Table 3-Multlple components model representing 5 forest structure components (data are forest age-class means with standard 

errors In parentheses) 

smlcnrre 

Forest sgeclass coefficient 

Variable selected YOUtQ MCUI~ Old growth CVl cv2 

Basal area of conifers 240 m tall 3.2 (1.1) 25.7 (4.0) 40.1 (2.4) 0.93 -0.15 

Basal area of conifers Z90 cm 

in d.b.h. 1.1 m 12.5 (2.5) 34.8 (2.4) .88 .20 

Basal area of conifers ~45 cm 

in d.b.h. 14.4 (2.5) 6.7 (1.5) 2.0 C.4) -.79 -.03 

Density of hardwood saplings 

1.2mwu 322.3 (53.4) 274.5 (76.3) 633.0 (70.6) .42 .41 

Percentage cnver of hardwoods 

<8mtall 12.5 (2.3) 16.8 (4.3) 25.0 (2.2) .47 .I9 

Density of hardwood snags >ZOcmindb.hand~mtall 6.7 (2.3) 20.0 (5.1) 5.1 (1.2) -.lO -.56 

Basal area of hardwoods 

45.90 cm in d.b.h. 5.3 (1.3) 28 (1.0) 5.4 C.7) .39 .34 

Density of hardwood seedlings 

25.50 cm tall 1307.1 (305.0) 1370.4 (314.2) 1496.7 (144.3) .18 .07 

Wilks’ lambda 0.048 Eigenvalue 4.97 2.48 

Exact F statistic (df = 16, 92) (significant at P < 0.001) 20.45 (9) 67 33 

Cla.ssificaticm mcces8 f%l 100 100 100 

powafal in discriminatiog among the forest ageclasses. The 

variables selected represented five of the six forest componems (table 3). No down-wowl (log) variables were retained. 

The most important variables discriminating the age-classes 

were the basal areas of conifers HO m tall, s90 cm in d.b.h., 

and ~45 cm in d.b.h. The density of hardwood saplings 1 to 

2 m tall, the percentage cover of hardwoods 28 m tall, the 

basal area of hardwoods 45 to 90 cm in d.b.h., and the density of hardwood snags XI0 cm in d.b.h. and Z2 m tall were 

of moderate importance. The eighth variable, the density of 

hardwood seedlings 25 to 50 cm, made a very minor contribution to the model. 

Featores most distinctive of old gmwth (fig. 12) were high 

basal areas of conifers St0 m tall and conifers -XXl cm in 

d.b.h., and a low basal area of conifers ~45 cm in d.b.h. A 

high cover of hardwoods G m tall and a high density of 

hardwood saplings 1 to 2 m tall also contributed (table 3). 

Young forests were distinguished by low basal areas of 

conifers 540 m tall and conifers SO cm in d.b.h., along with 

a high basal area of conifers ~45 cm in d.b.h. Mature forests 

were typified by basal area values tbat were all intermediate 

to old-growth sod young forests. Another feature of the 

mature age-class was a relatively high density of hardwood 

snags 220 cm in d.b.h. and t2 m tall. Two orher features, the Figwc I2dimtion of forest agechases according to seven variables. 

density of hardwood saplings 1 to 2 m tall, and the basal area Signifcant separation of ageclass means c-mmed for both canonid variates 

of hardwoods 45 to 90 cm in d.b.h. were both lower in (Wl md CVZ). Plated are the 95 percent cmnidmce elites mound ageclass cmtmids. 

mature stands thao in young and old-growth forests. 

313 
Of the 14 validation stands used to test the model, all 10 oldgrowth and three of the four mature stands were correctly

assigned. One mature stand dominated by trees > 185 years

old and on a productive site was incorrectly assigned to old

growth.

The jackknife classification of the training set (56 stands)

correctly assigned 100 percent of the old-growth stands, 79

percent of the mature stands, and 100 percent of the young

stands. One mature stand, about 135 years old, was incorrectly assigned to the young class. It was an unmanaged

stand characterized by a considerably higher density of

hardwoods, and a lower density of conifers 45 to 90 cm in

d.b.h. than was typical of mature stands. Another mature unmanaged stand, 190 years old, was incorrectly assigned to

old-growth. It had a moderate density of large conifers > 90

cm in d.b.h. and high densities of hardwoods ranging from

seedlings to large trees. The third stand was also incorrectly

assigned to the old-growth class. The stand was logged 115

years ago but retained several residual large conifers per

hectare and had a high density of hardwoods.

Discussion

As indicated by our multiple components model and by our

analyses of individual forest components, features associated

with tree size provide the strongest discrimination among

different-aged Douglas-fir/hardwood forests. In the multiple

components model, the most distinctive features of oldgrowth forests were a high basal area of very large Douglasfir trees and a low basal area of small Douglas-fir trees. The

reverse was true of young forests and intermediate values

were typical of mature forests.

The four discriminant models based on variables representing

the tree height and tree diameter components were the most

powerful of the 11 individual-components models. The remaining models indicated that features of tree reproduction,

understory, and dead-wood components, on their own, provide little-to-moderate discrimination. The variation in such

features, between stands as well as within a stand, can be

extreme. Changes in microhabitat conditions affect seedling

and sapling densities, and understory cover values. Tree reproduction, especially of Douglas-fir, varies from scattered

individuals to densely populated patches associated with canopy openings regardless of forest age. The influences of total

canopy cover on tree reproduction and understory growth are

similar for different-aged forests. Regardless of age-class,

hardwood reproduction is mainly from crown sprouts. Reproduction from seed is variable, showing patterns in distribution

similar to those of Douglas-fir. As a result, seedling and

sapling densities, and understory cover can each include a

wide range of stand values that typically overlap among

different-aged forests.

The accumulation and distribution of coarse woody debris

are affected by environment, disturbance, decay rates, and

topography (Harmon and others 1986). Wet sites typically

have greater amounts of coarse wood than do dry sites (Spies

and others 1988). Recruitment of coarse woody debris as

snags and logs often occurs in waves related to some event.

Stands with histories of hot or frequent fire can contain small

quantities of dead wood. Managed stands can inherit large

quantities of wood on the ground as slash. Low numbers of

large snags, and higher numbers of stumps are also carried

over. Decay progresses at different rates depending on species, size, microclimate, and cause of mortality. Topography

affects accumulations and distributions by influencing storm

patterns, the direction of tree-fall, and the movement of

material by gravity. Such influences are important regardless

of stand age, and help explain similarities among differentaged forests in certain features of coarse woody debris.

Our multiple components model provides forest managers

with a set of features that, in combination, are distinctive of

young, mature, and old-growth Douglas-fir/hardwood forests.

