NOAA Technical Memorandum NMFS-NWFSC-79

U.S. DEPARTMENT OF COMMERCE

National Oceanic and Atmospheric Administration

National Marine Fisheries Service

Identification of HistoricaI

Populations of Coho Salmon

(Oncorhynchus kisutch)

in the Oregon Coast

Evolutionarily Significant Unit

January 2007
NOAA Technical Memorandum

NMFS Series

The Northwest Fisheries Science Center of the National

Marine Fisheries Service, NOAA, uses the NOAA Technical Memorandum NMFS series to issue informal scientific 

and technical publications when complete formal review 

and editorial processing are not appropriate or feasible due 

to time constraints. Documents published in this series may 

be referenced in the scientific and technical literature.

The NMFS-NWFSC Technical Memorandum series of the 

Northwest Fisheries Science Center continues the NMFSF/NWC series established in 1970 by the Northwest & 

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split into the Northwest Fisheries Science Center and the 

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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 cited as follows:

Lawson, P.W., E.P. Bjorkstedt, M.W. Chilcote, C.W.

Huntington, J.S. Mills, K.M.S. Moore, T.E. Nickelson, G.H. 

Reeves, H.A. Stout, T.C. Wainwright, and L.A. Weitkamp. 

2007. Identification of historical populations of Coho 

salmon (Oncorhynchus kisutch) in the Oregon coast evolutionarily significant unit. U.S. Dept. Commer., NOAA Tech. 

Memo. NMFS-NWFSC-79, 129 p.
NOAA Technical Memorandum NMFS-NWFSC-79

U.S. DEPARTMENT OF COMMERCE

National Oceanic and Atmospheric Administration

National Marine Fisheries Service

Identification of HistoricaI

Populations of Coho Salmon

(Oncorhynchus kisutch)

in the Oregon Coast

Evolutionarily Significant Unit

Peter W. Lawson, Eric P. Bjorkstedt1, Mark W. Chilcote2, 

Charles W. Huntington3, Justin S. Mills4, Kelly M.S. Moore5,

Thomas E. Nickelson6, Gordon H. Reeves7, Heather A. Stout,

Thomas C. Wainwright, and Laurie A. Weitkamp

Northwest Fisheries Science Center

Newport Research Station

2032 Southeast OSU Drive

Newport, Oregon 97365

Southwest Fisheries Science Center

HSU Telonicher Marine Laboratory

PO Box 690

Trinidad, California 95570

Oregon Department of Fish and Wildlife

3406 Cherry Avenue Northeast

Salem, Oregon 97303

Clearwater Biostudies, Inc.

23252 South Central Point Road

Canby, Oregon 97013

Frank Orth and Associates

4040 Lake Washington Boulevard Northeast, Suite 208

Kirkland, Washington 98033

Oregon Department of Fish and Wildlife

Corvallis Research Laboratory

28655 Highway 34

Corvallis, Oregon 97333

Kisutch Consulting

75 Alydar Place

Paso Robles, California 93446

US Forest Service

PNW Research Station, Forestry Sciences Laboratory

3200 Jefferson Way

Corvallis, Oregon 97331

January 2007

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Most NOAA Technical Memorandums

NMFS-NWFSC are available online at the 

Northwest Fisheries Science Center

web site (http://www.nwfsc.noaa.gov)

Copies are also available from:

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5285 Port Royal Road

Springfield, VA 22161

phone orders (1-800-553-6847)

e-mail orders (orders@ntis.fedworld.gov)

ii
Table of Contents 

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

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

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

Acknowledgements......................................................................................................................................xi

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

Population Concepts.................................................................................................................................3

Populations and ESUs ..............................................................................................................................4

Conceptual Approach to Identifying and Classifying Historical Populations..........................................5

Identifying Populations........................................................................................................................5

Classifying Populations........................................................................................................................6

Methods and Results...................................................................................................................................12

Criteria for Identifying the Distribution of Historical Populations ........................................................12

Documented Historical Use................................................................................................................12

Geographical Isolation .......................................................................................................................16

Biological Characteristics...................................................................................................................16

Ecological Characteristics..................................................................................................................37

Methods for Population Identification and Classification......................................................................47

Identification Method.........................................................................................................................47

Identification Results..........................................................................................................................48

Population Classification........................................................................................................................52

Classification Methods.......................................................................................................................53

Classification Results.........................................................................................................................57

Discussion...................................................................................................................................................67

Uncertainties...........................................................................................................................................68

Other Applications of the Connectivity-Viability Model.......................................................................69

Definition of Biogeographic Strata in the Oregon Coast Coho Salmon ESU.............................................70

Glossary ......................................................................................................................................................77

References...................................................................................................................................................85

Appendix A: Vegetation .............................................................................................................................97

 iii 
Appendix B: Ecoregions of the Oregon Coast Coho Salmon ESU from South of the Columbia River 

to Cape Blanco............................................................................................................................................99

Level 3 Ecoregion Descriptions .............................................................................................................99

Level 4 Ecoregion Descriptions ...........................................................................................................100

Appendix C: Potential Historical Abundance of Coho Salmon................................................................103

Calculating Adult Abundance ..............................................................................................................103

Results..................................................................................................................................................104

Discussion ............................................................................................................................................105

Appendix D: Principal Components and Clustering Analysis..................................................................113

Methods................................................................................................................................................114

Results..................................................................................................................................................116

Discussion ............................................................................................................................................125

 iv 
List of Figures 

Figure 1. Coho salmon ESUs.......................................................................................................................2 

Figure 2. Conceptual model of ESU population structure ...........................................................................7 

Figure 3. River and stream basins in the Oregon Coast Coho Salmon ESU..............................................13 

Figure 4. Potential historical coho salmon distribution in the Oregon Coast Coho Salmon ESU. ............14 

Figure 5. Changes from historical distribution of Oregon Coast coho salmon due to the addition 

or removal of passage barriers. ...................................................................................................................15 

Figure 6. Generalized life cycle of the coho salmon in Oregon.................................................................22 

Figure 7. Coho salmon freshwater proportion of jacks caught in Tahkenitch, Siltcoos, and 

Tenmile lakes basins 1960–1994. ...............................................................................................................27 

Figure 8a. North Coast Monitoring Area spawn timing for Oregon Coast coho salmon for 2001............28 

Figure 8b. Mid-Coast Monitoring Area spawn timing for Oregon Coast coho salmon for 2001..............29 

Figure 8c. Suislaw River to Tenmile Lakes spawn timing for Oregon Coast coho salmon for 2001........30 

Figure 8d. Mid-South Coast Monitoring Area spawn timing for Oregon Coast coho salmon for 2001....31 

Figure 8e. Small systems spawn timing for Oregon Coast coho salmon for 2001 ....................................32 

Figure 9. A maximum likelihood tree of Oregon Coast coho salmon genetic samples.............................35 

Figure 10. Timing of annual peak flows in rivers of the Oregon Coast Coho Salmon ESU. ....................38 

Figure 11. Mean annual flow in rivers of the Oregon Coast Coho Salmon ESU. .....................................39 

Figure 12. Seasonality of monthly stream flow in rivers of the Oregon Coast Coho Salmon ESU. .........40 

Figure 13. Duration of high flows in the Oregon Coast Coho Salmon ESU .............................................41 

Figure 14. Average annual precipitation in watersheds of the Oregon Coast Coho Salmon ESU. ...........43 

Figure 15. Vegetation zones in the watersheds of the Oregon Coast Coho Salmon ESU. ........................44 

Figure 16. Level 3 ecoregions of the Oregon Coast Coho Salmon ESU. ..................................................45 

Figure 17. Level 4 ecoregions of the Oregon Coast Coho Salmon ESU. ..................................................46 

Figure 18. Level 4 ecoregions in the Nehalem River Basin and the surrounding area..............................49 

Figure 19. Level 4 ecoregions of the Tillamook Basin and the surrounding area. ....................................49 

Figure 20. Level 4 ecoregions of the Umpqua River Basin and the surrounding area. .............................51 

Figure 21. Level 4 ecoregions of the Coos Basin and surrounding area....................................................53 

Figure 22. Historical coho population potential versus basin area for Oregon Coast basins.....................55 

Figure 23. Box-whisker plots of estimated historical coho salmon productivity for Oregon Coast 

basins smaller and larger than 5,000 hectares.............................................................................................57 

Figure 24. Connectivity-viability analysis for Oregon Coast coho salmon ...............................................58 

 v 
Figure 25. The relationship between the quantity of high-quality habitat and probability of extinction...59 

Figure 26. Proposed historical coho populations in the Oregon Coast Coho Salmon ESU.......................64 

Figure 27. Allozyme clusters discerned in Olin’s 1984 report on genetic variability in coho salmon 

of the Oregon Coast. ...................................................................................................................................72 

Figure 28. Gene conservation groups for Oregon Coast coho salmon as defined in Kostow....................73 

Figure 29. Oregon Coast coho salmon monitoring areas defined by ODFW in 2003. ..............................74 

Figure 30. Biogeographic strata defined within the Oregon Coast Coho Salmon ESU.............................75 

Figure C-1. The relationship between historical potential coho salmon adult abundance estimated 

by historical catch records and adult abundance calculated from GIS data..............................................107 

Figure C-2. Intrinsic potential of rivers and streams on the north coast segment of the Oregon 

Coast Coho Salmon ESU. .........................................................................................................................109 

Figure C-3. Intrinsic potential of rivers and streams on the mid-coast segment of the Oregon 

Coast Coho Salmon ESU. .........................................................................................................................110 

Figure C-4. Intrinsic potential of rivers and streams on the Umpqua River Basin segment of the 

Oregon Coast Coho Salmon ESU. ............................................................................................................111 

Figure C-5. Intrinsic potential of rivers and streams on the mid-south coast segment of the 

Oregon Coast Coho Salmon ESU. ............................................................................................................112 

Figure D-1. Dendrogram showing clustering of the first three principal components for 

environmental data in the Oregon Coast Coho Salmon ESU ...................................................................126 

Figure D-2. The first five clusters from cluster analysis of the first three principal components for 

environmental data from the Oregon Coast Coho Salmon ESU...............................................................127 

Figure D-3. Dendrogram of heirarchical clustering of the first three principal components for 

environmental data for watersheds within the Umpqua River Basin........................................................128 

Figure D-4. Clusters of fifth-field watersheds in the Umpuqa River Basin identified by shading 

corresponding to groups shown in Figure D-3..........................................................................................129 

 vi 
List of Tables 

Table 1. Ocean entry basin areas with stream lengths...............................................................................17 

Table 2. Locations of ocean entries for basins along the Oregon Coast. ...................................................19 

Table 3. Oregon Coast coho salmon smolt outmigration peak timing and duration..................................23 

Table 4. Oregon Coast coho salmon smolt sizes........................................................................................25 

Table 5. Potential historical smolt and adult abundance for 56 putative populations of coho salmon 

in the Oregon Coast Coho Salmon ESU. ....................................................................................................54 

Table 6. Other basins originally included as historical dependent populations.........................................62 

Table 7. Proposed historical populations, listed north to south, with classification ..................................63 

Table 8. Locations of ocean entry and distance to the nearest functionally independent population 

ocean entry point for basins along the Oregon Coast .................................................................................65 

Table C-1. Estimate of potential historical abundance of coho salmon in large basins of the Oregon 

Coast Coho Salmon ESU..........................................................................................................................106 

Table C-2. Potential historical smolt and adult abundance for 56 putative populations of coho 

salmon in the Oregon Coast Coho Salmon ESU.......................................................................................108 

Table D-1. Data sources for the principal components analysis..............................................................114 

Table D-2. Reclassification scheme for geology data from USGS..........................................................115 

Table D-3. Climate data for the Oregon Coast ESU used in the PCA for the Oregon Coast Coho 

Salmon ESU..............................................................................................................................................117 

Table D-4. Physiographic and biogeographic data used for PCA for the Oregon Coast Coho 

Salmon ESU..............................................................................................................................................120 

Table D-5. Principal component eigenvectors and variance for the Oregon Coast Coho Salmon ESU..123 

Table D-6. Principal component eigenvectors and variance for the Umpqua River Basin......................124 

 vii 
 viii 
Executive Summary 

In 2003 the Oregon Workgroup (Workgroup) of the Oregon Northern California Coast 

Technical Recovery Team (TRT) convened to review and analyze information that could shed 

light on historical populations of Oregon Coast coho salmon (Oncorhynchus kisutch). This 

document presents the preliminary conclusions of the Workgroup. A historical perspective 

describing how these populations functioned is an important first step in assessing the viability of 

present-day populations, in developing delisting criteria, and as an overall recovery strategy. 

Documentation of life history traits, distribution, or abundance of Oregon Coast coho 

salmon prior to 1940 is limited. Considerable biological information has been gathered during 

the past 30 years, and particularly the past 12 years; however, it is difficult to relate the 

biological characteristics of modern populations to those that existed historically in the same 

basin. Human activities over the past 200 years have altered every aspect of salmon habitat on 

the coast, harvest has changed abundance patterns, and hatcheries may have blurred the 

distinctions among stocks. Coho salmon have adapted their behavior to many of these changes 

and, as a result, present-day Oregon Coast coho salmon populations function differently than 

they did historically. Nonetheless, we have tried to address where populations existed 

historically and how these historical populations functioned. 

To establish historical population boundaries, we relied on geographical and ecological 

characteristics of the landscape that have not been greatly altered by human activities. 

Geographical information was used in calculating the distance between ocean-entry points. 

Ecological characteristics were utilized in partitioning the Umpqua Basin into four historical 

populations. A total of 56 historical populations were identified through this analysis. 

Our view of the historical population structure of Oregon Coast coho salmon relies on a 

simple conceptual model of the spatial relationships of 56 populations. We used a rule-based 

approach to identify populations. Subsequently, we utilized a connectivity-viability model to 

classify these populations on the basis of two key characteristics: persistence (their relative 

abilities to persist without input from neighboring populations), and isolation (the relative degree 

to which they might have been influenced by adult fish from other populations migrating into 

their spawning areas). The interaction of these two factors across what we believe to have been 

the historical populations of Oregon Coast coho salmon gives us a measure of relative 

independence. This relative independence gives us a basis for classifying the populations as 

functionally independent, potentially independent, and dependent. Thirteen populations were 

identified as functionally independent, 8 as potentially independent, and 35 historical populations 

were identified as dependent populations. We will use this classification in the next step—

analyzing the viability of populations and ultimately of the ESU in order to identify quantitative 

goals for recovery. Two other recovery groups (the Southern Oregon Northern California Coast 

Workgroup and the Central California Coast TRT) are also using the connectivity-viability 

model to classify their populations. 

 ix 
These proposed historical populations are intended to represent the range and diversity of 

populations of Oregon Coast coho salmon, not necessarily to be an exact reconstruction. In this 

representation of historical populations, we assume that ocean feeding areas were a shared 

resource and that, in the Umpqua River Basin, populations probably shared juvenile rearing and 

migration corridors. Understanding the historical structure of populations in addition to their 

abundance and life history characteristics provides a framework for comparing the historical to 

the present status of populations, the changes that have affected them, and the restoration of 

processes that may be necessary to recover them. 

 x 
Acknowledgments 

Identification of the historical populations of Oregon Coast coho salmon was conducted 

by a team of scientists from the NOAA Fisheries Service Northwest Fisheries Science Center 

(NWFSC), Oregon Department of Fish and Wildlife (ODFW) Research Division, U.S. Forest 

Service (USFS) Pacific Northwest Research Station, Oregon Watershed Enhancement Board 

(OWEB), and Clearwater Biostudies, Inc. This Oregon Workgroup is a committee of the Oregon 

and Northern California Coast Technical Recovery Team (ONCC TRT). The Workgroup relied 

on published literature, informational reports, and unpublished data made available by state, 

tribal, and federal agencies. The authors acknowledge the efforts of all who contributed to this 

process, especially the ODFW and the OWEB. 

Numerous scientists and fishery managers deserve special thanks for providing 

information that aided in preparation of this report on historical populations. We particularly 

want to thank the Independent Multidisciplinary Scientific Team for its in-depth analyses on the 

role of lowlands in coho salmon life history. Thanks are also due to Lance Kruzic (NOAA 

Fisheries Service Northwest Regional Office (NWR), Bridgette Lohrman (NOAA Fisheries 

Service NWR), and Cid Hughes (MES, Inc.) for their significant contributions to this effort. 

The ONCC TRT consists of Walt Duffy, USGS California Cooperative Fish Research 

Unit; Dave Hillemeir, Yurok Tribe Fishery Biologist; George Kautsky, Hoopa Valley Tribe 

Fishery Biologist; Thomas Lisle, USFS, Pacific Southwest Research Station; Mike McCain, Six 

Rivers National Forest; Mike Rode, California Fish and Game Region I; Cochairs Tommy 

Williams, Southwest Fisheries Science Center, and Peter Lawson, NWFSC; Thomas 

Wainwright, NWFSC; Thomas Nickelson, ODFW; Charles Huntington, Clearwater Biostudies, 

Inc.; and Gordon Reeves, USFS Pacific Northwest Research Station. Recovery Coordinators are 

Rosemary Furfey of NOAA Fisheries Service NWR and Greg Bryant of NOAA Fisheries 

Service Southwest Regional Office. 

The Oregon Workgroup for Oregon Coast coho salmon consists of Peter Lawson, 

Thomas Wainwright, Gordon Reeves, Thomas Nickelson, and Charles Huntington. Adjunct 

members are Mark Chilcote and Kelly Moore, both of ODFW. Heather Stout of NWFSC staffs 

the Oregon Workgroup. 

 xi 
 xii 
Introduction 

The Oregon Coast Evolutionarily Significant Unit (ESU) of coho salmon (Oncorhynchus 

kisutch) was listed as threatened under the U.S. Endangered Species Act (ESA) (Fed. Reg. 

63:42587–42591) in 1998. The ESA requires that a recovery plan be produced for listed species. 

As part of the recovery planning process, the National Marine Fisheries Service (NOAA 

Fisheries Service) has convened a group of scientists (NOAA 2003) to act as the Technical 

Recovery Team (TRT) for the Oregon and Northern California Coast (ONCC) recovery domains 

(Figure 1).1

 The two recovery domains are composed of the Oregon Coast Coho Salmon and 

Southern Oregon and Northern California Coast (SONCC) Coho Salmon ESUs. The ONCC 

TRT is made up of the Oregon Coast and Southern Oregon, Northern California Coho 

Workgroups. As a team, our goal was to provide a scientific context for identifying necessary 

actions to help the species recover. The TRT was asked to 1) identify population and ESU 

delisting goals; 2) characterize habitat/fish abundance relationships; 3) identify the factors for 

decline and limiting factors for the ESU; 4) identify early actions that are important for recovery; 

5) identify research, evaluation, and monitoring needs; and 6) serve as science advisors to groups 

charged with developing measures to achieve recovery. This report is the first in a series 

providing the scientific foundation for biological delisting goals for the Oregon Coast Coho 

Salmon ESU. Subsequent reports will discuss population and ESU biological recovery criteria, 

factors limiting the recovery of the ESU, and research and monitoring needs. 

Under the ESA, biological delisting goals define the biological conditions under which 

the listed species or ESU is no longer in danger of extinction nor likely to become endangered in 

the foreseeable future in any significant portion of its range. That is, these goals define the 

conditions necessary for the long-term persistence of the ESU as a whole. An ESU has, by 

definition, persisted as a unit on an evolutionary time scale. Knowledge of its structure (its 

component populations, their functions, and their interactions) under historical conditions before 

current threats became substantial provides a background against which to evaluate recent status 

and minimum conditions needed for long-term persistence. Because the persistence of the ESU 

depends on the aggregate performance of its component populations, an essential first step in 

developing delisting goals is to identify the historical populations of the ESU and define their 

interrelationships. 

An ESU is composed of numerous constituent populations with varying features and 

behaviors. Some populations function essentially independently over moderate time scales, 

while others interact more strongly with nearby populations. In this report we describe what we 

believe were historical populations in the Oregon Coast Coho Salmon ESU. We draw on a 

variety of data sources and analyses to estimate the historical size, relative independence, and 

geographical range for each population. 

 

1 A complete description of TRT composition, tasks, and operating principles can be found in the NOAA Fisheries Service 

document “Recovery planning guidance for technical recovery teams” (online at http://www.nwfsc.noaa.gov/trt/ 

about.htm).
 Figure 1. Coho salmon ESUs (NOAA 1999). 

 2
This document does not attempt to define current populations or what future populations 

will look like. It is our view that recovery will require a restoration of landscape processes that 

will enable fish to establish populations in whatever configuration suits them currently, not 

necessarily what has existed in the past. 

The next part of the TRT deliberation will define population and ESU biological recovery 

criteria and delisting goals based initially on these historical populations. However, these 

proposed populations may change in the future, depending on this analysis. This process will 

continue to feed back to each step if changes are needed. 

This document describes how the TRT divided the ESU into populations and further 

classified these populations into independent (functionally and potentially) and dependent 

populations and geographic strata. This identification and classification system assumes a model 

for delisting criteria that 1) uses geographic strata as a means for ensuring geographical, genetic, 

and ecological diversity of the recovered ESU, and 2) distinguishes between independent 

populations that are the focus of rigorous viability analyses and dependent populations, which 

may be less intensively monitored or managed. Under this model, ESA delisting goals would 

differ among the population classes, with rigorous quantitative productivity, abundance, and 

habitat goals for functionally and potentially independent populations and more qualitative goals 

such as presence and absence for dependent populations. 

Population Concepts 

In the biological literature, the term “population” often refers simply to a group of 

organisms of the same species that occur in the same area (such as McNaughton and Wolf 1973, 

Ehrlich and Roughgarden 1987). In a fishery research and management context, Ricker (1972) 

provided a more specific definition of a local population or “stock” as the “fish spawning in a 

particular lake or stream (or portion of it) at a particular season, which fish to a substantial 

degree do not interbreed with any group spawning in a different place, or in the same place at a 

different season.” This definition has been widely used in assessments of salmon populations 

(such as WDF et al. 1993, Kostow 1995). McElhany et al. (2000) based their definition of 

“independent population” on Ricker’s definition of “stock.” They made the phrase “to a 

substantial degree” more specific and drew a distinction between independent and 

nonindependent populations. “Independent populations” were described as basic units for 

assessing population viability in the context of Pacific salmon (Oncorhynchus spp.) recovery 

planning. While we draw heavily from the review of population structure provided by 

McElhany et al. (2000), we found that their strict distinction between independent and 

nonindependent populations was overly simplistic when applied to the Oregon Coast Coho 

Salmon ESU. We therefore have taken a somewhat different approach to classifying 

populations, starting with Ricker’s (1972) definition of a stock. 

Definition of a Population 

A population is 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. 

 3
Our purpose was to describe the historical population structure of the Oregon Coast Coho 

Salmon ESU. The structure and dynamics of the ESU populations in a historical context 

represent the conditions under which we are most certain that the ESU was not at risk of 

extinction. We are increasingly uncertain of the ability of the ESU to persist as the condition of 

the populations diverges from this baseline. We do not propose that historical conditions are the 

benchmark for population or ESU viability. Rather, we identify historical population structure as 

a template against which current and possible future population structures can be compared in 

the course of developing ESU biological recovery criteria. This document is concerned only 

with historical populations. There is no attempt to evaluate current population structure or 

compare current populations with historical populations. 

Populations and ESUs 

To develop conservation plans, planners must clearly define the organizational units of 

the organisms of concern (Meffe and Vrijenhoek 1988) and understand how those units behave 

and interact over time. Two biological units are considered in developing recovery plans for 

coho salmon listed under the ESA: ESUs and populations. In defining units for potential ESA 

listings of Pacific salmon, NOAA Fisheries Service adopted the concept of ESUs as the 

definition of listable “species” under the ESA (NMFS 1991, Waples 1991a).2 ESUs are 

collections of local populations that share common demographic and genetic features. Over 

moderate time frames (1 to 10 generations), there may be periodic exchanges of individuals 

among the populations that make up an ESU, but there is little interaction with populations in 

other ESUs (Moritz et al. 1995). This document focuses on identifying the structure and relative 

independence of local populations within the Oregon Coast Coho Salmon ESU. 

We acknowledge the link between biological structure and scales of space and time in our 

approach to identifying and classifying populations. The scale of ESUs was defined in terms of 

major patterns of genetic and life history diversity (Waples 1991b). Implicit in this definition is 

the idea that an ESU is made up of a number of populations, so the scales relevant to population 

structure are smaller than those for ESU structure. Populations are expected to exchange 

individuals at substantially higher rates within an ESU than between ESUs (Moritz et al. 1995). 

ESUs are defined primarily with respect to large genetic divergences (Waples 1991a). 

Populations are demographic units within which individuals interact at time scales of a few days 

to a few generations, whereas ESUs are genetic units in which relevant variation and structure 

change on time scales of tens to hundreds of generations. 

The genetic structure of salmon ESUs is dynamic, at least on evolutionary time scales. 

There is no single array of genes (or combination of alleles) that can be said to make up an ESU. 

Rather, the integrity of an ESU is linked to maintaining the dynamic nature of natural 

evolutionary processes (gene flow, genetic drift, and adaptation) (Waples 1995). These 

processes are only imperfectly understood for salmon in general, and this applies as well to the 

Oregon Coast Coho Salmon ESU. Nevertheless, within most salmon ESUs a number of natural 

population units have persisted as largely independent entities for periods that are long on 

ecological time scales (100 years or more). The effort to identify historical populations of 

 

2

 The term “species” included any subspecies of fish or wildlife or plants, and any distinct population segment of 

any species of vertebrate fish or wildlife that interbreeds when mature (ESA section 3). 

 4
Oregon Coast coho salmon has focused on such units, because they are natural units for 

assessing viability. In many ESUs, including Oregon Coast coho salmon, the role of small 

populations and their relationship to larger, historical populations is poorly understood. We 

would expect that our understanding of Oregon Coast coho salmon population genetics will 

improve as results from ongoing genetics research and other studies become available. 

Meanwhile, we consider that a population of any size may play a significant evolutionary role 

within the ESU. 

Viability of an ESU is coupled with the viability and dynamics of its constituent 

populations. Our approach to these populations defines the relationships among the populations 

in terms of their interactions; this approach provides us with a basis for comparing historical 

populations with current populations and for assessing population viability and, subsequently, 

ESU viability, in a variety of restoration scenarios. 

