NOAA Technical Memorandum NMFS-NWFSC-118

Scientific Conclusions 

of the Status Review 

for Oregon Coast Coho Salmon 

(Oncorhynchus kisutch)

June 2012

U.S. DEPARTMENT OF COMMERCE

National Oceanic and Atmospheric Administration

National Marine Fisheries Service

Northwest Fisheries Science Center
NOAA Technical Memorandum

NMFS-NWFSC Series

The Northwest Fisheries Science Center of the National 

Marine Fisheries Service, NOAA, uses the NOAA Technical 

Memorandum NMFS-NWFSC series to issue scientific and 

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and edited. Documents published in this series may be cited 

in the scientific and technical literature.

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Alaska Fisheries Science Center, which has since been split 

into the Northwest Fisheries Science Center and the Alaska 

Fisheries Science Center. The NMFS-AFSC Technical 

Memorandum series is now used by the Alaska Fisheries 

Science Center.

Reference throughout this document to trade names does not 

imply endorsement by the National Marine Fisheries Service, 

NOAA.

This document should be referenced as follows:

Stout, H.A., P.W. Lawson, D.L. Bottom, T.D. Cooney, M.J. 

Ford, C.E. Jordan, R.G. Kope, L.M. Kruzic, G.R. Pess, G.H. 

Reeves, M.D. Scheuerell, T.C. Wainwright, R.S. Waples, 

E. Ward, L.A. Weitkamp, J.G. Williams, and T.H. Williams. 

2012. Scientific conclusions of the status review for Oregon 

coast coho salmon (Oncorhynchus kisutch). U.S. Dept. 

Commer., NOAA Tech. Memo. NMFS-NWFSC-118, 242 p.
NOAA Technical Memorandum NMFS-NWFSC-118

Scientific Conclusions 

of the Status Review 

for Oregon Coast Coho Salmon 

(Oncorhynchus kisutch)

Heather A. Stout, Peter W. Lawson, Daniel L. Bottom, 

Thomas D. Cooney, Michael J. Ford, Chris E. Jordan, 

Robert G. Kope, Lance M. Kruzic,1 George R. Pess, 

Gordon H. Reeves,2 Mark D. Scheuerell, Thomas C. Wainwright, 

Robin S. Waples, Eric Ward, Laurie A. Weitkamp, 

John G. Williams, and Thomas H. Williams3

Northwest Fisheries Science Center

2725 Montlake Boulevard East

Seattle, Washington 98112

1

NMFS Northwest Regional Office

2900 Northwest Stewart Parkway

Roseburg, Oregon 97471

2

U.S. Forest Service

Pacific Northwest Research Station

333 Southwest First Avenue

Portland, Oregon 97204

3

Southwest Fisheries Science Center

110 Shaffer Road

Santa Cruz, California 95060

June 2012

U.S. DEPARTMENT OF COMMERCE

National Oceanic and Atmospheric Administration

National Marine Fisheries Service
Most NOAA Technical Memorandums

NMFS-NWFSC are available at the 

Northwest Fisheries Science Center

Web site, http://www.nwfsc.noaa.gov

Copies are also available from the

National Technical Information Service

5285 Port Royal Road

Springfield, VA 22161

Phone orders: 1-800-553-6847

E-mail orders: orders@ntis.fedworld.gov

ii
iii

Table of Contents

List of Figures...............................................................................................................................................v

List of Tables..............................................................................................................................................vii

Executive Summary.....................................................................................................................................ix

Acknowledgments......................................................................................................................................xiii

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

Summary of Previous BRT Conclusions......................................................................................................7

ESU Determination...................................................................................................................................7

Status Evaluation in 1994.........................................................................................................................9

Status Evaluation in 1996.........................................................................................................................9

Status Evaluation in 2003.......................................................................................................................11

New Contributions to Understanding and Assessing Status of Oregon Coast Coho Salmon.....................14

ESU Delineation.....................................................................................................................................14

Artificial Propagation—Membership in the ESU...................................................................................15

Population Delineation ...........................................................................................................................15

Definition of Biogeographic Strata.........................................................................................................18

Biological Recovery Criteria Used to Inform Risk Assessment.............................................................18

New Comments...........................................................................................................................................20

Oregon Coast Coho Salmon Symposium....................................................................................................23

New Data and Updated Analyses................................................................................................................26

Current Biological Status........................................................................................................................26

Factors for Decline and Threats..............................................................................................................53

Overall Risk Assessments.........................................................................................................................114

Risk Matrix Approach ..........................................................................................................................115

Summary of Risk Conclusions.............................................................................................................117

Significant Portion of its Range Question ............................................................................................119

Glossary ....................................................................................................................................................121

References.................................................................................................................................................129

Appendix A: Threats Matrix and DSS Criteria.........................................................................................153

Appendix B: Disturbance..........................................................................................................................157
iv

Appendix C: Summary of Findings of the BRT-ODFW Habitat Trends Working Group.......................163

Introduction ..........................................................................................................................................163

Methods................................................................................................................................................165

Results ..................................................................................................................................................168

Summary...............................................................................................................................................172

Appendix D: Peer Reviews and Public Comments with the BRT’s Responses .......................................175

Comments of Eight Peer Reviewers.....................................................................................................175

Comments of the Oregon Department of Fish and Wildlife.................................................................193

Comments of the MidCoast Watersheds Council Coordinator ............................................................205

Comments of Douglas County, Oregon................................................................................................212
v

List of Figures

Figure 1. West Coast coho salmon ESUs ....................................................................................................3

Figure 2. Critical habitat designation for the OCCS ESU, February 2008 ..................................................5

Figure 3. Historical populations and biogeographic strata for OCCS ESU...............................................17

Figure 4. OCCS naturally produced recruits per spawner, 1972–2009 .....................................................28

Figure 5. OCCS naturally produced recruits, 1969–2008..........................................................................28

Figure 6. Comparison of historical and recent estimates of spawner abundance and 

preharvest recruits.......................................................................................................................................29

Figure 7. Trends in natural spawner abundance for the whole ESU and the five 

biogeographic strata....................................................................................................................................31

Figure 8. Trends in natural return ratio for the whole ESU and the five biogeographic strata ..................32

Figure 9. Releases of juvenile hatchery coho in the OCCS ESU by hatchery type from 

1980 to 2003 ...............................................................................................................................................43

Figure 10. Proportion of hatchery origin coho salmon in each stratum of the OCCS ESU, 

1994–2008 ..................................................................................................................................................44

Figure 11. Decision tree for the biological recovery criteria .....................................................................47

Figure 12. Truth value colors showing degree of certainty interpretation for colors found in 

Figure 11.....................................................................................................................................................48

Figure 13. The PDO index from 1900 through 2009.................................................................................57

Figure 14. Conceptual diagram of multiple pathways by which climate influences the salmon 

life cycle......................................................................................................................................................60

Figure 15. Barriers to fish passage.............................................................................................................67

Figure 16. Historic splash dam and log driving locations..........................................................................71

Figure 17. Beaver dam density in the OCCS ESU from 1998 to 2009......................................................75

Figure 18. Active road densities by fifth-field hydrologic unit .................................................................77

Figure 19. Distribution and intensity of vegetation disturbance from 1986 to 2008 .................................81

Figure 20. Ranking of river basins and the Umpqua subbasins by cumulative percent vegetation 

disturbance from 1986 to 2008 ...................................................................................................................82

Figure 21. Time series of cumulative area of vegetation disturbance for four river basins in the 

OCCS ESU .................................................................................................................................................83

Figure 22. Total area of vegetation disturbance in the Alsea River area of the OCCS ESU by four 

land ownership categories from 1986 to 2008............................................................................................84

Figure 23. Projected building densities, 2044............................................................................................92

Figure 24. Projected development zones, 2035 .........................................................................................95
vi

Figure 25. Locations of major estuaries.....................................................................................................97

Figure 26. Tidal estuary gains in strata of the OCCS ESU......................................................................100

Figure 27. EPA 303(d) water quality impaired waters ............................................................................105

Figure 28. EPA 303(d) listed streams with temperature impairment.......................................................106

Figure B-1. Distribution and intensity of vegetation disturbance from 1986 to 2008 .............................160

Figure B-2. Ranking of river basins and the Umpqua subbasins by cumulative percent vegetation 

disturbance from 1986 to 2008 .................................................................................................................161

Figure B-3. Time series of cumulative area of vegetation disturbance for four river basins in the 

OCCS ESU ...............................................................................................................................................162

Figure B-4. Total area of vegetation disturbance in the Alsea River area of the OCCS ESU by four 

land ownership categories from 1986 to 2008..........................................................................................162

Figure C-1. Map of Oregon coho spawning and rearing sites .................................................................164

Figure C-2. Box plots of habitat complexity, percent fine sediment in riffles, and volume of large 

woody debris by region for all sites..........................................................................................................166

Figure C-3. Illustration of year random effects for four hypothetical populations with a shared trend 

and different trends...................................................................................................................................167

Figure C-4. Illustration of multiple site visits with no process variation and process variation 

representing environmental stochasticity..................................................................................................168

Figure C-5. Posterior distributions of trend estimates for three measures of habitat complexity and 

two habitat metrics....................................................................................................................................171

Figure C-6. Posterior distributions of trend estimates for two habitat metrics........................................172
vii

List of Tables

Table 1. ESA chronology for the OCCS ESU .............................................................................................2

Table 2. Independent and dependent historical populations of OCCS ......................................................16

Table 3. OCN coho salmon spawners and recruits from 1969 to 2009, with approximate ocean 

exploitation rates.........................................................................................................................................27

Table 4. OPI hatchery marine survival calculated as adults per smolt from adult recruits and smolts 

in previous year, 1970–2008.......................................................................................................................34

Table 5. OCCS ESU spawning escapement reported by ODFW, 1990–2009...........................................35

Table 6. Hatchery influence at coho population, stratum, and ESU scales, 1994–2010............................36

Table 7. Biological recovery criteria definitions........................................................................................46

Table 8. Decision support system results by criterion and independent population, stratum, and ESU....49

Table 9. Decision support system results based on using area under the curve spawner density 

estimates for the critical abundance criterion for comparison with Wainwright et al ................................50

Table 10. VSP attributes related to the DSS criteria and results................................................................51

Table 11. Factors for decline and habitat limiting factors for OCCS ........................................................54

Table 12. Threats to OCCS ESU identified by NMFS NWR....................................................................54

Table 13. Threats to OCCS ESU identified by NMFS NWR and the 2009/2010 BRT.............................55

Table 14. Summary of effects of physical climate changes on OCCS by habitat type..............................61

Table 15. Primary and secondary limiting factors for independent populations in the OCCS ESU..........70

Table 16. Graphical representation of the maximum likelihood analysis and Bayesian analysis 

trend results.................................................................................................................................................87

Table 17. Trend analysis summary for five habitat metrics by region, including only sites 

designated as coho spawning/rearing habitat..............................................................................................88

Table 18. Trend analysis summary for two habitat metrics by region, using only sites that are not 

designated as coho salmon spawning/rearing habitat .................................................................................89

Table 19. Results of Kline et al. by biogeographic stratum in the OCCS ESU.........................................91

Table 20. Change in land use types predicted by Lettman et al.................................................................93

Table 21. Population or population aggregates with the largest estimated area of intertidal 

marsh habitat.............................................................................................................................................100

Table 22. Summary of recent restoration versus current and historical estimates of intertidal 

marsh habitats aggregated across populations within OCCS ESU biogeographic strata..........................101

Table 23. Oregon Department of State Lands summary of wetland fill, compensatory wetland 

mitigation, enhancement and restoration, and OWEB-funded restoration projects authorized/

completed from 1 July 2000 to 30 June 2004 in acres..............................................................................103
viii

Table 24. BRT summary comments on threats........................................................................................112

Table 25. Risk Matrix template used by the BRT to capture comments and assessment of risk.............116

Table 26. FEMAT voting sheet ...............................................................................................................116

Table 27. Assessment of the risk associated with each of four demographic factors..............................117

Table A-1. Threats matrix used by Oregon Coast Coho Salmon BRT....................................................154

Table A-2. Descriptions, metrics, data sets, and sources for DSS criteria...............................................155

Table C-1. Individual habitat metrics used by the HTWG for the trend analysis, the HTWG 

codes, and the transformations used to achieve normality........................................................................165

Table C-2. Differences between DIC scores between four competing models of changes in 

habitat metrics over time...........................................................................................................................168

Table C-3. Maximum likelihood estimates of trend parameters by region for two measures of 

habitat complexity and two habitat metrics ..............................................................................................169

Table C-4. Graphical representation of the maximum likelihood analysis and Bayesian analysis 

trend results...............................................................................................................................................170

Table C-5. Bayesian trend estimates applying the BRT’s trend model to the HTWG’s data set ............173
ix

Executive Summary

Beginning in the 1990s, the National Marine Fisheries Service (NMFS) conducted a 

series of reviews of the status of West Coast populations of Pacific salmon and steelhead 

(Oncorhynchus spp.) with respect to the U.S. Endangered Species Act (ESA). This report 

summarizes the scientific conclusions of the most recent status review of the Oregon Coast Coho 

Salmon (Oncorhynchus kisutch) (OCCS) Evolutionarily Significant Unit (ESU).

On 10 August 1998, NMFS first listed the OCCS ESU as threatened under the ESA 

(NMFS 1998). From 2000 until 2008, considerable litigation surrounded the listing status of this 

species. (Additional information is online at http://www.nwr.noaa.gov/ESA-Salmon-Listings

/Salmon-Populations/Alsea-Response/Alsea-OCC.cfm.) The OCCS’s listing status changed 

between “not warranted for listing” and “threatened” several times during this period. The most 

recent determination listed the ESU as threatened (NMFS 2008). As part of a legal settlement, 

NMFS agreed to initiate a new status review of OCCS on 29 April 2009 (NMFS 2009a). To 

conduct the status review, NMFS formed a biological review team (BRT) to evaluate the risk of 

extinction of the OCCS ESU based on the best available information. NMFS asked the BRT to 

judge whether the ESU was at low, moderate, or high risk of extinction based on current 

biological status and existing and projected threats, and to give particular attention to the status 

and trend of freshwater habitat conditions and marine survival conditions.

The BRT used a variety of information sources for this review, including the scientific 

literature; data and reports from federal, state, local, and tribal government sources; and 

information submitted by nongovernmental organizations. The BRT hosted a symposium in 

Corvallis, Oregon, on 14 September 2009, where the State of Oregon, comanagers, and other 

interested parties were invited to make presentations of scientific information related to OCCS 

status. The BRT met 15 September 2009 and 8−10 December 2009, and released its preliminary 

report 25 May 2010, concluding that the OCCS ESU was at moderate risk of extinction. 

Concurrent with the release of the preliminary status review report, NMFS proposed to retain the 

threatened listing of the OCCS ESU and invited public comment on the proposal (NMFS 2010, 

FR 75:29489–29506). In addition, the BRT solicited technical review of the draft status report 

from nine independent scientists selected from the academic and scientific community. Each of 

these reviewers is an expert in salmon biology, risk assessment methodology, ocean/salmon 

ecology, climate trend assessment, or landscape-scale habitat assessment. Eight of the reviewers 

responded.

This BRT report is a revision of the 25 May 2010 preliminary report. In revising the 

report, the BRT considered the comments from the expert reviewers, the scientific or technical 

comments submitted during the public comment period, updated spawner counts, other 

biological information that became available between May and December 2010, and the results 

of a joint Oregon Department of Fish and Wildlife (ODFW)/NMFS working group that 
x

reanalyzed freshwater habitat trend data. The BRT met on 18 January 2011 to discuss the 

updated information and analysis and reach a conclusion on the extinction risk of the OCCS.

In the past, BRTs have used a variety of methods to evaluate different categories of risk 

contributing to overall risk to an ESU. After 2000 the method was standardized to use a risk 

matrix method based on the four major criteria identified in the NMFS viable salmonid 

populations document (McElhany et al. 2000): abundance, growth rate/productivity, spatial 

structure, and diversity. For this analysis, the BRT followed that approach, but also included the 

work of the Oregon and Northern California Coast Technical Recovery Team on historical 

population structure (Lawson et al. 2007) and biological recovery criteria (Wainwright et al. 

2008) as additional sources of information on OCCS status.

After considering the new and updated information, the BRT was uncertain about the 

status of the ESU, with opinion about evenly split between “moderate risk” and “not at risk,” and 

a small minority indicating “high risk.” Overall, a slight majority of BRT opinion considered the 

ESU to be at moderate or high risk of extinction. The uncertainty in risk status was largely due 

to the difficulty in balancing the clear improvements in some aspects of the ESU’s status over the 

last 15 years against persistent threats driving the longer term status of the ESU, which probably 

have not changed over the same time frame and are predicted to degrade in the future.

The BRT concluded that some aspects of the ESU’s status have clearly improved since 

the initial status review in the mid-1990s (Weitkamp et al. 1995). In particular, spawning 

escapements were higher in some recent years than they had been since 1970. Recent total 

returns (preharvest recruits) were also substantially higher than the low extremes of the 1990s, 

but still mostly below levels of the 1960s and 1970s. The BRT attributed these increases largely 

to a combination of lower harvest rates, reduced hatchery production, and improved ocean 

conditions. The BRT also noted that the ESU contained relatively abundant wild populations 

throughout its range, and that additional improvements to status from ongoing and past 

reductions in hatchery production could be expected in the future.

Despite these positive factors, the BRT had considerable concerns about the long-term 

viability of the ESU. Even with the recent increases, spawning abundance remains at 

approximately 10% of estimated historical spawning abundance. Despite some improvements in 

productivity in the early 2000s, the BRT was concerned that the overall productivity of the ESU 

remains low compared to what was observed as recently as the 1960s and 1970s. The BRT was 

also concerned that most of the improvement in productivity seen in the early 2000s was likely 

due to improved ocean conditions, rather than (presumably more lasting) improvements in 

freshwater conditions. The BRT noted that the legacy of past forest management practices

combined with lowland agriculture and urban development have resulted in a situation in which 

the areas of highest potential habitat capacity are now severely degraded. The combined 

ODFW/NMFS analysis of freshwater habitat trends for the Oregon coast found little evidence for 

an overall improving trend in freshwater habitat conditions since the mid-1990s and evidence of 

negative trends in some areas, a result which concerned the BRT. The BRT was also concerned 

that recent changes in the protection status of beaver (Castor canadensis), an animal which 

creates coho salmon habitat, could result in further negative trends in habitat quality.
xi

The BRT was particularly concerned that the long-term loss of high value rearing habitat 

has increased the vulnerability of the ESU to near-term and long-term climate effects. In the 

short term, the ESU could rapidly decline to the low abundance seen in the mid-1990s when 

ocean conditions cycled back to a period of poor survival for coho salmon. The BRT was also 

concerned that global climate change will lead to a long-term downward trend in freshwater and 

marine coho salmon habitat compared to current conditions. There was considerable uncertainty 

about the magnitude that most of the specific effects of climate change will have on salmon 

habitat, but the BRT was concerned that most changes associated with climate change are 

expected to result in poorer and more variable habitat conditions for OCCS in freshwater and 

marine environments.
xii
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Acknowledgments

We are grateful to the large number of people who participated in collecting and 

analyzing the information used in this status review, including Kelly Christiansen and Kelly 

Burnett, U.S. Forest Service; and Carol Volk, Jonathon Malstedt, Chris Moyer, Katie Barnas, 

Monica Diaz, and David Hamm, Northwest Fisheries Science Center. We also appreciate the 

assistance of Joy Vaughn, Oregon Department of State Lands; Andrew Herstrom, Oregon 

Department of Forestry; and Oregon Department of Fish and Wildlife (ODFW) Habitat Trends 

Working Group members Kim Jones, Kara Anlauf, and Jeff Rodgers.

We are also grateful for the contributions of participants in the September 2009 Oregon 

Coast Coho Salmon Symposium: Kelly Moore and Kim Jones, ODFW; Suzanne Knapp, Oregon 

State Governor’s Office; Jim Paul, Oregon Department of Forestry; Robert Kennedy, Oregon 

State University; Joe Ebersole, U.S. Environmental Protection Agency; Paul Engelmeyer, Native 

Fish Society; Chris Frissell, Pacific Rivers Council; David Loomis, Douglas County 

Commissioners; Stan van de Wetering, Confederated Tribe of Siletz Indians; and Joe Moreau, 

U.S. Bureau of Land Management.
xiv
Introduction

Coho salmon (Oncorhynchus kisutch) is a widespread species of Pacific salmon, 

spawning and rearing in rivers and streams around the Pacific Rim from Monterey Bay in 

California north to Point Hope, Alaska, through the Aleutians, and from the Anadyr River in 

Russia south to Korea and northern Hokkaido, Japan (Godfrey et al. 1975, Laufle et al. 1986). 

From central British Columbia south, the vast majority of coho salmon adults return to spawn as 

3-year-olds, having spent approximately 18 months in freshwater and 18 months in saltwater 

(Gilbert 1912, Pritchard 1940, Sandercock 1991). The primary exceptions to this pattern are 

jacks, sexually mature males that return to freshwater to spawn after only 5 to 7 months in the 

ocean. West Coast coho salmon smolts typically leave freshwater in the spring (April to June) 

and when sexually mature reenter freshwater from September to November and spawn from 

November to December and occasionally into January (Sandercock 1991). Coho salmon 

spawning habitat consists of small streams with stable gravels. Summer and winter freshwater 

habitats most preferred by young salmon consist of quiet areas with low flow, such as backwater 

pools, beaver (Castor canadensis) ponds, dam pools, and side channels (Reeves et al. 1989).

For purposes of U.S. Endangered Species Act (ESA) listings, coho salmon status has 

been reviewed repeatedly beginning in 1990. The first two reviews were in response to petitions 

to list coho salmon in the lower Columbia River and Scott and Waddell creeks in central 

California. Based on these reviews, the National Marine Fisheries Service (NMFS) concluded 

that no populations warranted protection under the ESA in the lower Columbia River (Johnson et 

al. 1991, NMFS 1991a), and that the Scott Creek and Waddell Creek populations were part of a 

larger, undescribed evolutionarily significant unit (ESU) (Bryant 1994, NMFS 1994).

Oregon Coast coho salmon (OCCS) were first petitioned for listing in 1993 (NMFS 

1993). For a chronology of the legal history of this species, see Table 1. This and other petitions 

led NMFS to initiate a review of West Coast (Washington, Oregon, and California) coho salmon 

populations. This 1995 coast-wide review identified six coho salmon ESUs (Figure 1): the three 

southernmost ESUs (central California, northern California/southern Oregon and Oregon coast) 

were proposed for listing, two ESUs (Puget Sound/Strait of Georgia and lower Columbia 

River/southwest Washington) were identified as candidates for future consideration for listing,

and one ESU (Olympic Peninsula) was deemed “not warranted” for listing (NMFS 1995, 

Weitkamp et al. 1995). In 1996 a biological review team (BRT) updated the status review for 

proposed and candidate coho salmon ESUs (NMFS 1996a, 1996b, 1996c). However, because of 

the scale of the review, requests from comanagers for additional time to comment on the 

preliminary conclusions, and the legal obligations of NMFS, the status review was finalized for 

proposed coho salmon ESUs in 1997 (NMFS 1997d) but not for candidate ESUs. In May 1997 

NMFS listed the Southern Oregon/Northern California Coast (SONCC) Coho Salmon ESU as 

threatened (NMFS 1997b), while it announced that listing of the OCCS ESU was not warranted 

due to conservation measures in the Oregon Coastal Salmon Restoration Initiative (OCSRI) plan 
2

Table 1. ESA chronology for the OCCS ESU.

Date Action

May 2010 NMFS proposes to retain ESA threatened status of OCCS.

April 2009 NMFS initiates ESA status review of OCCS.

February 2008 In accordance with district court opinion, NMFS lists OCCS as threatened under the 

ESA.

October 2007 U.S. District Court in Oregon invalidates January 2006 decision not to list OCCS.

July 2007 U.S. District Court in Oregon rules that NMFS’ decision not to list OCCS is 

“arbitrary, capricious, contrary to the best available evidence, and a violation of the 

ESA.”

June 2006 Trout Unlimited challenges NMFS’ decision not to list OCCS.

January 2006 NMFS concludes that OCCS are “not likely to become endangered” in foreseeable 

future and therefore listing them under ESA is not warranted; agency withdraws 

ESA listing proposal.

June 2005 NMFS releases final ESA hatchery listing policy and announces 6-month extension 

on listing determination for OCCS.

May 2005 Oregon releases final report of its Coastal Coho Assessment, concluding OCCS are 

viable and likely to persist into foreseeable future.

February 2005 NMFS requests public review and comment on Oregon’s draft Coho Project Report.

June 2004 NMFS formally proposes to list OCCS as “threatened” under ESA and issues draft 

hatchery policy.

October 2003 Oregon begins Coastal Coho Project to evaluate effectiveness of Oregon Plan at 

recovering OCCS; state and NMFS work jointly on project.

November 2002 NMFS convenes OCCS Technical Review Team, charged with establishing 

biologically based delisting criteria and ESA recovery goals, and serving as science 

advisor to recovery planning.

July 2002 NMFS responds to ESA petition to redefine OCCS population.

February 2002 NMFS initiates ESA status review of West Coast salmon, including OCCS.

November 2001 NMFS begins developing new hatchery policy to address issues raised in Hogan 

decision and says it will apply new policy to all West Coast ESA-listed salmon and 

steelhead.

September 2001 Alsea Decision, U.S. District Court Judge Michael Hogan in Oregon finds that the 

ESA does not allow NMFS to split a salmon ESU into two components—hatchery 

and wild—then list only one of those components; functional effect of ruling is to 

delist OCCS.

August 1998 NMFS lists OCCS as threatened under ESA.

June 1998 Federal District Court for Oregon rules that “not warranted” determination for 

OCCS is arbitrary and capricious, saying the ESA doesn’t allow NMFS to consider 

biological effects of future or voluntary conservation measures.

May 1997 NMFS determines OCCS is “not warranted” for listing under the ESA, based in part 

on Oregon’s conservation measures contained in the plan.

March 1997 Oregon completes its Salmon Initiative Plan and submits it to NMFS.

October 1995 Oregon embarks on its Coastal Salmon Restoration Initiative to conserve and 

restore coastal salmon and steelhead.

July 1995 NMFS proposes to list OCCS as threatened under the ESA.

October 1993 NMFS receives petition from Pacific Rivers Council and 22 others requesting the 

agency list OCCS salmon under the ESA.
3

Figure 1. West Coast coho salmon ESUs.
4

(NMFS 1997b). This finding for OCCS was overturned by the Federal District Court for Oregon 

in August 1998 and the ESU was listed as threatened (NMFS 1998).

On 10 September 2001, Judge Michael R. Hogan, ruling in Alsea Valley Alliance v. 

Evans for the U.S. District Court for the District of Oregon, found that for the OCCS ESU,

“NMFS’s listing decision is arbitrary and capricious, because the Oregon Coast ESU includes 

hatchery spawned and naturally spawned coho salmon, but the agency’s listing decision 

arbitrarily excludes hatchery spawned coho. Consequently, the listing is unlawful” (161 F. Supp. 

2d 1154, D. Oreg. 2001). The lawsuit was brought by the Alsea Valley Alliance, partly in 

response to an action by the Oregon Department of Fish and Wildlife (ODFW) to terminate a 

domesticated coho salmon broodstock at the Fall River Hatchery on the Alsea River.

The effect of the ruling was to delist the OCCS ESU. The ruling was appealed by the 

appellant interveners to the U.S. Court of Appeals for the Ninth Circuit. On 14 December 2001 

the court stayed the District Court ruling pending final disposition of the appeal (Alsea Valley 

Alliance v. Evans, Ninth Circuit appeal, No. 01-36071). This returned the OCCS ESU to 

threatened status under the ESA. In response NMFS initiated development of a new hatchery 

policy to address issues raised in the ruling.

In November 2002 NMFS convened the OCCS Workgroup (hereafter, workgroup), a 

subcommittee of the Oregon/Northern California Coast (ONCC) Technical Recovery Team 

(TRT). This workgroup was charged with establishing biologically based recovery criteria and 

ESA recovery goals as well as providing scientific advice to recovery planners. Results of the 

workgroup deliberations are published in Lawson et al. (2007) and Wainwright et al. (2008). In 

October 2003 Oregon began its Coastal Coho Project to evaluate the effectiveness of the Oregon 

Plan at recovering OCCS.1

The next coho salmon BRT met in January, March, and April 2003 as part of a coastwide review of listed species to determine what portions of the artificially propagated salmon in 

each ESU should be listed with natively spawned fish and to discuss new data and determine 

whether conclusions of the original BRTs should be modified as the result of new information. 

In June 2004 NMFS published the proposal to list the OCCS ESU as threatened under the federal 

ESA (NMFS 2004a) and issued its draft hatchery policy (NMFS 2004b). The hatchery policy 

was finalized in 2005 (NMFS 2005a).

In May 2005 Oregon released the final Coast Coho Assessment (Nicholas et al. 2005), 

concluding that the OCCS ESU was viable and likely to persist into the foreseeable future. 

Subsequently, in January 2006 NMFS concluded that OCCS are “not likely to become 

endangered” in the foreseeable future, therefore that listing them under the ESA was not 

warranted, and withdrew its listing proposal (NMFS 2006).

In June 2006 Trout Unlimited challenged NMFS’s decision not to list the OCCS ESU. In 

July 2007 a U.S. District Court in Oregon invalidated the January 2006 decision not to list the 

OCCS ESU. In February 2008, in accordance with the court’s decision, NMFS listed the ESU as 

threatened under the ESA (NMFS 2008) and declared critical habitat (Figure 2).

 1 Comments from the workgroup on the Oregon Coastal Coho Conservation Plan are online at http://www.oregon

.gov/OPSW/cohoproject/PDFs/NOAA_Conservation_Plan_comments.pdf.
5

Figure 2. Critical habitat designation for the OCCS ESU, February 2008.
6

In 2008 NMFS, its Northwest Regional Office (NWR), and the Northwest Fisheries 

Science Center (NWFSC) formed the Recovery Implementation Science Team, a regional 

science team that provides scientific advice related to recovery plan implementation. Several 

TRTs, including the ONCC TRT, continued to provide local science support as subteams of the 

Recovery Implementation Science Team. In April 2009 NMFS announced a new status review 

for the OCCS ESU (NMFS 2009a) and formed a BRT.

2

 The BRT met in September and 

December 2009.

This technical memorandum summarizes new information and the preliminary BRT 

conclusions on the OCCS ESU. It is intended as a summary of the information considered by the 

BRT in making its conclusion. It does not include specific recommendations for management; 

that is the role of the recovery plan. Many large sets of past analyses and conservation 

documents are included in this information and it is the goal of this presentation to include their 

information by reference to keep this document to a reasonable size. Details of previously 

published analytical methods are referred to in citations; details of those analyses can be found in 

the previously published documents. However, the BRT has utilized some analyses not 

previously published in this particular format, so a more detailed description of those is included 

in the appendices.

 2 The BRT consisted of Peter W. Lawson (chair), John Williams, Laurie Weitkamp, Robin Waples, Thomas 

Wainwright, Mark Scheuerell, George Pess, Robert Kope, Mike Ford, Chris Jordan, Tom Cooney, and Dan Bottom,

NWFSC; Lance Kruzic, NMFS Northwest Regional Office; Tommy Williams, NMFS Southwest Fisheries Science 

Center; and Gordon Reeves, U.S. Forest Service. Heather Stout, NWFSC, acted as administrative staff for the BRT.
7

Summary of Previous BRT Conclusions

The OCCS ESU has been the subject of detailed assessments in three previous status 

reviews: one in 1994 (Weitkamp et al. 1995), another in 1996 (NMFS 1997d), and a third in 

2003 (Good et al. 2005).

ESU Determination

As amended in 1978, the ESA allows listing of “distinct population segments” of 

vertebrates as well as named species and subspecies. However, the ESA provides no specific 

guidance for determining what constitutes a distinct population. To clarify the issue for Pacific 

salmon, NMFS published a policy describing how the agency will apply the definition of species 

in the ESA to anadromous salmonid species, including sea-run cutthroat trout (Oncorhynchus 

clarkii clarkii) and steelhead (O. mykiss) (NMFS 1991b). A more detailed discussion of this 

topic appeared in the NMFS definition of species paper (Waples 1991).

The NMFS policy stipulates that a salmon population (or group of populations) will be 

considered distinct for purposes of the ESA if it represents an ESU of the biological species. An 

ESU is defined as a population that 1) is substantially reproductively isolated from conspecific 

populations and 2) represents an important component of the evolutionary legacy of the species. 

The term evolutionary legacy is used in the sense of inheritance—that is, something received 

from the past and carried forward into the future. Specifically, the evolutionary legacy of a 

species is the genetic variability that is a product of past evolutionary events and that represents 

the reservoir on which future evolutionary potential depends. Conservation of these genetic 

resources should help ensure that the dynamic process of evolution will not be unduly 

constrained in the future.

The NMFS policy identifies a number of types of evidence that should be considered in 

the species determination. For each of the criteria, the NMFS policy advocates a holistic 

approach that considers all types of available information as well as their strengths and 

limitations. Isolation does not have to be absolute, but it must be strong enough to permit 

evolutionarily important differences to accrue in different population units. Important types of 

information to consider include natural rates of straying and recolonization, evaluations of the 

efficacy of natural barriers, and measurements of genetic differences between populations. Data 

from protein electrophoresis or DNA analyses can be particularly useful for this criterion,

because they reflect levels of gene flow that have occurred over evolutionary time scales.

The key question with respect to the second criterion is: If the population became extinct, 

would this represent a significant loss to the ecological/genetic diversity of the species? Again, a 

variety of types of information should be considered. Phenotypic and life history traits such as 

size, fecundity, migration patterns, and age and time of spawning may reflect local adaptations of 

evolutionary importance, but interpretation of these traits is complicated by their sensitivity to 
8

environmental conditions. Data from protein electrophoresis or DNA analyses provide valuable 

insight into the process of genetic differentiation among populations, but little direct information 

regarding the extent of adaptive genetic differences. Habitat differences suggest the possibility 

for local adaptations, but do not prove that such adaptations exist.

The OCCS ESU was identified as one of six West Coast coho salmon ESUs in a coastwide coho status review NMFS published in 1995 (Weitkamp et al. 1995). The six ESUs 

identified in that status review were: Puget Sound/Strait of Georgia, Olympic Peninsula, 

Columbia River/southwest Washington coast, Oregon coast, northern California/southern 

Oregon coast, and central California coast (Weitkamp et al. 1995). Subsequently, the Columbia 

River/Southwest Washington Coast ESU was divided into two ESUs (Columbia River and 

Southwest Washington Coast [NMFS 2001]), resulting in seven coho salmon ESUs.

Weitkamp et al. (1995) considered a variety of factors in delineating ESU boundaries, 

including environmental and biogeographic features of the freshwater and marine habitats 

occupied by coho salmon, patterns of life history variation and patterns of genetic variation, and 

differences in marine distribution among populations based on tag recoveries. Regarding the 

OCCS ESU, Weitkamp et al. (1995) concluded that Cape Blanco to the south and the Columbia 

River to the north constituted significant biogeographic and environmental transition zones that 

likely contributed to reproductive isolation and evolutionary distinctiveness for coho salmon 

inhabiting opposite sides of these features. These findings were reinforced by discontinuities in 

the ocean tag recoveries at these same locations. Finally, the available genetic data also 

indicated that OCCS north of Cape Blanco formed a discrete, although quite variable, group 

compared to samples from south of Cape Blanco or the Columbia River and northward.

Based on these sources of information, Weitkamp et al. (1995) described the OCCS ESU 

as follows:

This ESU covers much of the Oregon coast, from Cape Blanco to the mouth of 

the Columbia River, an area with considerable physical diversity ranging from 

extensive sand dunes to rocky outcrops. With the exception of the Umpqua 

River, which extends through the Coast Range to drain the Cascade Mountains, 

rivers in this ESU have their headwaters in the Coast Range. These rivers have a 

single peak of flow in December or January and relatively low flow in late 

summer. Upwelling north of Cape Blanco is much less consistent and weaker 

than in areas south of Cape Blanco. Sitka spruce is the dominant coastal 

vegetation and extends to Alaska. Precipitation in coastal Oregon is higher than 

in southern Oregon/northern California but lower than on the Olympic Peninsula. 

Oregon coast coho salmon are caught primarily in Oregon marine waters and have 

a slightly earlier adult run timing than populations farther south.

Genetic data indicate that Oregon coast coho salmon north of Cape Blanco form a 

discrete group, although there is evidence of differentiation within this area. 

However, because there is no clear geographic pattern to the differentiation, the 

area is considered to be a single ESU with relatively high heterogeneity.
9

Status review updates in 2001 (NMFS 2001) and 2003 (Good et al. 2005) did not 

reconsider ESU boundaries, with the exception of the Columbia River/southwest Washington 

Coast.

Status Evaluation in 1994

For the first review in 1994 (Weitkamp et al. 1995), extensive survey data were available 

for coho salmon in the Oregon coast region and information on trends and abundance was better 

for the OCCS ESU than for the more southerly ESUs. Overall, spawning escapements for OCCS 

had declined substantially during the twentieth century and natural production was at 5 to 10% of 

production in the early 1900s. Productivity and abundance showed clear long-term downward 

trends. Average spawner abundance had been relatively constant since the late 1970s, but 

preharvest abundance was declining. Average recruits per spawner were also declining and 

average spawner:spawner ratios were below replacement levels in the worst recent years. OCCS 

populations in most major rivers were found to be heavily influenced by hatchery stocks, 

although some tributaries may have maintained native stocks. The 1994 BRT noted widespread 

habitat degradation as a risk factor that, along with low abundance, posed a risk to the ESU due 

to increased variability. Because of these risks, the 1994 BRT concluded that the ESU was likely 

to become endangered in the foreseeable future if present trends continued.

Status Evaluation in 1996

Despite relatively good information on trends and abundance, the 1996 BRT (NMFS 

1997d) faced some important uncertainties related to lack of information. Main uncertainties in 

the assessment included the extent of straying of hatchery fish, the influence of such straying on 

natural population trends and sustainability, the condition of freshwater habitat, and the influence 

of ocean conditions on population sustainability. For absolute abundance, the 1996 total average 

(5-year geometric mean) spawner abundance (44,500) and corresponding ocean run size (72,000) 

were less than one-tenth of ocean run sizes estimated in the late 1800s and early 1900s, and only 

about one-third of 1950s ocean run sizes (ODFW 1995). These abundances were well below 

estimated freshwater habitat production capacity for this ESU of run sizes of 141,000 under poor 

ocean conditions and 924,000 under good ocean conditions (OCSRI Science Team 1997). 

Abundance was unevenly distributed within the ESU through the early to mid-1990s.

Long-term trend estimates through 1996 showed that for escapement, run size, and 

recruits per spawner, trends were negative, while 6 years of stratified random survey population 

estimates showed an increase in escapement and decrease in recruitment. Furthermore, in the 

1990s recruitment remained only a small fraction of average levels in the 1970s. Although 

spawner:spawner ratios had remained above replacement since the 1990 broodyear, 

recruit:spawner ratios for 1991–1993 broodyears were among the lowest on record. Recruits per 

spawner continued to decline after the OCCS ESU was reviewed in 1994. And the new data 

from 1994 to 1996 did not change the overall pattern of decline. This pattern was one of decline 

coupled with peaks in recruits per spawner every 4 to 5 years, with the height of the peaks 

declining over time. Risks that this decline in recruits per spawner posed to sustainability of 

natural populations, in combination with strong sensitivity to unpredictable ocean conditions, 
10

were the most serious concern the OCCS BRT identified in 1996, including whether recent 

ocean and freshwater conditions would continue into the future.

Widespread spawning by hatchery fish, as indicated by scale data, continued to be a 

major concern to the 1996 BRT, even though Oregon had recently made some significant 

changes in its hatchery practices including reduced production levels in some basins, switching 

to on-station smolt releases, and minimizing fry releases. Uncertainty regarding the true extent 

of hatchery influence on natural populations, however, was a strong concern. Another concern 

the BRT discussed in 1996 was asymmetry in the distribution of natural spawning in this ESU; a 

large fraction of the naturally spawned fish occurred in the southern portion. Northern 

populations were also relatively worse off by almost every other measure: steeper declines in 

abundance and recruits per spawner, higher proportion of naturally spawning hatchery fish, and 

more extensive habitat degradation.

With respect to habitat, the 1996 BRT had two primary concerns: 1) that habitat capacity 

for the OCCS ESU had significantly decreased from historical levels; and 2) that the Nickelson 

and Lawson (1998) model predicted that, during poor ocean survival, only high-quality habitat is 

capable of sustaining coho populations and subpopulations dependent on medium- and lowquality habitats would likely become extinct. Both of these concerns caused the 1996 BRT to 

consider risks from habitat loss and degradation to be relatively high for this ESU. The effects of 

the 1996 floods were not specifically discussed in this forum, but were included in factors for 

decline identified by NMFS NWR.

In addition to considering status based on recent conditions, the 1996 BRT was asked to 

consider ESU status if two sets of measures from the OCSRI were implemented: 1) harvest 

management reforms and 2) hatchery management reforms.

Some 1996 BRT members felt that the harvest measures were the most encouraging part 

of the OCSRI plan, representing a major change from previous management. However, there 

was concern among some of the 1996 BRT members that the harvest plan might be seriously 

weakened when it was reevaluated in 2000, while the ability to monitor nontarget harvest 

mortality and to control overall harvest impacts were also seen as a source of uncertainty. Of the 

proposed hatchery measures, the 1996 BRT thought substantial reductions in smolt releases 

would have the most predictable benefit for natural populations and marking all hatchery fish 

was anticipated to resolve uncertainties about the magnitude of those interactions.

In 1996 the BRT concluded that, assuming current conditions continued into the future 

(and that proposed harvest and hatchery reforms were not implemented), the OCCS ESU was not 

at significant short-term risk of extinction, but likely to become endangered in the foreseeable 

future. A minority disagreed, believing that the ESU was not likely to become endangered. The 

BRT generally agreed that implementation of the OCSRI’s harvest and hatchery proposals would 

have a positive effect on the ESU’s status, but was about evenly split as to whether the effects 

would be substantial enough to move the ESU out of the “likely to become endangered” 

category.
11

Status Evaluation in 2003

The OCCS ESU continued to present challenges to those assessing extinction risk in 

2003. The 2003 BRT (Good et al. 2005) found several positive features compared to the 

previous assessment in 1996. For example, adult spawners for the ESU in 2001 and 2002 

exceeded the number observed for any year in the past several decades and preharvest run size 

rivaled some of the high values seen in the 1970s (although well below historical levels), 

including increases in the formerly depressed northern part of the ESU. Hatchery reforms were 

increasingly being implemented and the fraction of natural spawners that were first generation 

hatchery fish were reduced in many areas, compared to highs in the early to mid-1990s.

On the other hand, the years of good returns just prior to 2003 were preceded by 3 years 

of low spawner escapements—the result of 3 consecutive years of recruitment failure, in which 

the natural spawners did not replace themselves, even in the absence of any directed harvest. 

These 3 years of recruitment failure were the only such instance observed in the entire time 

series. Whereas the increases in spawner escapement just prior to 2003 resulted in long-term 

trends in spawners that were generally positive, the long-term trends in productivity as of 2003 

were still strongly negative.

For the OCCS ESU, the 2003 BRT received updated estimates of total natural spawner 

abundance based on stratified random survey techniques, broken down by ODFW’s monitoring 

areas (Figure 29 in Lawson et al. 2007), for 10 major river basins and for the coastal lakes 

system.3 In 2003 the total 3-year geometric mean spawner abundance was estimated at about 

140,600 with spawners more evenly distributed than they had been previously.

The 2003 BRT used ODFW stratified random survey escapement data that indicated 

ESU-wide spawning escapement reached 30-year highs in 2001 and 2002. By contrast, in return 

years 1997–1999 (broodyears 1994–1996), and for the first time on record (since 1950), recruits 

failed to replace the parental spawners: a recruitment failure occurred in all three brood cycles, 

even before accounting for harvest-related mortalities. From 1999 until 2003, improving marine 

survival and higher rainfall were thought to be the factors contributing to an upswing in wild 

recruitment. However, it was far from certain that favorable marine conditions would continue 

and, with the freshwater habitat conditions, whether OCCS ESU could survive another prolonged 

period of poor marine survival remained in doubt.

In 2003 long-term (33-year) trends in spawner abundance for the lakes and rivers were 

slightly upward. Lakes increased about 2% per year and rivers increased about 1% per year. In 

lakes and rivers, long-term trends in recruits declined about 5% per year since 1970. For the 

ESU as a whole, spawners and recruits declined at a 5% rate from 1970 to 2003.

There had been notable changes in harvest management since the 1996 status review. 

The Pacific Fishery Management Council (PFMC) in 1988 (PFMC 1998) adopted Amendment 

13 to its Salmon Fishery Management Plan, which was developed as part of the Oregon Plan for 

Salmon and Watersheds (Oregon Plan, formerly OCSRI). It specified an exploitation rate 

 3 ODFW’s monitoring areas are similar to but not identical to gene conservation groups (Figure 28 and Figure 29 in 

Lawson et al. 2007) that were the population units in the 1997 update.
12

harvest management regime with rates for naturally produced Oregon coast coho salmon (OCN)4

dependent on marine survival and parental and grandparental spawning escapements. Allowable 

exploitation rates under the amendment can range 0−8% (poor marine survival) to a maximum of 

45% (high survival and parent population).

Also, beginning in 1998 most adult hatchery-origin coho salmon in the Oregon 

Production Index (OPI) area were marked with an adipose fin clip, allowing the implementation 

of mark-selective fisheries. Recreational mark-selective fisheries were conducted on the Oregon 

coast in each year between 1998 and 2003, with quotas ranging from 13,000 to 24,000 marked 

fish. The 2003 BRT expressed concern that these incidental mortality rates estimated by PFMC 

were underestimates. Despite these uncertainties, there was no doubt that harvest-related 

mortalities were reduced substantially after 1994. This reduction was reflected in 2003 in 

positive short-term trends in spawner escapements despite continued downward trends in 

preharvest recruits. In summary, the higher returns in the early 2000s were tempered by the 

overall decline since 1970. When considered in the context of historical abundance and hatchery 

influence, this trend indicated a continuing decline in abundance across the ESU. Therefore, the 

BRT considered that future remedies outside of harvest management were required until the 

decline in productivity reversed.

As of 2003, the Oregon Plan (OCSRI Science Team 1997) was the most ambitious and 

far-reaching program to improve watersheds and recover salmon runs in the Pacific Northwest. 

The original OCSRI was written in 1997, so the plan had been in operation for several years by

2003.

Between 1991 and 2003, some Oregon coastal hatchery facilities were closed and the 

numbers of smolts released from the remaining facilities were reduced from 6.2 million in 1992 

to 930,000 in 2001. Efforts to include more native broodstock were accomplished. The 2003 

BRT considered that these changes would somewhat reduce risks to naturally spawning OCCS. 

As of 1999, most adult coho salmon of hatchery origin were marked with an adipose fin clip for 

fishery management; an additional benefit was better accounting of hatchery fish spawning in the 

wild.

The 2003 BRT conclusions for the ESU as a whole reflected ongoing concerns for the 

long-term health of this ESU: a majority of BRT opinion was in the “likely to become 

endangered” category, with a substantial minority falling in the “not likely to become 

endangered” category. Although they considered the significantly higher returns in 2001 and 

2002 to be encouraging, most members thought that the factor responsible for the increases was 

more likely to be unusually favorable marine productivity conditions than improvement in 

freshwater productivity. The majority of BRT members thought that to have a high degree of 

confidence that the ESU was healthy, high spawner escapements should be maintained for a 

number of years and the freshwater habitat should demonstrate the capability of supporting high 

juvenile production from years of high spawner abundance.

The 2003 BRT considered the long-term decline in productivity to be the most serious 

concern for this ESU. With all directed harvest for these populations already eliminated, harvest 

 4 Oregon Coast coho salmon naturally produced fish also includes SONCC populations in Oregon.
13

management (i.e., reducing harvest rates) could no longer compensate for declining productivity. 

The BRT was concerned that the long-term decline in productivity reflected deteriorating 

conditions in freshwater habitat and that the OCCS ESU would likely experience very serious 

risks of local extinctions during the next cycle of poor ocean conditions. With the cushion 

provided by strong returns in 2001−2003, the 2003 BRT had much less concern about short-term 

risks associated with abundance than did earlier BRTs.
14

New Contributions to Understanding and 

Assessing Status of OCCS

ESU Delineation

The 2009 BRT evaluated new information related to ESU boundaries. The 

biogeographical and environmental information summarized by Weitkamp et al. (1995) remains 

unchanged, and the 2009 BRT did not reevaluate this information. The data on tag recoveries 

that Weitkamp et al. (1995) evaluated were subsequently expanded, revised, and published 

(Weitkamp and Neely 2002). The revised analysis continues to show a distinct pattern of ocean 

tag recoveries for the OCCS ESU, consistent with the Weitkamp et al. (1995) conclusions.

Since the earlier status reviews, several new genetic studies of West Coast coho salmon 

that included samples from the Oregon coast have been published. Ford et al. (2004) analyzed 

data at 6 microsatellite loci from 22 populations of OCCS and several populations of Puget 

Sound coho salmon. Van Doornik et al. (2007) examined patterns of variation at 11 

microsatellite loci from 84 coho salmon populations from northern California to southern British 

Columbia. Van Doornik et al. (2008) examined patterns of variation at eight microsatellite loci 

from coho salmon sampled from central California to Alaska. Johnson and Banks (2008)

analyzed 23 populations of OCCS (including one population from the Rogue River in the 

SONCC Coho Salmon ESU) at 8 microsatellite loci.

The patterns of genetic variation in these newer studies are generally similar to those 

observed in the earlier studies summarized by Weitkamp et al. (1995). In particular, the new 

studies confirm that coho salmon are characterized by relatively low levels of population 

differentiation compared to other salmon species, particularly in the central part of their range. 

The new studies that include coast-wide samples (Van Doornik et al. 2007 and 2008) are also 

consistent with the data cited by Weitkamp et al. (1995), indicating genetic discontinuities at or 

around Cape Blanco and the Columbia River mouth. In particular, in a neighbor-joining tree 

cluster analysis, Van Doornik et al. (2007 and 2008) found 100% genetic bootstrap support for a 

cluster containing samples from the Rogue and Klamath rivers distinct from Oregon coast 

samples north of Cape Blanco. The same result has been confirmed with a more recent analysis 

of 18 microsatellite loci from approximately 6,000 coho salmon sampled coast wide.5

 These 

analyses indicate that the Oregon coast samples are distinct from the Columbia River and more 

northern populations, with moderate to high levels of genetic bootstrap support.

After considering the new information, the 2009 BRT concluded that a reconsideration of 

the ESU boundaries for the OCCS ESU is not necessary. The basis for this conclusion is that the 

environmental and biogeographical information considered by Weitkamp et al. (1995) remains 

 5 Carlos Garza, SWFSC, 110 Shaffer Rd. Santa Cruz, CA. Pers. commun., November 2009.
15

unchanged, and new tagging and genetic analysis published subsequently to the original ESU 

boundary designation continue to support the current ESU boundaries.

Artificial Propagation—Membership in the ESU

At the time of the 2004 proposed rule and January 2006 final determination not to list the 

OCCS ESU, the Cow Creek (ODFW stock #37), North Umpqua River (ODFW stock #18), Coos 

Basin (ODFW stock #37), North Fork Nehalem stock, and Coquille River (ODFW stock #44) 

hatchery coho programs were considered part of the OCCS ESU. The Trask (Tillamook) and 

Salmon (Salmon, Siletz) stocks were excluded from the ESU due to observed or suspected 

divergence from natural populations (see Table 22.1 in NMFS 2004b). The North Umpqua, 

Coos, and Coquille programs have been discontinued since the 2006 final determination (NMFS 

2008). The last year of returns for these programs was 2007. At the time of 2008 listing, only 

the Cow Creek stock was included in the ESU (the North Fork Nehalem was excluded from the 

ESU based on comments from ODFW, NMFS 2008). As of 2009, only three coho hatchery 

stocks are released within the freshwater boundaries of the OCCS ESU. These are the North 

Fork Nehalem, Trask (Tillamook Basin) and Cow Creek (South Umpqua) stocks.6 The BRT 

found no new information to suggest that current ESU membership status of these stocks (Cow 

Creek in the ESU, others out of ESU) should be changed.

Population Delineation

Recently, the workgroup, a subcommittee of the ONCC TRT, published two documents, 

Identification of Historical Populations of Coho Salmon (Oncorhynchus kisutch) (Lawson et al. 

2007) and Biological Recovery Criteria for Oregon Coast Coho Salmon (Wainwright et al. 

2008). These defined historical population structure and biological recovery criteria and are 

discussed below. Because of these analyses, the discussion of risk to the species was focused at 

a finer scale than in previous status reviews.

The TRT’s analysis of historical population structure of the ESU relies on a simple 

conceptual model of the spatially dependent demographics of the 56 populations that the 

workgroup considered likely to have been present historically within the ESU. This model 

classifies populations on the basis of two key characteristics: persistence (their relative abilities 

to persist in isolation from one another), and isolation (the relative degree to which they might

have been influenced by adult fish from other populations straying into their spawning areas). 

The 56 populations are also used by ODFW and other resource agencies and have been 

incorporated into the State of Oregon’s monitoring framework (ODFW 2007).

The TRT classified historical populations as dependent and functionally and potentially 

independent. For the purposes of this BRT, historical populations were reduced to two groups: 

independent and dependent (Table 2, Figure 3). Oregon coast drainage basins of intermediate to 

large size are thought to have each supported a coho salmon population capable of persisting in 

isolation. Some of them may have been demographically influenced by adult coho salmon 

straying into spawning areas from elsewhere in the ESU. Populations that appeared likely to 

 6 Reported by BRT member L. Kruzic, December 2009.
16

Table 2. Independent and dependent historical populations of OCCS. (Adapted from Lawson et al. 

2007.)

Population Type Population Type

Necanicum Independent Alsea Independent

Ecola Dependent Big (near Alsea) Dependent

Arch Cape Dependent Vingie Dependent

Short Sands Dependent Yachats Dependent

Nehalem Independent Cummins Dependent

Spring Dependent Bob Dependent

Watseco Dependent Tenmile Creek Dependent

Tillamook Bay Independent Rock Dependent

Netarts Dependent Big Dependent

Rover Dependent China Dependent

Sand Dependent Cape Dependent

Nestucca Independent Berry Dependent

Neskowin Dependent Sutton (Mercer Lake) Dependent

Salmon Independent Siuslaw Independent

Devils Lake Dependent Siltcoos Independent

Siletz Independent Tahkenitch Independent

Schoolhouse Dependent Threemile Dependent

Fogarty Dependent Lower Umpqua Independent

Depoe Bay Dependent Middle Umpqua Independent

Rocky Dependent North Umpqua Independent

Spencer Dependent South Umpqua Independent

Wade Dependent Tenmile Independent

Coal Dependent Coos Independent

Moolack Dependent Coquille Independent

Big (near Yaquina) Dependent Johnson Dependent

Yaquina Independent Twomile Dependent

Theil Dependent Floras/New Independent

Beaver Independent Sixes Independent

have been capable of persisting in isolation were classified as independent (21 populations). 

Small coho salmon populations found in smaller coastal basins and that may not have been able 

to maintain themselves continuously for periods as long as hundreds of years without strays from 

adjacent populations were classified as dependent populations (Lawson et al. 2007).

The TRT concluded that dependent populations relied at times on the strength of adjacent

larger populations for their continuous historical presence in the Oregon coast’s smaller basins. 

As long as the larger persistent populations within the ESU remained strong, the smaller 

(dependent) populations would rarely if ever have disappeared from their basins. However, if 

some form of broadscale environmental change triggered a substantial decline in one or more of 

the larger populations, the reduction in migrants would have increased the possibility that the 
17

Figure 3. Historical populations and biogeographic strata for OCCS ESU.
18

same environmental change, perhaps coupled with local disturbances, would have resulted in the 

intermittent disappearances of the dependent populations found in some of the smaller basins. 

This may have occurred in the ESU in 1998 when no spawners were observed returning to 

Cummins Creek (Lawson et al. 2007.)

Definition of Biogeographic Strata

Within the OCCS ESU, there is substantial genetic and biogeographic structure, with 

populations clustering into a few larger geographic units that were identified by the workgroup. 

These biogeographic strata represent genetic and geographic similarities and assume that 

preserving sustainable populations in each of them will conserve major genetic diversity in the 

ESU, as well as spread risks to the maintenance of genetic and geographic diversity due to 

catastrophes. The workgroup considered that all strata must be secure for the entire ESU to be 

sustainable (Wainwright et al. 2008).

In defining the biogeographic strata, the workgroup considered that the four ODFW 

monitoring areas (Figure 29 in Lawson et al. 2007) in the ESU, for the most part, reflected the 

geography, ecology, and genetics of the landscape. However, the lakes are very different from 

the other portions of the Mid-South Coast Monitoring Area ecologically, geographically, and 

genetically. In order to reflect this diversity and reduce the risks to genetic and geographical 

diversity due to catastrophes, they accepted the Ford et al. (2004) Lakes Complex as a fifth 

biogeographical stratum for use in defining areas of diversity important in conservation (Figure 

3).

Because these units represent biological diversity (genetic and ecological) and geographic 

variation, the workgroup considered that preserving all of them will accomplish two goals: 1) 

preserving major genetic and life history variation in the ESU and 2) spreading risks due to 

catastrophes. The 2009 BRT used these strata in considering risks to genetic and life history 

diversity.

Biological Recovery Criteria Used to Inform Risk Assessment

Wainwright et al. (2008) outlined biological recovery criteria (also called viability 

criteria) for the OCCS ESU, as identified in NMFS’s status review for West Coast coho salmon 

(Weitkamp et al. 1995). The report was developed by the workgroup of the ONCC TRT. The 

BRT used the Wainwright et al. (2008) report as one important source to inform its risk 

assessment process. However, the BRT also considered other factors, such as environmental 

threats not included in the Wainwright et al. (2008) criteria, in making its overall risk 

determination.

A complete assessment of the biological condition of the ESU is necessarily multifaceted, 

including a variety of interrelated criteria, with varying data quality. The recovery criteria 

developed by the TRT relate to biological processes at a variety of time and space scales, with 

processes varying from individual stream reaches to the entire range of the ESU. To track this 

large suite of data and criteria in a transparent and logically consistent framework, Wainwright et 

al. (2008) constructed a knowledge-based decision support system (DSS).
19

The DSS uses a network framework to link criteria at a variety of scales and aggregate 

them from fine scale watershed-level criteria, through population-level criteria and 

biogeographic stratum-level criteria, to criteria for the entire ESU. The links take the form of 

logical operators that define specific relationships among the input values. In this knowledgebased system, a type of fuzzy logic extends the ability to work with imprecise knowledge of 

attributes of the OCCS ESU. The advantage of using this logic is that it allows evaluation and 

expression of certainty in an outcome, ranging from certainly false through uncertain to certainly 

true. The ability to work with a gradation of levels of certainty and uncertainty assisted the 2009 

BRT in evaluating the degree of risk and uncertainty in its assessments. This analysis is further 

described in the Current Biological Status subsection below.
20

New Comments

Below are brief summaries of comments NMFS received in response to the April 2009 

Federal Register notice asking for new scientific information for consideration by the BRT. Full 

texts of the comments are available from NMFS NWR.7 The BRT considered these comments 

in its deliberations.

Trout Unlimited commented that it favors maintaining the current listing status of 

threatened. It asked the BRT to take a close look at hatchery practices, harvest, bycatch in 

estuary fisheries, and climate change during this status review. No specific information 

regarding these issues was provided (Trout Unlimited 2009).

U.S. Environmental Protection Agency (EPA) comments focused on the inadequacy of 

state programs to protect water quality and other OCCS habitat requirements. EPA presented

comments previously included in other OCCS reviews that the Oregon Forest Practices Rules 

and Best Management Practices will not consistently meet water quality standards or protect 

riparian function. An EPA letter sent to the State of Oregon in 2005 regarding the inadequacy of 

the State’s Oregon Coast Coho Conservation Plan was attached (EPA 2009).

The Pacific Rivers Council (PRC) and Center for Biological Diversity supported

maintaining the current listing of threatened and asserted that they have no knowledge of 

credible information available to support changing this ESU’s status. They included by 

reference that the State of Oregon was unable to secure an ESA Section 10 Habitat Conservation 

Plan for the Elliot State Forest Management Plan. They cited a letter from NMFS/NWR Habitat 

Conservation Division stating that NMFS has unresolved concerns regarding the ability of the 

plan to protect OCCS habitat. They also pointed out that other state forest plans throughout the

range of OCCS are similar to the Elliot State Forest situation and may be equally inadequate. 

The PRC also suggested that watershed road density be used as a measure of risk for OCCS. It 

cited a new U.S. Bureau of Land Management (BLM) analysis indicating that road densities are 

relatively high throughout almost all subwatersheds occupied within OCCS distribution. The 

council’s final point was about considering local extirpation and population homogenization due 

to the population dynamics driven by ocean conditions (PRC 2009).

The American Forest Resources Council commented on measurable habitat 

improvements since adoption of the Oregon Plan in 1997. It cited several publications and 

reports indicating that recent improvements in OCCS habitat demonstrate that the Oregon Plan is 

working. It also supported a population viability assessment that is tailored to this particular 

ESU and its naturally wide swings in abundance. The council cautioned against using the more 

simple population viability models relying primarily on abundance and productivity adopted by 

other West Coast salmon TRTs (e.g., Puget Sound TRT 2002) (American Forest Resources 

Council 2009).

 7 NMFS Northwest Regional Office, 1202 NE Lloyd Blvd., Suite 1100, Portland, OR 97232.
21

ODFW provided a significant amount of new information about the status of this ESU. 

Its comments highlight recent hatchery release reductions and changes to marine harvest. It 

pointed out that during times of low ocean survival, harvest will be managed under Amendment 

13 of the Pacific Salmon Treaty, but stated that at times of higher abundance, coho salmon 

harvest may occur at levels that limit progress toward recovery but do not represent a threat to 

viability. ODFW also provided new population data and information on habitat conditions. It 

generally concluded that range-wide stream and riparian habitat conditions have remained 

relatively stable between 1998 and 2008. But ODFW also concluded that this habitat is in a 

condition suitable for producing enough smolts to maintain viability even during periods of low 

marine survival. ODFW reported that stream productivity seems to be improving slightly in all 

areas except the Umpqua Basin (Anlauf et al. 2009, ODFW 2009b).

The Douglas County Commissioners supplied a list of habitat improvement projects 

carried out in the Umpqua River basin. They stated that the number of projects occurring in this 

basin was evidence that the Oregon Plan works as intended. The commissioners also 

commented that significant harvest reform has been completed to ensure harvest no longer 

represents a threat to this ESU’s viability. They asserted that recent high abundance realized by 

Umpqua populations and the cancellation of the North Umpqua hatchery program further 

demonstrate that this ESU does not need to be listed. Finally, they pointed out what they believe 

are some problems with the BRT population models. The commissioners were in favor of a not 

warranted finding for this ESU (Douglas County Commissioners 2009).

