United States

Department of

Agriculture

Forest Service

Pacific Northwest

Research Station

General Technical

Report

PNW-GTR-468

January 2000

Biological Characteristics

and Population Status of

Anadromous Salmon in

Southeast Alaska

Karl C. Halupka, Mason D. Bryant, Mary F. Willson, and

Fred H. Everest
KARL C. HALUPKA was a postdoctoral research associate at the time this work was

done; and MASON D. BRYANT and FRED H. EVEREST (retired) are research fisheries biologists and MARY F. WILLSON was a research ecologist, Forestry Sciences

Laboratory, 2770 Sherwood Lane, Juneau, AK 99801. Halupka currently is a fisheries

biologist, National Marine Fisheries Service, Santa Rosa, CA, and Willson is the 

science director, Great Lakes Program, The Nature Conservancy, Chicago, IL.

Cover art by: Detlef Buettner

Authors
Halupka, Karl C.; Bryant, Mason D.; Willson, Mary F.; Everest, Fred H. 2000.

Biological characteristics and population status of anadromous salmon in southeast Alaska. Gen. Tech. Rep. PNW-GTR-468. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station. 255 p.

Populations of Pacific salmon (Oncorhynchus spp.) in southeast Alaska and adjacent

areas of British Columbia and the Yukon Territory show great variation in biological

characteristics. An introduction presents goals and methods common to the series of

reviews of regional salmon diversity presented in the five subsequent chapters. Our

primary goals were to (1) describe patterns of intraspecific variation and identify 

specific populations that were outliers from prevailing patterns, and (2) evaluate

escapement trends and identify potential risk factors confronting salmon populations.

We compiled stock-specific information primarily from management research conducted by the Alaska Department of Fish and Game. We used mainly exploratory

and descriptive statistical procedures to examine patterns of intraspecific variation,

and linear regression to evaluate escapement trends. We describe the most pervasive 

limitations of available data and recommend cautious evaluation of our results. These

reviews nonetheless provide insight into the ecological and evolutionary ramifications

of intraspecific variation for managing diversity and sustaining productivity of salmon

resources.

Keywords: Pacific salmon, Oncorhynchus, southeast Alaska, intraspecific diversity,

population status, variation.

Abstract
1 General Introduction

1 Purpose, Scope, and Objectives

3 Study Area

6 The Database

7 Methods

11 Acknowledgments

11 Literature Cited

15 Coho Salmon (Oncorhynchus kisutch)

15 Abstract

15 Introduction

20 Methods

25 Results

45 Discussion

52 Risk Factors

54 Conclusions

58 Acknowledgments

58 Literature Cited

67 Chinook Salmon (Oncorhynchus tshawytscha)

67 Abstract

68 Introduction

77 Methods

78 Results

91 Discussion

98 Risk Factors

Contents
100 Conclusions

104 Acknowledgments

104 References

113 Sockeye Salmon (Oncorhynchus nerka)

113 Abstract

113 Introduction

119 Methods

121 Results

139 Discussion

147 Risk Factors

149 Conclusions

153 Acknowledgments

153 References

165 Pink Salmon (Oncorhynchus gorbuscha)

165 Abstract

165 Introduction

175 Methods

178 Results

195 Discussion

200 Risk Factors

202 Conclusions

204 Acknowledgments

205 References

215 Chum Salmon (Oncorhynchus keta)

215 Abstract
215 Introduction

220 Methods

222 Results

236 Discussion

244 Risk Factors

247 Conclusions

249 Acknowledgments

249 References

255 English Equivalents
1

Fisheries program managers of the Tongass National Forest (U.S. Department of

Agriculture, Forest Service) identified the need to summarize biological characteristics

and determine population status of anadromous salmonids in southeast Alaska

because of declines in stocks of anadromous salmonids in California, Oregon, Idaho,

and Washington (Nehlsen and others 1991). The purpose of this paper is to identify

distinct or sensitive stocks that may require special consideration during planning of

land-management activities within the Tongass National Forest, and to determine

population trends as stable, increasing, or declining. 

We reviewed stocks of coho (Oncorhynchus kisutch), chinook (O. tshawytscha),

sockeye (O. nerka), pink (O. gorbuscha), and chum (O. keta) salmon in southeast

Alaska. Steelhead are reported separately (Lohr and Bryant 1999). For each

species, we established a context for evaluating potentially distinctive populations by

beginning with a summary of the life history typical of populations in the region.

Management and enhancement programs also were reviewed to assess the potential

for these programs to either contribute to unusual levels of variation or pose a risk to

wild stocks. Stock-specific data, collected primarily by the Alaska Department of Fish

and Game (ADF&G) in their management research programs, were the basis of our

analyses of biological characteristics and population trends. Results of these analyses are discussed in the context of managing salmon diversity and in regard to 

conceptual issues in ecology and evolutionary biology. The final component of each

species report is an evaluation of natural and human-caused risk factors that may

contribute to declines in salmon abundance. Stock-specific risk factors are evaluated

for stocks with distinctive characteristics or declining populations.

We defined a stock, following Ricker (1972) and Nehlsen and others (1991), as a

population of fish that spawns in a particular tributary of a drainage, during a particular time of year. This definition implies that gene flow among stocks is limited.

Although low rates of gene flow often are assumed to be sufficient to homogenize

allele frequencies among populations, gene flow does not preclude evolutionary

divergence (Slatkin 1987). Biologically distinctive stocks are those that diverge from

other stocks in the region in their expression of one or more phenotypic characteristics. Body length, migratory timing, and various demographic characteristics were 

the bases of our analysis of biological distinctiveness. We evaluated demographic 

characteristics of populations as indicators of distinctive features of most individuals

in these populations. The traits we evaluated were limited to those considered to be

Purpose, Scope,

and Objectives

Background

General Introduction
relevant to commercial fisheries management, because these are the only traits for

which data are available for enough stocks in southeast Alaska to make a comparative analysis possible. These traits are only a small sample of characteristics 

important to salmonid diversity, and they are not necessarily the traits most likely 

to display local adaptation.

Stocks that display distinctive phenotypic characteristics may be important to the evolutionary potential of their species, assuming that some component of the variance in

those phenotypic traits is heritable. Moderate levels of additive genetic variance have

been found in most life-history traits of salmonids analyzed (Hard 1995). Phenotypic

plasticity in response to environmental variables is common in salmonids (reviewed in

Ricker 1972), but the basis of plasticity may be heritable (Thorpe 1994, Thorpe and

others 1983). Phenotypic variation also may facilitate and accelerate evolutionary

processes (West-Eberhard 1989); therefore, populations exhibiting particular patterns

of phenotypic plasticity may possess unique elements of genetic diversity. 

Analyzing phenotypic traits to identify components of intraspecific diversity provides a

useful complement to genetic analysis (Utter and others 1993). Patterns detected by

phenotypic analysis reflect different evolutionary processes that operate at different

spatial and temporal scales compared to patterns detected by genetic analysis (Utter

and others 1993). For example, electrophoresis can fail to distinguish populations

having highly divergent life histories (e.g., Sacramento River winter-run chinook;

Bartley and others 1992), and more sophisticated (and costly) techniques such as

analysis of mitochondrial DNA polymorphism may correlate better with phenotypic

divergence (Nielsen and others 1994). Lack of significant variation in allozyme 

frequencies measured electrophoretically should not be interpreted as signifying a

lack of adaptive variation in phenotypic traits (Smoker and others 1993). We incorporated genetic information (primarily from allozyme analysis) into our evaluation to

define broad-scale ancestral lineages (Utter and others 1993) and to identify particular stocks with unusual allele frequency combinations. For all species, though, a 

limited subset of stocks in the region have been sampled for genetic analysis, and

the degree of overlap between stocks included in genetic surveys and stocks for

which biological data are available differs considerably among species. Areas inhabited by stocks identified as distinctive, based on phenotypic characters, may be the

most appropriate focus of future biochemical and genetic studies.

We have attempted to describe the diversity of anadromous salmon at several levels.

Specific populations with distinctive characteristics represent the finest level of resolution for intraspecific diversity. At larger geographic scales, stocks can be grouped by

shared characteristics such as patterns of allozyme frequencies and use of particular

spawning habitats, migratory pathways, or timing windows. These factors used to

group stocks can influence or reflect patterns of gene flow and natural selection and

therefore are relevant to the evolutionary dynamics of these groups. The baseline

survey of hierarchical levels of diversity presented here will provide a comparative

basis for evaluating future patterns of diversity as well as ongoing trends in biological

characteristics.

We used escapement estimates from stream surveys and weir counts to determine

population status of stocks. Estimates of total returns are preferable for evaluating

abundance because escapement can be strongly influenced by harvest patterns, 

but total return estimates were available for very few stocks. The time series of 

2
escapement data begins in 1960, when several species were generally at low abundance levels. Thus, stable or increasing abundance trends, resulting from rebuilding

efforts, improved habitat management, and natural factors, are not surprising.

Escapement data collected before 1975 are not strictly comparable to the post-1975

data, but we have included many pre-1975 surveys in our analyses to broaden the

coverage of this paper to as many stocks as possible. Since 1975, the Alaska

Department of Fish and Game (ADF&G) has sought to verify and standardize its

escapement estimation techniques, but many difficulties remain. Numerous intrinsic

and idiosyncratic factors limit the precision of escapement survey techniques; most

escapement survey techniques provide indices of escapement that are subject to a

wide range of variation owing to combinations of these factors (Cousens and others

1982) nonetheless, the demographic status of stocks is commonly evaluated by using

escapement trends (e.g., Baker and others 1996, Nehlsen and others 1991), because

survey counts or other indices of escapement often are the only information available

for many stocks in a region. 

