between the two sample years. We did not evaluate observer
bias directly because it is evaluated and discussed elsewhere
in this volume (see Manuwal, Gilbert and Allwine b, and
Carey and others). Potential effects of sampling biases on the
results are evaluated in the discussion.
Table W-values for 3 planned comparisons
when limiting experimental error rates to 5,
10, 15, and 20 percent
Analytical Methods
5
10
15
20
This study was designed to be exploratory, thus no a priori
hypotheses were identified. In light of this objective, the
statistical tests were used to elucidate trends and consistent
patterns of variation in the data rather than for testing specific hypotheses. We report exact P-values to evaluate the
strength of the patterns, except where we needed to define a
level of significance to proceed with further analyses. The
exceptions were using a P-value of <O.05 to indicate a significant main effect or an interaction between main effects
of two-way analysis of variance before we proceeded with
appropriate planned comparisons, and using a P-value of
<0.151 with the Kruskal-Wallis procedure to identify which
bird species showed strong differences in abundance among
forest age-classes in at least two of the three provinces.
Bird abundance was calculated as the number of birds detected per survey per stand for each of the two sample years,
where one survey day equals 12 counting stations x 8 minutes. We calculated species richness as the number of unique
species detected in a stand over all surveys during one year.
Only detections estimated to be < 50 m from the counting
station were used. Nocturnal and raptor species were poorly
sampled by the counting technique and were not included in
the analysis. To remove vagrants and species detected in few
stands, we used two criteria: a species was included in the
count for a particular stand if it was detected during at least
two surveys in that stand, and, to be included, a species had
to be detected in >8 percent of the stands within a subprovince. Thus, rare species (that is, species detected in low numbers) were included in the analysis if detection criteria were
met at the stand and subprovince level. This procedure removed species that commonly occurred in habitats substantially different from ones dominated by Douglas-fir (for example, red-winged blackbird, northern oriole, belted kingfisher, mourning dove). We did not distinguish between hermit
and Townsend’s warblers (hereafter, hermit warbler) or between dusky and Hammond’s flycatchers (hereafter, Empidonax flycatchers) during our analyses because these species
were difficult to distinguish in the field.
Because our primary objective was to evaluate regional
patterns of species composition and abundance, and not
yearly variation, we used the mean of the two sample years
in our analysis. Thus, mean bird species richness and mean
abundance values represent the average of two sample years.
Mean abundance values were calculated for individual bird
Experimental error
rate (percent)
P-value for 3
planned comparisons’
0.017
.035
.053
.072
a
a' = l- (1-a)l/K, where a’ = significance level of each
individual comparison for an experimental error rate of a,
and K = the number of comparisons (Sokal and Rohlf 1981).
species, all species combined, all resident species, all migrant
species, and for each of four spatial-foraging guilds: bark,
aerial, canopy, and understory foragers (see appendix table 8
for list of species associated with each group).
Province and age comparisons-To evaluate whether bird
abundance or number of species differed among forest ageclasses, species richness values and mean abundance values
for all species combined, residents, migrants, and the four
foraging guilds were analyzed by a two-way analysis of
variance (ANOVA) for unbalanced designs (Wilkinson 1988).
For all ANOVA’s, stand age (that is, young, mature, oldgrowth) and province (that is, southern Washington Cascades,
Oregon Cascades, Oregon Coast Ranges) were used as the
independent factors (the main effects). Normality and homogeneity of variance of richness and abundance values were
improved by performing a square-root transformation before
the ANOVA.
Multiple comparisons were planned; thus, we used F-tests to
determine differences among age-classes and among provinces (Sokal and Rohlf 1981). Because the planned comparisons were nonorthogonal (that is, lacked independence), we
used the Bonferroni procedure (Klockars and Sax 1986,
Wilkinson 1988) to reduce the probability of interpreting a
difference as related to ages and provinces when in fact the
patterns were a result of random variation. Given that the
interaction between the main effects was not significant, we
tested three planned comparisons per main effect (Sokal and
Rohlf 1981). Instead of setting a specific experimental error
at 5 percent, for example, we reported the exact P-value for
each comparison, and provide a list of what the acceptable
P-values are for experimental errors of 5, 10, and 15 percent
(table 3).
Abundance patterns of individual bird species-Species
were categorized into four groups based on general knowledge of territory size, percentage of all detections that were
< 50 m versus >50 m from the counting station, and consistency of detection within a stand (see appendix table 8).