The State of Oregon Governor’s Office commented that the State, “through its natural 

resource agencies, continues to put substantial effort on the ground and in policy to improve 

conditions for and status of coastal coho salmon.” Its comments provided a summary of the 

Oregon Plan and the 2007 Oregon Coast Coho Conservation Plan. It also listed the state 

agencies responsible for implementation of these plans and some of their recent 

accomplishments (Oregon 2009a).

Coquille Indian Tribe comments mostly focused on coho salmon in the Coquille River 

basin. It listed several habitat limiting factors and provided an update on recent restoration 

projects carried out by the tribe and its partners. It also provided some information on recent 

abundance estimates and cited a study (Jacobs 2002) that concluded that recent surveys may 

have underestimated the abundance of returning coho spawners. The tribe stated that predators 

(marine mammals, birds, and fish) may be having significant effects on OCCS. The tribe 

concluded its comments by suggesting that some basins like the Coquille, Coos, and Umpqua be 

examined differently in the status review because listing is not warranted (Coquille Indian Tribe 

2009).

Thad Springer (a private citizen) was not in favor of a listing and commented that the 

presence of a listed species is a disincentive to private landowners to carrying out restoration 

projects on their land. Mr. Springer also provided a list of information sources the BRT should 

consider, mostly related to state programs (Springer 2009).

The Native Fish Society (Paul Engelmeyer) commented that OCCS should remain listed 

as threatened. He asserted that the Oregon Forest Practices Act and state programs for 

agricultural lands are insufficient to protect water quality in the ESU. He also pointed out 
22

several other threats including pesticide runoff into coho salmon streams, designation of beaver 

as a nuisance species by the State of Oregon, and ongoing floodplain development. He 

commented against terminal recreational harvest of OCCS in TRT-identified independent 

populations (Umpqua, Coos, Yaquina, etc.) and was critical of Amendment 13 of the Pacific 

Salmon Treaty. Mr. Engelmeyer included numerous reports with his comments that have been 

made available to the BRT (Native Fish Society 2009).
23

Oregon Coast Coho Salmon Symposium

In order to provide an opportunity for the State of Oregon and ODFW to present their 

information to the BRT, a one-day symposium was organized. In addition to the State of 

Oregon, comanagers and interested parties were invited to make presentations of new scientific 

information and information on restoration activities. This section provides a short summary of 

the main topics presented at the symposium. The BRT considered the information presented in 

its deliberations.

OCCS ESU: Population status and conservation measures update from Oregon 

Department of Fish and Wildlife. Kelly Moore, ODFW, presented an overview of fish metrics 

for the ESU. These were wild or natural spawner and hatchery spawner abundance time series 

from 1950 to 2008, spawner abundance by population, spawner distribution, spawner surveys 

from 2005−2008 occupancy, modeled parr capacity, juvenile occupancy rates, hatchery release 

history, trends in hatchery influence, life cycle monitoring egg-to-smolt and smolt-to-adult 

survival, habitat limiting factors model (HLFM) smolt capacity, population abundance patterns 

and spatial distribution variability, and 2008−2009 returns. Oregon Plan and Oregon Coast Coho 

Conservation Plan information also were presented. This included additional factors for decline 

and issues of concern, the Oregon Plan habitat strategy, recognition of contributions to habitat by 

beavers, and what ODFW is doing to encourage conservation of beavers and the contributions of 

Oregon watershed councils.

The status and trends of physical habitat and rearing potential in coho bearing 

streams in the OCCS ESU. Kim Jones, ODFW, presented information on the Habitat Survey 

Program and included a discussion of factors for decline, Oregon Plan integrated monitoring, 

survey design, distribution of sites, and balancing status and trends sampling requirements. He 

discussed the four monitoring strata and the status of stream habitat in the OCCS ESU. The 

monitored aspects of wadeable streams are pools, large wood volume, fine sediments, and winter 

habitat. The HLFM (Anlauf et al. 2009) was discussed with a presentation of the capacity of 

differing kinds of pools, winter rearing, and spawner abundance. Monitoring trends analysis 

done by Kara Anlauf concluded that the ESU’s streams are generally pool rich but structurally 

simple, mean values of the monitored attributes are all low, there are few off-channel habitats or 

beaver pools, and most streams have low volumes of wood and high fine sediment.

Oregon’s plan for protecting salmon and watersheds. Suzanne Knapp, Governor’s 

Natural Resources Office, discussed the Oregon Plan framework and which agencies are 

addressing limiting factors such as water removal, water quality, and stream complexity.

BLM and U.S. Forest Service (USFS) land management in OCCS ESU. Joe Moreau, 

BLM State Office, presented information on the types of restoration activities and the costs that 

BLM and USFS have engaged in to help restore OCCS habitat.
24

Satellite-based summaries of yearly timber harvest rates on all lands within the 

OCCS ESU from 1985 to 2008. Dr. Robert Kennedy, Department of Forest Ecosystems and 

Society, Oregon State University, presented his work on a new application of his land remote 

sensing satellite (Landsat) analytical method. He presented information that attempts to address 

the question: Does terrestrial habitat condition matter for coho salmon with respect to 

temperature, sediment type, and delivery? His conclusions were that the yearly disturbance 

information is useful for interpretation of impacts of policy and economics, that disturbance 

magnitude shows variability across ownerships and time, and that private lands dominate the 

land base and disturbance impacts. He also suggested that variation in disturbance rates and 

timing across basins may provide leverage for useful inferences about land management actions.

Maintaining Oregon’s forest land base: The Forest Practices Act role in the 

conservation of forest values on nonfederal forest lands. Jim Paul, Oregon Department of 

Forestry (ODF), presented the Oregon Plan accomplishments of private timber landowners and 

discussed the threat of forest conversion to other land uses.

Road density, watershed condition, and implications for salmonid conservation in 

the range of the Oregon coastal coho salmon. Dr. Chris Frissell, PRC, presented a summary 

of his and others’ work on applicable science from studies in the Columbia Basin on bull trout 

(Salvelinus confluentus). These centered on habitat response: more fine sediment, fewer pools, 

less wood, water quality decline (temperature and nutrients/toxics), watershed degradation, and 

salmon population response such as status, abundance, and species diversity.

Observations on water quality improvement under SB1010 and other lowland 

issues. Paul Engelmeyer, Native Fish Society, presented an overview of four issues that need 

significant change to improve the chances of coho population recovery at a landscape scale: 

agricultural water quality management, State of Oregon beaver policy, policies to protect 

floodplain function, and improvement in forest practices.

Recent observations of Oregon coast coho salmon in Smith River. Dr. Joe Ebersole, 

EPA, presented some of his work that attempts to help identify where habitat restoration 

activities should take place. He concluded that OCCS utilize intermittent stream habitat for a 

significant amount of winter rearing. In addition, what should be very good habitat (high 

intrinsic potential) is presently poor habitat in the study area due to legacy stream effects such as 

splash damming. He suggested that habitat that should be improved and conserved is the 

existing habitat currently at the center of coho salmon production. In other words, “fix the best 

first.”

Hinkle Creek paired watershed study. Daniel Newton, working with the Watershed 

Research Cooperative, presented preliminary results of the Hinkle Creek paired watershed study. 

Their preliminary findings were that initial temperature response was small compared to the 

original Alsea Watershed Study, downstream recovery of nutrient increases following timber 

harvest is typical of other studies, sediment increased following timber harvest but was 

attenuated downstream, and that fish (coastal cutthroat trout and steelhead) survival and 

distributions were similar to preharvest patterns.
25

Comments of Douglas County, Oregon, on OCCS ESU. David Loomis, Douglas 

County Board of Commissioners and Public Works Department, presented information on the 

effects of unreported habitat restoration projects and the unreported decline of “likely to 

adversely affect” activities in freshwater habitat on the evaluation of habitat conditions. He also 

discussed habitat restoration projects reflecting specific needs of OCCS populations 

(instantaneous and long-term), spawner to spawner ratios, and generational health of individual 

populations. A discussion of recent ocean and in-river harvest history and the hatchery program 

level for North Umpqua and for Umpqua Basin spawning hatchery strays was included. He 

requested that the BRT use the North Umpqua Population Case Study as “truth value” of model 

sensitivity and risk of extinction status (Douglas County Commissioners 2009).
26

New Data and Updated Analyses

Current Biological Status

This section addresses new data and updated analyses for the viable salmonid population 

(VSP) parameters of abundance, growth rate (productivity), spatial structure, and diversity 

(McElhany et al. 2000). In addition, Harvest Impacts and Artificial Propagation subsections are 

included here for consistency with previous BRT analyses. Finally, a new analysis utilizing the 

ONCC TRT’s biological recovery criteria is included.

Population Size

In past status reviews (Weitkamp et al. 1995, NMFS 1997d, Good et al. 2005), the BRTs 

considered two measures of recent population abundance—spawner abundance and preharvest 

recruits—and also considered recent estimates in the context of published estimates of 

abundance in the late 1800s and early 1900s (Mullen 1981a, Lichatowich 1989, ODFW 1995).

The 2009 BRT received updated estimates of total natural spawner abundance (and 

corresponding recruits) based on stratified random survey techniques broken down by historical 

populations for 10 major river basins and the coastal lakes system.8 These data are shown in 

Table 3, Figure 4, and Figure 5. Since the previous status review, natural spawner abundance 

was generally up relative to the late 1990s and in all but 1 year (2007) has been well above the 

recent mean.

In the 1994 status review, Weitkamp et al. (1995, p. 113) considered historical estimates 

of abundance for this ESU and concluded that “these numbers suggest current abundance ...

may be less than 5% of that in the early part of the century.” The current BRT reexamined that 

information and reanalyzed some of the historic abundance information. The earlier review 

based this conclusion largely on estimates of spawning escapement published by ODFW (Mullen 

1981a). A reexamination of Mullen’s tables found that he made a miscalculation such that the 

spawning escapement estimates included in-river gill net harvest and were thus inflated.

We made an independent estimate of spawners and recruits for the ESU for the period 

1892–1956 using in-river gill net harvest estimates from other ODFW reports (Cleaver 1951, 

Mullen 1981b). Spawner escapement was estimated by expanding estimated gill net harvest, 

assuming a 40% harvest rate for 1892−1925 (Mullen 1981a, Lichatowich 1989), which was 

reduced as rivers were closed to fishing (Table 7 in Mullen 1981b, 12 rivers open in early years, 

7 rivers remained open until 1956). Recruits were then calculated by adding in-river harvest and 

ocean troll catch. Ocean troll catch estimates are available for 1925−1927 and we assumed a 

10% ocean harvest rate for 1912−1924 (Mullen 1981b). Results are shown in Figure 6, 

 8 River basins from Pacific Coast Salmon Plan September 2003. Data from K. Moore, Research and Monitoring 

Supervisor, ODFW Corvallis Research Lab, Corvallis, OR. Pers. commun., September 2009.
27

Table 3. OCN coho salmon spawners and recruits (rivers, lakes, total) from 1969 to 2009, with 

approximate ocean exploitation rates. Data are from PFMC 2009 spreadsheet T6, version 1 

(PFMC 2010).

Year

Spawners (thousands) Exploitation 

rate

Recruits (thousands)

Rivers Lakes Total Rivers Lakes Total

1969 129.2 10.0 139.2 0.67 391.5 30.2 421.7

1970 51.2 21.5 72.7 0.65 183.1 61.7 244.8

1971 65.6 30.0 95.6 0.83 416.3 171.1 587.4

1972 24.1 10.6 34.7 0.84 185.5 67.5 253.0

1973 37.8 18.1 55.9 0.82 235.0 100.4 335.4

1974 28.1 6.8 34.9 0.84 196.4 41.0 237.4

1975 34.8 6.3 41.1 0.81 208.4 33.8 242.2

1976 39.2 1.7 40.9 0.90 451.7 17.1 468.8

1977 13.7 6.0 19.7 0.89 161.2 53.9 215.1

1978 18.2 1.8 20.0 0.83 111.6 10.3 121.9

1979 38.4 6.6 45.0 0.79 188.8 32.1 220.9

1980 25.6 5.0 30.6 0.73 108.3 18.6 126.9

1981 30.1 3.2 33.3 0.81 174.5 16.9 191.4

1982 68.3 8.3 76.6 0.62 188.4 22.0 210.4

1983 19.4 3.8 23.2 0.79 104.8 19.5 124.3

1984 59.7 16.3 76.0 0.32 95.3 24.1 119.4

1985 66.3 7.9 74.2 0.43 126.2 14.1 140.3

1986 58.2 12.3 70.5 0.34 98.9 18.7 117.6

1987 25.9 4.3 30.2 0.60 71.1 10.9 82.0

1988 51.0 6.2 57.2 0.56 127.3 14.6 141.9

1989 41.6 5.4 47.0 0.55 107.9 12.5 120.4

1990 16.5 4.7 21.2 0.69 60.6 15.3 75.9

1991 29.1 7.7 36.8 0.44 69.4 14.0 83.4

1992 38.6 2.1 40.7 0.51 87.7 4.4 92.1

1993 44.3 10.2 54.5 0.42 81.3 17.7 99.0

1994 37.5 5.9 43.4 0.07 40.3 6.0 46.3

1995 41.3 11.3 52.6 0.12 47.2 14.7 61.9

1996 59.5 13.6 73.1 0.08 64.9 15.9 80.8

1997 14.1 8.7 22.8 0.13 16.1 9.9 26.0

1998 19.8 11.2 31.0 0.08 21.5 12.0 33.5

1999 34.6 12.8 47.4 0.08 37.5 13.9 51.4

2000 54.1 12.8 66.9 0.07 58.4 13.8 72.2

2001 148.0 19.9 167.9 0.07 160.0 21.5 181.5

2002 231.4 22.3 253.7 0.12 264.2 25.2 289.4

2003 206.3 16.3 222.6 0.14 241.3 18.8 260.1

2004 149.2 19.3 168.5 0.15 175.2 21.8 197.0

2005 119.3 14.3 133.6 0.11 134.4 15.7 150.1

2006 87.2 22.7 109.9 0.06 92.8 23.6 116.4

2007 42.3 9.4 51.7 0.11 47.8 10.1 57.9

2008 142.1 23.6 165.7 0.04 146.5 24.6 171.1

2009 215.5 17.4 232.9 0.11 241.6 19.6 261.7
28

Figure 4. OCCS naturally produced recruits per spawner (recruits are from spawners 3 years earlier), 

1972–2009. Horizontal unity line is replacement value. Data are from Table 3, this document.

Figure 5. OCCS naturally produced recruits, 1969–2008. Each bar shows spawners and harvest. Harvest 

was gradually reduced starting in the late 1970s and sharply curtailed in 1994. Data are from 

Table 3, this document.
29

Figure 6. Comparison of historical (1892–1956) and recent (1958–2009) estimates of spawner abundance 

and preharvest recruits. Horizontal lines are the geometric mean recruits for 1892–1940 and 

1960–2009. Analysis based on data from Cleaver 1951, Mullen 1981a, and Mullen 1981b; recent 

data from Wainwright et al. 2008 and ODFW 2009a.

compared with more recent estimates. From this historical perspective, recruits over the past few 

years have been close to the 1960−2009 average, but are only a fraction of the abundance before 

1940.

While these historical abundance estimates are very rough and based on an assumed gill 

net harvest rate derived from expert opinion, they suggest that there has been a substantial 

decrease in ESU-wide abundance during the twentieth century. In fact, the decline was a 

concern to state biologists as early as the late 1940s (Cleaver 1951). Cleaver did not discuss 

causes of the decline other than to note that it was not caused by changes in harvest rates. 

However, Lichatowich (1989) related the overall decline to habitat loss, reporting a decline in 

production potential from about 1.4 million recruits ca 1900 to only 770,000 in the 1980s, likely 

resulting from habitat alterations related to timber harvest and agriculture, which both expanded 

on the coast between 1910 and 1950.

Population Growth Rate

Previous status reviews noted strong concerns regarding long-term and short-term trends 

in population productivity of the ESU. The BRT examined population growth rate (productivity) 

via two parameters: the ratio of recruits to spawners (R/S), and the natural return ratio (NRR). 

These measure different aspects of population dynamics. R/S indicates the basic productivity of 

populations in the absence of harvest, that is, the intrinsic ability of spawners in one generation 

to produce adults in the next generation. NRR is defined as the ratio of naturally produced 
30

spawners in one generation to the total (natural + hatchery-produced) spawners in the previous 

generation. NRR indicates the realized ability of populations to replace themselves, given 

intrinsic production and the effects of harvest and hatchery production.

Recruits from the return years 1997–1999 failed to replace parental spawners: a 

recruitment failure occurred in all three brood cycles even before accounting for harvest-related 

mortalities (Figure 4). This was the first time this had happened since data collection began in 

the 1950s. In most years since 2000, improved marine survival and higher rainfall are thought to 

be factors that have contributed to an upswing in recruits. However, in the return years 2005, 

2006, and 2007, recruits also failed to replace parental spawners (Figure 4). There are several 

possible explanations for the more recent recruitment failure. It may reflect population dynamics 

that have not been allowed to occur since 1950; prior to 1994 harvest had consistently 

maintained spawner abundance near 50,000 fish (Figure 5). With harvest sharply curtailed in 

1994, most recruits have been able to return to spawn. Ocean conditions improved for the 1998 

broodyear, and recruits since 2001 have returned to spawn in numbers higher than previously 

observed. Harvest and hatchery reductions have changed the population dynamics of the ESU. 

Assuming these changes continue into the future, response of the system to fluctuations in 

environmental conditions and spawner escapements may show a different pattern than seen in 

the recent past. However, it is too soon to discuss with confidence the nature of these changes or 

the degree to which they may have improved the status of the ESU. In particular, it has not been 

demonstrated that productivity during periods of poor marine survival is now adequate to sustain 

the ESU.

Response of the system to higher escapements is essentially unknown; there are several

possible interpretations of the recent patterns in productivity as measured by R/S and NRR. 

These productivity statistics are influenced by marine survival, freshwater survival, and 

freshwater carrying capacity (there is little evidence for an ocean carrying capacity). The current 

data set measures only the endpoints of spawners and ocean recruits, so we cannot easily 

separate the effects of freshwater and marine survival, although the ODFW life cycle monitoring 

sites help address this concern for recent years. Several lines of evidence based on patterns in 

the marine environment (CalCOFI 2010) and patterns of survival and abundance of a variety of 

salmon stocks in the Pacific Northwest (PFMC 2011) indicate that marine survival has been 

relatively good during the period from about 1998 to the present.

Despite apparently high marine survival, OCCS recruitment never exceeded 275,000, 

suggesting that current freshwater habitat capacity is substantially lower than it was up to the 

1980s, when production potential was estimated at about 767,000 (Lichatowich 1989). The 

observation that recruits failed to replace spawners in 2005–2007 could be an indication that 

productive capacity had been reached or simply be a reflection of patterns in marine survival. 

Recent increases do not provide strong evidence that the century-long downward trend has 

changed. Abundance observations are consistent with the pattern of cyclical abundance 

overlying a downward trend as hypothesized by Lawson (1993).

While total spawners has been at its highest level since the 1950s, total recruits has not 

(Figure 5 through Figure 7). This suggests that the overall productivity (Figure 4 and Figure 8) 

and capacity (Figure 5 and Figure 6) of the system has, at best, been stable over the past half

century.
31

Figure 7. Trends in natural spawner abundance for the whole ESU (top panel) and the five biogeographic 

strata (lower panels). The dotted line marks the long-term mean and the gray background spans 

the mean ±1 SD. Note the logarithmic scale. Data from Wainwright et al. 2008 and ODFW 

2009a.
32

Figure 8. Trends in natural return ratio for the whole ESU (top panel) and the five biogeographic strata 

(lower panels). The dotted line marks the long-term mean and the gray background spans the 

mean ±1 SD. The dashed line is the replacement line. Note the logarithmic scale. Data from 

Wainwright et al. 2008 and ODFW 2009a.
33

Given current habitat conditions, OCCS are thought to require an overall marine survival 

rate of 0.03 to achieve a spawner:recruit ratio of 1:1 in high quality habitat (Nickelson and 

Lawson 1998). Less productive habitats require higher marine survivals to sustain populations. 

Based on OPI hatchery survival rates (Table 4), marine survival (adults/smolt) exceeded 0.03 

only in 2001 and 2003. Assuming natural spawners survive at twice the hatchery rate (Lawson 

et al. 2004, Wainwright et al. 2008), in 11 out of 18 years since 1990 marine survivals were high 

enough to sustain the ESU. Increases in recruits (Figure 6) reflect improved marine survival 

after 2000. Marine conditions will continue to cycle (Lawson 1993) and, with current freshwater 

habitat conditions, the ability of the OCCS ESU to survive another prolonged period of poor 

marine survival remains in question.

For the ESU as a whole, the 12-year NRR is higher than the long-term NRR mean, with 

an up-and-down trend over the recent 12 years (Figure 8). The pattern is similar for the North 

Coast, Mid-Coast, and Mid-South Coast strata. The Lakes and Umpqua River strata have recent 

mean NRRs close to the long-term mean. The trend for the Umpqua River stratum is similar to 

the other riverine strata, while the Lakes stratum has a flat trend in recent years.

Population Spatial Structure

The 2009 BRT utilized historical populations defined and classified in Lawson et al. 

(2007). The TRT identified 56 populations, 21 independent and 35 dependent. The dependent 

populations rely on strays from other populations to maintain them over long time periods. The 

TRT also identified five biogeographic strata. This is a change from the 1996 status review, 

which partitioned OCCS into ODFW’s three gene conservation groups, and from the 2003 status 

review, which partitioned OCCS into ODFW’s four monitoring areas (Figure 28 and Figure 29 

in Lawson et al. 2007).

Spatial structure was identified as a problem in the 1980s and 1990s, when it was 

observed that river systems on the north coast had substantially lower spawner escapements than 

those on the south coast. This problem persisted into the late 1990s (see Table 5). Causes of 

these disproportionately lower escapements were never clearly identified, but contributing 

factors may have included more intense fisheries north of Cape Falcon near the mouth of the 

Columbia River and high percentages of hatchery fish on the spawning grounds (Table 6). Stray 

hatchery spawners originated primarily from large hatcheries in the Nehalem and Trask rivers, 

but also came from the Columbia River hatcheries. Harvest was generally reduced in 1994 

(although not as severely north of Cape Falcon as south). Hatchery releases in the Nehalem and 

Trask rivers have been reduced or eliminated so that the percentage of hatchery fish on the 

spawning grounds has declined from a high of 67% in 1996 to less than 5% in most recent years 

(Table 6). Since about 1999, the north coast basins have had escapements more on a par with the 

rest of the ESU. Reduced harvest, reduced hatchery influence, and improved ocean conditions 

are all likely contributors.

Current concerns for spatial structure focus on the Umpqua River. Of the four 

populations in the Umpqua stratum, two—the North Umpqua and South Umpqua—were of 

particular concern. The North Umpqua is controlled by Winchester Dam and has historically 

been dominated by hatchery fish (Table 6). Hatchery influence has recently been reduced, but 

the natural productivity of this population remains to be demonstrated. The South Umpqua is a 
34

Table 4. OPI hatchery marine survival calculated as adults per smolt from adult recruits and smolts in 

previous year, 1970–2008 (t-1 refers to year previous). Smolt data are from PFMC 2009 Table 

T3, adult data are from OPITT 2009 Table T6, version 1, and 2009 data are preliminary (PFMC 

2010).

Smolts (t-1) Adults (t)

Year (t) (millions) (thousands) Adults/smolt

1970 28.8 2,765.1 0.096

1971 33.3 3,365.0 0.101

1972 35.3 1,924.8 0.055

1973 33.6 1,816.9 0.054

1974 32.6 3,071.1 0.094

1975 34.0 1,652.8 0.049

1976 34.2 3,885.2 0.114

1977 36.6 987.5 0.027

1978 37.4 1,824.2 0.049

1979 35.1 1,476.7 0.042

1980 36.4 1,223.9 0.034

1981 43.9 1,064.5 0.024

1982 35.9 1,250.8 0.035

1983 32.2 572.8 0.018

1984 35.9 679.2 0.019

1985 37.0 705.1 0.019

1986 42.6 2,383.0 0.056

1987 35.5 876.7 0.025

1988 37.1 1,634.6 0.044

1989 38.1 1,660.7 0.044

1990 40.0 717.2 0.018

1991 42.1 1,898.3 0.045

1992 39.7 538.5 0.014

1993 39.5 260.2 0.007

1994 32.3 201.2 0.006

1995 29.5 144.8 0.005

1996 31.6 185.5 0.006

1997 24.6 199.4 0.008

1998 29.1 211.6 0.007

1999 29.7 334.0 0.011

2000 32.1 668.8 0.021

2001 26.8 1,410.7 0.053

2002 25.2 641.9 0.025

2003 24.5 934.1 0.038

2004 23.4 614.4 0.026

2005 22.0 433.4 0.020

2006 21.8 454.0 0.021

2007 22.7 546.2 0.024

2008 22.8 565.3 0.025

2009 22.3 1,066.1 0.047
35

Table 5. OCCS ESU spawning escapement reported by ODFW, 1990–2009. Estimation methodologies changed in 2005 to enable ODFW to 

assess populations as defined by the OCCS TRT. Populations, reporting groups, and escapement numbers are different from those used by 

the TRT, and may be considerably different in some populations in some years. ODFW is currently working with the BRT to reconcile the 

differences. General patterns are consistent among all versions of this data set.

Spawner abundance by return year

Monitoring area, Basin/group based estimates Population based estimates

 Basin/group 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

North Coast

 Necanicum River

 and Elk Creek

191 1,135 185 941 408 211 768 253 946 728 474 5,247 2,896 3,068 3,142 1,218 750 431 1,105 3,827

 Nehalem River 1,552 3,975 1,268 2,265 2,007 1,463 1,057 1,173 1,190 3,713 14,285 22,310 20,903 33,059 21,479 10,451 11,614 14,033 15,690 21,753

 Tillamook Bay 265 3,000 261 860 652 289 661 388 271 2,175 1,983 1,883 15,715 14,584 2,290 1,995 8,774 2,295 4,897 16,251

 Nestucca River 189 728 684 401 313 1,811 519 271 169 2,201 1,171 3,940 13,003 8,929 6,152 686 1,876 394 5,444 4,252

 Sand Lake and

 Neskowin Creek

— 240 24 41 77 108 275 61 0 47 0 71 16 0 0 — — — — —

 Miscellaneous — 204 — — — — — — — — — — — — — 2,116 1,121 376 540 2,052

 Total 2,197 9,282 2,422 4,508 3,457 3,882 3,280 2,146 2,576 8,864 17,913 33,451 52,533 59,640 33,063 16,466 24,135 17,529 27,676 48,135

Mid-Coast:

 Salmon River 385 39 28 364 107 212 271 237 8 175 0 310 372 0 2,374 79 513 59 784 753

 Siletz River 441 984 2,447 400 1,200 607 763 336 394 706 3,553 1,437 2,252 9,736 6,399 14,567 5,205 2,197 14,519 24,070

 Yaquina River 381 380 633 549 2,448 5,668 5,127 384 365 2,588 647 3,039 23,981 13,254 4,989 3,441 4,247 3,158 8,710 11,182

 Devil’s Lake and

 Beaver Creek

23 — 756 500 1,259 — 1,340 425 1,041 3,366 738 5,274 8,754 5,812 7,179 2,264 1,950 611 1,182 3,575

 Alsea River 1,189 1,561 7,029 1,071 1,279 681 1,637 680 213 2,050 2,465 3,339 6,170 8,957 6,005 13,907 1,972 2,146 11,431 14,638

 Yachats River 280 28 337 287 67 117 176 99 102 150 79 52 1,245 1,635 641 — — — — —

 Siuslaw River 2,685 3,740 3,440 4,428 3,205 6,089 7,625 668 1,089 2,724 6,767 11,024 57,129 29,257 8,443 16,907 5,869 3,552 17,042 30,607

 Miscellaneous 207 — 700 180 250 231 1,188 13 71 0 12 764 4,063 217 4,364 242 1,468 547 4,204 1,610

 Total 5,591 6,732 15,370 7,779 9,815 13,605 18,127 2,842 3,283 11,759 14,261 25,239 103,966 68,868 40,394 51,407 21,224 12,270 57,872 86,435

Umpqua

 Lower Umpqua

 and Smith River

589 1,316 1,759 4,804 1,689 6,803 4,904 935 5,118 2,323 3,696 8,850 14,492 12,760 8,046 18,591 7,994 4,237 12,267 19,245

 Mainstem 

Umpqua

455 — 192 1,431 1,240 352 339 397 444 1,289 2,774 8,177 9,349 5,770 5,309 7,608 4,852 1,587 4,594 15,075

 Elk and Calapooya 

 Creek

185 — — — 708 2,315 1,709 196 379 434 1,864 2,581 1,555 4,450 2,602 — — — — —

 South Umpqua R. 2,508 2,284 201 2,415 579 755 1,685 512 678 1,219 479 6,482 1,670 2,345 9,333 14,364 2,246 4,549 12,007 15,944

 Cow Creek — — — 661 269 1,124 1,112 193 1,807 1,234 1,582 6,661 6,745 1,277 2,351 — — — — —

 Winchester Dam

 (wild adult coho)

376 1,273 1,607 933 851 1,460 1,075 727 727 1,186 1,838 2,951 3,780 3,005 3,705 2,113 3,062 1,410 3,438 7,720

 Total 4,113 4,873 3,759 10,244 5,336 12,809 10,824 2,960 9,153 7,685 12,233 35,702 37,591 29,607 31,346 42,676 18,154 11,783 32,306 57,984

Lakes

 Siltcoos Lake 1,622 2,895 391 3,622 1,426 4,497 4,775 2,653 3,122 2,819 3,835 5,104 4,812 7,225 8,025 4,364 5,473 1,447 3,873 5,197

 Tahkenitch Lake 1,085 1,215 318 954 1,062 1,627 1,627 1,858 2,817 3,769 634 3,526 3,489 3,203 3,496 1,897 3,718 3,551 2,604 2,977

 Tenmile Lake 1,687 3,141 1,277 5,569 3,354 5,092 7,092 4,092 5,169 6,123 8,278 11,039 13,861 6,260 7,166 8,464 15,187 3,957 17,131 9,175

 Total 4,393 7,251 1,986 10,145 5,841 11,216 13,493 8,603 11,107 12,710 12,747 19,669 22,162 16,688 18,687 14,724 24,378 8,956 23,608 17,349

Mid-Coast South

 Coos Bay and

 Big Creek

2,273 3,813 16,545 15,284 14,685 10,351 12,128 1,127 3,167 4,945 5,386 43,301 35,688 29,559 24,116 17,048 11,266 1,329 13,312 26,979

 Coquille 2,712 5,651 2,115 7,384 5,035 2,116 16,169 5,720 2,466 3,001 6,130 13,310 8,610 23,909 22,276 11,806 28,577 13,968 9,874 22,286

 Floras & Sixes R. — — — — — — — — 252 164 1,440 1,945 20 310 5,498 NAS* 1,104 340 637 3,203

— — — — — — — — — — — — — — — NAS NAS NAS 77 176

— — — — — — — — — — — — — — — NAS NAS NAS NAS 188

 Total 4,985 9,464 18,660 22,668 19,720 12,467 28,297 6,847 5,885 8,110 12,956 58,556 44,318 53,778 51,890 28,854 40,947 15,637 23,900 52,832

Oregon Coast ESU 21,279 37,602 42,197 55,344 44,169 53,979 74,021 23,398 32,004 49,128 70,110 172,617 260,570 228,581 175,380 154,127 128,838 66,174 165,362 262,735

*NAS = not adequate surveys or samples for estimate.
36

Table 6. Hatchery influence at coho population, stratum, and ESU scales, 1994–2010. Hatchery influence expressed as percent of total spawning 

escapement. Table from ODFW 2009a.a

 EL = extremely low, L = low, and M = medium.

ESU/strata

Population

Return year 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Marine 

survival EL EL EL EL EL L L M L M M L L M EL M L

Oregon 

Coast ESU 

Total

Hatchery

% hatchery 

59,418

12,394

20.9%

71,219

10,448

14.7%

107,150

26,128

24.4%

28,237

4,576

16.2%

40,614

8,139

20.0%

51,730

4,688

9.1%

82,644

8,953

10.8%

186,139

24,321

13.1%

265,122

12,028

4.5%

239,743

12,186

5.1%

183,366

10,633

5.8%

166,211

11,616

7.0%

141,352

12,784

9.0%

72,121

5,850

8.1%

182,957

3,271

1.8%

269,645

6,910

2.6%

258,719

3,953

1.5%

North Coast 

stratum 

Total

Hatchery

% hatchery 

8,239

3,755

45.6%

7,026

3,267

46.5%

6,484

4,368

67.4%

3,451

1,500

43.5%

2,837

496

17.5%

8,860

766

8.6%

18,704

486

2.6%

33,944

1,076

3.2%

50,465

1,222

2.4%

58,768

672

1.1%

29,953

1,131

3.8%

16,509

43

0.3%

25,524

1,389

5.4%

18,126

597

3.3%

25,777

206

0.8%

50,505

2,370

4.7%

53,655

495

0.9%

Necanicum 

River 

Total

Hatchery

% hatchery 

448

179

40.0%

301

120

39.9%

693

277

40.0%

161

64

39.8%

958

383

40.0%

370

19

5.1%

378

19

5.0%

5,112

280

5.5%

2,143

96

4.5%

2,535

158

6.2%

2,339

141

6.0%

1,252

34

2.7%

843

93

11.0%

464

33

7.1%

1,183

128

10.8%

3,869

42

1.1%

3,183

0

0.0%

Nehalem 

River 

Total

Hatchery

% hatchery 

5,556

2,712

48.8%

3,818

2,118

55.5%

4,293

3,766

87.7%

2,538

1,351

53.2%

1,257

51

4.1%

4,155

600

14.4%

14,580

118

0.8%

22,342

414

1.9%

17,862

698

3.9%

32,801

284

0.9%

18,825

89

0.5%

10,451

0

0.0%

12,816

1,202

9.4%

14,458

425

2.9%

17,205

0

0.0%

23,493

1,740

7.4%

29,729

354

1.2%

Tillamook 

Bay 

Total

Hatchery

% hatchery 

1,922

817

42.5%

1,096

755

68.9%

979

246

25.1%

481

44

9.1%

384

26

6.8%

1,978

147

7.4%

2,477

299

12.1%

2,119

175

8.3%

13,707

373

2.7%

13,129

121

0.9%

3,360

828

24.6%

1,995

0

0.0%

8,774

0

0.0%

2,429

134

5.5%

4,906

78

1.6%

16,811

560

3.3%

14,346

103

0.7%

Nestucca 

River 

Total

Hatchery

% hatchery 

313

47

15.0%

1,811

274

15.1%

519

79

15.2%

271

41

15.1%

238

36

15.1%

2,357

0

0.0%

1,269

50

3.9%

4,371

207

4.7%

16,753

55

0.3%

10,303

109

1.1%

4,768

73

1.5%

695

9

1.3%

1,895

19

1.0%

399

5

1.3%

1,844

0

0.0%

4,252

0

0.0%

5,129

26

0.5%

North Coast 

Dependents 

Total

Hatchery

% hatchery 

NAb

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

— 

NA

—

—

661

0

0.0%

2,116

0

0.0%

1,196

75

6.3%

376

0

0.0%

639

0

0.0%

2,080

28

1.3%

1,268

12

0.9%

Mid-Coast 

stratum 

Total

Hatchery

% hatchery 

12,219

4,805

39.3%

16,156

4,104

25.4%

24,278

9,633

39.7%

3,529

1,197

33.9%

5,067

2,626

51.8%

10,879

1,261

11.6%

15,824

262

1.7%

23,731

2,656

11.2%

95,721

1,514

1.6%

71,535

2,135

3.0%

44,066

1,996

4.5%

53,402

1,995

3.7%

22,695

1,471

6.5%

13,663

1,393

10.2%

70,742

2,604

3.7%

88,044

1,609

1.8%

53,661

150

0.3%

Salmon 

River 

Total

Hatchery

% hatchery 

1,554

1,463

94.1%

1,325

1,220

92.1%

2,703

2,621

97.0%

417

401

96.2%

432

346

80.1%

173

159

91.9%

394

215

54.6%

877

652

74.3%

1,108

565

51.0%

1,738

1,696

97.6%

3,525

1,883

53.4%

817

738

90.3%

1,160

647

55.8%

993

934

94.1%

2,664

2,012

75.5%

753

0

0.0%

1,438

92

6.4%

Siletz River Total

Hatchery

% hatchery 

1,200

579

48.3%

607

293

48.3%

763

368

48.2%

336

38

11.3%

357

41

11.5%

1,364

155

11.4%

3,387

0

0.0%

2,454

859

35.0%

2,504

375

15.0%

8,421

383

4.5%

8,179

0

0.0%

15,234

667

4.4%

5,323

118

2.2%

2,416

219

9.1%

20,634

0

0.0%

25,032

962

3.8%

5,814

0

0.0%

Yaquina 

River 

Total

Hatchery

% hatchery 

2,448

408

16.7%

5,668

945

16.7%

6,104

1,526

25.0%

529

110

20.8%

644

134

20.8%

2,567

4

0.2%

638

1

0.2%

3,760

171

4.5%

23,800

0

0.0%

16,484

0

0.0%

5,652

113

2.0%

3,613

172

4.8%

4,306

59

1.4%

3,355

197

5.9%

10,913

0

0.0%

11,690

508

4.3%

8,727

0

0.0%

Beaver 

Creek

Total

Hatchery

% hatchery 

675

0

0.0%

308

0

0.0%

1,701

405

23.8%

644

147

22.8%

520

119

22.9%

1,511

0

0.0%

1,510

46

3.0%

2,114

282

13.3%

3,360

143

4.3%

5,552

0

0.0%

4,569

0

0.0%

2,264

0

0.0%

2,122

172

8.1%

611

0

0.0%

1,218

0

0.0%

3,575

0

0.0%

2,442

0

0.0%

Alsea River Total

Hatchery

% hatchery 

1,279

451

35.3%

681

240

35.2%

1,637

577

35.2%

928

327

35.2%

1,732

1,624

93.8%

2,071

730

35.2%

3,363

0

0.0%

3,920

692

17.7%

9,254

181

2.0% 

10,281

0

0.0%

5,233

0

0.0%

13,907

0

0.0%

1,972

0

0.0%

2,146

0

0.0%

13,442

122

0.9%

14,777

139

0.9%

8,218

0

0.0%

Siuslaw 

River 

Total

Hatchery

% hatchery 

5,063

1,904

37.6%

7,567

1,406

18.6%

11,370

4,136

36.4%

675

174

25.8%

1,382

362

26.2%

3,193

213

6.7%

6,532

0

0.0%

10,606

0

0.0%

55,695

250

0.4%

29,059

56

0.2%

8,729

0

0.0%

17,321

414

2.4%

6,260

391

6.2%

3,581

29

0.8%

17,864

373

2.1%

30,607

0

0.0%

24,594

0

0.0%

Mid-Coast 

Dependents 

Total

Hatchery

% hatchery

NAb

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

8,179

0

0.0%

246

4

1.6%

1,552

84

5.4%

561

14

2.5%

4,007

97

2.4%

1,610

0

0.0%

2,428

58

2.4%
37

Table 6 continued. Hatchery influence at coho population, stratum, and ESU scales, 1994–2010. Hatchery influence expressed as percent of total 

spawning escapement. Table from ODFW 2009a.a

 EL = extremely low, L = low, and M = medium.

ESU/strata

 Population

Return year 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 

Marine 

survival EL EL EL EL EL L L M L M M L L M EL M L

Umpqua 

stratum 

Total

Hatchery

% hatchery

9,639

2,735

28.4%

22,423

2,311

10.3%

32,758

11,578

35.3%

5,126

1,792

35.0%

14,639

4,888

33.4%

11,004

2,428

22.1%

22,787

8,193

36.0%

52,842

17,758

33.6%

52,036

8,532

16.4%

43,702

8,919

20.4%

37,160

7,240

19.5%

51,845

9,313

18.0%

27,647

9,555

34.6%

15,630

3,847

24.6%

38,302

434

1.1%

60,428

2,444

4.0%

62,735

3,114

5.0%

Lower 

Umpqua River 

Total

Hatchery

% hatchery 

2,918

156

5.3%

10,854

0

0.0%

8,435

450

5.3%

1,445

188

13.0%

4,552

0

0.0%

2,708

85

3.1%

5,896

115

2.0%

12,872

1,233

9.6%

19,787

906

4.6%

16,529

35

0.2%

9,053

64

0.7%

19,014

423

2.2%

9,478

1,484

15.7%

4,661

424

9.1%

9,332

309

3.3%

20,026

781

3.9%

14,819

90

0.6%

Middle 

Umpqua River 

Total

Hatchery

% Hatchery 

2,309

147

6.4%

3,250

0

0.0%

5,431

345

6.4%

601

38

6.3%

1,336

79

5.9%

1,914

166

8.7%

4,719

164

3.5%

9,817

877

8.9%

11,669

931

8.0%

11,090

0

0.0%

6,433

58

0.9%

8,203

595

7.3%

6,111

1,259

20.6%

1,763

176

10.0%

4,472

0

0.0%

15,075

0

0.0%

11,649

0

0.0%

North Umpqua 

River 

Total

Hatchery

% hatchery

1,889

990

52.4%

3,049

1,756

57.6%

4,812

3,743

77.8%

1,956

1,379

70.5%

4,144

3,379

81.5%

3,173

1,979

62.4%

9,262

7,585

81.9%

16,728

14,094

84.3%

10,063

6,695

66.5%

11,746

8,884

75.6%

10,265

6,706

65.3%

10,264

8,295

80.8%

9,662

6,662

69.0%

3,975

2,565

64.5%

3,563

125

3.5%

8,185

465

5.7%

10,124

662

6.5%

South Umpqua 

River 

Total

Hatchery

% hatchery

2,523

1,442

57.2%

5,270

555

10.5%

14,080

7,040

50.0%

1,124

187

16.6%

4,607

1,430

31.0%

3,209

198

6.2%

2,910

329

11.3%

13,425

1,554

11.6%

10,517

0

0.0%

4,337

0

0.0%

11,409

412

3.6%

14,364

0

0.0%

2,396

150

6.3%

5,231

682

13.0%

20,935

0

0.0%

17,142

1,198

7.0%

26,143

2,362

9.0%

Lakes 

stratum 

Total

Hatchery

% hatchery

5,842

130

2.2%

11,216

132

1.2%

13,494

68

0.5%

8,603

16

0.2%

11,108

0

0.0%

12,711

168

1.3%

12,747

0

0.0%

19,669

65

0.3%

22,097

120

0.5%

16,091

15

0.1%

18,642

45

0.2%

14,725

0

0.0%

24,127

251

1.0%

8,955

0

0.0%

23,608

0

0.0%

17,349

0

0.0%

38,859

0

0.0%

Siltcoos Total

Hatchery

% hatchery

1,426

124

8.7%

4,497

82

1.8%

4,775

68

1.4%

2,653

0

0.0%

3,122

0

0.0%

2,819

63

2.2%

3,835

0

0.0%

5,104

0

0.0%

4,749

113

2.4%

6,628

0

0.0%

7,998

27

0.3%

4,364

0

0.0%

5,452

21

0.4%

1,447

0

0.0%

3,873

0

0.0%

5,197

0

0.0%

7,843

0

0.0%

Tahkenitch Total

Hatchery

% hatchery

1,062

6

0.6%

1,627

50

3.1%

1,627

0

0.0%

1,858

16

0.9%

2,817

0

0.0%

3,769

105

2.8%

634

0

0.0%

3,526

16

0.5%

3,487

7

0.2%

3,203

15

0.5%

3,496

0

0.0%

1,897

0

0.0%

3,611

107

3.0%

3,551

0

0.0%

2,604

0

0.0%

2,977

0

0.0%

10,631

0

0.0%

Tenmile Total

Hatchery

% hatchery

3,354

0

0.0%

5,092

0

0.0%

7,092

0

0.0%

4,092

0

0.0%

5,169

0

0.0%

6,123

0

0.0%

8,278

0

0.0%

11,039

49

0.4%

13,861

0

0.0%

6,260

0

0.0%

7,148

18

0.3%

8,464

0

0.0%

15,064

123

0.8%

3,957

0

0.0%

17,131

0

0.0%

9,175

0

0.0%

20,385

0

0.0%

Mid-South 

Coast stratum 

Total

Hatchery

% hatchery

23,479

969

4.1%

14,398

634

4.4%

30,136

481

1.6%

7,528

71

0.9%

6,963

129

1.9%

8,276

65

0.8%

12,582

12

0.1%

55,953

2,766

4.9%

44,803

640

1.4%

49,647

445

0.9%

53,545

221

0.4%

29,730

265

0.9%

41,359

118

0.3%

15,747

13

0.1%

24,528

27

0.1%

53,319

487

0.9%

49,809

194

0.4%

Coos River Total

Hatchery

% hatchery

15,207

707

4.6%

10,447

145

1.4%

12,128

0

0.0%

1,127

15

1.3%

2,985

0

0.0%

4,818

0

0.0%

4,704

0

0.0%

34,259

664

1.9%

33,265

145

0.4%

25,950

189

0.7%

23,450

113

0.5%

17,305

257

1.5%

11,266

0

0.0%

1,342

13

1.0%

14,881

0

0.0%

27,216

237

0.9%

27,228

194

0.7%

Coquille River Total

Hatchery

% hatchery

5,119

0

0.0%

2,116

82

3.9%

16,169

355

2.2%

5,720

0

0.0%

2,412

0

0.0%

2,667

0

0.0%

6,253

0

0.0%

15,665

1,832

11.7%

7,866

190

2.4%

22,565

162

0.7%

22,182

44

0.2%

11,806

0

0.0%

28,577

0

0.0%

13,968

0

0.0%

8,791

0

0.0%

22,513

227

1.0%

16,374

0

0.0%

Floras Cr. Total

Hatchery

% hatchery

2,893

240

8.3%

1,751

400

22.8%

1,628

109

6.7%

525

43

8.2%

958

79

8.2%

730

60

8.2%

1,477

0

0.0%

5,752

88

1.5%

3,568

296

8.3%

1,038

86

8.3%

7,446

0

0.0%

506

0

0.0%

1,214

110

9.1%

340

0

0.0%

803

17

2.1%

3,203

0

0.0%

5,629

0

0.0%

Sixes River Total

Hatchery

% hatchery

260

22

8.5%

84

7

8.3%

211

17

8.1%

156

13

8.3%

608

50

8.2%

61

5

8.2%

148

12

8.1%

277

182

65.7%

104

9

8.7%

94

8

8.5%

467

64

13.7%

113

8

7.1%

302

8

2.6%

97

0

0.0%

53

10

18.9%

190

14

7.4%

104

0

0.0%

Mid-South

Dependent 

Total

Hatchery

% hatchery

NAb

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

NA

—

—

0

0

NA

197

9

4.6%

474

0

0.0%

a

Updated by K. Moore, ODFW, Corvallis, OR. Pers. commun., January 2011. b

NA = not available.
38

large, warm system with degraded habitat. Spawner distribution appears to be seriously 

restricted in this population and it is probably the most vulnerable of any population in this ESU 

to increased temperatures.

The TRT’s biological recovery criteria (Wainwright et al. 2008) describe a DSS to help 

evaluate the status of the ESU. One component of this DSS explicitly addresses diversity. Three 

of the diversity criteria are sensitive to abundance at the population (PD-1) and watershed (PD-3, 

PD-4) levels (see TRT Biological Recovery Criteria Analysis and Results subsection). The DSS 

is structured to provide high scores when spawner escapements are high and uniformly 

distributed among populations and strata. In addition, higher scores are generated when 

juveniles and spawners are widely distributed within each population.

Population and Life History Diversity

In the spatially and temporally varying environment inhabited by OCCS, diversity is 

important for species and population sustainability. Diversity allows OCCS to use a wider array 

of environments than they could without it (see reviews in Groot and Margolis 1991) and 

protects against short-term spatial and temporal changes in the environment. Genetic diversity 

provides the raw material for surviving long-term environmental changes; fish with different 

characteristics have different likelihoods of persisting, depending on local environmental 

conditions. The more diverse a population, the more likely it is that some individuals would 

survive and reproduce in the face of environmental variation (McElhany et al. 2000). As we see 

in this assessment of current status and future threats, OCCS as a species, population, or as 

individuals, regularly face changes in their freshwater, estuarine, and ocean environments due to 

natural and human causes.

Compared to other species of Pacific salmon, coho salmon exhibit moderate levels of life 

history diversity (reviewed by Groot and Margolis 1991, Weitkamp et al. 1995). Coho salmon 

also tend to have somewhat lower levels of genetic diversity among populations compared to 

other Pacific salmon species, particularly in the central portion of their range (reviewed by 

Weitkamp et al. 1995 and Ford et al. 2004). These patterns have been interpreted as evidence for 

relatively high levels of gene flow among coho salmon populations (Ford et al. 2004, Johnson 

and Banks 2008). In the extremes of their range in California and Alaska, coho salmon tend to 

have higher levels of population differentiation than in their central range, probably due to 

genetic drift in relatively small populations (Olsen et al. 2003, Bucklin et al. 2007). Even within 

the OCCS ESU, the geographically central populations had higher levels of genetic diversity 

compared to populations at the northern and southern boundaries of the ESU, apparently due to 

overlapping migration patterns from strong northern and southern populations (Johnson and 

Banks 2008).

Most studies of molecular genetic variation within and among Oregon coho salmon 

populations utilized either allozymes (reviewed by Weitkamp et al. 1995) or microsatellite loci 

(e.g., Ford et al. 2004, Johnson and Banks 2008). These types of genetic markers (particularly 

microsatellites) are typically interpreted under an assumption that the dominant forces driving 

their evolution are mutation, drift, and migration. In contrast, Johnson and Banks (2008) 

examined patterns of variation at several genes that play a role in olfaction, and are therefore 

potential candidates for evolution by natural selection. Their study focused on several of the 
39

Lakes populations and the lower Umpqua River. The authors found notably higher levels of 

population differentiation at one of the olfactory loci than was observed at microsatellite loci, 

suggesting that natural selection is increasing patterns of genetic differentiation among these

populations at some specific genes. This result suggests that despite the relatively high rates of 

genetic flow among OCCS populations, there is potential for local adaptation among these 

populations.

Within the OCCS ESU, there is substantial genetic and geographic variation and 

structure, with genetic similarities clustering into a few geographic units. In the workgroup 

analyses, they designated these clusters as biogeographic strata that represent genetic and 

geographic similarities, as well as identifiable diversity among them (Lawson et al. 2007). 

Biological recovery criteria (Wainwright et al. 2008) were based on the principle that preserving 

sustainable populations in each of these biogeographic strata would conserve major genetic 

diversity in the ESU, as well as spread risks to the maintenance of genetic and geographic 

diversity due to catastrophes.

Providing access to a diversity of productive habitat types allows expression of 

phenotypes that may not otherwise occur. Although it is unknown which particular life history 

type will be successful in a given year, the expectation is for some types to be more successful 

than others. Consequently, by ensuring that a wide range of productive habitats are accessible to 

coho salmon, the opportunity is provided for greater expression of life history diversity, which in 

turn should increase the chances that at least some coho salmon life history types will be 

successful (Wainwright et al. 2008). In a more recent analysis, Greene et al. (2010) “strongly 

suggest that life history diversity can increase production and buffer population fluctuations, 

particularly over long time periods. Our findings provide new insights into the importance of

biocomplexity beyond spatio-temporal aspects of populations, and suggest that maintaining 

diverse life history portfolios of populations may be crucial for their resilience to unfavorable 

conditions such as habitat loss and climate change.”

As an example, extensive loss of access to habitats in estuaries and tidal freshwater may 

have been an important factor in reducing population diversity in OCCS. The Oregon coastal 

drainages supporting independent OCCS populations all terminate in tidally influenced 

freshwater/brackish/saltwater wetland and estuarine habitats (e.g., Good 2000). Recent sampling 

in coastal rivers from northern California to Alaska indicates that coho salmon juveniles are 

often present in these lower river/tidal freshwater/estuarine habitats (e.g., Koski 2009). Migrant 

trapping studies indicate that a substantial number of coho salmon fry emigrate downstream from 

natal streams into tidal reaches and therefore use lower river wetland/estuarine habitats (e.g., 

Chapman 1962, Miller and Sadro 2003, Koski 2009). In the past, observations of spring or early 

summer downstream migration of coho salmon fry were thought to represent a passive 

displacement in response to increased stream flows, competitive interactions, or capacity 

limitations. However, in recent studies summarized by Koski (2009) there is evidence that 

downstream migrations of coho salmon may be associated with specific life history strategies 

that contribute to resiliency in the face of fluctuating environmental conditions.

More recently, working in the Coos River, Bass (2010) reported that “widespread 

estuarine wetland losses have likely reduced the rearing capacity of coastal basins and decreased 

resiliency by diminishing the expression of subyearling migrant life histories within and among 
40

coho salmon populations.” Bass (2010) also reported nine coho salmon jacks PIT (passive 

integrated transponder) tagged as subyearling reservoir residents in spring 2008 and detected in 

the fall of 2009. For the 2007 broodyear, there were 33 returns from 1,191 coho tagged as 

presmolts (age 0) and 38 returns from 742 fish tagged as smolts.9 This suggests that these 

“nomad” early downstream migrants can survive and contribute to the spawning population. 

Bass (2010) concludes: “By affecting coho salmon nomads to a greater extent than other life 

history types, estuary loss may reduce the potential productivity boost and resilience component 

that this life history may contribute to its natal and neighboring populations.”

In the recent past, the effect of hatchery releases had a significant effect on life history 

diversity in the OCCS ESU. ODFW has significantly reduced hatchery releases of coho salmon, 

therefore the effect of hatchery fish on native population diversity should be abating, although 

there is little information about the duration of hatchery genetic effects on naturally spawning 

populations. Because of the significant reduction in hatchery releases of coho, the hatchery 

fraction of spawners observed on the spawning grounds has been substantially reduced (ODFW 

2009b). This should lead to improvement of diversity in naturally produced OCCS in those 

populations once dominated by hatchery fish.

Since 1990 there have been years with extremely low escapements in some systems and 

many small systems have shown local extirpations, presumably reducing diversity due to loss of 

dependent populations. For example, Cummins Creek on the central coast had no spawners 

observed in 1998, indicating the potential loss of a brood cycle. These small systems are apt to 

be repopulated by stray spawners, most likely from larger adjacent populations during periods of 

higher abundance (Lawson et al. 2007), and recent local extirpations may represent loss of 

genetic diversity in the context of normal metapopulation function.

Current status of diversity shows improvement through the waning effects of hatchery 

fish on populations of OCCS. In addition, recent efforts in several coastal estuaries to restore 

lost wetlands should be beneficial. However, the loss of diversity brought about by legacy 

effects of freshwater and tidal habitat loss, coupled with the restriction of diversity from very low 

returns over the past 20 years, led us to conclude that diversity is lower than it was historically.

Harvest Impacts

Historical harvest rates on OPI area coho salmon were in the range of 60% to 90% from 

the 1960s into the 1980s (Table 3). Modest harvest reductions were achieved in the late 1980s, 

but rates remained high until a crisis was perceived and most directed coho salmon harvest was 

prohibited in 1994. Subsequent fisheries have been severely restricted (ODFW 2005c, 2009a) 

and most reported mortalities are estimates of indirect (noncatch) mortality in Chinook salmon 

(Oncorhynchus tshawytscha) fisheries and selective fisheries for marked (hatchery) coho salmon. 

Estimates of these indirect mortalities are somewhat speculative and there is a risk of 

underestimation (Lawson and Sampson 1996, PFMC 2009).

 9 K. Nordholm, Oregon State University, Dept. Fisheries and Wildlife, Corvallis, OR. Pers. commun., February 

2011.
41

Amendment 13

PFMC (1998) adopted Amendment 13 to its Salmon Fishery Management Plan in 1998. 

This amendment was developed as part of the Oregon Plan for Salmon and Watersheds. It 

specified an exploitation rate harvest management regime with rates for OCN dependent on 

marine survival (as indexed by hatchery jack:smolt ratios) and parental and grandparental 

spawning escapements. Exploitation rates ranged from 13% to a maximum of 35%. 

Amendment 13 was reviewed in 2000 and the harvest rate matrix was modified to include an 8% 

category under conditions of extremely poor marine survival, as was observed in the late 1990s. 

At the same time, the maximum exploitation rate was increased to 45% and the grandparental 

escapement criterion was dropped. Exploitation rates were calculated to allow a doubling of 

spawners under conditions of moderate-to-good ocean survival.

Risk assessment was conducted for Amendment 13 (PFMC 1998) and the 2000 

Amendment 13 Review (PFMC 2000) using the Nickelson/Lawson coho salmon habitat-based 

life cycle model (Nickelson and Lawson 1998). The models were augmented to include a 

management strategy evaluation that simulated the fishery management process, including errors 

in spawner assessment, prediction, and harvest management. In general, exploitation rate 

management with a 35% cap showed a lower risk of pseudoextinction than managing for an 

escapement goal of 200,000 spawners, but higher risk than a zero harvest scenario. Starting from 

the very low escapements of 1994, basins on the north coast had higher extinction risks than 

those on the Mid-North and Mid-South coasts.

Mark-selective fisheries

Beginning in 1998, most adult hatchery-origin coho salmon in the OPI area were marked 

with an adipose fin clip. This marking allowed the implementation of mark-selective fisheries, 

with legal retention only of marked fish. Unmarked fish were to be released unharmed. 

Recreational mark-selective fisheries have been conducted on the Oregon coast in each year 

since 1998, with quotas ranging from 9,000 to 88,000 marked fish.

Commercial troll fisheries targeting Chinook salmon were also operating. In 2007 a 

mark-selective commercial troll fishery targeting hatchery coho salmon was implemented with a 

quota of 10,000, and a similar fishery was implemented in 2008 with a quota of 21,240. Actual 

catch in these fisheries was about half of the quota in each year. A concern with these fisheries 

is the high ratio of unmarked to marked fish that was encountered.

The mark-selective coho and commercial troll Chinook salmon fisheries catch and

release coho salmon, resulting in incidental mortalities. In addition some coho, so-called dropoffs, encounter the gear but escape or are eaten by predators. Estimates of noncatch mortalities 

from hook and release and drop-offs are difficult because they are, by their nature, unobserved. 

Field studies in the 1990s (NRC 1997) and a literature review and meta-analysis resulted in the 

adoption by the PFMC of hooking mortality rates of 13% for recreational fisheries and 26% for 

commercial fisheries. In addition, drop-off mortalities were assumed to equal 5% of the number 

of fish brought to the boat. These rates are used by the PFMC for a coho Fisheries Resource 

Allocation Model to estimate mortalities in council-managed fisheries. Postseason estimates of 

OCN exploitation rates based on that modeling have ranged from 0.07 to 0.15 since the 
42

curtailment of directed coho salmon fishing in 1994. The BRT considers that these rates may be 

underestimates and that actual mortalities may have been greater (Lawson and Sampson 1996).

Freshwater fisheries

A few small freshwater fisheries have been allowed in recent years, based on the 

provision in Amendment 13 that terminal fisheries can be allowed on strong populations as long 

as the overall exploitation rate for the ESU does not exceed the Amendment 13 allowable rate 

and population escapement is not reduced below full seeding of the best available habitat. The 

difference between these fisheries and the mark-selective fisheries in the ocean is that the 

freshwater fisheries are directed take on a listed species. NMFS has approved these fisheries 

with the condition that the methodologies used by ODFW to predict population abundances and 

estimate full seeding levels are presented to the PFMC for review and approval.

Despite these uncertainties, there is no doubt that harvest-related mortalities have been 

reduced substantially since harvest was curtailed in 1994. This reduction is reflected in positive 

short-term trends in spawner escapements (Figure 5 and Figure 6). Harvest management has 

succeeded in maintaining spawner abundance in the face of a continuing downward trend in 

productivity of these stocks. Further harvest reductions can have little effect on spawning 

escapements. Future remedies must be found outside of harvest management until the decline in 

productivity is reversed (Lawson 1993).

Artificial Propagation

As of 2009, there are only three coho hatchery stocks in propagation within the OCCS 

ESU. All other hatchery programs have been terminated. (For more discussion, see Artificial 

Propagation−Membership in the ESU subsection).

In previous OCCS status reviews, coho salmon hatchery programs were a major concern 

throughout the ESU. High numbers of hatchery coho that could not be differentiated from 

naturally produced fish were released in most populations, hatchery broodstocks were intermixed 

among stocks of different populations, multiple life stages of juvenile hatchery coho were 

stocked into wild production areas, and hatchery origin (stray) coho were common in natural 

spawning areas throughout the ESU. However, since the early 1990s the State of Oregon has 

reformed hatchery practices due to a variety of genetic, ecological, and economic factors. This 

has lessened the risks of hatchery programs to wild coho populations in the ESU. These 

management changes have been described in detail in previous BRT assessments (i.e., Good et 

al. 2005) and are summarized below.

Releases of hatchery coho salmon in the ESU have declined from a peak of 

approximately 35 million fish in 1981 to approximately 260,000 smolts in 2009 (Figure 9), 

(Oregon 2005, ODFW 2009a, 2009b). In the early 1990s, hatchery coho were released in 17 of 

19 ESU populations. In 2009 hatchery coho salmon were released in 3 of 19 ESU populations 

(Nehalem, Trask, and South Umpqua). In the early 1990s, ODFW managed 16 different brood 

stocks throughout the ESU. In 2009 there were only three brood stocks still in propagation 

(ODFW 2009b).
43

Figure 9. Releases of juvenile hatchery coho (all age classes) in the OCCS ESU by hatchery type from 

1980 to 2003. The 1980 through 1984 release years are missing unfed fry release data. Vertical 

line marks the beginning of the Oregon Plan. Further reductions occurred from 2004 to 2009, as 

described in text.

Since 1997 all hatchery coho released have been adipose fin clipped in order to 

differentiate between hatchery-origin and natural-origin fish in mark-selective fisheries and 

evaluate straying of hatchery fish into natural spawning areas. External marking of all hatchery 

fish helped to resolve uncertainties about the magnitude of these interactions on the spawning 

grounds that had previously been assessed by evaluating fish scale data. In the 1990s many 

populations had proportions of hatchery fish in the natural spawning populations in excess of 

40%, with the north coast populations having the highest proportion of hatchery spawners 

(Figure 10, Table 6).

By the early 2000s, stray rates had decreased in most populations due to the elimination 

of hatchery programs and reductions in the number of fish released. Most populations are now 

below Oregon’s stray rate standard of no more than 10% hatchery coho on the spawning grounds 

(Oregon 2007). The notable exceptions are the Salmon River and North Umpqua River 

populations, where stray rates were still greater than 50%. However, in broodyear 2006, the 

Salmon and North Umpqua hatchery coho programs were eliminated entirely in order to 

decrease the straying problems. The percentage of hatchery fish spawning naturally in these two 

populations showed a substantial decrease beginning in the spawning season of 2009−2010.

Since the previous status review assessments in 1997 and 2003, new information and 

analyses are available that help inform the BRT of the potential risks associated with hatchery 

programs and the conservation of the ESU. Interactions between hatchery and wild fish are 
44

Figure 10. Proportion of hatchery origin coho salmon in each stratum of the OCCS ESU, 1994–2008. 

