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.

Analytical Methods

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

Table W-values for 3 planned comparisons

when limiting experimental error rates to 5,

10, 15, and 20 percent

Experimental error P-value for 3

rate (percent) planned comparisons’

5 0.017

10 .035

15 .053

20 .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.

Relation to habitat-Of the vegetation and site characteristic 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).

182
q = Oregon cbast Range 

0 = Oregon Cascade flange 

A = Southern Washington Cascade Range 

8 

exclusion of raptorial, nocturnal, and poorly detected species. 

Of these 41 species, 56 percent regularly used all three pmvinces, and 73 percent regularly used two provinces. Six speties regularly used only the Oregon Coast Range: the blackcapped chickadee, wrentit, purple fiich, rufous-sided towhee, 

song sparrow, and orange-crowned warbler. 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 stands low and high in elevation tended to be in the Oregon Coast Ranges and Oregon 

Cascades, respectively. Total bird abundance was correlated 

negatively with elevation and latitude and correlated positively with longitude (fig. 2). 

•1 = Oregon coast Range 

0 = Oregon Cascade Range 

* = Southern Washington Cascade Range 

z 42.5 43.0 43.5 44.0 44.5 45.0 45.5 46.0 45.5 47.0 

‘0 Latitude 
Table 4-The percentage of young, mature, and old-growth stands in which 16 species were detected that showed abundance 

differences in at least 2 of the 3 provinces 

‘omg 

50 

90 

tco 

80 

lco 

100 

90 

80 

100 

70 

1ca 

80 

80 

60 

0 

40 

_1___ 

ll&gl-OW 

5 

103 

102 

95 

100 

100 

100 

53 

95 

84 

95 

84 

84 

84 

58 

1w 

Table S-Number and percentage (in parentheses) of 

bird species with significantly different abundances 

among age-claws at P-values of 0.05, 0.10, 0.15, and 

0.20 

0.05 7 (21%) 5 (15%) 18 (51%) 

0.10 9 (27%) 7 (21%) 20 (57%) 

0.15 14 (42%) 9 (26%) 26 (74%) 

0.20 16 (48%) 11 (32%) 26 (74%) 

Total number of 

species” 33 34 35 

Abundance Patterns of Individual Bird Species 

Chestnut-backed chickadees and hermit warblers, detected in 

all 132 study stands, and winter wrens, western flycatchers, 

and golden-crowned kinglets, detected in >95 percent of the 

study stands, were the most abundant species over all three 

provinces (table 4). 

Bird abundance differences among stand age-classes were 

detected for 29 species at P 5 0.151. Twice as many species 

had differences in abundance at P < 0.050 among stand 

age-classes in the Oregon Coast Ranges than in the southern 

Washington Cascades or Oregon Cascades (table 5). 

Sixteen species showed abundance differences 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 species in all three provinces. Abundance of all sixteen 

species, except Vaux’s swift, showed age-class differences in 

the Oregon Coast Ranges. Six hole nesters-the chestnutbacked chickadee, red-breasted nuthatch, hairy woodpecker, 

pileated woodpecker, red-breasted sapsucker, and Vaux’s 

swift-were most abundant in old-growth stands in at least 

two provinces (figs. 3-5). Brown creeper abundance was 

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 grosbeak and 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 

sapsucker differed in all three provinces at P < 0.151 (fig. 5). 

184 
Black-throated gray warbler 

I.:...-..: 

IL- I 1 

Chestnut-backed chickadee 

185 
Evening grosbeak 

.;-;” 

Hairy woodpecker 

Steller’s jay 

r 
Northern flicker 

7 

Province and Age Comparisons 

Interaction and main effectsNo province x age interaction effects were detected in 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 tests at P < 0.010. Only half the 

tests on stand age-namely, total abundance and 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 

comparisons of mean abundance and species richness were 

higher in the Oregon Coast Ranges than in the Oregon and 

southern Washington Cascades at P < 0.050 (figs. 6.13).- 

Bird abundance was generally higher in the Oregon than 

southern Washington Cascades, except for resident species 

and understory foragers, which were more abundant in the 

southern Washington Cascades, and bark foragers. whose 

abundance did not differ between the two provinces (figs. 6- 

13). 

Pairwise comparisons of stand ageStand-age pairwise 

comparisons showed that total abundance and abundance of 

resident species and 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-class was 

the abundance of bark foragers (fig. 10). In six of the eight 

ANOVA comparisons, mean abundance and richness were 

lowest in mature stands (figs. 6-13). No comparisons were 

lowest in old growth. 
B 

188 
r 

‘t 

189 
B 

c 

i ,,I 

tz CR ocSW