Status and Trends of Northern Spotted 

Owl Habitats

Raymond J. Davis, Bruce Hollen, Jeremy Hobson, Julia E. Gower, and David Keenum

United States Department of Agriculture

Forest 

Service

Pacific Northwest

Research Station

General Technical Report

PNW-GTR-929

NORTHWEST

FOREST PLAN

The First20 Years (1994–2013)

March

2016
Authors

Raymond J. Davis is the monitoring leader for old forests and northern spotted 

owls for the Northwest Forest Plan Interagency Monitoring Program, U.S. 

Department of Agriculture, Forest Service, Pacific Northwest Region, 3200 SW 

Jefferson Way, Corvallis, OR 97331; Bruce Hollen is the state wildlife biologist, 

U.S. Department of the Interior, Bureau of Land Management, Oregon State 

Office, 1220 SW 3rd Avenue, Portland, OR 97204; Jeremy Hobson, Julia E. 

Gower, and David Keenum are geographic information system/data services 

analysts, U.S. Department of Agriculture, Forest Service, Pacific Northwest 

Region, Data Resources Management, 1220 SW 3rd, Portland, OR 97204.

Cover Photo: Spotted owl by Jason Mowdy.

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Abstract

Davis, Raymond J.; Hollen, Bruce; Hobson, Jeremy; Gower, Julia E.; Keenum, 

David. 2016. Northwest Forest Plan—the first 20 years (1994–2013): status 

and trends of northern spotted owl habitats. Gen. Tech. Rep. PNW-GTR-929. 

Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest 

Research Station. 54 p.

This is the third in a series of periodic monitoring reports on northern spotted owl 

(Strix occidentalis caurina) habitat status and trends on federally administered 

lands since implementation of the Northwest Forest Plan (NWFP) in 1994. The 

objective of this monitoring is to determine if the NWFP is providing for conservation and management of northern spotted owl (NSO) habitat as anticipated. This 

report focused on the amount, distribution, and spatial arrangement of NSO habitats 

across the NWFP area; and how these have changed as a result of disturbance and 

ingrowth starting with the year of the NWFP analyses in 1993. Results showed a 

net decrease from 9,089,700 ac to 8,954,000 ac (-1.5 percent) of nesting/roosting 

habitat on NWFP federal lands. This occurred despite gross losses from wildfire 

of 5.2 percent (474,300 ac), 1.3 percent from timber harvest (116,100 ac), and 0.7 

percent from insects or other causes (59,800 ac), indicating that processes of forest 

succession have compensated for some of the losses resulting from disturbance. 

Dispersal habitat on NWFP federal lands increased by 2.2 percent (net change), but 

dispersal-capable landscapes experienced a 5 percent net decrease owing to habitat 

losses on the surrounding nonfederal lands. Large wildfires continue to be the leading cause for loss of NSO habitat on federal lands. Most of these losses occurred 

within the network of large reserves designed for NSO conservation.

Keywords: Northwest Forest Plan, effectiveness monitoring, northern spotted 

owl, MaxEnt, owl habitat, habitat suitability.
Preface

Northern spotted owl (Strix occidentalis caurina) monitoring of the Northwest 

Forest Plan area was approved by an intergovernmental advisory committee and is 

consistent with the framework for effectiveness monitoring described in “The Strategy and Design of the Effectiveness Monitoring Program for the Northwest Forest 

Plan” published in 1999. It follows protocols and guidance in the “Northern Spotted 

Owl Effectiveness Monitoring Plan for the Northwest Forest Plan” published in 

1999. An interagency effectiveness monitoring framework was implemented to 

meet requirements for tracking the status and trends of older forests, populations 

and habitats of northern spotted owls and marbled murrelets (Brachyramphus marmoratus), watershed conditions, social and economic conditions, and tribal relationships. Monitoring is conducted and reported in 1- to 5-year intervals. Monitoring 

results for the first 10 and 15 years were documented in a series of general technical 

reports available online at http://www.fs.fed.us/pnw/publications/gtrs.shtml. This 

report, and the others in the current series, covers the first 20 years of the plan.
Contents

1 Introduction

2 Habitat Monitoring Under the NWFP

4 Data Sources and Methods

4 Physiographic Provinces

4 Land Use Allocations

6 Forest-Capable Area

6 LandTrendr Maps

6 Gradient Nearest Neighbor Maps

7 Northern Spotted Owl Presence Data 

7 Habitat Modeling and Mapping

7 Nesting/Roosting Habitat

11 Dispersal Habitat

11 Habitat Assessments

11 Bookend Analysis

12 Habitat Fragmentation

12 Dispersal-Capable Landscape

13 Results

13 Habitat Modeling and Mapping

23 Habitat Assessments

23 Nesting/Roosting Habitat

24 Habitat Fragmentation

27 Habitat Dispersal

34 Discussion

38 Geographic Pattern of Large Wildfires

38 Habitat and Demographic Trends

41 Uncertainty in Habitat Monitoring

42 Conclusion

43 Acknowledgments

44 Metric Equivalents

44 References

51 Appendix: Habitat Suitability Histograms
For more than two decades, the northern spotted owl 

monitoring program has been following the life histories of 

hundreds of banded northern spotted owls throughout their 

geographic range in the Pacific Northwest forests of the 

United States (left). This is a brief accounting of one of those 

owls that spent her entire life in the coastal forests near Coos 

Bay Oregon. 

She was hatched in 1987 at an owl territory 

known as the Old Blue site. She was one of 

two fledglings. Eventually she dispersed 

from her natal site to establish a territory 

of her own in 1990, traveling almost five

miles to the northwest. That same year she 

fledged two owlets with the first of five males 

she would eventually mate with. Two years later 

she moved about 2.5 miles to the Little Camp Creek 

site (below) and fledged two more young with her 

second mate. There she paired with her third mate in 1993 

and for the next 11 years these two owls fledged several more young 

at this site. In 1995 she briefly moved to Otter Creek with her fourth 

mate, a 1.5 mile move, but returned the following year. 

Her final location at age 21 was in the Upper Hound Creek site in 2008, where 

she had paired with her fifth mate. After traveling over 16 miles linear distance 

between five territories, her last known location was about a mile from where 

she was fledged. We collected data from 17 years of her life and she 

contributed to the population with at least 8 owls fledged. 

Photo by 

Jason Mowdy
1

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

Introduction

It has been slightly more than two decades since implementation of the Northwest 

Forest Plan (hereafter referred to as “NWFP”). The NWFP amended 19 existing 

Forest Service and 7 Bureau of Land Management resource management plans 

across three states and two Forest Service regions within the range of the northern 

spotted owl (Strix occidentalis caurina). An interagency effectiveness monitoring 

framework was implemented in the late 1990s to meet NWFP requirements for 

tracking the status and trends of late-successional and old-growth forests, northern 

spotted owl (hereafter referred to as “NSO”) populations and habitat, marbled 

murrelet (Brachyramphus marmoratus) populations and habitat, watershed condition, social and economic conditions, and tribal relationships (Mulder et al. 1999). 

Beginning in 2005, monitoring reports have been published at 5-year intervals and 

made available at http://www.reo.gov/monitoring/. 

This report is the third in the series of NSO monitoring reports outlined by an 

interagency effectiveness monitoring plan (Lint et al. 1999) and covers the time 

period from 1993 to 2012. The goal of NSO monitoring is to periodically evaluate 

the success of the NWFP in arresting downward trends in NSO populations and in 

maintaining and restoring habitat necessary to support viable NSO populations on 

federally administered forest lands throughout its range. Specific objectives are to:

1. Assess changes in NSO population trends and demographic rates on 

federal lands within its geographic range in the United States; and

2. Assess changes in the amount and distribution of NSO habitat on 

federal lands.

While the first two monitoring reports (Davis et al. 2011, Lint 2005) included 

chapters addressing both objectives, this report focused only on the second objective (habitat status and trends). Status and trends of population and demographic 

rates were concurrently covered in a refereed science journal (Dugger et al. 2016.) 

to eliminate redundancy and to be more cost effective.

Each round of monitoring used new and improved data. While this improved 

the overall quality of the information provided, it also means that individual reports 

should not be compared directly without fully understanding the processes used 

to develop the results. Although we used new data, we mainly followed methods 

described in the second monitoring report (Davis et al. 2011). For efficiency and 

to avoid repetitiveness, we summarized methods that did not change and only 

discussed changes in data or analytical techniques made between the 15-year report 

and this 20-year report.
2

GENERAL TECHNICAL REPORT PNW-GTR-929

As in previous reports, we summarized an assessment of NSO habitat for the 

22.1 million acres of federally administered forest lands affected by the NWFP, 

but also included information on the surrounding 23.8 million acres of nonfederal 

forest lands to provide a broader landscape context across the 57 million acres that 

comprise the NSOs geographic range in the United States.

Habitat Monitoring Under the NWFP

Habitat status and trends are estimated every 5 years because it was believed that 

changes in forest vegetation conditions would not be reliably discernable at more 

frequent intervals using the Landsat remote sensed vegetation data that this broadscale monitoring relies upon (Lint et al. 1999). 

The intent of habitat effectiveness monitoring is to evaluate assumptions 

made during development of the NWFP. In particular, the assumption that habitat 

would not decline faster than the estimated 5 percent per decade (from wildfire and 

timber harvesting combined) in the NWFP’s final environmental impact statement 

(USDA and USDI 1994). Specific habitat assumptions from Lint et al. (1999) were 

as follows:

1. Habitat conditions within late-successional reserves (LSRs) would improve 

over time at a rate controlled by successional processes in stands that currently are not habitat. However, this was not expected to produce any significant changes in habitat conditions for several decades.

2. Habitat conditions outside of reserved land use allocations (LUAs) would 

generally decline because of timber harvest and other habitat-altering disturbances, but the vegetation structure across the landscape would continue 

to facilitate NSO movements.

3. Catastrophic events were expected to halt or reverse the trend of habitat 

improvement in some reserves; however, the repetitive design of reserves 

would provide resiliency, and not result in isolation of population segments.

The rangewide network of reserved federal lands that was designed to support 

well-distributed and connected populations of reproducing NSO pairs is central to 

these assumptions. But, also important is the land between these reserves because 

it provides for recruitment of NSOs into the territorial populations within reserves 

(see chapter 2 in Davis et al. 2011) and dispersal and movement of NSOs between 

larger reserves. To assess these assumptions, the following questions are addressed 

in habitat monitoring:

1. What proportion of the total forested landscape on federal lands are NSO 

nesting/roosting and dispersal habitat?
3

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

2. What are the trends in amount and changes in distribution of NSO habitat, 

particularly in large, reserved blocks?

3. What are the trends in amount and distribution of dispersal habitat outside 

of the large, reserved blocks?

4. What are the primary factors leading to loss and fragmentation of NSO 

nesting/roosting and dispersal habitat?

We evaluate these questions at three broad geographic scales: (1) by physiographic province, (2) by state, and (3) for the geographic range of the NSO. Within 

these spatial extents, we assess habitat conditions inside broad federal LUAs 

representing “reserved” and “nonreserved” landscapes. 

As in previous monitoring reports, to answer these questions we produced time 

series maps of forest stands (regardless of patch size and spatial configuration) that 

are structurally and compositionally similar to forest conditions known to be used 

for nesting and roosting by NSOs. We referred to these maps as “nesting/roosting habitat” maps throughout this document. We also produced maps of dispersal 

habitat based on the definition used in Thomas et al. (1990). We developed these 

habitat maps for the baseline year (1993) that matches the year that the NWFP was 

designed and for the end of this monitoring cycle (2012). We referred to the time 

period maps as “bookend” maps, and the differences between them were used to 

assess habitat status and trends. 

At the time the habitat monitoring plan was designed and written (Lint et al. 

