USDA United States 

7?:Zi5 Department 

of Agriculture 

Forest Service 

Rocky Mountain 

Research Station 

General Technical 

Report RMRS-GTR-32 

\ 

July 1999 

Habitat Relationships of 

Landbirds in the Northern 

Region, USDA Forest 

Service 

Richard L. Hutto 

Jock S. Young 

This file was created by scanning the printed publication.

Errors identified by the software have been corrected;

however, some errors may remain.
Abstract 

Hutto, Richard L.; Young, Jock S. 1999. Habitat relationships of landbirds in the Northern Region, USDA Forest 

Service. Gen. Tech. Rep. RMRS-GTR-32. Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain 

Research Station. 72 p. 

A series of first-generation habitat-relationships models for 83 bird species were detected in a 3-year study on point 

counts conducted in association with the USDA Forest Service's Northern Region Landbird Monitoring Program. The 

models depict probabilities of detection for each of the bird species on 100-m-radius, 1 O-minute point counts conducted 

across a series of major vegetation cover types. Based on these models, some bird species appear to be restricted in 

their habitat distribution to: (1) postfire, standing-dead forests, (2) relatively uncut, older forests, (3) harvested forest 

types, (4) marshes, (5) riparian environments, and (6) grasslands and sagebrush. Such restricted distributions highlight 

the need to provide adequate amounts of these cover types to maintain viable species populations. Many bird species 

were relatively abundant in harvested forests, suggesting a need for nesting success studies because timber harvesting 

creates unnatural cover types that may elicit settling responses by species that are 'iprogrammed" to respond to similar 

naturally occurring cover types. Thus, these unnatural cover types could be acting as "ecological traps," where species 

are being attracted to sites where suitability is relatively poor. 

These preliminary results demonstrate the utility of a landbird monitoring program, and suggest that agencies such as 

the Forest Service should consider broadening the indicator species concept to monitor groups of species (such as 

landbirds and butterflies) that can be easily sampled with a single field method. The list of species covered by this 

program is indeed large enough and ecologically broad enough to help managers predict and monitor the effects of 

management activities on almost all the major vegetation types in the region. The detail and region-specific nature of this 

information can be matched by no other database in existence on landbirds, and the information should prove useful to 

land managers in planning areas that might consist of alternative cover types. 

Keywords: bird-habitat associations, ecological trap, fire effects, indicator species, logging effects, monitoring, Northern 

Rocky Mountains, point count, riparian . 

The Authors 

Richard L. Hutto is a Professor of biology and wildlife biology in the Division of Biological Sciences at the 

University of Montana. He holds a B.A. degree in zoology from the University of California, Los Angeles, an 

M.S. degree in biology from Northern Arizona University, and a Ph.D. degree in biology from the University of 

California, Los Angeles. He has been working with the Northern Region of the USDA Forest Service on the 

development and implementation of a landbird monitoring program since 1990. Phone: 406-243-4292, and 

e-mail at hutto@selway.umt.edu 

Jock S. Young is a Research Assistant in the Division of Biological Sciences at the University of Montana. He 

holds a B.S. degree in zoology from Oregon State University, an M.A. degree in ecology from the University of 

California, San Diego, and an M.S. degree in biology from the University of Montana. He has worked on the 

landbird monitoring program in different capacities since 1993, and as a data analyst since 1996. 
Acknowledgments 

We received financial support for developing the landbird monitoring program from the USDA Forest Service's 

Northern Region (contract #53-0343-2-00207), the Bureau of Land Management (PO# 1422E070P50036), 

and Plum Creek Timber Company (check #191090). 

This support would not have been possible without the 

efforts of Alan Christensen, Sally Sovey, and Lorin Hicks 

from each agency, respectively. Indirect and in-kind 

support was provided by Montana Fish, Wildlife and 

Parks (thanks to Dan Casey), and Potlatch Corporation 

(thanks to Bill Wall). Alan Christensen, Skip Kowalski, 

and Kirk Horn provided the political support necessary to 

stimulate the growth of this program from an experimental one to one that has become a priority for Montana and 

the Forest Service. Sallie Hejl, of the Rocky Mountain 

Research Station, USDA Forest Service, provided detailed consultation and guidance during the design phases 

of our field studies. The first full-time Northern Region 

Landbird Monitoring Program Coordinator, Christine 

Paige, provided the logistic help necessary to hire field 

crews and then organized and cleaned the data that were 

submitted by the crews. Chris also provided just the right 

amount of resistance to proposed methodology so that 

we could develop the best working protocol to assure 

success before, during, and afterthefield season. Forest 

and District biologists were instrumental in positioning 

transects and in supervising field crews on their Forests. 

We are especially grateful to Paul Hendricks and Andrew 

Bosma for help with data management and analyses, 

and to Wendy Williams for help preparing graphics for 

this report. Sallie Hejl, Jared Verner, Kevin McKelvey, 

and Martin Raphael provided detailed comments on an 

earlier draft of the manuscript. Finally, we thank all of the 

field assistants, who, as readers will be able to judge for 

themselves, did a great job collecting the point-count 

data; from 1994 to 1996thesewereJ. Adams, J. Balcomb, 

L. Ballinger, J. Barilla, L. Bates, D. Bergeron, A. Bosma, 

D. Bourdin, D. Casey, A. Cilimburg, C. Couch, F. Curim, 

C. Cutler, M. DeVries, J. Dodge, K. Duell, R. Fergus, G. 

Fitzgerald, J. Goodell, G. Grunder, T. Grunder, D. Harvey, 

P. Heglund, S. Henderson, P. Hendricks,A. Hicks, E. Hill, 

S. Hitchcox, J. Hoffland, K. Hughes, R. Hutto, A. 

Jaunakais, K. Johnson, B. Keene, S. Kremer, E. Loomis, 

D. Martasian, G. Mazer, J. McBride, T. Mears, M. Mercurio, 

D. Miller, K. Miller, L. Miller, M. Mitchell, J. Moghaddas, 

B. Pitman, A. Porth, R. Pott, D. Powless, K. Pullen, J. 

Quinn, D. Reinkensmeyer, P. Reynolds', S. Ritter, J. 

Ross, J. Siotterback, C. Snetsinger, M. Teesdale, E. 

Thompson, P. Town, S. Winsor, N. Warren, D. Wirta, and 

J. Young. 

Contents 

Introduction ................................................................. 1 

Methods ...................................................................... 1 

Overall Design ......................................................... 1 

Locations of Long-Term Monitoring Points .............. 2 

Field Methods .......................................................... 2 

Point-Count Methodology ........................................ 2 

Vegetation Cover Type Associated with 

Each Point ........................................ , ................... 3 

Habitat-Relationships Models .................................. 7 

Bias .......................................................................... 8 

Bird Names ............................................................ 13 

Results ...................................................................... 13 

Species Accounts .................................................. 17 

Discussion ................................................................. 69 

Post-Fire, Standing-Dead Forests ......................... 69 

Relatively Uncut Forests ........................................ 69 

Harvested Forest Types ........................................ 69 

Marshes ................................................................. 70 

Riparian Vegetation ............................................... 70 

Grassland, Sagebrush, or Both ............................. 70 

Conclusions ............................................................... 70 

References ................................................................ 71 

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Habitat Relationships of 

Landbirds in the Northern 

Region, USDA Forest Service 

Introduction 

Richard L. Hutto 

Jock S. Young 

----------------------------

In 1993, the Northern Region of the USDA Forest 

Service initiated a regionwide landbird monitoring 

program so that managers might better understand 

the habitat relationships of landbirds that breed in 

the Northern Rocky Mountains and, in the future, 

might be able to assess longer-term landbird population trends. The program was initiated to help the 

Forest Service meet its legal mandate (National Forest Management Act of 1976) to monitor populations 

of "indicator" species as a mechanism to maintain 

viable populations of native vertebrates. Landbirds 

are a good indicator species "survey group" (Hutto 

1998) because they are highly visible and many species can be surveyed simultaneously. 

Maintaining the integrity of ecosystems will probably involve maintaining major vegetation cover 

types in "natural" amounts and distributions across 

a landscape. Therefore, the first step in the landbird 

monitoring program was to establish an objective 

and quantitative description of the distributions of 

bird species across the major vegetation types in the 

Northern Region. Although published bird field 

guides contain a rough idea of habitat associations, 

they do not provide quantitative information on 

differences in the probabilities of occurrence among 

vegetation types, especially the vegetation types created through timber harvesting and occupying large 

extents of landscape. Thus, we established a series of 

broadly distributed bird survey points throughout 

the region in an attempt to sample each major 

vegetation cover type adequately for the models. 

This publication (1) describes the overall design 

and field methods involved with the habitat relationships part of the Northern Region Landbird 

Monitoring Program, and (2) presents preliminary 

results of habitat relationships based on field surveys conducted between 1994 and 1996, the initial 

years of full-scale data collection at permanently 

marked points. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

49 

Q) 48 "C 

.~ 

16 

-J 47 If) 

Q) 

~ C) 

Q) 46 

0 

45 

44 

118 116 114 112 110 

Degrees Longitude 

Figure 1-The distribution of permanent landbird 

monitoring transects in northern Idaho and western 

Montana. 

108 106 

Methods __________ _ 

Overall Design 

Sample points were distributed across all 13 N ational Forests in the Northern Region. Data from the 

Custer National Forest, however, were confined to 

the Little Missouri National Grasslands of North 

Dakota and involved a different assemblage of species in largely nonforested cover types, so these data 

are not included here. A total of 566 10-point transects were geographically stratified by 7.5-minute 

topographic quadrangle maps throughout the nonwilderness lands of the other 12 National Forests 

(fig. 1) and were permanently marked in the field in 

1994 as part of this long-term monitoring effort. 

Each point was sampled once during each breeding 

season in three consecutive years (1994 to 1996), with 

a small number of changes in transect locations 

between years, as discussed in the results. Plans are 

to continue sampling about half of these points every 
2 years to provide a long-term database for monitoring. During the breeding season of 1994, we also 

conducted one-time visits to 761 additional sampling 

points among 84 transects that were stratified by 

cover type within a focal Landsat scene (path 41, row 

27), regardless of land ownership. This assured adequate coverage in each major cover type that we 

wanted to include in the models. 

Many variables affect the probability of detecting 

a bird at anyone point in space and time, including a 

bird's distance from the observer (Emlen 1971), the 

particular survey year (Hejl and others 1988), the 

observer (Cyr 1981, O'Connor 1981a, Kavanagh and 

Recher 1983, Ramsey and Scott 1981), time of day 

(Grue and others 1981, Robbins 1981a, Shields 1977), 

time of season (Best 1981, Ralph 1981), and weather 

(O'Connor and Hicks 1980, Robbins 1981b). Many 

researchers choose to minimize potential bias associated with data from a given point by conducting 

multiple counts per point, rotating observers among 

points, and collecting data across several years. The 

cost of increasing the accuracy of information from 

any point, however, is a reduced saniple size for each 

treatment (in this instance, cover type). Given that 

the goal of a habitat-relationships effort is to provide a reasonable estimate of the relative probability 

of occurrence across fairly broadly defined vegetation 

cover types, we felt that the best approach was to 

maximize the coverage of each type through large 

sample sizes, at the expense of repeat visits (Ralph 

and others 1995). Larger sample sizes do not necessarily eliminate such potential biases, however. We do 

not know the extent to which the pattern of a bird 

species' distribution across cover types is biased by 

factors confounding the actual relationship, but we 

highlight instances where we suspect that the reported distribution might be significantly biased, as 

discussed later in this report. 

Locations of Long-Term Monitoring Points 

The permanently marked, 10-point transects were 

initially mapped by Forest and District biologists 

who used the following transect and point placement 

protocol: 

1. They obtained 7.5-minute U.S. Geological Survey 

topographic quad maps, blue-line quads, or orthophoto maps for the entire target area (a National 

Forest). A topographic quad map was included in the 

set ifit contained at least 25 percent non-Wilderness 

Forest Service lands. 

2. Four transects were initially mapped in each 

topographic quad, one in each of four quartersections. Transect start points were located by positioning a random point within each quad quartersection and then finding the nearest point on an 

2 

unpaved, secondary or tertiary, open or closed road 

or trail. The remaining nine points constituting a 

transect were positioned at 300-m intervals in the 

direction determined by the flip of a coin, but not in the 

direction that would take the transect out of the 

quad quarter-section. Where there were curves or 

switch-backs, points were placed at least 250 m 

(straight-line distance) apart. 

3. Potential transects were retained only if there 

was reasonable access, defined as no more than a 

1.5-mile hike in (less than 1 hour) from where a 

vehicle could be parked, and no more than a 1- to 

1.5-hour drive from ,the nearest designated camping 

site. A single transect was randomly chosen from the 

potential transects within each topographic quad, 

and any others were retained as backups in the event 

that, after a field visit, the selected transect proved to 

be inaccessible. 

The same methods were used to position a series of 

transects on Potlatch Corporation lands in central 

Idaho and a small subset of Bureau of Land Management lands in western Montana. 

Field Methods 

The order of visits to transects was set by elevation 

and seasonal access. Relatively low-elevation transects were visited first, and relatively high-elevation 

sites last. While in the field, an observer marked the 

location of each permanent survey point with a numbered aluminum tag. The precise location of a point 

was marked on a color copy of the aerial photo associated with a given transect, and the aerial photo was 

subsequently used by personnel in the University of 

Montana Spatial Analysis Laboratory to position 

those locations onto a Geographic Information System 

(GIS) data layer. The following information was also 

entered on the cover page of a field booklet designed 

to contain all data pertaining to a particular transect 

in a given year: (1) year, (2) state, (3) name of topographic quad, (4) transect number-unique ninedigit identifier representing the latitude and longitude of the first count point to the nearest minute, 

(5) USDA Forest Service Region, (6) National Forest, 

and (7) Forest District. 

Point-Count Methodology 

Our field technique followed recommendations discussed by Ralph and others (1995) and methods described by Hutto and others (1986). All observers 

participated in a joint, I-week training session and 

then spent several days in calibration on their respective forests prior to the formal data collection. In 

general, a 10-minute point count was conducted at 

each of the 10 sampling points along a transect. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Points were visited once each breeding season between mid-May and mid-July. All birds seen or heard 

within the count period were recorded. Field observers generally began counts about 15 minutes after 

sunrise (after the predawn chorus), which was usually sometime between 0630 and 0700, and generally 

completed counts by 1030 or 1100. Counts were not 

conducted on days with continuous rain (not light 

drizzles) or days with wind that was constant and of 

enough strength to bend the tops of trees (Beaufort 5, 

as defined below). At each point, an observer recorded 

the following information into the field data booklet: 

1. The observer's name 

2. Date 

3. Point number on transect 

4. Time-of-day that the count was started 

5. Beaufort wind speed, coded as 0 [< 1 mph, smoke 

rises vertically], 1 [1 to 3 mph, wind direction shown 

by smoke drift], 2 [4 to 7 mph, wind felt on face, leaves 

rustle at times], 3 [8 to 12 mph, leaves and small 

twigs in constant motion, light flag extended], 4 [13 to 

18 mph, raises dust and loose paper, small branches 

in motion], 5 [19 to 24 mph, small trees sway, crested 

wavelets on inland waters] 

6. Weather condition coded as 0 [clear, or very 

few clouds], 1 [partly cloudy with sky roughly half 

obscured], 2 [mostly cloudy with a few sky openings], 

3 [fog or smoke that impairs visibility beyond 30 m], 

4 [light drizzle], 5 [constant snow] 

7. Air temperature 

8. Four-letter bird species code for each simultaneous detection of one or more individuals from a 

given distance and direction 

9. Number of individuals detected at a given distance and bearing 

10. Distance to the bird(s) to the nearest 5 m inside 

50 m, and to nearest 10 m beyond. 

"Spishing" was not allowed during a count, but 

was a perfectly acceptable way to attract nearby 

birds after a count to get positive identifications of 

birds detected before the end of the count. 

Vegetation Cover Type Associated with 

Each Point 

After the 10 point counts had been conducted, observers stopped at each point on the return trip to 

record additional information associated within a 

prescribed area surrounding each point. For the purposes of this report, the relevant variable was cover 

type-a 5-digit code (table 1) representing the vegetation cover type within which the count point was 

positioned. If the point was precisely on the edge 

between two or more types, the observer used the 

type in which the majority of birds were detected. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

We considered the Rocky Mountain landscape to 

consist of a matrix of land units, each relatively 

homogeneous in vegetation structure and plant species composition, and each differing from adjacent 

units according to the same criteria. Each sample 

point, therefore, fell within one of a range of vegetation 

cover types defined by a combination of the dominant 

plant species in the tallest vegetation layer and the 

vertical and horizontal vegetation structure (table 1). 

The basic cover type framework was one that included vegetation types dominated by one or more 

plant species. Open lands were usually dominated by 

grasses or sagebrush (Artemisia spp.). Several riparian covertypes1were used, including marshes, shrubby 

riparian areas (with willow [Salix spp.] or miscellaneous shrubs), aspen (Populus tremuloides) stands or 

cottonwood (Populus trichocarpa) bottomlands. 

Because conifer forest stands frequently undergo 

natural or human-induced disturbance that creates 

structurally different cover types, we defined our 

conifer cover types based on three criteria: tree species 

composition, successional stage, and, for the earlier 

stages, structure following disturbance (amount of 

canopy remaining). Tree species composition was categorized as either mixed conifer or as· a tree species 

type if more than 80 percent of the canopy consisted 

of one (or an associated pair) of conifer species 

(Douglas-fir [Pseudotsuga menziesii], ponderosa pine 

[Pinus ponderosa], lodgepole pine [Pinus contorta], 

western larch [Larix occidentalis], grand fir [Abies 

grandis], whitebark pine [Pinus albicaulis], limber 

pine [Pinus flexilis], a combination of western red 

cedar [Thuja plicata] and western hemlock [Tsuga 

heterophylla], a combination of Engelmann spruce 

[Picea engelmannii] and subalpine fir [Abies 

lasiocarpa]). 

We defined seven successional stages: recent disturbance, low shrub, tall shrub, pole/sapling, young, 

mature, and old growth. For the first four stages we 

designated a structural type (following disturbance). 

By the time the stand could be defined as young 

forest, the original structure following disturbance 

was considered less important and was usually unknown, so it was no longer designated. Our classification of disturbed forest types was based on the existing plant species composition and stand structure 

(what the birds respond to) without regard to the 

process that actually caused the structure. Names 

associated with structural types (patch cut, shelterwood, seed tree, clearcut) are, therefore, merelydescriptive of the process that probably (but not necessarily) 

gave rise to the current stand condition. We also had 

a common and diverse partially cut category (includingthinning, single-tree selection, overstoryremoval), 

which, because of the complexity of the stands, we did 

not assign to a successional stage. 

3 
4 

Table 1-Northern Rocky Mountain cover type classification scheme. 

10100-URBAN HUMAN DWELLING ("blocked" on quad maps; largely non-native vegetation) 

1 0200-RURAL HUMAN DWELLING (man-made structures imbedded in native vegetation) 

20100-IRRIGATED CROPLAND, RANGELAND, PASTURE 

20200-DRY CROPLAND 

301 xx-NATIVE GRASSLAND 

30111-short-grass; decent shape (no evidence of well-worn cattle trails) 

30112-short-grass; grazed by cattle (with bare soil, trails visible) 

30121-mid-grass; decent shape (no evidence of well-worn cattle trails) 

30122-mid-grass; grazed by cattle (with bare soil, trails visible) 

302xx-SAGEBRUSH, SHRUBSTEPPE 

30201--decent shape (no evidence of well-worn cattle trails) 

30202-grazed by cattle (with bare soil, trails visible) 

30300-DRY SHRUBFIELD (grasses generally fill the interstices between shrubs) 

401 xx-JUNIPER WOODLAND (grasses and sagebrush generally fill interstices between trees) 

401 01--decent shape (no evidence of well-worn cattle trails) 

40102-grazed by cattle (with bare soil, trails visible) 

402xx-PONDEROSA PINE (>80 percent of the canopy trees) 

40201-old growth (snags, down, self-thinned, big trees) 

40202-mature (multi-story, trees about 20-40 cm dbh) 

40203-young (few shrubs, canopy closed, most trees < 20 cm) 

40204-partially cut (multi-story, more open than mature) 

40205-group-selection cut; recent 

40206-group-selection cut; low shrub 2nd-growth 

40207-group-selection cut; tall shrub/seedling 2nd-growth 

40208-group-selection cut; pole-sapling stage 

40209-shelterwood cut; recent 

40210-shelterwood cut; low shrub 2nd-growth 

40211-shelterwood cut; tall shrub/seedling 2nd-growth 

40212-shelterwood cut; pole-sapling stage 

40213-seed-tree cut; recent 

40214-seed-tree cut; low shrub 2nd-growth 

40215-seed-tree cut; tall shrub/seedling 2nd-growth 

40216-seed-tree cut; pole-sapling stage 

40217-clearcut; recent 

40218-clearcut; low shrub 2nd-growth 

40219-clearcut; tall shrub/seedling 2nd-growth 

40220-clearcut; pole-sapling stage 

40221-postfire (standing dead); recent «5 yr) 

40222-postfire (standing dead); low shrub 2nd-growth 

40223-postfire (standing dead); tall shrub/seedling 2nd-growth 

40224-postfire (standing dead); pole-sapling stage 

403xx-DOUGLAS-FIR (>80 percent of the canopy trees) 

40301-40324-as defined above for ponderosa pine 

404xx-WESTERN LARCH (>80 percent of the canopy trees) 

40401-40424-as defined above for ponderosa pine 

405xx-LODGEPOLE (>80 percent of the canopy trees) 

40501-40524-as defined above for ponderosa pine 

406xx-MIXED-CONIFER (mix of conifer species; no single species >80 percent of the canopy) 

40601-40624-as defined above for ponderosa pine 

407xx-SPRUCEIFIR (>80 percent of canopy trees are Engelmann spruce or subalpine fir) 

40701-40724-as defined above for ponderosa pine 

408xx-WHITEBARKlLlMBER PINE (>80 percent whitebark pine or >80 percent limber pine) 

40801-40824-as defined above for ponderosa pine 

409xx-GRAND FIR (>80 percent of the canopy trees) 

40901-40924-as defined above for ponderosa pine 

410xx-CEDAR-HEMLOCK (>80 percent of canopy trees are cedar or hemlock) 

41001-41024-as defined above for ponderosa pine 

41500-ASPEN (includes both young and old stands) 

42000-CONIFER-DECIDUOUS FOREST MOSAIC (too mixed to classify as one or the other) 

50100-MARSH, BOG (often cattails along the edge) 

50200-SEDGELAND, WET MEADOW 

50300-WILLOW FLATS (associated with broad, meandering rivers) 

504xx-COTTONWOOD BOTTOMLAND 

50401--decent shape (lush understory, no visible browse line) 

50402-grazed by cattle (understory, sharp browse line) 

505xx-STREAMSIDE RIPARIAN (narrow strip of deciduous vegetation along stream) 

50501--decent shape (stream banks intact, no well-worn trails or shrub "notching") 

50502-grazed by cattle (stream banks trampled, stock trails apparent, shrubs "notched") 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Because our classification scheme resulted in a 

large number of possible cover types (243; table 1), 

and many of these ended up with few or no sample 

points, we combined types to create a smaller series 

of vegetation types prior to model building (table 2). 