Together, these features act as a powerful tool for discriminating among the forest age-classes. The models composed

of variables selected by analyses of individual forest components can further assist managers in identifying important

features of each forest age-class. For example, the analysis

of the snag component showed that managed young forests

generally have higher sound-snag and rotten-snag densities

than does old growth. Old-growth forests, however, typically

have higher densities of large conifer snags > 40 cm in d.b.h.

and > 4 m long. As another example, analyses of the features

of the log component showed that managed young stands

and old growth generally have relatively high densities and

biomasses of logs >44 cm in diameter and > 4 m long, while

mature stands typically contain low quantities.

Testing our model with the validation data set and the jackknife classification helps confirm certain ideas about the

development of old-growth features. Age alone may be a

poor indicator of old-growth structure. Old-growth conditions

develop gradually, with the rate related to the environmental

conditions and the disturbance history of the stand (Spies

and Franklin 1988). Certain features of old growth, such as

a high density of very large trees, do appear on productive

sites before 200 years. Stands on sites that are poor at

producing large conifers may require much longer periods

or may never develop certain features commonly associated

with old growth. On managed sites, logging practices can

retain large conifers and hardwoods at densities more

characteristic of old growth than younger stands.

374
Forest Definitions

We define young, mature, and old-growth Douglas-fir/

hardwood forests by using ranges of means observed in the

majority of the stands we sampled in each age-class. The

ranges, therefore, represent typical stand values and not

minimums or maximums. To provide the most thorough

descriptions, we included features beyond those selected by

our stepwise discriminant analyses. The major features we

used to define each forest age-class, such as tree densities for

dominant height- and diameter-classes, and total snag and

log densities, all exhibited standard errors that were < + 20

percent of the age-class mean. Other features, such as those

of seedling densities and understory cover, are more affected

by changes in microhabitat conditions and tend to show

greater variation.

Young Douglas-fir/hardwood forests

Canopy <40 m tall, singIe-tiered, total cover 65 to 80

percent.

Trees 12 to 40 m tall, conifers 105 to 525 per ha and hardwoods 160 to 660 per ha. Dominant stems, conifers <45 cm

in d.b.h., 260 to 780 per ha; hardwoods <45 cm in d.b.h.,

225 to 1215 per ha. Stand basal area, 30 to 75 percent

hardwoods.

Saplings 1 to 8 m tall, conifers 150 to 450 per ha and hardwoods 300 to 1200 per ha.

Seedlings <1 m tall, conifers 100 to 2500 per ha and hardwood seedlings or sprouts 1500 to 7000 per ha.

Understory cover > 8 m tall, conifers 2 to 10 percent and

hardwoods 5 to 20 percent.

Ground cover < 2 m tall, 10 to 25 percent. Moss and lichen

cover including epiphytes on the ground, 1 to 5 percent.

Snags > 10 cm in d.b.h., 45 to 135 per ha. Hardwood snags

20 to 60 percent of snag density. Large snags >40 cm in

d.b.h. and >4 m tall, 0.5 to 5 per ha.

Logs > 10 cm in diameter, 200 to 530 per ha. Hardwood logs

20 to 65 percent of log density. Large logs >44 cm in

diameter and > 4 m long, 7 to 48 per ha.

Biomass of snags and logs, 10 to 50 metric tons per ha.

Mature Douglas-fir/hardwood forests

Canopy <55 m tall, two-tiered but indistinct, total cover 65

to 80 percent.

Trees 12 to 40 m tall, conifers 60 to 215 per ha and hardwoods 120 to 330 per ha; > 40 m tall, conifers 30 to 60 per

ha. Dominant stems, conifers 45 to 90 cm in d.b.h., 40 to 70

per ha: hardwoods <45 cm in d.b.h. 255 to 760 per ha. Stand

basal area, 15 to 45 percent hardwoods.

Saplings 1 to 8 m tall, conifers 50 to 400 per ha, and hardwoods 30 to 1100 per ha.

Seedlings <1 m tall, conifers 250 to 1200 per ha and hardwood seedlings or sprouts 3000 to 9000 per ha.

Understory cover < 8 m tall, conifers 1 to 5 percent and

hardwoods 5 to 35 percent.

Ground cover <2 m tall, 5 to 55 percent. Moss and lichen

cover including epiphytes on the ground, 1 to 20 percent.

Snags 210 cm in d.b.h., 35 to 125 per ha. Hardwood snags

20 to 90 percent of snag density. Large snags > 40 cm in

d.b.h. and > 4 m tall, 0.5 to 4 per ha.

Logs > 10 cm in diameter, 225 to 385 per ha. Hardwood logs

45 to 75 percent of log density. Large logs >44 cm in

diameter and > 4 m long, 0.5 to 16 per ha.

Biomass of snags and logs, 5 to 30 metric tons per ha.

Old-growth Douglas-fir/hardwood forests

Canopy >55 m tall, two-tiered and well to defined, total

cover 65 to 80 percent.

Trees 12 to 40 m tall, conifers 15 to 55 per ha and hardwoods 105 to 280 per ha; 240 m tall, conifers 35 to 50 per

ha. Dominant stems, conifers > 90 cm in d.b.h. 20 to 40 per

ha; hardwoods <45 cm in d.b.h. 425 to 690 per ha. Stand

basal area, 15 to 40 percent hardwoods.

Saplings 1 to 8 m tall, conifers 30 to 300 per ha and hardwoods 650 to 1500 per ha.

Seedlings <1 m tall, conifers 150 to 1100 per ha and hardwood seedlings or sprouts 3500 to 9900 per ha.

Understory cover < 8 m tall, conifers 1 to 5 percent and

hardwoods 15 to 30 percent.

Ground cover <2 m tall, 10 to 65 percent. Moss and lichen

cover including epiphytes on the ground, 5 to 25 percent.

Snags > 10 cm in d.b.h., 20 to 40 per ha. Hardwood snags 15

to 75 percent of snag density. Large snags > 40 cm in d.b.h.

and > 4 m tall, 0.5 to 11 per ha.

375
Logs > 10 cm in diameter, 215 to 385 per ha. Hardwood logs

20 to 55 percent of log density. Large logs >44 cm in diameter and > 4 m long, 14 to 38 per ha.

Biomass of snags and logs, 10 to 110 metric tons per ha.

Old-growth Douglas-fir/hardwood forest overstories are

strongly two-tiered. The hardwoods attain maximum heights

roughly half the height of Douglas-fir and dominate the

lower tier. In the upper tier, Douglas-fir dominates as widely

spaced individuals or as groups of trees. Within the forest,

the prevalence of either tier shifts from place to place. Forest

openings with hardwood and conifer regeneration at various

stages add to the high spatial diversity.

In addition to the forest canopy, the hardwood element of

Douglas-fir/hardwood forest influences other forest components. Hardwoods contribute importantly to snag and log

densities, but because of the smaller dimensions of hardwoods, along with several other factors (such as different

climatic and disturbance regimes), snag and log biomasses

are low in comparison to Douglas-fir forests farther north

where other conifers share dominance. Densities of large

snags and large logs are also typically lower.

