Authors RICHARD S. HOLTHAUSEN is a wildlife ecologist, U.S. Department of Agriculture, 

Forest Service, 104 Nash Hall, Oregon State University, Corvallis, OR 97331; 

MARTIN G. RAPHAEL is a chief research wildlife biologist, U.S. Department of 

Agriculture, Forest Service, Pacific Northwest Research Station, Forestry Sciences 

Laboratory, 3625 93d Ave., Olympia, WA 98512; KEVIN S. MCKELVEY is a research 

forester, U.S. Department of Agriculture, Forest Service, Pacific Southwest Research 

Station, Redwood Sciences Laboratory, 1700 Bayview Dr., Arcata, CA 95521; ERIC 

D. FORSMAN is a research wildlife biologist, U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station, Forestry Sciences Laboratory, 3200 SW 

Jefferson Way, Corvallis, OR 97331; EDWARD E. STARKEY is a research biologist, 

National Biological Service, Forest and Rangeland Ecosystem Science Center, 

3200 SW Jefferson Way, Corvallis, OR 97331; and D. ERRAN SEAMAN is a 

research biologist, National Biological Service, Forest and Rangeland Ecosystem 

Science Center, Olympic National Park Field Station, 600 E. Park Ave., Port Angeles, 

WA 98362. 

"The Olympic Peninsula From Space," a panoramic view of this region, was produced 

from digital data gathered by Landsat 5 satellite, which orbits Earth at an altitude of 

435 miles. 

This photo is available as a 25- by 36-inch poster from Satellite Images, Inc., P.O. 

Box 1257, Anacortes, WA 98221; phone 360/293-6388; fax 360/293-0441. Paper 

poster is $24.00 and laminated is $32.00 including postage and handling, lower 48 

States only. The image is reproduced courtesy of Satellite Images, Inc./Advanced 

Satellite Productions Inc., 1995. It may not be reproduced without permission. 

Cover Photo 
Abstract Holthausen, Richard S.; Raphael, Martin G.; McKelvey, Kevin S.; Forsman, 

Eric D.; Starkey, Edward E.; Seaman, D. Erran. 1995. The contribution of 

Federal and non-Federal habitat to persistence of the northern spotted owl on 

the Olympic Peninsula, Washington: report of the Reanalysis Team. Gen. Tech. 

Rep. PNW-GTR-352. Portland, OR: U.S. Department of Agriculture, Forest , 

Service, Pacific Northwest Research Station. 68 p. 

We analyzed likely patterns of distribution and persistence of northern spotted owls 

(Strix occidentalis caurina) on the Olympic Peninsula. Analysis focused on the effects 

of Federal habitat under provisions of the Northwest Forest Plan; additional benefits 

to the owl population of different levels of habitat retention on non-Federal lands; 

effects of establishing a habitat connection between the Olympic Peninsula and other 

parts of the owl's range; the likely rate of habitat regrowth in the National Forest and 

its effect on the owl population; and the likely effect of a worst-case fire. We used a 

spatially explicit population model for northern spotted owls for the analysis and also 

reviewed current information on demographics and likely owl population numbers on 

the Olympic Peninsula. We concluded that it is likely, but not assured, that a stable 

population of northern spotted owls would be maintained in portions of the Olympic 

National Forest and the Olympic National Park in the absence of any non-Federal 

contribution of habitat, and that the retention of non-Federal habitat would make a 

biologically significant contribution to the maintenance of the population. Finally, we 

concluded that a habitat connection across southwestern Washington, based on the 

design proposed by the Northern Spotted Owl Recovery Team, would have little 

effect on the status of the owl population on the peninsula if that population was 

stable or nearly stable. 

Keywords: Northern spotted owl, simulation model, spatially explicit population 

model, population dynamics, land management, Olympic Peninsula. 
Summary The analysis in this paper was requested by the U.S. Fish and Wildlife Service to 

provide background for development of a section 4(d) rule under the Endangered 

Species Act (ESA) that might authorize incidental "take" of some northern spotted 

owls from non-Federal forests on the Olympic Peninsula, Washington. The analysis 

describes likely patterns of distribution and persistence of owls on the Olympic 

Peninsula (fig. 1) under the provisions of the Northwest Forest Plan, benefits to the 

owl population of various levels of habitat contribution from non-Federal lands, and 

possible effects of establishing habitat connections between the Olympic Peninsula 

and other parts of the owl's range. Updated information about spotted owl habitat, 

population status, and birth and survival rates for the Olympic Peninsula were summarized, and much of the analysis focused on simulations of spotted owl populations 

under alternative scenarios. The analytical work provided useful insights, and our 

final conclusions, summarized below, represent a synthesis of those insights. 

We concluded that it is likely, but not assured, that a stable population of owls would 

be maintained within portions of the Olympic National Forest and the core area of the 

Olympic National Park in the absence of any non-Federal contribution of habitat. The 

lack of non-Federal habitat would make it unlikely, however, that an owl population 

would be maintained in the western coastal strip of the National Park, and it could 

result in fewer areas of remaining Federal land having high occupancy by owls. Our 

judgment that the maintenance of a stable population was not assured was based 

on significant uncertainty about the interpretation of demographic results; variability 

observed in simulations using different assumptions; and the effect of eliminating up 

to 64 600 hectares (159,700 acres) of suitable habitat on non-Federal lands. There 

also is uncertainty about the increase in the barred owl population and resulting competition and hybridization with spotted owls. Our confidence in the maintenance of a 

stable population on the peninsula would improve if the uncertainties in knowledge 

were resolved and indicated a favorable outcome, or the conditions on the peninsula 

became significantly more robust with respect to these uncertainties. 

We concluded that the retention of non-Federal habitat could result in a biologically 

significant contribution to the maintenance of a stable population of spotted owls distributed across currently occupied portions of the Olympic Peninsula. Our conclusion 

was based, to a large extent, on the results of the model simulations. The simulations 

consistently showed increases in the numbers of pairs of owls maintained over time 

and in the rate of occupancy of owl territories on Federal lands when non-Federal 

habitat was added to Federal habitat. Retention of non-Federal habitat in the western 

special emphasis area, under consideration as an alternative in the 4(d) rule process, 

could be particularly significant as this area contains the greatest concentration of 

habitat remaining on non-Federal land. The retention of this habitat likely would 

increase the chances of maintaining a population in the coastal strip of the Olympic 

National Park. Finally, non-Federal lands may provide the majority of low-elevation 

habitat, which is poorly represented on the Federal lands and might be of higher 

quality than higher elevation habitat. 

Although we concluded that retention of non-Federal habitat would significantly 

improve the projected status of the population, we do not believe that it would fully 

resolve the uncertainties about the future of spotted owls on the Olympic Peninsula. 

Therefore, although the retention of habitat on non-Federal land could be significant, 

we did not conclude that it would alter the basic uncertainties sufficiently to assure 

the maintenance of a population distributed across currently occupied portions of the 

peninsula. 
Our analyses also suggested that a habitat connection across southwestern 

Washington (from the design proposed by the Northern Spotted Owl Recovery 

Team) would have little effect on the demographic status of the owl population 

on the peninsula. It should be noted that the habitat connection described by the 

Northern Spotted Owl Recovery Team was constrained by feasibility and the high 

cost of developing habitat in this heavily harvested landscape. Other more ambitious 

designs likely would have significantly greater effects on the status of the Olympic 

Peninsula population, but their implementation would be increasingly unrealistic. 

The habitat connection would clearly have significant effects on the likelihood of 

maintaining owls in southwestern Washington, but those effects were outside the 

scope of this analysis. Additionally, the analysis does not address the need for or 

utility of dispersal habitat between relatively closely spaced reserves. It was specific 

to the role of corridors connecting reserves separated by large distances. The results 

do not imply that dispersal habitat in intervening areas between more closely spaced 

reserves is unimportant. 

Figure 1-Topographic projection of the Olympic Peninsula, from U.S.G.S. digital elevation model (U.S. Geological Survey 1990). 
These conclusions should not be extrapolated to other portions of the range of the 

northern spotted owl. Each portion of the range represents a different situation and 

different relationship between Federal and non-Federal lands. The Olympic Peninsula 

is unique because of the large block of relatively unfragmented habitat in the Olympic 

National Park, the relative isolation of the Olympic population from owls in the rest 

of the range, and the presence of suitable habitat on non-Federal land adjacent to 

a late-successional reserve on Federal land. Thus, the insights gained from this 

analysis are specific to the peninsula. Also, this assessment has focused only on 

spotted owls and their habitat. It does not address effects on other species for 

which there are legal, social, or biological concerns. 

We recommend that the techniques used in this analysis be applied more broadly 

throughout the owl's range as plans for owls continue to be implemented and refined. 

Although the results are not definitive, they help clarify the relative contributions that 

could be made by Federal and non-Federal lands to maintain spotted owl populations. 

One of the prerequisites for such analyses is the availability of reliable habitat information for both Federal and non-Federal lands. Additional cooperative efforts between 

the states and the Federal government could help generate this information, and participation by private landowners in such efforts would greatly improve the reliability of 

the results. 

This analysis also emphasizes the need to continue monitoring owl populations 

and to continue demographic studies as part of that monitoring. We support current 

efforts to review owl demographic studies and to ensure the continuance or expansion 

of those studies that are critical to our understanding of owl population dynamics 

throughout the range. 
Contents 1 Introduction 

2 Terminology 

 2 General Information 

3 Known Owl Sites 

 7 Population Estimates 

 9 Demographic Studies 

10 Density Studies 

10 Home Range and Habitat Use Studies 

11 Barred Owls 

11 Habitat Dynamics 

14 Federal and Non-Federal Plans for the Olympic Peninsula 

15 Methods 

15 Development of a Habitat Map 

22 Spotted Owl Population Simulation 

28 Land Management Scenarios 

31 Results 

31 Amount and Distribution of Current Habitat 

31 Habitat Projection 

34 Simulated Owl Population Trends 

47 Discussion 

47 Condition of the Population 

50 Projected Future 

56 Conclusions 

59 Recommendations 

60 Acknowledgments 

60 References 

65 Appendix 1: Reanalysis Team Charter 

67 Appendix 2: Additional Model Parameters 
Introduction Conservation of the northern spotted owl (Strix occidentalis caurina) has been a 

focal point in the debate over forest management in the Pacific Northwest for at 

least the last decade (Thomas and others 1990, USDA and USDI 1994, USDI 1992). 

Spotted owls use large home ranges and nest, roost, and forage in predominantly 

older forests. Thus, maintenance of their habitat was not consistent with the rates 

of timber cutting that occurred on Federal and non-Federal lands through at least 

the decades of the 1970s and 1980s. Major milestones in the effort to manage forest 

lands for owls have included the plan developed by the Interagency Scientific Committee (Thomas and others 1990); listing of the owl as threatened (USDI 1990); 

development of a final but unsigned recovery plan (USDI 1992); development of a 

series of options for ecosystem management on Federal forest lands by the Forest 

Ecosystem Management Assessment Team (FEMAT 1993); and adoption of one of 

those options as a strategy for managing late-successional and old-growth forests on 

Federal forest lands in the range of the owl (USDA and USDI 1994). That strategy is 

termed the "Northwest Forest Plan" throughout this paper. 

Adoption of the Northwest Forest Plan put in place a set of land allocations (table 1) 

and management standards and guidelines that were judged adequate for the 

Federal contribution to the recovery of northern spotted owls under the Endangered 

Species Act (ESA) (USDA and others 1994: app. G). Conservation measures for 

Federal forests under this plan are stronger in many areas (USDA and USDI 1994) 

than the recommendations made in the "Final Draft Recovery Plan for the Northern 

Spotted Owl" (USDI 1992). The Northwest Forest Plan does not, however, contain 

any specific recommendations concerning owl habitat in non-Federal forests. The supporting supplemental environmental impact statement (SEIS; USDA and others 1994) 

simply notes that there are areas of concern where non-Federal contributions remain 

important to recovery of owls. For purposes of analysis, the SEIS assumes that owls 

will continue to be protected in those areas of concern, but it defers further consideration of non-Federal lands to a series of potential actions to be pursued by the 

U.S. Fish and Wildlife Service (FWS) in compliance with the ESA. 

One of the actions being considered by the FWS is adoption of a special rule under 

section 4(d) of the ESA that addresses the conservation of northern spotted owls 

while reducing the prohibition against incidental take of owls in the course of timber 

harvest and related activities on non-Federal lands. A notice of intent was published 

on 29 December 1993 that identified a series of special emphasis areas (SEA) where 

the FWS believed that maintenance of non-Federal habitat was necessary. The FWS 

is further evaluating those areas and additional alternatives to develop a proposed 

4(d) rule. 

The analysis in this document was requested by the FWS to provide additional background for development of the 4(d) rule. The charter requesting this analysis is shown 

in appendix 1. Our analysis focuses on northern spotted owls and their habitat on 

the Olympic Peninsula in Washington. The Olympic Peninsula has been consistently 

noted as an area of concern because the owl population on the peninsula probably 

has very little interaction with owls in the remainder of the range (Thomas and others 

1990; USDA 1988, 1992; USDI 1992). The specific purposes of the analysis were to 

assess: 

• Likely patterns of distribution and persistence of owls on the Olympic Peninsula 

under the provisions of the Northwest Forest Plan. 

1 
Terminology

General Information 

2 

Source: USDA and others 1994. 

• Possible effects on the owl population of habitat loss due to large-scale natural 

disturbances. 

• Benefits to the owl population of various levels of habitat contribution from 

non-Federal lands. 

• Possible effects of establishing habitat connections between the Olympic 

Peninsula and other parts of the northern spotted owl's range. 

Information about northern spotted owl habitat, population status, and demographic 

rates on the Olympic Peninsula was updated for this analysis from information used 

in the SETS (USDA and others 1994). Much of the analysis focused on simulations of 

northern spotted owl populations under various habitat scenarios. These simulations 

used a spatially explicit model of spotted owl populations developed by McKelvey 

and others (1992). Our simulations are refined for conditions on the peninsula from 

range-wide simulations done by Raphael and others (1994) for the SEIS. The analytical work provided useful insights into current and possible future trends of the owl 

population, as well as insights into the structure and function of the analytical tools. 

The final conclusions represent a synthesis of those insights. 

Throughout this report, the terms "owl" and "spotted owl" are used as synonyms for 

the northern spotted owl. Also, the term "suitable habitat" is used to mean nesting, 

roosting, and foraging habitat and is distinguished from dispersal habitat. The term 

"spotted owl activity center" indicates an area of concentrated activity of either a pair 

of spotted owls or a single owl. For some portions of the analysis, we subdivided 

the Olympic Peninsula Province into western and eastern subprovinces based on 

topography and major river drainages. 

We report here on field estimates of population size and demographic rates of spotted 

owls on the Olympic Peninsula. Home range characteristics of spotted owls and the 

range expansion of the barred owl (Strix varia) also are discussed. This information, 

in conjunction with the results of population simulation models, provides the background for an informed professional judgment about the security of the owl population 

under different management scenarios. 

Table 1-Land allocations under the 

Federal Forest Plan on the Olympic 

Peninsula 

Land allocation Hectares 

Congressionally reserved 400 364 

Late-successional reserves 167 503 

Adaptive management areas 50 384 

Administrative withdrawals 121 

Riparian reserves 405 

Matrix 405 

 Total 619 183 
Known Owl Sites 

Studies of spotted owls on the Olympic Peninsula began in the early 1980s, when 

calling surveys and home range studies were initiated by the Washington Department 

of Fish and Wildlife (WDFW). Additional studies of home range and habitat use were 

conducted by the USDA Forest Service in 1987-89,1

 by the National Park Service in 

1988-89 (Mills and others 1993), and by North (1993). Beginning in 1987, the USDA 

Forest Service Pacific Northwest Research Station began a long-term demographic 

study of spotted owls on the peninsula. The National Park Service joined in this effort 

in 1989. The primary objectives of the demographic study have been to estimate 

survival rates and reproductive rates and to determine population trends. Survival 

rates have been estimated by using mark-recapture techniques (Burnham and others 

1987). Owls were marked with unique color bands and FWS bands. Each study area 

was searched each year to document previously marked owls, to band any replacements, and to count numbers of young produced by each female. The majority of 

resident adults and their offspring have been banded on National Forest and Washington Department of Natural Resources (WDNR) lands. The sample of banded owls 

also includes about 40 pairs monitored within Olympic National Park. 

We used professional judgment in assessing the numbers and status of known owl 

sites; for example, some sites that had not been occupied by owls for several years 

were dropped from the tally. Our intent was to estimate as accurately as possible the 

number of known sites occupied by spotted owls in 1993 or 1994. We also included 

data from 1994 surveys on National Forest and National Park lands, whereas previous summaries included only 1993 data. For these reasons, there are minor differences between our estimates of known owls and those of previous reviews. 

In the following summary, "pair" refers to any male and female found nesting or 

roosting together or heard calling together in the same area on at least two occasions. Surveys across all ownerships on the peninsula between 1989 and 1994 

confirmed about 155 sites occupied by pairs of owls and 79 sites occupied by single 

owls or multiple owls of undetermined pair status (table 2). Further surveys will likely 

reveal pairs at some of the latter sites; however, some sites where pairs or single 

owls were found early in the survey period appeared to have been abandoned by 

1993-94. 

On National Forest lands, there were 79 confirmed pair sites and 16 confirmed 

sites occupied by one or more owls of undetermined pair status in 1993 and 1994 

(table 2). This count excluded six sites where pairs were observed before 1992 but 

that were not occupied in 1993 or 1994. Some sites where single or multiple owls 

of undetermined pair status were observed could represent pair sites, but recent 

surveys have not confirmed this. 