1999), barred owls (Strix varia) were already present within the NWFP area, but at 

low levels (rangewide, <10 percent of monitored territories). The habitat monitoring 

design did not factor in the potential effect that the barred owl (hereafter referred to 

as “BO”) might have on NSO habitat selection. However, this effect was considered 

in the previous two monitoring reports, as well as this one. In Lint (2005), the decision to use “presence-only” modeling methods was based partially on the potential 

to get “false absence” data owing to NSO displacement by BOs. In other words, 

NSOs might be absent from a stand with highly suitable forest structure and species 

composition solely due to presence of BOs. Likewise, habitat modeling was done 

using NSO presence data from early in the BO invasion to minimize the potential 

effects of interspecific competition between NSOs and BOs that could potentially 

confound NSO habitat selection and use (Davis et al. 2011). In this report, we used 

NSO presence data from 1993 to develop our habitat models.
4

GENERAL TECHNICAL REPORT PNW-GTR-929

Data Sources and Methods

Many, but not all, of the data sources used in this report were initially developed 

and used for the 10- and 15-year monitoring reports (Davis et al. 2011; Lint 2005; 

Moeur et al. 2005, 2011). During each 5-year monitoring cycle, previously used data 

sources are occasionally updated to incorporate new research findings and other 

information, or to correct errors. More indepth descriptions of these data sources 

can be found in previous monitoring reports.

Physiographic Provinces

The NWFP boundary was based on the geographic range of the NSO in the United 

States. Because the range was so large, it was divided into 12 physiographic provinces for analytical purposes (FEMAT 1993, Thomas et al. 1990, USDA and USDI 

1994). Physiographic provinces were delineated in an attempt to reduce the complex 

and diverse nature of the NSO range into broad areas that represented different 

forest zones, plant communities, and disturbance regimes that differ geographically 

with climate, topography, soils, and geology. These physiographic provinces were 

largely based on subdivisions by Franklin and Dyrness (1973). We used the same 

physiographic province geographic information system (GIS) layer that was used 

for the 15-year monitoring report (Davis et al. 2011). 

Land Use Allocations

Federal LUAs have specific management directions under the NWFP. This 

report groups LUAs into two broad categories: (1) reserved and (2) nonreserved. 

Reserved allocations are areas where the restoration and maintenance of older 

forests are expected to occur under the current land use plans. They included the 

following LUAs:

• Congressionally reserved areas: Lands reserved by the U.S. Congress 

such as wilderness areas, wild and scenic rivers, and national parks 

and monuments.

• Late-successional reserves: Lands reserved for the protection and restoration of late-successional and old-growth forest ecosystems and habitat for 

associated species; including marbled murrelet reserves and NSO activity 

core reserves.

• Managed late-successional areas: Areas for the restoration and maintenance of optimum levels of late-successional and old-growth stands on a 

landscape scale, where regular and frequent wildfires occur. Silvicultural 

and fire hazard reduction treatments are allowed to help prevent older forest 

losses from large wildfires or disease and insect epidemics.
5

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

• Administratively withdrawn areas: Areas identified in local forest and 

district plans; they include recreation and visual areas, back country, 

and other areas where management emphasis does not include scheduled 

timber harvest.

• Adaptive management area—reserved: Identified to develop and test innovative management to integrate and achieve ecological, economic, and 

other social and community objectives. Emphasis on restoration of late-successional forests and managed as an LSR.

Nonreserved LUAs were designed for multiple land use objectives including 

sustained-yield management for timber production. They included:

• Matrix: Federal lands outside of reserved allocations where most timber 

harvest and silvicultural activities were expected to occur.

• Adaptive management area—nonreserved: Identified to develop and test 

innovative management to integrate and achieve ecological, economic, and 

other social and community objectives. Some commercial timber harvested 

was expected to occur in these areas, but with ecological objectives.

The GIS layer representing these LUAs was originally delineated during the 

analysis for the NWFP (USDA and USDI 1994). The LUA-GIS layer has since been 

updated three times. Each update was done prior to a monitoring cycle, including 

this one. Previous updates were described in the 10- and 15-year monitoring reports 

(Davis et al. 2011, Lint 2005). The latest update for this report mainly involved 

the addition of congressionally reserved allocations (364,000 ac) as a result of a 

few new wilderness designations since the 15-year report. Other updates included 

land exchanges and acquisitions as well as minor editing to correct errors and 

clean map features. About 71,000 ac remained without assigned allocations. We 

attributed these areas as “no data” (ND), which represented about 0.1 percent of 

the total federal area and were reported as nonreserved in this report. Since NWFP 

implementation, LUA updates indicate a slight overall increase in federal lands (1.5 

percent) with a 0.4 percent increase in reserved LUAs.

As in previous monitoring reports, riparian reserves (another NWFP-LUA consisting of protected strips along the banks of rivers, streams, lakes, and wetlands) 

were not delineated because of a lack of consistency in defining and delineating the 

stream network at the NWFP scale and varying site-specific definitions (Moeur et 

al. 2005). Riparian reserves were also subject to change over time based on results 

of watershed analysis (FEMAT 1994). Rangewide, riparian reserves were estimated 

to cover about 32 percent of the nonreserved matrix and AMA LUAs (USDA and 

USDI 1994). Thus, our estimates for reserved federal lands are biased low, and federal nonreserved estimates are biased higher than they would be if riparian reserves 

were accounted for.
6

GENERAL TECHNICAL REPORT PNW-GTR-929

Forest-Capable Area

Areas capable of developing into forests were delineated using a 30- by 30-m (0.22-

ac) resolution GIS raster map covering the NWFP area. This map was developed 

for the 15-year monitoring report (Davis et al. 2011) and was not updated for this 

report. We used this map to “mask out” (ignore for analytical purposes) nonforested 

areas for each time-period map. Area estimates and other analyses in this report 

only apply to forest-capable areas.

LandTrendr Maps

LandTrendr maps are remotely sensed (Landsat TM) forest vegetation change 

detection maps that identified where, when, how much, and how long disturbance 

had occurred between 1993 and 2012 (Davis et al. 2015). They were developed 

following methods in Kennedy et al. (2010, 2012) and verified for accuracy using 

the TimeSync method (Cohen et al. 2010). These maps represent three aspects of 

vegetation change: (1) year of disturbance, (2) magnitude of disturbance, and (3) 

duration of disturbance. We classified these three maps to produce a single map 

of where timber harvesting, wildfire, insect and disease, and other natural disturbances (e.g., blowdown, floods, landslides, etc.) have occurred between 1993 and 

2012 (app. D in Davis et al. 2015). Where this map overlapped losses of habitat, it 

helped to explain the causes for habitat loss during the 20 years since the NWFP’s 

implementation. 

Gradient Nearest Neighbor Maps

We used Gradient Nearest Neighbor (GNN) maps of forest structure and species 

composition (Ohmann and Gregory 2002) on forest-capable lands from two different dates, 1993 and 2012. We developed these GNN maps specifically for NWFP 

monitoring. Earlier versions of these GNN maps have also been used for the 15-year 

monitoring reports (Davis et al. 2011, Moeur et al. 2011, Raphael et al. 2011) and 

other broad-scale vegetation analyses across a wide range of forest ecosystems for 

multiple objectives (Ohmann et al. 2007, 2011, 2012; USDI FWS 2011). Along with 

each map, a large suite of diagnostics detailing model reliability and map accuracy 

were provided (app. E in Davis et al. 2015).

For both the 15- and 20-year reports, the GNN maps were developed 

using Landsat TM time-series data that were temporally normalized using the 

LandTrendr algorithm (Kennedy et al. 2010, 2012). The LandTrendr methodology 

removed superfluous signals (noise) in the satellite imagery, captured real trajectories of change through time, and improved consistency of GNN maps across years. 

This allowed us to better separate real changes in forest structure and composition 
7

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

from false changes owing to satellite imagery differences. For the 20-year report 

maps, we made several other incremental improvements to our data and methods 

that are summarized in Davis et al. (2015). From these GNN products, we used the 

same forest structure and species composition maps as environmental response 

variables in our habitat modeling (table 1).

Northern Spotted Owl Presence Data 

Northern spotted owl pair nesting/roosting location data were needed to train and 

test the habitat models described below. Demographic study areas provided survey 

data collected annually for population monitoring. We used the most biologically 

important pair location based on the following hierarchical ranking: (1) active nest, 

(2) fledged young, (3) primary roost location, (4) diurnal location, and (5) nocturnal 

detection from 1993. To address sampling bias in relationship to the larger modeling region background (Fourcade et al. 2014, Phillips et al. 2009), we reduced the 

geographically clumped nature of these data by using only one location per NSO 

territory. We then filled in the modeling region spaces between demographic study 

areas with NSO pair presence data compiled for the 10-year monitoring report 

(Lint 2005). These supplemental locations were geographically thinned out and 

spaced using nearest-neighbor distances to randomly select a subset of these points 

(as described in Davis et al. 2011, pg. 30 and app. B). We did not limit the number 

of random supplemental locations to match the sample size from the demographic 

study area. Instead, we used all available location data from the 10-year monitoring 

report (Lint 2005) that occurred between our study areas. This produced a better 

spatial (less clumped) distribution of NSO locations throughout each modeling 

region. All locations were compiled and checked for spatial accuracy.

Habitat Modeling and Mapping

Nesting/Roosting Habitat

Methods used for modeling and making rangewide maps of NSO nesting/roosting habitat have evolved to stay abreast of the science and technology of species 

distribution modeling (SDM). Given the nature of rangewide NSO location data, 

presence-only SDM was determined to be the most feasible method for producing 

rangewide models and maps. Biomapper software (Hirzel et al. 2002, 2004) was 

used for the 10-year report (Lint 2005). For the 15-year monitoring report, we tested 

Biomapper with the newly developed MaxEnt software (Phillips et al. 2006, Phillips and Dudík 2008). MaxEnt outperformed Biomapper and was thus used for that 

reporting cycle (Davis et al. 2011). MaxEnt is now the most widely used software 

for conducting presence-only SDM (Merow and Silander 2014), and a recent survey 

of over 300 scientists found MaxEnt software is currently one of the most useful 
8

GENERAL TECHNICAL REPORT PNW-GTR-929

Table 1—Forest structure and species composition variables used in the nesting/roosting 

habitat modeling processa

 Model

Plot region

Variable Description and expected habitat relationship Units accuracy used

Forest structure

 and age:

 Diameter A measure of the structural diversity of a forest stand based on tree densities Index 0.71 All

 diversity in different diameter at breast height (d.b.h.) classes. Calculation procedures (±0.06)

 index are described in appendix 1 of McComb et al. (2002). Positive relationship

 with habitat suitability.

 Canopy Percentage of conifer cover in the canopy as calculated using methods in the Percentage 0.77 All

 cover of Forest Vegetation Simulator. Positive relationship with habitat suitability. (±0.04)

 all conifers 

 Stand height Average height of dominant and codominant trees. Positive relationship with Meters 0.64 All

 habitat suitability. (±0.10)

 Mean conifer Basal area weighted mean d.b.h. of all live conifers. Positive relationship with Centimeters 0.56 All

 diameter habitat suitability. (±0.12)

 Density of Estimated tree density for all live conifers ≥ 30 in d.b.h. Positive relationship Trees/ha 0.60 All

 large conifers with habitat suitability. (±0.09)

 Stand age Average stand age based on field-recorded ages of dominant and codominant Years 0.64 All

 (no remnant) tree species, and excluding remnant trees. Positive relationship with (±0.10)

 habitat suitability.

Forest species 

 composition:

 Subalpine Stand component of Pacific silver fir (Abies amabilis Dougl. ex Forbes), Percentage 0.40 221, 

 forest subalpine fir (A. lasiocarpa (Hook.) Nutt.), noble fir (A. procera of total (±0.02) 222,

 Rehd.), Shasta red fir (A. shastensis (Lemmon) Lemmon), Alaska basal area 224,

 cedar (Chamaecyparis nootkatensis (D. Don) Spach), Engelmann spruce 225

 (Picea engelmannii Parry ex Engelm.), whitebark pine (Pinus albicaulis,

 Engelm.), and mountain hemlock (Tsuga mertensiana (Bong.) Carr.). 