Specific human-caused and natural risk factors may be related to specific biological

characteristics or stock status. In most cases, specific risks were difficult to assign,

because of severe limitations in the data or absence of stock-specific data. Stockspecific risk factors were identified where possible for stocks with distinctive characteristics or declining populations. Risk factors in broad categories were evaluated for

each species. 

The needs for additional research on salmon populations in southeast Alaska are

great. The economic importance of salmon fisheries in southeast Alaska has been

responsible for most research and monitoring of salmon populations. As a result,

most data have been collected to manage and allocate harvest at sustainable levels.

Studies of individual populations and watersheds usually are short term and often

address only specific aspects of the life history or effects of management—either 

fishery or habitat—within one or two watersheds. All together, these studies consider

only a small proportion of the stocks in the region. Most stocks monitored for fisheries-management purposes do not inhabit watersheds that either have been or are

being intensively managed for timber harvest. Studies of intensively managed watersheds typically do not have good escapement records or records that extend for multiple years. A long-term monitoring program is needed, as well as additional baseline

data. Likewise, additional surveys of genetic diversity are needed to define stock

groups at finer levels of resolution. The ecology and evolutionary biology of salmon

in southeast Alaska offer a wealth of promising research opportunities. In the chapters that deal with each species, we identify specific research needs and propose

tentative explanatory hypotheses, thereby seeking to stimulate research to address

gaps in understanding the life history, ecological relations, and biodiversity of salmon

in southeast Alaska.

The geographic area covered in this report includes all of southeast Alaska from the

international boundary at Dixon Entrance, north and west to Cape Suckling (fig. 1).

We also included large transboundary river systems, such as the Stikine, Taku,

Chilkat, and Alsek drainages, whose stocks spawn in British Columbia and the Yukon

Territory.

3

Study Area
4

Figure 1—The study area, with approximate locations of some geographic features mentioned in the text.
5

Figure 2—The study area, with the approximate locations of statistical districts used by the ADF&G

Division of Commercial Fisheries.
6

Stream numbers in this report are those used by the ADF&G, Division of Commercial

Fisheries. These numbers are abbreviated versions of the numbers assigned and

catalogued by the ADF&G, Habitat Division (1994). The first three digits of these

numbers also designate the commercial fishing statistical areas in the region (fig. 2).

All data tables are organized by ascending stream number.

Our intent was to evaluate wild stocks of anadromous salmonids within southeast

Alaska; however, widespread official and unofficial stocking of fish raises the possibility that some nonnative stocks were inadvertently included. The interaction of wild

and artificially reared fish in southeast Alaska is poorly documented, but many 

studies from other regions document the impacts of hatchery fish on wild stocks

(reviewed in Goodman 1990, Thomas and Mathisen 1993).

Our primary sources of stock-specific biological data for southeast Alaska were

reports and computerized data files from ADF&G. Other sources of data were

reports by the Pacific Salmon Commission (PSC), National Marine Fishery Service

(NMFS), USDA Forest Service, U.S. Fish and Wildlife Service (USFWS), and the 

former U.S. Bureau of Fisheries (USBF). A comprehensive search of the primary 

literature for papers on salmonid research in Alaska was conducted using the Dialog

database.1 Current volumes not covered by the Dialog system were searched with

Current Contents or by inspection. Very few data from the primary literature were

available for inclusion in this report series, however. Anecdotal reports from fisheries

biologists also contributed to the database. Electronic versions of the database are

available from the primary author.

All data were compiled and analyzed by return year rather than brood year. Because

our primary goals were to describe variation and identify distinctive stocks, we placed

a high priority on including as many stocks as possible in our analyses. Return-year

compilations enabled us to include additional stocks in our analyses, because they

did not require several consecutive years of sampling, as brood-year compilations 

do. Many salmon stocks in the region have not been sampled for enough consecutive years to complete brood-year analysis but have been sampled for enough nonconsecutive years to provide reliable estimates of means and variances across years.

Many more populations in the region have been sampled for less than 4 years. We

have included these stocks in comparative analyses under the implicit assumption

that the few years sampled are representative. Of course, the likelihood of this

assumption being fulfilled decreases with decreasing numbers of sample years.

Stocks determined to have distinctive characteristics, based on limited sampling,

require additional sampling for confirmation.

Throughout this report we have used the European system for designating the age 

of fish. In this system, the number of winters the fish have spent rearing in freshwater after emergence are separated from the number of winters spent in saltwater by a

period. For example, a fish of age class 1.3 has spent one winter in freshwater and

three winters in saltwater; an age 0.4 fish emigrated to saltwater soon after emergence and spent four winters in the ocean.

The Database

1 The use of trade or firm names in this publication is for reader

information and does not imply endorsement by the U.S.

Department of Agriculture of any product or service.
Statistical procedures consisted primarily of descriptive statistics. The primary goals

for these descriptive procedures were to detect stocks deviating from the overall 

distribution of a given variable for their species and to illustrate the range of variability

present throughout the region. Distributions of biological variables were generated by

plotting mean values (calculated across all sample years) from all studied stocks in

southeast Alaska. Studied stocks were not a random sample of all stocks in the

region. Most stocks were chosen for study because they were either representative

of a certain population type in the region or thought to be of particular importance to

commercial or sport fisheries. The ADF&G has not explicitly attempted to include

stocks reported anecdotally as distinctive in its management research programs.

When many populations had been sampled for a particular biological characteristic,

we identified distinctive stocks by using the graphic procedures described by Tukey

(1977; also SAS 1994). This analysis produces a standard frequency distribution, 

an outlier box plot, and a normal quantile plot (fig. 3). In the outlier box plot, points

beyond the whiskers are extreme values or potential outliers, which for our purposes

represented distinctive stocks.

We used the Shapiro-Wilk W-statistic to verify the presence of outliers. This statistic

tests for the presence of an undefined number of discordant values in a random sample, assuming a normal population (Barnett and Lewis 1978) and also can be applied

as a test of the null hypothesis that the data are a random sample from a normal 

7

Figure 3—Frequency distribution, outlier box plot and normal quantile plot used

to identify distinctive stocks. In the frequency distribution, values increase toward

the top of the plot so that if the plot is viewed in the typical vertical orientation,

values decrease from left to right. In the outlier box plot, the ends of the box are

the 25th and 75th quantiles. The difference between these values is the

interquartile range. The ends of the “whiskers,” labeled A and B, are the outermost data points from their respective quartiles that fall within the distance calculated as 1.5 x (interquartile range). Points beyond the whiskers are potential 

outliers and are highlighted in all three plots. The normal quantile plot provides 

a visual way to assess both the overall normality of a variable distribution and

which points deviate most from the normal expectation. A normal distribution

would have all points on a diagonal straight line. Each point in the normal quantile plot represents the mean value of a stock included in the analysis. The

shortest half, marked with a bracket, is the most dense 50 percent of the 

observations (SAS 1994).

Methods

Data Analysis

Procedures
8

population (SAS 1988). A significant test result therefore can be interpreted as indicating both the existence of outliers and a nonnormal sample distribution. Discordant

values identified in the plot then can be excluded, and the Shapiro-Wilk statistic

reevaluated to determine if outliers were the cause of the previously significant test

result. To use this procedure, we applied standard transformations to all nonnormal

distributions to approximate normality. In cases where the Shapiro-Wilk W-statistic

yielded a nonsignificant result, but the box-and-whisker plot indicated the presence of

an outlier, we relied on the graphic analysis.

We preferred a graphic approach to outlier detection over specific discordancy tests

for two reasons: (1) most discordancy tests are based on specific underlying probability models—for many of our variables the most appropriate model was unclear;

and (2) we suspected the existence of multiple outliers in both directions for many

variables, and most test procedures are designed to detect a given number of outliers

(one or two) and are susceptible to "masking" by multiple outliers, even when used

consecutively (Barnett and Lewis 1978).

Outlier analysis was not possible for nominal characteristics of populations, such as

use of unusual habitats or geographic locations for spawning. For these characteristics, distinctive populations were identified from descriptive or anecdotal information.

For these cases, we have provided as much supportive information as is available. 

When biological evidence suggested that the entire region was not an appropriate

scale for analysis, subregional analyses were conducted. Separate analyses were

conducted, for example, for pink salmon in northern and southern subregions,

because tagging studies of pink salmon indicated that little intermingling occurs

between stocks located on opposite sides of Sumner Strait (see fig. 1). Likewise, if

different habitat types were known to have effects on biological characteristics of a

species, separate analyses were conducted on stocks found in the different habitat

types (e.g., lake- vs. river-type sockeye salmon stocks).

Descriptive statistics for migratory timing past weirs or traps (both juvenile emigration

and spawning migrations of adults) were calculated by the formulas of Mundy (1984).

We also calculated an index of spawning-run timing based on the timing of escapement surveys. This index took the form of a mean date of spawning migration; it was

calculated by converting the date of the highest survey count for each year to a

Julian date and computing an ordinary mean of these Julian dates. This index was

calculated only for those stocks with 7 or more years of surveys.

Age structure of stocks was evaluated by comparing both mean freshwater age

(MFWA) and mean saltwater age (MSWA) among stocks, as well as proportions of

total escapement samples in each age class. Both were calculated as the mean number of years spent in freshwater or saltwater, respectively, weighted by the number of

individuals sampled from each age class. These weighted means served as overall

indices facilitating both comparison of stocks and analysis of interannual variation in

age structure of a single population. Age-structure comparisons based on means

were supplemented with comparisons of proportions of stocks in each age class,

because mean calculations can obscure patterns such as bimodal age distributions.
9

The linear regression method of Konkel and McIntyre (1987) was used to evaluate

trends in spawning escapement. The independent variable was time in years, and

the dependent variable was peak escapement count. This analysis was conducted

only on stocks with counts from at least 7 years. Trends in escapement counts were

categorized as increasing, declining, or stable (having no significant trend). A twotailed P-value of 0.05 was used for this test with n - 2 degrees of freedom. Similar

regression procedures were used to evaluate temporal trends in body size, run 

timing, age structure, and sex ratio. Although the presence of nonlinearity or 

auto-correlation is likely in these analyses of time-series data, we did not examine 

residuals to check for these deviations from regression assumptions (Draper and

Smith 1981). With the coarse data involved, and the many analyses to be conducted, we sought a simple indicator of trends. 

