documented by studies done in the coniferous
forests of Arizona by Balda (1969) and Szaro and
Balda (1979). Szaro and Balda (1979) reported that
gleaners exhibited a positive correlation with in-
creasing foliage volume across five study sites.
Medin (1985) reported that among five recognized
foraging guilds, gleaners were less numerous on
logged plots where foliage volume had been reduced.
Foliage volume also represents a number of impor-
tant niche dimensions other than food quantity,
including quality and quantity of perches, and shel-
ter from weather and predators—all important
characteristics for survival.

For this study, snags were defined as standing
dead trees greater than 1.2 m tall. Snag abundance
is assumed to be related to the reproduction of
cavity-nesters because they prefer these types of
trees in which to excavate holes for nesting. Recom-
mendations for snag size and densities in ponderosa
pine forests are documented by Cunningham and
others (1980). Snags are also preferred foraging
strata for insectivorous birds (Szaro and Balda
1979). Balda (1975) found that snags were used
intensively throughout the season relative to their
availability. Kendeigh (1944) and Moore (1945) also
provide evidence that snag use is not limited to the
breeding season. For these reasons snags were in-
cluded, even though this was not a breeding season
study.

Other habitat variables included in the study
were woody understory cover and time since

logging.

STUDY AREAS

This study was conducted at two locations in the
ponderosa pine zone of the northwestern corner of
Arizona, which is separated from the rest of the
State by the Colorado River. The area is commonly
referred to as the Arizona strip. Study area 1 was
on the Kaibab Plateau and will subsequently be
referred to as Kaibab. Study area 2, just south of
Mount Trumbull, will be referred to as Trumbull.
It is approximately 80 km southwest of Kaibab. The
ponderosa pine zone occurs from 2,074 to 2,501 m
elevation.

Kaibab includes the Pinus ponderosa/ Poa
longiligula community type and the Pinus
ponderosa /Bouteloua gracilis habitat type (Hanks
and others 1983). Kaibab is intensively managed
for timber. All stands have been thinned to some
extent, and the whole area is heavily used by hunt-
ers and tourists. Trumbull includes only the Pinus
ponderosa/Bouteloua gracilis habitat type. Plants
common to both areas are Gambel oak (Quercus
gambelii), New Mexican locust (Robinia neomexi-
cana), cliffrose (Cowania stansburiana), mountain
muhley (Muhlenbergia montana), blue grama
(Bouteloua gracilis), and Indian ricegrass (Oryzopsis
hymenoides). Trumbull is a more remote and less
intensively managed area. There were greater con-
trasts of forest conditions at Trumbull, including
more thickets and more overstocked stands. There
was a larger component of oak understory at Trum-
bull than at Kaibab.

METHODS

The study was conducted in conjunction with the
Forest Survey field inventory of Arizona. Twelve
plots were sampled for bird numbers at each study
area during July and August 1985. Included were
actual Forest Survey plots and some supplemental
plots added to provide a variety of tree height and
canopy cover conditions in order to encompass a
wide range of food availability. Five bird counting
points approximately 120 m apart were established
around each Forest Survey plot (fig. 1), in similar
forest conditions. The area sampled for birds at
each plot was roughly 6 ha. Birds were counted
using the point sampling procedure recommended
by Verner and Ritter (1985). Counts were made at
each point on two separate days, within 1 hour of
sunrise, based on the findings of Robbins (1981).
Ten minutes were spent at each of the five points
where the number and species of birds were de-
tected and recorded. Detection and identification
were based on sightings and calls. Two counts per
point, five points per plot, and 12 plots per study
area totaled 120 counts at each study area, fora
total of 240 counts between Kaibab and Trumbull.