New Standards for Old-Growth Douglas-Fir/Hardwood

Forests

Our research indicates that the minimum standards prepared

by the Old-Growth Definition Task Group (1986) for oldgrowth Douglas-fir/hardwood forests require revision (table

4). We introduce standards for some additional features not

included in the interim definition, but identified as key features by our analyses. Along with new minimum standards,

we present average values + 95-percent confidence limits for

each key feature.

The most diagnostic feature of nonmanipulated old-growth

Douglas-fir/hardwood forests is the presence of large old

trees in densities adequate to form an upper tier that dominates over a hardwood layer. Stands that fail to meet minimum standards for other features, such as those for large

snags and large logs can qualify as old growth. For example,

wet and mesic sites are more likely to exceed the minimum

values, and dry sites are more likely to approach or even

drop below the minimum criteria. We believe that the new

minimum standards will include the majority of old-growth

Douglas-fir/hardwood stands in northwest California and

southwest Oregon.

Table 4-Interim and new standards for old-growth Douglas-fir/hardwood forests in northwestern California and

southwestern Oregon

Stand Interim minimum standards from Old- New average standards + 95%

characteristic Growth Definition Task Group 1986a New minimum standards confidence limits

Live trees Douglas-fir and evergreen

hardwood (tanoak, Pacific

madrone, and canyon live

oak) associates (40 to 60

percent of canopy)

Douglas-fir and evergreen

hardwood associates

(e.g. tanoak, Pacific

madrone, and canyon live

oak), hardwoods account

for > 10 percent of the

total stand basal area

Basal area of hardwoods

average 30 + 5 percent

of the total stand basal area

Douglas-fir or sugar pine

> 15 per ha of trees >80 cm

in diameter or >200 years

old

Douglas-fir or minor

conifers (e.g. sugar

pine, Port-Orford-cedar,

iucense-cedar, or

redwood) > 14

per ha of trees > 90cm

diameter or >200 years

old

Douglas-fir or minor conifers

average 29 + 3 per ha of

trees > 90 cm in diameter

or >200 years old

Intermediate and small size- Intermediate and small sizeclasses may be evergreen classes of hardwoods and

hardwoods or include a Douglas-fir, >lO percent

component of conifers (e.g., total cover of trees < 8 m tall,

Douglas-fir or white fir) may include minor conifers

Intermediate and small size-classes

with high numbers of hardwoods

and moderate numbers of

Douglas-fir or minor conifers,

small sires < 8 m tall average

25 + 5 percent cover of

hardwoods and 2 + 1 percent

cover of conifers

376
Table tiontinued 

Stand Interim minimum standards from Old- Newaveragesmdardsf95% 

characteristic Growth Lkfintion Task Group 1986” New minimum standards confidence limits 

C-PY Diitinct two-tiered campy 

with an upper tier of 

Douglas-fir with trees 

reaching heights >40 m 

and a lower tier of 

cdfm and hardwoods 

<40mta!.landamtal 

canopy CoveI of >60 

percent 

conifers 2: 40 m tall average 

44 f 2 trees pa ha, conifas 

12 to 40 In tall average 39 f 15 

trees per ha, hardwwds 12 to 40 m 

tall average 221 f 43 trees per 

ha, and an average total canopy 

cover of 71 * 3 percent 

Conifer or hardwood snags 

>13 per ha that ax 210 

cm in diameter including 

>0.25 pa ha of conifer snags 

that are ~40 cm in diameter 

and>4mtaU 

Conifer or hardwood snags 210 cm 

diameter average 32 f 6 per ha 

including 5 f 2 per ha of 

conifer snags that are 240 cm 

diameter and 54 m tall 

Logs>22metrictom 

per ha including 5 

piecesperha>M)cmin 

diameter and >15 m long 

Logs>2.5meuictonsper 

ha including >l piece 

perha>44cmindiameter 

and 24 m long, of which 

9.25 piece per ha are 

>15 In long 

Logs average26f8meuictom 

per ha including 25 f 6 pieces 

per ha that are >44 cm in diameter 

and 24 m long, of which 5 f 2 

pieces per ha are >I5 m long 

The new minimum standards are intended to assist managers 

in identifying nonmanipulated and manipulated stands that 

contain key old-growth features. Additionally, the minimum 

standards can be used as guidelines for retaining features 

associated with old growth when manipulating stands. We 

view the mean values and 95 percent confidence limits as 

being mire appropriate for identifying optimal old-growth 

conditions. We also suggest that the new old-growth definition be used to supplement the minimum and average standards. The old-growth definition goes beyond the standards 

for large trees, snags, and logs in providing criteria for additional understory features. The deftitions for young and 

matnre stands will also assist managers when making ageclass comparisons over a wide range of stmcti features. 

Acknowledgments 

We thank Thomas Atzt and Dale Thombwgh for their 

assistance in locating and selecting study stands. Kenneth 

Clark, Carl Meyer, Thomas Quinn, and Kristin Schmidt 

made the three summers of difficult field work a success. 

Barry Noon and Sylvia Mori provided statistical reviews. 

Valuable reviews of the manuscript were also provided by 

Sheri Forbes, Chad RoLwts, Thomas Spies, Jeff Waters, and 

Cindy Zabel. The California Nature Conservancy provided 

facilities for field crews located at the Northern California 

Coast Range Preserve. m 

311 

Habitat Association Patterns of Breeding Birds

and Small Mammals in Douglas-Fir/Hardwood

Stands in Northwestern California and

Southwestern Oregon

C. John Ralph, Peter W.C. Paton, and Cathy A. Taylor

Authors

C. JOHN RALPH is a research ecologist, USDA Forest

Service, Pacific Southwest Forest and Range Experiment

Station, Arcata, California 95521; PETER W.C. PATON is a

graduate student in the Cooperative Fish and Wildlife Unit,

Utah State University, Logan, Utah 84322; and CATHY A.

TAYLOR is a district biologist, Blue Ridge District,

Coconino National Forest, Happy Jack, Arizona 86024.

Abstract

We surveyed birds and small mammals in 45 forest stands

from southern Oregon, near Cave Junction, south into northern California, near Branscomb. Over this 350-km distance,

we found 71 species of birds and 7 species of mammals that

were common enough for detailed analysis. Fourteen species

of birds and two mammals reached peak abundances in older

(mature and old-growth) forests; however, none appeared

limited to these forests. The species were: Allen’s hummingbird, hairy woodpecker, pileated woodpecker, Hammond’s

flycatcher, western flycatcher, gray jay, chestnut-backed

chickadee, red-breasted nuthatch, brown creeper, winter wren,

golden-crowned kinglet, wrentit, hermit warbler, blackheaded grosbeak, Douglas’ squirrel, and the California

red-backed vole. In addition, about half of the species were

correlated with total conifer or hardwood stems. The abundance of many species also differed among the three geographic regions we sampled. These differences could also be

associated with elevation because our northern stands tended

to be at higher elevations than were the southern stands. Our

community analysis of the birds showed separations between

different regions, and between the avian communities of

young forests and those of older (mature and old-growth)

forests. The mature and old-growth bird communities were

not readily separable from each other.