We categorized data quality for spawning escapement surveys as “good,” “fair,” or

“poor” to provide a subjective basis for evaluating the reliability of calculated abundance trends. Our assessment of data quality was based on the total number of

years surveyed, consistency of survey type (methodology), number of surveys per

year, the distribution of survey effort through time, and the presence-absence of

apparently anomalous survey counts. Significant population trends calculated from

“fair” and “poor” data sets should be regarded as provisional.

The distribution of variance components for adult body lengths were evaluated by

using a modified version2 of the SAS VARCOMP procedure (SAS 1988). This procedure reconstructed a nested analysis of variance from available body length data

(sample sizes, mean lengths, and standard errors) and partitioned total variance into

components attributable to differences among streams, differences among years

within streams, and differences among individuals within streams and years. This

analysis required a balanced data set, relatively large samples, and data for at least 5

years for each stock included. These requirements limited the number of stocks that

we could include in the analysis. This analysis nonetheless provided an important

tool for interpreting patterns of variation in adult body lengths among stocks. 

In addition to statistical analysis, the demographic status of populations was evaluated in view of water quality assessments. Lists of streams for which the ADF&G had

collected escapement survey data were compared to lists of “impaired” and “suspected” water bodies compiled by the Alaska Department of Environmental Conservation.

An impaired water body or segment of a water body has definitive and credible 

documentation of a violation of State Water Quality Standards or documentation of

impairment of designated uses, as established in the Water Quality Standards. A

suspected water body does not have monitoring data or other definitive documentation establishing violation of the Water Quality Standards or use impairment due to

point or nonpoint sources, but information indicates that pollutant sources are present, the water body is affected, and water quality violations may be occurring or may

have occurred. Further investigation is needed to establish whether the water body

is impaired (ADEC 1992). All stocks inhabiting impaired or suspected water bodies

for any portion of their life cycle were tabulated because exposure to contaminants

may render these populations susceptible to decline.

2 Written by Tim Max, Station Statistician, U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station,

P.O. Box 3890, Portland, OR 97208.
10

We conducted all other statistical tests by using SYSTAT (1992) and following application guidelines provided in Sokal and Rohlf (1981). Coefficients of variation calculated for run timing, age, and sex-ratio characteristics included the correction for

small samples specified by Sokal and Rohlf (1981). All statements of statistical significance were based on the probability criterion that P < 0.05. In some cases, we

discuss “nearly significant” results (0.05 < P < 0.1) when sample sizes were small or

trends were apparent but statistical tests did not reach the 0.05 criterion. 

We encountered difficulties in interpreting the data because it was collected by a variety of investigators, for various purposes, from numerous locations, at different times,

and with different methods. The data limitations we encountered can be categorized

into three general types: (1) insufficient sampling (within years, across years, and

among populations); (2) lack of consistency and comparability; and (3) low accuracy

and precision. Various data sets evaluated in this paper suffered from these limitations to different degrees. The following general patterns were apparent, but these

limitations were not universal, and for each species some very reliable data sets exist

for individual populations.

Body length data were limited by small sample size, length of sample time, variations

in sample sites, and use of different types of length measures. Within years, body

size of most species can change throughout the migration season, and samples from

only one or a few consecutive days may not be representative of the entire population. Samples taken throughout the season at weirs are the most reliable. For many

populations, the number of years sampled were not sufficient to evaluate temporal

trends in body size or to adequately characterize interannual variation. A small proportion of coho and chum salmon populations were sampled for body length. The 

difficulty of inconsistent measurements could generally be overcome by transforming

data with regression equations (Pahlke 1989), but in some instances the type of

length measure could not be determined and data were not included in analyses.

Migratory timing data from weirs tended to be incomplete for all species, except sockeye salmon. In most cases, weir operation was discontinued before completion of

the run, and the size of the uncounted proportion of the run was unknown. Accuracy

of weir counts was sometimes doubtful when differing counts for the same run were

reported in different sources. Furthermore, a wide range of circumstances, such as

floods, can prevent a weir from being “fish tight.”

Our index of run timing was confounded primarily by all the problems of consistency

and accuracy associated with escapement surveys. Escapement surveys in the

region are conducted primarily for pink salmon with other species counted secondarily. Thus the timing of surveys is oriented toward peak pink salmon escapements and

may not reflect the true run timing of other species.

Data on age composition suffered from many of the same limitations described above

for length data. Sample sizes often were inadequate to characterize age composition

with a high level of confidence. Estimates of overall age structure are enhanced by

sampling throughout the run, because different age classes can predominate in different run segments. In addition, the accuracy of age data for some species, especially

coho salmon, is questionable in some situations. The proportion of jacks (male fish

that return in the fall after one summer in the ocean) is not known for most 

populations.

Limitations of

Biological Data
Like age structure, sex ratio often varies predictably through a run; therefore, repeated sampling is recommended. This sort of repeated sampling is best accomplished

at a weir, but even weir estimates of sex ratio can be confounded by jacks passing

undetected through a weir.

Because these limitations of data quality were so widespread, we conducted most of

our analyses of biological characteristics on grand means calculated across all years

sampled. This approach should provide reasonable estimates of true means, assuming errors or biases in the data vary randomly in direction. We discuss all instances

where biases may be systematic.

R. Baker, through her initiative, diligence, and meticulous work, was essential to the

completion of this report.

Alaska Department of Environmental Conservation. 1992. Alaska water quality

assessment 1992. Juneau, AK: Water Quality Management Section. 88 p.

Alaska Department of Fish and Game, Habitat Division. 1994. Catalog of waters

important for spawning, rearing or migration of anadromous fishes. Juneau, AK:

Southeast Region, Resource Management Region I. 195 p.

Baker, T.T.; Wertheimer, A.C.; Burkett, R.D. [and others]. 1996. Status of Pacific

salmon and steelhead escapements in southeast Alaska. Fisheries. 21(10): 6-18.

Barnett, V.; Lewis, T. 1978. Outliers in statistical data. New York: John Wiley &

Sons. 365 p.

Bartley, D.; Bentley, B.; Brodziak, J. [and others]. 1992. Geographic variation in

population genetic structure of chinook salmon from California and Oregon. Fishery

Bulletin. [Place of publication unknown]: U.S. National Marine Fisheries Service.

90(1): 77-100.

Cousens, N.B.F.; Thomas, G.A.; Swann, C.G.; Healey, M.C. 1982. A review of

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[Place of publication unknown]: [Publisher unknown]. 122 p.

Draper, N.R., Smith, H. 1981. Applied regression analysis. 2d ed. New York: John

Wiley & Sons. 709 p.

Goodman, M.L. 1990. Preserving the genetic diversity of salmonid stocks: a call for

Federal regulation of hatchery programs. Environmental Law. 20: 111-166.

Hard, J.J. 1995. A quantitative genetic perspective on the conservation of intraspecific diversity. In: Nielson, J.J., ed. Evolution and the aquatic ecosystem: defining unique units in population conservation: Symposium 17; [dates of meeting unknown]; [location unknown]. Bethesda, MD: American Fisheries Society: 304-326.

Konkel, G.W.; McIntyre, J.D. 1987. Trends in spawning populations of Pacific

anadromous salmonids. Fish and Wildlife Tech. Rep. 9. Washington, DC: U.S.

Department of the Interior, Fish and Wildlife Service. 25 p.

11

Acknowledgments

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750 p.

Thomas, G.L.; Mathisen, O.A. 1993. Biological interactions of natural and enhanced

stocks of salmon. Fisheries Research. 18(special issue): 1-17. 
Thorpe, J.E. 1994. Performance thresholds and life-history flexibility in salmonids.

Conservation Biology. 8: 877-879.

Thorpe, J.E.; Morgan, R.I.G.; Talbot, C.; Miles, M.S. 1983. Inheritance of developmental rates in Atlantic salmon, Salmo salar L. Aquaculture. 33: 119-128.

Tukey, J.W. 1977. Exploratory data analysis. Reading, MA: Addison-Wesley Publ.

Co. 688 p.

West-Eberhard, M.J. 1989. Phenotypic plasticity and the origins of diversity. Annual

Review of Ecology and Systematics. 20: 249-278.

13
Intraspecific variation in biological characteristics among coho salmon stocks in

southeast Alaska was evaluated for up to 48 stocks, and regression analyses of

escapement trends were conducted for 129 stocks, a very small portion of the estimated 2,300 stocks in the area. The biological characteristics of coho stocks that rear

primarily in lake, river, or stream watershed types, as well as interior (east and north

of the Coast Mountains) and coastal locations, were compared. Smolts from lakes

and rivers tended to be larger than those from streams. Stocks from watersheds with

lakes have higher mean freshwater ages, a wider range of age classes, and higher

survival rates than stocks from watersheds without lakes. Stocks spawning in the

interior had lower mean freshwater ages, male-biased sex ratios with few or no precocial males, and low survival rates, compared to stocks spawning near the coast,

and these differences were more pronounced than differences among watershed

types. Redoubt Lake and the Tsiu River system support clearly distinctive coho stocks.

Sixteen additional stocks may have distinctive characteristics. Most stocks have stable escapement trends, with 7 percent (nine stocks) showing significant increases,

and 5.4 percent (seven stocks) showing significant declines from 1960 to 1992. 

Keywords: Coho salmon, Oncorhynchus kisutch, southeast Alaska, intraspecific

diversity, conservation, age distribution, run timing, sex ratio, body size.

