NOAA Technical Memorandum NMFS-NWFSC-78

U.S. DEPARTMENT OF COMMERCE

National Oceanic and Atmospheric Administration

National Marine Fisheries Service

Independent Populations

of Chinook Salmon

in Puget Sound

July 2006
NOAA Technical Memorandum

NMFS Series

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to time constraints. Documents published in this series may 

be referenced in the scientific and technical literature.

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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:

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.
NOAA Technical Memorandum NMFS-NWFSC-78

U.S. DEPARTMENT OF COMMERCE

National Oceanic and Atmospheric Administration

National Marine Fisheries Service

Independent Populations

of Chinook Salmon

in Puget Sound

Mary H. Ruckelshaus, Kenneth P. Currens1, William H. Graeber2,3, 

Robert R. Fuerstenberg4, Kit Rawson5, Norma J. Sands,

and James B. Scott6

Northwest Fisheries Science Center

Conservation Biology Division

2725 Montlake Boulevard East

Seattle, Washington 98112

1 Northwest Indian Fisheries Commission

6730 Martin Way East

Olympia, Washington 98516

2 Washington Department of Natural Resources

PO Box 47001

Olympia, Washington 98504

3 National Marine Fisheries Service

Regional Office

510 Desmond Drive Southeast, Suite 103

Lacey, Washington 98503

4 King County Department of Natural Resources and Parks

201 South Jackson Street, Suite 700

Seattle, Washington 98104

5 Tulalip Tribes

6700 Totem Beach Road

Tulalip, Washington 98271

6 Washington Department of Fish and Wildlife

600 Capitol Way North

Olympia, Washington 98501

July 2006
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:

National Technical Information Service

5285 Port Royal Road

Springfield, VA 22161

phone orders (1-800-553-6847)

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

ii
Table of Contents 

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

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

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

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

Abbreviations and Acronyms .....................................................................................................................xv

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

Definition of a Population Used in this Approach ....................................................................................1

Structure below and above Population Level............................................................................................3

Conceptual Approach to Identifying Populations.........................................................................................4

Indicators of Population Structure.............................................................................................................4

Geography .............................................................................................................................................4

Migration Rates .....................................................................................................................................4

Genetic Attributes..................................................................................................................................5

Patterns of Life History and Phenotypic Characteristics.......................................................................5

Population Dynamics.............................................................................................................................5

Environmental and Habitat Characteristics ...........................................................................................5

Data Quality ..............................................................................................................................................6

Evaluating Similarity Between Groups.....................................................................................................6

Methods and Results.....................................................................................................................................8

Geographic Distribution of Puget Sound Chinook Salmon ......................................................................8

Direct Observations of Migration..............................................................................................................8

Genetic Attributes ...................................................................................................................................12

Methods...............................................................................................................................................12

Results .................................................................................................................................................14

Patterns in Life History Characteristics...................................................................................................17

Methods...............................................................................................................................................17

Results .................................................................................................................................................19

Spatial Synchrony in Spawner Abundance .............................................................................................22

Habitat Characteristics ............................................................................................................................22

Population Structure Decisions...............................................................................................................22

Genetic Indicators................................................................................................................................25

Life History Indicators.........................................................................................................................26

Migration Indicators............................................................................................................................26

iii
Population Dynamics Indicators.......................................................................................................... 26

Habitat Indicators ................................................................................................................................27

Conclusions.................................................................................................................................................28

Habitats and Fish Outside Primary Spawning Areas: Implications for Recovery Planning.......................32

Naturally Spawning Chinook Salmon not Assigned to an Independent Population ...............................32

Importance of Habitats Outside Watersheds Containing Primary Spawning Areas...............................32

Independent Populations in Puget Sound................................................................................................33

Nooksack River Basin .........................................................................................................................33

Skagit River Basin ...............................................................................................................................36

Stillaguamish River Basin ...................................................................................................................39

Snohomish River Basin .......................................................................................................................41

Central and South Puget Sound ...........................................................................................................44

Lake Washington.................................................................................................................................46

Duwamish/Green River.......................................................................................................................48

Puyallup River .....................................................................................................................................49

Nisqually River....................................................................................................................................51

Hood Canal..........................................................................................................................................53

Strait of Juan de Fuca ..........................................................................................................................57

References...................................................................................................................................................61

Appendix A: Methods and Results for Less Informative Population Indicators ........................................67

Direct Observations of Migration............................................................................................................67

Methods...............................................................................................................................................67

Results .................................................................................................................................................70

Patterns in Life History Characters.........................................................................................................70

Methods...............................................................................................................................................70

Results .................................................................................................................................................74

Spatial Synchrony in Spawner Abundance .............................................................................................76

Methods...............................................................................................................................................76

Results .................................................................................................................................................78

Environmental Effects on Population Synchrony ...................................................................................80

Methods...............................................................................................................................................80

Results .................................................................................................................................................83

Habitat Characteristics ............................................................................................................................83

Identifying Hydrologic Regions in Puget Sound.................................................................................83

Comparisons of Stream Temperature among Puget Sound Chinook Salmon Spawning Areas..........85

EPA Ecoregions...................................................................................................................................88

Geology ...............................................................................................................................................91

Appendix B: Data Tables............................................................................................................................95

iv
List of Figures 

Figure 1. Major Chinook salmon spawning areas in the Puget Sound. .......................................................9

Figure 2. Basin area of rivers in the Puget Sound Chinook Salmon ESU. ................................................11

Figure 3. Relationship between genetic differentiation and geographical distance for groups 

of Puget Sound Chinook salmon.................................................................................................................15

Figure 4. UPGMA dendrogram of genetic similarity of Puget Sound Chinook salmon groups................17

Figure 5. Consensus dendrogram of genetic similarity among Puget Sound Chinook salmon groups. ....18

Figure 6. Multidimensional scaling of genetic similarity of Puget Sound Chinook salmon groups..........19

Figure 7. Similarity of Puget Sound Chinook salmon based on weighted-mean date of spawning 

from different index areas...........................................................................................................................20

Figure 8. Weighted-mean spawning dates for Chinook salmon in Puget Sound index survey areas. .......21

Figure 9. Proposed independent populations of Chinook salmon in the Puget Sound evolutionarily 

significant unit. ...........................................................................................................................................29

Figure A-1. Dispersal curve for Puget Sound Chinook salmon based on coded-wire tag recoveries........74

Figure A-2. Dendrogram of Puget Sound Chinook salmon stocks based on similarity in length 

at age of maturity. .......................................................................................................................................75

Figure A-3. Representative age distributions for Puget Sound Chinook salmon stocks, based on 

scale samples from carcasses on spawning grounds...................................................................................76

Figure A-4. Difference in the temporal correlation in abundance time series from stocks 

of Puget Sound Chinook salmon.................................................................................................................79

Figure A-5. Relationships among Puget Sound Chinook salmon stocks, based on UPGMA 

cluster analysis using temporal correlation in abundance as the similarity measure. .................................81

Figure A-6. Spatial correlogram for spawner abundance in Puget Sound Chinook salmon stocks...........82

Figure A-7. Classification tree used to predict hydrograph type from average basin elevation 

and average annual precipitation.................................................................................................................86

Figure A-8. Runoff-pattern regions in Puget Sound derived from mean basin elevation 

and mean annual precipitation using classification tree analysis................................................................87

Figure A-9. Clustering of Puget Sound Chinook salmon spawning areas based on differences 

in mean temperature during Chinook salmon egg incubation. ...................................................................89

Figure A-10. U.S. Environmental Protection Agency level IV ecoregions in Puget Sound......................90

Figure A-11. Sum of areas for the level IV ecoregions occurring in the Puget Sound ESU. ....................91

Figure A-12. Geology of Puget Sound region using 10 major lithologies from U.S. Geological 

Survey data..................................................................................................................................................92

v
vi
List of Tables 

Table 1. List of putatively extinct populations or spawning aggregations of Chinook salmon 

in Puget Sound. .............................................................................................................................................2

Table 2. Distances separating the spawning grounds of Puget Sound Chinook salmon populations. .......10

Table 3. Data available for analyses of population genetic structure, age at reproduction, 

and spawner abundance. .............................................................................................................................13

Table 4. Estimates of genetic differentiation among major geographical groups of Puget Sound 

Chinook salmon and genetic exchange among spawning aggregations based on 31 allozyme loci...........16

Table 5. Median independence scores based on genetic data for groups of Chinook salmon 

in Puget Sound watersheds. ........................................................................................................................24

Table 6. Summary of losses in Chinook salmon diversity in Puget Sound river and drainage basins. .....30

Table A-1. Distribution of independence scores for each pairwise comparison of streams. .....................68

Table A-2. Straying matrix for Puget Sound Chinook salmon. .................................................................71

Table A-3. Sum of acres for the lithology classes occurring in the Puget Sound ESU. ............................93

Table B-1 Estimates of θ and Nm. .............................................................................................................96

Table B-2. Estimates of time since divergence between sites. ..................................................................98

Table B-3. Cavalli-Sforza and Edwards’ chord distance.........................................................................100

Table B-4. Nei's genetic distance.............................................................................................................102

Table B-5. P values from pairwise G-tests for heterogeneity in allele frequencies at 29 loci. ................104

Table B-6. Absolute differences in the overall mean of yearly weighted mean spawning dates.............106

Table B-7. Dissimilarity matrix for smolt-spawner age distributions......................................................110

Table B-8. Absolute differences in mean spawner length of Puget Sound Chinook salmon...................113

Table B-9. Correlation coefficients on residuals from autoregressive trend model.................................114

Table B-10. Correlation matrix for mean monthly discharge at USGS stream gauges in Puget 

Sound. .......................................................................................................................................................117

Table B-11. Absolute difference in mean temperature during incubation for Chinook salmon in 

Puget Sound. .............................................................................................................................................122

vii
viii
Executive Summary 

In developing a species recovery plan, it is important to delineate the independent 

populations that comprise an evolutionarily significant unit (ESU) listed under the Endangered 

Species Act. In 2000 the Puget Sound Technical Recovery Team (TRT) began work to identify, 

for recovery planning purposes, the populations that historically existed and currently remain 

within the geographic boundaries encompassing the Puget Sound Chinook Salmon ESU. 

The TRT set forth with the goal to distinguish demographically quasi-independent groups 

of Chinook salmon (Oncorhynchus tshawytscha) within Puget Sound. To do this, the team 

analyzed a number of attributes indicating independence among groups of fish and examined the 

degree to which those attributes exhibited biologically significant differences. The TRT 

determined that the following 22 historical populations currently contain Chinook salmon: 

 1) North Fork Nooksack River 

 2) South Fork Nooksack River 

 3) Lower Skagit River 

 4) Upper Skagit River 

 5) Cascade River 

 6) Lower Sauk River 

 7) Upper Sauk River 

 8) Suiattle River 

 9) North Fork Stillaguamish River 

10) South Fork Stillaguamish River 

11) Skykomish River 

12) Snoqualmie River 

13) Sammamish River 

14) Cedar River 

15) Duwamish/Green River 

16) White River 

17) Puyallup River 

18) Nisqually River 

19) Skokomish River 

20) Mid-Hood Canal Rivers 

21) Dungeness River 

22) Elwha River 

Results 

Based on genetic and historical evidence reported in the literature, the TRT determined 

that there were 16 additional spawning aggregations or populations in the Puget Sound Chinook 

Salmon ESU that are now putatively extinct. It was not possible in most cases to determine 

whether these Chinook salmon spawning groups historically represented independent 

populations or were distinct spawning aggregations within larger populations. Regardless of 

ix
their population status, the losses in these 16 spawning aggregations represent important losses in 

ESU diversity, especially among early run Chinook salmon forms. 

Brief descriptions for each population are in the Conclusions section of this technical 

memorandum. The TRT did not assign all Chinook salmon groups spawning naturally in Puget 

Sound streams (WDF et al. 1993) to independent populations for two reasons: 

• First, spawning adults are known to occur intermittently in certain streams—spawning in 

groups of tens to hundreds of fish in some years and none in others. A plausible 

explanation for intermittent occurrence of Chinook salmon in some streams is that those 

adults are part of a larger independent population that uses some spawning habitats only 

during years of high abundance or favorable habitat conditions. The streams that 

intermittently harbor spawning adults could also contain fish from more than one 

independent population, depending on their locations relative to the primary spawning 

areas of independent populations. 

• Second, it is possible that some streams presently containing Chinook salmon never 

supported naturally spawning Chinook salmon historically. In many of these instances, 

the origin of the naturally spawning Chinook salmon present is most likely due to 

returning adults from hatchery production. As more information becomes available, it is 

possible that Chinook salmon in some intermittently used streams can be clearly 

associated with one or more populations. Their assignment will change to reflect their 

association with a particular population. 

Methods 

The TRT defined an independent population following Ricker’s (1972) definition of a 

“stock” as “a group of fish of the same species that spawns in a particular lake or stream (or 

portion thereof) at a particular season and which, to a substantial degree, does not interbreed with 

fish from any other group spawning in a different place or in the same place at a different 

season.” In the context of a viable salmonid population, not interbreeding to a substantial degree 

means that two groups are considered to be independent populations if they are isolated to such 

an extent that exchanges of individuals among populations do not substantially affect the 

population dynamics or extinction risk of the independent populations over a 100-year time 

frame. 

The definitive information needed to identify populations is migration rates between 

groups and their demographic consequences. In practice, information is rarely available about 

salmon straying between streams and the demographic consequences of such straying. 

Consequently, we use different kinds of information, which are proxies for understanding the 

degree of reproductive isolation between Chinook salmon groups. Each type of information 

contributes to our understanding of population boundaries, but none alone provides us with 

complete confidence in our answer. The six indicators of historical population structure used, in 

order of the strength of inference, are: 

1) geographic orientation of groups, 

2) migration rates, 

3) genetic attributes, 

x
4) patterns of life history or phenotypic characteristics, 

5) population dynamics, and 

6) environmental/habitat characteristics. 

Because populations are organized hierarchically, the basic approach to the six proxy 

indicators of reproductive exchange is to identify nested patterns of Chinook salmon groups that 

are more similar to each other than they are to other groups. The TRT distinguished biologically 

significant differences for each attribute among Chinook salmon groups that were judged to 

correspond to population-level independence. The main document describes data analyses and 

summary results for those indicators that were useful in population structure decisions (i.e., 

geography, genetics, and some life history information). The remaining indicators did not 

produce results that were as useful for our population structure decisions for various reasons, 

including irresolvable data quality problems, weak inference, and inconclusive results. The 

analyses for the relatively uninformative indicators are presented in Appendix A. To make final 

population structure decisions, the TRT (with help from others familiar with genetic data) used a 

population independence scoring system to delineate the degree of differences among Chinook 

salmon stocks. The final independence scores provided a summary of the differences among 

Chinook stocks among the key indicators, and thus are the basis for population delineation. 

xi
xii
Acknowledgments 

The authors thank Eric Buhle, Lisa Holsinger, and Tim Beechie for help with data 

analyses and interpretation. Anne Marshall and Craig Busack provided genetic and life history 

data and analyses. The authors are grateful to a number of state and tribal biologists who helped 

provide the most recent data and accurate descriptions of the watersheds. Ned Currens, Jeff 

Dickison, and Bob Hayman offered comments on numerous drafts. Jim Doyle offered valuable 

comments and direction in the early stages of this endeavor. The authors also thank Jeremy 

Davies for his work on the figures. 

xiii
xiv
Abbreviations and Acronyms 

AIC Akaike Information Criterion 

CWT coded-wire tag 

EPA U.S. Environmental Protection Agency 

ESU evolutionarily significant unit 

GDU genetic diversity units 

GIS geographic information system 

ha hectare 

MANOVA molecular analysis of variance 

MDS multidimensional scaling 

Nb harmonic mean of the effective number of breeders per cohort

Ne genetic effective population 

Nm number of migrants

NMFS National Marine Fisheries Service 

NWIFC Northwest Indian Fisheries Commission 

PHYLIP Phylogeny Inference Package 

PSMFC Pacific States Marine Fisheries Commission 

SASSI Salmon and Steelhead Stock Inventory 

SPS southern Puget Sound 

TRT Technical Recovery Team 

UPGMA unweighted pair group method using arithmetic averages 

VSP viable salmonid population 

WDF Washington Department of Fisheries 

WDFW Washington Department of Fish and Wildlife 

USGS U.S. Geological Survey 

xv
xvi
Introduction 

Delineating the independent populations that comprise an evolutionarily significant unit 

(ESU) listed under the Endangered Species Act (ESA) is an important step in developing a 

recovery plan. Populations are the building blocks for recovering many salmon ESUs. 

Understanding the size and spatial extent of populations is critical to viability analyses, which 

are a necessary step in recovery planning and conservation assessments for any species. The 

identification of populations essentially amounts to defining the units in which most 

demographic feedbacks occur, which helps in the development of effective management actions 

designed to improve population status. 

This technical memorandum identifies for recovery planning purposes the populations 

that historically existed within the geographic boundaries encompassing the Puget Sound 

Chinook Salmon ESU. As part of the recovery planning process, the seven-member Puget 

Sound Technical Recovery Team (TRT)1 characterizes each population’s historical and present 

status and identifies viability criteria. The TRT considers these populations when answering the 

question “What are the necessary population characteristics that will provide a high likelihood of 

persistence of the ESU?” 

It is likely that some of the Puget Sound Chinook Salmon ESU’s historical population 

structure was lost or substantially modified within the past 200 years due to human manipulation 

of watersheds and Chinook salmon (Oncorhynchus tshawytscha) populations. Evidence suggests 

that some Chinook salmon stocks in Puget Sound have gone extinct or lost major components of 

their life history diversity (Table 1) (Myers et al. 1998).2

 Although rigorous identification of 

extinct populations is not possible, the existing information is important for recovery planning 

and should be used to guide options for enhancing the ESU’s diversity and persistence, including 

reestablishing populations and recovering the range of historical life history diversity. 

Definition of a Population Used in this Approach 

The definition of a population used in this technical memorandum is in the context of a 

viable salmonid population (VSP) defined by McElhany et al. (2000): 

an independent population of any Pacific salmonid (Oncorhynchus spp.) that 

has a negligible risk of extinction over a 100-year time frame due to threats 

 

1

 The Puget Sound TRT consisted of Mary Ruckelshaus and Norma Sands, Northwest Fisheries Science Center, 

Kenneth Currens, Northwest Indian Fisheries Commission, William Graeber, Washington Department of Natural 

Resources and National Marine Fisheries Service, Robert Fuerstenberg, King County Department of Natural 

Resources and Parks, Kit Rawson, Tulalip Tribes, and James Scott, Washington Department of Fish and Wildlife. 2

 There likely were more historical populations than the 22 identified in this document; the TRT could not determine 

whether most lost aggregations were historically independent populations. 
Table 1. List of putatively extinct populations or spawning aggregations of Chinook salmon in Puget 

Sound. Populations or spawning aggregations are included in this list if they are presumed to be 

extirpated or if introduced populations replaced indigenous populations (based on genetic 

evidence). Locations signify rivers unless otherwise noted. 

Extinct 

spawning aggregation Region Evidence/source 

Late-run Nooksack Strait of Georgia Genetic evidence/Young and Shaklee 2002 

Baker North Puget Sound Smith and Anderson 1921 

Early run Stillaguamish North Puget Sound Nehlsen et al. 1991, WDF et al. 1993 

Early run Snohomish North Puget Sound Nehlsen et al. 1991, WDF et al. 1993 

Late-run Sammamish Central/south Puget Sound Genetic evidence/Marshall et al. 1995,

Marshall 1999 and 2000b 

Early run Duwamish/Green Central/south Puget Sound Nehlsen et al. 1991, WDF et al. 1993 

Late-run White Central/south Puget Sound Shaklee and Young 2003 

Late-run Puyallup Central/south Puget Sound Genetic evidence/Marshall 1999 and 

2000b 

Early run Puyallup Central/south Puget Sound Nehlsen et al. 1991 

Early run Nisqually Central/south Puget Sound Nehlsen et al. 1991 

Late-run Nisqually Central/south Puget Sound Genetic evidence/Marshall et al.1995 

Early run North Fork Hood Canal Smoker 1952, Deschamps 1954, WDF 

Skokomish 1957, Nehlsen et al. 1991, WDF et al. 1993 

Early run South Fork Hood Canal Smoker 1952, Deschamps 1954, WDF 

Skokomish 1957, Nehlsen et al. 1991, WDF et al. 1993 

Late-run Skokomish Hood Canal Genetic evidence/Marshall 1999 and 2000a 

Early run mid-Hood Canal Hood Canal Nehlsen et al. 1991, 

(Hamma Hamma, Marshall 1999 and 2000a 

Duckabush, and Dosewallips) 

Early run Elwha Strait of Juan de Fuca Nehlsen et al. 1991, WDF et al. 1993 

from demographic variation (random or directional), local environmental 

variation, or threats to genetic diversity (random or directional). 

The TRT defines an independent population following Ricker’s (1972) definition of a stock, as 

“a group of fish of the same species that spawns in a particular lake or stream (or portion thereof) 

at a particular season and which, to a substantial degree, does not interbreed with fish from any 

other group spawning in a different place or in the same place at a different season.” Thus in the 

context of a VSP, “not interbreeding to a substantial degree” means that two groups are 

considered to be independent populations if they are isolated to such an extent that exchanges of 

individuals among populations do not substantially affect the population dynamics or extinction 

risk of the independent populations over a 100-year time frame. The exact level of reproductive 

isolation that is required for a population to have substantially independent dynamics is not well 

understood. Theoretical work suggests that substantial independence occurs when a population’s 

migrant proportion is less than about 10% (Hastings 1993). Thus independent populations are 

units for which it is biologically meaningful to examine extinction risks that derive from intrinsic 

factors such as demographic, genetic, or local environmental stochasticity. 

2
Where the TRT used data from other population aggregations or reproductively based 

management units for analyses, the term stock is used to distinguish these groups from the 

populations identified. In the Salmon and Steelhead Stock Inventory (SASSI) (WDF et al. 

1993), for example, Washington state and tribal comanagers also used Ricker’s (1972) definition 

of a stock, but they did not restrict their interpretation of interbreeding to exchanges of 

individuals among the populations that do not substantially affect the population dynamics or 

extinction risk of the independent populations over a 100-year time frame as the TRT did. They 

delineated individual Pacific salmon (Oncorhynchus spp.) stocks based on geographical and 

temporal separation in spawning and distinct biological characteristics (e.g., population gene 

frequencies, return timing, fish size, age structure, etc.) and identified them by the name of the 

river to which they return. For some rivers they identified two different stocks that reflect 

differences in return or run timing, distinctions that have been used for harvest management. For 

example Snohomish summer Chinook salmon are the early returning stocks, whereas Snohomish 

fall Chinook salmon are the late-returning stocks. Although the TRT used the same indicators as 

SASSI and added or updated information to delineate independent populations, our results 

differed slightly because of different definitions. We also did not use the seasonal run timing 

label because of ambiguities in the definition. Where it was necessary to distinguish diversity in 

run timing within a river system, we describe it more generally to avoid confusion with stocks 

identified for different harvest management strategies. 

Structure below and above Population Level 

A population is a group of fish that is reproductively isolated “to a substantial degree.” 

As a criterion for defining groups of fish, the degree of reproductive isolation is a relative 

measure, however, and can vary continuously from the level of pairs of fish to the degree of 

reproductive isolation separating species. The population-level separation defined in this 

document therefore may not reflect the only biologically isolated groups that can be identified. 

For example some Chinook salmon groups may be somewhat reproductively isolated from other 

groups, but not enough to be considered independent by the criteria adopted in this study. The 

TRT considers these groups subpopulations. The existence, distribution, and interactions of 

subpopulations within an independent population have important consequences for viability, 

because they affect population diversity and spatial structure, two of four key parameters for 

evaluating a population’s viability. 

Just as there may be substructuring within a population, there may be structure above the 

level of a population. This is explicitly recognized in the designation of an ESU. An ESU may 

contain multiple populations that are connected by some small degree of migration. Thus 

organisms can be grouped in a hierarchical system where we define the levels of individual, 

subpopulation, population, ESU, and finally species. Other hierarchical systems with more or 

fewer levels could be constructed. Though reproductive isolation forms a continuum, it is 

probably not a smooth continuum, and there exists a biological basis for designating a hierarchy 

of subpopulations, populations, and ESUs. 

3
Conceptual Approach to Identifying Populations 

The TRT’s definition of a population implies that the populations of Chinook salmon 

described in this technical memorandum have been demographically independent for at least 100 

years. In some cases the Chinook salmon currently within the historical geographic boundaries 

of these populations do not represent the genetic legacy of the fish that were present historically 

(e.g., if the fish are an introduced hatchery stock). The TRT’s main objective is to identify 

geographic boundaries of historical populations of Chinook salmon as they relate to current 

populations. Subsequent analyses of introduced populations during the recovery planning 

process will determine what their role should be in recovery. 

Indicators of Population Structure 

The definitive information needed to identify populations is migration rates between 

groups and their demographic consequences. Information about salmon straying between 

streams, and the demographic consequences of such straying, is rarely available. Consequently 

we use different kinds of information that are proxies for understanding the degree of 

reproductive isolation between Chinook salmon groups. Each type of information contributes to 

our understanding of population boundaries, but none alone provides us complete confidence in 

our answer. In the next six subsections, the TRT discusses these information types in order of 

the strength of inference about population structure, everything else being equal, beginning with 

the most powerful. Depending on the quality and availability of the data (Data Quality 

subsection, page 6), however, and the genetic and demographic history of salmon in different 

regions, the usefulness of these indicators varies in any one area. 

Geography 

The geographical boundaries of a salmon population are defined in part by the spatial 

distribution of its spawning habitat. Physical features such as a river basin’s topographical and 

hydrological characteristics dictate, to a large degree, where and when salmon can spawn and 

delimit the spatial area over which a single group of fish can be expected to interact. Geographic 

constraints on population boundaries (e.g., distance between streams) can provide a useful 

starting point from which to closely examine Chinook salmon group attributes within 

circumscribed geographic areas, but geographic constraints generally will not support strong 

inferences at finer scales (e.g., distinguishing separate populations within a small river basin). 

Biogeographic characteristics and historical connections between river basins on geological time 

scales also can be informative in defining population boundaries. 

Migration Rates 

The extent to which adults move between sites affects the degree of reproductive 

isolation and, therefore, demographic independence between sites. Straying estimates (the 

number or percent of fish originating from one location that are found in another) are the primary 

4
available indicator of connectivity between spawning aggregations. Stray rates are particular to a 

group of fish and the season and streams in which they are estimated. Thus stray rates provide 

useful information about straying under those conditions. Unfortunately it is not possible to 

obtain estimates of the magnitude of stray rate variation over long time periods (e.g., 100 years) 

because the data do not exist. In contrast, compared to mark-recapture and other direct estimates 

of straying, indirect estimates, such as genetically based estimates of gene flow or genetic 

exchange, can be used to estimate exchange between Chinook salmon groups integrated over 

longer time periods. 

Genetic Attributes 

Geographical patterns in neutral genetic markers are useful in identifying salmon 

populations, because they indicate the extent of reproductive isolation among groups. Patterns 

can be difficult to interpret, because they may reflect recent introductions, effects of hatchery 

practices, or nonequilibrium conditions. Consequently they should be interpreted with caution. 

Adaptive genetic differences among Chinook salmon groups (as indicated by quantitative traits 

or molecular markers) are more difficult to document than discrete marker differences, but they 

offer good supporting evidence for distinct populations. 

Patterns of Life History and Phenotypic Characteristics 

Phenotypic variation can be used as a proxy for two reasons. First, many phenotypic 

differences are based partially on underlying genetic variation (rather than environmentally 

induced variation), and geographical patterns in these traits can be informative in identifying 

populations (defined by reproductive isolation and demographic independence). Second, 

phenotypic differences may indicate different selective environments experienced by salmon in 

different streams that could have led to adaptive differences and restricted exchange among 

populations. 

Population Dynamics 

Abundance data can be used to explore the degree to which demographic trajectories of 

two groups of Chinook salmon are independent of each other. All else being equal, the less 

correlated time series of abundance are between two Chinook salmon groups, the less likely the 

groups are to be part of the same population. Complicating the interpretation of correlations in 

abundance between Chinook salmon groups is the potentially confounding influence of 

correlated environmental characteristics that affect abundance. When Chinook salmon groups 

that are in close proximity are not correlated in abundance over time, it is likely that they are not 

linked demographically. The reverse is not always the case. Thus when correlations in 

abundance between Chinook salmon groups are detected, more work is needed to rule out 

confounding sources of correlation. 

Environmental and Habitat Characteristics 

The collective biotic and abiotic characteristics of occupied salmonid habitat can help 

define populations, because those ecological characteristics constitute the selective environment 

in which the salmon exist. Differences in these selective environments could have led to 

adaptive differences or restricted exchange among populations. The relative strength of 

5
inference for these characteristics is weak, because we generally do not know which 

environmental variables influence fitness or whether those effects will be observed at the 

population level. If different salmon groups experience different selective environments and 

there is very little migration between those environments, we expect those groups’ phenotypic 

characteristics to diverge. 