Surveys on lands administered by the WDNR in 1993-94 documented 11 sites occupied by pairs and 17 sites occupied by single owls or multiple owls of undetermined 

status2

 (table 2). Some of these have been inconsistently occupied in recent years, 

1 E.D. Forsman. Unpublished data. On file with: Pacific 

Northwest Research Station, Forestry Sciences Laboratory, 

3200 SW Jefferson Way, Corvallis, OR 97331.

2 Personal communication. 1994. A. Potter, Washington 

Department of Fish and Wildlife, 600 N. Capitol Way, 

Olympia, WA 98501. 

3 
― = survey data not available. a Sites where 1 to 2 owls were located but pair status could not be confirmed. 

b Low estimate assumes that sites where pairs were not documented were not occupied by pairs. High estimate 

assumes that all sites where 1 or more owls were located were occupied by pairs of owls. c WDNR = Washington Department of Natural Resources. 

d Olympic N.P. = Olympic National Park. 

e Population estimate for Park lands was based on extrapolation from random survey plots within Olympic National 

Park (described in the text). 

which suggests that they may be relatively marginal habitat.3 Most owls located 

on WDNR lands were clustered in the northwest corner of the peninsula, which 

reflects the distribution of habitat on lands administered by the WDNR. 

Surveys in Olympic National Park confirmed 63 sites occupied by pairs of owls and 

44 sites occupied either by a single owl or by two owls with unknown pair status 

(table 2). Because of difficult access, survey efforts in the Park have been limited 

compared to efforts on adjacent National Forest and WDNR lands. 

We know of only two sites occupied by owls on tribal lands and two sites occupied 

by owls on private lands in 1992-94 (table 2). The low number of owls on these 

ownerships may reflect low population numbers, but survey efforts on these ownerships have been limited. Although numbers of known owls with activity centers on 

private lands are low, many activity centers on National Forest and National Park 

lands were adjacent to private lands. Owls in those situations may use private lands 

for foraging. 

3 Personal communication. 1994. S. Horton, Washington 

Department of Natural Resources, 1111 Washington St. SE, 

Olympia, WA 98504. 

Table 2-Numbers of known spotted owl sites and estimates of total 

numbers of spotted owl sites on the Olympic Peninsula, by agency or 

landowner, based on surveys conducted from 1989 to 1994 

Landowners 

Known owl sites Estimate of 

 ownership 

Pairs Othera

 surveyed 

Estimated number 

of sites with 

territorial pairsb

Low High 

Percent 

USDA Forest Service: 

 Soleduck District 18 5 85 21 27 

 Quinault District 20 7 90 22 30 

 Quilcene District 25 2 75 33 36 

 Hood Canal District 16 2 75 21 24 

WDNRc

 11 17 90 12 31 

Olympic N.P.d

 63 44 NA 173 173e

Private lands 1 1 NA - - 

Tribal lands _1 _1 NA - - 

 Totals 155 79 282 321 
Figure 2-Sites where pairs and territorial (single) spotted owls were located 

(n = 191) on the Olympic Peninsula between 1989 and 1993. Map based on 

data maintained by WDFW. 

The distribution of known owl locations indicates that the range of the owl includes 

the entire peninsula (fig. 2), but most known owls are concentrated on Federal lands 

or lands administered by the WDNR. To some extent the uneven distribution of owls 

may represent survey and reporting effort. It seems, however, that the primary reason 

for the unequal distribution of owls is that almost all late-successional forests on 

private lands and tribal lands were clearcut between 1940 and 1990. 

5 
a

 Based on data maintained by the Washington Department of Fish and Wildlife, 

600 N. Capitol Way, Olympia, WA 98501. 

b Elevations of activity centers were based on intersecting their locations 

(fig. 2) with a digital elevation model. 

c

 Forsman, E.D.; Seaman, D.E. Unpublished data. On file with: Pacific 

Northwest Research Station, Forestry Sciences Laboratory, 3200 SW Jefferson 

Way, Corvallis, OR 97331. 

d Nest elevations are from 281 nest records. Values are the number of 

owls, or nest records, located in each elevation band. 

The elevations of owl nest sites and activity centers indicated that owl distribution 

is limited by elevation and that the upper limit is higher in the eastern than in the 

western subprovince. Elevations of nests in the eastern subprovince ranged from 

114 to 1189 meters (375 to 3,900 feet), with 90 percent of 154 nest records at 

elevations below 1006 meters (3,300 feet) and 95 percent below 1067 meters 

(3,500 feet) (table 3). Elevations of nest sites in the western subprovince ranged 

from 85 to 732 meters (280 to 2,400 feet), with 90 percent of 127 nest records 

at elevations below 622 meters (2,040 feet) and 95 percent below 652 meters 

(2,140 feet) (table 3). 

The differences in upper elevational limits and elevational distribution of nest sites 

between the eastern and western subprovinces were probably a function of habitat 

differences (Henderson and others 1989:38-43). In the western subprovince, forests 

below about 550 meters (1,800 feet) are typically dominated by western hemlock 

(Tsuga heterophylla (Raf.) Sarg.), western redcedar (Thuja plicata Donn ex D. Don), 

and Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco). At elevations above about 

550 meters, forests are increasingly dominated by Pacific silver fir (Abies amabilis 

Dougl. ex Forbes). In comparison, the transition to Pacific silver fir forests in the 

eastern subprovince occurs at much higher elevations, typically between 850 and 

0-152 17 0 11 3 

153-305 27 6 28 5 

306-457 22 14 37 18 

458-610 19 23 34 36 

611-762 10 16 17 30 

766-914 4 13 0 36 

915-1067 5 10 0 19 

1068-1219 0 7 0 7 

1220-1372 0 1 0 0 

1373-1524 0 0 0 0 

>1524 0 1 0 0 

Table 3-Elevation of northern spotted owl activity 

centers (n = 195) and nest sites on the Olympic 

Peninsula 

Elevation band West East West East 

Meters -------- Number -------- 

Activity centers 

 by subprovincea b Nest locations by 

 subprovincec d
Population Estimates 

1030 meters (2,800 to 3,400 feet). The relative infrequency of nesting in highelevation forests on the peninsula indicates that those forests are marginal or 

unsuitable habitat for spotted owls. It is reasonable to assume, however, that owls 

nesting in the transition zone between western hemlock/Douglas-fir forests and true 

fir forests do forage and roost in true fir stands if those stands occur within 2 to 3 

kilometers (1 to 2 miles) of the nest (Mills and others 1993). For that reason, any 

assessment of the amount of habitat available to spotted owls on the peninsula 

should assume some contribution from true fir stands located above the elevations 

at which nests occur. Our analysis of potential habitat on the peninsula made such 

an assumption (see "Development of a Habitat Map"). 

Numbers of territorial pairs on the peninsula were estimated with two different 

approaches. On lands administered by the Forest Service and WDNR, where 

surveys covered much of the land base and usually were repeated in multiple 

years, we estimated the proportion of the area that was surveyed in two or more 

years and extrapolated from the number of confirmed owl sites to the entire ownership. This was done by dividing the number of known owl sites by the estimated 

proportion of the area that was surveyed. Two estimates were made for each 

National Forest Ranger District and for lands administered by the WDNR. One 

estimate assumed that pairs were present at all sites where either pairs or single 

owls were documented. The other estimate was more conservative; we assumed 

that pairs were present only at confirmed pair sites. Estimates of owl numbers on 

National Forest lands were subdivided by Ranger District because estimates of 

the survey coverage differed with District. The combined population estimate for all 

National Forest lands was either 97 or 117 pairs, depending on which assumption 

was made about occupancy of sites where single owls were located (table 2). 

Comparable population estimates for lands administered by the WDNR were 12 or 

31 pairs (table 2). 

On National Park lands, the population was estimated by extrapolating densities 

from randomly selected sample areas to the entire Park (Seaman and others 1992). 

Population estimates from private lands and tribal lands were not possible because 

detailed survey data were not available for those areas. 

The Olympic National Park surrey has been conducted over three years, with an 

additional year scheduled for 1995. We report preliminary results here. Because the 

area of potential owl habitat was too large and remote to be surveyed completely, 

26 census plots in three survey strata were chosen randomly and surveyed. The 

density of owls in the census plots was extrapolated to the total area of potential 

owl habitat in the Park to produce a population estimate. 

For the census, potential owl habitat was defined as all forested habitat in the Park, 

excluding the Pacific coastal strip and the Queets River corridor. This definition 

allowed sampling of higher elevation forests to determine the upper limit of owl 

distribution but did not include alpine habitats (rock, ice, meadows) or large lakes. 

The coastal strip and Queets corridor were excluded because they are very different 

landscapes than those in the core of the Park, with narrow segments of habitat 

bounded by extensive clearcuts. 

7 
8 

The Park was divided into three survey strata: two low-elevation strata separated 

along a line running northwest to southeast, and a high-elevation stratum that included all potential habitat above 910 meters (3,000 feet) elevation in the western 

subprovince and above 1219 meters (4,000 feet) elevation in the eastern subprovince. 

Each random plot was sampled in only one year. Plots averaged about 800 hectares 

(1,977 acres) in area, and the total area of the 22 sampled plots represented roughly 

10 percent of the forested land in the Park, excluding the coastal strip and Queets 

corridor. Calling stations were placed every 400 meters (1,312 feet) along transects 

spaced 400 meters apart to cover the entire plot. When spotted owls were detected, 

they were captured if possible and individually banded. 

Each census plot was surveyed during the nesting season (15 March to 15 June). 

Closed population mark-recapture statistics (Otis and others 1978) were used to 

estimate the proportion of owls missed by this survey scheme, and the observed 

densities were adjusted accordingly. 

Owl pairs were considered residents of a plot and were counted in its density estimate only if their nest or habitual roost sites were within the plot (defined as all area 

within 200 meters [656 feet] of a calling station). We used nest or habitual roost sites 

so that density would not be overestimated by including nonresident owls that entered 

the plot. 

Of 43 sites where one or more owls were located within survey plots, 22 did not 

meet the criteria for pair status and, therefore, were excluded from the pair density 

estimate. Of the 21 sites with confirmed pairs, one was excluded from the pair density 

estimate because the nest was outside the plot; 20 sites were included in the pair 

density estimate of which five had nest locations in a plot, five had young juveniles in 

a plot (before 9 June in all cases), and 10 had no nest or juveniles found, but survey 

evidence (habitual roosts) indicated that they were plot residents. 

Analysis of the density data for Olympic National Park has not been completed. 

Preliminary calculations estimate a population of 173 pairs in the Park study area; 

confidence limits have not yet been developed for this estimate. Because the estimate 

is an extrapolation from a small sample, variance in the surrey plot densities may 

translate into considerable uncertainty in the Park-wide estimate, and the resulting 

confidence limits may be quite wide. Again, the study area includes only the forested 

interior of the Park, not the coastal strip and the Queets corridor, which both contain 

small numbers of territorial spotted owls. 

In summary, surveys in 1992-94 confirmed a minimum of 155 pairs, and extrapolations from the survey data suggest a total population of either 282 or 321 pairs of 

spotted owls on the peninsula, depending on assumptions about the status of sites 

occupied by single owls (table 2). These numbers represent two separate point estimates using different assumptions; they do not indicate anything about the variability 

of the population estimate. These estimates assume few pairs with activity centers on 

private lands or tribal lands, simply because there are no data to indicate otherwise. 
Demographic Studies In December 1993, data from the Olympic demographic study were analyzed at a 

workshop in Fort Collins, Colorado, and presented in a report to the Secretary of the 

Interior (Burnham and others 1994). This report subsequently was included as an 

appendix to the SEIS (USDA and others 1994) produced for the Northwest Forest 

Plan. The analysis for the Olympic Peninsula population indicated no significant 

changes over time in birth or death rates but suggested that the population of 

territorial owls was declining at about 5.3 percent per year during the period of study. 

A range-wide meta-analysis that examined 12 study areas, including the Olympic 

Peninsula, suggested an overall decline in adult female survival rates over the years 

of study. An overall estimate of population growth based on the survival estimates 

from the meta-analysis and fecundity estimates from 11 study areas indicated an 

average annual rate of population decline of 4.5 percent (Burnham and others 1994). 

The analysis also indicated that the rate of population decline was accelerating 

(Burnham and others 1994). Burnham and others (1994) state that their analysis 

applied only to the territorial population. 

The results of the Fort Collins workshop generated considerable disagreement 

within the scientific community over interpretation of the data (see for example, 

Bart, in press b; Lande and others 1994; USDA and others 1994). One of the 

primary concerns regarding banding studies of spotted owls is that emigration of 

juvenile owls might cause an underestimation of juvenile survival rates, which in 

turn could result in an underestimate of the population growth rate (Bart, in press b; 

Burnham and others 1994). In their combined analysis of 12 study areas, Burnham 

and others (1994) attempted to compensate for this potential bias by adjusting the 

average juvenile survival estimate upward based on estimates of juvenile emigration 

from two radio-telemetry studies (Forsman and others, in prep.). This increased the 

estimate of the population rate of change (lambda, indicated by λ) from 0.9253 to 

0.9548, but did not alter the conclusion of a significant population decline. Bart (in 

press b) concluded that the population growth rates reported by Burnham and 

others (1994) were underestimates because they considered only one source of 

bias (juvenile emigration out of the study area) and did not take into account a 

number of other potential biases, such as adult emigration and juvenile emigration 

into unmonitored portions of study areas. 

Forsman and others (in prep.) used emigration data from a radio-telemetry study in 

Washington to adjust the juvenile survival estimate presented in Burnham and others 

(1994) for the Olympic Peninsula. The juvenile survival estimate from the banding 

study reported in Burnham and others (1994) was 0.245 with a standard error of 

0.064. The estimated emigration rate from the radio-telemetry study was 0.600 with 

a standard error of 0.083, where emigration was defined as any instance when an 

owl dispersed into an area not regularly searched for owls, survived at least to age 1, 

and went undetected by conventional calling techniques. After adjustment for emigration, the estimate of juvenile survival was 0.612 with a standard error of 0.204. 

When this value was substituted in the population growth rate equation, the resulting 

estimate of population rate of change (λ) for the peninsula was 1.058 with a standard error of 0.065, which was not significantly different from 1.0. Although this result 

appears to contradict the conclusion of a declining population from the earlier analysis, Forsman and others (in prep.) urged caution in this interpretation for several 

reasons: only 35 owls were used to estimate emigration rates, emigration estimates 

were based on only two years of data, and rates of immigration were unknown. All 

these factors could affect the outcome of the analysis. 

 9 
Density Studies 

Home Range and 

Habitat Use Studies 

10 

It also could be argued that the above analysis underestimates the effect of emigration on the estimated survival rate because the analysis did not consider "internal" 

emigration. Internal emigration refers to owls that stay within the boundaries of the 

study area, but settle in areas not regularly surveyed. Such owls would appear to 

have died when they actually survived, thereby causing survival to be underestimated 

The analysis performed by Forsman and others (in prep.) compensated for internal 

emigration to some extent. In that analysis, radio-marked juveniles dispersing into 

unsurveyed portions of the Olympic National Park were labeled as emigrants, even 

though the general study area included the entire Park plus surrounding National 

Forest and WDNR lands. Thus, much of the internal emigration was accounted for, 

and the estimation of juvenile survival rates should not be greatly underestimated. 

Field studies of changes in the number of territorial owls on the peninsula have been 

used to evaluate population trends (Forsman and others, in prep.) (fig. 3). The results 

have been inconclusive, primarily because changes in the number of territorial owls 

may not reflect the trend in the total population, which also includes floaters (owls 

without territories), and regression analyses of trends based on small samples cannot 

detect small annual changes in population size (Taylor and Gerrodette 1993). 

Data on home range areas and habitat use of spotted owls on the Olympic Peninsula are available from two as-yet unpublished studies, one conducted by the WDFW 

from 1984 to 1986,4

 and another conducted by the Forest Service from 1987 to 1989 

(Forsman and others, in prep.). These studies indicate that annual home range areas 

(estimated by the minimum convex polygon [MCP] method) on the Olympic Peninsula 

are relatively large and typically encompass large amounts of late-successional forest. 

Annual home ranges of 10 pairs indicated a median home range of 5775 hectares 

(14,271 acres; range = 1820 to 11 052 hectares, or 4,497 to 27,309 acres). The 

median amount of old-growth and mature forest in the annual ranges of seven pairs 

4

 D.W. Hays. Unpublished data. On file with: Washington 

Department of Fish and Wildlife, 600 N. Capitol Way, Olympia, 

WA 98501. 

Figure 3-Number of territorial spotted owls located each 

year on the 355-square-kilometer (137-square-mile) Quinault 

density study area on the Olympic Peninsula, 1988-94. 
Barred Owls

was 1853 hectares (4,579 acres) (range = 1128 to 3419 hectares, or 2,787 to 8,448 

acres). Based on habitat classifications used in our analysis, home range size tended 

to decrease with increasing proportion of late-successional forest in the home range 

(r = -0.73, P = 0.10). Although other home range estimation techniques produce 

differing estimates of home range size, the estimated amount of late-successional 

forest used by owls will be unaffected by the estimator if all the late-successional 

forest within the MCP home range is used. 

Barred owls have invaded much of the range of the northern spotted owl during 

the last 50 years (Dunbar and others 1991, Thomas and others 1993). Numbers of 

barred owl sightings on the Olympic Peninsula have increased steadily since spotted 

owl surveys began on the peninsula. Most records of barred owls have been from 

the western subprovince in western hemlock and spruce forests. 5

 Because barred 

owls have displaced spotted owls and hybridized with spotted owls, the range 

expansion of the barred owl may represent a threat to the spotted owl population 

(see for example, Hamer and others 1994, Thomas and others 1993). 

There have been two records of barred owl-spotted owl hybrids on the peninsula. 