Coho salmon inhabit a broad range of habitat types and spawn in nearly 4,000 watercourses throughout southeast Alaska and in the headwaters of transboundary rivers

in British Columbia and the Yukon Territory (ADF&G, Habitat Division 1994).

Because of the high probability of gene flow within drainages, these 4,000 spawning

sites are estimated to support 2,300 coho salmon populations (Baker and others

1996). The wide range of habitats used by coho salmon reflects the plasticity of this

species. The following generalized summary of coho salmon life history provides a

starting point for describing the wide range of life history variation displayed by populations of this species in southeast Alaska.

15

1 Janice K. Troyer coauthored this chapter. She was a biological

technician at the time this work was done, U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station,

2770 Sherwood Lane, Juneau, AK 99801.

Coho Salmon 

(Oncorhynchus kisutch)

1

Abstract

Introduction

Life History
Coho salmon typically return to the outside waters of southeast Alaska in July and

August and enter freshwater in September and October. The direction of the return

migration generally moves from northwest to southeast along the coast. Relatively 

little is known about the migration routes used by specific coho salmon stocks

(Schmidt 1988). Migratory pathways that have been studied indicate some stocks 

follow a direct route (e.g., Politofski Lake) and others take complicated paths to their

natal stream (e.g., Kegan Lake; Shaul and others 1984, 1986). In general, run timing

is earliest in outer coast stocks on islands and latest in northern mainland stocks

(Van Alen and Wood 1986). Most spawning occurs in late October and November;

however, some runs return as early as mid-July and adults may hold for several

months before spawning. Spawning areas tend to have groundwater seepage or

high intergravel flow rates, and small low-gradient tributaries are commonly used.

Hatching of eggs occurs in about 50 days. Fry typically emerge from the gravel in

April. In southeast Alaska, all juveniles spend at least 1 year rearing in freshwater

before emigration, and most juveniles rear in freshwater for 2 years. This schedule

contrasts with coho salmon stocks in southern British Columbia and the Pacific

Northwest, where most juveniles spend 1 year in freshwater. The availability of suitable rearing habitat is considered to be the limiting factor for most coho salmon populations. Optimum rearing habitat for coho juveniles is typically found in small

streams, beaver ponds, off-channel areas of river flood plains, and lakes (Bryant

1985a, 1985b; Elliott and Reed 1974; Gray and Marriott 1986). These areas all feature a complex habitat structure with abundant aquatic and bank cover (McMahon

1983). Coho smolt typically migrate in May and early June. The mean length of age

2.0 smolts in southeast Alaska is nearly 100 mm.

Most coho salmon in southeast Alaska spend about 16 months in saltwater before

returning to spawn. Individuals that spend 28 months in the ocean are rare. Adult

body length in escapements averages 618 mm for males and 634 mm for females.

Coho salmon from northern stocks typically are larger than those from southern

stocks. This difference may reflect the later timing of the run for northern stocks,

which provides additional opportunity for growth in the summer of return (Van Alen

and Wood 1986). 

Survival of rearing juveniles to return as adults, based on coded-wire-tag studies of

13 coho stocks, is 5.6 percent (SE = 0.2 percent) and includes both the late segment

of freshwater rearing and oceanic life history stages. The estimated mean ocean 

survival rate, from smolt emigration to adult return, is 10 percent (SE = 0.69 percent)

for six coho stocks in southeast Alaska, when all years for which data are available

are included in the average. During the late 1980s, however, estimated ocean 

survival averaged 14 percent (Shaul and others 1991).

Jacks are males that smolt in late spring and return to spawn in the fall, after spending only 4 to 5 months in saltwater. The proportion of jacks present in spawning runs

has been determined for few stocks in southeast Alaska.

Coho salmon are a valuable resource in the commercial, sport, and subsistence fisheries of southeast Alaska. In 1987, 1.5 million coho were harvested in southeast

Alaska fisheries (Wood 1992). The $17-million value of this harvest was the highest

single-species contribution to the total economic value of all salmon species 

16

Management
17

harvested in the region for that year. Coho salmon harvests during the late 1980s

and early 1990s averaged over 2 million fish per year, nearly double the average

annual harvest for the previous 30 years (fig. 4). The high economic value of coho

increases the pressure for high-level harvests and artificial enhancement of run sizes.

General management goals include the maintenance of sustained-yield fisheries and

escapement levels that will sustain stocks. Management of coho salmon in southeast

Alaska is based on inseason assessment of relative annual abundance. Catch or

catch-per-unit-effort data from ongoing fisheries are used to evaluate run strength

and guide inseason management decisions. The effectiveness of inseason management decisions is evaluated by postseason spawning escapements and exploitationrate estimates [catch/(catch + escapement)] for particular “indicator” stocks.

Acquisition of data to manage the fishery is difficult, in part because it is primarily a

mixed-stock fishery (harvesting fish from several watersheds in a common fishery).

Furthermore, the spawning migrations return to fresh water in fall and winter during

inclement weather and high water flow. All these factors contribute to the complexity

and cost of obtaining data. As a result, most data are derived from a small and limited subset of the stocks throughout southeast Alaska.

During the 1970s, management research used marked juveniles or smolts from 29

locations to determine migration and exploitation patterns (Shaul 1994). From 1982

to 1991, research shifted to more intensive studies of the population dynamics of a

small number of indicator stocks considered representative of larger areas (Hugh

Smith Lake for southern inside waters, Ford Arm Lake for northern coastal waters,

and Auke Lake and Berners River for northern inside waters [Shaul and others 1986,

1991]). All stocks within an area are assumed to experience similar environmental

conditions, to have similar migration patterns, and to incur similar exploitation rates.

These studies form most of the database available for analyzing stocks throughout

southeast Alaska.

Figure 4—Annual commercial harvest of coho salmon in southeast

Alaska, 1888 to 1991 (data from Rigby and others 1991).
Enhancement activities, primarily through hatcheries, can affect run size, genetic

composition, and life history of coho salmon. Before 1955, enhancement of coho

salmon in southeast Alaska was limited to egg transfers and releases, and to relatively small-scale hatchery production lasting only a few years at a few sites (Roppel

1982). The first site of hatchery coho production in southeast Alaska was Callbreath

hatchery, located on what is now called Hatchery Lake near McHenry Inlet in the

South Etolin Island Wilderness. The average number of returning adult coho salmon

counted at the hatchery barricade was 840 from 1894 to 1900 when separate records

for coho salmon were maintained (Roppel 1982). The only record of the number of

coho sac fry produced by the hatchery was 750,000 in 1904. The coho fry produced

were released near the hatchery or transferred to nearby Falls Creek, also on

McHenry Inlet. Coho salmon also were produced briefly (1903) at Olive Creek, south

of Wrangell, at Fortmann hatchery on the Naha River from 1903 to 1906, and at Yes

Bay hatchery from 1908 to 1909 (Roppel 1982). At the Fortmann hatchery, the 1903

coho brood stock was taken from Miller Lake in Moira Sound, but in subsequent

years Naha River coho salmon were used (Roppel 1982). All fry produced were

released near the hatchery. After 1906 the Fortmann hatchery focused on sockeye

production and coho salmon were actively persecuted because of the perceived negative effects of predation by coho juveniles on sockeye fry (Roppel 1982). At Yes Bay

hatchery, coho salmon were used as food for sockeye fry after very limited attempts

at coho production.

The earliest transfer of large numbers of coho eggs recorded by Roppel (1982) was

conducted by A.J. Sprague between 1917 and 1920. During this period, at least

700,000 eyed eggs and fry from unknown sources were transferred to Baranof Lake,

a lake that did not support any anadromous salmon runs due to a barrier falls. No

further coho salmon enhancement activities were recorded by Roppel (1982) until

1953, when eggs were taken from Reflection Lake on the Cleveland Peninsula and

planted in the Wolf Creek system north of Ketchikan (Roppel 1982).

More extensive enhancement of coho salmon did not begin until 1955 when the Deer

Mountain hatchery began releasing coho salmon derived from Soos Creek, Washington, Buschmann Creek (Hugh Smith Lake), Reflection Lake, and Ward Creek

brood stocks into Ketchikan Creek. From 1955 to 1959, large numbers of coho fry

from all these brood stocks were transferred to seven other lakes and streams in the

Ketchikan area that did not have native anadromous runs (Manzanita, Whipple, and

Deer Creeks, Smugglers and Tsa Coves, and Ella and Princess Lakes; Roppel 1982).

From 1978 to 1990, Snettisham hatchery was a major producer of coho salmon in

northern southeast Alaska, but the coho program at this facility has been discontinued. Snettisham brood stock was derived primarily from the Speel River, with supplemental eggs taken from the King Salmon River, Pavlof Lake, and Montana Creek.

Releases of Snettisham coho occurred near the hatchery as well as at Indian,

Sweetheart (both near the hatchery), Twin, and Dredge (Juneau) lakes, and Fish

(Douglas Island), Sheep, and Salmon (Juneau) Creeks. 

Nine large hatchery programs currently are producing coho salmon in southeast

Alaska (table 1). Hatchery production of coho salmon is concentrated in southern

southeast Alaska, with the first five hatcheries listed in table 1 clustered in the

Ketchikan area. 

18

Enhancement
Numerous habitat enhancement projects, which include instream structures, stream

habitat modifications, or fish ladders for coho salmon, have been completed in southeast Alaska. Descriptions of many of these projects have been compiled by Bibb

(1987) and Parry and others (1993). No comprehensive review has been completed

for numerous projects that stocked coho salmon above barrier falls. Examples

include Banner, Deer, Osprey, Ludvik, and Tranquil Lakes on Baranof Island, Sea

Lion Cove Lake on Kruzof Island (see Crone and Koenings 1985), and Sweetheart

and Indian Lakes near Snettisham. Coho presmolts were stocked in Margaret Lake

after the construction of a fish ladder (Bryant and others 1994).