Conceptual Approach to Identifying and Classifying 

Historical Populations 

In preparing for a coast-wide effort to develop recovery plans for all listed Pacific salmon 

ESUs, NOAA Fisheries Service developed a general approach to assessing the viability of ESUs 

(McElhany et al. 2000). The first step involves identifying the historical populations within an 

ESU and then classifying them in terms of their degree of historical independence. McElhany 

et al. (2000) acknowledged that the extinction risk of an entire ESU is a complex function of the 

dynamics of the ESU’s component populations. They also considered that, although the 

population structure of ESUs is both complex and variable, the problem of ESU risk could be 

simplified by identifying “independent”3 populations whose viability4 could be assessed as 

individual units. ESU viability can be defined largely in terms of the viability of these 

independent components. To define and classify historical Oregon Coast coho salmon 

populations, we have followed the broad concepts outlined by McElhany et al. (2000). However, 

we recognize that population independence in this region is more complex, and is relative rather 

than absolute. We have, therefore, developed a population classification scheme that reflects the 

properties of individual populations and the interactions among populations. This proposed 

approach is intended to provide a uniform means of identifying the population structure of coho 

salmon for coastal ESUs south of the Columbia River. It was developed in collaboration with 

the Oregon Coast Workgroup of the ONCC TRT and the Central California Coast TRT, but has 

had additional input from the full ONCC TRT and staff from other coastal TRTs. 

Identifying Populations 

Our approach to identifying populations differs somewhat from the approach taken by 

other TRTs (Myers et al. 2006, Ruckelshaus et al. 2006) due to differences among the listed 

 

3

 An independent population, according to McElhany et al. (2000, p. 3), is “any collection of one or more local 

breeding units whose population dynamics or extinction risk over a 100-year time period is not substantially altered 

by exchanges of individuals with other populations.” 

4

 A viable salmonid population (McElhany et al. 2000, p. 2) is “an independent population of any Pacific salmonid 

(genus Oncorhynchus) that has a negligible risk of extinction due to threats for demographic variation (random or 

directional), local environmental variation, and genetic diversity changes (random or directional) over a 100-year 

time frame.” 

 5
salmon species. Along the linear Oregon Coast, there are many basins of all sizes, each with a 

separate ocean entry point. This landscape contrasts with the river networks of the Columbia 

Basin, and with the hub-and-spoke geography of Puget Sound, where populations distribute 

themselves from a central basin or hub into contributing river basins or spokes. These 

differences in the geometric patterns of rivers result in different patterns of movement of fish 

between rivers and, therefore, different population structures and population dynamics. We 

sought a population definition that would be relevant to the geography and population dynamics 

on the Oregon Coast and would accommodate rivers and streams of vastly different sizes. While 

the role of large basins in ESU viability is obvious, it was also clear to the TRT that smaller 

basins are also an important part of the ESU. Our approach was designed to reflect this structure 

and to elucidate the historical role of each population in the demographic functioning of the 

ESU. 

One of the problems in describing the historical population structure for Oregon Coast 

coho salmon was that this region of coast is composed of basins with a wide range of sizes. In 

this ESU, direct ocean tributaries range from less than 1 to greater than 4,600 stream miles (less 

than 1.6 to over 7,400 km). Large basins may have multiple populations. Smaller basins that 

drain directly into the ocean probably did not support enduring populations, but are not 

necessarily a part of a single larger unit. We had no basis for combining smaller basins with 

larger ones, and we thought it was important to reflect the full range of coho salmon habitats on 

the Oregon Coast. Spawners have a strong tendency to return home to their basin of origin, so 

each basin would naturally form a separate population. We have, therefore, defined historical 

populations based on their points of saltwater entry. 

Classifying Populations 

In order to classify historical populations of Oregon Coast coho salmon, we first had to 

explain our view of the population dynamics historically operating in this ESU. Because of the 

linear nature of the Oregon Coast, our approach to this problem is somewhat different from the 

other TRTs (Myers et al. 2006, Ruckelshaus 2006). We based our conceptual model of 

population dynamics for this ESU on existing literature regarding the functioning of complex 

populations in general and salmon populations in particular (Rieman and Dunham 2000). Two 

assumptions we made were 1) populations interact through the exchange of individuals, and 2) 

movement of individuals in salmon populations is strongly influenced by the physical 

relationship of ocean entry points (Figure 2). None of the published literature exactly matched 

the patterns of connectivity implied by the geography of the Oregon Coast or population 

interactions of coho salmon. Consequently, we adapted concepts from the published literature 

(see, for example, Hanski and Gilpin 1997) to develop our own population classification system, 

with quantitative support from the Bjorkstedt connectivity-viability model (Bjorkstedt et al. 

2005) and estimates of historical population size based on a new synthesis of physical habitat 

features (intrinsic potential) and historical population abundance calculations (Appendix C). 

 6
 

Figure 2. Conceptual model of ESU population structure. Arrow widths are proportional to number of 

migrants. 

 7
Persistence, isolation, and independence in population classification 

In developing the classification system for historical Oregon Coast coho salmon 

populations, we utilized three key population characteristics: persistence, isolation, and 

independence. 

Persistence is the ability of a population to sustain itself through time without inputs 

from other populations. 

Isolation is the degree to which a population is unaffected by immigration to and from 

other populations: as the influence of immigration decreases, a population’s isolation increases. 

Independence reflects the interaction between isolation and persistence: a persistent 

population that is highly isolated is highly independent. 

A population’s persistence relies on the quantity and quality of habitat, which in turn 

influences potential population size. Habitat quantity and quality can be expressed in terms of 

the habitat’s capacity to produce fish (in other words, the potential population size supported by 

the habitat). All else being equal, persistence is related to population size, with large populations 

tending to have a greater probability of persistence than small populations. 

Processes that influence population dynamics affect small populations differently than 

large ones (McElhany et al. 2000). These processes include density effects, variation in 

environmental conditions, genetic processes, demographic stochasticity, and catastrophic events. 

Density effects can be positive or negative for small populations. As population numbers decline 

below carrying capacity, population production may increase because more resources are 

available to the remaining individuals. This gives a population resilience as productivity 

increases when numbers decline. If numbers decline below a critical point, reproduction may 

start to decline because individuals are unable to secure mates (Hilborn and Walters 1992). 

Environmental variation may result in periods of unfavorable conditions for a population. If the 

duration of unfavorable conditions persists longer than the reproductive cycle of the species, then 

populations may decline (Dennis et al. 1991, Lande 1993). Small populations may produce 

poor-quality offspring through the effects of genetic processes such as loss of diversity and 

inbreeding depression (accumulations of deleterious genes that reduce their ability to survive). 

Demographic stochasticity includes nongenetic changes in fecundity, mortality, and sex ratios. 

Changes in the reproductive potential and capacity that result from these factors are much more 

pronounced in small populations than in large ones (Lande 1998). Catastrophic events, either 

natural or man-made, may result in large mortality in a short time period. Through a 

combination of genetic and demographic factors, population numbers may be reduced below the 

level at which the population is able to maintain itself (Mangel and Tier 1994). Taken together, 

the various processes that cause small populations to lose productivity are termed “depensation.” 

Watershed size also influences population size. Larger watersheds in general will be 

expected to support more fish than smaller watersheds. Additionally, larger watersheds will be 

composed of smaller subwatersheds. Larger populations may, therefore, contain subunits. This 

resulting structure within larger systems provides a buffer against infrequent catastrophic events, 

which historically were fires and floods and the subsequent landslides on the Oregon Coast 

 8
(Reeves et al. 1995). These events generally affected only parts of the landscape. Some subunits 

may have been lost temporarily while unaffected subunits continued to produce fish. Smaller 

populations, without the buffering effect of subunits, may have been lost in such cases. Larger 

populations may also have a greater genetic diversity, which increases the potential for a 

population to respond to unfavorable or changing conditions (Waples 1990, Waples and Teel 

1990). 

There is a theoretical lower limit to the size of (or habitat required for) a persistent 

population (reviewed in Soulé 1987); below this minimum, random events and depensation 

cause the risk of extinction to increase substantially. This concept informs our consideration of 

independence; any extant population occupying a basin with sufficient habitat to support a 

minimum population size is likely to persist continuously. Populations with less habitat are 

likely to persist only if there is significant immigration from other populations. If we knew the 

minimum habitat capacity necessary to support a persistent population, we could separate those 

populations that can function independently in isolation from those that cannot simply on the 

basis of habitat capacity. Even if we do not know the theoretical lower limit to the population 

abundance or habitat capacity required to produce that minimum population size, we may be able 

to use habitat capacity as a proxy measure for the relative ability of a population to persist 

without immigration. 

A population’s isolation reflects the degree to which immigration from other populations 

affects its dynamics: as the influence of immigration decreases, a population’s isolation 

increases. This concept can also be thought of in terms of the ratio of spawners hatched in that 

basin to spawners from other basins. This ratio is influenced by the rate that spawners from 

other populations migrate in, and the size of the other populations. A small population next to a 

large one is apt to have a high proportion of spawners from the larger population even if 

migration rates are low. It only takes a few fish from a large population spawning in a small 

population to lower the smaller population’s degree of isolation. A simplifying assumption we 

are using here is that there is an underlying rate of dispersal among basins. We recognize that 

dispersal rates can be highly variable. 

McElhany et al. (2000) suggest that, for the purposes of recovery planning, a particular 

population should be considered independent if exchanges of individuals with other populations 

do not substantially affect the dynamics of that population over a 100-year time frame. 

However, in our view, independence is relative and reflects the interactions between isolation (in 

other words, proportion of spawners hatched in that population returning to a population) and 

persistence. When we consider whether a population is independent in the context of this 

analysis, we do not base our consideration on the current state or predicted fate of that population 

(in other words, the population’s historical persistence or whether the population has a high 

likelihood of persisting for 100 years into the future). Instead, we combine the degree of 

isolation of a population with the inferred historical abundance to compare the relative 

independence of each population in relation to others in the ESU, regardless of its likely 

persistence. 

 9
Categories of historical populations 

As a specific criterion for relative persistence, we chose to define “high-persistence 

populations” as those that would have a high likelihood of persisting with no migrants from 

neighboring populations for 100 years. The boundary between high persistence and low 

persistence reflects the abundance (or habitat capacity) below which persistence begins to 

decline rapidly (Nickelson 2001). Those populations that did not meet this criterion were 

classified as “dependent populations.” These low-persistence populations would probably not be 

in existence if they were not receiving migrants from neighboring populations. As a next step, 

high-persistence populations were further divided into two types (“potentially independent” and 

“functionally independent”) on the basis of their historical interaction with other populations 

(isolation). The boundary between functionally and potentially independent populations reflects 

the likelihood of influence from other nearby populations (the proportion of native spawners 

returning to a population). Functionally independent populations on average provide more 

migrants to other populations than they receive, so their demographics are not greatly influenced 

by outside migrants. 

We separated historical populations into three categories based first on their relative 

persistence and then on their degree of isolation: 

Functionally independent populations: high-persistence populations whose population 

dynamics or extinction risk over a 100-year time frame is not substantially altered by exchanges 

of individuals with other populations. These 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). 

Potentially independent populations: high-persistence populations whose population 

dynamics may be 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. 

Dependent populations: low-persistence populations that rely upon immigration from 

other populations. Without these inputs, dependent populations would have a lower likelihood 

of persisting over 100 years. They are “receiving” populations that are dependent on sufficient 

immigration from surrounding populations to persist. 

Isolation depends primarily on two factors: 1) the size and potential productivity of a 

population relative to nearby populations, and 2) the effective migration (migrants who 

contribute to the next generation) among nearby populations (Moilanen and Nieminen 2002, 

Bjorkstedt et al. 2005). The effective migration among nearby populations is a function of the 

size of the donor population, the distance from the donor to the receiving population, and the 

ability of the migrants to contribute offspring to the receiving population. The larger the donor 

population and the closer it is to the receiving population, the greater the rate of effective 

migration. Functionally independent populations, in that they are highly persistent and hence 

larger populations, are more likely to have individuals that stray to other populations. Thus 

populations closest to large functionally independent populations will have a greater potential for 

receiving migrants than will populations that are farther away from larger donor populations 

 10
(Figure 2). A population that is classified as potentially independent due to its proximity to a 

very large functionally independent population might function at some other time as functionally 

independent if the very large neighboring population experienced a significant population crash. 

Dependent populations are very likely to rely on immigration from both functionally and 

potentially independent populations. Seldom would dependent populations be expected to 

contribute directly to the long-term persistence of other population types by providing migrants. 

Both functionally and potentially independent populations tend to be larger than 

dependent populations (Figure 2). Populations with larger numbers of individuals spread over a 

larger area are better buffered than are smaller populations from the impact of catastrophic flood 

and fire events (Reeves et al. 1995); catastrophic events on the scale of a large watershed are rare 

(Reeves et al. 1995). In addition, these larger populations often occur in larger watersheds with a 

greater variety of habitats, including areas of stable, lowland habitat that is most productive for 

coho salmon. Dependent populations are smaller and thus more vulnerable to periodic declines 

resulting from events in the freshwater and marine environments. 

All population types, in varying degrees, contribute to the persistence and productivity of 

the ESU. Functionally independent populations are the foundation of the ESU. Because of their 

large size, these populations make the greatest contribution to the productivity and persistence of 

the ESU. The potentially independent populations are also important sources of productivity that 

may function as “giver” populations to the dependent populations. A potentially independent 

population may play an important role in the persistence of a functionally independent 

population if the productivity of that system declines due to disturbance in freshwater or 

estuarine habitats. Dependent populations contribute to the overall health of the ESU by 

increasing the total productive area, and may provide reservoirs of potentially adaptive diversity 

for the ESU (Buckling et al. 2003). They may also be important for maintaining the integrity of 

a given watershed. For example, returning adults provide nutrients that are used by a wide array 

of other aquatic and terrestrial organisms and vegetation (Cederholm et al. 1999). 

One task of the TRT is to determine the modern population structure necessary to restore 

the aspects of life history diversity, distribution of populations, and abundance needed to provide 

for a sustainable Oregon Coast Coho Salmon ESU into the future. Understanding the number, 

abundance, life history diversity, and distributions of historical populations of Oregon Coast 

coho salmon is an important first step in determining biological recovery criteria and recovery 

scenarios. The organization and abundance of populations are dynamic (Hanski and Gilpin 

1997). However, the static picture of historical structure we have reconstructed here provides a 

template for sustainable populations and a sustainable ESU. 

 11
Methods and Results 

In developing the population identification and classification system that reflects the 

persistence, isolation, and independence of populations of Oregon Coast coho salmon, we sought 

an approach that had three desirable characteristics: consistency, reproducibility, and 

transparency. Consistency means that the same approach can be applied across ESUs over a 

broad geographic area and lead to comparable results in different areas. Reproducibility means 

that conclusions are predictable; in other words, another group of scientists could apply the same 

methods to the same information and reach essentially the same result. Transparency means that 

methods are reasonably simple and understandable, so that nonspecialists can understand the 

logical connection between information and conclusions. We chose a rule-based approach that 

we believe meets these criteria. 

Criteria for Identifying the Distribution of Historical Populations 

The task of identifying historical coho salmon populations within the Oregon Coast Coho 

Salmon ESU is challenging because anthropogenic factors such as hatchery operations, stock 

transfers, harvest effects, and habitat destruction and degradation have significantly influenced 

the population structure and interactions we observe today. There are no extant populations 

unaffected by these anthropogenic factors to provide information regarding historical population 

structure and number. Information about historical abundance and distribution of fish is 

available only for a few large basins. We have no alternative, therefore, but to examine a suite of 

characteristics of modern populations and their watersheds in our effort to identify the selective 

and isolating factors that may have lead to demographically independent historical populations. 

The factors we have considered include 1) historical use of habitat; 2) geographical isolation; 

3) biological characteristics of populations; and 4) ecological characteristics of river, stream, and 

lake watersheds. This information was considered across the coastal river, stream, and lake 

basins that may have historically supported coho salmon (Figure 3). 

Documented Historical Use 

The extent of historical use of Oregon Coast coho salmon habitat (Figure 4) is not very 

different from the extent of present use in most basins within the ESU. There are areas, such as 

the Smith River (Figure 5), that have had a major barrier removed. There are also new barriers 

that restrict access to historical habitat. However, large areas of lowland habitat have been cut 

off or restricted from access by dikes, tidegates, and other hydrologic changes. Therefore, the 

extent of Oregon Coast coho salmon use does not show much restriction, but what is not shown 

is the loss of very significant areas that were historically the core of the populations. Because of 

these changes, the core of many Oregon Coast coho populations has subsequently persisted only 

in more marginal, less productive areas (IMST 2002). 

 12
 Figure 3. River and stream basins in the Oregon Coast Coho Salmon ESU. 

 13
 Figure 4. Potential historical coho salmon distribution in the Oregon Coast Coho Salmon ESU. 

 14
Figure 5. Changes from historical distribution of Oregon Coast coho salmon due to the addition ( ́) or 

removal () of passage barriers. 

 15
Geographical Isolation 

Geographical isolation is an important factor in the evolution of separate populations 

within a basin or between basins. The Oregon Coast Coho Salmon ESU, in general, is made up 

of relatively small basins (Figure 3). The exception to that general rule is the Umpqua River 

Basin, which is quite large and drains areas of very different vegetation, geology, and distance 

from the marine influence. Table 1 lists the ocean entry basins discussed in Kostow (1995) with 

their stream lengths and basin areas. We utilized this list as our starting point in defining 

historical coho salmon populations on the Oregon Coast. 

The distance between saltwater entry points of each basin may have a significant effect 

on the degree of migration among populations. Table 2 shows the locations of the basins and the 

distances between each successive basin. Some populations may be significantly affected by 

migrants from larger or more productive systems. Long-term sustainability as a population may 

be affected by the distance from these larger or more productive systems. 

Biological Characteristics 

The first step in the process of identifying historical population patterns in the Oregon 

Coast Coho Salmon ESU was to consider several types of biological evidence. We examined 

life history traits for naturally spawning coho salmon populations, including smolt size and 

outmigration timing, age at spawning, river entry and spawn timing, ocean migration patterns 

based on marine coded-wire-tag (CWT) recoveries, homing fidelity, and genetics. The primary 

objective of this analysis was to discover patterns in these traits that might indicate how 

historical populations were structured. Interpretation of this evidence is complicated by the 

presence of life history variations within and between basins, and by the opportunistic behavior 

of coho to different configurations of habitat. Only recently have we begun to recognize and 

document these life history variations. For example, in the Coos Basin, it has been demonstrated 

by Miller and Sadro (2003) that fry who migrate out of their natal streams and enter the estuary 

and other tidal habitats during their first spring and summer are not necessarily lost from 

production at that time, and may survive to spawn. Because the traits we examined are believed 

to have both genetic and environmental bases, similarities among populations could indicate 

either shared genetic heritage or similar responses to shared environmental conditions. 

Several factors make compiling and comparing life history trait information on a basin 

scale difficult. First, these traits vary greatly over time and space, presumably due in large part 

to the highly variable environment. Fish examined in different years or from different locations 

or habitats within a basin may display different life history characteristics, making it difficult to 

estimate values that characterize historical or basin-wide populations. Because traits also vary 

greatly from year to year, study results may be sensitive to the period over which they were 

conducted. For example, measurements of many life history traits for Oregon coho salmon 

during the 1983 El Niño were very different from those in the years before and after that event 

(Johnson 1988). A second factor that has confounded our analysis is the lack of information on 

life history traits, especially the lack of long-term data sets, from most naturally spawning 

populations. A third complication is that anthropogenic activities such as land-use practices 

(Hartman et al. 1984, Holtby 1987) and artificial propagation (Steward and Bjornn 1990, Flagg 

et al. 1995) may alter life history traits. To help limit this bias, life history trait comparisons in 

 16
Table 1. Ocean entry basin areas with stream lengths (1:100,000 scale data set) (Kostow 1995 and 

Streamnet 2003). 

Basin size 

Basin name 

Approx. 

stream miles 

Approx. 

stream km Acres Hectares 

Necanicum River 93 150 53,320 21,578 

Indian Creek 1 2 262 106 

Canyon Creek 2 4 1,127 456 

Ecola Creek 19 30 13,538 5,479 

Red Rock Creek 1 2 149 60 

Austin Creek 1 2 203 82 

Asbury Creek 4 6 1,574 637 

Arch Cape Creek 3 5 2,317 938 

Short Sands Creek 6 10 2,950 1,194 

Nehalem River 932 1,502 545,738 220,853 

Spring Creek 4 6 1,874 758 

Watseco Creek 2 4 845 342 

Tillamook Basin 622 1,002 358,830 145,214 

Netarts Bay 17 27 9,705 3,927 

Rover Creek 2 3 634 257 

Sand Creek 20 32 10,825 4,381 

Nestucca River 381 613 204,119 82,605 

Neskowin Creek 24 38 12,355 5,000 

Salmon River 104 168 47,742 19,321 

Devils Lake 20 31 7,799 3,156 

Siletz River 548 882 235,531 95,316 

Schoolhouse Creek 2 3 743 301 

Fogarty Creek 8 12 3,324 1,345 

Depoe Bay Creek 8 12 2,985 1,208 

Rocky Creek 8 13 5,047 2,043 

Johnson Creek* (near Siletz) 2 4 712 288 

Spencer Creek 8 13 3,807 1,541 

Wade Creek 4 7 1,709 692 

Coal Creek 4 6 1,527 618 

Moolack Creek 3 6 1,311 530 

Big Creek (near Yaquina) 8 13 3,429 1,388 

Yaquina River 351 566 160,658 65,016 

Henderson Creek 2 3 604 244 

Grant Creek 2 3 366 148 

Moore Creek 2 3 554 224 

Theil Creek 6 10 2,767 1,120 

Beaver Creek 42 68 21,532 8,714 

 17
Table 1 continued. Ocean entry basin areas with stream lengths (1:100,000 scale data set) (Kostow 1995 

and Streamnet 2003). 

Basin size 

Basin name 

Approx. 

stream miles 

Approx. 

stream km Acres Hectares 

Alsea River 530 854 301,778 122,126 

Little Creek 1 2 646 262 

Big Creek (near Alsea) 14 22 5,740 2,323 

Vingie Creek 4 6 1,264 511 

Yachats River 59 94 27,845 11,268 

Gwynn Creek 2 4 800 324 

Cummins Creek 11 17 6,282 2,542 

Bob Creek 6 10 3,669 1,485 

Tenmile Creek 24 38 14,963 6,055 

Squaw Creek 3 4 1,086 439 

Rock Creek 6 10 3,648 1,476 

Big Creek (near Siuslaw) 17 28 10,125 4,097 

China Creek 6 9 2,128 861 

Blowout Creek 2 3 290 118 

Cape Creek 15 24 7,340 2,971 

Berry Creek 6 9 2,442 988 

Sutton Creek (Mercer Lake) 18 29 10,692 4,327 

Siuslaw River 916 1,474 496,047 200,744 

Siltcoos Lake 84 135 48,632 19,681 

Tahkenitch Lake 39 63 23,276 9,420 

Threemile Creek 5 8 2,105 852 

Umpqua River Basin (Total) 4,611 7,424 2,998,976 1,213,647 

Tenmile Lakes 99 159 57,569 23,297 

Coos River 760 1,223 384,393 155,559 

Coquille River 1,222 1,968 676,342 273,707 

Johnson Creek (near 

Coquille) 

6 9 2,656 1,075 

Twomile Creek 24 38 9,704 3,927 

Floras Creek/New River 133 215 81,414 32,947 

Sixes River 130 209 85,832 34,735 

* Not included in future discussions due to falls at ocean, impassable to coho historically. 

 18
Table 2. Locations of ocean entries for basins along the Oregon Coast.* 

Basin name Latitude Longitude 

Distance (km) from 

Columbia River 

Columbia River 46.244 124.057 0.0 

Necanicum River 46.012 123.926 27.7 

Indian Creek 45.930 123.978 37.6 

Canyon Creek 45.930 123.977 37.6 

Ecola Creek 45.899 123.962 41.2 

Red Rock Creek 45.845 123.961 47.3 

Austin Creek 45.819 123.964 50.2 

Asbury Creek 45.815 123.962 50.6 

Arch Cape Creek 45.804 123.966 51.9 

Short Sands Creek 45.760 123.963 56.8 

Nehalem River 45.658 123.933 68.4 

Spring Creek 45.620 123.937 72.6 

Watseco Creek 45.589 123.984 77.6 

Tillamook Bay 45.488 123.901 90.5 

Netarts Bay 45.403 123.944 100.6 

Rover Creek 45.328 123.967 109.1 

Sand Creek 45.290 123.937 113.9 

Nestucca River 45.184 123.956 125.8 

Neskowin Creek 45.100 123.986 135.4 

Salmon River 45.047 124.005 141.5 

Devils Lake 44.968 124.016 150.3 

Siletz River 44.904 124.010 157.4 

Schoolhouse Creek 44.873 124.041 161.6 

Fogarty Creek 44.839 124.053 165.5 

Depoe Bay 44.806 124.058 169.2 

Rocky Creek 44.779 124.071 172.4 

Spencer Creek 44.729 124.059 178.0 

Wade Creek 44.716 124.060 179.5 

Coal Creek 44.708 124.061 180.4 

Moolack Creek 44.703 124.063 180.9 

Big Creek (near Yaquina) 44.659 124.058 185.8 

Yaquina River 44.613 124.017 191.9 

Henderson Creek 44.589 124.068 196.7 

Grant Creek 44.581 124.068 197.6 

Moore Creek 44.572 124.069 198.6 

Theil Creek 44.565 124.070 199.4 

Beaver Creek 44.524 124.075 204.0 

 19
Table 2 continued. Locations of ocean entries for basins along the Oregon Coast.* 

Basin name Latitude Longitude 

Distance (km) from 

Columbia River 

Alsea River 44.423 124.080 215.2 

Little Creek 44.393 124.088 218.6 

Big Creek (near Alsea River) 44.371 124.088 221.0 

Vingie Creek 44.341 124.098 224.5 

Yachats River 44.309 124.107 228.1 

Gwynn Creek 44.271 124.110 232.3 

Cummins Creek 44.266 124.108 232.9 

Bob Creek 44.244 124.110 235.3 

Tenmile Creek 44.226 124.110 237.3 

Squaw Creek 44.208 124.113 239.3 

Rock Creek 44.183 124.114 242.1 

Big Creek (near Suislaw River) 44.177 124.114 242.8 

China Creek 44.169 124.115 243.7 

Blowout Creek 44.157 124.117 245.0 

Cape Creek 44.134 124.123 247.6 

Berry Creek 44.095 124.122 251.9 

Sutton Creek (Mercer Lake) 44.060 124.127 255.9 

Siuslaw River 44.017 124.136 260.7 

Siltcoos Lake 43.874 124.153 276.6 

Tahkenitch Lake 43.815 124.165 283.3 

Threemile Creek 43.748 124.180 290.8 

Umpqua River Basin 43.669 124.204 299.8 

Tenmile Lakes 43.562 124.231 311.9 

Coos River 43.429 124.229 326.6 

Coquille River 43.124 124.429 364.2 

Johnson Creek 43.093 124.431 367.6 

Twomile Creek 43.044 124.441 373.1 

Floras Creek/New River 42.913 124.496 388.3 

Sixes River 42.854 124.543 395.9 

Elk River 42.810 124.533 400.9 

* Columbia and Elk rivers are included to locate the ESU boundary. Tributaries to Tillamook 

Bay are assumed to harbor a single population. 