181
Group 1 species were detected more often 150 m of a counting station and, typically, were the ones detected most consistently and often on the surveys. To determine their abundance, we used all detections 150 m from a counting station,
the same criteria used for calculating abundance throughout
this study. Species included in groups 2 and 3 were detected
more often >50 m from a counting station and detected less
often than group 1 species. Group 3 species were more difficult to detect than group 2 species. Group 3 species have
large territories and were detected less consistently within a
stand. If single occurrences accounted for >30 percent of the
stands in which a species was detected, then that species was
put in group 3. Detections < 150 m from a counting station
were used for calculating abundance of both group 2 and 3
species. Group 2 species had to be detected > 2 times within
a stand but group 3 species only once. If a species was detected in <3 percent of the stand counts, it was placed into group
4 and no abundance was calculated. We gauged our interpretation of the results according to the reliability of the count
data. We assumed group 1 was the most reliable abundance
data and group 3 the least.
Within each province, mean abundance of individual species
was compared between stand age-classes by the KruskalWallis procedure. Experimental error rates were evaluated by
comparing the number of significant comparisons to the total
number of comparisons made. Of all the species evaluated,
16 had P-values that were <0.151 in at least two of the three
provinces. Because of their strong trends among forest ageclasses, these species were discussed in further detail.
Ordination of bird data-We used detrended correspondence analysis (DECORANA or DCA), an ordination procedure, to describe differences in bird communities of the
sampled stands. DECORANA uses species composition and
abundance data to determine a sample’s position in relation
to all other samples (Gauch 1982, Hill 1979a). Thus, samples
(that is, stands) that are similar are close together and dissimilar samples are far apart To simplify interpretation, we
removed the effects of abundance differences between stands
and provinces by relativizing the data, so that species abundances totaled 100 in each stand (Mohler 1987). We plotted
the position of each stand using DECORANA scores for
the first and second axes, where the scores represented the
position of a stand along some identifiable environmental
gradients (that is, each axis represents an environmental gradient). Median scores for age-class and province categories
were calculated, and the position of each age-class and province category was plotted such that the boundaries included
at least 90 percent of the stands. Spearman rank (rs) correlations and scatterplots were used to evaluate relations between all DECORANA scores for the first and second axes,
and environmental (elevation, latitude, stand age) as well as
biological (species richness, bird abundances) variables.
182
Relation to habitat-Of the vegetation and site characteris-
tic variables measured by Spies, we selected 143 as potentially important to our analysis. Variables selected included
58 live-tree, 13 stand-condition, 32 snag, 25 log, and 15
understory-plant variables (see appendix table 9). Each variable was tested for normality by the Kolmogorov-Smimov test
(Zar 1984), and, if necessary and useful, transformations were
applied. No one transformation worked well on all variables;
thus, we used three: log (X + l), square root (X + 0.375),
and arcsine (square root X) on some of the percentage variables (see appendix table 9).
We used all possible subsets multiple regression (Dixon
1985) to evaluate which vegetation variables explained the
most variation in species richness, total bird abundance, abundance of resident and migrant species, and abundance of each
of the four foraging guilds. The analysis was approached
from two levels. Multiple regressions were performed using
data from all three provinces together, and then on each
province individually. Pearson correlations of vegetation and
bird abundance variables were done as a first step before
regression analysis. This analysis determined which variables
were most associated with bird abundance; variable selection
was based on strength of the correlations with dependent
variables; and the correlations were generally low so that any
variable with an absolute value >0.200 was considered; low
intercorrelations with other vegetation variables; and ease of
measurement and applicability to management decisions.
Vegetation variables that were intercorrelated but were highly
correlated with the dependent variable were not removed at
this stage because of their potential importance to the total
equation. No intercorrelated variables were selected in the
final regression equations.
The ‘best’ multiple regression equation was selected from all
possible subsets by evaluating which group of variables explained the most variance (adjusted R ), low inter-correlation
among vegetation variables, and ease of interpretation. The
number of independent variables in an equation (see Johnson
1981) was limited to no more than four for the withinprovince regressions, and no more than six for the all-stands
regressions.
Results
Over 115,000 birds were detected during more than 16,000
station counts in the three physiographic provinces. Ninetythree bird species were detected. We detected 41 species that
regularly used’ Douglas-fir forests >40 years old, after the
1
This term refers to the analysis criteria established for this study:
bird species within a province detected < 50 m from a counting station
on > 2 sample days per stand in >3 stands (>8 percent).
q = Oregon cbast Range
0 = Oregon Cascade
flange
A = Southern
Washington
Cascade
•1= Oregon coast Range
0 = Oregon Cascade Range
* = Southern Washington
Cascade
Range
Range
8
z
‘0
exclusion of raptorial, nocturnal, and poorly detectedspecies.
Of these41 species,56 percent regularly used all three pmvinces, and 73 percent regularly used two provinces. Six speties regularly used only the Oregon CoastRange: the blackcapped chickadee, wrentit, purple fiich, rufous-sided towhee,
song sparrow, and orange-crownedwarbler. The Townsend’s
solitaire regularly used only the Oregon Cascades.The red
crossbill and Vaux’s swift regularly used only the southern
Washington Cascades.