 Negative relationship with habitat suitability.

 Pine forest Stand component of lodgepole pine (Pinus contorta Dougl. ex Loud.), Jeffrey Percentage 0.39 222,

 pine (P. jeffreyi Grev. & Balf.), Bishop pine (P. muricata D. Don), of total (±0.05) 224,

 and ponderosa pine (P. ponderosa Dougl. ex Laws.). Negative relationship basal area 225,

 with habitat suitability. 226

 Oak woodland Stand component of blue oak (Quercus douglasii Hook. & Arn.), Oregon Percentage 0.40 222,

 white oak (Q. garryana Dougl. ex Hook.), and California black oak of total (±0.06) 223,

 (Q. kelloggii Newb.). Negative relationship with habitat suitability. basal area 224,

 225,

226

 Evergreen Stand component of Pacific madrone (Arbutus menziesii Pursh), tanoak Percentage 0.38 223,

 hardwood (Lithocarpus densiflorus Rehd.), California live oak (Quercus agrifolia Née), of total (±0.07) 224,

 canyon live oak (Q. chrysolepis Liebm.), and California laurel basal area 225,

 (Umbellularia californica (Hook. & Arn.) Nutt.). Positive relationship 226

 with habitat suitability at lower levels, then negative at higher levels.

 Redwood forest Stand component of redwood (Sequoia sempervirens (D. Don) Endl.). Percentage 0.60 226

 Negative relationship with habitat suitability. of total 

 basal area 

a

 Structure variables were consistently used in all modeling regions. Species composition variables were used in modeling regions where they occur. 

Plot accuracies for structure variables are shown as mean Pearson correlations with 95-percent confidence intervals shown in parenthesis. Species 

composition plot accuracies were based on the mean Cohen’s kappa statistic. 
9

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

SDM methods available (Ahmed et al. 2015). For this reporting cycle, we followed 

habitat modeling and mapping methods used in the 15-year report. 

MaxEnt uses a machine learning process to develop algorithms that relate 

environmental conditions at documented species presence locations to that of 

the surrounding background environment in which they occurred (Elith et al. 

2011, Phillips and Dudík 2008). We used the same set of environmental variables 

(updated with new GNN maps) and suite of response functions (linear, product, and 

hinge) as in the 15-year report (Davis et al. 2011). Habitat models were developed 

using GNN and NSO data from 1993, then model algorithms were applied to GNN 

data from 2012. 

The NSO range was divided into six modeling regions as in the 15-year report. 

Within each modeling region, 10 replicated habitat models were trained using a random subset of 75 percent of NSO locations and then tested using the remaining 25 

percent in a bootstrapping procedure. In each bootstrapped replicate, environmental 

variables at NSO locations were analyzed against a random sample of 10,000 

background locations from within the modeling region. We constrained background 

samples and model outputs to only forest-capable portions of the modeling region 

(e.g., nonforested areas such as urban areas, agricultural fields, rocks, meadows, and 

snow were masked out from the SDM process).

We calibrated each habitat model by evaluating how well it fit the training and 

testing data by varying MaxEnt’s regularization multiplier (RM) setting from 0.25 

to 3.0 in increments of 0.25. The regularization multiplier “tightens” (lower RM 

settings) or “loosens” (higher RM settings) the fit (a.k.a. the gain, which is similar 

to deviance) of the model output to the data. Usually, if the model fits the training 

data too tightly, it performs poorly when tested against species locations not used 

to train the model (e.g., the test gain will be lower than the training gain). During 

this procedure, we examined the differences between regularized training gain and 

testing gain. Model overfitting was indicated when training gain was significantly 

higher than testing gain. We also generated predicted-to-expected (P/E) ratio curves 

for each model using only the testing data to evaluate its predictive performance 

based on the shape of the curves and Spearman rank statistics (Hirzel et al. 2006). 

The shape of the P/E curve was based on the ratio of the proportion of NSO test 

locations to the proportion of modeled area available within each interval of the 

predicted species distribution output. A good model was indicated by low P/E ratios 

where the model predicted lower species occurrence and high P/E ratios where 

the model predicted higher species occurrence (see Davis et al. 2011 for further 

details). We then evaluated the predictive performance of each model based on the 

area under the curve (AUC) statistic (Fielding and Bell 1997), again using only the 
10

GENERAL TECHNICAL REPORT PNW-GTR-929

testing data. The best models were the ones with similar regularized training and 

testing gain (e.g., overlapping 95 percent confidence intervals), highest test AUCs, 

and stable P/E curves producing high Spearman rank statistics. 

We used the logistic output from MaxEnt as the relative index of habitat suitability (HS) of forest structure and species composition for nesting and roosting by 

territorial NSO pairs. Habitat suitability ranged from 0 to 1.0, where values closer 

to zero have environmental conditions that are not similar to those found at NSO 

locations and higher values have more in common with nesting/roosting habitat. For 

our final habitat map products, we used the average and standard deviation of the 

logistic outputs from the 10 bootstrapped replicates to produce maps representing 

the average and 95 percent confidence intervals. Following procedures from Hirzel 

et al. (2006), we examined the P/E curve for each averaged model to reclassify the 

continuous output into four biologically meaningful habitat classes as follows:

• Unsuitable—MaxEnt logistic output from zero to the mean value between 

zero and the P/E = 1 threshold. This habitat class represents the lowest suitability class, and NSOs will normally avoid using it for nesting and roosting.

• Marginal—MaxEnt logistic output from the mean value between zero and 

the P/E = 1 threshold to the P/E = 1 threshold. This habitat class represents 

a condition approaching what NSOs will nest and roost in. Occasionally, 

these habitat characteristics are associated with nesting and roosting NSOs; 

however, this could be due to occurrence of legacy habitat features such as 

large trees, extreme rarity of suitable nesting/roosting habitat, or perhaps 

interspecific competition with BOs.

• Suitable—MaxEnt logistic output from the P/E = 1 threshold to 0.5. A 

MaxEnt logistic output value of 0.5 represents the “average” environmental 

condition associated with the NSO training data. This habitat class represents habitat conditions where the probability of NSO presence is higher 

than expected by random chance and up to average conditions associated 

with nesting and roosting.

• Highly suitable—MaxEnt logistic output from 0.5 to the highest output from 

the habitat model. This habitat class represents the most suitable, or “above 

average,” conditions used by nesting and roosting territorial NSO pairs.

To produce rangewide maps of NSO nesting/roosting habitat, we built mosaics of the reclassified maps from each modeling region for each time period and 

then removed small pixel noise using a 3- by 3-pixel majority filter. We did not 

mosaic the continuous outputs from each model region as the HS values with each 

modeling region were not directly comparable (e.g., the suitable habitat thresholds 
11

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

between models differed). A final evaluation of the rangewide map (1993) was 

performed using NSO pair locations from the 10-year report (Lint 2005) that were 

not used in the model building described above, nor within 30 m (one pixel) of NSO 

locations that were used (n = 6,433). 

Dispersal Habitat

Habitat used by dispersing juvenile NSOs moving away from natal areas or by 

subadults and adults moving between territories was mapped following methods 

in Davis et al. (2011, pg. 40) and briefly described here. We did not use presence 

locations and SDM to model dispersal habitat. Instead we developed rangewide 

dispersal habitat maps for both bookend periods using simple GIS queries of GNN 

data for mean conifer diameter at breast height (d.b.h.) ≥11 in and conifer cover ≥40 

percent (Thomas et al. 1990). We also included the suitable habitat classes from 

our rangewide nesting/roosting habitat maps (that did not overlap pixels that met 

the above definition) because NSOs obviously disperse through this habitat. This 

accounted for just a small percentage (2.8 percent) of dispersal habitat. An examination of where suitable habitat did not overlap with the above definition showed 

a majority (86 percent) was due to areas where conifer cover was ≥40 percent, but 

mean conifer diameters were slightly below the 11-in threshold (mean = 7.1 in, 

standard dev. = 2.1 in). This mainly occurred in the Klamath and California Coast 

modeling regions where smaller diameter (<11 in d.b.h.) trees are known to make 

up a larger proportion of stand tree density in nesting habitat compared to other 

areas of the NSO range (Hershey et al. 1998). In addition, the presence of evergreen 

hardwoods (table 1) in these modeling regions might be expected to raise the 

modeled relative HS index above the suitable threshold in these stands (Diller at al. 

2007, Meyer et al. 1998). We did not provide means and confidence interval maps 

for dispersal habitat as we did not use a bootstrap modeling procedure to produce 

the maps.

Habitat Assessments

Bookend Analysis

To assess habitat change in nesting/roosting and dispersal habitat, we spatially differenced the bookend maps (bookend 2012 – bookend 1993) using ArcGIS Spatial 

Analyst tools. This allowed us to quantify gross losses and gains as well as net 

changes in amount of habitat. We emphasized gross losses that were corroborated 

by the LandTrendr change detection data as the most reliable assessment in these 

bookend analyses.
12

GENERAL TECHNICAL REPORT PNW-GTR-929

Habitat Fragmentation

Following methods from Davis et al. (2011, pgs. 41–43), we used software GUIDOS 

v1.3 (Soille and Vogt 2009) to conduct a morphological spatial pattern analysis 

(MSPA) on resampled 100- by 100-m (2.47-ac) resolution binary maps of nesting/

roosting habitat (“0” if unsuitable or marginal, “1” if suitable or highly suitable) for 

both time periods. These binary maps were converted by the MSPA process into 

maps showing edge, core-edge, and core patterns of habitat that were evaluated for 

changes using bookend analyses. As in the 15-year report, edge was not quantified 

as a linear perimeter measure, but instead as the area of the interface (one pixel 

width or 328 ft) of habitat and nonhabitat. Habitat within this distance of nonhabitat 

was considered “edge habitat.” This distance was similar to that used by Franklin et 

al. (2000) and Zabel et al. (2003) to define core habitat in their analyses, thus habitat 

greater than this distance from nonhabitat was considered “core habitat.” Habitat 

pixels along the periphery of core habitat were called “core-edge habitat.” The 

combination of “core” plus “core-edge” habitat formed habitat patches that were 

at least 22 ac. We assessed nesting/roosting habitat fragmentation using the ratio 

of habitat patches (core plus core-edge) to the sum of all nesting/roosting habitat 

(included edge habitat). This ratio served as an index where higher percentages 

represented more contiguous landscapes. Decreases in this ratio between 1993 and 

2012 indicated increased fragmentation of habitat, whereas positive changes in the 

ratio indicated less fragmentation.

Dispersal-Capable Landscape

Northern spotted owls are capable of dispersing long distances, and gene flow from 

one part of the range to another can occur in a few generations (Forsman et al. 

2002). We used the same approach to detect changes in amounts of dispersal habitat that might affect NSO movement across the landscape as in Davis et al. (2011, 

pgs. 40 and 41). Briefly, we evaluated dispersal habitat at the NWFP scale using a 

spatial extent derived from Forsman et al. (2002). Specifically, we used a 15.5-mi 

radius roving circular analysis window to quantify the percentage of dispersal 

habitat within it for both bookend periods and included all land ownerships. A 

threshold of ≥40 percent dispersal habitat within this circle captured 90 percent of 

documented NSO movements from Forsman et al. (2002). We called areas that met 

this threshold “dispersal-capable landscapes.” A bookend analysis was conducted 

on binary maps of dispersal-capable landscapes (“0” if less than 40 percent, “1” if 

greater than or equal to 40 percent).
13

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

Results

Habitat Modeling and Mapping

Nesting/roosting habitat models performed fair to good (Swets 1988) with mean 

testing AUCs ranging from 0.78 to 0.87 and mean Spearman rank correlation 

coefficients from 0.75 to 0.98 (P < 0.001) (table 2). Predicted-to-expected curves are 

shown in figure 1. Our habitat models produced continuous relative indices of habitat suitability for nesting and roosting. We in turn classified these continuums into 

discrete habitat classes for monitoring purposes. Nesting/roosting habitat bookend 

maps are displayed in figures 2 and 3, showing patterns of habitat classes across the 

range of the NSO. The majority (95 percent) of the subset of the 10-year report (Lint 

2005) NSO locations were in or within 100 m (the spatial accuracy of these data) of 

mapped suitable habitat. About 4.5 percent occurred within marginal habitat, and 

less than 1 percent occurred within unsuitable habitat. Suitable nesting/roosting 

habitat in both time periods was concentrated on federally managed lands. 