Introduction

The Douglas-fir forests of northwestern California are a

major source of timber products in the United States, with

almost half of the Nation’s timber supply contained in the

old-growth forests of the West (Society of American Foresters Task Force 1983: 1). Clearcutting has been the primary method of harvesting timber in the region for the past

30 years. Morrison (1988) has documented the great reduction of old-growth timber in many forests of the Pacific

Northwest, which includes Washington, Oregon, and

northern California.

379
Present management guidelines state that the USDA Forest

Service shall “maintain viable populations” of all vertebrates

found on each National Forest (National Forest Management

Act 1976, 16 U.S.C. 1600-1614), yet the impacts of the decline of old-growth forests on vertebrate populations in northwestern California are uncertain, with only a few studies on

the subject (Hagar 1960, Raphael 1984, Raphael and others

1988). Our study’s goal is better understanding of the association patterns of flora and fauna across a chronosequence

of forests in the Northwest; it was conducted as a part of

research that extends north into Washington (Carey and

Spies, this volume; Ruggiero and Carey 1984).

We studied the relative abundance of small mammals and

diurnal birds along an age gradient of selected forest stands

in northwestern California and southwestern Oregon during

the summers of 1984 and 1985. We surveyed the entire diurnal avian community and trapped small mammals to determine if the relative abundance of each species differed between the stands, and to determine which habitat variables

correlated with the abundances of each species. We detected

23 small mammal species and 102 bird species over 2 years

of field work; in this paper, we concentrate on the more

common species.

Methods

Study Areas

We selected 45 principal study stands (table 1) in three regions of northwestern California and southwestern Oregon to

represent a successional gradient typical of the Douglas-fir

communities (see frontispiece). We selected stands nonrandomly based on accessibility by road, presence of a representative age-class of trees, and moderate topography. The stands

were conveniently divided into three geographical regions of

15 stands each (table 1): Cave Junction in the north, Willow

Creek in the central area, and Branscomb in the south. Stands

ranged in elevation from about 400 m to 1550 m, and most

were dominated by Douglas-fir in association with tanoak

and madrone. Six low-elevation plots had some redwood,

and four high-elevation stands in the Cave Junction region

were dominated by white fir.

Bird Counting Techniques

Diurnal birds were counted in 1984 and 1985 during the

breeding seasons from May to June. Each stand was visited

5 to 7 times each field season, with counts conducted over

the entire breeding season at the rate of about once per week

for each stand. We minimized observer bias by rotating observers at each stand. In 1984, we had 5 to 6 observers per

region, so each stand was usually counted once per observer.

During the 1985 field season, we had only 3 to 4 observers

in each region, so stands were usually visited on the average

of twice per observer. Counts were conducted on 12 fixed

stations placed 150 m apart at least 100 m from adjoining

habitat types. Observers counted at each station for 8 minutes,

recording horizontal distance to each bird seen or heard. All

counts were initiated within 15 minutes of official sunrise

and took approximately 3.5 hours to complete, to minimize

time-of-day bias.

We used the number of individuals detected per station as a

relative index of population abundance, which corrects for

differences in effort. We did not establish an arbitrary distance from the observer beyond which detection would be

excluded because the unit of analysis was the stand as a

whole, not individual stations within the stand. Double

registrations of an individual consequently would not affect

the conclusions. We include in this report only those species

that we recorded more than about 10 times during the survey

in abundances greater than or equal to a total of 0.001 birds

per station, which included all but the rarest species.

Mammal Trapping

For the mammalstudies, we included an additional two

stands at Butte Creek, near Dinsmore, California. A single

trapping-grid for snap and livetrapping was laid out in each

stand in a pattern of 12 rows with 12 trap stations per row.

Trap stations were placed at 15-m intervals in a 165-m x

165-m grid.

In 1984, two Museum Special snaptraps were placed at each

trap station within 1.5 m of the grid coordinate in all 47

stands. We trapped in six stands simultaneously (two in each

region) for 5 days (4 nights) until all stands were sampled

(July 3 to August 31). In 1985, a single Sherman livetrap

(7.6 cm x 8.9 cm x 22.0 cm) was used at the same stations in

43 of the stands, and we trapped again in six stands during

each 5-day session from July 9 to August 30. We did not

livetrap in four stands (two in Branscomb area and two in

Cave Junction area). We also used pitfall traps to sample

small mammal populations in all 47 stands during both 1984

and 1985. A pitfall grid consisted of six rows of six pitfall

traps per row spaced at 15-m intervals in each stand. Snap

and pitfall grids were usually separated by more than 100 m.

Traps were constructed from two No. 10 cans taped together

and sunk until the top was flush with the ground. A funnel

collar prevented animals from escaping. We propped a cedar

shake 3 to 4 cm above the opening of each pitfall trap to act

as a cover, and examined the traps at 5-day intervals for 50

days in October and November 1984, and for 30 days in

October 1985. In the analyses below, we used the number of

mammals captured, without standardizing the data for effort

(table 4). Total trap nights were adjusted for inoperative traps.

380
Table l-List of study stands by region, with stand abbreviation, elevation, mean age, age-class, and mean density in stems per

1000 m2 of hardwood and conifer trees

Canopy trees Mean density of trees

1 Region Stand Elevation Age Age-class Hardwoods Conifers

Cave Junction

(AC)

(BP)

(CG)

(FR)

(GG)

(HC)

(HO)

(LG)

(LH)

(OC)

(PM)

(SK)

(TU)

(UH)

(WC)

Willow Creek

(BA)

(BE)

(BM)

(BR)

(CC)

(EB)

(FN)

(GR)

(HP)

(LE)

(LR)

(SF)

(SH)

(WR)

Branscomb

(AP)

(BT)

(DP)

(EC)

(EH)

(EX)

(FC)

(FP)

(HN)

(HT)

(MS)

(SC)

(SG)

(TM)

(WH)