Data Quality 

An important first step in analyzing and interpreting any population structure indicator is 

to carefully screen the data and information for potential sources of error or bias. To minimize 

such error, the TRT consulted with biologists familiar with adult and juvenile sampling methods 

and calculations used to expand from index counts to total abundance estimates for each stream 

before using the data in analyses. Wherever possible (e.g., to calculate abundance trends), index 

counts are used in lieu of expansions in order to minimize errors or bias due to spatial variation 

in expansion methods (e.g., Smith and Castle 1994). Coded-wire tag (CWT) expansion methods 

are variable in different streams and years, for example. In cases where fish survey methods are 

unreliable or expansion methods are undocumented or inconsistent over time, data were not used 

in analyses. In many instances juvenile and adult counts include an unknown mixture of 

naturally produced fish and first-generation hatchery fish. Abundance measures used in these 

analyses refer to estimates of naturally spawning adults. 

Genetic data can be rendered uninformative for population structure considerations if a 

stream contains nonnative, hatchery-origin fish that cannot be easily separated in a sample. 

Wherever possible the TRT uses the history of stock transfers and broodstock origin to determine 

whether a genetic sample from a stream would be indicative of the genetic makeup of native fish. 

Even if the existing fish in a particular stream were not native, estimates of their genetic 

similarity to fish in other streams can be informative in determining migration estimates if the 

length of time the nonnative stock has been present in the stream can be estimated. 

Evaluating Similarity Between Groups 

Because populations are organized hierarchically, the basic approach in using the proxy 

indicators of reproductive exchange is to identify nested patterns of Chinook salmon groups that 

are more similar to each other than they are to other groups. However this requires making 

difficult decisions about how similar fish must be before they are considered part of the same 

independent population, which is not a simple statistical exercise. For example, with advances in 

genetic markers, individual differences between fish can be statistically significant even though 

the different fish are not different populations. The TRT’s goal is to distinguish biologically 

significant differences for each attribute among groups of Chinook salmon that the team believes 

would correspond to population-level independence. In general, for conservation and recovery 

applications, it is appropriate to assume that two Chinook salmon groups are independent unless 

the data indicate they should be combined into a single group. This approach errs on the side of 

conserving diversity that might otherwise be lost if a distinct group of fish is incorrectly lumped 

with a larger group. 

The challenge in interpreting the results of statistical analyses is to decide how the 

biological differences and statistical significance can be used to inform decisions about 

6
demographic independence. For example studies of the adaptive significance of phenotypic 

traits can be helpful in determining the magnitude of biological differences that might be 

associated with independent populations. Similarly population genetic theory can be 

instrumental in estimating the genetic consequences of particular migration rates and whether 

those rates are significant enough to indicate that they are the same population. Barring such 

information, however, statistical significance (or the lack of it) is informative for ruling out 

instances in which Chinook salmon groups should not be considered independent. If statistical 

power were adequate to detect differences, two Chinook salmon groups would not be considered 

independent populations if there were no statistically significant differences in attributes between 

them (unless, of course, the data were suspect—e.g., if the data were scarce or likely to be 

affected by the presence of nonlocal hatchery fish). The converse is not true. In some cases the 

TRT combined groups into a single population where there were statistically significant 

differences between the groups for some attributes. Such combinations occurred only when the 

power of the test was great enough to detect significant subpopulations within a population but 

the differences between group attributes were not biologically significant enough to indicate 

independent populations. 

In a few cases reports of current Chinook salmon distribution are greater in spatial extent 

than estimates or reports of historical Chinook salmon distribution. In these instances the TRT 

assumed that the historical distribution was similar to current distribution, unless credible 

biological evidence to the contrary was available. 

The Methods and Results section (page 8) describes data analyses the TRT conducted for 

indicators that were useful in population structure decisions (i.e., geography, genetics, and some 

life history information). At the end of the section we describe how we summarized analyses for 

these indicators and how we determined population structure. The remaining indicators did not 

produce results that were as useful for population structure decisions. Results were relatively 

uninformative for various reasons, including irresolvable data quality problems, weak inference, 

and inconclusive results. The method and results for the relatively uninformative indicators are 

presented in Appendix A (page 67). The TRT presents those results in Appendix A to complete 

the documentation of analyses and to motivate further data collection that may render such 

information more useful in the future. 

7
Methods and Results 

Geographic Distribution of Puget Sound Chinook Salmon 

Chinook salmon in the Puget Sound ESU spawn from Dakota Creek north of the 

Nooksack River in the north, through south Puget Sound, into Hood Canal, and out the Strait of 

Juan de Fuca to the Elwha River (Figure 1). These spawning distributions are relatively well 

known (WDF et al. 1993) compared to information on the location of juvenile rearing areas and 

historical spawning distributions in most basins. 

Disjunct spawning areas can suggest different populations. The TRT measured the 

geographic distances (km) separating spawning areas as the shortest nautical distance separating 

each pair of spawning sampling sites, including the river distance plus the distance between river 

mouths, where applicable (Table 2). Distances were measured using geographic information 

system (GIS) software (ERSI―Seattle, Washington) and a 1:250,000-scale map. 

The theory of island biogeography (MacArthur and Wilson 1967), when applied to 

salmon populations, suggests that a “minimum catchment area” could exist, which defines the 

minimum watershed area needed to support a self-sustaining Chinook salmon population. This 

relationship, if known, could help identify potential historical populations, but it has yet to be 

defined for Chinook salmon. Catchment areas for major Puget Sound river basins vary by an 

order of magnitude (Figure 2). Areas range from more than 600,000 hectares (ha) in the Skagit 

River basin to slightly less than 20,000 ha in the Duckabush River basin. The TRT was not able 

to use such a minimum area criterion for analyses, because it first requires an independent 

assessment of populations, which the team did not have. We calculated catchment area for Puget 

Sound streams containing Chinook salmon using a GIS program and including the entire 

watershed from the river’s mouth upstream to its headwaters. Exceptions are large watersheds, 

such as the Skagit River, which have main channel splits as well as substantial contributing 

tributaries. In these cases calculation of catchment area excluded portions of the watershed 

above major upstream confluences (e.g., the lower Skagit River includes the area from the river’s 

mouth to its confluence with the Sauk River) (Figure 2). The smallest watershed containing 

what the TRT believed to be an independent population (based on multiple lines of evidence) is 

the South Fork Nooksack River (47,700 ha). Whether smaller watersheds can support 

independent populations is not possible to determine with the existing information. 

Direct Observations of Migration 

Some direct observations of straying among Puget Sound Chinook salmon stocks were 

available. Most were based on releases and subsequent recoveries of hatchery Chinook salmon 

marked with CWTs, available in a database maintained by the Pacific States Marine Fisheries 

Commission (PSMFC) (RMPC 1997). The TRT was not able to get good estimates of stray 

8
9

TFigure 1. Major Chinook salmon spawning areas in the Puget Sound. Locations signify rivers unless 

otherwise noted. 
Table 2. Distances (km) separating the spawning grounds of Puget Sound Chinook salmon populations.* Locations signif

otherwise noted. Source: Spawning distributions based on WDF et al. 1993. 

North Fork

Nooksack 

South Fork

Nooksack 

Lower Skagit 

Upper Skagit 

Cascade 

Lower Sauk 

Upper Sauk 

Suiattle 

North Fork

Stillaguamish 

South Fork

Stillaguamish 

Skykomish

Snoqualmie 

Sammamish 

Cedar 

Duwamish/ 

Green 

White 

Puyallup 

Nisqually

Skokomish

Hamma 

North Fork

―

NooksackSouth Fork 5 

―

Nooksack

Lower Ska

git 143 138 ―

Upper Skagit 218 213 13 

―

Cascade 244 239 39 4 ―Lower Sau

k 219 213 14 2 27 ―

Upper Sauk 254 249 48 37 62 7 ―Suiattle 249 244 44 32 58 11 27 ―North Fork 200 195 112 187 213 188 222 218 ―Stillag

uamish

South Fork 178 173 90 165 191 166 201 196 2 ―Stillag

uamish

Sky

komish 251 178 188 171 196 263 206 201 67 45

―

Snoqual

mie 225 220 138 213 238 213 248 243 109 87 22

―

Sam

mamish 226 221 139 213 239 214 249 244 114 92 149 127 ―

Cedar 230 225 143 218 243 218 253 248 118 96 154 131 31 

―

Duwamish/Green 215 210 128 202 228 203 238 233 103 81 137 116 41 46 

―

White 270 265 182 257 283 258 292 288 158 136 129 171 96 100 65

―

Puyallup 268 263 181 256 281 256 291 286 156 134 190 170 95 99 64 0.1 ―Nisqually 273 268 187 262 288 263 298 293 163 141 194 176 101 106 72 64 62

―

Skokomish 251 246 188 263 288 263 298 293 165 143 136 178 149 154 137 191 190 194 ―Ham

ma Ham

ma 226 221 163 238 264 239 274 269 141 119 112 154 125 129 112 167 165 170 27

Duckabush 213 208 150 225 251 226 261 256 128 106 99 141 112 116 99 154 152 157 41 Dosewallips 209 204 146 221 247 222 256 252 123 101 94 137 107 112 95 150 148 153 46 Du

ngeness 149 109 90 165 190 165 200 195 131 109 139 144 117 122 105 160 158 163 139 

Elwha 171 166 123 198 223 198 233 228 164 142 173 177 151 155 138 193 191 196 173 

* Distances were calculated as the shortest nautical distance separating each pair of spawning sites, including the river distance plus the 

mouths, where applicable. Distances were measured using GIS software and a 1:250,000-scale map. 

10
11

0 100,000 200,000 300,000 400,000 50

Skagit total

Snohomish total Upper Skagit

Puyallup total

Skykomish Lower Skagit

Nooksack total

Nisqually

Stillaguamish total

Snoqualmie

Puyallup (no White)

Duwamish/Green

White

Suiattle

Upper South Fork Skykomish

Elwha

Baker

North Fork Stillaguamish

Upper Sauk

Sammamish South Fork Stillaguamish

North Fork Nooksack

Skokomish

Carbon

Samish Dungeness

South Fork Nooksack

Cascade

Cedar

Chambers Creek

North Fork Skykomish

Pilchuck Creek

Lower Sauk

North Fork Skokomish

Dosewallips

Sultan

South Fork Skokomish

Middle Fork Nooksack

Tolt

Mashel

Hamma Hamma

Duckabush

Area (ha)

Figure 2. Basin area (ha) of rivers in the Puget Sound Chinook Salmon ESU. Total catchment area of river basins from he

of the stream (or to its confluence with another large river) was calculated using GIS-based maps.
rates—the proportion of all fish in a tag group (or from a release site) that are recovered 

somewhere other than their tagging or release site—because methods of estimating the total 

number of returning tagged fish vary among recovery locations and the geographic area sampled 

for strays is not usually designed to estimate straying. Furthermore how well straying patterns of 

hatchery fish reflect those of wild Chinook salmon is not well known. Estimates of straying 

rates based on small-scale experimental studies were available in a few locations. More 

extensive estimates of stray rates of naturally produced; naturally spawning Chinook salmon are 

sorely needed, especially as recovery of populations proceeds. A summary of information 

collected and results for this indicator are reported in Appendix A (page 67). 

Genetic Attributes 

Methods 

The Washington Department of Fish and Wildlife (WDFW) systematically samples 

Chinook salmon from Puget Sound streams for genetic and life history characterizations and has 

developed an extensive database covering multiple broodyears (1980–1996) (Table 3), which it 

provided for these analyses. The TRT used variation at 29 polymorphic allozyme loci to test for 

allele frequency differences among 35 groups of Chinook salmon sampled from Puget Sound 

streams to visualize patterns of genetic differences and to estimate genetic parameters of 

divergence and reproductive exchange. To test for differences in allele frequencies, the team 

used contingency table analyses of log likelihood ratio tests (G-tests) to test the null hypothesis 

that samples were drawn from the same population. Multiple broodyears from a site 

subsequently were combined, because among-site variation was greater than variation among 

broodyears within a site. To visualize patterns of genetic differences, the TRT used cluster 

analysis and multidimensional scaling. Cluster analyses of genetically similar groups of samples 

were based on pairwise estimates of Cavalli-Sforza and Edwards chord genetic distance 

(Cavalli-Sforza and Edwards 1967) and the unweighted pair-group method using arithmetic 

averages (UPGMA) clustering algorithm (Sneath and Sokal 1973) using the CONSENSE 

program in the Phylogeny Inference Package (PHYLIP) software, version 3.5c (Felenstein 

1993). The team examined the robustness of the patterns by bootstrapping the allele frequencies 

for 1,000 iterations and constructing a consensus dendrogram using PHYLIP. The patterns of 

genetic differences also were visualized using multidimensional scaling (Lessa 1990) on the 

matrix of genetic chord distances using XLSTAT software (AddinSoft USA, New York). 

To better understand the biological significance of these patterns, the TRT calculated 

three genetic parameters to estimate population divergence, rate of genetic exchange, and time 

since two groups of Chinook salmon diverged from a common population. The team estimated 

population differentiation, FST, using Weir and Cockerham’s (1984) analog, theta (θ), which is 

based on using molecular analysis of variance (MANOVA) to partition the total genetic variation 

into components among and within groups. Theta equals zero indicates no significant 

differentiation; θ equals one indicates that the two groups have completely fixed genetic 

differences. 

12
Table 3. Data available for analyses of population genetic structure, age at reproduction, and spawner 

abundance. Y = available, ND = not available. Locations signify rivers unless otherwise noted. 

Name of spawning aggregationa Genetics (years) 

Age at 

reproduction Abundanceb

Miscellaneous streams, area 7A (North Puget Sound) ND Y 

North Fork Nooksack spring (hatchery) 1988, 1993 Y ND 

South Fork Nooksack spring 1993–1995, 1998 Y Y 

Samish fall (North Puget Sound) 1986 Y Y 

Lower Skagit fall 1986–1988, 1998 Y Y 

Upper Skagit summer 1986, 1994–1995 Y Y 

Lower Sauk summer 1986 Y Y 

Upper Sauk spring 1986, 1994, 1998 Y Y 

Suiattle spring 1986–1990, 1998 Y Y 

Skagit spring 1990, 1993–1994, Y 

1996 

Upper Cascade spring 1993–1994 Y ND 

North Fork Stillaguamish summer 1987–1988, 1996 Y Y 

South Fork Stillaguamish fall 1992–1996 Y Y 

Snohomish (Skykomish) summer 1988–1989, 1993,1996 Y Y

Snohomish summer (hatchery) 1987–1988, 1996 Y 

Snohomish (Snoqualmie) fall 1988 Y Y 

Wallace (Skykomish) summer/fall 1988–1989 Y Y 

Skykomish summer (hatchery) 1987 Y ND 

Bridal Veil Creek (Skykomish) summer/fall 1987–1988 Y ND 

Sultan fall 1987–1989 

Miscellaneous streams, area 10 (South Sound) ND Y 

Issaquah Creek fall (hatchery) 1992 Y ND 

North Lake Washington (Sammamish) summer/fall 1998 Y Y 

Cedar summer/fall 1993–1994 Y Y 

Duwamish/Green summer/fall (hatchery) 1987–1988, 1990, 1998 Y Y

Newaukum Creek (Green) summer/fall 1992–1993 Y ND 

Puyallup summer/fall (hatchery) 1992–1993 Y Y 

Puyallup (South Prairie Creek) fall 1992–1993 

White spring 1995–1997 Y Y 

White spring (hatchery) 1991–1994 

Nisqually summer/fall 1998–1999 Y Y 

Deschutes summer/fall (hatchery) 1987 Y Y 

Miscellaneous streams, area 13 (South Sound) ND Y 

Miscellaneous streams, area 13A (South Sound) ND Y 

Miscellaneous streams, area 13B (South Sound) ND Y 

Miscellaneous streams, area 10E (South Sound) ND Y 

Skokomish summer/fall 1998 Y Y 

Hood Canal fall (Hoodsport hatchery) 1988 Y 

Hamma Hamma (Hood Canal) summer/fall 1999 Y Y 

Duckabush (Hood Canal) summer/fall ND Y 

Dosewallips (Hood Canal) summer/fall ND Y 

Dungeness summer/fall (hatchery) 1986 ND Y 

Elwha summer/fall (hatchery) 1988, 1991 Y Y 

a Miscellaneous areas and numbers correspond to the map in Figure A-5 (page 81). 

b In some cases data were available but did not meet the TRT’s sample size criteria for inclusion in analyses. 

13
We estimated an indirect measure of gene flow following Slatkin (1985) where: 

θ = 1/(1 + 4Nm) 

Nm is the effective number of migrants per generation. This approximation assumes an infinite 

island population genetic model and that the pattern of allele frequencies among populations is 

due to gene flow (e.g., instead of mutation, selection, or random genetic drift). Extensive 

simulations have shown that the approximation of gene flow using this equation is robust to 

violations of the simplifying assumptions (Slatkin and Barton 1989). Pairwise estimates of 

θ were calculated between all groups within a watershed. 

In identifying populations the TRT was interested in whether divergence times between 

groups are greater or less than 100 years. The team estimated the time since divergence (t) of 

two groups from a common population where: 

t/2Ne = –Ln(1 – θ) (2)

Ne is the genetic effective population size and Ln is the natural logarithm. Under this model the 

two groups are assumed to have diverged from a common ancestral population t generations ago, 

have had no gene flow between them since divergence, have discrete generations, mate randomly 

within groups, and have selectively neutral genetic variation (Weir 1996). 

Although Pacific salmonids do not have discrete generations, Waples (1990) showed that 

this violation is not likely to greatly affect estimates of t over long time periods. Likewise low 

levels of gene flow since divergence, which may have occurred between many populations, are 

likely to result in underestimates of the time since divergence. The TRT estimated pairwise Ne 

between groups where: 

Ne = gNb (3)

g is the mean age at spawning for each group and Nb is the harmonic mean of the effective 

number of breeders per cohort. The team estimated Nb using census data, N, and an Nb/N ratio 

of 0.3, based on values from the literature for a number of salmonid species (Waples 1990, 

Waples et al. 1993, Ford et al. 1999). 

In order to assess the spatial scale of genetic similarity, the TRT examined the association 

between genetic differentiation, θ, and geographic distance separating sampling sites (Figure 3). 

The team tested for a positive association between genetic differentiation and geographic 

distance using a one-tailed Mantel test with 2,000 bootstrap iterations and reduced major axis 

regression (Sokal and Rohlf 1981, Hellberg 1994) using Isolation by Distance (IBD) 1.4 

(Bohonak 2002). 

Results 

Significant differences in allele frequencies among samples from different river basins 

and streams within basins indicated that population differentiation occurred at the geographical 

level of river basins or smaller. The only sample pairs that were not statistically significantly 

different were the Wallace River-Skykomish River, Wallace River-Bridal Veil Creek, and Bridal 

 (1) 

14
Figure 3. Relationship between genetic differentiation and geographical distance for groups of Puget 

Sound Chinook salmon. Open diamonds and closed squares compare samples within and 

between major river basins, respectively. 

Veil Creek-Skykomish River in the Snohomish River basin and the Newaukum Creek-Green 

River comparisons. Genetic differences between aggregations generally increased with 

geographic distance (Mantel Z = 1608.19, P < 0.001) (Figure 3). Distances separating spawning 

aggregations within river basins usually occur at a scale of 120 km or less, whereas distances 

between river basins occur at greater than 100 km, and most river basins are separated by 160 km 

or more. No obvious discontinuities in the distribution of θ existed at this scale, but on average θ

was 0.015, which corresponds to genetic exchange of 17 effective migrants or less per year 

(Table 4). 

Clusters of genetically similar Chinook salmon in Puget Sound streams were consistent 

generally with the spatial configuration of the streams, especially in the northern Puget Sound 

region (Figures 4, 5, and 6). There were six major genetic clusters of Chinook salmon in Puget 

Sound: 

1) Strait of Juan de Fuca, 

2) Nooksack River early run, 

3) Skagit River and North Fork Stillaguamish River, 

4) Snohomish River and South Fork Stillaguamish River, 

15
Table 4. Estimates of genetic differentiation among major geographical groups of Puget Sound Chinook 

salmon (θ) and genetic exchange (Nm) among spawning aggregations (subgroups) based on 31 

allozyme loci. 

Number of 

Group name subgroups θ 

Lower 

confidence 

interval 

Upper 

confidence 

interval Nm 

Puget Sound 35 0.033 0.023 0.046 7 

Nooksack 2 0.017 0.004 0.036 14

Skagit 7 0.006 0.004 0.008 41

Skagit spring 4 0.004 0.003 0.006 62 

Skagit summer/fall 3 0.003 0.000 0.006 83 

Stillaguamish 2 0.023 0.010 0.037 11

Snohomish 7 0.005 0.003 0.009 50

Lake Washington 3 0.006 0.001 0.010 41 

South Sound 6 0.013 0.006 0.024 20 

Hood Canal 2 0.000 –0.003 0.004 –– 

Strait of Juan de Fuca 2 0.014 0.003 0.026 18 

5) Central/southern Puget Sound and Hood Canal late-returning, and 

6) White River early run. 

The bootstrap values for the consensus tree (Figure 5) showed good statistical support for 

the major groups in the dendrogram. The specific relationships between individual aggregations 

within the major groups were less supported, especially in central and south Puget Sound and 

Hood Canal. Lack of definitive relationships in these regions may reflect the extensive history 

and continuing presence of Chinook salmon from hatchery programs. Many south Puget Sound 

and Hood Canal samples are very similar genetically to Chinook salmon from the Green River, 

which have been extensively introduced throughout those areas. Consequently patterns of 

genetic differentiation were not very informative for identifying historical population structure in 

central and south Puget Sound and Hood Canal. 

Average genetic differentiation (θ ) among all groups of Chinook salmon in Puget Sound 

was 0.033, corresponding to an estimated average gene flow between groups of seven effective 

migrants per generation (Table 4). Within major watersheds θ ranged from 0.000 among sites 

sampled in the south Puget Sound and Hood Canal to 0.023 among two stocks within the 

Stillaguamish River basin. In general θ values among stocks within a river basin were less than 

0.02 (Figure 3). 

Estimates of Ne for Puget Sound Chinook salmon groups varied from Ne = 101 for the 

fish in the North Fork Nooksack River to Ne = 7,971 for upper Skagit River fish (mean Ne over 

all groups = 1,320 fish per generation; median Ne = 573). Estimates of t between Chinook 

salmon groups ranged from fewer than zero generations since divergence (for Bridal Veil 

Creek-Skykomish River and Bridal Veil Creek-Wallace River comparisons) to 324 generations 

since divergence for Chinook salmon in the lower Skagit and lower Sauk rivers (Appendix B, 

16
Figure 4. UPGMA dendrogram of genetic similarity of Puget Sound Chinook salmon groups. Locations 

signify rivers unless otherwise noted. Asterisk (*) signifies a release site. 

Table B-2, pages 98–99). Mean t over all pairwise comparisons was 77 generations; median t

was 25. Pairwise estimates of t indicate that roughly half the Chinook salmon groups (12 of 26) 

have been isolated for less than 100 years (assuming a 5-year generation time). As discussed in 

the Population Structure Decisions subsection (page 22), these low estimates of t need to be 

interpreted considering violations of assumptions in the model used to estimate t. For example, 

when low gene flow levels occur that are not demographically significant, the true time since 

divergence is likely to be longer than the estimated time. However high values of t are not likely 

to be misleading, so the pairwise comparisons with t estimates greater than 100 years are more 

reliable. 

Patterns in Life History Characteristics 

Methods 

Similarities in life history or phenotypic characteristics were used as possible indicators 

of genetic relationships among Chinook salmon stocks. In addition examining the spatial pattern 

17
Figure 5. Consensus dendrogram of genetic similarity among Puget Sound Chinook salmon groups. 

Numbers at nodes indicate bootstrap support percentage. Locations signify rivers unless 

otherwise noted. Asterisk (*) signifies a release site. 

of phenotypic variation (such as that exhibited by life history traits) can suggest differences 

among sites in environmental characteristics that could promote adaptive divergence of fish. 

More detailed analyses are needed to determine the adaptive significance of phenotypic 

variation, but in the context of this technical memorandum the TRT considers life history trait 

variation to be qualitatively informative for population identification. Four life history 

characteristics—age at downstream migration, age at spawning, age-specific length, and timing 

of spawning—were analyzed in detail. Only time of spawning was informative for our 

population structure decisions. Summaries of the other life history data are in Appendix A (page 

67). Other life history characteristics were considered but not analyzed in detail. Ocean 

distribution and timing of return to the river basin of origin, in particular, have been used 

extensively to define and manage salmon stocks. Both of these characteristics have been well 

recognized as persistent attributes of Chinook salmon stocks (Williams et al. 1975, Healey 1991, 

Stouder et al. 1997, Meyers et al. 2003). Given other available data, and low power of these 

characteristics as indicators of population differences for Puget Sound Chinook salmon, the TRT 

did not use them. However these characteristics may be informative for further analyses of 

population and ESU persistence. 

18
Figure 6. Multidimensional scaling of genetic similarity of Puget Sound Chinook salmon groups. 

Locations signify rivers unless otherwise noted. Asterisk (*) signifies a release site. 

For the time of spawning analysis the TRT inferred the timing of spawning for Chinook 

salmon from time series of spawner densities (fish per mile) in index surveys conducted annually 

throughout Puget Sound. The team used only years in which at least six surveys were conducted 

and the densities on the first and last survey dates were at most 20% of the maximum density for 

the year. These criteria were intended to select annual time series that provide a reasonable 

estimate of the shape of the timing curve, particularly the tails. Yearly data were standardized to 

remove interannual variation in abundance and averaged over all years to give an average 

relative density curve for each index area. From each curve we calculated a weighted mean date 

of spawning, using the daily-average relative spawner densities as weights. The absolute value 

of the difference between the mean spawning dates was calculated for every pair of index areas 

and used as a dissimilarity matrix in a UPGMA cluster analysis. 

Results 

Cluster analysis based on differences in mean spawning date indicates that there are at 

least three fairly distinct groups, corresponding roughly to early through late August, late August 

through mid-September, and mid-September through late October (Figure 7). These breakpoints, 

however, are not obvious from inspection of the range of mean spawning dates (Figure 8), which 

suggests a more continuous distribution of spawn timing. At a finer level, different index areas 

19
Figure 7. Similarity of Puget Sound Chinook salmon based on weighted-mean date of spawning from 

different index areas. Locations signify rivers unless otherwise noted. 

20
Figure 8. Weighted-mean spawning dates for Chinook salmon in Puget Sound index survey areas. The 

top chart is for the north Puget Sound index areas. The bottom chart is for the south Puget Sound 

index areas. Locations signify rivers unless otherwise noted. 

within a single SASSI stock are sometimes very similar in their spawn timing (e.g., Suiattle 

River tributaries) but not always. In general there is a latitudinal cline in timing with earlier 

spawning in more northerly basins. 

21
Spatial Synchrony in Spawner Abundance 

Examining the patterns of covariation in abundance between Chinook salmon groups can, 

theoretically, indicate the degree to which the groups may be linked by migration. Unfortunately 

there is another reason why fish groups might exhibit similar population dynamics: they may 

experience similar environmental conditions. It is not possible to tease apart these two 

potentially confounding sources of covariation without experimentation. For these reasons (and 

the unknown proportion of hatchery fish in many groups), the results from these analyses were 

only partly informative for population structure decisions. On the whole the relationships among 

stocks suggested by correlations in abundance are not concordant with the pattern suggested by 

geography and genetic similarity (i.e., geographically proximate stocks do not consistently show 

stronger correlations in abundance than geographically distant stocks). The analytical approach 

to quantifying correlations and results from these analyses is reported in Appendix A (page 67). 

Habitat Characteristics 

Patterns of regional habitat characteristics can provide insights into the different selective 

environment fish experience, which may influence population structure. These analyses, which 

provide the weakest inference of population structure, are potentially most useful in areas where 

genetic, abundance, and life history data are not available. The TRT explored differences in 

habitat characteristics that might be correlated with different selective environments, including: 

1) hydrological characteristics of rivers and streams, 

2) water temperatures, 

3) EPA ecoregions, which are defined by a composite of habitat features, and 

4) underlying geological substrate. 

Although differences in habitat characteristics among Puget Sound streams are apparent, the 

biological significance of those differences to Chinook salmon population structure is not 

known. The strength of inference from these results is relatively low, and the team did not rely 

on them heavily in identifying populations. The analytical approaches and results from these 

analyses are in the appendixes. 

Population Structure Decisions 

The six different indicators of population structure that the TRT used (geographical 

distribution, migration, genetic differences, life history differences, spatial synchrony in spawner 

abundance, and environmental differences) have different values for identifying independent 

populations. Recognizing these differences, the team examined the data hierarchically to make 

decisions about population structure. The members made decisions in a stepwise fashion, using 

geography, genetic differentiation, and differences in life history (i.e., spawn timing) as 

indicators of population structure. Although inferences from the other indicators (migration, 

spatial synchrony in spawner abundance, and environmental differences) were too weak to 

identify independent populations, the team used these differences as “weight of the evidence” for 

lending support (or increasing the certainty) to populations identified with geographic, genetic, 

and life history information. 