19

Table 1—Hatchery programs producing coho salmon in southeast Alaska

Annual

egg-take

Hatchery Management Location Brood stock sources Release sites goal

Whitman Lake SSRAAa Herring Bay, George Chickamin River Whitman Lake 5,000,000

Inlet, South Nakat Inlet

Revillagigedo Island Kendrick Bay

Neets Bay

Earl West Cove

Beaver Falls SSRAAa George Inlet, South Reflection Lake (from Neck Lake 1,500,000

Revillagigedo Island Ward Lake)

Deer Mountain Ketchikan Indian Ketchikan Reflection Lake (from Ward Lake 400,000

Corp. Ward Lake) Ketchikan Creek

Mountain Point

Bold Island

Lakes

Blank Inlet

Gem Cove

Margaret Lake

Neets Bay SSRAAa Neets Creek, Neets Chickamin River Neets Bay 500,000

Bay, North

Revillagigedo Island

Bell Island American Bell Island, West Reflection Lake Bell Island Creek (not

Aquaculture Behm Canal available)

Corp.

Klawock River City of Klawock Klawock River, West- Klawock River Klawock River 3,000,000

Central Prince of

Wales Island

Port Armstrong Armstrong-Keta, Jetty Lake, South Blanchard Lake Armstrong Bay 650,000

Inc. Baranof Island Deer Lake

Crystal Lake ADF&Gb Crystal Lake, Blind Duncan Creek Crystal Creek 30,000

Slough, Mitkof Mitchell Creek Mitchell Creek

Island Portage Creek Portage Creek

St. John’s Creek

DIPAC Douglas Island Pink Salmon Creek, Steep Creek Gastineau 1,000,000

and Chum, Inc. Gastineau Channel, Montana Creek Channel

Juneau Sheep Creek Sheep Creek

Pavlof River Twin Lakes

Auke Bay

Picnic Creek

Davidson Creek

Fish Creek

a SSRAA = Southern Southeast Regional Aquaculture Association.

b ADF&G = Alaska Department of Fish and Game.

Source: Information primarily from hatchery management plans providd by S. McGhee, ADF&G Division of Commercial Fisheries, 1255

West 8th Street, Juneau, AK 99802.
Coho salmon stocks discussed in this report are defined entirely by geographic location and timing of the runs. Preliminary attempts to develop genetic stock discrimination for selected coho stocks are in progress at the NMFS Auke Bay Laboratory, but

no regional surveys have been completed.2 Scale-pattern analysis has been successfully employed to separate wild and hatchery stocks (Wood and Van Alen 1987), but

hatchery stocks are not included in this review. Some differences in scale patterns

among wild stocks are described (Gray and others 1981). The usefulness of these

characteristics in stock separation has not been evaluated, however.

We categorize coho salmon stocks in southeast Alaska into three groups, based on

watershed type. These watershed types are (1) small to medium streams without

lakes, (2) drainages containing lakes, and (3) large mainland rivers. The life histories

of coho stocks may be affected in consistent ways by easily identified watershed

characteristics. 

Roughly 2,000 coho salmon stocks in southeast Alaska are found in small to medium

streams. Coho populations in these systems tend to consist of fewer than 1,000

spawners, often less than 200 spawners. The age structure of these stocks is relatively simple, to consisting of fewer age classes than populations found in other

watershed types. Production of juveniles is highly variable through time, which

reflects the relative instability of this environment. Nonetheless, these systems are

estimated to provide roughly 60 percent of the annual return of coho salmon to southeast Alaska (Elliott and Kuntz 1988). Fewer data for our analyses were available for

coho salmon in stream systems than in lake systems. 

Coho salmon populations found in drainages containing lakes are characterized by

spawning escapements between 1,000 and 8,000 individuals, large smolts, high 

survival from juvenile to adult, high variability in duration of freshwater residence of

juveniles, relatively stable production patterns, and relatively high proportions of jacks

in spawning populations. Coho salmon inhabit about 200 lake-containing drainages

in southeast Alaska. Lake systems provide the most data of the three general watershed types.

Coho populations in large rivers provided the least data for our analyses; consequently, statements about general patterns are tentative. The Stikine River may be a

major producer of coho salmon in the region (Shaul and others 1984), but there are

few data for these stocks. The average annual inriver harvest of coho salmon from

the Stikine River was over 7,700 fish from 1979 to 1987. In interior tributaries of the

Taku and Alsek Rivers, freshwater survival of juveniles appears to be reduced, possibly due to increased predation rates (Shaul 1990). Production of smolts appears to

be highly variable, perhaps due to the dynamic nature of the rearing environment.

Spawning escapements in large river watersheds differ widely throughout the region.

The Tsiu-Tsivat River system west of Yakutat may support the largest population in

the region with total inriver returns of greater than 100,000 individuals reported historically (Shaul and others 1987). The frequency of jacks in these stocks tends to be

less than 1 percent.

20

Methods

Stock Discrimination

2 Personal communication. 1996. A. Gharrett, professor of fisheries, University of Alaska Southeast, 210 Anderson Building,

11120 Glacier Highway, Juneau, AK 99801.
21

Biological data (other than escapement survey counts) were available for only 48 (2.1

percent) of the estimated 2,300 coho stocks in southeast Alaska (Baker and others

1996). Of these, 26 stocks inhabit lake-containing watersheds, 12 are in watersheds

with small to medium streams, and 10 occupy large rivers or tributaries to large rivers

(table 2). Lake systems are disproportionately represented (56 percent of studied

systems, but only about 10 percent of all watersheds with coho salmon). More information is available for large coho salmon stocks than for small stocks. Watershed

classification of each system was based either on site descriptions contained in

reports or inspection of U.S. Geological Survey topographic maps. Watershed classification of each stock was not clear in some cases (e.g., lakes, such as Speel,

Windfall, and Chilkat Lakes, that connect closely with mainstem rivers). In such

cases, classification was based on professional judgment about which watershed

types were predominantly used by rearing coho salmon.3

Table 2—Location and rearing habitat type for coho salmon stocks for which

biological data are available

Stream Location

Number Name Habitat typea Generalb N. latitudec W. longitudec

101-29-006 Vallenar Creek S I 55°22 ́37 ̋ 131°49 ́39 ̋

101-30-075 Hugh Smith Lake L MC 55°05 ́56 ̋ 130°38 ́40 ̋

101-80-068 McDonald Lake L MC 55°57 ́53 ̋ 131°50 ́19 ̋

101-90-050 Naha River L I 55°35 ́34 ̋ 131°35 ́33 ̋

102-30-067 Kegan Lake L I 55°02 ́11 ̋ 132°12 ́16 ̋

102-60-087 Karta River L I 55°33 ́36 ̋ 132°34 ́35 ̋

102-70-058 Snaky Lakes L I 55°45 ́d 132°42 ́d

103-15-027 Klakas Lake L I 55°01 ́35 ̋ 132°21 ́51 ̋

103-80-031 Warm Chuck Lake L I 55°46 ́28 ̋ 133°27 ́44 ̋

103-90-010 Sarkar Lake L I 55°57 ́05 ̋ 133°12 ́33 ̋

103-90-030 Staney Creek S I 55°49 ́12 ̋ 133°09 ́11 ̋

106-30-051 Hatchery Creek L I 55°56 ́25 ̋ 132°58 ́14 ̋

106-41-010 Salmon Bay Lake L I 56°14 ́11 ̋ 133°11 ́10 ̋

106-43-021 Castle River R I 56°38 ́35 ̋ 133°15 ́14 ̋

107-10-030 Black Bear Creek L MC 55°43 ́35 ̋ 132°10 ́00 ̋

108-70-002 Stikine River R MC 56°36 ́d 132°23 ́d

109-10-009 Sashin Creek S I 56°22 ́49 ̋ 134°39 ́04 ̋

109-20-013 Falls Lake L I 56°49 ́28 ̋ 134°41 ́58 ̋

111-17-010 King Salmon River R I 58°02 ́36 ̋ 134°20 ́18 ̋

111-32-032 Taku River R MC 58°25 ́32 ̋ 133°58 ́25 ̋

111-32-068 Johnson Creek S MC 58°30 ́22 ̋ 133°52 ́57 ̋

111-32-066 Yehring Creek S MC 58°30 ́06 ̋ 133°47 ́03 ̋

111-32-203 Wilms Creek S MC

111-32-254 Little Tatsamenie Lake L MN 58°25 ́d 132°20 ́d

111-32-260 Hackett River R MN

111-32-270 Nahlin River R MN 58°48 ́d 132°01 ́d

111-32-280 Dudidontu River R MN 58°47 ́d 132°03 ́d

111-33-034 Speel Lake L MC 58°08 ́04 ̋ 133°42 ́55 ̋

111-50-007 Windfall Lake L MC 58°30 ́26 ̋ 134°43 ́32 ̋

111-50-042 Auke Lake L MC 58°23 ́17 ̋ 134°37 ́49 ̋

3 Personal communication. 1996. L. Shaul, fisheries biologist,

Alaska Department of Fish and Game, 802 3d Street, Douglas, 

AK 99824.
We also compared coho populations in coastal and interior sites. Coho stocks inhabiting coastal and interior sites were expected to show differences in biological characteristics, because of considerable differences between these different geographic

zones in climate, fish communities, and difficulty of migration. However, because 

relatively limited data were available for five interior stocks (Hackett, Dudidontu,

upper Nahlin, and Tatsamenie Rivers—all Taku River tributaries in British Columbia;

and the Klukshu River—a tributary of the Alsek River in the Yukon Territory), most

comparisons made between interior and coastal habitats were descriptive rather than 

inferential.

We compared and identified general patterns in the biological characteristics of coho

populations found in the three watershed types, as well as compared interior and

coastal stocks. These categories provided a convenient and intuitive separation to

evaluate potentially sensitive or biologically distinct stocks. Most of the comparisons

were among the three watershed types.