Althouse Flat 427 107

Buck Peak 1366 60

California Gray Back 1556 265

Frog Pond 1439 196

Galagy Grove 1334 259

Happy Camp Road 1053 179

Holcomb Peak 1411 235

Little Grayback 1205 72

Left Hand 1362 96

Oregon Caves Road 872 192

Page Mountain 1519 204

Skag Hope 1305 267

Tunnel Site 624 65

Upper Horse 1502 91

Waters Creek 614 240

Bald Mountain East

Brannon Mountain

Beartooth Mountain

Brush Mountain

Cedar Creek

East Fork Big Creek

Fawn Prairie

Gray II

Hennessy Peak

Lord Ellis

Ladder Rock

South Fork

Sharber

Tish Tang

Waterman Ridge West

846 43 Young .862 0.701

750 236 Old .597 1.379

1144 327 Old .383 2.176

1050 116 Mature .420 1.773

665 347 Old .396 1.728

1134 246 Old .589 1.383

750 44 Young .983 .945

972 101 Mature .292 1.481

949 100 Mature .172 1.700

778 48 Young 1.366 1.024

805 319 Old .828 2.072

659 289 Old .470 1.291

747 283 Old .673 .932

680 204 Old .888 1.484

633 85 Mature 1.091 1.140

Alpine

Barnes

Darby

Elder Creek

Elkhorn Ridge Hydric

Elkhorn Ridge Xeric

Fox Creek

Fanny’s Place

Harwood’s Ninty

Homestead

Mud Springs

Skunk Creek

Standley Grove

Ten Mile

White House

444 210 Old .730 1.899

467 53 Young .357 .329

587 240 Old .317 1.021

555 155 Mature .402 2.361

518 137 Old .230 .603

518 140 Mature .487 .291

543 187 Old .576 1.757

445 122 Mature .375 1.372

695 118 Mature 1.010 .424

726 40 Young 1.071 1.300

689 70 Young .691 .678

529 291 Old .278 1.223

481 450 Old .082 3.555

445 241 Old .317 1.718

427 136 Mature .655 1.451

Mature

Young

Old

Mature

Old

Mature

Old

Young

Young

Mature

Old

Old

Young

Young

Old

0.531 1.890

.O34 .919

.ooo 1.352

.ooo 3.141

.ooo 2.639

.179 1.879

.042 3.235

.016 1.359

.O44 2.997

.316 1.157

.007 3.450

.011 3.890

.368 1.679

.013 1.581

.246 1.338

381 I
Vegetation Sampling

Vegetation was quantified on each of the 12 bird-count stations in each stand. On the snap-livetrap grid we measured

16 plots overlaying the 144 trap stations. Nine vegetation

plots were also uniformly distributed among the 36 pitfall

stations. For this analysis, we used the mean number of all

hardwood and conifer stems greater than 50 cm in d.b.h.

within 15 m of each mammal-trapping station and 25 m for

bird observations. We reasoned that, for this study, individual plant species would be too detailed for our analysis.

Stand ages were based on data supplied by B. Bingham (pers.

comm.) from core samples of three to five dominant Douglasfirs on each of three plots in each young and mature stand

(up to about 180 years). In old-growth stands, tree cores

could not always be taken because trees were so large and

had rotten cores; thus, some stand ages were estimated from

rings counted on stumps in adjacent clearcuts or beside nearby roads, or they were based on ages provided by local

Forest Service offices.

We minimized the number of variables for the small mammal

community by comparing the capture rates associated with

logs that have fallen relatively recently, hard logs of decayclasses 1 and 2 of Thomas (1979: 80), and soft logs of decay

classes 3 to 5.

Data Analysis

The objective of this analysis was to estimate how much

variation in bird abundance among stands could be explained

by stand age or geographical region, and whether abundance

was affected by interaction between stand age and region.

For most analyses, stand age was considered as a continuous

variable, and entered into calculations as a square-root transformation. Region was considered a categorical variable. A

probability level of P < 0.05 was used to signify statistical

significance.

We considered that the bird counts, as discrete variables,

approximated normal distributions with means linear on the

independent variables and with equal variances.

A general linear model (GLM) in SAS (Freund and others

1986: 145) was used to compare relations between the abundance of each bird species with stand age and region. This

comparison was treated as an analysis of covariance with

interaction between age and region, with region as the covariate. The interaction term determines if the relation (the

slope of the line describing the relation between age and

abundance) was statistically different among regions.

The SAS procedure “GLM,” produces two sets of statistics,

Type I and III Sums of Squares, which we used in constructing table 2. If the interaction between age and region was

not significant, then we used the statistics from Type I (the

unadjusted treatment sums of squares), where age was entered

into the model after region. If the interaction term was significant, then we used Type III (adjusted treatment sum of

squares), which takes into account the other variables before

calculating the effect of the variable under consideration. For

example, if an age and region interaction was significant,

then the statistic appearing in table 2 was the effect of age

after accounting for the effects of both region and the

interaction of age and region.

We also treated stand age as a classification variable when

separating the sites into young, mature, or old-growth, based

on a discriminant function analysis of vegetation data sampled from the entire stand (Bingham and Sawyer, this volume). These classifications, based on vegetative structure

and composition, sometimes differed from stand age as

determined by counting tree rings. Bird abundances are

presented in table 2 according to the stand-age classifications of Bingham and Sawyer. A least-squares test (Freund

and others 1986) determined significant differences in bird

abundances between age-classes and regions.

We compared numbers of species and individuals detected

between years and habitat types by using Pearson productmoment correlation coefficients.

Our analysis of the data aggregated the various stands according to similarities in the abundance of bird species found

in each stand. For this, we used Ward’s method of cluster

analysis (SAS 1982: 423), but only for the commoner species,

which we defined as the 29 species with average abundances

greater than 0.1 birds per station in either 1984 or 1985

(table 3). We acknowledge that this analysis is only an

approximation because it is not based on actual densities, but

we believe that the figures were indicative of the relative

abundance of most species.

382
Table Z-Comparison of the number of individuals of each bird or mammal species detected or captured per station in the three 

regions; the signitkmce (2’ c) of region alone as a contribution to a model; the number of individuals per station in young, mature, 

and old-growth stands; the significance of age alone as a contribution to a model; the significance of the interaction of age and 

region; and the amount of variance explained by the model (R ) 

0.008 0.001 o.ocQ 

.Wl ,003 .““I 

.W6 .“a0 .ow 

.w4 ,006 ,008 

.a”0 .a00 ,051 

,014 .““I ,009 

325 ,075 ,071 

,002 ,013 ,003 

- 

.“I9 ,001 ,025 

.““a .““I ,003 

n m 

.“I, :a03 

,005 

.003 

+ .046 

.a75 

-025 

,003 

,055 

.a00 

,426 

,152 

+ -ms 

0”” 