22
The TRT first examined the geographic distribution of spawners within Puget Sound to 

circumscribe the watersheds considered to be the largest scale at which independent populations 

are likely to occur, using a list of spawning aggregations in Puget Sound derived from 

information in SASSI (Table 2) (WDF et al. 1993). The team began at this level because allele 

frequency differences among aggregations were always significant at the level of major rivers 

entering salt water and analysis of isolation by distance suggested minor levels of genetic 

exchange that were unlikely to affect persistence of independent populations. In south Puget 

Sound and Hood Canal, the team combined smaller watersheds draining directly to Puget Sound 

into a larger geographic area for consideration, usually focused around a large river system. 

Although the members had no formal criteria for a minimum watershed size for Chinook salmon, 

aggregation of these smaller watersheds reflects the general observations that many of them had 

little historical or anecdotal evidence of self-sustaining populations, were much smaller than the 

streams that have been actively managed by state and tribal fishery managers (hereafter referred 

to as comanagers) for natural Chinook salmon production, had lower gradients and flow, and in 

recent times had abundances that were largely influenced by the abundance of hatchery fish 

returning to nearby hatcheries. 

Within each group defined by geographical separation at the largest scale, the TRT 

examined each possible pair of spawning groups for population independence, first using genetic 

data. If the genetic data did not provide strong inference for defining group identities, the team 

then examined life history and other indicator differences to make a decision. To standardize 

population data across indicators, all information for each indicator was summarized in a matrix 

representing the pairwise differences in the data types between all groups within a watershed (see 

Appendix B, pages 95–125). The TRT judged independence in two ways: 

1) For genetic indicators the team relied on expert opinions of the significance of eight 

genetic relatedness metrics. 

2) For the life history indicator the team developed a quantitatively based decision rule to 

decide whether a group was independent. 

In each case the TRT assigned an independence score to each pair of sites within a watershed 

ranging from –4 (groups are part of the same population) to +4 (groups are independent 

populations). Scores ranging between –4 and +4 indicated the degree of difference suggested by 

the data and the level of confidence the scorer had in those data. For example 0 indicated that 

either intermediate differentiation existed between the groups or that their population structures 

were ambiguous from the available information. A positive score indicated that the evidence 

suggested that the two groups were independent populations. Scores of 3 to 4 for the genetic 

indicators (see the following subsection) provide strong support that the two groups were 

independent populations, and no further information was needed. In contrast, when 

independence scores for genetic indicators ranged from 1 to 2, indicating population 

independence but with less confidence, the TRT used life history differences to further inform its 

decisions. For each indicator the team summarized the independence between each pair of sites 

as the median independence score across scorers (with 6–10 scorers per indicator) and the 

distribution of independence scores among scorers (Table 5 and Appendix A, Table A-1, pages 

68–69). 

23
Table 5. Median independence scores (n = 10 scorers) based on genetic data for groups of Chinook 

salmon in Puget Sound watersheds. 

Nooksack River basin 

South Fork Nooksack North Fork Nooksack 

South Fork Nooksack 

North Fork Nooksack 

— 

3 — 

Skagit River basin 

Lower Skagit Upper Skagit Lower Sauk Upper Sauk Suiattle Cascade 

Lower Skagit — 

Upper Skagit 2 — 

Lower Sauk 2 2 — 

Upper Sauk 2 2 2 — 

Suiattle 3 2 2 2 — 

Cascade 3 2 2.5 2 2 —

Stillaguamish River basin 

North Fork Stillaguamish South Fork Stillaguamish 

North Fork Stillaguamish 

South Fork Stillaguamish 

— 

3 — 

Snohomish River basin 

Lower Snohomish Skykomish Sultan Wallace Bridal Veil Creek Snoqualmie

Lower Snohomish — 

Skykomish 0 — 

Sultan (Skykomish) 0 2 — 

Wallace (Skykomish) 0 –2 1 — 

Bridal Veil Creek 

(Skykomish) 0 –2 2 –3 — 

Snoqualmie 0 2 2 1 1 —

Lake Washington 

Cedar North Lake Washington Sammamish Issaquah Creek

Cedar — 

North Lake Washington 0 — 

Sammamish 2 0 — 

Issaquah Creek 2 0 1 —

24
Table 5 continued. Median independence scores (n = 10 scorers) based on genetic data 

for groups of Chinook salmon in Puget Sound watersheds. 

South Puget Sound 

 Duwamish/Green Puyallup White Nisqually Deschutes

Duwamish/Green ― 

Puyallup 1 ― 

White 3 3 ― 

Nisqually 1 2 3 ― 

Deschutes 0 0 0 0 ―

Hood Canal

Skokomish Hamma Hamma Duckabush Dosewallips

Skokomish ― 

Hamma Hamma –1 ― 

Duckabush 0 0 ―

Dosewallips 0 0 0 ―

Strait of Juan de Fuca 

Dungeness Elwha 

Dungeness — 

Elwha 3 —

Genetic Indicators 

Ten geneticists from the WDFW, the Northwest Indian Fisheries Commission (NWIFC), 

and the National Marine Fisheries Service (NMFS) provided independence scores based on the 

same set of analyses (Table 5 and Appendix A, Table A-1, pages 68–69). These analyses were 

as follows: 

• Pairwise P values from log-likelihood ratio tests (G-tests) for significant differences in 

allele frequencies (Appendix B, Table B-5, pages 104–105). 

• Pairwise Cavalli-Sforza and Edwards genetic distances (Appendix B, Table B-3, pages 

100–101). 

• A dendrogram and multidimensional scaling of similarities of Puget Sound Chinook 

salmon based on Cavalli-Sforza and Edwards genetic distance (Figures 4, 5, and 6). 

• Pairwise Nei’s genetic distances (Appendix B, Table B-4, pages 102–103). 

• Dendrogram (figure not shown) of similarities of Puget Sound Chinook salmon based on 

Nei’s genetic distance (data in Appendix B, Table B-4, pages 102–103). 

• Pairwise estimates of θ, a measure of genetic differentiation between groups (Appendix 

B, Table B-1, pages 96–97). 

25
• Pairwise estimates of migrants per generation (Nm) (Appendix B, Table B-1, pages 

96–97). 

• Pairwise estimates of migrants per generation (Nm) (Appendix B, Table B-1, pages 

96–97). 

Analysis of the scoring indicated that P values from G-tests, estimates of θ, and genetic 

istances were most influential in assessing independence. Because of the relatively large 

ample sizes and statistical power of the G-tests, the group of scorers decided that if two fish 

roups were not statistically significantly different, they were unlikely to be in two different 

opulations. However it is possible that a single population could contain two subpopulations 

hat are statistically significantly different from one another in one or more genetic metrics. 

The geneticists also relied on estimates of time since divergence, because any bias in the 

stimates would tend to underestimate the time since divergence. Most of the people scoring 

ifferences between groups indicated that they assigned scores closer to zero in cases where data 

ere ambiguous, rather than using zero scores to indicate intermediate degrees of independence. 

Life History Indicators 

The TRT ranked independence using a decision rule that related the degree of potential 

eproductive overlap (P) based on spawn timing to empirical evidence of reproductive isolation 

mong sympatric populations. The team scored groups as follows: 

• Independent if P is less than 0.01. 

• Likely to be independent if P is less than 0.100. 

• Unsure because of insufficient information if P is greater than 0.100. 

This approach assumes that the degree of temporal overlap between spawning groups is a 

ood estimate of reproductive independence (i.e., spatial distances separating groups and 

ehavioral isolating mechanisms are not included in this estimate). Values of P from sympatric 

roups of winter and summer steelhead (Oncorhynchus mykiss) and summer and fall chum 

almon (O. keta) were used to set threshold values that corresponded to different levels of 

onfidence that the populations were independent (Appendix A, Figure A-1, page 74). 

Migration Indicators 

Estimates of straying from CWT groups were the only direct indicators of migration 

vailable. These data were not designed to address the question of population independence. 

onsequently estimates were only mildly informative. Nevertheless a matrix of straying 

stimates and dispersal curves generated from the CWT database (Table 2 and Appendix A, 

igure A-1, page 74) were helpful in identifying where straying has occurred between sites and 

he distances over which fish traveled to stray. 

Population Dynamics Indicators 

Correlations in the time series of abundance were available for some groups of Chinook 

almon in Puget Sound (Appendix A, Figure A-4, page 79). Because of the potentially 

r

a

g

b

g

s

c

a

C

e

F

t

s

d

s

g

p

t

e

d

w

26
confounding effects of correlated environmental conditions, these analyses were only mildly 

informative. 

Habitat Indicators 

The most informative habitat information for identifying population structure that we 

examined was the correlation in flow from unregulated gauges in Puget Sound rivers. 

Correlations in flow between those gauges in close proximity to spawning aggregations were 

used to score similarity in flow regime between sites (Appendix A, Figure A-8, page 87). Other 

habitat-related characteristics such as temperature during incubation (Appendix A, Figure A-9, 

page 89), EPA ecoregions (Appendix A, Figures A-10 and A-11, pages 90–91), and geological 

characteristics (Appendix A, Figure A-12 and Table A-3, pages 92–93), provided some 

corroborative information. The TRT did not use these indicators to identify independent 

populations, but they did offer support for (or added certainty to) conclusions based on the three 

primary indicators. 

27
Conclusions 

This section lists and describes the extant demographically independent populations of 

Chinook salmon the TRT defined for recovery planning in the Puget Sound Chinook salmon 

ESU (Figure 9) as follows: 

 1) North Fork Nooksack River 

 2) South Fork Nooksack River 

 3) Lower Skagit River 

 4) Upper Skagit River 

 5) Cascade River 

 6) Lower Sauk River 

 7) Upper Sauk River 

 8) Suiattle River 

 9) North Fork Stillaguamish River 

10) South Fork Stillaguamish River 

11) Skykomish River 

12) Snoqualmie River 

13) Sammamish River 

14) Cedar River 

15) Duwamish/Green River 

16) White River 

17) Puyallup River 

18) Nisqually River 

19) Skokomish River 

20) Mid-Hood Canal Rivers 

21) Dungeness River 

22) Elwha River 

In all cases the populations reflect the TRT’s best estimate of the corresponding populations that 

spawned and reared in these streams under historical conditions and that presently contain fish. 

As stated earlier, in some watersheds the fish present do not represent those that were there 

historically. Likewise some watersheds have lost populations and major components of 

historical Chinook salmon diversity that have not been replaced. The potential roles of these 

populations in recovery will be determined in subsequent documents. Table 6 offers a more 

detailed summary of the within-population life history diversity types that likely occurred 

historically within the Puget Sound ESU. The narratives following the populations briefly 

summarize the data and information the TRT has assembled to date. 

28
29

Figure 9. Proposed independent populations of Chinook salmon in the Puget Sound evolutionarily 

significant unit (ESU). Locations signify rivers unless otherwise noted. 
Table 6. Summary of losses in Chinook salmon diversity in Puget Sound river and drainage basins. 

River/ Inddrainage basin Diversity lost Summary findings pop

Nooksack Late run Historical diversity in late run form is no longer extant Nor

Sou

Skagit Baker River Baker River diversity form is no longer extant; no evidence that this Low

form represented an historically independent population Upp

CasLow

Upp

Suia

Stillaguamish Early run Early run diversity form is extinct; not clear whether this form Nor

represented an historically independent population Sou

Main stem Historical and current status are unknown; no evidence that this form

represented an historically independent population 

Snohomish Early run Early run diversity form is extinct; not clear whether this form Sky

represented an historically independent population Sno

Lake Sammamish Basin Historical diversity in Lake Sammamish form is no longer extant SamWashington CedDuwamish/Green Early run Early run diversity form is extinct; not clear whether this form Duw

represented an historically independent population 

Puyallup Early run Early run diversity form is extinct; not clear whether this form Puy

represented an historically independent population Whi

Late-run upper Historical diversity in late run form is no longer extantPuyallup/White 

Nisqually Late run Historical diversity in late run form is no longer extant Nisq

Early run Historical diversity in early run is extinct; not clear whether diversity 

form represented an historically independent population 

30
31

River/ drainage basin Diversity lost Summary findings 

Indpop

Skokomish Late run Historical diversity in late run form is no longer extant Sko

Early run Early run diversity form is no longer extant; not clear whether early run 

diversity form represented one or more historically independent populations 

Mid-Hood Canal Late run Historical diversity in late run form is no longer extant Mid

Early run Early run diversity form is extinct

Dungeness Late run The late- and early run groups currently spawning in the Dungeness Dun

River are part of the historical diversity

Elwha Early run Early run diversity form is extinct; not clear whether this form Elw

represented an historically independent population 

Table 6 continued. Summary of losses in Chinook salmon diversity in Puget Sound river and drainage basins. 
Habitats and Fish Outside Primary Spawning 

Areas: Implications for Recovery Planning 

Naturally Spawning Chinook Salmon not Assigned to an 

Independent Population 

The TRT did not assign all groups of Chinook salmon spawning naturally in Puget Sound 

streams (WDF et al. 1993) to independent populations for two reasons: 

1) Spawning adults are known to occur intermittently in certain streams—spawning in 

groups of tens to hundreds of fish in some years and none in others. A plausible 

explanation for intermittent occurrence of Chinook salmon in some streams is that those 

adults are part of a larger independent population that uses some spawning habitats only 

during years of high abundance or favorable habitat conditions. The streams that 

intermittently harbor spawning adults also could contain fish from more than one 

independent population, depending on their locations relative to the primary spawning 

areas of independent populations. 

2) It is possible that some streams presently containing Chinook salmon never supported 

naturally spawning Chinook salmon historically. In many of these instances, the origin 

of the naturally spawning Chinook salmon present is most likely due to returning adults 

from hatchery production. Some streams may therefore contain Chinook salmon only 

because of the presence of a hatchery or releases of hatchery fish, and these streams 

would not have represented historical Chinook salmon spawning habitat that could 

sustain an independent population. 

As more information becomes available, it is possible that Chinook salmon in some 

intermittently used streams can be clearly associated with one or more populations, and their 

assignment will change to reflect their association with a particular population. For the purposes 

of specifying viable population criteria and evaluating ESU recovery scenarios, Chinook salmon 

occurring in small streams that are not within the geographic boundaries of independent 

populations should be considered possibly to contribute to the population dynamics of 

independent populations in Puget Sound. 

Importance of Habitats Outside Watersheds Containing Primary 

Spawning Areas 

It is important to remember that the geographic boundaries of independent populations 

defined in this technical memorandum focus on spawning habitat and do not include all habitats 

that may be important to population viability or ESU recovery (Figure 9). Habitats used by 

Chinook salmon throughout the life cycle and their potential importance to recovery—including 

those used occasionally by spawning adults—must be identified throughout the Puget Sound 

32
region. For example habitats used by juveniles for freshwater, estuarine, and nearshore rearing 

and foraging typically will not be included in the geographic boundaries of independent 

populations identified in this study. That does not mean that those habitats are unimportant to 

recovery. Many are likely to be critical to the ESU’s viability, as discussed in detail in 

McElhany et al. (2000). The challenge for forthcoming analyses conducted by the TRT and 

others is to identify which habitats are the most important to protect or restore to ensure the 

viability of populations and the ESU. An important step in conducting these analyses is 

identifying which habitats fish occupy throughout their life history and the population origins of 

fish in particular areas. 

Independent Populations in Puget Sound 

Nooksack River Basin 

Chinook salmon in the Nooksack River basin are distinctive from Chinook salmon in the 

rest of Puget Sound in their genetic attributes, life history, and habitat characteristics, indicating 

support for the geographical evidence of independence of these fish. Although some Chinook 

salmon from the Nooksack River basin may sometimes stray into other Puget Sound rivers 

(based on releases from Kendall Creek Hatchery), the low numbers probably have not had a 

significant effect on the population dynamics of other populations. The TRT identified two 

existing independent populations in the Nooksack River basin (The numbering sequence follows 

the list of populations in the Conclusions section, page 28.): 

1) North Fork Nooksack River (including Middle Fork Nooksack River) 

2) South Fork Nooksack River 

The Nooksack River may have lost some of the Chinook salmon diversity that once 

occurred in the basin (Table 1). Historical evidence suggests that a later-returning life history 

occurred in the Nooksack River. Summer and fall Chinook salmon were reported entering the 

river beginning in July, with spawning occurring in mid-September and October, in contrast to 

the remaining populations of Chinook salmon that continue to enter the river beginning in March 

and spawn beginning in mid-August (Williams et al. 1975, WDF et al. 1993). A long history of 

introductions of late-returning fish from other basins, especially from the Green River (Myers et 

al. 1998), has obscured genetic evidence of historical later-returning spawning aggregations. 

The TRT concluded that this life history was part of the historical diversity of Chinook salmon 

within the basin, but the team had insufficient information to determine whether it existed as an 

independent population or as a part of the diversity of another population or other populations. 

Summary of information used in population structure decisions 

Chinook salmon historically had access to spawning areas in the north fork, middle fork, 

south fork, and mainstem of the Nooksack River. A diversion dam eliminated spawning in the 

most of the middle fork, but spawning has continued in the other areas. 

Genetic data showed strong support for independence of early returning Chinook salmon 

from the north and south forks (independence score = 3). Allele frequencies were significantly 

different (P < 0.0000) (Appendix B, Table B-5, pages 104–105). Genetic population 

33
differentiation (θ = 0.024) was one of the largest observed between spawning aggregations 

within a river basin in the Puget Sound; it indicated only 2–3 genetically effective migrants 

exchanged between the two populations annually, which should not significantly affect either 

e. Likewise the genetic distance separating fish from the 

two forks is the second largest in the dendrogram

g 

 and 

north and south forks differs by approxim

t 

Nooksa or 

that 

3

 exist, it was extirpated. Consequently the team used geography and 

ncluding the middle fork in the north fork population 

the north fork to form a single fork of the river, 

wherea

in. 

on 

 

population’s demographic independenc

 for the entire Puget Sound region (Figure 4). 

The estimated time of divergence (t ≈ 28 years), however, is lower than expected and suggests 

that this estimate may be biased downward because 1) there were low levels of gene flow, 2) t

was calculated using recent low effective population sizes, or 3) the divergence is relatively 

recent because of large amounts of genetic drift. Previous analyses (Marshall et al. 1995) also

considered the Chinook salmon in the two Nooksack River forks to be independent, designatin

them as separate genetic diversity units (GDUs), based on genetic differences, geographic 

distribution, and life history. Chinook salmon in the north and south forks are of natural origin 

and the limited influence of hatchery fish in spawning escapements (WDF et al. 1993, Myers et 

al. 1998) would not have affected the data. 

Spatial isolation within the watershed and life history information support the TRT’s

decision on population structure. The primary spawning areas of the two groups of fish are 

separated by at least 10 km. Peak spawning time between fish groups from the main stem

ately two weeks (Figure 8 and Appendix B, Table B-7, 

pages 110–112), with south fork Chinook salmon spawning later on average and over a longer 

time (Figure 8). The differences in spawn timing of Chinook salmon in the two forks may reflec

a mixing of late return, nonindigenous Chinook salmon that now spawn in the south fork with 

the early returning south fork spawning population (see the Data needs and remaining 

uncertainties subsection, page 35). These nonnative, later returning Chinook salmon primarily 

are from the Samish Hatchery broodstock; they were released from several hatcheries within the 

basin. Furthermore the spawn timing information in Figure 8 for the mainstem and North Fork

ck River includes unknown fractions of late- and early returning fish. A third fact

complicating the interpretation of the differences in spawn timing between the two forks is 

survey efforts missed most of the spawning that occurs in July in the north and middle forks.

The TRT had no genetic, life history, or migratory data to determine whether Chinook 

salmon that historically spawned in the middle fork were an independent population. If an 

independent population did

environmental information as rationale for i

for recovery efforts. The middle fork joins 

s the south fork enters the main stem as a tributary lower in the system. The middle and 

north forks are influenced by glacial-origin waters and flow through steep mountainous terra

The TRT had no genetic, life history, or migratory data to determine whether an 

independent population of late-returning Chinook salmon historically existed in the Nooksack 

River. Evidence for an historical population includes historical catch records, which indicate 

that late-returning Chinook salmon existed in the Nooksack River, although these fish may have 

been part of populations with a broader distribution of return timing than exists now. In additi

introduced late-returning fish have become established in the river, which suggests that the 

habitat and opportunity once existed for an historical population. The team concluded that the 

3

 N. Currence, Nooksack Indian Tribe, Natural Resource Dept., Deming, WA. Pers. commun., 23 March 2001. 

34
late-returning life history was part of the historical diversity of Chinook salmon within th

but could not determine whether it constituted an independent population. 

Summary of additional information 

e basin, 

Information about straying is mixed. Genetic data indicate that straying was low in the 

past, but may have increased in recent years. CWT data from 1973 to 1997 (RMPC 1997) 

indicate that some straying has occurred from the Kendall Creek Hatchery on the north fork and 

from the Skookum Creek Hatchery on the south fork, although the data are inadequate to 

quantitatively estimate stray rates. Marshall et al. (1995) concluded that straying between the 

two forks was very low based on mixed CWT recoveries (n = 10 fish from 1984 to 1992). 

ery 

d 

data 

ence (TRT 

ey are subtle relative to 

differences among basins across the Puget Sound region. The two forks occur in different 

he north fork is predominantly dominated by snowmelt, and the south fork is 

dominated by mixed rain and snowmelt (Appendix A, Figure A-8, page 87). Geological 

substra

major uncertainty is whether a separate 

population of later-returning Chinook rically in the Nooksack River. 

Although some information exists about the historical distribution of Chinook salmon in the 

Nooksa the 

 et 

Recent studies suggest much more straying occurs between the forks, although it may reflect 

hatchery releases of early returning north fork fish and late returning Green River fish. Hatch

strays of north fork Chinook salmon have been detected in the South Fork Nooksack River in

recent years, and later returning Chinook strays have been found in north fork and south fork 

spawning areas.4 Young and Shaklee (2002) noted that of the naturally produced juveniles 

migrating from the south fork, 9% were of south fork genetic origin, 7% were of north fork 

genetic origin, and 84% were late-returning fish of predominantly hatchery origin. 

Additional life history information supports the TRT’s decision. Age distributions of 

spawning fish from the two forks are very different. More Chinook salmon from the south fork 

tend to spawn as 5-year-olds. There are slight differences in marine and Puget Sound inlan

water distributions of Chinook salmon from the north and south forks, according to CWT 

(Marshall et al. 1995). Marshall et al. (1995) reported a greater proportion of subyearlings from 

the north fork than the south fork, but more recent analyses do not support that differ

no date). Length at age of maturity of fish from the two streams is not significantly different. 

The north and south forks have habitat differences, but th

hydroregions. T

te in the north fork is distinct from that in the south fork (Appendix A, Figure A-12 and 

Table A-3, pages 92–93). 

Data needs and remaining uncertainties 

As noted in the previous subsections, a 

salmon occurred histo

ck River basin (Norgore and Anderson 1921, Pollock 1932, Williams et al. 1975),

return timing of adults and their spawning distributions is not well known. A long history of 

introductions of late-returning fish from other basins, especially from the Green River (Myers

al. 1998), has obscured genetic evidence of historical population structure in current 

late-spawning aggregations. Microsatellite DNA analysis of late-spawning aggregations and 

wild juveniles show that current spawners typically closely resemble Green River late-returning 

 

4

 N. Currence, Nooksack Indian Tribe, Natural Resource Dept., Deming, WA. Pers. commun., 2 March 2004. 

35
fish, and that they are reproducing successfully in the river (Young and Shaklee 2002). 

Therefore the TRT concluded that the historical late-returning life history is likely genetically 

extinct (Table 1) and that, at this time, there is insufficient information to determine whether the 

lost group was an independent population or diversity associated with the two remaining 

historical populations (Table 6). 

The potential straying of nonnative, late-returning Chinook salmon and its effect on the 

two early returning populations is another critical uncertainty. Although recent studies indicate 

that late-returning fish use habitat in the north fork, south fork, and mainstem of the Nooksack 

River, the extent of hybridization between the late-returning fish and the early returning fish is 

unknown, and how this might influence the trend toward population recovery or extinction of the 

early returning fish is unclear. Information about the origins and geographical and temporal 

distribution of these groups, where they may overlap, and genetic studies of hybridization is 

essential to prevent the extinction of the historical populations. The distribution of juvenile 

rearing areas for Chinook salmon in the Nooksack River basin is poorly understood, although the 

Nooksack Indian Tribe and the Lummi Nation are conducting freshwater and estuarine studies 

that will improve the understanding. 

The extent to which present patterns of genetic distinctness between fish in the north and 

south forks have been influenced by hatchery production is another uncertainty. Hatchery 

production in the south fork stopped in 1993 (Marshall et al. 1995). Likewise the origin of north 

fork fish is ambiguous because of extensive hatchery inputs from the north fork itself and 

releases of hatchery-origin fingerlings throughout the upper north fork (WDF et al. 1993, 

Marshall et al. 1995). In addition recent sampling of outmigrants from the Nooksack River basin 

indicates that naturally produced outmigrants are in very low abundance relative to 

hatchery-produced fish (Conrad and MacKay 2000). Because there currently are no marks on 

hatchery fish in the basin, further genetic testing of natural-origin outmigrants is needed to better 

estimate the fraction of outmigrants that are naturally produced. 

Samish River 

Chinook salmon may have used the Samish River historically because they do so today. 

The TRT has no evidence that an independent population of Chinook salmon existed in the 

Samish River. To evaluate ESU recovery scenarios, Chinook salmon occurring in the Samish 

River are considered a spawning aggregation that possibly contributes to other independent 

populations in north Puget Sound. 

Skagit River Basin 

Chinook salmon in the Skagit River basin occupy a large diverse river drainage. 

Spawning areas are geographically the most removed from other Puget Sound tributaries (Figure 

1 and Table 2). Chinook salmon in the Skagit River basin are somewhat genetically distinct 

from Chinook salmon in other Puget Sound rivers (Figures 4, 5, and 6). Marshall et al. (1995) 

assigned all Skagit and Stillaguamish Chinook salmon stocks to the same GDU, based on life 

history, genetic, and habitat similarities within the Skagit River and Stillaguamish River basins 

(The numbering sequence follows t

is continued from page 33.): 

he list of populations in the Conclusions section, page 28, and 

36
3) Lower Skagit River 

4) Upper Skagit River 

5) Upper Cascade River 

6) Lower Sauk River 

7) 

ce 

ove the 

ion used in population structure decisions 

g 

 by 

a showed moderately strong support for independence of the six populations 

(median independence = 2, Table 6). Allele frequencies were highly significantly different 

(P = 0.

ich the 

8–99). 

e 

uk River and upper and lower Skagit River populations. 

s are 

Upper Sauk River 

8) Suiattle River 

The Skagit River basin may have lost some of the Chinook salmon diversity that on

occurred there. However the loss appears relatively less severe than it has been in other areas of 

the ESU. Historically Chinook salmon used the habitat in the upper Baker River (i.e., ab

present dam site) but apparently not in great numbers (Smith and Anderson 1921). The TRT 

could find no evidence that the upper Baker River supported an independent population of 

Chinook salmon. 

Summary of informat

Geographically different tributaries of the Skagit River have disjunct Chinook salmon 

spawning distributions, except for the mainstem Skagit and lower Sauk rivers, where spawnin

areas adjoin or are in close proximity (Figure 1 and Table 2). For example the early run 

spawning areas currently are separated from the late-run stocks lower in their tributaries

12–16 km of unsuitable spawning habitat (Table 2) (Marshall et al. 1995). 

Genetic dat

000–0.009) (Appendix B, Table B-5, pages 104–105). Genetic differentiation ranged 

from high between the lower Sauk River and Suiattle River and Cascade River populations 

(θ = 0.237–0.376) (Appendix B, Table B-1, pages 96–97) to small between the lower Sauk 

River, upper Sauk River, and lower Skagit River populations (θ = 0.013–0.016). This 

corresponded to 0.1–5 genetically effective migrants per year under the island model, wh

TRT would not expect to affect the demographic independence of the populations. Likewise 

time since divergence ranged from 17 to 313 generations (Appendix B, Table B-2, pages 9

The lower estimates of time since divergence may be biased downward (Appendix B, Table B-1, 

pages 96–97), or they may indicate that independence has not quite lasted 100 years between th

upper Sa

Summary of additional information 

Quantitative estimates of migration rates were not possible and did not inform the TRT’s 

decisions. Data indicate that fish do move among basins, but the demographic consequence

unknown. For example Chinook salmon from the North Fork Stillaguamish River were 

recovered in the upper and lower Skagit River (Table 3; Appendix A, Table A-2, pages 71–73). 

In addition out-of-system Chinook salmon collected at Baker trap in the lower Skagit River 

represented a large proportion of the trap returns, and they came from as far away as Vancouver 

37
Island, British Columbia, Canada.5

 Hatchery-origin, early and late-run Chinook salmon from the 

Skagit River also have been recovered in the Stillaguamish River and Snohomish River basins. 

Likewise, within the Skagit Basin, Chinook salmon stocks reared at Marblemount Hatchery have 

been re

the 

t River 

 but the degree of 

differences in smolt-spawner age distributions did not depend on the stock return times 

(Appen

tion 

he 

covered in the mainstem Skagit River, as well as tributaries such as Illabot Creek, Jordan 

Creek, and the Cascade River (Appendix A, Table A-2, pages 71–73). 