Timber inventory variables were collected accord-
ing to standard Intermountain Forest Survey inven-
tory procedures (USDA FS 1985) by Forest Survey
field crews. The Intermountain Forest Survey uses
five variable-radius point samples to sample a 0.4-
ha plot (fig. 1). Because points are sampled propor-
tional to basal area, exact snag counts for a fixed
area are unavailable. In addition to Forest Survey
snag counts, every snag 10.2 cm diameter at breast
height (d.b.h.) or larger within 60 m of each bird
sampling point was recorded. The relationship
between snag densities obtained with a

BIRD PLOT

CRAY

FOREST SURVEY PLOT

Figure 1—A representation of one study plot
including Forest Survey plot and bird point
configuration.

variable-radius point sample compared to total
fixed-area snag counts is the subject of a separate
study and will not be addressed here.

Forest Survey does not measure foliage volume
directly. Crown volume was estimated from the
Forest Survey data base using measurements of
tree height, crown ratio, minimum and maximum
crown widths, and crown shape. Foliage volume
was then estimated by discounting the crown vol-
ume estimates to bring them in line with other esti-
mates reported in the literature for ponderosa pine
forests (Cunningham and others 1980). These foli-
age volume estimates represented the relative foli-
age volume differences between the plots and made
it possible to separate other tree foliage volume
from ponderosa pine foliage volume. Cunningham
and others (1980) found that bird use of foliage may
be better explained if foliage volume is partitioned
into ponderosa pine and other tree volume.

Foliage volume was also estimated using an index
of food availability developed by Schroeder (1983) as
part of a Habitat Suitability Index (HSI) model for
assessing potential habitat of the black-capped
chickadee (Parus atricapillus)—another cavity-
nesting gleaner species. This index is an assess-
ment of food availability (the term “availability” was
substituted for “suitability” in this paper) computed
from a measure of average height of overstory trees
and tree canopy closure. These variables are each
assigned a rating, then combined in an equation
(fig. 2) to arrive at an overall food availability rank-
ing between 0 and 1.0.

Food Availability Index = (CI * HI)"

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Percent Cover

Average Height of Overstory (m)

Figure 2—Overall food availability index
equation with individual cover and height
indices (Schroeder 1983).

Simple correlation and simple and multiple re-
gression were used to analyze the relationships be-
tween bird species numbers and the independent
habitat variables: average height of tallest trees,
crown canopy cover, snag density, foliage volume
(ponderosa pine and other), the index of food availa-
bility, woody understory vegetation cover, and time
since logging. The Spearman test for correlation
(SAS 1982) was used because it was assumed that
the precision of bird counts was low and because the
relationship between variables might not be linear.

RESULTS

The relationship between bird numbers and habi-
tat variables varied depending on study area. Total
numbers of the five species of cavity-nesting glean-
ers were three times more abundant at Trumbull

(199) as at Kaibab (65) for sites with similar foliage
volume and snag density. There were more than six
times the number of white-breasted nuthatches at
Trumbull than at Kaibab. This supports one obser-
vation made by Cunningham and others (1980) of a
positive correlation between white-breasted nut-
hatches and Gambel oak. No brown creepers were
observed on any of the locations.

Table 1 presents a summary of bird numbers and
canopy-related habitat variables. Trumbull plots
had slightly higher mean canopy cover and food
availability, similar mean height and foliage vol-
ume, and fewer snags than Kaibab plots.

Spearman correlation coefficients (r) were com-
puted between bird numbers and all habitat vari-
ables for the two study areas separately and com-
bined and are presented in table 2. Correlation
coefficients between bird numbers and habitat