 20
this document have focused on naturally spawning populations. However, because of the 

practice of releasing hatchery fry and smolts in widespread locations, often outside the basin 

where the parents originated, many studies of naturally spawning populations probably include 

first- or second-generation hatchery fish. Information on life history traits from hatchery 

populations was used only when there was insufficient information available from naturally 

spawning populations, as in the case of ocean migration patterns. As with environmental 

variability, the effects of anthropogenic activities may confuse the determination of average life 

history traits and are difficult to factor out. 

Because of these potential sources of variability, data were collected from as many 

sources as possible to give some indication of average results. We especially sought older data 

sets to indicate coho salmon population traits prior to the 1960s, when technological advances in 

hatchery practices made it possible to raise large numbers of salmon to juvenile or smolt stages. 

The resulting proliferation of hatchery release programs has probably decreased local variability 

among coho populations (Weitkamp et al. 1995, Ford et al. 2004). 

The generalized coho salmon life cycle is summarized in Figure 6. Adult coho salmon 

begin migrating into coastal streams and rivers with the first freshets in the fall. Spawning 

begins in November, peaks in December or January, and may continue into March. Wild 

spawners typically migrate and spawn later than hatchery fish in the same area. Eggs hatch in 

the spring and fry grow rapidly to parr stage by summer or early fall. Parr then seek out areas 

protected from high flows and spend a second winter in freshwater before migrating to the ocean 

as smolts in March through June. About 20% of males mature at age 2 and return to freshwater 

as “jacks” in the same year they entered the ocean as smolts. The remainder of juveniles rear in 

the ocean for 18 months and return as 3-year-old adults in the following fall (Lawson et al. 

2004). Other life history variations do occur, particularly in the timing of life history changes 

between fry and smolts (Miller and Sadro 2003). 

Smolt size and outmigration timing 

Recent data do not suggest any population-based pattern for either smolt outmigration 

timing (Table 3) or smolt size (Table 4) in modern Oregon Coast coho salmon. Regardless of the 

basin of origin, peak outmigration timing generally occurs in May, with some runs earlier or 

later, and with most smolts measuring 90–115 mm (3.5–4.5 inches) fork length. 

Smolt outmigration timing and smolt size appear to respond to small-scale habitat 

variability. Smolts residing in ponds or lakes often have different outmigration timing and are a 

different size than smolts residing in streams within the same basin (Rodgers et al. 1993, Nielsen 

1994). For example, large smolts observed in Tenmile Lakes were thought to have resulted from 

a productive lake-rearing environment (McGie 1970). Both smolt outmigration timing and size 

exhibit considerable interannual variation; mean smolt sizes from a single system can vary 

substantially between years (Table 4), whereas peak outmigration timing can vary by several 

weeks to a month (Table 3). 

Because of their responses to small-scale habitat variability, smolt size and outmigration 

timing have also been shown to be affected by anthropogenic activities, including habitat 

degradation (Moring and Lantz 1975, Holtby 1987) and habitat restoration (Johnson et al. 1993, 

 21
Oct.

July

Apr.

Jan.

Oct.

July

Apr.

Jan.

Oct.

July

Apr.

Jan.

Spawn

Eggs

Fry

Summer

parr

Winter

parr

Smolts

Ocean

juveniles

Adults

Spawning

migration

Jacks

(spawning

migration)

Figure 6. Generalized life cycle of the coho salmon in Oregon (modified from Lawson et al. 2004). 

 22
Table 3. Oregon Coast coho salmon smolt outmigration peak timing and duration (after Weitkamp et al. 

1995). Asterisks (**) indicate no data. 

Basin (tributary) 

Smolt 

outmigration 

duration 

Peak smolt 

outmigration 

Years 

covered Source 

Wilson River 

(Spring Creek) 

Feb–June April 1949–1958 Skeesick 1970 

Tillamook River 

(Sand Creek) 

Mid Mar– 

mid June 

Early May 1946–1949 Sumner 1953 

Nestucca River 

(East Creek) 

** Late April 1988–1991 Johnson et al. 1993, Rodgers et al. 

1993, Weeks 1994 

Nestucca River 

(Moon Creek) 

** Late April–

early May 

1988–1991 Rodgers et al. 1993 

Salmon River ** May 1975–1976 McGie 1977 

Alsea River Mar–May Mar–April 1959–1973 Moring and Lantz 1975 

Alsea River 

(Lobster Creek) 

Feb–June Late Mar– 

early April 

1988–1993 Johnson et al. 1993, Rodgers et al. 

1993, Weeks 1994 

Alsea River 

(Drift Creek) 

Feb–May Chapman 1965 

Alsea River 

(Crooked Creek) 

** May 1973–1979 Weeks 1994 

Tenmile Creek ** May 1992–1993 Johnson et al. 1993, Weeks 1994 

Cummins Creek ** Late April–

early May 

1992–1993 Johnson et al. 1993, Weeks 1994 

Siuslaw River Feb–June Mid-May 1983 Rodgers et al. 1993 

Siuslaw River 

(Triangle Lake) 

** Early May 1973 Weeks 1994 

Tenmile Lakes ** Mid-May 1970–1975 McGie 1970–73, 1975 

Floras Creek/New 

River 

** Mid-May 1973 Weeks 1994 

Coquille River ** Late April–

early May 

1979 Weeks 1994 

Sixes River Mar–June Early–mid 

May 

1969 Reimers 1971 

Nehalem River 

(N. fork) 

** Late April–

early May 

1998–2002 Solazzi et al. 2003 

Tillamook 

(LS fork Kilchis) 

** Late March–

early May 

1998–2002 Solazzi et al. 2003 

Tillamook (LN fork 

Wilson River) 

** Late April– 

late May 

1998–2002 Solazzi et al. 2003 

Siletz River 

(Mill Creek) 

** Late April– 

mid-May 

1998–2002 Solazzi et al. 2003 

Siletz River 

(Bales Creek) 

** Late March–

mid-May 

1998–2002 Solazzi et al. 2003 

Yaquina River 

(Mill Creek) 

** Late April–

early May 

1998–2002 Solazzi et al. 2003 

Yaquina River 

(Cascade Creek) 

** Mid–late April 1998–2002 Solazzi et al. 2003 

 23
Table 3 continued. Oregon Coast coho salmon smolt outmigration peak timing and duration (after 

Weitkamp et al. 1995). Asterisks (**) indicate no data. 

Basin (tributary) 

Smolt 

outmigration 

duration 

Peak smolt 

outmigration 

Years 

covered Source 

Alsea River 

(UM Lobster) 

** Early April–

mid-May 

1998–2002 Solazzi et al. 2003 

Alsea River 

(E. fork Lobster) 

** Early–late 

April 

1998–2002 Solazzi et al. 2003 

Tenmile Creek ** Late April–

early June 

1998–2002 Solazzi et al. 2003 

Smith River (W. fork) ** Mid April–

mid-May 

1998–2002 Solazzi et al. 2003 

Smith River 

(Fall Creek) 

** Early April–

mid-May 

1998–2002 Solazzi et al. 2003 

 24
Table 4. Oregon Coast coho salmon smolt sizes. Note that there is more variation between years than 

between systems (after Weitkamp et al. 1995). Asterisks (**) indicate no data. 

Basin (tributary or 

location) 

Smolt size 

range 

(mm) 

Mean 

smolt size 

(mm) 

Avg. length 

at peak migration (mm)

Years 

covered Source 

Tillamook (Wilson River) ** 100 ** 1949–1958 Skeesick 1970 

Tillamook (Sand Creek) 41–184 105–110 ** 1946–1949 Sumner 1953 

Nestucca River (East 

Creek) 

** 100 ** 1988–1990 Rodgers et al. 1993 

Nestucca River (East 

Creek) 

** 116 ** 1991–1992 Rodgers et al. 1993 

Nestucca River (Moon 

Creek) 

** 97–102 ** 1988–1992 Rodgers et al. 1993 

Yaquina River 88–160 118 ** 1980 Nicholas et al. 1982 

Alsea River (Lobster 

Creek) 

** 86 ** 1988–1991 Rodgers et al. 1993 

Alsea River (Lobster 

Creek) 

** 91 ** 1992–1993 Rodgers et al. 1993, 

Weeks 1994, Johnson 

et al. 1993, Johnson et al. 

1993 

Alsea River (E. fork 

Lobster Creek) 

** 82–83 ** 1988–1992 Rodgers et al. 1993 

Alsea River (Drift Creek) ** 80–90 ** 1959–1962 Chapman 1965 

Alsea River (Deer Creek) ** 97 ** 1960–1973 Knight 1979 

Alsea River (Flynn Creek) ** 95 ** 1960–1973 Knight 1979 

Alsea River (Needle Creek) ** 93 ** 1960–1973 Knight 1979 

Siuslaw River ** 100–107 ** 1983 Rodgers et al. 1987 

Umpqua River ** 100 ** 1991 Roper 1994 

Tenmile Lakes ** 152 ** 1970–1975 McGie 1970–73, 1975 

Sixes River 88–150 120 ** 1969 Reimers 1971 

Nehalem River (N. fork)   101–122 1998–2002 Solazzi et al. 2003 

Tillamook (LS fork Kilchis 

River) 

**  ** 99–118 1998–2002 Solazzi et al. 2003 

Tillamook (LN fork Wilson 

River) 

  102–111 1998–2002 Solazzi et al. 2003 

Siletz River (Mill Creek) **  ** 95–117 1998–2002 Solazzi et al. 2003 

Yaquina River (Bales 

Creek) 

  98–101 1998–2002 Solazzi et al. 2003 

Yaquina River (Mill Creek) **  ** 122–157 1998–2002 Solazzi et al. 2003 

Alsea River (Cascade 

Creek) 

  100–140 1998–2002 Solazzi et al. 2003 

Alsea River (UM Lobster 

Creek) 

**  ** 81–98 1998–2002 Solazzi et al. 2003 

Alsea River (E. fork 

Lobster Creek) 

  77–100 1998–2002 Solazzi et al. 2003 

Cummins Creek **  ** 105–115 1998–2002 Solazzi et al. 2003 

Tenmile Creek   111–121 1998–2002 Solazzi et al. 2003 

Umpqua River (W. fork 

Smith) 

**  ** 102–116 1998–2002 Solazzi et al. 2003 

Coos (Fall Creek) ** ** 100–123 1998–2002 Solazzi et al. 2003 

 25
 26

Rodgers et al. 1993). These factors thoroughly complicate the assessment of any basin-linked 

pattern that may exist for either trait because these activities have occurred throughout the range 

of Oregon Coast coho salmon. Sampling design may also influence reported smolt sizes and 

outmigration timing. It is impossible to discern the historical patterns of smolt size and 

outmigration timing from the modern patterns cited here. We are unable to predict the effects of 

anthropogenic activities on these patterns and from this describe the historical condition. 

Therefore, these characteristics do not appear to be useful in defining historical populations 

within the Oregon Coast Coho Salmon ESU.

Age at spawning 

In the Oregon Coast Coho Salmon ESU, the vast majority of adult fish are 3-year-olds, 

having spent approximately 18 months in freshwater and 18 months in salt water (Gilbert 1912, 

Pritchard 1940, Loeffel and Wendler 1968). Exceptions to this pattern are jacks—sexually 

mature males that return to freshwater to spawn after only 5–7 months in the ocean. A small 

fraction of adults return at age 4, having spent an extra year in freshwater before spawning 

(Moring and Lantz 1975). 

Drucker (1972) suggested that there is a latitudinal cline in the proportion of jacks in 

coho salmon populations, with populations in California having more jacks and those in British 

Columbia having almost none. Although the production of jacks is a heritable trait in coho 

salmon (Iwamoto et al. 1984), it is also strongly influenced by environmental factors (Silverstein 

and Hershberger 1992). The proportion of jacks in a given coho salmon population appears to be 

highly variable through time (Figure 7) (Zhou 2000), likely as a response of the population to 

environmental variation. 

Some systems have also shown long-term changes in the proportion of jacks produced. 

The Tenmile Lakes system (Oregon) historically produced large numbers of jacks (Morgan and 

Henry 1959) but no longer does so (Ursitti 1989), presumably because of altered freshwater 

predation pressures (Reimers et al. 1993). Because of the high level of variability in the relative 

production of jacks in a population and its sensitivity to environmental change, the proportion of 

jacks appeared to be a poor indicator of historical population patterns and was not pursued 

further. 

River entry and spawn timing 

In general, river entry and spawn timing show considerable spatial and temporal 

variability. Most modern Oregon Coast coho salmon enter rivers in October (Mullen 1981a). 

Spawning occurs from November through January and occasionally into February, depending on 

the population (Figures 8a–e). Some coho may spend one or two months in freshwater before 

spawning (Flint and Zillges 1980). 

Coho salmon river entry timing is influenced by many factors; one of the most important 

appears to be river flow (Sumner 1953). Coho salmon wait for freshets before entering rivers, so 

a delay in fall rains delays river entry and spawn timing. Delays in river entry of over a month 

are not unusual (Eames et al. 1981). Several small Oregon Coast coho salmon systems have 

sandbars that block their mouths for most of the year except during winter (such as Devils Lake, 
Proportion of jacks in coho caught in lakes basins 1960-1994

0

0.10.20.30.40.50.60.70.80.9

1960 1965 1970 1975 1980 1985 19

Year

Proportion of jacks

Figure 7. Coho salmon freshwater proportion of jacks caught in Tahkenitch, Siltcoos, and Tenmile lakes basins 1960–1994 

27
North Coast Monitoring Area

0.000.100.200.300.400.50

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 

Week

Proportion of spawners

NNTN

Figure 8a. North Coast Monitoring Area spawn timing for Oregon Coast coho salmon for 2001 (NOAA 2004). To conver

dates: week 1 = Oct. 15–21; week 3 = Oct. 29–Nov. 4; week 7 = Nov. 26–Dec. 2; week 11 = Dec. 24–31; week 16 week 18 = Feb. 12–18. 

28
Mid-Coast Monitoring Area

0.000.100.200.300.400.50

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 

Week

Proportion of spawners

Figure 8b. Mid-Coast Monitoring Area spawn timing for Oregon Coast coho salmon for 2001 (NOAA 2004). To convert 

week 1 = Oct. 15–21; week 3 = Oct. 29–Nov. 4; week 7 = Nov. 26–Dec. 2; week 11 = Dec. 24–31; week 16 = Jan. 18 = Feb. 12–18. 

29
Siuslaw River to Tenmile Lakes 

0.000.100.200.300.400.50

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 

Week

Proportion of spawners

SiSiTaUTe

Figure 8c. Suislaw River to Tenmile Lakes spawn timing for Oregon Coast coho salmon for 2001 (NOAA 2004). To conv

dates: week 1 = Oct. 15–21; week 3 = Oct. 29–Nov. 4; week 7 = Nov. 26–Dec. 2; week 11 = Dec. 24–31; week 16 

week 18 = Feb. 12–18. 

30
Mid-South Coast Monitoring Area

0.000.100.200.300.400.50

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 

Week

Proportion of spawners

Figure 8d. Mid-South Coast Monitoring Area spawn timing for Oregon Coast coho salmon for 2001 (NOAA 2004). To co

dates: week 1 = Oct. 15–21; week 3 = Oct. 29–Nov. 4; week 7 = Nov. 26–Dec. 2; week 11 = Dec. 24–31; week 16 

week 18 = Feb. 12–18. 

31
32

Small Systems

0.000.100.200.300.400.50

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 

Week

Proportion of spawners

Figure 8e. Small systems spawn timing for Oregon Coast coho salmon for 2001 (NOAA 2004). To convert weeks to calen

Oct. 15–21; week 3 = Oct. 29–Nov. 4; week 7 = Nov. 26–Dec. 2; week 11 = Dec. 24–31; week 16 = Jan. 29–Feb. 4

12–18. 
Sixes River, New River). In these systems, coho and other salmon species are unable to enter the 

rivers until sufficiently strong freshets breach the sandbars (Sandercock 1991). 

These factors make determining and comparing average or peak river entry and spawn 

timing difficult because of the high spatial and temporal variability exhibited within basins. 

Compared to normal run times, river entries of some coho salmon populations are exceptionally 

early or late. It was originally thought that this might be helpful in delineating historical 

populations. However, the relationship between populations with unusually timed runs is not 

well understood and exceptional run timing is found in numerous geographical areas. The 

strongest pattern evident from these data is the later run timing in small systems. Historically, 

the range of variation might have given clues to population structure in the basins. However, 

because of the effect of stock transfer and hatchery programs, as well as other anthropogenic 

effects, it is impossible to discern historical patterns from modern observations. Because there is 

no evidence to suggest that all runs of a certain type are closely related, we now consider 

differently timed modern runs to be a component of overall life history diversity within each area 

and not an indication of historical population structure. 

Marine distribution 

Coho salmon smolts from the Oregon Coast enter the ocean in the spring and usually 

encounter a southward-flowing coastal current. Once in the coastal ocean they tend to swim 

north, but depending on the strength of the currents, may initially be displaced to the south 

(Pearcy 1992). As juveniles grow larger, swimming speed increases, resulting in a net northward 

movement. By late summer, juveniles from the coast are distributed off the mouth of the 

Columbia River and the Washington Coast (Pearcy and Fisher 1988, Brodeur et al. 2004). In the 

fall, early maturing males (jacks) return to their natal streams. 

Fall and winter distribution of Oregon coastal coho salmon are less well-known. Hartt 

and Dell (1986) report results of tagging experiments conducted from 1956 to 1968. Juvenile 

salmon in the Gulf of Alaska were tagged at sea and recovered as adults the following year. 

They estimated that up to 37% of the fish they tagged returned to Oregon and California, with 

20% of tags recovered south of the Columbia River. Recent sampling efforts in British 

Columbia and the Gulf of Alaska confirm the presence of juvenile coho salmon from the Oregon 

Coast in northern British Columbia (Welch et al. 2004) and the Gulf of Alaska (Weitkamp 

2004). However, it does not appear that they are as abundant as Hartt and Dell (1986) observed. 

Pearcy (1992) postulates that ocean conditions may have changed, altering migration patterns. 

Alternatively, the shift from predominantly wild to predominantly hatchery fish may have 

affected migration patterns, because the wild fish tend to enter the ocean earlier and migrate 

farther north. 

There is a southward migration during the winter or early spring. Maturing fish first 

appear in ocean salmon fisheries in May off the coast of northern California, as far south as 

Monterey (Weitkamp and Neely 2002). There is a northward migration in late spring and 

summer, with fish arriving in the Coos Bay area in June, and in the ocean off Yaquina Bay and 

Tillamook Bay in July. A few adults are caught as far north as northwest Vancouver Island 

(Canada), but the majority are caught south of the Columbia River. By August adults are starting 

to home to their natal systems, returning to freshwater in September through November. 

 33
 34

Coded-wire tags (CWTs) can provide information on marine distribution of specific 

hatchery populations. They are primarily recovered from marine fisheries or when the salmon 

return to hatcheries. Consequently, CWT recovery patterns only indicate ocean migration 

patterns during the last few months of a 11⁄2-year-long migration. Although patterns of 

movement during earlier stages of ocean migration have been studied (such as Loeffel and 

Forster 1970, Hartt 1980, Miller et al. 1983, Hartt and Dell 1986, Pearcy and Fisher 1988), the 

studies are not broad enough in scope to adequately compare early migration patterns for coho 

salmon released from different areas of the Oregon Coast. 

CWT recoveries show distinctive differences between regions, as is observed between the 

SONCC and the Oregon Coast Coho Salmon ESUs (Weitkamp and Neely 2002). Within the 

Oregon Coast there is a tendency for north coast fish to be caught in more northerly fisheries, 

while south coast fish contribute more heavily to southern fisheries. However, the tendency is 

not strong enough for us to draw conclusions about neighboring populations within regions, such 

as between the Yaquina and the Siuslaw rivers. The CWT recovery data provide information at 

the ESU scale, but are not useful for distinguishing between historical populations. 

Genetics 

Weitkamp et al. (1995) reviewed the genetics studies available at the time and presented 

a new analysis of samples collected by NOAA Fisheries Service. In allozyme studies, coho 

salmon from the Oregon Coast Coho Salmon ESU consistently showed genetic differences from 

other groups, including the Columbia River to the north and the Rogue and Klamath rivers to the 

south (Olin 1984, Solazzi 1986, Hjort and Schreck 1982). One study (Hjort and Schreck 1982) 

also found that hatchery populations from the north coast of Oregon were distinct from the 

natural spawners. Studies of DNA patterns concluded there was a unique stock unit south of the 

Columbia River to Cape Blanco (Currens and Farnsworth 1993, Forbes et al. 1993). 

Samples of DNA from California to Alaska (Johnson et al. 1991, Milner 1993) were 

analyzed for allele frequencies and genetic distances at six gene loci (Weitkamp et al. 1995). 

Cluster analysis identified two overlapping groups on the Oregon Coast: a north-central group 

(with samples from Alsea, Trask, Siletz, and Nehalem basins) and a central to south-central 

group (with samples from the Rogue, Sixes, Eel, Tenmile, New, Coos, Tahkenitch, Alsea, 

Beaver, Siletz, Salmon, Smith, and Coquille basins). The Umpqua River Basin was in a third 

group along with Trinity, Rogue, and Elk basins. The same analysis also grouped Washington 

Coast and Puget Sound coho salmon separately from Columbia River fish. 

Recently, NOAA Fisheries Service (Ford et al. 2004) analyzed seven microsatellite loci 

in DNA extracted from coho salmon scales collected from 12 systems on the south-central and 

central Oregon Coast in 2000 and 2001. Additional fin and muscle samples from nearby systems 

collected between 1991 and 1997 were also used in the analysis. Samples were selected to 

examine variability within and between three groups of fish. On the central coast, samples from 

three large basins and one small basin (Siletz, Yaquina, and Alsea rivers and Beaver Creek) were 

compared in an attempt to see if the small system (Beaver Creek) had a particular affinity to one 

of its larger neighbors (see Figure 9). Within the Umpqua River, samples were compared from 

Calapooya Creek, Elk Creek, Smith River, South Fork Umpqua River, and mainstem 
35

Figure 9. A 

0.01

UmpMS 01

UmpMS 00 Cala 01

Rock 97

Smith 96 Rock 96

UmpSF 01

UmpSF 00

Smith 94

Smith 01

Smith 00

Cala 00

Elk 01

Elk 00 Ten 92

Ten 01

Ten 00

Siltcoos 00

Sutton 02 Mercer 02

Siltcoos 01

Tahk 00

Tahk 01

Siletz 01

Alsea 96 Yaq 01

Alsea 00 Yaq 00

Siletz 00

Alsea 01

Beaver 00

Beaver 01

Devil 01

Devil 02

Marlow 93

Tioga 93

Sixe

Millicoma 97

Umpqua Complex

Lakes Complex

Siletz, Alsea, YaquinaComplexes

Coquille Comple

Genetic distance scale

maximum likelihood tree of Oregon Coast coho salmon genetic samples. Branches not significantly greater th

thin dotted lines. Clusters are outlined by heavy curved line. Analysis by M. Ford based on data from Ford et al. 2
Umpqua River. The objective was to look for population structure within this large river basin. 

The third group of scales was sampled from fish returning to four coastal lakes: Devils Lake, 

Siltcoos Lake, Tahkenitch Lake, and Tenmile Lake. The lake habitats are distinct from the 

rivers, and coho salmon from these lakes are thought to be distinct from the coastal river runs. 

A phylogenetic tree based on these data (Figure 9) showed some obvious geographic 

structure, although the internal branches connecting the geographic groups were relatively short 

compared to the terminal branches (branch length is proportional to genetic differences). The 

samples from the lakes formed a coherent group, as did the samples from the Umpqua River 

Basin. There was some suggestion of structure within each of these groups. The Siletz, 

Yaquina, and Alsea rivers and Beaver Creek also grouped together. There was no population 

structure identified within this group, although the authors stressed that this was not a strong 

conclusion. More generally, there is no strong evidence whether or not there are independent 

populations within these groups. Despite sample size limitations, this study was able to use 

modern genetic techniques to show a finer scale of population structure than had been 

demonstrated in earlier studies. In particular, this study supports Siltcoos, Tahkenitch, and 

Tenmile lakes as at least one independent group. Devils Lake clustered with mid-coast rivers 

rather than the other lakes. The study also supports dividing the modern populations within the 

Umpqua River Basin into more than one population. There was no clear discrimination among 

the mid-coast basins. This may be due to recent hatchery practices and stock transfers blurring 

the boundaries between historical populations. 

Homing fidelity 

The rate of migration between basins is an important component of our population model. 

For an indication of stray rates, we utilized the Uremovich (1977) study, which found that, over 

the 7-year period of 1970–1976, 6.5% of the Chinook salmon (Oncorhynchus tshawytscha) 

carcasses in the Sixes River came from the Elk River hatchery, about 5 km to the north. 

However, he had no data to indicate the proportion of Elk River fish that were straying. 

Shapovalov and Taft (1954) found that an average of about 20% of coho spawners in two 

neighboring streams on the California Coast were migrants from the other stream. These two 

streams, Waddell and Scott creeks, are small systems with ocean entry points about 8.5 km apart. 

They saw a pattern in migration rates that suggested variability between years in response to 

abundance. Such variability certainly occurs on the Oregon Coast, but we have no way at 

present to identify this variability or incorporate it in our isolation models (Labelle 1992). 