Life history characteristics also showed differences among some populations in the 

Skagit River. Upper and lower Skagit River Chinook salmon had similar lengths, whereas 

three early run populations did not cluster with one another or with late-returning Skagi

populations (Appendix A, Figure A-2, pages 71–73). Age distributions of early returning 

Chinook salmon populations in the Skagit River basin were somewhat distinct,

dix B, Table B-7, pages 110–112). The spawn timing of Suiattle Chinook salmon was 

distinctively earlier than that of the other two early run stocks (Figure 6). Juvenile migration 

patterns derived from scale data suggest that Suiattle River, Cascade River, and upper Sauk 

River Chinook salmon populations also had a relatively high proportion of yearling outmigrants 

(Marshall et al. 1995).

Spatial synchrony in spawner abundance also indicates differences among populations. 

Regardless of the model used to estimate correlations in abundance, the three late-run Skagit 

Basin stocks were always clustered together (Appendix A, Figures A-4 and A-5, pages 79 and 

81). In contrast the two early run stocks for which we have data were very different in 

abundance over time from all other Skagit Basin stocks. In general the influence of hatchery 

stray Chinook salmon on the population dynamics of early run Chinook salmon in the Skagit 

Basin is minimal. 

Differences exist in habitat among spawning aggregations. In the lower Skagit and lower

Sauk rivers, Chinook salmon spawned in the low-precipitation and low-elevation hydroregion; in 

the upper Skagit, Chinook salmon spawned in the low-precipitation and low- and high-eleva

hydroregions. All three early run streams in the Skagit Basin had snowmelt-dominated 

hydrographs (Appendix A, Figure A-8, page 87). The upper Cascade River was in the 

low-precipitation/high-elevation hydroregion, and the upper Sauk and Suiattle rivers were in t

high-precipitation/high-elevation hydroregion. The geology of the three river basins was 

somewhat distinctive. The lower Sauk and lower Skagit rivers had similar lithology, whereas the 

upper Skagit River was somewhat distinctive (Appendix A, Figure A-12 and Table A-3, pages 

92–93). 

Remaining uncertainties and data needs 

More extensive genetic sampling of stocks throughout the Skagit River basin may clarify 

uncertainty in population structure determinations, especially if sampling evenly spans the 

existing spawning areas. The contiguous spawning distribution and genetic differentiation of 

Chinook salmon spawning in the lower Skagit, upper Skagit, and lower Sauk rivers, for example, 

suggest that these groups may be linked demographically. Information about the extent of 

 

5

 B. Hayman, Skagit River System Cooperative, La Connor, WA. Pers. commun., 6 August 2003. 

38
straying among the three late-returning stocks within the Skagit River basin would help interpre

genetic differences. 

t 

e of native origin (WDF et 

al. 1993), the effects of hatchery practices on stock composition are unknown. Interpreting 

historic run 

distinct from Chinook salmon in other major Puget Sound basins and from each other. The 

geograp other 

n 

to 

dwaters were diverted to 

the Skagit River, they flowed into the Stillaguamish River basin (Weisberg and Riedel 1991). 

The TR bering 

on, 

Although Chinook salmon stocks in the Skagit River basin ar

al patterns of population structure from genetic data may be confounded by lateGreen River Chinook salmon at the Skagit hatchery. Likewise broodstock collections for the 

Skagit Hatchery early run Chinook salmon relied on timing differences to separate spring, 

summer, and fall Chinook salmon broodstocks. This was difficult because run-timing 

distributions overlapped (Marshall et al. 1995). Errors in assignment to different stocks during 

culture could have affected inferences of historical patterns of differentiation. 

Although the TRT did not use life history information in the determinations, it provided 

some corroborating evidence of different populations. The genetic and length at age of maturity 

data for lower Sauk River fish were based on one sample year, 1986; so the extent to which these 

data were representative is not known. 

Stillaguamish River Basin 

Chinook salmon in the North and South Fork Stillaguamish River are geographically 

hic distances separating Stillaguamish River Chinook salmon spawning areas from

rivers (Table 2) and their population dynamics indicate that Stillaguamish River Chinook salmo

are not part of a larger population encompassing fish in other river basins. Although different 

Chinook salmon within a river basin generally are genetically more similar to each other than 

populations in other basins, this pattern does not hold true in the Stillaguamish River. North 

Fork Stillaguamish River Chinook salmon were more similar to Skagit River basin fish, and the 

South Fork Stillaguamish River Chinook salmon were most closely allied with Snohomish River 

basin Chinook salmon (Figure 4 and Figure 6). This genetic diversity pattern may reflect a 

complex geological history. Before the Sauk River-Suiattle River hea

T identified two independent populations in the Stillaguamish River (The num

sequence follows the list of populations in the Conclusions section, page 28, and is continued 

from page 37.): 

 9) North Fork Stillaguamish River 

10) South Fork Stillaguamish River 

Although the North and South Fork Stillaguamish River populations remain, the 

Stillaguamish River may have lost some of the Chinook salmon diversity that once occurred in 

the basin (Table 1). Historical evidence suggests that an early returning life history occurred in 

the Stillaguamish River. These fish entered the river beginning in mid-April and spawned 

beginning in mid-August, in contrast to summer north fork and fall south fork Chinook salm

which currently enter the river beginning in mid-June and August, respectively (Williams et al. 

1975, WDF et al. 1993). Between 1966 and 1971, abundances of early returning Chinook 

salmon ranged from 50 to 300 (Williams et al. 1975). The TRT concluded that this life history 

39
was part of the historical diversity of Chinook salmon within the basin, but the team could not 

determine whether it constituted an independent population. 

Summary of information used in population structure decisions 

Genetic data show strong genetic support for two independent Chinook salmon 

populations in the Stillaguamish River (independence score = 3; Table 6). Allele frequencies 

were significantly different (P = 0.000, Appendix B, Table B-5, pages 104–105). Genetic 

differentiation was moderate (θ = 0.51) and corresponded to exchange of approximately one 

genetically effective migrant per year under the island model, which the TRT concluded would 

not be expected to affect the demographic independence of these populations (Appendix B, 

Table B-1, pages 96–97). Estimated time since divergence was 26 generations (Appendix B, 

Table B-2, pages 98–99). Genetically North Fork Stillaguamish River Chinook salmon are more 

similar to Skagit River Chinook salmon than to South Fork Stillaguamish River Chinook salmon, 

which are more similar to Snohomish Basin Chinook salmon (Figure 4). The WDFW concluded 

that North Fork Stillaguamish River Chinook salmon are indigenous, but origins of the South 

Fork Stillaguamish River Chinook salmon were unknown (WDF et al. 1993, Marshall et al. 

1995). 

Summary of additional information 

Quantitative estimates of migration rates were not possible and did not inform our 

decisions. Data indicated that fish do move among basins, but the demographic consequences 

are unknown. Chinook salmon from the North Fork Nooksack River (Kendall Creek Hatchery) 

have been recovered in the North Fork Stillaguamish River. North Fork Stillaguamish River 

Chinook salmon also have been reported in the upper and lower Skagit River and the Snohomish 

River basin (Appendix A, Table A-2, pages 71–73). Within the basin, Chinook salmon reared at 

the Stillaguamish Tribal Hatchery on the North Fork Stillaguamish River have been recovered at 

north fork tributaries such as Boulder River and Squire Creek, but no Chinook salmon from the 

Stillaguamish Tribal Hatchery have been recovered in the south fork. 

Life history differences corroborated genetic patterns of differentiation. Age 

distributions and length at age of maturity of North Fork Stillaguamish River Chinook salmon 

also are more similar to Chinook salmon spawning in the lower portions of the Skagit River 

basin than they are to Chinook salmon in the South Fork Stillaguamish River. Spatial synchrony 

in spawner abundance in the two Stillaguamish River forks is not strongly correlated, although 

statistical power may have been inadequate to detect a significant relationship (Appendix B, 

Table B-9, pages 114–116). 

The habitat characteristics experienced by Chinook salmon in the two forks of the 

Stillaguamish River are similar. The hydrographs are mixed for both streams: in the upper 

reaches of the streams, hydrographs are mixed snowmelt and rainfall, and hydrographs for lower 

river tributaries are rainfall dominated. Both streams are in the low-precipitation and lowelevation hydroregion, although the north fork drains more high-precipitation areas (Appendix 

A, Figure A-8, page 87). Mean incubation temperatures in the two streams are very similar 

(Appendix B, Table B-11, pages 122–125). In contrast each fork is in a different EPA ecoregion 

40
(Appendix A, Figures A-10 and A-11, pages 90–91) and geological characteristics of the two 

forks are different (Appendix A, Figure A-12 and Table A-3, pages 92–93). 

Remaining uncertainties and data needs 

gregations in the 

Stillaguamish Basin are unknown. One is the early returning Chinook salmon in the 

Stillagu

ts that 

versity in life history may have contributed to 

broader geographic and temporal distribution of Chinook salmon originating from this 

watersh

er 

ng 

Chinoo 6). 

n that 

e list 

12)

rical 

The historical and current status of two different spawning ag

amish River. The comanagers did not identify these fish as a distinct stock or describe 

their return timing as a part of the summer or fall stocks (WDF et al. 1993), which sugges

they are no longer present. Nehlsen et al. (1991) described them as extinct. The second group 

whose status is unknown is Chinook salmon spawning in the mainstem Stillaguamish River 

below the forks. The additional historical di

ed, both within the watershed and in marine environments, and may have been an 

important part of the viability of Chinook salmon in the watershed. Further evaluation will be 

needed to understand the roles these spawning aggregations may have or still play in 

Stillaguamish River population viability. 

Although the genetic and life history similarities between North Fork Stillaguamish Riv

Chinook salmon and Skagit River late-run Chinook salmon may reflect common ancient 

ancestry, the genetic origins of the south fork population are less well known. Hatchery 

introductions may have played a role in producing the observed differences. Late-returni

Green River-origin Chinook salmon have been introduced into the south fork (Marshall et al. 

1995, Myers et al. 1998), and their genetic influence is unknown (WDF et al. 1993). 

Snohomish River Basin 

Chinook salmon in the Snohomish River basin are geographically distinct from Chinook 

salmon in other Puget Sound streams (Figure 1 and Table 2). Genetically the Snohomish River 

k salmon form a group that includes the South Fork Stillaguamish (Figures 4, 5, and

Because of their genetic distinctness and the geographic distances separating the nearest 

spawning areas outside of the Snohomish River basin (Table 2), the TRT concluded it was 

unlikely that Chinook salmon in the Snohomish River basin were part of a larger populatio

included Chinook salmon from other rivers in the Puget Sound. The team identified two 

independent populations in the Snohomish River basin (The numbering sequence follows th

of populations in the Conclusions section, page 28, and is continued from page 39.): 

11) Skykomish River 

 Snoqualmie River 

Although the TRT identified at least two independent populations in the Snohomish 

River, an important component of the basin’s diversity may have been lost (Table 1). Histo

evidence suggests that an early returning life history also occurred in the Snohomish River. 

These fish entered the river in May through July and stayed in deep pools before spawning in 

mid-August and September in accessible areas of the North and South Fork Skykomish River 

and possibly the Snoqualmie and Tolt rivers (Williams et al. 1975). These returns occurred at 

different times than current returns to similar areas (WDF et al. 1993). Between 1966 and 1971, 

41
annual abundances of early returning Chinook salmon ranged from 150 to 500 (Williams et al. 

1975). The team concluded that this life history was part of the basin’s historical diversity of 

Chinook salmon, but could not determine whether it constitutes an independent historical 

population. 

Summary of information used in population structure decisions 

Geographically disjunct spawning grounds for Chinook salmon in the Snoqualmie River 

and Skykomish River basins support their delineation as separate populations (Table 2). 

Chinook salmon spawning in the mainstem Snohomish River have continuous distributions wi

those in the Skykomish River, however, which suggests that Snohomish mainstem spawners 

belong in the Skykomish River population. 

Genetic data indicate moderately strong support for considering Skykomish River 

Chinook salmon as a separate population from those spawning in the Snoqualmie River basin 

(genetic independence score = 2) (Table 6). Wallace River and Bridal Veil Creek stocks w

th 

ere 

genetically very similar to each other and to the Skykomish River stock (genetic independence 

ed together within the Skykomish population. 

Allele frequencies between Skykomish River and Snoqualmie River stocks were significantly 

differen

t 

t 

originate from the Wallace River Hatchery (Rawson et al. 2001). Chinook salmon from the 

Tulalip

 found 

s 

ajor Snohomish River basin tributary needs more study. Likewise, 

based o

e 

< 0). Consequently these stocks were includ

t (P = 0.001). Genetic differentiation was low, however (θ = 0.005–0.013), and 

corresponded to exchange of 5–10 genetically effective migrants per year under the island model 

(Appendix B, Table B-1, pages 96–97), although we concluded this would not affect the 

demographic independence of these populations. Time since divergence ranged from 7 to 19 

generations (Appendix B, Table B-2, pages 98–99). This may reflect downward bias in the 

analysis (Appendix B, Table B-1, pages 96–97), or it may indicate that independence lasted no

quite 100 years. 

Summary of additional information 

Quantitative estimates of migration rates were not possible and did not inform our 

decisions. Good documentation exists for straying of Chinook salmon from the Wallace River 

Hatchery. Studies of the distribution of hatchery fish using thermally marked otoliths sugges

that many naturally spawning Chinook salmon in the Skykomish River and its tributaries 

 Hatchery also make up a fraction of the naturally spawning Chinook salmon in the 

Snoqualmie River system, especially Tokul Creek. Wallace River Hatchery fish rarely are

in the Snoqualmie River system. 

Life history differences support the genetic differences. Skykomish River Chinook 

salmon from the Wallace River had a distinct spawner-smolt age distribution from the 

Snoqualmie River Chinook salmon sampled from Tokul Creek (Appendix B, Table B-7, page

110–112). The Snoqualmie River sample is based on a single year of data, so how distinct 

Chinook salmon are in each m

n the available data, little overlap in spawn timing existed among Snohomish River basin

stocks (Figure 8), although the true spawn timing may be later than that depicted in the databas

42
because sampling was uneven across years and throughout the season.6

 In contrast length at age

of maturity data suggest that Bridal Veil Creek and Snoqualmie River Chinook salmon were ver

similar (Appendix A, Figure A-2, page 75), but Walla

y 

ce River, Skykomish River, and Sultan 

River Chinook salmon were in a separate cluster. The distinctive length at age of maturity of 

Bridal Veil Creek and Snoqualmie River Chinook salmon, however, may reflect the small 

number of years of data (2 and 1 years, respectively) included in those samples. 

Differences in spawning and rearing habitat also exist within the Snohomish River basin. 

l 

d demographic relationships of several 

spawning aggregations in addition to the two independent populations the TRT identified. Lack 

of adeq

e 

 the 

er and 

wn. The comanagers did not identify these as a distinct stock or 

describe their return timing as a part of summer or fall stocks (WDF et al. 1993), which suggests 

that the em as 

l 

Chinook salmon in the Pilchuck, Sultan, Snoqualmie, and lower Skykomish rivers spawn in 

streams with rainfall-dominated hydrographs. In contrast Bridal Veil Creek Chinook salmon 

experience a mixed hydrograph that exhibits snowmelt and rainfall peak flows. As a result of 

hydrograph patterns Bridal Veil Creek Chinook salmon spawn in the rainfall or 

snowmelt-transition hydroregion, and all other Snohomish Basin Chinook salmon are in the 

low-precipitation or low-elevation hydroregion (Appendix A, Figure A-8, page 87). Bridal Vei

Creek also occurs in a different EPA ecoregion and has a different lithology (Appendix A, 

Figures A-10 and A-11, pages 90–91; Figure A-12 and Table A-3, pages 92–93). 

Remaining uncertainties and data needs 

More information is needed about genetic an

uate genetic and migration data hampered the team’s ability to identify the population 

structure of Chinook salmon spawning in the lower Snohomish and Pilchuck rivers. Likewis

the relationship of Sultan River aggregations to other Skykomish River or Snoqualmie River 

stocks needs resolution. The Pilchuck River and Sultan River watersheds are smaller than the 

smallest watershed area with an identified independent population in the Puget Sound area, the 

Cedar River (Figure 2). Consequently it is difficult to tell whether the Pilchuck River and Sultan 

River watersheds are big enough to have supported an independent population or subpopulation. 

The best way to classify these fish would be to conduct genetic sampling and analysis from

Pilchuck and lower Snohomish rivers, with concurrent sampling from the Skykomish Riv

Snoqualmie River populations. Samples from the South Fork Stillaguamish River should be 

collected at the same time because of the apparent relationship between this population and 

Snohomish River Chinook salmon populations. 

The historical and current status of early returning Chinook salmon in the Snohomish 

River basin also is unkno

y were no longer present during that assessment. Nehlsen et al. (1991) describe th

extinct. This life history diversity may have contributed to broader geographic and tempora

distribution of Chinook salmon originating from this watershed, within the watershed and in 

marine environments, and it may have contributed to the viability of Chinook salmon in the 

watershed (Table 6). 

The influence of hatchery fish on the population structure in the basin remains unclear. 

The Wallace River stock may have been heavily influenced by introductions, including Green 

 

6

 C. Kraemer, Washington Dept. Fish and Wildlife, Mill Creek, WA. Pers. commun., November 2001. 

43
River fall fish, Skykomish River summer stock, and possibly some wild stocks that strayed in

the river (WDF et al. 1993). In contrast the Snohomish River and Bridal Veil Creek stocks ar

considered to be of native origin (WDF et al. 1993). 

Central and South Puget Sound 

This region includes the Lake Washington (Sammamish River and Cedar River 

watersheds), Duwamish/Green, Puyallup, and Nisqually basins, as well as small, independent 

tributaries to Puget Sound. Extensive human alterations to historical hydrologic connections th

shaped metapopulation structure, dynamic geological histories, and the confounding effects of 

hatchery releases made population identification in this region even more challenging than in 

watersheds to the north. Most existing spawning aggregations are genetically similar and a

to reflect extensive influence of hatchery releases, mostly from the Green River broodstock 

(WDF et al. 1993, Myers et al. 1998). Life history variation also was not very informative for 

identifying population structure. Most Chinook salmon in this region have similar spawn 

timings (Figures 7 and 8; Appendix B, Table B-6, pages 106–109), and few data are available for 

other life history traits. Because genetic and life history data do not provide good evidence of 

historical population structure, to interpret the current genetic and life history patterns the TRT 

relied heavily on information about historical connections between the Lake Washington, Green 

River, Puyallup River, and White River drainages. 

Chinook salmon spawning areas in central and south Puget Sound are geographically 

disjunct from each other and from other Puget Sound river basins (Table 2). Because of the 

geographic separation of the basins, the TRT considered each major basin’s Chinook salmon to 

be distinct and independent from Chinook salmon populations in other major Puget Sound rivers 

(Figure 1). Although humans modified hydrological connections among streams during the past 

century, the geologic history of these watersheds as separate tributaries to Puget Sound suggests 

that Chinook salmon spawning aggregations were historically more geographically isolated from 

one another than they are now. After the glaciers retreated and streams were colonized by 

salmonids from the Columbia River (McPhail and Lindsey 1986) but before the Osceola 

Mudflow (4,800 years ago), Lake Washington and the Green, White, and Puyallup rivers each 

drained independently to an arm of Puget Sound that is now the Kent-Auburn and Puyallup 

valleys. Subsequent episodic volcanic events as recently as 600 years ago disrupted the 

post-glacial morphology of this subbasin and created the geomorphology present at the time of 

European settlement of these watersheds (Crandell 1963, Dragovich et al. 1994, Barnhardt et al. 

1998, Scott et al. 1995). 

The TRT reviewed genetic and historical evidence of independent populations or 

spawning aggregations in small, independent tributaries to south and central Puget Sound 

to 

e 

at 

ppear 

pendent 

Although the TRT did not establish a minimum watershed size that might indicate a 

self-sustaining independent populat

we are 

nt 

(Table 1). The team concluded that Chinook salmon using smaller streams in south and central 

Puget Sound probably did not occur there in large numbers historically and were not inde

populations. 

ion, many of these watersheds are much smaller than those 

confident have supported independent populations. 

It is not obvious to what extent the spawning habitat potential of the small, independe

tributaries in south and central Puget Sound may have contributed to viability of nearby 

44
independent populations and the overall persistence of the ESU. It is possible that Chinook 

salmon spawning in small, independent tributaries of this region are present only beca

relatively recent hatchery releases. Alternatively these smaller streams may have contained 

satellite populations that were never very large historically and that relied on contributions of 

spawning adults in significant numbers during years when self-sustaining, independent 

populations, such as those in the Nisqually or Puyallup rivers, had strong returns (WDF et al. 

1993). It is difficult to test these possibilities with existing data. Recoveries of CWT Chinook 

salmon throughout southern Puget Sound suggest that hatchery Chinook salmon move readily 

within this region (Appendix A, Table A-2, pages 71–73), but the data are inadequate to 

determine how spawning in smaller, independent tributaries was related to population dynamics 

of larger populations. It would be useful to summarize historical records of spawning presence, 

timing, and abundance of Chinook salmon in other south Puget Sound streams in order to 

use of 

estimate their population structure. In addition the extent to which the straying behavior of 

hatchery Chinook salmon reflects behavior of native, naturally spawning fish under historical 

conditions is not known. This same discussion applies to other small, independent tributaries 

throughout Puget Sound. 

Within this region, the TRT identified six independent populations (The numbering 

sequence follows the list of populations in the Conclusions section, page 28, and is continued 

from page 41.): 

13) Sammamish River 

14) Cedar River 

15) Duwamish/Green River 

16) White River 

17) Puyallup River 

18) Nisqually River 

Although the TRT identified six independent populations in this region, important 

components of the basin’s historical diversity may be lost (Table 1). These include early 

returning life histories that no longer are expressed and genetic diversity among late-returning 

populations that was lost due to extensive introductions of nonnative hatchery fish. Early 

returning life histories once occurred in the Green, Nisqually, and potentially the upper Puyallup 

rivers (Williams et al. 1975). Nehlsen et al. (1991) considered these extinct populations. The 

limited data available suggest that these fish returned approximately a month earlier than 

later-returning Chinook salmon and abundances were small. Consequently these fish also might 

have been early returning life histories of a larger population. The TRT concluded that these life 

histories were part of the historical diversity of Chinook salmon within the region, but the team 

could not determine whether they constituted an independent population or independent 

populations. 

In the Puyallup and Nisqually rivers, strong genetic similarities of extant populations to 

Green River Chinook salmon (Figures 4, 5, and 6) suggest that the historical genetic differences 

between the indigenous, late-returning populations were replaced or substantially altered by 

Green River-origin fish, which were extensively released in the region (Myers et al. 1998). 

45
Consequently, although the TRT identifies these watersheds as having independent populations

Chinook salmon in these rivers no longer represent historical populations. Likewise 

late-returning Chinook salmon in the W

, 

hite River, where the extant population is a genetically 

distinct, early returning life history, also are characteristic of Green River-origin Chinook salmon 

(Shakle

as 

er-origin hatchery fish (Table 6). 

he Green River (Table 2). Prior 

ke Washington discharged through the Black River 

r was a tributary to the Black River. It is not clear 

whethe n 

on 

receive e 

e and Young 2003). Consequently these fish may represent: 

• a life history that was a distinct historical population, 

• a later-returning form that was once part of the historical White River population but w

replaced by nonnative Chinook salmon, 

• a part of the historical late-returning Puyallup River population that used the lower White 

River, or 

• recent establishment of the life history in the White River from introductions of Green 

Riv

Lake Washington 

Summary of information used in population structure decisions 

The Lake Washington watershed includes the Sammamish River and Cedar River 

populations. Geographically, spawning areas in the two tributaries are separated by Lake 

Washington and are as distant from each other as they are from t

to construction of the ship canal in 1916, La

into the Duwamish River and the Cedar Rive

r the historical Duwamish River watershed provided more or less geographical separatio

among historical populations. 

Genetic data provide moderately strong support for the current independence of Chinook 

salmon spawning in the Sammamish River basin and the Cedar River (genetic independence 

score = 2) (Table 6). Allele frequencies were significantly different (Appendix B, Table B-5, 

pages 104–105). Genetic divergence was minor (θ = 0.008 to 0.012), corresponding to a genetic 

exchange of 5–8 migrants per year (Appendix B, Table B-1, pages 96–97). Genetic 

differentiation is most likely influenced by extensive use of Green River-origin Chinook salm

in the Sammamish River, which do not occur regularly in the Cedar River. Chinook salmon 

released from Issaquah Hatchery in the Sammamish River were Green River stock (Marshall et 

al. 1995), and naturally spawning Chinook salmon in tributaries to the Sammamish River were 

genetically similar to the hatchery stock (Marshall 2000b). The Cedar River basin has not 

d many hatchery introductions (WDF et al. 1993, Myers et al. 1998), but there is evidenc

that hatchery strays into the Cedar River have occurred in recent years.7

Summary of additional information 

Quantitative migration rate estimates were not possible and did not inform the TRT’s 

decisions. The available data indicate that hatchery Chinook salmon may move between the 

Sammamish River (Issaquah Hatchery) and Duwamish/Green River basins (Appendix A, Table 

 

7

 H. Berge, King County Water and Land Resources, Dept. Natural Resources and Parks, Seattle, WA. Pers. 

commun., 15 March 2005. 

46
A-2, pages 71–73). In addition a few Green River-origin Chinook salmon released from south 

Puget Sound and north Kitsap Peninsula hatcheries have been recovered in the Lake Washington 

drainage and Sammamish River basin. 

Life history variation also was not very informative for estimating population 

independence. Most Chinook salmon in this region have similar spawn timings (Figures 7 and 8; 

Appendix B, Table B-6, pages 106–109), and few data are available for other life history traits. 

Likewise the population dynamics of Chinook salmon in Lake Washington (Sammamish and 

Cedar rivers) and the Duwamish/Green River were closely correlated (Appendix B, Table 

B-9, pages 114–116), but because no straying data support the correlated population dynamics 

within Lake Washington, the abundance correlations were not useful as independent evidence for 

population structure. It is likely that those correlations reflect similar patterns of hatchery 

releases, harvest levels, or other environmental conditions, rather than high rates of demographic 

exchange. 

Although the current Sammamish River population is largely supported by naturally 

spawning hatchery fish, the basin area suggests it had the capacity to support a self-sustaining, 

independent population. The cumulative catchment area of tributaries draining into the 

Sammamish River and from Swamp, North, Bear, Little Bear, and Issaquah creeks is more than 

60,000 ha, which is larger than the smallest watershed containing an independent population in 

the TRT’s analyses (the South Fork Nooksack River, Figure 2). 

Remaining uncertainties and data needs 

The history of hatchery releases in the Sammamish River raises two key uncertainties. 

First, although the TRT identified an historical population associated with this river, the Chinook 

salmon that currently use the watershed likely do not represent the historical population. This 

population is believed to be genetically extinct because of many factors for decline, including an 

extensive history of introductions of Green River-origin hatchery fish (Table 1). The historical 

connection and currently limited gene flow between Lake Washington and the Duwamish/Green 

River Chinook salmon via the Black River also may have limited extensive divergence and may 

have influenced these populations’ similarity to Green River Chinook salmon. The 

characteristics of this historical population are unknown, but it represents a loss of historical 

diversity in this region and in the Puget Sound ESU. Likewise status and potential contributions 

(if any) of lake-spawning Chinook salmon life histories in Lake Washington are unknown. The 

significance of these diversity losses to the ESU’s viability is unknown. 

Better information on stray rates among streams in the Lake Washington area will help 

e 

t to 

interpret the genetic differences the TRT observed. In 2000 the City of Seattle, the WDFW, th

U.S. Fish and Wildlife Service, and the Muckleshoot Indian Tribe began a cooperative effor

mark hatchery fish reared at the Issaquah Hatchery. Preliminary results indicate a high incidence 

of hatchery fish in the natural spawning areas.8 Monitoring marked hatchery fish will help 

determine presence of hatchery fish in the wild. 

 

8

 See footnote 5. 

47
Duwamish/Green River 

Summary of information used in population structure decisions 

The Duwamish/Green River basin contains the Duwamish/Green River population. The 

TRT considers this population independent based on geographic distance from other rivers with 

independent populations (Table 2). Genetic data also provide some support for independence 

from Puyallup River and Nisqually River Chinook salmon (genetic independence score = 1, 

Table 6) and strongly support independence from White River Chinook salmon (genetic 

independence score = 3, Table 6), based on current differentiation patterns. Allele frequencies 

antly different, 

ese levels of differentiation most likely reflect homogenization from 

extensive hatchery introductions

and Nis

ed in 

n. 

d 

y different management actions. The TRT detected few 

correlations in spawner abundance that might indicate demographic associations between the 

ppendix B, Table B-9, pages 114–116). 

Remai

ion of hatchery fish throughout the basin most likely resulted in significant genetic 

changes. The historical and current status of early returning Chinook salmon in the Green River 

also is heir 

itional 

 of 

between the Duwamish/Green River and Puyallup River samples were not signific

but they were significantly different from the Nisqually River and White River Chinook salmon 

(Appendix B, Table B-5, pages 104–105). Genetic differentiation was minor (θ = 0.001 to 

0.026), although the differentiation between White River and Duwamish/Green River Chinook 

salmon was an order of magnitude greater than the others (Appendix B, Table 

B-1, pages 96–97). Th

 of Green River-origin Chinook salmon in the Puyallup River 

qually River watersheds (Myers et al. 1998). 