Table 1—Summary of average number of birds and habitat variables per plot

Average Ponderosa Other Number
White Mountain Pygmy Crown height pine tree Woody snags Food
Location breasted chicka- House nut- Total canopy tallest foliage foliage understory >10.2 availability
number nuthatch dee wren hatch guild cover trees volume volume cover cm/ha index
<3 oe eee eee -- Number --------------- Percent = ™m ------9nP/ha----- Percent
Study area 1 (Kaibab)
01 1.0 0.5 0.5 0 2.0 51 28 60,864 0 9 1.3 1.00
02 1.0 5 ) 0 1.5 57 26 16,661 4,318 12 1.3 1.00
03 0) 0 0 3.5 3.5 37 27 59,519 0 0 3 84
04 5 25 0 0 3.0 21 29 36,641 0 0 aA 63
05 5 2.0 0 0 2.5 46 10 25,964 0 1 3 79
06 5 6.0 0 0 6.5 42 16 15,055 4,586 29 2 .89
07 0 0) 0 0 0) 35 22 35,289 1,229 24 5 84
08 1.5 5.5 0 0 7.0 16 13 11,495° 5,796 29 3 52
09 5 2.0 2.0 6.5 11.0 49 28 35,226 0 9 2.3 1.00
10 1.5 3.0 1.5 8.0 14.0 81 30 89,253 0 6 3.2 95
11 0 0 0 0 65 16 59,004 0 0 8 1.00
12 1.0 13.0 0 0 14.0 20 15 8,582 6,578 50 3 63
Mean Ao 2.9 3 1.5 5.4 43 22 37,796 1,876 14 1.0 84
Study area 2 (Trumbull)
13 0 6.5 0 6.5 13.0 23 21 34,425 0 11 0 71
14 6.5 10.0 0 3.5 20.0 54 21 34,650 7,272 35 3 1.00
15 45 10.5 0 9.5 24.5 54 21 63,079 1,445 1 2 1.00
16 5 3.0 0) 1.0 45 75 18 15,998 9,689 0 2 1.00
17 4.0 7.0 0) KS 18.5 58 14 60,232 4,529 6 0) 95
18 5.0 45 1.0 5.5 16.0 80 27 53,987 1,222 0 3 95
19 7.0 6.5 0) 14.5 28.0 48 26 64,622 9,137 11 15 1.00
20 4.5 Lo 0 10.5 22.5 50 23 37,752 4,358 17 1.2 1.00
21 0) 0 0 0) 0 5 13 8,408 0 14 3 .30
22 5 2.0 0 3.0 5.5 38 23 12,894 0 16 2 89
23 8.0 3.5 0 9.0 20.5 59 27 63,423 1,697 2 5 1.00
24 6.0 12.5 0 7.5 26.0 58 16 20,308 382 4 0 1.00
Mean 3.9 6.1 1 6.5 16.6 50 21 39,148 3,311 10 4 90

Table 2—Spearman correlation coefficients (1) for bird numbers compared with habitat variables; study areas separate and

combined
Average Ponderosa Other Number
Crown height pine tree Woody snags Food
canopy tallest foliage foliage understory >10.2 availability
cover trees volume volume cover cm/ha index
Percent M — -------- me/ha------- Percent
Study area 1 (Kaibab)
White—breasted nuthatch 0.03 0.07 -0.21 0.35 0.46 0.24 —0.13
Mountain chickadee —.37 -.18 —.56 53 56 —.29 —.48
House wren 51 .64 .48 -.46 —.08 174 53
Pygmy nuthatch 37 59 49 —.46 -.31 47 .28
Total birds —.23 ont —.23 .23 xyes —.06 —.32
Study area 2 (Trumbull)
White-breasted nuthatch .46 56 170 .46 -.10 51 V3
Mountain chickadee BIW —.11 38 .22 .05 —.21 56
House wren .48 44 ens) -—.13 —.44 13 —.20
Pygmy nuthatch .06 42 182 .30 -.04 32 55
Total birds A5 31 76 32 -.01 .26 72
All locations
White—breasted nuthatch .47 5 of 153 .07 .08 151
Mountain chickadee al -.23 .00 158 27 —.40 16
House wren OT. 158 34 —.36 -.18 48 .20
Pygmy nuthatch 44 .32 160 16 -.18 -.01 150
Total birds 31 .08 .34 45 .07 —.18 38
'P $0.01.

variables produced some significant positive rela-
tionships. Pygmy nuthatch exhibited significant
positive correlations (r = 0.82 and 0.60) (P < 0.01)
with ponderosa pine foliage volume at Trumbull and
both study areas combined. House wren exhibited
significant positive correlation with the average
height of the tallest trees on both study areas com-
bined (r = 0.58). White-breasted nuthatch exhibited
a significant positive correlation with ponderosa
pine volume at Trumbull (r = 0.70), as did the four
species combined (r = 0.71). At all locations com-
bined, white-breasted nuthatch and mountain
chickadee had significant positive correlations