On average, stand structure variables provided most (68 percent) of the explanatory information in the habitat models. The strongest structural variables were 

density of large conifers and conifer cover (table 1). Conifer cover was particularly 

strong (31 percent) in the California Coast model. Stand age contributed about 11 

percent on average, while species composition variables contributed about 21 percent on average. Species composition was more important in drier modeling regions 

(e.g., east Cascades and Klamath) and also in the redwood region (California Coast). 

We summarized forest structure and age attributes to help interpret what map 

Table 2—Species distribution modeling bootstrapped replicate (n = 10) results for model fit (gain) and testing 

statistics (95 percent confidence limits shown in parenthesis)

Modeling Training Testing Training Testing Testing Spearman

region sample size sample size RM gain gain AUC rank

---- Number ----

Washington Coast 250 83 0.25 1.07 (±0.04) 1.02 (±0.05) 0.87 (±0.01) 0.93 (±0.04)

 and Cascades

Washington Eastern 87 28 1 0.93 (±0.06) 0.86 (±1.00) 0.84 (±0.01) 0.75 (±0.15)

 Cascades

Oregon Coast 247 82 1.75 0.98 (±0.02) 0.99 (±0.01) 0.86 (±0.01) 0.95 (±0.01)

 Range

Oregon and California 596 198 1.25 0.66 (±0.03) 0.64 (±0.03) 0.80 (±0.01) 0.90 (±0.07)

 Cascades

Oregon and California 757 252 2 0.53 (±0.01) 0.54 (±0.03) 0.78 (±0.01) 0.98 (±0.02)

 Klamath

California Coast 175 58 1 0.74 (±0.05) 0.62 (±0.09) 0.80 (±0.02) 0.83 (±0.13)

RM = regularization multiplier, AUC = area under the curve.
14

GENERAL TECHNICAL REPORT PNW-GTR-929

habitat classes represent on the ground (table 3 and fig. 4). Relationships between 

habitat variables and modeled habitat suitability (table 1) were as expected based 

on examination of response function curves in the MaxEnt outputs and also NSO 

habitat associations as summarized by Courtney et al. (2004). Consistently, modeled habitat suitability showed positive relationships with stand structure attributes 

commonly associated with NSO nesting habitat (fig. 4). Stand age showed lower differences between suitability classes in the California Coast modeling region where 

NSOs have been documented to use younger stands (Diller et al. 2007).

We explored the BO effect on NSO habitat selection by analyzing the change 

in modeled habitat suitability from the 1993 map and a time series of annual NSO 

locations from the Tyee density study area. This study area surveys all habitat 

within its boundary, as opposed to the “territorial study areas” that only survey historical NSO territories that are sometimes separated by large areas of unsurveyed 

habitat outside of the territory bounds. We detected a strong negative correlation (r 

= −0.894) between the increasing trend in proportion of NSO territories with BO 

detections and the average habitat suitability at annual NSO locations. The average 

habitat suitability at NSO sites in 2013 was significantly lower than it was in 1990, 

when the study began (fig. 5).

Figure 1—Predicted-to-expected (P/E) ratio curves for northern spotted owl nesting/roosting habitat models. The red dashed line represents P/E = 1 (random model line). The 

dashed vertical line represents the habitat suitability threshold that denotes habitat suitable for nesting and roosting by northern spotted owls.

Oregon and California Cascades

suitable

Washington Coast and Cascades

suitable

Washington Eastern Cascades

suitable

Oregon Coast Range

suitable

Oregon and California Klamath

suitable

California Coast

suitable

Relative habitatsuitability Relative habitatsuitability

30

25

20

15

10

5

0

30

25

20

15

10

5

0

30

25

20

15

10

5

0

30

25

20

15

10

5

0

30

25

20

15

10

5

0

30

25

20

15

10

5

0

0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85

0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 

0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85

0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85

0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85

Predited/expected

(PE) ratio

Predited/expected

(PE) ratio

Predited/expected

(PE) ratio

Predited/expected

(PE) ratio

Predited/expected

(PE) ratio

Predited/expected

(PE) ratio
15

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

Figure 2—Bookend #1 nesting/roosting habitat map for the Northwest Forest Plan area in Washington (WA), 

Oregon (OR), and California (CA).
16

GENERAL TECHNICAL REPORT PNW-GTR-929

Figure 3—Bookend #2 nesting/roosting habitat map for the Northwest Forest Plan area in Washington (WA), 

Oregon (OR), and California (CA). 
17

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

Table 3—Average (standard deviation) forest structure and age (gradient nearest neighbor) attributes for 

nesting/roosting habitat classes in each modeling region

Modeling

region

Habitat

 class

Habitat

suitability

Conifer

cover

Average 

conifer

d.b.h.

Large conifer

(≥30 in d.b.h.)

Diameter

diversity 

index

Average

stand 

height

Average

stand age

Old-growth 

structure 

index

Percent Inches Trees/acre Index Feet Years Index

Washington

 Coast and

 Cascades

Unsuitable

 Marginal

 Suitable

 Highly

 suitable

0–8

9–30

31–50

>50

41 (31)

81 (12)

84 (11)

89 (16)

10 (9)

17 (7)

26 (11)

31 (8)

0 (1)

3 (6)

10 (9)

16 (8)

2 (2)

5 (2)

6 (2)

7 (1)

44 (33)

76 (31)

95 (35)

110 (30)

33 (32)

102 (83)

192 (109)

247 (78)

3 (10)

16 (23)

40 (25)

58 (20)

Washington

 Eastern

 Cascades

Unsuitable

 Marginal

 Suitable

 Highly

 suitable

0–8

9–31

32–50

>50

50 (29)

62 (19)

70 (14)

79 (11)

13 (6)

16 (6)

18 (6)

21 (6)

1 (2)

2 (3)

3 (4)

6 (7)

50 (2)

62 (1)

70 (1)

79 (1)

43 (23)

55 (22)

72 (19)

91 (18)

99 (55)

106 (47)

125 (58)

155 (61)

15 (22)

18 (21)

23 (23)

36 (21)

Oregon

 Coast

 Range

Unsuitable

 Marginal

 Suitable

 Highly

 suitable

0–12

13–37

38–50

>50

37 (30)

68 (18)

67 (14)

71 (11)

9 (9)

20 (8)

32 (12)

35 (7)

0 (1)

2 (3)

10 (7)

18 (8)

2 (2)

5 (1)

6 (1)

7 (1)

37 (25)

84 (20)

118 (27)

141 (26)

29 (20)

60 (22)

118 (61)

159 (56)

3 (11)

10 (18)

37 (24)

55 (18)

Oregon-

 California

 Cascades

Unsuitable

 Marginal

 Suitable

 Highly

 suitable

0–12

13–33

34–50

>50

34 (24)

72 (16)

76 (12)

76 (9)

11 (9)

16 (6)

21 (6)

30 (6)

1 (2)

2 (4)

5 (5)

16 (9)

2 (1)

4 (1)

6 (1)

7 (1)

35 (25)

64 (20)

88 (23)

123 (25)

58 (46)

107 (62)

132 (65)

229 (75)

6 (16)

18 (22)

30 (23)

54 (18)

Oregon-

 California

 Klamaths

Unsuitable

 Marginal

 Suitable

 Highly 

 suitable

0–15

16–37

38–50

>50

24 (23)

49 (21)

60 (18)

62 (16)

11 (9)

19 (8)

26 (9)

31 (9)

1 (3)

3 (5)

7 (7)

10 (6)

2 (2)

4 (1)

6 (1)

7 (1)

32 (20)

54 (22)

74 (29)

89 (27)

65 (35)

97 (50)

139 (68)

161 (63)

6 (16)

20 (24)

40 (21)

47 (18)

California

 Coast

Unsuitable

 Marginal

 Suitable

 Highly 

 suitable

0–14

15–39

40–50

>50

17 (20)

52 (22)

66 (22)

79 (16)

10 (11)

21 (14)

25 (14)

25 (12)

0 (1)

2 (4)

5 (7)

8 (8)

3 (2)

5 (2)

5 (1)

6 (1)

37 (13)

55 (25)

73 (35)

81 (27)

63 (24)

73 (71)

86 (72)

76 (47)

12 (22)

16 (23)

23 (25)

26 (27)

d.b.h. = diameter at breast height.
18

GENERAL TECHNICAL REPORT PNW-GTR-929

Figure 4—Relationship between nesting/roosting habitat classes with forest structure and age 

(see table 3). U = unsuitable, M = marginal, S = suitable, HS = highly suitable, d.b.h. = diameter 

as breast height.

Figure 5— Relationship between barred owl presence and northern spotted owl (NSO) habitat 

selection. CI = confidence interval.
19

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

Table 4—Bookend map areal estimates of nesting/roosting habitat and net changes from 1993 to 2012 on nonreserved federal lands (left), assigned causes for losses from LandTrendr disturbance maps (right)State and physiographic province

Nesting/roosting habitat 

estimates from bookend maps LandTrendr disturbance assignment for losses

1993 2012

Net area 

change

Net 

percentage 

change Harvest Wildfire Insect Other

Total 

explained 

loss

Percentage 

loss from 

1993

- - - - - - - - - - - - - Acres - - - - - - - - - - Percent - - - - - - - - - - - - - - - - - - - - - Acres - - - - - - - - - - - - - - - - - Percent

Washington:

Olympic Peninsula 23,000 23,100 100 0.4 300 0 0 0 300 -1.3Western Lowlands 0 0 0 0 0 0 0 0 0 0Western Cascades 209,800 212,300 2,500 1.2 3,700 0 100 0 3,800 -1.8Eastern Cascades 221,600 224,800 3,200 1.4 10,200 10,600 4,700 0 25,500 -11.5

 Total 454,400 460,200 5,800 1.3 14,200 10,600 4,800 0 25,500 -6.5Oregon:

Coast Range 74,700 79,500 4,800 6.4 4,400 0 100 0 4,500 -6.0Willamette Valley 5,700 6,100 400 7.0 200 0 0 0 200 -3.5Western Cascades 1,029,100 1,070,900 41,800 4.1 30,100 11,900 1,600 0 43,600 -4.2Klamath 361,400 381,700 20,300 5.6 10,400 15,600 700 0 26,700 -7.4Eastern Cascades 105,500 134,600 29,100 27.6 6,700 3,600 800 0 11,100 -10.5

 Total 1,576,400 1,672,800 96,400 6.1 51,800 31,100 3,200 0 86,100 -5.5California:

Coast Range 7,300 10,000 2,700 37.0 0 100 0 0 100 -1.4Klamath 615,100 621,800 6,700 1.1 8,200 41,800 1,100 0 51,100 -8.3Cascades 84,000 89,300 5,300 6.3 6,100 2,300 800 0 9,200 -11.0

 Total 706,400 721,100 14,700 2.1 14,300 44,200 1,900 0 60,400 -8.6NWFP total 2,737,200 2,854,100 116,900 4.3 80,300 85,900 9,900 0 176,100 -6.4NWFP = Northwest Forest Plan.
20