Summary of additional information 

Quantitative estimates of migration rates were not possible and did not inform the TRT’s 

decisions. A few fish from Grovers Creek on the north Kitsap Peninsula have been recover

the Green River (Appendix A, Table A-2, page 71–73), but stray rates generally are unknow

Life history variation also is not very informative. Most Chinook salmon in this region 

have similar spawn timings (Figures 7 and 8; Appendix B, Table B-6, pages 106–109), an

few data are available for lengths of age at maturity (Appendix A, Figure A-2, page 75), 

smolt-spawner age distributions (Appendix B, Table B-7, pages 110–112) or other life history 

traits. Likewise analysis of spatial synchrony in spawner abundance is not informative, because 

abundance trends are confounded b

Green River and other river systems (A

ning uncertainties and data needs 

The historical characteristics of Green River Chinook salmon are unknown. Although 

Green River-origin Chinook salmon were used as a broodstock in the basin since hatchery

production was established more than a century ago, the long period of fish culture and wide 

distribut

unknown. The comanagers did not identify these as a distinct stock or describe t

return timing as a part of the summer or fall stock (WDF et al. 1993), which suggests that they 

were no longer present in significant numbers during that assessment. However the add

diversity in life history may have contributed to broader geographic and temporal distribution

Chinook salmon originating from this watershed, both within the watershed and in marine 

48
environments. This diversity may have been an important part of Chinook salmon viability in 

the watershed. 

Puyallup River 

Summary of information used in population structure decisions 

The Puyallup River basin includes the Puyallup River and White River populations. The 

TRT used geographic and genetic information to identify these populations. Geographically, 

River are disjunct from other Puget Sound 

populat

 2). 

 passage 

d 

es 

0, 

extensive hatchery introductions of Green River-origin Chinook 

ers et al. 1998). Genetically Puyallup River 

Chinook salmon are very similar to Green River Chinook salmon (Figures 4, 5, and 6; Appendix 

B, Tabl and 

gan 

’s 

ovement has been 

reporte

Chinook salmon spawning areas in the Puyallup 

ions. The closest river drainages containing independent populations, the 

Duwamish/Green River and Nisqually River, are 83 km and 60 km away, respectively (Table

Recent modifications to the river’s physical configuration, water management, and fish

regimes, however, disrupted access to habitat in the White River and Puyallup River basins an

may have led to current patterns of habitat utilization that differ from historical distributions 

(WDFW et al. 1996). 

Genetic data also support independence from Duwamish/Green River and Nisqually 

River Chinook salmon (genetic independence score = 1, Table 6) and strongly support 

independence between the Puyallup River and White River Chinook salmon (genetic 

independence score = 3, Table 6), based on current patterns of differentiation. Allele frequenci

are significantly different between Puyallup River and White River Chinook salmon (P = 0.00

Appendix Table B-5, pages 104–105). Genetic differentiation is minor (θ = 0.019), which 

corresponds to genetic exchange of 2–3 migrants per year (Appendix B, Table B-1, pages 

96–97). These current differentiation levels most likely do not completely reflect historical 

patterns, however, because of 

salmon in the Puyallup River watershed (My

es B-1, pages 96–97, and B-5, pages 104–105). The White River early run hatchery

wild genetic samples are very similar, reflecting the effects of the broodstock program that be

in the 1970s (WDFW et al. 1996). 

Summary of additional information 

Quantitative estimates of migration rates were not possible and did not inform the TRT

decisions. CWT Chinook salmon reared at the White River Hatchery have been recovered in 

Puyallup River tributaries, such as Voights and South Prairie creeks. Fish movement has been 

recorded between the Puyallup River and Green River basins, but no m

d between the Puyallup River and Nisqually River basins (Appendix A, Table A-1, page

68-69). 

Life history differences support genetic and geographical evidence of different 

populations. White River Chinook salmon return earlier, beginning in late May, than Puyallup 

River Chinook salmon, which begin entering the river in late July (WDF et al. 1993). 

Length at age of maturity for White River Chinook salmon is different from Puyallup River 

Chinook salmon (Appendix A, Figure A-2, page 75; Appendix B, Table B-8, page 113). Age 

distributions of White River Chinook salmon (hatchery and wild) are similar to those of the 

49
Puyallup Hatchery Chinook salmon, although Chinook salmon from South Prairie Creek in the 

Puyallup River are slightly different in their age distributions (TRT no date). Mean spawning 

dates of Puyallup River and White River Chinook salmon are similar (Figure 8). 

Spawner abundances of White River and Puyallup River aggregations were not correlated 

with other stocks (Appendix A, Figures A-4 and A-5, pages 79 and 81; Appendix B, Table B-9, 

pages 114–116), but this is not necessarily strong evidence of population independence. The 

population dynamics of both populations were influenced by hatchery programs and 

environmental alterations to the rivers. 

Habitat differences support genetic and geographical evidence of different populations. 

White River early run Chinook salmon spawn in a mixed snowmelt and rainfall-dominated 

river, whereas the Puyallup River is at a lower elevation and its hydrograph is mostly 

rainfall-dominated (Appendix A, Figure A-8, page 87). Based on their historical distribution 

above the Buckley trap, in the past an even greater proportion of White River Chinook salmon 

spawning areas would have been in the snowmelt transition hydroregion. Furthermore the 

dynamic and high glacial sediment load of the historical lower White and Stuck rivers (Crandell 

1963, Mullineaux 1970, Salo and Jagielo 2003) probably rendered those areas inhospitable to 

spawning. These areas may have served to maintain separation between spawning aggregations 

that existed in the independent drainages prior to the Osceola Mudflow. Not surprisingly, 

incubation temperatures in the Puyallup River are variable but differ from temperatures in the 

ne. 

on of 

spawning or rearing Chinook salm

e 

er 

White River (Appendix A and Table B-11, pages 122–125). The Chinook salmon spawning 

areas in the White and Puyallup rivers also occur in different EPA ecoregions (Appendix A, 

Figure A-10, page 90) and have different lithology (Appendix A, Figure A-12 and Table A-3, 

pages 92–93). 

Remaining uncertainties and data needs 

The inability to reconstruct historical patterns of genetic similarity among Chinook 

salmon because of extensive Green River-origin hatchery transfers is problematic. The TRT 

concluded that late-returning Chinook salmon in the Puyallup River were historically an 

independent population, although the existing population does not represent the historical o

To verify our conclusions, we need better data on straying, homing, and historical distributi

on in smaller tributaries throughout south Puget Sound, 

including utilization of smaller, independent marine tributaries (e.g., Garrison and Chambers 

creeks). Also needed are CWT and genetic information to determine hatchery influence on th

naturally spawning population (WDF et al. 1993). 

The historical and current status of early returning Chinook salmon that used the upp

Puyallup River (Williams et al. 1975) are unknown. Nehlsen et al. (1991) considered this 

population extinct. The comanagers did not identify these as a distinct stock or describe their 

return timing as a part of the summer or fall stock (WDF et al. 1993), which suggests that they 

were no longer present in significant numbers during that assessment. The TRT lacks 

information to determine whether these are either an independent population or part of a broader

return timing of the historical population. 

50
The origins of late-returning Chinook salmon in the White River also are uncertain. 

Genetic evidence indicates that the extant population is characteristic of Green River-origin 

Chinook salmon and genetically distinct from the early returning White River population 

 may represent:

•

ic and 

lmon in 

qually River 

Summ

may have been an independent population 

from the Chinook salmon spawning throughout the rest of central and south Puget Sound (Figure 

1, Tabl

s. 

993), 

(Shaklee and Young 2003). These fish

a life history form that was a distinct historical population, 

• a late-returning form that was once part of the historical White River population but was 

replaced by nonnative Chinook salmon, 

• a part of the historical late-returning Puyallup population that used the lower White 

River, or 

• recent establishment of the life history in the White River from introductions of Green 

River-origin hatchery fish. 

The effects of disruptions to habitats and fisheries on the spatial and temporal distribution 

of salmon in the Puyallup Basin are unclear. Alterations in flow, temperature, fish passage, and 

harvest management strategies probably altered utilization relative to historical distribution 

patterns. This makes reconstructing historical patterns difficult. The additional life history 

diversity within the Puyallup River watershed may have contributed to broader geograph

temporal distribution of Chinook salmon from this watershed, both within the watershed and in

marine environments, and may have been an important part of the viability of Chinook sa

the watershed. 

Nis

ary of information used in population structure decisions 

The Nisqually River basin contains the Nisqually River Chinook salmon population. The

geographic location of spawning grounds within the Nisqually River basin suggest that, 

historically, Chinook salmon in the Nisqually River 

e 2). The closest river drainages containing independent populations, the 

Duwamish/Green and Puyallup rivers, are 60 km and 70 km away, respectively (Table 2). 

Genetic data also provide moderate support for independence of the Nisqually River 

Chinook salmon from White River, Puyallup River, and Duwamish/Green River populations 

(median genetic independence score = 2, Table 6), based on current differentiation pattern

Allele frequencies are significantly different (P = 0.000–0.026) (Appendix A and Table B-5, 

pages 104–105). Genetic differentiation is minor (θ = 0.002–0.019), which corresponds to 

genetic exchange of 3–40 migrants per year (Appendix B, Table B-1, pages 96–97). These 

patterns of differentiation and exchange most likely reflect extensive hatchery introductions of 

Green River-origin Chinook salmon in the Nisqually River (Myers et al. 1998, WDF et al. 1

which interbred with or replaced the historical population. Genetically Nisqually River Chinook 

salmon are very similar to Green River Chinook salmon (Figure 3; Appendix B, Table B-1, 

pages 96–97; Table B-5, pages 104–105) (Marshall 1999 and 2000b). Evidence that Nisqually 

River Chinook salmon evolved differently from the Puyallup River, which also has received 

51
large introductions of Green River-origin Chinook salmon (Appendix B, Table B-1, pages 

96–97) suggests that Nisqually River Chinook salmon are demographically independent. 

Summary of additional information 

Quantitative estimates of migration rates were not possible and did not inform the TRT’s 

decisions. Life history data also were not informative for reconstructing historical population 

structure. Chinook salmon in the Nisqually River have the same general life history traits of 

s of 

y River Chinook salmon were not correlated with other stocks (Appendix A, Figures 

A-4 and A-5, pages 79 and 81; Appendix B, Table B-9, pages 114–116), which might suggest 

natural lation 

haracteristics of Nisqually River Chinook salmon are unknown. 

Histori , 

among streams would be useful to verify our conclusions of independence and 

to determ

ed the 

Nisqually River is unknown. Sm

closely sts on 

n 

n that 

rshed and in 

other late-returning Chinook salmon in central and south Puget Sound. Spawner abundance

Nisquall

 demographic independence, but this evidence is not necessarily strong. The popu

dynamics of Nisqually River Chinook salmon have been influenced by hatchery programs, 

environmental alterations to the river, and fishery management regimes. 

Three dams on the Nisqually River restrict the present distribution of Chinook 

salmon from their historical spawning areas and have altered flow regimes in the river. Over a 

large scale, however, habitat differences are similar to other central and south Puget Sound 

streams except the White River. Nisqually River Chinook salmon experience the same 

rainfall-dominated hydroregion and lithology (Appendix A, Figures A-8, page 87, and Figure 

A-12 and Table A-3, pages 92–93), although the Nisqually River lies in a different EPA 

ecoregion (Appendix A, Figure A-9, page 89). 

Remaining uncertainties and data needs 

The historical c

cal returns and distributions to the basin were affected by construction of dams, fishing

and the introduction of nonnative hatchery fish. Better data on movement of wild and hatchery

Chinook salmon 

ine hatchery influence on this population. 

The historical and current status of early returning Chinook salmon that us

oker (1952) noted that historical peak harvest, which is usually 

 correlated with entry timing, occurred more than a month earlier than current harve

naturalized, nonnative, Green River-origin Chinook salmon, which begin entering the river in 

early July (Williams et al. 1975). Current entry timing also corresponds to the lowest flows in 

the historical hydrograph (which are now controlled by flow regulation), suggesting that 

historical entry timing must have been different. Nehlsen et al. (1991) considered this populatio

extinct. The TRT lacked information to determine whether these early returning fish were a 

distinct independent population or part of a broader return timing of the historical populatio

has since been lost. Before dams limited the distribution of Chinook salmon and altered river 

flows, this life history diversity may have contributed to broader geographic and temporal 

distribution of Chinook salmon originating from this watershed, both within the wate

marine environments, and it may have been an important part of the viability of Chinook salmon

in the watershed. 

52
Hood Canal 

Hood Canal streams are geographically isolated from other streams in the Puget Sound 

ESU (Figure 1). The two closest river basins to the Dosewallips River (the northernmost 

omish and Dungeness 

rivers, which are 97 km and 103 km away, respectively (Table 2). The Skokomish River is even 

farther 

l. 

e 

A 

lips, Duckabush, and Hamma Hamma) 

m 

d 

tories 

6) 

primary spawning aggregation identified in Hood Canal) are the Snoh

from streams in other regions. Because of the geographic isolation of the Hood Canal 

streams, the TRT concluded that Chinook salmon spawning historically in Hood Canal streams 

were independent populations from other Chinook salmon spawning aggregations in Puget

Sound. 

Within Hood Canal, Chinook salmon spawn in the Skokomish, Hamma Hamma, 

Duckabush, and Dosewallips rivers, which drain the Olympic Mountains to the west and which 

are larger, steeper, and deeper than streams to the east. On the eastern shore, Chinook salmon 

use the Tahuya, Union, and Dewatto rivers in limited numbers (Williams et al. 1975, WDF et a

1993). Identifying historical independent populations within Hood Canal from these extant 

spawning aggregations is problematic because of early alterations to habitat, fish passage, and 

fisheries; limited historical and life history data; and introductions of nonnative hatchery fish, 

which likely confounded genetic patterns. Genetically most of this region’s present spawning 

aggregations are similar and appear to reflect the extensive influence of hatchery releases in th

region, mostly from the Green River broodstock (Figures 4, 5, and 6) (WDF et al. 1993, Myers et 

al. 1998, Marshall 1999 and 2000b). Nevertheless the TRT used information on historical 

distributions and life histories to identify at least two independent anadromous populations. 

nonanadromous extant aggregation of unknown age and origin also occurs in Lake Cushman in 

the Skokomish River. 

The TRT identified two independent populations within this region. (The numbering 

sequence follows the list of populations in the Conclusions section, page 28, and is continued

from page 45.): 

19) Skokomish River 

20) Mid-Hood Canal Rivers (Dosewal

Although the TRT identified two independent populations in this region, the tea

concluded that extensive diversity of the historical Skokomish River population or populations 

has been lost. These losses include early returning life histories that no longer are expressed, an

genetic diversity that was lost due to extensive introductions of nonnative hatchery fish. Early 

reports on salmonid use of Hood Canal streams documented early returning life histories in the

Skokomish, Dosewallips, Duckabush, and Hamma Hamma rivers and late-returning life his

in the Skokomish River (Royal 1932, Smoker 1952, Deschamps 1954, WDF 1957). More

recently, Williams et al. (1975) noted the historical occurrence of early returning life histories 

and reported late-returning life histories in the Dosewallips, Duckabush, and Hamma Hamma 

rivers; however, whether these fish represented historical population components or 

introductions of nonnative hatchery fish remains unclear. Nehlsen et al. (1991) considered the 

early returning populations extinct, and the comanagers concluded that if these fish still existed 

in the Skokomish River, they were at very low abundances (WDF et al. 1993). The strong 

genetic similarities of extant populations to Green River Chinook salmon (Figures 4, 5, and 

53
(Marshall 1999 and 2000b) suggest that the historical genetic characteristics of the early and 

late-returning populations were replaced or substantially altered by Green River-origin fish, 

which have been released extensively in the region (Myers et al. 1998).

Summary of information used in population structure decisions 

The TRT identified the Skokomish River as an independent population because of the 

watershed’s size, available habitat, isolation from other streams, and historical information. The 

Skokomish River is the largest Hood Canal stream (Figure 2), and historically it produced 

Chinook salmon with extensive life history diversity. These characteristics indicate that it was a 

region. Historically three Chinook salmon run-timing 

groups were reported to have occurred in the Skokomish River (Smoker 1952). Early returning 

Chinoo

south 

e 

n between 

populations in other river basins. The geographic separation between the spawning habitats in 

the upp , 

r 

y 

ly spawning Chinook salmon in the Dosewallips, Duckabush, and 

Hamma Hamma rivers to independent populations was more difficult. The balance of 

informa an 

) is larger 

st 

stable and productive watershed in the 

k salmon (i.e., spring and summer fish) were reported to have migrated above the upper 

dam site on the North Fork Skokomish River (Deschamps 1954, WDF 1957). Early returning 

Chinook salmon also occurred in the upper South Fork Skokomish River and the lower 

fork from the canyon to Vance Creek. In contrast late-returning Chinook salmon spawning was 

documented only in the lower north and south forks and in the main stem below their confluence 

(Deschamps 1954, WDF 1957). The return timing and distribution suggest there might hav

been two different populations, but the degree of geographical separation was equivocal. The 

historical geographic separation of the upper north fork spawning area from other Skokomish 

watershed spawning areas was approximately 21 km, which is comparable to separatio

er and lower south fork and mainstem Skokomish River is less than 3 km, however

which is at the extreme lower end of reported geographic separations of other Puget Sound 

Chinook salmon populations (Table 2). Although the TRT did not find a minimum watershed 

area that could support an independent population, the overall size of the north fork (30,000 ha) 

and the south fork (27,000 ha) Skokomish River watersheds are smaller than the Cedar Rive

watershed area (46,000 ha), which is the smallest watershed for which the team confidentl

identified an independent population. Because the TRT could not confidently identify two 

historical populations in the Skokomish River, we concluded that there was at least one historical 

population. 

Assigning the natural

tion the TRT has at this time supports treating these three spawning aggregations as

additional independent population, although other categorizations are possible. The degree to 

which these spawning aggregations were historically demographically linked is not clear, and 

only further monitoring and evaluation will resolve the relationships. The similarity of the 

freshwater and estuarine habitats, environmental conditions, and proximity of these three 

mid-Hood Canal watersheds suggests that their collective area could support a single 

independent population. The combined overall size of the three watersheds (72,000 ha

than other watersheds for which the TRT identified independent populations (Figure 2). Mo

Chinook salmon spawning in the mid-Hood Canal streams likely occurred in the Dosewallips 

River, because it is larger and has more area accessible to anadromous fish. Unpublished WDF 

survey records from 1932 documented a smaller-than-expected Chinook salmon run in the 

Dosewallips River given the size of watershed (Royal 1932). This may have led others to 

conclude that self-sustaining production in these streams was limited. The TRT’s research 

54
reveale

l 

 cluster as late-returning Chinook salmon in south Puget Sound streams, all of 

which have been stocked with Green River broodstock (Figures 4, 5, and 6). Genetic data 

availab

decisio

streams

areas a

regions

Chinoo

saltwat ber 

of C n rn 

end of from George Adams and Hoodsport hatcheries and the hatchery 

net n ips, 

Uni ,

differen

Hood Canal rivers (ranging from mid-September to early October) was somewhat earlier than in 

south P rth 

Fork Sk o

Skokomish le B-6, pages 106–109). Average age of 

spawne

correla

Duckabush

another (Appendix B, Table B-9, pages 114–116), but these patterns were suspect because the 

methods for estimating abundance in north Hood Canal streams were inconsistent over time. 

 

d, however, that at the time of the survey, in 1932, an impassable dam built many years

before at river mile 3 had been destroyed and had only allowed passage for a period of severa

years (Royal 1932). Consequently the early reports likely did not represent the historical 

population, which may have already been lost. Habitat capacity analysis also supports the 

hypothesis that the Dosewallips River (the largest watershed) and the other two streams had 

sufficient spawning and rearing habitat to support an independent population. Although the three 

spawning areas are separated by small distances (8–21 km), juvenile Chinook salmon are thought 

to leave the three streams early to rear in the shallow estuarine and nearshore habitats at the 

mouths of the three rivers. 

Summary of additional information 

Genetic data were not informative in reconstructing population structure under historical 

conditions. Allele frequencies between Skokomish River and Hamma Hamma River Chinook 

salmon are not different (P = 0.136) and probably reflect the use of Green River-origin 

broodstock for hatchery programs in Hood Canal. Extant Hood Canal Chinook salmon belonged

to the same genetic

le for Chinook salmon from Lake Cushman also were not informative for reconstructing 

historical population structure because their origin is unknown and they reflect a history of low

population abundance that could have resulted in the loss of historical characteristics. 

Quantitative estimates of migration rates were not possible and did not inform our 

ns. However, compared to other regions, Chinook salmon spawning in Hood Canal 

 do not have to travel far to move between streams (Figure 1 and Table 2). Spawning 

re mostly in the stream’s lower reaches because the upper reaches extend to high-gradient

 of the eastern Olympic Range. The only straying data available were recoveries of 

k salmon from the Skokomish River and Hoodsport Hatchery programs and from 

er net pens (which were discontinued). The Hoodsport Hatchery has received a num

hi ook salmon from the Skokomish River, possibly because of its location near the southe

Hood Canal. Some strays 

pe s also have been recovered in natural spawning areas on the Skokomish, Dosewall

on and Dewatto rivers.9

Life history information for the extant populations was not useful in discriminating 

t independent populations. Mean spawn timing of the extant spawning aggregations in

uget Sound. Within Hood Canal, spawning occurred earlier in the Dosewallips and No

ok mish rivers than in the Hamma Hamma, Duckabush, South Fork Skokomish, and

 rivers (Figures 6 and 7; Appendix B, Tab

rs at Hoodsport and George Adams hatcheries was highly dissimilar. Lack of 

tions in abundance of spawners suggest that the Chinook salmon in the Dosewallips, 

, Hamma Hamma, and Skokomish rivers could be demographically isolated from one

9

 T. Johnson, Washington Dept. Fish and Wildlife, Montesano, WA. Pers. commun., 8 April 2002. 

55
Habitat differences do exist within the Hood Canal basin. The biggest differences are 

between the streams draining the Kitsap Peninsula lowlands, where the TRT did not identify 

independent populations, and those draining the Olympic Mountains, which are in different 

ecoregions (Appendix A, Figures A-10 and A-11, pages 90–91). On the western shoreline, the 

Dosewallips River occurs largely in the snowmelt-transition hydroregion (Appendix A, Figure 

A-8, page 87), whereas the Skokomish River basin hydrograph is rainfall-dominated and it is 

distinguished in its lithology (Appendix A, Figure A-8, page 87; Figure A-12 and Table A-3, 

pages 92–93). 

Remaining uncertainties and data needs 

The historical characteristics of Hood Canal Chinook salmon are largely unknown. 

Historical returns and distributions of Chinook salmon to this region have been affected by 

construction of dams, habitat degradation, fisheries, and the introduction of nonnative hatchery 

fish. Better data on movement of wild and hatchery Chinook salmon among streams would be 

useful to verify the TRT’s conclusions of independence and to determine hatchery influence on 

these populations. 

The largest uncertainty is the degree to which Chinook salmon spawning aggregations are 

demographically linked in the Dosewallips, Hamma Hamma, and Duckabush rivers. Further 

evaluation is needed to resolve this issue. Several alternative scenarios also are possible: 

• Chinook salmon spawning in the Hamma Hamma, Duckabush, and Dosewallips rivers 

were subpopulations of a single, large Hood Canal Chinook salmon population with a 

primary spawning aggregation in the Skokomish River. Only a few historical reports 

document Chinook salmon spawning in the mid-Hood Canal streams, which might 

suggest that they were not abundant in any one stream before hatchery supplementation 

began in the early 1900s. In addition the overall size of each watershed and the area 

accessible to anadromous fish are small relative to other independent populations. 

• Chinook salmon in the Hamma Hamma, Duckabush, and Dosewallips rivers each are 

independent populations. 

• An additional uncertainty is the degree of demographic independence among the 

historical Chinook salmon spawning aggregations in the upper north fork, upper south 

fork, and the lower reaches of the Skokomish River. Further evaluation is needed to 

understand their relationships. Two alternative scenarios should be considered for the 

Skokomish River: 

o First, early returning Chinook salmon spawning in the upper forth fork and upper 

south fork are a separate population from another population of Chinook salmon 

spawning in the lower Skokomish River. 

o Second, early returning Chinook salmon spawning in the upper north fork are a 

separate population from another Chinook salmon population spawning throughout 

the upper south fork and lower Skokomish River. The geographic separation of the 

upper North Fork Skokomish River from the rest of the watershed and the north 

fork’s physically distinctive character support this scenario. 

56
The plausibility of the above hypotheses needs to be examined using a variety of 

information, including demographic evidence. First, monitoring abundance of the Chinook 

salmon spawning aggregations in these rivers may help determine whether their dynamics are 

likely to be quasi-independent. Information about fish movement and straying between streams 

also will be useful. Finally additional documentation of Chinook salmon spawning and rearing 

habitat in Hood Canal streams under historical conditions, if it exists, would help in determining 

the likelihood of these hypotheses. 

As is the case throughout Puget Sound, it is not clear to what extent Chinook salmon 

spawning regularly or occasionally in smaller independent tributaries may have been 

demographically linked to independent populations the TRT identified. Further work is needed 

to determine the relationship of Chinook salmon that may intermittently utilize those streams to 

the overall population structure at the population and ESU levels. The Northwest Fisheries 

Science Center (NWFSC) assessed the status of Chinook salmon populations in eastern Hood 

Canal streams and concluded that the Union, Tahuya, and Dewatto rivers probably did not 

historically support self-sustaining Chinook salmon populations and that Chinook salmon 

presently occurring in these streams were primarily the result of hatchery introductions or 

straying from hatchery releases in other Hood Canal streams (NOAA 1999). As with Chinook 

salmon occurring in small streams that are not within the geographic boundaries of independent 

populations, further work is needed to determine the relationship of Chinook salmon that may 

intermittently utilize those streams to the viability of independent populations and the recovery 

of the ESU. 

Estimates of straying among Hood Canal streams by naturally spawning Chinook salmon 

are lacking, but hatchery adults have been recovered in natural spawning grounds. In addition 

the length of time certain broodstocks were introduced into the Skokomish and Hoodsport 

hatcheries is information that will help in interpreting any potential biological significance of 

differences in life history data. Finally independent and consistent sampling to estimate spawner 

escapements, which began in 1998, will reduce uncertainty in assessments for each of the four 

main western Hood Canal streams. 

The origins and significance of the Chinook salmon in Lake Cushman also are unknown. 

Although they originated from anadromous fish, the age and source remains a mystery. Genetic 

analyses indicated that these fish either originated from a few founders or suffered a severe 

population reduction in the past (Marshall 1995). Loss of genetic variation makes it difficult to 

determine whether they are descended from historical Hood Canal populations or introduced 

hatchery fish. They are genetically different, smaller in size (and presumably less fecund) than 

their anadromous counterparts (Myers et al. 1998). What biological role, if any, these Chinook 

salmon may play in the recovery of Hood Canal Chinook salmon remains unclear. The NWFSC 

considers them to be part of the Puget Sound Chinook salmon ESU (Myers et al. 1998, NMFS 

1999), but the TRT did not identify them as a remnant of the historical population or a viable 

independent population. 

Strait of Juan de Fuca 

This Strait of Juan de Fuca region includes the Dungeness River and Elwha River basins 

and adjacent independent tributaries, such as Morse Creek. The TRT identified two independent 

57
populations in this region, based on geographical and genetic information (The numbering 

sequence follows the list of populations in the Conclusions section, page 28, and is continued 

from page 53.): 

22)

nt 

of historical diversity may have been lost (Table 1), including early and 

late-returning life histories that no longer are expressed and genetic diversity lost to nonnative 

hatcher

s 

 Tribe 2003). 

wning in the basin. 

Nehlsen et al. (1991) identified th

ness River was a 

significant part of the histori

on structure decisions 

21) Dungeness River 

 Elwha River 

Although the TRT identified two independent populations in this region, importa

components 

y fish introductions. Historical evidence suggests that an early returning life history 

occurred in the Elwha River before construction of the lower Elwha Dam eliminated access to

habitat in 1914. The team concluded that the early returning life history in the Elwha River wa

a significant part of the historical diversity of Chinook salmon within that basin and that 

information was insufficient to determine whether the lost form was an independent population 

or within-population diversity. In contrast in the Dungeness River extensive human disruptions, 

including introductions of nonnative hatchery fall Chinook salmon, may have more severely 

impacted late-returning life histories (Williams et al. 1975, Jamestown S’Klallam

Questions remain about the population structure of the Chinook salmon spa

e late-run fish as being at high risk of extinction. More recent 

assessments indicate that only one Chinook salmon stock with no discontinuity in spawning 

distribution through time or space exists in the basin (Marlowe et al. 2001). Based on available 

evidence, the TRT concluded that the late-returning life history in the Dunge

cal diversity of the Chinook salmon population, which remains at 

high risk of extinction. 