One of these was banded as a juvenile in the Gifford Pinchot National Forest in 

1984 and subsequently dispersed 190 kilometers (118 miles) to the northwest 

corner of the peninsula (Hamer and others 1994). The other was first documented 

as a breeding adult along the Bogachiel River in 1994.6

We anticipate that the numbers of barred owls will continue to increase on the 

peninsula, but there is no way to predict with certainty how the barred owl range 

expansion will affect the long-term persistence of the spotted owl (Thomas and 

others 1993). It is unclear whether the range expansion of the barred owl is due 

to human influences on habitat. 

Spotted owls have evolved with natural disturbance as an important process within 

their habitat; however, humans have altered disturbance regimes and reduced the 

availability of suitable habitat in most areas (USDI 1992). The potential exists for 

natural disturbance to further reduce the amount of suitable spotted owl habitat on 

the Olympic Peninsula and elsewhere. 

Fire and wind are the most significant sources of natural disturbance in peninsula 

forests. Insects are usually secondary agents of disturbance, but no devastating 

outbreaks have been documented (Henderson and others 1989). Forest diseases 

are a greater source of disturbance than insects but do not generally cause substantial negative impacts on spotted owl habitat (Agee and Edmonds 1992). 

Wind is the most important source of disturbance along the coast but is less 

important in interior areas (fig. 4). Near the coast, return intervals for major wind 

disturbances are about 30 years, with fire return intervals exceeding 1,100 years 

(Agee 1993). In interior portions of the peninsula, fire is relatively more significant 

than wind but still relatively infrequent, with fire return intervals of 400 to 750 years 

(Agee 1993, Henderson and others 1989). 

5

 E.D. Forsman and D.E. Seaman. Unpublished data. On file 

with: Pacific Northwest Research Station, Forestry Sciences 

Laboratory, 3200 SW Jefferson Way, Corvallis, OR 97331. 

6 D.E. Seaman. Unpublished data. On file with: National 

Biological Service, Olympic National Park Field Station, 

600 E. Park Ave., Port Angeles, WA 98362. 

11 

Habitat Dynamics
12 

Figure 4-Relative frequency of fire and wind disturbance events on 

the Olympic Peninsula (from Agee and Edmonds 1992, Henderson 

and others 1989). 

Fire may be more frequent in some areas as a result of local wind patterns or topography. For example, east winds are funneled through a valley near Lake Crescent, 

in the northwest portion of the peninsula, resulting in an increased likelihood of highseverity fires (Agee 1993) during the next 100 to 200 years7

 (fig. 5). In 1951, the 

Forks fire burned more than 13 360 hectares (33,000 acres) in this area. Fires 

burning when east wind conditions occur in this area are likely to be difficult to 

control (Agee 1991a).

The Olympic Mountains cast a rain shadow to the east and northeast, where the 

climate is drier and fire is more frequent (Agee and Edmonds 1992, Henderson and 

others 1989). Much of the area has burned several times during the last 700 years. 

Fire is an important element of these ecosystems, and stand-replacing fires are likely 

during the next 100 to 200 years, especially along the northeastern boundary of 

Olympic National Park (Ages 1991a) (fig. 5). Because of the steep and deeply

dissected terrain, fire control efforts are likely to be severely constrained (Agee 

1991a). In this portion of the peninsula, there is a high likelihood that significant 

areas of suitable spotted owl habitat will burn in the future. 

Wind and fire affect spotted owl habitat differently. Wind tends to thin stands by 

toppling codominant and intermediate crown class trees, leaving some windfirm 

dominants. Understory trees become the dominants in the succeeding stand. In 

some cases, such as the blowdown associated with a severe storm on the peninsula in 1921, spotted owls may reoccupy disturbed areas in less than 70 years 

(North 1993). Although wind may cause short-term habitat loss, in the long term it 

7

 Personal communication. 1994. J.K. Agee, College of Forest 

Resources, University of Washington, Seattle, WA 98195. 
Figure 5-Areas with relatively high likelihood of fire on the Olympic Peninsula. 

Estimated fire return intervals are also shown (see footnote 7). Simulated worst 

case analyses included all areas with return intervals less than or equal to 

300 years. The solid line bisecting the peninsula from northwest to southeast in 

this and subsequent figures is a subprovincial boundary following topographic 

relief that splits the peninsula into east and west subprovinces. 

may also contribute to the development of key attributes of spotted owl habitat, such 

as a multilayered canopy. Mills and others (1993) found that vertical canopy layering 

was an important predictor of owl presence on the Olympic Peninsula. 

13 
Federal and Non-Federal 

Plans for the Olympic 

Peninsula 

14 

Fires on the Olympic Peninsula are generally stand-replacing events (Agee 1991 a), 

resulting in the loss of suitable spotted owl habitat for a significant period. Following 

fire on the peninsula, new seedlings may continue to establish for as long as 60 years 

(Huff 1984). This extended regeneration period may be responsible for some of the 

structural diversity associated with suitable spotted owl habitat (for example, diverse 

age and size distribution of trees, multilayered canopies). In the long term, fire has 

probably been beneficial for spotted owls. But until additional suitable habitat has 

been regrown, short-term loss of habitat to fire could increase the risk of extirpation 

within some areas of the peninsula. 

An intensive fire suppression strategy is likely to be successful in restricting most 

fires in the western and interior Olympic Peninsula to a relatively small size (Agee 

1991a). From 1950 to 1980, the average size of larger fires on the peninsula was 

less than 364 hectares (900 acres), and it is unlikely that most fires in the foreseeable future will exceed this average size (Agee 1991a). In especially vulnerable 

areas in the northeastern portion of the peninsula and near Lake Crescent (areas 

with 100-year fire return intervals; see fig. 5), there is a risk of relatively large fires 

resulting in broad gaps in suitable habitat (Agee 1991a). Under worst case conditions 

(dry easterly winds, extended summer drought), these fires could include most of the 

Elwha Valley and much of the eastern portion of the peninsula (fig. 5) and not be 

extinguished until the arrival of seasonal precipitation (Agee 1991b).

Under the Northwest Forest Plan, a large percentage of the Federal lands on the 

Olympic Peninsula is either in congressionally reserved status or allocated as 

late-successional reserves (table 1). Nearly all the suitable nesting, roosting, and 

foraging habitat for spotted owls is in allocations where it likely will be maintained 

over time. Only 3400 hectares (8,400 acres) of nesting, roosting, and foraging habitat are in either an adaptive management area or matrix and are potentially available for scheduled timber harvest. Plans at the Olympic National Forest do not call 

for clearcutting any of this habitat in the foreseeable future 8

. In late-successional 

reserves, efforts may be undertaken to accelerate the development of characteristics 

associated with nesting, roosting, and foraging habitat in currently young forest. 

Firm schedules for such treatments have not been developed. 

The WDNR administers about 164 000 hectares (405,250 acres) of state lands 

on the Olympic Peninsula (table 4). It has voluntarily followed the FWS guidance for 

determining when the risk of take may occur on lands that it administers. That 

guidance included (1) retaining 28 hectares (70 acres) of suitable habitat around 

a spotted owl activity center; (2) retaining about 200 hectares (500 acres) of suitable spotted owl habitat within 1.1 kilometers (0.7 mile) of an activity center; and 

(3) retaining suitable habitat on 40 percent of the landscape within a circle around 

an activity center 4.3 kilometers (2.7 miles) in radius. This guidance was used in 

our analysis to represent the situation that would exist on non-Federal lands if take 

prohibitions remain in effect. 

8 Personal communicaton. 1994. W. Hoffman, Olympic National 

Forest, 1835 Black Lake Blvd. SW, Olympia, WA 98512. 
Methods 

Development of a 

Habitat Map 

a

 All values rounded to nearest 100 hectares prior to summing. 

Source: Habitat derived from FEMAT (1993) and unpublished data on file with: Washington Department 

of Natural Resources, 111 Washington St. SE, Olympia, WA 98504. 

Evaluation of relationships between spotted owls and habitat on the Olympic Peninsula requires an accurate map of current habitat conditions and prediction of future 

conditions, including both forest growth and disturbance. In addition, rules must be 

developed relating habitat conditions to owl behavior and demographic performance. 

Such an evaluation is greatly assisted by standardized, repeatable, and biologically 

reasonable methods to compare potential future scenarios in terms of spotted owl 

population dynamics. 

We created maps of suitable owl habitat given various non-Federal contributions to 

total habitat on the peninsula (scenarios), ran computer models to simulate population trends and population distributions under each scenario, and investigated the 

sensitivity of our simulations to alternative assumptions about demographic rates. 

Effects of change in habitat condition due to fire and regrowth of habitat were also 

investigated through simulations. 

Current conditionsFederal lands-A digital map of suitable spotted owl habitat on National Forest lands 

throughout the range of the owl was first developed as part of the 1992 final EIS 

(USDA 1992). The Northern Spotted Owl Recovery Team expanded this map to 

include lands managed by the U.S. Bureau of Land Management (BLM) and National 

Park Service. This map of spotted owl habitat on Federal lands was enhanced and 

resampled on a 16-hectare (40-acre) grid during the FEMAT process (FEMAT 1993) 

and subsequent SEIS (USDA and others 1994); we used this enhanced map as the 

best information about currently suitable owl habitat on Federal lands on the Olympic 

Peninsula for our original report to the FWS (Holthausen and others 1994). 

Table 4-Amount of nesting, roosting, and foraging (NRF) habitat for 

northern spotted owls in relation to total land area and land ownership, 

Olympic Peninsula 

Landowner Land area classified 

Total area Total NRF habitat as NRF habitat 

- - - - - Hectares a

 - - - - - Percent 

National Forest 254 300 97 600 38 

National Park 364 800 168 300 46 

Other Federal 700 100 11 

 Total Federal 619 800 266 000 43 

Tribal 95 600 6 800 7 

State 164 000 33 500 20 

Other non-Federal 347 200 24 400 7 

 Total non-Federal 606 800 64 600 11 

Total, all lands 1 226 600 330 600 27 
Figure 6-Map of the Olympic Peninsula showing ownership patterns and 

4.3-kilometer (2.7-mile) radius buffers surrounding owl activity centers. 

16

As noted by Holthausen and others (1994), this map seemed to underestimate the 

amount of nesting, roosting, and foraging habitat on National Park lands, especially 

in the eastern subprovince. For this analysis, we obtained a 1988 Landsat classifycation with 1991 updates (Green and others 1993) and used the "late-seral" class to 

represent the nesting, roosting, and foraging habitat in the National Park. We evaluated the new map by examining the distribution of habitat in relation to its overlap 

with the distribution of spotted owl activity centers, and we concluded that the new 

map produced a better fit than did the original map. 
We further refined the habitat definition for Federal lands by applying an upper elevation limit to exclude areas above the elevations where spotted owls are known to 

successfully reproduce. To determine this upper limit, we first subdivided the Olympic 

Peninsula Province into western and eastern subprovinces based on topography and 

major river drainage patterns (figs. 1 and 6). The dividing line runs diagonally from 

the northwestern tip of the peninsula to the southeast. For each subprovince, we 

tallied locations of each spotted owl activity center (n = 195, 1992 data) in relation 

to 152-meter (500-foot) elevation bands (table 3). We then determined the amount 

of total mapped habitat that fell within the elevation limits of the 90th, 95th, and 

100th percentiles of the distribution of these owls (after dropping two outliers from 

the eastern subprovince). After examining these maps and data about the distribution 

of known nest sites of spotted owls on the peninsula in relation to elevation (table 3), 

we concluded that upper elevation limits of 914 meters (3,000 feet) in the western 

subprovince and 1219 meters (4,000 feet) in the eastern subprovince were reasonable. We used a U.S. Geological Survey 1:250,000-scale digital elevation model 

(DEM; U.S. Geological Survey 1990) coded into 152-meter (500-foot) elevation 

zones to identify and screen out any potential habitat that occurred above the 

upper elevation limits in each subprovince. 

Non-Federal lands-No widely reviewed maps of habitat were available for the nonFederal lands on the peninsula; however, we evaluated two draft maps identifying 

suitable habitat on these lands. The first, "WDNR mosaic," is a product of the WDNR 

(map version of 31 October 1994) and is being developed in support of that department's proposed habitat conservation plan (HCP). The second, "FWS mosaic," is a 

product of the FWS's 4(d) rule team. Our evaluation of these two maps was based 

on a visual review of the maps, tallies of the total amount and distribution of habitat 

throughout the peninsula, tallies of the distribution of habitat within circles 4.3 kilometers (2.7 miles) in radius centered on owl activity centers, and review by WDFW 

biologists who are familiar with the area. We concluded that the "WDNR mosaic" was 

the best choice for our analysis. First, its derivation was easily understood, having 

been assembled from ground-verified data whenever possible. In contrast, attributes 

on the "FWS mosaic" map were derived attributes; that is, they were themselves 

derived from other attributes. For example, much of the map begins with a latesuccessional stage classification. From a given late-successional stage, an average 

diameter at breast height (d.b.h.) was assumed, and from that d.b.h. an age was 

assumed. Thus, the final attributes were somewhat removed from the source data, 

with the potential to propagate errors. Second, the "WDNR mosaic" was based on 

a well-documented series of rules for inclusion of data. It was clear to us how and 

where each data source was used. Third, the WDFW biologists stated that the 

"WDNR mosaic" provided the best overall fit with what is known about the 

on-the-ground distribution of owl habitat on the peninsula. 

The "WDNR mosaic" (fig. 7, table 4) is an assemblage of the best available information from a variety of different sources, including the FEMAT (1993) habitat 

classification for National Forest lands and data from the WDFW for some lands 

administered by the WDNR. For remaining State lands, the WDNR used inventoried 

stands (land use and land cover database) that met habitat definitions proffered by 

the Washington Spotted Owl Science Advisory Group. For all other lands, the WDNR 

used a satellite-derived forest cover classification (Green and others 1993) and 

17 
Figure 7-Current habitat on the Olympic Peninsula based on the "WDNR mosaic" and FEMAT 

databases. Buffers around owl activity centers and the boundary between Federal and 

non-Federal lands also are shown. A: Base Federal and non-Federal habitat layers; B: the 

derived 1500-hectare (3,707-acre) hexagonal cells used in simulation runs. 

selected as habitat either the late-sera] (generally stands with more than 10 percent 

cover by trees greater than 53 centimeters [21 inches] d.b.h.) or a combination of 

the late-seral and mid-seral (less than 10 percent cover by 53-centimeter trees) 

categories, whichever had the best fit to classified owl habitat within a particular 

planning unit. The late-seral category is the same as the category selected to 

represent habitat in the National Park, as discussed above. 

18 
Map processing-Our habitat maps were binary maps depicting presence or 

absence of nesting, roosting, and foraging habitat for northern spotted owls. They 

were originally digitized in a vector (line) format but were generalized into a raster 

(grid) format for our analysis. The minimum resolution (cell size) of the gridded maps 

was about 16 hectares (40 acres). This data resolution is equal to the spatial unified 

database used in the FEMAT (1993) effort. A comparison of the original line maps 

to their gridded equivalents showed an overall difference of less than 0.3 percent in 

amount of habitat (Raphael and others 1994). Each cell on the resulting grid map 

was coded as suitable habitat if at least half of the underlying map was suitable 

habitat, and as unsuitable habitat otherwise. All map operations were conducted 

by using the ARC/INFO geographic information system (GIS).9

Projecting habitat through time-Portraying habitat change over time requires 

(1) a base map displaying stand ages or relative stages of structural development 

for areas not currently suitable as owl habitat but that may become owl habitat, 

(2) a model of how those stands change over time, and (3) a determination of the 

characteristics required for a stand to function as nesting, roosting, and foraging 

habitat. 

Base map-The base map was the successional-stage map of Federal lands 

developed for FEMAT (1993). This map was derived from Landsat classification. 

The Landsat imagery and classification covered both National Forest and National 

Park lands on the west side of the Cascade Range crest in Washington and Oregon. 

Date of the imagery was 1988. The map created for FEMAT grouped 34 classified 

vegetation types into 13 vegetation types (table 5) and six structural stages (table 6). 

Change in vegetation over time-A preliminary successional model was created for 

successional vegetation stages as part of the FEMAT analysis (1993:IV.54-IV.55). 

For coastal areas, including the Oregon Coast Ranges and the Olympic Peninsula, 

ages and duration associated with each of the conifer stages were estimated by 

FEMAT (1993). For the current analysis, we refined this model based on consultation 

with forest ecologists familiar with the peninsula. Separate ages were assigned to the 

stages for the eastern and western subprovinces of the Olympic Peninsula based on 

differences in average site indices for those areas (table 7). Average 50-year site 

indices of 115 and 100 were used to estimate rates of succession for the western 

and eastern subprovinces, respectively. 

Characteristics of spotted owl habitat-It is likely that all four larger successional 

stages (table 8) contain some stands that have characteristics making them suitable 

spotted owl habitat. To determine which stages best represented owl habitat, we 

overlaid the map of structural stages on the map of current spotted owl habitat in 

the Olympic National Forest and tallied the hectares classified as suitable or not by 

each successional stage (table 8). Based on this simple comparison, the three 

oldest stages (medium multistory conifer and large single-story and multistory 

conifer) contain the largest ratio of suitable habitat to unsuitable habitat and thus 

seemed to best represent owl habitat. 

9 ARC/INFO is a product of Environmental Systems Research 

Institute, Redlands, CA. The use of trade or firm names in 

this publication is for reader information and does not imply 

endorsement by the U.S. Department of Agriculture of any 

product or service. 

19 
a Multiply inches by 2.54 to find centimeters. 

Source: Teply, J. Unpublished data. On file with: 

Pacific Northwest Region, USDA Forest Service, P.O. 

Box 3623, Portland, OR 97208. 

Application of the model to the Olympic Peninsula-Growth of habitat was 

modeled only for Olympic National Forest lands. The Olympic National Park, which 

has been essentially undisturbed by logging, was assumed to be in a state of 

dynamic equilibrium, where development of young stands is balanced by natural 

disturbance of older stands. Non-Federal lands were represented in a series of 

scenarios in the analysis, none of which assumed that additional nesting, roosting, 

and foraging habitat would be allowed to grow on those lands. The late-successional 

reserves in the National Forests, which have been harvested in the past, are the 

lands where regrowth of habitat is likely to occur through time. 