We combined categories based on our subjective impression of similarity in both vegetation structure and 

bird composition, aided by exploratory cluster analyses of those cover types with sufficient data. The 

mature and old growth stages under each forest type 

were combined into a single undisturbed category 

for each forest type. These stands showed no significant signs of recent logging activity, although they 

might have been initiated by logging in the past. This 

resulted in six types of uncut forest based on species 

composition (table 2). Data from each of four harvest 

treatments (Partial Cuts, including thinned, shelterwood, overstory removal; Patch Cuts, including 

group-selection cuts; Seed-tree Cuts, including other 

similar harvest units; and Clearcuts) and Post-Fire 

conditions were combined across conifer forest types, 

resulting in five "disturbance" categories for conifer 

forests (table 2). For clearcuts, the pole-sapling stage 

was retained separately from the earlier three successional stages as "Old Clearcut" because this stage is 

structurally different from recently cut areas and 

represents a transitional stage to Young Forest. The 

three early stages (recent, low shrub, and tall shrub/ 

seedling) were combined as "Clearcut." Within the 

other four disturbance categories, we combined all 

four temporal stages of postharvest development from 

the "recent" stage to the pole-sapling stage (these 

stages were never reported for the Partial Cut category) . Young I Forest also included all tree species 

compositions. Data from residential areas, croplands, 

mixed broadleaf/conifer, dry shrubfield, juniper 

(Juniperus scopulorum) woodland, tundra, and barren land cover types were insufficient for separate 

analyses and were eliminated rather than lumped into 

one of the other cover types because of the relatively 

distinct vegetation structure associated with each. 

Larch, whitebark, and limber pine forests were also 

Table 2-For each of 18 cover type categories used to depict available habitat in the Northern Rocky Mountains, the table includes the finer 

resolution cover types included in that category, a category description, and the number of transect points that were used in habitatrelationships in each of the 3 years of the study. Photographs of representative cover types within each of the 18 broader categories are 

in a companion field methods manual (Hutto and Hoffland 1996). 

Cover type 

category 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Number of points used 

1994 1995 1996 

57 40 49 

53 65 62 

84 118 108 

344 522 587 

140 105 126 

24 20 32 

157 213 144 

Cover types included 

41001,41002,40901,40902 

40701,40702 

40501,40502 

40601,40602 

40301,40302 

40201,40202 

40203,40303,40403,40503, 

40603,40703,40803,40903, 

41003 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Description 

At least 80 percent of the canopy cover in this type was 

comprised of grand fir or a combination of cedar and 

hemlock, and it included mature and old growth stages. 

At least 80 percent of the canopy cover in this type was 

comprised of a combination of spruce and subalpine fir. 

The type includes forests in mature and old growth 

stages. 

At least 80 percent of the canopy cover in this type was 

comprised of its namesake, and it included mature and 

old growth stages. 

No single conifer species made up more than 80 

percent of the canopy cover in this forest type. This 

category included mature and old growth stages. 

At least 80 percent of the canopy cover in this type was 

comprised of its namesake, and it included mature and 

old growth stages. 

At least 80 percent of the canopy cover in this type was 

comprised of its namesake, and it included mature and 

old growth stages. 

This type includes young forest from all of the above 

types, regardless of tree species combination. These 

were stands with the majority of trees under 20 cm dbh. 

Physiognomically, these were usually closed-canopy 

stands with little understory. 

(con.) 

5 
Table 2 (Con.) 

Cover type Number of points used 

category 1994 1995 1996 Cover types included Description 

Partial Cut 755 432 416 40204,40304,40404,40504, This type includes forest stands with a variable amount 

40604,40704,40804,40904, of mature canopy trees removed, from minor thinning 

41004 to major overstory removal. It includes shelterwood 

40209-40212,40309-40312, cuts, in which uniformly spaced, large trees were left 

40409-40412, 40509-40512, to provide shade for regenerating seedlings. 

40609-40612, 40709-40712, 

40809-40812, 40909-40912, 

41009-41012 

Patch Cut 73 43 43 40205-40208, 40305-40308, This type includes forest stands wherein clusters 

40405-40408, 40505-40508, of trees were removed, leaving the appearance of 

40605-40608, 40705-40708, clusters of trees with large open spaces in between. 

40805-40808, 40905-40908, Physiognomically, this type includes stands in the 

41005-41008 earliest postharvest successional stage (with shrub and 

seedling development still below 1 m in height) up to 

the pole-sapling stage (with trees up to about 10-cm 

dbh). A relatively small proportion (less than 5 percent) 

of this type consisted of what were fairly pure stands of 

one of the conifer species designated above; most of 

the pretreatment stands were mixed-conifer. 

Seed-tree cut 68 51 34 40213-40216,40313-40316, This type includes forest stands wherein most trees 

40413-40416, 40513-40516, were removed and a few widely spaced (generally 

40613-40616, 40713-40716, fairly mature) trees were left. All stands with these 

40813-40816,40913-40916, general features were included regardless of. what 

41013-41016 the silvicultural prescription may have been. 

Clearcut 100 95 76 40217-40219, 40317-40319, This type includes forest stands within which nearly 

40417-40419,40517-40519, all trees have been removed; only a few snags or a 

40617 -40619, 40717-40719, smattering of (generally small) trees remain. This type 

40817-40819,40917-40919, is similar to the postfire category except that there are 

41 017 -41 01 9 numerous standing dead trees in the "natural" postfire 

situation. Succesional stages from recent to tall shrub 

stages are included here. 

Old Clearcut 175 90 76 40220,40320,40420,40520, This type includes forest stands within which nearly all 

40620,40720,40820,40920, trees were removed, as above; only the more advanced 

41020 sucessional stage is included here, generally consisting 

of a pole-sapling conifer stand. 

Post-Fire 44 37 46 40221-40224, 40321-40324, This type consisted of forest stands that had experienced 

40421-40424, 40521-40524, a relatively intense stand-replacement crown fire, as 

40621-40624, 40721-40724, evidenced by the presence of numerous blackened, 

40821-40824, 40921-40924, standing-dead trees. 

41021-41024 

Sagebrush 79 84 61 30201,30202 This type is dominated by its namesake, although 

native grasses and junipers may have been present. 

It includes both heavily grazed and relatively ungrazed 

subgroups. 

Grassland 111 74 57 30111,30112,30121,30122 This type includes short- and mid-grass prairies. 

Wetland 24 57 34 50100,50200 This riparian type includes areas with standing water 

that supported either short-statu red marsh or meadow 

vegetation. 

Riparian Shrub 212 344 252 50300,50501,50502 This type includes areas that have a well developed 

riparian vegetation component dominated by shrubs 

(for example, alder, maple, willow). 

Cottonwood/Aspen 57 83 48 41500,50401,50402 This riparian type includes aspen stands of all kinds, 

and streamside areas that generally contain an 

abundant cottonwood canopy cover. 

6 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
excluded due to low sample sizes. Grand fir forests 

were combined with cedar-hemlock, because birds 

probably respond to these similarly, and each was 

sampled insufficiently when considered alone. Aspen 

was also combined with Cottonwood for the same 

reasons. Bird species that responded differently to 

these two types are noted. The final categorization 

resulted in 18 cover types (table 2). 

Habitat-Relationships Models 

We present habitat distributions as the observed 

percentage of points within each cover type at which 

a given species was detected. The histogram bars for 

each species show the mean and standard deviation 

of the observed percentages across the 3 years of 

data within each cover type. The error bars should not 

be used as a statistical test of differences among cover 

types because they involved only 3 years, they were 

not strictly independent samples, and they do not 

reflect the differing sample sizes (and thus the variable accuracy) associated with each cover type. Error 

bars were included only as indications of the consistency of the results across years. 

For nonriparian cover types, we excluded points 

that were positioned within 100 m of the edge of 

another cover type to reduce the chance that birds 

would have been detected within a cover type that 

differed from that recorded at the census point. For 

each of the three riparian types (Wetland, Riparian 

Shrub, and Cottonwood/Aspen), however, we had to 

include all points, whether or not another cover type 

was within 100 m, because most riparian patches 

are small or narrow and, therefore, virtually all points 

were located within 100 m of another cover type. Thus, 

the number of points used to calculate the probabilities of occurrence across cover types was substantially 

less than the number actually conducted in the field 

(about 40 percent, including removal of minor cover 

types). In addition, we used only bird detections that 

occurred within 100 m of the observer, to exclude birds 

that may have been in another, unknown cover type 

beyond this observation limit. Thus, the resultant 

probabilities of detection are associated with relatively homogeneous patches of each cover type. The 

fixed radius also increased the chance that a difference in the probability of occurrence between two 

cover types was the result of a difference in the abundance of a species and not a difference in its detectability within different vegetation types (Hutto and 

others 1986). 

For most species, individuals detected flying over 

the site were excluded. However, species that forage 

or display aerially, such as swifts, swallows, Common 

Snipe (see table 3 for scientific names of all bird 

species observed), and Common Nighthawk, were 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

frequently detected as flyovers and were generally 

"using" the airspace within 100 m of the observer 

when detected. Therefore, for those species, we included flyover data with the fixed-radius data before 

building habitat models. 

We used individual points as sample units for calculating the percentage detected on a 10-minute point 

count in a given cover type. Unfortunately, because 

sample points occurred across the landscape in clusters of 10 (per transect), multiple samples of a given 

cover type within a single transect were not statistically independent estimates of bird composition 

within that cOlver type. Nevertheless, we used individual points as sample units because (1) combining 

data from all points on a transect would create meaningless sample units with respect to cover type, given 

that transects themselves run through a series of 

different cover types; (2) given a mixture of cover 

types on each transect, and the elimination of points 

near edges, we included, on average, only 2.3 points 

per transect from any single cover type; and (3) we are 

not drawing conclusions based on statistical evaluation of the differences among cover types. 

Unfortunately, it is difficult to know the minimum 

number of detections needed to generate a meaningful model, although the bird species that were detected on only a few points were certainly not detected 

frequently enough to justify plotting the distribution 

of occurrences among cover types. Because model 

reliability undoubtedly increases with number of detections, but the shape of the relationship between 

accuracy and sample size is unknown, the minimum 

number of detections needed becomes a subjective 

decision. One guideline may be the sample size recommended for a chi-square contingency table. To achieve 

expected values of at least five for all 18 cover types 

would require 90 individuals. There were 28 species 

that were detected on at least 90 points in each year. 

Because we were not actually conducting statistical 

tests, however, we felt that species with fewer individuals still provided sufficient data to produce meaningful graphical models. We chose to present patterns 

of distribution for species that were detected within 

100 m on at least 25 points in each of the 3 years. In 

addition, for 29 less frequently detected species, we 

included graphs that were based on a pooling of data 

from all 3 years. These species had more than 30 

detections over the total period, and their graphs can 

be readily distinguished from the data-rich graphs 

because they consist of open histograms that lack 

error bars. These graphs may not be as reliable an 

indicator of habitat distribution due to the small 

sample size and the nonindependence of points from 

several years, but the resulting patterns of occurrence for some of the rarer species were instructive to 

look at and may serve to stimulate further research. 

7 
In figures 8 to 101, the vegetation cover types are 

listed from the moister to the drier "uncut" conifer 

types, followed by the harvested conifer forest, 

nonforest, and riparian types. The harvested forest 

types are listed in order of increasing amount of 

timber removed (although the Partial Cut category is 

variable and the Patch Cuts were, by definition, heterogeneous). It may be noted that Old Clearcuts may 

be structurally more similar to Young Forest than to 

the more recent Clearcuts next to which they were 

placed on the graphs. Patterns of habitat use for a 

species were made as clear as possible by scaling the 

percent occurrence relative to the longest bar (cover 

type within which the species was detected most 

frequently). Unfortunately, this does not facilitate 

across-species comparisons of abundance because the 

longest bars of a common species represent a much 

higher detection percentage than those of a rarer 

species. Such comparisons of abundance are inappropriate in any event because the point-count data have 

not been adjusted for differences in baseline detectability among species. 

Bias 

The reported models show the observed percentages of detection for all species. Any assumption that 

these may be used to predict future occurrence in the 

various cover types depends on our having an unbiased representation of true habitat distributions. As 

discussed earlier, many variables are known to affect 

the probability of detecting a bird at anyone point in 

space and time, including the bird's distance from the 

observer, the particular year, the observer, time of 

day, time of season, weather, and so forth. Our large 

sample size over a wide region helps to average out 

many of these sources of variation. However, any 

variable affecting the birds that also differs consistently among cover types may confound our results for 

observed bird distributions across those types. Because we collected data on many of these potential 

sources of bias, we examine their possible effects on 

our results and discuss each source of bias briefly. 

Yearly Variation-We present the data for the 

more frequently detected species (some of fig. 8 to 

101) as means of all 3 years with a standard deviation. 

This will help to average out year-to-year changes in 

habitat distribution and avoid possible bias associated 

with results from anyone year. While it is unlikely 

that a bird species will shift between structurally 

different cover types between years, it is quite possible that the pattern of use of the relatively similar 

forest types may differ from one year to the next, and 

the error bars will reflect such variation. The error 

bars are, of course, a reflection of all sources of sampling error, including yearly variation in cover type 

occupancy. 

8 

Other data on patterns of cover type use suggest 

that the relative abundance of a species among cover 

types is similar from one year to the next, even though 

the absolute abundance in anyone cover type may 

change markedly from year to year (for example, 

O'Connor 1981b). Such a pattern would result in 

large error bars, even though the relative differences 

among cover types might be consistent from year to 

year. Thus, the error bars must be viewed with some 

caution, but should, nevertheless, provide an indication of the consistency of our results. 

Geographic Distribution-Habitat distribution 

models may be biased by the inclusion of points outside the geographic range of the species because of the 

inclusion of suitable habitat that is geographically 

unavailable to the birds. The Continental Divide represents a climatic and biogeographic boundary within 

our region, with drier and more open vegetation cover 

types on the eastside. About 32 percent of the points 

were east of the Divide, but these included 76 percent 

of the Grassland and Sagebrush cover, 58 percent of 

the riparian areas, 63 percent of the Lodgepole Pine, 

46 percent of the Douglas-fir, and 42 percent of the 

Ponderosa Pine, but no Cedar/Grand Fir and only 15 

percent of the harvested forest stands, 17 percent of 

the Spruce/fir, and 18 percent of the Mixed Conifer. 

Many bird species also had different probabilities of 

detection on either side of the Divide, and most of 

these differences were probably due to differences in 

the occurrence of their respective habitats on either 

side of the Divide. However, of 46 species that were 

regularly detected west of the Divide (on more than 

2 percent of the points), 12 species were so rare east of 

the Divide (0 to 21 records) that they may be considered limited in geographic range to west of the Continental Divide. Inclusion of data from the eastside in 

habitat models may give misleading results for these 

species. To determine if this would change any conclusions about relative habitat distributions, we 

created new habitat distribution graphs for these 

species (Pileated Woodpecker, Steller's Jay, Blackcapped Chickadee, Chestnut-backed Chickadee, 

Brown Creeper, Winter Wren, Varied Thrush, Nashville 

Warbler, Wilson's Warbler, Black-headed Grosbeak, 

Fox Sparrow, and Evening Grosbeak), which included 

only the data from west of the Continental Divide. We 

present this alternative graph in addition to the original if the differences were noteworthy. 

In addition, several common species were several 

times more likely to be detected in the westside than 

in the eastside, but because these species did occur in 

the eastside at low levels, the difference may have 

been due to habitat rather than geographic range 

limitations. However, the Townsend's Warbler appears to have a fairly clear range restriction (Montana 

Bird Distribution Committee 1996), so this species 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
was treated as above. Restricting data to the westside 

meant that several cover types were represented by 

less than 10 to 20 points in some years, so we pooled 

the data from all 3 years to construct these graphs. 

Inspection showed all resulting patterns to be the 

same as would result from showing the means and 

(standard deviations) of the 3 separate years. 

Time of Season-Although we restricted our data 

collection to the period of the breeding season during 

which most bird species were actively singing, many 

species showed variation in singing intensity during 

this period. Thus, detection probabilities for many 

species apparently changed as the breeding season 

progressed. For example, we detected many species 

less often in the first week or the final 2 to 3 weeks of 

our sampling period. Some species reduced their 

singing even earlier, and a few strongly increased 

their singing through the season. The habitat distribution graphs for these species may have been biased 

if there were cover types that were sampled more (or 

less) frequently during the period of peak singing than 

during the period of relatively infrequent singing. 

Overall, the various cover types were well sampled 

throughout the season (fig. 2), but a close inspection 

of histograms showed that there may still be some 

potential biases associated with a few cover types 

that were sampled relatively unevenly across the 

season. This is especially true for high-elevation cover 

types such as Spruce/Fir (fig. 3a) and Lodgepole Pine. 

More accessible cover types, such as Ponderosa Pine 

Cedar/Grand Fir""! + + -ttttt+ +-H+++Hi- +-t+++tt+H-+ +Hi- -++ +-H+ + 

Spruce/Fir~ 

Lodgepole Pine~ 

Mixed Conifer1 

DouglaS-Fir~ 

Ponderosa Pine~ 

+ -tt++ + -H+ -Httt-++ 11111111111111111111 +-++ 

+Hi- + -H+++++ttt -Httt +H+H+++++++-+t++++ -H+I-l+ ++++++++-+++++ 

11111111111111111111111111111111111111111111111111111111111111111111 

+H+ttH+Ht+ -t++H++++H+ +tH+ -H+ 1111111111111111 + -H+I-l+ + 

+ -ttttt+++H- ++Hi- +H-+ ++ -++ + + + -+++ 

Young Forest"i +Hi- 111111111111111111111111111111111111111111111111111111111111 + 

Partial Cut ~ 1111111111111111111111111111111111111111111111111111111111111111111 

Patch cut"i -Httt -Httt -tt+++t++++-++++t++- -tt++-H++ +-++ +Hi- + 

Seed-tree Cut-i + +-Httt-t+tt+t++t+H++++++++++++I++++--++ +++-++tt+tt 

Clearcut~ + -++++t++-+H-IIIIIIIIIIIIIIII-Httt +tt+++-IIIIIIIIIIIII +HOld Clearcut-1 -++ +-1++-+++-++-++ t+++tH+tt+t+tt+tt+++++++++++l++tt+tt++ 

Post-Fire"i ++-++ +-+++++ -++ + +H--Httt-++ + +tt+tt+ 

Sagebrush~ -++-++-tt++ +H++t-+++++Itt -H+ -H+ +++ + ++ 

Grassland~ -+++-t++t+t+t + -+++++H++++ -++++ -Httt ++ ++ttt- + + 

Wetland-1 +-++ +-H++-+++Hi- ++-++++#- -+++ +++ +I-H+H-H+tt+++ 

Riparian Shrub1 ++H+-H+H+t 111111111111111111111111111 IIIIIIIIIIIIIIIIIIII-H++ 

CottonwoodlAspen-! ++#- +++Itt +t++++++H+-Httt ++++ttt-H+H+++ + +tt+++-++ : 

I , I I I I I I i 130 140 150 160 170 180 190 200 210 

Julian date (130 = May 10) 

Figure 2-Sampling effort of point counts across 

season by cover type. Plus signs may represent 

multiple points. Note the limited sampling of Spruce/ 

Fir early in the season. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

I/) 

C 

'0 

a.. 

'0 

:v 

.0 

E 

:::l 

Z 

I/) 

c 

'0 

a.. 

'0 

Q; 

.0 

E 

:::l 

Z 

70 

60 

50 

40 

30 

20 

10 

0 

a. Spruce/Fir 

515 522 529 612 619 626 703 710 717 

Week (with beginning date) 

b. Ponderosa Pine 

Week (with beginning date) 

Figure 3-Sampling effort of point counts across 

season within (a) Spruce/Fir, sampled mostly late in 

the season, and (b) Ponderosa Pine, sampled 

mostly early in the season. 

(fig. 3b), Sagebrush, and Riparian Shrub, were sampled 

more frequently in the early part of the season. Therefore, for a bird species that sang more later in the 

season, such as the Swains on's Thrush (fig. 4), our 

results may have shown artificially low probabilities 

of detection in earlier sampled cover types, because 

many of the points in those cover types were not 

sampled in the period during which the species was 

most detectable. Likewise, bird species with declining 

detection rates through the season, such as Brownheaded Cowbird (fig. 5a) or, in the most extreme case, 

Ruffed Grouse (fig. 5b), may not be accurately represented in the samples of higher elevation cover types 

sampled later in the season. Therefore, for those bird 

9 
Swainson's Thrush 

50~-------------------------------------~ 

en 

c 

o U 40 Q) 

Q) 

u 

.r:. 30 j 

en 

C '&. 20 

'0 

C 

~ 10 Q) 

0.. 

529 605 612 619 626 703 710 717 

Week (with beginning date) 

Figure 4-Percent of 10-minute point counts with 

at least one detection of the Swainson's Thrush, by 

week (3 years combined) across the season. 

species that showed marked seasonal shifts in detectability, we constructed an alternative cover type bar 

chart from a more restricted period of the breeding 

season during which the species was consistently 

common. 

Specifically, for each of the 19 species for which 80 

percent of the detections occurred by June 28 we 

included data from dates that covered the first 80 

percent of the data (80 percent of the total points 

were not completed until July 5). Likewise, for the 

six species with the most dramatic increase in detection rates (80 percent of detections after June 6) we 

included data from dates covering the last 80 per~ent of the detections. Because of reduced sample sizes, we 

pooled the data from all 3 years to construct these 

graphs. A comparison of the two alternative bar 

charts was used to search for potential biases in the 

pattern of cover type use based on the entire data set. 

We present the alternative graph in addition to the 

original if the differences were noteworthy. 

Detectability-The pattern of distribution among 

cover types for a given species may be biased by 

detectability differences among cover types of different vegetation structure (Verner 1985). This will be 

especially true if unlimited-distance survey methods 

are used, or if there is an attempt to estimate density 

based on detection distances. One of the main advantages of the fixed-radius point count method that we 

used is the elimination of long-distance detections 

that would be especially subject to detectability bias 

among cover types (Hutto and others 1986). Many 

authors, in fact, suggest using data taken from a 

maximum distance of 50 m (Ralph and others 1995, 

10 

en 

c 

o 

U 

2 

Q) 

u 

:5 

-~ 

en 

C 

'0 

0. 

'0 

C 

Q) 

~ Q) 

0.. 

en 

C 

o 

U 

2 

Q) 

u 

:5 

'~ 

a. Brown-headed Cowbird 

Week (with beginning date) 

b. Ruffed Grouse 

Week (with beginning date) 

Figure 5-Percent of 10-minute point counts 

with at least one detection of the (a) Brownheaded Cowbird, and (b) Ruffed Grouse, by 

week (3 years combined) across the season. 

Verner 1985). However, our results showed that using 

this distance as a maximum would result in an average of only five bird detections (of 3.5 species) per 

point count. Increasing the distance to 100 m allowed 

us to use an average of nine bird detections (of 6.1 

species) per point in our analyses. 