Data from ODFW 2009a.

generally considered to have negative outcomes for the wild fish. A large body of literature 

documents reduced spawning success, freshwater survival, and production of wild fish when 

hatchery fish are present (NRC 1997, Flagg and Nash 1999, Flagg et al. 2000, ISG 2000, Einum 

and Fleming 2001, IMST 2001, Chilcote 2003, Hoekstra et al. 2007, Araki et al. 2008, Naish et 

al. 2008). Analyses of the specific effects of hatchery coho salmon on wild coho salmon on the 

Oregon coast have all concluded the existing hatchery programs were detrimental to the survival 

and productivity of this ESU (Nickelson 2003, Oosterhout et al. 2005, Buhle et al. 2009). The 

recent management changes by the State of Oregon are therefore expected to largely alleviate the 

detrimental effects of hatchery programs on wild coho salmon.

Overall, the reduction in hatchery activity is expected to benefit wild runs throughout the 

ESU. For example, Buhle et al. (2009) used data on natural spawning abundance, hatchery 

releases, and the proportion of hatchery fish in spawning populations to fit a model that allowed

estimation of the impacts of hatchery releases on natural OCCS productivity. Their model found 

a significant negative effect of hatchery releases and naturally spawning hatchery fish; they 

estimated the reductions in hatchery production since the mid-1990s accounted for 

approximately 27% of the increase in wild OCCS seen in the 1997 to 2000 brood cycles. These 

results indicate that at least some of the benefits from reduced hatchery production have already 

been observed in the recent abundance trends. To the degree that past hatchery practices led to 

genetic deterioration of wild salmon stocks, additional benefits from the reduced levels of 

hatchery production may continue to accrue in the future as these populations adapt back to wild 

conditions. In addition, the two populations that have only recently seen reductions in hatchery 
45

releases (North Umpqua and Salmon rivers) may also experience nearer term gains in 

productivity due to the recent elimination of hatchery coho salmon released in those watersheds.

TRT Biological Recovery Criteria Analysis and Results

The biological recovery criteria developed by the TRT (Wainwright et al. 2008) are 

framed within the context of a DSS. At the highest level, the DSS is structured to represent the 

hierarchical population structure of the ESU. Populations are grouped into biogeographic strata, 

which in combination make up the ESU. The DSS framework is organized into two categories, 

persistence and sustainability, which imply different levels of risk.

The persistence analysis assesses the ability of the ESU to persist (i.e., not go extinct) 

over a 100-year period without artificial support. This includes the ability to survive prolonged 

periods of adverse environmental conditions that may be expected to occur at least once during 

the 100-year time frame. This analysis has three population-level criteria that measure 

population productivity, probability of persistence, and abundance relative to critically low 

thresholds.

The sustainability analysis assesses the ability of the ESU to maintain its genetic legacy 

and long-term adaptive potential for the foreseeable future. Sustainability implies stability of 

habitat availability and other conditions necessary for the full expression of the population’s (or 

ESU’s) life history diversity into the foreseeable future. The criteria within the DSS (Table 7, 

Figure 10) are used to evaluate population diversity using objective measures of spawner 

abundance, artificial influence, spawner and juvenile distribution, and habitat capacity. In 

addition, ESU-level diversity that includes genetic diversity (a function of genetic structure, 

effects of selection, effects of migration, and effects of introgression), phenotypic and habitat 

diversity, and small populations was evaluated. The BRT then used recent observations of these 

population metrics to inform its assessment of risk to the OCCS ESU.

In practice, application of the DSS began with evaluating a number of primary biological 

criteria that are defined in terms of logical (true/false) statements about biological processes 

essential to the persistence or sustainability of the ESU. Evaluating these primary criteria with 

respect to available observations results in a truth value in the range from –1 (false) to +1 (true). 

Intermediate values between these extremes reflect the degree of certainty of the statement, given 

available knowledge, with a value of 0 indicating complete uncertainty about whether the 

statement is true or false. These primary criteria are then combined logically with other criteria 

at the same geographic scale, then combined across geographic scales to result in an evaluation 

of ESU-wide criteria. Thus the end result is an evaluation of the biological status of the ESU as 

a whole, with an indication of the degree of certainty of that evaluation.

Metrics for the DSS are derived from data provided by ODFW10 from various survey and 

monitoring studies. Data include: spawner survey data (peak counts and area under the curve 

[AUC] estimates), estimates of wild and hatchery fish on the spawning grounds, distribution of 

spawners and summer juveniles, and estimates of habitat capacity. These contribute to a set of 

objectively measurable criteria. ESU-level diversity was more difficult to evaluate because 

 10 K. Moore, ODFW, Salem, OR. Pers. commun., December 2010.
46

Table 7. Biological recovery criteria definitions (Wainwright et al. 2008).

ESU-level criteria

EP. ESU persistence: ESU will persist over the next 100 years. All biogeographic strata are persistent (see 

stratum persistence, SP).

ES. ESU sustainability: ESU is self-sustaining into the foreseeable future.

ES-1. All strata sustainable: All biogeographic strata are sustainable (see stratum sustainability, SS).

ES-2. ESU-level diversity: ESU has sufficient broadscale diversity to maintain its ecological and 

evolutionary functions into the foreseeable future.

ED-1. Genetic diversity: ESU-level genetic diversity is sufficient for long-term sustainability of the ESU.

ED-1a. Genetic structure: Genetic diversity within the ESU is comparable to healthy coho salmon ESUs 

and forms the basis for life-history diversity.

ED-1b. Effects of selection: Human-driven selection is not sufficient to decrease genetic diversity.

ED-1c. Effects of migration: Genetic diversity is not compromised by changes in movements of fish.

ED-2. Phenotypic and habitat diversity: ESU-level phenotypic and habitat diversity are sufficient for longterm sustainability of the ESU.

ED-2a. Phenotypic diversity: Phenotypic diversity is present within the ESU at levels comparable to 

healthy ESUs or the historical template. 

ED-2b. Habitat diversity: Habitats are sufficiently productive, diverse, and accessible to promote 

phenotypic plasticity.

ED-3. Small populations: Dependent populations within the ESU are not permanently lost.

Biogeographic stratum–level criteria

SP. Stratum persistence: Most of the historically independent populations in the stratum are persistent (see 

population persistence, PP).

SS. Stratum sustainability: Stratum is self-sustaining (re: diversity and functionality) into the foreseeable future.

SD. Stratum diversity: Most of the historically independent populations in the stratum are at present sustainable 

(see population sustainability, PS).

SF. Stratum functionality: All of the historically independent populations in the stratum are functional (see 

population functionality, PF).

Population-level criteria

PS. Population sustainability: Population is able to sustain itself into the future. Requires both population 

persistence (PP) and population diversity (PD).

PP. Population persistence: Population will persist for the next 100 years.

PP-1. Population productivity: Productivity at low abundance is sufficient to sustain the population through 

an extended period of adverse environmental conditions.

PP-2. Probability of persistence: Population has a high likelihood of persisting over the next 100 years, as 

estimated from PVA models.

PP-3. Critical abundance: Population abundance is maintained above levels where small-population 

demographic risks are likely to become significant.

PD. Population diversity: Population has sufficient diversity and distribution to ensure continued fitness in the 

face of environmental change.

PD-1. Spawner abundance: Population has sufficient naturally produced spawners to prevent loss of 

genetic variation due to random processes over a 100-year time frame.

PD-2. Artificial influence: Abundance of naturally spawning hatchery fish will not be so high as to be 

expected to have adverse effects on natural populations.

PD-3. Spawner distribution: On average, the historically occupied watersheds in the population’s range 

have spawners occupying the available spawning habitat (see watershed spawner occupancy, W-Sp).

PD-4. Juvenile distribution: On average, the historically occupied watersheds in the population’s range 

have juveniles occupying the available juvenile habitat (see watershed juvenile occupancy, W-Ju).

PF. Population functionality: Habitat quality and quantity are adequate to support sufficient abundance to 

maintain long-term genetic integrity of the population.

Watershed-level criteria

W-Sp. Watershed spawner occupancy: Spawners occupy a high proportion of the available spawning habitat 

within the watershed.

W-Ju. Watershed juvenile occupancy: Juveniles occupy a high proportion of the available juvenile habitat within 

the watershed.
47

objectively measurable criteria were not available, so scores were produced using a formal 

process by an expert panel (Wainwright et al. 2008). ESU-level diversity was not reevaluated 

for this report.

The DSS was run with data through the 2009 spawning run. ODFW provided the data 

used in the update. In the process of compiling data for the 4 years since the TRT analysis, 

several inconsistencies were discovered and reconciled. For this reason, the DSS results reported 

in Figure 11, Figure 12, and Table 8 are not directly comparable to the results presented in 

Wainwright et al. (2008). Table 9 is presented for historical comparison but was not used by the 

BRT in its deliberations. Table 10 summarizes VSP attributes (McElhany et al. 2000) related to 

DSS results.

Figure 11. Decision tree for the biological recovery criteria. Flow lines show the logical connections 

from the primary criteria (blue hexagons) through intermediate levels (black rectangles) to ESUwide evaluations (magenta ovals) for ESU persistence (EP) and sustainability (ES). Colored 

maps show results at each geographic scale, with dark red indicating poor conditions and dark 

green indicating good conditions Criteria abbreviations are as in Table 7.
48

Figure 12. Truth value colors showing degree of certainty interpretation for colors found in Figure 11. 

(Reprinted from Wainwright et al. 2008.)

Two criteria were not updated. Persistence probability, PP-2, based on four population 

viability analysis (PVA) models, was not updated because sensitivity analysis presented in 

Wainwright et al. (2008) showed that DSS results were not very sensitive to small changes in 

individual model results. The main utility of the PVA model runs is to evaluate relative 

vulnerabilities of the populations. These relative vulnerabilities are unlikely to change with the 

addition of a few more years of data. The population functionality criterion, PF-1, based on 

habitat quantity, was not updated because it would have required a major analysis of recent 

habitat data. The BRT considered that this criterion was not sensitive to small changes in habitat 

conditions and was also not particularly informative. Habitat issues were addressed with more 

rigor in new analyses outside the structure of the DSS. A 10-year time series of habitat survey 

data was analyzed for evidence of trends in habitat quality, providing a much more informative 

metric than the habitat quantity measure currently used for PF-1 (see the habitat complexity 

discussion). In the future it may be possible to incorporate a habitat trend index in the DSS.

The critical abundance criterion, PP-3, in Wainwright et al. (2008), was discovered to 

have been evaluated by the TRT using the wrong data set. It was originally calculated using 

AUC spawner data rather than peak-count data as specified in the criterion. The updated critical 

abundance values are based on peak counts (Table 8). AUC estimates are always higher than 

peak counts because they include fish present on the spawning grounds over a longer period of 

time. Peak counts are simply the highest number observed at any one time. The object of the 

criterion was to evaluate the likelihood of depensation due to low spawner numbers. If too few 

fish are present on the spawning grounds at any one time, then the probability that individuals 

will be able to locate mates is reduced. This effect, termed depensation, is thought to become a 

problem at spawner densities below four fish per mile (Wainwright et al. 2008). Therefore, peak 

counts are more suitable than AUC estimates for evaluating this effect. For comparison with 

results presented in Wainwright et al. (2008), DSS values based on AUC spawner estimates are 

also presented (Table 9).

The DSS result for ESU persistence was 0.34 (Table 8). Recall that a value of 1 (Figure 

12) would indicate complete confidence that the ESU will persist for the next 100 years, a value 
49

Table 8. Decision support system results by criterion and independent population, stratum, and ESU. Critical abundance data (PP-3) from peak 

counts. See Figure 12 for color representation of truth value for each stratum.

OCCS ESU

EP

0.34

ED-1a

0.28

ED-1b

–0.01

ED-1c

0.26

ED-2a

0.30

ED-2b

–0.20

ED-3

0.40

ED-1

0.18

ED-2

0.05

ES-1

0.42

ES-2

0.13

ES

0.24

Stratum SP SD SF SS

North Coast 0.27 0.33 0.53 0.39

Mid-Coast 0.25 0.36 0.47 0.40

Lakes 0.88 0.64 0.38 0.47

Umpqua 0.40 0.26 0.88 0.45

Mid-South Coast 0.24 0.37 0.68 0.48

Stratum Population PP-1 PP-2 PP-3 PD-1 PD-2 PF-1 PD-3 PD-4 PP PD PS PF

North Coast Necanicum River 0.95 –0.44 0.06 0.10 0.35 0.18 0.85 0.96 –0.26 0.36 –0.15 0.18

North Coast Nehalem River 0.80 0.92 0.51 1.00 0.66 1.00 0.46 0.63 0.69 0.62 0.65 1.00

North Coast Tillamook Bay 0.90 0.50 0.15 0.35 0.42 1.00 0.35 0.60 0.36 0.40 0.37 1.00

North Coast Nestucca River 0.82 0.74 –0.08 0.26 0.92 0.89 0.66 0.77 0.18 0.51 0.28 0.89

Mid-Coast Salmon River –0.51 –1.00 –1.00 –0.14 –1.00 0.20 –0.14 1.00 –1.00 –1.00 –1.00 0.20

Mid-Coast Siletz River 0.91 0.66 0.09 0.24 0.67 0.98 0.54 0.91 0.34 0.46 0.38 0.98

Mid-Coast Yaquina River 0.97 0.76 0.20 0.46 0.69 1.00 0.80 1.00 0.47 0.66 0.54 1.00

Mid-Coast Beaver Creek 0.97 0.62 0.90 0.08 0.86 0.14 1.00 1.00 0.79 0.44 0.56 0.14

Mid-Coast Alsea River 0.63 0.96 –0.29 0.51 0.97 1.00 0.47 0.88 –0.03 0.65 0.13 1.00

Mid-Coast Siuslaw River 0.89 0.98 –0.14 1.00 0.81 1.00 0.65 0.85 0.17 0.80 0.35 1.00

Lakes Siltcoos River (Lake) 0.81 1.00 0.86 0.47 0.99 0.32 1.00 1.00 0.88 0.76 0.81 0.32

Lakes Tahkenitch Lake 0.69 0.70 1.00 0.21 0.95 0.32 1.00 1.00 0.78 0.56 0.64 0.32

Lakes Tenmile Lake 0.96 0.98 1.00 0.85 0.98 0.59 1.00 –0.36 0.98 –0.05 0.20 0.59

Umpqua Lower Umpqua R. 0.68 0.86 0.48 0.96 0.42 1.00 0.66 0.59 0.63 0.59 0.60 1.00

Umpqua Middle Umpqua R. 0.73 0.84 0.00 0.32 0.35 1.00 0.27 0.48 0.26 0.33 0.28 1.00

Umpqua North Umpqua River –0.96 0.52 0.22 0.97 –0.96 0.67 –0.37 –0.87 –0.95 –0.95 –0.95 0.67

Umpqua South Umpqua River 0.92 0.94 0.26 0.28 0.50 1.00 –0.05 0.41 0.54 0.11 0.23 1.00

Mid-South Coast Coos Bay 0.92 0.86 0.33 1.00 0.94 1.00 0.95 1.00 0.58 0.97 0.74 1.00

Mid-South Coast Coquille River 0.96 0.96 0.72 1.00 0.98 1.00 0.67 0.81 0.86 0.83 0.85 1.00

Mid-South Coast Floras Creek 0.99 0.92 –0.38 0.18 0.81 0.87 0.27 1.00 –0.11 0.40 0.01 0.87

Mid-South Coast Sixes River 0.52 –1.00 –0.71 –0.87 0.17 0.38 –0.17 –0.58 –1.00 –0.83 –1.00 0.38
50

Table 9. Decision support system results based on using area under the curve (AUC) spawner density estimates for the critical abundance (PP-3) 

criterion for comparison with Wainwright et al. (2008).

OCCS ESU

EP

0.70

ED-1a

0.28

ED-1b

–0.01

ED-1c

0.26

ED-2a

0.30

ED-2b

–0.20

ED-3

0.40

ED-1

0.18

ED-2

0.05

ES-1

0.53

ES-2

0.13

ES

0.28

Stratum SP SD SF SS

North Coast 0.69 0.54 0.53 0.53

Mid-Coast 0.55 0.54 0.47 0.50

Lakes 0.92 0.64 0.38 0.47

Umpqua 0.66 0.36 0.88 0.53

Mid-South Coast 0.91 0.74 0.68 0.70

Stratum Population PP-1 PP-2 PP-3 PD-1 PD-2 PF-1 PD-3 PD-4 PP PD PS PF

North Coast Necanicum River 0.95 –0.44 0.54 0.10 0.35 0.18 0.85 0.96 –0.22 0.36 –0.11 0.18

North Coast Nehalem River 0.80 0.92 0.85 1.00 0.66 1.00 0.46 0.63 0.85 0.62 0.72 1.00

North Coast Tillamook Bay 0.90 0.50 0.80 0.35 0.42 1.00 0.35 0.60 0.68 0.40 0.50 1.00

North Coast Nestucca River 0.82 0.74 0.60 0.26 0.92 0.89 0.66 0.77 0.70 0.51 0.58 0.89

Mid-Coast Salmon River –0.51 –1.00 –1.00 –0.14 –1.00 0.20 –0.14 1.00 –1.00 –1.00 –1.00 0.20

Mid-Coast Siletz River 0.91 0.66 0.46 0.24 0.67 0.98 0.54 0.91 0.62 0.46 0.51 0.98

Mid-Coast Yaquina River 0.97 0.76 0.82 0.46 0.69 1.00 0.80 1.00 0.84 0.66 0.74 1.00

Mid-Coast Beaver Creek 0.97 0.62 1.00 0.08 0.86 0.14 1.00 1.00 0.82 0.44 0.57 0.14

Mid-Coast Alsea River 0.63 0.96 0.15 0.51 0.97 1.00 0.47 0.88 0.39 0.65 0.48 1.00

Mid-Coast Siuslaw River 0.89 0.98 0.19 1.00 0.81 1.00 0.65 0.85 0.49 0.80 0.60 1.00

Lakes Siltcoos River (Lake) 0.81 1.00 1.00 0.47 0.99 0.32 1.00 1.00 0.92 0.76 0.83 0.32

Lakes Tahkenitch Lake 0.69 0.70 1.00 0.21 0.95 0.32 1.00 1.00 0.78 0.56 0.64 0.32

Lakes Tenmile Lake 0.96 0.98 1.00 0.85 0.98 0.59 1.00 –0.36 0.98 –0.05 0.20 0.59

Umpqua Lower Umpqua R. 0.68 0.86 0.85 0.96 0.42 1.00 0.66 0.59 0.78 0.59 0.66 1.00

Umpqua Middle Umpqua R. 0.73 0.84 0.34 0.32 0.35 1.00 0.27 0.48 0.54 0.33 0.40 1.00

Umpqua North Umpqua River –0.96 0.52 0.76 0.97 –0.96 0.67 –0.37 –0.87 –0.94 –0.95 –0.95 0.67

Umpqua South Umpqua River 0.92 0.94 0.75 0.28 0.50 1.00 -0.05 0.41 0.86 0.11 0.31 1.00

Mid-South Coast Coos Bay 0.92 0.86 0.94 1.00 0.94 1.00 0.95 1.00 0.90 0.97 0.94 1.00

Mid-South Coast Coquille River 0.96 0.96 0.93 1.00 0.98 1.00 0.67 0.81 0.95 0.83 0.89 1.00

Mid-South Coast Floras Creek 0.99 0.92 0.85 0.18 0.81 0.87 0.27 1.00 0.92 0.40 0.58 0.87

Mid-South Coast Sixes River 0.52 –1.00 –0.39 –0.87 0.17 0.38 –0.17 –0.58 –1.00 –0.83 –1.00 0.38
51

Table 10. VSP attributes related to the DSS criteria and results.

VSP Factor DSS Criterion Status Comments

Abundance (PP-2)

a Probability of persistence 

(multiple PVA models)

Most (18 of 21) truth 

values > 0.25

PP-3 Critical abundance (mean 

spawner densities in low years)

Many (9 of 21) truth 

values > 0.25

PD-1 Spawner abundance (harmonic 

mean sufficient to avoid 

genetic risks)

Many (14 of 21) truth 

values > 0.25

Growth rate 

(productivity)

PP-1 Population productivity 

(geometric mean of natural 

return ratio in low years)

Most (19 of 21) truth 

values > 0.25

PP-2 Probability of persistence 

(multiple PVA models)

Most (18 of 21) truth 

values > 0.25

Spatial structure 

and connectivity

PD-3 Spawner distributions (>4 fish 

per mile in half of watersheds)

Many (17 of 21) > 

0.25

South Coast has 

most low scores

(PD-4)

a Juvenile distributions (pools 

with ≥1 fish)

Most (18 of 21) truth 

values > 0.25

Questions 

about 

usefulness of 

this criterion

ED-1cb Barriers to 

migration/connectivity

Low-moderate 

changes compared to 

historical template

Diversity PD-1 Spawner abundance (harmonic 

mean)

Most (14 of 21) truth 

values > 0.25

PD-2 Artificial influence (% 

hatchery fish spawning)

Most (19 of 21) truth 

values > 0.25

Improved since 

last assessment

ED-1b Genetic diversity (genetic 

structure, effects of selection, 

barriers to migration)

Low-moderate 

changes compared to 

historical template

ED-2b Phenotypic and habitat 

diversity

Moderate changes 

compared to 

historical habitat 

diversity, lowmoderate to 

phenotypic diversity

ED-3b Small populations not 

permanently lost

Moderately certain 

small populations not 

lost

Threats (PF-1)

a Habitat sufficient (habitat 

model)

Most (18 of 21) truth 

values > 0.25

Usefulness of 

criterion 

questioned a

Population criteria (PP-2, PD-4, and PF-1) were not reevaluated in 2009 or 2010. b

ESU-level criteria were not reevaluated in 2009 or 2010.
52

of −1 would indicate complete certainty of failure to persist, and a value of 0 would indicate no 

certainty of either persistence or extinction. The BRT therefore interpreted a value of 0.34 as 

indicating a moderate certainty of ESU persistence over the next 100 years. The DSS result for 

ESU sustainability, ES, was 0.24, indicating a low-to-moderate certainty that the ESU is 

sustainable for the foreseeable future.

The overall ESU persistence and sustainability scores summarize a great deal of 

variability in population and stratum-level information on viability. For example, although the 

overall persistence score was 0.34, the scores for individual populations ranged from −1 (Salmon 

River, Sixes River) to +0.98 (Tenmile Lakes), and approximately two-thirds (13/21) of the 

populations had persistence scores greater than 0.25 (Table 8). The stratum-level persistence 

scores, SP, were calculated as the median of the population scores. Only the Lakes stratum had a 

very high certainty of stratum persistence (0.88) followed by the Umpqua (0.40). The three 

remaining strata and persistence scores range narrowly from 0.24 to 0.27. Population 

sustainability scores, PS, ranged from −1.0 in two populations to a high of 0.85 in the Coquille 

River. The stratum scores for sustainability, SS, were less variable (Table 8), in the narrow 

range of 0.39 to 0.48.

The data set adjustment from AUC counts to peak counts for critical abundance lowered

the persistence score substantially. Persistence is evaluated using three factors, while 

sustainability uses seven (including the three persistence factors). As a result, persistence is 

much more sensitive to changes in a single factor than is sustainability, so this score is 

considerably lower than was reported in Wainwright et al. (2008) while sustainability is slightly 

higher.

Spawning escapements in some recent years have been higher than has been seen in the 

past 60 years. This is attributable to a combination of management actions and environmental 

conditions. In particular, harvest has been strongly curtailed since 1994, allowing more fish to 

return to the spawning grounds (Figure 5). As shown in Figure 10, hatchery production has been 

reduced to a small fraction of the wild production (ODFW 2009a). Nickelson (2003) found that 

reduced hatchery production led directly to higher survival of naturally produced fish. Ocean

survival, as measured by smolt to adult survival of OPI area hatchery fish, generally started 

improving for fish returning in 1999 (Table 4). In combination, these factors have resulted in the 

highest spawning escapements that have been seen since 1950, although total abundance before 

harvest peaked at the low end of what was observed in the 1970s (Figure 6).

Higher spawner abundance in recent years has resulted in higher scores for population

diversity, PD. Three of the population diversity factors are directly or indirectly related to 

abundance. The spawner abundance criterion is based on long-term harmonic mean abundance, 

so it will increase in periods of high abundance. Spawner distribution, PD-3, and juvenile 

distribution, PD-4, measure the distribution of coho salmon among watersheds within the 

populations. At higher spawner abundance, coho salmon tend to spread out through a greater 

area of habitat. This leads to a similar expansion of juvenile distribution. The criterion for 

evaluation of juvenile distribution was considered by some members of the BRT to be 

uninformative, so this criterion was given a lower weight in the BRT deliberations (but not in the 

computation of DSS results). In evaluating the DSS, both of the distribution criteria score higher 

during periods of high abundance unless all habitat is already occupied or unoccupied habitat is 
53

unsuitable or inaccessible. With minor exceptions, these scores increased from those in the TRT 

analysis, indicating that habitat was available for range expansions within most populations. 

Consequently, the peak in spawner abundance in the early 2000s, combined with the reduction in 

hatchery production, resulted in strong scores for population diversity (Table 8).

Factors for Decline and Threats

Introduction

The BRT utilized the results of the DSS and information on population abundance, 

growth rates (productivity), spatial structure, and diversity to inform its assessment of the current 

OCCS ESU biological status. Current information on harvest and hatcheries also was included. 

In addition, the BRT evaluated current and future threats to the ESU that may or may not be 

manifest in its current biological status. The BRT categorized these threats according to ESA 

Section 4(a)1:

• The present or threatened destruction, modification, or curtailment of its habitat or range;

• Overutilization for commercial, recreational, scientific, or educational purposes;

• Disease and predation; and

• Other natural or man-made factors affecting its continued existence.

To the degree possible, the BRT attempted to characterize threats whose effects are likely to 

already be reflected in the current biological status of the ESU and those that are likely to 

become manifest in the future.

As a starting point for reviewing threats, the BRT reviewed the factors for decline, which 

had been identified as part of the original ESA status review process for the ESU. For example, 

Table 11 lists freshwater habitat factors for decline that were identified in Oregon’s OCSRI 

(1997) and subsequently discussed in NMFS (1997c). Other factors for decline were identified 

during the 1996 status review.

In the next step toward not only understanding what affected the ESU in the past, but 

identifying what affects the ESU now and may affect it in the future, NWR (NMFS 1997a) listed

threats to the ESU as shown in Table 12. Threats were defined as:

human activities or natural events (e.g., road building, floodplain development, 

fish harvest, hatchery influences, volcanoes) that cause or contribute to limiting 

factors. Threats may exist in the present or be likely to occur in the future.

Limiting factors were defined as:

physical, biological, or chemical features (e.g., inadequate spawning habitat, high 

water temperature, insufficient prey resources) experienced by the fish at the 

population, intermediate (e.g., stratum or major population grouping), or ESU 

levels that result in reductions in VSP parameters (abundance, productivity, 

spatial structure, and diversity). Key limiting factors are those with the greatest 

impacts on a population’s ability to reach its desired status (NMFS 1997a).
54

Table 11. Factors for decline and habitat limiting factors for OCCS (NMFS 1997c).

Modification or 

curtailment of range Harvest

Disease and 

predation

Regulatory 

mechanisms

Other natural or 

man-made factors

Fish passage (hydro, 

tide gates, culverts)

Marine Disease NW Forest Plan Droughts

Water withdrawal Recreational Predation Forest practices Floods

Land use and 

management

Dredge and fill Ocean conditions

Logging

Agricultural 

activities

Estuary loss

Wetland loss

Riparian area/ 

quality loss

Channel 

complexity loss

Floodplain 

connectivity loss

Splash dams/

log drives

Gravel/placer 

mining

Forest and ag 

conversion to urban

Urbanization

Ag practices 

(sedimentation, 

temperature)

Logging practices 

(sedimentation, 

temperature)

Urban growth

Artificial propagation

Table 12. Threats to OCCS ESU identified by NMFS NWR (NMFS 1997c).

Human threats Natural threats

Agriculture:

Instream wood, water temperature, substrate sediment

Drought 

Forestry and private lands:

Instream wood, water temperature, substrate sediment

Floods

Gravel mining:

Particular concern on the southern Oregon Coast where the Umpqua 

and Coquille River basins have significant sediment deficits

Wildfire

Water withdrawals or diversions:

Current concern on the southern Oregon coast; future concern on 

mid-coast as urban areas grow

Drought interaction

Tsunami

Urbanization:

Floodplain functions, instream wood, substrate sediment, storm water
55

Because the list of threats has changed over the years, Table 13 compares the list of 

threats and limiting factors between those identified in 2003 (Good et al. 2005) and those 

considered by the BRT in this review. The BRT considered these factors for decline, limiting 

factors, and threats that had been previously identified, then reviewed additional information that 

has become available since 1997. The BRT utilized a threats matrix (see Appendix A, Table A1) to summarize the major human and natural threats facing the OCCS ESU at this time and in 

the future.

Table 13. Threats to OCCS ESU identified by NMFS NWR (NMFS 1997c) and the 2009/2010 BRT.

Threats previously identified by NWR Threats identified by BRT 2009/2010

Agriculture and forestry Agriculture and forestry

Instream wood Stream complexity (includes disturbance, 

roads, splash damming, stream cleaning)

Water temperature Water temperature

Substrate sediment Substrate sediment analyzed in stream 

complexity section

Estuary and wetland habitat loss not identified as a 

major threat

Estuaryand wetland habitat loss, due to 

effect on life history diversity and numbers

Beaver dam loss not identified as a major threat Beaver dam loss analyzed in stream 

complexity section

Fish passage restriction not identified as a major threat Fish passage restriction

Gravel mining:

Umpqua River and Coquille River basins

Gravel mining:

Umpqua River, Coquille River, and 

Tillamook River basins

Water withdrawals or diversions:

Mid-South Coast, Umpqua strata

Drought interaction

Water withdrawals or diversions:

Mid-South Coast, Umpqua strata

Drought interaction

Global climate change

Urbanization Land use conversion, urbanization

Floodplain functions Floodplain functions 

Instream wood Instream wood addressed in stream 

complexity analysis

Substrate sediment Substrate sediment addressed in stream 

complexity analysis

Storm water Storm water

Disease and parasites not identified as a major threat Disease and parasites

Artificial propagation Artificial propagation

Harvest Harvest

Predation not identified as a major threat Predation

Global climate change not identified as a major threat Global climate change

Marine productivity not identified as a major threat by 

NWR, was identified by 2003 BRT

Marine productivity

Drought, floods, and wildfire Drought, floods, and wildfire addressed under 

global climate change

Tsunami Tsunami not addressed

NIS not previously identified NIS introductions: ecosystem impacts of NIS, 

effects of NIS fish, and effects of NIS plants 

on stream complexity establishment not 

identified as a threat
56

Other Natural and Man-made Factors

This portion of the BRT review started with the discussion of other natural and manmade factors for decline. These include the effects of ocean conditions and marine productivity,

which have been recognized as significant issues for the OCCS ESU since the 1993 status review 

(Weitkamp et al. 1995), and the effects of global climate change on freshwater and marine 

habitats.

Past ocean conditions and marine productivity

Evidence has accumulated to demonstrate 1) recurring, decadal-scale patterns of ocean

and atmosphere climate variability in the North Pacific Ocean (Mantua et al. 1997, Zhang et al. 

1997, Overland et al. 2009, Schwing et al. 2009), and 2) correlations between these oceanic 

changes and salmon population abundance in the Pacific Northwest and Alaska (Hare et al. 1999, 

Mueter et al. 2002, Francis and Mantua 2003, Lawson et al. 2004). There seems to be little 

doubt that survival rates in the marine environment can be strong determinants of population 

abundance for Pacific salmon and steelhead. It is also generally accepted that for at least two 

decades, beginning about 1977, marine productivity conditions were unfavorable for the majority 

of salmon and steelhead populations in the Pacific Northwest (in contrast, many populations in 

Alaska attained record abundances during this period). Good et al. (2005) cited evidence that an 

important shift in ocean and atmosphere conditions occurred around 1998 that was expected to 

persist for several years. However, that change has not persisted.

One indicator of the ocean-atmosphere variation for the North Pacific is the Pacific 

Decadal Oscillation (PDO) index. Since 1900 the PDO has shown a number of multidecade 

periods of predominantly positive (1926−1947, 1977−1998) or negative (1948−1976) values 

(Figure 13), which correspond roughly to periods of low (positive PDO) or high (negative PDO) 

West Coast salmon returns (Mantua et al. 1997). There was a sharp transition to negative values 

in 1999, followed closely by a positive transition in 2003 and a negative transition in 2007. 

Negative PDO values are associated with relatively cool ocean temperatures (and generally high 

salmon productivity) off the Pacific Northwest, and positive values are associated with warmer, 

less productive conditions. Wide fluctuations in many salmon populations in recent years may 

be largely a result of these shifts in ocean conditions.

Although these climate-related facts are relatively well established, much less certainty 

can be attached to predictions about what this means for the viability of listed salmon and 

steelhead. For several reasons, considerable caution is needed to project into the future. First, 

empirical evidence for cycles in PDO, marine productivity, and salmon abundance extends back 

only about a century, or about three periods of two to four decades in duration. These periods 

form a very short data record for inferring future behavior of a complex system. Thus as with 

the stock market, the past record is no guarantee of future performance. Second, the past decade 

has seen particularly wide fluctuations not only in climatic indices (e.g., the 1997–1998 El Niño 

was in many ways the most extreme ever recorded, and the 2000 drought was one of the most 

severe on record) but also in abundance of salmon populations. In general, as the magnitude of 

climate fluctuations increases, population extinction risk also increases. Third, as 

anthropogenically caused global climate change occurs in the future, it will affect ocean 

productivity and likely change the dynamics of ocean variation as well as ecosystem processes 
57

Figure 13. The PDO index from 1900 through 2009. Values shown are standardized deviations from the 

long-term (1900–1993) mean. Data from University of Washington (http://jisao.washington.edu

/pdo/PDO.latest).

(Overland et al. 2009). Finally, changes in the pattern of ocean/atmosphere interactions do not 

affect all species (or even all populations of a given species) in the same way (Peterman et al. 

1998).

Ocean ecosystem conditions

As ocean temperatures warm, empirical and theoretical studies show that marine fish and 

invertebrates tend to shift their distributions towards higher latitudes and deeper water at 

observed and projected rates of 30 to 130 km/decade towards the pole and 3.5 m/decade to 

deeper waters (Cheung et al. 2009). Although this change may occur gradually, anomalously 

warm conditions may allow temporary range expansions. For example, during the 1997−1998 El 

Niño, warm water fishes invaded Oregon waters, including striped marlin (Tetrapturus audux), 

Dorado (Coryphaena hippurus), and Pacific barracuda (Sphyraena argentea) (Pearcy 2002). In 

Alaska the summers of 2004 and 2005 were unusually warm and southern fish species including 

thresher shark (Alopias vulpinus), blue shark (Prionace glauca), opah (Lampris guttatus), and 

large numbers of Pacific sardines (Sardinops sagax) were recorded, often extending the northern 

limit of the species’ known ranges (Wing 2006).

One species that is actively undergoing a substantial range expansion is the Humboldt or

jumbo squid (Dosidicus gigas) (Field et al. 2007, Zeidberg and Robison 2007). Like most 

squids, Humboldt squid are ecological opportunists with a short life span (typically <2 years) and 

high fecundity, allowing their abundances to fluctuate greatly on short time scales; they have 
58

been likened to locusts of the marine realm, reaching plague proportions and creating famine 

(Rodhouse 2001). Even among squid species, Humboldt squid stand out; they have the highest 

growth rates (Mejia-Rebollo et al. 2008) and fecundity (up to 13 million eggs per female, Keyl et 

al. 2008) of any squid, are tolerant of water of a wide range of temperatures and oxygen levels, 

including water typically considered hypoxic (Gilly et al. 2006, Zeidberg and Robison 2007), 

and can move horizontally nearly 200 km in a week (Gilly et al. 2006). Humboldt squid 

typically make diel migrations between surface waters at night and depths in excess of 250 m 

during the day, although large numbers of squid have been observed at the surface during the 

day, indicating considerable plasticity in their behavior (Olson et al. 2006).

The normal range of Humboldt squid is the eastern tropical Pacific Ocean, extending as

far north as southern California (≈30°N, Keyl et al. 2008), although they have been sporadically 

reported off the California coast throughout the last century (Field et al. 2007). In their current 

range expansion, they were first reported north of their normal distribution during the 1997 El 

Niño when they were observed in Monterey Bay (Zeidberg and Robison 2007) and off Oregon 

(Pearcy 2002). Reports of squid north of their typical range resumed in 2000 (Zeidberg and 

Robison 2007, Keyl et al. 2008) and Humboldt squid were reported from British Columbia and 

Alaska in 2004 (Cosgrove 2005) and again in Alaska in 2005 (Wing 2006).

Numerous long-term coastal sampling programs provide excellent documentation of this 

dramatic spread, in particular the apparent explosion of squid during summer 2009. For 

example, the joint U.S.-Canada Pacific hake (Merluccius productus) acoustic-trawl survey has 

documented a rapid increase in the number and frequency of Humboldt squid caught in trawls 

since the survey began in 1977 (Holmes et al. 2008). The first confirmed catch occurred in 2003 

and, by the 2007 survey, the range and abundance of squid had greatly expanded (Holmes et al. 

2008). In the 2009 survey, catches of Humboldt squid were extremely large and frequent: 44% 

of hauls in 2009 included at least one Humboldt squid.11 Similarly, the NWFSC Predator 

(Emmett et al. 2006) and Stock Assessment Improvement Program (Auth 2008) research cruises, 

both of which sample with large trawls (mouth ≈25 m wide x 20 m deep) at night, first caught 

Humboldt squid in 2006 and 2004, respectively. In summer 2009, these studies caught 

Humboldt squid in 14% (n = 84 hauls) and 19% (n = 85) of their hauls, respectively, with the 

highest catches in late summer.12

A recent analysis of factors contributing to the collapse of Sacramento fall Chinook 

salmon includes one section on Humboldt squid (Lindley et al. 2009). The authors conclude that 

Humboldt squid likely had limited impact on Sacramento Chinook salmon due to limited spatial 

overlap; most squid were beyond the continental shelf while most juvenile salmon were on the 

shelf. However, in 2005 and 2009 squid were caught off the Washington and Oregon coasts by 

research programs targeting juvenile salmon, suggesting overlap of squid and juvenile salmon 

within the range of OCCS.

Humboldt squid are a “voracious, opportunistic predator” (Gilly and Markaida 2007), 

capable of feeding on a wide range of prey. Prey items identified in squid stomachs collected off 

the coasts of California and Oregon included commercial (e.g., Pacific hake, northern anchovy 

 11 D. Chu, NWFSC, Seattle, WA. Pers. commun., November 2009. 12 R. Emmett, NWFSC, Newport Research Station, Newport, OR. Pers. commun., December 2009.
59

[Engraulis mordax], Pacific sardine, rockfishes [Sebastes spp.], and flatfishes 

[Pleuronectiformes]) and noncommercial (e.g., northern [Stenobrachius leucopsarus] and blue 

[Tarletonbeania crenularis] lantern fishes) fish species (Field et al. 2006), with perhaps the 

biggest impact on hake populations (Holmes et al. 2008). Fishes found in squid stomachs were 

up to 42 cm in length, with greater than 10% of the total biomass ingested consisting of prey at 

least 35 cm in length. Squid have also been observed attacking larger fish (up to 50 cm) when 

the prey are confined, such as skipjack (Katsuwonus pelamis) and yellowfin (Thunnus albacares) 

tunas caught together with squid in purse seines (Olson et al. 2006). A Chinook salmon jack 

(262 mm fork length) was caught in the lower Columbia River estuary in October 2009 with 

what appeared to be a squid bite mark,13 indicating that squid may attempt to take small salmon.

For OCCS, the timing of Humboldt squid presence in our area is of particular concern,

because squid abundances typically peak during late summer (August, September) and are 

considerably lower in early summer (June, July) (Field et al. 2007, Gilly and Markaida 2007, 

Litz et al. 2011). The best predictor of Columbia River coho year-class success is the number of 

juveniles caught off the Washington and Oregon coasts in September of the previous year (Van 

Doornik et al. 2007, Wainwright and Weitkamp in prep.). This relationship indicates that the 

individuals that reside in local waters throughout the summer are the ones that return as adults. 

Unfortunately, these individuals will likely overlap with the highest abundances of Humboldt 

squid and therefore face high predation risk. By contrast, spring Chinook salmon originating 

from Pacific Northwest streams are present in local waters in early summer, then move 

northwards towards Alaska by mid-summer (Trudel et al. 2009). Because of their migratory 

patterns, these fish will likely experience much lower habitat overlap with Humboldt squid 

unless squid densities are also high farther north.

It is not clear whether this most recent population explosion is long lasting or transient, 

why it has occurred, or whether it includes a northern expansion of squid spawning areas 

(currently Gulf of California, the Costa Rica Dome, Gilly and Markaida 2007). No direct data or 

information indicated that the presence of Humboldt squid will lead to reduced abundance of 

OCCS, although the BRT was concerned that squid may potentially be a risk to the salmon or the 

ecosystem on which they depend. Overall, the BRT concluded that the presence of this warm 

water species off the Oregon coast and further north beyond its previously known range is a sign 

that the coastal ocean ecosystem on which coho salmon depend is in an unpredictable state of 

flux.14

Effects of climate change on the OCCS ESU

Recent climate change has had widespread ecological effects across the globe, including 

changes in phenology, changes in trophic interactions, range shifts (both in latitude and elevation 

and depth), extinctions, and genetic adaptations (reviewed by Parmesan 2006) and these changes 

have influenced salmon populations (ISAB 2007, Crozier et al. 2008a, Mantua et al. 2009). 

Although these changes have undoubtedly influenced the observed VSP attributes for the OCCS 

ESU, we cannot partition past climate effects from other factors influencing the status of the 

ESU. Continuing climate change poses a threat to aquatic ecosystems (Poff et al. 2002) and 

 13 Reported by BRT member L. Weitkamp, December 2009. 14 By 2011 Humboldt squid had nearly disappeared from Oregon waters.
60

more locally to Pacific salmon (Mote et al. 2003). Recently, Wainwright and Weitkamp (in 

prep.) reviewed the major potential physical effects of climate change in western Oregon, 

presented an approach to integrating these effects across life history stages, and applied that 

approach to evaluate potential effects on the OCCS ESU. Here we summarize their findings.

The coho salmon life cycle extends across three main habitat types: freshwater rivers and 

lakes, estuaries, and marine environments. In addition, terrestrial forest habitats are also 

essential to coho salmon because they determine the quality of freshwater habitats by influencing 

the types of sediments in spawning habitats and the abundance and structure of pools in juvenile 

rearing habitats (Cederholm and Reid 1987). Wainwright and Weitkamp (in prep.) begin by 

considering these four habitats, how physical climate change is expected to affect them over the 

next 50 years, and how salmon will respond to those effects during specific life history stages 

(Figure 14). Climate conditions have effects on each of these habitats, thus affecting different 

portions of the life cycle through different pathways. This leads to a very complex set of 

potential effects to assess.

Wainwright and Weitkamp (in prep.) recognized that, while we have quantitative 

estimates of likely trends for some of the physical climate changes, we do not have sufficient 

understanding of the biological response to these changes to reliably quantify the effects on 

salmon populations and extinction risk. For this reason, the analysis is qualitative: summarizing 

likely trends in climate, identifying the pathways by which those trends are likely to affect 

salmon, and assessing the likely direction and rough magnitude of coho salmon population 

response. Their assessment is summarized in Table 14 and discussed below.

Figure 14. Conceptual diagram of multiple pathways by which climate influences the salmon life cycle. 

The climate system affects four habitats (terrestrial, freshwater, coastal ocean, and estuary) vital 

to salmon life stages, which in turn influence salmon reproduction, growth, and mortality. 

(Printed from Wainwright and Weitkamp in prep.)
61

Table 14. Summary of effects of physical climate changes on OCCS by habitat type. Strength and 

direction of effects are rated from strongly positive (+ +) through neutral (0) to strongly negative 

(– –). (Modified from Wainwright and Weitkamp in prep.)

Physical change

Certainty 

of change Processes affecting salmon

Effect on 

salmon

Certainty 

of effect

Terrestrial

Warmer, drier 

summers

High Increased number and intensity of fires, increased 

tree stress and disease affect large woody debris, 

sediment supplies, riparian zone structure

0 to – – Low

Reduced 

snowpack

High Increased growth of higher elevation forests 

affect large woody debris, sediment, riparian 

zone structure

+ to 0 Low

Freshwater

Reduced summer 

flow

High Less accessible summer rearing habitat – Moderate

Earlier peak flow High* Potential migration timing mismatch 0 to –

Umpqua:

0 to – –

Moderate

Increased floods Moderate* Redd disruption, juvenile displacement, 

upstream migration

0 to –

Umpqua:

– to – –

Moderate

Higher summer 

stream 

temperature

Moderate Thermal stress, restricted habitat availability, 

increased susceptibility to disease and parasites

– to – – Moderate

Estuarine

Higher sea level High Reduced availability of wetland habitats – to – – High

Higher water 

temperature

High Thermal stress, increased susceptibility to 

disease and parasites

– to – – Moderate

Combined effects Changing estuarine ecosystem composition and 

structure

+ to – – Low

Ocean

Higher ocean 

temperature

High Thermal stress, shifts in migration, range shifts, 

susceptibility to disease and parasites

– to – – Moderate

Intensified 

upwelling

Moderate Increased nutrients (food supply), coastal 

cooling, ecosystem shifts; increased offshore 

transport

+ + to 0 Low

Delayed spring 

transition

Low Food timing mismatch with outmigrants, 

ecosystem shifts

0 to – Low

Intensified 

stratification

Moderate Reduced upwelling and mixing lead to reduced 

coastal production and reduced food supply

0 to – – Low

Increased acidity High Disruption of food supply, ecosystem shifts – to – – Moderate

Combined effects Changing composition and structure of 

ecosystem, changing food supply and predation

+ to – – Low

*Effects are strongest and most certain in higher elevation snow-fed basins.
62

The impacts of change in terrestrial forest habitats on salmon are indirect through effects 

on hydrology, water quality, and physical habitat structure. While there is widespread agreement 

on the atmospheric changes likely to affect forests (warmer, drier summers and reduced 

snowpack), the effects of resulting changes in forests are uncertain. Also, the subsequent effects 

on salmon are of low certainty and could range from slightly positive to strongly negative.

For freshwater habitats, climate change is expected to reduce summer flows and raise

summer stream temperatures throughout western Oregon. These trends would reduce the 

amount of available summer rearing habitat for coho salmon and increase thermal stress, which 

would result in reduced growth and increased susceptibility to disease and parasites, and thus 

have a weak to strong negative effect on freshwater salmon production. Furthermore, increased 

water temperature will necessarily increase the consumptive demands of juvenile coho and their 

predators (Petersen and Kitchell 2001). It remains to be seen how the food web as a whole will 

respond to these changes in energetics. In addition, reduced winter and spring snowpack is 

expected to result in earlier peak flows and increased flooding in snow-fed rivers. For this ESU, 

changes in snowpack are likely to have a significant effect on salmon only in the lower main

stem and upper portions of the Umpqua River basin (north and south Umpqua populations); the 

effect would be negative for those populations.

In estuaries, the main expected physical changes are rising sea level and warmer water 

temperatures. The effect of these changes on salmon is likely to be negative, due to losses of 

intertidal wetland habitats and increased thermal stress during migrations. As in freshwater, 

increased water temperature will increase the metabolic demand of coho salmon and their 

predators (Petersen and Kitchell 2001). Changing temperatures may also lead to unpredictable 

changes in estuarine community composition, which might have either positive or negative 

effects on salmon.

In the ocean, a number of anticipated physical changes could affect OCCS. These 

include higher water temperature, intensified upwelling, delayed spring transition, intensified 

stratification, and increasing acidity in coastal waters. Of these, only intensified upwelling 

would be expected to benefit coastal-rearing salmon; all the other effects would likely be 

negative. Increasing temperature and acidity have a high certainty of occurring and both would 

likely have negative effects on coho salmon. As with freshwater and estuarine ecosystems, 

increased water temperature will also lead to increased metabolic demand for coho salmon and 

their predators (Petersen and Kitchell 2001). However, the local physical interactions of wind 

patterns and stratification on upwelling and the timing of the spring transition for our coast are 

difficult to predict with certainty, so the response of salmon to these other ocean factors is of low 

certainty. In combination, all of these physical effects are likely to result in changes in the 

species composition and structure of the coastal ecosystem, with unpredictable consequences for 

coho salmon.

While we have noted some expected positive effects, negative effects of climate change 

predominate for each habitat and life history stage (Table 14). While many of the individual 

effects of climate change on OCCS are expected to be weak or are uncertain, we need to consider 

the cumulative impacts across the coho salmon life cycle and across multiple generations. 

Because these effects are multiplicative across the life cycle and across generations, small effects 

at individual life stages can result in large changes in the overall dynamics of populations. This 
63

means the mostly negative effects predicted for individual life history stages will most likely 

result in a substantially negative overall effect of climate change on OCCS over the next few 

decades. Despite large uncertainties surrounding specific effects at individual life stages, 

expectations for increasing air and water temperatures, drier summers, higher incidence of 

flooding, and altered estuarine and marine habitats lead us to expect increasingly frequent years 

with low survival, resulting in an overall increase in risk to the ESU from climate change over 

the next 50 years.

Ecosystem impacts of nonindigenous species

OCCS and other salmonids traverse large geographic areas from freshwater to estuarine 

and ocean habitats during their life cycle. During this time, they encounter numerous 

nonindigenous species (NIS) (Sanderson et al. 2009). Boersma et al. (2006) verified many 

invertebrate and plant species introduced into the Pacific Northwest (and more specifically the 

OCCS ESU) that have documented effects. In the OCCS ESU, the majority of NIS are plants 

and fishes. The mechanisms of impact by these NIS are predation, competition, hybridization, 

infection (disease and parasites), and habitat alteration (Mack et al. 2000, Simberloff et al. 2005).

The presence of NIS fishes poses one of the greatest threats to the persistence of healthy 

native fish populations (Rahel 2002). Sanderson et al. (2009) report high to moderate densities 

of NIS fishes in the ESU. Effects of these fishes include predation by channel catfish (Ictalurus 

punctatus), American shad (Alosa sapidissima), brook trout (Salvelinus fontinalis), smallmouth 

bass (Micropterus dolomieu), and largemouth bass (Micropterus salmoides). Other NIS fishes 

alter habitats and ecosystem function. For example, NIS warmwater fishes in Tenmile Lakes 

alter planktonic community structure. This affects the summer rearing and residency of OCCS 

juveniles (ODEQ 2007). Additional discussion of NIS fishes is found in the Predation 

subsection.

Plant and animal NIS invade and displace native plant species and communities when 

human disturbance such as timber harvest (USFS 2005) or climate change (Wainwright and 

Weitkamp in prep.) occurs. Brazilian elodea (Egeria densa), eurasian water milfoil 

(Myriophyllum spicatum), reed canary grass (Phalaris arundinacea), giant and Japanese 

knotweed (Polygonum spp.) [reed canary grass and giant knotweed effects are discussed in the 

Stream Complexity subsection], cordgrasses (Spartina anglica, S. densiflora, and S. patens), 

Japanese eelgrass (Zostera japonica), evergreen and Himalayan blackberry (Rubus laciniatus, R. 

armeniacus), purple loosestrife (Lythrum salicaria), and New Zealand mudsnail (Potomopygyrus 

antipodarum) are already found in the ESU (Boersma et al. 2006). These plants and 

invertebrates alter habitats and ecosystem function. For example, purple loosestrife displaces 

sedges and cattails (Typha spp.). This causes shifts in local nutrient availability and affects 

detrital foodwebs (Blossey et al. 2001). New Zealand mudsnails blanket streambeds, can 

consume a majority of gross primary production, and outcompete other macroinvertebrates such 

as larval mayflies, stoneflies, and caddis flies, which are important freshwater salmon prey (Hall 

et al. 2003, Kerans et al. 2005).

Potential new invasions that have been identified include zebra mussel (Dreissena 

polymorpha), Chinese mitten crab (Eriocheir sinensis), and hydrilla (Hydrilla verticillata). A 

list of potential invasive species is identified in the Oregon Conservation Strategy’s discussion of 
64

the Coast Range Ecoregion (ODFW 2011) and in USFS (2005) Invasive Plant Program 

documents. Some of these have already caused significant damage to aquatic and terrestrial 

ecosystems in other parts of the United States. Of present concern, however, is the collapse of a 

major food source of OCCS in some estuaries. During outmigration of OCCS smolts in the MidCoast stratum, one of their major food sources is mudshrimp (Upogebia pugettensis). These 

intertidal benthic invertebrates are among the most dramatically affected by recent introduced 

species invasions and associated hydrological and geochemical alterations of the estuaries 

(Dumbauld et al. 2010).

Some members of the BRT were concerned that invasions by NIS present a risk to the 

salmon or the ecosystem on which they depend. Though some NIS species already established 

in the ESU may be reflected in current biological status, invasions by NIS and the subsequent 

ecosystem changes brought about by their establishment may constitute a future threat to the 

species.

The Present or Threatened Destruction, Modification, or Curtailment of its Range

Fish passage

The foundation of ESU viability is built on the ability of populations to function in an 

integrated manner and persist across the landscape. This integration includes dispersal within 

and among populations (i.e., connectivity) and a diversity and distribution of habitat types and 

conditions that allow for the expression of a range of life history types (Williams and Reeves 

2003). Dams are not the only barrier to migration; barriers can include smaller scale features 

such as road culverts that block seasonal passage to and from mainstem rivers and also 

intertributary and intratributary movement.

Any habitat modification that prevents annual or seasonal movement across the landscape 

can affect coho salmon populations. Ebersole et al. (2006) described within-basin movement of 

juvenile coho salmon in a coastal Oregon basin (West Fork Smith River, Douglas County, 

Oregon). Although the focus of their work was on winter movement and overwinter use of 

tributaries, Ebersole et al. (2006) suggested that during wetter years, small tributaries could also 

provide improved summer survival and subsequently higher densities of juvenile salmonids prior 

to the overwinter period. Culverts, tide gates, and temperature blockages can affect access of 

juveniles to these small systems.

The BRT utilized the original factors for decline summarized by NMFS (1997a) in 1997 

as a starting point for its assessment. A discussion of fish passage was included in this 

assessment because it was part of the original factors for decline discussion and some members 

of the BRT felt that it may be an important source of risk to the OCCS ESU. Fish passage was 

not identified in the State of Oregon’s Oregon Coastal Coho Assessment (Oregon 2005) as either 

a primary or secondary limiting factor for any population of OCCS.

There are wholesale blockages of fish passage by hydropower projects, which is 

considered a major factor for decline in many salmonid ESUs. The effect of hydropower 
65

development in the ESU was reviewed in the Oregon Coast Coho Assessment (Oregon 2005).15 

Oregon’s conclusion was:

Generally, within the majority of the ESU, impacts from hydroelectric projects 

are insignificant or nonexistent. Specifically, within the Umpqua Basin, Oregon 

coastal coho have been prevented from reaching 36 miles of spawning and rearing 

habitat by hydroelectric projects. Impacts to downstream reaches include 

alteration of flows and interruption of natural sediment and large woody debris 

regimes (ODFW 2005e).

As discussed, fish passage problems are not just related to blockage by hydropower 

projects. As part of the Oregon Coastal Coho Assessment, Dent et al. (2005) gathered data on 

stream crossings from private industrial landowners (60% of data captured), federal (USFS 

100% of data captured) and state (90% of data captured) agencies, and data sets with a complete 

census of state and county roads (100% of data captured). Fish passage status was provided by 

the landowners and crossing status was not verified. These crossings were binned in three 

categories: high intrinsic potential for coho salmon, low intrinsic potential, and non-coho. Their 

results show that for the entire ESU, 11% of low intrinsic potential streams, 10% of high intrinsic 

potential streams (these are probably minimal estimates because ODF did not have complete 

coverage of intrinsic potential streams for this analysis16), and 16% of non-coho streams have 

limited access. They estimated that of all the stream miles with limited access, approximately 

18% were high intrinsic potential streams. The percent of stream crossings in high intrinsic 

potential areas are: 60% of the total number of stream crossings pass fish, 14% limit fish 

passage, and 26% are unknown. Dent et al. (2005) concluded:

Our analysis suggests that a relatively small percent of coho habitat remains 

inaccessible (10−11%) and that Oregon Plan fish passage restoration projects 

have improved access to 6−11% of coho habitat. However, our analysis also 

suggests that a significant proportion of the coho habitat has unknown access 

status (28−31%). With unknown access to approximately one-third of the habitat, 

fish passage cannot be eliminated as a risk to coho at this point in time.

As part of the review of the Oregon Coastal Coho Assessment, NMFS NWR commented

that fish passage through culverts, tide gates, and bridges presented a higher risk to OCCS than 

the Oregon (2005) assessment.

The technical document (Oregon 2005) concludes that nearly a third of the area 

has an unknown passage status, that fish passage restoration projects have not 

been tested at high flows, that fish passage projects have rarely been monitored to 

test whether they are actually passable, and that fish passage cannot be eliminated 

as a risk to coho at this point in time (NMFS 2005a).

Since 2005 a concerted effort was made to improve the fish passage barrier geographic 

information system (GIS) layer, which was released in late 2009 (Oregon Fish Passage Barrier 

Data Set [OFPBDS], ODFW 2009d). This layer includes bridges, cascades, culverts, dams, 

 15 Peer reviewer 2 (reference Appendix D) reports that future hydropower projects may occur in this ESU on the 

Siletz River at the old town site of Valsetz (Pacific 2009) 16 G. Reeves, USFS, Corvallis, OR. Pers. commun., February 2011.
66

debris jams, fords, natural falls, tide gates, and weirs. The OFPBDS data set, however, does not 

include dikes, levees, or berms. Barriers in the data set may have information on their 

passability to salmonids. This information may designate complete or partial blockage to fish 

passage, complete passability, or an unknown passage status. The data set comes mainly from 

ODFW, Oregon Department of Transportation, and BLM (2009). It does not include barrier data 

from ODF, Oregon Water Resources Department (OWRD), soil and water conservation districts, 

watershed councils, tribes, and other originators; so the barriers shown in Figure 15 do not 

include those from private timber or agricultural lands, which contain 81% of the high intrinsic 

potential habitat in the ESU (Burnett et al. 2007). In addition, it reflects only a handful of the 

tide gates in the ESU; a newly available data set (Mattison 2011) documents approximately 350 

tide gates, which we know from Bass (2010) are at least partial barriers to fish passage.

An aspect of fish passage that has been ignored until recently is the blockage of fish 

access to tidal stream, marsh, and swamp habitat by dikes and levees in estuarine and freshwater 

tidal areas. It is possible however, to utilize the presence of a tide gate as a proxy for blockage of 

habitat. Giannico and Sauder (2005) reviewed the effect of tide gates on migratory behavior of 

salmonids and found that tide gates had direct effects on salmonid movements through abrupt 

changes in salinity, elevated water velocities and turbulence, and a total physical barrier to fish 

passage during the time the gate is completely closed. Bass (2010) found that in Coos Bay, 

Oregon, tide gates have the potential to restrict movement of OCCS subyearlings and smolts 

when compared to a nongated channel. At a minimum, tide gates in the OCCS ESU act as 

partial barriers to fish passage and were, for the most part, previously unaccounted for in past 

analyses. Few tide gate locations are included in the 2009 OFPBDS, so are not shown in Figure 

15. A noncomprehensive database of tide gates in the OCCS ESU is now available (Mattison 

2011).

Fish passage barriers have not been identified as a major limiting factor for OCCS by 

ODFW, however, within the OCCS ESU, of barriers that are in the data set, nearly half (49%) 

are of unknown status. The incompleteness of the information in the 2009 OFPBDS and new 

information regarding the effect of tide gates on fish passage for OCCS led some members of the 

BRT to consider that, because information is unavailable on a large portion of important OCCS 

habitat (low gradient agricultural lands, low elevation private timber lands), and where 

information is available, 49% of crossings are of unknown status, fish passage may continue to 

be a significant information gap in identification of habitat problems in the ESU. In the absence 

of information regarding blockages due to dikes and levees from ODF, OWRD, soil and water 

conservation districts, watershed councils, and tribes, it is clear that there is a substantial 

uncertainty as to the true effect that fish passage barriers present to OCCS.

For the purposes of this risk assessment, the current biological status probably reflects, 

for the most part, the status of fish passage in the ESU. Improved passage status information in 

the database would allow a better assessment of the effect of fish passage on OCCS and therefore 

on the potential effects of any future increase in road building (culverts) or protection of low 

lying areas from higher flood elevations and sea level rise (tide gates). Future effects of fish 

passage barriers depend on the success of Oregon Plan programs to address fish passage 

problems, the anticipated effects of land use changes in the ESU, and the response to anticipated 

sea level rise.
67

Figure 15. Barriers to fish passage. The database does not include barrier data from the ODF, OWRD, 

soil and water conservation districts, watershed councils, tribes, and other originators. It also 

includes approximately 28 tide gates.
68

Water availability

In its discussion of water availability as a threat, the BRT noted that the State of Oregon 

in the Conservation Plan (Oregon 2007) identified water availability as a primary limiting factor 

for the Middle Umpqua and South Umpqua OCCS populations. The Mid-South Coast stratum 

was identified as an area where water availability and water withdrawal is a problem as well, but 

was not identified as a primary limiting factor (Oregon 2007). Instream water availability 

problems can present limitations to OCCS through several mechanisms. May and Lee (2004) 

found that juvenile coho salmon abundance in pools decreased by 59% during the summer, with 

significantly higher losses occurring in gravel-bed versus bedrock pools. This means that gravelbedded streams that have water withdrawals would likely have a higher potential impact on 

summer juvenile coho abundance than those in bedrock-dominated reaches. In addition, if 

connectivity is reduced due to the removal of water, then growth rates can be altered, which in 

turn has an effect on survivorship. For example, Kahler et al. (2001) found that juvenile coho 

salmon moved out of smaller and shallower habitat units, and fish that moved among habitat 

units grew faster than fish that remained in the same habitat unit (Kahler et al. 2001).

Ebersole et al. (2006) found that tributary streams that were naturally nearly dry in 

midsummer supported high densities of spawning coho salmon in the fall, and juveniles rearing 

there exhibited relatively high growth rates and emigrated as larger smolts. They also reported 

that improved winter growth and survival of juvenile coho salmon utilizing tributary habitats 

underscore the importance of maintaining connectivity between seasonal habitats and providing 

a diversity of sheltering and foraging opportunities, particularly where mainstem habitats have 

been simplified by human land uses.

What this means for water withdrawals is that where and when they occur in the 

landscape are critical to coho salmon. So water withdrawals that affect tributaries, particularly

those that are gravel bedded, are most sensitive to changes in flow. If future water withdrawals 

are concentrated in tributaries of main river systems and are in gravel-bedded systems, this could 

lead to a decline in the summer abundance and overall survivorship of coho smolts. Another less 

investigated aspect of water availability is the effect of surface erosion on surface runoff. If 

climate change contributes to an increase in flooding, this flooding is often accompanied by mass 

wasting. As small valleys fill with coarse alluvium from such mass wasting, this could result in 

less surface flow and more subsurface flow.17

For most subbasins in the Umpqua stratum, water withdrawal for irrigation is a major 

consumptive use and, during the summer months from August to October, there is no natural 

stream flow available for new water rights (PUR 2007) except in the lowermost reaches of the 

Umpqua River (INR 2005) main stem. At times in the South Umpqua population, the flow is 

below one cfs in systems as large as Days Creek due to other consumptive uses (PUR 2007). 