Biological characteristics included juvenile and adult (primarily from escapement data)

length, mean freshwater ages (MFWA) of juvenile, smolt, and adult fish, and migration timing of smolt emigration and immigration of returning adult fish. Demographic

variables included escapement indices (estimates of population size), exploitation

rates, and freshwater and marine survival. Compared to databases for other species

22

Table 2—Location and rearing habitat type for coho salmon stocks for which

biological data are available (continued)

Stream Location

Number Name Habitat typea Generalb N. latitudec W. longitudec

111-50-052 Montana Creek S MC 58°22 ́54 ̋ 134°35 ́46 ̋

111-50-056 Steep Creek S MC 58°24 ́56 ̋ 134°34 ́30 ̋

112-42-025 Kadashan Creek S I 57°42 ́08 ̋ 135°13 ́05 ̋

112-50-010 Pavlof Lake L I 57°50 ́39 ̋ 135°02 ́54 ̋

113-22-008 Politofski Lake L I 56°44 ́36 ̋ 134°56 ́36 ̋

113-22-028 Plotnikof Lake L I 56°33 ́51 ̋ 134°53 ́56 ̋

113-41-032 Salmon Lake L I 56°57 ́46 ̋ 135°08 ́54 ̋

113-41-043 Redoubt Lake L I 56°54 ́07 ̋ 135°12 ́36 ̋

113-62-005 Eagle River S I 57°15 ́d 135°40 ́d

113-62-008 Sinitsin Creek S I 57°19 ́d 135°44 ́d

113-66-006 St. John Creek S I 57°17 ́d 135°32 ́d

113-73-003 Ford Arm Lake L I 57°35 ́d 135°53 ́d

115-20-010 Berners River R MC 58°50 ́49 ̋ 134°58 ́08 ̋

115-32-032 Chilkat Lake L MC 59°13 ́33 ̋ 135°30 ́54 ̋

115-33-020 Chilkoot Lake L MC 59°19 ́15 ̋ 135°32 ́37 ̋

182-30-020 Klukshu Lake L MN

182-70-010 Situk River R MC 59°26 ́47 ̋ 139°33 ́58 ̋

192-42-020 Tsiu River R MC 60°04 ́d 143°07 ́d

a L = lake; R = river; and S = stream.

b I = island; MC = mainland coastal; and MN = mainland interior.

c Latitude and longitude are given for mouths of streams and rivers.

d Value interpolated from topographic maps.

Source: ADF&G 1994 for most locations.

Data Analysis

Procedures
of Pacific salmon in the region, more data were available on characteristics of rearing

juvenile coho, including body length for 28 stocks and emigration 

timing for 7 stocks. Consistent data were not available for all variables, and sample

sizes differed among variables depending on availability of adequate data.

Six stocks were included in the variance-component analysis of adult fork lengths.

Stocks were included based on the criteria of having at least 5 years of sampling with

samples of at least 15 individuals of each sex in the 2.1 age class, the only age class

that could be evaluated. The years sampled were not the same for all stocks. 

Migratory timing characteristics were evaluated for 24 stocks with daily weir counts

and 126 stocks for which our run-timing index could be calculated (see “General

Introduction”). Six of the systems with weirs also were included in the run-timing

index sample. Because of differences in data-collection methods and calculation 

procedures, mean dates from weirs and surveys were not comparable. Timing statistics also were compiled and compared for coho smolt emigration from seven systems

monitored with fyke nets or traps. 

Escapement survey data for 129 coho stocks with at least 7 survey years were taken

entirely from the computerized data files maintained by ADF&G, Division of Commercial Fisheries. This sample represented about 5 percent of all coho salmon

stocks in the region. For coho salmon, escapement survey records span 1960 to

1992, but only 20 percent of all stocks we analyzed were surveyed in 15 or more of

these years. Escapement counts made at weirs were extracted from ADF&G and

USFWS reports. Some weir counts for coho salmon collected before 1950 by the

USBF also are included in this report. Analysis of trends in abundance was hampered by the lack of consistent census methods and limited sample size. Furthermore, escapement data series for most coho stocks began in the 1970s or 1980s,

after many factors may have already resulted in declines in abundance.

Mean freshwater age and proportions of escapements in each age and sex class

were used to describe the age structure of 31 coho salmon stocks. Adult MFWAs

were calculated for each sex separately as well as combined. Jacks were not 

included in the calculation of MFWAs, because of inconsistent sampling of jacks from

escapements. The protocol for sampling the age structure of escapements frequently

consists of single, brief visit to each run. This sampling regime cannot detect seasonal shifts in age structure. Short-term sampling may be adequate for small stocks

with relatively brief runs, but serious bias can result from a few days of sampling from

large stocks with protracted runs.4 5 The most reliable age-structure data came from

stocks sampled throughout their runs at weirs. Interannual variation in MFWA was

examined only for stocks sampled at weirs. Because of the numerous limitations

associated with age-structure data, we relied entirely on grand means from all sample

years for our analyses of age-structure outliers. Age-structure analyses based on

small samples and few sample years should be regarded as highly provisional. 

23

4 Personal communication. 1996. M. Haddix, limnologist, Alaska

Department of Fish and Game, 2030 Sea Level Drive, Suite 215,

Ketchikan, AK 99901.

5 Personal communication. 1996. T. Zadina, fisheries biologist,

Alaska Department of Fish and Game, 2030 Sea Level Drive,

Suite 215, Ketchikan, AK 99901.
24

Mean freshwater ages and percentages in each age class were also calculated from

samples of juveniles (18 stocks) and emigrating smolts (9 stocks); these samples

could not be separated by sex. The age structure of juvenile coho samples may be

biased because of differences in trap efficiency for age classes, particularly age 0.0

fry, which may be undersampled when large (6.25 mm) mesh traps are used to 

capture juvenile fish.

Systematic errors in aging may be present in some age estimates, in particular those

for 1982 and 19836 (also see footnote 3). The ADF&G is in the process of reevaluating its scale-aging procedures for several species, including coho salmon. Since

1984, coho salmon aging techniques have been applied with enhanced consistency

but still may contain systematic errors (see footnote 3). Some portion of observed

patterns or trends in age structure of coho stocks may be an artifact of ongoing

changes in ADF&G scale-aging techniques.

Sex-ratio values were derived from escapement age-structure or body-length samples, whichever contained the most individuals. We expressed sex ratio both as a

numeric ratio, with the male portion of each sample standardized to one, and as the

percentage of each sample consisting of males. Statistical evaluation of sex ratios

was conducted only on weir samples; we assumed these samples were unbiased in

regard to sex. Because of the possibility of run-timing differences between the sexes,

weir samples were included only from years in which weirs were operational for the

entire run.

Survival rates from smolt to adult return or juvenile to adult return were compiled for

19 stocks of coded-wire-tagged coho salmon juveniles. Despite differences in methods used to estimate survival (Elliott and Kuntz 1988; Elliott and Sterritt 1990, 1991;

Elliott and others 1989; Gray and others 1978; Josephson 1985; Schmidt 1985, 1986,

1987, 1988, 1990; Schmidt and DerHovanisian 1991; Shaul 1989, 1990; Shaul and

Koerner 1988; Shaul and others 1986, 1987, 1991), computed values can be compared within each age class. Estimates of survival of rearing juveniles to time of

adult return incorporated some proportion of survival in freshwater as well as ocean

survival. Estimates for smolt survival rates reflect marine mortality. Estimates were

based on total return (catch and escapement) and reflect natural mortality. Only four

stocks had sufficient data to allow evaluation of long-term temporal trends in survival. 

The term “exploitation rate” is used here to refer to the total catch of a stock by all

fisheries divided by the total return (catch plus escapement) (Shaul 1988). Methods

used to estimate exploitation rates also can be found in Elliott and Kuntz 1988; Elliott

and Sterritt 1990, 1991; Elliott and others 1989; Gray and others 1978; Josephson

1985; Schmidt 1985, 1986, 1987, 1988, 1990; Schmidt and DerHovanisian 1991;

Shaul 1989, 1990; Shaul and Koerner 1988; and Shaul and others 1986, 1987, 1991.

Again, these estimates are roughly comparable despite differences in estimation 

techniques used by various authors.

6 Personal communication. 1996. S. Elliott, fisheries biologist,

Alaska Department of Fish and Game, 802 3d Street, Douglas, AK

99824.
25

One major goal of this project, to identify distinctive coho salmon stocks, was thwarted by the paucity of studied stocks relative to the total number of stocks in the region.

Intensive study of indicator systems provided the long-term temporal data sets necessary to understand patterns of temporal variation, but these systems may not represent the full range of geographic variation found throughout the region. If the small

sample of stocks for which biological data exist is representative of the distribution of

variation among all stocks in the region, then stocks identified by outlier analysis as

distinctive are likely to represent unusual elements of regional intraspecific diversity.

The existing small sample was chosen because it was considered by ADF&G to be

typical among stocks found in different watershed types in different districts, but it is

difficult for such a small proportion of stocks to represent the spectrum of variation.

Stream stocks clearly were undersampled. 

For various reasons, data for coho salmon are particularly prone to the limitations

described in the “General Introduction.” Most of the reasons for limited data quality

are associated with the late run timing of most coho salmon stocks; i.e., coho run 

timing coincides with periods of high precipitation and increased stream flow, resulting in logistical difficulties, poor visibility, and inconsistent sampling effort and survey

methodology. Furthermore, most weirs at which coho salmon are enumerated and

sampled for biological characteristics are operated primarily for sockeye salmon, and

frequently the weirs are removed before completion of the coho salmon runs. Early

weir removal has obvious effects on run-timing statistics and abundance estimates,

and because age composition and sex ratio can vary during the course of a run, 

termination of sampling before run completion can introduce bias into data for these

characteristics as well. Potential sources of bias should be kept in mind when evaluating our results for these characteristics. Sampling and counts conducted at weirs,

nonetheless, provide the most detailed data available for biological characteristics of

coho stocks.