Bias in detect ability among cover types is likely to 

be due to a decreased probability of detection in denser 

vegetation. Indeed, the mean distance to observed 

birds differed significantly among cover types (fig. 6), 

with the mean detection distance being highest in 

Grassland and Sagebrush areas and lowest in the 

forested cover types. Within forest types, however, 

results were unexpected, with the highest detection 

USDA Forest Service Gen. Tech, Rep, RMRS-GTR-32. 1999 
Cedar/Grand Fir f------tr---i 

Spruce/Fir ~ Lodgepole Pine f----B--i 

Mixed Conifer fe1 

Douglas-fir H 

Ponderosa Pine f-------e-----1 

Young Forest ~ Partial Cut fej 

Patch Cut f--e---1 

Sparse Cut f--a---1 

Clearcut H 

Old Clearcut H 

Post-Fire f------a--1 

Sagebrush ~ Grassland f-----B-1 

Wetland ~~ Riparian Shrub ~j 

Cottonwood/Aspen f--a---1 

40 50 60 

Mean detection distance (m) 

Figure 6-Mean distance (with 95 percent 

confidence interval) to individuals of the 30 

most common species (combined) within each 

cover type. 

70 

distances in Cedar/Grand Fir, which was the cover 

type with the densest vegetation (highest average 

canopy cover; fig. 7). This result may have been due to 

errors in distance estimation. If a detected bird song 

sounded quieter than one heard in another cover type, 

the observer may well have estimated a greater distance to the bird, even if the actual cause of the lower 

volume was the denser vegetation rather than the 

distance. The end result would be similar: fewer birds 

would be recorded as being within 100 m in dense 

vegetation relative to open. However, we cannot 

quantify this bias because the only measure we have 

(estimated distance) is itself biased by the same differences between cover types. 

If we cannot quantify the bias, we at least know 

what to expect; our analyses should be conservative 

in claiming species to be relatively abundant in dense 

versus open stands, but may be too liberal in finding 

the reverse. Fortunately, the former are more likely to 

be the species of most concern because management 

practices are more likely to convert dense forest to 

open rather than vice versa (with the possible exception of dense young stands). It is also of interest that 

two of the species most difficult to detect at greater 

distances (Golden-crowned Kinglet and Brown 

Creeper) can still be shown by our methods to be more 

abundant in dense forests. 

Old Growth-Another source of bias may be the 

nonuniform inclusion of important habitat elements 

among cover types. For example, since old growth and 

mature forests are lumped together in each of the 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

uncut forest cover types, a species that actually prefers old growth may be more frequently detected in a 

cover type such as Cedar/Grand Fir (which happens 

to have a relatively large proportion of its points in 

old growth). To examine whether a bird species' distribution among cover types was biased by the nonuniform coverage of old growth among cover types, we 

determined which species were more frequently detected in old growth compared with mature forests 

(regardless of cover type), and we then examined the 

distribution of these species among uncut forest 

types for each successional stage. These distributions 

were compared with that produced by the overall data 

set to check fo~ any apparent differences. We present 

the alternative graph in addition to the original if 

the differences were noteworthy. 

Roadside Counts-The reliance on roads or easily 

accessed trails for our transect locations resulted in 

some geographic biases (fig. 1). Roadless areas, especially wilderness, were not sampled, except at the 

edges by transects anchored at trailheads. This greatly 

reduced sampling in high-elevation vegetation types 

and remote landscapes. However, most cover types 

were adequately sampled (table 2). The question remains, however, whether data from those cover types 

were biased by the physical presence of roads. 

If bird species abundance data collected at points on 

roads differs from that which would have been collected at points in the interior of stands, then placement of most transects along roads would give rise to 

two issues of potential concern: (1) that some bird 

Cedar/Grand Fir f------tr---i 

Spruce/Fir f--e---1 

Lodgepole Pine f----B--i 

Mixed Conifer fe1 

Douglas-fir H 

Ponderosa Pine f-------e-----1 

Young Forest ~ Partial Cut fej 

Patch Cut f--e---1 

Sparse Cut f--a---1 

Clearcut H 

Old Clearcut H 

Post-Fire f------a--1 

Sagebrush f-t;----1 

Grassland ~ 

Riparian 

Wetland 

Shrub 

~ 

M 

Cottonwood/Aspen f--a---1 

40 50 60 

Mean detection distance (m) 

Figure 7-Mean canopy cover (percent) within 

each cover type. Canopy cover was estimated 

within 30 m of the bird count point by the field 

observer following the bird surveys. 

70 

11 
species may use particular cover types only because of 

the presence of the road, and (2) that the proportion of 

on- and off-road points differs among cover types such 

that a roadside effect might produce a biased picture 

of habitat use. 

Most transects were on tertiary logging roads, and 

many were closed to motorized vehicles, so disturbance from traffic was not likely to be an issue. N evertheless, even tertiary logging roads often resulted in 

wide gaps in the tree canopy, as well as roadside 

shrubs and saplings due to increased light and runoff 

water. These habitat modifications may result in 

changes in bird use. However, our sampling of a 100-

m-radius circle assured that we were including a large 

area unmodified by the road. The use of presence/ 

absence data may have also helped mitigate the quantitative effect of roads. 

Hutto and others (1995) studied the difference between on-road and adjacent off-road point counts in 

Montana as part of this Landbird Monitoring Program. They found that almost all species were readily 

detected at on-road points, with no species significantlymore abundant at the off-road points, but seven 

species were significantly more abundant at on-road 

points. Habitat modification from roads seemed to 

bring bird species normally associated with open forest (such as Chipping Sparrow and American Robin) 

and shrubby vegetation (such as Warbling Vireo, 

MacGillivray's Warbler and Wilson's Warbler) into 

areas of closed forest canopy. Similar results were 

found by Keller and Fuller (1995) in Virginia, and 

Hanowski and Niemi (1995) in Minnesota. 

This study was not designed to test the effects of 

roads on bird detections. The vast majority of our 

points were along roads. Roadside and trailside points 

were not paired, and trails may have been in different 

landscapes, cover types, and elevations relative to 

roads. Also, trails may still involve some habitat modification. Therefore, we cannot analyze the potential 

effects of roads using our data. It is clear, however, 

that most logged stands were near roads, whereas 

trails were much more likely to. be in undisturbed 

cover types such as uncut conifer forest. Thus, it may 

not always be possible to separate the effects of roads 

per se from differences in cover type use. 

The use of roadside counts may bias our habitat 

models to some extent. Species of dense forest may 

have been detected less frequently than they would 

have at off-road points, but the relative abundance 

among cover types is not likely to have been altered, 

unless 'they avoid roads to differing degrees in different habitats. On the other hand, species such as 

the Black-capped Chickadee or Warbling Vireo may 

be drawn by roadside vegetation to forest cover types 

where they might otherwise not occur. However, the 

preference of most of these species for logged or 

12 

riparian vegetation was still obvious from our graphs. 

Managers must be aware of the potential effects of 

roads in our models, especially for species more or less 

abundant in the more heavily roaded cover types (such 

as logged forests). 

Observer Bias-A large sampling program such as 

this requires numerous observers to complete. Although all observers participated in an intensive, 

week-long training session, their abilities ~nd motivation in the various aspects of data collection certainly 

varied. Dramatic differences have been shown in the 

ability to detect birds among observers (Cyr 1981, 

Kavanagh and Recher 1983, Smith 1984, Verner 1985). 

We expect that observers also differed in their ability 

to identify bird species, estimate distances, and categorize cover types. 

We cannot quantify these differences because we did 

not have multiple observers visiting the same points 

simultaneously (except for a few informal tests during 

the training sessions). We have assumed that the 

diversity of observers would spread the variability 

among cover types and regions so that there were no 

systematic biases. Systematic biases were most likely 

to occur where multiple observers were prone to the 

same errors. Such errors were especially likely in the 

identification of bird species pairs that are difficult to 

distinguish. Dusky and Hammond's Flycatchers were 

the most difficult species to distinguish by sight and 

song. Other pairs of species that had similar songs 

were Dark-eyed Juncos and Chipping Sparrows, and 

Mountain and Black-capped Chickadees. A few observers may have had difficulties with other species, 

such as some of the warblers or woodpeckers. These 

biases would increase the apparent breadth of cover 

type usage by some species if they were falsely reported in cover types where they are less likely to occur 

(such as Hammond's Flycatchers in clearcuts). 

Each National Forest had two observers in each 

year, and usually a new set every year. In only four 

cases did observers cover the same National Forest for 

2 years (conducting 19 to 37 percent of analyzed points 

on the forest), and none for 3 years. Overall, 66 percent 

of the point counts were conducted by observers who 

were employed for only 1 year. By cover type, the most 

dominant observer within each type accounted for 6 to 

20 percent of the points in that type. Specifically, the 

cover types most dominated by a single observer were 

Grassland (19.7 percent), Cedar/Grand Fir (17.8 percent), Cottonwood/Aspen (17.0 percent), and Patch 

Cut (16.4 percent). Therefore, although interobserver 

biases were probably significant, no one observer dominated any given region or cover type. The less common 

cover types are, as usual, most vulnerable to such 

biases, especially the most regionally restricted ones 

such as Cedar/Grand Fir. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Bird Names 

Common and .scientific bird names, as well as species order, follow the American Ornithologists' Union 

Check-list of North American Birds (1998). Species 

that were split into distinct species (for example, 

Solitary Vireo) after we collected our field data were 

identified on the basis of geographic range. 

Results ----------------------------------

We recorded bird and vegetation data from a single 

visit to each of 5,509 points in 1994, and 6,144 points 

in 1995, and 5,581 points in 1996, on 708 permanently 

marked transects distributed across 12 National Forests in the Northern Region as well Bureau of Land 

Management and Potlatch lands, in addition to 762 

nonpermanently marked points that were visited in 

1994. Some transect locations were changed between 

years for logistical reasons. Thus, 428 transects were 

visited all 3 years, 184 transects were visited in 2 of the 

3 years, and 96 transects were visited in only a single 

year. When nonriparian points within 100 m of an 

edge (as recorded by each field observer) were excluded, as well as some points with miscellaneous or 

unknown cover types, the final data set used in these 

habitat analyses consisted of2,557 points in 1994 (470 

permanent transects and 511 nonpermanent points), 

2,473 points in 1995 (557 transects), and 2,251 points 

in 1996 (515 transects). 

The distribution of points among cover types was 

fairly consistent among years (table 2). Twelve of the 

18 cover types were represented by at least 50 points 

in all 3 years. Ponderosa Pine and Wetland categories 

had the poorest representation and might be considered the least reliably sampled cover types. It must 

also be reiterated that all three riparian categories 

were sampled at points that were within 100 m of the 

edge of another major cover type, so some bird detections may have been from within adjacent nonriparian 

cover types. 

In the 3 years of data collected at all permanently 

marked monitoring points, we detected 195 bird species. Within 100 m of the points used in this report, we 

detected 166 species (table 3), most (128) of which were 

those that the point count method was designed to 

detect-the smaller, diurnal, visually, and vocally 

conspicuous landbirds. Also included were 22 waterbird species and 15 raptors. The 10 most frequently I 

detected species were Dark-eyed Junco, Yellow-rumped 

Warbler, Red -breasted Nuthatch, Swainson's Thrush, 

Townsend's Warbler, Western Tanager, Ruby-crowned 

Kinglet, American Robin, Chipping Sparrow, and 

MacGillivray's Warbler (table 3). 

We detected 54 species on at least 25 points in each 

of the 3 years, and 29 additional species with at least 

30 total detections when all 1994 to 1996 data were 

pooled. For each species, we provide our subjective 

impression of the pattern of cover type use as well as 

specific comments on management implications of 

that distribution pattern below. 

The error bars in the habitat distribution graphs 

show a wide range of variation in the probability if 

detection across the 3 years. As expected, less common 

species show more variation. Also, undersampled cover 

types, such as Ponderosa Pine and Wetlands, tend to 

have much larger error bars than well-sampled cover 

types such as Mixed Conifer. Beyond this, however, it 

is still apparent that some species have high and 

consistent probabilities in some cover types over others, illustrating distinctly nonrandom patterns of cover 

type use. 

Table 3-Bird species detected on point counts conducted between 1994 and 1996 as part of the USDA 

Forest Service's Northern Region Landbird Monitoring Program, with the number of points 

(non edge or riparian) at which each was detected within 100 m in each year. The order is based 

on the American Ornithologists' Union Checklist of North American Birds (1998). 

Figure Species 

Red-necked Grebe, Podiceps grisegena 

American Bittern, Botaurus len tigin os us 

Great Blue Heron, Ardea herodias 

Canada Goose, Branta canadensis 

American Wigeon, Anas americana 

Mallard, Anas platyrhynchos 

Blue-winged Teal, Anas discors 

Cinnamon Teal, Anas cyanoptera 

Northern Shoveler, Anas clypeata 

Green-winged Teal, Anas crecca 

Ring-necked Duck, Aythya col/aris 

Common Goldeneye, Bucephala c1angula 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Year of data collection 

1994 1995 1996 

2 

2 

1 

2 

9 

1 

1 

1 

2 

1 

2 

(con.) 

13 
Table 3 (Con.) 

Year of data collection 

Figure Species 1994 1995 1996 

Barrow's Goldeneye, BucephaJa islandica 

Hooded Merganser, Lophodytes cucul/atus 2 

Common Merganser, Mergus merganser 1 

Osprey, Pandion haliaetus 6 2 

Bald Eagle, Haliaeetus leucocephalus 1 

Northern Harrier, Circus cyaneus 1 

Sharp-shinned Hawk, Accipiter striatus 4 1 4 

Cooper's Hawk, Accipiter cooperii 3 2 2 

Northern Goshawk, ACCipiter gentilis 4 

Swainson's Hawk, Buteo swainsoni 1 1 

8 Red-tailed Hawk, Buteo jamaicensis 18 13 15 

9 American Kestrel, Falco sparverius 23 10 8 

Prairie Falcon, Falco mexicanus 1 

Gray Partridge, Perdix perdix 

Ring-necked Pheasant, Phasianus colchicus 1 

10 Blue Grouse, Oendragapus obscurus 9 14 7 

Spruce Grouse, Falcipennis canadensis 2 1 1 

11 Ruffed Grouse, Bonasa umbel/us 61 92 76 

Wild Turkey, Meleagris gal/opavo 1 1 

Mountain Quail, Oreortyx pictus 2 

California Quail, CaliipepJa californica 

Sora, Porzana carolina 5 

American Coot, Fulica americana 1 

Sandhill Crane, Grus canadensis 2 1 3 

Killdeer, Charadrius vociferus 7 3 1 

Spotted Sandpiper, Actitis macularia 7 10 5 

Long-billed Curlew, Numenius americanus 3 1 1 

12 Common Snipe, Gallinago gallinagif 22 27 11 

Rock Dove, Columba Iivia 1 

13 Mourning Dove, Zenaida macroura 26 7 14 

Flammulated Owl, Otus flammeolus 1 1 1 

Great Horned Owl, Bubo virginianus 1 

Northern Pygmy-Owl, Glaucidium gnoma 2 4 

Barred Owl, Strix varia 1 

Short-eared Owl, Asio flammeus 1 

Common Nighthawk, Chordeiles mino,a 13 5 6 

14 Vaux's Swift, Chaetura vauxfl 10 14 17 

15 Calliope Hummingbird, Stel/ula calliope 23 10 6 

Broad-tailed Hummingbird, Selasphorus platycercus 1 

16 Rufous Hummingbird, Selasphorus rufus 33 19 28 

Belted Kingfisher, Ceryle alcyon 3 1 4 

Lewis' Woodpecker, Melanerpes lewis 3 2 2 

Yellow-bellied Sapsucker, Sphyrapicus varius 1 

17 Red-naped Sapsucker, Sphyrapicus nuchalis 90 70 44 

18 Williamson's Sapsucker, Sphyrapicus thyroideus 18 23 11 

Downy Woodpecker, Picoides pubescens 13 8 5 

19 Hairy Woodpecker, Picoides villosus 65 55 58 

20 Three-Toed Woodpecker, Picoides tridactylus 18 8 9 

Black-backed Woodpecker, Picoides arcticus 1 1 1 

21 Northern Flicker, Colaptes auratus 251 166 111 

22 Pileated Woodpecker, Oryocopus pileatus 61 51 26 

23 Olive-sided Flycatcher, Contopus cooperi 88 62 58 

24 Western Wood-Pewee, Contopus sordidulus 24 14 11 

25 Willow Flycatcher, Empidonax trailii 52 19 23 

Least Flycatcher, Empidonax minimus 1 10 1 

26 Hammond's Flycatcher, Empidonax hammondii 156 126 104 

27 Dusky Flycatcher, Empidonax oberholseri 317 245 227 (con.) 

14 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Table 3 (Con.) 

Year of data collection 

Figure Species 1994 1995 1996 

28 Cordilleran Flycatcher, Empidonax occidentalis 32 10 

Say's Phoebe, Sayornis saya 

Western Kingbird, Tyrannus verticalis 1 

Eastern Kingbird, Tyrannus tyrannus 13 2 

29 Cassin's Vireo, Vireo cassinii 306 234 227 

31 Warbling Vireo, Vireo gilvus 387 382 348 

32 Red-eyed Vireo, Vireo olivaceus 24 11 11 

33 Gray Jay, Perisoreus canadensis 150 114 122 

34 Steller's Jay, Cyanocitta stelleri 74 43 53 

35 Clark's Nutcracker, Nucifraga columbiana ;109 63 62 

Black-billed Magpie, Pica pica 10 3 4 

American Crow, Corvus brachyrhynchos 3 4 5 

36 Common Raven, Corvus corax 62 34 40 

37 Horned Lark, Eremophila alpestris 30 27 20 

38 Tree Swallow, Tachycineta bicolo~ 40 43 23 

39 Violet-green Swallow, Tachycineta thalassinaa 7 14 10 

N. Rough-winged Swallow, Stelgidopteryx serripennisa 11 4 5 

Bank Swallow, Riparia riparia8 2 2 

Cliff Swallow, Petrochelidon pyrrhonotaa 10 7 2 

Barn Swallow, Hirundo rusticaa 10 7 1 

40 Black-capped Chickadee, Poecile atricapillus 94 124 120 

42 Mountain Chickadee, Poecile gambeli 437 477 376 

43 Chestnut-backed Chickadee, Poecile rufescens 102 85 10'9 

Boreal Chickadee, Poecile hudsonicus 1 3 2 

45 Red-breasted Nuthatch, Sitta canadensis 994 805 772 

46 White-breasted Nuthatch, Sitta carolinensis 25 21 16 

Pygmy Nuthatch, Sitta pygmaea 1 

47 Brown Creeper, Certhia americana 33 42 57 

49 Rock Wren, Salpinctes obsoletus 19 10 22 

Canyon Wren, Catherpes mexicanus 3 

50 House Wren, Troglodytes aedon 60 48 33 

51 Winter Wren, Troglodytes troglodytes 137 196 164 

Marsh Wren, Cistothorus palustris 1 2 2 

American Dipper, Cinclus mexicanus 3 1 5 

54 Golden-crowned Kinglet, Regulus satrapa 408 506 383 

55 Ruby-crowned Kinglet, Regulus calendula 591 586 465 

Western Bluebird, Sialia mexicana 1 

57 Mountain Bluebird, Sialia currucoides 74 65 37 

58 Townsend's Solitaire, Myadestes townsendi 275 199 178 

Veery, Catharus fuscescens 8 8 8 

59 Swainson's Thrush, Catharus ustulatus 733 565 543 

61 Hermit Thrush, Catharus guttatus 126 102 119 

63 American Robin, Turdus migratorius 624 538 403 

64 Varied Thrush, Ixoreus naevius 209 266 152 

Gray Catbird, Dumetella carolinensis 14 5 5 

Sage Thrasher, Oreoscoptes montanus 8 4 

European Starling, Sturn us vulgaris 21 3 1 

65 Cedar Waxwing, Bombycilla cedrorum 23 12 18 

Tennessee Warbler, Vermivora peregrina 2 

66 Orange-crowned Warbler, Vermivora celata 217 176 171 

67 Nashville Warbler, Vermivora ruficapilla 49 54 37 

69 Yellow Warbler, Dendroica petechia 101 74 57 

70 Yellow-rumped Warbler, Dendroica coronata 1022 932 764 

71 Townsend's Warbler, Dendroica townsendi 614 611 599 

Blackpoll Warbler, Dendroica striata 1 

72 American Redstart, Setophaga ruticilla 22 30 15 

73 Ovenbird, Seiurus aurocapillus 15 12 9 (con.) 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 15 
Table 3 (Con.) 

Year of data collection 

Figure Species 1994 1995 1996 

74 Northern Waterthrush, Seiurus noveboracensis 26 21 27 

Mourning Warbler, Oporornis philadelphia 1 

75 MacGillivray's Warbler, Oporornis tolmiei 537 419 448 

76 Common Yellowthroat, Geothlypis trichas 26 38 34 

77 Wilson's Warbler, Wilsonia pusil/a 74 76 108 

Yellow-breasted Chat, Icteria virens 1 

Western Tanager, Piranga ludoviciana 663 486 542 

80 Green-tailed Towhee, Pipilo chlorurus 18 23 8 

81 Spotted Towhee, Pipilo maculatus 51 65 61 

82 Chipping Sparrow, Spizel/a passerina 698 1 

480 350 

Clay-colored Sparrow, Spizel/a pal/ida 1 2 

83 Brewer's Sparrow, Spizel/a breweri 47 14 19 

Field Sparrow, Spizel/a pusil/a 1 

84 Vesper Sparrow, Pooecetes gramineus 178 146 101 

Lark Sparrow, Chondestes grammacus 4 8 

85 Savannah Sparrow, Passerculus sandwichensis 40 29 26 

86 Grasshopper Sparrow, Ammodramus savannarum 29 1 

87 Fox Sparrow, Passerella iliaca 99 128 91 

88 Song Sparrow, Melospiza melodia 135 110 124 

89 Lincoln's Sparrow, Melospiza lincolnii 22 34 38 

90 White-crowned Sparrow, Zonotrichia leucophrys 38 43 53 

91 Dark-eyed Junco, Junco hyemalis 1295 1100 1082 

92 Black-headed Grosbeak, Pheucticus melanocephalus 73 55 69 

93 Lazuli Bunting, Passerina amoena 57 51 46 

Bobolink, Dolichonyx oryzivorus 2 

94 Red-winged Blackbird, Agelaius phoeniceus 19 12 4 

95 Western Meadowlark, Sturnella neglecta 137 65 42 

Yellow-headed Blackbird, Xanthocephalus xanthocephalus 2 4 

Brewer's Blackbird, Euphagus cyanocephalus 15 13 1 

96 Brown-headed Cowbird, Molothrus ater 190 120 85 

Bullock's Oriole, Icterus bullockii 6 

97 Pine Grosbeak, Pinicola enucleator 20 14 15 

98 Cassin's Finch, Carpodacus cassinii 83 74 36 

House Finch, Carpodacus mexicanus 1 

99 Red Crossbill, Loxia curvirostra 75 59 162 

White-winged Crossbill, Loxia leucoptera 2 13 3 

100 Pine Siskin, Carduelis pinus 224 332 594 

American Goldfinch, Carduelis tristis 6 5 7 

101 Evening Grosbeak, Coccothraustes vespertinus 39 36 49 

House Sparrow, Passer domesticus 2 

Total number of point counts 2557 2473 2251 

a Flyovers included for these species. 