EPA has placed all of the subbasins in the South Umpqua on the 303(d) list for flow 

modification; the North Umpqua and lower Umpqua River are on the list as well (PUR 2007).

OWRD has initiated instream water rights and leasing to mitigate loss of instream flow. 

The Oregon Watershed Enhancement Board (OWEB) 2007−2009 Oregon Plan update (Oregon 

 17 Peer reviewer 7 (reference Appendix D). Pers. commun., September 2010.
69

2009b) reports that OWRD places a high priority on monitoring and protecting instream water 

rights statewide. Fifty-six percent of those streams regulated by OWRD during the 2007 water 

year were regulated on behalf of instream rights. Leases provide a mechanism for temporarily 

changing the type and place of use for a certificated water right to an instream use. The leased 

water remains in channel and benefits stream flows and aquatic species while leased and the 

instream use counts as use under the right for purposes of avoiding forfeiture (PUR 2007). 

However, the effectiveness of instream water rights protection does not provide certain instream 

flow for fish and wildlife because virtually all of these existing rights for instream flow have 

priority dates after 1955; they are fairly junior to other water rights in most basins and therefore 

do not often affect water deliveries (INR 2005).

In a landscape already significantly affected by instream water availability issues, 

increased demand (Kline et al. 2003), temperature rise, and the anticipated changes in 

precipitation patterns (see discussion of Effects of climate change on the OCCS ESU above)

could have substantial effects on the OCCS ESU. In the Umpqua River stratum, the South 

Umpqua and Middle Umpqua populations are the most likely to be significantly affected by 

global climate change and temperature rise due to their interior position on the landscape. The 

Middle and Lower Umpqua populations are also the most subject in the ESU to downstream 

flow effects from the anticipated shift from a snow melt hydrology to rain hydrology that will 

affect stream flow timing and temperature due to shifts in precipitation in the Cascades. They 

are also the most likely to be affected by increased demand due to population growth (Kline et al. 

2003).

Some water availability problems, such as the effect of summer rearing limitations 

experienced in the Umpqua River stratum, are probably already reflected to a large degree in the 

current biological status. However, future impacts to water availability from the effects of 

population growth, global climate change, or even shifts in shorter term climate variability are 

not reflected in current biological status and may constitute a future threat.

Land management—stream habitat complexity

Freshwater habitat complexity has been defined as the number of habitat units per length 

of stream (Quinn and Petersen, 1996), the number of pools per channel width (Montgomery et al. 

1995), and the amount of wood and other obstructions that control specific channel features such 

as the amount of instream cover juvenile salmonids have during specific times of the year (Quinn 

and Petersen 1996). Freshwater habitat complexity is identified as a key limiting factor to the 

recovery of OCCS by ODFW (OCSRI 1997, Anlauf et al. 2009). Stream complexity has been 

identified as a factor for decline since 1997 (NMFS 1997a, OCSRI 1997). The State of Oregon 

also specifically identified it as a primary limiting factor for the purposes of the Oregon Coastal 

Coho Conservation Plan (Oregon 2007). Table 15 shows which populations ODFW considers to 

be limited by stream complexity. Thirteen of the 21 independent populations are considered 

stream complexity limited. The BRT’s habitat subcommittee decided stream complexity was 

such an important component to any risk assessment of habitat that it would pursue analyses 

based on techniques and data sets utilized by ODFW.
70

Table 15. Primary and secondary limiting factors for independent populations in the OCCS ESU 

(Oregon 2005).

Population Primary limiting factor Secondary limiting factor 

Necanicum Stream complexity None identified

Nehalem Stream complexity Water quality

Tillamook Stream complexity Water quality

Nestucca Stream complexity None identified

Salmon Hatchery impacts Stream complexity

Siletz Stream complexity None identified

Yaquina Stream complexity Water quality

Beaver Spawning gravel Stream complexity

Alsea Stream complexity Water quality

Siuslaw Stream complexity Water quality

Lower Umpqua Stream complexity Water quality

Middle Umpqua Water quantity Stream complexity, water quality

North Umpqua Hatchery impacts Stream complexity

South Umpqua Water quantity Stream complexity, water quality

Siltcoos NIS Stream complexity, water quality

Tahkenitch NIS Stream complexity, water quality

Tenmile NIS Stream complexity, water quality

Coos Stream complexity Water quality

Coquille Stream complexity Water quality

Floras Stream complexity Water quality

Sixes Stream complexity Water quality

Legacy splash damming, log driving, and stream cleaning—From an historical view, 

the stream complexity narrative begins with activities associated with the impacts of timber 

harvest. Three that have been identified are splash damming, log driving, and stream cleaning.

Splash damming and log driving are no longer practiced on Oregon coastal streams and 

rivers, but were used extensively during the deforestation phase of timber harvest (Maser and 

Sedell 1994). Splash dams were used to hold back enough water so that the logs that had been 

harvested and yarded to the pool behind the dam would sluice down the stream channel carrying 

the logs. This practice was well documented by Benner (1992) in the Coquille Basin. Often 

before the release took place, the downstream channel would be cleared as much as possible of 

impediments. These included instream boulder fields and debris jams. Figure 16 shows sites 

identified by Maser and Sedell (1994) and Miller (2010) for splash dams and log drives in the 

OCCS ESU. Legacy effects from these activities are still affecting geomorphic processes and 

landscape and local scale stream complexity in the OCCS ESU (Montgomery et al. 2003). These 

activities have contributed to loss of wood or boulders that acted to hold back gravel in the 

channel, loss of large trees that act as key constituents of log jams, and incision of stream 

channels and loss of floodplain connectivity (Montgomery et al. 2003).

Another aspect to the simplification of the complexity of streams in the OCCS ESU is 

that of stream cleaning activities formerly practiced by ODFW. Information presented in the 

Elliott Forest Watershed Analysis (ODF 2003) presents a picture of the effect of stream cleaning 

in Oregon coastal streams.
71

Figure 16. Historic splash dam and log driving locations.
72

Damage caused to streams and rivers by early logging operations (splash dams, 

slash disposal in streams, log drives, etc.) often resulted in substantial logjams. In 

some cases, these jams could be a mile or more in length, and undoubtedly 

prevented or impeded anadromous fish passage. Largely as a result of these 

spectacular cases, in the 1930s the Oregon Game Commission began to require 

loggers to prevent woody debris from entering streams ....

While the early stream surveys often called for clearing debris, its removal was 

effected in two ways. First, the Oregon Game Commission employed a stream 

improvement crew that drove throughout the region identifying obstructions and 

contacting land managers about their removal. This program lasted for 20 years, 

from about 1956−1976, according to ODFW files. The second tactic was to 

include stream cleaning, and specifically logging debris removal, in timber sale 

contracts. It appears to have continued until at least the mid-1980s ....

Both kinds of stream cleaning were often done by running bulldozers up and 

down the stream (this technique also applied to log yarding from the 1950s into 

the 1970s). Notations ... often identified the number of Cat D6 or D8 hours 

required for each job (although this also included winching logs out of streams). 

Without a doubt, stream cleaning had a widespread impact on aquatic habitat and 

the effects are still seen today in the amounts and distribution of wood in stream 

channels.

ODFW ended this practice, but legacy effects from the loss of large amounts of wood in the 

stream system endure. It is not surprising, therefore, that despite the number of instream 

complexity projects undertaken by watershed councils, ODFW, USFS, BLM, and private 

landowners (OWEB 2009), according to ODFW (Anlauf et al. 2009), “All monitoring areas are 

low in key pieces of wood relative to reference conditions.”

Beavers in OCCS habitat—Beavers are an important species to proper watershed 

functioning in coastal Oregon streams. They are considered a keystone species (Naiman et al. 

1988) that provide significant coho salmon rearing habitat, primary productivity, nutrient 

retention/cycling, floodplain connectivity, and stream flow moderation (Reeves et al. 1989). 

Beavers and associated ponded habitats occur throughout the OCCS ESU and can be found from 

the headwaters to the estuarine environment. Found in estuarine and freshwater tidal marshes,

beavers can build dams in the upper portions of sloughs and provide physical habitat for juvenile 

coho (Miller and Sadro 2003). Beavers are well known for damming smaller, lower gradient 

(less than 3%) streams with unconfined valleys (valley widths greater than four channels widths) 

(Retzer et al. 1956, Suzuki and McComb 1998, Pollock et al. 2003) as well as the floodplains of 

larger river systems (Murphy and Koski 1989, Pess et al. 2005). The potential benefits of 

beavers and their associated habitats to juvenile coho salmon thus may be dependent on their 

location within the landscape.

Historically, beavers were abundant throughout North America, with estimates ranging 

between 55 million and 400 million (Seton 1929, Pollock et al. 2003). Their pelt and castoreum 

was considered of great value and they were overexploited for centuries (Rosell et al. 2005). To 

reverse the effects of this overexploitation, beavers were protected and in the 1920s 

reintroduction programs were initiated. Their U.S. population is currently estimated to be 6 to 12 
73

million (Naiman et al. 1986). While populations have increased, their abundance levels are

typically 3 to 10% of their historic levels and have been so for some time (Pollock et al. 2003).

Several lines of evidence point to the importance of beaver ponds and side channels as 

principal habitat features for coho salmon (e.g., Naiman et al. 2000, Pollock et al. 2003). When 

evaluating habitat for OCCS using HLFM version 7 (Nickelson 1998), reaches with beaver 

ponds have rearing capacities an order of magnitude higher than reaches without beaver ponds 

(Beechie et al. 1994). As Pollock et al. (2004) report:

Watershed-scale restoration activities designed to increase coho salmon 

production should emphasize the creation of pond and other slow-water 

environments; increasing beaver populations may be a simple and effective means 

of creating slow-water habitat.

The Pollock et al. (2004) study focused, for the most part, on sites in the Puget Sound 

Region; however, the BRT noted that areas where beaver pond density is highest typically have

the same physical characteristics regardless of the ecological region—lower gradient (less than 

2%), unconfined valley bottoms, in smaller watersheds (drainage areas typically less than 10 

km2

). Smaller, lowland, rain-dominated Puget Sound watersheds have the same basic physical 

and hydrological characteristics as the smaller Oregon coast watersheds, thus the relationships 

we see with respect to beaver pond densities in Puget Sound should also hold true for the Oregon 

coast.

Beavers have been recognized as important to OCCS recovery by the State of Oregon in 

the Oregon Plan (OCSRI 1997) and the Oregon Coast Coho Conservation Plan (Oregon 2007). 

Notably, the Fisheries Section of ODFW has long recognized the importance of beavers to 

recovery of OCCS (ODFW 2005h) and is actively working to stress their importance to other 

sections of their agency as well as other state agencies (ODFW 2009b).

The BRT discussed the importance of beavers to coho salmon on the landscape and 

considered whether there have been changes that would lead BRT members to consider what loss 

of beavers would be expected over the next few decades. Two studies were discussed in regard 

to the present and future status of beavers in the OCCS ESU.

The first was a MidCoast Watersheds Council study (MCWC 2010), which attempts to 

address anecdotal evidence for major declines in large winter-persistent beaver ponds over the 

past 2−3 decades. In order to examine the issue, the MidCoast Watersheds Council engaged in a 

study to quantify trends, not on beaver populations, but the presence and habitat metrics of 

beaver dams and ponds. This study covered streams in the Upper Five Rivers (Alsea River), 

Tillamook Basin, Upper Yaquina River, and the rest of the Yaquina Basin. The results show that 

the Mid-Coast region included in the study has experienced widespread declines in numbers of 

beaver dams and ponds. Currently, the majority of dams are low and ponds are small and 

ephemeral. Only 5 of 40 streams surveyed in the Yaquina survey had healthy reaches of beaver 

habitat, with large, stair-stepped ponds. All five of these streams have difficult public access, 

with gated roads or no roads.

Another study was pursued in the Tillamook population (Biosurveys 2009); the entire 

basin was snorkeled with 320 miles of stream, from head of tide to end of coho salmon 
74

distribution in five river basins: Tillamook, Trask, Wilson, Kilchis, and Miami, plus small 

tributaries (tribs) entering the bay directly. These surveys also recorded beaver dams. The same 

360 miles snorkeled in 2006 was repeated in 2007. The beaver dam summary was as follows.

Year Tillamook Trask Wilson Kilchis Miami Bay tribs Total

2006 99 16 7 0 9 5 136

2007 70 23 13 0 7 0 113

The interannual comparison shows a decline in beaver ponds, most importantly in the Tillamook 

River. The Tillamook River has the proper morphology for extensive beaver colonization and a 

historical legacy of their presence (Coulton et al. 1996) in many reaches where they are currently 

absent. Because of limited stream morphology, the remaining Tillamook Basin rivers (Wilson, 

Kilchis, Miami, and Trask) have limited potential for broad colonization of beaver except for the 

Devils Lake Fork of the Wilson River. As expected, most beaver activity was found in the low 

stream gradients and sedimentary geologies. No active beaver dams were found in the Kilchis 

Basin, which is generally high gradient or highly disturbed.

In the past, ODFW has been able to track the harvest of beaver populations because all 

trapping required a permit and a harvest report. However, because of a change in the application 

of state regulations, no permit or harvest report is presently needed for trapping of nuisance 

animals on private land, making assessment of beaver harvest difficult (ODFW 2005h). As of 

2005, an analysis of the data collected in aquatic habitat surveys showed no significant trend in 

beaver dams in the entire ESU from 1998 to 2003 (ODFW 2005h). Some monitoring areas such 

as the Umpqua River showed a very low percent of habitat that contains beaver pools.

Based on these limited sources of information, the BRT concluded that there is some 

evidence for continued concern in regard to beaver abundance, but of very uncertain extent or 

scope. Due to the limited data set, we cannot conclude that there is an overall trend and would 

recommend a more extensive monitoring effort be pursued to identify short-term and long-term 

trends throughout the OCCS ESU. If beaver abundance has in fact declined or does not trend 

upward in the form of beaver dam density throughout the ESU, the BRT would consider this to 

be a significant threat to the availability of high quality habitat for OCCS.

The BRT had no information on beaver population trends over time in the ESU, therefore 

the habitat subcommittee examined the ODFW stream monitoring habitat data for the Oregon 

coast to gain a better understanding of the overall trends in beaver dam density in the different 

strata from 1998 to 2009. The habitat subcommittee found that the densities of beaver dams in 

the surveyed streams for each stratum averaged less than 1 (0.53 dams/km ±0.33) beaver dam 

per kilometer, with the exception of the North Coast stratum (1.31 ±1.4) (Figure 17). The trend 

in beaver dam density over this time period is flat (Figure 17). In addition, the density of beaver 

dams throughout this time period is considerably less than what typically occurs in protected or 

remote areas throughout North America (Pollock et al. 2003).

There are also some stratum-specific trends that relate to overall habitat condition. For 

example, the occurrence of beaver dams in the Umpqua stratum was 36% of those streams 

surveyed between 1998 and 2009, while the occurrence level was 82% for all other strata with 

the exception of the Lakes stratum (18%). Thus not only were beaver dam densities the lowest 

(0.09 dams/km ±0.16) in the Umpqua of any strata, they typically were nonexistent in many of 
75

0

1

2

3

4

5

6

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Dams per kilometer

Year

Lakes

Mid-Coast

Mid-South Coast

North Coast

Umpqua

Figure 17. Beaver dam density in the OCCS ESU from 1998 to 2009. Data from Anlauf et al. 2011.

the streams surveyed. Possible causes for the consistently low numbers of beaver dams across 

the ESU could be natural population fluctuations, forest succession, disease (tularemia), 

trapping, increased cougar predation, reduced food supply, reduced supply of building materials,

or a combination of all.

Pollock et al. (2003) summarized beaver dam density from pristine, remote, and protected 

areas in the North America and found the average to be 24.9 dams/km (±21.9). A low level of 

beaver dam density is typically correlated with lower abundance levels of beavers (Pollock et al. 

2003). Managed and recovering beaver dam density typically ranges between 2 and 6 dams/km 

and an average of approximately 3 dams/km (Pollock et al. 2004). Assuming habitat preference, 

that is, the types of stream characteristics that beavers prefer (less than 4% stream channel 

gradient, unconfined valleys [greater than 4 channel widths] [Suzuki and McComb 1998, Pollock 

et al. 2004]), then the density of beaver ponds will vary as a function of the number of beaver 

colonies and beavers in those areas.

Because the number of empirical studies that assess beaver abundance on the Oregon 

coast is limited, a brief analysis was pursued based on the published literature. Pollock et al. 

(2003) identified that remote or protected beaver populations (i.e., where no trapping is occurring 

and they are either protected with regulations or due to their remoteness) have a density that 

ranges from 0.4 to 0.9 colonies/km2

, while recovering or managed populations have a range from

0.1 to 0.4 colonies/km2. The number of beavers per colony ranges from 4 to 8 (Jenkins 1979, 

Pollock et al. 2007). This means the range of the number of beavers is 1.6 to 6.4 per km2. 

Assuming a watershed size of 500 km2, then the estimate for a beaver population in a pristine or 

protected area would be between 800 and 3,200 beavers, while in a managed or recovering area 

the same watershed would be between 200 and 1,600. Pollock et al. (2004) estimated the 

number of beavers in a pristine environment in a west Cascade watershed at 236 to 473 colonies 

and a population estimate that ranged from 946 to 3,782 beavers in any given year.
76

As of 2004, nuisance beavers may be removed by landowners or their agents without 

permits from ODFW (ODFW 2009b), and trapping is open in its entirety in all the coastal 

counties, including BLM and USFS lands, with the exception of Curry County (ODFW 2008a). 

The regulations state the following regarding the Coast Range:

Attention Coastal Beaver Trappers. ODFW requests your continued cooperation 

in protecting beaver dams in coastal areas important to coho salmon rearing. If 

you are not familiar with this program, which was initiated in 1998, please contact 

your local ODFW biologist (ODFW Furbearer Regulations 2008b, page 2).

Thus while trapping is not promoted and beavers are acknowledged as an important part 

of the coastal area, only beaver dams are protected in some manner and not the population of 

beavers that create and maintain their existence (ODFW 2008a). Therefore the range of beaver 

colonies and the number of beaver in the OCCS ESU would likely fall into the managed, not 

recovering, and not protected category. This is also evident in the low density of beaver dams 

per kilometer from 1998 to 2009.

The effect of past declines in beaver dams in the OCCS ESU is probably manifest in the 

current biological status of the species, because beaver-created habitat degrades rapidly in the 

absence of active beaver populations (Naiman et al.1988). The combination of one agency 

promoting the importance of beavers with the lack of any protection for beavers on private lands 

and minimal or no requirements for monitoring the take of beavers makes it extremely difficult 

to predict the abundance of beavers in the future compared to current levels. Despite this 

uncertainty, the BRT was concerned that lack of protection for beavers could result in a potential 

decline of this important habitat-forming species, with continued low levels of beaver dams and 

potentially resultant declines in the abundance of high quality OCCS habitat. The BRT 

concluded that a lack of protection of beavers and degraded beaver dam density levels is an 

ongoing threat to OCCS that is not fully manifest in the current biological status of the species.

There is an important point to consider: even if beaver populations and beaver ponds 

increase in the Oregon coast, other ecological constraints need to be incorporated into the 

management actions of beaver ponds. One particular concern is the invasion of reed canary 

grass in ponded areas. The cycle of beaver impoundment and abandonment disrupts the native 

community and provides an ideal environment for reed canary grass, which once established 

tends to exclude development of herbaceous communities and limits vegetation species richness 

(Perkins and Wilson 2005). Strong management actions to control reed canary grass are most 

likely needed to reestablish native flora that is considered beaver food, which may be relatively 

expensive and a slow process (Healy and Zedler 2010, Hoffman 2010).

Roads—A number of studies have found negative correlations between road density and 

coho salmon productivity. Bradford and Irvine (2000) found that the rate at which individual 

coho populations declined between 1988 and 1998 in the Thompson River, British Columbia, 

was related to the extent of agricultural and urban land use and the density of roads in the 

watershed. An increase in road density was correlated to an increase in coho salmon population 

decline. The road densities in the Bradford study ranged 0−2 km/km2 compared to 1.5−4 

km/km2 in the OCCS ESU (Figure 18). The road densities for the OCCS ESU in Figure 18 are 

an underrepresentation of actual road densities in the ESU because industrial forest land roads 

are not included in the data set.
77

Figure 18. Active road densities by fifth-field hydrologic unit. These include only partial road densities 

from private lands.
78

Sharma and Hilborn (2001) found that lower valley slopes, lower road densities, and 

lower stream gradients were correlated with higher smolt density in 14 western Washington 

streams between 1975 and 1984. The results suggest a decrease of 500 smolts/km for each 1 

km/km2 increase in road density. If road densities affect Oregon streams similarly, they could 

have a significant effect on OCCS smolt production in much of the ESU (Figure 18).

Pess et al. (2002b) also found a negative relationship between road density and the 

number of fish-days18 for coho salmon over time in the Snohomish River basin, Washington. 

Most of the negative correlation was the result of urbanization and impervious surface. 

Urbanization can lead to an increase in impervious surface area and increase stream flooding 

frequency and magnitude (Hollis 1975). The preurbanized 10-year recurrence interval flow 

event can occur every 2–5 years in urbanized areas of the Puget Sound region (Booth 1990), 

which can lead to declines in adult coho salmon (Moscrip and Montgomery 1997).

In a study of the tributaries of Elk River, Oregon, Burnett et al. (2006) found that density 

of large wood in pools was negatively correlated with road density. Road density was also 

negatively correlated with forest cover, and at the scale they examined, may integrate the impacts 

of timber harvest associated with the road network.

At the Oregon Coast Coho Salmon Symposium, Chris Frissell of PRC presented 

information on known road densities throughout the OCCS ESU and related those to the properly 

functioning condition defined for bull trout in the Columbia Basin (see New Comments section). 

His hypothesis was that with the high road densities that are known and included in the BLM 

roads GIS layer and the probable road densities that are not known,19 road density in the OCCS 

ESU is probably very high and constitutes risk to OCCS as he has shown that road densities 

affect bull trout.

The effects of current road densities may not yet be reflected in the biological status, as 

existing and legacy roads can contribute to continued stream degradation over time through 

restriction of debris flows, sedimentation, restriction of fish passage, and loss of riparian 

function. Future land management actions in forest, agriculture, and urban settings with their 

resultant additions to the roads network have the potential to contribute to future reductions in 

OCCS populations and could constitute a future threat.

Nonindigenous plant species—Another aspect of human disturbance that can affect 

stream habitat complexity has been identified in the Oregon Conservation Strategy (ODFW 

2011) and in the USFS Pacific Northwest Region Invasive Plant Program (NMFS 2005b, USFS 

2005). Invasive nonnative species can be powerful disrupters of native plant and animal 

communities. Two examples of how exotic plants can affect stream complexity are those of 

giant knotweed (Polygonum sachlinense) and reed canary grass. Giant knotweed displaces 

regenerating alder and conifer trees in riparian areas (Urgenson et al. 2009) and reed canary grass 

prevents regeneration of willow and alder, species that may affect physical stream complexity 

but are also food items for beaver use (Perkins and Wilson 2005, Healy and Zedler 2010).

 18 Fish-days were calculated by multiplying the live fish observed on each survey date by the number of days 

between surveys. These values were then summed for the entire observation period to generate a relative index of 

spawner abundance at a reach for any given year.

19 Industrial forest land road density data sets are not generally available and therefore not included in the GIS layer.
79

Human landscape disturbance—The condition of aquatic ecosystems and associated 

fish populations are a function, at least in part, of the characteristics of the surrounding landscape 

(Frissell et al. 1986, Naiman et al. 2000, Gregory et al. 2008). Timber harvest and associated 

roads have extensively altered aquatic ecosystems throughout the Pacific Northwest (Everest and 

Reeves 2007). A consequence of the effects of timber harvest activities is that the behavior of 

ecosystems is altered, which in turn has consequences for fish populations and their habitat 

(Reeves et al. 1993). There is a negative association between the amount of in-channel large 

wood and percent of area intensively logged in a watershed (Murphy and Koski 1989, Bilby and 

Ward 1991, Montgomery et al. 1995). Burnett et al. (2006) found that that the mean density of 

large wood in Elk River (on the southern Oregon coast) was positively related to the area in 

larger trees in the catchment. Reeves et al. (1993) examined watersheds in the Oregon Coast 

Range and found that the diversity of the fish assemblage and the amount of large wood was 

significantly greater in streams in which less than 25% of the watershed was clear-cut, compared 

to watersheds in which more than 25% of the area was clear-cut. This pattern was observed in 

other areas for other land uses including agriculture (Berkman and Rabini 1987) and 

urbanization (Scott et al. 1986).

The condition of aquatic habitat and fish populations is also directly correlated with the 

density of roads in a watershed, which in turn is generally directly related to the amount and 

intensity of land management activities (Lee et al. 1997). Roads are sources of sediment either 

as surface erosion or as mass erosion (Furniss et al. 1991). They also can alter water delivery by 

increasing the drainage network, particularly in the upper portions of the network. Sharma and 

Hilborn (2001) examined 14 streams in Washington and found that smolt density was inversely 

correlated with the density of roads. Logging activities involve the creation and maintenance of 

roads and logging has been linked directly to increased sediment levels in streams (Platts et al. 

1989).

Despite the connection between human disturbance and fish habitat and population 

performance, the ONCC TRT (Wainwright et al. 2008) was unable to include habitat condition 

directly in its biological recovery criteria. Therefore, habitat condition was not included in the

DSS analysis because at the time there was no uniform measure of habitat quality over the entire 

ESU. ODFW habitat surveys were available, but the density and distribution of on the ground 

surveys made them unsuitable for fine-scale analysis needed for biological recovery criteria.

Recent public availability of Landsat imagery and the development of tools for analysis 

now make it possible to analyze human disturbance patterns on a fine temporal and spatial scale. 

Satellite images have the potential for measuring properties of large landscapes at a relatively 

fine scale. In an analysis conducted for the BRT, satellite annual vegetation maps of the OCCS 

ESU were updated through 2008 and analyzed for patterns of disturbance for the time period 

1986 to 2008. The scale of resolution of these analyses is approximately 100 m, so disturbances 

as small as 1 ha can theoretically be detected. This made it possible to detect individual 

disturbance events from the satellite images and map new disturbances on an annual basis. 

Intensity of disturbance can also be measured, so low-intensity disturbances (i.e., thinning) can 

be distinguished from high-intensity disturbances (i.e., clear-cut). Fires were also mapped, but 

fire has had a small role in shaping habitat in the OCCS ESU over the past 23 years (for more 

information on methods, see Appendix B and Kennedy et al. 2010).
80

Human disturbance was widespread over the ESU and predominantly of high intensity 

(Figure 19). Disturbance patterns varied over space, time, and land ownership. Some river 

systems have experienced higher disturbance than others (Figure 20). The time series of 

cumulative disturbance, derived from Landsat images, is shown for four major river systems in 

the OCCS ESU in Figure 21. Disturbance in these systems spans the range observed in the ESU, 

from a low of 10% (Upper Nehalem) to 50% (Siletz). Most disturbance is in the high category, 

with a lesser amount of low intensity disturbance, and the proportion of high to low disturbance 

is fairly constant through the time period. Three patterns of disturbance are evident (Figure 21). 

Constant rates of annual disturbance occurred in the Siletz and Alsea river systems. The 

Necanicum River basin showed little harvest activity early in the time period, with an 

exponential increase in more recent years. By contrast, the North Umpqua River basin showed 

an overall low rate of disturbance, with most of the activity early in the time period.

Changes in the regulatory environment have largely driven patterns of land disturbance 

over the past two decades. Disturbance in four land ownership categories in the Alsea River 

basin is shown in Figure 22. Prior to 1990, there were high rates of disturbance on federal lands 

(BLM and USFS). With implementation of the Northwest Forest Plan, federal logging activity 

decreased to very low levels. Logging on private lands proceeded at a steady pace through the 

late 1990s, then increased. This general pattern is evident throughout the ESU, with logging on 

National Forest and BLM land decreasing after 1989 and activity on private lands increasing.

Caution is needed in interpreting the implications of the vegetative disturbance on OCCS 

and their freshwater habitat. Other researchers have found relationships between landscape 

characteristics and the condition of habitat of coho salmon (Pess et al. 2002a) and other species 

of Pacific salmon (e.g., Steel et al. 2004). Hicks and Hall (2003) noted that discerning the effects 

of timber harvest on fish and fish habitat in the Oregon Coast Range was particularly difficult 

because of the inherent variability in rock types and associated stream features. The use of 

Landsat imagery to assess the rate of vegetative change and the extent of disturbance does not 

assess the impacts of timber harvest on populations and habitat of coho salmon. However, it can 

provide insights into the potential effects and the extent of the impacts across the ESU, which in 

turn has implications for the assessment of the status of the ESU.

Because of limits on time and resources, the BRT was unable to conduct an analysis to 

determine whether there is a relationship between the rates of vegetation disturbance and 

changes in the abundance of coho salmon and habitat conditions. However, this information on 

rates of disturbance can be a potential indicator of current and, at least in part, future habitat 

conditions. The diversity of the salmonid assemblage and the amount of large wood in the 

channel is related to the amount of timber harvest in watersheds in the Oregon Coast Range. 

Once large wood is removed from upslope areas, recruitment to streams is reduced, perhaps for 

hundreds of years. Legacy effects of logging will be felt as long as existing wood in streams is 

decaying faster than it is being replaced (Reeves et al. 1993).

There is recognition in the scientific literature about the importance of periodic 

disturbances for creating and maintain fish habitat (Naiman et al. 1992, Reeves et al. 1995, 

Rieman et al. 2006). Timber harvest can alter the disturbance process and ultimately have 

negative rather than positive consequences to fish populations and habitat (Reeves et al. 1995, 

Bisson et al. 2009, Cover et al. 2010). Naturally occurring disturbance events were important 
81

Figure 19. Distribution and intensity of vegetation disturbance from 1986 to 2008, based on analysis of 

Landsat imagery.
82

Figure 20. Ranking of river basins and the Umpqua subbasins by cumulative percent vegetation 

disturbance from 1986 to 2008.
83

Figure 21. Time series of cumulative area of vegetation disturbance for four river basins in the OCCS 

ESU. High disturbance (dark gray) is usually clear-cut logging, while low disturbance (light 

gray) is related to forest thinning. Data from Kennedy et al. 2010 and Kennedy et al. 2012.

sources of sediment and large wood, the basic structural components of habitat. This is 

particularly true in the Oregon Coast Range (Reeves et al. 1995, May and Gresswell 2003, 

Reeves et al. 2003, Bigelow et al. 2007). Disturbances associated with timber harvest, primarily 

landslides and debris flows, have less large wood associated with them than those that occurred 

naturally (Hicks et al. 1991, Lancaster et al. 2003). The loss of wood results in decreased habitat 

quantity and quality (Reeves et al. 1995, Cederholm et al. 1997).

Burnett et al. (2007) suggested widespread recovery of coho salmon in the OCCS ESU is 

unlikely unless habitat improved in areas of high intrinsic potential on private lands. Timber 

harvest effects on fish and habitat are likely most pronounced on private and state lands. 

Requirements for management of riparian zones on these lands are less than on federal lands. 

Current forest practice regulations reduce the size of the streamside riparian area to less than that 

needed to maintain the full suite of ecological processes provided by riparian areas and allow for 

removal of trees from within this zone, which further reduces ecological effectiveness. 

Additionally, there is no requirement for protection on small intermittent streams, which are 

important sources of wood (May and Gresswell 2003, Reeves et al. 2003, Bigelow et al. 2007) 

on private lands. These streams are given consideration on a portion of each stream on state 
84

Figure 22. Total area (hectares) of vegetation disturbance in the Alsea River area of the OCCS ESU by 

four land ownership categories from 1986 to 2008. BLM = Bureau of Land Management 

timberlands, ODSL = Oregon state timberlands, Private = industrial and nonindustrial private 

timberlands, and FS = U.S. Forest Service. Data from Kennedy et al. 2010 and Kennedy et al. 

2012.

lands. Botkin et al. (1995) and the Independent Multidisciplinary Science Team (IMST 1999) 

found these regulations insufficient to improve or recover habitat that is currently degraded.

The recent availability of Landsat images, along with the development of tools for 

analysis, allowed a comprehensive, uniform picture of human disturbance patterns that was 

previously unavailable. This analysis showed that disturbance has been widespread in the ESU, 

some basins experienced much higher disturbance than others, rates of disturbance are relatively 

constant, and the most intense disturbance has moved from federal to private lands, presumably 

in response to policy changes. The BRT thought that human landscape disturbance is captured 

somewhat in the current biological status, but the effects of human landscape disturbance 

constitute an ongoing threat to OCCS.

Loss/gain of large wood for future habitat conditions—Large wood is a key 

component of habitat complexity for coho salmon in the OCCS ESU. This wood is recruited 

from riparian areas immediately adjacent to the stream and from upslope sources, primarily 

along smaller, nonfish-bearing streams (Reeves et al. 2003). Currently wood is lacking in many 

streams in the OCCS ESU because of past management activities.

Burnett et al. (2007) examined the current and future condition of riparian areas along 

streams with coho salmon within the entire ESU. Thirty-six percent of the stream length 

available to coho salmon were classified as high intrinsic potential (see Glossary). The vast 
85

majority of that (81%) was primarily on nonindustrial private lands. Forty-four percent of the 

riparian areas along streams with high intrinsic potential are currently either nonforested or 

recently logged; 10% have stands that are dominated by large (50−75 cm quadratic mean 

diameter) or very large (>75 cm quadratic mean diameter) trees. The large and very large trees 

are the size that creates more complex habitat conditions (Abbe and Montgomery 1996) and are 

found almost entirely on federal lands, which have a relatively small proportion of the high coho 

salmon intrinsic potential streams (Burnett 2007).

The percentage of buffers with large and very large trees is projected to increase to at 

least 75% on federal lands and 60% on state lands in 100 years under current policies. Less than 

25% of the buffers in private ownership will have vegetation in these size classes at the end of 

that time. As a result, Burnett et al. (2007) concluded that widespread recovery of habitat in high 

intrinsic potenital streams, a key element of future OCCS habitat recovery, is unlikely unless 

there are greater improvements on private lands.

The likelihood of complex stream habitat recovery for coho salmon in the ESU is 

potentially further limited because of the lack of or limited requirements to consider nonfishbearing streams on private and state lands, respectively, in current management policies. Reeves 

et al. (2003) found that 65% of the large wood in Cummins Creek, a small watershed in a 

federally designated wilderness area on the central Oregon coast, originated in areas outside of 

the stream-adjacent riparian zone. Bigelow et al. (2007) found that wood delivered in debris 

torrents in nonfish-bearing streams was a key component of habitat in a sandstone watershed on 

the central Oregon coast. Thus the potential of landscape and local scale stream complexity in 

habitat for coho salmon in the ESU to improve is likely to be less than what Burnett et al. (2003) 

concluded, because current policies guiding the management of riparian areas on state and 

private lands have limited or no management requirements for this important potential source of 

wood. The BRT thought that the loss of large wood from streams in the OCCS ESU is captured 

to some degree in the current biological status, but the effects of continued loss and lack of 

replacement of large wood in areas that can contribute to stream complexity constitutes an 

ongoing threat to OCCS.

In-channel habitat complexity—Since the original status review, the ESU has

experienced an increase in abundance and productivity that largely reflects improved marine 

survival conditions. This increase may have reduced short-term risks to the ESU; however, the 

BRT was also concerned that freshwater habitat may not be sufficient to maintain the ESU at 

times when marine conditions are poor. The BRT also noted that the criteria in the DSS do not 

take advantage of some important habitat monitoring data. To address the latter deficiency and 

generally evaluate trends in freshwater habitat, the BRT in collaboration with ODFW conducted 

some additional analyses of trends in the freshwater habitat attributes of this ESU.

From 1998 to the present, ODFW has monitored wadeable streams to assess freshwater 

rearing habitat for the OCCS ESU during the summer low flow period (Anlauf et al. 2009). The 

goal of this program is to measure the status and trend of habitat conditions throughout the range 

of the ESU through variables related to the quality and quantity of aquatic habitat for coho 

salmon: stream morphology, substrate composition, instream roughness, riparian structure, and 

winter rearing capacity (Moore et al. 2008). In 2009 ODFW and NMFS scientists independently 

analyzed these data to ask the question: Has juvenile coho habitat changed over the past 11 
86

years? These analyses reached somewhat different conclusions. In particular, the Anlauf et al. 

(2009) analysis generally indicated that there were no significant trends in habitat attributes 

(either positive or negative) across the ESU, while the 2009 NMFS analysis indicated declining 

trends in some measures of habitat quality across several regions of the ESU.

To better understand and resolve the discrepancies between these analyses, NMFS and

ODFW formed a joint Habitat Trends Working Group (HTWG). The HTWG determined that 

the differences in results were caused primarily by the use of two different data sets and the use 

of slightly different statistical models of data analysis. In particular, the Anlauf et al. (2009) 

analysis focused on data only from within the spawning and rearing distribution of OCCS, while 

the NMFS team used a data set that also included habitat sites upstream from these areas. In 

addition, the Anlauf et al. (2009) analysis used a statistical model with some parameters that 

were supported by the survey design but that the NMFS analysis found as currently unsupported 

by the data.

The HTWG (Appendix C) estimated trends for five habitat metrics—1) Aquatic and 

Riparian Effectiveness Monitoring Program (Reeves et al. 2004, 2006) channel score, 2) summer 

parr capacity, 3) winter parr capacity, 4) percent of riffle that is sand/silt/organics, and 5) volume 

of large woody debris (LWD) per 100 m (Table 16). The first three metrics are multivariate 

measures of habitat complexity and capacity, and the latter two are univariate metrics of habitat 

condition that are reasonably well understood to indicate quality of coho salmon rearing habitat. 

The HTWG used three statistical models to evaluate trends. Two models were forms of a 

maximum likelihood–based analysis of variance linear model and the third was a similarly 

structured linear model in a Bayesian framework (see Appendix C for model details). The 

analyses were conducted on two nonoverlapping data sets, one limited to data collected within 

coho rearing habitat and the other from habitat monitoring locations upstream and inaccessible to 

coho salmon, but potentially important nonetheless as determinants of downstream habitatforming processes (e.g., source areas for wood and sediment). For the data from areas upstream 

of coho rearing habitat, only the two univariate metrics (LWD and percent sand) were evaluated. 

Overall, the predicted spatial and temporal patterns in multiple metrics of fish habitat were very 

similar between the multiple models (Appendix C). Therefore, to simplify the presentation, here 

we discuss just the results from the Bayesian modeling framework, since this approach provides 

more explicit information on the relative certainty/uncertainty of trends in the data.

The results from the coho rearing areas are summarized in Table 17. Trend estimates are 

mixed and vary among metrics and population strata. Positive indications of habitat condition 

change include trends of decreasing fine sediment levels in the North Coast and Mid-Coast, 

increasing wood volume in the Mid-Coast and Mid-South Coast, and increasing habitat 

complexity (as indexed by channel score) in the North Coast and Mid-Coast. However, the 

monitoring data also show that habitat conditions are declining in some regions for some metrics. 

For example, fine sediment levels are increasing in the Mid-South Coast and wood volume is 

decreasing in the North Coast and Umpqua. Similarly, habitat complexity, in this case as 

indexed by channel score and summer and winter parr capacity, is declining in the Mid-South 

Coast (winter parr capacity and channel score) and the Umpqua (winter and summer parr 

capacity).
87

Table 16. Graphical representation of the maximum likelihood analysis and Bayesian analysis trend results. Arrow style indicates strength of 

trend: black vertical arrow represents greater than 90% Bayesian probability or significance (P < 0.05) of trend; light gray vertical arrow 

represents greater than 65% Bayesian probability of trend; horizontal gray arrow represents lower (<65%) Bayesian probability of trend or 

no significant trend detected (maximum likelihood). Upward pointing arrow indicates a positive trend and downward pointing arrow 

indicates a negative trend.

Stratum

North Coast Mid-Coast Mid-South Umpqua River

Maximum likelihood (BRT)Maximum likelihood (ODFW)Bayesian probabilitiesMaximum likelihood(BRT)Maximum likelihood (ODFW)Bayesian probabilitiesMaximum likelihood (BRT)Maximum likelihood (ODFW)Bayesian probabilitiesMaximum likelihood (BRT)Maximum likelihood (ODFW)Bayesian probabilities

Winter 

parr

Summer 

parr

Channel 

score

Wood 

volume

% fine 

sediment 

in riffles
88

Table 17. Trend analysis summary for five habitat metrics by region, including only sites designated as 

coho spawning/rearing habitat. The Bayesian posterior mean (estimate) is given for each metricregion combination. As a measure of uncertainty, the probability of a negative trend (proportion 

of the posterior distribution < 0) is given for each estimate. AREMP = Aquatic and Riparian 

Effectiveness Monitoring Program, LWDVOL = volume of LWD, RIFSNDOR = percent of fine 

sediment/organic matter in riffles.

Metric North Coast Mid-Coast Mid-South Coast Umpqua

Winter parr Estimate 0.000 0.000 –0.025 –0.013

Pr < 0 0.550 0.640 0.950 0.790

Summer parr Estimate 0.009 0.027 0.030 –0.028

Pr < 0 0.320 0.080 0.090 0.880

AREMP Estimate 0.006 0.006 –0.025 0.003

channel score Pr < 0 0.170 0.180 1.000 0.360

LWDVOL Estimate –0.062 0.016 0.020 –0.026

Pr < 0 1.000 0.110 0.090 0.940

RIFSNDOR Estimate –0.010 –0.004 0.026 0.002

Pr < 0 0.970 0.760 0.000 0.400

Across the OCCS ESU in the coho salmon rearing areas, habitat conditions show positive 

and negative trends. These trends vary in magnitude and are supported to varying degrees by the 

data (e.g., probability of trend being non-zero). In contrast to the coho rearing areas, trends in 

upstream areas were more pronounced. In particular, LWD declined substantially in all regions. 

Trends in sediment were mixed, with increases in the Mid-Coast and Mid-South strata and 

declines in the North Coast and Umpqua strata (Table 18). However, the fundamental take home 

message from the data analysis is that the data do not indicate a clear, consistent pattern of 

habitat improvement or degradation over the ESU for these metrics and this time frame.

The BRT was impressed with the ODFW habitat monitoring program and believes that it 

is a valuable source of information on freshwater habitat trends on the Oregon coast. The results 

from the HWTG were encouraging in that they resolved some clear discrepancies between 

earlier analyses. The BRT concluded that the results paint a complex picture of habitat trends 

along the Oregon coast. Some trends, such as the increase in habitat complexity and summer 

parr capacity in three of the four regions, were clearly encouraging, but the declining trends in 

winter parr capacity (believed to be a limiting life stage for coho salmon production) in two 

strata concerned the BRT. Other trends, such as the declines in LWD in the North Coast and 

Umpqua strata and in upstream areas in all strata, appear more troubling. The North Coast trend 

in LWD may be a result of large debris dams that formed during the 1996 floods and have been 

actively redistributed over the past several years, reducing overall LWD densities. While the 

North Coast stratum experienced a large decline in LWD frequency in the past decade, it is 

important to note that it also had the largest amount of LWD relative to the other strata.

Summary of stream habitat complexity—Stream habitat complexity at landscape and 

local scales has been identified as a factor for decline (OCSRI 1997, NMFS 1997a), a key 

limiting factor (OCSRI 1997, Anlauf et al. 2009), and a primary limiting factor (Oregon 2007) 

for OCCS. Complex stream habitats are diverse and dynamic. Complexity is maintained
89

Table 18. Trend analysis summary for two habitat metrics by region, using only sites that are not 

designated as coho salmon spawning/rearing habitat. The Bayesian posterior mean (estimate) is 

given for each metric-region combination. As a measure of uncertainty, the probability of a 

negative trend (proportion of the posterior distribution < 0) is given for each estimate.

Metric

North 

Coast

MidCoastMid-South 

Coast Umpqua

RIFSNDOR Estimate –0.008 0.009 0.009 –0.007

Pr < 0 0.94 0.1 0.04 0.93

LWDVOL Estimate –0.041 –0.031 –0.058 –0.027

Pr < 0 1 0.95 1 0.97

through connection to the surrounding landscape and it has been well established that a century 

and a half of land use activities have simplified Oregon coastal streams (Reeves et al. 1993, 

1995, Burnett et al. 2007). Because of its importance to the status and recovery of the species, 

the BRT considered multiple aspects of this issue. These included legacy effects of splash dams, 

log drives, and stream cleaning; beaver status and management; road densities and their effects 

on coho smolt densities; disturbance, large wood in riparian zones; and trends in landscape and 

local stream complexity across the ESU (Naiman et al. 1988, Maser and Sedell 1994, Bradford 

and Irvine 2000).

The BRT habitat subcommittee analyzed the complexity of available freshwater habitat 

using multidimensional stream complexity metrics developed by ODFW’s Oregon Plan coho 

salmon monitoring program (HLFM winter and summer parr capacity). The subcommittee 

analyzed channel score and parr capacity metrics that were constructed from the ODFW stream 

habitat monitoring data sets. Newly available Landsat data were also analyzed to examine 

anthropogenic disturbance to the landscape of the OCCS ESU. Other impacts such as roads were 

discussed with reference to their effects on coho smolt densities from Washington and British 

Columbia (Bradford and Irvine 2000). Legacy effects of splash dams and stream cleaning and 

current and future condition of large wood in riparian areas were discussed with respect to the 

availability of wood for stream complexity. Indications as to the present and future status of 

beavers were examined through beaver studies that occurred in the ESU and an analysis based on 

published literature.

Even though splash damming, log drives, and stream cleaning are no longer practiced or 

endorsed by ODFW, legacy effects of these activities still affect the amount and type of wood 

and gravel substrate available and, therefore, stream complexity across the ESU (Miller 2010, 

Montgomery et al. 2003). Increasing complexity would indicate that these legacy effects are 

being mitigated as wood and gravel move into the stream channel. The resulting channel would 

be more hydraulically diverse, with pools, side channels, and backwater units that support higher 

summer and winter capacity for spawning and rearing. Eleven-year trends of stream complexity 

metrics were analyzed at the level of the stream, population, and stratum (HLFM version 7). 

Similar to the ODFW/Anlauf et al. (2009) trend analysis of individual habitat attributes, the 

subcommittee’s analyses found that habitat complexity across the ESU exhibited no consistent 

trends over the period of consideration (1998−2008). There are exceptions, such as increasing 
90

summer parr capacity in the Mid-South or Mid-Coast strata. But for any metric or any stratum, 

no trends were identified.

To help understand these patterns, the BRT examined several other lines of evidence. 

Clear-cut logging removes wood from upslope, disturbs the riparian zone (Montgomery et al. 

2003), reduces the amount of large wood available to the streams, and interferes with processes 

that generate complexity (Reeves et al. 2003, Burnett et al. 2007). Use of Landsat images 

allowed the BRT to look at patterns of clear-cutting and thinning from 1986 to 2009. Timber 

harvest and other land use activities were widespread throughout the ESU, with about 40% of the 

total forest area experiencing anthropogenic disturbance in the 23-year period. Timber harvest 

rates varied by basin, but there was no evidence of a general reduction in the pace of logging. 

The cumulative percentage of forest clearing by basin was highest in the Siletz Basin, followed 

by the Necanicum to the north, and Coos, Coquille, and mid-Umpqua to the south. The most 

striking change was a shift in impacts from National Forest land to private industrial land.

The patterns of simplification of stream habitat and reductions in salmon habitat capacity 

caused by forestry activities are consistent with other information (ODFW 2005b, 2009a) that 

indicate low levels of large wood (Burnett et al. 2006) and high levels of sediment (Lee et al. 

1997) in streams of the Oregon Coast Range. The BRT considered the long-term (multiple 

decades) effects of logging activities and associated road building on stream conditions, the 

widespread occurrence of these activities, and lack of any sign that logging activities are abating 

as indications that these threats to habitat are pervasive and ongoing in the OCCS ESU.

Beavers are an important species to proper watershed functioning in coastal Oregon 

streams, and the loss of beavers and their dams has been identified by ODFW (OCSRI 1997, 

ODFW 2007) and many other authors as an important loss to stream complexity that 

significantly affects OCCS. Because ODFW has only aquatic habitat survey data from which to 

infer beaver populations and structures, knowledge of what could be a significant contributor to 

OCCS recovery is severely limited; however, continued loss of this important keystone species 

constitutes a continuing risk to stream complexity and impediment to habitat improvement.

In summary, habitat complexity across the ESU did not improve over the period of

consideration (1998−2008). Road densities are high and affect stream quality through 

hydrologic effects like runoff and siltation and by providing access for human activities. Beaver 

activities, which produce highly productive coho salmon rearing habitat, appear to be reduced, 

and recovery of beaver populations could be impaired by their classification as a nuisance 

species. Stream habitat restoration activities may be having a short-term positive effect in some 

areas and passive efforts to restore landscape condition may be effective on much longer time 

periods than is considered here, but the quantity of impaired habitat and the rate of continued 

disturbance appears at this time to be countering the efforts to restore complex instream 

habitat.20

Some stream complexity problems such as the legacy effects of splash damming and 

stream cleaning are probably already reflected to a large degree in the current biological status. 

 20 The effect of restoration projects not reflected in the ODFW data set is not discussed in this document, but is 

discussed in the Federal Register notice as conservation measures.
91

However, future impacts to stream complexity from large wood availability; disturbance from 

road building, logging, and other land use practices; and reduction of beaver populations are not 

reflected in current biological status and may constitute a future threat.

Land management—forest and agriculture conversion

The pressures of urban and rural residential land use affect aquatic ecosystems and 

salmonids through alterations of and interactions among hydrology, physical habitat structure, 

water quality, and fish passage. These alterations occur at local and especially watershed scales, 

and thus require study and management at multiple scales. Urban and rural residential 

development causes profound changes to the pathways, volume, timing, and chemical 

composition of stormwater runoff. These changes alter stream physical, chemical, and biological 

structure and potential, as well as the connectivity of streams with their watersheds (IMST 2010).

The BRT discussed several modeling studies undertaken to understand the potential for 

conversion of lower density land uses to higher density ones. These were modeling studies by 

Kline et al. (2003) (see Table 19) and Lettman et al. (2009) that looked at the potential for land 

use conversion based on land use regulations existing at the time of the study. Kline et al. 

(2003), as part of the Coastal Landscape Analysis and Modeling Study (CLAMS) Project, 

modeled the potential expansion of urban and suburban areas in most of the OCCS ESU (Figure 

23). Land use is projected to change in the ESU; primary changes are expected to be from 

agriculture, forest, and rural residential to urban (Table 20). Figure 23 shows a possible scenario 

between 1994 and 2044 based on existing land use zoning and property ownership as of 1994 

Table 19. Results of Kline et al. (2003) by biogeographic stratum in the OCCS ESU. The year 1994 is 

used as a baseline for analyses predicting change in land use to rural residential and urban land 

use in 50 years and 100 years.

Land use %

Stratum Other Rural residential Urban

1994

Lakes 91.87 7.18 0.96

Mid-Coast 97.91 1.88 0.21

Mid-South Coast 96.61 2.32 1.07

North Coast 97.31 2.51 0.18

Umpqua 97.15 2.48 0.36

2044

Lakes 92.85 5.59 1.56

Mid-Coast 97.22 1.93 0.85

Mid-South Coast 95.69 2.67 1.64

North Coast 96.11 2.99 0.89

Umpqua 95.82 3.29 0.88

2094

Lakes 89.95 6.47 3.58

Mid-Coast 95.58 3.21 1.21

Mid-South Coast 93.05 4.66 2.30

North Coast 91.97 5.89 2.14

Umpqua 93.32 4.97 1.71
92

Figure 23. Projected building densities, 2044.
93

Table 20. Change in land use types predicted by Lettman et al. (2009). The baseline land use types are from 2005 information with 2035 

as a 30-year projected change.

Stratum

Lakes Mid-Coast Mid-South Coast North Coast Umpqua

Land use type 2005 2035

Area 

(ha) 2005 2035

Area 

(ha) 2005 2035

Area 

(ha) 2005 2035

Area 

(ha) 2005 2035

Area 

(ha)

% wild land 

forest

81.56 81.09 –266 93.90 93.70 –1,065 85.41 85.20 –1,157 94.00 94.80 +4,145 87.88 87.63 –3,036

% mixed forest 

and agriculture

0 0 0 1.67 1.66 –56 4.80 4.80 0 0.59 0.50 –444 5.61 5.52 –1,093

% intensive 

agriculture

1.06 1.06 0 1.18 1.18 0 5.00 4.93 –352 2.82 2.58 –1,184 4.12 3.84 –3,400

% low density 

residential

5.64 6.07 +244 2.57 2.56 –56 3.33 3.44 +553 1.63 2.03 +1,977 1.60 1.98 +4,615

% urban 0.49 0.53 +23 0.44 0.67 +1,288 0.86 1.07 +1,057 0.59 0.71 +592 0.55 0.79 +2,914

% other 11.25 11.25 0 0.18 0.16 –112 0.59 0.58 –50 0.37 0.34 –148 0.24 0.24 0
94

(Kline et al. 2003). This model allows building densities to increase on any private lands, with 

some lands or ownerships (e.g., nonindustrial private) having greater likelihood of increases. By 

2044 in this analysis, some change is anticipated in certain areas, particularly the area of the ESU 

near the urban centers along the Oregon coast. The Lakes stratum is anticipated for urban 

densities to nearly double, the Mid-Coast stratum to increase by a factor of 4, the North Coast to 

increase by a factor of 5, the Mid-South coast by a factor of 1.5, and the Umpqua stratum to 

increase by 2.5. This analysis did not include the entire Umpqua Basin, however.

While these increases are relatively large, they are still below the potential threshold 

effects of fundamentally altering the magnitude and frequency of flood events (Booth 1990,

1991). However, if urbanization is concentrated in distinct areas, as is typically the case, then 

watersheds with those areas could have increases that result in urbanized drainage areas of 

greater than 10−15% where the 1-year to 4-year flood event has a magnitude that is more similar 

to a 10-year flood recurrence interval (Moscrip and Montgomery 1997). This change in the 

hydrology of the streams could then result in decreases in coho salmon abundance levels from 

2.5 to 4 times the levels typically seen in forested environments, particularly if urbanization also 

included alteration to wetland habitats directly associated with the stream network (Pess et al. 

2003).

ODF also developed a model that predicts potential future land use changes in the ESU 

due to increased conversion of forest land to agriculture and urban/suburban uses (Figure 24, 

Table 20) (Lettman et al. 2009). The results of these projections show that under each of these 

scenarios, the most likely effects will be in the Mid-Coast, Mid-South Coast, and Umpqua River 

strata.

Human disturbances such as agriculture and urbanization can lead to a decrease in coho 

salmon habitat availability and quality (Berkman and Rabeni 1987, Beechie et al. 1994, Bradford 

and Irvine 2000). Beechie et al. (1994) found a decrease in tributary and off-channel habitats 

(e.g., wetlands, sloughs, and ponds) of up to 75%, almost all of which was due to deliberate 

modifications of the channel and floodplain. The vast majority of these impacts are related to the 

conversion of forested areas to agricultural and subsequently residential use. Maintained 

channelization can increase channel incision to the point where the streambed is disconnected 

from its floodplain (Booth 1990). Floodplain isolation reduces the amount of off-channel habitat 

available for adult salmonid spawning and juvenile rearing, which can lead to the downstream 

displacement of newly emerged salmonids to less desirable habitats (Seegrist and Gard 1972, 

Erman et al. 1988). Stream cleaning and riparian vegetation removal reduces the amount of inchannel wood, leading to a loss of pool habitat quantity (Montgomery et al. 1995, Collins et al. 

2002), which can substantially reduce coho redd density (Montgomery 1999).

Urbanization can lead to an increase in impervious surface area and increase streamflooding frequency and magnitude (Hollis 1975). The preurbanized 10-year recurrence interval 

flow event can occur every 2–5 years in urbanized areas of the Puget Sound region (Booth 

1990), which can lead to declines in adult coho (Moscrip and Montgomery 1997). Urban 

watersheds also generate high concentrations of compounds that are toxic to salmon or alter their 

behavior in ways that could reduce survival (Scholz et al. 2000).
95

Figure 24. Projected development zones, 2035.
96

Conversion of lower intensity land use to higher intensity land use with a greater amount 

of impervious surface was identified by NMFS (NMFS 1997a) as a factor for decline in portions 

of the OCCS ESU. If urbanization, rural residential development, and loss of forest cover are 

concentrated in distinct areas, as is often the case due to land use zoning, then those watersheds 

would experience a change in the hydrology of the streams that would result in decreases in coho 

salmon abundance levels. IMST (2010) found that:

In the Pacific Northwest, there is a growing understanding that aquatic habitat 

affected by existing development is important for salmonids (e.g., Pess et al. 

2002b, Regetz 2003, MacCoy and Blew 2005, Sheer and Steel 2006, Burnett et al.

2007, Bilby and Mollot 2008). Projections of future land use and land cover in

Oregon’s coastal mountains show increasing rural residential and urban

development within 328 foot (100 m) buffers surrounding high quality coho and 

steelhead habitat, with more rapid development projected for coho habitat 

(Burnett et al. 2007).

The BRT considered that the existing land use in the ESU was reflected in the current 

biological status of OCCS. Future conversions of lands to urban, suburban, and agriculture are 

dependent on many factors including economic conditions and land use planning and are 

therefore uncertain. Some BRT members thought that urbanization presented a smaller problem 

to OCCS compared to salmon in the Willamette Valley. Other BRT members, however, thought

that urbanization and rural residential development retard advances in recovering important 

OCCS habitat in locations such as Tillamook Bay and Coos Bay. They also considered that 

conversion of agriculture and forests to urban and rural residential land uses results in a 

disproportional impact to high potential coho salmon habitat; the effects of conversion of land to 

uses with levels of impervious surface above 15% within a watershed were therefore considered 

a potential future threat with uncertain magnitude to OCCS populations.

Land management—loss/gain of estuarine and freshwater intertidal habitat

The Oregon coastal drainages supporting independent OCCS populations terminate in 

tidally influenced freshwater wetland and estuarine habitats (Figure 25) (e.g., Good 2000). In 

declaring critical habitat for OCCS, NMFS (2008) recognized that Oregon’s estuaries and tidal 

freshwater wetlands provide habitat important to the migratory and rearing life stages of this 

ESU. IMST (2002) also highlighted the importance of estuaries for the “productive foraging 

environments for juvenile salmonids before they enter the ocean, refuge from predation, refuge 

from strong tidal and river currents, habitats of intermediate salinity for juvenile salmonids 

transitioning from fresh water to the ocean, migration corridors for adult salmonids returning 

from the sea, and at times, cooler water temperatures than [occur in] mainstem lowland rivers.” 

ODFW has also cited the role of estuaries in providing foraging and growth opportunities for 

outmigrating coho smolts and the importance of stream and estuary ecotones for rearing coho 

juveniles21 (Miller and Sadro 2003).

OCCS use of estuarine and freshwater intertidal habitat—The predominant life 

history pattern for coho salmon originating south of the central British Columbia coast is a 3-

year cycle, including freshwater rearing for approximately 18 months followed by an equivalent 

 21 R. Buckman, ODFW, Newport, OR. Pers. commun., January 2011.
97

Figure 25. Locations of major estuaries.
98

period of ocean residence (Weitkamp et al. 1995). Several studies (Schreck 2002, Chapman et 

al. in prep., Power22) have focused on the use of estuaries and tidal freshwater habitats by 

yearling smolts emigrating to the ocean from natal rearing reaches. Koski (2009) reviewed 

results from several studies of downstream coho migration and rearing and discussed the 

importance of the stream and estuary ecotone as a rearing area.

The stream and estuary ecotone, defined as the transition zone from tidal fresh to tidal 

brackish waters, can serve as a transition area for smolts adapting to saltwater. This zone, 

characterized by low salinity, warm temperatures in the summer, and an abundance of food for

juvenile salmonids, can serve as acclimation areas allowing coho salmon juveniles to adapt to the

higher salinity levels associated with downstream subtidal reaches. Smolts outmigrating from 

upstream freshwater reaches may feed and grow in lower mainstem or estuarine habitats for a 

period of days or weeks prior to entering the nearshore ocean environment23, 24 (Miller and Sadro 

2003, Chapman et al. in prep.). Chapman et al. (in prep.) found that wild juvenile coho smolts 

rearing in several Mid-Coast Oregon estuaries prey almost exclusively on intertidal benthic 

invertebrates found on mudflats that are available only during high tides. In addition to serving 

as transition areas for outmigrating smolts, estuarine (brackish and freshwater) areas may 

provide more extended rearing opportunities for young of the year (age 0) coho juveniles (Miller 

and Sadro 2003).

Juvenile sampling studies in coastal rivers from northern California to Alaska indicate 

that coho salmon (age-0) juveniles are often present in these lower river and estuarine habitats, 

particularly in freshwater tidally influenced habitats (e.g., Jones et al. unpubl. manuscr.). Koski 

(2009) summarized information from recent studies indicating that downstream migrations of 

coho salmon may be associated with specific life history strategies that contribute to resiliency in 

the face of fluctuating environmental conditions. The relative contribution to adult returns from 

variations on an early downstream emigration pattern is not known for OCCS populations (Jones 

et al. unpubl. manuscr.).

Migrant trapping studies have shown that substantial numbers of coho salmon fry may 

emigrate downstream from natal streams into tidally influenced lower river wetland and 

estuarine habitats (e.g., Chapman 1962, Koski 2009, Bass 2010). Observations of spring or early 

summer downstream migration of coho salmon fry were originally thought to represent a passive 

displacement in response to increased stream flows, competitive interactions, or capacity 

limitations. Chapman (1962) used the term nomads to characterize coho salmon juveniles 

moving downstream between emergence and early fall, which is well before typical smolt 

migration in the spring. However, little direct quantitative information exists on the relative 

proportions of coho salmon juveniles that use this life history pathway, the survival rates and 

capacity relationships involved, and the relative contribution to adult returns.

At least three discrete life history strategies involving downstream coho fry and presmolt 

migrations into lower river habitats have been identified in the literature (e.g., Sandercock 1991, 

Koski 2009):

 22 J. Power, EPA, Newport, OR. Pers. commun., May 2011. 23 See footnote 21. 24 See footnote 22.
99

• Late fall migration into side-channel or pond habitats connected to lower mainstem 

reaches from mainstem summer rearing habitats. For example, juveniles following this 

pattern had relatively high growth and overwinter survival rates in the freshwater sidechannel habitats in lower Clearwater River, a major tributary to the Queets River on the 

Washington coast (Peterson 1982). In Winchester Creek (a relatively short tributary 

draining into the South Slough of Coos Bay, Oregon), some of the coho salmon juveniles 

that had emigrated downstream and reared over the summer in the brackish portion of the 

creek migrated into off-channel beaver pond habitats to overwinter (Miller and Sadro 

2003). Similarly, Wallace and Allen (2009) determined that coho salmon juveniles rear 

through the summer in the tidal freshwater portions of Humboldt Bay tributaries. A 

portion of those juveniles emigrate into side-channel habitats for overwintering.