GENERAL TECHNICAL REPORT PNW-GTR-929 Table 5—Bookend map areal estimates of nesting/roosting habitat and net changes from 1993 to 2012 on reserved federal lands (left), assigned causes for losses from LandTrendr disturbance maps (right) Nesting/roosting habitat estimates from bookend maps LandTrendr disturbance assignment for losses State and physiographic province 1993 2012 Net area change Net percentage change Harvest Wildfire Insect Other Total explained loss Percentage loss from 1993 - - - - - - - - - - - - - - - - Acres - - - - - - - - - - - Percent - - - - - - - - - - - - - - - - - - - - - Acres - - - - - - - - - - - - - - - - - Percent

Washington:

Olympic Peninsula 742,900 714,500 -28,400 -3.8 1,400 1,000 700 2,200 5,300 -0.7Western Lowlands 12,900 12,900 0 0 0 0 0 600 600 -4.7Western Cascades 947,900 957,200 9,300 1.0 3,100 2,600 800 3,500 10,000 -1.1Eastern Cascades 611,200 554,600 -56,600 -9.3 14,300 41,500 29,400 3,100 88,300 -14.4

 Total 2,314,900 2,239,200 -75,700 -3.3 18,800 45,100 30,900 9,400 104,200 -4.5Oregon:

Coast Range 421,300 426,800 5,500 1.3 3,300 100 100 0 3,500 -0.8Willamette Valley 1,400 1,400 0 0 0 0 0 0 0 0Western Cascades 1,315,200 1,300,500 -14,700 -1,1 4,800 51,100 900 1,100 57,900 -4.4Klamath 637,200 550,400 -86,800 -13.6 3,600 116,400 200 200 120,400 -18.9Eastern Cascades 193,700 205,000 11,300 5.8 1,700 11,200 800 300 14,000 -7.2

 Total 2,568,800 2,484,100 -84,700 -3.3 13,400 178,800 2,000 1,600 195,800 -7.6California:

Coast Range 106,100 113,800 7,700 7.3 100 1,700 0 500 2,300 -2.2Klamath 1,245,700 1,142,900 -102,800 -8.3 2,200 158,000 2,200 2,600 165,000 -13.2Cascades 117,400 120,000 2,600 2.2 1,000 4,900 300 300 6,500 -5,5

 Total 1,469,200 1,376,700 -92,500 -6.3 3,300 164,600 2,500 3,400 173,800 -11.8NWFP total 6,352,900 6,100,000 -252,900 -4.0 35,500 388,500 35,400 14,400 473,800 -7.5NWFP = Northwest Forest Plan.
21

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

Table 6—Bookend map areal estimates of nesting/roosting habitat and net changes from 1993 to 2012 on all federal lands (left), assigned causes for losses from LandTrendr disturbance maps (right)

Nesting/roosting habitat 

estimates from bookend maps LandTrendr disturbance assignment for losses

State and physiographic province 1993 2012

Net area 

change

Net 

percentage 

change Harvest Wildfire Insect Other

Total 

explained 

loss

Percentage 

loss from 

1993

- - - - - - - - - - - - Acres - - - - - - - - - Percent - - - - - - - - - - - - - - - - - - - - Acres - - - - - - - - - - - - - -- Percent

Olympic Peninsula 765,800 737,600 -28,200 -3.7 1,700 1,000 800 2,200 5,700 -0.7Western Lowlands 12,900 12,900 0 0 0 0 0 600 600 -4.7Western Cascades 1,157,700 1,169,500 11,800 1.0 6,900 2,600 900 3,500 13,900 -1.2Eastern Cascades 832,700 779,400 -53,300 -6.4 24,400 52,100 34,000 3,100 113,600 -13.6

 Total 2,769,100 2,699,400 -69,700 -2.5 33,000 55,700 35,700 9,400 133,800 -4.8Oregon:

Coast Range 496,000 506,200 10,200 2.1 7,700 100 200 0 8,000 -1.6Willamette Valley 7,000 7,500 500 7.1 300 0 0 0 300 -4.3Western Cascades 2,344,300 2,371,400 27,100 1.2 34,900 63,000 2,500 1,100 101,500 -4.3Klamath 998,700 932,100 -66,600 -6.7 14,000 132,000 900 200 147,100 -14.7Eastern Cascades 299,200 339,600 40,400 13.5 8,400 14,700 1,700 300 25,100 -8.4

 Total 4,145,200 4,156,800 11,600 0.3 65,300 209,800 5,300 1,600 282,000 -6.8California:

Coast Range 113,300 123,800 10,500 9.3 200 1,800 0 500 2,500 -2.2Klamath 1,860,800 1,764,700 -96,100 -5.2 10,400 199,800 3,300 2,600 216,100 -11.6Cascades 201,300 209,300 8,000 4.0 7,200 7,200 1,100 300 15,800 -7.8

 Total 2,175,400 2,097,800 -77,600 -3.6 17,800 208,800 4,400 3,400 234,400 -10.8NWFP total 9,089,700 8,954,000 -135,700 -1.5 116,100 474,300 45,400 14,400 650,200 -7.2NWFP = Northwest Forest Plan.
22

GENERAL TECHNICAL REPORT PNW-GTR-929 Table 7—Bookend map areal estimates of nesting/roosting habitat and net changes from 1993 to 2012 on all (federal and nonfederal) lands (left), assigned causes for losses from LandTrendr disturbance maps (right) Nesting/roosting habitat estimates from bookend maps LandTrendr disturbance assignment for losses State and physiographic province 1993 2012 Net area change Net percentage change Harvest Wildfire Insect Other Total explained loss Percentage loss from 1993 - - - - - - - - - - - - Acres - - - - - - - - - - Percent - - - - - - - - - - - - - - - - - - - - - Acres - - - - - - - - - - - - - - - - - - - - Percent Washington: Olympic Peninsula 936,200 859,600 -76,600 -8.2 41,400 1,000 2,500 2,200 47,100 -5.0

Western Lowlands 184,500 108,900 -75,600 -41.0 81,200 0 1,400 600 83,200 -45.1Western Cascades 1,391,700 1,350,600 -41,100 -3.0 71,400 2,900 2,000 3,500 79,800 -5.7Eastern Cascades 1,181,200 1,068,400 -112,800 -9.5 110,100 58,600 40,500 3,100 212,300 -18.0

 Total 3,693,600 3,387,500 -306,100 -8.3 304,100 62,500 46,400 9,400 422,400 -11.4Oregon:

Coast Range 788,600 696,500 -92,100 -11.7 137,400 400 1,800 0 139,600 -17.7Willamette Valley 88,400 70,900 -17,500 -19.8 26,700 0 300 0 27,000 -30.5Western Cascades 2,820,000 2,710,700 -109,300 -3.9 255,100 65,000 5,100 1,100 326,300 -11.6Klamath 1,238,900 1,175,300 -63,600 -5.1 85,500 134,400 2,200 200 222,300 -17.9Eastern Cascades 408,500 438,400 29,900 7.3 37,200 19,300 2,900 300 59,700 -14.6

 Total 5,344,400 5,091,800 -252,600 -4.7 541,900 219,100 12,300 1,600 774,900 -14.5California:

Coast Range 970,700 1,198,500 227,800 23.5 79,500 5,600 2,900 500 88,500 -9.1Klamath 2,148,500 2,063,400 -85,100 -4.0 50,100 208,100 5,600 2,600 266,400 -12.4Cascades 368,500 362,500 -6,000 -1.6 44,700 10,500 3,300 300 58,800 -16.0

 Total 3,487,700 3,624,400 136,700 3.9 174,300 224,200 11,800 3,400 413,700 -11.9NWFP total 12,525,700 12,103,700 -422,000 -3.4 1,020,300 505,800 70,500 14,400 1,611,000 -12.9NWFP = Northwest Forest Plan.
23

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

Figure 6—Nesting/roosting habitat losses on federal lands between 1993 and 2012 by physiographic province. 

Habitat Assessments

Nesting/Roosting Habitat

Habitat area net change and loss estimates are shown in tables 4 thru 7. We estimated a rangewide gross loss of about 650,200 ac of nesting/roosting habitat on federal lands (table 6). This amounted to about 7.2 percent of what was present in 1993. 

Most of the losses (73 percent) occurred within the federally reserved LUAs, or a 

loss of about 7.5 percent of the habitat reserved by the NWFP. Nonreserved federal 

LUAs experienced a 6.4 percent rangewide loss of habitat that existed in 1993. 

Wildfires were the primary cause of habitat loss since 1993, accounting for 

about 82 percent of the loss in reserved allocations (388,500 ac) and about half of 

the loss in nonreserved allocations (85,900 ac). Timber harvesting accounted for 

about 45 percent of the loss in nonreserved allocations (80,300 ac) and 8 percent 

within reserved allocations (35,500 ac). Harvests within reserved allocations were 

due to (1) timber sales that were under contract at the implementation of the NWFP 

and (2) harvesting that occurred in nonreserved allocations that were subsequently 

added to reserved allocations (e.g., land exchanges, wilderness designations, etc.). 

Insects, diseases, and other natural disturbances accounted for a minor proportion 

(0.7 percent) of habitat loss since 1993.

Relative to the baseline maps based on LandTrendr change-detection data, the 

physiographic province that experienced the greatest loss of habitat was the California Klamath province (fig. 6). The Oregon and California Klamath physiographic 

provinces experienced the largest amounts (132,000 to 199,800 ac, respectively) 

and double digit percentage losses (13.2 and 10.7 percent, respectively) of habitat 
24

GENERAL TECHNICAL REPORT PNW-GTR-929

lost owing to wildfires. Other physiographic provinces that experienced significant 

amounts of habitat loss to wildfire include the Oregon Western Cascades (63,000 

ac) and the Washington Eastern Cascades (52,100 ac). Most of these wildfire-related 

habitat losses occurred in the federally reserved LUAs (fig. 7)

Habitat recruitment estimates have a higher level of uncertainty than estimates 

of habitat loss for reasons explained in the 15-year monitoring report (Davis et al. 

2011, pgs. 48 and 49). However, we used gains and losses to estimate net changes 

in this report. Considering both gains and losses, we estimated a rangewide net 

decrease in nesting/roosting habitat of 1.5 percent on all federal lands (table 6). 

Within the federally reserved allocations, the net change was a 4.0 percent decline 

(table 5), which was less than the 2.5 percent per decade (5 percent over two 

decades) loss rate anticipated in the NWFP’s design. In nonreserved federal LUAs, 

we estimated a net increase of 4.3 percent since 1993. Most of the gains occurred 

in the moister physiographic provinces (e.g., Coast Ranges and Western Cascades); 

however, we also observed a large gain (13.5 percent) in the Oregon Eastern 

Cascades. When compared to the results of the concurrent late-successional and 

old-growth forest monitoring (Davis et al. 2015), which estimated a net decrease of 

0.8 to 2.8 percent of older forests defined purely by structural attributes (e.g., oldgrowth structure index) in the same area, we suspect the reason behind the net gain 

in NSO habitat was driven by species composition changes (e.g., understory development of Douglas-fir [Pseudosuga menziesii (Mirb.) Franco] and grand fir [Abies 

grandis Douglas ex D. Don Lindl.]) that in pine stands would lower the percentage 

of stand basal area composed of pine (see table 1). Shifts in species compositions 

in the higher elevations (e.g., silver fir [Abies amabilis (Douglas ex Loud) Douglas 

ex Forbes], mountain hemlock [Tsuga mertensiana (Bong.) Carr.], etc.) could have 

similar results. Regardless, given the uncertainty in our nesting/roosting habitat 

map estimates, the net habitat changes fell within the 95 percent confidence intervals of our estimates (fig. 8).