16 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Species Accounts 

Figures 8 through 101 show the percent of 10-minute point counts with at least one detection of each 

subject bird. Bars represent data from all 3 years combined, and some figures (for example, fig. 11) contain 

error bars that represent the standard deviation. 

Red-tailed Hawks (fig. 8) were detected on 46 

points in all 3 years combined. As a wide-ranging 

predator with large territories, this species can be 

found in many cover types. Although based on few 

detections, the high occurrence in open Ponderosa 

Pine and harvested stands is biologically logical in 

light ofa need for open areas to hunt small mammals, 

as well as large trees for nesting. This, in turn, suggests that the restoration of much of the lower elevation ponderosa pine to more open park-like conditions 

may benefit this species. 

American Kestrels (fig. 9) were detected on 41 of 

the points in all 3 years combined. Kestrels are opencountry, cavity-nesting birds that need large dead or 

dying trees for nesting purposes. They were most 

frequently detected in open areas that have large 

trees scattered throughout, including cottonwood 

bottomlands and heavily cut forests (and in agricultural lands, as recorded in additional surveys not 

reported here). The abundance of this species in relatively heavily cut forests appears, on the surface, to 

reflect a high suitability of these forests to kestrels. 

However, because there are numerous aspects of 

harvested forests that are not typical of similar conditions created through natural processes, those areas 

could also be acting as ecological traps; we need data 

on reproductive success to determine whether harvested forests are as suitable as suggested by the 

occurrence data. 

USDA Forest SeNice Gen. Tech. Rep. RMRS-GTR-32. 1999 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood! Aspen 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

Figure 8 

Red-tailed Hawk 

-

-

- I I 

- I 

- I 

-

-0 

- I 

- I 

- l 

- l - l 

0 

0 l 0 l o-J 0 l 

o 

Percent of points with detections 

Figure 9 

American Kestrel 

-

-

-

-b 

-

-

- I 

I 

I 

. 

-

. I 

I 

o 

I 

I 

I 

I 

Percent of pOints with detections 

I 

3 

I 

3 

17 
Blue Grouse (fig. 10) were detected on only 30 of the 

points in all 3 years combined, so the details of its 

pattern of cover type use may not be entirely accurate. 

Nonetheless, the pattern agrees with existing literature, which suggests that they are most common in 

open conifer forests (Zwickel 1992). The detections in 

Sagebrush are interesting, but involved only three 

transects, two of which were over 7,000 feet elevation. 

Zwickel (1992) stated that the species may occur in 

shrubsteppe and grassland communities out to 2 km or 

more from conifer forest edge, but it requires nearby 

conifer forest for winter foraging habitat. No special 

management considerations are suggested by the data. 

Ruffed Grouse (fig. 11) were detected on 61, 92, 

and 76 of the points in the 3 years. They were detected 

with highest probability in aspen (12 percent of points 

with detections) and other riparian cover types. Although this species is primarily associated with riparian areas in the West, it was recorded in a variety of 

additional cover types as well. This species may use 

shrubby or other deciduous microhabitats within cut 

or uncut forests, and it would be helpful to know 

what is required for successful use of such areas. We 

also suspect that detections were recorded in 

nonriparian cover types due to a failure to detect the 

streamside riparian cover type within which they 

were drumming. Such error is especially likely for this 

species because of its low-pitch drumming, which 

makes it difficult to estimate location and distance. 

Ruffed Grouse were much more likely to drum early 

than late in the breeding season. Detections declined 

rapidly after the first week, becoming rare by the 

fourth week of June (fig. 5b). Eighty percent of the 

detections occurred by June 11, but when the data 

were restricted to this period (not shown), the relative 

probabilities of detection in all cover types did not 

change significantly, except for an artificially high 

estimate for SprucelFir (due to two detections out of 

only 11 SprucelFir points). Because Ruffed Grouse were 

rarely drumming when Spruce/Fir was sampled later 

in the season, the estimate for this species in Spruce/ 

Fir is suspect, although it is still expected to be low. 

Because this species is relatively restricted to riparian corridors, the main concern should be whether 

riparian management practices are compatible with 

its needs. We need nesting success data in relation to 

alternative streamside management scenarios (especially cattle grazing, which may, through mechanical 

damage, remove the cover needed for suitable display 

sites). 

18 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

Figure 10 

Blue Grouse 

-

- I 

-

-t=J 

- I 

-

-

-p 

-

-

.. 

- I 

I 

-

-

-

-

- I 

- I 

o 

I 

Percent of points with detections 

Figure 11 

Ruffed Grouse 

Cedar/Grand Fir ~":+-----i 

Spruce/Fir ~~----i 

Lodgepole Pine 

Mixed coniferilliS@fuit--l 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut: 

Patch Cut 

Seed-tree cut111~~-----l Clearcut; 

Old Clearcut -!,:::,:,:",:,:,:,:,:,:::RI--1 

Post-Fire -[fu%¥'~---j 

Sagebrush 

Grassland 

J 

3 

Riparian wetiandjiiii Shrub 

Cottonwood/Aspen illlliemeD====L __ 1 o 20 

Percent of pOints with detections 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Common Snipe (fig. 12) were detected on 60 of 

the points in all 3 years combined, and were relatively 

restricted to Wetlands, but were also detected moderately often in Grassland (and in agricultural lands, as 

recorded in additional surveys not reported here). 

They generally nest adj acent to marshes, flooded fields, 

and bogs (Paulson 1993), and often perform their 

aerial display over adjacent grasslands or irrigated 

agricultural fields. No management considerations 

are suggested by the data independent of the widespread conversion of wetlands to drier (less suitable) 

agricultural land and the possible destruction of 

nests due to use of agricultural machinery during the 

nesting season. 

Mourning Doves (fig. 13) were detected on 47 of 

the points in all 3 years combined. This is a lowelevation, open-country species that nests in Cottonwood/Aspen, Ponderosa Pine forests, and trees and 

shrubs associated with agricultural land and Grassland. No special management considerations are 

suggested by the data. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Figure 12 

Common Snipe 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

0 

Percent of points with detections 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

Figure 13 

Mourning Dove 

-

-

-

-:J 

- J - I 

-:=1 

-~ 

-

-

- I 

:~ -

-

-

- I 

-

o 

J 

I 

I 

Percent of pOints with detections 

15 

5 

19 
Vaux's Swifts (fig. 14) were detected on 41 of the 

points in all 3 years combined, including flyover data. 

They were seen foraging over logged stands as well 

as many uncut areas. The data are simply too sparse 

to give a clear picture of which undisturbed cover 

types are of primary importance to this species (the 

bar in Cedar/Grand Fir represents detections at only 

two points), especially because many detections were 

in foraging areas that were probably different from 

nesting habitats. Under natural conditions, they rely 

on large, hollow snags for nesting (Bull and Cooper 

1991). In a Washington study they were common in 

Douglas-fir forests, where they appeared to be dependent on old growth conditions (Manuwal 1991). We 

need more information on the conditions that provide 

for suitable nest sites for this species. 

Calliope Hummingbirds (fig. 15) were detected 

on 39 of the points in all 3 years combined. The two 

sexes use largely different cover types; the males rely 

most heavily on open shrubfields in early successional 

patches, or open riparian areas, where they use tall 

shrubs as perch sites and display areas, and the 

females nest primarily in riparian streamside vegetation and road/forest edges. The relative restriction 

of males to disturbed forest types, especially harvested 

types, suggests that the openness and availability of 

perches makes harvested types quite suitable as 

aerial display sites. The unknown is whether they 

are able to obtain nectar resources that would otherwise be abundant in naturally occurring early successional cover types; in other words, are the harvested 

cover types acting as energetic traps because they lack 

the floral composition necessary for the hummingbirds to meet their energy needs? 

20 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

Figure 14 

Vaux's Swift 

-

-

-0 

- I 

- I 

-

-t=J 

-

-

-

-CJ 

-

- I 

-

-

-

- I 

-

o 

I 

I 

I 

Percent of points with detections 

Figure 15 

Calliope Hummingbird 

- I 

-

-

-Q -0 

-

-t::J 

- I 

I 

- ==:=J - I 

-

-

- I 

I 

- J 

o 

Percent of points with detections 

3 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Rufous Hummingbirds (fig. 16) were detected on 

80 of the points in all 3 years combined, primarily in 

early successional, postharvest situations (after 

shrubs have become abundant again). A larger study 

of postfire forests (Hutto 1995) indicated a higher 

probability of detection than we obtained in that cover 

type in this study. When data were restricted to the 

westside of the Continental Divide, where all but 

three detections of this species occurred, riparian 

cover types were shown to be used more frequently 

than indicated in figure 16. This is one of seven bird 

species that revealed a significant population decline 

in the West from 1968 to 1991, according to the 

Breeding Bird Survey database (HejI1994). The main 

management concern here lies with whether the nesting success of birds that use the artificially created 

forest types (for example, Clearcuts and Seed-tree 

Cuts) are comparable with nesting success in the 

naturally occurring early successional postfire habitat. If not, the harvested types could be acting as 

"ecological traps" by attracting the birds, but then 

failing to provide other necessary resources. 

Red-naped Sapsuckers (fig. 17) were detected on 

90, 77, and 44 points in the 3 years, primarily in 

harvested conifer forests and riparian cover types. It 

is likely that the birds detected in the drier uncut 

conifer forest types were associated with deciduous 

trees (such as birch) that occur sparsely throughout 

the more moist northwestern forests. The relative 

abundance in cut forests is undoubtedly due to the 

presence of deciduous vegetation there as well. The 

apparent suitability of harvested conifer forests to 

Red-naped Sapsuckers could be misleading if they do 

not do well there in terms of reproductive success. 

Fortunately, published information based on a study 

conducted in Coram Experimental Forest, Montana, 

revealed that nest success did not differ significantly 

between unharvested and harvested forest plots 

(Tobalske 1992, Tobalske and others 1990). 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

Figure 16 

Rufous Hummingbird 

- \ 

-

- I \ 

-

- I 

- I 

- I 

- I 

I 

-

-==:J 

-

-

-

:EY_ 

o 

Percent of points with detections 

Figure 17 

Red-naped Sapsucker 

I 

5 

Cottonwood/Aspen Riparian ShrUb1Iii~~;~BiillBiillBiilli:::==:::L_J ~ . . 

o 15 

Percent of points with detections 

21 
Williamson's Sapsuckers (fig. 18) were detected 

on 52 of the points in all 3 years combined, primarily 

in the more heavily harvested conifer forest types 

that still retained some green trees. Williamson's 

Sapsucker provides the most graphic example of a 

species that is more abundant in harvested forest 

cover types than anywhere else. This would appear, on 

the surface, to be a benefit of harvesting activity, but 

we would need information on nesting or survival 

success before we could conclude such. Because harvested forests are artificial in a number of respects, 

there is a chance that the proper visual stimuli exist 

to attract birds to settle, but that they then do poorly 

because other necessary requisites are not provided. 

In other words, there isa chance that these unnatural 

forests are acting as "ecological traps." 

Hairy Woodpeckers (fig. 19) were detected on 65, 

55, and 58 of the points in the 3 years. As with most 

woodpeckers, which are infrequently detected and 

have large home ranges, the error bars for the detection probabilities of this species tended to be large. 

Hairy Woodpeckers were detected in most forest 

types, including aspen forests and associated wetlands, although they were generally more frequently 

in cut than in uncut forests. They were detected most 

frequently in early Post-Fire forests (although there 

is considerable variation about that mean in this 

study, the trend is also strongly supported by Hutto, 

1995). Saab and Dudley (1998) found this species to be 

less abundant and have lower nesting success in 

salvage-logged stands relative to unlogged postfire 

forests. The relative abundance in cut stands may 

indicate that Hairy Woodpeckers are being drawn into 

such forests because of the superficial similarity of 

those conditions to burned forests. Whether the birds 

do well in the artificially created Partial Cut situations is unknown. If not, then that forest type (and 

possibly other cut forests) may be acting as "ecological 

traps." 

22 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

Figure 18 

Williamson's Sapsucker 

... 

-

- 1 

- 1 

-

-tJ 

... I 

- I 

- I 

-0 -D I 

-

-

-

- I 

- I 

- I I o 

Percent of pOints with detections 

Figure 19 

Hairy Woodpecker 

Cedar/Grand Fi~:IIII~~==r---------l Spruce/Fir 

Lodgepole Pine ~~:I------1 

Mixed Conifer ... {:~:::::;::::{::§:::::::: 

Douglas-fir -f.:;:;:::::;:;:::::;:I?:#' 

Ponderosa Pine -t:$fuB~ 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland -IJiffiffiEEillHtiffiEti----------1 

Riparian Shrub 

Cottonwood/Aspen -t1mEillmemiB:===~ ______ 1 

o 10 

Percent of points with detections 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Three-toed Woodpeckers (fig. 20) were detected 

on 35 of the points in all 3 years combined, most 

frequently in Post-Fire. They were not quite as restricted to such conditions as the Black-backed Woodpecker (Hutto 1995) because they occurred fairly frequently in Spruce/Fir stands as well, but it is clear 

that postfire conditions are important to this species, 

which relies on dead or dying standing timber for 

feeding and nesting purposes. Postfire salvage logging is an activity that may be in conflict with the 

needs of this species (see also Caton 1996, Hitchcox 

1996). 

Northern Flickers (fig. 21) were detected on 251, 

166, and 111 of the points in the 3 years. As the most 

abundant woodpecker, its habitat distribution is 

well represented, revealing a pattern of habitat use 

that includes a wide variety of the more open cover 

types. They were detected most frequently in variously cut, early Post-Fire, and Cottonwood/Aspen 

forests. This species is dependent on trees for nesting 

but not foraging, and its preference for open habitat is 

well documented. Because of its breadth of habitat 

use, we suspect there is little of potential management concern here, but the relative abundance in cut 

forests suggests either that cut forests serve as "supernormal releasers" and draw the birds into places that 

are otherwise unsuitable, or that the cut forests are 

truly great places to be. Data on reproductive success 

of flickers in unlogged and salvage-logged postfire 

forests (Hitchcox 1996) suggested that success was 

significantly lower in salvage-logged areas. We suspect they do well in other harvested cover types as 

well. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Cedar/Grand Fir 

Spruce/Fir 

lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

Figure 20 

Three-toed Woodpecker 

-

- I - I - I 

-0 

-

-

- I 

- I 

- I -

-t=J 

- I J -

-

-

-tJ 

-

o 

Percent of pOints with detections 

Figure 21 

Northern Flicker 

Mixed conlifer-tmggt---1 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

o 

, :~ 

" : ::' . 

Percent of pOints with detections 

3 

30 

23 
Pileated Woodpeckers (fig. 22) were detected on 

61,51, and 26 of the points in the 3 years. This is an 

uncommon species with large territories encompassing many cover types, so the specific locations of 

observations may not reflect cover type use per se. 

This was probably the reason for the large standard 

deviations around the estimates. This species was 

detected in both uncut and cut mid-elevation conifer 

forests, but its abundance in harvested forest types 

may have been, in part, a consequence of their mobility. They need large trees in the relatively uncut 

stands for nesting and roosting purposes (Bull and 

others 1992, Bull and Holthausen 1993). 

We detected Pileated Woodpeckers in a somewhat 

higher percentage of old growth relative to mature 

conifer forests (3.9 percent versus 2.2 percent, p = 

0.082). This species appears to do well in a matrix of 

forest types, but the inclusion of some older forest 

with large trees in their territories is probably necessary (Bull and Holthausen 1993). There was probably 

an intact forest near wherever these birds were detected (though not necessarily within 100 m). Thus, 

detecting them in Clearcuts and Seed-tree Cuts 

should not be taken to mean they can do well in large, 

homogeneous stands of those kinds, or even in landscapes with a preponderance of cut units. 

Pileated Woodpeckers were rarely detected east of 

the Continental Divide. There was only one detection 

in the database used here (and only 19, out of 6738 

points, in all data). The Montana Bird Distribution 

Committee (1996) indicates that this is indeed a restriction of geographical distribution. Therefore, we 

determined its pattern of occurrence using only the 

westside data, but found no appreciable differences. 

24 

Figure 22 

Pileated Woodpecker 

Cedar/Grand Fir-l;gpmF=====r--------l 

o 10 

Percent of paints with detections 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Olive-sided Flycatchers (fig. 23) were detected on 

88,62, and 58 of the points in the 3 years. Considering 

the naturally occurring cover types, this species was 

detected most often in Post-Fire stands. It appears to 

be common in the variously harvested cover types as 

well. Olive-sided Flycatchers were less frequently detected early in the season, when many harvested 

stands were surveyed, so their use of harvested 

stands may actually be more pronounced than indicated here. A graph based on the second half of the 

season shows little change in relative habitat distribution, although sparse cuts are even more strongly 

favored. The absence of this species in Ponderosa Pine 

stands could be due, in part, to this seasonal effect as 

well as the overall low sample size. A strong increase 

in detectability of this species as the season progressed 

resulted in 80 percent of the detections occurring from 

June 11 onward. However, restricting the data to this 

period did not change the habitat distribution pattern. 

The Olive-sided Flycatcher is one of the species that 

has declined significantly on western Breeding Bird 

Survey routes between 1968 and 1991 (Hejl 1994). 

Given its propensity to use harvested forest types, this 

is a bit of a mystery unless conditions during winter or 

migratory passage have deteriorated. Another possibility' however, is that the breeding census data are a 

misleading indicator of nesting success. In other words, 

we may be creating an "ecological trap" for the species 

by cutting in a way that provides only the appearance 

of an early postfire scene and little else. We need to 

know whether harvested forest patches are really 

suitable in terms of reproductive success, or whether 

they are acting as demographic sinks for this species. 

Western Wood-Pewees (fig. 24) were detected on 

49 points in all 3 years combined. They occurred 

mostly in riparian areas, especially Cottonwood! Aspen, 

as well as open conifer situations such as Ponderosa 

Pine and Post-Fire forests. Because of their relative 

abundance in the Post-Fire cover type (a pattern even 

more pronounced in Hutto, 1995), and their dependence on standing dead trees therein for nest sites, 

there is a potential negative effect of postfire salvage 

logging on this species. This is also a species that may 

be susceptible to excessive cowbird parasitism in the 

cottonwood bottomland and residential cover types. 

We need data on nesting success under various riparian management regimes to determine (1) whether 

cowbird parasitism is a problem or not, and (2) whether 

such rates depend on the management regime. Although there were only three detections in Ponderosa 

Pine, the data suggest that this species might benefit 

from the restoration of lowland old growth ponderosa 

pine stands. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Figure 23 

Olive-sided Flycatcher 

Cedar/Grand Fir111~~~=~--------l Spruce/Fir 1 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

o 

Percent of points with detections 

Figure 24 

Western Wood-Pewee 

-

-

-

-J 

- I 

-::::J 

-~ 

-

-

-tJ -::J 

- I -

-~ 

- I 

- I -I 

o 

Percent of pOints with detections 

15 

I 

6 

25 
Willow Flycatchers (fig. 25) were detected on 94 

points in all 3 years combined, and were strictly tied 

to riparian areas with adequate shrub cover. Even 

the rare occurrences in Clearcuts are generally tied 

to wet microhabitats. The Willow Flycatcher is one of 

the best examples of a species restricted to riparian 

areas. Because so little land area consists of this 

cover type, and because Willow Flycatchers occur in 

no other cover type, it becomes important to know 

whether the occurrence and nesting success of this 

shrub-nesting species varies among the various 

streamside management practices. In a review of 

literature on grazing effects in the West (Saab and 

others 1995), all studies reported a negative impact of 

cattle grazing on this species, probably because of the 

associated destruction of vegetation at the flycatcher's 

preferred foraging and nesting height or because of an 

associated increase in cowbird parasitism. 

Hammond's Flycatchers (fig. 26) were detected 

on 156, 126, and 104 of the points in the 3 years, most 

frequently in relatively uncut conifer forests, as well 

as in riparian areas, which may be closely associated 

with conifer forests. They were seen more often in 

cedar-hemlock (11 percent) than in grand fir (4 percent), but the sample sizes were too small to be 

significant (10 versus 2 detections; Fisher's Exact 

test, p = 0.26). A decline in detectability of this species 

as the season progressed resulted in 80 percent of the 

detections occurring by June 28. Restricting the data 

to this period resulted in a small increase in the 

apparent importance of dry forest types (Douglas-fir 

and Ponderosa Pine). This species is consistently found 

to be negatively affected by clearcutting (Hejl and 

others 1995), and many of the apparent detections in 

Clearcuts reported here may be misidentified Dusky 

Flycatchers because the latter species is abundant in 

clearcuts and these two species are difficult to dis tin -

guish in the field. 

Hammond's Flycatchers were detected in a somewhat higher percentage of old growth relative to mature conifer forests (7.1 percent versus 4.6 percent, 

p = 0.057). This biased the results upward for Cedar/ 

Grand Fir because nine of the twelve detections in 

that cover type were in old growth. Therefore, within 

mature forest the species was less likely to be found in 

Cedar/Grand Fir than in Mixed Conifer, whereas within 

old growth it was more likely. The numbers were low 

enough to make conclusions at that level questionable, 

however. The distribution pattern suggests that we 

need to retain older, uncut forest patches to provide for 

the needs of this species. This mirrors the conclusions 

of Hejl and Woods (1991). 

26 

Figure 25 

Cedar/Grand FirSpruce/Fir -

Lodgepole Pine 

Willow Flycatcher 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young ForestPartial Cut-J 

Patch CutSeed-tree CutClearcut-~ Old ClearcutPost-FireSagebrushGrasslandWetland -~:::::::::::::::-==-==-==-==-==-=-==-=-=-::;--_-_-"---'--.J Riparian Shrub-i:::===--________ --.-J1 

Cottonwood/Aspen - ] ~==d-______________ '

o 

Percent of pOints with detections 

Figure 26 

Hammond's Flycatcher 

Cedar/Grand Fir-{f'2I1H12±tl::::: :::] I 

Spruce!Fi 

Lodgepole Pine~::H""""----l 

Mixed Con ifer-{illzm~leait=j Douglas-fi 

Ponderosa Pine 

Young Forest-fulftG"tni+f.+:=i 

Partial Cut 

Patch Cut 

Seed-tree Cut E:=r0~' I 

Old ~:::~~~!tl~H. I 

Post-Fire fZEEJ9 I 

Sagebrush ET~ I 

Grassland -f-l 

Wetland,iIESE37i ---j 

Riparian Shrub -fuI:i:I2JT2/1:;lrDI2~ 

Cottonwood! Aspen i£TIW:7TIJillm:TTTI1t7t---i 

o 

Percent of points with detections 

j 

20 

12 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Dusky Flycatchers (fig. 27) were detected on 317, 

245, and 227 of the points in the 3 years, primarily in 

riparian areas and early successional forests that 

contain a good shrub layer. Those habitat conditions 

are naturally provided in postfire forests, but cut 

forests seem to provide suitable conditions as well. 