We examined freshwater CWT recoveries on the Oregon Coast to test assumptions about 

patterns of migration between basins. For the period of 1990–2003, 52 tagged coho from 17 

Columbia River hatcheries were recovered in freshwater areas of coastal basins. Of the 52 

tagged fish, 32 were recovered in 2001, including 4 fish from 3 Oregon hatcheries and 28 fish 

from 9 Washington hatcheries. Twenty-three of these fish were found in basins from the 

Umpqua River to the Rogue River. Surprisingly, 6 of the 52 fish were Cowlitz River stock, 

which is typically considered a north-migrating stock. These data would suggest that migration 

of Columbia River fish in 2001 was episodic and irregular. Because most of the migrants were 

found in the largest systems on the coast, it may be that fish originating from large systems 

prefer other large systems. 

 36
Migration patterns between hatcheries on the Oregon Coast may be more relevant to the 

historical behavior of natural fish. For the period 1990–2003, there were 71 CWTs from 4 

Oregon coastal hatcheries recovered outside the basin of hatchery origin. This represents 0.5% 

of the CWTs recovered. The actual migration rate is almost certainly higher because CWTs are 

much more likely to be recovered at the hatchery than on the spawning ground or from 

freshwater fisheries. In any case, modeling with a 0.5% vs. 5% rate would have no effect on our 

isolation results. More importantly, the pattern of recoveries showed that most fish were 

recovered from neighboring basins, falling off rapidly with increasing distance. This supports 

the negative exponential migration distribution assumed in our connectivity-viability model 

(Bjorkstedt et al. 2005). 

Summary of biological characteristics 

In conclusion, data for comparison of life history traits of coho salmon populations on the 

Oregon Coast are not usually collected at the broad geographic scale that would be useful for 

distinguishing populations. The data that are available show high variability in run timing, smolt 

outmigration and spawner returns, jacking rate, and homing fidelity that are largely attributable 

to environmental variation or alternative life histories. Genetic data indicate modern population 

differences on the scale of regions and, to a lesser extent, individual basins. Lake populations 

(Tahkenitch, Siltcoos, Tenmile, and Sutton) appear different from river populations, and the 

large Umpqua River Basin shows genetic differentiation within the basin. However, due to the 

significant anthropogenic impacts to the landscape, none of these biological characteristics were 

able to shed light on population structure in historical Oregon Coast coho salmon populations. 

Ecological Characteristics 

Hydrology 

North of Cape Blanco, all coastal Oregon rivers with the exception of the Umpqua River 

drain only the west side of the Oregon Coast Range. The range is relatively low, with peaks at 

500–1,000 m (1,640–3,280 feet) high. Interior portions of the Umpqua River Basin, however, 

drain the east slope of the Coast Range and the west side of the Cascade Range, which has peaks 

from 1,000 to 2,000 m (3,280–6,560 feet) high. 

Stream flows in this region follow a similar pattern, with seasonal highs typically 

experienced in December or January (Figure 10). Mean annual flows are relatively similar for 

the basins draining the west slope of the Coast Range. Where they have been measured, these 

flows have ranged from 0.027 to 0.080 m3

/s per sq. km (Figure 11). Mean annual flows for the 

interior drainages within the Umpqua River Basin have ranged from 0.009 to 0.042 m3/s per sq. 

km. Lowest flows generally occur in summer and fall and are a small percentage of the peak 

flows. Expressed as a percentage of mean flow during the month of greatest runoff, low flows 

during the month of least runoff range between 1.0% and 5.1% (Figure 12). The exception to 

this is the North Umpqua River (3.5% and 42.3%). The difference in this basin is related to the 

strong influence of high Cascades geology and hydrology. Duration of high flows range from 4 

to 6 months in basins proximal to the coast. In the interior drainages of the Umpqua River Basin, 

high flows can persist for as long as 7 months in unregulated systems (Figure 13). 

 37
 Figure 10. Timing of annual peak flows in rivers of the Oregon Coast Coho Salmon ESU. 

 38
 Figure 11. Mean annual flow in rivers of the Oregon Coast Coho Salmon ESU. 

 39
 Figure 12. Seasonality of monthly stream flow in rivers of the Oregon Coast Coho Salmon ESU. 

 40
Figure 13. Duration of high flows in the Oregon Coast Coho Salmon ESU. The number of months of 

duration of peak flow is shown at gauging stations. 

 41
Air and stream temperatures 

There are few clear broad-scale differences in air or stream temperatures from north to 

south within coastal areas occupied by the historical Oregon Coast Coho Salmon ESU. 

Minimum average winter air temperatures are typically around 4oC (39oF), whereas minimum 

average stream temperatures have a range of 4–8oC (39–46oF). Maximum average air 

temperatures are typically around 21oC (70oF) and maximum average stream temperatures at 

selected sites in coastal basins have been observed to range from 15oC to 21oC (59–70oF). 

Higher maximum stream and air temperatures have been observed in the South Umpqua River, 

which is an interior basin. 

Precipitation 

The Oregon Coast receives high rainfall (120–305 cm [47–120 inches] per year) 

compared to areas east of the Coast Range (60–120 cm [24–47 inches] per year). Generally, 

however, it receives less rainfall than the Olympic Peninsula, Washington, farther north (>240 

cm [95 inches] per year). The exceptions to this are in the Nehalem River Basin, the upper areas 

of the five rivers of the Tillamook Basin, and the upper Salmon River and Siletz River basins 

(Figure 14). Much of the Umpqua River Basin receives considerably less rainfall than the areas 

proximal to the coast, with precipitation averages between 102 cm (40 inches) and 152 cm (60 

inches). Because of the relatively low elevation, snowfall in the Coast Range is low, averaging 

30–60 cm (12–24 inches) annually, while the higher Cascade Range receives from 250 cm (98 

inches) to 760 cm (300 inches) annually. This difference in snowfall is important for the 

Umpqua River Basin, as the North and South Umpqua rivers drain a portion of the west slope of 

the Cascade Range (Oregon Climate Service 2000a). 

Vegetation 

Dominant vegetation types are a valuable indicator of relative precipitation, temperature, 

soil type, solar radiation, and altitude because of the specific requirements of different forest 

communities. Consequently, changes of vegetation types can indicate differences in the physical 

environment, which may affect the freshwater habitat of salmon. (A more detailed discussion of 

vegetation has been compiled in Appendix A.) Potential vegetation is similar in most of the 

basins of the Oregon Coast Coho Salmon ESU with the exception of the Siuslaw and Umpqua 

river basins, which extend into the interior away from marine influence (Figure 15). 

Ecoregion 

Ecoregions as shown in Figures 16 and 17 are representations of the integrations of 

vegetation, geology, soils, precipitation, and evaporation potential (ONHP 2001). Level 3 

ecoregions of the Oregon Coast Coho Salmon ESU from south of the Columbia River to Cape 

Blanco show large-scale geologic provinces. Level 4 ecoregions show a finer scale of 

differences, reflecting areas such as coastal lowlands and volcanics, which often indicate 

differing potential for development of good coho salmon habitat. Descriptions of each type of 

level 3 and 4 ecoregion are found in Appendix B. 

 42
 Figure 14. Average annual precipitation in watersheds of the Oregon Coast Coho Salmon ESU.

 43
 Figure 15. Vegetation zones in the watersheds of the Oregon Coast Coho Salmon ESU. 

 44
 Figure 16. Level 3 ecoregions of the Oregon Coast Coho Salmon ESU. 

 45
 Figure 17. Level 4 ecoregions of the Oregon Coast Coho Salmon ESU. 

 46
The ecological information shows a relative uniformity of conditions throughout the 

Oregon Coast Coho Salmon ESU (Weitkamp et al. 1995). This is not surprising, given the 

dominant effect of the ocean on coastal climate. Differences relate to the effects of topography 

on rainfall and of geology on vegetation and slope stability. Inland areas of the Umpqua River 

Basin are drier, with more extreme temperatures than the coastal areas. Ecoregions integrate a 

variety of biotic and abiotic factors to show patterns of habitat variation that may be important to 

coho salmon. 

Summary of potential isolating ecological characteristics 

We reviewed a wide range of factors of potential use in distinguishing among populations 

of coho salmon on the Oregon Coast. Most of the data indicated differences on a broad scale, 

but there were few data sets useful at the finer scale of individual basins. The most recent 

genetic analysis indicated that modern populations are probably structured at a smaller scale than 

broad regions (north coast to south coast). Geographic isolation is potentially useful for defining 

the degree of interactions among populations, and ecoregions may define habitat divisions 

significant to life history adaptations that could potentially become isolating factors in population 

structure. These more enduring ecological characteristics (which include geological history, 

vegetation, and climate) appear to be more informative when considering the historical 

population structure of Oregon Coast coho salmon. We used ecological characteristics 

specifically when considering population structure within the Umpqua River Basin. 

Methods for Population Identification and Classification 

We identified two steps for defining populations and their structure: 1) identifying 

population units, and 2) classifying the units into categories. Identification delineates 

populations and defines where they occur. Classification categorizes those populations into 

groups. Based on our conceptual model, we defined three groups: functionally independent 

populations, potentially independent populations, or dependent populations. Both steps are 

based on simple rules. 

Identification Method 

We used two rules for identifying populations. The first identifies all main basins that 

encompass the range of one or more populations. 

Rule 1: No population will span salt water; in other words, populations are divided at 

saltwater entry such that each direct ocean tributary wholly encompasses the range of any 

populations that spawn within the freshwater basin. For purposes of this rule, estuaries are 

considered part of the freshwater system, so multiple streams entering a single bay may contain a 

single population. 

This rule is based on two postulates regarding salmon populations. First, population 

structure is largely determined by the structure of freshwater spawning and rearing habitats and 

the migration pathways connecting these habitats. Second, saltwater entry/exit is a major break 

point in migration pathways, so migration among habitats within a basin is more likely than 

migration through salt water among basins. Coho salmon spawn and rear in freshwater, which 

 47
allows periods of migration for juveniles before saltwater entry and for adults during spawning 

migrations. 

Applying Rule 1, we initially identified 67 direct ocean entry basins with coho salmon 

habitat within the range of the Oregon Coast Coho Salmon ESU (Table 1). These are basins 

greater than 2 km (≈1 mile) in stream length and at least minimally accessible to coho salmon. 

These basins range in size from Rover Creek (60 ha [148 acres]) to the Umpqua River Basin (1.2 

million ha [3 million acres]). 

The second rule describes when a basin contains more than one persistent population. 

Rule 2: To be considered separate populations, two breeding groups within a basin must 

be sufficiently isolated to be considered functionally or potentially independent. 

Evidence for isolation may include major ecological differences among subbasins, large 

spatial separation of spawning and rearing habitats, or noteworthy life history or genetic 

differences. Under Rule 2, we considered subdividing several of the larger basins into multiple 

populations. These are discussed from north to south below. 

Identification Results 

Nehalem River 

We considered defining two populations within the basin divided just below the 

confluence of the mainstem and Humbug Creek (Figure 18). In favor of this split is the 

geological distinctness of the upper basin, which is largely in the Willapa Hills Ecoregion 

(Figure 17). However, there was no apparent isolating mechanism to limit migrations between 

spawning areas in the upper and lower basins, and the upper basin is ecologically similar to the 

north fork, which would have been included in the lower population. 

Tillamook Basin 

The Tillamook Basin drains several moderate-sized rivers (Figure 19)—Miami, Kilchis, 

Wilson, Trask, and Tillamook—each of which could have supported an independent coho 

salmon population. We considered subdividing the basin into multiple populations. However, 

we ultimately concluded that historically there probably were not separate populations in this 

basin. Considerations leading to this conclusion included 1) habitat is ecologically similar across 

the rivers; 2) most historical production was in lowland areas, where tributaries are close 

together and likely merged during floods (Coulton et al. 1996); and 3) most coho habitat is in the 

Tillamook, Trask, and Wilson rivers, which are all close together. The Miami River is somewhat 

separated geographically from the other main tributaries, but was probably not large enough to 

support a functionally or potentially independent population without input from its neighbors. At 

present, coho habitat is widely dispersed in the upper reaches of the tributaries; however, this 

appears to be largely a result of loss of higher quality lowland habitats rather than the historical 

structure of the population. 

 48
Figure 18. Level 4 ecoregions in the Nehalem River Basin and the surrounding area. 

Figure 19. Level 4 ecoregions of the Tillamook Basin and the surrounding area. 

 49
 50

Nestucca River 

Kostow (1995) identified two tributary populations (Nestucca and Little Nestucca rivers). 

We found no significant ecological differences or isolating mechanisms between the two 

tributaries to justify subdividing the population. 

Siletz River 

Kostow (1995) identified three populations entering Siletz Bay. We found no significant 

ecological differences or isolating mechanisms among the tributaries to justify subdividing the 

population. 

Siuslaw River 

Two populations (Siuslaw and North Fork Siuslaw) were identified by Kostow (1995). 

We considered separating the north fork from the main river, but found no significant ecological 

differences and noted likely historical lowland habitat connections between the two rivers. 

Umpqua River Basin 

This is a large basin (Table 1) draining a diverse region (Figure 20). We considered 

several possible population scenarios with between one and five populations in the basin. The 

single population scenario was eliminated because of the size of the basin, its ecological 

diversity as indicated by multiple level 3 and level 4 ecoregions (Figures 16 and 17), and the 

apparent genetic diversity within the basin (Figure 9) (Ford et al. 2004). The finest-scale 

divisions we considered included independent populations in the North Umpqua River, South 

Umpqua River, mainstem Umpqua River, lower Umpqua Basin (lower mainstem and bay 

tributaries), and Smith River. The Smith River, a large tributary entering the Umpqua River 

below tidewater, was eliminated from consideration as a historically independent population 

because until 1930 most of the habitat in the basin was inaccessible due to an impassable falls 

low in the basin. In addition, the lower reaches of the Smith River are geographically close and 

ecologically similar to other lower basin streams. 

Given these considerations, we initially reduced the likely scenarios to two: 1) three 

populations based on fourth-field Hydrologic Units (HUC) (Smith River and mainstem to the 

forks, north fork, and south fork), and 2) two populations based on dominant level 3 ecoregions 

(Figure 16) within subbasins. The HUC-based approach is appealing for simplicity and 

recognizes that major tributary branches within basins are possible isolating points for migrating 

adults. The ecoregion approach focuses more on potential isolation via local adaptation to 

geology, hydrography, and vegetation differences among regions. The Umpqua River Basin 

spans four level 3 ecoregions: Coast Range, Klamath Mountains, Willamette Valley, and 

Cascades. However, the latter two historically had little coho salmon habitat (Figures 4 and 16). 

The two dominant ecoregions are the Coast Range, which spans the lower tributaries and main 

stem, except for Elk and Calapooya creeks, and the Klamath Mountains, which span upper Elk 

Creek, Calapooya Creek, and the lower portions of the North and South Umpqua rivers. 
51

 Figure 20. Level 4 ecoregions of the Umpqua River Basin and the surrounding area. 
There are large uncertainties inherent in reconstructing historical population patterns, and 

there is no clear support favoring one of these scenarios over the other. Recent genetic analysis 

(Figure 9) (Ford et al. 2004) supports some division within the basin, but patterns of genetic 

variation are ambiguous and we do not know to what extent they reflect recent management 

rather than historical population structure. Pending further evidence, we provisionally identified 

two historical populations based on ecoregion differences within the Umpqua River Basin: 

Lower Umpqua and Upper Umpqua (Figure 16), with the division in the mainstem immediately 

below the confluence of Elk Creek. The Lower Umpqua population occupies the Coast Range 

Ecoregion, while the Upper Umpqua population inhabits primarily the Klamath Mountains 

Ecoregion, with some habitat in the Cascades and Coast Range ecoregions. 

Subsequently, on the advice of ONCC TRT members and in response to several 

comanager comments, we revisited the identification of independent populations in the Umpqua 

River Basin. In order to be consistent with the population identification process in the SONCC, 

we performed a principal components analysis (Appendix D) utilizing the methods in Williams 

et al. (2006). After assessing the results of the analysis, we decided that the configuration that 

made the most sense was one with lower, middle, north, and south Umpqua populations. This 

reflects our observation that the temperatures, rainfall, hydrology, and ecoregions are quite 

different between the North and the South Umpqua rivers. We decided to include a Middle 

Umpqua population due to the presence of the Willamette Valley Ecoregion in the Elk Creek 

system and the significant hydrological differences from the North and South Umpqua river 

populations. The Lower Umpqua is substantially different from all three of the other 

populations, based on its landscape position and its proximity to marine climate influence. More 

recently, Johnson (2006) has shown that the Lower Umpqua is quite different genetically and has 

its affinities with the nearby lake populations. The upper Umpqua populations are less distinct, 

with high migration rates and substantial gene flow mediated by jacks. The Workgroup decided 

that, with the substantial differences in biogeography and hydrology between the North, South, 

and Middle Umpqua basins, in the face of uncertainty it is more conservative in terms of risk to 

define three upper Umpqua populations instead of one. Therefore, the Umpqua River Basin has 

four historical populations defined: lower, middle, north, and south. 

Coos River 

We considered splitting the south fork of the Coos River and Millicoma River (Figure 21) 

as separate populations, following the lead of Kostow (1995). However, this was rejected 

because of lowland habitat connections in the lower basin where much historical production 

likely occurred, similar to the situation in Tillamook Bay and Siuslaw Bay. 

Population Classification 

We classified historical populations into the three population categories: functionally 

independent, potentially independent, and dependent, based on relative persistence and degree of 

isolation. Because no direct measure of persistence was available, we used historical potential 

population size as a proxy. We reconstructed historical population potential from a landscapebased model (Appendix C, Burnett et al. 2003). We then used a connectivity-viability model 

based on the distances between the ocean entry points of basins (Bjorkstedt et al. 2005). These 

models are described in the following subsections. 

 52
 Figure 21. Level 4 ecoregions of the Coos Basin and surrounding area. 

Classification Methods 

Historical population size (persistence) 

We used habitat metrics and recent studies of relationships between habitat and juvenile 

production to estimate historical abundance. Of course, using current habitat metrics to derive an 

index of historical abundance requires measuring habitat features that are relatively stable over 

time. Therefore, we used geomorphic measures of stream conditions that can be calculated from 

current GIS databases (Coastal Landscape Analysis and Modeling Study [CLAMS]) and digital 

elevation models (DEMs), adjusted for known changes in the landscape (such as construction or 

removal of migration barriers) (Burnett et al. 2003). To estimate historical abundance, we 

combined key geomorphic measures (gradient, valley width, and active channel width) from the 

DEMs with habitat intrinsic potential (an integrated measure of habitat quality described in 

Burnett et al. 2003 and illustrated in Figures C-2 through C-5 in Appendix C), smolt capacity 

estimates for different types of habitat, and a smolt-to-adult survival rate based on a good marine 

survival year. We compared these habitat-based estimates with estimates derived from cannery 

records from the turn of the century to confirm that our estimates were reasonable (Lichatowich 

1989). Appendix C presents a detailed description of the methods used to estimate these 

potential historical population sizes. 

The advantage of calculating adult abundance from computed GIS data is that estimates 

can be made for basins where there are no historical fishery data. Table 5 lists the estimated 

potential historical abundance of coho salmon for the 56 populations in the Oregon Coast Coho 

Salmon ESU delineated by the process of identification described above. Total adult abundance 

derived from smolt numbers and a 10% marine survival rate was about 3.3 million adults if all 

populations peaked in the same year. 

 53
Table 5. Potential historical smolt and adult abundance for 56 putative populations of coho salmon in the 

Oregon Coast Coho Salmon ESU (Appendix C, Table C-2). 

Population 

Potential 

smolts 

Adults at 

10% marine 

survival Population 

Potential 

smolts 

Adults at 

10% marine 

survival 

Necanicum 685,000 68,500 Alsea 1,628,000 163,000

Ecola 72,000 7,000 Big (near Alsea) 34,000 3,000

Arch Cape 3,000 300 Vingie 3,000 300

Short Sands 4,000 400 Yachats 110,000 11,000

Nehalem 3,330,000 333,000 Cummins 10,000 1,000

Spring 5,000 500 Bob 6,000 600

Watseco 5,000 500 Tenmile Creek 28,000 3,000

Tillamook Bay 3,288,000 329,000 Rock 6,000 600

Netarts 15,000 1,500 Big 18,000 2,000

Rover 2,000 200 China 5,000 500

Sand 123,000 12,000 Cape 15,000 2,000

Nestucca 1,037,000 104,000 Berry 54,000 5,000

Neskowin 49,000 5,000 Sutton (Mercer Lake) 84,000 8,000

Salmon 168,000 17,000 Siuslaw 2,674,000 267,000

Devils Lake 85,500 9,000 Siltcoos 771,000 77,000

Siletz 1,217,000 122,000 Tahkenitch 228,000 23,000

Schoolhouse 2,000 200 Threemile 22,000 2,000

Fogarty 18,000 2,000 Umpqua (Total) 8,199,000 820,000

Depoe Bay 7,000 700 Lower Umpqua 1,293,000 129,000

Rocky 10,000 1,000 Middle Umpqua 2,420,000 242,000

Spencer 11,000 1,000 North Umpqua 1,180,000 118,000

Wade 5,000 500 South Umpqua 3,310,000 331,000

Coal 4,000 400 Tenmile 525,000 53,000

Moolack 4,000 400 Coos 2,058,000 206,000

Big (near Yaquina) 26,000 3,000 Coquille 4,169,000 417,000

Yaquina 1,217,000 122,000 Johnson 8,000 800

Theil 20,000 2,000 Twomile 134,000 13,000

Beaver 265,000 27,000 Floras/New 396,000 34,000

Sixes 372,000 37,000

 54
0

50000

100000

150000

200000

250000

300000

350000

400000

0 50000 100000 150000 200000 250000

Basin area (hectares)

Historical coho population potential Historical coho population potential 

Tillamook Bay

quina R.

Tillamook Bay

Ya

Siltcoos k. L

Necanicum R.

Tenmile Lk.

Beaver Cr.

ahkenitch Lk.

Beave Yaquina r

Siltcoos 

Necanicum 

Tenmile Lakes

Tahkenitch T

Basin area (hectares) 

Figure 22. Historical coho population potential versus basin area for Oregon Coast basins (data sources: 

Appendix C, Streamnet 2003). 

Our GIS-based modeling of the historical capacity of Oregon Coast basins to produce 

coho salmon shows considerable between-basin variation in the ability to produce these fish. 

Large coastal basins have a greater absolute capacity to produce coho than do smaller basins 

because they contain a greater abundance of suitable habitat (Figure 22). However, the potential 

of Oregon Coast basins to produce coho salmon is influenced by habitat quality as well as 

quantity. Some basins are inherently more productive for these fish than others because they 

have the capacity to form disproportionate quantities of the kinds of complex, low-gradient 

habitats most favored by coho salmon. These basins, including the Tillamook Basin, Yaquina 

River, Beaver Creek, the lake basins (Siltcoos Lake, Tenmile Lakes, Tahkenitch Lake), and 

others once produced more coho salmon than would be expected on the basis of their size alone 

because they contain disproportionately large lowland areas (or lakes) that can provide highly 

productive rearing environments for juvenile coho. 

When compared in terms of their historical capacity to produce coho salmon per unit of 

basin area, larger basins on the Oregon Coast appear to have been generally more productive 

than smaller basins because they were more likely to contain relatively extensive lowland areas 

and complex low-gradient habitats (Figure 23). Though there were exceptions to this pattern, as 

indicated earlier, the lower inherent productivity of the smaller basins tended to make the coho 

salmon populations within them even smaller than expected on the basis of basin size alone. 

This made the coho populations within these smaller basins particularly vulnerable to periodic 

local extinctions unless there was a consistent influx of stray spawners from larger basins. The 

relatively higher vulnerability of these populations is attributable to demographic risks associated 

with small population size, increased sensitivity to fluctuations in marine survival due to lower 

freshwater productivity, and the vulnerability of small natal basins to single catastrophic 

disturbances. 

 55
Isolation (proportion of native spawners) 

One of the defining properties of salmon is their propensity to undergo a long ocean 

migration and return with high fidelity to their natal spawning grounds. This is what isolates 

salmon populations from one another. However, homing is not perfect and the movement of 

migrant salmon between populations is also a defining property of salmon populations. The 

degree of isolation between populations is determined by the proportion of salmon adults that are 

migrants from another population and the effectiveness of these migrant salmon at placing 

competitive offspring into the habitat to which they stray. The proportion of migrants into a 

population also affects the demographic independence of each population. Our rules for 

classifying a population are based on a calculation of historical abundance and on the proportion 

of nonmigrant or native spawning adults based on distances between populations and the relative 

sizes of these populations. 

We used a connectivity-viability model developed by Bjorkstedt et al. (2005) to calculate 

the relative isolation of each population on the Oregon Coast. Quantitative data on coho salmon 

dispersal rates are lacking, so the model is relatively simple, reducing the number of assumptions 

at the risk of reducing the descriptive power of the model. Dispersal of migrants among basins 

separated by salt water is modeled as a function of distance between the mouths of ocean 

tributaries. All basins were treated as single units. Thus the Umpqua River Basin, where four 

populations were delineated, was treated as a single population from the perspective of its 

neighbors. 

In this model, fidelity to native basins (proportion of native spawners) was assumed a 

constant 95% of potential returning adults. We used our estimates of historical abundance as the 

number of returning adults for each population. The remaining 5% of the returning population 

dispersed as migrants along the coast with an exponential decline with distance (Bjorkstedt et al. 

2005). After they were dispersed along the coast, they entered the basin nearest to their final 

location. Distances among watersheds along the Oregon Coast were calculated using the 

latitude-longitude coordinates for the mouths of each river. The distance between each pair of 

neighboring river mouths was calculated “as the crow flies.” Distances between nonneighboring 

rivers were calculated as the sum of all intervening neighbor-pair distances. In this way, the 

curvature of the coast was included in the distance calculations. Tributaries of Tillamook Basin 

were considered as a single watershed. Two out-of-ESU systems, the Columbia River to the 

north and Elk River to the south were included to allow estimation of migrants across the ESU 

boundaries. Elk River historical abundance was estimated from intrinsic potential. Columbia 

River abundance was based on Chapman (1986).