.a00 

+ l.780 ^. _ 

.I93 ,159 

,110 ,089 

.038 ,119 

m9 .082 

-A!$ ,374 

,053 

1.175 ,520 

.“‘3 .ooil .a”” 

ma .a00 ,011 

,978 ,748 ,555 

.“I 1 ,004 .““a 

W” our .“a6 

,373 ,086 ,083 

coo .oou ,041 

+ .M)9 ,548 ,317 

.013 .oo* ml 

264 544 830 

.coo :014 :002 

,528 ,218 .222 

,001 .oiKl .004 

.0”4l -im 

:I60 

m 

,084 :235 

+ ,013 2’10 114 

,003 :050 :149 

+ J&2 ,671 .453 

.ooo ,023 .w8 

,251 ,086 .I24 

0.0369 

.4094 

.38M 

.7967 

ma1 

.3832 

.OOOl 

.06N 

.4213 

.0932 

.0828 

.x62 

al13 

.9853 

.9042 

.1922 

x133 

2019 

.0001 

.0880 

.““a3 

.0259 

.0001 

.0001 

.4531 

.2297 

2236 

.““a7 

.0116 

.I604 

.OOOl 

,003, 

.OOOl 

.I262 

.OOOl 

.1906 

.OOOl 

.0783 

A594 

.0452 

2346 

.W18 

.0413 

,154, 

.0024 

o.ow 

,033 

0.003 

.002 

0.005 

,021 

,027 

.“a0 

.OQ4 

,321 

.““I 

,116 

,003 

,169 

.a00 

,169 

,015 

.a00 

ml 

.a05 

,005 

,001 

,013 

CO9 

,024 

,006 

,008 

.ow ,692 .a”2 

,005 ,025 ,024 

,004 ,005 ,007 

,003 ,007 ,036 

.a44 ,064 ,056 

.a91 ,157 ,198 

II42 ,008 ,016 

-1.230 1.420 

.019 ,002 .coo 

-003 .a00 Jg 

-55r ,850 -743 

.“I” ,005 .w* 

,001 ,005 .M)o 

,075 ,213 .209 

-016 ,002 .022 

,339 ,533 ,535 

.005 .“I” ,006 

,335 ,514 .684 

,001 ,010 .004 

.118 .313 .438 

.w4 ,001 .““I 

,005 JO5 .w2 

45 ,068242 -vTT ,229 

,139 ,034 ,057 

.551 ,422 ,543 

.016 .““I ,016 

.053 ,195 ,173 

.9224 

.0128 

.9229 

0.3124 

.2360 

.4902 

,183, 

.2228 

.I425 

.I561 

.a008 

.9610 

.6857 

.8319 

.4709 

.0133 

.0562 

.2669 

.2979 

.a285 

.089” 

.2404 

.0377 

.2122 

.wo* 

.1010 

.a360 

.8193 

.0772 

,363, 

.3 174 

.3456 

.0113 

.7712 

.“a47 

.7786 

.Owl 

.I569 

3365 

.0134 

.156il 

.0710 

.9865 

A395 

.I515 

0.5512 

.7576 

.5607 

.9966 

.9369 

.4107 

.9037 

,930, 

.6863 

.3008 

.3939 

.0036 

.Oool 

.4755 

.1850 

X798 

.2767 

.a900 

3135 

.9227 

.5924 

.4916 

.2185 

.2818 

.0480 

II752 

.0257 

A286 

.5351 

.3815 

.4458 

.I819 

.9390 

,066, 

.1853 

.95w 

.ow, 

.2103 

.7833 

.0319 

.“301 

a291 

.9476 

.7464 

2447 

0.1951 

.1030 

.a*64 

.0389 

.3848 

2137 

.3844 

.I635 

.0717 

.1936 

.I834 

.3402 

.5540 

,038, 

.0908 

.0876 

.20”7 

.2403 

.5251 

.2124 

.3788 

2185 

,461, 

.4s94 

.x194 

.2264 

,388, 

.3187 

,272” 

.1459 

.5036 

.3149 

.5574 

.2083 

.5344 

.0854 

,852, 

.2164 

.0720 

,338, 

.6618 

.4630 

.I528 

.1046 

.3293 

383 
- 

Region 

sign*- 

icance 

0.0132 

,011s 

.0078 

.a005 

.OOOl 

.a010 

.a021 

,000, 

.0030 

.ooo* 

.w32 

.lwot 

.wo, 

.OOM 

.0414 

.0095 

.OW, 

.0119 

.I153 

.1137 

,003 

.0965 

,072s 

,000, 

2265 

.OOOl 

.OOM 

.OOOl 

.0004 

!-q/j I ,137 I, '.102 

: '.359 * ' : S82 : : : ,.283 

: i.073 , I ."ZY '.032 

: i.306 : : ; ; ,280 4. 

, ,.155 I I I - ,062 : :150 : 

: :.a84 : : : : ,632 : : ;a. 

:zoii::::.oo8 00 .OM 

:rs55 : : : :1.761: : : :i,O78 : 

b ,023 4 * ,010 * h ,011 : 

:,165: : : : 259: : : : ',309 

: :319 : : : : t933 : : :m: 

: 304 : : ,552 : ,503 

: .001 : : : : .a02 : : ,003 

: i&7! : : : : ,.156 : : : ,106 

: &MS : i : : ,.OOl' : : ,008 

: :a17 : : I : ,002 : : ,003 I 

: ,401 : : : : 354 j : ,478 

:oLou:::;,a34':::'w: 

/ *52 * * / * .a84~: 1:-%5i-: 

: :026. : : : : ,013 I ' ,021 + 

~~.164:::::.127::::.182:: 

~~.004:~::~.004::::.003 : 

~~.03,~~~~~.012~~~~.017,; 

/:.uZO::::,~16,,,,.014 o 

1~.180“""".235“':.362 j 

Age*Regian 

significance 

0.187, 0.0413 0.2756 

.0063 .1002 .3728 

.9630 6651 ,233, 

.0931 3535 .A776 

.0090 .WOl 6070 

.2956 .6806 .32@4 

3731 3871 .3060 

.5975 3089 .4645 

.ozw .W36 .4468 

S187 6717 ,484, 

.0040 .M‘l7 .A630 

.X80 .0964 .5076 

.04& .I203 .5021 

.4929 2290 .3833 

,869, .0235 .3260 

3790 .8622 .2295 

.5147 ,327-I .6540 

,414 3890 .2407 

.1152 .I683 .I998 

,942s .0791 .2045 

.4290 .5470 .I784 

.2313 .2122 .1987 

.5273 .O249 .2474 

.OSM .I588 .7240 

.9962 ,874s .0792 

.4127 .8730 6541 

.9837 9731 .3408 

.0363 .0755 .4589 

.9808 .8263 3340 

Results 

Bird Abundances 

Overall abundance patterns-Seventy-one bird species 

(table 3) were found in the study plots in both years in numbers greater than 0.001 birds per station. The most abundant 

species was the hermit warbler, with over 1.7 birds per 

station in both years. The western flycatcher was next in 

abundance with more than 1.1 birds per station. 