For each variable considered, results are generally presented in the following

sequence. First, comparisons among watershed types are presented and basic 

patterns described. Second, age classes and sexes are compared within stocks, and

age-sex effects on biological variables such as body length are considered (the number of stocks studied was inadequate to conduct multivariate analyses). Third,

results of analyses conducted to examine relations among biological variables are

presented. These analyses were possible in only a few cases. Fourth, chronological

trends are presented. Finally, stocks are identified that deviate substantially from typical patterns described in any of the preceding analyses. 

Juveniles and smolts—Rearing habitat did not have any consistent effects on fork

lengths of rearing juvenile coho salmon. Fry in stream systems appeared to be smaller than fry in other watershed types (fig. 5A), but the stream watershed type is represented by samples from only two streams that are in the same drainage. Fork

lengths of juvenile (age 1.x) coho salmon did not differ consistently among watershed

types (fig. 5B); the data set for age 2.x was too small to analyze. Chilkat Lake juveniles were consistently the largest measured in all age classes, but an insufficient

number of stocks were sampled to conduct outlier analysis.

Results

Body Length
Smolts of all ages emigrating from stream systems were consistently smaller than

those emigrating from lake and river systems (fig. 6). The difference in body size

between watershed types increased with increasing freshwater age (fig. 6). Smolts

from Eagle River were consistently the smallest in all age classes (fig. 6). The minimum length of coho salmon smolts in southeast Alaska is about 70 mm. Combining

data from all systems, the mean size of smolts increased by about 15 mm for each

additional year spent in fresh water. In all cases where early and late samples were

taken during the same season, larger smolts of a given age class emigrated later.

Adults—A graphic comparison of watershed types indicated no consistent pattern of

adult body size (mideye-to-fork length) variation by watershed type for either sex (fig.

7). Severely unbalanced sample sizes precluded statistical comparisons among

watershed types; 20 of the 27 stocks sampled inhabited lake systems. All watersheds were pooled for subsequent analyses of body length.

Male and female adult body lengths were significantly different for all age classes

(paired t-tests, maximum P = 0.02; females always larger); sexes were evaluated 

separately in all comparisons. Male body length did not differ significantly among

freshwater age classes (Kruskal-Wallis, P = 0.39, nonsignificant [NS]) but female size

increased significantly with increasing freshwater age (Kruskal-Wallis, P = 0.01). 

26

Figure 5—Body lengths of rearing coho salmon juveniles by habitat

type: (A) age 0.x, (B) age 1.x. Plotted values are means for all years

sampled, for each stock. Means are for samples taken in June and

July only.
27

Figure 6—Body lengths of coho salmon smolts by freshwater age,

stock, and habitat type. Despite its name, Eagle River is considered

a stream stock (see table 2). Plotted values are means for all years

sampled for each stock. Samples taken in mid-April to May only.

Figure 7—Body lengths of coho salmon adults by habitat type: (A)

males, (B) females. Plotted values are grand means for all stocks in

each of the three habitat types. Bars give standard errors of grand

means. Sample size differs with sex and age class but never

exceeds 20 for lake stocks, 4 for river stocks, and 3 for stream
The body sizes of males and females within stocks were correlated (age class 1.1, 

r = 0.78, P < 0.0001; age class 2.1, r = 0.82, P < 0.0001; age class 3.1, r = 0.55, 

P = 0.032). When male and female body sizes within each stock were compared, 

no stock showed an unusual pattern of sexual dimorphism.

Variance-component analysis indicated that over 90 percent of total variation in male

body length and 89 percent of female body-length variation were attributable to 

differences among individuals within the six stocks evaluated (table 3). Interannual

variation within stocks was twice as great in females (11 percent) as in males (5.5

percent). For females, variation among stocks was negligible.

No significant temporal trends were found in adult body-length variation from 1982

through 1990 for the eight stocks analyzed (table 4). Nine of sixteen regression coefficients were negative, and only one result approached significance (Salmon Lake

males, slope = -0.73, P = 0.06). Interannual variation in body length was high, but

this variation did not show any consistent trend during the relatively short period 

covered. A regression analysis on the body weights of commercially caught coho

salmon in southeast Alaska from 1958 to 1985 (Marshall and Quinn 1988) revealed 

a nonsignificant trend of decline (R2 = 0.09, F = 2.59, P = 0.12). 

28

Table 3—Variance component analysis of age 2.1 coho salmon mideye-to-fork

lengths from escapement samplesa b

Degrees Percentage

Source of of Type 1 sum of Expected mean Variance of 

variation freedom squares F-test Error term square component total

Males

Total 3,507 18,758,882 5,348.98 5,403.81 100

Stocks 5 850,769.69 4.57 Years 170,153.94 215.23 3.98

Years 24 892,654.85 7.60 Error 37,193.95 296.27 5.48

Error 3,478 17,015,457 4,892.31 4,892.31 90.53

Females

Total 3,663 9,895,958.2 2,701.60 2,724.68 100

Stocks 5 209,493.73 1.15 Years 41,898.75 -9.74 0

Years 24 877,062.69 15.08 Error 36,544.28 300.52 11.03

Error 3,634 8,809,401.8 2,424.16 2,424.16 88.97

a Variance components computed from means, standard errors and sample sizes.

b Stocks included in the analysis:

101-30-075 Hugh Smith Lake

111-32-066 Yehring Creek

111-50-042 Auke Lake

113-41-032 Salmon Lake

113-73-003 Ford Arm Lake
Females from Pavlof Lake in the 1.1 and 2.1 age classes were distinctively small (fig.

8). The spawning migration of this stock also is unusually early (see “Adult Spawning

Migrations,” below). The Pavlof Lake stock was among the stocks with the smallest

body sizes in all age and sex classes for which data were available. There is a positive association between age 2.1 adult body sizes and mean dates of spawning

migrations from systems with weirs (males, N = 20, R2 = 0.12, b = 0.34, P = 0.16, 

NS; females, N = 20, R2 = 0.57, b = 0.57, P = 0.01). 

Smolt emigration—The grand mean emigration date for smolts in all years in all

seven systems measured was 21 May (Julian date of 141, SE = 2.2 days). Daily

count data indicated that, although the mean date of migration was relatively consistent both within and among stocks, the duration of runs differed considerably both

among years within stocks and among stocks (table 5).

No differences in emigration timing were apparent among watershed types. The 

single year of data available from the Nahlin River indicated late emigration timing,

which may be attributed to the colder climate associated with the interior location of

this drainage. Salmon Lake and Eagle River stocks, both near the outer coast, had

the earliest emigration timing.

Adult spawning migrations—Klawock River, Warm Chuck Lake, and Redoubt Lake

were three locations where both historic and contemporary weir counts were available. In all three cases, the contemporary mean migration dates were later than

those from the recent past. The mean migration date of adult coho salmon returning

to the Klawock River from 1930 through 1938 was about 10 days earlier than that

observed between 1982 and 1987; similarly, returns to Redoubt Lake were about 

29

Table 4—Regression analysis of trends across years in mideye-to-fork lengths

from coho salmon escapements

Stream Males Females

No. No.

years R- Signifi- years R- SignifiNumber Name sampled squared Slope P-value cance sampled squared Slope P-value cance

101-30-075 Hugh Smith 

Lake 6 0.11 0.33 0.52 NS 6 0.22 0.46 0.35 NS

111-32-032 Taku River 5 0.05 -0.23 0.71 NS 5 < 0.00 0.003 0.99 NS

111-32-066 Yehring 

Creek 5 0.09 0.30 0.63 NS 5 0.27 0.52 0.37 NS

111-50-042 Auke Lake 6 0.01 -0.10 0.85 NS 6 0.004 0.07 0.90 NS

113-41-032 Salmon 

Lake 7 0.53 -0.73 0.06 NS 8 0.07 -0.26 0.54 NS

113-41-043 Redoubt 

Lake 7 0.10 -0.10 0.83 NS 7 0.01 -0.11 0.82 NS

113-73-003 Ford Arm 

Lake 5 0.46 -0.68 0.21 NS 7 0.40 -0.64 0.25 NS

115-20-010 Berners

River 5 0.01 -0.11 0.86 NS 5 0.006 0.08 0.90 NS

NS = not statistically significant

Timing
10 days earlier from 1953 through 1957 than from 1982 through 1988. Returns to

Klawock River after 1980 may have been influenced by the presence of the hatchery

on the river. During the same period, Redoubt Lake was fertilized to increase primary

productivity.

The mean date of spawning migration at Salmon Lake showed no prevailing trend

across the 8 recent years for which daily weir count data were available (R2 =0.002, 

P = 0.92 NS). At Auke Lake, 20 years of daily weir counts from 1971 through 1990

showed a nearly significant trend toward earlier migration (R2 = 0.19, P = 0.06 NS). 