In early drafts of this document, we modeled the influence of the Umpqua River Basin as 

one large system. This system dominated the southern portion of the ESU. However, the 

SONCC Workgroup, in applying the connectivity-viability model, considered that most 

out-of-basin migrants originated from the lower reaches in large systems. For consistency, we 

reanalyzed the Oregon Coast Coho Salmon ESU using only the Lower Umpqua River population 

metrics to represent the contribution of the Umpqua River Basin for the connectivity-viability 

analysis. 

 56
 57

Establishing a horizontal line to distinguish the functionally independent populations was 

straightforward because of the model structure. The native return rate used in the model was 

95%. Thus all populations with greater than 95% proportion native return were net donors, and 

those with fewer than 95% proportion native return were net receivers. The horizontal line at 

0.95 in Figure 24 depicts this division. 

The connectivity-viability model reports the proportion of spawners in each stream that 

originated from that stream (proportion of native return). Streams with a higher proportion of 

native return are more isolated. Figure 24 is an analysis of relative independence based on the 

isolation of each population in the ESU and the historical population size (persistence). It shows 

a continuum from small, dependent populations to large, independent populations. Defining the 

relative roles of populations on this continuum required us to create divisions that were, to some 

extent, artificial and arbitrary. We focused on understanding the axes of isolation and historical 

population size in terms of the analytical techniques used and the population dynamics. We were 

concerned with finding criteria for these break points that were realistic and defensible in terms 

of existing analyses. 

Figure 23. Box-whisker plots of estimated historical coho salmon productivity (adults per hectare of 

basin area per year) for Oregon Coast basins smaller and larger than 5,000 hectares. Boxes depict 

the 25th to 75th percentile productivity values for basins of a given size; whiskers extend to the 

10th and 90th percentile values (data sources: Appendix C, Streamnet 2003). 

0.0

Adult coho per hectare per year

0.5

1.0

1.5

2.0

2.5

3.0

3.5

maller (0-5000 hectare) arger (>5000 hectare)

asin size

S L

B

Adult coho per hectare per year 

Smaller (0–5,000 hectare) 

Estimated Historic Productivity

 n=20 n=45 n = 45 

Classification Results

Basin size

Larger (> 5,000 hectare) 

n = 20 
58

Figure 24. Connectivity-viability analysis for Oregon Coast coho salmon using estimates of potential historical coho salmo

dispersal model in which fidelity is fixed at 95% and dispersers are spread across neighboring watersheds accordindecline with distance (decay parameter = 0.05). This analysis includes the influence of the Columbia and Elk riverline represents the isolation criterion of 95% native spawners. The solid vertical line represents the persistence crit

coho at 10% marine survival. The shaded area represents ± 50% of 15,000. The logit transformation is used to linwhen many of the proportions are near 0 or 1. The horizontal line at 0.95 represents 95% native spawners. The mo

of spawners stray, so points below this line received a net influx of spawners. The location of this line is determine

The relative position of points on the y-axis do not change if this value is varied. 

-8-6-4-2

0246

log10(Historic population potential)

logit(Proportion native return)

log10(15,000)

logit(0.95) 

Functionally Independent PopulationsNehalemTillamookNestuccaSiletzYaquinaAlsea

SiuslawUmpquaCoosCoquille

Dependent PopulationsEcolaSandNeskowinDevils LakeYachatsBerrySuttonTwomileOthers OTHER HABITATS
Establishing a vertical line to distinguish between persistent and nonpersistent 

populations was more difficult. As population abundance or their habitat areas (or capacity) gets 

smaller, the probability of extinction rises. It is, however, harder to quantify that probability than 

it is to characterize the functional relationship between habitat size and extinction probability. 

The stochastic life cycle model (Nickelson and Lawson 1998) can be used to produce 

quantitative extinction probabilities. However, these probabilities are sensitive to many of the 

model parameters, including patterns of freshwater production, density dependence, straying, and 

marine survival. As a consequence, we were unwilling to use the absolute extinction 

probabilities from the model to define the vertical line criterion. We were, however, more 

comfortable with the qualitative model result; as habitat quantity decreases, extinction 

probability increases exponentially. We chose as our criterion for persistence the point where 

the probability of extinction started to increase rapidly (Figure 25). We considered 24 km (≈15 

miles) of habitat as the break point. The resulting habitat quantity would be expected to produce 

15,000 adult spawners at 10% marine survival, so we set the vertical line in Figure 24 at 15,000 

adult spawners on the historical population potential axis. This does not mean that populations 

to the left of this point would necessarily go extinct in 100 years without input from other 

populations. It does mean that the probability of such extinctions is high enough so that on an 

evolutionary time scale of tens to thousands of years, we expect such extinctions to be a normal 

part of the populations’ dynamics and reflected in the genetic population structure. 

0

0.05

0.1

0 10 20 30 40 50 60 70 80 90

0.15

100

Probability of Extinction in 99 Years

Miles of High Quality Habitat

<5 Spawners

<10 Spawners

<20 Spawners

Probability of extinction in 99 years 

< 5 spawners 

< 10 spawners 

< 20 spawners 

Breakpoint Breakpoint

Miles of high-quality habitat 

Figure 25. The relationship between the quantity of high-quality habitat (habitat that will support 

populations of coho salmon when marine survival is 3%) and probability of extinction defined as 

the number of spawners less than 5, 10, or 20 per mile of high quality habitat (from Nickelson 

2001). 

We explored the effect of increasing or decreasing this number by 50% (7,500 or 

22,500), as represented by the vertical shaded area in Figure 24. If our estimate is low only one 

population, the Salmon, would be reclassified as dependent. With a high estimate, five of the 

larger dependent populations (Twomile, Sand, Yachats, Devils Lake, and Sutton [Mercer Lake]) 

59 
would be reclassified as potentially independent. We wanted to portray a zone of likely 

scenarios. 

Fifteen thousand adult spawners sounds, at first, like a high threshold for persistence. 

However, the historical population potential was calculated as a maximum, assuming 10% 

marine survival. In years with 1% marine survival, as we have experienced recently, these 

populations would have been below 1,500 adults. These estimates assume the best possible 

production from these populations, a condition that probably occurred only rarely. The smallest 

populations were probably composed of 10 to 100 spawners during periods of poor ocean 

conditions. 

Using Figure 24, we can assign each population a classification according to our 

conceptual model. All populations to the left of the vertical line had a relatively low probability 

of persistence and were classified as dependent. Their long-term existence depended on input 

from larger neighboring populations. Populations to the right of the vertical line were capable of 

persistence over longer periods. The populations above the horizontal line were considered 

functionally independent, with demographics not greatly influenced by neighboring populations. 

Those persistent populations below the horizontal line were classified potentially independent, 

capable of sustaining themselves without input from neighboring populations, but with 

demographics influenced by their larger neighbors. Populations in the upper-left quadrant would 

be both isolated from other populations and unlikely to persist over a time frame of 100 years. 

These could be considered ephemeral populations. Such populations would experience periodic 

extinctions with low probability of recolonization from other populations. None of our historical 

populations fell into this category. This lends some support to the break points we chose for the 

horizontal and vertical lines. 

In the previous two drafts of this document, we relied on geographical and ecological 

characteristics of the landscape to establish historical population boundaries. Geographical 

information was used in calculating the distance between ocean-entry points. Ecological 

characteristics were utilized in partitioning the Umpqua River Basin into two historical 

populations. A total of 67 historical populations were originally identified through this process. 

As we proceeded with the analyses for recovery criteria, comments from several sources, 

including the SONCC Workgroup, spurred us to take another look at the reasons for including 

some of the smallest populations in the dependent populations list. We determined that 

dependent populations are important to the recovery of the ESU based on their reflection of the 

robustness of nearby independent populations and also for their potential to provide a place 

where new alleles can be “fixed.” New alleles that confer a selective advantage can then be 

transferred into larger populations. This is thought to be an important mechanism for long-term 

ESU viability. The dependent populations in previous drafts of this document are made up of a 

large size range of basins from those with less than a mile of coho salmon habitat to as much as 

18 miles. Some of the very small basins would have abundances that would be at quasiextinction (50 fish) levels under ocean conditions as great as 3% marine survival. This level of 

marine survival is one that is often seen over a 100-year time series. We felt that those very 

small populations would not persist long enough to fix alleles and to provide that function for the 

ESU. Therefore, we chose a threshold of historical production potential of less than 2,000 smolts 

as tabulated in Table 5 for exclusion from the designation of dependent population. These are 

60 
shown in Table 6. This threshold results in 11 fewer populations than were presented initially. 

In addition, a reviewer pointed out that Johnson Creek near the Yaquina River has a waterfall 

into the ocean at its mouth and, therefore, probably never had a coho salmon population. The 

historical populations total 56 with these new configurations. The final list of populations is 

shown in Table 7. 

Thirty-five (about 65%) of the 56 populations we identified were classified as dependent 

populations. Altogether they inhabited less than 6% of the coho salmon habitat in the Oregon 

Coast Salmon ESU. Based on our models, these populations probably would have experienced 

periodic extinction and recolonization events on a time frame of 10 to 1,000 years. There is a 

wide range of basin sizes in this category, ranging from Twomile Creek, supporting up to 13,000 

adults at 10% marine survival, to Schoolhouse Creek and Rover Creek, estimated to produce 

only 200 adults under good marine survival. The larger dependent populations are expected to 

be occupied most of the time, while many of the smaller systems probably do not have spawning 

coho salmon in most years. Some of the smaller systems we have identified may seldom have 

supported coho salmon, while there may be other small systems not on our list where coho 

occasionally spawn. 

Figure 26 is a map of proposed populations and Table 7 is the list of populations and their 

proposed classification. Table 8 allows a comparison between population classification and the 

distance to the nearest functionally independent population. Thirteen of the 56 populations were 

classified as functionally independent, including the four in the Umpqua River Basin. An 

additional eight populations were classified as potentially independent, including the populations 

in the three large lake basins. The Coos River, which had been classified as potentially 

independent in early analyses becomes functionally independent if only the Lower Umpqua is 

utilized in modeling connectivity-viability as exchanging migrants with neighboring basins. 

Using only the Lower Umpqua River population in the model run was an assumption made to be 

consistent with the SONCC Workgroup, which utilized this approach for the Rogue, Klamath, 

and Eel basins. Their reasoning was because of the greater distances to the upper basins on these 

rivers, the most likely source and receivers of strays would be the lower basins in these systems, 

and the similarity of the habitat in the lower basin to the habitat in the other smaller coastal 

basins. This reasoning was therefore also applied to the Umpqua Basin. In addition, Johnson’s 

(2006) analysis has shown a genetic difference between the fish of the upper Umpqua Basin and 

a genetic affinity of the Lower Umpqua with the nearby lakes populations. 

61 
Table 6. Other basins originally included as historical dependent populations (Table 1). 

Basin size

Basin Acres Hectares Potential smolts 

Indian Creek 262 106 100 

Canyon Creek 1,127 456 400 

Red Rock Creek 149 60 100 

Johnson Creek (near Siletz River) Not accessible 

Austin Creek 203 82 300 

Henderson Creek 604 244 1,000 

Grant Creek 366 148 400 

Moore Creek 554 224 1,000 

Little Creek 646 262 1,000 

Gwynn Creek 800 324 1,000 

Squaw Creek 1,086 439 100 

Blowout Creek 290 118 1,000 

62 
Table 7. Proposed historical populations, listed north to south, with classification (Appendix C, 

Bjorkstedt et al. 2005). 

Population Population type Population Population type 

Necanicum Potentially independent Alsea Functionally independent

Ecola Dependent Big (near Alsea) Dependent 

Arch Cape Dependent Vingie Dependent 

Short Sands Dependent Yachats Dependent 

Nehalem Functionally independent Cummins Dependent 

Spring Dependent Bob Dependent 

Watseco Dependent Tenmile Creek Dependent 

Tillamook Bay Functionally independent Rock Dependent 

Netarts Dependent Big Dependent 

Rover Dependent China Dependent 

Sand Dependent Cape Dependent 

Nestucca Functionally independent Berry Dependent 

Neskowin Dependent Sutton (Mercer Lake) Dependent 

Salmon Potentially independent Siuslaw Functionally independent

Devils Lake Dependent Siltcoos Potentially independent 

Siletz Functionally independent Tahkenitch Potentially independent 

Schoolhouse Dependent Threemile Dependent 

Fogarty Dependent Lower Umpqua Functionally independent

Depoe Bay Dependent Middle Umpqua Functionally independent

Rocky Dependent North Umpqua Functionally independent

Spencer Dependent South Umpqua Functionally independent

Wade Dependent Tenmile Potentially independent 

Coal Dependent Coos Functionally independent

Moolack Dependent Coquille Functionally Independent

Big (near Yaquina) Dependent Johnson Dependent 

Yaquina Functionally independent Twomile Dependent 

Theil Dependent Floras/New Potentially independent 

Beaver Potentially independent Sixes Potentially independent 

63 
Figure 26. Proposed historical coho salmon populations in the Oregon Coast Coho Salmon ESU. 

Dependent-population basins are identified in Figure 3. 

64 
Table 8. Locations of ocean entry and distance to the nearest functionally independent (FI) population 

ocean entry point for basins along the Oregon Coast.a

Basin name Latitude Longitude 

Population 

typeb

Distance (km) from 

Columbia River 

Distance (km) to 

nearest FI 

population 

Columbia River 46.244 124.057 N/A 0.0 – 

Necanicum River 46.012 123.926 PI 27.7 40.7 

Ecola Creek 45.899 123.962 D 41.2 27.2 

Red Rock Creek 45.845 123.961 D 47.3 21.1 

Arch Cape Creek 45.804 123.966 D 51.9 16.5 

Short Sands Creek 45.760 123.963 D 56.8 11.6 

Nehalem River 45.658 123.933 FI 68.4 0.0 

Spring Creek 45.620 123.937 D 72.6 4.2 

Watseco Creek 45.589 123.984 D 77.6 9.2 

Tillamook Basin 45.488 123.901 FI 90.5 0.0 

Netarts Bay 45.403 123.944 D 100.6 9.9 

Rover Creek 45.328 123.967 D 109.1 18.6 

Sand Creek 45.290 123.937 D 113.9 23.4 

Nestucca River 45.184 123.956 FI 125.8 0.0 

Neskowin Creek 45.100 123.986 D 135.4 9.6 

Salmon River 45.047 124.005 PI 141.5 15.7 

Devils Lake 44.968 124.016 D 150.3 7.1 

Siletz River 44.904 124.010 FI 157.4 0.0 

Schoolhouse Creek 44.873 124.041 D 161.6 4.2 

Fogarty Creek 44.839 124.053 D 165.5 8.1 

Depoe Bay Creek 44.806 124.058 D 169.2 11.8 

Rocky Creek 44.779 124.071 D 172.4 15.0 

Spencer Creek 44.729 124.059 D 178.0 13.9 

Wade Creek 44.716 124.060 D 179.5 12.4 

Coal Creek 44.708 124.061 D 180.4 11.5 

Moolack Creek 44.703 124.063 D 180.9 11.0 

Big Creek (near 

Yaquina) 

44.659 124.058 D 185.8 6.1 

Yaquina River 44.613 124.017 FI 191.9 0.0 

Theil Creek 44.565 124.070 D 199.4 7.5 

Beaver Creek 44.524 124.075 PI 204.0 11.0 

Alsea River 44.423 124.080 FI 215.2 0.0 

Big Creek (near 

Alsea River) 

44.371 124.088 D 221.0 5.8 

65 
Table 8 continued. Locations of ocean entry and distance to the nearest functionally independent (FI) 

population ocean entry point for basins along the Oregon Coast.a

Basin name Latitude Longitude 

Population 

typeb

Distance (km) from 

Columbia River 

Distance (km) to 

nearest FI 

population 

Vingie Creek 44.341 124.098 D 224.5 9.3 

Yachats River 44.309 124.107 D 228.1 12.9 

Cummins Creek 44.266 124.108 D 232.9 17.7 

Bob Creek 44.244 124.110 D 235.3 20.1 

Tenmile Creek 44.226 124.110 D 237.3 22.1 

Rock Creek 44.183 124.114 D 242.1 18.6 

Big Creek (near 

Suislaw) 

44.177 124.114 D 242.8 17.9 

China Creek 44.169 124.115 D 243.7 17.0 

Cape Creek 44.134 124.123 D 247.6 13.1 

Berry Creek 44.095 124.122 D 251.9 8.8 

Sutton Lake 44.060 124.127 D 255.9 4.8 

Siuslaw River 44.017 124.136 FI 260.7 0.0 

Siltcoos Lake 43.874 124.153 PI 276.6 15.9 

Tahkenitch Lake 43.815 124.165 PI 283.3 16.5 

Threemile Creek 43.748 124.180 D 290.8 9.0 

Umpqua River 43.669 124.204 FI 299.8 0.0 

Tenmile Lakes 43.562 124.231 PI 311.9 12.1 

Coos River 43.429 124.229 FI 326.6 37.6 

Coquille River 43.124 124.429 FI 364.2 0.0 

Johnson Creek 43.093 124.431 D 367.6 3.4 

Twomile Creek 43.044 124.441 D 373.1 8.9 

Floras Creek/New 

River 

42.913 124.496 PI 388.3 24.1 

Sixes River 42.854 124.543 PI 395.9 31.7 

Elk River 42.810 124.533 N/A 400.9 – 

a

 Columbia and Elk rivers are included to locate the ESU boundary. Tributaries to Tillamook Bay are assumed to 

harbor a single population. 

b

 D = dependent; FI = functionally independent; PI = potentially independent. 

66 
Discussion 

Our view of the historical population structure of Oregon Coast coho salmon relies upon 

a simple conceptual model of the spatially dependent demographics of the 56 populations we 

consider likely to have been present 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 interaction of these 

two factors across what we believe to have been the historical populations of Oregon Coast coho 

salmon gives us a measure of relative independence. 

Our model of the interplay between the persistence and isolation of historical coho 

populations within the Oregon Coast ESU provided us a clear method for classifying the relative 

independence of individual populations. We classified historical populations into three distinct 

groups: functionally independent, potentially independent, and dependent. In general, Oregon 

Coast drainage basins of intermediate to large size (whose coho salmon populations fell to the 

right of a persistence threshold in Figure 24) are thought to have each supported a coho 

population capable of persisting indefinitely in isolation, though some of them (seen below a 

horizontal line representing an isolation threshold in Figure 24) may have been demographically 

influenced by adult coho straying into spawning areas from elsewhere in the ESU. Those 

persistent populations with minimal demographic influence from adjacent populations were 

classified as functionally independent (13 populations), while populations that appeared likely to 

have been capable of persisting in isolation but were demographically influenced by adjacent 

populations were classified as potentially independent (8 populations). Small coho salmon 

populations would have been found in smaller coastal basins (seen falling both to the left of the 

persistence line and below the isolation line in Figure 24) and may not have been able to 

maintain themselves continuously for periods as long as hundreds of years without the 

demographic boost provided by migrating spawners from other populations. For this reason, 

these populations were classified as dependent. 

We believe that the dependent populations relied at times upon 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 broad-scale 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 

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. 

67 
Uncertainties 

Despite the simplicity of the conceptual model we used to classify the connectivityviability of historical coho salmon populations within the Oregon Coast Coho Salmon ESU, it 

should be emphasized that analytical components of our model are no different from those of 

other mathematical models of populations or habitat. Our model produces results that we 

consider a reasonable but uncertain approximation of an imperfectly understood biological 

phenomenon: the interactions of historical Oregon Coast coho salmon populations. 

We are confident in the way our modeling has arrayed 56 historical populations of 

Oregon Coast coho salmon on the basis of their potential abundance. The abundance levels 

assigned to the populations reflect what is known about how the species uses its habitat and are 

consistent with patterns evident in both recent and historical data on coho abundance. However, 

the specific coho population size we used to define our persistence (threshold) line in Figure 24 

was based on results from a simple habitat-based model of coastal coho populations developed 

by Nickelson and Lawson (1998). That model fits data on the recent performance of Oregon 

Coast coho salmon populations, but habitat available to these populations has been substantially 

altered from that which supported historical populations, and is of lower quality (IMST 2002). 

Historical habitats may have been somewhat more stable and productive than those we can study 

today, raising the possibility that historical coho populations may have been able to persist on 

smaller quantities of relatively higher quality habitat than recent data on coho salmon abundance 

and population performance might suggest. There are also inherent between-basin differences in 

the stability or aggregate productivity of coho salmon habitat that could affect the persistence of 

some smaller populations but that were only weakly accounted for when we used absolute coho 

abundance as a proxy for population persistence. Taking these things into account, we assessed 

the sensitivity of our population classifications to a 50% reduction in the coho salmon population 

size used as a persistence threshold and found that only 5 of 35 coho populations otherwise 

classified as dependent (Twomile, Sand, Devils Lake, Sutton [Mercer Lake], and Yachats) would 

be reclassified as potentially independent. Similarly, a 50% increase in the persistence threshold 

would have resulted in only one potentially independent population (Salmon) being reclassified 

as dependent. Most of our classifications of populations would thus be unaffected by what we 

might consider as reasonable changes to our persistence threshold. 

Another area of uncertainty within our classification model is the dispersal pattern used 

to simulate migration between coho salmon populations, and thus to distinguish between 

functionally independent and potentially independent populations in the historical ESU. The 

pattern that we used assumes an exponential decline in migration rate with increasing distance 

from the natal basin and does not account for a variety of environmental gradients that may (or 

may not) affect the relative attractiveness of nonnatal basins to straying coho salmon. A more 

complex pattern might be more realistic, but we are not aware of any data or studies that would 

provide us a sufficient basis for structuring such a pattern. This simplification creates 

uncertainty about the degree to which the results of our model reflect the true isolation of 

individual coho populations. Sensitivity analyses by Bjorkstedt et al. (2005) have shown that 

changes in the assumed dispersal pattern of migrant coho salmon tend to have only minor effects 

on the apparent isolation of the larger coho populations within the historical Oregon Coast Coho 

68 
Salmon ESU, but variable effects on the apparent isolation of intermediate-sized to smaller 

populations. This is a topic worthy of further investigation. 

Other Applications of the Connectivity-Viability Model 

Our model-based approach to classifying the connectivity-viability (relative 

independence) of coho salmon populations within the Oregon Coast Coho Salmon ESU may be 

of interest to other NOAA Fisheries Service TRTs because it provides a structured way to 

delineate independent salmon populations within geographically linked coastal areas. At 

present, the general model is being used to help identify historically independent coho salmon 

populations within two additional ESUs, both along the California coast (Bjorkstedt et al. 2005, 

Williams et al. 2006). The model may also prove useful in examining recent changes in the 

interactive demographic behavior of geographically linked salmon populations and establishing a 

conceptual framework for the development of ESU recovery goals. 

In addition to identifying and classifying historical populations of the Oregon Coast Coho 

Salmon ESU, we have examined the ESU for evidence of genetic and geographic structure. 

These patterns will be used in developing biological recovery criteria that conserve diversity and 

avoid loss of critical diversity components of the ESU through catastrophe. 

69 
Definition of Biogeographic Strata in the Oregon 

Coast Coho Salmon ESU 

Within the Oregon Coast Coho Salmon ESU, there is substantial genetic and geographic 

structure, with genetic similarities clustering into a few geographic units. For our analyses, we 

have designated these clusters as “biogeographic strata” or “strata.” These biogeographic strata 

represent both genetic and geographic similarities, and we 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. Each of these 

strata must be secure for the entire ESU to be sustainable. Development of the information 

needed for the Workgroup to develop the concept of biogeographic strata has occurred over the 

last two decades. There have been substantial advances, particularly in genetic analysis. 

Utilizing allozyme loci, Olin (1984) identified three major genetic groupings within what 

was subsequently described as the ESU. These groupings are 1) the Nehalem River south to the 

Coos River (just north of Cape Arago), 2) the Nehalem River south to the Alsea River, and 3) the 

Siuslaw River south to Morton Creek (just north of Cape Blanco). Geographic coverage of 

groups 1 and 2 overlapped and also were the most genetically similar (see Figure 27). 

Subsequently, Kostow (1995) defined 82 coho salmon populations within the ESU based 

on geographic similarity, adjacency, and unpublished genetics data.5

 Kostow described three 

gene conservation groups (GCG) (see Figure 28) that are also based on geographic proximity as 

well as the somewhat poorly defined genetic structure. At the time of the Kostow work, 

allozyme analyses in coho salmon was not very revealing of finer scale genetic structure. 

After Kostow (1995), ODFW scientists, in the process of defining the Environmental 

Monitoring and Assessment Program (EMAP) (Stevens and Olsen 2002) sampling stratification 

for the Oregon Coast Coho Salmon ESU, decided that the North/Midcoast GCG was very large 

and included areas that were geographically and ecologically different from north to south. They 

therefore defined north coast and mid-coast monitoring areas in order to be able to have higher 

resolution due to increased sampling in the North/Mid Coast GCG (see Figure 29). The 

monitoring areas were defined as following the former ODFW “Fish Districts” with four areas 

defined. These are north coast, mid-coast, Umpqua River, and mid-south coast monitoring 

areas.6

In the Workgroup deliberations on historical Oregon Coast coho salmon populations, we 

examined information on ecoregions, hydrology, precipitation, and other ecological and physical 

differences in the basins that drain directly to the ocean or to Tillamook Bay. In addition, we had 

a newly completed genetic study (Ford et al. 2004) that showed four genetic clusters within the 

ESU (Figure 9). The most northerly basins of the ESU were not sampled by Ford due to 

 

5

 D. Teel, NWFSC, Manchester Laboratory, Port Orchard, WA. Pers. commun., 8 July 2005. 6

 T. Nickelson, ODFW, Corvallis Research Laboratory, Corvallis, OR. Pers. commun., 7 July 2005. 

70 
resource limitations. Three of these clusters correspond well to the mid-coast (Siletz, Alsea, and 

Yaquina complexes), mid-south coast (Coquille and Coos complexes), and the Umpqua River 

(Umpqua complex) monitoring areas. What stands out as different from the ODFW monitoring 

areas is the Lakes Complex, which was originally included in the ODFW mid-south coast 

monitoring area. 

In defining our biogeographical strata, we considered that the four ODFW monitoring 

areas 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 and geographically, as well as genetically. In order to reflect this 

diversity and to reduce the risks to genetic and geographical diversity due to catastrophes, we 

partitioned the Ford et al. (2004) Lakes Complex into a fifth biogeographical stratum for use in 

defining areas of diversity important in conservation (Figure 30). 