Habitat Fragmentation

Rangewide, nesting/roosting habitats have become slightly more fragmented on 

federal lands (both reserved and nonreserved) with about a 1.1 percent conversion 

of core habitat to edge habitat. The changes vary by physiographic province (table 

8). In Washington, the reserved allocations have become slightly more contiguous 

(0.1 to 4.5 percent increase), except for the Eastern Cascades, where core/core-edge 

habitat decreased by 1.7 percent. In Oregon, federal reserves have generally become 

slightly more fragmented (0.5 to 2.7) with the highest increase in fragmentation in 

the Oregon Klamath province. However, habitat has become slightly more contiguous in the Oregon Eastern Cascades (4.9 percent). In California, reserved habitat 
25

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

Figure 7—Map of nesting/roosting habitat losses on all lands by disturbance agent between 1993 and 2012 in Washington 

(WA), Oregon (OR), and California (CA). Note wildfires within federal reserved land use allocations.
26

GENERAL TECHNICAL REPORT PNW-GTR-929

Figure 8—Histogram of nesting/roosting habitat bookend analysis results showing areal estimates of habitat for 

1993 and 2012. Error bars represent 95-percent confidence intervals.
27

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

has become slightly more contiguous in the Coast Range and Cascades (0.8 to 1.2 

percent, respectively) and more fragmented in the Klamath province (3.8 percent).

In nonreserved federal LUAs, habitat has generally become more fragmented 

(0.4 to 3.9 percent) on the west side, and slightly more contiguous on the east side 

(2.9 percent). In Oregon, the same pattern was observed with more fragmentation in 

the moister provinces (1.2 to 4.0) and more contiguous habitat in the drier provinces 

(1.7 to 3.1). In California, as in the reserved allocations, nonreserved federal habitat 

became more fragmented in the Klamath province and less in the Coast and Cascades provinces.

Habitat Dispersal

Rangewide, we report an estimated gross loss of about 789,500 ac of dispersal 

habitat on federal lands, most (79 percent) from wildfire (621,900 ac). The causes 

for dispersal habitat loss were similar to those for nesting/roosting habitat losses, 

with wildfire being the main cause in reserved allocations and more than half of the 

Table 8—Nesting/roosting habitat fragmentation bookend analysis 

Physiographic 

province

Reserved Nonreserved

1993 2012 Change 1993 2012 Change

-------------------------- Percentage ------------------------------

Washington 

Olympic Peninsula 85.5 85.6 0.1 39.4 39.0 -0.4

Washington Western 

Lowlands 18.7 23.2 4.5 0 0 0

Washington Western 

Cascades 69.4 70.6 1.2 61.0 57.1 -3.9

Washington Eastern 

Cascades 66.5 64.8 -1.7 59.8 62.7 2.9

Oregon Coast Range 69.7 69.2 -0.5 47.3 43.4 -3.9

Oregon Willamette 

Valley 56.3 54.7 -1.6 62.4 58.5 -4.0

Oregon Western 

Cascades 84.3 82.7 -1.6 75.5 74.2 -1.2

Oregon Klamath 74.5 71.7 -2.7 60.8 62.5 1.7

Oregon Eastern 

Cascades 63.4 68.3 4.9 53.6 56.7 3.1

California Coast 

Range 76.2 77.0 0.8 51.8 68.9 17.1

California Klamath 72.5 68.7 -3.8 62.2 60.2 -2.0

California Cascades 60.4 61.6 1.2 47.8 49.7 1.9

a

 The level of fragmentation was based on the proportion of all nesting/roosting habitat consisting of patch 

habitat (core plus core-edge). Lower percentages indicate higher levels of fragmentation.
28

GENERAL TECHNICAL REPORT PNW-GTR-929

loss in nonreserved allocations (tables 9 through 12). Timber harvesting accounted 

for the 17,800 ac of the loss in nonreserved allocations, and insects and disease 

account for a small percentage of loss in all allocations. However, these losses were 

offset by a 1.13-million-ac gross gain in dispersal habitat on federal land from forest 

succession, resulting in a 2.2-percent overall net gain of dispersal habitat coverage 

across the NSO’s range (table 11). In general, the gains in dispersal habitat were 

higher in federal nonreserved allocations than in reserved allocations.

At the NWFP scale, we detected a 10 percent gross loss of dispersal-capable 

landscape, mostly around the periphery of the federal forests. We suspect this may 

be due to second-rotation regeneration timber harvesting occurring in dispersal 

habitats on nonfederal lands that border federal lands. Large wildfires on federal 

lands played a role in this decrease in the eastern Cascade provinces and the 

Oregon Klamath Mountain province. We also detected a 5 percent gross gain in 

dispersal-capable landscapes along the periphery of some federal forests caused by 

forest succession in younger forests, resulting in an overall net decrease of 5 percent in dispersal-capable landscapes since 1993. In general, the dispersal-capable 

landscape has receded by a few miles into federally managed lands in Washington 

and Oregon (fig. 9). Some internal losses occurred within large reserves in the 

Washington Eastern Cascades. California has been resilient to many large wildfires 

and dispersal-capable lands mostly expanded along the coastal regions owing to 

rapid growth of redwood forests. The large reserve network remains mostly intact 

for dispersal, even with many large wildfires occurring within some of them. One 

notable change is due to the large Biscuit Fire that caused a wide loss of dispersalcapable lands within a large reserve, separating the northern portion from the 

southern portion by about 15 mi (fig. 9). Other noteworthy changes include the 

loss of a connection between the Oregon Coast Range and the Oregon Western 

Cascades, the loss of a connection between the central portion of the Oregon Coast 

Range physiographic province and its northern end, a widening of the southern 

connection in the same province, and an increased isolation of the Olympic Peninsula (fig. 9).
29

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

Table 9—Bookend map areal estimates of dispersal habitat and net changes from 1993 to 2012 on nonreserved federal lands (left), assigned causes for losses from LandTrendr disturbance maps (right)

Dispersal habitat estimates 

from bookend maps LandTrendr disturbance assignment for losses

State and physiographic province 1993 2012

Net area 

change

Net 

percentage 

change Harvest Wildfire Insect Other

Total 

explained 

loss

Percentage 

loss from 

1993

- - - - - - - - - - - Acres - - - - - - - - - - - - Percent - - - - - - - - - - - - - - - - - - - Acres - - - - - - - - - - - - - - - - - - Percent

Washington:

Olympic Peninsula 71,600 84,400 12,800 17.9 600 0 0 0 600 -0.8Western Lowlands 200 300 100 50.0 0 0 0 0 0 0Western Cascades 410,800 471,100 60,300 14.7 3,900 0 100 0 4,000 -1.0Eastern Cascades 387,100 393,800 6,700 1.7 10,100 16,400 3,000 0 29,500 -7.6

 Total 869,700 949,600 79,900 9.2 14,600 16,400 3,100 0 34,100 -3.9Oregon:

Coast Range 245,300 287,900 42,600 17.4 7,500 0 200 0 7,700 -3.1

Willamette Valley 9,700 10,700 1,000 10.3 200 0 0 0 200 -2.1Western Cascades 1,384,700 1,507,300 122,600 8.9 24,400 13,700 1,200 0 39,300 -2.8Klamath 555,900 592,900 37,000 6.7 10,100 23,600 600 0 34,300 -6.2Eastern Cascades 312,700 366,700 54,000 17.3 10,600 7,900 2,700 0 21,200 -6.8

 Total 2,508,300 2,765,500 257,200 10.3 0 -4.1California:

Coast Range 20,500 26,000 5,500 26.8 200 400 0 0 600 -2.9Klamath 898,100 938,100 40,000 4.5 8,700 45,000 1,100 0 54,800 -6.1Cascades 311,600 335,800 24,200 7.8 8,900 3,200 1,900 0 14,000 -4.5

 Total 1,230,200 1,299,900 69,700 5.7 17,800 48,600 3,000 0 69,400 -5.6NWFP total 4,608,200 5,015,000 406,800 8.8 85,200 110,200 10,800 0 206,200 -4.5NWFP = Northwest Forest Plan.
30

GENERAL TECHNICAL REPORT PNW-GTR-929 Table 10—Bookend map areal estimates of dispersal habitat and net changes from 1993 to 2012 on reserved federal lands (left), assigned causes for losses from LandTrendr disturbance maps (right) Dispersal habitat estimates from bookend maps LandTrendr disturbance assignment for losses State and physiographic province 1993 2012 Net area change Net percentage change Harvest Wildfire Insect Other Total explained loss Percentage loss from 1993 - - - - - - - - - - - - - Acres - - - - - - - - - - - Percent - - - - - - - - - - - - - - - - - - - Acres - - - - - - - - - - - - - - - - - - Percent Washington: Olympic Peninsula 1,053,900 1,078,100 24,200 2.3 1,000 1,100 400 1,400 3,900 -0.4 Western Lowlands 55,700 59,300 3,600 6.5 0 0 100 1,300 1,400 -2.5

Western Cascades 1,844,200 1,911,900 67,700 3.7 2,700 3,700 700 4,300 11,400 -0.6Eastern Cascades 1,462,800 1,395,900 -66,900 -4.6 8,600 88,900 14,300 2,900 114,700 -7.8

 Total 4,416,600 4,445,200 28,600 0.6 12,300 93,700 15,500 9,900 131,400 -3.0Oregon:

Coast Range 713,900 811,000 97,100 13.6 6,200 100 200 200 6,700 -0.9Willamette Valley 2,300 2,600 300 13.0 0 0 0 0 0 0Western Cascades 1,887,600 1,877,300 -10,300 -0.5 4,000 75,600 1,700 1,000 82,300 -4.4Klamath 849,200 750,900 -98,300 -11.6 3,400 137,600 200 300 141,500 -16.7Eastern Cascades 635,800 632,800 -3,000 -0.5 3,000 33,400 5,500 700 42,600 -6.7

 Total 4,088,800 4,074,600 -14,200 -0.3 16,600 246,700 7,600 2,200 273,100 -6.7California:

Coast Range 160,300 176,600 13,300 8.3 200 2,900 0 300 3,400 -2.1Klamath 1,851,500 1,751,900 -99,600 -5.4 1,800 163,500 1,300 2,300 168,900 -9.1Cascades 255,300 265,200 9,900 3.9 900 4,700 600 500 6,700 -2.6

 Total 2,267,100 2,190,700 -76,400 -3.4 2,900 171,100 1,900 3,100 179,000 -7.9NWFP total 10,772,500 10,710,500 -62,000 -0.6 31,800 511,500 25,000 15,200 583,500 -5.4NWFP = Northwest Forest Plan.
31

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

Table 11—Bookend map areal estimates of dispersal habitat and net changes from 1993 to 2012 on all federal lands (left), assigned causes for losses from LandTrendr disturbance maps (right)

Dispersal habitat estimates 

from bookend maps LandTrendr disturbance assignment for losses

State and physiographic province 1993 2012

Net area 

change

Net 

percentage 

change Harvest Wildfire Insect Other

Total 

explained 

loss

Percentage 

loss from 

1993

- - - - - - - - - - Acres - - - - - - - - - - - - Percent - - - - - - - - - - - - - - - - - - - Acres - - - - - - - - - - - - - - - - - - Percent

Washington:

Olympic Peninsula 1,125,600 1,162,500 36,900 3.3 1,600 1,100 400 1,400 4,500 -0.4Western Lowlands 55,900 59,600 3,700 6.6 0 0 100 1,300 1,400 -2.5Western Cascades 2,255,000 2,383,000 128,000 5.7 6,500 3,800 800 4,300 15,400 -0.7Eastern Cascades 1,849,900 1,789,700 -60,200 -3.3 18,700 105,400 17,300 2,900 144,300 -7.8

 Total 5,286,400 5,394,800 108,400 2.1 26,800 110,300 18,600 9,900 165,600 -3.1Oregon:

Coast Range 959,300 1,098,900 139,600 14.6 13,700 100 300 200 14,300 -1.5Willamette Valley 12,000 13,200 1,200 10.0 200 0 0 0 200 -1.7Western Cascades 3,272,300 3,384,500 112,200 3.4 28,300 89,300 2,900 1,000 121,500 -3.7Klamath 1,405,100 1,343,900 -61,200 -4.4 13,500 161,200 800 300 175,800 -12.5Eastern Cascades 948,500 999,500 51,000 5.4 13,600 41,400 8,200 700 36,900 -6.7

 Total 6,597,200 6,840,000 242,800 3.7 69,300 292,600 12,200 2,200 375,700 -5.7California:

Coast Range 180,800 199,600 18,800 10.4 400 3,300 0 300 4,000 -2.2Klamath 2,749,600 2,690,000 -59,600 -2.2 10,500 208,500 2,400 2,300 223,700 -8.1Cascades 566,900 600,900 34,000 6.0 9,800 7,800 2,400 500 20,500 -3.6

 Total 3,497,300 3,490,500 -6,800 -0.2 20,700 219,600 4,800 3,100 248,200 -7.1NWFP total 15,380,900 15,725,300 344,400 2.2 116,800 621,900 35,600 15,200 789,500 -5.1NWFP = Northwest Forest Plan.
32

GENERAL TECHNICAL REPORT PNW-GTR-929 Table 12—Bookend map areal estimates of dispersal habitat and net changes from 1993 to 2012 on all (federal and nonfederal) lands (left), assigned causes for losses from LandTrendr disturbance maps (right) Dispersal habitat estimates from bookend maps LandTrendr disturbance assignment for losses State and physiographic province 1993 2012 Net area change Net percentage change Harvest Wildfire Insect Other Total explained loss Percentage loss from 1993 - - - - - - - - - - - - - - Acres - - - - - - - - - - - Percent - - - - - - - - - - - - - - - - - - - Acres - - - - - - - - - - - - - - - - - - Percent Washington: Olympic Peninsula 1,819,800 1,781,500 -38,300 -2.1 190,900 1,200 4,600 1,400 198,100 -10.9

Western Lowlands 1,966,300 1,524,100 -442,200 -22.5 708,700 0 11,000 1,300 721,000 -36.7Western Cascades 3,290,000 3,359,200 69,200 2.1 296,000 4,300 4,000 4,300 308,600 -9.4Eastern Cascades 2,737,200 2,516,500 -220,700 -8.1 179,400 120,500 26,400 2,900 329,200 -12.0

 Total 9,813,300 9,181,300 -632,000 -6.4 1,375,000 126,000 46,000 9,900 1,556,900 -15.9Oregon:

Coast Range 2,783,200 2,589,300 -193,900 -7.0 745,000 800 9,800 200 755,800 -27.2Willamette Valley 205,600 179,400 -26,200 -12.7 56,400 0 700 0 57,100 -27.8Western Cascades 4,130,000 4,082,000 -48,000 -1.2 367,700 94,000 6,900 1,000 469,600 -11.4Klamath 1,984,000 1,918,100 -65,900 -3.3 150,200 165,500 3,100 300 319,100 -16.1Eastern Cascades 1,275,300 1,307,700 32,400 2.5 72,500 51,000 11,700 700 135,900 -10.7

 Total 10,378,100 10,076,500 -301,600 -2.9 1,391,800 311,300 32,200 2,200 1,737,500 -16.7California:

Coast Range 1,848,200 2,192,600 344,400 18.6 54,300 9,200 2,300 300 66,100 -3.6Klamath 3,285,300 3,249,800 -35,500 -1.1 62,600 221,000 5,800 2,300 291,700 -8.9Cascades 1,004,700 1,029,000 24,300 2.4 61,400 13,600 6,400 500 81,900 -8.2

 Total 6,138,200 6,471,400 333,200 5.4 178,300 243,800 14,500 3,100 439,700 -7.2NWFP total 26,329,600 25,729,200 -600,400 -2.3 2,945,100 681,100 92,700 15,200 3,734,100 -14.2NWFP = Northwest Forest Plan.
33

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

Figure 9—Changes in dispersal-capable landscape in Washington (WA), Oregon, (OR), and California 

(CA) between 1993 and 2012.
34

GENERAL TECHNICAL REPORT PNW-GTR-929

Discussion

Habitat loss for the NSO became a concern in the early 1970s (Forsman 1975, 

Gould 1974, Mouat and Schrumpf 1974). Slightly less than two decades later, the 

NSO was listed as threatened under the Endangered Species Act owing to continued chronic habitat loss (USDI FWS 1990). Shortly thereafter, a series of related 

events led to the implementation of the NWFP (Marcot and Thomas 1997), the 

boundary of which was defined by the NSO’s geographic range in the United States. 

Since the NWFP’s implementation, the rate of nesting/roosting habitat loss with 

this area has lessened, but still continues to decline (fig. 10). This continued decline 

in habitat was not unexpected. When the NWFP was designed, rangewide NSO 

habitat loss on federal lands was projected to be about 5 percent per decade, split 

evenly between wildfires and timber harvesting (FEMAT 1993, USDA and USDI 

Figure 10—The rate of loss of older forests and northern spotted owl nesting/roosting habitat lessened when the Northwest Forest Plan 

(NWFP) was implemented in 1994. Since then, nesting/roosting habitat has continued to decline but at a much lower rate. Continued 

habitat monitoring will inform management of future habitat changes (source of map for 1940 was Andrews and Cowlin 1940) and 

Weislander and Jensen 1946).
35

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

1994). In fact, nesting/roosting habitat was projected to continue to decline for up to 

50 years or until about 2044 (USDA and USDI 1994, chap. 3 and 4, pg. 228).

Eventually, habitat recruitment was expected to exceed losses and nesting/

roosting habitat within the LSR network would begin to increase and become less 

fragmented, providing greater benefits for NSOs as well as other late-successional 

forest species (USDA and USDI 1994, apps. J3-8). Two decades into the NWFP, the 

amount of nesting/roosting habitat within reserved LUAs rangewide has declined 

by about 4.0 percent (252,900 ac), primarily owing to wildfire. The losses from 

wildfire amounted to about 6.1 percent (388,500 ac) of what existed within them 

when they were reserved. At the range scale, the gross loss of nesting/roosting 

habitat was slightly higher than the 5.0 percent loss expected over two decades from 

wildfire. It was two to three times higher in the Klamath physiographic provinces, 

where most nesting/roosting habitat losses have occurred.

With foresight, the LSRs within fire-prone provinces were designed with 

wildfire in mind. Late-successional reserves were delineated to be large enough to 

withstand large wildfire events over 50 years such that unburned portions would 

maintain a well-connected network of nesting/roosting and dispersal habitat (USDA 

and USDI 1994, app. J3-8 and 9). However, given the increased frequency of large 

wildfires within the NWFP area since the turn of this century (Davis et al. 2011 

and recent unpublished data), which have far exceeded the area burned in the recent 

decades leading to the design of the NWFP, this design feature may be challenged 

in the near future.

Although wildfire losses have occurred episodically, timber harvesting has 

resulted in more stable annual rates of habitat loss (fig. 11). Timber-harvesting 

related losses removed less than 10,000 ac of nesting/roosting habitat each year. 

Within nonreserved LUAs, the percentage loss from timber harvesting was 2.9 

percent (80,300 ac) or slightly more than half of what the NWFP had anticipated 

(2.5 percent per decade or 5.0 percent over two decades). Even though the NWFP 

allowed for more timber harvesting from federal lands, the debates and litigation 

surrounding the harvesting of older forests has resulted in federal land managers 

focusing harvest efforts on younger forests via commercial thinning with multiple 

resource objectives, including accelerating the development of future NSO habitat 

as one of them. Losses resulting from insects and disease accounted for a minor 

amount (<1 percent) of nesting/roosting habitat loss, mostly in the Washington 

Eastern Cascades where the trend of this loss began to increase on federal lands in 

the early part of this century (fig. 11).

While there are indications of gains, especially in the moister portions of the 

range, not enough time has passed to allow for significant recruitment of nesting/
36

GENERAL TECHNICAL REPORT PNW-GTR-929

Figure 11—Trends in nesting/roosting habitat losses on federal and nonfederal forest lands by (a) wildfire; (b) timber 

harvesting; and (c) insects, disease, and other natural disturbances.

roosting habitat (fig. 8). However, we observed a rangewide 2.2 percent net gain 

in dispersal habitat on federal lands (table 11). But, losses of dispersal habitat on 

adjacent nonfederal lands resulted in a net decrease of 2.3 percent on all lands (table 

12). The result has been a receding of the dispersal-capable landscape by a few 
37

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

miles toward the federal land base with losses of connections to certain portions of 

the range particularly in the Oregon Coast Range (fig. 9). Habitat gains in the last 

20 years were likely due to younger forests of marginal habitat transitioning into 

slightly older forests that are just becoming suitable for nesting and roosting (app. 

A). Given past history of timber harvesting in this region (Gale et al. 2012), we 

anticipate significant recruitment of future habitat, and some of the gains observed 

in this report may be part of the leading edge of this peak in the harvest history (fig. 

12). Another potential cause for habitat gains in this report may be due to changes 

in forest species composition owing to natural succession or disturbance processes. 

Our nesting/roosting habitat suitability models included forest species composition 

variables (table 1), and decreases in subalpine forest, pine forest, or oak woodland 

basal areas over 20 years could increase habitat suitability. While any changes in 

forest species composition over two decades were most likely due to disturbances 

(e.g., wildfire, timber harvest, etc.) or natural succession, the potential for forest 

species composition changes resulting from changes in climate will need to be 

considered in future monitoring.

Figure 12—Oregon timber harvest between 1849 and 2010 (fig. 1 from Gale et al. 2012). The shaded area has the potential to become 

future northern spotted owl habitat by the middle of this century.
38

GENERAL TECHNICAL REPORT PNW-GTR-929

The recovery of future NSO habitat may be affected by climate change that 

could alter the pattern and frequency of large wildfire within the NSO’s range. Climate change is also expected to alter forest species composition within the Pacific 

Northwest by the end of the 21st century (Peterson et al. 2014). Subalpine forests are 

expected to recede in area while pine-dominated forests will likely expand. Both 

of these forest types are normally not used for nesting and roosting by NSOs, and 

these potential changes will affect amounts and distribution of future NSO habitat.

Geographic Pattern of Large Wildfires

The geographic distribution of large wildfires exceeding 1,000 ac (fig. 13) and the 

habitat loss from wildfire was highest in fire-prone areas of the range as delineated 

by Davis et al. (2011). Based on total area of habitat lost to wildfire (all federal 

lands), the Klamath provinces accounted for most (331,800 ac), followed by the 

Eastern Cascades (66,800 ac). A large amount (63,000 ac) of nesting/roosting habitat was lost to large wildfires in the southern half of the Oregon Western Cascades 

(table 5). Most of this habitat loss also occurred in the reserved LUAs, which were 

designed for the restoration and maintenance of older forests and NSO habitat. The 

physiographic provinces of the Klamath Mountains and Eastern Cascades exceeded 

the 2.5-percent-per-decade losses projected for reserved allocations (see table 5).

Habitat and Demographic Trends

This report focused on status and trends of NSO habitat; however, the status and 

trends of NSO populations were the focus of a second report developed concurrently 

(Dugger et al. 2016). The estimates of nesting/roosting habitat developed in the 

15-year report (Davis et al. 2011) were used to explore relationships between habitat 

conditions and NSO demographic parameters from 11 study areas (8 federal, 3 nonfederal) across the species’ range (Dugger et al. 2016). Likewise, we anticipate that 

the estimates of habitat developed in this report will be used in future demographic 

analyses. Indeed, the ultimate objective of NSO effectiveness monitoring has 

always been to link habitat to population demographics with good reliable statistical 

models, such that future monitoring would rely more on a model-driven, habitatbased approach (Lint et al. 1999). To date, we have not been able to accomplish this 

objective, and the uncertainties in mapping habitat described in the next section, 

and perhaps more so, the increased presence of BOs that compete for similar habitat 

with the result that they exclude NSO (Dugger et al., 2016, Wiens et al. 2014, Yackulic et al. 2014) pose significant challenges in achieving this monitoring objective. 