• Lower mainstem and estuarine summer rearing followed by upstream migration for 

overwintering. Skeesick (1970) documents upstream movements of coho salmon 

juveniles into overwintering habitats in three Oregon coastal streams including Munsell 

Creek in the tidal portion of the Siuslaw River. Koski (2009) also cites a number of 

studies that demonstrate fall movement of coho salmon juveniles into habitats with 

conditions conducive to overwintering survival.

• Lower mainstem and estuarine rearing followed by subyearling outmigration to ocean. A 

substantial number of subyearling coho in the Salmon River (Oregon coast) migrate 

downstream through the summer and early fall and rear in estuarine and freshwater tidal 

marsh habitats. Some of these juveniles may enter the ocean as subyearlings. Scale 

analyses conducted in one system, the Salmon River, indicated that the annual 

proportions of adult coho returning to the Salmon River that entered the ocean as 

subyearlings varied from 1% to 18% between 1993 and 2003 (Jones et al. unpubl. 

manuscr.). Future otolith analyses may provide estimates of relative adult return 

contributions from subyearlings that migrate directly to sea from upstream natal habitats 

versus those that may rear for an extended period in intertidal habitats prior to entering 

the ocean.

The relative contributions of these alternative life history pathways to either current or 

historical adult coho returns to Oregon coastal populations is not known. For example, 

numerous historic studies reporting age structure of adult coho salmon from scales very rarely 

find individuals that did not spend at least 1 year in freshwater prior to ocean entry (reviewed in 

Weitkamp et al. 1995). Few systematic surveys exist of the relative density and timing of 

juvenile coho rearing in upper and lower estuarine habitats for Oregon coastal drainages. 

Examples of Oregon coast stream and estuary ecotones cited by Koski (2009) include the upper 

3 km of Winchester Arm of South Slough of Coos Bay (Miller and Sadro 2003), Lint Slough 

(Garrison 1965), and the Salmon River (Cornwell et al. 2001). More recent work not reported in 

Koski has been done in the Salmon, Alsea, Siuslaw, Nestucca, and Yaquina rivers (Jones et al. 

unpubl. manuscr.), as well as Coos Bay (Bass 2010). ODFW has also sampled juveniles and 

smolts in these habitats in the Siletz, Yaquina, and Alsea river basins.25

Losses of intertidal habitat—Historical losses of tidal habitat are documented in two 

reports that summarize estimates of current and historical tidal wetland habitats within Oregon 

 25 See footnote 21.
100

coastal drainages with independent coho salmon populations (Good 2000, Adamus et al. 2005). 

Because the two assessments used different techniques to determine losses, the estimated 

quantities of wetland habitat loss were also different, although the two analyses yield similar 

trends among coastal basins (Table 21 and Figure 26).

Both assessments indicate that the historical ratio of estuarine and tidally influenced 

wetlands to total drainage area for the Coquille, Coos, and Tillamook basins were relatively high 

in comparison with other Oregon coastal drainages. The Umpqua River represents the largest 

single drainage on the Oregon coast and includes four independent populations. Adamus et al. 

(2005) estimated the highest proportion of historical lower river wetlands habitat in the Umpqua 

River, while the river ranked fourth among Oregon coastal drainages in total estuarine habitat in 

the Good (2000) analysis.

Table 21. Population or population aggregates with the largest estimated area of intertidal marsh habitat.

Rank Good (2000) Adamus et al. (2005)

1 Coos Bay Umpqua River

2 Coquille River Coquille River

3 Tillamook Bay Coos Bay

4 Umpqua River Tillamook Bay

0

2000

4000

6000

8000

10000

12000

North 

Coast 

(4/4)

Mid Coast 

(5/6)

Lakes 

(0/3)

Umpqua 

(4/4)

Mid-South 

Coast 

(2/4)

 

 

Loss

Restored

1970

0

5000

10000

15000

20000

25000

30000

North 

Coast 

(4/4)

Mid Coast 

(6/6)

Lakes 

(2/3)

Umpqua 

(4/4)

Mid-South 

Coast 

(4/4)

 

 

Loss

Restored

1970

Figure 26. Tidal estuary gains in strata of the OCCS ESU. The top plot reflects the Good 2000 analysis 

and the bottom plot reflects the Adamus et al. 2005 analysis.

Tidal habitat (acres) Tidal habitat (acres)
101

The amount of tidal wetland habitat available to support coho salmon migration, 

foraging, and rearing has declined substantially relative to historical estimates across all of the 

biogeographic strata (Table 21, Figure 26). The greatest historical losses (total area and 

proportional reduction) have occurred across populations in the North Coast and Mid-South 

Coast strata, driven by the relatively high proportional reductions in the largest estuaries. The 

time frame for contemporary estimates of tidal wetland areas differ between the two sources: 

Good (2000) reported values as of 1970, whereas Adamus et al. (2005) summarized wetland 

totals for the early 2000s. In addition to the direct losses, restriction of access to sections of tidal 

habitat and stream and estuary ecotone through the installation of tide gates (Bass 2010) has 

severely changed habitats available to outmigrating smolts relative to historical conditions. 

Overall, the results of recent coho salmon surveys imply that beyond the potential effects on the 

smolt rearing capacity of coastal basins, widespread estuarine and tidal freshwater wetland losses 

have also likely diminished the expression of subyearling migrant life histories within and 

among coho salmon populations.

Restoring and protecting intertidal habitat—Estuarine and tidal freshwater restoration

projects have been carried out in several drainages in more recent years. Additional wetland 

habitat that has become potentially available to juvenile salmon through these OWEB, USFWS, 

and USFS projects are incorporated in Table 22. If aggregated across OCCS independent 

populations, recent restoration efforts have targeted a total area equivalent to 14−20% of current 

baseline of tidal habitat (Table 22). The largest increase has been in the Mid-South Coast 

stratum (Coos Bay and Coquille Bay), with a 28−37% aggregate increase in potential intertidal 

rearing habitat. The North Coast (11−14%) and Mid-Coast (11−19%) strata also had relatively 

large proportional increases. Intertidal habitat gains in a small basin, the Nestucca River, 

accounted for the change in the aggregate North Coast area total. Likewise, the Mid-Coast 

stratum increase was accounted for largely by changes in the Salmon River. These gains 

notwithstanding, the proportional change in the total amount of available intertidal habitat after 

adding in gains through recent restoration efforts is small relative to historical conditions (Table 

22). In addition to the restoration actions, approximately 2,900 acres of existing high quality 

intertidal or adjacent riparian habitat has been afforded protection through OWEB fee title and 

conservation easement programs in recent years.26

Table 22. Summary of recent restoration versus current and historical estimates of intertidal marsh 

habitats aggregated across populations within OCCS ESU biogeographic strata.

Recent restoration vs. 

current (%)

Recent restoration vs. 

historical (%)

Biogeographic 

strata

Good 

2000

Adamus et al. 

2005

Good 

2000

Adamus et al. 

2005

North Coast 14 11 0.03 0.02

Mid-Coast 19 11 0.07 0.04

Umpqua 2 2 0.01 0.01

Mid-South Coast 37 28 0.07 0.03

Total 20 14 0.05 0.02

 26 M. Hulst, OWEB, Salem, OR. Pers. commun., 15 October 2010.
102

The OCCS biological recovery criteria directly considered the status of tidally influenced

habitats at the population and ESU levels as an indication of remaining diversity (Wainwright et 

al. 2008). Two of the component criteria in the DSS are informed by measures of the relative 

status of tidally influenced habitats. The workgroup noted that while it was clear that estuarine 

habitat conditions have changed relative to historical conditions, it is difficult to determine the 

degree to which those changes have affected fish.

Future threats to OCCS from loss of estuarine and freshwater tidal habitat may also come 

in the form of sea level rise in Oregon’s estuaries (NWF 2007, OCCRI 2010). Although recent 

restoration efforts have increased the amount of estuarine habitats suitable for coho rearing, it is 

uncertain whether gains can continue to be realized in light of the potential impact of sea level 

rise. If the human response to sea level rise is to raise the protection level of dikes and levees, 

then there would likely be widespread loss of tidal habitat because the opportunity for tidal 

marshes, swamps, and mudflats to move to higher ground will be blocked by protection 

structures and basin topography. Tidal marshes and mudflats are substantial contributors to the 

estuarine food chain in direct and indirect ways (Gray 2005, Chapman et al. in prep.). Loss of 

more tidal habitats through sea level rise could have a negative effect on feeding and rearing of 

OCCS in estuarine and tidal freshwater habitats.

The current biological status of Oregon coastal coho populations reflects the effects of 

estuarine tidal habitat loss relative to historical conditions, including the potential impacts of the 

associated diminished life history diversities. With an increasingly variable marine ecosystem, 

this loss of life history diversity may constitute a future threat, particularly for production from 

smaller tributaries associated with relatively large estuaries. It is difficult to quantify the 

potential impact of those losses, given the current uncertainty regarding the historical 

contributions from the various life history patterns.

Land management—loss/gain of freshwater wetland habitat

Determining the freshwater wetland losses outside estuaries in each population of the 

OCCS ESU is not possible with the data sets available at present. There have been estimates of 

estuarine wetland losses in several studies (Good 2000, Christy 2004, Adamus et al. 2005). All 

have differing estimates, probably from the use of differing data and methodologies. As an 

example of the severity of the losses, Christy (2004) found that the estimated total acres of 

wetlands in estuaries in the OCCS ESU that were converted to other uses from 1850 to 2000 was 

estimated at 43,672 acres. Of these losses, freshwater wetlands were highest with 34,276 acres, 

salt marsh losses were next with 9,383 acres, lake-associated wetlands were reduced by only 13 

acres, and subtidal habitat had zero acres of loss. Of course, these numbers do not reflect any 

losses upstream of the estuaries.

For somewhat recent losses and gains to wetlands in the OCCS ESU, Table 23 (ODSL 

2005) details the information available at the time. This analysis is not restricted to just estuarine 

wetlands, so is not comparable to Christy (2004), but shows continued wetland loss to filling 

activities as well as restoration of wetlands in counties occupied by the OCCS ESU.

More recent requests for information (2007−2008) from the Oregon Department of State 

Lands (ODSL) permit tracking system reported 12.5 acres of freshwater and estuarine wetlands 
103

Table 23. Oregon Department of State Lands (ODSL) summary of wetland fill, compensatory wetland 

mitigation (CWM), enhancement and restoration, and OWEB-funded restoration projects 

(nonmitigation) authorized/completed from 1 July 2000 to 30 June 2004 in acres. (Reprinted 

from ODSL 2005.)

County

Wetland fill 

permitted by ODSL 

(county area)

CWM required by 

ODSL* (county area)

OWEB-funded wetland 

restoration projects 

(nonmitigation) (ESU)

Clatsop 5.2 4.3

Coos 9.0 20.1

Douglas 41.2 90.1 30 (Dawson Creek)

Lane 48.7 44.4 30 (Enchanted Valley)

Lincoln 0.3 0.4 70 (Lint Slough)

Tillamook 0.6 1.8

Totals 105.0 161.2 130

* Creation, enhancement, or restoration.

lost, 9.6 acres gained, and 46.21 acres enhanced in the counties of the ESU.27 There are still 

wetland losses occurring, and some wetland gains being made, but probably not at the scale that 

historical freshwater wetlands (just in estuaries) were lost. Substantial development of data and 

historical reconstructions are necessary before the true magnitude of wetland losses throughout 

the OCCS ESU are understood.

The results of coho salmon habitat surveys (ODFW 2009b), however, imply that loss of 

wetlands throughout the ESU has had a significant effect on rearing capacities of coastal basins, 

not just in estuaries. These losses may originate from, to name a few, stream incision and loss of 

connection with the floodplain, filling and diking of wetlands for agriculture and urban 

development, and loss of beaver-engineered wetlands due to trapping and disease. This, in 

addition to estuarine losses, may also have diminished the nomad life history in OCCS 

populations due to loss of slow water rearing areas.

Although it is apparent that wetland losses in estuaries have slowed and in some basins 

reversed, losses in freshwater wetlands upstream of the estuaries in the ESU are difficult to 

quantify. Some information about recent losses is available through the ODSL permit tracking 

system, but studies of historic freshwater wetland losses are either too large scale for usefulness, 

or restricted to the Willamette and Klamath basins (Morlan 2000). Many of the freshwater 

wetlands important to coho salmon are not inventoried because they are outside the wadeable 

stream restriction for the ODFW aquatic habitat surveys. Because wetlands are so important to 

coho rearing (Nickelson 1998, Burnett et al. 2003), lack of information regarding these offchannel and slow water areas constitutes a risk in making future management decisions without a 

robust understanding of OCCS life cycle and utilization of these habitats. The BRT considered 

that freshwater wetland losses were probably reflected in the current biological status of the 

species. Because the potential magnitude of future freshwater wetland losses is poorly 

understood, the scale of the future threat to the OCCS ESU is uncertain.

 27 J. Vaughn, ODSL, Salem, OR. Pers. commun., December 2009.
104

Land management—mining

Mining in general and gravel mining in particular were identified as factors for decline by 

NMFS (1997c). Until recently, gravel mining, particularly in the Umpqua River and Tillamook 

River basins, has been a serious concern in the past to fishery managers and remains a concern in 

the Coquille River. Providing for fisheries in gravel mining operations has been the subject of 

substantial effort for protection of all anadromous salmonids in the Umpqua stratum. At this 

point in time, there are no active instream gravel mining operations in the Umpqua; however, 

there are continuing operations in the Tillamook and Nehalem basins in the North Coast stratum. 

There is a concern that if ESA protections are removed, instream gravel mining operations could 

become a serious threat to the OCCS ESU in the future. The BRT considered that the effects of 

mining were probably reflected in the current biological status of the species. However, because 

the potential for future gravel mining activities are poorly understood, the scale of the future 

threat to the OCCS ESU is uncertain.

Land management—water quality degradation

Water quality has long been identified as a factor for decline (NMFS 1997a) and a 

limiting factor for recovery (Oregon 2005) for OCCS. Water quality is made up of many facets 

that were presented in NMFS (1997c), ODEQ (2005), and Oregon (2005). Table 15 lists the 15 

populations where water quality is an important limiting factor.

In 2005 the Oregon Department of Environmental Quality assessed the situation in the 

OCCS ESU:

Water quality improvements in an area like the coastal coho ESU—where the 

problems largely relate to nonpoint source pollution and flow and channel 

modification—take time. At this time, we are not able to demonstrate an 

improving trend in water quality, but there are some indications that 

improvements will occur. One sign of progress is reflected in the on-the-ground 

efforts of landowners and others and the partnerships being forged to conduct 

total maximum daily loads implementation activities (ODEQ 2005).

For the purposes of this status review, the focus is on temperature limitations within the

ESU because of temperature’s important effect on coho salmon success in freshwater. For an 

overview of water quality status of the OCCS ESU streams, Figure 27 shows a substantial 

amount of the streams and rivers in the ESU as water quality limited. Category 5 shows 

impairment by one or more pollutants and Category 4 shows that the reach is impaired but has an 

approved total maximum daily loads management plan. The mileage of impairments in the 

OCCS ESU is difficult to assess because impairments of stream reaches may be different and 

overlap. However, as illustrated in Figure 28 (ODEQ 2007), the temperature impairments in the 

OCCS ESU are 40% of OCCS distribution stream miles.

It can be argued that water temperature is the primary source of water quality impairment 

in the OCCS critical habitat. Welsh et al. (2001) found in the Mattole River, California, that 

juvenile coho were not found in streams with mean weekly average temperatures greater than 

18°C, and that all streams in their study area with mean weekly average temperatures below 

14.5°C held juvenile coho. Temperatures above about 15°C stress salmon in a variety of ways. 
105

Figure 27. EPA 303(d) water quality impaired waters.
106

Figure 28. EPA 303(d) listed streams with temperature impairment.
107

At higher temperatures, metabolic rates are higher so fish must forage more actively to maintain 

growth rates. This adds stress if the food supply is limited and forces fish to be more exposed to 

predators. Dissolved oxygen is lower at higher temperatures, further stressing the fish. Many of 

the diseases to which salmon are susceptible occur at higher rates as temperatures increase

(Marcogliese 2001, 2008). These include fungal infections such as Columnaris, which can cause

mortality in juveniles and returning adults.

Temperature has been negatively correlated with coho salmon survival and abundance in 

freshwater (Lawson et al. 2004, Crozier et al. 2008b). Temperature effects operate through a 

wide variety of mechanisms; beaver pond wetlands tend to moderate water temperatures, 

parasites are more virulent at higher temperatures (Lawson et al. 2004), and life cycle timing can 

be disrupted at higher temperatures, potentially leading to a mismatch between smolt 

outmigration timing and onset of upwelling in spring (Crozier et al. 2008b). Higher temperatures 

in the summer limit the quantity of stream habitat that is available for juvenile salmon rearing, 

while high temperatures in the fall can block adult migrants from reaching spawning grounds 

(Ebersole et al. 2006). The broad conclusion is that the rising temperatures anticipated with 

global climate change will have an overall negative effect on the status of the ESU. If 40% of 

the OCCS ESU is already temperature impaired (ODEQ 2007), just the effects of climate change 

in the absence of threats from other human activities like forestry and agriculture pose a 

significant risk to those systems already impaired, and increase the likelihood of temperature 

impairment in the rest of the aquatic systems in the ESU. The BRT considered that the effects of 

current water quality impairment were probably reflected in the current biological status of the 

species. Because of the expected effects of global climate change on OCCS habitat, water 

quality was considered a significant future threat to the OCCS ESU.

Disease or Predation

Disease and parasitism

In its assessment of OCCS, ODFW (2005b) asserted that disease is not an important 

consideration in the recovery of OCCS. However, Jacobson et al. (2003, 2008) identified 

Nanophyetus salmincola as a potentially important source of early marine mortality. Cairns et al. 

(2005) have also shown that “the direct effects of temperature associated with increased 

metabolic demand can be exacerbated by other factors, including decreased resistance to disease 

and increased susceptibility to parasites.” Jacobson (2008) reports that annual parasite 

prevalences of N. salmincola in yearling coho salmon caught in ocean tows off the coast of 

Oregon were 62−78%. Yearling coho had significantly higher intensities of infection and higher 

infection in wild versus hatchery juveniles, presumably due to the greater exposure to 

metacercaria in natal streams. Parasite prevalences and intensities of yearling coho salmon 

caught in September were significantly lower (21%) than those caught in May or June in 3 of 4 

years of data. This suggests parasite-associated host mortality during early ocean residence for 

yearling coho salmon. Pearcy (1992) hypothesized that ocean conditions (food and predators) 

are very important to marine mortality, especially soon after the juveniles enter the ocean. This 

is the time period that Jacobson et al. (2008) observed the loss of highly infected juveniles. 

Jacobson hypothesizes that high levels of infection may lead to behavioral changes in the fish 

and thus make the juveniles more susceptible to predation.
108

The issue that Cairns et al. (2005) investigated is the influence of summer stream 

temperatures on black spot infestation of juvenile coho salmon in the West Fork of the Smith 

River, Oregon, in the OCCS ESU. Their studies show that, “although other environmental 

factors may affect the incidence of black spot, elevated water temperature is clearly associated 

with higher infestation rates in the West Fork of the Smith River stream network.” This may be 

an important issue for coho salmon juveniles, as many of the streams they inhabit are already 

very close to lethal temperatures during summer months (see Figure 28) and, with the 

expectation of rising stream temperatures due to global climate change, changes in metabolic 

rates may act as a stressor that may result in higher infection rates in coho salmon.28 Changes in 

infection rates of juvenile coho by parasites as well as new parasites associated with invasive 

species may become an increasingly important stressor for freshwater and marine survival.

Parasitism and disease was not considered an important factor for decline in early status 

reviews for OCCS. However, some of the studies discussed above suggest that it may become 

more important as temperatures rise due to global climate change and may become a very 

important risk for juveniles in the early ocean entry stage of the life cycle. The BRT considered 

that the effects of disease and parasitism were probably reflected in the current biological status 

of the species. However, because of the expected temperature effects of global climate change 

on OCCS freshwater habitat, disease and parasitism was considered a potential future threat to 

the OCCS ESU.

Predation

Due to the visibility of predators and their interactions with resource users in freshwater

and salt water, predators are often mentioned by stakeholder groups as a serious threat to OCCS 

populations (ODFW 2005g). Fresh (1997) concluded that predation was probably not a primary 

factor in OCCS population declines. IMST (1998) examined the question of predation and 

concluded that salmon have evolved with predators and that, despite the presence of many kinds 

and large numbers of predators, coho salmon have persisted over many millennia. It notes that 

there is variability in predators over time depending on ocean conditions, the size of the predator, 

and availability of salmon juveniles. It also concluded that when populations are low, however, 

predation can have a significant effect on extinction risk.

Birds and marine mammals—Cormorants (Phalacocrorax spp.), terns (Sterna spp.), 

brown pelicans (Pelecanus occidentalis), sooty shearwaters (Puffinus griseus), common murres

(Uria aalge), mergansers (Mergus spp.), gulls (Larus spp.), belted kingfishers (Megaceyle 

alcyon) grebes and loons (Gavia spp.), herons (Family Ardeidae) ospreys (Pandion haleaetus) 

and bald eagles (Haliaeetus leucocephalus) all prey on juvenile salmonids in the OCCS ESU to 

one degree or another (IMST 1998). In the Columbia River estuary just adjacent to the OCCS 

ESU, terns and double-crested cormorants have been shown to affect juvenile salmonid survival 

significantly (Collis et al. 2002, Roby et al. 2003, Antolos et al. 2005). However, river basins in 

the OCCS ESU do not have dredge spoil islands to attract large tern and double-crested 

cormorant colonies. Neither do they have an extended time period of juvenile salmonid 

outmigration similar to the Columbia River system.

 28 Although Bisson and Davis (1976) found that elevated temperatures reduced infestation rates by Nanophyetus on 

juvenile Chinook salmon.
109

Predation by avian predators may, however, be important in the loss of salmonid 

juveniles in some populations in the ESU. In a study of steelhead outmigrants in the Nehalem 

River, Schreck et al. (2002) observed substantial mortality of juvenile steelhead in the estuary, 

presumably from predation by double-crested cormorants, Caspian terns, and harbor seals

(Phoca vitulina). More recently, Johnson et al. (2010) observed mortality rates on naturally 

reared steelhead juveniles as high as 53% in the Alsea River, mainly in the lower estuary and 

presumably from avian predation and harbor seals. Neither study, however, demonstrated direct 

evidence of predation by any particular predator. Bass (2010) in Coos Bay was able to 

demonstrate predation on OCCS juveniles by double-crested cormorants by utilizing PIT tag 

detections of deposits below the rookery. These were smolts that he had tagged for a study on 

the effect of tide gates on juvenile coho salmon movement.

The common murre is the most abundant seabird in the OCCS ESU, but does not appear 

to have a significant impact on juvenile salmonids in the nearshore at present. The common 

murre breeding population on the north coast of Oregon has been severely affected by bald eagle 

predation. They have abandoned their nesting sites on the north coast rocks. Murres therefore 

are not feeding on juveniles from those coho salmon populations in the large concentrations that 

they would if they were breeding on the nearshore rocks.29 Other species have shown substantial 

increases in population levels, particularly Caspian terns and double-crested cormorants in the 

lower estuary of the Columbia River (Collis et al. 2002). However, outside of the Columbia 

River system, Adkins and Roby (2009) report that there were 2,384 breeding pairs of doublecrested cormorants nesting at 22 colony sites along the Oregon coast. This is similar to the 1992 

estimate of 1,850 breeding pairs in 13 colonies (Carter et al. 1995), so there is no reason to 

believe that substantially higher abundance in double-crested cormorant populations has 

contributed significantly to OCCS population declines in recent years.

Because of the increasing abundance and visibility of marine mammal predators since the 

passage of the Marine Mammal Protection Act, there is a perception among users of the estuarine 

and marine environment that reducing predation by harbor seals and California sea lions 

(Zalophus californianus) is important for the restoration of OCCS (Smith et al. 1997). Botkin et 

al. (1995) concluded that marine mammal predation on anadromous fish stocks in northern 

California and southern Oregon was only a minor factor for their decline. NMFS (1997d) also 

examined the issue and determined that marine mammal predation in some northwest fisheries 

has increased on the Pacific Coast. This predation may significantly affect salmonid abundance 

in some local populations when other prey are absent and physical habitat conditions lead to the 

concentration of adults and juveniles in restricted areas or stocks.

IMST (1998) concluded “that the California sea lion, Pacific harbor seal, Caspian tern, 

and cormorant populations along the Oregon coast have all increased in recent years, coinciding 

with historic lows in salmon abundance. Predation by these species may be a factor in the lack 

of recoveries of some depressed stocks, but there is no compelling scientific evidence that 

predation has been a primary cause for decline of salmonids.” In the 2005 Oregon State Coho 

Assessment, ODFW (2005h) reported that there is little new evidence that allows analysis 

beyond the summary statements made by NMFS (1997d) and IMST (1998). It said the result of 

 29 R. Lowe, U.S. Fish and Wildlife Service, Oregon Coastal Refuges, Newport, OR. Pers. commun., September 

2010.
110

future investigations is “not likely to change the general conclusion that, while negative effects 

can occur in specific situations where other prey is in unusually low abundance, local predator 

numbers are high and restrictions in passage or reduction in habitat quality have all increased

predation success, natural predation by pinnipeds or seabirds has not been a significant cause in 

the decline of salmonid stocks at the ESU scale.”

A recent study by Brown et al. (2005) reports that though the abundance of harbor seals 

has increased since the passage of the Marine Mammal Protection Act, the Oregon and 

Washington harbor seal population grew rapidly until the 1990s but appears to be stable around 

an equilibrium with variability due to ocean conditions. Whether or not the harbor seal 

population is growing, Schreck et al. (2002) (Nehalem River) and Johnson et al. (2010) (Alsea 

River) implicate harbor seals as well as birds in significant (29−66%) loss of juvenile steelhead. 

Avian and mammalian predation may not have been a significant factor for decline when 

compared with other factors, but this more recent work shows that it may be important to 

recovery actions in certain populations and specific situations within the OCCS ESU.

Nonindigenous fish—In contrast to mammalian and avian predators, OCCS have not 

evolved with NIS fish. Fish predation can be a significant source of mortality of coho salmon 

juveniles, particularly in lake and slow water systems. Largemouth bass and smallmouth bass 

are particularly efficient predators of juvenile coho salmon30 (Bonar et al. 2004).

Lake-rearing coho salmon represent life history diversity that is essential to the resilience 

of OCCS (Lawson et al. 2007). While river populations exhibited wild swings in abundance 

during the low return years of the 1990s, lakes produced consistent returns during that time 

period. However, the change in productivity of the Tenmile Lakes system in the 1970s shows 

the effect of NIS fish on OCCS. High abundance was observed from 1955 to 1973 when adult 

spawners ranged from about 5,700 to 42,000 adults. The Tenmile Lakes escapement from 1974 

to 1999 after introduction of NIS warm water fishes and treatment with rotenone to rid the lake 

of them fell to an average of only 3,453 (777 to 7,581) (Zhou 2000). Current returns in the

Tenmile Lakes system remain substantially lower than returns prior to the introduction of NIS 

fish. For Siltcoos and Tahkenitch lakes, which had introductions of these warm water game fish 

in the 1930s, it is impossible to discern changes due to lack of data. The effects of these NIS fish 

are not consistent across the landscape of the OCCS ESU; the North Coast and Mid-Coast 

monitoring areas have some introduced fish species, but they do not have much in the way of 

lakes and slow water like the Lakes, Umpqua, and Mid-South Coast strata. Also, higher summer 

temperatures in these more southerly systems favor NIS fish (ODFW 2005f). This effect is 

expected to increase with rising temperatures in the lakes and slow water areas of the Oregon 

coast.

EPA (2009) commented that NIS fish are capable of ecosystem changing effects as well 

of those of predation. NIS warm water fishes pose a future threat to coho rearing due to 

ecosystem change as well as predation if anticipated temperature rise associated with global

climate change occurs. Peer reviewer 2 (reference Appendix D) commented that predation and 

competition, particularly in light of the warming water temperatures from global climate change, 

could significantly affect the lakes and slow water rearing life history of OCCS, not only by NIS 

 30 Reported by BRT member L. Kruzic, December 2009.
111

fish but by native invasions as well (Reeves et al. 1998). As water temperatures increase, NIS 

warm water and other native fish will be at an even greater advantage over OCCS in lake and 

slow water situations due to predation, competition, and ecosystem alterations.

For this analysis on the current status of the effect of predation, effects of current 

populations of NIS warmwater fish are probably reflected in the OCCS current biological status 

of these populations. However, in anticipating future conditions, as water temperatures increase 

there is greater risk to OCCS in lake and slow water situations due to predation, competition, and 

ecosystem alterations. This effect on the slow water and lake life histories of OCCS may present 

a significant threat to diversity of the species.

Summary of Factors for Decline and Threats

As described above, the BRT analysis started with the list of major threats previously 

identified by the NMFS NWR and revised it to include discussion of emerging issues such as 

global climate change. Some threats, in particular hatchery production and harvest, have been 

greatly reduced over the last decade and appear to have been largely eliminated as significant 

sources of risk. Other factors, such as habitat degradation and water quality, were evaluated to 

be ongoing threats that appear to have changed little over the last decade. Changes to freshwater 

and marine habitat due to global climate change were considered threats likely to become 

manifest in the future. A summary of the threats considered by the BRT is found in Table 24.
112

Table 24. BRT summary comments on threats.

2009 BRT threats Comments

Agriculture and forestry

Splash dams Legacy effects on stream complexity.

Human landscape disturbance Effects constitute an ongoing threat.

Roads Existing and legacy roads can contribute to continued stream 

degradation, could constitute a future threat.

Stream cleaning Legacy effects on stream complexity.

Substrate sediment See stream habitat complexity analysis.

Stream habitat complexity Habitat complexity and summer parr capacity are decreasing in the 

Umpqua but increasing in the other strata. Winter parr capacity is 

trending flat in the North Coast and Mid-Coast, but declining in the 

Mid-South and Umpqua strata. For the percent of fine sediment in 

riffles, there appear to be declines in the North and Mid-Coast, a 

positive trend in the Mid-South, and little change in the Umpqua 

strata. Large wood volume appears to be declining in the North 

Coast and Umpqua, while increasing in the Mid-Coast and MidSouth strata. LWD trends in upstream areas declined substantially 

in all strata. Trends in sediment were mixed, with increases in the 

Mid-Coast and Mid-South and declines in the North Coast and 

Umpqua strata.

Water temperature, water 

quality degradation

Because of the expected effects of global climate change (especially 

temperature), water quality was considered a significant future 

threat.

Estuary, wetland habitat loss With an increasingly variable marine ecosystem and sea level rise, 

loss of life history diversity may constitute a future threat.

Water availability Future impacts to water availability from effects of population 

growth; global climate change may constitute a future threat.

Beaver dam loss due to effect 

on local stream complexity

Lack of protection of beavers and degraded beaver dam density 

levels is an ongoing threat.

Fish passage restriction Incomplete data in important OCCS habitat is a significant 

information gap to some BRT members.

Gravel mining Because the potential for future gravel mining activities are poorly 

understood, the scale of the future threat is uncertain.

Land use conversionurbanization, rural residential

Floodplain functions

Instream wood

Substrate sediment

Storm water

Future conversions of lands to urban, suburban, and agriculture use 

are dependent on many factors and are therefore uncertain. Some 

BRT members felt that urbanization did not present a significant 

future threat. Other members believed that urbanization and rural 

residential development retards advances in recovering important 

OCCS habitat in locations like Tillamook Bay and Coos Bay. 

Some members considered that conversion of agriculture and 

forests to urban and rural residential land uses results in a 

disproportional impact to high potential coho salmon habitat. The 

effects of conversion of land to uses with levels of impervious 

surface above 15% within a watershed were considered a potential 

future threat with uncertain magnitude.
113

Table 24 continued. BRT summary comments on threats.

2009 BRT threats Comments

Disease and parasitism Because of the expected temperature effects of global climate 

change on OCCS freshwater habitat, disease and parasitism was 

considered a potential future threat.

Predation May be important to recovery actions in certain populations and 

specific situations.

Harvest Further harvest reductions would have little effect on spawning 

escapements. Future remedies must be found outside of harvest 

management until the decline in productivity is reversed.

Artificial propagation Reduction in hatchery activity is expected to significantly benefit 

wild runs throughout the ESU.

Global climate change It was noted that there are some expected positive effects; however, 

negative effects of climate change predominate for each habitat and 

life history stage. While many of the individual effects of climate 

change on OCCS are expected to be weak or are uncertain, we must 

consider the cumulative impacts across the coho salmon life-cycle 

and across multiple generations. Because these effects are 

multiplicative across the life cycle and across generations, small 

effects at individual life stages can result in large changes in the 

overall dynamics of populations. This means the mostly negative 

effects predicted for individual life history stages will most likely 

result in a substantially negative overall effect of climate change on 

OCCS over the next few decades. Despite large uncertainties 

surrounding specific effects at individual life stages, expectations 

for increasing air and water temperatures, drier summers, higher 

incidence of flooding, and altered estuarine and marine habitats, 

lead us to expect increasingly frequent years with low survival, 

resulting in an overall increase in risk to the ESU resulting from 

climate change over the next 50 years.

Marine productivity BRT concluded that the coastal ocean ecosystem on which coho 

salmon depend is in an unpredictable state of flux.

Drought Addressed in global climate change.

Floods Addressed in global climate change.

Wildfire Addressed in global climate change.

Tsunami Not considered.

NIS May affect stream complexity; invasions by NIS and subsequent 

ecosystem changes may constitute a future threat. Effects of NIS 

fish are expected to increase with rising temperatures in lakes and 

slow water areas.
114

Overall Risk Assessments

The BRT’s determination of overall risk of extinction to the OCCS ESU used the three 

categories of high risk, moderate risk, and low risk (not at risk). The high and moderate risk 

levels were defined by the NMFS NWR in its status review request as follows:

Moderate risk: A species or ESU is at moderate risk of extinction if it exhibits a 

trajectory indicating that it is more likely than not to be at a high level of 

extinction risk. A species/DPS [distinct population segment] may be at moderate 

risk of extinction due to projected threats or declining trends in abundance, 

productivity, spatial structure, or diversity. The appropriate time horizon for 

evaluating whether a species or DPS is more likely than not to be at high risk 

depends on the various case-specific and species-specific factors. For example, 

the time horizon may reflect certain life history characteristics (e.g., long 

generation time or late age-at-maturity) and may also reflect the time frame or 

rate over which identified threats are likely to impact the biological status of the 

species or DPS (e.g., the rate of disease spread). The appropriate time horizon is 

not limited to the period that status can be quantitatively modeled or predicted 

within predetermined limits of statistical confidence.

High risk: A species or ESU with a high risk of extinction it is at or near a level of 

abundance, productivity, or spatial structure that place its persistence in question. 

The demographics of a species/DPS at such a high level of risk may be highly 

uncertain and strongly influenced by stochastic or depensatory processes. 

Similarly, a species/DPS may be at high risk of extinction if it faces clear and 

present threats (e.g., confinement to a small geographic area, imminent 

destruction, modification or curtailment of its habitat, or disease epidemic) that 

are likely to create such imminent demographic risks.

Quantitative and qualitative conservation assessments for other species have often used a 

100-year time frame in their extinction risk evaluations (McElhany et al. 2000, Morris and Doak 

2002) and the BRT adopted this time scale as the period over which it had confidence in 

evaluating risk. In particular, the BRT interpreted the high risk category as a greater than 

approximately 5% risk of extinction within approximately 100 years, and the moderate risk 

category as a greater than 50% risk of moving into the high risk category within 30–80 years. 

Beyond the 30–80 year time horizon, the projected effects on OCCS viability from climate 

change, ocean conditions, and trends in freshwater habitat become very difficult to predict with 

any certainty. The overall extinction risk determination reflected informed professional 

judgment by each BRT member, based on the quantitative and qualitative information reviewed 

in this report. This assessment was guided by the results of the risk matrix analysis (see below), 

supplemented by results from the DSS (Table 7), and integrating information about demographic 

risks with expectations about likely interactions with threats and other factors.
115

Risk Matrix Approach

In previous NMFS status reviews, BRTs have used a risk matrix as a method to organize 

and summarize the professional judgment of a panel of knowledgeable scientists. This approach,

described in detail by Wainwright and Kope (1999), has been used for more than 10 years in 

Pacific salmonid status reviews (e.g., Good et al. 2005, Hard et al. 2007), as well as in reviews of 

Pacific hake, walleye pollock (Theragra chalcogramma), Pacific cod (Gadus macrocephalus) 

(Gustafson et al. 2000), Puget Sound rockfishes (Stout et al. 2001a, Drake et al. 2010), Pacific 

herring (Clupea pallasii) (Stout et al. 2001b, Gustafson et al. 2006), eulachon (Thaleichthys 

pacificus) (Gustafson et al. 2010), and black abalone (Haliotis cracherodi) (VanBlaricom et al.

2009).

In this risk matrix approach, the collective condition of individual populations is 

summarized at the ESU level according to four demographic risk parameters: abundance, growth 

rate/productivity, spatial structure and connectivity, and diversity (Table 25). These viability 

parameters, outlined in McElhany et al. (2000), reflect concepts that are well founded in 

conservation biology and are generally applicable to a wide variety of species. They describe 

demographic risks that individually and collectively provide strong indicators of extinction risk. 

The summary of demographic risks and other pertinent information obtained by this approach is 

then considered by the BRT in determining the species’ overall level of extinction risk.

After reviewing all relevant biological information for the species, including the threats 

currently impacting the ESU or reasonably certain to impact the ESU in the future, each BRT 

member assigned a risk score (Table 25) to each of the four parameters. The scores were tallied 

(means, modes, and range of scores), reviewed, and the range of perspectives discussed by the 

BRT before making its overall risk determination. Although this process helped to integrate and 

summarize a large amount of diverse information, there was no simple way to translate the risk 

matrix scores directly into a determination of overall extinction risk. For example, an ESU with 

a single extant population might be at a high level of extinction risk because of high risk to 

spatial structure and connectivity, even if it exhibited low risk for the other parameters. Another 

species might be at risk of extinction because of moderate risks to several parameters.

To allow individuals to express uncertainty in determining the overall level of extinction 

risk facing the species, the BRT adopted the likelihood point method, often referred to as the 

FEMAT (Forest Ecosystem Management Assessment Team) method because it is a variation of 

a method used by scientific teams evaluating options under the Northwest Forest Plan (FEMAT 

1993). In this approach, each BRT member distributes 10 likelihood points among the 3 

extinction risk categories, reflecting his or her opinion of how likely that category correctly 

reflects the true species status (Table 26). Thus if a member were certain that the species was in 

the low risk (not at risk) category, he or she could assign all 10 points to that category. A 

reviewer with less certainty about the species’ status could split the points among two or even 

three categories. This method has been used in all status reviews for anadromous Pacific 

salmonids since 1999, as well as in reviews of Puget Sound rockfishes (Stout et al. 2001a, Drake 

et al. 2010), Pacific herring (Stout et al. 2001b; Gustafson et al. 2006), Pacific hake, walleye 

pollock, Pacific cod (Gustafson et al. 2000), eulachon (Gustafson et al. 2010), and black abalone 

(VanBlaricom et al. 2009.)
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Table 25. Risk Matrix template used by the BRT to capture comments and assessment of risk. Risks for 

each VSP parameter are ranked on a scale of 1 (very low risk) to 5 (very high risk).*

Risk assessment matrix

Risk category Risk score

Abundance

Comments:

Growth rate/productivity

Comments:

Spatial structure and connectivity

Comments:

Diversity

Comments:

*The rankings are defined as follows.

1. Very low risk: It is unlikely that this factor contributes significantly to risk of extinction, either by itself or 

in combination with other factors.

2. Low risk: It is unlikely that this factor contributes significantly to risk of extinction by itself, but there is 

some concern that it may, in combination with other factors.

3. Moderate risk: This factor contributes significantly to long-term risk of extinction, but does not in itself 

constitute a danger of extinction in the near future.

4. High risk: This factor contributes significantly to long-term risk of extinction and is likely to contribute to 

short-term risk of extinction in the foreseeable future.

5. Very high risk: This factor by itself indicates danger of extinction in the near future.

Table 26. FEMAT voting sheet. Each of 13 BRT members allocated 10 likelihood points among the three 

status categories. The numbers allocated across the categories should add up to 10 points. Low 

risk category = not at risk.

ESU is at high risk ESU is at moderate risk ESU is at low risk Total = 10 pts.
117

In its May 2010 draft report, the BRT reported the risk assessment matrix analysis and 

the overall extinction risk assessment that was conducted under two different sets of 

assumptions. First, the BRT evaluated extinction risk based on the demographic risk parameters

(abundance, growth rate/productivity, spatial structure and connectivity, and diversity) recently 

exhibited by the ESU, assuming that the threats influencing ESU status would continue 

unchanged into the future. This case in effect assumed that all of the threats evaluated in the 

previous section of the report were already fully manifest in the current ESU status and would in 

aggregate neither worsen nor improve in the future. In the 2010 draft report, the BRT also 

evaluated extinction risk based on the demographic risk criteria currently exhibited by the ESU, 

taking into account consideration of predicted changes to threats that the BRT evaluated to be 

not yet manifest in the current demographic status of the ESU. In effect, this scenario asked the 

BRT to evaluate whether threats to the ESU would lessen, worsen, or remain constant compared 

to current conditions.

In the time since the completion of the last risk assessment in 2010, the BRT considered 

additional information on the potential magnitude and trajectory of threats including climate 

change, changes in ocean conditions, and trends in freshwater habitat. The BRT also further 

refined the time horizon used to evaluate whether the OCCS ESU was at moderate risk of 

extinction. Considering this new information, the BRT felt it unnecessary and potentially 

confusing to conduct the risk assessment under multiple sets of assumptions. For the final risk 

assessment reported here, therefore, each BRT member evaluated all the available information 

on current demographic status and threats to come to a single overall conclusion on the degree of 

extinction risk.

Summary of Risk Conclusions

The mean risk matrix scores for each demographic risk factor fell between the low risk 

(not at risk) (2) and moderate risk (3) categories (Table 27), indicating that the BRT as a whole 

did not consider any of the demographic risk parameters as likely to contribute substantially to a 

high risk of short-term extinction when considered on its own. The overall assessment of 

extinction risk to the OCCS ESU, taking into account both the demographic risk parameters and 

an evaluation of threats, indicated considerable uncertainty about its status; most likelihood 

points were evenly split between moderate risk and low risk at 47% each, and a small minority of 

points amounting to 6% indicated high risk.

That lack of a strong mode in the overall assessment of risk (6%, 47%, 47%) and the 

large range in the demographic risk scores (Table 27) were indicative of considerable uncertainty 

Table 27. Assessment of the risk associated with each of four demographic factors. Risks for each 

demographic factor are ranked on a scale of 1 (very low risk) to 5 (very high risk).

Abundance

Growth rate/

productivity

Structure and 

connectivity Diversity

Mean 2.21 2.63 2.33 2.67

Median 2 3 2 2.75

Minimum 1 2 1 2

Maximum 4 3.5 4 4
118

within and among BRT members about the current level of risk facing the ESU. This

uncertainty was due largely to the difficulty in balancing the clear improvements in some aspects 

of the ESU’s status over the last approximately 15 years against persistent threats driving the 

longer term status of the ESU, which probably have not changed over the same time frame and 

are predicted to degrade in the future. Both issues are discussed in more detail below. In 

addition, the BRT noted that accurately predicting the long-term trend of a complex system is 

inherently difficult, and this also led to some uncertainty in the overall risk assessment.

The BRT concluded that some aspects of the ESU’s status have clearly improved since 

the initial status review in the mid-1990s (Weitkamp et al. 1995). In particular, the BRT 

assigned a relatively low mean risk score to the abundance factor, noting that spawning 

escapements were higher in some recent years than they had been since 1970 (Figure 5). Recent 

total returns (preharvest recruits) were also substantially higher than the low extremes of the 

1990s, but still mostly below levels of the 1960s and 1970s (Figure 5). The BRT attributed the 

increased spawner escapements largely to a combination of greatly reduced harvest rates, 

reduced hatchery production, and improved ocean conditions (see New Data and Updated 

Analysis section). Even with the recent increases, however, abundance remains at approximately 

10% of estimated historical abundance (≈150,000 current compared to ≈1.5 million historical; 

see discussion in the Current Biological Status subsection).

The BRT noted that compared to the mid-1990s, the ESU contained relatively abundant 

wild populations throughout its range, leading to a relatively low risk associated with spatial 

structure (Table 27). The BRT also discussed the observation that the recent natural origin 

spawning abundance of the OCCS ESU was higher than that observed for other listed salmon 

ESUs, although some members noted that the fifteenfold variability in abundance since the mid1990s brings into question how heavily to weigh abundance as an indicator of status. Finally, the 

BRT noted that hundreds of individual habitat improvement projects over the last approximately 

15 years had likely benefited the ESU, although quantifying these benefits is difficult.

The BRT discussed some ongoing positive changes that are likely to become manifest in 

abundance trends for the ESU in the future. In particular, hatchery production continues to be 

reduced with the cessation of releases in the North Umpqua River and Salmon River populations, 

and the BRT expects that the near-term ecological benefits from these reductions would result in 

improved natural production for these populations in future. In addition, the BRT expected that 

reductions in hatchery releases that have occurred over the past decade may continue to produce 

some positive effects on the survival of the ESU in the future, due to the time it may take for past 

genetic impacts to become attenuated.

Despite these positive factors, the BRT also had considerable concerns about the longterm viability of the ESU. The BRT continued to be concerned that there had been a long-term 

decline in the productivity of the ESU from the 1930s through the 1990s (Figure 5). Despite 

some improvements in productivity in the early 2000s, the BRT was concerned that the overall 

productivity of the ESU remains low compared to what was observed as recently as the 1960s 

and 1970s (Figure 5 and Figure 6). The BRT was also concerned that the majority of the 

improvement in productivity in the early 2000s was likely due to improved ocean conditions, 

with a relatively smaller component due to reduced hatchery production (Buhle et al. 2009).
119

The BRT noted that the legacy of past forest management practices combined with 

lowland agriculture and urban development has resulted in a situation in which the areas of 

highest habitat capacity (intrinsic potential) are now severely degraded (see Land management—

stream habitat complexity subsection). The BRT also noted that the combined ODFW/NMFS 

analysis of freshwater habitat trends for the Oregon coast found little evidence for an overall 

improving trend in freshwater habitat conditions since the mid-1990s and evidence of negative 

trends in some strata (Appendix C). The BRT was also concerned that recent changes in the 

protection status of beavers, which through their dam building activities create coho habitat, 

could result in further negative trends in habitat quality. The BRT was therefore concerned that 

when ocean conditions cycle back to a period of poor survival for coho salmon, the ESU may 

rapidly decline to the low abundance seen in the mid-1990s.

Some members of the BRT observed that the reduction in risks from hatchery and harvest 

are expected to help buffer the ESU when marine survival returns to a lower level, likely 

resulting in improved status compared to the situation in the mid-1990s. Others noted that 

potential declines in beavers, observed negative trends in some habitat features, and the potential 

for more severe declines in marine productivity could result in even lower abundance levels than 

during the last period of poor ocean conditions. On balance, the BRT as a whole was uncertain

about whether the long-term downward trajectory of the ESU’s status has been arrested and 

uncertain about the ESU’s ability to survive another prolonged period of low ocean survivals.

Finally, the BRT was also concerned that global climate change will lead to a long-term 

downward trend in freshwater and marine coho salmon habitat compared to current conditions 

(see Effects of climate change on the OCCS ESU subsection). There was considerable 

uncertainty about the magnitude of most of the specific effects climate change will have on 

salmon habitat, but the BRT was concerned that most changes associated with climate change 

are expected to result in poorer and more variable habitat conditions for OCCS than exist 

currently (Table 14). Some members of the BRT noted that changes in freshwater flow patterns 

as a result of climate change may not be as severe in the Oregon coast as in other parts of the 

Pacific Northwest, while others were concerned by recent observations of extremely poor marine 

survival rates for several West Coast salmon populations. The distribution of overall risk scores 

reflects some of this uncertainty.

Significant Portion of its Range Question

The BRT concluded that, when future conditions are taken into account, the OCCS ESU 

as a whole is at moderate risk of extinction. The BRT therefore did not explicitly address 

whether the ESU was at risk in only a significant portion of its range.
120
121

Glossary

abundance. The number of fish in a population. See also population.

artificial propagation. Hatchery spawning and rearing of salmon, usually to the smolt stage.

AUC. For area under the curve. A statistical technique for estimating an annual total number of 

spawners from periodic spawner counts. See also spawner.

barrier. A blockage such as a waterfall, culvert, or rapid that impedes the movement of fish in a 

stream system.

BLM. For U.S. Bureau of Land Management.

BRT. For biological review team. The team of scientists who evaluate scientific information for 

National Marine Fisheries Service status reviews.

catastrophic events. Sudden events that disastrously alter large areas of landscape. These can 

include floods, landslides, forest fires, and volcanic eruptions.

channel gradient. The slope of a stream reach.

CLAMS. For Coastal Landscape Analysis and Modeling Study. A cooperative project between 

the Oregon State University Department of Forestry and the U.S. Forest Service Pacific 

Northwest Forest Science Laboratory.

comanagers. Federal, state, and tribal agencies that cooperatively manage salmon in the Pacific 

Northwest.

critical habitat. 1) specific areas within the geographical area occupied by the species at the 

time of listing, on which are found those physical or biological features that are essential to 

the conservation of the listed species and that may require special management 

considerations or protection, and 2) specific areas outside the geographical area occupied by 

the species at the time of listing that are essential for the conservation of a listed species. If a 

species is listed or critical habitat is designated, ESA section 7(a)(2) requires federal agencies 

to ensure that activities they authorize, fund, or carry out are not likely to jeopardize the 

continued existence of such a species or to destroy or adversely modify its critical habitat 

(NMFS 2008).

delisting. Taking a species off the endangered species list.

demographic risk. Risks to a small population resulting from population processes such as 

depensation or chance events in survival or reproductive success.
122

density effects. Survival of juvenile salmon may be influenced by their density. Survival is 

usually higher when density is low.

dependent populations. Populations that rely on immigration from surrounding populations to 

persist. Without these inputs, dependent populations would have a lower likelihood of 

persisting over 100 years.

depensation. The effect where a decrease in spawning stock leads to reduced survival or

production of eggs through either 1) increased predation per egg given constant predator

pressure, or 2) the Allee effect (a positive relationship between population density and the 

reproduction and survival of individuals) with reduced likelihood of finding a mate.

DNA. For deoxyribonucleic acid. A complex molecule that carries an organism’s heritable

information. The two types of DNA commonly used to examine genetic variation are

mitochondrial DNA (mtDNA), a circular molecule that is maternally inherited, and nuclear 

DNA, which is organized into a set of chromosomes. See also electrophoresis.

DPS. For distinct population segment. A population or group of populations of a vertebrate 

species that is discrete from other populations and significant to the biological species as a 

whole. See also ESU.

DSS. For decision support system. A computer application that assists users in using data and 

models to solve problems. It typically links and analyzes many pieces of data or models at a 

variety of scales, producing results that aid in decision making rather than replacing human 

judgment.

ecoregion. An integration of physical and biological factors such as geologic history, climate, 

and vegetation.

electrophoresis. The movement of charged particles in an electric field. This process has been 

developed as an analytical tool to detect genetic variation revealed by charge differences on 

proteins or molecular weight in DNA. See also DNA.

endangered species. A species in danger of extinction throughout all or a significant portion of 

its range. See also ESA and threatened species.

EPA. For U.S. Environmental Protection Agency.

ESA. For U.S. Endangered Species Act. Passed by Congress in 1973, its purpose is to provide a 

means to conserve the ecosystems on which endangered species and threatened species 

depend. See also endangered species and threatened species.

escapement. Usually refers to adult fish that escape from fisheries and natural mortality to reach 

the spawning grounds.

estuarine habitat. Areas available for feeding, rearing, and smolting in tidally influenced lower 

reaches of rivers. These include marshes, sloughs and other backwater areas, tidal swamps, 

and tide channels.
123

ESU. For evolutionarily significant unit. An ESU represents a distinct population segment of 

Pacific salmon under the Endangered Species Act that 1) is substantially reproductively 

isolated from conspecific populations and 2) represents an important component of the 

evolutionary legacy of the species. See also DPS.

exploitation rate. The proportion of adult fish from a population that die as a result of fisheries.

extinction. The loss of a species or ESU; may also be used for the extirpation of local

populations.

factors for decline. These are factors identified that caused a species to decrease in abundance 

and distribution and become threatened or endangered.

fecundity. The number of offspring produced per female over her lifetime.

fish-day. Fish-days are calculated by multiplying the live fish observed on each survey date by 

the number of days between surveys. These values are then summed for the entire 

observation period to generate a relative index of spawner abundance at a reach for any given 

year (Pess et al. 2002b).

fourth-field and fifth-field hydrologic units. In the U.S. Geological Survey, hydrologic units 

have been divided at different scales. The area of a fourth-field hydrologic unit is 440,000 

acres and a fifth-field hydrologic unit is between 40,000 and 250,000 acres.

freshwater habitat. Areas available for spawning, feeding, and rearing in freshwater.

fry. Young salmon that have emerged from the gravel and no longer have a yolk sack.

full seeding. Having enough spawners to fully occupy available juvenile habitat with offspring.

functionally independent population. A high-persistence population whose dynamics or 

extinction risk over a 100-year time frame is not substantially altered by exchanges of 

individuals with other populations (migration). Functionally independent populations are net 

donor populations that may provide migrants for other types of populations. This category is 

analogous to the independent populations of McElhany et al. (2000).

fuzzy logic. A system of logic in which a statement can be true, false, or any of a continuum of 

values. A type of logical analysis that allows a system to process imprecise information in 

evaluating conditions.

gene conservation group. Management area defined by Kostow (1995) to conserve genetic 

diversity in Oregon Coast coho salmon. See also monitoring area.

genetic bootstrap support. A measure of the confidence in a particular branch in a genetic tree. 

Specifically a large number of trees are created using randomly drawn sets of loci sampled 

from the data with replacement. The bootstrap value for a node is the proportion of the trees 

that have all the samples contained on that node.

gradient. The slope of a stream segment.
124

habitat quality. The suitability of physical and biological features of an aquatic system to 

support salmon in the freshwater and estuarine system.

hatchery. A facility where artificial propagation of fish takes place.

historical abundance. The number of fish produced before the influence of European 

settlement.

HLFM. For habitat limiting factors model.

HTWG. For Habitat Trends Working Group. A joint group formed by NWFSC and ODFW 

and composed of scientists from each agency, with contributions by statisticians from the 

EPA and Oregon State University.

hydrology. The distribution and flow of water in an aquatic system.

IMST. For Independent Multidisciplinary Science Team. A scientific advisory body to the 

Oregon legislature and governor on watershed, forestry, agriculture, and fisheries science 

issues.

independent population. A population that historically would have a high likelihood of 

persisting in isolation from neighboring populations for 100 years.

integrated hatchery. In this case, the Cow Creek hatchery program where wild coho salmon 

are regularly taken into the hatchery program’s broodstock. Typically more than 10% of the 

broodstock annually is of wild fish origin. In some years, 100% of the broodstock is wild 

fish.

intrinsic potential. A modeled attribute of streams that includes the channel gradient, valley 

constraint, and mean annual discharge of water. Intrinsic potential in this report refers to a 

measure of potential coho salmon habitat quality. This index of potential habitat does not 

indicate current actual habitat quality.

isolation. The degree to which a population is unaffected by migration to and from other

populations. As the influence of migration decreases, a population’s isolation increases.

jack. A male coho salmon that matures at age-2 and returns from the ocean to spawn a year 

earlier than normal.

juvenile. A fish that has not matured sexually.

keystone species. A species that plays a pivotal role in establishing and maintaining the 

structure of an ecological community. The impact of a keystone species on the ecological 

community is more important than would be expected based on its biomass or relative 

abundance.

Landsat. For land remote-sensing satellite. The satellites supply global land surface images 

and data.
125

life history. The specific life cycle of a fish from egg to adult. Life history includes changes 

experienced from birth through death and variation in traits such as the size and age at 

maturity and fecundity. Traits such as juvenile growth rate and age at ocean emigration are 

aspects of coho salmon life history.

limiting factors. Factors that limit survival or abundance. They are usually related to habitat 

quantity or quality at different stages of the life cycle. Harvest and predation may also be 

limiting factors.

listed species. Species included on the List of Endangered and Threatened Species, authorized 

under the Endangered Species Act and maintained by the U.S. Fish and Wildlife Service and 

NMFS.

lowland habitat. Low-gradient stream habitat with slow currents, pools, and backwaters used 

by fish. This habitat is often converted to agricultural or urban use.

LWD. For large woody debris. Large piece of woody material such as a log or stump that 

intrudes into a stream channel.

marine survival rate. The proportion of smolts entering the ocean that return as adults.

metacercaria. Tiny cysts that contain the intermediate stages of parasites.

microsatellite. A class of repetitive DNA used for estimating genetic distances.

migrant. A fish that is born in one population but returns to another population to spawn.

migration. Movement of fish from one population to another.

migration rate. The proportion of spawners that migrate from one population to another. See 

also stray rate.

monitoring area. ODFW’s monitoring areas are similar to but not identical to gene 

conservation groups. Additional information online at http://nrimp.dfw.state.or.us/crl

/default.aspx?pn=AIProjOrPlnSalWtrshd. See also gene conservation group.

naturally produced fish. Fish that were spawned and reared in natural habitats, regardless of 

parental origin. See also wild fish.

NIS. For nonindigenous species.

NRR. For natural return ratio. The ratio N/T, where N is naturally produced spawners in one 

generation and T is total (hatchery produced + naturally produced) spawners in the previous 

generation.

OCCS. For Oregon coast coho salmon.

OCN. For Oregon coast natural coho salmon. Often used by ODFW to distinguish from 

hatchery-raised fish and includes fish from the Southern Oregon/Northern California Coasts 

Coho Salmon ESU in Oregon.
126

OCSRI. For Oregon Coastal Salmon Restoration Initiative. Now the Oregon Plan for Salmon 

and Watersheds. A plan established by the State of Oregon in 1997 to restore salmon runs, 

improve water quality, and achieve healthy watersheds and strong communities throughout 

the state.

ODF. For Oregon Department of Forestry.

ODFW. For Oregon Department of Fish and Wildlife.

OFPBDS. For Oregon Fish Passage Barrier Data Set.

ONCC TRT. For Oregon and Northern California Coast Technical Recovery Team.

OPI. For Oregon Production Index.

OWEB. For Oregon Watershed Enhancement Board.

OWRD. For Oregon Water Resources Department.

parasite prevalence. The number of hosts infected with one or more individuals of a particular 

parasite species (or taxonomic group) divided by the number of hosts examined for that 

parasite species.

parr. The life stage of salmonids that occurs after fry and is generally recognizable by dark 

vertical bars (parr marks) on the sides of the fish.

PDO. For Pacific Decadal Oscillation. A long-term pattern of Pacific Ocean climate 

variability, with events lasting 20 to 30 years and oscillating between warm and cool 

regimes.

persistent population. One that is able to persist (i.e., not go extinct) over a 100-year period 

without support from other populations. This includes an ability to survive prolonged 

periods of adverse environmental conditions, which may be expected to occur at least once in 

the 100-year time frame.

PFMC. For Pacific Fishery Management Council.

PIT tag. For passive integrated transponder tag. An injectable, internal, radio-type tag that 

allows unique identification of a marked fish passing within a few inches of a monitoring 

site.

population. A group of fish of the same species that spawns in a particular locality at a

particular season and does not interbreed substantially with fish from any other group. See 

also abundance.

population classification. The grouping of populations into functionally independent, 

potentially independent, and dependent classes.
127

population dynamics. Changes in the number, age, and sex of individuals in a population over 

time, and the factors that influence those changes. Five components of populations that are 

the basis of population dynamics are birth, death, sex ratio, age structure, and dispersal.

population identification. Delineating the boundaries of historical populations.

population structure. This includes measures of age, density, and growth of fish populations.

potentially independent population. High-persistence population whose population dynamics 

are substantially influenced by periodic immigration from other populations. In the event of 

the decline or disappearance of migrants from other populations, a potentially independent 

population could become a functionally independent population.

production. The number of fish produced by a population in a year.

productivity. The rate at which a population is able to produce fish.

recovery. The reestablishment of a threatened or endangered species to a self-sustaining level in 

its natural ecosystem (i.e., to the point where the protective measures of the ESA are no 

longer necessary).

recovery domain. The area and species for which a TRT is responsible.

recovery plan. A document identifying actions needed to make populations of naturally 

produced fish comprising the OCCS ESU sufficiently abundant, productive, and diverse so 

that the ESU as a whole will be self-sustaining and will provide environmental, cultural, and 

economic benefits. A recovery plan also includes goals and criteria by which to measure the 

ESU’s achievement of recovery, and an estimate of the time and cost required to carry out 

the actions needed to achieve the plan’s goals.

recovery scenario. Sequence of events expected to lead to recovery of Oregon coast coho 

salmon.

run timing. The time of year (usually identified by week) when spawning salmon return to the 

spawning beds.

salmonid. Fish of the family Salmonidae, including salmon, trout, and char.

significant. Biological significance refers to an effect that has a noteworthy impact on health or 

survival.

smolt. A life stage of salmon that occurs just before the fish leaves freshwater. Smolting is the 

physiological process that allows salmon to make the transition from freshwater to salt water.

smolt capacity. The maximum number of smolts a basin can produce. Smolt capacity is related 

to habitat quantity and quality.

spawner. Adult fish on the spawning grounds. See also AUC.
128

spawner survey. Effort to estimate the number of adult fish on spawning grounds. It uses 

counts of redds and fish carcasses to estimate escapement and identify habitat. Annual 

surveys can be used to compare the relative magnitude of spawning activity between years.

species. Biological definition: A group of organisms formally recognized by the scientific 

community as distinct from other groups. Legal definition: refers to joint policy of the 

USFWS and NMFS that considers a species as defined by the ESA to include biological 

species, subspecies, and DPSs.

stray rate. As used in this document, stray rate refers to the number of spawning adults that 

return to a stream other than their natal stream within a basin. See also migration rate.

sustainability. An attribute of a population that persists over a long period of time and is able to 

maintain its genetic legacy and long-term adaptive potential for the foreseeable future.

threatened species. A species not presently in danger of extinction, but likely to become so in 

the foreseeable future. See also endangered species and ESA.

TRT. For technical recovery team. The TRT establishes biologically based ESA recovery goals 

for listed salmonids within a given recovery domain. Members serve as science advisors to 

the recovery planning phase.

USFS. For U.S. Forest Service.

valley constraint. The valley width available for a stream or river to move between valley 

slopes.

viability. The likelihood that a population will sustain itself over a 100-year time frame.

viability criteria. A prescription of a population conservation program that will lead to the ESU 

having a negligible risk of extinction over a 100-year time frame.