Elevation, Latitude, and Longitude
Stand elevation varied with latitade and longitude within and
between provinces (fig. 1). Study standslow and high in elevation tended to be in the Oregon Coast Rangesand Oregon
Cascades,respectively. Total bird abundancewas correlated
negatively with elevation and latitude and correlated positively with longitude (fig. 2).
42.543.043.544.044.545.045.546.045.547.0
Latitude
Table 4-The percentage of young, mature, and old-growth stands in which 16 specieswere detected that showed abundance
differences in at least 2 of the 3 provinces
_1___
Table S-Number and percentage (in parentheses) of
bird specieswith significantly different abundances
among age-claws at P-values of 0.05, 0.10, 0.15, and
0.20
0.05
0.10
0.15
0.20
Total numberof
species”
7 (21%)
9 (27%)
14(42%)
16(48%)
33
5 (15%)
7 (21%)
9 (26%)
11 (32%)
34
Abundance Patterns of Individual
18 (51%)
20 (57%)
26 (74%)
26 (74%)
35
Bird Species
Chestnut-backedchickadeesand hermit warblers, detectedin
all 132 study stands,and winter wrens, western flycatchers,
and golden-crowned kinglets, detectedin >95 percent of the
study stands,were the most abundant speciesover all three
provinces (table 4).
184
‘omg
ll&gl-OW
50
90
tco
80
lco
100
90
5
103
102
95
100
100
100
80
100
70
1ca
80
53
95
84
95
84
80
60
0
40
84
84
58
1w
Bird abundancedifferences among stand age-classeswere
detectedfor 29 speciesat P 5 0.151. Twice as many species
had differences in abundanceat P < 0.050 among stand
age-classesin the Oregon Coast Rangesthan in the southern
Washington Cascadesor Oregon Cascades(table 5).
Sixteen speciesshowed abundancedifferences in at least two
of the three provinces at P < 0.151 (figs. 3-5, table 4). yet
despite the large sample size, pauems were not similar for
any speciesin all three provinces. Abundance of all sixteen
species,except Vaux’s swift, showed age-classdifferences in
the Oregon CoastRanges. Six hole nesters-the chestnutbacked chickadee,red-breastednuthatch, hairy woodpecker,
pileated woodpecker,red-breastedsapsucker,and Vaux’s
swift-were most abundant in old-growth standsin at least
two provinces (figs. 3-5). Brown creeperabundancewas
highest in old-growth and mature stands (fig. 3). but western
flycatcher (fig. 3) and hermit thrush (fig. 4) were most abundant in old-growth and young stands. Black-throated gray and
hermit warblers tended to be most abundant in young stands
(fig. 3). Evening grosbeakand American robin abundance
was highest in young and mature.stands (fig. 4). No clear
pattern was observed for gray jay, Steller’s jay, and northern
flicker (figs. 3-5). Abundance of only the red-breasted
sapsuckerdiffered in all three provinces at P < 0.151 (fig. 5).
Black-throated
gray warbler
I.:...-..:
IL- I 1
Chestnut-backed
chickadee
185
Steller’s jay
Evening grosbeak
r
.;-;”
Hairy woodpecker
Northern flicker
7
Province and Age Comparisons
Interaction and main effectsNo province x age interaction effects were detectedin the eight two-way ANOVA
tests at P < 0.146. except for the comparison of migrant
species(P = 0.060) (figs. 6-13). The main effect of province
was different in all ANOVA testsat P < 0.010. Only half the
tests on stand age-namely, total abundanceand abundance
of resident species,bark foragers. and aerial foragers-were
different at P < 0.050 (figs. 6-13). All other stand age cornpafisons were different at P > 0.250.
Pairwise comparisons of provinc+All
multiple painvise
comparisonsof mean abundanceand speciesrichness were
higher in the Oregon CoastRanges than in the Oregon and
southern Washington Cascadesat P < 0.050 (figs. 6.13).Bird abundancewas generally higher in the Oregon than
southern Washington Cascades,except for resident species
and understory foragers, which were more abundant in the
southernWashington Cascades,and bark foragers. whose
abundancedid not differ between the two provinces (figs. 613).
Pairwise comparisons of stand ageStand-age pairwise
comparisonsshowed that total abundanceand abundanceof
resident speciesand bark foragers were highest in old-growth
stands(figs. 7,8, 10). Abundance of aerial foragers was
highest in young and old-growth stands(fig. 11). The only
substantial and consistent increase with stand age-classwas
the abundanceof bark foragers (fig. 10). In six of the eight
ANOVA comparisons,mean abundanceand richness were
lowest in mature stands(figs. 6-13). No comparisonswere
lowest in old growth.
B
188
r
‘t
189
B
i
,,I
tzCR
oc
SW
c
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