The high frequency in Ponderosa Pine could in part be 

due to misidentifications of Hammond's Flycatchers, 

although the two species may overlap in this cover 

type, with the Dusky Flycatcher in shrubby microhabitats. They were more likely to be detected in 

aspen than in cottonwood stands (44 percent versus 

23 percent; Fisher's Exact test, p = 0.02). A decline in 

detectability of this species as the season progressed 

resulted in 80 percent of the detections occurring by 

June 26. Part way through the season, both Dusky 

and Hammond's Flycatcher switch to an alternative 

partial-song type of call note that makes the two 

species almost impossible to distinguish. However, 

restricting the data to the early period did not change 

the habitat distribution pattern. Although the 30-year 

(1966 to 1995) population trend data generated from 

the Breeding Bird Survey do not reveal a significant 

increase for this species (Peterjohn and others 1996), 

other analyses suggest that this species is more common now than in the historical past because of forest 

cutting practices (Sharp 1996). The possibility that we 

are creating "ecological traps" by pulling them into 

artificially created situations (cut forests) where they 

do poorly is unlikely, but certainly possible; the issue 

merits study. 

Cordilleran Flycatchers (fig. 28) were detected 

on 43 points in all 3 years combined. Except for the 

Douglas-fir type, they were relatively restricted to 

riparian bottomlands and adjacent conifer forests. 

There were nine detections in cottonwood stands (21 

percent) and only one in aspen. This species was also 

more likely to occur in areas with a relatively large 

number of snags, reflecting an association with the 

older, denser vegetation types. The species relies 

heavily on intact riparian corridors, where they nest in 

cavities (rock pockets) in cut banks (RLH, personal 

observation). Thus, streambank erosion associated 

with excessive cattle grazing and streambank alteration due to channelization or stabilization efforts 

may have a significant negative impact on this 

species. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Figure 27 

Dusky Flycatcher 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine .. 

Young Forest 

Partial Cut 

Patch Cut :~ ;. : 

Seed-tree Cut 

Clearcut : . 

Old Clearcut 

',: . " 

o 

Percent of points with detections 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Figure 28 

Cordilleran Flycatcher 

1='----, 

Douglas-fir f------' 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland f-----------, 

Wetland F====,-----' 

50 

Riparian Shrub F=====~-------------' 

Cottonwood/Aspen ~=~=============:!. __ I 

o 6 

Percent of points with detections 

27 
Cassin's Vireos (fig. 29) were detected on 306, 234, 

and 227 of the points in the 3 years, primarily in the 

drier coniferous forest cover types. It was more likely 

to be found in grand fir than in cedar-hemlock (19 

percent versus 7 percent; Fisher's Exact test, p = 0.06). 

Although the Cassin's Vireo is common in the partially 

cut forest types, its occurrence drops off continuously 

with increasing levels of tree removal. This is the same 

pattern exhibited by several common forest bird species, including Red-breasted Nuthatch, Yellow-rumped 

Warbler, and Western Tanager, and it implies a certain degree of dependence on the retention of a significant density of trees. 

Restriction of the data to points west of the Continental Divide (fig. 30), where the species was over 

seven times as likely to be detected, increased the 

apparent use of Ponderosa Pine and Douglas-fir by 

this species. However, restriction of data to the period 

through June 28 (including 80 percent of the detections) resulted in a decrease in the apparent use of 

Ponderosa Pine and an increase in detection probability in Cedar/Grand Fir and mixed-conifer stands. The 

small sample size and large error bars in Ponderosa 

Pine make these conclusions questionable, however. 

In our experience outside formal surveys, Cassin's 

Vireos are common in ponderosa pine. In fact, within 

the mixed-conifer cover type (1994 only), they were 

much more likely to be detected (38 percent versus 17 

percent) when at least some ponderosa pine was present 

in the canopy layer (but the presence of cedar or grand 

fir made no difference). We need to find out if pure 

stands of ponderosa pine are less suitable or if some 

other factor is contributing to the variability. 

28 

SagebrushGrasslandFigure 29 

Cassin's Vireo 

RiParia~:t~::::'= Cottonwood/Aspen -~i;,:,;""lt(!!:!H~:;;Log:B_...:...1 _____________ , 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

o 

Percent of paints with detections 

Figure 30 

Cassin's Vireo - westside of the 

Continental Divide 

- I 

:6 

- I 

- I 

-

- I 

- I 

- I 

· J 

· I 

- I 

· I 

· 

· 

· 1 

· 1 

· I 

o 

I 

Percent of points with detections 

35 

35 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Warbling Vireos (fig. 31) were detected on 387, 

382, and 348 of the points in the 3 years. Warbling 

Vireos were frequently detected in both riparian and 

harvested forest cover types. In nonriparian cover 

types, they are strongly associated with deciduous 

shrubs; this explains their high probability of detection in cut coniferous forests, where there is an early 

successional "release" of shrub vegetation after timber 

harvesting. They may also be drawn into other conifer 

cover types by roadside vegetation. The abundance of 

this species in the cut forest types would make it 

appear to be in good shape because of the abundance 

of those cover types across the landscape. N onetheless, this is another species that could be drawn into 

those artificially created forests and then not do well; 

we need data to test whether the cut forests are acting 

as "ecological traps." This is especially important because of the high vulnerability of this species to cowbird parasitism (Tewksbury and others 1998). Warbling Vireos are known to be especially common in 

aspen stands, and this is indicated in these data as 

well. They were twice as likely to be detected in aspen 

than in cottonwood stands (66 percent versus 33 percent; Fisher's Exact test, p < 0.001). 

Red-eyed Vireos (fig. 32) were detected on 46 

points in all 3 years combined, primarily in the riparian cover types. In our experience outside of this study, 

this species is entirely restricted to cottonwood bottomland forests, and the data are at least partially 

consistent with this impression. There were five detections in cottonwood stands and none in aspen. The 

minor occurrences in a few cut forest types reflect 

either misidentifications or the fact that large deciduous trees are sometimes left after a harvest. The 

abundances in Wetland and Riparian Shrub types are 

likely to be artifacts of the presence of nearby cottonwood stands. Because of its near restriction to a forest 

cover type that is rare on the landscape, it becomes 

critical to ensure that the species is doing well there. 

The management issue of primary concern is the high 

cowbird parasitism rates associated with excessive 

cattle grazing in most riparian bottomlands. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

Figure 31 

Warbling Vireo 

o 

:: ,,: 

Percent of paints with detections 

Figure 32 

Red-eyed Vireo 

0 

Percent of points with detections 

75 

29 
Gray Jays (fig. 33) were detected on 150, 114, and 

122 of the points in the 3 years. They were found in a 

wide variety of conifer forest types, but most often in 

the higher elevation, uncut conifer forests with Spruce/ 

Fir or Lodgepole Pine. If this wide-ranging species 

uses harvested forests for foraging and egg predation, 

it may be a big reason why nest success of other 

songbirds might not mirror their relative abundance 

in harvested forests. 

Steller's Jays (fig. 34) were detected on 74,43, and 

53 of the points in the 3 years. They were found in most 

conifer forest types, but were most frequent in the 

harvested cover types. Among uncut forest stands, 

they were detected in a somewhat higher percentage 

of old growth relative to mature conifer forests (3.0 

percent versus 1.3 percent, p = 0.03). This is consistent 

with a preference for more open forest (as is the near 

absence in Lodgepole Pine and Young Forest), although we need more data to explore this further. 

Although only 11 detections occurred east of the Continental Divide, restricting the data to westside points 

did not change the habitat distribution results appreciably. This wide-ranging species may use harvested 

forests for foraging (egg predation?) rather than nesting activity. If so, this species may be a big reason why 

nest success of other songbirds might not mirror their 

relative abundance in harvested forests. The relative 

abundance of this species and other corvids in harvested forests underscores the need for nest success 

studies therein. 

30 

Figure 33 

Gray Jay 

Cedar/Grand 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Dougl 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

0 15 

Percent of points with detections 

Figure 34 

Steller's Jay 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

0 15 

Percent of points with detections 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Clark's Nutcrackers (fig. 35) were detected on 

109,63, and 62 of the points in the 3 years, and they 

were distributed broadly across the conifer forest 

cover types, although absent from Cedar/Grand Fir. 

These results may be deceiving because the "nomadic" 

nature of this species makes it tough to use pointcount detections to draw inferences about patterns of 

habitat use. Also, we had few points in the subalpine, 

whitebark pine forests known to be used by this 

species. However, the use of Douglas-fir and especially Ponderosa Pine forests is supported by the 

literature CTomback 1998). The occurrence of this 

species may be closely linked to areas of high conifer 

seed production, including early postfire habitat 

(Hutto 1995), so this may be another species that is 

negatively affected by postfire salvage cutting. 

Common Ravens (fig. 36) were detected on 62, 

34, and 40 of the points in the 3 years. Although they 

occur in open country areas with sagebrush and 

ranching activity, this species is most frequently detected in coniferous forests of all types. A decline in 

detectability of this species as the season progressed 

resulted in 80 percent of the detections occurring by 

June 27. However, restricting the data to this period 

did not change the habitat distribution pattern. The 

wide-ranging nature of this species makes it difficult 

to determine specific habitat needs, but they commonly use large trees for nesting, so they are probably benefitted by the occurrence of old growth in the 

landscape. Ravens are notable egg predators, and 

whether their effect on open cup-nesting bird species 

is more pronounced in harvested forests is unknown. 

The abundance data alone do not suggest any special 

problem associated with forest harvesting practices. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Figure 35 

Clark's Nutcracker 

Cedar/Grand Fir 

Spruce/Fir imilEillI1PEJEElBIB---1 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire-tEffiBBBt---1 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

o 

Percent of points with detections 

Figure 36 

Common Raven 

20 

Cedar/Grand Fir-tffiTIml4TIi1ti=r----------i 

Spruce/Fir 

Lodgepole Pine 

Mixed conifer-W]tmill~gl=~ Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut~~'.4----1 

Old Clearcut -I::"""~I---i 

Post-Fire 

Sagebrush -tttttilltt8i±lm------l 

Grassland 

Wetland 

Riparian Shrub-l@]@ffilli]H 

Cottonwood/Aspen1L""'ill;':':';t;,~~,:,r-_-_-_-_~ ____________ , 

o 

Percent of pOints with detections 

31 
Horned Larks (fig. 37) were detected on 77 points 

in all 3 years combined, but were restricted to Grassland and Sagebrush (as well as agricultural areas, 

from counts not otherwise reported here). Because 

of the relative restriction of this species to the cover 

types that are most heavily influenced by cattle grazing, we need information on the nesting success of 

this species in relatively grazed and relativelyungrazed 

situations. However, we do not anticipate any problems, because this species prefers bare ground or 

grasses less than a few centimeters high (Wiens and 

others 1987), and achieves the highest population 

densities in areas with the most bare ground. This 

species has been universally positive in its response 

to grazing (Saab and others 1995). 

Tree Swallows (fig. 38) were detected on 106 points 

in all 3 years combined, primarily in riparian bottomlands, wetlands, and some open country situations, 

although the latter may be an artifact of the proximity 

of artificial roadside nest boxes. Many harvested forest stands will attract Tree Swallows if snags remain. A study involving postfire stands found this 

species to be detected more frequently in that cover 

type than we found here (Hutto 1995). If the Postfire 

and Cottonwood/Aspen cover types are especially important to naturally occurring populations, then the 

loss of nest trees in postfire salvage sales may be 

detrimental, and the presence of nest-usurping 

European Starlings in the bottomlands may also 

pose a special threat to this swallow species. 

32 

Cedar/Grand FirSpruce/FirLodgepole Pine 

Mixed Conifer": 

Douglas-fir 

Ponderosa PineYoung ForestPartial CutPatch CutSeed-tree CutClearcut 

Old Clearcut 

Post-Fire 

Figure 37 

Horned Lark 

~------, 

Sagebrush f=====I..-...-----------, 

Grassland-I--____________ ---'1 

WetlandRiparian ShrubCottonwood/Aspen-, _________________ , 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cui 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

o 

Percent of points with detections 

Figure 38 

Tree Swallow 

-

-b 

-

-

-

-

-0 -:J 

-

-

-

-0 

- I 

- l 

-

- I 

- I 

o 

Percent of points with detections 

30 

1 

20 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Violet-green Swallows (fig. 39) were detected 

on only 31 points in all 3 years combined. Under 

natural conditions, this species may be fairly restricted 

to riparian bottomland conditions. The eight detections in Sagebrush may be due to the proximity of 

riparian areas or roads with nest boxes, although this 

species does occur in more remote sagebrush country. 

Further study may be of interest. The management 

issue of primary concern is whether the presence or 

reproductive success of naturally occurring populations of this species are affected negatively by various 

riparian land-use practices. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Figure 39 

Violet-green Swallow 

f------'---, 

Post-Fire I==i=====:d...-.--------, 

Sagebrush 1::==--_________ ----' 

Grassland ~=---------, 

Wetland 1=:==-_____ ---' 

Riparian Shrub 1====-----, 

Cottonwood/Aspen ,=-~~~=-L ___________ '

o 

Percent of points with detections 

33 
Black-capped Chickadees (fig. 40) were detected on 94, 124, and 120 of the points in the 3 years. 

Of the three chickadee species in the region, this one 

is relatively common in riparian cover types, as well 

as in conifer forests with riparian stringers or early 

successional vegetation. Although Black-capped 

Chickadees do occur east of the Continental Divide 

(Montana Bird Distribution Committee 1996), we had 

only 21 detections there, and the species was seven 

times more likely to be detected at points on the 

westside. Restriction of data to the west (fig. 41) better 

showed the expected importance of riparian areas to 

this species. The apparent usage of pine forests is 

interesting but would need to be confirmed. Many 

detections in the conifer forest types may represent 

misidentifications by observers who were willing to 

identify the species on the basis of song alone-a song 

that is similar to that of the Mountain Chickadee. 

However, Black-capped Chickadees do use many open 

conifer and harvested cover types when deciduous 

elements are present. Deciduous vegetation may occur along roadsides, so this species may be drawn into 

conifer cover types by the presence· of roads. We need 

to learn whether this leads to successful reproduction 

in these areas, and how this species is affected "best 

management practices" in the riparian areas where it 

is known to breed. The species also depends on snags, 

especially rotting stumps. Thus, excessive woodcutting in riparian areas may be a concern as well. 

34 

Figure 40 

Black-capped Chickadee 

Cedar/Grand Fir-mllilli·::Ej.'.[jfu5F=~----------1 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut ~:::::::::::::mi:!--1 

Old Clearcut -I~illEElliEffiE88-----1 Post-Fire -f,Mq;r---i 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 1Mlli .::. .. 

o w 

Percent of points with detections 

Figure 41 

Black-capped Chickadee - westside of the 

Continental Divide 

.. 

.. ] 

-

· 

· 

-

-

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

.~ 

Riparian Shrub 

Cottonwoodl Aspen 

· 

-~ 

· 

-==:J 

-

-

-

o 

I 

I 

I 

I 

I 

I 

I 

I 

I 

I -l 

j 

20 

Percent of points with detections 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Mountain Chickadees (fig. 42) were detected on 

437,477, and 376 of the points in the 3 years. This 

species is a cavity nester that often uses rotting stumps 

as nest sites. This species is most common in the 

coniferous forest types, and it appears to be somewhat 

less common in harvested forest types, as has been 

found in other timber harvesting studies (Hejl and 

others 1995). It was also common in Young Forest, and 

it was detected in a lower percentage of old growth 

relative to mature conifer forests (11.6.percent versus 

19.1 percent, p = 0.001). Nine of 10 detections in the 

Cedar/Grand Fir cover type were in cedarlhemlock. 

Although primarily a coniferous forest species they 

were abundant in or near aspen stands (30 percent 

versus only 7 percent in cottonwood), so aspen may 

enhance the worth of a conifer forest for this species. 

The Mountain Chickadee requires snags for nesting 

and is negatively affected by clearcutting, but otherwise seems to be a generalist species of little management concern. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Figure 42 

Mountain Chickadee 

Grassland -f.8:8~--i 

wetland~liliiii~;;::=~ __ J Riparian Shrub 

Cottonwood/Aspen 

o 40 

Percent of pOints with detections 

35 
Chestnut-backed Chickadees (fig. 43) were detected on 102,85, and 109 of the points in the 3 years. 

This species is clearly associated with Cedar/Grand 

Fir forests, a type largely avoided by the Mountain 

Chickadee. The species used grand fir as often as 

cedarlhemlock (Fisher's Exact test, p = 0.80), and a 

large proportion of the mixed -conifer and harvested 

forest stands where this species occurred also had a 

major component of cedar, hemlock, or grand fir. This 

species also appeared to occur predominantly in relatively intact forest. This species is largely restricted in 

geographic distribution to northern Idaho and far 

northwestern Montana. Restriction of the data to 

west of the Continental Divide, or even to just the 

Kootenai National Forest and Idaho, did not change 

the pattern of habitat distribution, however, probably 

because Cedar/Grand Fir was also restricted to the 

western areas. The detect ability of this species declined as the season progressed, resulting in 80 percent of the detections occurring by June 28. When the 

data were restricted to this period, the detection 

probability of Mixed Conifer became equal to Cedar/ 

Grand Fir. When both restrictions were applied 

simultaneously (fig. 44), the probability of detection 

was highest in Mixed Conifer (the percentage within 

SprucelFir also increased, but represented only four 

detections) . 

36 

Figure 43 

Chestnut-backed Chickadee 

Cedar/Grand Firllll~~~MErt±8EEF===j--l spruce/Firi 

Lodgepole Pine 

Mixed Conifer -ttglIETIflmIT§tEB-----1 

Douglas-fir 

Ponderosa Pine 

Young Forest""'i::::]b.+.f.R+---i 

Partial Patch Cut~lli~~~~f~~~~~~~-1 Cut 

Seed-tree Cut 

Sagebrush 

Riparian Shru 

Cottonwood/Aspen """---.:.-_______________ , 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post·Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

o W 

Percent of pOints with detections 

Figure 44 

Chestnut-backed Chickadee - to June 28, 

westside of the Continental Divide 

- I 

- J - ] 

- I 

-p 

-

- I 

- I 

- I 

- I - J 

I 

-=:J 

-

-

- I - J - I 

o 

Percent of pOints with detections , 

20 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Red-breasted Nuthatches (fig. 45) were detected 

on 994, 805, and 772 of the points in the 3 years. This 

is one of the most common species throughout the 

conifer forests of the Northern Rockies, and it was 

especially common in the lower-elevation forest types. 

It was also detected in a higher percentage of old 

growth relative to mature conifer forests (52.5 percent 

versus 45.3 percent, p = 0.014). Although Red-breasted 

Nuthatches also occurred commonly in cut forest types, 

it is clear that their probability of occurrence decreased steadily with increasing amounts of timber 

removed. In fact, this is one species that has been 

shown through literature review to be consistently 

less abundant in harvested than unharvested Rocky 

Mountain forests (Hejl and others 1995, Hutto and 

others 1993). Were it not for its widespread occurrence 

across most of the relatively uncut conifer forest types, 

this would be a more serious management concern. 

White-breasted Nuthatches (fig. 46) were detected on only 62 points in all 3 years combined. The 

habitat distribution graph for this species may be 

misleading because, in our experience outside of formal surveys, White-breasted Nuthatches are most 

common in ponderosa pine forests and in cottonwood 

bottomland forests with the pine element present. It is 

uncertain why they were detected in neither of those 

cover types, except that those cover types were not well 

represented in our sample. Because 38 of the 62 

detections (on 25 of 45 transects) of this species were 

in Idaho (where only 31 percent of the sample points 

occurred), it may be that Montana is more on the 

periphery of their range, or simply that their preferred 

habitat was more commonly sampled in Idaho. The 

relative abundance in Cedar/Grand Fir was based on I 

only two detections. The relative abundance in PostFire (based on only three detections) is inconsistent 

with results from a study (Hutto 1995) based on over 

600 points in burned forests, in which no Whitebreasted Nuthatches were found. 

The biology of White-breasted Nuthatches suggests 

that they may need relatively large trees in the areas 

where they occur (McEllin 1979). Thus, the management issue of primary concern is one of determining 

which silvicultural methods used in ponderosa pine 

forests are most compatible with their needs. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Figure 45 

Red-breasted Nuthatch 

o 

Percent of points with detections 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

Figure 46 

White-breasted Nuthatch 

- J -

-

- J 

- I 

-

- J - I 

I 

-:=? 

-

-

-

- J 

-p 

-

o 

J 

Percent of points with detections 

90 

3 

37 
Brown Creepers (fig. 47) are uncommon birds of 

dense, mesic coniferous forests in the western part of 

the region. They were detected on only 34, 43, and 62 

of the points in the 3 years. This species was most 

common in Cedar/Grand Fir, and less so in other uncut 

coniferous forests types that may produce dense 

stands when old. It was seen more often in cedarhemlock (13 percent) than in grand fir (6 percent), but 

the sample sizes were too small to be significant (12 

versus 3 detections; Fisher's Exact test, p = 0.26). 

Brown Creepers were mostly absent from logged or 

nonconiferous cover types. A recent literature synthesis (Hejl and others 1995) also revealed that every 

study on the effects of timber harvesting in the Rocky 

Mountains has found creepers to be less abundant in 

harvested than unharvested forest types. 

Brown Creepers were much more likely to be detected in old growth than in mature forest (8.6 percent 

versus 3.1 percent, p < 0.001). This agrees with other 

studies (for example, Mannan and Meslow 1984). The 

distribution of creepers within mature forest was 

similar to that shown in figure 47, with Cedar/ 

Grand Fir greatly favored. When we restricted the 

data to old growth, a somewhat different picture 

emerged (fig. 48), and other cover types were used 

nearly as much Cedar/Grand Fir. This suggests the 

possibility that Brown Creepers use either old growth 

or cedar-hemlock, and that both criteria may not be 

necessary, but the sample sizes were too low to make 

any conclusions (a total of only 26 detections are 

represented in fig. 48). The maintenance of old growth 

conifer forest is probably important to this species in 

most areas, and fragmentation of old growth habitat 

may have negative consequences (Hejl and Paige 1994). 

There were not enough detections of this species for 

subsets of the data to be analyzed separately for examiningotherpotential biases either. For example, creepers were not consistently detected across the sampling 

season; there was a tendency in all years for more 

individuals to be detected later in the season. Overall, 

twice as many creepers were detected in the second 

half of the season as the first (93 versus 46). This may 

have biased some probability estimates for cover types 

that were unevenly sampled through time. In particular, the probability of occurrence in Spruce/Fir may be 

lower, and that in Ponderosa Pine may be higher, than 

the data suggest. Cedar/Grand Fir tended to be more 

common in the second half of the season as well, but 

this was probably not strong enough a bias to negate 

the obvious high usage of this cover type by creepers. 

As with most species, the average distance to detection was higher in Cedar/Grand Fir (fig. 6a), so there 

was no evidence that creepers were harder to detect 

there. In fact, creepers were detected most often in 

dense forest, where average detectability was expected to be less. Therefore, if there were any bias, 

there would be an even greater relative occurrence in 

uncut relative to cut forest cover types than was 

demonstrated here. 