20 

Table 5-Vegetation types classified in the 

available seral-stage base map 

Conifer Hardwood 

Grass/shrub Grass/shrub 

Seed sap pole Small hardwood 

Low-density conifer Medium hardwood 

Small conifer Large hardwood 

Medium single-story conifer 

Large single-story conifer 

Medium multistory conifer 

Large multistory conifer 

Naturally sparse 

Source: Teply, J. Unpublished data. On file with: Pacific 

Northwest Region, USDA Forest Service, P.O. Box 3623, 

Portland, OR 97208. 

Table 6-Structural classifications 

from the available seral-stage base 

map 

Structural class D.b.h. 

Inchesa

Seedling <0.9 

Sapling 1.0 - 4.9 

Pole 5.0 - 8.9 

Small 9.0 - 20.9 

Medium 21.0 - 31.9 

Large >31.9 
Table 7-Duration of each structure stage used to 

project vegetation through time in the western and 

eastern subprovinces of the Olympic Peninsula 

Subprovince 

Structural stage West East 

---- Years--- 

Grass shrub 0-5 0-5 

Seedling, sapling, pole 5-45 5-50 

Small conifer 45-130 50-150 

Medium single-story conifer 130-180 150-210 

Medium multistory conifer 180-235 210-275 

Large conifer 235+ 275+ 

Table 8-Comparison of land classifications for the Olympic National Forest 

developed bar overlaying the base seral-stage map over the suitable owl 

habitat mapa 

 FEMAT classification 

 Ratio of suitable habitat 

Seral stage Suitable Not suitable to unsuitable habitat 

---- Hectares--- 

Grass shrub 4288 18 048 0.24 

Seedling, sapling, pole 9472 42 304 .22 

Small conifer 23 488 52 512 .45 

Medium single-story conifer 15 744 14 896 1.06 

Large single-story conifer 304 112 2.71 

Medium multistory conifer 7472 5104 1.46 

Large multistory conifer 35 120 13 104 2.68 

a Nonforested and hardwood-dominated lands were not included. 

Source: FEMAT (1993); modified to mask high-elevation habitat. 

All stands currently classified as suitable in the spotted owl habitat map ("WDNR 

mosaic," fig. 7) were considered suitable regardless of their successional -stage 

designation. Stands not currently classified as suitable became suitable habitat 

when sufficient time elapsed for them to develop into medium multistory conifer 

(table 7). Stands already classified in that or later stages, but not currently 

classified as suitable habitat, did not immediately become suitable. Instead, they 

were treated as if they were medium single-story conifer at the current time; they 

were grown from that point and allowed to become suitable habitat when they 

reached the appropriate age during the simulation. Within each successional stage, 

we assumed stand age to be uniformly distributed for purposes of the projection. 

21 
22 

Spotted Owl 

Population Simulation 

The extent of future precommercial or commercial thinning that will occur in the 

reserves is unknown. The Northwest Forest Plan encourages thinning to accelerate 

development of owl habitat in plantations, and significant funding is being projected 

for forest restoration work. Because no operational plans exist for thinning of currently 

unsuitable stands to produce suitable owl habitat, none was assumed in the model. 

To the extent that thinning actually occurs, our simulations could underestimate 

regrowth of owl habitat for later decades. 

To evaluate the relative likelihood of persistence and the pattern of distribution of 

the northern spotted owl in the Olympic Peninsula Province under various land 

management alternatives, we used OWL (version 2.01), a single organism, spatially 

explicit life-history simulator developed by McKelvey and others (1992), and used 

methods similar to those of Raphael and others (1994). This model is based mainly 

on models developed by Lande (1987, 1988) and Lamberson (Lamberson and others 

1992, 1994; Thomas and others 1990: app. M). It is similar to Pulliam's BACHMAP 

model (Pulliam and others 1991). The model is sensitive to the shape and location of 

high-quality habitat. We view this model as a tool for landscape design that creates a 

logical framework for assessing the effects of qualitative differences in various land 

management plans on population dynamics of the northern spotted owl. 

Parameterizing the model— 

Hexagonal cell size--The population simulator uses a hexagonal grid of cells as 

the fundamental unit of spatial analysis. Habitat quality is coded for each cell, and 

all life-history functions occur at the hexagonal cell level. The total number of cells in 

the simulated landscape sets an upper limit for carrying capacity of owl pairs on that 

landscape. Thus, it is important to set an appropriate cell size. We tried to select a 

cell size that would result in a total population of pairs within the range of likely 

estimates for owls on the peninsula. As shown above (table 2), we made our own 

point estimates of the size of the Olympic Peninsula population of owls. We considered the range of realistic population size to be between the 155 known pairs and 

the 321 estimated pairs. Thus, we sought to set a cell size that would produce an 

estimate of carrying capacity within this range. 

To investigate cell size, we developed a table showing the expected number of territorial pairs for a range of cell sizes and a range of assumptions about the percentage of habitat within the cell that would support occupancy by a pair (table 9). If 

the models began with pairs occupying any cell with more than 30 percent habitat 

(Lehmkuhl and Raphael 1993, Thomas and others 1990), either the 1500-hectare 

(3,707-acre) or 1250-hectare (3,089-acre) cells would produce reasonable numbers 

of pairs (table 9). 

To choose between the 1500-hectare (3,707-acre) cell or the 1250-hectare (3,089-

acre) cell, we examined available information on the mean area per pair of owls, 

calculated as the inverse of density. Several density estimates were available and 

were used to estimate average total land area per pair of owls (table 10). These 

estimates ranged from 714 to 3100 hectares (1,764 to 7,660 acres) per pair, with 

highest estimated densities in the Park (recognizing that Park estimates were 

preliminary). The 1250-hectare (3,089-acre) cell resulted in a closer fit with the 

estimated population size on the peninsula, but 1250 hectares per pair was at the 

low end of the range of estimates from the density data (table 10); only the estimates 

from the Park were lower but all others were higher. Given all the above, we selected 

1500-hectare (3,707-acre) cells. 
Table 9-Expected numbers of pairs of northern 

spotted owls on the Olympic Peninsula based 

on different assumptions about territory size 

and about the percentage of currently suitable 

habitat assumed necessary to support a pair 

of owls 

Suitable habitat (percent) 

Territory >0 >20 >30 >40 >60 

Hectares - - - Number of pairs - - - 

3500 360 182 128 99 34 

2500 476 248 204 133 53 

1500 736 402 302 229 108 

1250 857 468 365 271 137 

Table 10-Estimates of density of pairs of northern 

spotted owls on the Olympic Peninsula 

Source Density Hectare/pair 

Pairslkm2

 Hectares 

South Quinault District 0.037 2731 

North Quinault District .042 2400 

West Soleduck District .032 3100 

Olympic National Park, west .087 1149 

Olympic National Park, east .140 714 

Source: Forsman, E.D.; Seaman, D.E. Unpublished data. On file with: Pacific 

Northwest Research Station, Forestry Sciences Laboratory, 3200 SW 

Jefferson Way, Corvallis, OR 97331. 

Vital rates in relation to habitat quality--To link the population of spotted owls to 

the landscape as portrayed by our GIS maps of habitat, relationships were developed 

between the amount and distribution of habitat and the survival and reproductive per 

formance of the owl. The model allows for input of parameter estimates relating these 

vital rates to six classes of habitat. Our analysis was meant to compare the relative 

effects of different habitat configurations, not to predict the precise number of owls 

over time. Because there are great uncertainties in such comparisons, we compared 

results under various sets of assumptions. For this analysis, we developed four "rule 

sets"; that is, four different sets of vital rates based on different assumptions con 

cerning the effects of the proportion of habitat in each hexagonal cell. The rule sets 

were modified from those used by Raphael and others (1994), which were developed 

to apply across the entire range of the owl. For the current analysis, we modified 

these values to better fit conditions on the Olympic Peninsula. Mean estimates of 

23 
vital rates in these rule sets could be taken directly from demographic analysis 

reported in Burnham and others (1994). To model effects of differing habitat management scenarios, however, the owl's vital rates need to be appropriately varied 

depending on the amount of suitable habitat in owl home ranges. Burnham and 

others (1994) do not address the range in vital rates that might be expected in 

habitats of differing quality. 

Several studies have shown that sites occupied by northern spotted owls are 

located in areas with greater amounts of suitable habitat than are random sites 

or unoccupied sites (Lehmkuhl and Raphael 1993, Meyer and others 1992, Ripple 

and others 1991, Thomas and others 1990, USDI 1992). We are aware of only 

two analyses that relate the amount of suitable habitat to specific demographic 

performance of spotted owls: Bart and Forsman (1992) report relationships of the 

amount of habitat available in sites to the density of owls per site, the number of 

fledglings per site, and the number of fledglings per pair. Bart and Earnst (in: USDI 

1992: app. B) report the relationship of adult turnover on sites to the amount of 

habitat available on those sites. They suggest that turnover is likely to be strongly 

related to survival but acknowledge that more study is needed to establish the 

relationship. Even so, this information is the best available to relate habitat to 

survival and fecundity. 

Information from both sources was used by Bart (in press c) to develop regressions 

of fecundity and survival (as estimated from persistence on sites) to the amount of 

suitable habitat in those sites. Those regressions were: 

f = 0.32 + 0.54p 

and 

sa = 0.63 + 0.39p, 

where f is fecundity, sa is adult survival, and p is the proportion of the area surrounding an owl activity center that is composed of suitable habitat. Bart reported 

that slopes of both regressions were significantly different from 0.0 at significance 

levels less than 0.001. 

We used these regressions to establish rule sets relating percentage of suitable 

habitat in owl territories to demographic parameters. By applying the regression to the 

categories of suitable habitat, as used in Raphael and others (1994), the resulting 

rule set is: 

Suitable habitat (percent) 

Parameter 0-20 >20-30 >30-40 >40-60 >60 

Adult survival 0.67 0.73 0.77 0.82 0.94 

Fecundity .37 .46 .51 .59 .75 
25 

These parameters, and the others listed in table 11 and appendix 2, were used as 

input to the simulation model and were labeled "rule set B." In this rule set, we used 

an estimate of juvenile survival of 0.29, an estimate that had been used in previous 

model simulations (Raphael and others 1994) and that was the median from the 

values in Burnham and others (1994) for 11 study areas. This estimate is slightly 

higher than that reported by Forsman and others (in prep.) for juvenile survival 

unadjusted for emigration on the Olympic Peninsula. Rule set A was identical except 

that the parameters were shifted to the right (into the next highest habitat category); 

the parameters of rule set C were shifted to the left (into the lower habitat category). 

A fourth rule set, rule set D, was identical to rule set B except that juvenile survival 

was increased to 0.38, the estimate from Burnham and others (1994) that was 

adjusted for emigration of juveniles out of study areas. 

These rule sets can be compared based on the estimates of the rate of population 

change for each habitat percentage class that result from the survival and fecundity 

rates associated with each habitat class under each rule set (table 12). For the 30- to 

40-percent habitat class, which includes the average of 38 percent nesting, roosting, 

and foraging habitat for National Forest lands, predicted rate of population change (λ) 

ranges from 0.907 under rule set A to 1.038 under rule set C. The estimated λ from 

rule set A is lower than Forsman and others' (in prep.) unadjusted λ; λs from rule sets 

B, C, and D are within the range defined by Forsman and others' (in prep.) unadjusted 

and adjusted λs (0.947 to 1.058). 

Consistency is poor between this rule set and the demographic data reported by 

Forsman and others (in prep.) for the Olympic Peninsula. For National Forest lands 

on the Olympic Peninsula where most of the demographic data were obtained, the 

average percentage of suitable habitat is 38 percent (table 4). From 1987 to 1993, 

the rates of adult survival in the Olympic demographic study area are estimated to 

have been 0.86 (Burnham and others 1994). The estimate of fecundity was 0.38 

over the same period (Forsman and others, in prep.). To better match the average 

parameters with estimates from the Olympic studies, we retained the slope of the 

regression reported above, but adjusted the intercept to match the Olympic results. 

In addition, to avoid implausibly high rates, we truncated the survival and fecundity 

parameters in the highest quality cells. The resulting parameters were: 

Suitable habitat (percent) 

Parameter 0-20 >20-30 >30-40 >40-60 >60 

Adult survival 0.76 0.82 0.86 0.92 0.92 

Fecundity .24 .33 .38 .46 .46 
Table 11-Summary of parameters under 4 sets of rules used to simulate 

population dynamics of the northern spotted owl on the Olympic Peninsula 

Suitable habitat (percent) 

Rule set and parameter 0-20 >20-30 >30-40 >40-60 >60 

Rule set A: 

 Mean survival probabilitiesa

-- 

 Stage 0 (juvenile) 0.20 0.29 0.29 0.29 0.29 

 Stage 1 (subadult) .72 .76 .82 .86 .92 

 Stage 2 (adult) .72 .76 .82 .86 .92 

Rule sets B, D: 

 Mean survival probabilitiesa

-- 

 Stage 0 (juvenile)b

 .29, .38 .29, .38 .29, .38 .29, .38 .29, .38 

 Stage 1 (subadult) .76 .82 .86 .92 .92 

 Stage 2 (adult) .76 .82 .86 .92 .92 

Rule set C: 

 Mean survival probabilitiesa

-- Stage 0 (juvenile) .29 .29 .29 .29 .29 

 Stage 1 (subadult) .82 .86 .92 .92 .92 

 Stage 2 (adult) .82 .86 .92 .92 .92 

Rule sets A, B, C, D: 

Mean fledge probabilities 

 Rule set A .19 .24 .33 .38 .46 

 Rule sets B, D .24 .33 .38 .46 .46 

 Rule set C .33 .38 .46 .46 .46 

Fledge number = 2c

Male probability of fledging = 0.50c

Movementc

 Nesting OK .40 .55 .83 1.00 1.00 

 Aversion .50 .70 .90 1.00 1.00 

 Probability female finds male = 0.50 

 Male territorial aversion = 0.50 

 Directional weighting = 2.00 

 Wanderlust 0 .50 .50 .50 .50 

Boundary conditionc 

Total number of runs = 50 

Total run length = 100 Years 

Delta-t = 20 

a Variance of survival probabilities is 0 for all rule sets and stages. b Juvenile survival was 0.29 in rule set B, 0.38 in rule set D (adjustment for emigration from Burnham 

and others [1994]). 

c See McKelvey and others (1992) and appendix 2 for explanation of these factors. 

26 
27 

Initial population-To start the model, an initial population level must be set. One 

option was to manually place owls across the simulated landscape. We considered 

using the locations of all known owl activity centers, but this would have left gaps 

where owls have not been fully surveyed. Instead, we decided to assume an owl 

occurs in every cell with more than some specified proportion of habitat and to start 

the model with a population size within our range of estimates (table 2). We examined 

the distribution of habitat around known activity centers (fig. 8) and found most sites 

had more than 40 percent habitat, so we considered 40 percent habitat or greater to 

start the owl population. This level resulted in initial number of pairs (229 pairs, table 

9) lower than the estimated number of pairs on the peninsula. Starting the model with 

a pair at every cell that exceeded 30 percent habitat resulted in an initial population 

size (302 pairs) that was within our estimated range, so we used the 30-percent rule 

to begin our model runs. Because the initial number of pairs strongly influences 

simulation results over the first years of a simulation run, model results for the first 

decade or two are not as useful as those from later years. 

Simulation runs-Each simulation began with an appropriate habitat map. The map 

was converted into hexagonal cells, and each cell was coded into a habitat quality 

class (fig. 7). Each simulation was for 100 years and consisted of 50 replicated runs 

for each rule set and habitat scenario. For simulations where habitat was changed, 

either to simulate catastrophic events or habitat growth (discussed below), the run 

began with the current habitat map (under a particular habitat scenario), and a new 

map was inserted into the run at the prescribed time(s). 

Table 12-Rates of population change (lambda [λ]) 

associated with the various habitat classes and rule 

setsa

Suitable habitat within a cell (percent) 

Rule set 0-20 >20-30 >30-40 >40-60 >60 

λ a

A 0.756 0.824 0.907 0.959 1.038 

B .824 .907 .959 1.038 1.038 

C .907 .959 1.038 1.038 1.038 

D .842 .931 .986 1.070 1.070 

a λ values are generated by inserting the associated birth and death 

rates into a stage matrix and computing the dominant eigenvalue (see 

Thomas and others 1990: app. L). λ values greater than 1.0 indicate 

that sites occupied by pairs will be producing young at rates greater 

than the replacement rate. Sites with associated λs less than 1.0 will 

require immigration to maintain occupancy. 
Figure 8-Number of known pairs (see fig. 2) by habitat 

class. Habitat classifications are based on the percentage 

of 1500-hectare (3,707-acre) circles surrounding known 

pair locations (fig. 2). 

We summarized several results from each simulation. We calculated the mean 

number of pairs at each year (averaged over the 50 runs) and an associated 

95-percent confidence interval about the mean. Mean occupancy of each cell by 

pairs of owls over 100 years was calculated and mapped. For each run, a cell 

was scored as "occupied" if a pair was present in the cell at the end of a year. 

Mean occupancy was the total occupied cell-years divided by the product of years 

multiplied by replications. We also calculated the finite rate of population change (λ) 

for each simulation by using the average change in mean population size for each 

year from year 60 through year 100. This period was chosen because it eliminated 

the initial adjustment in the model to startup conditions. 

Current conditions-For our first series of simulations, we assumed that habitat 

conditions were static; that is, whatever habitat existed at the start of a run would 

persist to the end of the 100-year run. We examined five land management 

scenarios, each with different amounts of habitat retained on non-Federal lands 

(table 13). 