VSP. For viable salmonid population. An independent population of any Pacific salmonid 

(genus Oncorhynchus) that has a negligible risk of extinction due to threats from 

demographic variation, local environmental variation, and genetic diversity changes over a 

long time frame (McElhany et al. 2000).

warm water fish. Spiny-rayed fish such as sculpins, minnows, darters, bass, walleye, crappie, 

and bluegill that generally tolerate or thrive in warm water.

wild fish. Fish whose ancestors have always lived in natural habitats, that is, those with no 

hatchery heritage. See also naturally produced fish.
129

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153

Appendix A: Threats Matrix and DSS Criteria

This appendix consists of two tables: Table A-1, the Oregon Coast Coho Salmon 

(OCCS) Biological Review Team’s (BRT) threats matrix; and Table A-2, the 

descriptions, metrics, data sets, and sources for decision support system (DSS) criteria.
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Table A-1. Threats matrix used by OCCS BRT. This was used as a memory tool to keep track of information presented.

Stratum

Marine productivity/ocean conditionsGlobal climate changeArtificial propagationRestriction of fish passageWater withdrawalDisturbanceRiparian loss (not addressed)Splash damming, log drives legacyWetland, beaver dam lossEstuary destructionStream complexity Mining Water quality degradationLand use conversion, urbanizationHarvestDisease and parasitismPredationUrban growthAgricultural practicesDredge and fillForest practicesNorthwest Forest Plan

North Coast

Mid-Coast

Lakes

Umpqua River

Mid-South Coast

Whole ESU 

ESA listing 

factor

Other 

natural or 

human

factors

Destruction, modification, curtailment of OCCS habitat or range OverutilizationDisease 

and 

predation

Regulatory mechanisms
155

Table A-2. Descriptions, metrics (including time periods), data sets, and sources for DSS criteria.

Criterion Description Metric Data set Source

PP-1 Population productivity Geometric mean of the natural return 

ratio for broodyears with spawner 

abundances below the median of the last 

4 generations (12 years)

Spawner abundance by 

population, hatchery fish 

spawning naturally by 

population

ODFW random spawning 

surveys (Jacobs et al. 2002) 

as reported by ODFWa

PP-2 Probability of persistence Results of four population viability 

models

Various Models and associated data 

sets are described in detail in 

Wainwright et al. (2008)

PP-3 Critical abundance Average peak spawner density in the 

lowest 3 of the last 12 years

Spawner counts ODFW random spawning 

surveys (Jacobs et al. 2002) 

as reported by ODFWa

PD-1 Spawner abundances Long-term harmonic mean of naturally 

produced spawners (both 3-year-old 

adults and 2-year-old jacks)

Annual surveys 

conducted by ODFW 

using various 

methodologies from 1950 

to the present

ODFWa

PD-2 Artificial influence Six-year (2 generations) mean of annual 

estimates of the proportion of naturally 

produced fish in spawning surveys

Survey estimates of 

hatchery fish spawning 

naturally

ODFW random spawning 

surveysa

PD-3 Spawner distribution Average occupancy rate of watersheds 

during the most recent 12 years, 

analyzed by fifth field hydrologic units

ODFW random spawning 

surveys

Surveys (Jacobs et al. 2002) 

as reported by ODFWa

PD-4 Juvenile distribution Average occupancy rate of surveyed 

reaches with at least two pools during 

the most recent 12 years, analyzed by 

fifth field hydrologic units

ODFW summer juvenile 

surveys

ODFWa

PF Population functionality Estimated smolt capacity for each basin 

as estimated by the ODFW Habitat 

Limiting Factors Model version 6.0 

(Nickelson et al. 1992, Nickelson 1998)

ODFW habitat survey 

data

ODFWb

ED-1

ED-2

ED-3

ESU-level sustainability 

criteria

Expert opinion None Lawson et al. 2007

a K. Moore, Oregon Dept. Fish and Wildlife, Corvallis (ODFW), OR. Pers. commun., 9 September 2009. b T. Nickelson, ODFW, Corvallis, OR. Pers. commun., 5 January 2006.
156
157

Appendix B: Disturbance

The condition of aquatic ecosystems and associated fish populations are a function, at 

least in part, of the characteristics of the surrounding landscape (Frissell et al. 1986, Naiman et 

al. 2000). Timber harvest and associated roads have extensively altered aquatic ecosystems 

throughout the Pacific Northwest (Everest and Reeves 2007). A consequence of these effects of 

timber harvest activities is that the behavior of ecosystems is altered, which in turn has 

consequences for fish populations and their habitat (Reeves et al. 1995). There is a negative 

association between the amount of in-channel large wood and percent of area in a watershed 

intensively logged (Murphy and Koski 1989, Bilby and Ward 1991, Montgomery et al. 1995). 

Burnett et al. (2006) found that the mean density of large wood in Elk River on the southern 

Oregon coast was positively related to the area in larger trees in the catchment. Reeves et al. 

(1993) examined watersheds in the Oregon Coast Range and found that the diversity of the fish 

assemblage and the amount of large wood was significantly greater in streams in which less than 

or equal to 25% of the watershed was clear-cut, compared to watersheds in which more than 

25% of the area was clear-cut.

The condition of aquatic habitat and fish populations is also directly correlated with the 

density of roads in a watershed, which in turn is generally directly related to the amount and 

intensity of land management activities (Lee et al. 1997). Roads are sources of sediment as 

either surface erosion or mass erosion (Furniss et al 1991). They also can alter water delivery by 

increasing the drainage network, particularly in the upper portions of the network. Sharma and 

Hilborn (2001) examined 14 streams in Washington and found that smolt density was inversely 

correlated with the density of roads. Logging activities involve the creation and maintenance of 

roads, and logging has been linked directly to increased sediment levels in streams (Platts et al. 

1989).

The Oregon Northern California Coast Technical Review Team (ONCC TRT) 

(Wainwright et al. 2008) was unable to include habitat data directly in its biological status 

criteria, because at the time there was no uniform measure of habitat quality over the entire 

evolutionarily significant unit (ESU). Habitat surveys by the Oregon Department of Fish and 

Wildlife (ODFW) were available, but the density and distribution of on-the-ground surveys make 

them unsuitable for fine-scale analysis. ODFW and this biological review team (BRT) have used 

these habitat surveys to provide a general assessment of stream complexity (see Appendix C).

Satellite images have the potential for measuring properties of large landscapes at a 

relatively fine scale. Recent public availability of Landsat imagery and the development of tools 

for analysis now make it possible to analyze disturbance patterns on a fine temporal and spatial 

scale. In an analysis conducted for the BRT, satellite annual vegetation maps of the Oregon 

Coast Coho Salmon (OCCS) ESU were updated through 2008 and analyzed for patterns of 

disturbance for the time period 1986–2008. The scale of resolution of these analyses is 

approximately 100 m, so disturbances as small as 1 ha theoretically can be detected. This made 

it possible to detect individual disturbance events from the satellite images and map new 
158

disturbances on an annual basis. Intensity of disturbance can also be measured, so low-intensity 

disturbances (i.e., thinning) can be distinguished from high-intensity disturbances (i.e., clearcut). Fires were also mapped, but fire has had a small role in shaping habitat in the OCCS ESU 

over the past 23 years.

Yearly maps of forest disturbance were derived from Landsat Thematic Mapper (TM) 

satellite imagery. Useful Landsat TM images have been acquired continuously for the entire 

conterminous United States (and portions of the world) since 1984; they form the basis for many 

land cover and land cover change maps used in natural resource disciplines (Cohen and Goward 

2004). Time series of Landsat TM imagery were assembled for all areas that intersected the 

footprint of the OCCS ESU, then processed with LandTrendr, a change detection package 

developed at Oregon State University (Kennedy et al. 2010, Kennedy et al. 2012). Image 

preparation includes basic atmospheric correction (using the COST approach, Chavez Jr. 1996)

followed by radiometric normalization of all scenes within one time series (using the MADCAL 

algorithms, Canty et al. 2004) and a semiautomated cloud-screening approach with human 

supervision (Kennedy et al. 2010, Kennedy et al. 2012.). After image preparation, the time 

series of a spectral index (here the Normalized Burn Ratio, van Wagtendonk et al. 2004) for each 

pixel (30 × 30 m footprint) was extracted, and temporal segmentation algorithms were used to 

identify periods of both stability and change in each pixel’s trajectory (Kennedy et al. 2010, 

Kennedy et al. 2012) The segmentation approach utilizes information from nearly every year in 

the satellite record (with occasional gaps caused by persistent cloud cover), increasing the signalto-noise ratio of the data and improving the ability to distinguish subtle change from random 

noise.

Disturbance events detected in the segmentation phase were then used to create maps of 

forest disturbance. In each pixel, the magnitude of spectral change in a disturbance event was 

converted to an estimate of percent vegetation cover loss by relating spectral change to percent 

vegetation cover using a statistical model of cover developed from photo-interpreted plots 

(Cohen et al. 2010). Pixels with disturbance magnitude less than 10% vegetation loss were 

removed, groups of pixels with the same disturbance year and with size greater than 1 ha were 

retained as disturbance patches, and mean percent cover change across all pixels in the patch was 

recorded. Separately, a mask distinguishing forest from nonforest was created from summary 

results obtained during segmentation, capturing all areas where forest existed at any point in the 

23-year period (1985 to 2008). Pixels in nonforest areas were removed from further 

consideration.

Of the remaining disturbance patches, 300 disturbed in 2002, 2003, or 2004 were 

randomly selected for change labeling. A trained interpreter viewed each patch on 2005 digital

air photos and assigned a change-type label as either a clear-cut (less than 15% tree cover 

remaining) or a thinning (tree removal but more than 15% tree cover remaining). The labeled 

values were compared to the mean patch-level percent cover change calculated earlier and 

distributions of cover change were evaluated for clear-cuts and thins. The modal percent cover 

change for clear-cuts and thins was 55% and 22.5% change, respectively, with the intersection of 

the distributions occurring at 35% cover change. This value was used to separate patches into 

“harvest high” or “harvest low” categories for all subsequent analyses. Separately, a point-based 

validation tool was used to corroborate disturbance mapping across all years. At 274 points 

randomly distributed throughout the Coho ESU, the LandTrendr algorithms correctly identified 
159

disturbance or lack of disturbance in 89.7% of plots; omission and commission error were 

balanced at 5.4% and 4.7%, respectively.

Disturbance was widespread over the ESU, and predominantly of high intensity (Figure 

B-1). Disturbance patterns varied over space, time, and land ownership. Some river systems 

have experienced higher disturbance than others (Figure B-2). The Siletz, Necanicum, and 

Tahkenitch have had up to 50% of basin area disturbed in the analysis period, while North 

Umpqua has had less than 10% disturbance.

The time series of cumulative disturbance, derived from Landsat images, is shown for 

four major river systems in the OCCS ESU in Figure B-3. Disturbance in these systems spans 

the range observed in the ESU, from a low of 10% (Upper Nehalem) to 50% (Siletz). Most 

disturbance is in the high category, with a lesser amount of low intensity disturbance, and the 

proportion of high to low disturbance is fairly constant through the time period. Three patterns 

of disturbance are evident (Figure B-3). Constant rates of annual disturbance occurred in the 

Siletz and Alsea river systems. The Necanicum River basin showed little harvest activity early 

in the time period, with an exponential increase in more recent years. By contrast, the North 

Umpqua River basin showed an overall low rate of disturbance, with most of the activity early in 

the time period.

Changes in the regulatory environment have largely driven patterns of land disturbance 

over the past two decades. Disturbance in four land ownership categories in the Alsea River 

basin is shown in Figure B-4. Prior to 1990, there were high rates of disturbance on federal lands 

(BLM and USFS). With implementation of the Northwest Forest Plan, federal logging activity 

decreased to very low levels. Logging on private lands proceeded at a steady pace through the 

late 1990s, then increased. This general pattern is evident throughout the ESU, with logging on 

National Forest and BLM land decreasing after 1989 and activity on private lands increasing.

The recent availability of Landsat images, along with the development of tools for 

analysis, allowed us a comprehensive, uniform picture of disturbance patterns that was 

heretofore unavailable. Preliminary analysis showed that disturbance has been widespread in the 

ESU, some basins experienced much higher disturbance than others, rates of disturbance are 

relatively constant, and the most intense disturbance has moved from federal to private 

nonindustrial lands in response to policy changes. Short-term fluctuations in disturbance rates 

often can be attributed to economic conditions.
160

Figure B-1. Distribution and intensity of vegetation disturbance from 1986 to 2008, based on analysis of 

Landsat imagery.
161

Figure B-2. Ranking of river basins and the Umpqua subbasins by cumulative percent vegetation 

disturbance from 1986 to 2008.
162

Figure B-3. Time series of cumulative area of vegetation disturbance for four river basins in the OCCS 

ESU for years 1986 to 2008. High disturbance (dark gray) is usually clear-cut logging, while low 

disturbance (light gray) is related to forest thinning. Data from Kennedy et al. 2010 and 2012.

Figure B-4. Total area (hectares) of vegetation disturbance in the Alsea River area of the OCCS ESU by 

four land ownership categories from years 1986 to 2008. BLM = Bureau of Land Management 

timberlands, ODSL = Oregon state timberlands, Private = industrial and nonindustrial private 

timberlands, and FS = U.S. Forest Service. Data from Kennedy et al. 2010 and 2012.
163

Appendix C: Summary of Findings of the BRTODFW Habitat Trends Working Group

Introduction

From 1998 to the present, the Oregon Department of Fish and Wildlife (ODFW) has 

monitored wadeable streams to assess freshwater rearing habitat for the Oregon Coast Coho 

Salmon (OCCS) evolutionarily significant unit (ESU) during the summer low flow period 

(Anlauf et al. 2009). The goal of this program is to measure the status and trend of habitat 

conditions throughout the range of the ESU through variables related to the quality and quantity 

of aquatic habitat for coho salmon (Oncorhynchus kisutch): stream morphology, substrate 

composition, instream roughness, riparian structure, and winter rearing capacity (Moore 2008). 

In 2009 scientists from ODFW and scientists of the OCCS Biological Review Team (BRT) 

independently analyzed this data to ask the question: Has juvenile coho habitat changed during 

ODFW’s monitoring program over the past 11 years? These analyses reached different 

conclusions, necessitating that the discrepancies be resolved.

To address differences in the BRT’s analysis of habitat trends based on ODFW data and 

ODFW’s original analysis (Anlauf et al. 2009), NWFSC and ODFW formed a joint Habitat 

Trends Working Group (HTWG) composed of scientists from each agency (Eric Ward, Chris 

Jordan, and Mike Ford, NWFSC; Kara Anlauf, Kim Jones, Jeff Rodgers, Julie Firman, and Kelly 

Moore, ODFW). Statisticians from the U.S. Environmental Protection Agency (John Van 

Sickle) and Oregon State University (Don Stevens and Lisa Madsen) also contributed to the 

HTWG analysis. There were several important differences to address: in the BRT and ODFW 

analysis, different data sets were analyzed, different trend models considered, and different 

estimation approaches were used. The goal of the HTWG was to reconcile these differences.

The first discrepancy between the BRT’s analysis and the ODFW analysis (Anlauf et al. 

2009) that caused conflicting results was that different subsets of the ODFW habitat monitoring 

program were used. The ODFW approach focused only on sites designated as coho spawning or 

rearing habitat (first through third order wadeable streams and below barriers, Anlauf et al. 

2009). In contrast, the BRT’s analysis included sites within and outside of the area recognized as 

spawning and rearing for coho salmon habitat. The HTWG agreed that a common data set 

should be used in the joint analysis, and that initially only spawning or rearing sites within the 

coho ESU be included. A further selection was made on which sites were included. The ODFW 

monitoring program surveys 25% of sites annually, 25% of sites every 3 years, 25% of sites 

every 9 years, and 25% of sites only once. The HTWG analysis excluded sites with only 1 visit, 

yielding 530 data points over the period 1998–2008. These data are distributed among 4 regions 

or strata within the OCCS ESU (North Coast, Mid-Coast, Mid-South, Umpqua), with 133 unique 

sites within those regions (Figure C-1).
164 

Figure C-1. Map of Oregon coho spawning and rearing sites. 
165

A second potential discrepancy in the BRT and ODFW analysis was that the BRT 

adopted a Bayesian statistical approach, while ODFW had used maximum likelihood methods. 

We would expect the results to be identical, because when using normal linear models with 

noninformative priors, the Bayes posterior is approximately normal, centered on the maximum 

likelihood estimate (Gelman et al. 2006). After analyzing identical data sets with different 

estimation methods, the HTWG concluded that when the same trend model is applied to identical 

data sets, the point estimates (maximum likelihood estimates, posterior means) are identical 

using both the Bayesian and maximum likelihood approaches.

A third potential source of differences between the BRT and ODFW analysis was the 

choice of trend model used. In its analysis, ODFW advocated the inclusion of interaction terms 

consistent with the study design. The BRT’s approach was based on model selection, allowing 

the model with the most data support to be used for trend analysis. The HTWG considered both 

of these approaches.

Methods

In the BRT’s original analysis, three measures of habitat complexity were assessed for 

trends: winter parr capacity, summer parr capacity, and channel score (Aquatic and Riparian 

Effectiveness Monitoring Program [AREMP]). In addition to winter parr capacity, ODFW also

examined trends in large woody debris (LWD) and fine organic sediment (Anlauf et al. 2009). 

The HTWG agreed that the three measures of complexity would be reanalyzed, in addition to the 

volume of LWD and fine organic sediment in riffles. These five variables were then transformed 

using the methods shown in Table C-1 to make each approximately normally distributed.

The linear trend models used by the BRT and ODFW are similar, with only subtle 

differences. The model used in the BRT’s analysis can be described as 

Xhijk = αh + βht + sj + εhijk (1)

where Xhijk is the estimated response for site j, region h, and year i. The parameters αh and βh

represent region-specific fixed effects (intercept and slope, respectively). The intercept at each 

site is treated as a normally distributed random effect, sj ≈ Normal(0, σs), and residual error is 

included as εhijk ≈ Normal(0, σ). Biologically, these parameters mean that after accounting for 

variability between sites within a region, there are regional specific trends and differences in 

mean values (Figure C-2), reflecting shared overall patterns within sites in a given region.

Table C-1. Individual habitat metrics used by the HTWG for the trend analysis, the HTWG codes, and 

the transformations used to achieve normality.

Habitat metric HTWG code Transformation

Winter parr (ODFW) Winter parr ln(x)

Summer parr (ODFW) Summer parr x^(1/4)

Channel score (USFS) Channel score x

% of riffle that is sand/silt/organics RIFSNDOR asin(sqrt(x/100))

Volume of LWD per 100 m LWDVOL ln(x+1)
166

Figure C-2. Box plots of habitat complexity (Winter parr capacity, Summer parr capacity, Channel 

Score), percent fine sediment in riffles (RIFSNDOR), and volume of LWD by region for all sites 

(n = 530).

The linear trend model used by ODFW is identical to that used by the BRT, with the 

inclusion of two additional terms,

Xhijk = αh + βht + sj + γi + sj*γi + εhijk (2)

where γi is a year-specific random effect, and sj*γi represents a site-by-year interaction that 

allows each combination of site-year to be unique. Including year-specific random effects for all 

sites in all regions makes the assumption that all regions are similarly affected by large-scale 

environmental processes, regardless of whether the trends are shared (Figure C-3a) or regionspecific (Figure C-3b). Including the year-specific interaction term is justified by the survey 
167

Figure C-3. Illustration of year random effects for four hypothetical populations with a shared trend 

(panel a) and different trends (panel b). The response variable is simulated from arbitrary values 

and has no scale.

design; by revisiting some sites multiple times in the same year, the survey hopes to separate 

process variation from observation or measurement error. If data from the revisits are not 

substantially different from the long-term trend (Figure C-4a), it may be difficult to partition the 

total variance into observation and process components. If there are unique differences between 

years at the same site (Figure C-4b), including this additional variance will be warranted (and 

supported by model selection criteria).

As a first analysis, the HTWG used maximum likelihood methods to conduct significance 

on each of the five transformed metrics. As a second step, the HTWG repeated the BRT’s model 

selection exercise in a Bayesian statistical framework. Bayesian statistics offer advantages in the 

ability to communicate uncertainty as probabilities; one obvious disadvantage and source of 

criticism is the need to specify prior distributions on model parameters. Because the class of 

statistical models considered by the HTWG are normal linear models and well known 

noninformative priors exist (Gelman 2006), we were able to avoid introducing subjectivity into 

the trend analysis. For each metric, four candidate models were considered, reflecting a range of

models between the models used in the original ODFW and BRT analyses. These models all 

included region-specific trends and site-specific intercepts; their differences were whether or not 

site-by-year interactions and random effects in years were included (Table C-2). The data 

support for each of the regression models was evaluated independently for each metric using the 

Deviance Information Criterion (DIC, Spiegelhalter et al. 2002).
168

Figure C-4. Illustration of multiple site visits with no process variation (panel a) and process variation 

(panel b) representing environmental stochasticity. Each survey was simulated to have repeat 

visits in years 1, 5, and 8 (two surveys each). The response variable is simulated from arbitrary 

values and has no scale.

Table C-2. Differences between DIC scores between four competing models of changes in habitat metrics 

over time. In addition to the two models used in the ODFW and BRT reports, two intermediate 

models are considered. Delta DIC values represent the difference between each model and the 

best model (zeroes).

Model 1 (BRT) Model 2 Model 3 Model 4 (ODFW)

Site-specific intercepts x x x x

Regional trends x x x x

Year random effect x x

Site: year interaction x x

Habitat metric ∆DIC ∆DIC ∆DIC ∆DIC

Winter parr 0.0 7.3 3729.6 4460.1

Summer parr 0.0 2.4 3576.0 3266.9

Channel score 0.0 8.7 2346.4 3891.0

RIFSNDOR 0.0 7.1 4705.8 4714.0

LWDVOL 12.5 0.0 5777.1 4113.9

Results

For each of the three measures of complexity and for fine sediment in riffles, the 

HTWG’s model selection exercise found little data support for including either the year random 
169

effect term or the site-by-year interaction term (Table C-2). The exception was the model 

selection comparison for LWD volume; this metric suggested that year-specific random effects 

be included. This difference is important, because it suggests that unlike the complexity 

measures, there are large scale patterns across regions in the OCCS ESU that affect how wood 

volume is accumulated (or removed). To examine how the choice of model may affect trend 

estimates, the HTWG compared maximum likelihood estimates between the ODFW and BRT 

models. Both the trend estimates themselves and the results of significance testing are identical 

(Table C-3 and Table C-4), with two statistically significant results found (percent fine sediment 

organics in riffles in the Mid-South and large wood volume in the North Coast).

The advantage of examining the distributions of trend in a Bayesian setting is that we can 

quantify the proportion of the trend estimate that is negative or positive (e.g., Pr [X < 0] = 

0.03%, Figure C-5). Using winter parr capacity as an example, while none of the trend estimates 

meet the requirements to be considered “statistically significant,” there is strong support for 

negative trends in the two southern regions (95% in the Mid-South and 79% in the Umpqua). 

Although these negative annual rates of decline are small, they translate into reductions of winter 

parr capacity of 22% and 12%, respectively, over the 10-year time series.

Trend estimates for the other measures of complexity and habitat metrics are largely 

mixed. There is evidence of increasing trends in summer parr and channel score (AREMP) in 

three of the four regions (Figure C-5). For the percent of fine sediment in riffles, there appear to 

be declines in the North and Mid-Coast, a positive trend in the Mid-South, and little change in 

the Umpqua. Large wood volume appears to be declining in the North Coast and Umpqua, while 

increasing in the Mid-Coast and Mid-South regions.

The approaches taken by the BRT and ODFW are similar in that they both center on the 

use of the same likelihood function that relates parameters to data. The HTWG also considered 

exploring other approaches that are not likelihood based. One of these alternative approaches 

considered individual regressions on data from each site to graphically estimate the distribution 

of the trends for each metric. It is difficult to compare trends across sites, because some sites 

have few visits (n = 2–3) and others have been visited in each year (n = 10); sites with many 

visits will have much more precise estimates of trends. However, it is possible to overlay these 

trend estimates from individual sites on the posterior distributions of the regional trends from the 

Bayesian model to examine agreement between the site-level trends and regional trends.

Table C-3. Maximum likelihood estimates of trend parameters by region for two measures of habitat 

complexity (winter parr, summer parr) and two habitat metrics (% fine sand or organic material in 

riffles and the volume of LWD). Estimates are from the trend models used by ODFW and BRT 

(in parentheses); estimates found to be statistically significant (P < 0.05) are in boldface.

North Coast Mid-Coast Mid-South Umpqua

Winter parr 0.000 (−0.002) −0.005 (−0.004) −0.026 (−0.025) −0.016 (−0.013)

Summer parr 0.014 (0.009) 0.027 (0.027) 0.031 (0.030) −0.022 (−0.027)

RIFSNDOR −0.009 (−0.010) −0.003 (−0.003) 0.027 (0.026) 0.003 (0.002)

LWDVOL −0.063 (−0.062) 0.015 (0.016) 0.019 (0.020) −0.028 (−0.025)
170

Table C-4. Graphical representation of the maximum likelihood analysis and Bayesian analysis trend results. Arrow style indicates strength of 

trend: black vertical arrow represents greater than 90% Bayesian probability or significance (P < 0.05) of trend; light gray vertical arrow 

represents greater than 65% Bayesian probability of trend; horizontal gray arrow represents lower (<65%) Bayesian probability of trend or 

no significant trend detected (maximum likelihood). Upward pointing arrow indicates a positive trend and downward pointing arrow 

indicates a negative trend.

Stratum

North Coast Mid-Coast Mid-South Umpqua River

Maximum likelihood (BRT)Maximum likelihood (ODFW)Bayesian probabilitiesMaximum likelihood (BRT)Maximum likelihood (ODFW)Bayesian probabilitiesMaximum likelihood (BRT)Maximum likelihood (ODFW)Bayesian probabilitiesMaximum likelihood (BRT)Maximum likelihood (ODFW)Bayesian probabilities

Winter 

parr

Summer 

parr

Channel 

score

Wood 

volume

% fine 

sediment 

in riffles
171

Figure C-5. Posterior distributions of trend estimates for three measures of habitat complexity (winter 

parr, summer parr, channel score) and two habitat metrics (fine sediment, i.e., percent fine sand 

and sediment in riffles, and large wood, i.e., volume of LWD). Each probability distribution is 

colored to represent the region less than zero (red) and greater than zero (black). Ninety-five 

percent credible intervals are shown with vertical gray lines and trend point estimates at the level 

of individual sites are shown in blue circles (whose sizes correspond to the number of data 

points). The proportion of each posterior trend estimate less than zero is quantified in red in the 

upper left corner of each panel.

Ideally, the posterior trend estimate will be driven by the sites that have the most data, 

with outliers representing sites with few site visits. For many of the metrics, there is agreement 

in the posterior trend for the region and the individual site trends within the region (Figure C-5). 

For some combinations of regions and metrics, there appears to be some discrepancy (e.g., 

summer and winter parr in the North Coast, LWD pieces in all regions). This discrepancy is not 

a failure of the estimation or the modeling approach used, but suggests that the HTWG may want 

to consider further hypotheses in future analyses. For instance, rather than assuming all sites 

within a region share the same trend, the HTWG might consider alternative hypotheses based on 

trends being shared among populations.
172

The HTWG was interested in comparing trends in habitat metrics inside and outside coho 

salmon spawning/rearing habitat. The BRT’s analysis focused on all sites, and sites beyond 

spawning/rearing habitat may be different (they are generally located higher in watersheds). The 

HTWG repeated the trend analysis on the two raw metrics (percent sand and organic sediment in 

riffles, large wood volume) for sites not considered to be coho spawning or rearing habitat (n = 

887). The biggest difference between sites inside and outside spawning habitat is that sites not 

designated as spawning/rearing habitat have negative declines in large wood volume for all 

regions (Figure C-6).

Summary

The HTWG’s analysis expanded on the original BRT analysis, and there are important 

differences between the trends originally estimated by the BRT and those estimated by the 

HTWG. The primary source of these differences was the data set used for the analysis. After 

restricting the data to sites designated as coho spawning/rearing habitat and correcting several 

errors in the database, the HTWG is confident that results are insensitive to the choice of model 

or estimation approach used. In addition to changing some of the estimates reported by the BRT, 

the results from the HTWG also change the estimates reported in ODFW’s analysis (Anlauf et al. 

2009). An example of a result that changed is that rather than the AREMP channel score 

declining in three of the four regions, there is now evidence of increasing trends in three of the

Figure C-6. Posterior distributions of trend estimates for two habitat metrics (percent fine sand or organic 

material in riffles and volume of LWD). Estimates are presented for each region. The data set 

analyzed is all sites that are not designated as coho spawning or rearing habitat. Each probability 

distribution is colored to represent the region less than zero (red) and greater than zero (black). 

Ninety-five percent credible intervals around each estimate are shown with vertical light gray 

lines. The proportion of each posterior trend estimate less than zero is quantified in red in the 

upper right corner of each panel.
173

four regions (Table C-5). Some of the original results initially reported by the BRT remain 

unchanged, however. There appears to be little or no change in winter parr capacity in the two 

northern regions (North Coast, Mid-Coast), and negative declines in the two southern regions 

(Mid-South = –2.5% and Umpqua = –1.3%). Other measures of habitat complexity trend 

positive or negative, depending on region, and there is no strong positive increase in complexity 

for all regions.

Table C-5. Bayesian trend estimates (means) applying the BRT’s trend model to the HTWG’s data set. 

The original trend estimates and proportion of the posterior less than zero (Pr < 0) are given in 

parentheses.

Stratum

Channel score Summer parr Winter juveniles

Slope Pr < 0 Slope Pr < 0 Slope Pr < 0

North 

Coast

0.006 (–0.02) 0.17 (1.00) 0.009 (–0.02) 0.32 (0.80) 0.0 (–0.02) 0.55 (0.90)

Mid-Coast 0.006 (–0.01) 0.18 (0.88) 0.027 (0.02) 0.08 (0.24) 0.00 (0.00) 0.64 (0.48)

Mid-South 

Coast

–0.025 (–0.02) 1.00 (1.00) 0.03 (–0.08) 0.09 (1.00) –0.025 (–0.03) 0.95 (0.99)

Umpqua 

River

0.003 (0.00) 0.36 (0.48) –0.028 (–0.08) 0.88 (1.00) –0.013 (–0.03) 0.79 (0.99)
174
175

Appendix D: Peer Reviews and Public Comments

with the BRT’s Responses

This appendix has four subsections: Comments of Eight Peer Reviewers, Comments of 

the Oregon Department of Fish and Wildlife, Comments of the MidCoast Watersheds Council 

Coordinator, and Comments of Douglas County. Our Oregon Coast Coho Salmon Biological 

Review Team (OCCS BRT) responses to these comments are contained in brackets and placed 

within the text of the original comments. Some of the peer reviewer comments were edited for 

clarity and some style and format changes were made to those and the public comments, 

including inserting additional paragraph indents, to accommodate the insertion of responses. For 

the original text of the three public commentators, due to the length and public availability of 

their comments, we refer the reader to http://www.regulations.gov/#!docketDetail;dct=FR

%252BPR%252BN%252BO%252BSR%252BPS;rpp=25;po=0;D=NOAA-NMFS-2010-0112.

Comments of Eight Peer Reviewers

Reviewer 1

Here are some comments on the status of Oregon coastal coho. I read most of the report 

and found it comprehensive, well written and up to date on the literature. Nice job by the 

authors.

I thought that the Climate Change subsection was excellent, covering potential changes in 

both salmon physiology and change in habitats.

I did not see a section on specific recommendations for management and I think that this 

would be logical and desirable. For example, this review could state possible ways that climate 

change could be ameliorated: protection of cold water refugia, enhancement of wetlands and 

uplands, better riparian protection of “non-fish bearing” streams, beaver reintroduction, 

reduction of irrigation and promoting instream water rights during critical periods, removing 

catch limits on invasive species such as bass, etc. Some of these are covered in the text, but not 

emphasized as action items for managers or researchers.

[Response: The goal of this document is documentation of the OCCS BRT deliberations. It is 

not appropriate, therefore, to address action items for managers or researchers here. That is the 

function of the recovery planning process and should be included in a recovery plan.]

The subsection on predation is rather dated. Reference could be made to impacts of 

Caspian terns in the Columbia (Roby and Collis). What about predation in estuaries (Steve 

Johnson, Alsea), and cormorants in the Nehalem Bay? Paragraphs on Humboldt squid, however, 

were excellent.
176

[Response: We updated our discussion of predation with a look at new (Johnson et al. 2010) and 

somewhat older (Schreck et al. 2002) literature as a recent population assessment of doublecrested cormorants (Phalacrocorax auritis) in the evolutionarily significant unit (ESU) and other 

sources. We did conclude that the significant increases in avian predation appear to be restricted 

to the Columbia River System and does not affect the OCCS ESU as much as it does the 

Columbia River ESUs because of where the birds (Caspian terns [Hydroprogne caspia] and 

double-crested cormorants) are nesting and foraging during coho salmon (Oncorhynchus kisutch) 

smolt outmigration.

Reviewer 2

Please find my review of the suggested section of the Oregon Coast Coho status review 

(pages 59–85). Overall very well written, nice analysis and interpretations—very 

complementary to work by ODFW and other agencies. My comments are referenced by the 

draft’s page number, paragraph, and sentence.

Comments on section pertaining to “The Present, or Threatened Destruction, 

Modification, or Curtailment of its Range” (draft pages 59–85).

Conclusions quoted regarding present impacts of hydropower should be expanded to 

consider future development as well. I know there are possible plans for hydroelectric dams to 

be placed in some coastal rivers, such as the Siletz River near the former town site of Valsetz. 

Also the development of small hydro may come into play in the future as the region develops 

alternative energy sources. This is becoming an issue in other parts of western North America 

(e.g., British Columbia) (page 59, paragraph 1).

[Response: Mention of this possibility has been included in the revised document.]

Should also mention the U.S. Forest Service database on barriers and fish passage 

(contact Bruce Hansen: bhansen@fs.fed.us.) (page 59, paragraph 3.)

[Response: The ODFW 2009 fish barrier database includes the U.S. Forest Service data.]

In the Umpqua and other basins where nonnative centrarchid (bass, bluegill, and 

relatives) invasions are underway (e.g., Coquille and likely other systems), increases in 

temperature will shift the balance toward favoring these species at the expense of native 

salmonids. “Native” invasions are also likely to occur and be important, as pointed out by 

Reeves et al. and other work on interactions between minnows and salmonids in relation to water 

temperature. These points may be covered elsewhere in the document. Threats are also possible 

from invaders that have yet to reach the northwest, such as northern pike (Esox lucius) or Asian 

carp (Hypophthalmichthys harmandi). I hope species like this never reach habitats with Oregon 

Coast coho, but control of these invasions has proved less than complete in other areas. It is 

worth worrying about (page 61, paragraph 3).

[Response: In response to these comments, the BRT discussed this issue more fully; expanded 

discussion and literature citation is included in the revised document in the Ecosystem impacts of 

nonindigenous species subsection, Nonindigenous plant species subsection, and Nonindigenous 

fish subsection.]
177

Comment on “stream complexity:” This seems to deal mostly with local complexity and 

I assume larger-scale or “landscape” complexity is dealt with elsewhere (page 62).

[Response: Larger-scale or landscape complexity was treated in somewhat more depth in the 

revised BRT document; however, for this assessment, local complexity was the focus of our 

analyses.]

Useful to clarify that stream cleaning was a historical practice no longer endorsed by 

ODFW (page 63).

[Response: This has been clarified in the document.]

I think you mean to say inter-annual, not intra-annual (page 64, paragraph 5, line 5).

[Response: This was revised.]

Overall in this discussion I am not sure if we are seeing cycles or trends in beaver 

activity. The table seems to show three cases of declines, two of increases, and one of no change 

(zero in both years). Not sure if this is statistically or biologically “significant.” I don’t think 

there is good evidence for a trend of any kind.

[Response: We added the following statement in the Beaver in OCCS habitat subsection: “Due 

to the limited data set we cannot conclude that there is an overall trend and would recommend a 

more extensive monitoring effort be pursued to identify short-term and long-term trends 

throughout the OCCS ESU.”]

Also clarify that the work by Pollock et al. was done in Washington; useful for general 

comparisons, but specific numbers may not apply to Oregon coast.

[Response: We included a paragraph that addresses this comment. “The Pollock et al. (2004) 

study focused, for the most part, on sites in the Puget Sound region; however, the BRT noted that 

the areas where beaver pond density is highest typically have the same physical characteristics 

regardless of the ecological region—lower gradient (less than 2%), unconfined valley bottoms, in 

smaller watersheds (drainage areas typically less than 10 km2

). Smaller, lowland, raindominated Puget Sound watersheds have the same basic physical and hydrological 

characteristics as the smaller Oregon coast watersheds, thus the relationships with respect to 

beaver pond densities in Puget Sound should also hold true for the Oregon coast.”]

I think the simple conclusion to this discussion on beaver is sufficient and I would clarify 

by saying “potential” declines. Probably the largest threat to beaver is how they are currently 

managed. The current situation does not lend itself well to management of beaver to benefit fish. 

The state agencies have organized a working group to address this issue, however (page 66).

[Response: We have captured this comment in revised text in the Beaver in OCCS habitat 

subsection.]
178

Can you term this section “Human Disturbance,” as natural disturbance is usually viewed 

as a positive thing, so long as human activities have not rendered species excessively vulnerable 

to them (page 67)?

[Response: We have changed the subsection title.]

A more complete table caption would be helpful here (Table 15).

[Response: We have revised the caption to clarify the table.]

I think the conclusion here about complexity (rate of continued disturbance outpacing 

restoration) is likely correct, but we don’t know for sure. Local “active” restoration activities are 

likely dwarfed by the larger human footprint on the landscape, but passive efforts to restore 

landscape condition (e.g., improved forest harvest practices) will likely take decades to yield 

detectable positive trends. Might be worth clarifying the issue here because passive restoration 

is much likely to have longer term and more widespread benefits in the future (page 73).

[Response: A short clarification of this issue is now included in the Stream habitat complexity 

summary subsection.]

In the section on land conversion, I noted there was little attention to increases in effects 

associated with urban or rural/residential development, such as septic drainage (nutrients), 

fertilizers, pharmaceutical and personal care products (PPCPs), or other contaminants (e.g., 

herbicides and pesticides). The potential impacts of these factors are more obvious and more 

studied within urban areas, but they are a growing and difficult to detect threat outside of urban 

zones, as land is increasingly developed for homes, hobby farms, and other similar uses. Clearly 

this is an area of great uncertainty—even in well studied urban areas—but it should be 

mentioned here as a potentially serious, yet virtually unknown threat. The State of Oregon 

Independent Multidisciplinary Science Team is producing a report that summarizes many of 

these issues. It might be advisable to contact Dr. Carl Schreck at Oregon State University for 

more information related to this (page 75).

[Response: The IMST (2010) report has just been released and our revision reflects its findings 

in the Land management—forest and agriculture conversion subsection.]

Another place to possibly emphasize factors identified directly above (page 84).

[Response: The Land management—water quality degradation subsection discussion focused on 

temperature issues in the ESU. A discussion that briefly mentions these issues is found in the 

Land management—forest and agriculture conversion subsection.]

I work a lot on impacts of temperature on salmonids and was hoping to see a bit more 

than a paragraph on the issue. It is well studied, but the short amount of text devoted to this issue 

versus hydrogeomorphic factors seems out of balance. Perhaps a sentence or two emphasizing 

the primacy of temperature as a component of habitat and threat to salmon. I believe 

temperature is the number one source of water quality impairment in Oregon (page 85).
179

[Response: New text has been added in the Land management—water quality degradation, 

Effects of climate change on the OCCS ESU, Water availability, and Land management—forest 

and agricultural conversion subsections. Additional emphasis of temperature is found in 

Wainwright and Weitkamp (in prep).]

Overall I found the section I reviewed and supporting material to represent a very useful 

addition to existing information that has been used to evaluate status and threats for Oregon 

Coast coho. Once again the BRT has produced an excellent product and one that would be the 

envy of just about any other team working on threatened fish, thanks to the team’s work and the 

wealth of useful data collected by federal agencies and the state of Oregon.

A few clarifications and additions as suggested above would improve the document in 

my view and do not require major revisions. Thanks very much for the opportunity to review 

this.

Reviewer 3

I just finished with the BRT report and except for several mistakes in terms of incomplete 

sentences or repeated paragraphs, very short and not informative table headings, a few typos and 

other minor things, I think it is in general a good summary of the current situation for coastal 

coho salmon in Oregon.

I do think the emphasis given to the importance of estuarine habitat is moderate and 

adequate, given the information available in the literature. Based on my own experience 

working in creeks that drain into Coos Bay, I think that the early estuarine rearing life history 

strategy (nomadic) is rather common. What we do not know yet is whether it is genetically 

based (expressed by a particular genotype) or just one possible of various expressions of a 

flexible phenotype that is condition dependent (i.e., it becomes common under certain 

environmental conditions or at certain rearing densities). Regardless of the mechanisms behind 

it, this estuarine-based life history may serve as a bet hedging strategy that supports the 

population in years when stream conditions are poor.

In the fall of 2009, we detected nine coho salmon jacks PIT tagged as subyearling 

reservoir residents in spring 2008, suggesting that coho nomads do survive their early life history 

experience and contribute to the spawning population. By affecting coho salmon nomads to a 

greater extent than other life history types, estuary loss may reduce the potential productivity 

boost and resilience component that this life history may contribute to its population of origin

and any metapopulation it may be part of. I have to check Art Bass’ thesis, but he should have 

information in it about those nine jacks.

[Response: Text has been added in this section to capture these comments and to incorporate 

information from Bass (2010) into the text.]

We are going to look into if, and to what degree, “nomad” fish return as spawning adults 

in the next phase of our study. I have to talk Jessica Miller into reading some otoliths we have 

collected, but independently of this, this fall we could be getting the first PIT tagged “nomads” 

returning to spawn.
180

[Response: We have reported the most recent information as of March 2011 in the BRT 

document.]

In coastal streams with well-developed estuaries, the early estuarine rearing strategy coho 

display may be more important for the long-term viability of those populations than the opinion 

you shared with me (see ODFW comments below) reflects. If most or all of the thousands of 

coho fry that move into estuarine habitats early in their lives died before spawning, this would be 

a poorly adaptive behavior that natural selection forces would have eliminated from coastal 

populations (or at least it would be a very rare strategy).

[BRT note: In a written comment on the document, reviewer 3 requested more discussion of 

storm water and floodplain effects. Response: We added discussion of these issues in the Land 

management—forest and agriculture conversion subsection.]

Reviewer 4

Below please find my review of Scientific Conclusions of the Status Review for Oregon 

Coast Coho Salmon, by Stout et al. As requested, I focused my review on the assessment of 1) 

the scientific validity of the status review, including any assumptions, methods, results, and 

conclusions; 2) quality of data used; 3) appropriateness of the analyses; 4) validity of results and 

conclusions; and 5) appropriateness of the scope of the assessment.

Scientific validity of the status review, including any assumptions, methods, results, and 

conclusions: The authors have compiled and examined a tremendous amount of information to 

build on the three previous assessments. The process has been ongoing for more than a decade 

and many scientists with extensive experience and knowledge contributed to the report. The 

BRT concluded that, when future conditions are considered, the ESU is at moderate risk of 

extinction (54% agreement on this risk classification). The authors provide a synopsis of 

previous assessments, then present new information used in the current assessment. Overall, the 

document synthesizes an extensive amount of information in a succinct manner and incorporates 

future threats into the assessment. In many cases, it is difficult to assess the document’s 

scientific validity per se because much of the analyses presented are based on data or conclusions 

from previous studies or documents without sufficient information to assess the data quality or 

previous conclusions. I am not suggesting that complete syntheses of previous efforts be 

included in the current assessment. However, it is challenging to thoroughly assess the current 

conclusions independently, as they rely on much previous work.

The primary methods for the current assessment are the decision support system (DSS) 

based on previously developed criteria and the development of a risk matrix. It appears that the 

metrics and data sources for the criteria are presented in detail in Wainwright et al. (2008), which 

I only briefly examined. Overall, as presented, it is difficult to sort out which data sets were 

included or considered in each of the two analyses. It would be useful and informative to have a 

master table or appendix that clearly listed the metrics and associated data sets that were 

incorporated into the DSS and the criteria to which they were applied.

[Response: This has been included in Appendix A.]
181

It is also not clear how the “truth values” for the recovery criteria were determined. Were 

these based on the opinions of the BRT or some quantitative assessment? Although much of this 

information may be presented in Wainwright et al. (2008), it seems that inclusion of adequate 

information to understand the approach of the current DSS is appropriate.

[Response: More information on this is included in the TRT Biological Recovery Criteria 

Analysis subsection, but because of the length of the truth value discussion, we refer readers to 

Wainwright et al. (2008.)]

Table 6 and Table 7 provide great synthesis of the major conclusions. Similarly, a 

relatively minor amount of additional information presented as a summary table may help this 

important analysis stand-alone in this document more effectively.

[Response: This table is included in Appendix A.]

An example is the passage barrier data set. From the text, it appears that there are no data 

for private lands, although this is not clearly noted in Figure 14.

[Response: The caption has been revised to reflect the absence of private lands from the data 

set.]

How are these data used in the DSS? It is indicated that there are low to moderate 

changes compared to historical template for the passage criteria, although it is not clear what this 

means or how it was determined.

[Response: The historical template was determined by an expert panel made up of TRT 

members and discussed at length in Wainwright et al. (2008.) It is not included here due to 

length.]

Additionally, was the recent disturbance analysis included in the DSS or only considered 

in the ESU risk matrix? 

[Response: The disturbance analysis was not included in the DSS, as it was not one of the 

recovery criteria that was developed by the TRT and discussed in Wainwright et al. (2008.) It 

was individually taken into account by each BRT scientist in voting with the Risk Assessment 

Matrix and the FEMAT voting sheet.]

The second primary synthesis is the ESU risk matrix, which is based on professional 

opinion. In this matrix (Table 22), the analyses were separated into status with and status 

without consideration of future trends, so that two matrices were developed. There was another 

risk matrix (Table A-1), but it is not clear how those categories were scored and if or how they 

were incorporated into the overall ESU risk matrix (i.e., Table 22).

[Response: The second risk matrix found in the appendix was actually mislabeled in the BRT 

document. That matrix was utilized as a memory aid for the BRT’s discussion of threats so the 

BRT scientists could keep notes on the many types and magnitude of threats to OCCS at the 

ESU, biogeographic stratum, or population level.]
182

If it was presented, it could be more explicit, as I could not locate a specific explanation 

when I looked back through the document. Also, was there consideration of incorporating the 

results from the DSS into the ESU risk matrix?

[Response: The results from the DSS were considered with other information discussed by the 

members of the BRT. The BRT then used this in voting using the ESU risk matrix.]

As many of the DSS criteria could be grouped into the five categories used for the risk 

matrix, it appears that the DSS results could be averaged into the final assessment, perhaps 

counting as one or more “professional” opinions. It seems that an objective inclusion of the 

data-based DSS assessment combined with professional opinion may reduce the spread of 

opinion and would strengthen the overall conclusions.

[Response: Indeed, it would seem logical to include the DSS in the risk matrix which is, after 

all, a kind of DSS itself. However, the DSS used by the BRT was created by the TRT for a 

somewhat narrower purpose. The risk matrix as implemented by the BRT is a standard approach 

for evaluating the status of marine species in the Pacific Northwest. As we learned in the TRT, 

building a DSS for this kind of evaluation is difficult and time consuming. While taking the 

approach suggested by the reviewer may have “strengthened the overall conclusions,” it was not 

feasible, given the time available. Instead, we essentially used nested DSSs, with the TRT’s 

DSS informing the expert opinion input to the risk matrix.]

I also wondered if there was any discussion of incorporating “future threats” into a DSS 

framework to provide a more quantitative assessment of future risk. The challenges associated 

with quantifying future threats associated with climate change were discussed and a rationale 

was presented for a qualitative approach, but given the range of certainty associated with various 

future actions, it seems that some type of quantitative assessment could be developed and 

incorporated.

[Response: Incorporating future threats into a DSS framework would be an interesting and 

potentially valuable approach, but outside the scope and ability of the BRT within courtmandated time constraints.]

Quality of data used: As noted, it is not really possible to assess the quality of the data 

incorporated in the assessment itself, as very few details on data acquisition and analytical 

methods are included here. The status report obviously cannot be a summary of all data 

collection methods ever used to compile information on coastal coho. However, as noted above, 

a table or appendix that clearly lists the data sets included in the status assessment, along with 

their sources, the period of data collection, and which analyses they were used for, would be very 

useful. Given the “truth values” associated with the DSS, it appears that there are opinions or 

decisions rendered regarding the quality of the data sets, which could be included as well. With 

such an approach, it would be much easier for reviewers or other researcher/managers to assess 

the data availability and, potentially, quality of particular data sets.

[Response: The DSS was thoroughly documented and justified in Wainwright et al. (2008). A 

table summarizing data sets and sources is now provided in Appendix A.]

Several of the comments below address [items] 3 through 5 listed above.
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The scope of the document appears appropriate. I think the attempt to include some 

assessment of the extensive restoration activities throughout the region was a valuable and 

important component. The future threats assessment is important, although challenging, and 

synthesizes much of the available information. Given that the consideration of future threats 

effectively changed the conclusion from not at risk (low risk) to moderate risk, their inclusion is 

clearly an important aspect of the current assessment. Along those lines, as noted above, 

development of a more quantitative process to incorporate future threats into the methodology 

could prove valuable.

[Response: We agree that a more quantitative process for incorporating future threats would be 

desirable. Future threats must be evaluated in terms of effect on viability of the species. Likely 

effect depends on the likelihood of occurrence of the future conditions and the expected 

magnitude or strength of the effect. This is a highly subjective exercise that would require an 

advance in the state of the art of applying DSSs to conservation biology and resource viability 

assessment.]

Although possibly outside of the scope of this assessment, a clear identification of key 

data gaps would be an important outcome. Given that the adequacy of available information is a 

component of the risk assessment, future data collection efforts would be aided by a clear 

articulation of key gaps in knowledge that the BRT identified. Again, one can infer some of 

these by reading the text, but a clear summary of the combined opinion of the BRT as to which 

data gaps were the most relevant would be useful.

[Response: In response to this request, the BRT identified some of the most important data gaps 

such as beaver populations and fish passage and discussed them in the appropriate text.]

A more general comment related to organization: I had some trouble with the 

organization of the information. The initial section summarizes previous assessments, which is 

clear for the most part but would also be enhanced by a table with a timeline and relevant 

synthesis documents identified. The document then transitions from previous assessments into 

the current work. The New Contributions section includes basic information regarding the 

current approach. The populations are identified in a table but the biogeographical strata are not. 

It would be useful to include the recognized strata.

[Response: We have added additional text to enhance the clarity of the document and included 

the table of the timeline and a map of the biogeographic strata for a more informative 

discussion.]

This section is then followed by public comment and a qualitative summary of a 

symposium; it is not clear if or how this information was used in the current process. Perhaps 

these comments and the symposium summary could be included as an appendix or their purpose 

more clearly articulated in the document.

[Response: The public comments and information presented in the symposium were considered 

in the BRT’s deliberations and as such are germane to presentation of information in the BRT 

document. Additional text was added to clarify the use of these two sources of information.]
184

Then the New Data and Updated Analyses section presents the information used in the 

current assessment. Again, it was not always clear which categories where considered 

quantitatively as data incorporated into the DSS and which were qualitative assessments 

considered by the BRT for the Risk Matrix. I was a bit confused by some of the redundancies 

between the main body of the text and the appendices. For example, much of the habitat 

complexity discussion (≈p. 70–72) is repeated in Appendix E. Typically, I think of an appendix 

as supplementary data that are referenced at the appropriate location in the text for those readers 

seeking additional detail (similar to Appendix F).

[Response: For the Draft BRT document, source documentation of analyses were included in the 

appendices of the document because they are not yet published, and we wanted to make these 

analyses available for comment. In the final technical memo, most of these documents are in 

review or in press, so will not be included. Two reports, however, one on landscape disturbance 

and the other prepared by the Habitat Trends Working Group, remains in the appendices because 

of the utility in understanding the Land use management—stream habitat complexity discussion.]

The data since 1994 presented in Table 2 and Figure 6 do not match as the text indicates 

they should. For example, year 2000 had 66,900 spawners and 72,200 recruits but in Figure 6, 

the number of recruits is much less? I realize that harvest levels changed at this time but it does 

not appear to explain the discrepancy.

[Response: Figure 6 was erroneously cited. That has been rectified in the document.]

A somewhat broader definition of life history in the glossary may be useful. A life 

history encompasses changes experienced from birth through death, including variation in life 

history traits, such as the size and age at maturity, fecundity. Arguably traits, such as juvenile 

growth rate, age at ocean emigration, are aspects of species’ life history.

[Response: Text has been added to the glossary to capture this comment.]

Reviewer 5

I reviewed the document you provided and did not find anything surprising in the habitatrelated sections. I did have a couple of comments on the figures that went with the document. I 

think Figure 16 is of active road densities and does not account for legacy roads that are not 

maintained and that may pose long-term risks. Figure 26 appears to be of 303(d) listed streams 

with documented temperature problems or simply streams with documented temperature 

problems (?), though this is not clear in the title.

[Response: Captions for these two figures have been changed to respond to your suggestion.]

Reviewer 6

Review of Oregon Coast Coho status review: Ocean conditions section.

While Good et al. cite evidence for an important shift in climate around 1998, there are 

no methods for generating climate forecasts that have proven to have skill at lead times of greater 
185

than about 1 year (almost all the skill is linked to ENSO monitoring, predictions, and 

teleconnections) (p. 51).

Periodic warming of the CCS [California Current System] related to major El Nino 

events or more regionally generated wind anomalies (like those in the spring and early summer 

of 2005) can cause range expansions for some species, but also range contractions or depth 

changes for others. Basically, episodic warm extremes in the CCS are caused by a failure of the 

typical spring/summer seasonal upwelling process to pump cold and nutrient-rich water into the 

surface layer of the coastal ocean, and to reduce the north-south transport of “subarctic” water 

over the continental shelf (p. 52, first paragraph).

Changes in ocean conditions appear to simultaneously impact the lower tropic levels that 

influence the forage base for coho, and at the same time alter the horizontal (and perhaps 

vertical) distribution of coho competitors and predators. This section on ocean conditions is 

completely focused on the competitors and predators, and would be improved with more 

discussion of regional winds, stratification, nutrient concentrations, phytoplankton and 

zooplankton production and species assemblages, and forage fish.

I really like the discussion of Humboldt squid range changes, and how it is used to 

illustrate the complex and apparently unpredictable nature of important aspects of the CCS 

marine ecosystem.

Third sentence from bottom is missing some text (p. 54).

Lead sentence should be in bold, missing a period at the end (p. 55, second paragraph).

Table 11 [now Table 14, revised to reflect these comments]:

Note that early spring peak flow only applies to snowmelt-dominated watersheds, and 

many Oregon coast coho streams are rainfall dominated, so would not experience snowmeltrelated shifts in stream flow timing. Likewise, flood frequency and timing changes due to a 

warming climate are also dependent in part on the type of hydrology that characterizes different 

watersheds (e.g., rain-dominant, mixed rain/snow “transient,” or snowmelt dominant). For most 

coho watersheds, the main factor that influences flood frequency and intensity is rainfall 

frequency and intensity. Generally speaking, rainfall intensity is expected to increase in a 

warming climate, but confidence in this at the regional scale is relatively low. See Mantua et al. 

2010 for a recent analysis of projected changes in high and low flow statistics for Washington 

State watersheds:

Mantua, Tohver, and Hamlet. 2010. Climate change impacts on streamflow extremes and 

summertime stream temperature and their possible consequences for freshwater salmon 

habitat in Washington State. Clim. Change. DOI: 10.1007/s1058409845-2.

I think that the prediction for delayed spring transition as a consequence of climate 

change should be rated as “low confidence,” given that there is only one study that has looked at 

this (Snyder et al.), and that was based on a single climate model’s output. Bograd et al.’s 

analysis of trends in upwelling winds did identify a trend to a later spring transition in the 

northern part of the CCS over the 1967–2007 period, however, there was no attempt at 
186

attributing that trend to anthropogenic climate change. This relatively short period of record 

contains a great deal of natural variability at interannual to interdecadal time scales, so I would 

caution against overinterpreting the findings of their analysis.

For higher stream temperature, some discussion of potential benefits in winter is 

warranted. For instance, the experimental logging studies on Carnation Creek showed a strong 

stream temperature response to logging, and along with the temperature change came increasing 

growth rates for rearing coho. See:

Holtby, L. B. 1988. Effects of logging on stream temperatures in Carnation Creek, British 

Columbia, and associated impacts on the coho salmon (Oncorhynchus kisutch). Can. J. 

Fish. Aquat. Sci. 45:502–515.

Holtby, L. B., and M. C. Healey. 1986. Selection for adult size in female coho salmon 

(Oncorhynchus kisutch). Can. J. Fish. Aquat. Sci. 43:1946–1959.

For marine impacts, I would include increased upper ocean stratification. Increased 

stratification will likely limit the ability of wind-driven upwelling to pump cold, nutrient-rich 

water into the well-lit surface layer, and this may reduce phytoplankton production and alter the 

phytoplankton species community. Increased upwelling, if it becomes too strong, may not be 

favorable for increased phytoplankton and zooplankton production if surface layer waters are 

swept offshore so rapidly and consistently that phytoplankton and zooplankton are not able to 

keep pace with the too-energetic physical system.

This table appears to blend the climate change certainty with the ecological impacts 

certainty, and this is problematic. For instance, increased acidity due to increasing atmospheric 

concentrations of CO2 has already been documented, and is virtually certain to continue into the 

future. The ecological impacts are poorly understood, so that part can be rated with a lower 

certainty. Perhaps this distinction can be made explicitly in the table caption. For some physical 

changes, the certainty is much lower (e.g., changes in precipitation).

Appendix C, p. 17: The last sentence of the first full paragraph should be modified to 

better reflect the fact that no attempt has been made at attributing recent trends in various 

environmental factors related to coastal upwelling in the CCS to anthropogenic climate change. 

While the results of Snyder et al.’s modeling study and those of Bograd et al.’s analysis of 1967–

2008 upwelling winds share some commonalities, together they do not constitute evidence that 

anthropogenic climate change is already altering coastal upwelling in the CCS. In order to make 

that statement, one needs to carry out a formal detection and attribution study, and no such study 

has been done.

The issue of twentieth century trends in springtime Cascade snowpack has received a 

great deal of attention in recent years, and the section here should reflect some of the more recent 

contributions to the literature. A key issue evaluated in these studies is the relative roles of 

natural low-frequency variability like that associated with the Pacific Decadal Oscillation (PDO)

versus the “forced” part of climate change due to increasing concentrations of greenhouse gases 

and aerosols. Both appear to have played important roles in the observed snowpack trends 

between the 1930s, 1940s, and 1950s, and the late twentieth century/early twenty-first century. 
187

Basically, it is an oversimplification to say that the observed declines in Cascade snowpack from 

the mid- to late-twentieth century are due to the regional impacts of global warming.

Recent studies worth citing (along with their abstracts) include:

Casola, J. H., L. Cuo, B. Livneh, D. P. Lettenmaier, M. Stoelinga, P. W. Mote, and J. M. 

Wallace. 2009. Assessing the impacts of global warming on snowpack in the 

Washington Cascades. Journal of Climate 22:2758-2772, doi: 10.1175/2008JCLI2612.1.

The decrease in mountain snowpack associated with global warming is difficult to 

estimate in the presence of the large year-to-year natural variability in observations of snow 

water equivalent. A more robust approach for inferring the impacts of global warming is to 

estimate temperature sensitivity λ of spring snowpack and multiply it by putative past and future 

temperature rises observed across the northern hemisphere. Estimates of λ can be obtained from 

a) simple geometric considerations based on the notion that as the seasonal-mean temperature 

rises by the amount δT, the freezing level and the entire vertical profile of snowpack should rise 

by the increment δT/Γ, where Γ is the mean lapse rate, b) regression of April 1 SWE 

measurements on mean winter temperatures, c) a hydrological model forced by daily temperature 

and precipitation observations, and d) use of inferred accumulated snowfall derived from daily 

temperature and precipitation data as a proxy for snow water equivalent. All four methods yield 

an estimated 20% loss of spring snowpack for a 1°C temperature rise. The increase of 

precipitation accompanying a 1°C warming can be expected to decrease the sensitivity to 16%. 

Considering various rates of temperature rise over the northern hemisphere, it is estimated that 

spring snow water equivalent in the Cascades portion of the Puget Sound drainage basin should 

have declined by 8–16% over the past 30 years due to global warming and it can be expected to 

decline by another 11–21% by 2050.

Hidalgo H. G., T. Das, M. D. Dettinger, D. R. Cayan, D. W. Pierce, T. P. Barnett, G. Bala, A. 

Mirin, A. W. Wood, C. Bonfils, B. D. Santer, and T. Nozawa. 2008. Detection and 

attribution of stream flow timing change in the western United States. Journal of 

Climate.

The Hidalgo et al. article applies formal detection and attribution techniques to 

investigate the nature of observed shifts in the timing of stream flow in the western United 

States. Previous studies have shown that the snow hydrology of the western United States has 

changed in the second half of the twentieth century. Such changes manifest themselves in the 

form of more rain and less snow, reductions in the snow water contents, and earlier snowmelt 

and associated advances in stream flow “center” timing (the day in the “water-year” on average 

when half the water-year flow at a point has passed). However, with one exception over a more 

limited domain, no other study has attempted to formally attribute these changes to 

anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together 

with a set of global climate model simulations and a hydrologic model (applied to three major 

hydrological regions of the western United States, the California region, the Upper Colorado 

River basin, and the Columbia River basin), we find that the observed trends toward earlier 

“center” timing of snowmelt-driven stream flows in the western United States since 1950 are 

detectably different from natural variability (significant at the P < 0.05 level). Furthermore, the 

nonnatural parts of these changes can be attributed confidently to climate changes induced by 

anthropogenic greenhouse gases, aerosols, ozone, and land use. The signal from the Columbia 
188

dominates the analysis, and it is the only basin that showed detectable signals when the analysis 

was performed on individual basins. It should be noted that, although climate change is an 

important signal, other climatic processes have also contributed to the hydrologic variability of 

large basins in the western United States.

Stoelinga, M. T., M. D. Albright, and C. F. Mass. 2010. A new look at snowpack trends in the 

Cascade Mountains. Journal of Climate 23:2473–2491.

Stoelinga et al.’s study examines the changes in Cascade Mountain spring snowpack 

since 1930. Three new time series facilitate this analysis: a water-balance estimate of Cascade 

snowpack from 1930 to 2007 that extends the observational record 20 years earlier than standard 

snowpack measurements; a radiosonde-based time series of lower-tropospheric temperature 

during onshore flow, to which Cascade snowpack is well correlated; and a new index of the 

North Pacific sea level pressure pattern that encapsulates modes of variability to which Cascade 

spring snowpack is particularly sensitive.

Cascade spring snowpack declined 23% during 1930–2007. This loss is nearly 

statistically significant at the 5% level. The snowpack increased 19% during the recent period of 

most rapid global warming (1976–2007), though this change is not statistically significant 

because of large annual variability. From 1950 to 1997, a large and statistically significant 

decline of 48% occurred. However, 80% of this decline is connected to changes in the 

circulation patterns over the North Pacific Ocean that vary naturally on annual to interdecadal 

time scales. The residual time series of Cascade snowpack after Pacific variability is removed 

displays a relatively steady loss rate of 2.0% decade–1

, yielding a loss of 16% from 1930 to 2007. 