38 

Figure 47 

Brown Creeper 

Cedar/Grand Fir11111~~~gj§jitm===r-l Spruce/Fir 1 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir~~---i 

Ponderosa Pine 

Young Forest~:m~t---i 

Partial Cut~::::::;~~ 

Patch Cut~+--1 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire ~:+-----l 

Sagebrush 

Grassland 

Wetland ~,:,:f---i 

Riparian Shrub 

Cottonwood/Aspen , _________________ , 

o 15 

Percent of points with detections 

Figure 48 

Brown Creeper - old growth only 

Cedar/Grand Fir 

Spruce/Fir 

Douglas-fir 

o 12 

Percent of points with detections 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Rock Wrens (fig. 49) were detected on 51 points in 

all 3 years combined, especially in open Sagebrush, 

Grasslands, and even Post-Fire forests. This is a 

species of open habitats with rock outcrops or boulderstrewn slopes, a known microhabitat requirement 

that is not reflected in our data here. This is a good 

example of an uncommon, specialist species that is 

not well sampled by the broad-scale design of this 

study. 

House Wrens (fig. 50) were detected on 60,48, and 

33 of the points in the 3 years, primarily in riparian 

cover types and in a variety of cut and Post-Fire conifer 

forest types. They were detected more often in aspen 

than in cottonwood stands, although the sample sizes 

were too low to draw conclusions (18 versus 4 detections; Fisher's Exact test, p = 0.79). Although riparian 

lands may be the primary habitat of this species 

under natural conditions, the land area covered by cut 

forests is substantially greater. Thus, if cut forests 

are acting as "ecological traps" by having the appropriate superficial characteristics but being otherwise 

unsuitable, there is potential for a negative impact of 

cutting on this species. There is also the issue of nest 

usurpation by European Starlings in the bottomlands 

themselves. Finally, House Wrens are susceptible to 

nest-site loss from salvage cutting postfire forests. 

Indeed, in one study (Hitchcox 1996), House Wrens 

were three times less abundant I in salvage-logged 

plots, but their nest success was no different. 

A strong decline in detect ability of this species as 

the season progressed resulted in 80 percent of the 

detections occurring by June 21. Restricting the data 

to this period resulted in minor changes to the habitat 

distribution pattern that could be due to sampling 

error, including an even greater a pparen t use of Clearcuts. House Wrens are not known to occur in higher 

elevation forests, so it is unlikely that their absence 

there in this study was a misleading result of the lateseason sampling bias of higher elevation forests. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Figure 49 

Rock Wren 

l 

0 

Percent of paints with detections 

Figure 50 

House Wren 

Ponderosa Pine ooof.!'!'8'~-----; 

Young Forest 

Partial Cut 

Patch Cut "'{:;::::;:~~--l 

Seed-tree Cut 

15 

clearcut-fj~;rillllimEtEE21±Et5titt-------11 Old Clearcut -!:~~if.t---i 

Post-Fire -jllillS[illfEEEEBiEttt----/ 

Sagebrush 

Grassland 

Wetland+.;:,~~f.:if.:i:~f.:if.:i:+-----------i 

Riparian Shrub 

Cottonwood/Aspen ~~~~~~~~_~~ ___ --'-__ ' 

o 20 

Percent of paints with detections 

39 
Winter Wrens (fig. 51) were detected in the 

westernmost portion of the region on 137,196, and 164 

of the points in the 3 years. They were relatively 

restricted to uncut forest types, especially Cedar/ 

Grand Fir and SprucelFir. When the Cedar/Grand Fir 

category was split into separate components, Winter 

Wrens were shown to be twice as common in cedar/ 

hemlock (40.4 percent) than in grand fir (19.2 percent) 

or spruce/fir (21. 7 percent). The dramatic decrease in 

probability of detection with even moderate levels of 

forest cutting was also striking. 

The Winter Wren and the Brown Creeper were the 

only species that were more than twice as likely to be 

detected in old growth than in mature forests (21 

percent versus 9 percent for the wren, p < 0.001). This 

was not due to the large number of old growth points 

in Cedar/Grand Fir. Within Cedar/Grand Fir, wrens 

were still more than twice as likely to use old growth 

as mature forest (62 percent versus 23 percent). Also, 

within old growth, cedarlhemlock was still more 

strongly used than any other type (fig. 52a), including 

grand fir. Within mature forest only, however, cedar/ 

hemlock, grand fir, and spruce/fir were used to approximately the same degree (fig. 52b), suggesting it 

may be the old growth features that make cedarhemlock particularly useful to this species. These 

results imply that Winter Wrens need uncut, old 

growth forest to meet their habitat needs. Forest 

fragmentation may also have negative consequences 

(Hejl and Paige 1994). 

Of 497 detections of Winter Wrens over 3 years, only 

four occurred east of the Continental Divide. This is 

the eastern edge of their range in Montana, as confirmed by long-term distribution records (Montana 

Bird Distribution Committee 1996). It is not known 

whether this distribution is due only to cover type 

availability or to some independent climatic factor. 

When the analyses were redone with data restricted to 

west of the Divide, the same pattern resulted, although the association with riparian cover types was 

more apparent (fig. 53). 

The association with streamside riparian conditions 

was even more apparent when the 1994 data set was 

compared to the other points in 1994 that had riparian 

cover within 100 m (otherwise excluded in this report). 

Winter Wrens were detected on 26 percent of points 

with riparian edge nearby, compared to only 6 percent 

of points with no edge. Because of this strong association, this species may serve as a good indicator of the 

suitability of alternative streamside management practices for wildlife populations. 

40 

Figure 51 

Winter Wren 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

a 50 

Percent of pOints with detections 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Figure 52 

a. Winter Wren - old growth only 

Cedar/Grand Fir 

Spruce/Fir 

Mixed Conifer 

Douglas-fir 

a 

Percent of points with detections 

b. Winter Wren - mature forest only 

Cedar/Grand Fir 

Spruce/Fir 

Mixed Conifer 

Douglas-fir 

Percent of points with detections 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

50 

50 

Figure 53 

Winter Wren - westside of the 

Continental Divide 

Cedar/Grand Fir 1==========;-----' 

Spruce/Fir '==,--_______ -' 

Lodgepole Pine F='-------, 

Mixed Conifer '====-_---' 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Riparian Shrub 1======::;---' 

Cottonwood/Aspen ,==~==~..!...-____________ , 

o 50 

Percent of paints with detections 

41 
Golden-crowned Kinglets (fig. 54) were detected 

on 408, 506, and 383 of the points in the 3 years, 

primarily in uncut forest types, especially Cedar/ 

Grand Fir and Spruce/Fir. They were detected in 

grand fir as often as cedarlhemlock (Fisher's Exact 

test, p = 0.86), and avoided more open, dry forests 

such as Ponderosa Pine. The clear trend of a decline in 

abundance within increasingly cut forests suggests 

that Golden-crowned Kinglets may depend on relatively uncut forest conditions. They clearly prefer the 

trees with dense foliage (nonpine), in which they 

forage and build their nests (Galati and Galati 1985). 

Based on the Breeding Bird Survey database, they 

are one of only seven species whose populations declined significantly from 1968 to 1991 (HejI1994). As 

with Red-breasted Nuthatch, Brown Creeper, and 

Mountain Chickadee, this is a species for which 

virtually every timber harvesting study has revealed 

a negative effect (Hejl and others 1995). 

Golden-crowned Kinglets were more likely to be 

detected in old growth than in mature forests (35 

percent versus 25 percent, p < 0.001). This trend held 

up within every cover type except Spruce/Fir. The 

pattern of cover type use displayed by this species 

does not seem to have been biased by its apparent 

preference for old growth, since the pattern was the 

same using data from mature stands only. The only 

difference with old growth stands included was a 

relatively lower detection probability in Spruce/Fir. 

Because old growth spruce/fir is known to be an excellent habitat for this species (Galati and Galati 1985), 

the low probability of detection therein may have 

been due to a low sample size (37) in that cover type. 

It seems clear, however, that maintenance of healthy 

populations of Golden-crowned Kinglets will probably 

require maintenance of large amounts of older forest. 

The soft, high-pitched song of the Golden-crowned 

Kinglet makes it one of the most difficult species to 

detect, and this was reflected in the lowest average 

detection distance of any species (32.7 m versus 53.0 m 

for 40 species combined). However, average detection 

distances did not differ greatly among cover types, 

and any bias would be expected to be in the direction 

of greater detect ability in open cover types. This 

means there could be an even greater preference of 

uncut over cut forest cover types than was demonstrated here. 

42 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Figure 54 

Golden-crowned Kinglet 

Young Partial Forest11111Iii~-1 cuti 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut -m@llEJ---1 Post-Fire~H----1 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

o 

Percent of points with detections 

60 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Ruby-crowned Kinglets (fig. 55) were detected 

on 591, 586, and 465 of the points in the 3 years, 

primarily in conifer forest cover types. The apparent 

abundance of kinglets in riparian cover types was 

probably an artifact of the species being detected in 

nearby conifer forest types. In fact, within the conifer 

cover types it was less commonly detected when riparian cover was within 100 m (21 percent) than in the 

stands with no edge within 100 m (25 percent). This 

species commonly occurred in partially cut forest 

types, although it was rare in Clearcuts. Use of partially logged forest is somewhat inconsistent with 

results presented in Hejl and others (1995), and we 

need more study of what conditions promote increased 

abundance and nesting success in harvested stands. 

Song activity of the Ruby-crowned Kinglet declined 

in the later part of the season. This may mean that the 

probability of occurrence in Spruce/Fir is even higher 

than appears here, since this cover type was not as 

well represented earlier in the season. When data 

were restricted to before June 28, the habitat distribution remained largely the same, except that the 

relative detection probability in Lodgepole Pine was 

increased (fig. 56). 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Figure 55 

Ruby-crowned Kinglet 

Riparian wet,and~iilllliE::~~::::J Shrub ' ':," 

Cottonwood/Aspen 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

o W 

Percent of pOints with detections 

Figure 56 

Ruby-crowned Kinglet - through June 28, 

when 80 percent of detections occurred 

h 

I 

I 

I 

I 

=~,- I 

I 

I 

I 

l 

I 

l 

~ I 

I 

I 

o 

Percent of points with detections 

60 

43 
Mountain Bluebirds (fig. 57) were detected on 74, 

65, and 37 of the points in the 3 years. This species 

is likely to be found in any heavily logged or other 

open area that has sufficient nesting cavities. Note 

that it disappears as the age of a Clearcut advances. 

Because this species is most often detected visually, 

there may be a detectability bias toward more open 

cover types. However, considering the near total absence of detections within denser forests in this and 

other studies, this pattern may be considered reliable. 

Their association with early Post-Fire habitat is clearly 

evident, especially when one considers that the abundances reflected in the open Grassland, and Sagebrush cover types are likely to be an artifact of roadside nest boxes. A decline in detectability of this 

species as the season progressed resulted in 80 percent of the detections occurring by June 25. However, 

restricting the data to this period did not change the 

habitat distribution pattern. 

There are three issues of management interest 

here. First, this cavity-nesting species depends heavily 

on (is relatively restricted to) postfire habitat. This 

means that fire suppression and postfire salvage cutting operations may be affecting bluebird populations 

negatively. Data on reproductive success of Mountain 

Bluebirds in unlogged and salvage-logged postfire 

forests (Hitchcox 1996) suggest that both abundance 

and nest success may be lower in salvage-logged areas. 

The second issue is that the moderately high abundance in Seed-tree Cuts suggests either that this 

cutting style is a good surrogate for early postfire 

habitat, or that we are creating an "ecological trap" for 

this species. Studies of nesting success are clearly 

needed. Third is the use of nest boxes along public 

roadsides, which may create populations of this 

species in places they would not otherwise occur. 

From an ecosystem standpoint, introduced species 

often do more harm than good, so unless we need a 

last ditch effort to save the species, such activities 

should probably be discouraged. 

Townsend's Solitaires (fig. 58) were detected on 

275, 199, and 178 of the points in thl( 3 years. This 

species was common in both cut and relatively uncut 

conifer forests, but tends to prefer drier and more open 

cover types. The only potential management issue 

that we see is whether nest success is as good as 

suggested by the relatively common occurrence in 

harvested forest types. This appears to be a bird 

species of little management concern otherwise. 

44 

Figure 57 

Mountain Bluebird 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir ) 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree cut1111~~ clearcutl 

Old Clearcut :::::::: 

Post -Fire :~mrtm}@Iill[Ek@d:jiEL0:::ZZ:Z:;TI 

Sagebrush EifffiillnnItEti1'illZZZEffil I 

Grassland tlHilllrlltmmiLJ I 

RiParia~~t~~:: :1;~fEg1 I 

Cottonwood/Aspen 'If':,;! I ===-~----------------------------' 

o 

Percent of points with detections 

Figure 58 

Townsend's Solitaire 

Cedar/Grand Fir :' 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Old 

Clearcut 

Clearcut cut~iiiliii~!~~~ Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

30 

Cottonwood/Aspen ~2ill£EiIili±§~===i _______________ 1 

o 20 

Percent of points with detections 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Swainson's Thrushes (fig. 59) were detected on 

1064, 585, and 566 of the points in the 3 years. This 

species is associated with the understory shrub layer 

in coniferous forests, so it was detected most often in 

the moister forests and the later successional stages 

of logged stands. Old (pole/sapling) Clearcuts and 

Young Forest were consistently used at a high probability. All types of cut forests were also commonly 

used, making this another species for which data on 

nest success in harvested forests is needed to determine whether these conditions are as suitable as 

suggested by the distribution data. The species was 

also common in or near riparian areas. It was as likely 

to be found in grand fir as in cedarlhemlock (Fisher's 

Exact test, p = 0.73). 

Although it is a common species, the Swainson's 

Thrush was rarely detected early in the season (fig. 4), 

and the strong increase in detectability as the season 

progressed was more pronounced than for any other 

species. This may have biased some probability estimates for cover types that were unevenly sampled 

through time. In particular, the probability of occurrence in SprucelFir may be lower, and that in Ponderosa Pine may be higher, than the data suggest. 

Restriction of the data to the period beginning on 

June 14 (including 80 percent of detections) resulted 

in the expected change for Ponderosa Pine but little 

other difference (fig. 60). 

As with most species, the average distance to detection was highest in Cedar/Grand Fir (except for the 

small sample in Ponderosa Pine). The average distances did tend to be higher in cut than in uncut 

stands, especially for Patch Cuts and recent Clearcuts, but there did not seem to be a pattern that would 

strongly affect the overall results. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Figure 59 

Swainson's Thrush 

Cedar/Grand Lodgepole Spruce/Fir Pine Firllii;::;~::~F===::jl Mixed Conifer Douglas-fir Ponderosa Pine ~:::::::::::::li=i:i:i:ii--l 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut Clearcut 

Old Clearcut 

Post-Fire Sagebrush 

Grassland 

wetland~iiii!~C:==:~~~~~J Riparian Shrub Cottonwood/Aspen 

Cedar/Grand Fir 

Spruce!Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood! Aspen 

o 

Percent of points with detections 

Figure 60 

Swainson's Thrush - starting June 14 

including 80 percent of detections 

1 

1 

J 

l 

I 

I 

I 

I 

I 

I 

I 

1-. I 

I 

I 

I 1--. 

a 

Percent of points with detections 

60 

I 

60 

45 
Hermit Thrushes (fig. 61) were detected on 126, 

102, and 119 of the points in the 3 years. This species 

is found most often in high-elevation Spruce/Fir forests, but also frequents drier coniferous cover types 

such as Ponderosa Pine. All nine detections in the 

Cedar/Grand Fir cover type were in cedar-hemlock, 

and all seven detections in Cottonwood/Aspen were in 

aspen. Although the cover types with highest probability of detection were uncut forests, most of the 

cut forest stands were in mixed -conifer, and there was 

no difference between partially cut and uncut mixedconifer stands. Within Spruce/Fir stands, Hermit 

Thrushes were detected in uncut forest slightly more 

often, but this was not significant (p = 0.42). Within 

the three most used cover types, the difference was 

nearly significant (p = 0.08). Most studies on the 

effects of either clearcutting or partial cutting show 

that Hermit Thrushes are affected negatively by 

such activities (Hejl and others 1995). 

There was a pronounced and steady increase in the 

probability of detecting Hermit Thrushes as the season progressed (80 percent were detected beginning 

June 11). This was not entirely due to increased 

sampling of the Spruce/Fir cover type because the 

pattern remained without those data. Such an independent increase in detectability may have inflated 

our estimates of occurrence in Spruce/Fir, and underestimated the occurrence in Ponderosa Pine (which 

was mostly sampled early in the season). In fact, 

when data were restricted to the second half of the 

season (fig. 62), detections in Spruce/Fir remained 

high, but the detection probability in Ponderosa Pine 

was even higher (although the sample size was small; 

n = 35). In our experience, these two cover types are 

indeed the most widely used by Hermit Thrushes in 

the Northern Rockies. 

46 

Figure 61 

Hermit Thrush 

Cedar/Grand Spruce/Fir Fir~lli~~~;;;;;;;==~--l Lodgepole Pine 

o 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

Percent of points with detections 

Figure 62 

Hermit Thrush - starting June 11, date 

restricted to second half of the season 

I 

I 

J 

J 

I 

J 

I 

I 

I 

~ 

3 

o 

Percent of points with detections 

30 

30 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
American Robins (fig. 63) were detected on 624, 

538, and 403 of the points in the 3 years, where they 

occurred in virtually every cover type available. They 

were most commonly detected, however, in riparian 

areas and in early successional forest stages after 

cutting or fire. They were more likely to be found in 

grand fir than in cedar-hemlock (23 percent versus 11 

percent; Fisher's Exact test, p = 0.05). They were 

detected evenly across the season, and although they 

were more common in mature forest relative to old 

growth (p = 0.006), there is no reason to suspect biases 

in the habitat distribution of this conspicuous and 

ubiquitous species. Because of their commonness and 

their breadth of cover type use, robins pose no special 

management concerns. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

Figure 63 

American Robin 

,:, :. 

o 

Percent of points with detections 

70 

47 
Varied Thrushes (fig. 64) were detected primarily 

in the western portion of the region on 209, 266, and 

152 of the points in the 3 years, primarily in uncut 

Spruce/Fir and Cedar/Grand Fir forests. They were 

much more likely to be seen in cedar-hemlock than in 

grand fir stands (25 percent versus 8 percent, p = 0.01). 

Even within the mixed-conifer cover type (1994 only), 

the species was much more likely to be detected 

when at least some cedarlhemlock (21 percent versus 

8 percent) or spruce/fir (17 percent versus 9 percent) 

trees were present. 

Of 627 detections of Varied Thrushes over 3 years, 

only 11 occurred east of the Continental Divide. This is 

the eastern edge of their range in Montana, as confirmed by long-term distribution records (Montana 

Bird Distribution Committee 1996). It is not known 

whether this distribution is due only to habitat availability or to some independent climatic factor. When 

the analyses were redone with data restricted to 

west of the Divide, the same habitat distribution 

pattern emerged, although with an even higher probability of detection in SprucelFir relative to the other 

cover types. 

Within mixed-conifer forests, this species was more 

likely to be detected in mature than partially cut 

stands (14 percent versus 9 percent, p < 0.001). However, this was not the case within SprucelFir or Cedar/ 

Grand Fir, and the trend was actually reversed. Virtually every timber harvesting study that has been 

conducted in the Rocky Mountains has revealed a 

negative effect of timber harvesting (Hejl and others 

1995), so it may be of interest to discover what 

factors may ameliorate the effect of timber harvesting 

for this species-. 

This species is more likely to be detected in old 

growth than in mature forest (20.2 percent versus 

11.6 percent, p < 0.001). This is most pronounced 

within SprucelFir forests, and it is also true within 

mixed-conifer (but not Cedar/Grand Fir). Only the 

Winter Wren and Brown Creeper showed a stronger 

affinity for old growth. Thus, the maintenance of 

viable populations of this species may depend to some 

extent on the maintenance of some amount of older, 

uncut conifer forest, especially Cedar/Grand Fir and 

Spruce/Fir. This affinity did not bias our results, 

however, because the distribution pattern was similar within mature and within old growth. 

A strong increase in detectability of this species as 

the season progressed resulted in 80 percent of the 

detections occurring from June 7 onward, which was 

only partly due to an increase in sampling of its 

preferred habitat. However, restricting the data to 

this period did not change the habitat distribution 

pattern. Likewise, although only 11 detections occurred east of the Continental Divide, restricting 

the data to westside points did not change the habitat 

distribution results in any meaningful way, nor did a 

combination of time and geographic restrictions. 

48 

Figure 64 

Varied Thrush 

Cedar/Grand Fir 

Spruce/Fir :/ :: .. ' 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

a 50 

Percent of points with detections 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Cedar Waxwings (fig. 65) were detected on 53 

points in all 3 years combined. This species is relatively restricted to riparian vegetation types, so it 

shares the same concerns that accompany similarly 

restricted species: Are streamside management practices providing for the needs of species that are relatively restricted to such conditions? Grazing issues 

might be particularly important for this species because it depends on the fruit resources provided by 

shrubs, which is one vegetation layer that virtually 

disappears under heavy grazing pressure. 

Orange-crowned Warblers (fig. 66) were detected on 217,176, and 171 of the points in the 3 years. 

This warbler species uses shrubby patches within 

uncut forest and is more widely distributed throughout early successional forests after the disturbance 

caused by tree harvesting. This is a classic example of 

a species that is more abundant in harvested forest 

types than in any of the other cover types. The main 

management concern is one of whether the species is 

doing well in those artificially created forests where 

it is abundant. In such situations, we really need to 

know whether we are creating "ecological traps" or 

not. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood! Aspen 

Figure 65 

Cedar Waxwing 

- I - I -

-=:J 

-

-

- I 

-

I 

I 

-

-

-

o 

I 

Percent of pOints with detections 

Figure 66 

Orange-crowned Warbler 

Cedar/Grand Fir "":::::Il%'*--i 

Spruce/Fir ~~--1 

Lodgepole Pine -+.:;:;:;:i=i=4----l 

Mixed Conifer -1?f::::::::;:::}:::;:::\iH 

Douglas-fir 

Ponderosa Pine -41'!'8:,:,:o+---l 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Sagebrush 

Grassland 

Wetland 

Riparian ShnJb-t:,:,:,:, 

Cottonwood! Aspen 

o 

Percent of pOints with detections 

I 

I 

3 

35 

49 
Nashville Warblers (fig. 67) were detected on 49, 

54, and 37 of the points in the 3 years, primarily in 

Cedar/Grand Fir and Riparian Shrub communities 

and the drier forest types. This species is restricted in 

our region to west of the Continental Divide (Montana 

Bird Distribution Committee 1996). We had only three 

detections on the eastside, in the Lewis and Clark 

National Forest. Restriction of the data to the westside 

showed the species to be most frequently detected in 

Douglas-fir and Riparian Shrub. However, restriction 

of data to the period through June 24 (including 80 

percent of the detections) resulted in a different pattern, and a combination of both restrictions (fig. 68) 

changed the pattern again. Apparently, the small 

sample sizes of both the birds and some of the cover 

types make the results sensitive and the conclusions 

questionable. This is an uncommon species that is 

more attuned to shrubby microhabitats than to any 

particular cover type, and thus its specific habitat 

requirements cannot be sufficiently delineated by this 

survey. The affinity for Patch Cuts (such as group 

selection cuts) is interesting and logical, but needs to 

be confirmed with larger samples. 