Land Management 

Scenarios 

28 
a All values rounded to the nearest 100 hectares. b Includes National Forest and National Park only (does not include minor contri-butions 

of other Federal land (see table 4). 

c Selective removal of habitat cells based on successively higher mean occupancy 

see text for details). d Effect of fire as modeled from risk zones depicted in figure 5. e

 Habitat growth was modeled only for National Forest land. Totals reflect cumulative habitat 

80 years in the future. 

Scenario 1, Federal habitat only-This scenario modeled the lowest level of habitat protection envisioned. For this scenario, we assumed there was no habitat but 

Federal lands. Any habitat falling outside administrative boundaries of Federal lands 

was eliminated. Existing Federal habitat was tallied within the 1500-hectare (3,707-

acre) hexagonal cells and used as input for model runs. 

Scenario 2, Federal and Non-Federal habitat-This scenario modeled the highest level of habitat protection envisioned. It included all existing habitat ("WDNR mosaic"), 

whether Federal or non-Federal, with no regrowth or harvest. 

29 

Table 13-Total area of suitable spotted owl habitat under each 

management scenario, Olympic Peninsulaa

Scenario Total habitat Non-Federal habitat 

------- Hectares------- 

1. Federal habitat only b 265 900 0 

2. Federal and non-Federal 330 600 64 600 

3. Current take guidelines 297 900 32 000 

4. Special emphasis areas: 

 North 271 200 5200 

 West 287 100 21 100 

 Both 292 300 26 300 

5. Selective removal:c

 Rule B 

 10% 295 700 29 700 

 20% 288 600 22 600 

 40% 280 600 14 600 

 60% 271 500 5500 

 Rule D 

 10% 306 200 40 300 

 20% 298 900 32 900 

 40% 290 100 24 100 

 60% 283 800 17 800 

Catastrophic fired

 189 000 0 

Habitat growth:e

 Federal habitat only 303 200 0 

 Federal and non-Federal 367 900 64 600 

 Current take guidelines 335 200 32 000 
Scenario 3, current take guidelines-- This scenario modeled an intermediate level 

of habitat protection that would result from implementing current regulations. We 

plotted the locations of all known owl activity centers (n = 191, data through 1993 as 

provided by WDFW), each surrounded by a circular buffer 4.3 kilometers (2.7 miles) 

in radius following legal take guidelines (figs. 6 and 7A). First, we eliminated all 

non-Federal habitat outside the circular buffers. Then, if the remaining buffer area 

contained more than 40 percent habitat (the amount specified in the take guidelines), 

we eliminated any non-Federal habitat in excess of 40 percent, as long as that 

removal did not reduce the amount of habitat below 40 percent for any overlapping 

buffer. 

Scenario 4, special emphasis areas-- This scenario for special emphasis areas 

(SEAs) focused on areas being considered as alternatives under the 4(d) rule 

process. We obtained maps of proposed SEAs in the northern and western portions 

of the peninsula and plotted 4.3-kilometer (2.7-mile) buffers for all owl activity centers 

that overlapped these boundaries. We created a new boundary that followed the 

outside edge of all such circles. Within this boundary, we retained non-Federal 

habitat based on the take guidelines described for scenario 3 and eliminated all 

non-Federal habitat outside the SEAs. We also ran separate simulations on the 

northern SEA alone and on the western SEA alone. 

Scenario 5, selective removal of low-occupancy habitat-- This scenario modeled 

an intermediate level of habitat protection that would result from relaxing current 

regulations and using a hypothetical optimal process for selecting areas to protect. 

For this series of simulations, we selectively removed non-Federal habitat from the 

"WDNR mosaic" (all habitat) map (scenario 2) based on rates of occupancy by pairs 

from simulation runs using rule sets B and D under scenario 2. In this series of runs, 

we first eliminated any non-Federal habitat within hexagonal cells where mean 

occupancy by pairs of owls was less than or equal to 10 percent, and then ran the 

simulation based on this new map. Next, we eliminated any habitat from cells that 

had less than or equal to 20 percent habitat and repeated the run, then repeated 

all steps removing habitat at the 40-percent occupancy rate, and finally at the 

60-percent occupancy rate. 

Catastrophic fire-To simulate the effect of catastrophic fire, we defined a fire-risk 

zone (see footnote 7) covering about 270 000 hectares (666,400 acres) (fig. 5) and, 

as a worst case analysis, assumed that all habitat was eliminated throughout this 

zone. We simulated the fire at year 2. This simulation was based on scenario 1 

(Federal habitat only). 

Habitat growth-Scenarios 1, 2, and 3 were repeated but included an assumption 

of growth of new habitat within the Olympic National Forest. For these simulations, 

new maps in which habitat had been grown on National Forest lands were created 

for years 20, 40, 60, and 80 and inserted into the simulation run at those years. 

Connecting corridor-The relative isolation of the spotted owl population on the 

Olympic Peninsula has been of concern. There have been proposals to improve the 

interaction of the population on the peninsula with other populations by maintenance 

of dispersal habitat, as well as by developing small subpopulations that would link to 

populations along the west side of the Cascades. The northern spotted owl recovery 

plan (USDI 1992: 109) suggests creating a series of reserves large enough to 

support 20 pairs of owls and spaced at about 19.3-kilometer (12-mile) edge-to-edge 

intervals connecting the southern Washington Cascades with the Olympic Peninsula. 

30 
Results 

Amount and Distribution 

of Current Habitat 

Habitat Projection 

To analyze this proposal, we combined the map of current habitat on the Olympic 

Peninsula (fig. 7) with a hypothetical source population representing the Cascades. 

We created a series of intermediate reserves similar to those proposed in the final 

draft recovery plan (USDI 1992) and ran simulations with and without these intermediate reserves. Habitat in the source population (which had a carrying capacity of 

about 800 pairs of owls) and the intermediate reserves were assumed to be of high 

quality (more than 60 percent habitat). 

We ran 10 different scenarios using rule sets B and D with habitat maps for the 

Olympic Peninsula representing all habitat and Federal habitat only (table 11), either 

with intermediate reserves or without them. In addition, we generated two scenarios 

in which the spotted owl population of the Olympic Peninsula was reduced by 

80 percent at the outset. 

The population reduction runs were slightly different from all other simulations 

reported in this paper. In all other runs, all cells containing more than 30 percent 

habitat began with a pair. In these runs, we randomly removed 80 percent of the 

population on the peninsula while following normal initialization for the "source" 

habitat and the connecting corridor. This led to a starting point with an extremely 

diffuse population and therefore a higher likelihood of local extirpation. In addition, 

these simulations were run for 200 years to allow for recolonizing or extinction. 

Suitable habitat of the northern spotted owl (as determined from our databases) is 

concentrated in the western subprovince, primarily on National Park and National 

Forest lands (figs. 7 and 9). Of the 330 600 hectares (817,000 acres) of habitat on 

all ownerships, 197 700 hectares (488,400 acres; 60 percent) occur on the western 

subprovince and 266 000 hectares (657,300 acres; 80 percent) occur on Federal 

land in both subprovinces (fig. 7 and table 13). As shown in figures 7 and 9, habitat 

that occurs on non-Federal lands is distributed in smaller, less contiguous patches 

than that on Federal lands. Habitat represents an average of 43 percent of the 

landscape on Federal lands versus 11 percent on non-Federal lands (table 4). 

Our habitat growth model resulted in the following increases in amount of habitat on 

National Forest lands (fig. 10): 

Years Habitat growth 

0-20 9 400 hectares (23,200 acres) 

21-40 8 800 hectares (21,600 acres) 

41-60 8 800 hectares (21,700 acres) 

61-80 10 400 hectares (25,700 acres) 

 Total 37 400 hectares (92,200 acres) 

The growth rate was approximately linear and constant during the period we simulated, with an average of 466 hectares (1,152 acres) per year (fig. 10B). Much of 

the habitat grown during the 80-year period was concentrated in the northwestern 

31 
Figure 9-Distribution of nesting, roosting, and foraging habitat on non-Federal lands 

on the Olympic Peninsula. Map is summarized into 1500-hectare (3,707-acre) hexagonal cells, and the non-Federal contribution of habitat to each cell is presented 

as the percentage of each cell composed of suitable habitat. 

32 
Figure 10-Projected growth of suitable owl habitat on the Olympic Peninsula 

over the next 80 years. No habitat was grown above 914 meters (3,000 feet) 

elevation in the western subprovince or 1219 meters (4,000 feet) in the east. 

Habitat growth was projected for National Forest lands only. A: Areas in which 

habitat grew (magenta) in relation to existing habitat (green); B: overall increase 

in habitat over 80 years. 

33
Figure 11-Population trajectories associated with various rule 

sets and simulated on maps containing current levels of habitat 

for Federal lands only. The heavy lines are average trajectories 

based on 50 simulation runs. The thinner lines are 95-percent 

confidence intervals. 

Simulated Owl 

Population Trends 

Scenario 1, Federal habitat only, without regrowth-The results of the population simulations based on the 265 900 hectares (657,100 acres) of Federal habitat 

(table 13) remapped into suitability classes within hexagonal cells differed greatly 

depending on the rule set used (fig. 11). Rule set C, which had high rates of fe 

cundity and survival when habitat exceeded 30 percent of a cell, resulted in a slight 

rate of decline in mean numbers of pairs. Trends under rule set B, where high rates 

of fecundity and survival required habitat in excess of 40 percent of a cell, declined 

at a faster rate than under rule set C. Trends under rule set A, where habitat had to 

exceed 60 percent to support high fecundity and survival, declined even more steeply 

over the 100 years (fig. 11). Trends under rule set D, which was identical to rule set 

B except for use of a higher rate of juvenile survival, were nearly identical to those 

of rule set C (fig. 11). The mean numbers of pairs calculated over the 100 years of 

each simulation were 56, 143, 232, and 234 for rule sets A, B, C, and D, respectively. 

Under rule set B, which was designed to best fit the adult survival and fecundity 

parameters estimated for the peninsula (without a correction for juvenile emigration), 

the finite rate of population change (λ) was 0.9954 for years 60 through 100 (table 

14). Under rule set D, the simulated population declined more slowly (λ = 0.9996). 

Graphs of mean occupancy showed that occupancy was higher in the western 

subprovince than in the eastern subprovince under any rule set, thereby reflecting 

the greater concentration of habitat in the west (fig. 12). Plots of mean occupancy 

34 
Figure 12-Patterns of mean occupancy by reproductive pairs for simulations using rule sets A through D. 

All simulations were by run using scenario 1 (Federal habitat only) without regrowth. Occupancy rates are 

the proportion of years, averaged over all years and simulations, that a particular site was occupied by a 

reproductive pair. A: Rule set A; B: rule set B; C: rule set C; D: rule set D. 

Figure 13-Counts of cells in each of six mean occupancy classes 

(from fig. 12) of spotted owl pairs as simulated under the four rule 

sets for scenario 1 (Federal habitat only) without regrowth. Note that 

only rule sets C and D produce cells with occupancy rates greater 

than 80 percent. 

also revealed obvious differences among outcomes from the four rule sets. Rule set 

A did not result in any cells with more than 60-percent occupancy at the end of the 

100-year simulation period; more cells had higher occupancy under rules B, C, and 

D; and only rules C and D had cells with more than 80-percent occupancy (fig. 13). 

35 
Scenario 2, Federal and non-Federal habitat-The simulated population in the 

scenario representing all suitable habitat (330 600 hectares [817,000 acres]) but with 

no regrowth (table 14), was larger than that of scenario 1 for each rule set. Under 

rule set B, for example, the average number of pairs over the 100-year simulation 

was 177 for scenario 2 versus 143 pairs under scenario 1; the rate of decline of the 

population was lower as well (table 14). Mean occupancy was also greater under 

scenario 2 than under scenario 1, with 124 cells having occupancy rates exceeding 

60 percent for scenario 2 versus 85 such cells for scenario 1 at the end of the 

100-year simulation period. This is readily apparent in figure 14A, which shows a 

large, contiguous area of high-occupancy cells, an area we interpret as representing 

source habitat where the estimated rate of population change exceeds 1.0. For this 

scenario, we replicated the entire simulation (fifty 100-year runs) to assess variation 

in occupancy rates due to stochastic variation within the model. Rule sets B and D 

were used for these simulations (table 15). 36 

a

 SEAs are special emphasis areas being considered as alternatives under the 4(d) rule process (see fig. 15). b Year 2. 

Table 14-Summary of simulation results under various management scenarios using rule sets A, B, C, and 

D and assuming no regrowth of habitat, Olympic Peninsula 

Scenarios 

1 (Federal only) 2 (All 3 (Take 4 (Take guidelines in SEA)a 

Criterion Without fire With fire habitat) guidelines) Both West North 

Rule set A: 

Amount of habitat (ha x 1000) 

Number of cells >60-80% mean occupancy 

Number of cells >80% mean occupancy 

Total of cells >60% mean occupancy 

Mean number of pairs 

Pairs at year 60 

Pairs at year 100 

λ evaluated for year 60-100 

Rule set B: 

Amount of habitat (ha x 1000) 

Number of cells >60-80% mean occupancy 

Number of cells >80% mean occupancy 

Total of cells >60% mean occupancy 

Mean number of pairs 

Pairs at year 60 

Pairs at year 100 

λ evaluated for year 60-100 

Rule set C: 

Amount of habitat (ha x 1000) 

Number of cells >60-80% mean occupancy 

Number of cells >80% mean occupancy 

Total of cells >60% mean occupancy 

Mean number of pairs 

Pairs at year 60 

Pairs at year 100 

λ evaluated for year 60-100 

Rule set D: 

Amount of habitat (ha x 1000) 

Number of cells >60-80% mean occupancy 

Number of cells >80% mean occupancy 

Total of cells >60% mean occupancy 

Mean number of pairs 

Pairs at year 60 

Pairs at year 100 

λ evaluated for year 60-100 

266 

0 

0 

0 

56 

27 

10 

0.9762 

266 

85 

0 

85 

143 

120 

99 

0.9954 

266 

171 

48 

219 

232 

223 

217 

 189b

 331 

 0 0 

 0 0 

 0 0 

 43 66 

 21 33 

 6 12 

0.9698 0.9760 

 189b

 331 

 62 124 

 0 0 

 62 124 

 100 177 

 80 153 

 68 132 

0.9961 0.9963 

189b

107 

29 

136 

159 

142 

136 

331 

132 

132 

264 

293 

289 

283 

0.9993 0.9989 0.9995 

266 

105 

107 

212 

234 

230 

226 

0.9996 

 189b

 331 

 50 115 

 88 140 

 138 255 

 160 285 

 148 282 

 149 276 

1.0001 

298 

0 

0 

0 

63 

29 

11 

0.9769 

298 

108 

0 

108 

162 

138 

122 

0.9969 

298 

151 

 91 

242 

263 

258 

254 

0.9996 

298 

103 

131 

234 

263 

260 

253 

0.9995 0.9994 

292 

 0 

0 

0 

62 

32 

12 

0.976

292 

102 

0 

102 

155 

132 

110 

0.9954

292 

153 

83 

236 

258 

250 

250 

1.0000

292 

106 

119 

225 

252 

242 

244 

1.0003 

287 

0 

0 

0 

61 

32 

11 

0.9749 

287 

97 

0 

97 

152 

132 

107 

0.9948

287 

146 

87 

233 

252 

248 

237 

0.9989

287 

110 

116 

226 

250 

246 

242 

0.9996 

271 

0 

0 

0 

58 

27 

9 

0.9719 

271 

92 

0

92 

146 

124 

103 

0.9955

271 

161 

60 

221 

240 

235 

225 

0.9989

271 

102 

112 

214 

239 

233 

231

0.9998
a

 Ranges are the extreme values generated from 10 separate simulation runs for each rule set (each run consisted of 50 separate simulations). Simulations assumed that current vegetation patterns were 

static (no regrowth), and all habitat currently on the Olympic Peninsula was retained. Values in parentheses are ranges. 

37 

Figure 14-Mean occupancy of spotted owl pairs simulated by using rule sets B and D. A and B: Based 

on current habitat conditions for all lands on the Olympic Peninsula (scenario 2), using rule sets B and 

D, respectively. C and D: Based on current habitat conditions for habitat on Federal lands and 

including habitat within the buffer areas surrounding owl activity centers on non-Federal lands 

following current take guidelines (scenario 3) using rule sets B and D, respectively. In scenario 3, 

non-Federal habitat was removed from owl buffers if the combined contribution from Federal and 

non-Federal lands exceeded 40 percent. 

Table 15-A comparison of occupancy patterns 

associated with simulating owl population dynamics using rule sets B and D under scenario 2, 

Federal and non-Federal habitat, Olympic Peninsula 

Range of cells by cell counta

Mean ocupancy Rule B Rule D 

Percent 

0 871-893 (22) 797-815 (18) 

>0-10 424-446 (22) 372-395 (23) 

>10-20 62-72 (10) 72-84 (12) 

>20-40 84-92 (8) 87-97 (10) 

>40-60 88-99 (11) 59-68 (9) 

>60-80 120-125 (5) 109-121 (12) 

>80 0 138-144 (6) 
Scenario 3, current take guidelines-Under current take guidelines, we estimated 

the retention of a total of 297 900 hectares (736,200 acres) of suitable habitat (assuming no regrowth), a reduction of 32 700 hectares (80,800 acres) from scenario 2 

(table 13). Under this habitat scenario, the size of the simulated owl population and 

rates of occupancy (figs. 14C and D) were intermediate to those of scenarios 1 and 2 

(figs. 12B and 14A). Compared to scenario 2 (fig. 14A), the pattern of high-occupancy 

cells (those greater than 60 percent) was more fragmented and constricted at the 

end of the 100-year simulation period. 