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

geographic variation, we consider that preserving all of them will accomplish two goals: 

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

catastrophes. These diversity strata and independent populations are very important to our 

analysis of persistence and sustainability found in the document describing biological recovery 

criteria (Wainwright et al. 2006). 

71 
Figure 27. Allozyme clusters discerned in Olin’s 1984 report on genetic variability in coho salmon of 

the Oregon Coast. 

72 
Figure 28. Gene conservation groups for Oregon Coast coho salmon as defined in Kostow (1995). 

73 
Figure 29. Oregon Coast coho salmon monitoring areas defined by ODFW in 2003. 

74 
Figure 30. Biogeographic strata defined within the Oregon Coast Coho Salmon ESU. These strata 

reflect both biological clustering of genetic traits and geographical similarities. 

75 
76 
Glossary 

Abundance. The number of fish in a population.

Active channel width. The distance across a stream or channel as measured from bank to bank 

at bankful flow.

Allelle. Any one of a number of alternative forms of a gene that can occur at the same location 

(locus) on a chromosome. A population can have many alleles for a particular locus, but an 

individual can carry no more than two alleles at a diploid locus.

Allozymes. Alternative forms of an enzyme that have the same function, are produced by 

different alleles, and are often detected by protein electrophoresis.

Anthropogenic factor. A circumstance or influence caused or produced by human action.

Artificial propagation. Hatchery spawning and rearing of salmon, usually to the smolt stage.

AUC (Area Under the Curve). A statistical technique for estimating an annual total number of 

spawners from periodic spawner counts.

Barrier. A blockage such as a waterfall, culvert, or rapid that impedes the movement of fish in a 

stream system.

Biological Review Team (BRT). The team of scientists who evaluate scientific information for 

the National Marine Fisheries Service (NMFS) status reviews. 

Carrying capacity. The number of individuals that the resources of a habitat can support.

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. 

CIMRS (Cooperative Institute for Marine Resources Studies). A cooperative project 

between Oregon State University and NOAA Fisheries Service. 

CLAMS (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. 

Coded-wire tag (CWT). A small piece (0.25 × 0.5 or 1.0 mm) of stainless steel wire that is 

injected into the snouts of juvenile salmon and steelhead. Each tag is etched with a binary 

code that identifies its release group. 

77 
Comanagers. Federal, state, and tribal agencies that cooperatively manage salmon in the Pacific 

Northwest. 

Delisting. Taking a species off of the endangered species list. 

Demographic stochasticity. “Chance events in the survival and reproductive success of a finite 

number of individuals” (Shaffer 1981). 

DEM (Digital Elevation Model). A digital data set representing a topographic map that can be 

used for computer analysis. We used DEMs to calculate the intrinsic potential of stream 

systems. 

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 upon 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” (the positive relationship between population density and 

the reproduction and survival of individuals) with reduced likelihood of finding a mate. 

Diploid. Having two complete chromosome pairs in a nucleus. 

Distinct population segment (DPS). 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.

DNA (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 allele and electrophoresis).

Donor populations. These are functionally independent or potentially independent populations

that are large enough to “donate” migrant adults to dependent populations. 

Ecoregion. An integration of physical and biological factors such as geologic history, climate, 

and vegetation. 

Effective migration rate. The proportion of successfully spawning adults that migrate to a new 

population. (Excludes migrants that do not successfully reproduce.) See also Migration 

rate. 

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.

78 
Endangered species. A species in danger of extinction throughout all or a significant portion of 

its range.

ESA. U.S. Endangered Species Act.

Escapement. Usually refers to adult fish that “escape” from both 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.

Evaporation potential. The maximum depth of water that could evaporate in a year. 

Evaporation potential is principally determined by temperature and relative humidity. It is a 

measure of how much moisture “stress” plants are under due to dry conditions.

Evolutionarily Significant Unit (ESU). 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 Distinct population segment.

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.

Fourth-field and fifth-field hydrologic units. In the United States Geological Survey (USGS), 

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 an egg sack.

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). 

Genetic distance. A quantitative measure of the genetic difference between a pair of samples, 

based on allele frequencies at multiple loci.

79 
Genetic drift. Random changes in gene frequencies of populations.

Gradient. The slope of a stream system. 

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 that were produced before the influence of European 

settlement.

Homing fidelity. The propensity of an adult salmon to return to its natal stream.

Hydrology. The distribution and flow of water in an aquatic system. 

Independent Multidisciplinary Science Team (IMST). A scientific advisory body to the 

Oregon legislature and governor on watershed, forestry, agriculture, and fisheries science 

issues.

Inbreeding depression. Reduced survival rates of individuals in a population suffering from the 

effects of harmful recessive genes through matings between close relatives. Inbreeding 

depression may become a problem when populations get very small.

Independence. Reflects the interaction between isolation and persistence. A persistent 

population that is highly isolated is highly independent.

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 (Burnett et al. 2003).

Isolating mechanisms. Things that reduce the ability of populations to interbreed. These could 

include physical mechanisms such as distance and behavioral mechanisms such as run 

timing.

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.

Jacking rate. The proportion of adult coho salmon from a brood that return as jacks.

Juvenile. A fish that has not matured sexually. 

Latitudinal cline (also known as a latitudinal diversity gradient.) A change in a biological 

trait that occurs across latitudes. For example, jacking rate generally increases from north to 

south.

80 
Life history. The specific life cycle of a fish from egg to adult.

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 NOAA Fisheries Service.

Littoral zone. In lakes, the area of lake bottom that receives enough light for rooted plants to 

grow. In the ocean, the marine ecological realm that experiences the effects of tidal and 

longshore currents and breaking waves to a depth of 5 to 10 m (16 to 33 feet) below the lowtide level, depending on the intensity of storm waves. (Encyclopædia Britannica 2004).

Locus. Location on a chromosome that holds a specific gene. Plural is loci.

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. 

Marine survival rate. The proportion of smolts entering the ocean that return as adults. 

Mean annual discharge of water. A single value or average that summarizes or represents the 

annual discharge amount, typically expressed in cubic meters per second. 

Metric. A unit of measure.

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 Effective migration rate. 

Mitochondrial DNA (mtDNA). The DNA genome contained within mitochondria and encoding 

a small subset of mitochondrial functions. Only female mtDNA is transmitted to the next 

generation.

NMFS. National Marine Fisheries Service, also known as NOAA Fisheries Service. 

NOAA. National Oceanic and Atmospheric Administration. 

NOAA Fisheries Service. NOAA’s National Marine Fisheries Service, also known as NMFS.

81 
Nuclear DNA (nDNA). The DNA contained in the chromosomes within the nucleus of 

eukaryotic cells. The nuclear genome in Pacific salmon is approximately 4.6 billion base 

pairs in size.

ODFW. Oregon Department of Fish and Wildlife.

ONCC TRT. Oregon and Northern California Coast Technical Recovery Team.

OWEB. Oregon Watershed Enhancement Board. 

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.

Persistence in isolation. A population’s relative ability to sustain itself without input from 

neighboring populations.

Phylogenetic tree. The genetic distances and relationships among populations, frequently 

represented with a branching or tree-like diagram. 

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. 

Population classification. The grouping of populations into functionally independent, 

potentially independent, and dependent classes.

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 populations. High-persistence populations 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.

Productive capacity. Maximum possible production from a given area.

Productivity. The rate at which a population is able to produce fish. 

Protein electrophoresis. An analytical laboratory technique that measures differences in the 

amino acid composition of proteins from different individuals. See also Electrophoresis. 

82 
Recovery. The reestablishment of a threatened or endangered species to a self-sustaining level 

in its natural ecosystem (in other words, to the point where the protective measures of the 

ESA are no longer necessary). 

Recovery domain. The area and species that the TRT is responsible for. 

Recovery plan. A document identifying actions needed to make populations of naturally 

produced fish comprising the Oregon Coast Coho Salmon 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 will also include 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 scenarios. Various sequences 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. 

Salmonids. Any of the species included in salmon, trout, and char. 

Sclerophyllous. Describing trees and shrubs that have hard leaves or needles, and a short 

distance between leaves on the stem. This applies to tan oak, madrone, and chinquapin in 

mixed evergreen forest zones found in the interior Umpqua River Basin. 

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. 

Spawners. Adult fish on the spawning grounds. 

Species. Biological definition: A small 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. 

Stock transfer. The practice of moving fish between basins or populations. 

Stray rate. As used in this document, the 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. 

83 
Threatened species. A species not presently in danger of extinction but likely to become so in 

the foreseeable future. 

TRT. Technical Recovery Team. 

USFS. United States Forest Service. 

USGS. United States Geologic Survey. 

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. 

Warm-water fish. Spiny-rayed fish such as sculpins, minnows, darters, bass, walleye, crappie, 

and bluegill that generally tolerate or thrive in warm water. 

84 
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96 
Appendix A: Vegetation 

Because of the specific requirements of different plant communities, dominant vegetation 

types are a valuable indicator of relative precipitation, temperature, soil type, solar radiation, and 

altitude. Therefore, changes of vegetation types can indicate changes in the physical 

environment, which may affect freshwater salmon habitat. The following discussion of 

vegetation was compiled from studies by Franklin and Dyrness (1973), Barbour and Major 

(1977), and Hickman (1993). 

Sitka Spruce Zone—Coastal regions in Oregon are forested with a Sitka spruce-dominated plant 

community: Sitka spruce (Picea sitchensis), western hemlock (Tsuga heterophylla), western red 

cedar (Thuja plicata), red alder (Alnus rubra), and Douglas fir (Pseudotsuga menziesii) are major 

species that occur there. This vegetation type is restricted to coastal regions and river valleys 

and only on the coastal plains does it extend farther than a few kilometers inland. The Sitka 

Spruce Zone reaches elevations above 150 m (490 feet) only in areas immediately adjacent to the 

ocean. However, where mountains are adjacent to the coast, the zone may extend to 600 m 

(1,970 feet). This vegetation type only occupies areas with a uniformly wet and mild climate. 

Sitka spruce forests could be considered a variant of western hemlock forests of higher 

elevations and inland areas, but they are distinguished by frequent summer fogs and proximity to 

the ocean (Franklin and Dyrness 1973). 

Western Hemlock Zone—Along the Oregon Coast, the western hemlock-dominated plant 

community replaces Sitka spruce at elevations above 150 m (490 feet). This zone includes 

western hemlock, Douglas fir, red alder, and western red cedar as major tree species. South of 

the Columbia River, the Western Hemlock Zone extends southward along the Coast Range to the 

Klamath Mountains and southward along the Cascade Mountains to the Umpqua River. 

Alpine and Subalpine zones—The headwaters of rivers draining higher mountains, such as the 

Cascade Mountains and Oregon Coast ranges, begin in alpine meadows and subalpine parklands, 

before they change to western hemlock-dominated forests below 700–1,000 m (2,300–3,280 

feet). The higher alpine regions appear as a mosaic of meadows and tree patches with longlasting and deep snow cover. The Subalpine Zone is dominated by mountain hemlock (Tsuga 

mertensiana) and subalpine fir (Abies lasiocarpa var. lasiocarpa) and is wetter and colder than 

areas at lower elevations, but has less extended snow cover than the higher alpine areas. With 

the exception of some of the higher peaks in the Coast Range, the majority of this zone is found 

in the drainage of the North Umpqua River. 

Umpqua Valley—The interior Umpqua River Valley area is a complex of many different 

vegetation types. These include coniferous tree associations including Douglas fir, Ponderosa 

pine (Pinus ponderosa) and incense-cedar (Calocedrus decurrens), oak forest stands, woodlands 

and savannas with Oregon oak (Quercus garryana), California black oak (Quercus kelloggii) and 

madrone (Arbutus menziesii), grasslands with Kentucky bluegrass (Poa pratensis), orchard grass 

(Dactylis glomerata), and Idaho bent (Agrostis Idahoensis), sclerophyllus hillside communities 

97 
dominated by Douglas fir, tan oak (Lithocarpus densiflora), canyon live oak (Quercus 

chrysolepis), madrone, chinquapin (Chrysolepis chrysophylla), and riparian communities with 

black cottonwood (Populus balsamifera ssp. trichocarpa), many willow species (Salix rigida, S.

lasiandra, S. fluviatilis, and S. sessilifolia), Oregon oak, and California laurel (Umbellularia 

california). 

Mixed Conifer and Evergreen Forest zones—The Klamath Mountain Province (ONHP 2003) 

extends into the Umpqua River Basin in the region of the south Umpqua River and mainstem 

Umpqua River. This section of the province is the northern Siskiyou Mountains. In the western 

Siskiyou Mountains, the dominant vegetation is a mixed forest of evergreen-needle-leaved trees 

and broad-leaved evergreen sclerophyllous trees. Dominants in these mixed evergreen forests 

are Douglas fir, tan oak, madrone, and chinquapin. These species are more allied with forests 

found to the south than those in the more mesic coastal areas. 

98 
Appendix B: Ecoregions of the Oregon Coast 

Coho Salmon ESU from South of the Columbia 

River to Cape Blanco 

Level 3 ecoregions are shown in Figure 16; level 4 ecoregions are shown in Figure 17. 

These descriptions are compiled from OWEB (1999) and ONHP (2003). 

Level 3 Ecoregion Descriptions 

Klamath Mountain Ecoregion—The Klamath Mountain Ecoregion within the Oregon Coast 

Coho Salmon ESU is found in the interior Umpqua River Basin, encompassing systems such as 

Cow Creek, south Umpqua River, and a portion of the north Umpqua River. This area is the 

most northerly of a system of mountains that extend into northwestern California (the Siskiyou 

Mountains). These are the oldest landscapes in Oregon, due to their origin as ocean crust or 

island archipelago environments that were carried eastward on a tectonic plate that collided with 

the continent of North America. These terranes (exotic pieces of landscapes) were then welded 

to the continent by granitic intrusives (Orr and Orr 2000). This area is a very diverse geological 

landscape, which includes serpentine, limestone, and gabbro, as well as granite and basalt. The 

Umpqua portion of the Klamath Mountains Ecoregion is less rugged than others found in the 

Rogue Basin just to the south. This portion of the ecoregion tends to receive less precipitation 

than the more coastal portions of the Klamath Mountains and summer high temperatures can 

average more than 32oC (90oF). Vegetation is diverse in this area and is described in the level 4 

ecoregion descriptions for the Siskiyou foothills, Umpqua interior foothills, and coastal 

Siskiyous. 

Oregon Coast Range Ecoregion—The entire coast of Oregon is included within the Oregon 

Coast Range Ecoregion, and extends eastward to include the northern and central Oregon Coast 

Range Mountains. Geology is a mix of sedimentary sandstones, siltstones, and mudstones, with 

areas of volcanic activity. Elevations range from sea level to 1,200 m (4,000 feet). The marine 

climate moderates temperatures, which average 10oC (50oF). Average annual rainfall may vary 

from 152 to 460 cm (60 to 180 inches) per year. The soils in this region are generally deep and 

mature and vegetation is dominated by giant Sitka spruce, Douglas fir, and western hemlock 

forests. In the southern end of the range, Coast redwood, Port Orford cedar, red alder, and tan 

oak also become codominants. 

West Cascade Ecoregion—The West Cascades Ecoregion within the Oregon Coast Coho 

Salmon ESU is found in the Umpqua River Basin, specifically in the north Umpqua River and 

south Umpqua River drainages. Geology is closely related to volcanic activity of the Cascade 

Crest. The ecoregion is dominated by Douglas fir/western hemlock forests to about 1,000 m 

(3,300 feet). Above that, silver fir/mountain hemlock forests dominate. Very little of the area 

within the Oregon Coast Coho Salmon ESU is alpine area. This drier portion of the West 

99 
Cascades Ecoregion is subject to lightning-caused fire regimes similar to the Klamath 

Mountains. Snows are not as heavy as in the northern portion of the West Cascades Ecoregion in 

Oregon. 

Level 4 Ecoregion Descriptions 

Descriptions below refer to areas mapped in Figure 17. 

Coastal Lowlands, elevations sea level to 90 m (300 feet)—Estuaries within the Oregon Coast 

Coho Salmon ESU are all drowned river mouths (Good 2000). They are mainly of three types: 

well-flushed drowned rivers, seasonally open to the ocean (such as Sixes River, Flores Creek/ 

New River); well-flushed drowned rivers, predominantly freshwater input (e.g., Coquille River, 

Umpqua River, Siuslaw River); and well-flushed drowned rivers with predominantly oceanic 

input (such as Coos River, Sand Creek, Yaquina River, Nestucca River). Many of these areas 

historically had relatively large areas of salt, brackish, and freshwater marshes; sloughs; and 

swamps. Most, however, have suffered losses of these areas of up to 80% of these tidally 

influenced systems through diking and channelization. 

Sand dune sheets are part of the Pacific Northwest Coastal Region (Terrel 1979, Proctor 

et al. 1980) between the Strait of Juan de Fuca in Washington State and Cape Mendocino in 

California. Two hundred and twenty-five km of the Oregon Coast is covered by these dune 

systems. Some are found as isolated areas associated with bays and river mouths between 

headlands (such as Netarts Bay). Others are extensive dune sheets found on broad terraces (such 

as Coos Bay Dune Sheet and Sand Lake). These broad terraces may have extensive dune 

systems and may also harbor extensive freshwater lakes, bogs, fens, and blackwater streams 

(Wiedemann 1984, ONHP 2003). 

Coastal Uplands, elevations to about 150 m (≈500 feet)—This ecoregion is characterized by 

uplifted marine consolidated and semiconsolidated sediments. These include sandstones and 

siltstones. Also included are some volcanics. 

Volcanics—Volcanic geology is found at elevations from 300 to 1,200 m (1,000 to 4,000 feet). 

These volcanics are of various origins: the Columbia River basalts, the Siletz River, and the 

Yachats series of basalts. Some of the mountains found in this ecoregion may have been 

offshore seamounts buried by continental sediments (KCM 1983, ONHP 2003). 

Willapa Hills—These low-lying hills are a continuation of a larger area north of the Columbia 

River (WDNR 2003). These are in the Western Hemlock Zone. 

Mid-Coastal Sedimentary—The Mid-Coastal Sedimentary Ecoregion is underlain by siltstone 

and sandstone. The mountains are more rugged (dissected and higher) than the Willapa Hills. 

These sedimentary mountains are very prone to landslides if devegetated. Stream gradients and 

fluvial erosion rates can be high in these rugged areas, but are lower in the higher order streams 

that occupy the lowlands. Many of these areas have deep soils, and most are in the Western 

Hemlock Zone (ONHP 2003). 

100 
Southern Oregon Coastal Mountains—These are mountainous areas in the south portion of the 

Oregon Coast Coho Salmon ESU with ocean-modified climate. They are transitional between 

the Siskiyou and Coast ranges. These areas are underlain by Jurassic sandstone, metmorphosed 

sediments, granite, and serpentine (metamorphosed ocean sediments). Soils are dependent upon 

parent material. This is a complex much like the inland Siskiyous, but the ruggedness is less and 

elevations are lower. This is an area of very high plant diversity. The northern distribution 

limits of southern plant and animal species and southern limit of northern plant species are one 

reason for the diversity. Also the area’s unusual geology and stable climate have lead to the 

evolution of local endemic plants. The Mixed Conifer and Evergreen zones are found in this 

subregion (Barbour and Major 1977, Orr and Orr 2000, ONHP 2003). 

Inland Siskiyous—This area encompasses the Umpqua and Rogue River valleys and is very 

complex vegetationally. These vegetation types include Douglas fir forests, oak woodlands and 

savanna, mixed evergreen forest, mixed conifer forests, and Ponderosa pine woodlands. 

Grasslands and chaparral are found in the valley bottoms. Geology is complex with large areas 

of metamorphosed rocks such as serpentine and gabbro, sedimentary rocks such as limestone, as 

well as granite and basalt. Floristic elements of the Sierra Nevada Mountains, Sacramento 

Valley, Cascade Mountains, and Great Basin are all found in this ecoregion and contribute to the 

high plant diversity found here. Because of its unusual geology, and stable climate, it is also a 

major locality of vascular plant species evolution as well. Conifers are especially diverse in the 

Oregon section of the inland Siskiyou subregion with 18 species. This area has major climatic 

extremes ranging from 254 cm (100 inches) of precipitation per year to 50 cm (20 inches) 

(Barbour and Major 1977, Orr and Orr 2000, ONHP 2003). 

Valley Foothills—This subregion is an extension of the Willamette Valley on the west side, and 

is transitional between the Cascade Mountains and the Coast Range. This area has lower rainfall 

than adjacent mountainous subregions due to a rainshadow effect. Oregon white oak and 

Douglas fir are potentially dominant in this area, but agricultural conversion has substantially 

reduced the native forests (ONHP 2003). 

Umpqua Interior Foothills—This is an area of narrow interior valleys, terraces, and foothills 

with elevations from about 120 to 460 m (400 to 1,500 feet). Vegetation is a mix of Oregon 

white oak woodlands and coniferous forests with pastureland, vineyards, row crops, and orchards 

replacing the native vegetation. Other dominant tree species found are Douglas fir, Ponderosa 

pine, and madrone (ONHP 2003). 

Umpqua Cascades—This portion of the Cascades is drier than the western Cascades. Grand fir, 

white fir, western hemlock, Pacific silver fir, Douglas fir, and Shasta red fir dominate. The 

diversity of vegetation is greater than the western Cascades subregions due to warmer summer 

temperatures and a longer growing season, as well as floristic elements from both northern and 

southern floristic provinces (ONHP 2003). 

101 
102 
Appendix C: Potential Historical Abundance of 

Coho Salmon 

Having estimates of potential historical abundance of coho salmon (Oncorhynchus 

kisutch) populations is useful for a number of reasons. Such estimates can be used to compare 

with current abundance, develop an understanding of limiting factors, and model the 

independence of individual populations. Here we use two independent approaches to estimate 

historical abundance of coho salmon in the Oregon Coast Coho Salmon ESU for the purpose of 

modeling the independence of individual populations. 

Calculating Adult Abundance from Catch 

Lichatowich (1989) estimated historical abundance of adult coho salmon based on inriver catch records. Mullen (1981a) compiled catch records for individual coastal basins within 

the Oregon Coast Coho Salmon ESU and converted pounds landed to estimated number of adult 

salmon. Both Mullen (1981b) and Lichatowich (1989) divided total number of fish landed coastwide by an assumed exploitation rate of 40% to estimate total abundance. Mullen (1981b) 

estimated mean annual abundance for 5-year intervals from 1892 to 1940. Lichatowich (1989) 

estimated mean annual abundance for the 5 peak years between 1892 and 1920, which he 

considered a conservative measure of production because of the many problems associated with 

the accuracy of the early cannery records. 

The methods of Mullen (1981b) and Lichatowich (1989) were adopted here with the 

exception that they were applied to the peak year of catch in each of 10 coastal basins during the 

period of 1882–1925 as estimated by Mullen (1981a). Because maximum catch of coho salmon 

in individual basins did not occur in a single year, this approach gives a better estimate of 

potential historical abundance. Peak catches in the 10 basins actually occurred in six different 

years. However, like the earlier estimates, these estimates of abundance only apply to streams 

where fisheries took place. The 10 basins included represent about 89% of the coho salmon 

distribution in the Oregon Coast Coho Salmon ESU. 

Calculating Adult Abundance from GIS Data 

An estimate of historical potential smolt abundance for each population in the Oregon 

Coast Coho Salmon ESU (Figure C-1) is from data converted from Coastal Landscape Analysis 

and Modeling Study (CLAMS) used to calculate intrinsic potential for coho salmon (Burnett et 

al. 2003) (Figures C-2 through C-5). The estimated smolt potential was then converted to adult 

potential by applying a marine survival rate. 

Stream reaches were divided into two categories based on their gradient. Those reaches 

with a gradient less than or equal to 0.5% were assumed to be associated with wetlands and an 

expansive floodplain (Rosgen 1994, 1996, Montgomery and Buffington 1997, Buffington et al. 

103 
2002), which would provide winter habitat for coho salmon outside the active channel. For 

reaches with a gradient greater than 0.5%, the assumption was made that coho salmon smolts 

were produced primarily within the active channel. 

For each population, potential smolt production was calculated as the sum of the potential 

of all reaches with intrinsic potential greater than 0. For each reach with a gradient less than or 

equal to 0.5%, potential smolt production was calculated from the equation 

S = 0.0741 L (V–W) P (1)

where S is the potential number of smolts produced in the reach, L is the length of the reach (m), 

V is the valley width (m), W is the active channel width (m), P is the intrinsic potential of the 

reach (an index without units), and 0.0741 is the number of smolts per square meter (741/ha) 

based on data from NMFS et al. (1983). 

Potential smolt production was calculated for each reach with a gradient greater than 

0.5% from the equation 

S = (0.3405) (0.5) L W P (2)

where 0.3405 is the number of smolts per square meter in main channel pools based on data from 

Nickelson (1998), and 0.5 is the proportion of the area in pools based on an assumed 50:50 

pool:riffle ratio. 

For lake populations, potential smolt production was estimated by multiplying the lake 

area by 741 smolts/ha. This is a deviation from the approach used in Washington (NMFS 1983), 

where only a 30-m-wide littoral zone is considered. However, Oregon coastal lakes are shallow, 

with littoral zones that cover most if not all of their area. 

Potential historical adult abundance was estimated for each population by applying a 10% 

marine survival rate to the smolt estimates. These estimates were capped for two stream 

populations and several lake populations at 1,500 adults per mile of spawning habitat based on 

current estimates of the miles of stream in each basin that would be available for spawning. The 

value of 1,500 adults per mile is consistent with the maximum level observed in a lake system 

tributary in 2001, a high-survival year (ODFW 2003b, 2003d, Nickelson7

), and the density of 

coho observed in Tenmile Lakes in the 1955 (Morgan and Henry 1959) before warm-water fish 

became a problem. 

Results 

The results of the two different approaches used to estimate potential historical 

abundance of coho salmon in the large basins of the Oregon Coast Coho Salmon ESU produced 

surprisingly similar results (Table C-1). Differences between the two estimates ranged from 1% 

for the Yaquina River to 73% for the Umpqua River. There is a strong correlation between the 

estimates derived by the two methods (Figure C-1). 

 

7

 T. Nickelson, ODFW, Corvallis Research Laboratory, Corvallis, OR. Pers. commun., 2003. 

104 
The advantage of calculating adult abundance from computed intrinsic potential is that 

estimates can be made for basins where there are no historical fishery data. Table C-2 lists the 

estimated potential historical abundance of coho salmon for 56 putative populations of coho 

salmon in the Oregon Coast Coho Salmon ESU. Total adult abundance derived from smolt 

numbers and 10% marine survival was about 3.5 million adults if all populations peaked the 

same year. 