50 

Figure 67 

Nashville Warbler 

Cedar/Grand Fir-mgEllifiliillEilllifitii±§ilfF=====r-j 

Spruce/Fir ~t----I 

Lodgepole Pine ~~f.+---I 

Mixed conifer-lDg~j . Douglas-fir ::::"*~;:;:t---I 

Ponderosa Pine 

Young Forest 

Partial PatchCut cut~iiil~~~t------1 Seed-tree Cut 

Clearcut~~if.+------i 

Old Clearcut 

Post-Fire -m~EEatEEtt------J 

Sagebrush 

Grassland 

Wetland 

Riparian Shr'ub-_illillffiiEEEEi-----J 

Cottonwood/Aspen ik~P.:w.;:j-_-_-_-=--t _____________ ' 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

-

-

-

-

-

-

-

-

-

-

-

o 

Percent of points with detections 

Figure 68 

Nashville Warbler - to June 24, westside of 

the Continental Divide 

I 

I 

I 

I 

I 

I 

I 

I 

I 

I 

I 

-0 

-

-

-

-

- I -

o 

Percent of points with detections 

10 

I 

12 

USDA Forest Service Gen. Tech. Rep_ RMRS-GTR-32. 1999 
Yellow Warblers (fig. 69) were detected on 101, 

74, and 57 of the points in the 3 years. This is a riparian 

obligate species that is most common in riparian 

areas with well developed shrub layers and large 

deciduous trees-this includes riparian bottomlands 

and streamside shrublands (as well as some urban 

areas). They were much more likely to be detected in 

cottonwood than in aspen stands (40 percent versus 

6 percent; Fisher's Exact test, p < 0.001). Because this 

species is restricted to riparian cover types, and those 

types occupy so little land area, it becomes critical to 

evaluate whether the species is doing well in what 

little area it occupies. There may be a problem with 

cowbird parasitism, especially in the bottomlands, 

where fragmentation and cattle ranching are more 

common (Tewksbury and others 1998). 

Yellow-rumped Warblers (fig. 70) were detected 

throughout the western part of the region on 1022, 

932, and 764 of the points in the 3 years. They were 

most common in the more open, dry conifer forest 

cover types, but were fairly common in the variously 

harvested forest types as well. As our most abundant 

warbler and one of the most abundant forest species 

in the region, this species does not pose any special 

management concerns unless the harvested forest 

types act as "ecological traps" within which the birds 

do poorly despite their abundance. Yellow-rumped 

Warblers certainly would not be expected to do as 

well in Clearcuts, where they were frequently detected, but the relationship between tree retention 

levels and reproductive success needs to be studied. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Figure 69 

Yellow Warbler 

o 

Percent of paints with detections 

Figure 70 

Yellow-rumped Warbler 

o 

Percent of paints with detections 

30 

70 

51 
Townsend's Warblers (fig. 71) were detected 

primarily in the westernmost part of the region on 

614,611, and 599 of the points in the 3 years, primarily 

in the coniferous forest cover types. Townsend's 

Warblers were notably less abundant in the drier 

and more open forest cover types, clearly avoiding 

pine. The clear trend of a decline in abundance within 

increasingly cut forests suggests that Townsend's 

Warblers may depend on relatively uncut forest conditions. It was twice as likely to be detected in grand fir 

as in cedar-hemlock (87 percent versus 43 percent). 

Even within Mixed Conifer (1994 only), the detection 

probabilities in stands with (64 percent) or without 

(32 percent) grand fir differed slightly more than 

stands with (59 percent) or without (36 percent) 

cedar-hemlock. 

This species is probably sensitive to timber harvesting activity, as evidenced by a continuous decline in 

probability of occurrence with increasing amounts of 

timber removed. Indeed, a review of published studies 

of timber harvesting effects in the Rocky Mountains 

revealed that most studies of the effects of timber 

harvesting have shown a decline in abundance of 

Townsend's Warbler (Hejl and others 1995). Townsend's 

Warblers were detected as frequently in mature forest 

as in old growth (0.35 versus 0.32, p = 0.42). 

Townsend's Warblers are largely restricted geographically to west of the Continental Divide (Montana 

Bird Distribution Committee 1996). There were only 

50 detections on the eastside, and they were over 16 

times more likely to be detected on the westside. 

However, restriction of the data to westside points 

did not change the habitat distribution pattern, 

other than an increase in detection probability in 

Douglas-fir, bringing it even with Partial Cuts. A 

decline in detectability of this species as the season 

progressed resulted in 80 percent of the detections 

occurring by June 27. Restricting the data to this 

period did not change the habitat distribution pattern 

either (nor did a combination of time and geographic 

restrictions). 

52 

Figure 71 

Townsend's Warbler 

Cedar/Grand Fir ;: :. : .. 

Spruce/Fir 

Lodgepole Pine 

Mixed conifer111111~~mE£~ Douglas-fir 1 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire-l •• =~ Sagebrush 

Grassland 

Wetland11lH--1 

Riparian Shrub, 

Cottonwood/Aspen ~..!..-______________ I 

o 70 

Percent of points with detections 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
American Redstarts (fig. 72) were detected on 67 

points in all 3 years combined, nearly exclusively in 

the riparian vegetation types. Within those types, 

they were further restricted to points that contained a 

good shrub layer. They were more likely to be detected 

in cottonwood than in aspen stands (19 percent versus 

3 percent; Fisher's Exact test, p = 0.001). The scattered 

observations from conifer forest types probably reflect 

either identification errors or a failure to detect that 

riparian vegetation was also nearby (which would 

have classified those points as "edge" and eliminated 

them from analysis). Nevertheless, some redstarts 

may occasionally show up in patches of deciduous 

regrowth in old harvest units. The apparent abundance in marshes is undoubtedly due to the presence 

of shrubs associated with the wetland complex. The 

most pressing concern here is whether "best management practices" near riparian areas are adequate 

to maintain productive redstart populations. The extent to which this species needs a matrix of relatively 

intact forest surrounding occupied streamside riparian corridors, for example, is unknown, but it has been 

shown to be vulnerable to cowbird parasitism, suffering about 40 percent parasitism rates in an ongoing 

study within the region (Tewksbury and others 1998). 

Ovenbirds (fig. 73) were detected only east of the 

Continental Divide, on 36 points in all 3 years combined, primarily in CottonwoodJ Aspen forests (14 of 15 

detections in this cover type were in aspen). Although 

they are known to use Ponderosa Pine in eastside 

forests, which is also suggested here, this bar represents only four detections. Here is another species that 

is strongly associated with a cover type (CottonwoodJ 

Aspen) that occurs across less than 0.5 percent of all 

the land area in the region. Because of its limited 

habitat distribution, we need to know the effect of 

alternative riparian management regimes on both the 

presence and nesting success of this species, as well as 

more information on the conditions that make ponderosa pine stands suitable for this species. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Figure 72 

American Redstart 

Seed-tree Cut F==----, 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland f------, 

Wetland I=====!.--------, 

Riparian Shrub 1============-___ ----, 

Cottonwood/Aspen '-=~_~ _____ ~=~_==,--_I 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

o 

Percent of paints with detections 

Figure 73 

Ovenbird 

Ponderosa Pine f===--------, 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen f===-------------, 

o 

Percent of paints with detections 

10 

53 
Northern Waterthrushes (fig. 74) were detected 

on 74 points in all 3 years combined, primarily in 

riparian areas. This species is probably more ripariandependent than indicated here. It occurs at small 

marshes and potholes within forested cover types, 

and such microhabitats are easily overlooked, so that 

observers may not have noted that a riparian cover 

type was near. We need to know which microhabitats 

are important for this species within conifer stands 

(note that the bar in Spruce/Fir represents only four 

individuals). This is another species that may be 

sensitive to streamside management practices and 

would, therefore, serve as a good indicator of whether 

streamside "best management practices" are serving 

the needs of wildlife species. 

MacGillivray's Warblers (fig. 75) were detected 

on 537, 419, and 448 of the points in the 3 years, 

across a wide variety of forest cover types. Despite its 

broad pattern of cover type use, this species needs 

shrubs, either in association with streamside riparian situations or in association with open patches 

within the forest where early forest succession has 

produced decent shrub growth. They may also be 

drawn into other conifer cover types by roadside vegetation. Because of the relatively high probabilities 

of detection in harvested forests, the MacGillivray's 

Warbler appears to benefit from a variety of forest 

harvesting methods. Whether their reproductive success mirrors the census data or whether we are creating "ecological traps" by attracting this species into 

places where they do poorly is, however, unknown. 

Management activity that encourages artificially 

rapid regeneration of the forest (for example, tree 

planting or use of herbicides) and reduces the duration of early successional stages would act to the 

detriment of this shrub-dependent species. 

54 

Figure 74 

Northern Waterthrush 

Cedar/Grand Fir 

Spruce/Fir 1--------------, 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest f----, 

Partial Cut 

Patch Cut F===--, 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

1-------------, 

Wetland F======~--------------' 

Riparian Shrub F========;------------' 

Cottonwood/Aspen '-~_~_~_..!..-_________ ' 

Cedar/Grand Fir 

o 

Percent of pOints with detections 

Figure 75 

MacGillivray's Warbler 

Ponderosa Pine ~::::::::~;'!j----I 

Young 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

5 

Riparian 

Wetland~iiiiiil!~~~=~==~J Shrub 

Cottonwood/Aspen 

o 60 

Percent of pOints with detections 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Common Yellowthroats (fig. 76) were detected 

on 26, 38, and 34 of the points in the 3 years, nearly 

exclusively in riparian cover types (especially marshes). 

Because this species is nearly restricted to marshes 

and willow flats, the draining of wetlands and the 

impact of adjacent land-use activity on this wetlanddependent species needs special consideration; without intact· wetland areas, they have little habitat 

available. In aspen, cottonwood, and willow cover 

types, this species is negatively affected by grazing 

activity, and is nearly four times less abundant in 

grazed than ungrazed conditions (Saab and others 

1995). 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Figure 76 

Common Yellowthroat 

o 

Percent of pOints with detections 

25 

55 
Wilson's Warblers (fig. 77) were detected on 74,76, 

108 of the points in the 3 years, primarily in higher 

elevation conifer forests. This species nests primarily 

in high elevation willow thickets (Stewart and others 

1977), and although they may penetrate into upland 

forests with sufficient shrubs (perhaps affected by 

roads), most individuals are probably still associated 

with nearby water sources. Nine of 10 detections in 

the Cedar/Grand Fir cover type were in cedarlhemlock. 

Although not restricted to west of the Continental 

Divide (Montana Bird Distribution Committee 1996), 

the Wilson's Warbler was over five times as likely to 

be detected there. Restriction of the data to westside 

points (fig. 78) resulted in an even greater apparent 

use of high-elevation forests (Spruce/Fir and Lodgepole Pine), Old Clearcuts, Post-Fire, and shrubby 

riparian areas. In western Oregon, it frequents early 

growth clearcuts with sufficient deciduous saplings 

(Morrison 1981). In our experience, this species is 

relatively common in riparian areas within highelevation conifer forests. If so, this species may be 

more sensitive to streamside management practices 

than is implied by the distribution data. We may also 

need more surveys of high-elevation Wilderness 

areas to fully understand the habitat requirements 

and population status of this species in our region. 

56 

Ponderosa 

Figure 77 

Wilson's Warbler 

Young Forest111i=~ Partial cuti 

Patch Cut -1::::::::::;:::::::::::::::::::!:H 

Seed-tree Cut iiHEmITItaiEi-------1 

Clearcut -;:::::::::::::::::::t*W'--I 

Old clearcutllll 

Post-Fire 1 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

o 

-

-

-

-

-

-

-

-

-

-

-

-

-

-

Percent of points with detections 

Figure 78 

Wilson's Warbler - westside of the 

Continental Divide 

I 

I 

1 

J 

1 

1 

1 

I 

1 

I 

I 

1 

I 

1 

o 

Percent of points with detections 

16 

I 

15 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Western Tanagers (fig. 79) were detected on 

663,486, and 542 of the points in the 3 years. They 

occurred across a wide range of coniferous forest cover 

types, but were most common in the lower elevation 

and drier forest types, especially Ponderosa Pine and 

the harvested forests with a relatively large number of 

green trees left. Because tanagers are widespread 

across most coniferous forest types, there is probably 

not much of management concern here. The issue of 

primary importance is whether their relatively high 

abundance in harvested forest types reflects the suitability of those types or not. In many respects, harvested forest types are "unnatural," so they may not 

hold all necessary requisites for species such as the 

tanager, which may be attracted to those sites because of their superficial similarity to some naturally 

occurring cover type. This species is so widespread, 

both spatially and temporally, that its distribution 

pattern is probably unbiased. 

Green-tailed Towhees (fig. 80) were detected in 

the south-central portion of the region on 49 points in 

all 3 years combined. They were relatively restricted 

to Sagebrush cover, as well as some riparian situations. The management issue of primary concern is 

probably whether this ground- or low-shrub-nesting 

species is affected negatively by grazing regimes in 

sagebrush. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Figure 79 

Western Tanager 

Cedar/Grand Fir-§!@&llitElmtElm2llilitElillB±i==r---l 

Spruce/Fir 

Lodgepole Pine 11111 

Mixed Conifer i 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut-f:::::::::::::;;;::::;:;:;:; 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland14@EIWBlffiEl---l 

Riparian Shrub ~::;:;:;~~:;:;:;:::::i:;::;:;jIj 

Cottonwood/Aspen -{':Iili[iillillmEmillit:===L ________ 1 

o 

Percent of pOints with detections 

Figure 80 

Green-tailed Towhee 

Cedar/Grand FirSpruce/FirLodgepole Pine 

Mixed Conifer 

Douglas-fir -

Ponderosa Pine 

Young Forest-w 

Partial CutPatch CutSeed-tree CutClearcut 

Old ClearcutPost-FireSagebrush r----------------.I 

Grass/and -Q 

WetlandRiparian Shrub-D 

50 

Cottonwood/Aspen _f==-----,I 

~----~---------__ ------_I 

15 

Percent of points with detections 

57 
Spotted Towhees (fig. 81) were detected on 51, 65, 

and 61 of the points in the 3 years, primarily in the 

drier brushy areas within riparian areas, in early 

successional Post-Fire and Clearcut stands, and in 

the brushy draws in shrublands and Grasslands. A 

strong decline in detectability of this species as the 

season progressed resulted in 80 percent of the detections occurring by June 21. However, restricting 

the data to this period did not change the habitat 

distribution pattern. The shrub microhabitats used 

by this species occur within a variety of open forest 

and range situations, so the broad cover types used 

here may not adequately reflect the needs of this 

species. The issue of primary management concern is 

livestock grazing, which is a common land-use practice in the cover types frequented by Spotted Towhees. 

A review of the literature on the effects of grazing in 

western riparian habitats did not suggest a problem, 

however (Saab and others 1995). 

Chipping Sparrows (fig. 82) were detected on 

698,480, and 350 of the points in the 3 years, primarily 

in the open, dry forest types and in forests that 

have become open through timber harvesting activity. 

This species is abundant and widespread, yet recent 

(1968 to 1991) data on population trends in the West 

(Hejl 1994) show significant declines. Managers 

might need to look in some of the harvested forest 

cover types to see if reproductive success is as good as 

implied on the basis of our census data. There are two 

studies of grazing effects in bottomlands that have 

data on Chipping Sparrows, and both showed that 

the species was less abundant in grazed than in 

ungrazed sites (Saab and others 1995)i 

58 

Figure 81 

Spotted Towhee 

Cedar/Grand Fir~:m---l 

Spruce/Fir 

Lodgepole Pine 

Mixed conifer-lgg~H 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 1Jj[ll1limEEE5EE!Eil3-----~ Old Clearcut -1::::;j;:;@.@@4---J 

Post_Fireliiii~~~~~~~----j Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen~~lt-==~!.--_____________ I

o 

Percent of pOints with detections 

Figure 82 

Chipping Sparrow 

o 

Percent of pOints with detections 

12 

70 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Brewer's Sparrows (fig. 83) were detected on 80 

points in all 3 years combined, primarily in southwestern Montana. This species is nearly restricted to 

Sagebrush. Because the species is so highly restricted 

in its habitat distribution, and because Breeding Bird 

Survey data suggest that it is one of the most severely 

declining songbird species on a nationwide basis 

(Peterjohn and others 1996), we should be focusing on 

this species in studies of the effects of sagebrush landuse practices on wildlife species. We did not obtain 

enough data from both heavily grazed and lightly 

grazed conditions to comment on potential effects. 

Brewer's Sparrows have shown inconsistent responses 

to grazing in the past, but they may now be harmed by 

heavy grazing that continues to remove herbaceous 

cover (Saab and others 1995). 

Vesper Sparrows (fig. 84) were detected throughout the eastern half of the region on 178, 146, and 101 

of the points in the 3 years, primarily in Grasslands 

and Sagebrush (and in agricultural lands, as recorded 

in additional surveys not reported here). Permanent 

monitoring points on the westside of the Divide do not 

cover appropriate cover types for this species. Only 

the 101 extra Grassland and Sagebrush points sampled 

in 1994, as.well as our personal experience, show this 

species to be abundant in appropriate habitat west of 

the Divide, at least in west-central Montana. This 

species declined in detect ability through the season, 

with 80 percent of the detections occurring by June 28. 

However, because this species was so strongly restricted to Grassland and Sagebrush, no subset of the 

data would change this pattern. We need information 

on the nesting success of this species under alternative 

management regimes in sagebrush and grassland 

cover types. Vesper Sparrows have shown inconsistent responses to grazing (Saab and others 1995). 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Cedar/Grand FirSpruce/Fir -

Lodgepole PineMixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young ForestPartial CutPatch CutSeed-tree CutClearcutOld ClearcutPost-FireFigure 83 

Brewer's Sparrow 

~-------------------------. 

Sagebrush I======,------------------'J 

Grassland - I 

Wetland-[J 

Riparian ShrubCottonwood/Aspen tJ 

~------------------------------' 

o 30 

Percent of points with detections 

Figure 84 

Vesper Sparrow 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian 

Cottonwood/Aspen 

0 90 

Percent of pOints with detections 

59 
Savannah Sparrows (fig. 85) were detected on 40, 

29, and 26 of the points in the 3 years, in open 

Grassland and Sagebrush cover types. However, this 

species was even more frequent (73 percent) in 56 

extra points we sampled in agricultural fields (not 

otherwise reported here). If this species is consistently 

drawn to agricultural fields, such a distribution would 

seem to beg for information on how well they do in 

terms of reproductive success. If they do poorly because of mechanical disturbance from farming activity, for example, then such fields would be acting as 

"ecological traps," especially since a disproportionately large segment of the bird population may be 

using such conditions. All studies to date on grazing 

effects in grasslands and shrubsteppe have shown 

this species to be affected negatively by grazing (Saab 

and others 1995). This species declined in detectability through the season, with 80 percent of the detections occurring by June 27. However, because this 

species was so strongly restricted to Grassland and 

Sagebrush, no subset of the data would change this 

pattern. 

Grasshopper Sparrows (fig. 86) were detected on 

30 points in all 3 years combined, nearly exclusively in 

Grasslands (the one observation in Spruce/Fir was 

not well documented). As with the other grasslanddependent species, Grasshopper Sparrows have been 

experiencing significant long-term (1966 to 1995) 

population declines (Peterjohn and others 1996) probably largely because of the conversion of land for 

agricultural purposes. There is also a clear need for 

information on the presence and reproductive success 

of this species in relation to grazing practices in grasslands; so far, the vast majority of studies on grazing 

effects in grassland have shown this species to be 

negatively affected (Saab and others J.995). 

60 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Figure 85 

Savannah Sparrow 

Sagebrush It" I": Itl:I:: 1:"I"'I'llr~==~-j Grassland ff ::: t 

Wetland 

Riparian Shrub 

Cottonwood/Aspen ~ ________________ '

o 

Percent of pOints with detections 

Figure 86 

Grasshopper Sparrow 

Cedar/Grand FirSpruce/Fir -tJ 

Lodgepole PineMixed ConiferDouglas-firPonderosa PineYoung ForestPartial CutPatch CutSeed-tree CutClearcutOld Clearcut 

Post-Firesagebrush-I---___________ ---, 

GrasSland-I---___________ ----I1 

WetlandRiparian Shrub30 

Cottonwood/Aspen-I _________________ , 

o 15 

Percent of points with detections 

USDA Forest SeNice Gen. Tech. Rep. RMRS-GTR-32. 1999 
Fox Sparrows (fig. 87) were detected in the northwestern portion of the region on 99, 128, and 91 of the 

points in the 3 years. They are the only species for 

which we have data that show a relative restriction to 

higher elevation Spruce/Fir forests. Because of its 

uniquely restricted habitat distribution pattern in 

the Northern Rockies, this species might be a good one 

to use as an indicator of conditions in the spruce-fir 

zone. All six detections in Cedar/Grand Fir were in 

cedar-hemlock. 

Although only four Fox Sparrows were detected 

east of the Continental Divide, restriction of the data 

to westside points did not change the habitat distribution pattern, except for an increase in detection probability within the Riparian Shrub cover type. A strong 

increase in detectability of this species as the season 

progressed resulted in 80 percent of the detections 

occurring from June 12 onward. However, restricting 

the data to this period did not change the habitat 

distribution pattern. 

Song Sparrows (fig. 88) were detected on 135, and 

110, 124 of the points in the 3 years. They are relatively restricted to riparian streamsides, bottomlands, 

and marshlands. They were more likely to be detected 

in cottonwood than in aspen stands (42 percent versus 

6 percent; Fisher's Exact test, p < 0.001). This is 

another species that may be sensitive to streamside 

management practices and would, therefore, serve as 

a good indicator of whether "best management practices" are really serving the needs of wildlife species. 

Nationwide, from 1966 through 1995, this species has 

declined significantly (Peterjohn and others 1996), 

possibly due to cowbird parasitism, which is prevalent in the habitats Song Sparrpws prefer. They are 

heavily parasitized in this region, affecting about 65 

percent of nests in one study (Tewksbury and others 

1998). 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Figure 87 

Fox Sparrow 

Cedar/Grand Fir ~~I-----l 

Spruce/Fir i]illITINTIillEilimTIillEiliillEEiIffiEa-----1 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest-4E~-~ 

Partial Cut 

Patch Cut i1ffiEaBa------i 

Clearcut 

Old Clearcut m;I@;g;;~~----.j 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen ~ ________________ , 

o 

Peicent of points with detections 

Figure 88 

Song Sparrow 

45 

Cottonwood/Aspen Riparian ShrUblllll!~~~~=!:===~1 1 '. ::. o ~ 

Percent of points with detections 

61 
Lincoln's Sparrows (fig. 89) were detected on 94 

points in all 3 years combined, primarily in higher 

elevation, Riparian Shrub and Wetland environments, including the riparian draws within some 

early postfire forests and harvested stands. Because 

the species is restricted to riparian conditions, any 

negative effects of streamside riparian practices 

would be of considerable consequence to the maintenance of a viable population. 