Chinook salmon also spawn in Morse Creek. The TRT concluded that they were not 

historically independent from the Elwha River or Dungeness River populations. Current return 

timings suggest that these fish are more similar to Elwha River Chinook salmon than to those in 

the Dungeness River (WDF et al. 1993). For that reason the team assigned the Morse Creek 

spawning aggregation to the Elwha River population. 

Summary of information used in populati

Geographically Chinook salmon spawning areas in the Dungeness and Elwha rivers are 

disjunct from other populations in east Puget Sound and Hood Canal. The closest independent 

populations to the Dungeness River in east Puget Sound and Hood Canal are in the lower Skagit 

River and Dosewallips River, which are 95 km and 103 km away, respectively. The Elwha 

River is even farther from these populations (Figure 1). In contrast spawning areas in the 

Dungeness and Elwha rivers are only 37 km apart (Table 2). 

Genetically Chinook salmon in the Dungeness and Elwha rivers are distinctive from other 

Puget Sound populations and from each other (Figures 4, 5, and 6; Table 5). Because of their 

geographic location, Dungeness River Chinook salmon were often presumed to be genetically 

intermediate between Elwha River Chinook salmon and those from east Puget Sound tributaries. 

The TRT’s analyses do not support this; the data show equal or greater divergence of Dungeness 

River Chinook salmon from other groups in Puget Sound (Figure 6). Because no data exist for 

58
wild, adult Dungeness Chinook salmon, the team used data from fish taken from redds and 

reared in the hatchery for genetic analyses. 

Summary of additional information 

Quantitative estimates of migration rates were not possible and did not inform our 

decisions. Information about Chinook salmon straying from the Dungeness River is available as 

part of the Dungeness captive broodstock program,10 which was designed to restore the 

population. 

Life history differences support the TRT’s decision, based on genetic and geographical 

criteria. The Elwha River and Dungeness River populations have some of the earliest spawn 

timings of Puget Sound Chinook salmon. Spawning in the Dungeness River, however, began 

earlier and was less protracted than in the Elwha River (Figure 8) (WDF et al. 1993). Spawning 

in the Dungeness River begins significantly earlier in the upper main stem and in the Grey Wolf 

River, a tributary, than in the main stem below the confluence with the Grey Wolf (Appendix B, 

Table B-6, pages 106–109), which is similar to spawn timing in the Nooksack River (Figures 7 

and 8). Elwha River and Dungeness River Chinook salmon also have different 

smolt-spawner age distributions (Appendix B, Table B-7, pages 110-112). 

Trends in population abundance of Chinook salmon in the Dungeness and Elwha rivers 

were largely uncorrelated (Appendix B, Table B-9, pages 114–116), but this probably reflects the 

influence of different hatchery programs in those rivers (WDF et al. 1993). 

Habitat differences exist between the Dungeness and Elwha rivers and other Puget Sound 

streams. The Dungeness River has a fairly large spawning area accessible to Chinook salmon 

that reaches into the snowmelt-transition hydroregion. Historically Elwha River Chinook salmon 

also would have used spawning areas in the snowmelt-transition hydroregion (Appendix A, 

Figure A-8, page 87). The Elwha River is in a different EPA ecoregion than other Puget Sound 

streams, (Appendix A, Figures A-10 and A-11, pages 90–91), and it is geologically different 

from other nearby streams (Appendix A, Figure A-12 and Table A-3, pages 92–93). 

Remaining uncertainties and data needs 

The historical population structure and diversity of the Elwha River are unknown because 

the population’s current distribution is severely constrained by the two dams. Likewise the 

Dungeness River population’s historical and current structure and diversity are poorly 

understood. In both rivers, past and present habitat alterations, hatchery programs, and harvest 

management strategies almost certainly altered population structure relative to historical patterns. 

As is the case throughout Puget Sound, it is not clear to what extent the Chinook salmon 

spawning (regularly or occasionally) in smaller independent tributaries may have been 

demographically linked to independent populations the TRT identified. Williams et al. (1975) 

noted that the few Chinook salmon were known to use independent tributaries in this region. In 

Morse Creek, current return timings suggest that these fish are associated with Chinook salmon 

 

10 B. Sele, Jamestown S’Klallam Tribe, Sequim, WA. Pers. commun., 14 August 2000. 

59
from the Elwha River (WDF et al. 1993). Further information is needed about fish movements 

and population dynamics to determine the relationship of Chinook salmon that may 

intermittently utilize smaller streams along the Strait of Juan de Fuca to the overall population 

structure at the population and ESU levels. 

60
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66
67

Appendix A: Methods and Results for 

Less Informative Population Indicators 

Appendix A contains data analyses and results for population indicators that were not as 

influential in delineating population boundaries as those reported in the body of this technical 

memorandum. For each indicator the Technical Recovery Team (TRT) summarized the 

independence between each pair of sites as the median independence score across (with 6–10 

scorers per indicator) and the distribution of independence scores among scorers (Table A-1). 

The relatively informative indicators are discussed in the main document. In contrast the 

indicators reported in Appendix A are those believed to be informative for identifying 

independent populations in a theoretical sense; however, because of data quality issues, 

confounding sources of variation, or uncertainty in interpretation of results, the TRT did not rely 

heavily on these results to make its determinations. The team included the analyses and results 

in Appendix A for completeness. Furthermore we hope to encourage further data collection, 

experimentation, or discussion of the natural levels of variation in these indicators and how they 

might suggest something about the population structure of Chinook salmon (Oncorhynchus

tshawytscha) in Puget Sound. 

Direct Observations of Migration 

Methods 

Some direct observations of straying among Puget Sound Chinook salmon stocks were 

available. Most of these observations are based on releases and subsequent recoveries of 

hatchery Chinook salmon marked with coded-wire tags (CWTs); the observations are available 

in a database maintained by the Pacific States Marine Fisheries Commission (RMPC 1997). The 

TRT searched the database for all records of tagged Chinook salmon reared in Puget Sound or 

Strait of Juan de Fuca watersheds and recovered at or near the probable spawning location (i.e., 

hatchery rack, spawning ground, carcass survey, and freshwater trap). These data allowed the 

team to estimate straying rates; straying is defined as recovery of a tagged fish at a location other 

than its rearing site. Stray rate refers to the proportion of all fish in a tag group (or from a release 

site) that is recovered somewhere other than their tagging or release sites. However stray-rate 

estimates must be viewed with caution, because methods of estimating the total number of 

returning tagged fish vary among recovery locations, and the geographic area sampled for strays 

is not comprehensive or selected based on a spatially stratified design. Estimates of straying 

rates based on small-scale experimental studies were available in a few locations. 

The TRT graphically examined the relationship between straying rate and dispersal 

distance in all CWT release groups that produced at least 20 freshwater recoveries (n = 3–98 

groups per release site). The team selected and summarized 16 release sites distributed 

throughout Puget Sound. For these sites we measured straying rates separately for each release 
Table A-1. Distribution of independence scores for each pairwise comparison of streams. Each number represents a score 

scorer. Locations signify rivers unless otherwise noted. 

Skagit River basin 

Upper/ Lower Skagit Upper Skagit Lower Sauk U

Lower 

Skagit 

Lower 

Sauk 

Upper 

Sauk Suiattle Cascade

Lower 

Sauk 

Upper 

Sauk Suiattle Cascade

Upper 

Sauk Suiattle Cascade Suiat

–2 2 2 3 3 1 –1 2 2 2 2 2 1 

2 2 4 4 4 2 4 4 4 4 4 4 4 1 1 2 3 2 1 1 1 1 1 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 2 2 3 1 3 3 3 3 0 1 2 2 2 0 1 2 1 1 2 2 1 3 4 2 3 3 3 4 3 3 3 4 4 3 2 2 3 2 2 2 2 2 2 2 2 2 2 1 1 2 2 3 1 2 2 2 2 2 3 2 

Stillaguamish 

River basin 

North fork/ 

South fork 

444333433

Snohomish River basin 

Skykomish Sultan Wallace 

Bridal Bridal Veil Bridal 

Sultan Wallace Veil Creek Snohomish Wallace Creek Snohomish Veil Creek Sno

2 –2 –2 3 –1 2 3 –1 2 –3 –3 3 2 2 2 –3 2 –3 –3 2 1 2 3 –3 2 –2 –2 2 1 1 2 –2 3 –2 –2 1 1 2 3 –3 2 –2 –2 1 0 1 1 –2 1 –3 –3 1 0 2 0 –3 2 –3 –3 2 2 2 2 –3 2 –2 –1 2 –3 1 2 –2 

68
69

Table A-1 continued. Distribution of independence scores for each pairwise comparison of streams. Each number represen

different genetic scorer. Locations signify rivers unless otherwise noted. 

Lake Washington 

Cedar Sammamish/

Sammamish Issaquah Issaquah 

2 

–1 –1 –1

2 2 21 1 12 0 02 1 02 2 12 2 12 2 1

Nooksack River basin 

North fork/ 

South fork 

3 

2 

3 1 3 3 2 3 3 

Hood Canal 

Skokomish/ 

Hamma Hamma 

–2

–2

–2

00

–2

0

–1

0

Central/south Puget Sound 

Duwam Puyallup White ish/Green 

Newaukum Newaukum New

Puyallup White Nisqually Creek White Nisqually Creek Nisqually C

3 4 3 –4 3 4 3 4 3 4 1 0 4 3 0 4 1 3 1 0 3 2 0 3 1 2 2 0 2 2 0 2 

–2 3 1 –4 3 2 1 3 

1 2 1 –3 2 2 0 3 1 3 1 0 3 2 0 3 1 1 2 –3 2 2 2 3 3 3 3 –4 2 3 0 3 
70

group as the proportion of recoveries that occurred at a given nautical distance from the release 

location. 

Results 

The pattern of releases and recoveries of tagged Chinook salmon (Table A-2) suggests 

that migration rates between basins or major subbasins in Puget Sound are generally quite low. 

For most stocks more than 95% of the tag recoveries from spawners occurred within the same 

subbasin where the juveniles were released (but see the caveat in the Methods subsection [page 

67] regarding estimates of stray rates based on these data). However some migration between 

major basins does occur. For example spring- and summer-run Chinook salmon released at 

Kendall Creek Hatchery on the North Fork Nooksack River have been recovered in the North 

Fork Stillaguamish River, and summer-run fish from the North Fork Stillaguamish River have 

returned to the Snoqualmie Basin. A small number of adults have been recovered outside of 

Puget Sound (e.g., spring-run Chinook salmon of Suiattle River origin released from 

Marblemount Hatchery have returned to the Cowlitz Hatchery on the Cowlitz River in the lower 

Columbia River basin). 

The dispersal curve for all locations and release groups (Figure A-1) shows a strongly 

nonlinear decline in straying rate as a function of distance between release and recovery 

locations, with the steepest decline occurring between 0 and approximately 75 km. The TRT did 

not attempt to model this relationship statistically. The individual dispersal curves from 16 

individual release sites suggest that the shapes of dispersal distributions are highly variable 

among streams and stocks. For example the number of fish recovered farther than 100 km from 

the source was very low for a number of release groups (e.g., those from Grovers, Skookum, and 

Garrison creeks and Wallace River). In contrast fish recoveries farther than 100 km from the 

source occurred from tag groups originating in the Elwha River, North Fork Stillaguamish River, 

Marblemount Hatchery, Skokomish River, and Kendall Creek. 

Patterns in Life History Characters 

Methods 

Data on spawner age and age at outmigration (WDFW 1995) were gathered by reading 

scales collected from carcasses on the spawning grounds. Scale samples for spawner age were 

taken from the same wild and hatchery stocks used in the genetic analyses, and sample sizes 

varied among stocks (n ≥ 40). Log-linear models were used to test for overall heterogeneity in 

age distributions among stocks, between sexes, and between hatchery and wild spawners; 5+ and 

6+year-old age-classes were pooled for these analyses. An index of percentage overlap in age 

distributions (Krebs 1989) was calculated for both spawner age and spawner and outmigrant age 

for each pairwise combination of stocks. The resulting similarity matrix was used in a UPGMA 

cluster analysis, with 1 minus percent overlap as the distance measure. 

Similar to the age-structure data, length (fork length or post-orbital length or both) was 

measured from all Chinook salmon adults collected for genetic analyses on the spawning 

grounds. The TRT grouped fish by age (3, 4, and 5 years old) and sex for initial length analyses. 

If multiple broodyears within an age and sex class existed, the team combined them to increase 
Table A-2. Straying matrix for Puget Sound Chinook salmon. Except where indicated, data are based on CWT recoveries 

salmon reared at hatcheries within Puget Sound.a Bold = recoveries within the same basin or subbasin where reare

successful homing). Italics = estimates based on otolith-marking study of Chinook salmon reared at Wallace HatchRecoveries are summed over 1997 and 1998 return years. Locations signify rivers unless otherwise noted. Source

b Stock or rearing l

ocati

o

n

Lake South 

Nooksack 

Basin 

Skagit 

Basin 

Stillagua

mish 

Basin 

Snoho

mish 

Basin 

Washington 

Basin 

Green 

Basin 

Puyallup 

Basin 

Nisqually

Basin 

Puget 

Sound

Kitsap 

Peninsula

S

Recovery

ing Kendall spr

um spring Skook

arblemount 

ing 

arblemount 

mmer 

Wild Skagit 

mmer 

rth Fork

Stillaguamish 

mmer 

r Wallace summe

Wallace fallc

allc Issaquah f

eek fallc Soos Cr

White spring 

allc Nisqqually f

n Garriso (Chambers 

allc Creek) f

vers Creek Gro fallc

basin 

M

spr

M

su

su

No

su

Nooksack 58.00 6.00 2.03 North Fork 4,966.11 10.19 Nooksack 

Middle Fork 7.00 Nooksack South Fork 6.35 2,38.26 Nooksack Samish 1.00 1.00 2.08 Skagit 5.37 20.00 7.00 20.40Lower Skagit 1.00 6.00Upper Skagit 7.02 1,465.70 1,15.03 3.13 4.00 2.03 1.00Cascade 6.74 77.26Stillagua

mish 5.00

North Fork 15.01 1.00 1,050.97Stillagua

mish 

South Fork 3.00Stillagua

mish 

Snoho

mish 5.69 9.00 1.02

Skyko

mish 16.12/

1,099.00 

Wallace 2.03 1.00 10.06 752.48/ 369.10 3.00 

8,913.00 

Bridal Veil 636.00 Creek/ North ForkSkyko

mish 

71
Table A-2 continued. Straying matrix for Puget Sound Chinook salmon. Except where indicated, data are based on CWT 

Chinook salmon reared at hatcheries within Puget Sound.a Bold = recoveries within the same basin or subbasin wh

successful homing). Italics = estimates based on otolith-marking study of Chinook salmon reared at Wallace Hatch

summed over 1997 and 1998 return years. Locations signify rivers unless otherwise noted. Source: RMPC 1997. 

b Stock or rearing l

ocati

o

n

Lake South 

Nooksack 

Basin 

Skagit 

Basin 

Stillagua

mish 

Basin 

Snoho

mish 

Basin 

Washington 

Basin 

Green 

Basin 

Puyallup 

Basin 

Nisqually

Basin 

Puget 

Sound

Kitsap 

Peninsula

S

Recovery

ing Kendall spr

um spring Skook

arblemount 

ing 

arblemount 

mmer 

Wild Skagit 

mmer 

rth Fork

Stillaguamish 

mmer 

r Wallace summe

Wallace fall 

allc Issaquah f

eek fallc Soos Cr

White spring 

allc Nisqqually f

n Garriso (Chambers 

allc Creek) f

vers Creek Gro fallc

basin 

M

spr

M

su

su

No

su

Snoqualmie 30.87 119.00 3.25 Issaquah 1,094.07 3.07Lake 1.00 1.00Washington Green 9.77 5,766.90 8.90Puyallup 1.34 6.03 White 1.00 3,530.89 1.00 1.03Garrison 1.04 3.00 2.01 74.60 18.32HatcheryNisqually 1,347.30McAllister 1.00 1.00 8.60HatcheryCapitol Lake 20.10 6.44 Burley Creek 5.41Coulter Creek 1.00 Minter 1.00 11.02 HatcheryHupp Spring 1.02 Ponds Grovers Creek 1.01 1,0830.37 HatcherySkoko

mish 

Hoodsport HatcheryDungeness 

72
73

Table A-2 continued. Straying matrix for Puget Sound Chinook salmon. Except where indicated, data are based on CWT 

Chinook salmon reared at hatcheries within Puget Sound.a Bold = recoveries within the same basin or subbasin 

successful homing). Italics = estimates based on otolith-marking study of Chinook salmon reared at Wallace H

are summed over 1997 and 1998 return years. Locations signify rivers unless otherwise noted. Source: RMPC 

b Stock or rearing location

Kendall spring 

Lake South 

Nooksack Skagit Stillaguamish Snohomish Washington Green Puyallup Nisqually Puget Kitsap S

Basin Basin Basin Basin Basin Basin Basin Basin Sound Peninsula 

Skookum spring 

Marblemount 

spring Recovery Marblemount basin summer 

Elwha 1.04 

Wild Skagit 

Outside Puget 11.38 1.02 1.00 

summer 

Sound Total 5,074.64 2,54.45 1,545.99 150.41 10.13 1,128.32 7,76.33/ 380.10 1,127.94 5,782.60 3,536.92 1,348.3 77.61 1,0898.17 

North Fork

1,0767.00

Stillaguamish summer 

Wallace summer

Wallace fall

c

Issaquah fall

c

Soos Creek fall

c

White spring 

Nisqqually fall

c

Garrison (Chambers 

Creek) fall

c

Grovers Creek fall

c

a Counts of CWT recoveries should be interpreted cautiously for the following reasons: 

• Straying rates of hatchery Chinook salmon likely differ from straying rates of wild fish, particularly where the hatchery stock has b

influenced by out-of-basin introductions. 

• Most counts shown in the table are summed over multiple tagged release groups and brood years, and the number and date of relea

• Counts from different locations or years may not be directly comparable because of differences in methods used to estimate the tot

on the number of tags sampled and sampling efficiency. In particular, some recoveries do not provide an estimate of sampling effithe number of tags observed. Thus the counts should not be directly interpreted as estimates of straying rates. 

b In general hatchery stocks were included in the matrix only if the original broodstock was of local wild origin or if the present-day sto

the local wild population. Note that recoveries are grouped geographically and may include both hatchery returns and wild spawners 

c Stocks with substantial out-of-basin influence are included to increase geographic coverage area.
Figure A-1. Dispersal curve for Puget Sound Chinook salmon based on coded-wire tag recoveries. Data 

shown represent a total of 167 tagged release groups from 15 hatcheries for which at least 20 

tagged spawners were recovered. Each point is the proportion of recoveries that occurred at a 

given distance from the release location. Proportions were calculated separately for each release 

group, so multiple dispersal “curves” are overlaid in the figure. 

the number of stocks with adequate sample size for analyses. Only 3-year-old males and 

4-year-old males and females had large enough sample sizes for length at age of maturity cluster 

analyses (n > 40). In most cases the TRT reported length data as either fork length or 

post-orbital length, so the team performed regressions within each age and sex class to 

standardize lengths to post-orbital length (regression [R2] ranged from 0.80 to 0.93). Differences 

in length between 4-year-old males and females were not statistically significant (ANOVA 

df = 1, P > 0.12), so we pooled the sexes for cluster analyses of 4-year-olds. The team computed 

differences in the mean length at age of maturity between all sites sampled and used them to 

generate a difference matrix for 4-year-old males and females combined. The analysis included 

hatchery and wild stocks. The TRT then used the matrix in a UPGMA cluster analysis to 

generate a dendrogram (Figure A-2). 

Results 

Representative age distributions of Puget Sound Chinook salmon spawners based on 

carcass samples are shown in Figure A-3. A log-linear model including only naturally 

produced stocks detected highly significant overall heterogeneity in spawner age distributions 

(G2

 = 674.83, df = 63, P < 0.0001). In general the cluster analysis based on overlap in spawner 

74
Figure A-2. Dendrogram of Puget Sound Chinook salmon stocks based on similarity in length at age 

of maturity (4-year-old females and males). The distance measure used in the UPGMA cluster 

analysis was Euclidean distance of mean length at age of maturity of 4-year-old fish. The 

analysis included wild and hatchery-produced stocks (stocks with an H in their name are hatchery 

stocks). Sample sizes and the numbers of broodyears sampled vary among stocks. Locations 

signify rivers unless otherwise noted. 

age distributions does not indicate any strong patterns of similarity concordant with the spatial 

distribution of stocks, although there are some exceptions (e.g., stocks from the Cedar River and 

the Issaquah Hatchery cluster together, as do the upper Cascade River spring, lower Sauk River 

summer, and Cascade Hatchery stocks). Distributions of age at outmigration and spawning also 

are shown in Figure A-3. An overall test for heterogeneity was not performed on distributions of 

age at outmigration and spawning. The UPGMA dendrogram developed from the combined data 

on age at outmigration and spawning shows two main clusters, one containing all spring-run 

stocks and a few summer or fall stocks (i.e., Wallace, Sauk, Snoqualmie, and Elwha rivers). The 

other main cluster in the dendrogram is a collection of summer or fall stocks from throughout 

Puget Sound, with no geographic pattern to the degree of similarity in juvenile or spawner age 

distributions.

Age-specific length varies significantly among 26 stocks of Puget Sound Chinook salmon 

(ANOVA F = 8.24, df = 25, P << 0.001; Figure A-3). The UPGMA dendrogram indicates that, 

unlike the age data, patterns in length at age of maturity of Puget Sound Chinook salmon are 

fairly concordant with the spatial arrangement of streams. Fish in streams that are closer 

together have more similar length at age of maturity than fish from streams that are farther apart. 

75
Figure A-3. Representative age distributions for Puget Sound Chinook salmon stocks, based on scale 

samples from carcasses on spawning grounds. The distributions of spawner age are on the top 

row and the distributions of age at outmigration (the subscript number) and spawning (the large 

number) are on the bottom row. All ages are expressed as year of life, beginning with egg 

deposition. Locations signify rivers unless otherwise noted. 

Spatial Synchrony in Spawner Abundance 

Methods 

The TRT obtained time series of spawner abundance for Puget Sound Chinook salmon 

from StreamNet (no date). Time series with less than 10 years of data were excluded from the 

analysis, as were abundance data for hatchery-produced stocks, although natural spawners in 

some areas include a substantial proportion of first-generation hatchery strays. Using these 

criteria, the team selected 31 stocks (loosely defined in this study to mean any fish group for 

which relevant data were available) to use in the analysis. Most of these stocks correspond to 

SASSI stocks (WDF et al. 1993), but we also included several spawner groups in small, 

independent Puget Sound tributaries not described by WDF et al. (1993). The time series for 

each stock consists of annual total spawning escapement, as estimated from counts of live 

spawners, carcasses, or redds in selected index stream reaches. The series range in length from 

10 to 30 years, and most include 1997 as the most recent sample year. In order to meet the 

requirements of statistical time-series models, the team interpolated missing observations that 

were not at the beginning or end of the series by averaging the abundance in the years 

immediately preceding and following the missing point. Only four values were interpolated, so 

the error introduced by this procedure was minimal. 

The TRT filtered the abundance data using standard time-series methods prior to the 

correlation analyses. Because the goal was to examine covariation in abundance that might be 

due to the exchange of migrants between stocks, the team first attempted to eliminate sources of 

76
variation within stocks that were not likely attributable to immigration or emigration (cf Hanski 

and Woiwod 1993, Bjørnstad et al. 1999). Statistically these sources of variation include 1) 

long-term temporal trends (which might be caused by changing environmental conditions due to 

natural or human causes), and 2) temporal autocorrelation (due to density-independent variation 

in cohort strength or autocorrelation in climate or other environmental variables). The team 

assumed that these relatively long-term patterns are driven by deterministic processes over long 

time scales, because migration rates in salmonid populations are more likely to vary over short 

time scales (see references in McElhany et al. 2000). The TRT recognizes that, after accounting 

for trends and autocorrelation, we cannot assume that all sources of spurious correlation in 

abundance time series were completely removed. Therefore inferences about possible migration 

rates between groups based on these abundance time series should be made with caution. 

Temporal trend was estimated separately for each time series using a third-order 

polynomial multiplicative model (Thomas 1996): 

N = λt

λ 2 3 ε N t λt t e t 0 1 2 3 (4)

where Nt is abundance in year t, lambdai (λi) are the trend parameters, and epsilont (εt) is a 

normal random variable. Equation 4 is equivalent to: 

log Nt = β β t β t

2 β t3

0 + 1 + 2 + 3 + εt (5)

where beta0 (β0) = log N0 and βi = log λi for i greater than 0. 

The TRT chose a third-order polynomial model because it was sufficiently complex to 

describe most obvious long-term patterns in the abundance data. We estimated the parameters in 

Equation 5 (hereafter called the trend model) by least squares, then used a stepwise procedure to 

find the most parsimonious model, based on Mallow’s Cp-statistic (Weisberg 1985, using the 

S-PLUS 5 program (MathSoft 1998). Thus the final trend model for any particular stock does 

not necessarily include all three polynomial terms, only those that contributed to the overall 

explanatory power of the regression. 

The TRT visually inspected residuals from each polynomial trend regression to check the 

assumption that εt are normally distributed. Residuals for many stocks showed significant 

temporal autocorrelation, so the team fitted a time-series model with trend and autoregressive 

parameters (Edwards and Coull 1987) to each abundance time series. This model (hereafter 

called the trend-AR) is: 

t NtttN t Nt N tptp log αββββ log α log α log ε 1 21 2

3

3

2

210 ++++= − + − L++ − + (6) 

where Nt-1 is the abundance in year t-1 and alphai (αi) are autoregressive parameters. 

The TRT chose the order p of the autoregression for each stock by fitting various 

autoregressive models (with p ≤ 8) to the residuals from the trend model and selecting the most 

parsimonious model based on the Akaike Information Criterion (AIC) (Burnham and Anderson 

1998). Once the team determined the autoregression order, we simultaneously estimated the 

parameters in the trend-AR model by least squares. 

The residuals from the trend and trend-AR time-series models formed two new data sets, 

which served as the input for the correlation analyses. The TRT used each set of residuals to 

77
compute a matrix of product-moment correlation coefficients between all pairs of stocks. The 

length of the residual time series varied among stocks, so the team computed correlations 

between residuals from the trend model in two ways: using pairwise deletion of missing 

observations (so that elements in the correlation matrix are based on differing sample sizes) and 

using casewise deletion (so that all correlation coefficients are based on n = 10 observations 

corresponding to years 1987–1996). The TRT could not use casewise deletion of missing 

observations in the correlation matrix based on trend-AR residuals because the data set had too 

few years with data on all stocks. 

The TRT examined patterns of cross-correlation between stocks by UPGMA cluster 

analysis, with 1–r as the pairwise distance measure. The team assessed the robustness of the 

resulting clusters by jackknifing over years. Each of the 30 years in the escapement data set was 

successively deleted, and we recalculated the correlation matrix on the reduced data set. The 

TRT used each correlation matrix in a UPGMA cluster analysis and found a consensus tree 

based on the 30 dendrograms using the CONSENSE program version 3.5c (Felenstein 1993). 

This procedure allows an evaluation of the sensitivity of the correlation matrix to inclusion of 

extreme observations in particular years. The jackknifing analysis was performed only on the 

data set consisting of residuals from the trend-AR model. 

The TRT investigated spatial autocorrelation in abundance by testing the association 

between pairwise correlation coefficients and pairwise geographic distances separating the 

spawning grounds of stocks, as described previously in this subsection. In addition the team 

statistically modeled the relationship between distance and correlation in abundance in order to 

estimate the spatial scale of demographic synchrony. We used a Gaussian model (Myers et al. 

1997, Bradford 1999): 

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

−= 2

2

0 2 exp)(

σ

ρρ

d d (7) 

in which the demographic correlation, rho (ρ) × distance (d), between two stocks declines 

monotonically with increasing distance, starting at an initial value of ρ0 when d = 0. This model 

can accommodate a “threshold” at which the correlation decays most rapidly. The model was fit 

using nonlinear least squares. The TRT made no attempt to account for the nonindependence of 

elements in the correlation and distance matrices. 

Results 

For a majority of stocks, residuals from the trend model show significant serial 

autocorrelation, indicating that the trend-AR model is the more appropriate model for these 

stocks. Interestingly there is no general pattern of strong autocorrelation at a lag of 3–5 years, as 

would be expected to result from density-independent variation in cohort strength, given the 

predominant age at reproduction of Puget Sound Chinook salmon. 

The jackknifed consensus tree for the cluster analysis, based on trend-AR residuals, 

indicates that low-level structure in the correlation matrix (i.e., clusters of 2–4 stocks) is 

generally robust to the deletion of single years from the data set. Higher-level structure, 

however, is much more sensitive to the inclusion or exclusion of particular years. The 

relationships among stocks indicated by the dendrogram (Figure A-4) are summarized 

78
Figure A-4. Difference in the temporal correlation (1-rs) in abundance time series from stocks of Puget 

Sound Chinook salmon. Product-moment correlation coefficients were computed between all 

pairs of stocks, based on residuals from time series models. Results below are from a UPGMA 

cluster analysis using (l-rs) as the distance measure. Locations signify rivers unless otherwise 

noted. 