Scenario 4, special emphasis areas-The respective amounts of non-Federal 

habitat retained under the three SEA options (without regrowth) were 5200 hectares 

(12,800 acres) with the north SEA retained, 21 100 hectares (52,100 acres) with the 

west SEA retained, and 26 300 hectares (65,000 acres) with the two SEAs retained 

(table 13). The simulated owl population trend and size reflected the relative amount 

of habitat in the three options, but the west SEA made a greater contribution to owl 

numbers and occupancy rates than did the north SEA under each of the four rule 

sets (figs. 15 and 16; table 14). Mean number of pairs over the 100-year simulation 

was nearly as large with the western SEA alone as with both SEAs (table 14). 

Scenario 5, selective removal of low-occupancy habitat-Selective removal of 

habitat (table 13) from cells supporting lower occupancy rates, as determined from 

our earlier simulation of scenario 2 (all habitat, no regrowth), suggested that it is 

possible to design alternative non-Federal habitat retention strategies that might 

be more efficient (require less area of habitat for a given number of owls) than the 

current take guidelines. Using the approach of successively removing all non-Federal 

habitat at cells where occupancy was lowest (less than or equal to 10 percent) 

and then moving to higher levels (more than 10 to 20 percent, more than 20 to 

40 percent, more than 40 to 60 percent) showed that removal at the lowest levels 

had little effect on mean number of pairs (fig. 17). Only after removing habitat where 

occupancy was up to 60 percent did populations fall below the level resulting from 

scenario 3 under rule set B; populations were always greater under rule set D. 

Effect of catastrophic fire-Simulations of scenario 1 (Federal habitat only) where 

all Federal habitat within the fire-risk zone was removed (76 900 hectares [190,000 

acres], fig. 5) showed a decline in mean numbers of pairs over the 100-year run 

from 143 to 100 pairs under rule set B, a change of 30 percent compared to the 

simulations of scenario 1 without fire (fig. 18). The magnitude of this population 

reduction was proportional to the size of the affected area, about 33 percent of the 

Federal land. Simulated population trends (that is, the rates of change in population 

size over time) were similar between the burned and unburned scenarios under each 

of the four rule sets (table 14). Rates and patterns of mean occupancy on the peninsula before and after the burn (figs. 12 and 19) also differed very little, except for the 

expected lower rate of occupancy within the burn zone itself. Burning in the eastern 

subprovince had little impact on occupancy patterns by owls in the western subprovince (fig. 19). 

Effect of habitat regrowth-Simulated populations were larger and more widely 

distributed (figs. 20 and 21) when currently unsuitable habitat on the National Forest 

was grown as described earlier (fig. 10). Populations declined at a slower rate than 

without habitat growth under rule sets A and B (table 16). Under rule sets C and D, 

the estimated rate of population change exceeded 1.0 under each of scenarios 1, 2, 

and 3 (table 16, fig. 20). 

38 
39 

Figure 15-Mean occupancy of spotted owl pairs based on current habitat conditions 

on Federal lands plus habitat on non-Federal lands that occurred within a 4.3-kilometer 

(2.7-mile) radius of owl activity centers and that fell within defined special emphasis 

areas (SEA). A: Northern SEA; B: western SEA; C: both. Simulations were run by 

using rule set B. 

Text continues on page 44. 
Figure 16-Mean occupancy of spotted owl pairs based on current habitat conditions on 

Federal lands plus habitat on non-Federal lands that occurred within a 4.3-kilometer 

(2.7-mile) radius of owl activity centers and that fell within defined special emphasis 

areas (SEA). A: Northern SEA; B: western SEA; C: both. Simulations were run by 

using rule set D. 

40 
41 

Figure 17-Relationship between non-Federal habitat added with each 

scenario and the expected average number of pairs. Scenario 1 models 

Federal habitat only without regrowth. Scenario 2 includes all existing 

Federal and non-Federal habitat without regrowth or harvest. Scenario 3 

retains habitat following the current take guidelines. Scenario 4N protects 

habitat in the northern special emphasis area (SEA), 4W the western SEA, 

and 4B both. Scenario 5 saves habitat based on its simulated contribution 

to population size; 5A results from removal of habitat with occupancy less 

than or equal to 10 percent, 5B from cells less than or equal to 20 percent, 

5C from cells less than or equal to 40 percent, and 5D from cells less than 

or equal to 60 percent. Occupancy patterns were based on simulations using 

rule sets B and D (fig. 14). 
Figure 18-Simulated trends in spotted owl populations over 100 years 

assuming a catastrophic burn at year 2 (see fig. 5 for map of fire-risk zone). 

Habitat was limited to Federal lands only (scenario 1). 

42
Figure 19-Mean occupancy for simulations with catastrophic burns. 

Rule sets B and D were used for simulations, and habitat was limited 

to current conditions and to only Federal lands with no regrowth 

(scenario 1). A: Rule set B; B: rule set D. 

43 
Figure 20-Simulated population trends for spotted owls on maps that 

included regrowth. Growth was limited to National Forest lands. In 

scenario 1, only Federal habitat was included, scenario 2 included 

all habitat, and scenario 3 implemented current take guidelines. 

Demographic support from a distant population 

Effect of Cascades Range source-We compared the simulations performed for 

the Olympic Peninsula with those including the Cascade Range source population 

but not including intermediate reserves to estimate the impact of a large distant 

source population. For this comparison, we were limited to an analysis of the levels 

of occupancy. The model is not designed to track the population dynamics for 

individual subpopulations, so population numbers for the peninsula could not be 

separated from the source population in these simulations. An evaluation of the 

occupancy classes shows that the presence of a distant source population had no 

44 
Figure 21-Average occupancy levels associated with simulations of scenario 1 (Federal habitat only) 

and scenario 2 (Federal and non-Federal habitat) with regrowth only on National Forest lands and 

maintaining all non-Federal habitat in its current condition. A: Scenario 1, rule set B; B: scenario 1, 

rule set D; C: scenario 2, rule set B; D: scenario 2, rule set D. 

significant impact on the mean occupancy. For instance, given rule set B and limiting 

the habitat to Federal lands, the number of cells in each occupancy class were: 

Occupancy class (percent)

Map 0 >0-10 >10-20 >20-40 >40-60 >60-80 

Number of cells 

Olympic Peninsula only 205 426 46 79 94 87 

Olympic + source 192 441 51 73 89 91 

These differences are all well within the anticipated range of variability associated 

with 50 simulations (table 15). 

45 
Table 16-Summary of simulation results under various management scenarios 

with habitat regrowth using rule sets A, B, C, and D, Olympia Peninsulaa

Criterion 1 (Federal only) 2 (All habitat) 3 (Take guideline) 

Rule set A: 

 Amount of habitata

 (ha x 1000) 303 368 335 

 Number of cells >60-80%mean occupancy 0 0 0 

 Number of cells >80%mean occupancy 0 0 0 

 Total of cells >60% mean occupancy 0 00 0 

 Mean number of pairs 59 69 64 

 Pairs at year 60 30 35 34 

 Pairs at year 100 10 16 15 

λ, evaluated for year 60-100 0.9730 0.9799 0.9803 

Rule set B: 

 Amount of habitata (ha x 1000) 303 368 335 

 Number of cells >60-80% mean occupancy 110 137 131 

 Number of cells >80% mean occupancy 0 0 0 

 Total of cells >60% mean occupancy 110 137 131 

 Mean number of pairs 154 186 175 

 Pairs at year 60 134 163 156 

 Pairs at year 100 130 160 148 

λ evaluated for year 60-100 0.9993 0.9996 0.9988 

Rule set C: 

 Amount of habitata

 (ha x 1000) 303 368 335 

 Number of cells >60-80% mean occupancy 156 142 148 

 Number of cells >80% mean occupancy 71 137 106 

 Total of cells >60% mean occupancy 227 279 254 

 Mean number of pairs 250 313 283 

 Pairs at year 60 240 310 278 

 Pairs at year 100 271 339 305 

λ evaluated for year 60-100 1.0030 1.0022 1.0023 

Rule set D: 

 Amount of habitat (ha x 1000) 303 368 335 

 Number of cells 60-80% mean occupancy 100 112 106 

 Number of cells >80% mean occupancy 124 161 142 

 Total of cells >60% mean occupancy 224 273 248 

 Mean number of pairs 254 307 280 

 Pairs at year 60 251 304 274 

 Pairs at year 100 278 342 313 

λ, evaluated for year 60-100 1.0026 1.0030 1.0033 

a Habitat regrowth was modeled only on National Forest land. Amount of habitat reflects cumulative habitat 

80 years in the future. 

Intermediate reserves as a connecting corridor-Runs with intermediate reserves and a distant source population consistently resulted in occupancies of 

up to 10 percent in cells that had 0-percent occupancy without these reserves 

(fig. 22). Cells that had occupancy levels greater than 10 percent were not significantly bolstered by the presence of the connecting reserves. Even in the 

reduced population runs, which were expected to be more sensitive to the effects 

of a connecting corridor, the intermediate reserves had little impact on recolonization 

and expected stability. Runs both with and without intermediate reserves showed 

lower occupancy rates than any of the previous runs, as would be expected given 

the low starting populations. Simulations that included a connecting corridor provided 

an additional 50 cells in the 0- to 10-percent occupancy class (figs. 22 and 23) but 

virtually no increases in the higher occupancy classes. The increase in the 1- to 

10-percent occupancy class indicated that recolonization occurs, but it appears to 

result only occasionally in the creation of successful populations. 

46 
Population estimate (and comparison to previously published numbers)-There 

are 155 known pairs of northern spotted owls on the Olympic Peninsula, and projections of the total population using two different sets of assumptions resulted in 

point estimates of 282 and 321 pairs. This was greater than other recently published 

figures, such as those in the SETS (USDA and others 1994). The SEIS figures were, 

however, simply the numbers of owls detected in a 5-year period, not a population 

estimate. A more appropriate comparison would be to the 185 owl pairs estimated 

to occur in the designated conservation areas on the Olympic Peninsula under the 

final draft recovery plan (USDI 1992). Were the estimated density of owls in these 

designated conservation areas projected to all Federal lands that could support 

spotted owls on the peninsula, the resulting estimate would be about 225 pairs. 

There could be about 30 additional pairs on non-Federal lands (table 2), thereby 

bringing the extrapolated estimate from the final draft recovery plan to 255 pairs. 

Thus, the estimates presented here are substantially higher than earlier numbers 

such as those reported by Thomas and others (1990), and the lower estimate 

presented here is about 15 percent higher than the estimate made by the Northern 

Spotted Owl Recovery Team (USDI 1992) in developing its recommendations for the 

Olympic Peninsula. As noted in the final draft recovery plan (USDI 1992), the number 

of spotted owls is less important than the trend in the population. The population 

estimates made for this paper were considered in establishing the territory size and 

initial population size used in model projections. This resulted in smaller territory size 

and higher carrying capacity than in model formulations used previously (Raphael 

and others 1994). 

47 

Discussion 

Condition of the 

Population 

Figure 22-Differences in occupancy levels associated with various combinations of rule 

sets and the presence or absence of a line of intermediate reserves connecting the 

Olympic Peninsula population to populations in the southern Washington Cascade Range. 

Values are the difference in occupancy patterns as evaluated cell by cell. Occupancy 

classes with negative values had fewer cells in those classes when intermediate reserves 

were added. 
48 

Figure 23-Maps of occupancy patterns with and without a string of intermediate reserves 

connecting the Olympic Peninsula population to populations in the southern Washington 

Cascade Range. For these simulations, the model began with a scattered population 

20 percent the size of the Olympic Peninsula population of owls that was used to begin 

all other simulations. Rule set B was used. A: Without the intermediate reserves; B: with 

the intermediate reserves. 
Population status— 

Demographic studies-Demographic values reported by Forsman and others (in 

prep.) for the Olympic Peninsula are generally comparable to the combined results 

reported by Burnham and others (1994) for 12 demographic studies in the range 

of the spotted owl (table 17), but they differ in two ways. First, the analysis of adult 

survival on the peninsula does not show a statistical trend over time as is seen in 

the analysis for all study areas combined (Burnham and others 1994). This declining 

trend in adult survival was identified as a cause for concern in the analysis of demographic studies (Burnham and others 1994; USDA and USDI 1994). Second, the rate 

of population change calculated from the Olympic Peninsula study is not significantly 

different from 1.0 when an adjustment is made for juvenile emigration. 

Burnham and others (1994) caution that inferences from individual study areas are 

weaker than the inferences drawn from analysis of all study areas combined. Standard errors for all parameter estimates are predictably higher for the single study on 

the Olympic Peninsula than they are for the combined study areas (table 17). The 

standard error is particularly high for juvenile survival rate adjusted for emigration, 

because the sample sizes used to estimate emigration were small. Even with a larger 

sample size, the correction for emigration would remain uncertain because it requires 

an assumption that emigrating juveniles survive at the same rate as nonemigrants. 

The lack of a statistical trend over time in adult survival also may be due to smaller 

sample sizes and lower statistical power in the individual study than was available 

in the analysis of 12 study areas. 

49 

Table 17-Comparison of demographic values estimated for the Olympic 

Peninsula and for 12 demographic study areas within the range of the 

northern spotted owl 

Olympic study areaa

 Rangewide studiesb

Standard Standard 

Parameter Mean error Mean error 

Adult survival 0.862 0.017 0.844 0.005 

Adult fecundity .380 .036 .339 .010 

Subadult fecundity .206 .106 .205 .034 

Juvenile survival .245 .064 .258 .036 

Juvenile emigration .600 .083 .3158 .053 

Adjusted juvenile survival .611 .204 .3769 .060 

Lambda unadjusted .9472 .0255 .9253 .0148 

Lambda adjusted 1.0582 .0648 .9548 .0173 

a Forsman and others, in prep. b Burnham and others 1994. 
Even with these cautions, the demographic rates observed for the Olympic Peninsula owl population could be viewed as relatively positive. The estimate of juvenile 

emigration is substantially higher than the value of 0.41, which Burnham and others 

(1994) calculate would result in a rate of population change of 1.0 when combined 

with other demographic values calculated for the peninsula study. Also, subsequent 

to the publication of Burnham and others (1994), Bart (in press, b) has completed 

simulations indicating that the methods used by Burnham and others (1994) underestimate the true rates of population change by values from 0.03 to 0.13. Given the 

confidence intervals surrounding the estimates of demographic rates on the peninsula, and the sources of bias discussed by Bart (in press, b), the results of the 

demographic analysis could be consistent with a nondeclining population, or with 

a population declining at a rate no greater than the rate of habitat loss (1.1 percent 

per year estimated for the peninsula for 1982-92 [Raphael and others, in prep.]). A 

decline in population caused by habitat loss and at about the same rate as the rate 

of habitat loss would not be surprising and does not suggest that the population 

would continue to decline if habitat stabilized. 

Genetic risk-Isolation of small populations can result in loss of genetic variation 

and increased risks of inbreeding depression and genetic drift (Frankel and Soule 

1981). Some early analyses of risks to northern spotted owls suggested that the 

population on the Olympic Peninsula might be so small and isolated as to be affected 

by loss of genetic variation (USDA 1988). Further analysis has suggested that the 

population of owls on the peninsula is sufficiently large to avoid any shortto midterm loss of genetic variation, and that the major problems facing spotted owls are 

short-term habitat loss and population performance (USDA 1988). Inbreeding depression was not explicitly considered, however, and could affect future persistence of the 

population, especially if it occurred in combination with environmental or demographic 

events that reduced population size or growth rate (Mills and Smouse 1994). Genetic 

variability of spotted owls on the peninsula therefore should be monitored. Losses of 

variability likely could be mitigated by transplanting owls or eggs from other portions 

of the range. 

Factors that could adversely affect spotted owl populations are summarized by the 

Northern Spotted Owl Recovery Team (USDI 1992) and include systematic habitat 

loss, habitat fragmentation, demographic variation, environmental variation, population decline to critically small size (Allee effect), loss of genetic variation, catastrophic events, and species interactions. Ideally, all these factors would receive 

some consideration in an evaluation of potential stability of a population or, conversely, potential risks to a population. The risk factors are interrelated, and the 

interactions of risk factors can increase overall risks. 

In this analysis, a spatially explicit life-history simulator for northern spotted owls was 

used to assess the effects on owl population dynamics of several of these 

factors including systematic habitat loss, habitat fragmentation, demographic 

variation, catastrophic events, and population decline. Several recent spotted owl 

management plans and analyses have discussed the value of simulation analysis 

in trying to compare the future population status of owls under different management 

scenarios (FEMAT 1993, Thomas and others 1993, USDI 1992). These discussions 

have noted that simulation analysis may be useful in risk assessment, but that the 

Projected Future 

50 
limitations of simulation models must be clearly understood. Simulation results are 

entirely dependent on the structure of the models, the assumptions incorporated 

in them, and the input data supplied to them. Some factors that could significantly 

influence outcomes, such as the interaction with barred owls, are not currently 

represented in the models used for this analysis. The results of the models should 

not be viewed as reality, but rather as a repeatable projection of the modelers 

understanding of the system. Considerations pertinent to the use and interpretation 

of models have been summarized by Bart (in press, a). His recommendations include 

the projection of a variety of scenarios, including best and worst cases, rather than 

the use of single predictions. Model use in this analysis was consistent with these 

recommendations. Parameter values were altered to provide both pessimistic and 

optimistic projections, and various scenarios of habitat growth and disturbance were 

projected. 

Because the relationship between any model run and reality is not known, the 

relative differences between land management scenarios under a particular rule 

set are of most interest in the interpretation of model results. Comparisons between 

rule sets then can show how sensitive those relative relationships are to change in 

biological understandings. Simulations of scenario 2, for instance, resulted in mean 

numbers of pairs 18 percent greater than those in scenario 1 under rule set A, 

24 percent greater than under rule set B, 26 percent greater than under rule set C, 

and 22 percent greater than under rule set D (table 14). We inferred from this relationship the probable magnitude of potential contribution from non-Federal lands. 