White-crowned Sparrows (fig. 90) were detected 

on 38, 43, and 53 of the points in the 3 years, especially 

woody draws in Sagebrush and Post-Fire cover types. 

In aspen and willow cover types, this species seems to 

be negatively affected by grazing activity, and is nearly 

five times less abundant, on average, in grazed than 

ungrazed conditions (Saab and others 1995). 

62 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Figure 89 

Lincoln's Sparrow 

Wetland f==---------------, 

Riparian Shrub F====:::;----I 

Cottonwood/Aspen ~===.d.-_____________ I 

Cedar/Grand Fir 

o 

Percent of points with detections 

Figure 90 

White-crowned Sparrow 

Spruce/Fir ~~>:f----j 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut -ItElEttta--i 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

15 

Cottonwood/Aspen "t,+';;"::'~~~-=--=--=--=--=!'-____________ I 

o 20 

Percent of points with detections 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Dark-eyed Juncos (fig. 91) were detected on 1295, 

1100, and 1082 of the points in the 3 years. They 

occurred in a wide range of forest cover types. They 

nest on the ground, often beneath downed logs, so it is 

not surprising that they are three times more likely to 

occur on points with an abundance of dead and down 

(57.9 percent occurrence) than on points without any 

dead and down nearby (18.8 percent occurrence). There 

would not seem to be much to worry about with a 

species as widespread and common as this one. N onetheless, maintaining the dead-and-down component 

in harvested areas may be needed to maintain healthy 

populations of this species. This species is so ubiquitous, both spatially and temporally, that no significant biases are expected in the data. 

Black-headed Grosbeaks (fig. 92) were detected 

on 73, 55, and 69 of the points in the 3 years, in riparian 

and early successional areas. They were relatively 

abundant in variously cut forest types, and may be 

benefitting from various cutting practices. Alternatively, cut forests may be acting as "ecological traps" 

by containing the appropriate superficial characteristics 'but being otherwise unsuitable. Research is 

needed to resolve this issue. Because of their abundance in riparian bottomlands, another issue is whether 

they may be affected negatively by land use practices 

therein, especially livestock grazing. In aspen, cottonwood, and willow cover types, this species is uniformly 

negatively affected by grazing activity (Saab and others 

1995). 

The Black-headed Grosbeak is not restricted to west 

of the Continental Divide (Montana Bird Distribution 

Committee 1996), but we had only two detections on 

the eastside. Restriction of data to westside points did 

increase the detection probabilities in riparian cover 

types, so that Cottonwood! Aspen became the most 

frequented cover type, as expected for this species. 

However, all of the standard deviations were still 

large, and there were a total of only nine detections in 

cottonwood stands (11 percent) and only one in aspen. 

A decline in detectability of this species as the season 

progressed resulted in 80 percent of the detections 

occurring by June 25. Restricting the data to this 

period increased its prominence in postdisturbance 

cover types (Clearcut and Post-Fire), but did not otherwise change the habitat distribution pattern. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Figure 91 

Dark-eyed Junco 

Cedar/Grand Fir :: :: ,: :: " 

'Spruce/Fir":';;, 

Lodgepole Pine :' :' 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

seed-treecut Clearcut __ illl~~ Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

o 

Percent of pOints with detections 

Figure 92 

Black-headed Grosbeak 

Cedar/Grand Fir~+--~ 

o 

Percent of points with detections 

80 

15 

63 
Lazuli Buntings (fig. 93) were detected on 57, 51, 

and 46 of the points in the 3 years. They are associated 

primarily with shrubfields (especially in postfire situations, where Hutto [1995] showed them to be at least 

as frequent as in the Clearcuts sampled here), and 

shrubby vegetation in riparian areas. Through fire 

suppression efforts and silvicultural treatments that 

shorten the shrub stages following disturbance, we 

may have decreased the amount of early successional 

habitat for this species, although the data suggest 

this is well compensated by shrubby Clearcuts, if the 

species is doing well in such cover types. Data from 

local studies (E. Greene, unpubl. data) suggest that 

Lazuli Buntings are susceptible to cowbird parasitism 

and are heavily parasitized in areas used by cowbirds. 

Thus, we need more information on parasitism rates 

under different management regimes (especially cattle 

grazing around riparian areas). An increase in detectability of this species as the season progressed resulted in 80 percent of the detections occurring from 

June 9 onward. However, restricting the data to this 

period did not change the habitat distribution pattern. 

Red-winged Blackbirds (fig. 94) were detected on 

35 points in all 3 years combined, nearly exclusively in 

marshlands (and in agricultural lands, as recorded in 

additional surveys not reported here). The main concern for this species is probably loss of habitat per se 

through draining of wetlands and conversion to agricultural uses. In addition, six of seven studies of 

grazing effects on western birds showed this species 

to be negatively affected by grazing (Saab and others 

1995). 

64 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Figure 93 

Lazuli Bunting 

Patch Cut-lmEB2ItfElBEB±j-----------i 

Seed-tree Cut 

Old Clearcut clearcut~iilll~~~~~~------1 Post-Fire 

Sagebrush -I::I*~:,:,;,:f----l 

Grassland ~:::::::::;~mt___i 

Wetland~~----l 

Riparian Shrub 

Cottonwood/Aspen ~~~+-----; 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

o 

Percent of paints with detections 

Figure 94 

Red-winged Blackbird 

~=--------------~ Wetland '===-______________ --' 

Riparian Shrub 

22 

Cottonwood/Aspen ~=.d-________________ '

o 15 

Percent of points with detections 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Western Meadowlarks (fig. 95) were detected on 

137, 65, and 42 of the points in the 3 years, nearly 

exclusively in Grasslands and Sagebrush (and in agricultural lands, as recorded in additional surveys not 

reported here). This species declined in detectability 

strongly through the season, with 80 percent of the 

detections occurring by June 12. However, because 

this species was so strongly restricted to Grassland 

and Sagebrush, no subset of the data would change 

this pattern. In terms of population response to grazing, this species has been shown to be negatively 

affected by grazing in many studies, but the effect is 

generally weak or inconclusive (Saab and others 1995). 

We need information on the nesting success (not 

just population density) of this species under alternative management regimes in sagebrush and grassland 

cover types. 

Brown-headed Cowbirds (fig. 96) were detected 

on 190, 120, and 85 of the points in the 3 years, in a 

wide variety of cover types. They were largely absent 

from dense, old growth, and high-elevation forests. 

Cowbirds were most abundant in open conifer forest 

(Ponderosa Pine and partially logged sites) as well as 

Grassland and riparian cover types (and in agricultural lands, as recorded in additional surveys not 

reported here). A decline in detectability of this species 

as the season progressed resulted in 80 percent of 

the detections occurring by June 26. However, restricting the data to this period did not change the 

habitat distribution pattern. 

Because cowbirds were fairly restricted to areas east 

of the Continental Divide until their expansion with 

the cattle industry, numerous western songbird species that had not evolved in the presence of cowbirds 

are now experiencing parasitism for the first time and 

at rates that may be too great for them to counter in an 

adaptive sense. The phenomenon is interesting but 

one that does not bode well for species that occur in the 

presence of high cowbird densities. In a multiple 

regression analysis offactors influencing cowbird distribution in the Northern Rockvr Mountains (Young 

and Hutto 1999), models were dominated by landscape rather than vegetation v~riables. In fact, distance to agricultural lands was the strongest predictor 

of cowbird presence. Cowbirds were so strongly associated with the proximity of agricultural areas that 

many areas of the forested mountains are probably 

still safe from parasitism pressure. Cowbirds may be 

a textbook example of the importance of landscape 

context in the distribution of a bird species. We need 

additional studies to determine how cowbird densities 

and parasitism rates are related to alternative landuse practices and to various landscape configurations. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Figure 95 

Western Meadowlark 

o 

Percent of points with detections 

Figure 96 

Brown-headed Cowbird 

Cedar/Grand Firoof.:ffit-----i 

Spruce/Fir 

Lodgepole Pine -iim~ff.:!----l 

Mixed conliferI]UEEHi--j 

Douglas-fir -t:::::::~+---i 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwoodl Aspen 

o 

Percent of pOints with detections 

60 

15 

65 
Pine Grosbeaks (fig. 97) were detected on 49 points 

in all 3 years combined, most commonly in the higher 

elevation SprucelFir forests. This is another species 

that appears to be more abundant in relatively uncut 

than in harvested forest types. Some studies have 

indicated a negative effect of logging (Hejl and others 

1995), but more information is needed. The maintenance of viable populations of this species probably 

necessitates the maintenance of tracts of relatively 

uncut, high elevation conifer forests. 

Cassin's Finches (fig. 98) were detected on 83, 74, 

and 36 of the points in the 3 years. They occurred in 

most of the conifer forest types but were detected most 

frequently in early Post-Fire, Partial Cut, and Ponderosa Pine, where they apparently hone in on conifer 

seed production. Seed resources that become available 

shortly after a stand-replacement fire may be important to this species. Thus, postfire salvage cutting may 

be in conflict with its needs. Partial Cuts look quite 

suitable, and food is probably not a problem in harvested forests because cone (seed) production in "leave" 

trees probably increases after harvesting. N onetheless, harvested forests may act as "ecological traps" by 

creating stands that take on a postfire, open appearance but fail to provide for other neetls. A decline in 

detectability of this species as the season progressed 

resulted in 80 percent of the detections occurring by 

June 27. When the data were restricted to this period, 

Ponderosa Pine and Post-Fire remained the dominant 

cover types, followed by Partial Cut, there were some 

shifts in the less used types. 

66 

Cedar/Grand Fir 

Spruce/Fir 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut 

Old Clearcut 

Post-Fire 

Sagebrush 

Grassland 

Wetland 

Riparian Shrub 

Cottonwood/Aspen 

Figure 97 

Pine Grosbeak 

-

-

- ] 

- I 

-

-

-0 

- I - I -

-

-t=J 

-

-

-

-

-0 

-

o 

Percent of pOints with detections 

Figure 98 

Cassin's Finch 

Cedar/Grand Fir..;?;""""."""': """,'*"I-----l 

Spruce/Fir ; .:: . 

Lodgepole Pine 

Mixed conifer-1@J@ggt--1 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut -IEillTIEillBlH 

Patch Cut 

Seed-tree Cut ~~f------l 

Clearcut-l[l~8----1 Old Clearcut ~:j;i>,;;.:s,:!'t-----l 

Post-Fire-t;ffiiBim9iEBEEaf---------l 

Sagebrush 

Grassland iM[lEffit--1 

Wetland-;\i:H~----1 

Riparian Shrlub-~::;:;::::::;':::::::::::; 

Cottonwood/Aspen 

o 

Percent of pOints with detections 

I 

5 

15 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Red Crossbills (fig. 99) were detected on 75, 59, 

and 162 of the points in the 3 years, and were broadly 

distributed across most of the conifer forest types. No 

special management considerations are suggested by 

the data, but we should point out that this is an 

extremely mobile and widespread bird species that 

can be detected in most conifer forest types. Its reliance on productive cone crops has implications for the 

effects of logging and loss of old growth (Benkman 

1993). Thus, managers will need to pay careful attention to its nesting and feeding biology (see, for example, Benkman 1993) to better determine the characteristics within conifer forests that best meet its 

needs. 

Pine Siskins (fig. 100) were detected on 224, 332, 

and 594 of the points in the 3 years, and were more 

broadly distributed across cover types than most any 

other songbird species in the region. The widespread 

distribution of this species suggests that there is little 

of current management concern here, but there are 

data from western Montana (Hunt 1989) that show a 

positive correlation between siskin density and the 

severity of a spruce budworm outbreak. Thus, their 

distribution and abundance may depend to some extent on the locations and extents of such outbreaks. 

Because the species is so vocal and wide-ranging, it 

may be impossible to determine its habitat needs 

from habitat distribution data alone. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Figure 99 

Red Crossbill 

Cottonwood/AspenjilililiiiB====L ________ -l o 

Percent of points with detections 

Figure 100 

Pine Siskin 

25 

Cottonwood/Aspen Riparian ShrUbliiiliii;;~======J ~ . .. 

o 55 

Percent of points with detections 

67 
Evening Grosbeaks (fig. 101) were detected on 39, 

36, and 49 of the points in the 3 years, and were fairly 

uniformly distributed across all the conifer forest 

types. No management issues of special concern are 

suggested by the data, although clearcut logging has 

also been shown elsewhere to negatively affect this 

species (Hejl and others 1995). The high variances 

around the mean detections may reflect true variability in abundance from year to year in response to 

variation in food (especially spruce budworm) availability. It is of special management interest that this 

and other irruptive, social fringillid species seem to 

feed heavily on spruce budworm (Takekawa and Garton 

1984). 

Only nine of the detections occurred east of the 

Continental Divide, although this does not reflect a 

range restriction (Montana Bird Distribution Committee 1996). Little change was observed when data 

were restricted to the westside. A decline in detectability of this species as the season progressed resulted in 80 percent of the detections occurring by 

June 24. When the data were restricted to this period, 

Ponderosa Pine and Mixed Conifer increased in prominence, with other minor differences, but the variability of this species makes conclusions questionable. 

68 

Figure 101 

Evening Grosbeak 

Cedar/Grand Fir ~;:;:;:;:;:;:;i:4---~ 

spruce/Firiillmmatl 

Lodgepole Pine 

Mixed Conifer 

Douglas-fir 

Ponderosa Pine 

Young Forest 

Partial Cut 

Patch Cut 

Seed-tree Cut 

Clearcut -F..~~f----4 

Old Clearcut 

Post-FirelBffi;E3!t-------1 

Sagebrush 

Grassland 

Wetland~~~ 

Riparian Shrub~~:.1--~ 

Cottonwood/Aspen "tti;ma====~ _________ 1 

o 9 

Percent of points with detections 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
Discussion -----------------------------

If the goal of our public land management agencies 

is to maintain ecosystem integrity in the face of many 

demands on the land, then know ledge of biological 

consequences of various actions will aid in land use 

decisions. A landbird monitoring program such as 

this, which is large enough and ecologically broad 

enough, can help us predict and monitor the effects of 

management activities on bird species for almost all 

the major vegetation types in a region. Results from 

our initial short-term effort clearly demonstrate some 

limits within which any agency aspiring to maintain 

ecological integrity must work. 

Specifically, some landbird species are relatively 

restricted in their habitat distribution to only one or 

two naturally occurring cover types that are themselves restricted in spatial extent, or at least less 

extensive than they were in the preindustrial past. 

The loss of anyone of these cover types will mean the 

loss of those bird species that are relatively restricted 

to it. Thus, managers need to maintain each of those 

cover types (defined at least as finely as we have 

defined them herein) on the broader landscape, although it is unclear how much of each needs to be 

retained to maintain viable populations of any given 

species. Even if we are not about to lose a given cover 

type from the broader landscape, land use practices 

within and surrounding that type may have im portant implications, especially for species restricted to 

that cover type. We provide specific examples and 

implications of relatively restricted distributions. 

Species that best illustrate a given distribution pattern are highlighted in bold lettering. 

Post-Fire, Standing-Dead Forests 

Examples of inhabitants of these forests are Threetoed Woodpecker and Mountain Bluebird. The Blackbacked Woodpecker may be the species most restricted 

to this cover type (Hutto 1995), although we did not 

have sufficient data to demonstrate that here. Even 

widespread species such as Hairy Woodpecker and 

American Robin tend to be most abundant in burned 

forests (Hutto 1995). Salvage ,logging may have a 

negative effect on species that are either relatively 

restricted to, or are most abundant in, early postfire 

conditions because those bird'species depend to a 

great extent on standing dead trees in burned forests 

for feeding or nesting (Caton 1996, Hitchcox 1996, 

Hutto 1995, Saab and Dudley 1998). The presence of 

such narrowly distributed habitat specialists leaves 

little doubt that clearcutting associated with a large 

portion of postfire salvage logging is in direct conflict 

with the needs of some of these bird species. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 

Relatively Uncut Forests 

Examples of inhabitants of these forests are Brown 

Creeper, Winter Wren, Golden-crowned Kinglet, 

Hermit Thrush, Varied Thrush, and Townsend's Warbler. Based on observed differences in the probabilities of occurrence between the cut and uncut forest 

types, the cutting (even light thinning) of dense, older 

forests (especially Cedar/Grand Fir) will have negative effects on several species that are relatively restricted to those conditions. In fact, some of these 

species (for example, Brown Creeper and Winter Wren) 

require not only relatively uncut, but relatively old 

forests as well. To assure the maintenance of their 

populations, we probably need to maintain relatively 

large patches of uncut forest types on the landscape. 

These conclusions are similar to those drawn after a 

comprehensive literature survey of the effects of timber harvesting on Rocky Mountain birds (Hutto and 

others 1993, Hejl and others 1995). 

Harvested Forest Types 

Although no bird species is entirely restricted to 

one or more of the harvested forest cover types, many 

show considerably higher probabilities of detection in 

cut than in uncut forests. Examples are American 

Kestrel, Calliope Hummingbird, Rufous Hummingbird, Williamson's Sapsucker, Northern Flicker, 

Olive-sided Flycatcher, Dusky Flycatcher, Steller's 

Jay, Cassin's Vireo, Warbling Vireo, Orange-crowned 

Warbler, MacGillivray's Warbler, and Black-headed 

Grosbeak. One potential management issue is related 

to the fact that harvested forests are "unnatural" in 

that their structure consists of combinations of elements (for example, widely, or evenly spaced live 

trees) that simply do not exist in natural successional 

seres. The problem is that these unnatural cover types 

may elicit settling responses by species that are "programmed" to respond to superficially similar, but 

fundamentally different, early successional forest 

types. In turn, these unnatural forest types may act as 

"ecological traps," where species are attracted to 

areas in which suitability (in terms of reproductive 

success or adult survival or both) is poor because food 

resources, predation, or parasitism rates are unnaturally high. Although demographic "source" and "sink" 

areas (as defined by Pulliam 1988) may occur naturally, sink areas are not synonymous with ecological 

traps. The only time an organism can be "trapped" 

(differentially attracted to an area within which suitability is poor) is when a system has been so artificially 

altered that the organism's success depends upon 

altering its usual settling response. 

Because no forest bird species is entirely restricted to 

harvested conditions, there will always be populations 

69 
in naturally occurring unharvested forest, which may 

serve as refuges. Moreover, if our abundance data 

accurately reflect suitability of cover types, conditions 

for many forest bird species may actually have improved through timber harvesting activities. We need 

information on survival and reproductive success of 

birds in harvested forests to determine whether relative abundance is a good reflection of relative suitability or not. 

Marshes 

Examples of inhabitants of marshes are Common 

Snipe, Common Yellowthroat, Lincoln's Sparrow, and 

Red-winged Blackbird. The draining and conversion of wetlands will have negative effects on species 

restricted to those conditions. Because our methods 

were not well designed to capture patchily distributed 

marsh lands, we did not detect enough of several 

additionallandbird species that are known to fall into 

this category of restricted distribution (for example, 

Virginia Rail [Rallus limicola], Sora, Marsh Wren, 

Yellow-headed Blackbird). 

Riparian Vegetation 

Numerous landbird species are relatively restricted 

to the shrubs or deciduous trees associated with 

riparian environments. Our data did not allow us to 

differentiate well between the species that prefer 

cottonwood bottomlands or upland riparian shrub 

communities, but many species are relatively restricted 

to one or both of these types (for example, Ruffed 

Grouse, Western Wood-Pewee, Willow Flycatcher, 

Cordilleran Flycatcher, Red-eyed Vireo, Cedar Waxwing, Yellow Warbler, American Redstart, Northern 

Waterthrush, Song Sparrow). This fact takes on special meaning when we consider that riparian cover 

types make up less than 0.5 percent of all land area in 

the Northern Region, and that this cover type (especially the bottomlands) incurs a disproportionate 

amount of human activity (for example, home building, 

recreation, and livestock grazing) and cowbird parasitism. Much of this land base is private, making 

publicly owned land of this type much more important 

as potential refuges for wildlife that might be sensitive 

to human activities. We currently lack, but desperately need, information on cowbird parasitism rates in 

relation to the presence of livestock in riparian bottomlands, and we need information on the effects of 

vegetation alteration and livestock presence on nesting success of riparian bottomland birds. Additional 

species that are restricted to riparian bottomlands, 

but for which we obtained insufficient data to develop 

models, include the Belted Kingfisher, Bank Swallow, Least Flycatcher, Veery, Gray Catbird, and 

American Goldfinch. Species restricted to upland 

riparian streamside vegetation may be especially 

70 

sensitive to so-called "best management practices," 

whose effects on a wide variety of riparian-dependent 

terrestrial wildlife species have never been evaluated. 

The American Dipper is perhaps the most dramatic 

example of a landbird species that is restricted to upland 

riparian (fast-moving stream) conditions, but we obtained too few data on this bird to include in a model. 

Grassland, Sagebrush, or Both 

Examples of species inhabiting these areas are 

Horned Lark, Brewer's Sparrow, Vesper Sparrow, 

Grasshopper Sparrow, and Western Meadowlark. 

If we couple the fact that many species are restricted 

to grassland, sagebrush, or both, with the fact that 

many of the same species are declining nationwide, 

the management of those lands becomes a pressing 

issue. Livestock grazing is a common land-use activity 

on grassland and shrubsteppe environments and 

may be incompatible with the needs of some of these 

bird species (Saab and others 1995). In addition, many 

species in eastern Montana and the Little Missouri 

National Grasslands of North Dakota, (for example, 

Sprague's Pipit [Anthus spragueii], Baird's Sparrow 

[Ammodramus bairdii], and Chestnut-collared Longspur [Calcarius ornatus]) are entirely restricted to 

grassland but were not detected in the data from the 

western portion of the region reported here. Data 

from the Little Missouri National Grasslands will be 

reported elsewhere. 

Conclusions _________ _ 

Many patterns of restricted habitat use were already common knowledge (for example, Grasshopper 

Sparrow is restricted to grasslands, or Brewer's Sparrow is restricted to sagebrush), but other patterns of 

relatively restricted distribution were probably not as 

evident prior to this work (for example, Brown Creeper 

to relatively uncut cedar-hemlock forests). Prior to 

this survey, it was also common knowledge that many 

bird species were widely distributed across cover 

types, but we had no knowledge of the relative abundance of these bird species among cover types, especially harvested forest types. It is now evident that 

Orange-crowned Warbler and Cassin's Vireo, for example, occur not only broadly across forest types, but 

most commonly in harvested forest types, and that 

Williamson's Sapsucker is even relatively restricted to 

such types. 

Although we gathered data for 3 years in the monitoring program, we suspect a well designed program 

could quite easily gather data from well-defined cover 

types within a single-season. The detail and regionspecific nature of this information can be matched by 

no other database in existence, and the information 

should prove useful in modeling probabilities of occurrence in planning areas that are projected to consist of 

alternative proportions of various cover types. 

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 
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USDA Forest Service Gen. Tech. Rep. RMRS-GTR-32. 1999 


ROCKY MOUNTAIN RESEARCH STATION 

I 

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