(r = 0.53 and r = 0.58) with other tree volume, which
included pinyon, juniper, and tree-form Gambel oak.
Significant positive correlations were exhibited with
the index of food availability by white-breasted nut-
hatch at Trumbull and the combined study areas

(r = 0.73 and r = 0.51), by pygmy nuthatch on the
combined study areas (r = 0.50), and by the four
species total at Trumbull (r = 0.72). These patterns,
similar to what Diem and Zeveloff (1980) and
Cunningham and others (1980) reported, were more

evident at Trumbull or at all locations combined
than at Kaibab.

There was little correlation between bird numbers
and snag densities, woody understory vegetation
cover, or time since logging on either study area,
except at Kaibab, where house wren had a signifi-
cant positive correlation with snag density. Regres-
sion analyses performed combining the habitat vari-
ables yielded little improvement.

DISCUSSION

Results of this study illustrate the potential asso-
ciated with using Forest Survey data for the assess-
ment of wildlife habitat. Results of the analyses
showed some correlation of bird numbers with the
interrelated tree vanopy variables: total foliage vol-
ume, ponderosa pine volume, other tree volume, and
the index of food availability. These findings indi-
cate that general foliage volume estimates or indices
can be used to indicate relative habitat suitability.

The food availability index is a good ordered vari-
able (Spearman correlation test) and is sensitive to

food availability reduction at high-canopy closure
levels (fig. 2). This index of food availability is more
easily obtained than foliage volume and appears to
be as useful an indicator of food availability for
gleaners.

This study also illustrates the problems associated
with using Forest Survey data for potential wildlife
habitat assessment. One problem is in using vari-
able-radius plots that sample trees proportional to
basal area to get information on snags for wildlife.
A study is under way to compare snag information
obtained with variable-radius plots to actual snag
counts.

Habitat variables were tested by comparing differ-
ences in bird use of different foliage volume and
snag density conditions. However, differences due
to study area overshadowed any differences within
study area. The threefold increase in bird numbers
from Kaibab to Trumbull can possibly be explained
by the greater diversity, patchiness, and layering of
the vegetation, the importance of which was re-
ported by Langelier and Garton (1986). Reduced
numbers of gleaners at Kaibab support the findings
of Medin (1985) that gleaners are less numerous on
logged plots where foliage volume has been reduced.

The difference due to study area was observable
but was difficult to detect using Forest Survey
methodology, except that Trumbull plots had
slightly higher mean canopy cover and food availa-
bility than Kaibab plots. There are two possible
reasons. First, a subset of Forest Survey plots were
selected and supplemental plots were located to
provide a wide range of foliage and snag conditions
for this study, thus overriding the inherent differ-
ences in the study areas. Second, analysis of addi-
tional Forest Survey plot data indicated that both
sites have similar percentages of plots on which
evidence of logging, occurrence of thickets, and mul-
tiple vegetation layers were reported. Forest
Survey data are somewhat insensitive to subtle dif-
ferences in vegetation structure and distribution,
due to the general nature of the variables measured.
The difference between areas was related to details
of horizontal and vertical distribution of the vegeta-
tion to which the birds were apparently more at-
tuned but which would require much more detailed,
time-consuming methodology to identify.

There are problems with using animal numbers
to assess habitat suitability. Van Horne (1983)
reported that density may sometimes be a mislead-
ing indicator of habitat quality. Density may reflect
temporary or recent conditions rather than long-
term conditions, social dominance may induce high
densities in poor habitats, and censuses may be
obtained in noncritical seasons. Diem and Zeveloff
(1980) found that the movements of birds can reflect

local perturbations that may be temporary re-
sponses to short-term environmental factors and
that are impossible to monitor. Therefore, high
correlation should not be expected when comparing
habitat suitability to bird numbers.