Discussion 

Historical abundance of coho salmon was estimated for the purpose of modeling the 

effects of relative abundance on population independence. For this exercise, marine survival was 

assumed to be 10% for all populations. This assumption results in an unrealistically high total 

abundance for the Oregon Coast Coho Salmon ESU when all populations are aggregated. This 

aggregate estimate of 3.3 million adult coho salmon is higher than the 978,000 for the peak fiveyear of Mullen (1981b) and the 1,385,000 (1,915,000 if you use the peak year) of Lichatowich 

(1989), both of which also included the Rogue River in the Southern Oregon Northern California 

ESU. The primary reasons for this result is that the populations are asynchronous; in other 

words, the peak abundance of the various populations did not occur in the same year as was 

assumed for this analysis. Thus it is an error to conclude that historical abundance was 3.3 

million adult coho salmon. One example of an approach to use this information to come up with 

a more realistic ESU abundance estimate is to assume that only 60% of the coastal habitat was 

productive at any given time.8

 This would yield an estimate of 2.0 million fish, which may be on 

the low side because most fish are produced from the lowlands, which were likely more stable 

than the uplands where the Reeves analysis9 applies. More work is needed to convert the smolt 

capacity estimates generated here into estimates of historical adult abundance. 

It is interesting to note that the basins with the greatest discrepancy between peak adult 

abundance estimated from catch and that estimated from intrinsic potential are the basins with 

the greatest effects from splash damming at the turn of the twentieth century (Sedell and Duvall 

1985). In each case, the abundance of adults estimated from intrinsic potential was at least 30% 

greater than that estimated from catch. Thus it could be that even as early as 1900, coho salmon 

populations had been significantly reduced by habitat destruction in some basins that would 

result in underestimates of abundance derived from harvest data. 

 

8

 G. H. Reeves, U.S. Forest Service, Pacific Northwest Research Station, Corvallis, OR. Pers. commun., September 

2004. 

9

 See footnote 7. 

105 
Table C-1. Estimate of potential historical abundance of coho salmon in large basins of the Oregon Coast 

Coho Salmon ESU using methods based on peak historical catch and estimated habitat 

capacity (based on data from Chapman 1986, Lichatowich 1989, Burnett et al. 2003). 

Estimated potential historical abundance 

Basin 

Based on 

catch (a) 

Based on IP 

(b) Difference (b–a)/a 

Nehalem River 240,000 333,000 93,000 39% 

Tillamook 292,500 329,000 36,500 12% 

Nestucca River 115,000 104,000 –11,000 –10% 

Siletz River 125,000 122,000 –3,000 –2% 

Yaquina River 120,000 122,000 2,000 2% 

Alsea River 150,000 163,000 13,000 9% 

Siuslaw River 292,500 267,000 –25,500 –9% 

Umpqua River 585,000 820,000 235,000 40% 

Coos River 150,000 206,000 56,000 37% 

Coquille River 310,000 417,000 107,000 35% 

106 
y = 1.4 23x - 57.351 5

2 R = 0.9595

100

200

300

400

500

600

700

800

900

100 200 300 400 500 600

Estimated from GIS data (in thousands)

Estimated from catch (in thousands)

Estimated from GIS data (in thousands)

y=1.4523x – 57.351 

R2

=0.9595 

Estimated from catch (in thousands)

Figure C-1. The relationship between historical potential coho salmon adult abundance estimated by 

historical catch records and adult abundance calculated from GIS data (data from Table C-1). 

107 
Table C-2. Potential historical smolt and adult abundance for 56 putative populations of coho salmon in 

the Oregon Coast Coho Salmon ESU. 

Population 

Potential 

smolts 

Adults at 

10% marine 

survival Population 

Potential 

smolts 

Adults at 

10% marine 

survival 

Necanicum 685,000 68,500 Alsea 1,628,000 163,000

Ecola 72,000 7,000 Big (near Alsea) 34,000 3,000

Arch Cape 3,000 300 Vingie 3,000 300

Short Sands 4,000 400 Yachats 110,000 11,000

Nehalem 3,330,000 333,000 Cummins 10,000 1,000

Spring 5,000 500 Bob 6,000 600

Watseco 5,000 500 Tenmile Creek 28,000 3,000

Tillamook Bay 3,288,000 329,000 Rock 6,000 600

Netarts 15,000 1,500 Big 18,000 2,000

Rover 2,000 200 China 5,000 500

Sand 123,000 12,000 Cape 15,000 2,000

Nestucca 1,037,000 104,000 Berry 54,000 5,000

Neskowin 49,000 5,000 Sutton (Mercer Lake) 84,000 8,000

Salmon 168,000 17,000 Siuslaw 2,674,000 267,000

Devils Lake 85,500 9,000 Siltcoos 771,000 77,000

Siletz 1,217,000 122,000 Tahkenitch 228,000 23,000

Schoolhouse 2,000 200 Threemile 22,000 2,000

Fogarty 18,000 2,000 Umpqua (Total) 8,199,000 820,000

Depoe Bay 7,000 700 Lower Umpqua 1,293,000 129,000

Rocky 10,000 1,000 Middle Umpqua 2,420,000 242,000

Spencer 11,000 1,000 North Umpqua 1,180,000 118,000

Wade 5,000 500 South Umpqua 3,310,000 331,000

Coal 4,000 400 Tenmile 525,000 53,000

Moolack 4,000 400 Coos 2,058,000 206,000

Big (near Yaquina) 26,000 3,000 Coquille 4,169,000 417,000

Yaquina 1,217,000 122,000 Johnson 8,000 800

Theil 20,000 2,000 Twomile 134,000 13,000

Beaver 265,000 27,000 Floras/New 396,000 34,000

Sixes 372,000 37,000

108 
Figure C-2. Intrinsic potential of rivers and streams on the north coast segment of the Oregon Coast 

Coho Salmon ESU. 

109 
110 

Figure C-3. Intrinsic potential of rivers and streams on the mid-coast segment of the Oregon Coast 

Coho Salmon ESU.
111 

Figure C-4. Intrinsic potential of rivers and streams on the Umpqua River Basin segment of the Oregon Coast Coho 
Figure C-5. Intrinsic potential of rivers and streams on the mid-south coast segment of the Oregon 

Coast Coho Salmon ESU. 

112 
Appendix D: Principal Components and 

Clustering Analysis 

Introduction 

The TRT identified historical coho salmon (Oncorhynchus kisutch) populations using 

river basins with unique ocean entry points as their fundamental units. Because these basins vary 

substantially in size and ecological conditions, these variations might mask potential 

subdivisions where local conditions produced multiple populations within a basin. In particular, 

the TRT and reviewers identified the large Umpqua River Basin as a candidate for subdivision, 

as the full river basin is more than four times the size of the next largest river basin, the Coquille 

River Basin (about 3 million acres vs. 0.7 million acres). Here, we describe our analysis of the 

Umpqua River Basin to determine whether it contains sufficiently diverse habitats as to represent 

multiple populations. 

As an aid to describing potential populations within river basins, the Southern 

Oregon/Northern California Coast (SONCC) Coho Salmon Workgroup of the TRT developed a 

method for using principal component and clustering analyses of climate, physiographic, and 

biogeographic data to identify areas of similar environmental conditions (Williams et al. 2006). 

The SONCC Workgroup used this analysis as a guide to delineating historical coho populations 

in the SONCC coho salmon ESU, providing a geographic basis for describing probable 

population boundaries within the interior river systems. 

The Oregon Coast Coho Salmon Workgroup (Workgroup) of the TRT used the SONCC 

Workgroup’s analytical method to explore potential population structure within the large river 

basins. To do so, the Workgroup conducted principal components and cluster analysis using data 

from fifth-field watersheds throughout the ESU and on a subset of watersheds in the Umpqua 

River Basin. 

Principal components analysis (PCA) is a statistical method for reducing the complexity 

of a data set while retaining most of the variability of the original data. In PCA, the data set is 

transformed into a set of new, uncorrelated variables that explain as much of the variability in the 

original data as possible. The analysis transforms the data to a new coordinate system for the 

data, making the first axis (or principal component) have the greatest variance, the second axis 

the second greatest, and so on. Because the first few principal components contain most of the 

variability of the original data, using principal components reduces the number of dimensions 

(variables) while retaining most of the information of the original set. This also serves to remove 

redundancy in correlated data so patterns within the data are apparent. PCA is frequently applied 

to complex data sets with internal correlation prior to cluster analysis, particularly in data mining 

and genetic analysis. 

113 
To identify areas of similarity, we used cluster analysis on the principal components 

across all the watersheds in the ESU and the subset of the watersheds in the Umpqua River 

Basin. Cluster analysis created groups of items within a data set by sequentially finding those 

items with minimal difference between them across all variables. In short, such analysis 

identifies which items (basins) are most similar given the input data and identifies major 

differences between groups of basins. 

Methods 

We analyzed environmental and ecological data according to the protocol described in 

Williams et al. (2006) for identifying potential population structure within river basins of the 

SONCC ESU, using all the data types in their analysis, and using the same source data where 

possible. We assembled data for this analysis in a geographical information system (GIS), 

including vegetation, weather, and lithology data. Table D-1 lists the data layers we used. As 

described in Williams et al. (2006), we reclassified the lithology into broad categories (Table 

D-2). 

We then summarized data by fifth-field watershed, using the watershed boundaries 

provided by the Regional Ecosystem Office (2002). The summary method varied according to 

data type (indicated in Table D-1). For continuous polygon vector data, such as lithology or 

ecoregion, we calculated the proportion of total watershed area consisting of each type for each 

watershed, using ArcMap 8.3 (ESRI 2002). For continuous raster data, such as elevation or 

precipitation, we calculated the mean value across each watershed with the Spatial Analyst 

extension to ArcMap. The stream flow data, in discrete point vector format, required more 

complex analysis, as did two index values we calculated for each watershed: snow potential and 

precipitation to wet-days ratio, as follows. 

Table D-1. Data sources for the principal components analysis. These data were stored in a GIS, which 

used various raster and vector formats for storage. 

Data layer Data typea Data source 

Fifth-field watershed boundaries CPV Regional Ecosystem Office 2002 

Elevation (10-m digital elevation models) CR USDI Bureau of Land Management 1998 

Annual precipitation (4-km PRISMb

model) 

CR Oregon Climate Service 2000b 

Annual temperature (4-km PRISM model) CR Daly et al. 2002a 

Lithology CPV USGS 1995 

Ecoregions (Level III) CPV ONHP 2001 

Monthly freeze days (1-km PRISM 

model) 

CR Daly et al. 2000b 

Annual and Monthly temperatures (1-km 

PRISM model) 

CR Daly et al. 2000a 

Stream flow DPV USGS 2004 

a CPV = continuous polygon vector, CR = continuous raster, DPV = discrete point vector. 

b

 Parameter-elevation regressions on Independent Slopes Model (Daly et al. 2002b). 

114 
Table D-2. Reclassification scheme for geology data from USGS 1995. This table lists the original 

geology type provided and the reclassified type used in this analysis. Our goal for the 

reclassification was to closely match the number and breadth of categories used in Williams et al. 

2006. 

Lithology type in USGS (1995) Reclassified type 

Alkalic intrusive Granitic 

Alluvium Alluvial 

Calc-alkaline intrusive Granitic 

Calc-alkaline volcanoclastic Volcanic 

Conglomerate Sedimentary 

Dune sand Alluvial 

Felsic pyroclastic Volcanic 

Felsic volcanic flow Volcanic 

Glacial drift Alluvial 

Lake sediment and playa Sedimentary 

Mafic gneiss Granitic 

Mafic intrusive Volcanic 

Mafic pyroclastic Volcanic 

Mafic volcanic flow Volcanic 

Meta-sedimentary phyllite and schist Sedimentary 

Mixed eugeosynclinal Sedimentary 

Sandstone Sedimentary 

Shale and mudstone Sedimentary 

Siltstone Sedimentary 

Ultramafic Made up <1% of the ESU area and 

was excluded from final analysis.

Many watersheds had no U.S. Geological Survey stream gage sites, so we were unable to 

directly use the gage data to determine the month of peak stream flow for each watershed. 

Instead, we estimated the month of peak flow for each watershed. We started by calculating the 

month of peak flow for each stream gage as the number of the month out of the 12-month long 

water year beginning October 1 (e.g., October was coded with a 1, June with an 8). Then, we 

used the spatial analyst’s inverse distance weighted approximation to create a continuous grid of 

peak stream flow months for the entire ESU. This estimation analyzed data from 637 gage sites 

throughout Oregon, including 94 within the ESU. We then calculated the mean result for each 

watershed from the grid approximation and used it as the month of peak stream flow. As 

validation, we visually compared the result to gage and precipitation data to verify they were 

similar. 

Williams et al. (2006) calculated a snow index to reflect the relative probability of snow 

in each watershed in the SONCC ESU from monthly precipitation and temperature data. Using 

their method for generating a snow index for each watershed, we calculated the mean 

precipitation for each month of the year, as well as the mean number of days with temperatures 

below freezing (freeze days). We then multiplied each month’s precipitation by its freeze days 

and summed the result for the entire year. Each watershed’s sum served as its snow index. 

In addition, we calculated the precipitation to wet-days ratio for each watershed. This 

ratio, described in Williams et al. (2006), divides the mean annual inches of precipitation for 

115 
each watershed by the watershed’s mean annual number of days with measurable precipitation. 

They calculated this ratio as a means to indicate whether precipitation is concentrated in large 

quantities over a short period during the year or if it is spread throughout the year. 

We conducted the principal components analysis at two scales: once with all 

environmental data for the Oregon Coast Coho Salmon ESU (Tables D-3 and D-4), and again 

with the subset of data for the watersheds within the Umpqua River Basin. We used the prcomp

function in the R statistical analysis package (R Development Core Team 2003) to perform the 

PCA after scaling the data to have a variance of one and a mean of zero. 

To identify potential clusters across the entire ESU and within the Umpqua River Basin, 

we applied agglomerative hierarchical analysis to the first three principal components of each 

watershed. We performed the cluster analysis with the agnes function in R using the average 

distance method. For presentation and comparison to the proposed historic coho populations, we 

imported the clustering results into ArcMap and we used the resulting GIS data to create maps 

for review. 

Results 

Each principal component (PC) is an axis in the new coordinate system with an 

associated linear transformation described by its eigenvalues. Variables with greater absolute 

values of eigenvalues for a PC are more influential than other variables. For PCA of 

environmental data from the entire ESU, the first three PCs explained 74.9% of the variance in 

the data. Eigenvalues for the first six PCs and the cumulative variances are listed in Table D-5. 

Within the first PC, high negative or positive factors (>0.25) indicate that the proportion of 

sedimentary lithology is strongly differentiated from the proportion of volcanic lithology, as are 

the proportions of Coast Range and Cascades ecoregion areas. This PC is also strongly 

influenced by elevation, the month of peak stream flow, mean annual temperature, and mean 

annual low temperature. The second PC is most influenced by climate variables, with the 

precipitation to wet day ratio, annual precipitation, snow index, temperature range, and mean 

high temperature having strong influence. The proportion of Klamath Mountains ecoregion area 

was also influential. 

Within the Umpqua River Basin data, the first three PCs accounted for 79.0% of the 

data’s variance. Results for the first six PCs for the Umpqua River Basin data are presented in 

Table D-6. The first PC is mostly influenced by climate variables, with mean temperature, mean 

low and high temperature, snow index, and month of peak stream flow having the strongest 

influence along with elevation. The second PC is strongly driven by precipitation and the 

precipitation to wet day ratio, but also by a separation between proportion of area in the Klamath 

Mountains and Coast Range ecoregions. 

116 
Table D-3. Climate data for the Oregon Coast ESU used in the PCA for the Oregon Coast Coho Salmon 

ESU. We used a subset of this data in the PCA for the Umpqua River Basin. Our analysis also 

included the data in Table D-4. The hydrologic unit code for each fifth-field watershed is listed 

in the HUC5 column.

 Temperature (°C) 

Watershed HUC5 Ppta Mean High Low Range SNWIb PWYRc Peakd

Lower Nehalem R. 1710020203 111.16 9.48 14.50 4.45 10.06 149.1 1427.1 4.5 

Necanicum R. 1710020101 111.89 10.44 15.06 5.82 9.24 96.9 1382.5 4.3 

Middle Nehalem 1710020202 64.68 9.56 15.09 4.04 11.05 82.6 966.2 5.3 

N. Fork Nehalem 1710020205 116.25 9.97 14.89 5.05 9.84 116.0 1446.1 4.2 

Upper Nehalem R. 1710020201 74.40 9.25 14.68 3.82 10.86 112.7 1089.9 4.7 

Lower Nehalem R. 1710020206 126.89 10.05 14.70 5.40 9.30 127.0 1533.1 4.1 

Salmonberry R. 1710020204 139.86 8.80 13.26 4.33 8.94 205.6 1696.2 4.5 

Kilchis R. 1710020306 132.71 10.29 15.08 5.50 9.59 143.2 1627.6 4.2 

Miami R. 1710020307 123.98 10.50 15.27 5.74 9.52 118.0 1571.8 4.1 

Wilson R. 1710020305 122.77 9.28 13.80 4.75 9.05 158.2 1517.6 4.5 

Tillamook Bay 1710020308 87.36 10.38 15.10 5.66 9.44 76.1 1252.9 4.2 

Spring Cr. 1710020309 93.54 10.68 15.36 5.99 9.37 67.2 1338.3 3.9 

Trask R. 1710020304 109.41 9.64 14.36 4.91 9.45 137.7 1459.0 4.4 

Tillamook R. 1710020303 97.08 10.47 15.28 5.66 9.62 92.9 1367.2 4.1 

Nestucca R. 1710020302 109.13 10.38 15.33 5.43 9.90 114.1 1448.2 4.0 

Little Nestucca R. 1710020301 105.27 10.83 16.08 5.58 10.50 88.5 1430.4 3.6 

Salmon R. 1710020408 113.15 10.11 15.06 5.17 9.89 171.3 1739.7 3.8 

Lower Siletz R. 1710020407 99.04 10.54 15.38 5.70 9.68 92.0 1400.9 4.1 

Upper Siletz R. 1710020404 151.60 8.51 13.20 3.82 9.38 257.4 1968.0 4.1 

Middle Siletz R. 1710020405 135.17 9.75 15.17 4.34 10.82 184.5 1711.6 4.1 

Rock Cr. 1710020406 99.58 10.17 15.93 4.40 11.53 127.5 1335.0 4.3 

Devils Lk./Moolack Cr. 1710020409 81.39 10.75 15.12 6.37 8.75 47.4 1203.2 4.2 

Upper Yaquina R. 1710020401 72.41 10.74 16.11 5.37 10.74 78.0 1119.3 4.1 

Lower Yaquina R. 1710020403 75.50 10.82 15.23 6.40 8.78 46.2 1206.7 4.3 

Big Elk Cr. 1710020402 80.78 11.03 16.40 5.66 10.74 85.6 1287.6 4.3 

Beaver Cr. 1710020505 82.47 10.87 15.40 6.33 9.13 49.4 1251.9 5.1 

Drift Cr. 1710020503 108.92 11.12 16.37 5.87 10.50 87.2 1554.1 4.4 

Upper Alsea R. 1710020501 90.75 11.11 16.40 5.82 10.58 106.7 1367.9 4.7 

Lower Alsea R. 1710020504 94.79 11.27 16.51 6.03 10.44 79.6 1454.0 4.5 

Big Cr./Vingie Cr. 1710020508 85.95 10.89 15.63 6.15 9.48 65.2 1398.0 4.4 

Five Rivers/Lobster Cr. 1710020502 89.18 11.81 17.19 6.43 10.76 76.6 1409.6 4.4 

Yachats R. 1710020506 89.10 11.33 16.63 6.04 10.59 65.1 1392.1 4.2 

Lake Cr. 1710020604 83.59 11.60 17.15 6.05 11.10 79.0 1224.5 4.4 

Cummins Cr./Tenmile 

Cr. 

1710020507 91.12 11.10 16.10 6.10 9.99 65.0 1362.6 3.9 

Deadwood Cr. 1710020605 88.23 11.69 17.00 6.38 10.62 72.2 1289.4 4.3 

Indian Cr./Lake Cr. 1710020606 88.08 11.69 17.13 6.26 10.87 65.1 1341.0 4.2 

N. Fork Siuslaw R. 1710020607 85.68 11.27 16.38 6.16 10.22 56.9 1272.6 3.9 

Wildcat Cr. 1710020603 60.94 11.34 17.64 5.04 12.60 71.2 1039.4 4.4 

Woahink L. 1710020701 74.17 11.13 16.04 6.22 9.82 42.9 1168.8 4.1 

Lower Siuslaw R. 1710020608 77.23 11.40 16.69 6.11 10.59 56.7 1207.5 4.1 

117 
Table D-3 continued. Climate data for the Oregon Coast ESU used in the PCA for the Oregon Coast 

Coho Salmon ESU. We used a subset of this data in the PCA for the Umpqua River Basin. Our 

analysis also included the data in Table D-4. The hydrologic unit code for each fifth-field 

watershed is listed in the HUC5 column. 

 Temperature (°C) 

Watershed HUC5 Ppta Mean High Low Range SNWIb PWYRc Peakd

Wolf Cr. 1710020602 56.60 11.40 17.63 5.16 12.47 63.5 977.5 4.4 

Lower Smith R. 1710030307 70.62 11.20 16.51 5.88 10.64 52.4 1110.1 4.3 

Upper Siuslaw R. 1710020601 52.94 11.34 17.50 5.18 12.32 55.7 942.2 4.4 

Upper Smith R. 1710030306 52.59 11.14 17.16 5.11 12.05 50.9 958.3 4.5 

Lower Umpqua R. 1710030308 71.23 11.21 16.40 6.02 10.37 51.6 1130.1 4.7 

Middle Umpqua R. 1710030304 54.19 11.57 17.72 5.42 12.30 43.9 1015.6 5.0 

Lakeside Frontal 1710030403 71.09 11.31 16.44 6.17 10.27 46.3 1131.1 4.4 

Elk Cr. 1710030303 49.36 11.51 17.82 5.20 12.62 51.7 903.1 4.7 

Upper Umpqua R. 1710030301 47.51 11.87 18.01 5.74 12.27 40.7 892.5 4.4 

Millicoma R. 1710030402 74.41 11.38 17.09 5.66 11.43 60.4 1156.2 4.6 

Calapooya Cr. 1710030302 50.53 11.74 17.84 5.63 12.20 55.0 922.4 4.4 

Canton Cr. 1710030109 65.56 10.66 16.20 5.13 11.07 74.3 1060.9 4.6 

Coos Bay 1710030404 66.92 11.45 16.54 6.37 10.18 40.5 1123.0 4.6 

Lake Cr. 1710030305 63.63 11.55 17.42 5.68 11.75 55.3 1079.3 5.0 

Steamboat Cr. 1710030108 63.75 9.76 15.48 4.04 11.43 81.9 1032.5 5.3 

Rock Cr. 1710030110 67.24 11.30 16.89 5.71 11.18 77.6 1121.4 4.5 

S. Fork Coos R. 1710030401 68.74 11.61 16.99 6.24 10.76 61.7 1117.2 4.4 

Boulder Cr. 1710030106 55.97 8.90 14.88 2.92 11.96 113.1 985.1 5.9 

Lemolo Lk. 1710030102 59.79 5.04 11.65 -1.58 13.23 213.7 1079.9 6.4 

Upper N. Umpqua R. 1710030103 58.58 7.86 14.17 1.55 12.61 126.4 1033.7 6.6 

Middle N. Umpqua R. 1710030107 56.03 10.26 16.29 4.23 12.03 86.2 985.9 5.2 

Lower N. Umpqua R. 1710030112 42.73 11.98 18.35 5.61 12.75 46.7 819.6 4.6 

Fish Cr. 1710030105 55.16 6.79 13.06 0.51 12.55 134.4 980.6 6.8 

Clearwater Cr. 1710030104 55.07 6.58 13.05 0.10 12.95 138.4 989.0 6.7 

Little R. 1710030111 58.31 11.10 17.09 5.11 12.01 68.5 1008.6 4.8 

Lower Coquille R. 1710030506 65.31 11.38 16.82 5.93 10.89 47.5 1175.0 4.5 

N. Fork Coquille R. 1710030505 69.09 11.56 17.44 5.69 11.75 56.8 1142.2 4.6 

Upper S. Umpqua R. 1710030201 51.79 8.45 14.39 2.51 11.88 100.9 955.3 6.2 

E. Fork Coquille R. 1710030504 72.32 11.42 16.63 6.21 10.50 62.5 1166.7 4.4 

Middle S. Umpqua R. 1710030203 52.87 10.78 16.88 4.68 12.20 68.5 939.1 4.8 

Lower S. Umpqua R. 1710030213 39.35 12.30 18.50 6.10 12.40 36.4 783.8 4.2 

Ollala Cr. 1710030212 46.70 11.71 17.62 5.80 11.82 47.3 894.8 4.1 

Diamond Lk. 1710030101 54.98 4.49 10.99 -2.01 13.00 179.1 1036.3 6.5 

Myrtle Cr. 1710030211 46.10 11.81 17.87 5.75 12.13 44.1 865.7 4.6 

Middle Main 

Coquille R. 

1710030503 59.74 11.81 17.87 5.75 12.12 57.8 1153.0 4.3 

Middle S. Umpqua R. 1710030210 40.59 11.99 18.11 5.87 12.24 35.9 815.9 4.3 

Middle Fork 

Coquille R. 

1710030502 64.57 11.52 17.19 5.84 11.32 67.7 1132.1 4.3 

New R. 1710030604 76.94 11.54 16.56 6.52 9.96 50.2 1366.8 4.2 

S. Umpqua R. 1710030205 46.08 11.41 17.37 5.45 11.92 49.8 895.7 4.6 

118 
Table D-3 continued. Climate data for the Oregon Coast ESU used in the PCA for the Oregon Coast 

Coho Salmon ESU. We used a subset of this data in the PCA for the Umpqua River Basin. Our 

analysis also included the data in Table D-4. The hydrologic unit code for each fifth-field 

watershed is listed in the HUC5 column. 