79
graphically in Figure A-5. Stock clusters depicted in Figure A-4 are those clusters that are joined

at a linkage distance less than or equal to 0.55 in the dendrogram. This linkage distance 

corresponds roughly to a statistically significant correlation coefficient for a sample size of n = 9,

which is the smallest sample size used in the correlation matrix. 

On the whole the relationships among stocks suggested by correlations in abundance are 

not concordant with the pattern suggested by geography and genetic similarity (i.e., 

geographically proximate stocks do not consistently show stronger correlations in abundance 

than geographically distant stocks). This conclusion is supported by inspection of the spatial 

correlogram based on trend-AR residuals (Figure A-6). Although a one-tailed Mantel test 

indicated a significant (P < 0.05) negative association between the correlation coefficient and 

geographic distance, the relationship is weak. Figure A-6 shows the fit of the Gaussian decay 

model. The estimate of the “threshold” parameter is sigma (σ) = 86.6, indicating that positive 

correlations tend to occur at a distance of equal to or greater than 86.6 km. This value is 

significantly different from zero (approximate t-test, P < 0.001). However the initial correlation 

is quite low (ρ0 = 0.15), although it too is significantly different from zero (P < 0.01). 

One of the most striking examples of a group of neighboring stocks with highly 

correlated dynamics is the group consisting of the lower Skagit River fall-, upper Skagit River 

summer-, and lower Sauk River summer-run stocks. This cluster is robust to different methods 

of computing the correlation matrix and filtering the abundance time series. However these 

Skagit Basin stocks also cluster with the geographically distant Dungeness River and area 7A 

stocks (Figure A-4). The upper Sauk River and Suiattle River spring-run stocks, which spawn in

the upper reaches of the Skagit Basin, appear unrelated to the lower Skagit Basin stocks in all the

cluster analyses. The summer- and fall-run stocks in the Stillaguamish River cluster together, 

but only when the correlation matrix is based on trend-AR residuals (Figure A-4). In contrast the

summer-run stocks in the Stillaguamish and Snohomish rivers appear related when the 

correlation matrix is based on residuals from the trend model (results not shown). In the analysis

based on trend-AR residuals, the Duwamish/Green River, Cedar River, and north Lake 

Washington stocks form a cluster, as do the Wallace River and Snohomish River summer-run 

stocks. 

Environmental Effects on Population Synchrony 

Methods 

In order to investigate the possibility that the observed cross correlations in abundance 

were due to correlated environmental influences (i.e., the Moran effect) rather than demographic 

exchange (e.g., Harrison and Quinn 1989, Lande et al. 1999, Bjørnstad et al. 1999, Ripa 2000, 

Kendall et al. 2000), the TRT examined the relationships between annual spawner abundance 

and some environmental variables. The rationale for this approach was that if the environmental 

variables explain a significant amount of the variance in abundance, then their effects could be 

removed from the abundance time series and the between-stock correlations could be 

recalculated. 

80
Figure A-5. Relationships among Puget Sound Chinook salmon stocks, based on UPGMA cluster 

analysis using temporal correlation in abundance as the similarity measure. The correlation 

matrix was calculated from trend-AR model residuals, using pairwise missing data deletion. 

Clusters were defined by taking all groups in the dendrogram that were joined at linkage distance 

greater than or equal to 0.55. Streams within a cluster are represented by the same letter. 

81
Figure A-6. Spatial correlogram for spawner abundance in Puget Sound Chinook salmon stocks. The 

correlation in abundance between each pair of stocks (based on trend-AR model residuals) is 

plotted against the geographic distance separating their spawning areas. The solid line is the 

Gaussian decay model fit to the correlation and distance data. 

The TRT chose to focus on two hydrologic variables, peak discharge during the 

incubation period and low flow during the upriver spawning migration, because previous studies 

indicated that these variables have strong effects on salmonid vital rates that may be detectable in 

spawner escapement data (Beamer and Pess 1999). Time series of discharge measured at stream 

gauges on or near Puget Sound Chinook salmon spawning grounds were obtained from the U.S. 

Geological Survey (USGS 2005). Gauge data were available for 22 of the 31 stocks. Peak flow 

during incubation was defined as the maximum instantaneous discharge observed between 1 

September and 31 March of each broodyear. Low flow during spawning migration was defined 

as the minimum 7-day mean flow observed between 1 May and 31 October of each return year. 

Scatter plots of abundance (the raw number of spawners and the residuals from the time-series 

models) against peak and low flow were used to check visually for effects of the hydrologic 

variables. Because peak discharge is hypothesized to affect egg-to-fry survival and most 

Chinook salmon in Puget Sound spawn between the ages of 3 and 5 (WDF 1993, Beamer and 

Pess 1999), the team used lagged scatter plots with the peak flow time series lagged by 3, 4, or 5 

years. Low flows during summer and early fall may delay migrating spawners, increase 

stress-related mortality, or prevent access to spawning grounds, so abundance in each year was 

plotted against low flow observed in the same year. 

82
Results 

Lagged scatter plots do not suggest a systematic relationship between spawner abundance 

and instantaneous peak flow at a time lag of 3, 4, or 5 years in any stock. This conclusion is not 

altered 

en 

f 

suc

env n h could 

in turn af

dentify hydrologic regions. First the team identified 

dist t

stream tree analysis to identify broad hydrologic 

ed 

auges located 

throughout Puget Sound from e 

s 

d 

s 

sure 

when residuals from the time-series models, rather than raw or log-transformed 

escapement estimates, are used as the index of abundance. Similarly scatter plots of spawner 

abundance against 7-day summer low flow provide no evidence of any relationship betwe

these variables. It is clear from inspection of the scatter plots that attempting to statistically

model the relationship between peak flow and abundance would not be informative for the 

question the TRT was addressing. In summary, in interpreting correlations in time series o

abundance data, the team could not distinguish between correlations due to environmental 

conditions experienced by groups of fish and those due to migrants between two groups. For this 

reason we feel that the level of inference from population synchrony analyses is relatively low. 

Habitat Characteristics 

Identifying Hydrologic Regions in Puget Sound 

Methods 

The TRT performed a set of analyses intended to classify all the rivers and streams in 

Puget Sound into hydrologic regions based on hydrologic patterns, mean basin elevation, and 

mean annual precipitation. An understanding of regional hydrologic regimes can provide 

insights into the selective environment fish experience and therefore illuminate a potential 

influence on population structure. These analyses are especially useful in areas where genetic, 

abundance, and life history data are not informative. For example winter hydrologic conditions, 

h as low flow and cold temperatures in high elevations, influence the intra-gravel 

iro ment and the success of overwintering of eggs and alevins (Blachut 1988), whic

fect spawn timing. 

The TRT used a two-step process to i

inc groups of streams based on the overall hydrograph pattern observed at a sample of 

gauges. Second the team used a classification 

regions across Puget Sound to describe hydrographs in areas where gauge data were not 

available. These are the two steps: 

Identifying stream-flow patterns based on annual hydrograph―The TRT obtain

time series of monthly mean discharge (cubic feet per second) at 52 USGS stream g

 the Washington Department of Ecology (USGS 2005). The tim

series included 8–74 years of data, depending on the gauge. The USGS gauges included in thi

analysis had at least a 10-year period of record, little to no artificial regulation, and were locate

within or adjacent to Chinook salmon spawning habitat. 

The log-transformed monthly means were averaged over all years for the gauge, 

producing an average annual hydrograph. The average hydrographs were treated as variable

with 12 observations (one observation per month), and rank correlation coefficients between 

these variables were computed for all pairs of gauges. Using correlation coefficients to mea

83
similarity between gauges emphasizes the timing and relative magnitude of peak and low flows, 

ignoring differences in the total magnitude of flow. The correlation matrix was used in a 

UPGMA cluster analysis with 1 – rs as the distance measure. 

Identifying hydrologic regions using predictive models―Because gauge data were not 

available for all stream reaches where Chinook salmon are known to spawn, the TRT developed 

empirical models to predict hydrograph patterns using known, easily measured variables. The

team chose average basin elevation, defined as the average elevation of all points upslope of a 

given point, and average annual precipitation as predictors for several reasons. First previous 

studies in Puget Sound (Beechie 1992, Amerman and Orsborn 1987) found predictive 

relationships between these variables and a variety of hydrologic characteristics. Measurements 

of elevation and precipitation were then easily obtained for the entire region. Because the 

models were fitted using data on gauge characteristics reported by the USGS, rather than 

geographic information system (GIS) data layers, three gauges were omitted from the analysis 

because elevation and precipitation measurements were not available. 

The TRT developed models using a parametric version of classification tree analysis 

(Venables and Ripley 1994). Classification tree analysis predicts group membership based on 

known variables, enabling us to predict hydrograph patterns for all of Puget Sound based on 

patterns at a set of stream-flow gauges. These classification tree models use a recursive 

partitioning algorithm to construct a binary decision tree, similar to a taxonomic key, in which 

observations are classified into predefined categories (in this case the four hydrograph types—R, 

RS, SR, and S—identified in the previous subsection on stream-flow patterns) based on their 

scores on one or more predictor variables (elevation and precipitation). Data for mean basin 

elevation and mean annual precipitation were obtained for each USGS gauge from Williams et 

al. (1985). 

In the classification tree analysis the observations in each tree node are partitioned into 

two daughter nodes by choosing the split along the range of a single predictor that maximizes the 

log-likelihood over all possible splits of all predictors, where the likelihood is based on a 

multinomial model for the frequencies of the categories (Venables and Ripley 1994). The 

splitting continues until a stopping criterion is reached (in this case nodes were not split when 

they contained two or fewer observations). The tree can then be “pruned” by sequentially 

eliminating terminal nodes and computing AIC for each nested subtree (Burnham and Anderson 

1998, Venables and Ripley 1994). The subtree with the lowest AIC score is selected as the most 

parsimonious model for the data. Because the sample size was small relative to the number of 

estimated parameters in the fully fitted tree, the TRT used the small-sample correction AICc in 

addition to AIC (Burnham and Anderson 1998), and compared the results of pruning on the two 

criteria. 

Based on those break points the TRT mapped the resulting hydrologic regions using GIS 

analysis. The team used 30-m digital elevation model data from USGS to calculate mean basin 

elevation across Puget Sound. We combined the mean basin elevation data with mean annual 

precipitation data for 1961–1990 (Daly and Taylor 1998) to produce a hydroregion map. 

84
Results 

Identifying stream-flow patterns based on annual hydrographs—Hydrographs of 

mean monthly flow showed three basic patterns: 

1. A rainfall-dominated pattern (hereafter R) with a winter peak and low flows in 

August–September (e.g., Issaquah Creek). 

2. A snowmelt-dominated pattern (S) with a peak in May–July and low flows in late winter 

or early spring (e.g., Suiattle River). 

3. An intermediate pattern with both rainfall- and snowmelt-driven peaks and low flows 

typically in August–September (Figure A-7). 

The intermediate category was further subdivided into streams (e.g., Duckabush River) whose 

highest peaks are driven by rainfall (RS) and those (e.g., White River) whose highest peaks are 

due to snowmelt (SR). This classification was supported by the UPGMA dendrogram (not 

shown), which showed four main clusters of streams based on hydrograph pattern. 

Identifying hydrologic regions using predictive models—The classification tree 

analysis resulted in an AIC-selected classification tree with six terminal nodes. (The terminal 

nodes represent the predictive classification scheme defined by the tree, with predicted values 

equal to the most common category in the node.) This tree had an overall misclassification rate 

of 6/49. That is, the predicted hydrograph category was incorrect for six of the 49 gauges in the 

sample, whereas the tree with the lowest value of AICc had only two terminal nodes and an 

overall misclassification rate of 13/49. Because the AIC-selected tree seemed clearly overfitted, 

but the two-node, AICc-selected tree was not predicatively useful, the TRT chose a tree of 

intermediate complexity to use for prediction. This tree had five terminal nodes and an overall 

misclassification rate of 7/49 (Figure A-7). For this tree, delta (Δ)AIC = 0.5 and ΔAICc = 8.65, 

where ΔAICi = AICi – min{AICj for all candidate models j}. Thus it was not the most 

parsimonious model, but it represented a reasonable compromise between the two criteria. 

In the final tree the discriminations among hydrograph types were based primarily on 

average basin elevation (Figure A-7). Streams with an average elevation of below 2,595 feet 

generally had type R hydrographs. Between 2,595 and 3,110 feet elevation, most streams were 

type RS. Streams between 3,110 and 4,285 feet elevation were generally type SR, as were 

streams higher than 4,285 feet that experience less than 101.5 inches of precipitation annually. 

Only streams higher than 4,285 feet with greater than 101.5 inches of precipitation were 

predicted to be type S. Figure A-8 shows the resulting four hydroregions mapped across Puget 

Sound, together with the SASSI Chinook salmon populations. 

Comparisons of Stream Temperature among Puget Sound 

Chinook Salmon Spawning Areas 

Methods 

Time series of monthly temperature at 47 river and stream monitoring stations were 

obtained from the Washington Department of Ecology. The data consist of temperatures taken 

once to several times a month, for portions of the year only or for all months. The TRT 

conducted two analyses of stream temperature. First the team examined the pattern of stream 

85
Figure A-7. Classification tree used to predict hydrograph type from average basin elevation (ft) and 

average annual precipitation (in). The hydrograph categories (R = rainfall dominated, RS = 

rainfall/snowmelt dominated, SR = snowmelt/rainfall dominated, S = snowmelt dominated) 

correspond to the clusters identified by UPGMA cluster analysis; typical examples of each 

category are shown. The category indicated on each terminal node (rectangles) is the predicted 

hydrograph type for the observations in that node. The fraction of observations in each node 

(ovals) that are incorrectly classified is indicated under the node. 

86
Figure A-8. Runoff-pattern regions in Puget Sound derived from mean basin elevation and mean annual 

precipitation using classification tree analysis. 

87
temperatures throughout all months of the year (contingent on available data). For this analysis, 

we calculated monthly mean temperatures for each station across all years, producing an average 

annual stream temperature profile. Then similar to the stream hydrograph pattern analysis, the 

team treated mean annual temperature profiles as variables and calculated rank correlation 

coefficients for pairwise combinations of variables. We used the resulting correlation matrix in 

UPGMA cluster analysis. 

In the second analysis the TRT evaluated differences between the average stream 

temperatures during the incubation period of the various Chinook populations. The team 

restricted data to temperatures during the three-month period following the median spawning 

date for each index area where Chinook are surveyed. Note that Chinook spawning surveys were 

not conducted in the vicinity of 11 of the 47 temperature monitoring stations. In these cases we 

used the median spawn date for the nearest index area to choose the beginning of the 3-month 

incubation period. We averaged stream temperatures over the 3-month incubation period for 

each station and across all years to produce an average monthly stream temperature. We 

calculated differences between average monthly stream temperatures for pairwise combinations 

of all stations. We used the resulting matrix for UPGMA cluster analysis. 

Results 

In the first analysis, annual stream temperature profiles, all stations demonstrated a 

similar pattern; temperatures are cool in the winter, rise to a peak in summer, and decline again 

during fall. The primary differences in temperature profiles were apparent in the incline and 

decline and range of temperatures. These differences, however, were not well resolved through 

UPGMA cluster analysis. The UPGMA dendrogram did not show any distinct stream groupings 

based on similar temperature profiles. Similarly differences in stream temperature during the 

Chinook salmon incubation period were not found with UPGMA cluster analysis. The resulting 

dendrogram (Figure A-9) did not show any notable groupings between temperature stations. 

EPA Ecoregions 

The U.S. Environmental Protection Agency (EPA) defines ecoregions based on a number 

of characteristics—geology, physiography, soils, land-use patterns, vegetation, climate, wildlife, 

and hydrology. The ecoregion definitions are based on scales over which the characteristics are 

relatively homogeneous. These ecoregions may partly describe differences in the selective 

environments that Chinook salmon experience throughout Puget Sound. The EPA defines 

ecoregions on a number of different spatial scales—the TRT summarized two of the EPA scales 

(or levels) for evaluating habitat characteristics and their possible relation to population 

structure. The EPA divides the North American continent into 78 regions at level III. Four main 

level III ecoregions occur within Puget Sound; North Cascades, Puget Lowland, Cascades, and 

the Coast Range. The EPA also developed finer scale level IV ecoregions for portions of the 

United States, including Puget Sound (Figures A-10 and A-11): 15 main level IV ecoregions 

occur within Puget Sound. 

88
Figure A-9. Clustering of Puget Sound Chinook salmon spawning areas based on differences in mean 

temperature during Chinook salmon egg incubation. Mean incubation temperature in each area is 

based on an assumed three-month incubation period beginning on the median date of Chinook 

salmon spawning in the nearest index survey area. Absolute difference in mean temperature was 

the dissimilarity measure used in the UPGMA cluster analysis. Locations signify rivers unless 

otherwise noted. 

89
Figure A-10. U.S. Environmental Protection Agency level IV ecoregions in Puget Sound. Ecoregions 

represent areas of general similarity in an ecosystem, and in quality and quantity of 

environmental resources. Source: EPA 2006. 

90
91

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

Central Puget lowland

Cascade subalpine/alpine

Eastern Puget riverine lowlands

Eastern Puget uplands

Fraser lowland

High Olympics

Low Olympics

North Cascades highland forests

North Cascades lowland forests

North Cascades subalpine/alpine

Olympic rainshadow

San Juan Islands

Southern Puget prairies

Volcanics

estern Cascades lowlands and valleys

Western Cascades montane highlands

Hectares

H t

Hectares 

W

Figure A-11. Sum of areas (in hectares) for the level IV ecoregions occurring in the Puget Sound ESU 

(including areas outside of population boundaries and the islands). Source: EPA 2006. 

Geology 

The USGS developed geologic maps for various western states using 40 different 

classifications. Distinct geological characteristics may partly describe differences in the 

selective environments that Chinook salmon experience throughout Puget Sound. The Interior 

Columbia Basin Ecosystem Management Project digitized and combined these state maps into 

one map (ICBEMP 2006). The TRT simplified the 40 geologic classifications into 10 main 

categories: alluvium, calc-alkaline igneous, carbonate, glacial drift, gneiss, mafic igneous, 

meta-sandstone, phyllite and schist, sedimentary, and ultramafic (Figure A-12, Table A-3). 
Figure A-12. Geology of Puget Sound region using 10 major lithologies from U.S. Geological Survey 

data. Source: ICBEMP 2006. 

92
Table A-3. Sum of acres (in hectares) for the lithology classes occurring in the Puget Sound ESU 

(including areas outside of population boundaries and the islands). Source: ICBEMP 2006. 

Broad geological type Lithology ha 

Igneous 

 Calc-alkaline intrusive 283,265.31

 Calc-alkaline meta-volcanic 3,072.52

 Calc-alkaline volcanoclastic 395,386.76

 Granitic gneiss 166,816.93

 Mafic gneiss 2,963.09

 Mafic intrusive 6,141.56

 Mafic meta-volcanic 373.22

Mafic volcanic flow 260,110.24 

 Ultramafic 14,507.79

Igneous totals 1,132,637.40

Metamorphic 

 Interlayered meta-sedimentary 61,837.42

Mafic schist and greenstone 36,196.50 

 Meta-sandstone 200,468.04

 Meta-sedimentary phyllite and schist 112,879.32 

Metamorphic totals 411,381.29 

Sedimentary 

 Carbonate 5,211.31

 Conglomerate 19,121.28

 Sandstone 302,058.78

 Siltstone 108,088.38

Sedimentary totals 434,479.75 

Unconsolidated sediments

 Alluvium 405,755.29

 Glacial drift 1,009,597.13

 Landslide 13,604.26

Unconsolidated sediments totals 1,428,956.69

Total ha in Puget Sound ESU region 3,407,455.14

93
94
95

Appendix B: Data Tables 

Appendix B includes results from data analyses conducted as part of the Technical 

Recovery Team’s (TRT’s) efforts to identify demographically independent populations of 

Chinook salmon (Oncorhynchus tshawytscha) in Puget Sound. Not all data were explicitly 

considered by the TRT for each indicator—they are included in this technical memorandum for 

completeness and to spur collection of additional data. The data are summarized in a matrix 

format for each watershed. Values in each cell represent some measure of distance or difference 

between the two sites being considered. Methods for calculating differences between sites for 

each data type are described in the body of this technical memorandum or in this appendix. The 

tables in Appendix B are: 

• B-1―Estimates of theta (θ) and Nm

• B-2―Estimates of time since divergence between sites 

• B-3―Cavalli-Sforza and Edwards’ chord distance

• B-4―Nei's genetic distance 

• B-5―P values from pairwise G-tests for heterogeneity in allele frequencies at 29 loci 

• B-6―Absolute differences in the overall mean of yearly weighted mean spawning dates 

• B-7―Dissimilarity matrix for smolt-spawner age distributions 

• B-8―Absolute differences in mean spawner length of Puget Sound Chinook salmon 

• B-9―Correlation coefficients on residuals from autoregressive trend model: 

product-moment correlations and Spearman’s rank correlations 

• B-10―Correlation matrix for mean monthly discharge at USGS stream gauges in Puget 

Sound 

• B-11―Absolute difference in mean temperature during incubation for Chinook salmon in 

Puget Sound 
Table B-1 Estimates of θ (above dashes) and Nm (below dashes). There is no comparison for the Strait of Juan de Fuca du

Locations signify rivers unless otherwise noted. Data source: WDFW no date. 

Nooksack River basin 

South Fork Nooksack North Fork Nooksack 

South Fork Nooksack North Fork Nooksack 

— 

10.321 

0.024 

— 

Skagit River basin 

Lower Skagit Upper Skagit Lower Sauk Upper Sauk Suiattle Cascade

Lower Skagit — 0.016 0.157 0.013 0.025 0.089 Upper Skagit 15.605 — 0.111 0.015 0.046 0.110 Lower Sauk 1.342 2.011 — 0.091 0.237 0.376 Upper Sauk 19.076 15.942 2.499 — 0.057 0.145 Suiattle 9.899 5.207 0.807 4.157 — 0.028Cascade 2.558 2.031 0.416 1.477 8.635 —Stillaguamish River basin 

North Fork Stillaguamish South Fork Stillaguamish 

North Fork Stillaguamish South Fork Stillaguamish 

— 

4.679 

0.051 

— 

Snohomish River basin

Skykomish Sultan Wallace Bridal Veil Creek Snoqualmie 

Skykomish — 0.012 0.003 0.000 0.007 Sultan 19.999 — 0.008 0.010 0.013Wallace 82.641 30.216 — 0.000 0.005 Bridal Veil Creek –753.262 23.712 –521.083 — 0.006 Snoqualmie 35.317 19.582 52.084 40.707 — 

96
Table B-1 continued. Estimates of θ (above dashes) and Nm (below dashes). There is no comparison for the Strait of Juan 

of data. Locations signify rivers unless otherwise noted. Data source: WDFW no date. 

Lake Washington

Cedar Sammamish Issaquah Creek 

Cedar Sammamish Issaquah Creek 

—

32.520 

21.328 

0.008 

— 

20.488 

0.012

0.012 

— 

South Puget Sound 

Duwamish/Green Newaukum Creek Puyallup White Nisqually Deschutes

Duwamish/Green — 0.004 0.024 0.005 0.001Newaukum Creek –295.061 — 0.007 0.021 0.002 0.002 Puyallup 59.688 36.151 — 0.019 0.016 0.008White 10.009 11.559 12.663 — 0.019 0.026 Nisqually 50.275 135.916 15.223 13.156 — 0.012

Deschutes 416.417 103.787 29.424 9.524 20.160 —

Hood Canal

Skokomish Hamma Hamma

Skokomish Hamma Hamma 

— 

20.935 

0.012

— 

97
Table B-2. Estimates of time since divergence between sites (t, in generations). There are no comparisons for Lake Washi

the Strait of Juan de Fuca due to a lack of data. Locations signify rivers unless otherwise noted. Data source: WD

Nooksack River basin 

South Fork Nooksack North Fork Nooksack 

South Fork Nooksack North Fork Nooksack 

— 

7.10 — 

Skagit River basin 

Lower Skagit Upper Skagit Lower Sauk Upper Sauk Suiattle Cascade

Lower Skagit — Upper Skagit 98.4

0 — 

Lower Sauk 324.80 274.30 — Upper Sauk 17.9

0 24.7

0 96.0

0 — 

Suiattle 41.90 94.40 313.40 55.00 — Cascade 67.3

0 90.1

0 285.10 84.4

0 16.6

0

—

Stillaguamish River basin 

North Fork Stillaguamish South F

ork Stillaguamish 

North Fork Stillaguamish South F

ork Stillaguamish 

— 

25.70 — 

Snohomish River basin

Skykomish Wallace Bridal Veil Creek Snoqualmie 

Skykomish — Wallace 5.10 — Bridal Veil Creek 

–0.60 

–0.60 — 

Snoqualmie 19.3

0 7.20 10.3

0 — 

98
Table B-2 continued. Estimates of time since divergence between sites (t, in generations). There are no comparisons for L

Canal, or the Strait of Juan de Fuca due to a lack of data. Locations signify rivers unless otherwise noted. Data date. 

South Puget Sound

Duwamish/Green Puyallup White Nisqually

Duwa

mish/Green — 

Pu

yallup 19.9

0 — 

White 

—

Nisqually 7.20 20.4

0

—

99
Table B-3. Cavalli-Sforza and Edwards’ chord distance. There is no comparison for the Strait of Juan de Fuca due to a lac

signify rivers unless otherwise noted. Data source: WDFW no date. 

Nooksack River basin 

South Fork Nooksac

k North Fork 

Nooksack 

South Fork Nooksack North Fork Nooksack 

— 

0.0748 — 

Skagit River basin 

Lower Skagit Upper Skagit Lower Sauk Upper Sauk Suiattle Cascade 

Lower Skagit — Upper Skagit

0.0382 

—

Lower Sauk 0.0573 

0.0514 — 

Upper Sauk 0.0528 0.0385 

0.05

60 

—

Suiattle 0.0523 0.0317 0.0543 0.0418 — Cascade 0.0575 0.0439 0.0669 0.0491 0.0439

—

Stillaguamish River basin 

North Fork Stillaguamish South F

ork Stillaguamish 

North Fork Stillaguamish South F

ork Stillaguamish 

— 

0.0713 — 

Snohomish River basin

Skykomish Sultan Wallace Bridal Veil Creek Snoqualmie 

Skykomish — Sultan 0.0518 — Wallace 0.0418 0.0451 — Bridal Veil Creek 0.0433 0.0513 0.0437 — Snoqualmie 0.0486 0.0566 0.0536 0.0573 — 

100
Table B-3 continued. Cavalli-Sforza and Edwards’ chord distance. There is no comparison for the Strait of Juan de Fuca d

Locations signify rivers unless otherwise noted. Data source: WDFW no date. 

Lake Washington

Cedar Sammamish Issaquah Creek

Cedar Sammamish Issaquah Creek 

— 

0.0573 

0.0472 

— 

0.0478 — 

South Puget Sound

D

uwamish/Green Newaukum Creek Puyallup White Nisqually Deschutes

Duwa

mish/Green — 

Newaukum Creek 

0.0244 

—

Pu

yallup 

0.0394 0.0461 — 

White 

0.0511 0.0531 0.0614 — 

Nisqually 0.0533 0.0499 0.0627 0.0677 

—

Deschutes 0.0356 0.0361 0.0480 0.0595 0.0596

—

Hood Canal

Skokomish Hamma Hamma

Skokomish Hamma Hamma 

— 

0.0488 — 

101
Table B-4. Nei's (1978) genetic distance. There are no comparisons for Hood Canal or the Strait of Juan de Fuca due to a 

signify rivers unless otherwise noted. Data source: WDFW no date. 

Nooksack River basin 

South F

ork Nooksack North Fork Nooksack 

South Fork Nooksack North Fork Nooksack 

— 

0.003 — 

Skagit River basin 

Lower Skagit Upper Skagit Lower Sauk Upper Sauk Suiattle Cascade 

Lower Skagit — Upper Skagit 0.0007 — Lower Sauk 0.00

05 0.0002 — 

Upper Sauk 0.0009 0.0007 0.0004 — Suiattle 0.0016 0.0006 

0.0009 0.0007 — 

Cascade 0.0012 0.0004 0.0011 0.0008 0.0009 — Stillaguamish River basin

North Fork Stillaguamish South F

ork Stillaguamish 

North Fork Stillaguamish South F

ork Stillaguamish 

— 

0.0043 — 

Snohomish River basin

Skykomish Sultan Wallace Bridal Veil Creek Snoqualmie 

Skykomish — Sultan 0.0018 — Wallace 0.0000 0.0010 — Bridal Veil Creek 0.0000 0.0018 0.0000 — Snoqualmie 0.0008 0.0024 0.0009 0.0015 

—

102
Table B-4 continued. Nei's (1978) genetic distance. There are no comparisons for Hood Canal or the Strait of Juan de Fuc

Locations signify rivers unless otherwise noted. Data source: WDFW no date. 