The absolute number of pairs projected in the scenarios was of less interest and 

was given less weight in interpretations of the results. Thus, in interpreting the 

model results, we generally placed more weight on relative occupancy values, 

relative number of pairs, and the rate of population change than we did on the 

absolute number of pairs. Interpretation of the rate of population change should 

focus on later years in the simulation because the results projected in the early 

decades of each simulation largely reflected a transition from the starting conditions 

of the simulation to the projected trends of that simulation. The distribution of the 

population also was of interest and has a strong effect on stability--the ability of 

the population to persist over time. Stability may be strongly influenced by population size when populations are small, but it is increasingly dependent on population distribution as population size increases. 

Effects of alternative rule sets for demographic parameters-As explained in 

"Methods," the rule sets for demographic parameters were based on birth and survival rates as estimated in the demographic analyses of Burnham and others (1994) 

and Forsman and others (in prep.). Regressions from Bart (in press, c) were then 

used to develop relationships among birth and survival rates and habitat quality in 

owl territories. Rule sets A, B, and C were formulated by adjusting the relationship 

of habitat quality to demographic performance. In rule set A, the actual values estimated from the demographic studies were applied to cells in the 40- to 60-percent

suitable habitat class (table 11). In rule set B, they were assigned to cells in the 

30- to 40-percent suitable habitat class. In rule set C, they were applied to cells in 

the 20- to 30-percent suitable habitat class. In all three rule sets, the regression 

51 
52 

from Bart (in press, c) was used to develop values for cells with greater and lesser 

amounts of suitable habitat. Rule sets A, B, and C used a juvenile survival rate 

uncorrected for juvenile emigration. Rule set D was developed from rule set B by 

replacing the uncorrected juvenile survival rate with the rate of 0.38 that was corrected for emigration in the analysis of Burnham and others (1994). 

Overall implications of the four different rule sets are displayed in the population 

trajectories of figure 11 and the calculated rates of population change in table 14. 

When simulations using all existing habitat (scenario 2) were run, rates of population 

change ranged from 0.9760 under rule set A to 0.9995 under rule sets C and D. 

Although these rates do not represent the full range of lambdas shown in table 17 

(0.9253 to 1.0582), they do produce a broad range of simulation results. Under all 

habitat scenarios (table 14), rule set A resulted in steep population declines and few 

pairs of owls at the end of 100 years. These results are similar to those that would 

be obtained by simply projecting into the future the demographic rates reported by 

Burnham and others (1994). 

At the other end of the range, rule sets C and D generally resulted in relatively 

stable populations, although at levels lower than the starting population size. Rule 

set B generally led to a slow decline from initial numbers, and the rate of decline 

was very slow in later years of the simulations (table 14). Because projected model 

populations approached but did not reach a rate of population growth of 1.0 under 

most scenarios with this rule set, it provided a relatively sensitive basis for comparison of different habitat scenarios. 

The relationship between habitat quality and demographic performance is central to 

all the rule sets, and few data are available to determine this relationship. As a result, 

any of the rule sets may be optimistic or pessimistic to an unknown degree. Thus, 

the simulation results should be viewed in a relative rather than an absolute sense. 

Results obtained by using different rule sets should be considered as a sensitivity 

analysis rather than being viewed as a range of real outcomes. 

Effects of large-scale disturbances-The possible effects of a catastrophic burn 

were simulated by projecting a 100-percent burn across the entire area mapped as 

having high risk of large-scale fire (fig. 5). This was more extreme than the actual 

"worst case" predicted for this area by Agee (1991a), who foresaw a possible burn 

of 25 percent across this high-risk zone in a single event and the possibility of three 

such events per century. No regrowth of habitat was projected after the burn. Under 

the 100-percent burn scenario and using rule set B, the owl population was essentially eliminated from the eastern subprovince of the peninsula, but there were only 

small changes in the distribution or occupancy rate of owl pairs in the western subprovince (fig. 19). The size and distribution of the most stable "core" area on the west 

side changed little. This result strongly suggests that the total area of Federal land 

that will be managed to maintain spotted owl habitat on the peninsula is large enough 

to be relatively robust against large-scale disturbance, and that a large-scale fire in 

the eastern subprovince of the peninsula would not destabilize an otherwise stable 

population. This finding is illustrated by graphs comparing population trends with and 

without the assumption of a catastrophic fire (fig. 18). A fire could, however, have the 

effect of removing the population from a large portion of the eastern subprovince. 

Owls might slowly resume their original distribution after such a fire, but the process 

of habitat regrowth and recolonization would take many decades. 
53 

Effects of large-scale wind events were not modeled, partially because effects of 

wind on spotted owl habitat are difficult to quantify. Even large, intense wind storms, 

like the one that occurred on the peninsula in 1921, do not uniformly remove the 

forest overstory from extensive areas. Wind events also can leave legacies of large 

snags and a diversity of tree heights and sizes, which are key elements of suitable 

spotted owl habitat on the Olympic Peninsula (Mills and others 1993, North 1993). 

Nonetheless, coastal areas have a return interval of about 30 years for major wind 

disturbances (Agee and Edmonds 1992), and the potential exists for loss of spotted 

owl habitat. If an unusually intense, large-scale wind event occurred in one or more 

of the major drainages of the western peninsula (for example, Quinault, Queets, or 

Hoh River watershed), spotted owl populations could be reduced significantly. If such 

a loss occurred in combination with a worst case fire in the eastern subprovince, 

effects on the spotted owl population peninsula wide could be significantly greater 

than those projected for a worst-case fire alone. The likelihood of a truly damaging 

wind event is small, however, and the chance of it occurring in combination with a 

significant fire is smaller. 

Effects of habitat regrowth-The history of forest harvest and natural disturbance 

has left fragmented forest conditions throughout virtually the entire range of the 

northern spotted owl. The Olympic Peninsula, outside of Olympic National Park, is 

no exception. Less than half the late-successional reserve proposed for the Olympic 

National Forest on the peninsula currently supports suitable habitat for owls. Much 

of the vegetation not currently of suitable habitat is composed of young stands that 

resulted from either human or natural disturbance. Young stands in appropriate 

ecological sites should generally begin to develop characteristics associated with 

suitable habitat as they age. Over time, such stands could make a significant 

contribution to landscape-scale habitat quality for spotted owls. 

Estimates of habitat regrowth used in this analysis were based on a series of assumptions. Stands not currently of suitable habitat had to grow to a medium, multistoried structural stage before being classified as suitable habitat. We projected that 

this would take 180 years from the time of stand initiation in the western subprovince 

of the peninsula and 210 years in the eastern subprovince. Appropriate management 

likely could accelerate this development, but none was assumed for this analysis 

because programs of thinning have not been scheduled. Also, development of young 

stands into suitable habitat conditions was projected only for National Forest lands 

and not for National Park lands. Olympic National Park was assumed to be in a state 

of dynamic equilibrium where development of young stands would be balanced by 

natural disturbance of older stands. No regrowth of habitat was assumed on nonFederal land because there is no regulatory requirement to develop new habitat on 

those lands, and normal commercial timber production would be unlikely to result in 

significant new acreage of suitable habitat. Development of new habitat on nonFederal land might occur under an HCP adopted under section 10 of the ESA, but 

we had no specific information to base such a projection on. As noted in the section, 

"Federal and Non-Federal Plans for the Olympic Peninsula," we assumed no loss of 

habitat due to cutting on Federal lands given current planning direction. 
54 

With these assumptions, we projected an increase of about 37 300 hectares (92,200 

acres) of nesting, roosting, and foraging habitat over 80 years in the National Forest 

(fig. 10). This development of additional habitat had a noticeable effect on model projections under all rule sets and all non-Federal habitat scenarios it was applied to 

(tables 14 and 16). Projected populations stabilized under more scenarios and rule 

sets with habitat regrowth than without it. Under rule sets C and D, a rate of population change of 1.0 was projected under all habitat scenarios when regrowth was 

assumed (table 16, fig. 20). The influence of habitat regrowth can be explained by its 

tendency to fill in the currently fragmented habitat pattern on National Forest lands. 

Within the assumptions of the model, this results in larger amounts of habitat in individual territory cells and improves demographic performance of owls in those cells. 

Because there is empirical evidence that increasing amounts of habitat in home 

ranges improves demographic performance (Bart and Forsman 1992, USDI 1992), 

it is likely that a beneficial effect from habitat regrowth will be observed in the 

population. 

Relative contributions of non-Federal lands-All the possible contributions of 

non-Federal habitat (scenarios 2 to 5, see "Methods") resulted in improvements in 

the status of projected owl populations (table 14, fig. 17). Differences were most 

obvious in two parameters: the number of cells in which at least 60-percent occupancy was maintained over 100 years, and the mean number of pairs present on the 

landscape averaged over the 100-year simulation. Relative differences among the 

scenarios were generally predictable, with greater contributions in habitat leading to 

greater improvement in simulated population status (fig. 17). The greatest differences 

were between scenarios 1 and 2 (table 14). Under rule set B, the number of territories 

with more than 60-percent occupancy was nearly 50 percent greater under scenario 

2 than scenario 1, and there were clear differences in mean number of pairs over 

100 years and the number of pairs at the end of 100 years (table 14). The rate of 

population change, however, was not substantially different between scenarios 1 and 

2. As with all the model results presented here, it is well to remember that these are 

projections and not observations. We believe, however, that the projected differences 

represent biologically significant increases in the stability of the owl population on the 

peninsula. It should be noted that greater improvements in population status would 

likely have been projected if our scenarios had included habitat restoration on nonFederal land in addition to retention of existing habitat. Such scenarios were not 

considered because they are outside the scope of the 4(d) process. Thus, the 

potential contributions of non-Federal lands in this analysis were limited by the 

current condition of those lands, which have been strongly modified by past timber 

harvest. 

The projected improvement in population performance associated with non-Federal 

habitats was generally proportional to the amount of non-Federal habitat included in 

each of the scenarios (fig. 17). Scenario 2 (all habitat) showed the greatest change 

from scenario 1, followed in decreasing order by scenario's 3 and 4. Scenario 5 

deviated somewhat from this pattern and is discussed below. Within scenario 4, the 

west SEA made a greater contribution to population performance than did the north 

SEA (table 14). The north SEA, when analyzed by itself, resulted in little noticeable 

improvement (table 14 and fig. 15) because this SEA contains only a limited amount 

of suitable habitat on non-Federal land (fig. 9 and table 13). 
55 

We developed scenario 5 with the objective of determining if non-Federal contributions of habitat could be made in a more efficient way than by following the current 

take guidelines. For scenario 5, we started with the map of territory occupancy rates 

projected for scenario 2 and then progressively removed non-Federal habitat that 

contributed less to occupancy by pairs. We first removed non-Federal habitats that 

supported occupancy of 0 to 10 percent, then removed habitats supporting occupancy 

of more than 10 and up to 20 percent, and so forth, up to the final cut that removed 

habitats supporting occupancy rates up to 60 percent. The future of the population 

was simulated under rule sets B and D with each of these habitat removals. Results 

are shown in figure 17 where they are compared to scenarios 1, 2, 3, and 4. Scenario 5 resulted in a much more efficient contribution of non-Federal habitat to the 

performance of the population, with a larger increase in mean pairs of owls per hectare of habitat than was seen in other scenarios. We believe this demonstrates that 

contributions of non-Federal habitat can be more efficient if they are made in appropriate locations rather than scattered across the landscape. We view the actual 

results of this scenario with caution, however. Using the results of the model to 

improve the performance of the model produces projections at least two steps 

removed from reality. Whereas the concepts of scenario 5 may suggest that there 

are more effective ways to design non-Federal contributions, the actual results 

require additional analysis before they can be used to design a more efficient 

strategy. 

It is interesting to compare the effects of regrowing habitat on the National Forest 

with the effects of retaining non-Federal habitat without an assumption of regrowth 

of new habitat on Federal land. The amount of non-Federal habitat retained under 

scenario 3 (32 000 hectares [79,000 acres], table 13) is similar to the amount projected to regrow on Federal land over 80 years (37 300 hectares [92,000 acres], 

fig. 10). Projected effects of these two habitat scenarios (scenario 3 in table 14 and 

scenario 1 in table 16) are quite similar. The small differences projected between 

these two scenarios likely reflect the different locations of the suitable habitat under 

each, and the fact that non-Federal habitat is available from the beginning of the 

projections while habitat regrowing on Federal land develops incrementally over the 

first 80 years of the projection. 

One significant caution must be applied to the interpretation of all the non-Federal 

habitat scenarios. These analyses are strongly dependent on the reliability of the 

habitat map that was used. The non-Federal map used for this analysis was developed by the WDNR Habitat Conservation Planning Team and data for the map came 

from several sources. For clusters of watersheds being used as planning units by 

WDNR, alternative source maps were compared to ground-verified maps of spotted 

owl habitat that had been completed for some portion of the planning unit. The 

source map that performed best in this comparison was then applied across the 

entire watershed. The reliability of the resulting map is not known. If it is significantly 

in error, then the results of these projections could be biased. 
Conclusions 

56 

Effects of the connecting corridor-The connecting corridor tested in this analysis 

followed the design criteria established by the Northern Spotted Owl Recovery Team 

(USDI 1992). This corridor consisted of a single chain of small reserves connecting 

the owl population on the peninsula to the population in the Washington Cascade 

Range. When both source populations began with a reasonable number of owl pairs, 

this chain of connecting reserves had little effect on the stability of the population on 

the peninsula. There were several probable reasons for this. One is that most of the 

high-occupancy cells predicted by the model were in the western subprovince and 

therefore were further from the connecting reserves. In addition, population size 

relationships must be taken into account. The Olympic Peninsula simulation began 

with about 200 pairs. The connecting reserves were each of a size that could support 

20 pairs. The internal rates of dispersal in the comparatively large population on the 

Olympic Peninsula will generally swamp the modest number of dispersers produced 

by the small connecting reserves. This relationship can be quantified by using some 

simple calculations in conjunction with published dispersal data. Fecundity rates for 

spotted owls differ greatly from year to year but on average are about 0.3 (Burnham 

and others 1994). If we assume that fecundity rate, a cluster containing 20 reproductive pairs will produce an average of six females per year. Of this number, some will 

die before dispersal and the rest will disperse. Of the dispersers, some will settle 

within the natal cluster. For this exercise, we assumed that all six females lived to 

disperse and that those that moved less than 16 kilometers (10 miles) settled within 

the natal cluster. Based on data from Thomas and others (1990:app. P, table P1), 

about 25 percent of dispersing females nest within 16 kilometers (10 miles) of their 

natal site. This leaves 4.5 dispersers that might emigrate to the Olympic Peninsula 

population each year from the hypothetical system of connecting reserves. Of course, 

not all will travel in the right direction. Assuming that 0.25 travel in the right direction, 

then we have on average 1.1 female juveniles entering the Olympic Peninsula population each year. Not all will live to reproduce. If we apply the juvenile survival rate of 

0.38 (Burnham and others 1994:20), then about 0.41 female per year will enter the 

Olympic Peninsula population as potential subadult breeders from the connecting 

reserve system. If the population is close to carrying capacity, then these owls may 

be forced to "float" for an indefinite period. 

Several recent spotted owl analyses have suggested that human judgment must 

ultimately be used to assess the efficacy of options for spotted owl management 

(FEMAT 1993, Thomas and others 1993, USDI 1992). Analytical tools can be 

extremely helpful but do not take the place of professional judgment. In particular, 

the results of models should not be viewed as reality but rather as repeatable projections of a set of assumptions. In this effort, we reviewed all the pertinent analytical 

information and then summarized our conclusions through response to the following 

questions. 

1. Given the design suggested by the Northern Spotted Owl Recovery Team (USDI 

1992), is there significant potential for a habitat connection across southwestern 

Washington to provide demographic rescue for the owl population on the Olympic 

Peninsula? 

Our conclusions on this question rested largely on the results of simulation analyses 

described under "Methods" and "Results." Those analyses suggested that a habitat 

connection across southwestern Washington would have little effect on the status of 

the owl population on the peninsula if that population was stable or nearly stable. 
57 

Whereas the habitat connection seemed to provide little demographic benefit, it 

likely would provide for significant interchange between owl populations on the 

Olympic Peninsula and in the Washington Cascades. This would increase genetic 

mixing, which could have a beneficial effect on the population. Loss of genetic 

variation is not currently considered a major risk to the owl population on the 

peninsula (Barrowclough and Coats 1985), but it cannot be entirely discounted 

as a future threat (Mills and Smouse 1994). Genetic variation can, however, be 

maintained by only a few immigrants per generation. Such rates of interchange may 

occur without significant development of new habitat across southwestern 

Washington, or a similar result likely could be achieved by transplanting a small 

number of owl eggs from another portion of the range. However, development 

of new habitat would help assure that immigration would take place. 

The habitat connection described by the Northern Spotted Owl Recovery Team 

(USDI 1992) was constrained by feasibility and the high cost of developing habitat 

in this heavily harvested landscape. Other more ambitious designs likely would have 

significantly greater effect on the status of the Olympic Peninsula population, but they 

would be increasingly unrealistic. Also, the connecting corridor clearly would have 

significant effects on the likelihood of maintaining owls in southwestern Washington, 

but those effects were outside the scope of this paper. 

We conclude that the stability of the owl population on the Olympic Peninsula will 

primarily depend on local habitat conditions. Modest alterations in land use patterns 

in southwestern Washington probably will not result in meaningful impacts on the owl 

population on the peninsula. Even the generation of connecting reserves, which 

required the development of 150 000 hectares (370,700 acres) of high-quality habitat, 

had little impact. 

This discussion was limited to the role of corridors connecting reserves separated 

by large distances. The results do not imply that dispersal habitat in the intervening 

areas between more closely spaced reserves is unimportant. 

2. What is the likelihood of maintaining a stable, well-distributed population of 

spotted owls on Federal lands on the Olympic Peninsula, for at least 100 years, 

with no non-Federal habitat contribution? 