 Temperature (°C) 

Watershed HUC5 Ppta Mean High Low Range SNWIb PWYRc Peakd

Jackson Cr. 1710030202 48.39 8.41 14.27 2.54 11.73 100.8 944.1 5.6 

Lower Cow Cr. 1710030209 50.67 11.29 16.56 6.02 10.54 48.8 945.3 4.3 

Elk Cr. 1710030204 47.99 9.82 15.68 3.96 11.72 79.4 928.6 4.6 

Sixes R. 1710030603 91.76 11.68 16.96 6.41 10.54 70.2 1549.3 4.2 

W. Fork Cow Cr. 1710030208 66.37 10.88 15.70 6.05 9.65 74.6 1181.1 4.3 

S. Fork Coquille R. 1710030501 94.71 11.44 17.15 5.73 11.42 114.4 1459.0 4.4 

Upper Cow Cr. 1710030206 54.04 10.47 15.85 5.09 10.78 83.7 994.4 4.6 

Middle Cow Cr. 1710030207 46.99 10.81 15.88 5.73 10.14 58.8 918.0 4.6 

a

 The mean annual inches of precipitation of the watershed. 

b The result of the snow index calculation. 

c

 The precipitation to wet-day ratio. 

d

 The numerical month of peak flow during the water year. 

119 
Table D-4. Physiographic and biogeographic data used for PCA for the Oregon Coast Coho Salmon 

ESU. We used a subset of this data in the PCA for the Umpqua River Basin. Our analysis also 

included the data in Table D-3. The hydrologic unit code for each fifth-field watershed is listed 

in the HUC5 column. The lithology and ecoregion columns list the proportion of each watershed 

in the respective type. 

 Lithology Ecoregion 

Watershed HUC5 Eleva Allb Sedc Grad Vole Coastf

WvalgCasch Klmi

Lower Nehalem R. 1710020203 319.6 0.05 0.72 0.00 0.23 1.00 0.00 0.00 0.00 

Necanicum R. 1710020101 206.5 0.14 0.48 0.00 0.33 1.00 0.00 0.00 0.00 

Middle Nehalem 1710020202 286.0 0.04 0.81 0.00 0.15 1.00 0.00 0.00 0.00 

N. Fork Nehalem 1710020205 235.4 0.06 0.72 0.00 0.22 1.00 0.00 0.00 0.00 

Upper Nehalem R. 1710020201 379.0 0.03 0.74 0.00 0.23 1.00 0.00 0.00 0.00 

Lower Nehalem R. 1710020206 275.2 0.07 0.20 0.00 0.70 1.00 0.00 0.00 0.00 

Salmonberry R. 1710020204 581.4 0.00 0.01 0.00 0.99 1.00 0.00 0.00 0.00 

Kilchis R. 1710020306 369.5 0.02 0.01 0.00 0.97 1.00 0.00 0.00 0.00 

Miami R. 1710020307 286.5 0.07 0.18 0.00 0.74 1.00 0.00 0.00 0.00 

Wilson R. 1710020305 470.4 0.02 0.20 0.00 0.78 1.00 0.00 0.00 0.00 

Tillamook Bay 1710020308 52.2 0.19 0.19 0.00 0.22 1.00 0.00 0.00 0.00 

Spring Cr. 1710020309 147.0 0.15 0.48 0.00 0.31 1.00 0.00 0.00 0.00 

Trask R. 1710020304 440.2 0.09 0.20 0.00 0.71 1.00 0.00 0.00 0.00 

Tillamook R. 1710020303 170.9 0.23 0.47 0.00 0.29 1.00 0.00 0.00 0.00 

Nestucca R. 1710020302 360.6 0.02 0.52 0.00 0.43 1.00 0.00 0.00 0.00 

Little Nestucca R. 1710020301 220.5 0.04 0.80 0.00 0.16 1.00 0.00 0.00 0.00 

Salmon R. 1710020408 320.9 0.04 0.51 0.00 0.45 1.00 0.00 0.00 0.00 

Lower Siletz R. 1710020407 193.3 0.08 0.55 0.00 0.36 1.00 0.00 0.00 0.00 

Upper Siletz R. 1710020404 619.6 0.06 0.39 0.00 0.54 1.00 0.00 0.00 0.00 

Middle Siletz R. 1710020405 338.7 0.04 0.50 0.00 0.46 1.00 0.00 0.00 0.00 

Rock Cr. 1710020406 279.7 0.00 0.91 0.00 0.06 1.00 0.00 0.00 0.00 

Devils Lk./Moolack Cr. 1710020409 92.1 0.10 0.76 0.00 0.13 1.00 0.00 0.00 0.00 

Upper Yaquina R. 1710020401 175.5 0.00 0.99 0.00 0.00 1.00 0.00 0.00 0.00 

Lower Yaquina R. 1710020403 80.0 0.03 0.90 0.00 0.00 1.00 0.00 0.00 0.00 

Big Elk Cr. 1710020402 226.7 0.00 0.99 0.00 0.00 1.00 0.00 0.00 0.00 

Beaver Cr. 1710020505 107.7 0.18 0.82 0.00 0.00 1.00 0.00 0.00 0.00 

Drift Cr. 1710020503 311.6 0.00 0.98 0.02 0.00 1.00 0.00 0.00 0.00 

Upper Alsea R. 1710020501 402.0 0.03 0.56 0.00 0.41 1.00 0.00 0.00 0.00 

Lower Alsea R. 1710020504 243.7 0.04 0.85 0.00 0.08 1.00 0.00 0.00 0.00 

Big Cr./Vingie Cr. 1710020508 138.9 0.32 0.31 0.00 0.37 1.00 0.00 0.00 0.00 

Five Rivers/Lobster Cr. 1710020502 255.0 0.00 0.98 0.00 0.02 1.00 0.00 0.00 0.00 

Yachats R. 1710020506 213.6 0.00 0.76 0.00 0.23 1.00 0.00 0.00 0.00 

Lake Cr. 1710020604 352.7 0.06 0.89 0.00 0.05 1.00 0.00 0.00 0.00 

Cummins Cr./Tenmile 

Cr. 

1710020507 251.4 0.01 0.22 0.00 0.76 1.00 0.00 0.00 0.00 

Deadwood Cr. 1710020605 279.9 0.00 0.99 0.00 0.00 1.00 0.00 0.00 0.00 

Indian Cr./Lake Cr. 1710020606 237.3 0.00 1.00 0.00 0.00 1.00 0.00 0.00 0.00 

N. Fork Siuslaw R. 1710020607 160.4 0.01 0.97 0.00 0.00 1.00 0.00 0.00 0.00 

Wildcat Cr. 1710020603 280.5 0.00 0.96 0.00 0.03 0.98 0.02 0.00 0.00 

120 
Table D-4 continued. Physiographic and biogeographic data used for PCA for the Oregon Coast Coho 

Salmon ESU. We used a subset of this data in the PCA for the Umpqua River Basin. Our 

analysis also included the data in Table D-3. The hydrologic unit code for each fifth-field 

watershed is listed in the HUC5 column. The Elev column lists the mean elevation of the 

watershed in feet. The lithology and ecoregion columns list the proportion of each watershed in 

the respective type. 

 Lithology Ecoregion 

Watershed HUC5 Eleva Allb Sedc Grad Vole Coastf

WvalgCaschKlmi

Waohink R. 1710020701 89.8 0.11 0.82 0.00 0.00 1.00 0.00 0.00 0.00 

Lower Siuslaw R. 1710020608 192.6 0.05 0.90 0.00 0.02 1.00 0.00 0.00 0.00 

Wolf Cr. 1710020602 298.6 0.00 0.99 0.00 0.01 0.98 0.02 0.00 0.00 

Lower Smith R. 1710030307 231.6 0.00 0.97 0.00 0.02 1.00 0.00 0.00 0.00 

Upper Siuslaw R. 1710020601 284.0 0.05 0.94 0.00 0.00 0.57 0.43 0.00 0.00 

Upper Smith R. 1710030306 294.4 0.01 0.98 0.00 0.00 0.92 0.08 0.00 0.00 

Lower Umpqua R. 1710030308 133.9 0.07 0.83 0.00 0.00 1.00 0.00 0.00 0.00 

Middle Umpqua R. 1710030304 198.3 0.03 0.92 0.00 0.00 1.00 0.00 0.00 0.00 

Lakeside Frontal 1710030403 112.4 0.17 0.78 0.00 0.00 1.00 0.00 0.00 0.00 

Elk Cr. 1710030303 267.0 0.03 0.83 0.00 0.13 0.27 0.31 0.12 0.30 

Upper Umpqua R. 1710030301 288.9 0.06 0.90 0.00 0.00 0.80 0.00 0.00 0.20 

Millicoma R. 1710030402 348.1 0.00 1.00 0.00 0.00 1.00 0.00 0.00 0.00 

Calapooya Cr. 1710030302 385.4 0.07 0.79 0.00 0.12 0.00 0.00 0.37 0.63 

Canton Cr. 1710030109 883.5 0.00 0.00 0.00 0.98 0.00 0.00 1.00 0.00 

Coos Bay 1710030404 91.8 0.19 0.72 0.00 0.03 1.00 0.00 0.00 0.00 

Lake Cr. 1710030305 331.1 0.00 1.00 0.00 0.00 1.00 0.00 0.00 0.00 

Steamboat Cr. 1710030108 966.4 0.00 0.00 0.00 0.93 0.00 0.00 1.00 0.00 

Rock Cr. 1710030110 787.9 0.00 0.46 0.00 0.44 0.00 0.00 1.00 0.00 

S. Fork Coos R. 1710030401 495.0 0.00 1.00 0.00 0.00 1.00 0.00 0.00 0.00 

Boulder Cr. 1710030106 1202.1 0.00 0.00 0.00 0.99 0.00 0.00 1.00 0.00 

Lemolo Lk. 1710030102 1671.4 0.27 0.00 0.00 0.72 0.00 0.00 1.00 0.00 

Upper N. Umpqua R. 1710030103 1270.0 0.11 0.00 0.00 0.86 0.00 0.00 1.00 0.00 

Middle N. Umpqua R. 1710030107 868.7 0.00 0.03 0.00 0.92 0.00 0.00 1.00 0.00 

Lower N. Umpqua R. 1710030112 300.2 0.06 0.50 0.00 0.44 0.00 0.00 0.07 0.93 

Fish Cr. 1710030105 1375.5 0.05 0.00 0.00 0.92 0.00 0.00 1.00 0.00 

Clearwater Cr. 1710030104 1458.9 0.16 0.00 0.00 0.84 0.00 0.00 1.00 0.00 

Little R. 1710030111 801.7 0.00 0.18 0.07 0.66 0.00 0.00 0.90 0.10 

Lower Coquille R. 1710030506 84.5 0.28 0.67 0.00 0.03 1.00 0.00 0.00 0.00 

N. Fork Coquille R. 1710030505 226.3 0.07 0.88 0.00 0.06 1.00 0.00 0.00 0.00 

Upper S. Umpqua R. 1710030201 1098.4 0.00 0.00 0.00 0.96 0.00 0.00 1.00 0.00 

E. Fork Coquille R. 1710030504 439.5 0.00 0.98 0.00 0.00 1.00 0.00 0.00 0.00 

Middle S. Umpqua R. 1710030203 820.7 0.00 0.13 0.01 0.81 0.00 0.00 1.00 0.00 

Lower S. Umpqua R. 1710030213 297.1 0.13 0.42 0.02 0.40 0.01 0.00 0.02 0.98 

Ollala Cr. 1710030212 409.4 0.06 0.88 0.00 0.04 0.02 0.00 0.00 0.98 

Diamond Lk. 1710030101 1814.2 0.19 0.00 0.00 0.74 0.00 0.00 1.00 0.00 

Myrtle Cr. 1710030211 496.3 0.00 0.27 0.43 0.29 0.00 0.00 0.18 0.82 

Middle Main Coquille R. 1710030503 188.5 0.09 0.91 0.00 0.00 1.00 0.00 0.00 0.00 

Middle S. Umpqua R. 1710030210 372.9 0.05 0.78 0.00 0.02 0.00 0.00 0.00 1.00 

121 
Table D-4 continued. Physiographic and biogeographic data used for PCA for the Oregon Coast Coho 

Salmon ESU. We used a subset of this data in the PCA for the Umpqua River Basin. Our 

analysis also included the data in Table D-3. The hydrologic unit code for each fifth-field 

watershed is listed in the HUC5 column. The Elev column lists the mean elevation of the 

watershed in feet. The lithology and ecoregion columns list the proportion of each watershed in 

the respective type. 

 Lithology Ecoregion 

Watershed HUC5 Eleva Allb Sedc Grad Vole Coastf

WvalgCasch Klmi

Middle Fork Coquille R. 1710030502 455.7 0.00 0.99 0.00 0.01 0.80 0.00 0.00 0.20 

New R. 1710030604 200.6 0.30 0.68 0.00 0.00 1.00 0.00 0.00 0.00 

S. Umpqua R. 1710030205 549.4 0.04 0.46 0.21 0.28 0.00 0.00 0.12 0.88 

Jackson Cr. 1710030202 1026.5 0.00 0.00 0.00 0.97 0.00 0.00 1.00 0.00 

Lower Cow Cr. 1710030209 563.2 0.03 0.78 0.00 0.10 0.01 0.00 0.00 0.99 

Elk Cr. 1710030204 833.3 0.00 0.15 0.17 0.57 0.00 0.00 0.81 0.19 

Sixes R. 1710030603 311.7 0.08 0.90 0.02 0.00 1.00 0.00 0.00 0.00 

W. Fork Cow Cr. 1710030208 735.0 0.00 0.85 0.03 0.10 0.67 0.00 0.00 0.33 

S. Fork Coquille R. 1710030501 656.5 0.02 0.91 0.00 0.00 0.99 0.00 0.00 0.01 

Upper Cow Cr. 1710030206 900.0 0.00 0.13 0.66 0.09 0.00 0.00 0.03 0.97 

Middle Cow Cr. 1710030207 697.0 0.10 0.47 0.02 0.37 0.00 0.00 0.00 1.00 

a

 Mean watershed elevation (feet above sea level) 

b

Alluvial lithology 

c

 Sedimentary lithology 

d

 Granitic lithology 

e

 Volcanic lithology 

f

 Coast Range Ecoregion 

g

 Willamette Valley Ecoregion 

h

 Cascades Ecoregion 

i

 Klamath Mountains Ecoregion 

122 
Table D-5. Principal component eigenvectors and variance for the Oregon Coast Coho Salmon ESU. 

Factor PC1 PC2 PC3 PC4 PC5 PC6 

Elevation 0.360 –0.058 –0.030 0.089 0.006 –0.139 

% Cascades Ecoregion 0.333 –0.096 0.060 0.113 0.279 0.184 

Month of peak stream flow 0.328 –0.080 0.234 –0.088 0.043 –0.170 

% Volcanic geology 0.303 0.124 –0.200 0.148 0.174 0.437 

Snow index 0.208 0.337 –0.072 0.175 –0.234 –0.171 

Mean range of temp 0.171 –0.332 0.247 0.176 –0.052 –0.179 

% Granitic geology 0.031 –0.157 –0.545 –0.018 –0.370 –0.316 

% Alluvial geology 0.030 0.085 0.152 –0.851 –0.146 0.205 

% Klamath Mtn Ecoregion –0.012 –0.302 –0.455 –0.171 –0.210 –0.038 

% Willamette Valley Ecoregion –0.029 –0.115 0.310 0.250 –0.746 0.480 

Precipitation –0.089 0.441 –0.135 0.148 –0.071 0.040 

Precipitation to wet-day ratio –0.099 0.434 –0.104 0.108 –0.054 –0.004 

Mean high temp –0.258 –0.309 0.004 0.157 0.129 0.112 

% Coast Range Ecoregion –0.263 0.292 0.211 –0.012 0.002 –0.187 

% Sedimentary geology –0.306 –0.086 0.314 0.076 –0.048 –0.396 

Mean temp –0.333 –0.183 –0.096 0.090 0.153 0.187 

Mean low temp –0.356 –0.043 –0.173 0.017 0.153 0.228 

Variance 6.81 4.37 1.55 1.14 0.93 0.82 

Cumulative % of total variance 40.0 65.8 74.9 81.6 91.9 95.1 

123 
Table D-6. Principal component eigenvectors and variance for the Umpqua River Basin. 

Factor PC1 PC2 PC3 PC4 PC5 PC6 

Mean temp 0.327 –0.012 –0.127 –0.151 0.067 0.019 

Mean low temp 0.325 0.044 –0.186 –0.084 0.067 –0.074 

Mean high temp 0.316 –0.078 –0.053 –0.224 0.065 0.128 

% Sedimentary geology 0.279 0.159 0.336 0.071 0.062 –0.047 

% Klamath Mtn Ecoregion 0.189 –0.369 –0.065 0.371 0.052 –0.304 

% Coast Range Ecoregion 0.151 0.397 0.309 0.035 –0.023 0.404 

% Willamette Valley Ecoregion 0.063 –0.026 0.306 –0.362 –0.739 –0.450 

% Granitic geology 0.054 –0.153 –0.341 0.429 –0.594 0.432 

Precipitation –0.078 0.522 –0.113 0.040 –0.045 –0.082 

Precipitation to wet-day ratio –0.106 0.514 –0.074 0.157 –0.071 –0.101 

Mean range of temp –0.147 –0.288 0.369 –0.275 –0.034 0.477 

% Alluvial geology –0.160 –0.141 0.461 0.351 0.207 –0.188 

% Volcanic geology –0.281 –0.079 –0.268 –0.306 0.120 –0.066 

% Cascades Ecoregion –0.294 0.010 –0.226 –0.312 0.059 –0.004 

Month of peak stream flow –0.315 0.009 0.124 –0.020 –0.051 0.180 

Snow index –0.326 0.029 0.100 0.171 –0.081 –0.056 

Elevation –0.329 –0.040 –0.094 0.125 –0.050 –0.104 

Variance 6.81 4.37 1.55 1.14 0.93 0.82 

Cumulative % of total variance 50.2 68.3 79.0 87.0 92.3 95.8 

Cluster analysis based on the first three PCs at the ESU scale generally identified bands 

of watersheds running north to south (Figures D-1 and D-2). The first cluster split eight 

watersheds in the upper Umpqua River Basin off from the rest of the ESU (Figure D-1). The 

next identified cluster consisted of the Salmonberry River in the Nehalem River basin and the 

Upper Siletz River, both systems with predominantly volcanic lithology. The Upper Siuslaw 

River and Elk Creek watersheds, each having a high proportion of area in the Willamette Valley 

ecoregion, formed a third cluster. The next cluster was a group of seventeen watersheds in the 

interior Umpqua River Basin. The remaining watersheds in the ESU along the Pacific Coast 

made up a fifth cluster. 

Cluster analysis at the Umpqua River Basin scale resulted in clusters spanning the fourthfield watersheds in generally north-to-south and low-to-high elevation patterns (Figures D-3 and 

D-4). The three fifth-field watersheds in the portion of the basin closest to the ocean clustered 

together with the west fork of Cow Creek watershed. The next four watersheds to the east form 

another cluster. The next band east runs north to south across the middle of the north Umpqua 

River Basin and the eastern portion of the south Umpqua River Basin, and includes 10 

watersheds mostly within the Klamath Mountains Ecoregion. Those in the extreme eastern 

portion of the basin, toward the headwaters of the north Umpqua River, also clustered together 

within the Cascades Ecoregion and all reflecting the strong influences identified in the first PCs. 

124 
Discussion 

Our analysis indicates that the most influential factors for the ESU overall tended to be 

physiographic, both ecoregion distribution and lithology, while the most influential factors for 

the Umpqua River Basin tended to be climate variables. Throughout the ESU, the watersheds 

tended to be clustered by ecoregion. This is unsurprising given the nature of the ecoregion data 

as a consolidated biogeographic measure that incorporates the effects of climate and geology. 

The first PC for the ESU-level analysis strongly separated the cluster of watersheds in the 

extreme eastern portion of the Umpqua River basin from the rest of the ESU. The first PC for 

the Umpqua River Basin analysis made a similar separation. These watersheds are generally in 

the Cascades ecoregion, tend to have higher elevation, lower mean temperatures, and 

substantially later peak stream flows than the rest of the ESU. These differences are clearly 

identified in the cluster analysis for both the ESU and the Umpqua River Basin, where these 

watersheds (with some variation on the western edge of the group) clustered together before any 

others. This indicates unique environmental conditions in this area. 

The first PC in the ESU-level analysis also identified the influence of two watersheds 

with predominantly volcanic lithology (the Salmonberry River and Upper Siletz River 

watersheds). The Upper Siletz River is not used by coho salmon (ODFW 2003c). Burnett et al. 

(2003) found no areas of high intrinsic potential in either watershed, indicating poor potential for 

supporting coho salmon. 

The clusters identified in the Umpqua Basin clearly identified similarities between the 

watersheds within the North Umpqua River fourth-field basin, as well as within those in the 

South Umpqua River Basin. Again, these watershed clusters strongly reflected ecoregion 

structure, as well as precipitation patterns. When considering the Umpqua River Basin PCA, the 

cluster including the upper Smith River, middle Umpqua River, upper Umpqua River, and Elk 

Creek watersheds includes mostly area in the Coast Range ecoregion but some area in the 

Willamette Valley ecoregion, and is clustered together in part because of their substantially 

lower annual precipitation than the watersheds closer to the Pacific Ocean. 

The strong and consistent cluster patterns in the Umpqua River Basin indicate the 

presence of areas with related environmental conditions, likely influencing habitat attributes in 

ways important to coho salmon. The major ecological differences identified between areas 

within the ESU and particularly the Umpqua River Basin are potentially evidence for isolation of 

populations within the basin and may result in genetic structure over time. 

125 
Figure D-1. Dendrogram showing clustering of the first three principal components for environmental 

data in the Oregon Coast Coho Salmon ESU, using the average distance method of agglomerative 

hierarchical clustering. Each watershed is identified by name and fifth-field watershed 

hydrologic unit code. The shaded boxes on the left identify the shaded clusters in Figure D-2. 

126 
Figure D-2. The first five clusters from cluster analysis of the first three principal components for 

environmental data from the Oregon Coast Coho Salmon ESU. Each cluster is identified by 

shading corresponding to the shading used to identify groups in Figure D-1. These clusters 

resulted from average distance method analysis. 

127 
128 

Figure D-3. Dendrogram of heirarchical clustering of the first three principal components for 

environmental data for watersheds within the Umpqua River Basin. The shaded boxes on the left 

identify the shaded clusters in Figure D-4. This dendrogram shows clusters resulting from the 

average distance method. 
Figure D-4. Clusters of fifth-field watersheds in the Umpuqa River Basin identified by shading corresponding to 

Figure D-3. These are the first five clusters identified in the average distance analysis. 

129 

Most NOAA Technical Memorandums NMFS-NWFSC are available online at the

Northwest Fisheries Science Center web site (http://www.nwfsc.noaa.gov).

NOAA Technical Memorandum NMFS-NWFSC78 Ruckelshaus, M.H., K.P. Currens, W.H. Graeber, R.R. Fuerstenberg, K. Rawson, N.J. Sands, and J.B. 

Scott. 2006. Independent populations of Chinook salmon in Puget Sound. U.S. Dept. Commer., NOAA 

Tech. Memo. NMFS-NWFSC-78, 125 p. NTIS number PB2007-104920.

77 Sloan, C.A., D.W. Brown, G.M. Ylitalo, J. Buzitis, D.P. Herman, D.G. Burrows, G. Yanagida, R.W. 

Pearce, J.L. Bolton, R.H. Boyer, and M.M. Krahn. 2006. Quality assurance plan for analyses of environmental samples for polycyclic aromatic compounds, persistent organic pollutants, fatty acids, stable isotope ratios, 

lipid classes, and metabolites of polycyclic aromatic compounds. U.S. Dept. Commer., NOAA Tech. Memo. 

NMFS-NWFSC-77, 30 p. NTIS number PB2007-104919.

76 Gustafson R.G., J. Drake, M.J. Ford, J.M. Myers, E.E. Holmes, and R.S. Waples. 2006. Status review 

of Cherry Point Pacific herring (Clupea pallasii) and updated status review of the Georgia Basin Pacific 

herring distinct population segment under the Endangered Species Act. U.S. Dept. Commer., NOAA Tech. 

Memo. NMFS-NWFSC-76, 182 p. NTIS number PB2007-104918.

75 Keller, A.A., B.H. Horness, V.J. Tuttle, J.R. Wallace, V.H. Simon, E.L. Fruh, K.L. Bosley, and D.J.

 Kamikawa. 2006. The 2002 U.S. West Coast upper continental slope trawl survey of groundfish resources

 off Washington, Oregon, and California: Estimates of distribution, abundance, and length composition. 

U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-75, 189 p. NTIS PB2006-111432.

74 Pool, S.S., and R.D. Brodeur. 2006. Neustonic mesozooplankton abundance and distribution in the northern California Current, 2000 and 2002. U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-74,

 76 p. NTIS PB2006-109275.

73 Myers, J., C. Busack, D. Rawding, A. Marshall, D. Teel, D.M. Van Doornik, and M.T. Maher. 2006.

 Historical population structure of Pacific salmonids in the Willamette River and lower Columbia River

 basins. U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-73, 311 p. NTIS PB2006-109278.

72 Keller, A.A., E.L. Fruh, K.L. Bosley, D.J. Kamikawa, J.R. Wallace, B.H. Horness, V.H. Simon, and 

V.J. Tuttle. 2006. The 2001 U.S. West Coast upper continental slope trawl survey of groundfish resources 

off Washington, Oregon, and California: Estimates of distribution, abundance, and length composition. U.S.

 Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-72, 175 p. NTIS PB2006-109277

71 Nash, C.E., P.R. Burbridge, and J.K. Volkman (editors). 2005. Guidelines for ecological risk assessment of marine fish aquaculture. U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-71, 90 p. 

NTIS PB2006-109287.

70 Keller A.A., T.L. Wick, E.L. Fruh, K.L. Bosley, D.J. Kamikawa, J.R. Wallace, and B.H. Horness.

 2005. The 2000 U.S. West Coast upper continental slope trawl survey of groundfish resources off

 Washington, Oregon, and California: Estimates of distribution, abundance, and length composition. U.S.

 Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-70, 163 p. NTIS PB2006-109276.

Recent NOAA Technical Memorandums

published by the

Northwest Fisheries Science Center