Lake Washington

Cedar Sammamish Issaquah Creek

Cedar Sammamish Issaquah Creek 

— 

0.0013 

0.0007 

—

0.0008 — 

South Puget Sound 

Duwamish/Green Newaukum Creek Puyallup White Nisquall

y Deschutes

Duwa

mish/Green — 

Newaukum Creek 0.0000 — Pu

yallup 0.0005 0.0007 — 

White 0.0010 0.00

08 0.0008 — 

Nisqually 0.0004 0.00

00 0.0010 

0.0015 — 

Deschutes 0.0002 0.0004 0.0003 0.0014 0.0007 

—

103
Table B-5. P values from pairwise G-tests for heterogeneity in allele frequencies at 29 loci. There is no comparison for the 

due to a lack of data. Locations signify rivers unless otherwise noted. Data source: WDFW no date. 

Nooksack River basin 

South Fork Nooksack North Fork Nooksack 

South Fork Nooksack North Fork Nooksack 

— 

0.0000 — 

Skagit River basin 

Lower Skagit Upper Skagit Lower Sauk Upper Sauk Suiattle Cascade 

Lower Skagit — Upper Skagit 0.0086 — Lower Sauk 0.0006 

0.00

42 — 

Upper Sauk 0.0000 0.0032 

0.00

09 — 

Suiattle 0.0000 0.0000 0.0000 0.0000 — Cascade 0.0000 0.0043 0.0000 0.0011 0.00

02 

—

Stillaguamish River basin 

North Fork Stillaguamish South F

ork Stillaguamish 

North Fork Stillaguamish — South F

ork Stillaguamish 0.0000 — 

Snohomish River basin

Bridal Veil 

 Skykomish Sultan Wallace Creek Snoqualmie

Skykomish — Sultan 0.0001 — Wallace 0.2673 0.0273 — Bridal Veil Creek 0.2276 0.0011 0.3247 — Snoqualmie 0.0009 0.0000 0.0002 0.0000 — 

104
Table B-5 continued. P values from pairwise G-tests for heterogeneity in allele frequencies at 29 loci. There is no compar

Juan de Fuca due to a lack of data. Locations signify rivers unless otherwise noted. Data source: WDFW no d

Lake Washington

Cedar Sammamish Issaquah Creek

Cedar — Sammamish 0.0000 — Issaquah Creek 0.0029 0.0384 — South Puget Sound 

Duwamish/Green Newaukum Creek Puyallup White Nisquall

y Deschutes

Duwa

mish/Green — 

Newaukum Creek 0.6

926 — 

Pu

yallup 0.0111 0.0013 — 

White 0.0000 0.0000 0.0000 — 

Nisqually 0.0071 0.0263 0.0006 0.0

000 

—

Deschutes 0.1283 0.1593 0.0073 0.0

000 0.0013

—

Hood Canal

Skokomish Hamma Hamma

Skokomish Hamma Hamma 

—

0.1359 — 

105
Table B-6. Absolute differences (d) in the overall mean of yearly weighted mean spawning dates. Bold = significant diffe

t-tests using a basinwide Bonferroni-adjusted alpha level. Italics = no test could be performed because fewer than were available. Locations signify rivers unless otherwise noted. Data source: WDFW no date. 

Nooksack River basin 

Nooksack South Fork Nooksack Middle Fork Nooksack 

North Fork Nooksack 

Kendall Creek Canyon C

Nooksack — 

South Fork Nooksack 9.20 — Middle Fork Nooksack 11.10 1.90 — 

North Fork Nooksack 

Kendall Creek 17.20 8.00 6.10 — 

Canyon Creek 4.40 13.60 15.50 21.60 — 

Skagit River basin 

Lower 

Skagit 

Upper 

Skagit

Lower 

Sauk 

Upper 

Sauk 

Suiattle 

Upper Skagit 

Illabot Creek Casc

Big 

Creek 

Tenas Creek

Buck 

Creek

Lime

Creek 

Sulphur

Creek 

Lower Skagit — Upper Skagit 17.90 — Lower Sauk 16.00 1.90 — Upper Sauk 27.20 9.30 11.20 — Suiattle 

Big Creek 61.40 43.60 45.50 34.30 — Tenas Creek 65.00 47.10 49.00 37.80 3.60 — 

Buck Creek 56.30 38.40 40.30 29.10 5.20 8.70 — 

Lime Creek 55.70 37.90 39.80 28.60 5.70 9.30 0.50 — Sulphur Creek 53.30 35.40 37.30 26.10 8.20 11.70 3.00 2.50 — 

Upper Skagit Illabot Creek 15.60 2.30 0.40 11.60 45.90 49.40 40.70 40.20 37.70 — Cascade 24.90 7.10 8.90 2.30 36.50 40.10 31.40 30.80 28.30 9.40 — 

Upper Skagit Bacon Creek 21.70 3.80 5.70 5.50 39.70 43.30 34.60 34.00 31.60 6.10 3.2

106
Table B-6 continued. Absolute differences (d) in the overall mean of yearly weighted mean spawning dates. Bold = signif

two-sample t-tests using a basin-wide Bonferroni-adjusted alpha level. Italics = no test could be performed becausannual means were available. Locations signify rivers unless otherwise noted. Data source: WDFW no date. 

Stillaguamish River basin 

North Fork Stillaguamish South Fork Stillaguamish 

North Fork Stillaguamish Squire Creek Jim Creek 

North Fork Stillaguamish — North Fork Stillaguamish 

Squire Creek 5.30 — 

South Fork Stillaguamish 

Jim Creek 20.90 15.60 — 

Snohomish River basin 

Snohomish Sultan Wallace Bridal Veil Creek Snoqualmie Snoqualmie-Tolt 

Snohomish —Sultan 9.30 —Wallace 11.80 2.50 —Bridal Veil Creek 2.70 6.60 9.10 — Snoqualmie 3.00 6.30 8.80 0.30 — 

Snoqualmie-Tolt 2.70 12.00 14.50 5.40 5.70 — 

Lake Washington 

Swamp Creek

North Lake Washington

North Creek Big Bear Creek Cottage Lake Creek Issaquah-Holder creeks 

North Lake Washington 

Swamp Creek — 

North Creek 13.60 — 

Big Bear Creek 19.50 5.90 — Cottage Lake Creek 18.30 4.60 1.20 —

Issaquah-Holder creeks 19.80 6.20 0.30 1.50 —Cedar 21.70 8.10 2.20 3.50 1.90 

107
Table B-6 continued. Absolute differences (d) in the overall mean of yearly weighted mean spawning dates. Bold = signif

two-sample t-tests using a basin-wide Bonferroni-adjusted alpha level. Italics = no test could be performed becausannual means were available. Locations are rivers unless otherwise noted. Data source: WDFW no date. 

South Puget Sound

Green

en White Puyallup Nisqually SoDu re wamish/G

CrispCreek

Newaukum

Creek 

Puyallup-Clarks 

Creek 

Stuck 

Boise Creek

Clearwater 

Greenwater Carbon 

South Prairie 

Creek 

powsin

Ka 

Creek

Nisqually

Ohop Creek

Skookum 

Creek Coulter Creek 

Burley Creek

Duwamish/Green —Green 

Crisp Creek 8.30 —

Newaukum Creek 2.40 5.80 —

Puyallup-Clarks Creek 3.70 12.00 6.20 —White River 

Stuck River 3.30 4.90 0.90 7.10 —

Boise Creek 4.40 3.90 2.00 8.10 1.10 —

Clearwater River 10.10 1.90 7.70 13.80 6.80 5.70 —

Greenwater River 14.20 6.00 11.80 18.00 10.90 9.80 4.10 —

Puyallup 

Carbon River 1.10 7.10 1.30 4.90 2.20 3.30 9.00 13.10 —

South Prairie Creek 5.20 3.00 2.80 8.90 1.90 0.80 4.90 9.00 4.10 —

Nisqually River 

Kapowsin Creek 1.40 9.60 3.80 2.30 4.70 5.80 11.50 15.60 2.50 6.60 —

Nisqually 6.50 14.70 8.90 2.70 9.80 10.90 16.60 20.70 7.60 11.70 5.10 —

Ohop Creek 9.10 17.40 11.60 5.40 12.50 13.60 19.30 23.40 10.30 14.40 7.80 2.70 —

South Sound 

Skookum Creek 10.90 19.20 13.30 7.20 14.20 15.30 21.00 25.10 12.00 16.10 9.50 4.40 1.70 —

Coulter Creek 2.10 10.30 4.50 1.70 5.40 6.50 12.20 16.30 3.20 7.30 0.70 4.40 7.10 8.80 —

Burley Creek 6.10 14.40 8.50 2.40 9.40 10.50 16.20 20.30 7.20 11.30 4.70 0.40 3.10 4.80 4.00 —

Blackjack Creek 21.70 30.00 24.20 18.00 25.10 26.10 31.80 36.00 22.90 27.00 20.40 15.30 12.60 10.80 19.70 15.60 

Gorst Creek 0.60 8.90 3.10 3.10 4.00 5.00 10.70 14.90 1.70 5.80 0.80 5.90 8.50 10.30 1.40 5.50 

Clear Creek 1.00 7.30 1.50 4.70 2.40 3.50 9.20 13.30 0.20 4.30 2.30 7.40 10.10 11.90 3.00 7.00 

Dogfish Creek 4.70 12.90 7.10 0.90 8.00 9.10 14.80 18.90 5.80 9.90 3.30 1.80 4.50 6.20 2.60 1.40 

108
Table B-6 continued. Absolute differences (d) in the overall mean of yearly weighted mean spawning dates. Bold = signif

two-sample t-tests using a basin-wide Bonferroni-adjusted alpha level. Italics = no test could be performed becausannual means were available. Locations signify rivers unless otherwise noted. Data source: WDFW no date. 

Hood Canal

Skokomish South Fork Skokomish Hamma Hamma Duckabush Dosewallips

Skokomish — South Fork Skokomish 17.8 — Hamma Hamma 8.9 9.0 — 

Duckabush 14.7 3.1 5.8 — Dosewallips 1.5 19.3 10.4 16.2 —

Strait of Juan de Fuca 

Dungeness Grey Wolf Elwha

Dungeness — 

Grey Wolf 21.1 — 

Elwha 4.1 25.2 —

109
Table B-7. Dissimilarity matrix (1 − % overlap) for smolt-spawner age distributions. Bold = significant differences in two

basin-wide Bonferroni-adjusted alpha level. There is no comparison for Lake Washington due to a lack of data. L

unless otherwise noted. Data source: WDFW no date. 

Nooksack River basin 

South Fork Nooksack North Fork Nooksack 

South Fork Nooksack North Fork Nooksack 

— 

0.32 — 

Skagit River basin 

Skagit Sauk 

Suiattle Upper Skagit

Buck Creek Lime Creek Sulphur Creek Illabot Creek Cascade Clark C

Skagit — Sauk 0.32 — Suiattle 

Buck Creek 0.38 0.19 — 

Lime Creek 0.48 0.27 0.12 — 

Sulphur Creek 0.69 0.46 0.31 0.27 — 

Upper Skagit

Illabot Creek 0.45 0.42 0.36 0.37 0.48 — 

Cascade 0.40 0.27 0.18 0.28 0.37 0.19 — 

Clark Creek 0.64 0.59 0.52 0.54 0.48 0.26 0.38 — 

Stillaguamish River basin 

North Fork Stillaguamish South Fork Stillaguamish 

North Fork Stillaguamish South Fork Stillaguamish 

— 

0.11 — 

110
Table B-7 continued. Dissimilarity matrix (1 − % overlap) for smolt-spawner age distributions. Bold = significant differen

t-tests using a basin-wide Bonferroni-adjusted alpha level. There is no comparison for Lake Washington due to a lsignify rivers unless otherwise noted. Data source: WDFW no date.

Snohomish River basin

Snoqualmie Tokul Creek Wallace May Creek 

Snoqualmie Tokul Creek Wallace May Creek 

— 

0.33 

0.540.54

— 

0.620.64

— 

0.62 — 

South Puget Sound 

Green Puyallup 

Duwamish/Green Big Soos Creek Newaukum Creek Voight Creek South Prairie Creek Des

Duwamish/Green — Green 

Big Soos Creek 0.14 — Newaukum Creek 0.16 0.25 — 

Puyallup 

Voight Creek 0.18 0.09 0.32 — South Prairie Creek 0.28 0.14 0.31 0.18 — 

Deschutes 0.17 0.13 0.28 0.11 0.22 

111
Table B-7 continued. Dissimilarity matrix (1 − % overlap) for smolt-spawner age distributions. Bold = significant differen

t-tests using a basin-wide Bonferroni-adjusted alpha level. There is no comparison for Lake Washington due to a lsignify rivers unless otherwise noted. Data source: WDFW no date.

Hood Canal

Skokomish Skokomish Purdy Creek Finch Creek 

Skokomish Skokomish Purdy Creek 

Finch Creek 

—

0.09 

0.13 

— 

0.19 — 

Strait of Juan de Fuca 

 Dungeness Elwha 

Dungeness — Elwha 0.41 — 

112
Table B-8. Absolute differences in mean spawner length (post-orbital hypural length of age-4 fish, cm) of Puget Sound Ch

and broodyears for each stock are pooled. There are no comparisons for Nooksack River basin, Lake Washington, 

of Juan de Fuca due to lack of data. Locations signify rivers unless otherwise noted. Data source: WDFW no date

Skagit River basin

Lower Skagit Up

per Skagit Suiattle 

Lower Skagit Upper Skagit

Suiattle 

— 

4.58 

4.61 

— 

9.19

—

Stillaguamish River basin 

North Fork Stillaguamish South 

F

ork Stillaguamish 

North Fork Stillagua

mish 

South F

ork Stillagua

mish 

— 

4.75

—

Snohomish River basin

Skykomish Sultan Bridal Veil Creek Snoqualmie 

Skykomish — Sultan 

–1.53 — 

Bridal Veil Creek 8.85 10.3

7 — 

Snoqualmie 6.79 8.32 

–2.05 

—

South Puget Sound

Green- Pu

yallupNewaukum Cree

k South Prairie Creek White

GreenNewaukum Creek — Pu

yallupSouth Prairie Creek 0.91 — 

White 

6.01 6.92

—

113
Table B-9. Correlation coefficients on residuals from autoregressive trend model: product-moment correlations below diag

Spearman’s rank correlations above. Bold = significant differences in two-sample t-tests using a basin-wide Bonfe

level. Locations signify rivers unless otherwise noted. Data source: WDFW no date. 

Nooksack River basin 

South Fork

Nooksack North Fork Nooksack 

South Fork Nooksack North Fork Nooksack 

1.00 

1.00 

Skagit River basin 

Lower Skagit Upper Skagit Lower Sauk Upper Sauk Suiattle Cascade 

Lower Skagit 1.00 0.26 0.75 0.27 0.11 Upper Skagit 0.37 1.00 

0.35

0.22 0.34 

Lower Sauk 0.75 0.41 1.00 0.30 0.21 

Upper Sauk 0.07 0.20

0.16 1.00 0.12 

Suiattle 0.21 0.38

0.28 0.07 1.00 

Cascade 1.00

Stillaguamish River basin 

North Fork Stillag

uamish

South F

ork Stillagua

mish 

North Fork StillaguamishSouth F

ork Stillaguamish 

1.00 

0.51 

0.35

1.00 

Snohomish River basin 

Lower Snohomish Skykomish Sultan Wallace Bridal Veil Creek Snoqualmie 

Lower Snohomish 1.00 0.46 0.07 

Skykomish 1.00 Sultan 1.00 Wallace 

0.43 1.00 0.08

Bridal Veil Creek 1.00 

Snoqualmie 0.08 0.11 1.00

114
Table B-9 continued. Correlation coefficients on residuals from autoregressive trend model: product-moment correlations 

Spearman’s rank correlations above. Bold = significant differences in two-sample t-tests using a basin-wide Bonfe

level. Locations signify rivers unless otherwise noted. Data source: WDFW no date. 

Lake Washington 

Cedar North Lake Washington Sammamish Issaquah Creek 

Cedar 1.00 0.19 

North Lake Washington 0.62 1.00 Sammamish 1.00 

Issaquah Creek 1.00 

South Puget Sound 

Duwamish/

Green Puyallup White Nisqually Deschutes Miscellaneous 13 Miscellaneous 13

Duwamish/Green 1.00 0.21 –0.02 0.29 –0.10 0.02 –0.19 Puyallup 0.25 1.00 0.08 0.41 0.65 0.18 –0.08 

White 0.01 0.13 1.00 –0.09 0.07 0.46 –0.10 

Nisqually 0.17 0.27 –0.01 1.00 –0.10 0.31 –0.20 Deschutes –0.11 0.73 0.09 –0.10 1.00 –0.03 –0.39 Miscellaneous 13 0.02 0.25 0.59 0.41 0.02 1.00 0.00 

Miscellaneous 13A –0.20 0.02 –0.06 –0.11 –0.35 0.13 1.00 Miscellaneous 13B 0.06 –0.14 0.04 0.06 0.15 –0.03 –0.13 

Hood Canal

 Skokomish Hamma Hamma Duckabush Dosewallips

Skokomish 1.00 0.18 0.09 –0.13 

Hamma Hamma –0.03 1.00 –0.33 0.67 

Duckabush 0.03 –0.44 1.00 –0.02 

Dosewallips –0.09 0.76 –0.15 1.00 

115
Table B-9 continued. Correlation coefficients on residuals from autoregressive trend model: product-moment correlations 

Spearman’s rank correlations above. Bold = significant differences in two-sample t-tests using a basin-wide Bonfe

level. Locations signify rivers unless otherwise noted. Data source: WDFW no date. 

Strait of Juan de Fuca 

 Dungeness Elwha

Dungeness 1.00 –0.04 Elwha –0.18 1.00 

116
Table B-10. Correlation matrix (Spearman’s rank correlations r) for mean monthly discharge at USGS stream gauges in Pu

significant correlations using a basin-wide Bonferroni-adjusted alpha level. There is no correlation matrix for Strato lack of data. Locations signify rivers unless otherwise noted. Data source: WDFW no date. 

Nooksack River basin 

South Fork Nooksack 

North Fork Nooksack 1 2

North Fork Nooksack 1.00 

South Fork Nooksack 

1 0.49 1.00

2 0.52 0.98 1.00 

Skagit River basin 

Upper Skagit Upper Sauk Suiattle Lower Skagit 

1 2 1 2 3 1 2 1 2

Upper Skagit

1 1.00 

2 0.76 1.00 

Upper Sauk 

1 0.85 0.87 1.00 2 0.99 0.71 0.78 1.00 

3 0.90 0.64 0.65 0.94 1.00 

Suiattle 

1 0.64 0.78 0.58 0.62 0.52 1.00 

2 0.83 0.94 0.87 0.82 0.80 0.66 1.00 

Lower Skagit 

1 0.04 

–0.50 

–0.34 0.12 0.23 

–0.38 

–0.27 1.00 

2 0.18 

–0.35 

–0.19 0.23 0.32 

–0.36 

–0.14 0.89 1.00 

117
Table B-10 continued. Correlation matrix (Spearman’s rank correlations r) for mean monthly discharge at USGS stream ga

Bold = significant correlations using a basin-wide Bonferroni-adjusted alpha level. There is no correlation matrix Fuca due to lack of data. Locations signify rivers unless otherwise noted. Data source: WDFW no date. 

Stillaguamish River basin 

South F

ork Stillaguamish North Fork Stillaguamish 

1 2 3 4 1 2 

Mainstem 

Pilc

South F

ork Stillaguamish 

1 1.00 

2 0.85 1.00 

3 0.74 0.96 1.00 

4 0.99 0.89 0.78 1.00 

North Fork Stillaguamish 

1 0.72 0.92 0.87 0.74 1.00 

2 0.94 0.97 0.90 0.97 0.84 1.00 

Mainstem Stillaguamish 

Pilchuck Creek 0.97 0.83 0.71 0.98 0.70 0.93

118
Table B-10 continued. Correlation matrix (Spearman’s rank correlations r) for mean monthly discharge at USGS stream ga

Bold = significant correlations using a basin-wide Bonferroni-adjusted alpha level. matrix Fuca due to lack of data. rivers unless otherwise noted. 

There is no correlation 

Locations signify Data source: WDFW no date. 

Snohomish River basin 

Skykomish Snoqualmie 

Nor

South fork South fork North fork North Woods Tokul Raging For

1 2 tributary fork Skykomish Creek Creek Creek Tributary Tol

Skykomish 

South fork 1 1.00 South fork 2 0.84 1.00 North fork tributary 0.83 0.97 1.00 North fork 0.83 0.97 1.00 1.00 Skykomish 0.82 0.98 0.94 0.94 1.00 Woods Creek 0.13 0.39 0.29 0.29 0.47 1.00 

Snoqualmie 

Tokul Creek 0.20 0.36 0.26 0.26 0.45 0.95 1.00 Raging Creek 0.13 0.39 0.26 0.29 0.47 1.00 0.95 1.00 Tributary 0.13 0.39 0.29 0.29 0.47 1.00 0.95 1.00 1.00 North Fork Tolt 0.29 0.58 0.48 0.48 0.65 0.96 0.89 0.96 0.96 1.0

Lower Snohomish 

Pilchuck 0.08 0.31 0.22 0.22 0.40 0.97 0.90 0.97 0.97 0.9Pilchuck tributaries 0.10 0.36 0.27 0.27 0.43 0.99 0.94 0.99 0.99 0.9

119
Table B-10 continued. Correlation matrix (Spearman’s rank correlations r) for mean monthly discharge at USGS stream ga

Bold = significant correlations using a basin-wide Bonferroni-adjusted alpha level. There is no correlation matrix Fuca due to lack of data. Locations signify rivers unless otherwise noted. Data source: WDFW no date. 

Lake Washington 

North Lake Washington 

Issaquah Creek Bear Creek 1 Bear Creek 2 Tributary 1 Tributary 2 

Issaquah Creek 1.00 

North Lake Washington 

Bear Creek 1 0.96 1.00 Bear Creek 2 0.96 0.98 1.00 

Tributary 1 0.97 0.97 0.99 1.00 

Tributary 2 0.98 0.98 0.98 0.99 1.00 

South Puget Sound 

 Deschutes Puyallup 

 1 2 

Nisqually

tributary

South Sound 

Clover Creek Tributary 1 Pu

yallup Tributary 2 

Deschutes 

1 1.00 2 0.99 1.00 

Nisqually tri

butary 0.97 0.97 1.00 

South Sound Clover Creek 0.89 0.91 0.82 1.00 Pu

yallup 

Tributary 1 0.97 0.97 0.98 0.89 1.00 

Pu

yallup 0.66 0.64 0.71 0.49 0.64 1.00 

Tributary 2 0.97 0.95 0.97 0.80 0.95 0.73 1.00 

White 

White 0.08 0.08 0.13 0.15 0.12 0.69 0.17 Tributary 0.52 0.52 0.53 0.63 0.57 0.70 0.56 

120
Table B-10 continued. Correlation matrix (Spearman’s rank correlations r) for mean monthly discharge at USGS stream ga

Bold = significant correlations using a basin-wide Bonferroni-adjusted alpha level. There is no correlation matrix Fuca due to lack of data. Locations signify rivers unless otherwise noted. Data source: WDFW no date. 

Hood Canal

South F

ork Skokomish 

Dosewallips Duckabush Hamma Hamma 1 2 

Dosewallips 1.00 

Duckabush 0.84 1.00 

Hamma Hamma 0.78 0.95 1.00 South F

ork Skokomish 

1 0.27 0.61 0.71 1.00 

2 0.32 0.65 0.76 0.98 1.00 

Dewatto 0.29 0.59 0.72 0.97 0.99 

121
Table B-11. Absolute difference in mean temperature (°C) during incubation for Chinook salmon in Puget Sound. 

USGS stations over variable time intervals. cubation temperature is estimated as the mean temperature dperiod beginning on the median date of spawning in the nearest Chinook index survey area. 

on means over all years of available data. fferences in two-sample t tests using a basin-wide Balpha level. performed because fewer than three annual means were available. 

otherwise noted. asin due to lack of data. urce: WDFW no date

Tempe

Annual in

Differences presented 

Bold = significant di

Italics = no test could be Locations 

There is no chart for the Nooksack River b Data so

Skagit River basin 

Lower Skagit Upper Skagit 1 Upper Skagit 2 Upper Skagit Baker Lower Sauk 

Lower Skagit — 

Upper Skagit 1 0.40 — Upper Skagit 2 0.15 0.55 — 

Upper Skagit Baker 2.31 1.91 2.46 — 

Lower Sauk 0.35 0.05 0.50 1.96 — 

Stillaguamish River basin 

Main stem South fork 1 South fork 2 North fork 1 

Main stem — 

South fork 1 2.32 — South fork 2 2.05 0.27 — 

North fork 1 2.08 0.24 0.03 — 

122
Table B-11 continued. Absolute difference in mean temperature (°C) during incubation for Chinook salmon in Puget Soun

measured at USGS stations over variable time intervals. Annual incubation temperature is estimated as the mean t

three-month period beginning on the median date of spawning in the nearest Chinook index survey area. Differenc

table are based on means over all years of available data. Bold = significant differences in two-sample t tests using Bonferroni-adjusted alpha level. Italics = no test could be performed because fewer than three annual means were 

signify rivers unless otherwise noted. There is no chart for the Nooksack River basin due to lack of data. Data sou

Snohomish River basin 

Sky

o

mish Snoqualmie 

Snohomish 

Lower 

Snohomish-Pilchuck 1 2 1 2 Sultan Snoq

Snohomish — 

Lower Snohomish-Pilchuck 0.38 — Skykomish 

1 0.50 0.88 — 2 0.52 0.90 0.02 — 

Snoqualmie 

1 0.33 0.72 0.17 0.19 — 

2 1.02 1.40 0.52 0.50 0.69 — 

Sultan 0.01 0.39 0.49 0.51 0.32 1.01 — 

Snoqualmie-Tolt 0.58 0.19 1.08 1.10 0.91 1.60 0.59 

Lake Washington 

Sammamish Issaquah Creek Cedar 1 Cedar 2 

Samma

mish — 

Issaquah Creek 0.84 — Cedar 1 1.24 0.40 — 

Cedar 2 1.62 0.78 0.38 — 

123
Table B-11 continued. Absolute difference in mean temperature (°C) during incubation for Chinook salmon in Puget Soun

measured at USGS stations over variable time intervals. Annual incubation temperature is estimated as the mean t

three-month period beginning on the median date of spawning in the nearest Chinook index survey area. Differenc

table are based on means over all years of available data. Bold = significant differences in two-sample t tests using Bonferroni-adjusted alpha level. Italics = no test could be performed because fewer than three annual means were 

signify rivers unless otherwise noted. There is no chart for the Nooksack River basin due to lack of data. Data sou

South Puget Sound 

Duwa

mish Green Puyallup Nisqually Chambers 

1 2 1 Big Soos 2 3 1 2 3 White 1 2 3 Creek 

Duwa

mish 

1 — 2 0.67 — 

Green 

1 0.34 1.01 — 

Big Soos 1.46 2.13 1.12 — 

2 0.59 1.26 0.26 0.86 — 3 1.46 2.13 1.12 0.00 0.86 — 

Pu

yallup 

1 3.92 4.59 3.58 2.46 3.32 2.46 — 

2 4.20 4.87 3.86 2.74 3.60 2.74 0.28 — 

3 5.53 6.20 5.19 4.07 4.94 4.07 1.61 1.33 — 

White 3.29 3.96 2.95 1.83 2.69 1.83 0.63 0.91 2.24 — 

Nisqually

1 3.30 3.98 2.97 1.85 2.71 1.85 0.61 0.89 2.23 0.02 — 

2 3.24 3.91 2.90 1.78 2.64 1.78 0.68 0.96 2.29 0.05 0.07 — 3 2.94 3.61 2.60 1.48 2.35 1.48 0.98 1.26 2.59 0.35 0.36 0.30 — 

Chambers Creek 2.22 2.89 1.89 0.77 1.63 0.76 1.69 1.97 3.31 1.06 1.08 1.01 0.72 — 

Deschutes 

1 3.06 3.73 2.72 1.60 2.46 1.60 0.86 1.14 2.47 0.23 0.25 0.18 0.12 0.84 

2 3.49 4.16 3.15 2.03 2.89 2.03 0.43 0.71 2.04 0.20 0.18 0.25 0.55 1.27 03 4.09 4.76 3.75 2.63 3.50 2.63 0.17 0.11 1.44 0.80 0.78 0.85 1.15 1.87 1

124
125

Table B-11 continued. Absolute difference in mean temperature (°C) during incubation for Chinook salmon in Puget Soun

measured at USGS stations over variable time intervals. Annual incubation temperature is estimated as the mean t

three-month period beginning on the median date of spawning in the nearest Chinook index survey area. Differenc

table are based on means over all years of available data. Bold = significant differences in two-sample t tests using Bonferroni-adjusted alpha level. Italics = no test could be performed because fewer than three annual means were 

signify rivers unless otherwise noted. There is no chart for the Nooksack River basin due to lack of data. Data sou

Hood Canal

 Skokomish Duckabush Dosewallips Big QuilceneSkokomish — Duckabush 1.44 — 

Dosewallips 1.53 0.09 — 

Big Quilcene 1.18 0.26 0.35 — 

Strait of Juan de Fuca 

Dungeness Elwha 1 Elwha 2 

Dungeness — 

Elwha 1 2.16 — 

Elwha 2 2.28 0.12 — 

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-NWFSC77 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 pending.

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 pending.

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