The relationships between habitat and NSO demographic parameters have 

been varied across the range, from one demographic study area to the next (e.g., 

Dugger et al. 2016, Forsman et al. 2011). However, when relationships are evident, 
39

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

Figure 13—Geographic distribution of large wildfires (≥1,000 ac) that have occurred within the owl’s range from 2010 to 

2014 in relation to large wildfire suitability modeling done in Davis et al. (2011).
40

GENERAL TECHNICAL REPORT PNW-GTR-929

they typically occur in the direction we might predict. For instance, more nesting/roosting habitat (or less habitat loss) has been associated with higher survival 

(Dugger et al. 2005, 2016; Franklin et al. 2000), fecundity (Dugger et al. 2016), and 

colonization rates (Dugger et al. 2011, 2016; Yackulic et al. 2014) of NSOs. Some 

of the strongest links between NSO demographics and habitat have been observed 

in relation to occupancy dynamics, with more suitable habitat typically associated with higher colonization rates and lower extinction rates, even when BOs are 

present in the landscape (Dugger et al. 2011, 2016; Yackulic et al. 2014). The results 

for federal demographic study areas from the most recent population meta-analysis 

(Dugger et al.2016) are summarized below (table 13).

Table 13—Habitat relationships with northern spotted owl population parameters in federal 

demographic study areas from top or competitive models in Dugger et al. 2016

Population 

parameter

Spatial scale 

of habitat 

covariates

Amount or 

percentage of 

nesting/roosting 

habitat (HAB)

Percentage of area 

with >50 percent 

nesting/roosting 

habitat within 800-

m radius (CORE)

Percentage of 

nesting/roosting 

habitat that had 

≥30% reduction 

in canopy cover 

during prior 3 

years (HC)

Percentage of area 

that interfaced 

(within 100 m) of 

nesting/roosting 

habitat (EDGE)

Reproduction Individual 

 study area

Strong positive 

relationships in 

TYE and NWC. 

Weak positive 

relationships in 

CLE, COA, 

and HJA

Weak positive 

relationship 

in CAS

None found None found

Survival Individual 

 study area

None found Weak positive 

relationship in KLA

Strong negative 

relationship in 

TYE. Weak 

negative 

relationship in 

CAS

Weak positive 

relationships in 

CLE and COA

Colonization 

 rates

Individual 

 territories

Strong positive 

relationships in 

OLY, COA, TYE, 

CAS, and NWC

None found Weak negative 

relationships in 

CLE and HJA

Strong positive 

relationship in KLA

Extinction rates Individual 

 territories

Strong negative 

relationship 

in HJA. 

Weak negative 

relationships in 

OLY, COA, 

and CAS

Strong negative 

relationships in KLA, 

and NWC

None found None found

Federal study area abbreviations are as follows: CLE = Cle Elum, OLY = Olympic, COA = Coast Ranges, HJA = H.J. Andrews, TYE = Tyee, 

KLA = Klamath, CAS = South Cascades, NWC = Northwest California
41

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

Uncertainty in Habitat Monitoring

Continued monitoring is important for informing managers on the effectiveness of 

the NWFP in achieving its goals and objectives. Information learned from it can be 

used in the adaptive management process. With each monitoring cycle, monitoring 

methods and technology have adapted also. Species distribution modeling for large 

landscapes is a relatively new science (Phillips et al. 2006) made possible by readily 

available broad-scale environmental data (e.g., remote sensed data) and advances in 

computing power. We use presence-only SDM methods because of the nature of the 

NSO location data available rangewide. Given the newness of these methods, caution has been advised in their use (Loehle et al. 2015, Yackulic et al. 2013). We exercised appropriate caution through the development of our modeling and calibration 

procedures as well as consideration and critical examination of our data sources, 

sampling biases, how species occurrence varied with environmental covariates, and 

the time and resources available for conducting this monitoring. 

Monitoring of habitat change across the large geographic range of the NSO was 

facilitated by the use of remotely sensed data. The habitat monitoring in this report 

relied heavily on imagery collected “passively” by the National Aeronautics and 

Space Administration’s Landsat satellite program. This imagery was converted 

into maps of forest structure and species composition by modeling relationships 

between on-the-ground data collected in forest inventory plots to geospatial environmental data (e.g., climate and topography), but most importantly, light being 

reflected by the forest canopy. The GNN variables for forest structure that we used 

had mean-plot accuracies that ranged from 0.56 to 0.77 (Pearson correlations). 

Forest species composition variables had mean Cohen kappas that ranged from 0.38 

to 0.4 (see table 1). Thus, errors in these data were transferred to the habitat models 

we produced. We tested our habitat models using known NSO locations and indeed, 

none of them were 100 percent accurate (see table 2). However, our map accuracies 

were fair to good and useful for broad-scale monitoring purposes. In the future, 

we may be able to improve map accuracy through the use of light detection and 

ranging (lidar) data. Lidar is a form of “active” remote sensing that provides direct 

measurements of forest vegetation and structure versus the inferred measures currently being used. A recent comparison of lidar- versus Landsat-based NSO habitat 

modeling and mapping showed that while both produced acceptable and similar 

areal estimates of nesting/roosting habitat, the lidar-based maps were more spatially 

accurate than Landsat-based maps (Ackers et al. 2015). Currently, lidar data do not 

provide the spatial or temporal coverage needed for monitoring habitat across the 

NSO’s range. 
42

GENERAL TECHNICAL REPORT PNW-GTR-929

The reliance of passively collected light measurements in forest mapping poses 

other monitoring challenges (Davis et al. 2015). This is especially when trying to 

measure habitat change over time when differences in sun angle, canopy shadowing, and atmospheric haze in imagery of the same area on different dates can result 

in false change. As described in the 15-year report (Davis et al. 2011, pgs. 48-49), 

we noted canopy shadowing created through light-intensity disturbances, such 

as thinning, resulted in erroneous GNN estimates of older forest attributes that 

were transferred to our habitat models. Uncertainty was highest for gains in older 

forests that make up nesting/roosting habitat. Gains in dispersal habitat, which 

includes younger forest, were less uncertain as were gains in the redwood region 

of the California Coast physiographic province where nesting/roosting habitat can 

develop rapidly over the course of a few decades. Detection of forest disturbance 

over two decades is more reliable and thus so was our estimate of habitat losses 

that were corroborated by the LandTrendr data. There were net gains in nesting/

roosting habitat in some physiographic provinces and net losses in others. All net 

changes in habitat were less than the error in our area estimates, thus considered not 

statistically significant. While we reported on net changes in this monitoring cycle, 

we consider habitat losses that were corroborated by forest-disturbance-changedetection data as the most reliable. 

Conclusion

During the first two decades of the NWFP, rangewide losses of nesting/roosting 

habitat on federal lands were estimated at 5.2 percent (474,300 ac) from wildfire; 

1.3 percent (116,100 ac) from timber harvesting; and 0.7 percent (59,800 ac) from 

insects, disease, or other natural disturbances. This accounted for a total rangewide 

loss of 7.2 percent, but we estimated an overall net decrease of 1.5 percent, owing to 

new nesting/roosting habitat recruitment. Rangewide, the observed rate of habitat 

loss on federal lands was less than what was anticipated when the NWFP was 

designed, mostly as a result of less timber harvesting than was anticipated. Losses 

from wildfire were slightly higher than anticipated in federal reserved LUAs at the 

range scale. Insects and disease accounted for less than 1 percent of losses. While 

dispersal habitat has shown a net increase of 2.2 percent on federal lands, dispersalcapable landscapes have been reduced in area by 5 percent, partially owing to 

losses of habitat on surrounding nonfederal lands but also owing to large wildfires 

on federal lands.
43

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

One of the goals of the NWFP was to protect and enhance habitat for the NSO 

on federal lands. The first step in achieving this goal was to reduce the rate at 

which habitat was being lost. Monitoring shows that the NWFP has been effective 

at achieving this. Eventually, the NWFP anticipated restoration of habitat within 

the large reserve network over the course of several decades. Two decades into the 

NWFP, we report that nesting/roosting habitat is still declining at the NWFP scale, 

but that recruitment is occurring in portions of the range and beginning to help 

offset losses. Based on past timber harvesting history (Gale et al. 2012) and current 

management of old clearcut plantations to accelerate the development of future 

habitat, significant habitat recruitment will likely be seen by the middle part of 

this century. 

Challenges remain: increasing concentrations of greenhouse gases and resultant 

climate change may expand the geographic extent and increase the frequency of 

large wildfires within the NSO range (Westerling et al. 2006). Changing climates 

may also cause large shifts in forest species compositions (Peterson et al. 2014), 

which will affect the suitability of forests for future nesting and roosting. And 

lastly, BOs are displacing NSOs from their historical territories at an increasing 

rate (Dugger et al., 2016) and may be forcing NSOs to use less suitable and more 

marginal habitat (Dugger et al. 2011, Wiens et al. 2014, Yackulic et al. 2104).

Acknowledgments

This report is the result of a large group effort over many years focused on monitoring the effectiveness of the NWFP. It would not have been possible without the 

continued hard work of many dedicated biologists who annually collect the NSO 

field data used to train and test our habitat models. Wall-to-wall maps of forest 

structure and species composition that we use as habitat model variables to produce 

maps of nesting/roosting habitat would not exist without the hard, dedicated work 

by the Landscape, Ecology, Modeling, Mapping, and Analysis team directed by 

Dr. Janet Ohmann. The mapping of forest vegetation benefited from the collaborative work with the Laboratory for Applications of Remote Sensing in Ecology 

research laboratory directed by Dr. Warren Cohen and the work of Dr. Robert Kennedy on the production of the LandTrendr change detection data set. We thank Drs. 

Peter Singleton, Betsy Glenn, Damon Lesmeister, Joan Hagar, and Katie Dugger for 

their reviews and constructive comments that resulted in a much improved report.
44

GENERAL TECHNICAL REPORT PNW-GTR-929

Metric Equivalents

When you know: Multiply by: To find:

Inches (in) 2.54 Centimeters (cm)

Feet (ft) 0.3048 Meters (m)

Acres (ac) 0.405 Hectares (ha)

Square feet per acre (ft2/ac) 0.2296 Square meters per hectare (m2/ha)

Square miles (mi2) 2.59 Square kilometers (km2)

Trees per acre (trees/ac) 2.47 Trees per hectare (trees/ha)

Tons (ton) 907.0 Kilograms (kg)

Tons per acre (ton/ac) 2.24 Megagrams per hectare (Mg/ha)

Cubic feet per acre (ft3/ac) 0.07 Cubic meters per hectare (m3/ha)

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Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats

Appendix: Habitat Suitability Histograms

The habitat histograms displayed in this appendix are based on habitat conditions at 

the time of the Northwest Forest Plan (NWFP) implementation (1993) and at the end 

of our analysis period in 2012. There are four pairs of histogram bars, one pair per 

nesting/roosting habitat suitability class. The first bar in the pair shows conditions 

at time 1 (1993), the second bar shows conditions at time 2 (2012). We provide an 

example histogram below to help with the interpretation of the histograms provided 

for each state and each physiographic province.

In the example above, we observe a slight decrease in unsuitable habitat 

between time 1 and time 2. We also observe a larger decrease in marginal habitat 

class during the same timeframe with a relatively similar increase in the suitable 

habitat class and very slight increase in the highly suitable habitat class. We can 

conclude that the decreases in the unsuitable and marginal classes were likely due to 

two forest successions resulting in increases in the suitable habitat classes. Most of 

the increase in suitable habitat occurred within the nonreserved land use allocation.

The tables under the graphs show the percentage of forest-capable lands having 

each habitat class as estimated from the habitat maps for both time periods. The 

percentages are split into nonreserved and reserved land use allocations. The 

habitat histograms on the following pages illustrate our best estimates of how 

habitat has changed since NWFP implementation. These graphs are primarily 

for interpretive purposes.
52

GENERAL TECHNICAL REPORT PNW-GTR-929
53

Northwest Forest Plan—The First 20 Years (1994-2013): Status and Trends of Northern Spotted Owl Habitats
54

GENERAL TECHNICAL REPORT PNW-GTR-929
Pacific Northwest Research Station

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