We concluded that it is likely, but not assured, that a stable population would be 

maintained on portions of the Olympic National Forest and the core area of the 

National Park in the absence of any non-Federal contribution of habitat. The lack 

of non-Federal habitat would make it unlikely that an owl population would be 

maintained on the western coastal strip of the National Park, and this could result 

in fewer high-occupancy or core areas on the remaining Federal land. 

Despite generally positive results observed in this analysis, there is significant 

uncertainty in interpreting demographic results; in variability observed in simulations 

under different assumptions; and in the effect of eliminating up to 64 600 hectares 

(159,700 acres) of suitable habitat on non-Federal land. There also is uncertainty 

associated with the increase in the barred owl population and resulting competition 

and hybridization with spotted owls. Our confidence in maintaining a stable population on the peninsula would improve if the uncertainties in knowledge were 

resolved and indicated a favorable outcome, or the conditions on the peninsula 

became significantly more robust given these uncertainties. 
58 

This conclusion was predicated on standards and guidelines for spotted owl habitat 

management contained in the Northwest Forest Plan (USDA and USDI 1994). We 

agreed on the following points in reaching this conclusion: 

• Assuming that other demographic values estimated on the peninsula do not 

contain significant bias, a juvenile survival rate of 0.422 would yield a stable 

population with a rate of population change of 1.0. The survival rate of 0.422 

falls within the range of estimates (0.24 to 0.61) calculated for the population 

on the peninsula. 

• Habitat on Federal lands is relatively stable and no significant harvest of habitat 

is expected. 

• Even a worst-case fire is projected to have little long-term effect on population 

stability. 

• Regrowth of habitat on the Olympic National Forest will likely provide significant 

benefit to the spotted owl population through time. 

• The increase in the barred owl population could have potentially serious effects 

on the spotted owl population, and such effects are not represented in modeling 

efforts. 

3. To what extent would the contribution of non-Federal habitat change the likelihood 

of maintaining a well-distributed and stable population on the Olympic Peninsula? 

We concluded that the retention of non-Federal habitat could result in a biologically 

significant contribution to the maintenance of a stable population of spotted owls 

distributed across currently occupied portions of the Olympic Peninsula. Our conclusion was based mainly on the results of simulations. The simulations consistently showed increases in the numbers of pairs of owls maintained over time and 

the rate of occupancy of owl territories on Federal lands when non-Federal habitat 

was retained. When all possible non-Federal habitat was retained in addition to the 

Federal habitat, the number of pairs maintained over 100 years increased about 

24 percent. When only habitat associated with the take guideline was added, the 

increase was close to 14 percent. Retention of non-Federal habitat in the west SEA 

would be particularly significant as this area contains the greatest concentration of 

habitat remaining on non-Federal land. The retention of this habitat likely would 

increase the chances of maintaining a population on the coastal strip of the Olympic 

National Park. Such an effect was not, however, observable in the model runs. NonFederal lands may provide the majority of low-elevation habitat, which is poorly 

represented on Federal lands and might be of superior quality compared to higher 

elevation habitat. 

Although we concluded that retention of non-Federal habitat would significantly 

improve the projected status of the population, we do not believe that it would fully 

resolve the uncertainties associated with the future of spotted owls on the Olympic 

Peninsula. Although the retention of non-Federal habitat could be significant, we did 

not conclude that it would alter the basic uncertainties enough to assure the maintenance of a population distributed across the portions of the peninsula currently 

occupied by owls. 
59 

Recommendations 

We caution that these conclusions should not be extrapolated to other portions of 

the range of the northern spotted owl. Each portion of the range represents a different situation and different relationship between Federal and non-Federal lands. 

The Olympic Peninsula is unique because of the large block of relatively unfragmented habitat in the Olympic National Park, the relative isolation of the Olympic 

population from owls in the rest of the range, and significant areas of non-Federal 

habitat occurring adjacent to the Federal late-successional reserve. Thus, the insights 

gained from this analysis are specific to the peninsula. We also emphasize that this 

assessment focused only on spotted owls and their habitat; it does not address 

effects on other species for which there are legal, social, or biological concerns. 

We believe that, in the interaction between science and policy, the appropriate role 

for scientists is to provide analyses that can be used to formulate policy. Therefore, 

we do not offer recommendations concerning the difficult issue of non-Federal roles 

under the ESA. We do offer the following recommendations for strengthening the 

scientific base that can be used in formulating policy for spotted owl management. 

First, we recommend that the techniques used in this analysis be applied more 

broadly throughout the owl's range as plans for owls continue to be implemented 

and refined. Although the results are not definitive, they help clarify the relative roles 

that could be played by Federal and non-Federal lands in maintaining spotted owl 

populations. The simulations done for this analysis provided a way to consistently 

test hypotheses about owl populations and their relationship to habitat management. 

The results of these simulations should not be accepted without critical evaluation, 

but they improve our ability to objectively analyze questions about the value of 

habitat connections between the Olympic Peninsula and other portions of the owl's 

range. 

One of the prerequisites for such analyses is the availability of reliable habitat information for both Federal and non-Federal lands. Data currently are unavailable for 

large portions of non-Federal lands, and the quality of data available for Federal 

lands could be improved. For example, we found that the current designation of 

nesting, roosting, and foraging habitat on the Olympic National Park underrepresents such habitat, especially in the eastern subprovince. This designation, which 

was originally developed by the Northern Spotted Owl Recovery Team, should be 

reassessed in light of our findings. One significant step toward the improvement of 

habitat data would be acceleration of efforts to understand the influence of different 

stand characteristics on the use of those stands by owls. Such research has long 

been recognized as a high priority (USDA 1988), but the amount of information 

available is still meager. 

A second step that would improve habitat data is the development of better databases 

for both habitat and owl locations for non-Federal land. We were fortunate in this 

analysis to have a habitat database developed by the WDFW and WDNR, but such 

data are not available for the entire range of the owl. Additional cooperative efforts 

between the states and the Federal government could help generate this information. 

Participation by private landowners in such efforts would greatly improve the reliability 

of the results. 
References 

60 

Acknowledgments 

This analysis also emphasized the need to continue monitoring owl populations, 

including their genetic variability, and to continue demographic studies as part of 

that monitoring. Uncertainty still exists concerning trends in owl populations and 

the influence of immigration and emigration, among other factors, on demographic 

estimates. Understanding of these issues can be improved only with additional 

years of data and with additional radio-tracking of owls in those studies. 

This analysis has reinforced the need to better understand how owls use their home 

ranges and the influence of both stand and home range characteristics on their 

reproduction and survival. The relationship between home range estimates and 

density estimates for owls on the peninsula is not straightforward, and additional 

collection of home range data from areas where densities are being estimated is 

needed. Better understanding of the relationships among habitat quality in home 

ranges, size of home ranges, and demographic performance is critical to improve 

our ability to manage habitats for owls. 

We thank the U.S. Fish and Wildlife Service for its support of this effort; Barry Mulder 

served as liaison. Salary and administrative assistance was provided by the Pacific 

Northwest and Pacific Southwest Research Stations, the National Biological Service, 

and the National Forest System. This analysis was also supported by the Washington 

Forest Landscape Management Project. We especially thank Beth Galleher for her 

painstakingly thorough efforts and sleepless nights in conducting GIS and other 

analytic operations. Graphics were produced at the Olympia Forestry Sciences 

Laboratory. Steve Holzman, Andy Wilson, and Steve Miller provided digital vegetation 

maps. Jeff Neighbert provided the relief map of the Olympic Peninsula. John Young 

and Patrick Wratchford gave additional GIS support and data analysis. Constance 

Harrington and Dave Peter provided advice on vegetation succession. Linda Kucera 

facilitated our meetings, provided administrative assistance, and contributed significantly to the preparation of the draft and final documents. Jill Carroll and Janet Jones 

provided careful edits of earlier versions of the manuscript. Karen Esterholdt and Del 

Thompson facilitated production of the manuscript and the cover design. E. Charles 

Meslow was instrumental in organizing our initial work and contributed to discussion 

of our approach. We thank David Hays, Ann Potter, James Agee, Russell Lande, 

Gary White, Tim Young, Richard Miller, and Michael Lynch for additional discussion 

or informal review comments. We thank Janet Jones for preparing the final draft of 

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Appendix 1: 

Reanalysis Team 

Charter 

Background 

Purpose: To determine the extent to which non-Federal lands contribute to and 

may be necessary for the conservation of the northern spotted owl on the Olympic 

Peninsula. 

The Reanalysis Team (Team) has been established to provide an analysis of the 

potential for and pattern of long-term persistence of the northern spotted owl on 

the Olympic Peninsula with varying levels of habitat contributions from non-Federal 

lands. Federal lands under the preferred alternative (Alternative 9) in the Final 

Supplemental Environmental Impact Statement on Management of Habitat for 

Late-Successional and Old-Growth Forest Related Species within the Range 

of the Northern Spotted Owl (FSEIS) and the non-Federal lands for which firm 

Habitat Conservation Plan (HCP) commitments have been made (for example, 

the Washington State Experimental Forest) will be included as the principal 

baseline for analysis. 

This assessment will provide additional information to support the development 

of regulations and policies affecting non-Federal forest management for the 

Olympic Peninsula, under section 4(d) and section 10 of the Endangered 

Species Act. Beyond this effort, we do not anticipate further involvement of 

the Team in the 4(d) effort. If a need arises for any additional efforts, however, 

they will be negotiated with individual members of the Team. 

At the time the President announced Alternative 9 as the basis for the then proposed Forest Plan, he also announced that the Administration would seek to 

ease the burden on non-Federal landowners through a 4(d) rule. The content 

and schedule for a 4(d) rule are receiving higher priority now that the President's 

Forest Plan for Federal lands has been completed and the injunctions have been 

dissolved. It remains Federal policy to rely primarily on contributions from Federal 

lands for the conservation of the northern spotted owl, and to rely on non-Federal 

lands only to the extent that they are believed to be necessary to supplement 

Federal contributions in order to achieve conservation goals. 

The unpublished Final Draft Recovery Plan for the Northern Spotted Owl (Final 

Draft Recovery Plan) provides recent guidance on the contributions needed 

from non-Federal lands; however, several developments have occurred since 

its completion that could change the contribution needed from non-Federal lands. 

One such development is the adoption of a new Federal lands late-successional, 

old-growth forest ecosystem management strategy. The new Federal strategy 

establishes reserves and management guidelines for Federal lands on the Olympic 

Peninsula that will provide nesting, roosting, and foraging habitat for the owl and 

meet the habitat requirements of numerous other species. The overall change in 

Federal management strategy on the Olympic Peninsula between the Final Draft 

Recovery Plan and Alternative 9 in the FSEIS is the increased Federal protection 

for the owl. In particular, the strength of the Federal land reserve system and 

the Adaptive Management Area, and the associated management guidelines 

in Alternative 9, may have important implications for the role of non-Federal 

landowners. 

65 
66 

Tasks To Be Performed 

Recent modeling work, carried out principally by Martin Raphael and Kevin McKelvey 

(Raphael and others 1994) served as one mechanism to compare Alternatives 1, 7, 

and 9 in the FSEIS-given a variety of assumptions. The model provides a good 

tool to address and simulate critical population size, but only in a relative sense. 

One cannot estimate absolute risk by using the model, but the model can be used 

to estimate the relative contribution from specific areas to the overall efficacy of 

management across ownership boundaries. The model, therefore, can provide a 

logical framework to evaluate the potential contributions associated with spotted 

owl habitat on non-Federal lands on the Olympic Peninsula. 

The Team should perform the following tasks: 

Task 1. Review the Forest Plan, FSEIS, and Record of Decision to develop an 

understanding of the habitat conditions that exist and are expected to develop on 

Federal lands. For purposes of this analysis, Alternative 9 is assumed to be the 

Federal contribution to recovery. 

Task 2. Review existing data and existing and new model output to assess the 

likelihood and pattern of persistence of the owl population on the Olympic Peninsula, 

given Alternative 9, including appropriate non-Federal lands as part of the principal 

baseline as discussed above. Assess how that persistence and its pattern would be 

changed by varying levels of contribution from non-Federal land, recognizing the 

limitations of current statutory authority regarding take prohibitions and the voluntary 

nature of HCPs. Where practicable, the following issues should be investigated and 

discussed: 

a. Ranges and effects of regrowth of habitat.

b. Possible ranges and effects of catastrophic events.

c. Ranges and effects of elevational gradients in suitability of habitat.

d. Benefits derived from various levels of contributions from non-Federal land.

e. Possible ranges and effects of birth and survival rates keying off those values 

used in previous published model runs to the extent possible.

f. Possible ranges and effects of dispersal rates.

g. Possible ranges and effects of connectivity to other provinces on persistence of

owls on the Olympic Peninsula. Where gaps in owl distribution between the Olympic 

Peninsula population and other populations occur now, or are anticipated in the 

future, the significance of the gap should be addressed relative to the persistence 

of the owl on either side of the gap.

h. Possible ranges and effects of genetic issues, including hybridization with the 

barred owl.

i. Possible ranges and effects of time periods.

Task 3. Prepare a draft report documenting the Team's review, indicating the degree 

of consensus of the Team regarding the conservation value from non-Federal lands 

and noting any significant dissent within the Team from that consensus.

Task 4. Work with appropriate staff in the Region 1 Regional Office [USDI Fish and 

Wildlife Service] to execute peer review.
Appendix 2: 

Additional Model 

Parameters 

Task 5. Revise the Team Report as appropriate to reflect peer review comments 

and submit it to the Regional Director by October 17, 1994. Meeting this deadline 

is contingent upon no major new analyses arising from the peer review process. 

For simulating owl dynamics on the peninsula, the rule sets that we constructed 

differed primarily in the assumed response of the population to changes in habitat 

quality. The relationships between vital rates and habitat quality were of primary 

concern because the potential land management rules (scenarios) that we postulated 

were defined by the retention and growth of suitable owl habitat. Here we describe 

varied other parameters listed in table 11 that are necessary to drive the model but 

that we did not change across runs. Additional discussion of these parameters can 

be found in McKelvey and others (1992) and McKelvey and others (in rev.). 

Fledge number, male probability of fledging-These two parameters determine 

the number of birds born and the sex ratio of those birds. The values used in these 

simulations cause the young to be born in groups of two and with a 1:1 sex ratio. 

Nesting OK-This parameter controls nest-site selectivity. When a dispersing male 

searches an unoccupied site it must make a decision to either become territorial or 

continue searching. The parameter values are the probability that a site of a given 

quality will be chosen. The parameters used in these simulations were developed to 

match observed relationships between density and habitat1

 (Bart and Forsman 1992). 

Aversion--This parameter controls the probability that a dispersing bird enters an 

adjacent cell of a given quality. It is assumed that owls will preferentially choose to 

enter high-quality habitat and the parameters used cause dispersers to be twice as 

likely to enter high-quality habitat as low-quality habitat. 

Probability that a female finds a male-If a nonterritorial female enters a site 

occupied by a territorial male, she obligately becomes territorial. This parameter 

sets the likelihood that she locates a territorial male in an adjacent cell before 

entering it. If she locates a male, she obligately moves to that site and pairs with 

the male. 

Male territorial aversion-It is assumed that a dispersing male will preferentially 

choose to enter unoccupied rather than occupied habitat if the quality is similar. 

Given the value presented, a dispersing male is twice as likely to move into 

unoccupied habitat. 

Directional weighting-Large values for this parameter cause an organism to move 

in a consistent direction. A value of 1.0 produces a random walk. The value we used 

causes a dispersing owl to move forward with twice the probability of moving in an 

alternate direction. 

Wanderlust At each move, an owl can either move in one of six possible directions 

or remain stationary. The values we used cause owls to never remain stationary in 

the poorest quality habitat. 

1 Personal communication. 1994. J. Bart. Cooperative Wildlife 

Research Unit, Ohio State University, 1735 Neil Ave., Columbus, 

OH 43210.

67 
68 

Boundary condition-Three global boundary conditions can be specified: absorbing, 

reflecting, and wrap-around. In addition, internal boundaries can be created by declaring cell types that have no chance of survival (and thus "absorb" the owl) or create 

total aversion (and thus "reflect" the owl). For modeling landscapes, combinations of 

these global and internal boundaries can be used to create reasonable boundary conditions. In the maps presented in this document, the southern map boundary was 

absorbing, and boundaries that represented the ocean were reflecting. Because 

dispersers can be expected to continue south beyond the map boundary, and 

because few owls from southwest Washington will be entering the map area due 

to the low numbers in this area, an absorbing boundary is the most reasonable 

choice for the southern boundary. 

Delta-t-This value is the number of habitat cells that an organism can search in 

a year. Sensitivity analyses (McKelvey and others, in rev.) and analytical models 

(Carroll and Lamberson 1993; Noon and McKelvey, in prep.) show that for organisms 

displaying the life history attributes of spotted owls, very little is gained in search 

effectiveness by searching more than 20 cells per year. 
Holthausen, Richard S.; Raphael, Martin G.; McKelvey, Kevin S.; Forsman,

Eric D.; Starkey, Edward E.; Seaman, D. Erran. 1995. The contribution of 

Federal and non-Federal habitat to persistence of the northern spotted owl on 

the Olympic Peninsula, Washington: report of the Reanalysis Team. Gen. Tech. 

Rep. PNW-GTR-352. Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station. 68 p. 

This report describes likely patterns of distribution and persistence of owls on the 

Olympic Peninsula under the provisions of the Federal Forest Plan, benefits to the 

owl population of varying levels of habitat contribution from non-Federal lands, and 

possible effects of establishing habitat connections between the Olympic Peninsula 

and other parts of the owl's range. Updated information about spotted owl habitat, 

population status, and birth and survival rates for the Olympic Peninsula were 

summarized, and much of the analysis focused on simulations of spotted owl 

populations under alternative scenaries. 

Keywords: Northern spotted owl, spatial model habitat, simulation model, land 

management, conservation. 

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