Some birds began to reach tbe limit of their distributions 

within the geographic range of this study. For instance, blue 

grouse and gray jay were only found at Cave Junction in the 

north, and Hammond’s flycatcher was not found at Branscomb in the south. These species could be found in areas we 

did not count to the north or south, but in limited numbers. 

They also probably were largely limited by the altitudinal 

gradient between study stands. The Cave Junction stands 

were generally at higher elevations and Branscomb tended 

to be lower. 

We divided the species into three groups: year-round residents, short-distance migrants (birds wintering in the United 

States), and long-distance migrants. More than half (59 percent) of the species were r&dents, 11 percent were. short-, 

and 30 percent long-distance migrants. By contrast, only 

42 percent of individuals (birds per station) were residents, 

6 percent short, and the majority (52 percent) long-distance 

migrants. 

Comparison between gears-We compared, by correlation, 

the abundance of each species between years in each stand to 

determine the concordance of the 2 years’ data. The closer 

the agreement between the 2 years, the greater the likelihood 

(but, by no means, certainty) that some aspect of the habitat 

was important in determining the abundance of that species 

at any sampling point. The less the agreement, the greater the 

likelihood that stochastic events in the population could be 

responsible for tbe abundance of the species. 

384 
- 

Region 

sign*- 

icance 

0.0132 

,011s 

.0078 

.a005 

.OOOl 

.a010 

.a021 

,000, 

.0030 

.ooo* 

.w32 

.lwot 

.wo, 

.OOM 

.0414 

.0095 

.OW, 

.0119 

.I153 

.1137 

,003 

.0965 

,072s 

,000, 

2265 

.OOOl 

.OOM 

.OOOl 

.0004 

!-q/j I ,137 I, '.102 

: '.359 * ' : S82 : : : ,.283 

: i.073 , I ."ZY '.032 

: i.306 : : ; ; ,280 4. 

, ,.155 I I I - ,062 : :150 : 

: :.a84 : : : : ,632 : : ;a. 

:zoii::::.oo8 00 .OM 

:rs55 : : : :1.761: : : :i,O78 : 

b ,023 4 * ,010 * h ,011 : 

:,165: : : : 259: : : : ',309 

: :319 : : : : t933 : : :m: 

: 304 : : ,552 : ,503 

: .001 : : : : .a02 : : ,003 

: i&7! : : : : ,.156 : : : ,106 

: &MS : i : : ,.OOl' : : ,008 

: :a17 : : I : ,002 : : ,003 I 

: ,401 : : : : 354 j : ,478 

:oLou:::;,a34':::'w: 

/ *52 * * / * .a84~: 1:-%5i-: 

: :026. : : : : ,013 I ' ,021 + 

~~.164:::::.127::::.182:: 

~~.004:~::~.004::::.003 : 

~~.03,~~~~~.012~~~~.017,; 

/:.uZO::::,~16,,,,.014 o 

1~.180“""".235“':.362 j 

Age*Regian 

significance 

0.187, 0.0413 0.2756 

.0063 .1002 .3728 

.9630 6651 ,233, 

.0931 3535 .A776 

.0090 .WOl 6070 

.2956 .6806 .32@4 

3731 3871 .3060 

.5975 3089 .4645 

.ozw .W36 .4468 

S187 6717 ,484, 

.0040 .M‘l7 .A630 

.X80 .0964 .5076 

.04& .I203 .5021 

.4929 2290 .3833 

,869, .0235 .3260 

3790 .8622 .2295 

.5147 ,327-I .6540 

,414 3890 .2407 

.1152 .I683 .I998 

,942s .0791 .2045 

.4290 .5470 .I784 

.2313 .2122 .1987 

.5273 .O249 .2474 

.OSM .I588 .7240 

.9962 ,874s .0792 

.4127 .8730 6541 

.9837 9731 .3408 

.0363 .0755 .4589 

.9808 .8263 3340 

Results 

Bird Abundances 

Overall abundance patterns-Seventy-one bird species 

(table 3) were found in the study plots in both years in numbers greater than 0.001 birds per station. The most abundant 

species was the hermit warbler, with over 1.7 birds per 

station in both years. The western flycatcher was next in 

abundance with more than 1.1 birds per station. 

Some birds began to reach tbe limit of their distributions 

within the geographic range of this study. For instance, blue 

grouse and gray jay were only found at Cave Junction in the 

north, and Hammond’s flycatcher was not found at Branscomb in the south. These species could be found in areas we 

did not count to the north or south, but in limited numbers. 

They also probably were largely limited by the altitudinal 

gradient between study stands. The Cave Junction stands 

were generally at higher elevations and Branscomb tended 

to be lower. 

We divided the species into three groups: year-round residents, short-distance migrants (birds wintering in the United 

States), and long-distance migrants. More than half (59 percent) of the species were r&dents, 11 percent were. short-, 

and 30 percent long-distance migrants. By contrast, only 

42 percent of individuals (birds per station) were residents, 

6 percent short, and the majority (52 percent) long-distance 

migrants. 

Comparison between gears-We compared, by correlation, 

the abundance of each species between years in each stand to 

determine the concordance of the 2 years’ data. The closer 

the agreement between the 2 years, the greater the likelihood 

(but, by no means, certainty) that some aspect of the habitat 

was important in determining the abundance of that species 

at any sampling point. The less the agreement, the greater the 

likelihood that stochastic events in the population could be 

responsible for tbe abundance of the species. 

384 
Table 3-Mean number of detections of each bird and rqammal species per station in 1984 and 1985, the linear correlation (RZ) 

between years and its sign, and the Linear correlation (R ) between the number of detections and the abundance of hardwood and 

conifer trees and its sign (significant correlations are indicated as: * - -P 5 .OS, ** = P S .Ol, and **I = P s .OOl) 