Lack of a high degree of correlation between bird
numbers and habitat variables does not mean that
the other variables included in the study would not
be useful indicators of wildlife habitat potential.
Even though the value of snags was not demon-
strated in this nonbreeding season study, the impor-
tance of snags for cavity-nesting birds and other
animals in general is well known (Thomas and
others 1979). Recent publications emphasize snag
management and Forest Service guidelines for
retention of snags (Langelier and Garton 1986;
Morrison and others 1986). A survey of snag densi-
ties on other northern Arizona Forest Survey plots
indicates that snag densities are rarely at recom-
mended levels. None of the sites in this study con-
tained recommended (Cunningham and others
1980) snag densities. Morrison and others (1986)
concluded that current guidelines for large snag
retention are appropriate, but even under snag
management strategies, recommended densities are
not being met. Although snag densities alone will
probably not be a useful indicator of abundance of
many bird species, general information on snags
from statewide inventories would be useful for
monitoring snag densities and, consequently, habi-
tat potential, on all forest lands.

SUMMARY

Forest Survey projects throughout the country
collect and maintain statewide multiresource data
bases that may be useful for assessing and monitor-
ing elements of wildlife habitat or trends over time
in general forest conditions that have relevance for
wildlife populations. One problem is that Forest
Survey data are primarily collected to generate re-
gional timber resource statistics, whereas most
wildlife habitat research is done on a site-specific
level. However, the State and regional level at
which Forest Survey operates is also the level at
which important information on the condition and
diversity of the Nation’s resources must be moni-
tored and at which program funding takes place.

This study involving bird numbers illuminated
some of the problems involved in habitat assess-
ment. It also provided some evidence that Forest
Survey data could be used as a starting point in
identifying key issues or problem areas that need
more site-specific studies. There is potential to use
Forest Survey data to assess the capacity of the
forests of an area to support insectivores or cavity-

nesters and to identify opportunities to improve
wildlife habitat through timber management. Inter-
mountain Forest Survey is investigating other ways
of monitoring change in forest conditions on a state-
wide basis that could have relevance for wildlife and
other forest resources.

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juniper woodland and ponderosa pine forest in
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Forest Survey data were used to assess nongame bird habitat potential based on
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wildlife habitat assessment.

KEYWORDS: foliage volume, forest inventory, wildlife habitat assessment

INTERMOUNTAIN
RESEARCH STATION

The Intermountain Research Station provides scientific knowledge and technology to im-
prove management, protection, and use of the forests and rangelands of the Intermountain
West. Research is designed to meet the needs of National Forest managers, Federal and
State agencies, industry, academic institutions, public and private organizations, and individu-
als. Results of research are made available through publications, symposia, workshops,
training sessions, and personal contacts.

The Intermountain Research Station territory includes Montana, Idaho, Utah, Nevada, and
western Wyoming. Eighty-five percent of the lands in the Station area, about 231 million
acres, are classified as forest or rangeland. They include grasslands, deserts, shrublands,
alpine areas, and forests. They provide fiber for forest industries, minerals and fossil fuels for
energy and industrial development, water for domestic and industrial consumption, forage for
livestock and wildlife, and recreation opportunities for millions of visitors.

Several Station units conduct research in additional western States, or have missions that
are national or international in scope.

Station laboratories are located in:

Boise, Idaho

Bozeman, Montana (in cooperation with Montana State University)

Logan, Utah (in cooperation with Utah State University)

Missoula, Montana (in cooperation with the University of Montana)

Moscow, Idaho (in cooperation with the University of Idaho)

Ogden, Utah

Provo, Utah (in cooperation with Brigham Young University)

Reno, Nevada (in cooperation with the University of Nevada)

USDA policy prohibits discrimination because of race, color, national origin, sex, age, reli-
gion, or handicapping condition. Any person who believes he or she has been discriminated

against in any USDA-related activity should immediately contact the Secretary of Agriculture,
Washington, DC 20250.