This loss is very nearly statistically significant and includes the possible impacts of 

anthropogenic global warming.

The dates of maximum snowpack and 90% melt out have shifted 5 days earlier since 

1930. Both shifts are statistically insignificant. A new estimate of the sensitivity of Cascade 

spring snowpack to temperature of −11% per °C, when combined with climate model projections 

of 850-hPa [hectopascals] temperatures offshore of the Pacific Northwest, yields a projected 9% 

loss of Cascade spring snowpack due to anthropogenic global warming between 1985 and 2025.

[Response: Wainwright and Weitkamp (in prep.) was revised to reflect the changes suggested by 

this peer reviewer and now includes information and citations of the suggested scientific articles. 

These are also reflected in the BRT document in the Effects of Climate Change on the OCCS 

ESU subsection.]

Reviewer 7

Review of Scientific Conclusions of the Status Review for Oregon Coast Coho Salmon 

(Oncorhynchus kisutch).

General Comments

The BRT is to be commended for producing an objective, professional assessment of the 

current status of Oregon coast coho salmon and the likelihood that this ESU will persist into the 

future. I found the presentation of data clear and the conclusions drawn from them reasonable. 
189

In particular, I found myself agreeing with the report’s overall risk analysis that Oregon coast 

coho face a moderate risk of extinction over the next century.

The inclusion of the potential impacts of climate change on coho habitat was helpful, as 

was the inclusion of other factors (e.g., human population growth and land use conversions) that 

will be likely to cause problems for the species. Given the overwhelmingly strong scientific 

evidence for climate change and the near certainty of population growth and land conversion 

along the Oregon coast—all of which have major implications for habitat quality—it would have 

been imprudent to ignore these factors. Additionally, it is quite probable that there will be 

interactions among these factors, many unforeseen at present, which could exacerbate habitat 

loss.

[Response: The underpinning of the analysis found in the BRT document is now found in detail 

in Wainwright and Weitkamp (in prep.) This manuscript has been significantly refocused and 

revised to respond to peer review and internal NWFSC review.]

If anything, I might have been tempted to emphasize the potential future spread of 

species not currently prominent in the area that could impact coho. Some of these are exotic 

plants and animals and some rare species will simply become more abundant along the Oregon 

coast as the climate gradually warms, but in any case the presence of more people and changes in 

land development patterns will favor a future with a different suite of species than the aquatic 

and riparian communities of today, and there really isn’t much we can do about it. In some 

recent literature restoration ecologists have referred to this as a “no analogue future.”1

[Response: In response to these comments, the BRT discussed this issue more fully and 

expanded discussion and literature citation is included in the revised document in the Ecosystem 

impacts of nonindigenous species subsection, Nonindigenous plant species subsection, and 

Nonindigenous fish subsection.]

I was impressed with the landscape-level analyses of overall habitat condition, which 

indicated that freshwater habitats for coho are gradually worsening (especially in the last decade, 

which surprised me a bit). This conclusion will surely draw the attention of policy makers. I 

wish there were a way in which future effects of restoration (again, on an ESU-wide basis) could 

be similarly quantified, but as the report points out, it is difficult to project future benefits with 

certainty of projects that take decades to mature. I’ve often felt there is a pressing need to 

determine whether habitat is currently being lost or damaged faster than it can be restored or 

rehabilitated, particularly because so much money is being spent on recovering salmon habitat 

based on the belief that long-term improvement can be achieved at very large spatial scales. 

Based on this assessment, covering an area that has received considerable restoration investment 

(Oregon Plan) and regulatory overhaul (Forest Practices Act and Northwest Forest Plan), I would 

have to conclude that the jury is still very much out.

 

1 Hobbs, R. J., and V. A. Cramer. 2008. Restoration ecology: Interventionist approaches for restoring and 

maintaining ecosystem function in the face of rapid environmental change. Annu. Rev. Env. Resour. 33:39–61.
190

I was pleased to read that ODFW has significantly altered its hatchery program to reduce 

impacts on naturally spawning coho populations. The state is probably at the forefront of 

acknowledging the potential evolutionary and ecological harm caused by unintended mixing of 

hatchery and wild stocks, and they are to be congratulated for taking positive steps to improve 

the situation.

Following are some comments specific to different sections of the report.

In the discussion of habitat changes prior to and including 1996, what was the impact of 

the (February?) 1996 flood? I would guess that this one event had a significant effect on coho 

habitat, but it isn’t mentioned here (page 15).

[Response: We added some text to highlight this important event, but the Habitat Trends 

Working Group did not examine this issue as such. Unfortunately, the flood predated the habitat 

monitoring program that ODFW operates that did allow an assessment of habitat changes over 

the last 11 years.]

The categorization of threats to coho habitat doesn’t really include anything about food 

web alterations, which may be an oversight. Although I realize we don’t know as much about 

trophic changes as we do about physical habitat changes, food web alteration is an issue that 

deserves more attention, in my opinion. Are we seeing any fundamental shifts in food web 

structure (say, in estuaries due to reductions in FPOM [fine particulate organic matter]) that

could affect productivity (pages 48 and 49)?

[Response: The BRT assessment did not focus on trophic level changes in lakes and estuaries, 

although we did mention the issue as a result of exotic fish and invertebrate species and 

temperature rise in a general sense.]

The discussion of water availability centers on water withdrawals, but I think there 

should be a few sentences on the effect of accelerated erosion on surface runoff. One of the 

predictions of climate change models is a slight increase in flooding, which is often accompanied 

by mass wasting. As valleys gradually fill with coarse alluvium, my guess is we will see less 

surface flow and more subsurface flow, and some streams that are currently perennial could 

become seasonally intermittent. This could become an issue in some of the smaller streams that 

will experience less runoff anyway over time. Perhaps someone already has considered this 

(page 60).

[Response: We added text to the Water availability subsection to highlight this issue.]

I thought the definition of stream complexity, as used in the report, was a little vague. In 

most cases it appeared to be used synonymously with pool abundance. A bit of clarification 

would help if pool habitat is really what was meant (page 62 and elsewhere).

[Response: We have attempted to clarify the definition of stream complexity with text changes 

wherever it is appropriate.]

Equating disturbance (in this case, logging) with habitat loss seems to be one of the main 

points of the discussion, but I would suggest some caution here. I agree that the evidence is 
191

strong that logging impacts have shifted from federal to state/private lands, but a more 

persuasive case should be made that private lands are where the problem now primarily resides. 

For example, long-term impacts to coho in the Alsea watershed study appear to be less than 

impacts to coastal cutthroat trout.2 The whole “disturbance = habitat loss” issue as it applies to 

coho deserves additional discussion. My personal bias, of course, is that some types of 

disturbance are beneficial (pages 68 and 69).

[Response: This comment led to a major addition to text in the Human landscape disturbance 

subsection.]

I agree that temperature increases will exact a greater metabolic toll on parasitized or 

infected fish, but temperature may also affect the infection/infestation rate itself. In my 

prehistoric thesis research I found that elevated temperature actually reduced infestation rates by 

Nanophyetus on juvenile Chinook.3 It is possible that climate change will promote the spread of 

some pathogens and reduce the problems caused by others. And we have a very poor 

understanding of the effects of new parasites and diseases associated with invasive species (page 

85).

[Response: We have added some brief text to capture this comment.]

Explicitly mentioning that climate change will contribute to both storm and wildfire 

severity will help to show why it is such an important factor in projecting future habitat changes 

(page 96).

[Response: Wainwright and Weitkamp (in prep.) included a more complete discussion of this 

issue.]

That’s it. Once again I’d like to compliment the BRT for its excellent work. If you have 

any questions, please don’t hesitate to contact me.

Reviewer 8

I enjoyed the executive summary, but frankly, I was disappointed at the brevity of the

section where I was hoping to find synthesis of the population structure work (p. 33).

Although Mike Ford’s and one of Marc Johnson’s papers were referenced, I could not 

find the area where these were discussed. Sorry my time is so short. Can you perhaps help lead 

me to where I might find further discussion of genetics work? Is this perhaps in Lawson et al. 

2007?

 2 Gregory, S. V., J. S. Schwartz, J. D. Hall, R. C. Wildman, and P. A. Bisson. 2008. Long-term trends in habitat 

and fish populations in the Alsea basin. In J. Stednick (ed.), Hydrological and biological responses to forest 

practices: The Alsea watershed study, p. 237–258. Ecological Studies 199, Springer, New York. This paper really 

should be cited in the report.

3 Bisson, P. A., and G. E. Davis. 1976. Production of juvenile Chinook salmon, Oncorhynchus tshawytscha, in a 

heated model stream. Fish. Bull. 74(4):763–774.
192

I attach a more recent paper from Marc’s work you might not be aware of. This was 

Among top 25 Hottest articles in Earth and Planetary Sciences: Marine Genomics January to 

March 2010.

Not that you have to cite this, just seems that (Ford et al. 2004, Johnson and Banks 2008, 

2009) provide evidence for structure, migration, distribution of diversity, etc., that have 

relevance to thoughts on history, contemporary population dynamics, and futures.

Bucklin et al. 2008 (also attached) provides an interesting comparison—evidence for 

deeper structure in California. This contrast could enable interesting comments related to the 

climate change section—genetic drift—potential futures for Oregon coho etc.

[Response: The Populations and life history diversity section was revised to capture these

comments.]
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Comments of the Oregon Department of Fish and Wildlife

These comments serve to illustrate some of ODFW’s primary concerns with respect to 

the BRT report evaluating the status of the Oregon Coast Coho ESU. The technical nature of 

these comments is intended to establish a starting point for further discussion.

Interpretation of Productivity Trends

Throughout the report, the BRT makes generalizations regarding trends in coho salmon 

productivity that are not consistent with patterns of productivity observed over the last 12 years. 

A typical example (p. 36) states, “Harvest management has succeeded in maintaining spawner 

abundance in the face of a continuing downward trend in productivity of these stocks.” It is 

more accurate to say that, based on the BRT 12-year moving average, coho productivity and 

abundance was generally maintained from the early 1970s until about 1999 and has increased 

significantly from 2000 until 2009.

On page 95, long-term trends are again characterized as “the current BRT was also 

concerned about the long-term downward trend in productivity of this ESU.” Productivity, in 

this sense, is measured as the ratio of returning spawners to parental spawners. The Oregon 

Coast Coho Technical Recovery Team (TRT) workgroup developed a productivity criteria based 

on this “Natural Return Ratio” (Wainwright et al. 2008) that included just the three lowest 

abundance years over the evaluation period. This adjustment was an attempt to evaluate 

productivity somewhat independently of variations in parental abundance or ocean survival. In 

the BRT document, however, Natural Return Ratio (NNR) information (cited as Figure 8 but 

actually Figure 7) includes all years to create and is interpreted by the authors as a long-term 

downward trend since 1959.

The problem with this approach is illustrated by the 2007 return year. The abundance of 

parental spawners was relatively high (168,500) and would not have been included in the TRT’s 

calculation of productivity. Relatively low spawner abundance in 2007 (51,700) is represented 

in the figure with a value for NNR of about –0.2. While low, spawner abundance in 2007 

actually exceeded expectations, given the extremely poor ocean conditions this brood 

encountered on ocean entry (Oregon Coast Coho Conservation Plan Annual Report Card 2008).

The BRT report’s characterization of declining productivity is inconsistent with data 

presented for the TRT Population Productivity (PP-1) criteria presented in Table 6. Comparing 

results from this most recent time series to the earlier TRT report (Wainwright et al. 2008) show 

an overall increase in productivity at the ESU scale. Productivity scores for some populations 

increased dramatically (Nehalem, Alsea) while others were stable or declined slightly from very 

high values in the preceding period. Overall, most populations (18 of 21) had truth values 

greater than 0.25 (BRT report Table 7). This would seem to be an important result; however, the 

text of the BRT report provides no discussion of the PP-1 scores or changes in population 

productivity.

[Response: This subsection has been extensively rewritten and updated and is found in the 

Current Biological Status subsection.]
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Problems with the Persistence Analysis

The BRT report recalculated the scores for critical abundance (PP-3) using data peak 

adult counts from ODFW’s spawning surveys. Peak counts are the highest number of fish 

observed at any one time. Unlike, area under the curve (AUC) counts, peak counts are not 

adjusted for observation bias or ability to see fish during high flow or turbid conditions. The 

BRT points out that the TRT criteria for critical abundance is defined in terms of peak counts. 

We agree, but ODFW is very concerned that use of the peak counts greatly overstates the risk of 

depensation and that, as a result, scores for PP-3 propagate to higher levels of analysis within the 

DDS to marginally reduce the value for ESU sustainability and greatly reduce the value for ESU 

persistence. The BRT acknowledges this effect, describing the 0.09 score for ESU persistence as 

“counterintuitive.” This new approach has not been subject to a sensitivity test, nor have the 

results been reviewed by members of the TRT Workgroup.

The BRT used the average of raw peak counts in each population for the three lowest 

abundance years since 1997. This criteria becomes the metric for critical abundance (PP-3) in 

their Decision Support System model. Critical abundance (PP-3) dominates the DSS model, as it 

is additive as the lowest score among a group of criteria is moved up in the analysis to calculate 

population persistence (PP). This explains why ESU sustainability only improves slightly as 

used in the BRT Report and why ESU persistence goes all the way down to 0.09.

The BRT report correctly says that this “counterintuitive” result is directly related to 

using peak counts instead of adjusted AUC and that using AUC was a mistake. We believe that 

the mistake was in the definition of the criteria, perhaps in the shape of the truth curve, and, 

lastly, the fact that they used averaged counts for all surveys. Taking the average for all surveys 

is inconsistent with the concept that coho populations become restricted to only the highest 

quality habitat during extended periods of poor ocean survival (Nickelson and Lawson 1988).

Depensation due to low spawner numbers is a concern because it may increase the risk 

that fish cannot locate mates and that spawning will not occur. Because salmon have high 

fecundity, and because straying allows for recolonization of unoccupied habitats, the risk of 

depensation is a rare occurrence in salmon populations. Examples of depensatory effects at low 

numbers come primarily from isolated populations at very low abundance. Our data show that 

coastal coho maintain adequate numbers of spawners within core areas of each population and 

that sufficient straying occurs both within and among populations to assure recolonization.

Barrowman et al. (2003) examined spawner counts and smolt production from 14 

independent watershed studies and concluded that depensation was rare, and that effects only 

occur when spawner density falls below about one female per mile. They also note that 

including streams with no fish at all results in a measure of depensation that occurs trivially.

ODFW’s Life Cycle Monitoring Project provides estimates of spawner abundance and 

smolt production at several small to medium-sized basins within the Coastal Coho ESU. These 

data are comparable to that used by Barrowman et al. (2003) and provide an opportunity to 

examine the occurrence of depensation in Oregon coast coho. Spawner to spawner ratios were 

calculated for years when parental spawner abundance was at or below 20 fish per mile, 5 fish 
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per mile, and 2 fish per mile. This range of abundance is the same as considered in the TRT 

critical abundance criteria.

Examination of these data (Table 1) demonstrates that average spawner to spawner ratios 

for each site always were greater than one, regardless of the number of parental spawners. This 

means that smolt production at low spawner abundance was sufficient to assure adequate 

abundance of spawners in successive generations over a range of ocean conditions. Also, smolt 

production measured as smolts per female spawner did not demonstrate any effect of depensation 

even at the lowest levels of spawner abundance (Suring et al. 2009, online at https://nrimp.dfw

.state.or.us/crl/reports/Annpro/LCMRpt0608.pdf).

Population size and distribution within basins expand and contract through time and as 

ocean conditions vary. Persistence of populations during periods of poor marine survival is 

dependent on the amount and spatial distribution of higher quality habitats (Nickelson and 

Lawson 1998). Through the process of straying, these habitats become source areas to replenish 

spawners in lower quality habitats as marine conditions improve. The TRT’s biological recovery 

criteria for spawner distribution (PD-3) is determined using minimum occupancy criteria for 

each fifth-field hydrologic unit (HUC5) within the geographic extent of each population. The 

spawner distribution criteria was designed to track patterns of occupation and to increase 

sensitivity to potential for local, catastrophic disturbance. Because of this spatial sensitivity, we 

believe that spawner distribution criteria (PD-3) combined with TRT spawner abundance criteria 

(PD-1) provide better metrics for assessing negative demographic effects at low abundance.

In summary, we believe that the use of peak count data fundamentally altered the results 

of the DDS analysis. In addition, we believe that negative depensatory effects on coastal coho is 

extremely unlikely, based on experience with other populations and because of the lack of any 

evidence of such effects in the life cycle basins or at the population scale. Table 2 shows the 

effect of recalculating the values for persistence and sustainability in the absence of depensatory 

effects. The ESU persistence truth value increases to 0.58, indicating a moderate to high level of 

certainty that ESU viability will be persistent over the long term. Values for ESU sustainability 

increase less dramatically, but solidify the interpretation that ESU viability is sustainable in the 

foreseeable future.

Table 1. Spawner replacement during periods of low abundance and poor marine survival measured by 

ODFW’s Life Cycle Monitoring Project. Values for the ratio of spawners in one year to the 

number of spawners in the parent generation are shown in bold. Any value greater than 1.0 

indicates that sufficient spawning occurred to at least replace the parent generation.

Spawner density (adults/mile)

Population Location ≤ 20 ≤ 5 ≤ 2

Nehalem NF Nehalem 2.7 — —

Siletz Mill Creek 4.8 5.0 —

Alsea Cascade 3.7 5.3 3.7

L. Umpqua NF Smith 11.3 22.2 —

L. Umpqua Winchester 6.4 6.4 8.8

Average spawner/spawner all locations 5.8 9.7 6.3

Number of years 21 8 3
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Table 2. DDS Results for ESU and stratum criteria assuming of absence of depensatory effects at the 

population scale.

ESU Persistence Sustainability

EP ES

0.56 0.29

Stratum Persistence Diversity Functionality Sustainability

SP SD SF SS

North Coast 0.53 0.43 1.00 0.63

Mid Coast 0.43 0.36 0.66 0.46

Lakes 0.93 0.76 0.65 0.69

Umpqua 0.78 0.10 1.00 0.35

Mid-South Coast 0.44 0.36 1.00 0.57

We can only speculate about the impact these different DSS scores would have made on 

the BRT review process. But, as it appears that the DSS analysis served as a starting point for 

subsequent discussion, it seems likely that this different interpretation may have had substantial 

effects on the outcome.

In informal discussions among some members of the Oregon Coast TRT Workgroup, it 

seems clear that the whole DSS approach should be revisited and revised. ODFW would 

welcome such an opportunity.

[Response: As was discussed in Stout et al. (2010), the critical abundance criterion was analyzed 

in Wainwright et al. (2008) inadvertently with AUC data instead of the chosen data set of the 

TRT: peak counts. This discrepancy was discovered when rerunning the DSS for the BRT 

analysis. The analysis found in Stout et al. (2010) is a correction, not a change.]

Assessment of Habitat Trends

It is clear that the results of the BRT analysis of habitat condition and trend were 

extremely important to the conclusions regarding ESU sustainability and persistence. However,

several aspects of the habitat trend analysis appear problematic and ODFW requests a fuller 

discussion of this issue before a final status determination is made.

Our primary concern is that the BRT report placed too much emphasis on a Bayesian 

analysis of habitat trends that used a small subset of the available data. We cannot comment on 

the quality of analysis because insufficient detail was provided in the report. However, even if 

the analysis were correct and confidence in the Bayesian results is high, we have serious 

concerns about the applicability of the results to the ESU scale. The use of the ODFW Habitat 

Limiting Factors Model (HLFM) may also be inappropriate, particularly when applied to the full 

range of streams within the ESU. This is because the “fuzzy logic curves” used in the AREMP 

[Aquatic and Riparian Effectiveness Monitoring Program] model and the smolt production 

values used in the ODFW HLFM analysis are both derived from assessments made on small 

watersheds, primarily on federal lands. While both are useful tools for interpreting habitat data, 

application of these approaches to other ownerships, different channel types and habitat forming 

processes, and different ecoregions clouds interpretation.
197

We are also concerned that the BRT essentially ignored the results of the ODFW habitat 

assessment provided to the BRT based on undocumented statements about the importance of 

interactions between variables. Interactions among variables are likely to be important, but the 

BRT document failed to document the nature of those interactions, or to provide appropriate 

citations, for us to do an independent analysis.

We do know that the AREMP “truth curves” used to assess interactions between habitat 

variables were developed by federal scientists to help monitor the aquatic and riparian strategy of 

the Northwest Forest Plan. The system is calibrated to conditions on federal lands, as interpreted 

by federal scientists whose professional opinions are largely based on their experience on federal 

lands. The BRT does not document if or how this approach may have been adjusted to access 

the range of land use, land management, and channel form and process that comprise the data set 

used in ODFW’s analysis.

The BRT report does reference a description of the AREMP (Reeves et al. 2004). That 

document states that a minimum of 50 sites per analysis area is necessary to meet the criteria of 

the AREMP sampling design and analysis. Based on what we can tell about the sample reaches 

from the map in the BRT appendix, there were only about 30–40 sites in each stratum that met 

this criteria. It appears at least 50 sites were included for the North Coast stratum, but 8–10 of 

those sites appear to be outside the range of coho distribution. Thus the analysis of habitat trend 

data appears to violate basic requirements of the AREMP design.

Additional comments on BRT Report Appendix E, Habitat complexity

Introduction (page 36)

1) Figure E-1 (sites used by BRT for trend analysis) does not appear to be the correct 

selection of a) sites within the range of coho and b) annual and 3-year sites. The map 

does not match that presented in Anlauf et al. (2009).

2) BRT states that “Anlauf et al. (2009) does not capture interactions among the various 

habitat attributes and does not adequately represent habitat complexity.”

a. Not true: HLFM represents peer reviewed integration of primary and off-channel 

pool habitat and wood complexity that represents the limiting factor for 

freshwater survival of coho salmon in Coast Coho ESU.

3) BRT stated that Anlauf et al. (2009) used sites that had been surveyed only once or twice.

a. Not true: Only sites surveyed at least twice or more times were used in the 

analysis. Sites were pulled from the annual and 3-year site list as described in 

Anlauf et al. 2009.

b. The BRT did not request clarification of the methods section in Anlauf et al. 

(2009).

4) Contrary to statement by the BRT (page 38), ODFW was not requested to rerun the 

analysis for any variable or data sets (pers. commun., K. Anlauf and K. Jones, ODFW). 

BRT did ask for the literature citations for the scientific basis of HLFM which was emailed to them (K. Jones, ODFW).
198

5) Contrary to the statement by BRT concerning the rerunning of the HLFM on first 

paragraph page 38, the ability to estimate summer habitat was present in the version of 

the HLFM published in 1989 and has remained in the model. The BRT did not review 

the literature supporting the HLFM model or interpret the published information 

correctly. Anlauf et al. 2009 did not present information on summer rearing capacity 

because summer habitat does not limit the populations of juvenile coho and the capacity 

is directly related to the amount of surface area in pool habitat.

6) Paragraph 2, page 38: The statistical validity of the AREMP model used by the BRT to 

combine variables for trend analysis is not supported in the document or referenced by 

published literature.

7) Page 38, paragraph 2: Statement by the BRT that Anlauf et al. (2009) did not stratify the 

analysis is not correct. The sample frame was designed to describe status and trends at 

the ESU and monitoring area scales; Anlauf et al. (2009) used the design strata to 

describe status and trends at these two scales. The sample size was too small (and the 

sample frame statistically inappropriate) to describe status or trends at the population or 

site scale as done by the BRT.

Habitat complexity indices (page 38)

1) Anlauf et al. (2009) used the HLFM model to describe habitat complexity for juvenile 

coho during the summer and overwinter life stages. It is a peer reviewed, quantitative 

model, which captures a combination of pool complexity and large wood. It considers 

habitat complexity relative to coho life history.

2) We do not agree that individual habitat variables are not useful for describing status and 

trends. It is essential to understand the trend in individual variables to be able to interpret 

the results of a metric that integrates variables. In addition, individual variables have a 

direct relationship to habitat requirements of each life stage of coho. For example, fine 

sediment can reduce the emergence success of egg to alevin stages in spawning areas 

(Everest et al. 1987) and the amount of pool habitat influences the carrying capacity for 

juvenile coho (Nickelson et al. 1992, Rosenfeld et al. 2000). An integrated metric may 

describe general conditions in a watershed (AREMP model), but it does not focus on 

habitat requirements for the different life stages of coho. To be appropriate to the review 

of viability of coho in coast populations, the integrated metric must be developed 

specifically for carrying capacity and quality of habitat for coho, as with the HLFM 

presented by Anlauf et al (2009).

3) Page 39: The validity of the BRT’s use of the AREMP decision support model channel 

condition score to evaluate productivity of aquatic habitat for coho populations is not 

evident or forthcoming. Information is not presented to describe the values, weights, or 

logic statements of the individual variables relative to habitat productivity for coho 

salmon.

4) Page 39, third paragraph: The interpretation of the HLFM model by the BRT was not 

correct. The HLFM was designed to estimate spring, summer, winter, and spawning 

habitat for coho salmon from the onset (Reeves et al. 1989, Nickelson et al. 1992). The 

modeling of capacity of winter habitat was improved recently with the addition of a large 

wood metric. Also, winter rearing capacity scores for the status assessment were 
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generated from winter and summer surveys (Anlauf et al. 2009). Because the trend 

analysis required data from repeat survey sites, we used the summer values converted by 

a regression model (R2 = 0.879) to reflect winter rearing capacity.

Trend modeling (page 39)

1) The sample frame and site selection were designed for application at the ESU and 

monitoring (referred to as the GCG unit by the BRT) scales. It is not statistically 

appropriate to use the site data to describe conditions at the population scale (number of 

sites per population unit, site weight issues).

Results (page 41)

1) First paragraph of Results section, first sentence: The ODFW did not rerun the HLFM in 

the trend model. No request was received from the BRT.

2) The BRT needs to provide the data sets, assumptions, and models used in its trend 

models. We are not able to evaluate the statistical rigor of its approach, use of the DSS 

model, variance partitioning, or its conclusions.

3) Page 42: the second paragraph is a repeat of the last paragraph on the previous page. The 

BRT should edit its report before release.

4) Table E-1: The BRT needs to provide statistical support to indicate that the probability 

estimates are significantly different from 0.

5) Last paragraph, second sentence: ODFW did not rerun the HLFM. The BRT needs to 

provide the data set and model they used when they apparently reran a trend model.

Conclusion

ODFW cannot evaluate the validity of the BRT’s conclusions because of:

a. inaccuracies in its statements,

b. apparent lack of understanding of the underpinnings of the HLFM model,

c. incorrect data set,

d. concern over use of DSS for quantifying habitat relationship to productivity of life 

stages of coho salmon, and

e. unknown statistical rigor of the BRT’s trend analyses.

[Response: National Marine Fisheries Service (NMFS) scientists and ODFW scientists formed a 

joint habitat group (Habitat Trends Working Group) to resolve these issues and come to 

consensus regarding appropriate analyses, data sets, data transforms, etc. Revised text is found 

in the In-channel habitat complexity subsection of the BRT document proper and a detailed

presentation is included in Appendix C.]
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Incomplete Discussion of Limiting Factors and Threats

Although it is difficult for us to determine the effect of the final BRT recommendations, 

we believe that, in some cases, the discussion of limiting factors and threats was often based on 

incomplete information or misunderstanding of available information. This was particularly true 

in the assessment of fish passage and estuary habitats. The fish passage issues are technical and 

may require additional analysis; we would like to discuss this further.

[Response: The report was revised to reflect information contained in several sources supplied 

by ODFW. In addition, we included information from a new data compilation that was, for the 

most part, absent from the most recent ODFW database. This is found in the Fish passage 

subsection.]

The following comments apply to coho use in estuary habitats.

The BRT hypothesizes that estuaries are critical habitat for the productivity and life 

history diversity of coho salmon. To date, these assertions of have not been born out in 

published studies. As described by the BRT (based on a synthesis paper by Koski 2009), 

juvenile coho are observed using tidal habitats in some estuaries of the Pacific Northwest. We 

(ODFW) have observed use of estuary habitats by yearling and subyearling coho in the spring, 

and subyearling coho in the summer (very limited) and winter. However, neither the Koski 

(2009) paper nor studies by ODFW have demonstrated a link of estuary rearing to adult 

contribution. There is no demonstrated evidence that estuary use is a critical life history strategy 

for coho for any independent populations.

Without question, estuary habitat has been significantly reduced over the past 100 years. 

However, the Oregon Watershed Enhancement Board (OWEB) has invested significant 

resources and had many successes in restoring, acquiring, and protecting estuary habitat since the 

inception of the Oregon Plan in 1997. The actions of OWEB will provide significant buffer to 

climate change and rising sea level.

Specific comments on BRT review:

Appendix D includes all the information that is sprinkled throughout the primary 

document (Scientific Conclusion of the Status Review). It is difficult to tell in the primary 

document whether the BRT concluded that estuaries were “critical” to the viability of coho:

1. Summary: The BRT states “However, little direct quantitative information exists on the 

relative proportions of coho salmon juveniles that use this life history pathway, the 

survival rates and capacity relationships involved, and the relative contribution to adult 

returns.” This is a true statement and in fact the literature suggests that the estuarine life 

history contribution is relatively small except possibly in small streams that feed directly 

into the estuary ecotone.

2. The Koski (2009) manuscript is a nice synthesis paper. It was published in Ecology and 

Society as part of the special edition on salmon in 2010. Koski’s basic statement 

regarding 0-age coho contribution to the adult population is: “documentation of age 0 

coho migrating to the ocean and surviving to adults is limited.”
201

3. Even though we (ODFW, Jones and Cornwell) have documented that age-0 and age-1 

coho use the estuary, we do not have evidence as to the contribution to the adult 

population. We suspect estuary rearing is a life history pattern, and in Salmon River, the 

abundance and quality of restored wetlands provides good prey resources as juvenile 

coho rear or migrate to the ocean. However, to suggest that the estuary life history 

pattern is critical to viability of the Salmon River population is an overstatement.

4. For the most part, our sampling in fresh and brackish wetlands and channels in 2003–

2004 in the Siuslaw, Alsea, Yaquina, and Nestucca document that subyearling coho are 

present in the spring through June, then disappear. Juvenile coho clearly prefer 

freshwater wetland habitats (K. Jones, T. Cornwall, D. Hering, L. Borgerson, D. Bottom, 

S. Simenstad and A. Bierber. 2007. Patterns of coho salmon migration and residency in 

Oregon estuaries. Oregon AFS presentation).

5. The fact that Lisa Borgerson has identified 2-year-old adult coho returning to Salmon 

River does not necessarily imply that they used the estuary, only that they migrated to the 

ocean as subyearlings.

6. The BRT’s reference to Bottom et al. (2005) regarding the life history of Chinook salmon 

as representative of coho use of estuarine habitat is not a valid template for life history of 

coho salmon. It is an inaccurate and misleading comparison.

7. The example from Skeesick (1970) is not valid. Skeesick (1970) focused on migrations 

of juvenile coho in and out of Spring Creek from the mainstem Wilson River (Tillamook 

basin), not Tillamook Bay. Skeesick also mentions observed migrations into Munson 

Creek, a tributary to the Siuslaw River, during high flow events. The theme of 

Skeesick’s paper was the importance of small tributaries, not the use of estuarine habitat.

8. OWEB is aggressively acquiring freshwater and brackish wetlands and supporting 

extensive restoration of tidally inundated habitats. The BRT should acknowledge fully 

the restoration and protection of tidal-fluvial and estuarine habitat by OWEB. The 

actions by OWEB will serve as a hedge against global climate change.

9. The BRT’s review of the relationship of coho viability and estuary habitat at the 

independent population scale is highly speculative and circumstantial (my opinion). That 

is not to denigrate the ecological importance of estuaries to the coast ecosystems and 

salmon populations, particularly Chinook and chum salmon, along with sea run cutthroat 

trout. The estuary environment may provide an alternative life history pathway for 

juvenile coho in some cases, but is unlikely to be a major factor in the viability of coast 

coho populations.

[Response: Additional text was included in the document to further explain the importance of 

estuaries to OCCS and to include information provided by ODFW and other sources. Both the 

BRT and ODFW are in agreement that there has been significant loss of estuary habitat along the 

Oregon Coast during the last 100 years. We acknowledge that there is some scientific 

disagreement between ODFW and the BRT regarding the severity of the effect of estuary loss on 

the viability of the OCCS ESU. However, the loss of estuary habitat is only one of many factors 

limiting the sustainability of this ESU. In contrast to the previous comments, Reviewer 3 stated 

that “the emphasis given to the importance of estuarine habitat is moderate and adequate, given 

the information available in the literature.” The reviewer notes that they have observed juvenile 
202

OCCS rearing in estuaries and feels that this life history strategy is fairly common. The reviewer 

also provided some specific scientific information to support the statement. This viewpoint is 

consistent with the BRT’s position on the importance of estuaries to juvenile OCCS. The BRT 

revised the report’s section on estuaries to include the information provided by the reviewer and 

by ODFW and OWEB.]

Incomplete Assessment of Restoration Efforts

ODFW believes that the BRT report underestimates both the variety and effectiveness of 

habitat and watershed process restoration efforts. Further discussion and evaluation is necessary 

to assist NMFS in its understanding of these efforts.

[Response: The SHAPE ( Salmon Habitat Assessment Project Evaluator) analysis has been

removed from the BRT document and protective efforts are assessed by the NMFS Northwest 

Region Office (NWR) and included in the Federal Register notice.]

Comments on “Restoration Projects” (page 90) of Scientific Conclusions of the Status 

Review for Oregon Coast Coho Salmon (Oncorhynchus kisutch)

We (ODFW) are submitting the comments of behalf of the OWEB and a summary of 

recent habitat restoration monitoring conducted by ODFW.

The analysis presented in Appendix F compares restoration projects from a NOAA 

database of restoration projects with habitat concerns identified in watershed assessments. The 

analysis is creative and useful to assist in better targeting funding. To be effective, the analysis 

should include a complete disclosure of data limitations, embodied assumptions in the analysis, 

and limits on the interpretation of the data. The following comments are provided to help build a 

fuller understanding of the analysis and the limits of the analysis.

Data Limitations

1. Watershed assessments using the OWEB Watershed Assessment Manual were completed 

between 1999 (when the manual was completed) and 2007. This means that many if not 

most of the restoration projects funded and available in the database (see 3, below) were 

finished prior to completion of the assessments. To have a direct comparison between 

the issues identified in assessments with projects completed would require analysis of 

only those projects implemented for each watershed following completion of an 

assessment. It would be interesting to see if there was a chance of power of association 

following completion of assessments.

2. The restoration data used in the analysis came from the Pacific Northwest Salmon 

Habitat Project Database (PNSHPD). This database is populated from the OWEB. The 

last time the PNSHPD was populated by the OWRI [Oregon Watershed Restoration

Inventory] was June 24, 2004 which included projects completed between 1995 and 

2002. This limits the analysis to most projects completed prior to the completion of 

watershed assessments.

3. The OWRI contains data compiled since 1995 on all restoration projects funded by 

OWEB and a significant number of projects (approximately 70%) reported voluntarily by 
203

others that do not use OWEB funding. The early reporting was dominated by voluntary 

projects primarily on private industrial forest lands. What this means is that there may be 

a reasonable disconnect between limiting factors for coho salmon and implemented 

projects.

4. OWEB funds projects for resources other than coho salmon. Projects that protect habitat 

for invertebrates and other species will not always align with priorities set for watershed 

functions.

Embodied Assumptions

1. Central to the analysis is the assumption that the two variables (habitat concerns and 

project types) have a temporal relationship, for example habitat concerns are known 

before projects are selected. Appendix F does not indicate that such a sorting was done. 

It appears that all projects funded in a geographic area were compared to habitat concerns 

regardless of when the projects were implemented and the concerns identified.

Limits on Data Interpretation

2. The data results state that “14 assessment units (28%) have a SHAPE score of between 0 

and 0.5 and 25 assessment units (50%) have a SHAPE score of between 0.5 and 1.0.” 

This should indicate that more than 78% of the assessment units have a positive 

relationship between habitat concerns and project types. If the same data were calculated 

on a HUC basis, the percentage of positive scores would be even higher (approximately

86%).

3. There were only two watersheds where there was a relatively high negative correlation 

between habitat concerns and restoration actions. It appears that this fact alone should 

indicate that overall there is a good to fair correspondence.

4. Even a cursory evaluation of the watersheds that have a low score would show that these 

watersheds are dominantly federally managed and it would not be expected that 

restoration activities on a minority of the watershed would address the principal habitat 

concerns (the Upper Cow Creek watershed is 73% public land and the West Fork Cow 

Creek watershed is 53% public land). The OWEB database does not have any projects 

from the West Fork Cow Creek watershed.

5. There was no power analysis of the results suggesting that small sample sizes might 

affect results significantly. If there was any data selection for small samples, it was not 

described in the appendix.

6. An equally valid interpretation of the results could be that there is a very high 

correspondence between habitat concerns and restoration projects implemented despite 

the data limitations and lack of analytical precision.

[Response: The SHAPE analysis has been removed from the BRT document and protective 

efforts are assessed by the NMFS NWR and included in the Federal Register notice.]

Summary of ODFW effectiveness monitoring report, cited as “in prep.” in Anlauf et al. 

(2009) in materials submitted to the BRT in September 2009:
204

Tippery, S., K. K. Jones, K. J. Anlauf, C. H. Stein., M. J. Strickland. 2010. Effectiveness 

monitoring report for the Western Oregon Stream Restoration Program, 1999–2008. 

OPSW-ODFW-2010-6, Oregon Dept. Fish and Wildlife, Salem.

The report examined the location of the instream large wood projects relative to the 

distribution of coho and reaches of high intrinsic potential, the long-term (6 years) retention of 

large wood and complexity of habitat, and estimated the overwinter rearing capacity for juvenile 

coho. The OWEB database has additional information on riparian and passage projects.

This is the first extensive study of before-after effects of restoration treatments over a 

broad geographic scale. Previous studies of the WOSRP [Western Oregon Stream Restoration 

Program] projects (e.g., Jacobsen et al. 2007) reported retention and recruitment of large wood,

but few other changes were significant. Here we demonstrated an increase in surface area of 

pools and sorting of substrate within the project areas in the majority of the projects. Of the 46 

projects evaluated over a 6-year period, only 8 (17%) were considered to have “failed,” losing 

large wood or pool area. Another 15 projects (30%) increased the amount of large wood, but 

generally did not experience other change. For 24 (53%) of the projects however, wood was 

maintained, additional pool area was created, gravel accumulated, and rearing capacity for 

juvenile coho increased. These projects, distributed throughout the coast and lower Columbia 

basins and including both large wood and wood/boulder projects, were considered successful 6

years following treatment. While 6 years may be marginally “long term,” this study is a first 

attempt to quantify change in habitat following restoration more than 6 years after treatment.

All of the projects were placed in appropriate geomorphic settings and within the 

distribution of coho, maximizing the effectiveness of restoring fish habitat. We expect that the 

projects have started to improve fish habitat (habitat complexity and rearing capacity) at the 

population and ESU scales. The WOSRP and OWEB large wood projects treated 750 km of 

stream from 1995–2007 in western Oregon, of which 550 km were within the distribution of 

coho. If half of the OWEB projects are successful (as indicated by the WOSRP evaluation), up 

to 2% of coho habitat in the Coast Coho ESU has been significantly improved. While limited 

relative to the kilometers of stream potentially inhabited by coho, the impact is more 

pronounced, given the projects were placed within the stream reaches most productive for 

overwintering juvenile coho.

Although the amount of stream treated was not statistically detectable by ODFW’s 

monitoring scale GRTS [Generalized Random Tessellation Stratified design] samples (we

sample approximately 3% of coho habitat), the placement in potentially productive habitat and 

effectiveness of the projects most likely improves conditions for juvenile coho in the Coast Coho 

ESU.

[Response: NMFS scientists and ODFW scientists formed a joint habitat group (Habitat Trends 

Working Group) to resolve these issues and come to consensus regarding appropriate analyses, 

data sets, data transforms, etc. Revised text is found in the In-channel habitat complexity

subsection of the BRT document proper and a detailed presentation is included in Appendix C. 

Other information presented here was taken into account by the NMFS NWR and included in the 

protective efforts section of the Federal Register notice.]
205

Comments of the MidCoast Watersheds Council Coordinator

21 July 2010

I am the Coordinator of the MidCoast Watersheds Council, based in Newport. The 

council does restoration work in the area from Cascade Head to Heceta Head, with an emphasis 

on improving watershed function and improving habitat for coho. I was a member of the OC 

Coho Stakeholders group assembled by the State of Oregon and NMFS that produced Oregon’s 

OC Coho Native Fish Conservation plan. I provide here a set of comments on particular sections 

of the text, followed by three more general comments on coho status.

Wayne Hoffman

Coordinator

MidCoast Watersheds Council

Pp. 9–18. Review of BRT and Listing. The review of previous status evaluations is very

useful, as is the history of listing decisions included in the Introduction. These are probably 

adequate for the purposes of this document, but I think it would be very useful to develop a 

document that integrates the status evaluations and listing decisions, with more detail provided 

on the latter than is present in the introduction. I think such a document would be very useful in 

understanding the evolution of thought on what constitutes an adequate status evaluation, and on 

what level of decline or risk supports listing decisions. I think such a document would be helpful 

to people managing other depleted, declining, or otherwise at-risk fish.

Pp. 20–21: Artificial Propagation. Membership in the ESU. This discussion could use 

some elaboration. More considerations than those mentioned here ought to go into decisions 

about inclusion or not in the ESU. Basically this says that the NF Nehalem and Trask hatchery 

stocks have not had naturally-spawning fish deliberately included in the brood stock for several 

generations, so they must be divergent. Conversely for Cow Creek, “wild” fish are included in 

the broodstock, so they must not be divergent.

If actual evidence for such divergence has been documented in Nehalem or Trask, it 

should be reported here: for example, has run timing diverged? Or other phenotypic or life cycle 

differences arisen? Average size? Frequency of jacks? For Cow Creek, has a lack of 

divergence been documented? If so, how?

I have concerns that we are still not adequately understanding how salmonid stocks 

evolve, and that as a result we tend to misinterpret the tools we use. On the one hand, we have 

abundant evidence that salmonid populations can respond with impressive speed to selection, 

and reasons to believe they are continuing to do so. On the other hand, the molecular tools we 

tend to use in studying salmon population structure (e.g., microsatellites) are assumed to be 

selectively neutral, such that their measures of divergence (or lack thereof) are independent of 

evolutionary changes resulting from strong selection.

In many cases, hatchery stocks do show evidence of rapid phenotypic divergence, and 

these ought to be documented. Dr. Michael Blouin and his coworkers have been reporting 

divergence in fitness of hatchery steelhead stocks so rapid that they are looking at epigenetic 

mechanisms to account for it. If the mechanisms they propose are in fact operating, inclusion of 
206

“wild” broodstock may not be adequate to prevent divergence in the Cow Creek stock, although 

microsatellites might not show it.

[Response: The Artificial propagation subsection has been revised with a link to the previously 

published (Federal Register notice) discussion of membership in the ESU and additional

explanatory text.]

P. 24. Is there a mistake in the description of EPA comments? I do not understand what 

the phrase “on other OC coho salmon reviews” means in this context.

[Response: This has been revised for clarity.]

Pp. 30–88. New Data and Updated Analyses. This section (really the meat of the Status 

Review) would be improved if each subsection included (perhaps ended with) a listing of 

remaining information and analytical gaps that affect the listing recommendation. This would be 

particularly useful in that information used in previous assessments is not really summarized. 

For example, the Population Diversity subsection (Pp. 33–34) discussed Koski’s new 

information on estuarine rearing but did not indicate whether or not the BRT considered current 

information adequate on other life history diversity (e.g., lake rearing, occupancy of beaver 

ponds, nontidal wetlands, etc.). In effect this is done for the Mark-Selective Fisheries subsection 

(p. 35) with reference to catch-release and drop-off mortality, but not so much for the other 

subsections.

[Response: We revised many of the subsections to capture some of the information gaps that 

existed. These include beaver populations and fish passage on private lands.]

P. 59. Quote from NMFS NWR, “fish passage restoration projects have not been tested 

at high flows, ... have rarely been monitored to test whether they are actually passable.” This is 

not true for the projects my organization (the MidCoast Watersheds Council) has been doing. 

We routinely check for coho upstream of our passage projects. This is often qualitative, that is, 

presence-absence, rather than abundance estimates. In addition we always monitor the 

replacement structures for compliance with the passage guidelines, which we think are good 

indicators of performance. If a replacement culvert retains a gravel substrate at appropriate 

gradient, without apparent barriers (subsurface flow, downstream lip, etc.) I think we can be safe 

to assume it is passable. I do not understand the need for testing “at high flows” because even if 

a structure is difficult to pass at highest flows, such flows are generally transient, and salmon 

needing to wait a few hours, or even a day or three to pass is hardly catastrophic. Salmon more 

commonly have to wait for proper flows at natural barriers (small waterfalls, beaver dams).

[Response: The Fish passage subsection has been substantially revised with additional 

information provided by ODFW and other sources.]

Pp. 63–66. Beavers. I agree with the general conclusion that “declines in beaver 

abundance is an ongoing threat to OC coho salmon” (p. 66), but I think this threat needs to be 

further analyzed and discussed.
207

First, it needs to be fully acknowledged that the habitat benefits beavers provide are 

landscape-context specific. Beavers occur within the ESU in a variety of contexts, from brackish 

estuarine marshes, to lakes, to large mainstem rivers, to smaller tributaries. The role of beavers 

in affecting coho habitat varies greatly among these landscape contexts. Beavers in estuarine 

marshes may build dams in upper portions of sloughs and both provide physical habitat for coho 

and may positively modify salinity by impounding freshwater inflow. Beavers in lakes and 

mainstem rivers generally do not build dams, and may have little effect, positive or negative, on 

coho habitat. Beavers in headwaters areas do build dams, and this is where their positive 

contributions to coho habitat are best understood. This is important because population trends in 

beavers and threats to beavers likely vary across the landscape. For example, recreational 

trappers are more likely to recognize opportunities and have access in headwaters areas than 

along main stems.

[Response: We added text to capture this comment in the Beaver in OCCS habitat subsection.]

Second, this section properly reviews the legal status of (non)protection for beavers, but 

needs also to address other potential causes for the documented declines in beaver dams. Two of 

these in particular need discussion. Cougar populations have increased substantially in the ESU 

in the past 2 decades, and cougars are probably effective predators of beavers, particularly in 

headwaters areas. This needs verification, but if true, may need to be treated as a fairly 

intractable increased threat to coho habitat.

[Response: We agree with the reviewer in part. Estimated cougar populations have increased 

since the 1970s over the entire State of Oregon from approximately 214 to more than 2,800 by 

1992 (Keister and VanDyke 2002). However, nothing in the literature suggests that predation on 

beaver is a primary cause for reduction in beaver population. The majority of studies identify 

deer and elk as the primary food source for cougars (Ackerman et al. 1984).]

Second, we see in many areas colonization of riparian zones by reed canary grass 

(Phalaris arundinacea), which outcompetes the trees and shrubs that beavers prefer. Likely 

beaver populations fluctuated on a decadal cycle, with population crashes followed by 

recolonization and proliferation of food plants, then recolonization by beavers. Reed canary 

grass seems to break this cycle by preventing the recolonization and proliferation of the shrubs 

and trees. We see many former beaver ponds now as grass flats in successional stasis, in some 

cases with the stream channel down-cutting. We currently are experimenting with brute force 

control of the grass to reestablish beaver food, but expect this to be expensive and slow with 

current methods.

[Response: This is an excellent point. Reed canary grass is an issue with respect to beaver 

ponds in the Oregon coast (Perkins and Wilson 2005). In addition, more aggressive management 

actions are needed to deal with it, as evidenced by recent work that suggests plantings and 

natural vegetation alone cannot control it (Kim et al. 2006, Healy and Zedler 2010, Spyreas et al. 

2010). We added text to capture this point in the Beaver in OCCS habitat subsection.]

Pp. 66–67. Roads. I am sure the negative relationships between road density and 

productivity are real, but that does not mean they are fully causal. Road density may be best 

thought of as a surrogate variable for landscape disturbance that depresses productivity on a 
208

long-term basis, and it is worthwhile to dig deeper and look at other aspects of the disturbance on 

a site specific basis, including direct effects of logging and yarding, stream cleaning, and so on, 

that likely correlate with road density. Clearly roads can affect productivity directly (e.g., 

through sediment inputs and passage impediments), but these may not necessarily correlate as 

tightly with road density as the cited studies imply. For example, obliterating a valley-bottom 

road and replacing it with two ridge top roads may improve productivity without reducing road 

mileage in the basin.

[Response: These are certainly good points regarding the relationship of road density and 

productivity that bear closer examination. This may be a task for the recovery planning process.]

Pp. 69–70. Loss/Gain of Large Wood. This discussion may overstate the issues with 

large wood recruitment from riparian areas. The statement, “the large and very large trees are 

the size of tree that creates more complex habitat conditions” is generally true, but wood size 

needed scales to stream size and power. I was informed recently that in consultation on thinning 

projects, NOAA has recently reported to the Siuslaw National Forest that in small headwaters 

streams, trees as small as 20 cm diameter are important for recruitment to the streams.

Pp. 70–75. Habitat Complexity. The conclusion here that habitat complexity is 

continuing to erode (so to speak) is certainly provocative, and I suspect very influential to the 

conclusions reached. I find this conclusion hard to evaluate because the descriptions of analyses 

lack necessary detail on the sampling protocol and particularly the sample sizes. I urge you to 

prepare a more complete report detailing these analyses.

I am familiar with the basic data collection method (ODFW Aquatic Habitat Inventory 

protocol), and am aware that the protocol gets updated periodically. It may well be that the 

particular parameters used are measured comparably through these updates, but this should be 

verified and, if so, stated. I know that some parameters are very sensitive to flow rates at the 

time of survey. For example, an area that will classify as “glide” at moderate flows may break 

out into multiple pools and riffles at minimum flows. The logistics of matching flows across 

multiple surveys in different years would be daunting, and I am not aware of any attempts to do 

this. Of course this is one of the things that with adequate sample size should even out, but this 

inflates the necessary sample size. I am also aware of flow-related inconsistencies in assessment 

of large wood, for example in the counting of logs that are wetted only at moderate or higher 

flows. I suspect that restoration projects may put in a higher percent of these than nature does 

(e.g., “top” logs on a jam added to improve stability, also logs placed into seasonal side 

channels).

So, I do not challenge the conclusion of ongoing declines in complexity, but more detail 

is needed to prove the case. In addition, it would be really useful for restoration efforts to 

partition this result among the various factors that can cause decreases in complexity and in 

channel context. How much results from reduction in number of beaver ponds? From loss of 

wood? How much is in streams at 0–1.5% gradient? Versus 2–4% gradient? How much is in 

second versus third versus fourth order streams? Knowing these things could really help us 

prioritize restoration. I doubt that the sample sizes available are sufficient for a lot of this 

partitioning, but it would be a productive direction for future research.
209

[Response: These are certainly good questions that may bear more investigation. This may be a 

task for the recovery planning process.]

P. 75. Forest and Agriculture Conversion. It is worthwhile also describing ongoing 

conversion trends. We are seeing three in the MidCoast, and I suspect they are playing out 

elsewhere (and maybe some others). First is a trend of conversion of agricultural land to forest 

land. As agricultural market structure becomes more difficult and owners get older, many are 

giving up on grazing and are planting trees. This has a variety of implications for coho habitat 

(jurisdiction of Forest Practices Act rather than SB1010 for example). Another trend is sale of 

“serious” agricultural land to hobby farmers who do not have the same income expectations from 

farming. This trend has led to more “ignorant” behavior such as gross overstocking with horses, 

but the hobby farmers tend to be receptive to advice on best practices. In addition, the last cattle 

dairy in Lincoln County has converted to raising beef cattle. The third ongoing trend is 

residential development on the banks of larger streams. Currently this is more of a problem the 

larger the river is and the better-developed the recreational fishery. A legal gap in riparian 

protection allows this trend to result in major riparian abuse.

[Response: We added several points to the Land management—forest and agriculture 

conversion subsection to capture the essence of these comments.]

Pp. 79–82. Estuary loss-gain. The caption to Figure 24 needs to explain the difference 

between the two histograms. I suspect one uses numbers from Good (2000) and the other from 

Adamus et al. (2005), but that is not explained and which is which is not identified.

[Response: This caption has been revised for clarity.]

Pp. 82–84. Loss/gain of Freshwater Wetlands. Another data source is potentially 

available for assessing freshwater wetland loss away from estuaries. If you look at soil surveys 

(complete for Lincoln County, not sure how complete in the rest of the ESU, but coverage should 

be extensive), hydric soils are good indicators of current + former wetland conditions. These are 

soils that form under wetland conditions, but are recognizable for quite a while (at least multiple 

decades) after loss of wetland hydrology. So if a hydric soils map layer were constructed from 

the overall soils maps, then checked for current conditions, either on aerial imagery or on the 

ground, a pretty good estimate of wetland trends could be obtained. I strongly suspect that such 

an analysis would show considerable “inadvertent” wetland loss as well as deliberate draining. 

The inadvertent loss would result from stream down-cutting following large wood removal or 

depletion. The result would be disconnection and eventual drying of lateral wetland areas. Such 

a map would also be very useful in identifying locations for projects to reestablish floodplain 

connection.

[Response: The Oregon Natural Heritage Information Center and The Wetlands Conservancy 

are engaged in a project of this kind; results are available at http://oregonexplorer.info/wetlands. 

This type of analysis is far beyond the scope of the BRT assessment. However, this may be a 

task for the recovery planning process now that LIDAR remote sensing has been flown for much 

of this area.]
210

P. 84. Land Management–Mining. I am surprised the Coquille is not mentioned in this 

discussion.

[Response: The Coquille River has been added to the discussion of mining.]

P. 84–85. Water Quality Degradation. Very recent data collection projects in the 

MidCoast area have identified more pervasive coliform bacteria and dissolved oxygen problems 

than previously recognized. The latter in particular seems to involve important coho rearing 

habitat, and seems connected to both agriculture and riparian domination by reed canary grass. 

The data are very new and preliminary, but this should be watched as a potential additional 

factor limiting coho recovery.

P. 90. Restoration Projects. This analysis has the potential to provide useful guidance to 

local groups performing restoration, but some logical lapses affect the conclusions drawn here. 

The detail provided, both in the text and in Appendix F, is insufficient to fully evaluate the 

methods or make good use of the results at the local level. Hopefully a more detailed 

presentation of these results will be made available to us.

Some concerns do arise from comparison of the SHAPE metrics to the identified limiting 

factors. Looking at Figure F1, it appears that many of the units with lower scores (darker 

shading) are units with limiting factors less amenable to locally developed projects. The lakes 

units, for example, list exotic fish as their primary limiting factor, and management of exotic fish 

is more of an ODFW responsibility than something local groups can or should tackle. Similarly, 

the hatchery impacts and water quantity issues in the Umpqua may be less amenable to local 

action. Certainly elsewhere local groups have invested in irrigation efficiency projects, but my 

sense is that some of the water quantity issues in the Umpqua are related to the operations of 

industrial-scale dams and reservoirs, and you should not be expecting local groups to be 

reporting projects to the database that address these.

So in general, what I take from this analysis is that local projects are lining up best with 

the limiting factors where the limiting factors can be best addressed by site-specific projects, and 

are not lining up so well where the limiting factors are more matters of policy (fisheries 

management, FERC relicensing, etc.).

[Response: This analysis is no longer part of the BRT document; the discussion of restoration 

activities is now found in the protective efforts section in the Federal Register notice. However, 

this type of analysis would be appropriate for a recovery planning effort.]

Overall Comments:

1. The status review has omitted a factor that may have major implications for reduced 

productivity of coho habitat. This is habitat loss/degradation through the action of exotic 

organisms. Several of these are known or can be expected to directly affect coho habitat. One 

category is exotic vegetation that impedes or prevents development of healthy woody riparian 

vegetation. Currently, particular problem species are reed canary grass, the giant knotweeds (3 

species [Polygonum spp.]) and Himalayan blackberries (Rubus discolor). All these can outcompete seedlings of native riparian trees and shrubs, and maintain a low-height riparian 

condition that does not provide adequate shade and obviously does not contribute large wood. 
211

The knotweeds and blackberry also appear to be poorer than native woody vegetation at bank 

stabilization, and may contribute to increased fine sediment input. Reed canary grass forms a 

thick thatch that is very effective at bank stabilization, and is also very effective at fine sediment 

trapping. Marshy riparian areas colonized by reed canary grass may tend to become 

disconnected through aggradation both from sediment trapping and from accumulation of 

organic remains. Reed canary grass also inhibits colonization by beavers and seems to be 

associated with dissolved oxygen problems.

A second category is colonization by exotic freshwater mollusks. One, New Zealand 

mud snail (Potomopygyrus antipodarum), is already present in Devils Lake and Tillamook, and 

perhaps elsewhere. It has the potential to displace other periphyton grazers that are important 

food sources for juvenile Coho. Zebra (Dreissena polymorpha) and quagga (Dreissena 

bugensis) mussels are also major threats, and would utterly change the ecology of any streams 

they colonize.

[Response: In response to these and other reviewers’ comments, the BRT discussed this issue 

more fully; expanded discussion and literature citation is included in the revised document in the 

Ecosystem impacts of nonindigenous species subsection, Nonindigenous plant species 

subsection, and Nonindigenous fish subsection.]

2. I will not argue with the overall conclusion that OC coho are at moderate risk of 

declining to endangered status, hence deserve continued listing as threatened, even though I have 

concerns about several of the analyses (described above). In summary, I think the analysis of 

hatchery influence/ESU membership is inadequate, passage issues are being treated more 

effectively than recognized, the road density concern needs to be developed more as a 

disturbance analysis, and the habitat complexity analyses are provocative but need to be 

presented more fully for review and analysis. On the other hand, the implications of beaver pond 

declines are not fully acknowledged, more informative analyses could be done of freshwater 

wetland loss, water quality degradation needs also to consider dissolved oxygen and perhaps 

other parameters, and current and potential effects of exotic organisms need to be considered.

3. When I compare the status of OC coho to several other local stocks, I see a likelihood 

of comparable risk. These include OC winter steelhead, coastal spring Chinook salmon, and 

Siletz summer steelhead. Some of these may be protected from ESA consideration by the ESU 

delimitation process; if so, that process may be flawed. I am not suggesting that these all need 

listed, but it would be good to have a clear rationale for differentiating their status from that of 

coho.
212

Comments of Douglas County, Oregon

Comments on the National Marine Fisheries Service’s listing endangered and threatened species: 

Completion of a review of the status of the Oregon Coast evolutionarily significant unit of coho 

salmon; Proposal to promulgate rule classifying species as threatened

Federal Register May 26, 2010 (Vol. 75, No. 101)

David Loomis (BS Fisheries Science)

Ronald Yockim (BA, MA, JD)

Douglas County appreciates this opportunity to provide the most recent information on 

the Oregon coast coho salmon (Oncorhynchus kisutch) with the Umpqua River basin and to 

provide observations to the National Marine Fisheries Service (NMFS) related to the “Proposal 

to Promulgate Rule Classifying Species as Threatened” as discussed in the Federal Register 

notice of May 26, 2010 and the draft report from the Biological Review Team (BRT) entitled 

“Scientific Conclusions of the Status Review for Oregon Coast Coho Salmon.”

This information is being provided to NMFS in response to its proposed rule to continue 

its classification of the Oregon Coast Coho Salmon Evolutionarily Significant Unit (ESU) as 

threatened and in response to the proposal to designate the Cow Creek (ODFW stock number 37) 

coho hatchery program as a threatened species within this ESU. We believe the information we 

are submitting is of particular importance to the NMFS status review, given that the Umpqua 

coho populations have been cited in past reviews as a focal point of concern for both the effects 

of habitat degradation and impacts from a high percentage of hatchery fish in the run. Again in 

the current BRT review, a concern is highlighted as to a purported decline in habitat condition in 

the Umpqua Basin.

Douglas County has previously compiled and submitted quantitative information on the 

four wild coho populations in the Umpqua Basin (See Douglas County 1994, Douglas County 

2002, Cramer et al. 2004, Douglas County 2009, Douglas County 2010). The material being

provided herein builds on these former submissions with specific focus on the long-term 

abundance of wild coho in the North Umpqua. This information relies heavily on readily 

available information maintained by the Oregon Department of Fish and Wildlife (ODFW), 

including ODFW’s Winchester Dam counts of coho that date back to 1946. While the 

information being submitted focuses on the Umpqua River, the information is also relevant to the 

BRT’s scientific conclusions as to status review for the entire Oregon Coast Coho Salmon ESU 

(Stout et al. 2010).

As discussed in more detail below, during this 64-year period of records at Winchester 

Dam, none of the four independent populations within the Umpqua have gone extinct,

notwithstanding periods of very low abundance. During the past six decades the Umpqua River 

basin stratum and overall ESU population numbers have varied considerably. It is of more than 

passing scientific interest that notwithstanding this high degree of variability, the population has 

rebounded during recent years to be at or above the highest levels ever observed during this 64-
213

year period and most significantly the populations are above the historical levels observed in the 

1940s1 (Douglas County 2010).

[Response: This comment encompasses two basic points that appear throughout the Douglas 

County comments: that the North Umpqua population (and by extension the whole ESU) has 

rebounded from low levels in the past, and that this rebound suggests that the ESU is unlikely to 

be at risk of extinction in the future. In both its 2010 preliminary report and 2011 final report, 

the BRT extensively discussed the recent abundance trends of the populations, strata, and ESU as 

whole, including the fact that ESU-wide spawning abundance in recent years has been higher 

than any time since the 1950s. Indeed, the BRT noted that the relatively high abundance of the 

ESU was an aspect of ESU status that has clearly improved since the first status review in the 

1990s, and the current level of abundance was not, on its own, a significant risk factor to the 

ESU.

Response continued: However, the BRT also reviewed historical estimates of the ESU 

abundance, and noted that even with the recent upswing in spawning abundance the ESU is still 

only at approximately 10% of its historical abundance. In addition, although spawning 

abundance is relatively high, total recruitment remains below even the levels seen as recently as 

the 1970s, indicating that total (preharvest) abundance of the ESU has not in fact rebounded even 

to the levels observed just a few decades ago. All of these factors were carefully considered by 

the BRT in its assessment, and are discussed at length in the final BRT report.]

In addition to this quantitative data derived from actual population counts, Douglas 

County is also submitting comments expressing its continuing scientific concerns relative to the 

BRT’s model assumptions. As we have addressed in prior comments (Cramer et al. 2004), the 

hypotheses that drive the model and assumptions therein have not been tested with quantified 

data to determine truth values. We continue to have these concerns over the lack of scientific 

validation of the model as well as new concerns that have arisen as a result of the additional 

changes in the model that have not been tested. These untested assumptions and new 

assumptions into the model have inserted an extremely high bias towards extinction.

Notable among these revisions is the BRT’s decision to use peak counts of coho 

spawners for the metric of spawner density in determining the status of the populations based on 

critical abundance levels. As discussed in more detail below, this criterion is very sensitive to 

changes of values within the BRT’s Decision Support System (DSS), as well as very sensitive to 

subjective interpretations as to the biological condition at the population, biogeographic, stratum, 

and ESU scales (Wainwright et al. 2008, Stout et al. 2010). Given this sensitivity, we are 

surprised that the BRT did not provide any documentation as to its scientific testing that supports 

the decision to change the model input data set, particularly given that it utilized the omitted data 

set in its prior assessments of coho populations in Oregon.