Y.%Z Tree type 

Species 

yfyyy’““,, “’ *-I 

ha+d (R% C”“if~~d1 

Turkey vulture 0.003 

Northern goshawk ,001 

Red-shouldered hawk ,000 

Red-tailed hawk ,007 

Blue grouse ,020 

California quail .Oll 

Mountain quail .I60 

Band-tailed pigeon ,007 

Mourning dove ,012 

Flammulated owl .oOl 

Northern pygmy-owl .019 

Anna’s hummingbird ,009 

Allen’s hummingbird ,027 

Acorn woodpecker ,055 

Red-breasted sapsucker ,023 

Downy woodpecker .OQl 

H+ woodpecker .061 

White-headed woodpecker ,001 

Nonhem flicker ,269 

P&Wed woodpecker ,136 

Olive-sided flycatcher ,041 

Western wood-pewee .045 

Hammond’s flycatcher .I54 

Dusky flycatcher ,015 

Western flycatcher 1.138 

Ash-throated flycatcher .005 

Gray jay ,005 

Steller’s jay ,791 

Scrub jay ,005 

America” crow ,002 

common rave” ,152 

Mountain chickadee ,014 

Chestnut-backed chickadee ,501 

Common bush& ,011 

Red-breasted nuthatch ,492 

White-breasted nuthatch ,010 

Bmwn creeper ,337 

Bewick’s wren ,001 

House we” ,001 

winter wren ,194 

Golden-crowned kinglet ,374 

Townsend’s solitaire .057 

Hermit thrush ,447 

Swainson’s thrush ,013 

America,, robin ,165 

Varied thrush ,020 

WLStit ,090 

solitary “ire0 ,279 

Hutton’s vireo ,109 

Warbling vireo ,447 

kmge-crowned warbler .040 

0.003 

,002 

,004 

,006 

,014 

,006 

,154 

,005 

,018 

.OOl 

.022 

,003 

,009 

,082 

,346 

,003 

.044 

,002 

,250 

,098 

,074 

,068 

,165 

,023 

1.177 

.005 

,003 

,730 

.005 

.002 

,209 

,013 

,482 

,004 

,600 

,001 

.308 

.002 

,006 

,125 

,331 

.077 

,557 

,007 

,143 

,024 

,121 

,331 

,129 

,366 

.040 

0.47 

-.06 

.oo 

-.06 

.37 

.90 

.68 

.37 

.88 

-.06 

.26 

-.lO 

.09 

28 

.65 

-.08 

.24 

-.04 

.63 

.71 

.62 

.63 

.92 

.55 

.91 

.98 

.21 

.61 

.21 

.54 

.88 

.76 

.52 

.05 

.89 

.86 

.93 

.36 

.I3 

.74 

.91 

.70 

.71 

.1.5 

.69 

.67 

.96 

.78 

.65 

.91 

X8 

O.OQll 

.7017 

l.OO!Xl 

.6836 

.0122 

..MOl 

.OOOl 

.0115 

.OOOl 

,720s 

.0796 

.4978 

.OOOl 

.OcQl 

.OOOl 

.5931 

.1112 

.8022 

.OOOl 

.OOOl 

.OOOl 

.ooOl 

.Oool 

.OOOl 

.OOOl 

.OOOl 

.1611 

.OOOl 

.I639 

.OOOl 

.ooOl 

.OOOl 

.0003 

.7498 

.OOOl 

.OOOl 

.OOOl 

.0144 

.4139 

.OOOl 

.OOOl 

.OOOl 

.OOOl 

.3250 

a001 

.OOOl 

.I001 

.OOOl 

.OoOl 

.OOOl 

.OOOl 
Table 3-mntinued 

Ye= Tree tvw . 

Nashville warbler 

Yellow-rumped warbler 

Black-th. gray warble, 

Townsend’s warbler 

Hermit warble, 

MacGillivray’s warbler 

Wilson’s warbler 

Western tanager 

Black-headed grosbeak 

Lazuli bunting 

Rufous-sided towhee 

Fox sParrow 

Song sparrow 

Darkeyed junco 

Brown-headed cowbird 

Purple finch 

Red cmssbill 

Pine siskh 

Lesser goldfinch 

Evening grosbeak 

Chipmunks 

Douglas’ squirrel 

Western gray squirrel 

0.236 0.288 0.85 0.0001 

,090 ,149 .86 .ooOl 

,354 ,545 .84 .ooOl 

,003 ,013 .20 .1873 

1.729 1.791 .86 .OOOl 

,011 ,017 .37 .0199 

,206 ,312 .94 .OOOl 

,702 ,720 .84 .OOOl 

,407 ,501 .81 .Oool 

,003 ,001 -.07 .6561 

,081 S63 .94 .OOOl 

,001 ,007 .50 

,008 ,003 .95 

,509 .466 .88 

,021 ,011 30 

,007 .03 1 .56 .OOOl 

,162 ,154 .83 .OOOl 

,003 .I03 .55 .OOOl 

,018 ,019 .81 .OOOl 

,014 .019 .57 .OOOl 

.228 .325 .84 .OOOl 

,031 .027 .60 .OOOl 

:. ql.27 -.09 

: .-.59*** .37* 1 

/ ’ : .29 I. ‘, -.40** 

: 

;: ,::;p ,318 

,: ’ .43** : 

$0 ’ ,-.40** L”, .15 

::,. .oo -.14 

‘:y:‘“s : -17 .-. 

-.32* : 

-07 .- 

-.ll 

.0005 .I7 : 

.OOOl -.09 

.Oool .27 

.OOOl .04 

,068 ,091 .31 .0359 .I4 

.09 : 

.42** 

Although the majority of species had similar detection rates 

between years, 15 (21 percent) species showed significant 

differences (table 3). Most of these were rare species that 

undoubtedly varied because of the low numbers that were 

detected; only five were fairly abundant, having detection 

rates in either year in excess of 0.01 birds per station. Common species with abundances that changed significantly between years were the northern pygmy-owl, common bushtit, 

hairy woodpecker, Swainson’s thrush, and Townsend’s warbler. No common thread (such as food habits or foraging 

methods) unites these species; changes such as these are. to 

be expected in a study of several species. 

Geographic differences-Geographical variation in abundance is a pattern that overlies the species’ response to 

changes in the amount and suitability of its habitat. Even 

though the habitat may be suitable, factors that are related 

to geography (such as climate or competition with existing 

species) may preclude or severely limit the species’ presence, 

and mute its response to habitat. 

By comparing the average number of species recorded on 

the 15 stands making up each region (fig. l), we found that 

the northern Cave Junction stands averaged 37.3 species 

per stand, the Willow Creek stands averaged 32.4, and the 

Branscomb stands 32.6. The Cave Junction stands had significantly greater species richness than the southern stands 

(Duncan’s Multiple Range Test). 

We also found distinct patterns in the abundances of individual species in the northern and southern study sites. The 

majority of the species that showed differences between 

geographic regions were on a north-south cline (table 2). 

This cline was also of higher elevation with more tme fir in 

the north, and more hardwoods in the south (table 1). When 

region was the only significant variable selected in a GLM 

model, 12 species were more abundant in northern stands, 

and 14 were more abundant in southern stands. Among the 

species more abundant in either the north or the south were 

species with geographic affinities in either direction. Significantly more common to the north were the more montane 

species, such as blue grouse, olive-sided flycatcher, dusky 

flycatcher, mountain chickadee, MacGillivray’s warbler, 

Nashville warbler, yellow-romped warbler, fox sparrow, pine 

siskin, and evening grosbeak. The brown-headed cowbird 

and Townsend’s warbler were also more abundant in the 

northern regions. More abundant southern species included 

turkey vulture, mountain quail, Anna’s hummingbird, northern flicker, Steller’s jay, scrub jay, common raven, American 

robin, Hutton’s video, solitary vireo, orange-crowned warbler, 

Wilson’s warbler, western tanager, and rufous-sided towhee.