[Response: The analysis found in Stout et al. (2010) was not a revision to the DSS because the 

TRT clearly intended that peak counts be used in this metric: “Metric: This is measured by the 

average peak spawner density (peak adults per mile of occupied spawning habitat) in the lowest 

 1 The 1946 time period wherein the Winchester Dam counts were initiated serves as an appropriate benchmark to 

compare the most recent 10-year period given that 1946–1947 was the end of a prior warm regime and the 

commencement of the 1947–1976 cool regime experienced under the Pacific Decadal Oscillation.
214

3 of the last 12 years.” (Wainwright et al. 2008, p. 38). As was discussed in the preliminary BRT 

report (Stout et al. 2010), Wainwright et al. (2008) inadvertently used AUC data instead of peak 

counts data in their initial application of the DSS, and this error was discovered when rerunning 

the DSS for the BRT analysis. For a more detailed discussion, please refer to Wainwright et al. 

(2008) on pages 38 and 39.

Response continued: Sharr et al. 2000 was a PFMC analysis, not a BRT assessment. The 

depensation criterion of four fish per mile (fpm) was determined by the TRT based on a variety 

of modeling and analysis, considering a variety of spawner density metrics. Barrowman et al. 

(2003) provided support for this criterion from analysis of productivity trends in many Canadian 

and U.S. river systems. Neville et al. (2006) and Isaak et al. (2007) provided evidence of the fine 

scale at which spawning salmon interact, supporting the use of peak count data for this metric.]

In addition to our concerns as to the failure of the BRT to adequately scientifically test its 

hypotheses prior to redefining the model metric relative to the spawner density data input, we are 

further concerned that this change resulted in a secondary error by failing to account for 25% of 

the actual peak numbers of coho on the spawning grounds. As a result of the model change,

along with this undercounting, the BRT has dramatically biased the results of the model.

[Response: The data set used by the BRT was provided by ODFW and was corrected for 

observer bias.]

Further, we note that notwithstanding the pessimistic outputs of the model, and despite 

the harsh ocean and freshwater conditions over the last several decades, the most recent 

population counts for the Umpqua River actually demonstrates a strong resiliency—a resiliency 

not acknowledged in the current BRT decision. Unfortunately, rather than rely on actual 

quantitative data, the BRT instead predicts a high risk of extinction based on pessimistic 

assumptions regarding depensatory mortality and future threats (Stout et al. 2010). As the data 

presented herein illustrates, the North Umpqua independent coho population has withstood all of 

the BRT’s identified past and current major threats to the viability of the population.2

[Response: It is not entirely clear which models and methodologies are being questioned here. 

However, the main points made in these comments seem to be that because the North Umpqua 

population has not in fact gone extinct, despite numerous risk factors, the results of the DSS and 

the assessment by the BRT that the population is at risk of extinction in the future must therefore

be in error. In fact, the BRT carefully considered the information discussed by the commentator, 

including the past variability in ESU abundance (including the North Umpqua) and threats such 

as the high fraction of hatchery fish and loss of high quality habitat. As the commentator points 

out, the ESU has demonstrated wide swings in abundance in the past in response to varying 

climate and other factors. As is discussed extensively in both the preliminary and final BRT 

reports, these wide swings in abundance, combined with ongoing threats such as climate change 

and habitat degradation, are one of the reasons the BRT was concerned about the viability of the 

ESU despite the recent upswing in abundance.

 2 It is questionable whether NMFS closely examined the most recent data set relative to environmental risks. For 

example, it describes the threats relating to sand and gravel operations on the Umpqua River but ignores the 

information provided by the State of Oregon that these same operations have ceased and are no longer permitted.
215

Response continued: The commentator also appears to be concerned that the negative 

persistence and sustainability values of the DSS for the North Umpqua population are not 

consistent with the relatively high current abundance of the population. However, until very 

recently (2008) the spawning composition of this population consisted largely of hatchery-origin 

fish. Consistent with both established NMFS policy (NMFS 2005b) and well-established science 

(e.g., McElhany et al. 2000, Nickelson 2003, Wainwright et al. 2008, Buhle et al. 2009), the DSS 

treats high proportions of hatchery fish in a population as a risk factor to the productivity and 

diversity of the population. As the BRT discussed in its reports (Stout et al. 2010 and this

technical memorandum), the recent reductions in hatchery production in the North Umpqua do 

improve the status of the ESU and this improvement was considered by the BRT in its final 

assessment. If data on returns from spawners in 2008 and subsequent years with low hatchery 

impacts indicate that the North Umpqua population is replacing itself without continual input of 

hatchery fish, the DSS persistence and sustainability scores will increase to reflect the 

population’s improved status.]

This population status is not only very well documented, it is also one that is notable for 

its sustainability and persistence over the past six decades despite high harvest levels of wild 

fish, very high percentage of hatchery fish returns mixed with wild spawners, various habitat 

impacts related to stream complexity on both public and private lands, low critical abundance 

levels, low marine survival rates, wide variations in stream flows, and other threats.

Notwithstanding that the BRT models produced results indicating that the North Umpqua 

population should currently be near or at a high risk of extinction, this conclusion is definitely in 

error, given that the actual production of wild coho currently, as well as in recent years, is near or 

above the 60-year average. Given the readily available data set for the coho within the Umpqua 

River system, one would expect that the BRT would have relied on this data set and at a 

minimum used it to validate the predictive certainty of the model. Rather than validate the 

model with existing quantitative data, the BRT relied on a model for which it acknowledged had 

a high uncertainty in its ability to predict a population’s persistence and sustainability over the 

next 100 years. As discussed below, we are concerned that NMFS is unscientifically placing the 

focus on qualitative and untested assumptions in a model rather than unbiased quantitative 

population data sets.

Based on the following discussion of the scientific data set, Douglas County is of the 

opinion that the Oregon Coast coho is best described as an opportunistic species that is not at risk 

of extinction. The information herein not only validates this opinion, it also provides the proper 

historical context to demonstrate that the current management policies and conservation

measures are and have been effective.

Not only are we concerned that the current BRT assessment does not reflect the true 

viability risk, as evidenced by the quantitative data that is available for the independent 

populations, we are also concerned that the BRT has adopted a new and untested qualitative 

prediction of climatic conditions for the next 100 years that also has a significantly high 

uncertainty of accuracy. Unfortunately, as with the other models the BRT did not test these 

predictive climatic models utilizing the long-term data sets that were available. In this case 

historic climatic records illustrate the coho evolved under a high range of climatic fluctuations, 

fluctuations which can be expected to occur in the future as well.
216

[Response: The BRT addressed the risks related to climate change using the best available 

scientific information, including a detailed review of available published, peer-reviewed 

literature relating to recent and future climate change in the Pacific Northwest and the likely 

effects of such change on OCCS. The BRT is aware of past and likely future trends and 

fluctuations in the local climate, and took those trends and fluctuations into account in the 

analysis. The BRT agrees that there is a great deal of uncertainty surrounding the effects of 

future climate on OCCS and took that uncertainty into account as a contributing risk factor. 

Much of the climate analysis does rely on predictive climate models that have been tested against 

long-term climate data. The BRT did not have the resources to conduct its own assessment of 

the accuracy of these models, instead relying on a large body of peer-reviewed scientific 

literature that has reported such assessments.]

We caution NMFS that the BRT report has selectively picked methodologies that support 

continued listing of the ESU. Further, we caution that notwithstanding these methodology 

concerns being raised in the past, the BRT continues to incorporate unscientific and untested 

methodologies into its assessment. Careful scrutiny and testing of the scientific validation of 

methodologies is warranted prior to any further reliance thereon.3

 This is particularly relevant,

given the extensive quantitative data set that is available that does not support the model results.

[Response: The BRT utilized the best available scientific information, including information 

submitted by the commentator. The overall methodology for conducting the status review was 

the same as NMFS has used for many past salmon status reviews and as such it has received 

extensive scientific review. The BRT also utilized specific methods and analyses developed by 

the Oregon/Northern California Coast TRT. The TRT consisted of a range of experts from 

NMFS, ODFW, USFWS, and independent consultants; the tools and methods it developed 

reflect that expertise.]

I. Viability of Naturally Spawned Coho Populations

The four independent coho populations in the Umpqua River Basin (Lower Umpqua, 

Middle Umpqua, South Umpqua, and North Umpqua), have a total of 1,624 miles of spawning 

habitat. By way of comparison, out of the total number of spawning miles within the Oregon 

Coast Coho Salmon Evolutionarily Significant Unit, the Umpqua River Basin represents 30% of 

the available spawning miles (ODFW 2009b).

The spawning habitat within the Umpqua River Basin is comprised of 409 miles in the 

Lower Umpqua and Smith River (Lower Umpqua), 433 miles in the upper main stem Umpqua 

including the Elk and Calapooya and other tributaries (Middle Umpqua), 656 miles in the South 

Umpqua basin including 131 miles in Cow Creek (South Umpqua), and 126 miles in the North 

Umpqua (North Umpqua). The wide distribution of habitat and spawning populations within the 

basin serves as an effective built-in protective mechanism against any one catastrophic event 

resulting in the extinction of the species.

[Response: We agree diversity and spatial structure are important factors to consider in 

evaluating extinction risk, and these factors were explicitly evaluated by the BRT and discussed 

 3 For example, if the models are correct, then there should be no set of circumstances which would have produced 

coho runs in the most recent years that exceed the historic averages.
217

in their report. In addition, the DSS developed by the TRT uses exactly this type of information 

in its diversity/spatial structure criteria.]

As discussed in more detail below, based on spawner abundance, density, and 

distribution within the North Umpqua independent population, the Umpqua Basin stratum, and 

the Oregon Coast ESU, the Umpqua River populations represent viable populations that are 

illustrative of coho populations throughout the ESU.

A. Wild coho population viability in the North Umpqua is supported by Winchester Dam 

counts since 1946

As the BRT correctly noted, the natural spawning (wild) abundance and total (preharvest) 

adult abundance have increased markedly over the past decade due to a combination of improved 

ocean conditions, lower harvest rates, and reduced hatchery production. The BRT, however, 

remained concerned that most of the increase in abundance to the populations could be attributed 

mostly to increased ocean survival rates, and to a lesser extent to hatchery and harvest recovery 

actions (Stout et al. 2010).

Since the 10-year window examined by the BRT provides only a very limited data set for 

describing events within an environment wherein decadal fluctuations of climate occur, we have 

compiled the ODFW data for the period of 1946 through 2009 as a more representative time 

frame to illustrate the spawning trends for the North Umpqua wild coho (Table 1).

[Response: The BRT report and analysis included the longest time series available. In the 

current revision we have added a reanalysis of ESU abundance from the 1880s to the present. 

This analysis suggests a 10-fold decrease in abundance over that time period. As detailed 

elsewhere, spawning trends in the North Umpqua by themselves are not sufficient to represent 

the entire ESU.]

We examined the extent of the increase in the wild coho population’s production by 

calculating the estimated total population for the North Umpqua and for the entire Umpqua Basin 

using the spawner abundance estimates plus the fraction of the population captured in ocean 

fisheries as estimated by ODFW (ODFW 2010b). This catch plus escapement of adults is the 

metric commonly applied by fisheries managers to estimate recruitment of adult coho from each 

brood.

By documenting the population’s and stratum’s annual production over a longer time 

frame than the BRT utilized, we found the production numbers strongly demonstrate that despite 

the combined threats—including naturally fluctuating marine conditions, high risk levels of 

hatchery fish, and harvest rates that occurred over the past 64 years—the ongoing abundance and 

resiliency of wild coho over this span of time is indicative of a viable population. When one 

tests the BRT models against this historical data, it is readily apparent the assumptions in the 

model are biasing the results toward a high degree of risk.

It is of more than passing interest to note that these same model assumptions were 

applied in the earlier BRT reviews which also resulted in predictions of a high risk of extinction; 

yet, subsequent to these earlier reviews, the actual populations have consistently been among the 

highest on record. For example, the 2009 total population (preharvest) count of more than 
218

Table 1. Total wild coho counts into North Umpqua, ocean harvest impact rates, and estimated total 

population, 1946–2009.

Return 

year

Wild coho 

Winchester counta

Harvest 

impact rateb

Wild coho total 

adult recruitsc

2009 8,233 0.19 10,164

2008 4,027 0.04 4,195

2007 1,798 0.28 2,497

2006 3,338 0.09 3,668

2005 2,388 0.12 2,714

2004 4,025 0.22 5,160

2003 3,363 0.23 4,368

2002 4,353 0.14 5,062

2001 3,069 0.16 3,654

2000 2,449 0.13 2,815

1999 1,506 0.10 1,673

1998 1,065 0.06 1,133

1997 909 0.12 1,033

1996 1,329 0.14 1,545

1995 1,570 0.22 2,013

1994 1,162 0.02 1,186

1993 1,012 0.42 1,745

1992 1,949 0.51 3,978

1991 1,823 0.45 3,315

1990 414 0.69 1,335

1989 1,798 0.57 4,181

1988 795 0.57 1,849

1987 1,063 0.60 2,658

1986 1,000 0.34 1,515

1985 1,317 0.38 2,124

1984 10 0.27 14

1983 10 0.75 40

1982 1,175 0.58 2,798

1981 1,491 0.78 6,777

1980 335 0.68 1,047

1979 465 0.73 1,722

1978 394 0.79 1,876

1977 578 0.85 3,853

1976 262 0.87 2,015

1975 529 0.76 2,204

1973 568 0.78 2,582

1972 407 0.80 2,035

1971 638 0.77 2,774

1970 204 0.61 523

1969 563 0.67 1,706

1968 1,647 0.73 6,100
219

Table 1 continued. Total wild coho counts into North Umpqua, ocean harvest impact rates, and estimated 

total population, 1946–2009.

Return 

year

Wild coho 

Winchester counta

Harvest 

impact rateb

Wild coho total 

adult recruitsc

1967 1,295 0.70 4,317

1966 917 0.60 2,293

1965 2,262 0.65 6,463

1964 1,166 0.67 3,533

1963 1,227 0.73 4,544

1962 548 0.57 1,274

1961 531 0.59 1,295

1960 346 0.57 805

1959 818 0.55 1,818

1958 573 0.72 2,046

1957 1,063 0.65 3,037

1956 2,760 0.66 8,118

1955 2,697 0.64 7,492

1954 389 0.64 1,081

1953 2,356 0.69 7,600

1952 3,066 0.45 5,575

1951 2,259 0.63 6,105

1950 1,375 0.62 3,618

1949 1,412 0.63 3,816

1948 790 0.63 2,135

1947 1,038 0.63 2,805

1946 1,438 0.63 3,886 a Jack counts are included in total. Many hatchery fish regenerated their fin marks in 1982, resulting in inaccurate 

(high) wild fish estimates. We caution reliance on the 1983 and 1984 populations in that the estimating techniques 

utilized do not accurately predict counts this low. All counts since 1991 reflect actual counts utilizing a video 

camera. Source of information is from ODFW records for the Winchester Dam on North Umpqua. b Estimated harvest impacts to naturally produced coho in the Oregon Production Index Area. From Table III-2 in 

the 2009 Preseason Report I, Pacific Fishery Management Council, Portland, OR. c Recruits = Winchester Dam Count / (1 – harvest rate).

10,000 wild coho is the highest on record since 1946. This compares to the record low numbers 

in 1983 and 1984, during which time periods less than 40 wild coho were estimated in the entire 

North Umpqua population.4

We selected the North Umpqua population as our reference for comparison based on: 1) 

the wild coho data for that basin are from Winchester Dam counts that are the actual fish counts 

of the total number of wild fish that crossed the dam since 1991 and the verified total counts 

 4 It is of more than passing interest that the population did not go extinct after reaching these low levels and in fact 

greatly expanded from less than 40 fish to more than 10,164 roughly 25 years later. This data indicates that neither 

the depensation nor the extinction levels are reached at the 40 fish over the dam level. Notably even at this low 

number, the coho still demonstrated a strong resiliency and ability to rebound relatively quickly.
220

since 1946, and 2) in prior and current analyses by NMFS this independent population was 

considered to be at the higher risk of extinction (Stout et al. 2010).

The following analysis also takes into consideration the annual variation in ocean harvest 

rates and reflects the current management policies and practices. It provides the best available 

scientific data set for comparing accurate population numbers over the long term (60 years) 

(Figure 1).

The annual fish population abundance trend over the last six decades is graphically 

displayed in Figure 1. It is important to note that this Winchester Dam data represent the total 

estimates of actual wild coho for the North Umpqua independent population. The North 

Umpqua population abundance records are not based on expansions or assumptions of fish 

population status using freshwater habitat condition indices (i.e., stream complexity) or ocean 

condition indices; rather these counts are the product of a very consistent monitoring method of 

returning coho at the same site (Winchester Dam) and are verified as being very accurate 

population counts dating back to 1946 (ODFW unpublished files).

[Response: The commentator seems to have misunderstood what data were used by the BRT. 

The BRT did in fact use the full record of Winchester Dam Counts as provided by ODFW.]

By way of comparison, the indices included in the BRT risk assessment have a higher 

statistical uncertainty than the actual counts derived from the Winchester Dam.

Further uncertainty around the BRT risk assessment is created by the BRT’s DSS model 

reliance on the untested assumptions that there are valid and sensitive (certainty) relationships 

for determining actual fish population productivity and sustainability.

 

0

2000

4000

6000

8000

10000

12000

19461948195019521954195619581960196219641966196819701972197419761978198019821984198619881990199219941996199820002002200420062008

Year

Wild Coho 

Wild Population 10 per. Mov. Avg. (Wild Population)

Figure 1. North Umpqua wild coho population, 1946–2009.
221

While the BRT recognized the limitations in its qualitative assumptions (Stout et al. 

2010), it did not take the necessary steps to scientifically validate the original or revised 

assumptions. Further, it is unfortunate that the BRT erroneously assumed that the spawning 

surveys represented the total counts of fish at a 1-mile habitat reach, population, stratum, or ESU 

level (1,000s of miles) when it changed the spawner density metric. It simply overlooked that 

these counts are not 100% estimates of every fish. While we agree that the spawner density 

metric is an appropriate metric, we point out that the failure to utilize the best available science 

relative to the spawner density data and verified population production that is available on the 

North Umpqua River system resulted in unscientific assumptions in the metric.

We also note that viability models for predicting fisheries’ responses are in relatively 

early stages of development, and as a result, the level of uncertainty in the projections remains 

high, especially when projecting out over very long time periods (i.e., 100 years) (IMST 1999).

[Response: The BRT does not disagree that there is significant uncertainty in long-term 

projections. This is why the BRT considered many aspects of Oregon Coast coho salmon 

ecology in assessing status and used a variety of information (population viability modeling, the 

TRT’s DSS, habitat assessments, climate assessments, assessment of other threats) in conducting 

its assessment. The BRT also was careful to characterize the degree of certainty of its 

conclusions and this was extensively discussed in both its preliminary and final reports.]

While the North Umpqua population production (preharvest estimates) over the last six 

decades covers a period wherein there has been large variation of marine survival rates, it is 

notable that this independent population has increased significantly in recent years (10-year 

moving average trend line in Figure 1), and in fact the population is at or above the highest 

abundance levels documented over the 64-year period of data.

This scientifically derived quantification of the population’s status alone strongly 

supports our assessment that the population is sustainable and persistent and has been so over a 

long-term span—a span that included all of the threats that the BRT used in its viability 

assessment for the independent populations and the ESU.

The observations of actual fish returns over the long term not only provides an indicator 

of the actual health status of a population, it also provides a critical monitoring tool that can be 

used to verify the scientific confidence level to be attributed to the qualitative model. As the 

Independent Multidisciplinary Science Team (IMST) cautioned, if model performance is of 

questionable scientific validity or reliability as is the case herein, then key indicators (e.g., 

observations of actual fish returns) should be used to supplement model estimates or replace the 

models (IMST 1999).

Another example wherein data was readily available to allow reasonable predictions yet 

was only selectively utilized is illustrated by the marine survival rates. While Douglas County 

agrees that marine survival rates are an important risk factor to include in this assessment and are 

especially critical during periods of low productively, we continue to have concerns over the 

manner in which this metric was applied in the model. As we expressed in prior comments 

relative to shifts in ocean conditions (Douglas County 1994), the BRT has made several key 

assumptions about future marine conditions that are not consistent with the known variability in 
222

ocean conditions. This is a particularly glaring omission, given that the BRT adopted these 

assumptions without taking the necessary steps to validate these assumptions against historic 

data on marine conditions. Key information was available on which the BRT could have 

assessed the marine conditions in both intra-annual and inter-decadal time frames. The recurring 

pattern of climatic variability is now well documented and accepted. As illustrated in Figure 2,

this pattern provides evidence of “reversals” of prevailing polarity and has distinct patterns of 

variation at intra-annual to inter-decadal time scales (Mantua et al. 1997).

Research in the 1990s demonstrated that marine ecosystem productivity is strongly 

correlated with the climatic regime changes brought about by the Pacific Decadal Oscillation 

(PDO), especially in the Northeast Pacific. This quantitative data supports the conclusion that in 

the future it is very likely that the PDO will continue to change polarity every few decades, as it 

has over the past century, and with it the abundance of salmon species (Mantua et al. 1997).

The warm regime of the 1900 to 1946 time period is represented by the above [zero] line 

... areas. Similarly, the cool regime of the 1946 to 1977 period is represented by the ... [areas 

below the zero line]. This shift in regimes is also depicted on the follow National Fisheries 

Science Center illustration.

The PDO index (Figure 3), illustrates a series of shifts from warm regimes ... [bars above 

the zero line] of the 1925 to 1946 time period and the 1977 to 1998 time period back to cold 

regimes ... [bars below the zero line] of the 1947 to 1976 time periods. Mantua related these 

regimes to adult salmon catches in the Northeast Pacific and demonstrated that these two events 

were correlated with the PDO. He found that major changes in the phase of the PDO have 

resulted in corresponding shifts in ocean biological productivity; warm eras have seen enhanced 

coastal ocean productivity of salmon in Alaska with corresponding inhibited productivity off the 

West Coast of the contiguous United States. Similarly, cold eras have resulted in relatively high 

salmon production in California, Oregon, and Washington and low salmon production in Alaska.

Figure 2. Monthly values for the PDO index: 1990–September 2009. Source: Mantua 2000, updated to 

2009 with online monthly values.
223

Figure 3. Pacific Decadal Oscillation warm-cold regimes.

The recent 1998 flip in the PDO is widely considered responsible for the current cooling 

ocean environment and upsurge in salmon runs.5

This shift in fisheries responses between the Alaska fishing zones and the OregonWashington regions is evidenced by the following excerpts from fishing reports of the time:

Pacific Fisherman Sept. 1915

“Never before have the Bristol Bay [Alaska] salmon packers returned to port after the 

season’s operations so early.”

“The spring [Chinook salmon] fishing season on the Columbia River [Washington and 

Oregon] closed at noon on August 25 and provided to be one of the best for some years.”

Pacific Fisherman 1939

“The Bristol Bay [Alaska] Red [sockeye salmon] run was regarded as the greatest in 

history.”

“The [May, June and July Chinook] catch this year is one of the lowest in the history of 

the Columbia [Washington and Oregon].”

National Fisherman 1972

“Bristol Bay [Alaska] salmon run a disaster.”

“Gillnetters in the Lower Columbia [Washington and Oregon] received an unexpected 

bonus when the largest run of spring Chinook since counting began in 1938 entered the 

river.”

Pacific Fishing 1995

“Alaska set a new record for its salmon harvest in 1994, breaking the record set the year 

before.”

 5 While there is reliable hindsight on which to assess climatic events, climate is highly variable and attempts to 

predict future events is fraught with high degree of error—particularly the further into the future one attempts to 

predict. The PDO is very valuable, however, in demonstrating the wide variations in climate experienced as well as 

to place into context the responses we experience today.
224

“Columbia [Washington and Oregon] spring Chinook fishery shut down; west coast troll 

coho fishing banned.”

These early reports illustrate the temporal variations in fisheries productivity that track 

the robust, recurring pattern of ocean-atmospheric variability of the PDO. Similar to the historic 

reports above, the coho populations from the Winchester Dam counts (Table 1) also dramatically 

illustrate this same phenomenon.

By overlaying the PDO cycles (Figure 3) on top of the graph depicting the 10-year 

moving average (Figure 1 and Figure 6), a similar variation in productivity is observed (Figure 

4). Note the productivity is depicted as a 10-year average which blurs the regime changes but 

nonetheless depicts the overall shift between cold and warm regimes on the 30–50 year cycles.

When one looks further back into the historic record, one finds similar climatic shifts 

dating back to 1735 in Oregon. The USGS study of tree rings covering the period of 1734 

through 1930 described similar oscillations as measured by the percentage deviation in normal 

precipitation in the Harney Basin of eastern Oregon [Figure 5].

The USGS report depicts the percentage deviation from normal precipitation as being a 

positive above the zero axis and a negative deviation below the zero axis. The positive 

deviations correspond to the cool regimes while the negative deviations correspond to warm 

regimes described by Mantua et al.

While the BRT acknowledged its uncertainty in its predictive model for quantifying risks 

from marine conditions for the foreseeable future, given global climatic change information, it

Figure 4. [North Umpqua wild coho population 1946–2009.]

Figure 5. Geology and groundwater resources of the Harney Basin, Oregon, Geological Survey Water 

Supply Paper 841, U.S. Department of the Interior, 1939, p. 13.
225

nonetheless adopted a pessimistic strategy in the face of this uncertainty (Stout et al. 2010). It 

did not, however, test its predictive model against the available historic records. This is a 

particularly glaring omission, given the BRT’s acknowledgment that it is relatively new to 

developing models for global warming and its failure to examine the coho in the context of the 

historic PDO events.

[Response: Douglas County does not specify what particular “key assumptions about future 

marine conditions” they question, so it is difficult to respond to this comment. However, any 

assumptions made by the BRT are consistent with the scientific literature regarding marine 

survival of coho salmon. The BRT agrees that fluctuations in marine conditions (including the 

PDO and other factors) strongly affect survival of OCCS, and has accounted for such 

fluctuations in its analyses.]

In examining the 64-year record of North Umpqua coho population production in the 

context of the PDO, one finds a more reliable tool for quantifying risk of extinction from 

climatic events. These quantitative data sets provide long-term historical evidence that the coho 

salmon species (independent populations and ESU-level) has evolved under many diverse and 

extreme habitat conditions, within both the marine and freshwater environments. These climatic 

extremes have resulted in the coho evolving with a genetic “natural climate insurance” that has 

been formed through many years of climatic and environmental conditions and cycles. This 

ability to survive within these climatic extremes is clearly demonstrated in the populations that 

are present today within the ESU.

Given this historical record, one would anticipate a qualitative prediction for the coho 

ESU over the next 100 years that is more likely optimistic, or at a minimum similar to the past 

century rather than the pessimistic approach of the BRT. One must assume that there will 

continue to be variability in season-to-season and year-to-year climatic rhythms, that there will 

be continued environmental uncertainty similar to that under which the species evolved, and that 

the range of variability in the future will be similar to that encountered in the past. Speculation 

as to future climate change may help planners prepare for all conceivable threats, however, this 

speculation does not satisfy the requirement that NMFS use best available scientific data in its 

determinations. When one examines the coho history in the climatic context, the pessimistic 

prediction of marine survival of coho in the foreseeable future is simply not warranted by the 

historical record.

The tie between salmon productivity and the PDO not only illustrates the widespread 

variation on which the coho have evolved and survived, it also demonstrates the error in not 

examining global warming predictions in the context of the greater historic record. 

Unfortunately, the BRT took a prospective model without validating the projected environment 

in the context of available historic records. Inclusion of speculative futures in the model enables 

NMFS to direct the model outcomes and therefore bias the results.

When one examines the variability in coho populations for the period of 1946 to the 

present in the context of the historical records of the PDO, one clearly becomes cognizant of the 

resilience of this species in the face of a highly variable climatic record. Further, one also 

readily becomes aware that the fluctuations experienced since the 1990s are not out of the realm 
226

of conditions experienced in the past—nor are they out of the realm to be expected to continue 

into the future.

B. Relationship of North Umpqua wild coho population compared to other independent 

populations in the Umpqua stratum and the OCCS ESU

In examining the coho spawner abundance estimates for the 1990–2009 time period 

(ODFW 2010b), one finds a similar annual variation in the abundance of wild coho returns 

irrespective of whether it is the North Umpqua or the entire Umpqua River basin. This variation 

allows us to examine the known population of the North Umpqua and make predictions for the 

entire basin. For example, North Umpqua spawner returns ranged from about 700 fish in 1997 to 

9,600 fish in 2009, with a 20-year average of 2,700 spawners and a median of 2,200 returns 

(Table 2). By way of comparison, the Umpqua Basin total spawner returns ranged from 3,400 in 

1997 to 65,000 in 2009, with a 20-year average of 21,100 spawners and a median of 16,300 

returns.6

One can readily assess the trend in spawner abundance for the North Umpqua, then 

extrapolate these numbers to the four independent Umpqua Basin populations (Umpqua stratum) 

to arrive at an accurate indication of annual production of wild coho for the entire stratum as well 

as the ESU.

[Response: The BRT is required to utilize the best available scientific information in conducting 

its assessment. To focus exclusively on dam counts for one population as an index of abundance 

for the entire ESU would be to ignore a vast amount of useful information collected from 

elsewhere in the ESU. In addition, the importance of spatial structure and diversity to ESU 

viability is well documented in the scientific literature (e.g., see review by McElhany et al. 

2000). Evaluating an entire ESU from dam counts for a single population would ignore 

important differences among populations. It would essentially restrict our analysis to a small 

amount of information, ignoring the vast majority of the information available to NMFS. It also 

does not take into account that the habitat in the North Umpqua population is not typical of the 

rest of the ESU, nor does it reflect the diversity of other habitats found in the ESU.]

In addition to the coho salmon population estimates set forth above, we were able to 

determine estimates of the annual wild coho spawner abundance for each of the four independent 

populations in the Umpqua (Table 3). The abundance values in Table 3 represent estimates for 

three of the populations and actual fish counts for the North Umpqua during the period of 1991 

to the present.

While there has been considerable variation in spawner returns over the past 20 years, in 

most cases the annual returns for the four independent populations track with each other, 

therefore indicating that the marine survival and ocean harvest rates were uniform influences on 

each population for that annual cohort.

 6 While ESU harvest impacts have varied significantly within these time periods, for this analysis we assumed that 

the individual harvest rate for the four populations was relatively equal. This assumption is appropriate given that 

most of the wild coho from the Umpqua system are harvested in the ocean fisheries and estuary where the four 

independent wild coho populations are mixed in the ocean, resulting in the harvest is spread across all four 

populations (Melcher 2005, ODFW 2009b).
227

Table 2. Coho population estimates for North Umpqua River and Umpqua River basin, based on adult 

spawner abundance and ocean harvest rates for 1990–2009. Total population estimate calculated from 

spawner abundance divided by (1 − ocean harvest rate %).

OCN ocean 

harvest (%)a

Spawner 

abundance

Total 

population 

estimateb

Spawner 

abundance

Total 

population 

estimateb

Return year North Umpqua Umpqua Basin

2009c 19 7,813 9,646 52,685 65,043

2008 4 3,438 3,581 32,306 33,652

2007 28 1,410 1,958 11,783 16,365

2006 9 3,062 3,365 18,154 19,950

2005 12 2,113 2,401 42,676 48,496

2004 22 3,705 4,750 31,346 40,187

2003 23 3,005 3,903 29,607 38,451

2002 14 3,780 4,395 37,591 43,710

2001 16 2,951 3,513 35,702 42,502

2000 13 1,838 2,113 12,233 14,061

1999 10 1,186 1,318 7,685 8,539

1998 6 727 773 9,153 9,737

1997 12 727 826 2,960 3,364

1996 14 1,075 1,250 10,824 12,586

1995 22 1,460 1,872 12,809 16,421

1994 2 851 868 5,336 5,445

1993 42 933 1,609 10,224 17,627

1992 51 1,607 3,280 3,759 7,671

1991 45 1,273 2,315 4,873 8,860

1990 69 376 1,213 4,113 13,268

Average 1990–2009 22 2,167 2,747 18,791 21,100

Median 1990–2009 15 1,533 2,214 12,008 16,325

a

Updated harvest rate impact rates estimates and total population numbers for previous years. ODFW and PFMC 

data.

b Total estimated number of naturally produced coho prior to harvest.

c Preliminary estimated coho spawner abundance and harvest impact rate for 2009.

Based on these spawner abundance estimates, the four independent populations in the 

Umpqua demonstrate an increasing trend in production during the most recent years. Notably, 

the data also illustrate that in 11 of the last 12 years the total spawner abundance has been in 

excess of the 20-year median—a result that tracks well with the projected PDO influences 

discussed earlier.

When one compares the coho spawner abundance in the Umpqua River basin with the 

entire ESU, one finds that on average, the Umpqua Basin represents about 18% of the total wild 

coho spawner returns to the ESU (Table 4). For example, in 16 of the last 20 years (1990–2009) 

the percent returns for the Umpqua stratum represented 13% to 21% of the entire ESU. In most 

years the Umpqua River spawner abundance is a very good indicator of annual production and 

trends for the entire ESU.
228

Table 3. Annual wild coho spawner abundance estimates in Umpqua River basin, 1990–2009.

Return year

Lower 

Umpqua

Middle 

Umpqua

South 

Umpqua

North 

Umpqua

Total 

Umpqua 

2009* 16,670 13,346 14,856 7,813 52,685

2008 12,267 4,594 12,007 3,438 32,306

2007 4,237 1,587 4,549 1,410 11,783

2006 7,994 4,852 2,246 3,062 18,154

2005 18,591 7,608 14,364 2,113 42,676

2004 8,046 7,911 11,684 3,705 31,346

2003 12,760 10,220 3,622 3,005 29,607

2002 14,492 10,904 8,415 3,780 37,591

2001 8,850 10,758 13,143 2,951 35,702

2000 3,696 4,638 2,061 1,838 12,233

1999 2,323 1,723 2,453 1,186 7,685

1998 5,118 823 2,485 727 9,153

1997 935 593 705 727 2,960

1996 4,904 2,048 2,797 1,075 10,824

1995 6,803 2,667 1,879 1,460 12,809

1994 1,689 1,948 848 851 5,336

1993 4,804 1,431 3,076 933 10,244

1992 1,769 192 201 1,607 3,769

1991 1,316 NA 2,284 1,273 4,873

1990 589 640 2,508 376 4,113

1990–2009 average 6,893 4,657 5,309 2,167 18,792

1990–2009 median 5,041 2,667 2,653 1,534 12,008

*Preliminary estimated coho spawner abundance. North Umpqua includes Winchester Dam counts (ODFW 2010a).

Comparing the annual spawner returns of the North Umpqua with the returns for the total 

ESU (Table 3), we found a close relationship which strongly supports the use of the North 

Umpqua data as a good index of the spawners within the total ESU (ODFW 2010b) (Figure 6).

The North Umpqua spawner abundance demonstrates that the four independent Umpqua 

River populations, as well as the ESU, continue to be viable over a long time span. In fact the 

data set illustrates that they are not only viable, but have significantly increased in recent years to 

a point wherein they are now near or above the historic levels that have occurred over the past 60 

years (Figure 6).

II. Model Results Do Not Reflect Abundance or Persistence of Populations in the ESU

A. Spawner density levels

Recent years of high spawner abundance have validated Douglas County’s previous 

comments that the NMFS models unduly overestimated the risk of extinction. As we discussed 

in earlier submissions, a continuing error in the BRT’s model is the use of spawner density as 

one of the critical abundance criterion utilized to determine the persistence truth value for a 

population.
229

Table 4. Annual estimates of wild coho spawner abundance in Umpqua River basin compared to Oregon 

Coast coho ESU, 1990–2009.

Return year

Umpqua 

Basin Oregon ESU % of ESU

2009* 52,685 230,458 23%

2008 32,306 165,324 20%

2007 11,783 66,169 18%

2006 18,154 128,838 14%

2005 42,676 154,131 28%

2004 31,346 175,380 18%

2003 29,607 228,681 13%

2002 37,591 260,570 14%

2001 35,702 172,617 21%

2000 12,233 70,110 17%

1999 7,685 49,128 16%

1998 9,153 32,004 29%

1997 2,960 23,398 13%

1996 10,824 74,021 15%

1995 12,809 53,979 24%

1994 5,336 44,169 12%

1993 10,244 55,344 19%

1992 3,759 42,197 9%

1991 4,873 37,602 13%

1990 4,113 21,279 19%

1990–2009 average 18,792 104,270 18%

*Preliminary estimate of coho spawner abundance (ODFW 2010a).

A demonstration of the lack of scientific reliability of the model’s reliance on this 

element is illustrated by the wild coho spawners in both the North Umpqua as well as the overall 

Umpqua stratum. ODFW surveys demonstrate that wild coho spawners have increased 

significantly over the past 10 years in relation to the total fish returns within the spawning areas 

since 1990 (Table 5).7

To calculate the spawner density, we used the available data relative to total spawner 

returns divided by the number of spawner miles8 over the selected time period. Given the long 

history of spawner returns on the North Umpqua, we selected the wild coho spawner return data 

as the data set that represents the most accurate record of spawner density in either the Umpqua 

stratum or the larger ESU (Figure 7).

 7 Significantly, during this period, there has not been a large decrease in the available spawning miles. While 

restoration projects have definitely increased fish passage and access to spawning stream miles in the basin, the 

number of these additional miles in relation to the overall total miles represents a proportionately small number of 

miles. Given that the increase in access is limited in comparison to the overall miles, the observed increase in 

spawner density is most directly related to increased spawner abundance levels basin wide, not a change in the 

number of spawner miles.

8 In the North Umpqua, there are currently approximately 126 miles of coho spawning habitat.
230

 

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005

YEAR

North Umpqua Wild Coho

0

50000

100000

150000

200000

250000

300000

350000

 Oregon Coast ESU Wild Coho 

North Umpqua Oregon Coast ESU 10 per. Mov. Avg. (North Umpqua) 10 per. Mov. Avg. (Oregon Coast ESU)

Figure 6. Numbers of wild coho returns to the North Umpqua and Oregon Coast ESU, 1950–2009. [Top 

line without symbols is Oregon Coast ESU; bottom line without symbols is North Umpqua.]

In Table 6, we summarize the wild coho returns in the North Umpqua segregated by

decades in order to provide the history of spawner abundance since records were first maintained 

at Winchester Dam (1946). This data set includes wild spawner numbers and total spawner 

numbers (wild and hatchery).

We divided the 10-year spawner average by the number of miles (126) in the basin to 

provide a data set for spawner density (Table 6). We utilized six decades since this closely 

reflects the three cycles of three generations of coho (9 years) typically utilized to assess spawner 

density.

In earlier BRT reports, as well as in other publications (i.e., Sharr et al. 2000 and 

Wainwright et al. 2008), the spawner density of four fish per mile has been utilized as the 

baseline in viability assessments as representing the minimum threshold wherein depensation 

problems based on low spawner abundance in the population can be avoided. Consistent with 

this approach, the current DSS model also includes the criteria of the average of the lowest 3 

years of spawner density over the past 12 years to address the persistence prediction.

Based on our analysis, the spawner density for the North Umpqua independent

population over the 10-year period from 1970 to 1979 averaged 4 wild fish per mile.9

 While at 

this density one would expect the population to face depensation problems, in fact, following this 

1970–1979 time period we experienced two decades (1980s and 1990s) wherein the spawner 

density of wild and total coho was well above the depensation threshold level—in large part due 

 9 In our analysis, we did not count hatchery fish in determining the spawner density or critical abundance.
231

Table 5. Annual wild coho spawners per mile in Umpqua River basin, 1990–2009.

Return year

Lower 

Umpqua

Middle 

Umpqua

South 

Umpqua

North 

Umpqua

Total 

Umpqua

2009* 41 31 23 62 32

2008 30 11 18 27 20

2007 10 4 7 11 7

2006 20 11 3 24 11

2005 45 18 22 17 26

2004 20 18 18 29 19

2003 31 24 6 24 18

2002 35 25 13 30 23

2001 22 25 20 23 22

2000 9 11 3 15 8

1999 6 4 4 9 5

1998 13 2 4 6 6

1997 2 1 1 6 2

1996 12 5 4 9 7

1995 17 6 3 12 8

1994 4 4 1 7 3

1993 12 3 5 7 6

1992 4 1 1 13 2

1991 3 NA 3 10 3

1990 1 1 4 3 3

1990-2009 average 17 11 8 17 12

1990-2009 median 12 6 4 12 7

* Preliminary estimated coho spawner abundance, (ODFW 2010a).

to the high abundance of hatchery fish returns to the Umpqua Basin (Figure 8 and Figure 9) until 

the elimination of the hatchery program on all but Cow Creek (located on the South Umpqua). 

This rebound in spawner density over the depensation level of four fish per mile, illustrates that 

the North Umpqua population does not have a long-term persistence problem that can be related 

to low spawner densities.

[Response: The spawner density levels cited were greatly influenced by hatchery returns, which 

make it impossible to assess the response of the wild population to low abundance events. Even 

if that were not the case, it would be inaccurate to conclude that because a population recovered 

from low abundance in the past that it will recover in the future under different conditions. 

Depensation includes random effects that do not necessarily happen every time low abundance 

occurs and recovery from one low abundance event does not necessarily mean that the 

population will recover from the next low abundance event. That is why the TRT included a 

criterion that assesses low spawner density, as it presents a risk to the recovery of the 

population.]

Notwithstanding the available data set illustrating a sustainable population, the BRT 

concluded that there was a high uncertainty of sustainability based on its interpretation of the 

modeled DSS scores.
232

 

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

19471949195119531955195719591961196319651967196919711973197519771979198119831985198719891991199319951997199920012003200520072009

Year

Winchester Dam Counts

Wild Spawners 10 per. Mov. Avg. (Wild Spawners)

Figure 7. Wild coho returns to the North Umpqua, 1946–2009.

Table 6. Average and median numbers and spawner density of wild and total coho counted at Winchester 

Dam, North Umpqua, 1946–2009, by decade. Source: ODFW unpublished data.

Average 

wild 

count

Median 

wild 

count

Average 

wild 

density

Median 

wild 

density

Average 

total 

densitya

Median 

total 

densitya

1946–1949 1,170 1,225 9 10 9 10

1950–1959 1,736 1,817 14 14 14 14

1960–1969 1,050 1,042 8 8 8 8

1970–1979 446 441 4 4 4 4

1980–1989 899 1,032 7 8 29 23

1990–1999 1,274 1,246 10 10 41 41

2000–2009 3,709 3,351 29 27 99 106

64-year average 1,487 1,164 12 9 31 31 a

Total wild and hatchery returns divided by 126 spawner miles.

B. Model results do not reflect actual production

While the BRT was concerned its population functionality criterion was strongly 

influenced by basin size since the four populations in the large Umpqua basin scored at the 

highest positive level under the model input,10 rather than rely on this result or validate the 

model or otherwise investigate this result, the BRT simply eliminated this criterion from the risk 

assessment and chose to use other habitat-based metrics. Unfortunately, the BRT did not

 10 Which is not surprising given the actual spawning counts and total number of coho present in the basin.
233

 

1,170

1,736

1,050

446

899

1,274

3,709

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

1946-49 1950-59 1960-69 1970-79 1980-89 1990-99 2000-09

Decade

Winchester Dam Counts

Figure 8. North Umpqua wild coho spawners average by decade, 1946–2009.

 

0 0 0 120

2785

3,854

8,799

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

1946-49 1950-59 1960-69 1970-79 1980-89 1990-99 2000-09

DECADE

Winchester Dam Counts

Figure 9. North Umpqua hatchery coho spawners average by decade, 1946–2009.11

 11 Hatchery releases on the North Umpqua were terminated in 2006.
234

validate the original model nor did it validate its modification of the model.12 This was 

surprising, given that under the BRT assessment, the North Umpqua, as the smallest of the four 

subbasins within the ESU, would have been expected to have resulted in one of the most 

accurate functionality scores.

[Response: This appears to be a misunderstanding of the report. The BRT included the 

population functionality criterion in the DSS. We discussed the need for reconsideration of this 

criterion in the future. In addition, the BRT did not rely only on the DSS in our deliberations, 

but rather included other factors and sources of information as well.]

This failure to accept its own model results is illustrative of the bias that the BRT utilized 

throughout its modeling. Rather than accept the model output, the BRT simply changed the 

model. Changing the model resulted in DSS scores for habitat functionality that not only 

differed significantly from actual habitat utilization, but also produced a biased appearance that 

the habitat status and trend for the most part are impaired and decreasing (Stout et al. 2010).

It is the BRT’s selectivity in the use of data that results in the counterintuitive DSS model 

results wherein the functionality of habitat within the relatively small North Umpqua basin is 

defined by the model as decreasing while at the same time fish productivity has actually been 

increasing.

We note that the DSS model scores for persistence and sustainability were –0.94 and 

–1.00 respectively for the North Umpqua. These negative scores are descriptive of a wild coho 

population that has a very high certainty of being in very poor shape and one that is in danger of 

extinction in the near future. 

The DSS characterizes a population with these scores as one where:

• abundance is low and declining,

• distribution of juveniles and spawners is very limited,

• genetic integrity is severely compromised,

• widespread destruction/alteration that create and maintain habitat has occurred,

• heroic measures are required for successful restoration,

• no opportunities for harvest, and

• hatchery programs should be restricted to captive breeding activities only.

Under the DSS scoring, one would therefore expect the numbers and productivity of the 

North Umpqua wild coho population to be dismal and at the lowest levels in history. Yet in fact, 

the opposite is true for the actual numbers of wild coho—and the persistence of the independent 

population as reflected in actual population counts over the last 60 years—simply do not reflect 

this result. The actual quantified data set for the North Umpqua reveals wild fish production in 

 12 The scientific approach would have been to truth test the model to either validate the result or delete the criterion 

as unscientific; in this case the BRT did neither, opting instead to simply eliminate the criterion since it did not 

produce the result it desired.
235

the North Umpqua that is neither impaired nor reflecting a declining trend. The long-term 

abundance data set actually demonstrates the population has a high certainty of persistence and 

sustainability, is in very good shape, and is at a very low risk of extinction.

The BRT’s negative scores for current viability status of the North Umpqua population is 

not merely counterintuitive, it simply does not reflect what is truly occurring in the North 

Umpqua population.

The lack of correlation between the actual quantified data (population numbers and 

spawning counts) and the model’s output reinforces our earlier concerns over the lack of 

reliability in the model. We continue to request that the BRT reexamine its model utilizing 

recognized scientific analyses and data—including truth testing. During the prior 2005 comment 

period, we and the ODFW raised similar concerns over the model’s results differing significantly 

from actual data. The existing data set for the North Umpqua not only demonstrates a very high 

certainty of a viable population, it also provides an excellent tool for validating the model.

C. The BRT arbitrarily changed population assessment model metric for spawner density

In spite of the lack of evidence that depensation (reduced survival at low population size) 

actually plays a key role in the population dynamics of coho salmon, the BRT continues to 

include depensation in its model, even while acknowledging that the model predictions are 

sensitive to the assumed depensation. Rather than removing or discounting the effects of 

depensation from the assessment, the BRT has amplified the effect that depensation has on coho. 

The manner in which depensation is applied is contrary to the best available science. Cramer et 

al. (2005) found that evidence supplied to NMFS by ODFW for Oregon coastal streams showed 

that coho survival continued to increase at the lowest observed spawner densities of less than one 

fish/mile. Thus even the criterion of less than 3.2 spawners/mile13 used previously by ODFW 

for assigning the onset of depensatory mortality was a substantially higher spawner density than 

for which such mortality was actually observed.

Another significant departure in the model that results in a significant bias towards listing 

is evidenced by the BRT election to use “peak count” data, rather than continue with the standard 

fisheries’ approach to utilizing “area under the curve” (AUC) for assessing the viability and risk 

level of the ESU.

In explaining this shift, the BRT stated:

The BRT concluded that peak abundance counts were more likely to capture the 

potential for depensation because the effect occurs for fish that are on the 

spawning grounds at the same time (that is, fish need to find mates that are on the 

spawning grounds at the same time they are.)

The BRT further stated:

The Critical Abundance criterion, ‘PP-3,’ in Wainwright et al. (2008), was 

discovered to have been evaluated using the wrong data set by the TRT 

(Wainwright et al. 2008). It was originally calculated using area-under-the-curve 

 13 The BRT compounded this error by using a spawner density of 4.0/mile as its depensation trigger point.
236

(AUC) spawner data rather than peak-count data as specified in the criterion. The 

updated Critical Abundance values are based on peak counts. AUC counts are 

almost always higher than peak counts ... . Peak counts are simply the highest 

number observed at any one time. The object of the criterion was to evaluate the 

likelihood of depensation due to low spawner numbers. ... This effect, termed 

‘depensation,’ is thought to become a problem at spawner densities below four 

fish per mile (Wainwright et al. 2008).

The BRT further acknowledged that the DSS scores resulted in a higher certainty of 

sustainability than persistence, which it described as an initially counterintuitive result. The 

BRT explained this disconnect by stating:

Even though population persistence is included in the sustainability criteria, the 

structure of the DSS logic tree and mathematical form of fuzzy logic used allows 

such a result. The cause of the relatively higher sustainability scores stem partly 

from the high scores for population functionality (PF) which was originally 

intended as a measure of habitat availability. Most populations scored very high 

for this criterion. However, in reviewing the DSS, the BRT was concerned that 

the metric for functionality—sufficient habitat to support a minimum number of 

smolts required for genetic integrity—did not adequately reflect the habitat 

quality issues this criterion was intended to address. The values for population 

functionality are strongly correlated with basin size ... . For example, the largest 

river system in the ESU, the Umpqua River, had all four populations with a 

functionality score of 1.0, even though there are serious concerns about habitat 

conditions in these populations.14 The BRT had several new analyses available to 

help evaluate habitat functionality ... and felt that these new analyses were more 

informative than the TRT’s Population Functionality criterion.

In addition, the data set adjustment from AUC counts to peak counts for Critical 

Abundance lowered the persistence score substantially. Persistence is evaluated 

using three factors, while sustainability uses seven (including the three persistence 

factors). As a result, persistence is much more sensitive to changes in a single 

factor than is sustainability, so this score is considerably lower than was reported 

in Wainwright et al. (2008) and, counterintuitively, lower than the sustainability 

score.

While the BRT was of the opinion that Wainright et al. (2008) used the wrong data set 

(AUC versus peak count), in fact, Wainright et al. followed not only the protocol generally 

accepted in the fisheries’ profession, it was also the same protocol that was used in prior BRT 

assessments (e.g., Sharr et al. 2000). Both Wainright and Sharr knowingly used the AUC data 

set in reaching the conclusion that four fish per mile standard was the best metric for the 

 14 When one examines the habitat conditions of concern, one finds that the sand and gravel mining has ceased, the 

instream water rights have not varied for more than 50 years and have been augmented with flows from Galesville 

Reservoir, stream side buffers have been implemented under the Northwest Forest Plan and the State Forest 

Practices Act, and other extension restoration projects have been successfully undertaken by the Partners for the 

Umpqua River and others. The serious concerns no longer exist or have been overstated. The sheer numbers and 

increasing population bring into question whether the habitat in fact justifies the “serious concerns” statement.
237

determination of the population density wherein there was risk of extinction as a function of 

depensatory factors affecting spawning success at low densities.

Rather than follow the standard AUC, the BRT elected to change from AUC to peak 

counts, effectively extrapolating data beyond the original experimental design under which this 

metric was developed. Unfortunately, the BRT does not provide any references or scientific 

analysis as to why the metric is still scientifically valid if peak counts is the measure as opposed 

to AUC. Nor does the BRT provide any justification for departing from the conclusions reached 

by Wainright and Sharr.

While the BRT elimination of part of the methodology relating to population 

functionality as described in Section B above in and of itself may not have been critical, the 

change away from AUC becomes critical in that it resulted in a significant bias as a result of the 

model continuing to utilize the less than four fish per mile as the numerical threshold for 

assuming there is a small-population demographic risk.

We caution that if the BRT continues to set the criteria at four fish per mile while 

utilizing the peak counts rather than the AUC, it needs to recognize that it is taking the original 

science out of context wherein the four fish per mile quantum was developed. To eliminate this 

bias, the BRT should reexamine the use of the same truth membership function for its critical 

abundance criterion (PP-3) notwithstanding its change to peak counts.

While we consider the shift to peak counts as a critical error in its own right, the bias is 

magnified when one recognizes that the BRT was assuming that the survey techniques utilized in 

developing the number of spawners per mile provided data on 100% of the population and that 

this population number was a reliable basis to assess depensation. Both were errors, for the 

survey techniques that are utilized for spawning surveys are recognized as understating the true 

number of fish per mile and are recognized as only a random sampling of the stream miles.15

The scientific literature documents the significant undercounting that results from this 

form of stream sampling. For example, Solazzi (1984) found that on average surveyors observed 

only 75.5% of adult coho, and only 49.1% of jack coho that were present in the survey sections. 

Solazzi further reported that surveyors observed only an average of 62.8% of coho carcasses. 

Solazzi observed that these percentages of coho and jacks observed did not significantly differ 

before or after the date of peak spawning (Solazzi 1984).

Based on Solazzi’s analysis, if the survey resulted in an adult peak count of four fish per 

mile, then the actual number of coho spawners in that reach would be at least five adults per 

mile. In addition to these five adults per mile, there could also be at least one jack coho. If one 

is to use the spawner surveys to assess depensation, then the number needs to be corrected to add 

 15 In this sampling technique, a large population may be present in the mile adjacent to the mile actually sampled. 

With a large unsampled neighboring population, it is scientifically impossible to accurately assess depensation for 

either the population sampled or the stream population as a whole.
238

in the additional 25% of adult spawners as well as the jacks which are not included in the 

spawner survey numbers reported in the ODFW data set.16

Our review reveals that the BRT failed to recognize the limitations in the sampling 

techniques that led to the area under the curve being the recognized standard as opposed to the 

peak count. By switching to peak counts for a depensation assessment without making the 

corrections improperly extrapolates data beyond the scientific design. This error can be 

corrected by either expanding the peak counts observed or by modifying the model’s truth 

membership function.

As a result of these errors, the BRT’s depensation risk at four fish per mile at peak times 

was erroneously triggered in the model for this viability assessment.

As the scientific literature illustrates, if the observed peak count is only 75% of total 

count, and one wants the threshold to be negative (below “0”), then the model should indicate 

this at three fish per mile recorded peak count, not four.

Since the AUC survey data used in previous assessments demonstrate the variability of 

timing of spawner return over several weeks and includes more accurate abundance data that 

bears on the possible problems that may be associated with depensation, we recommend that if 

depensation is important for the model, then at a minimum the BRT return to the AUC model 

rather than the peak count strategy that was adopted. Further, since the depensation model is so 

sensitive to low numbers, it should be adjusted to reflect actual populations rather than merely 

random samples which have a high risk of missing critical population blocks.

In addition, the adult peak counts do not account for the additional jack spawners or that 

there is some overlap in fish entering and spawning in the survey reach.

[Response: The BRT noted several places where the DSS could potentially be improved, and if 

the TRT or others update the DSS, this may be a useful comment to consider during that process. 

The BRT utilized the TRT product for its analysis as one important factor to consider in 

evaluating the viability of the ESU, but other than updating (or in some cases correcting) the 

input data did not elect to modify the DSS. However, the BRT extensively discussed the DSS 

structure and results, and considered the strengths and limitations of the DSS in its final 

assessment.]

Illustrating how the model is subject to bias as a result of not reflecting actual population 

behavior, we compared the actual counts derived from Winchester Dam with the spawner survey 

data. We found that when actual wild adult coho counted at Winchester Dam are compared with 

the spawning survey estimates, in four out of the past five years the spawning survey estimates 

resulted in density numbers that were well below the actual number of spawners (Table 7).

Further illustrating the care that must be used in applying spawner densities to measure 

depensation is demonstrated by data derived from sampling on the Smith River in the lower 

Umpqua Basin. The Smith River study found that there is an overall negative bias of about 27% 

 16 We note that the Winchester Dam counts indicate that about 22% of the spawners in the North Umpqua are jacks 

(ODFW unpublished data).
239

Table 7. Wild coho counts at Winchester Dam compared to spawner survey estimates on the North 

Umpqua above Winchester Dam.

Year

Winchester 

Dam counts*

Survey 

estimates

Winchester minus survey

Fish % bias

2009 7,724 2,310 +5,414 –70%

2008 3,438 1,500 +1,938 –56%

2007 1,410 1,081 +329 –23%

2006 3,000 2,154 +846 –28%

2005 2,113 3,692 –1,579 +75%

* Adjusted for harvest and brood stock collection.

associated with spawner survey-based estimates (Jacobs 2002). Again illustrating that the use 

solely of spawner surveys would most likely directly bias any predictive model based on 

spawner abundance numbers.

We also note that the current AUC monitoring conducted annually for spawner survey 

estimates has been previously recognized as having a low precision on a basin and stratum level 

(Jacobs and Nickelson 1998). If spawner density metrics derived from small population levels 

are used in the model, then the BRT model must recognize an uncertainty ranging up to ±80% of 

the stated value.

Jacobs and Nickelson (2008) caution that for a given level of sampling, coast-wide 

estimates will always be substantially more precise than estimates for individual basins, and 

precision is directly related to the number of surveys conducted and the size of the geographic 

unit where inference is being drawn.

When used for the spawner density criterion, the peak count data would be expected to 

result in an equal to or higher range of uncertainty whenever the number of surveys is below 50 

reaches for each population (Beidler and Nickelson 1980). Beidler and Nickelson found that the 

“peak count” to “total” ratio ranged from 0.20 to 0.74, which they concluded resulted in peak 

counts being a poor indicator of abundance on a year to year basis. Based on this study, the use 

of peak count data simply may not be a valid assumption for annual spawner density estimates in 

assessing critical abundance (depensation).

It appears that the BRT’s model, wherein depensation using peak counts is incorporated,

overstepped the scientific certainty values associated with this data, and in addition, it 

erroneously did not take into consideration the factor of about 25% unobserved fish and the jacks 

that are actually present on the spawning grounds.

While we are concerned that the BRT model was not based on the best available 

scientific data and results in a significant bias relative to depensation on the ESU level, we also 

note that as a practical matter it should not be an issue on the North Umpqua, given that actual 

quantitative data from the 1946–2009 time period illustrates that contrary to the model, this 

population has shown resiliency even during low density levels. Most telling is the fact that this 

population is increasing in production following years when the model predicted significant 

depensation.
240

Similar conclusions should be reached for the entire ESU, given that the Winchester Dam 

data set not only provides the best science for assessing the health of the Umpqua populations, it 

also provides a highly accurate data set on which to validate the model assumptions. Utilizing 

actual data that is available for the North Umpqua wild coho population would significantly 

change the overall scores for persistence and sustainability for not only this population, but for 

many other independent populations and most likely for the entire ESU.

III. Summary

Based on our review of the available scientific information, it is clear that the North 

Umpqua independent population is near or above historical levels of abundance as compared to 

the six decades of data from the Winchester Dam counts, has been increasing in the recent 

decade, and is not in danger of extinction in the near future (at least for 60 more years), given the 

threats currently identified.

Notwithstanding this actual data and history, the current BRT’s risk assessment 

concluded that this population has a very high certainty of being in very poor shape and in 

danger of extinction within the near future (within 100 years) assuming the very same threats it 

has encountered in the past.

Based on model results for the Umpqua Basin stratum relative to abundance and 

resiliency, we are concerned that at least one of the BRT model’s major criterion assumptions is 

not valid or reliable.

Based on actual quantitative data on fish abundance and density, along with the historic 

climatic patterns, there clearly is not sufficient certainty that the qualitative model is the best 

available science on which to base a decision that this ESU is threatened in the foreseeable 

future.

We recognize and share the BRT’s uncertainty as to the ability to predict future habitat 

and climatic conditions; however, given the wide variation experienced over the last 300 years,

as evidenced by tree rings, we strongly recommend that the BRT look to the historical record.

The historical review shows a well-documented history and scientific record of 

persistence and sustainability for the North Umpqua population. This history strongly supports 

the findings that current hatchery releases, harvest practices, escapement, and ocean and 

freshwater habitat conditions are not likely to change in a manner that would further risk the 

viability of this wild coho population and others within the ESU.

[Response: The BRT did examine the historical record and recognized that there are strong 

climate driven fluctuations in abundance and productivity. We incorporated fluctuations in both 

the TRT criteria and the BRT risk assessment.]

IV. References

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Recent NOAA Technical Memorandums

published by the

Northwest Fisheries Science Center

NOAA Technical Memorandum NMFS-NWFSC117 Maynard, D.J., T.A. Flagg, W.C. McAuley, D.A. Frost, B. Kluver, M.R. Wastel, J.E. Colt, and 

W.W. Dickhoff. 2012. Fish culture technology and practices for captive broodstock rearing of ESAlisted salmon stocks. U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-117, 65 p. NTIS 

number pending.

116 Lian, C.E. 2012. West Coast open access groundfish and salmon troller survey: Protocol and results 

for 2005 and 2006. U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-116, 52 p. NTIS 

number PB2012-107486.

115 Plummer, M.L., W. Morrison, and E. Steiner. 2012. Allocation of fishery harvests under the 

Magnuson-Stevens Fishery Conservation and Management Act: Principles and practice. U.S. Dept. 

Commer., NOAA Tech. Memo. NMFS-NWFSC-115, 84 p. NTIS number PB2012-107485.

114 Bradburn, M.J., A.A. Keller, and B.H. Horness. 2011. The 2003 to 2008 U.S. West Coast bottom 

trawl surveys of groundfish resources off Washington, Oregon, and California: Estimates of distribution, 

abundance, length, and age composition. U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC114, 323 p. NTIS number PB2012-105507.

113 Ford, M.J. (ed.). 2011. Status review update for Pacific salmon and steelhead listed under the 

Endangered Species Act: Pacific Northwest. U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC113, 281 p. NTIS number PB2012-104687.

112 Skidmore, P.B., C.R. Thorne, B.L. Cluer, G.R. Pess, J.M. Castro, T.J. Beechie, and C.C. Shea. 

2011. Science base and tools for evaluating stream engineering, management, and restoration proposals. 

U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-112, 255 p. NTIS number PB2012-104660.

111 Leonard, J., and P. Watson. 2011. Description of the input-output model for Pacific Coast fisheries. 

U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-111, 64 p. NTIS number PB2011-113405.

110 Ainsworth, C.H., I.C. Kaplan, P.S. Levin, R. Cudney-Bueno, E.A. Fulton, M. Mangel, P. TurkBoyer, J. Torre, A. Pares-Sierra, and H.N. Morzaria Luna. 2011. Atlantis model development for the 

northern Gulf of California. U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-110, 293 p. 

NTIS number PB2011-113404.

109 Levin, P.S., and F.B. Schwing (eds.). 2011. Technical background for an integrated ecosystem 

assessment of the California Current: Groundfish, salmon, green sturgeon, and ecosystem health. U.S. 

Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-109, 330 p. NTIS number PB2011-112724.

Most NOAA Technical Memorandums NMFS-NWFSC are available at the

Northwest Fisheries Science Center Web site, http://www.nwfsc.noaa.gov