30

Figure 8—Frequency distributions, outlier plots, and normal quantile plots for mideye-to-fork lengths of (A) age 1.1 females, N = 26, and (B) age 2.1 females, N =

27. For both age classes, females from the Pavlof Lake stock are distinctively

small. Both distributions are significantly non-normal by the Wilks test but become

acceptably normal when the Pavlof Lake data point is removed.
31

Table 5—Coho salmon smolt emigration counts and timing

Stream

Total Mean date

Number Name Notes Year count Calendar Julian Variance Source

101-29-006 Vallenar Creek a 1988 4,177 18-May 138 19.06 Elliott and others 1989

109-10-006 Sashin Creek b 1968 1,440 24-May 144 Crone and Bond 1976 c 1967 1,400 25-May 145  ̋

1964 334 24-May 144  ̋

1963 1,599 24-May 144  ̋

1962 2,865 27-May 147  ̋

1961 2,489 28-May 148  ̋

1960 1,258 10-Jun 161  ̋

1959 1,587 27-May 147  ̋

1958 1,015 20-May 140  ̋

1957 1,961 24-May 144  ̋

1956 928 15-Jun 166  ̋

Mean 148

SE 0.72

111-32-032 Taku River 

Canyon Island) d 1961 24-May Meehan and Siniff 1962

111-32-066 Yehring Creek 1989 9,654 25-May 145 31 Elliott and Sterritt 1990

1987 5,853 25-May 145 52.96 Elliott and Kuntz 1988

111-32-270 Nahlin River e 1990 2,053 11-Jun 162 11 Elliott and Sterritt 1991

113-41-032 Salmon Lake f 1990 7,494 4-May 124 108 Schmidt and 

DerHovanisian 1991

1989 6,683 11-May 131 49.78 Schmidt 1990 g 1988 7,281 09-May 129 21.76 Elliott and others 1989

113-41-032 Salmon Lake h 1987 10,952 11-May 131 71 Schmidt 1988 h, i 1986 7,397 16-May 136 35 Schmidt 1987 h, j 1985 6,834 27-May 147 33 Schmidt 1986 k 1984 4,089 12-May 132 17 Schmidt 1985

Mean 133

SE 1.03

113-62-005 Eagle River l 1990 2,880 5-May 125 64 Schmidt and 

DerHovanisian 1991 m 1989 3,259 10-May 130 66.04 Schmidt 1990

1988 3,919 11-May 131 45.44 Elliott and others 1989

Mean 129

SE 1.07

Total mean 21-May 141 44.58

Total SE 2.21

a Weir out 28 April through 2 May and on 22 May and 28 May.

b Mean dates reported for Sashin Creek are actually the date of the largest outmigration.

c Counting procedure changed from total to partial counts: holding facilities were inadequate for retaining all smolts 

captured.

d Midweek date from week with largest catch.

e Rapidly melting snow produced flood conditions during most of May. Few smolt were caught during this period because

the nets were plugged with debris.

f Fyke net washed out or deactivated because of high water 27-29 March and 19-22 April.

g Partial night of trapping on 12 May and no fishing done on 13-14 May because of high water.

h To calculate mean dates where cumulative totals for 3 or 4 days were given rather than daily counts, equal portions were

allocated for each day.

i Fyke nets were not fished 12-16 April owing to low water levels.

j Fyke nets were not fished 14-16 May owing to high water.

k Traps were not set on 22 April and 28 April.

l Fyke net washed out on 4 May. Fyke net washed out on 17 May.
The grand mean date of adult spawning migrations was 27 September (Julian date

270; N = 21 stocks with daily weir counts). The Falls Lake stock had a distinctively

early mean date of migration among the 21 stocks contained in the overall distribution (fig. 9A). The mean migration date for jacks was 23 September (Julian date 266;

N = 10 stocks). The Nahlin River stock returned early in comparison to other stocks

in the upper Taku drainage (see Elliott and Sterritt 1991), but the grand mean date for

the Nahlin stock was not an outlier. 

32

Figure 9—Frequency distributions, outlier plots, and normal quantile plots for (A)

mean dates of passage at weirs, N = 21, and (B) index dates based on the timing

of peak escapement survey counts, N = 126. The Falls Lake stock has a distinctively early weir mean date, 26 August, and a small mean escapement of 129 fish.

The Salt Chuck-George Inlet, Pavlof Lake, and Plotnikof Lake stocks all have distinctively early-run timing, with peak escapement surveys typically occurring during

the first 2 weeks of August. The George Inlet and Pavlof Lake stocks are small,

with mean escapement estimates of 159 and 158 fish, respectively. The mean estimated escapement for Plotnikof Lake is nearly 1,400 fish.
Outlier analysis of run timing index dates (N = 126 stocks) indicated that three stocks

had unusually early run timing (Salt Chuck-George Inlet, Port Banks [Plotnikof Lake],

and Pavlof Lake; fig. 9B). No stocks were detected with exceptionally late migration

timing, but this result probably reflects a lack of surveys late in the year during

adverse climatic conditions. Coho stocks in Lynn Canal migrate later than most

stocks, but none of the stocks for which data were available was an outlier from the

run-timing distribution. Late run timing often is correlated with spawning in glacial

systems (Shaul 1989), because delaying until after the onset of colder weather may

enable spawners to avoid high concentrations of glacial silt. Some coho stocks in the

Yakutat area (e.g., Tawah Creek) are known to spawn in February and even into

March (see footnote 3), perhaps because winter water temperatures there are relatively warm.

The demographic variables evaluated for coho salmon stocks were escapement

trends and magnitude, the effects of water quality on population status, age structure

(of rearing juveniles, emigrating smolts, and spawning adults), sex ratio of spawning

adults, survival, and stock exploitation rates.

Escapement—Among the five stocks monitored at weirs, the only significant 

result was a decline in the number of jacks counted at the Salmon Lake weir. 

Among stocks monitored with escapement surveys, nine of 128 stocks increased 

significantly, and seven decreased significantly (using stocks with at least seven

records from 1960 to 1992 and fair data quality; table 6). Of the nine increasing

stocks, four were near Juneau and exhibited high returns during the past 5 years

when coho returns were also high to the Douglas Island Pink and Chum (DIPAC)

hatchery on Gastineau Channel in Juneau. Three declining stocks on Mitkof Island

(Bridge, Lee's Cabin, and Powerline Creeks) are all in small streams within 1 km of

Crystal Lake hatchery that are affected by variable rates of straying by returning

hatchery fish and interception in commercial and sport fisheries for hatchery returns.7

Most of the stocks with declining escapements occurred in stream systems (six of

seven stocks); the lone exception was the Port Banks (Plotnikof Lake) stock (table

6). Increasing stocks were less likely to occur in lake-containing watersheds (7 percent of 27) than in stream or river systems (33 percent of 21; Fisher test, p = 0.03). 

Because lake systems often are considered more stable in their production of coho

salmon than stream systems, we compared variation over time (coefficient of variation) in weir escapement counts for these two watershed types. Coefficients of variation for lakes ranged from 23 percent to 73 percent, but the only available stream

(Sashin Creek) coefficient was 141 percent.

The Tsiu and Tsivat River stocks had the highest escapements among the 124 stocks

included in the outlier analysis of survey data (fig. 10). The coho salmon stocks in

these rivers have been noted historically for their exceptional productivity (Shaul and

others 1987).

33

Demography

7 Personal communication. 1996. F. Cole, staff officer, U.S.

Department of Agriculture, Forest Service, Tongass National

Forest, Stikine Area, P.O. Box 309, Petersburg, AK 99833.
34

Figure 10—Frequency distribution, outlier plot, and normal quantile

plot for mean peak escapement counts of stocks included in escapement surveys, N = 126. The Tsiu and Tsivat River stocks are distinctively large, with mean escapements over 22,000 and 11,000 fish,

respectively. These rivers are close together on the Yakutat forelands.

Table 6—Coho salmon stocks with significantly declining escapement trends

Stream Location

Data

Number Name VCUa General Land useb quality Possible factors

101-71-041 Indian Creek 796K Misty Fiords National 

Monument Wilderness Fair Unknown

105-10-024 Bear Harbor Creek 409S Kuiu Island Wilderness Fair Unknown

106-44-024 Bridge Creek 451S Mitkof Island LUD III Fair Habitat degradation;

timber harvest hatchery effects, road

in headwaters culverts

106-44-026 Lees Cabin Creek 451S Mitkof Island LUD III Fair Habitat degradation;

timber harvest hatchery effects; road 

culverts

106-44-027 Powerline Creek 451S Mitkof Island LUD III Fair Habitat degradation;

timber harvest hatchery effects; road

culverts

111-50-065 Johnson Creek 33C Douglas Island Private Fair Habitat degradation

113-22-028 Plotnikof Lake 344C South Baranof Island Wilderness Fair Unknown

a VCU = USDA, Forest Service value comparison unit; approximately equivalent to a watershed; K = Ketchikan Area; 

S = Stikine Area; and C = Chatham Area.

b LUD = land use designations:

LUD II = roadless areas

LUD III = multiple use

LUD IV = intensive resource use (especially logging)
Water quality and demographic status—Coho salmon stocks in water bodies 

currently listed as impaired in southeast Alaska (N = 9; table 7; ADEC 1992) were

typically small, with peak survey counts of less than 100 individuals. The only larger

stock in an impaired water body is in Rowan Bay on Kuiu Island, but survey counts

differed in methods and timing and ranged from 0 to 936. Of the coho stocks that

spawn in suspected water bodies, only 6 stocks had 7 or more years of escapement

surveys, enough to permit analysis of population trends. Montana Creek showed a

significant population increase that can be attributed to the DIPAC hatchery. Furthermore, Montana Creek is relatively undisturbed in the upper part of the watershed. 

In contrast, the coho stock in nearby Lemon Creek, a heavily impacted stream with

gravel extraction, timber harvest, and urbanization, began with low numbers and

decreased further. In Lemon Creek, 57 fish were counted in 1974; in the following

years, counts ranged between 15 and 5 fish with no fish observed during the last 

survey in 1985. No stocks with distinctive biological characteristics were found in

either impaired or suspected water bodies.

35

Table 7—Coho salmon stocks in impaired or suspected water bodies

Stream Location

Pollutant

Number Name VCUa General source typesb Comments

Impaired water bodies

101-47-015 Ward Cove 749K Ketchikan IN, Debris High count, 1,550 fish in 1985, below 100 fish 

since 1987, but surveys early. Highly 

manipulated population.

109-52-007 Rowan Bay 402S Kuiu Island TH Variable survey methods, high count 936 fish in 

1971. No recent surveys.

111-40-010 Lemon Creek 32C Juneau UR, PP, MI, High count 57 fish in 1974. Last count in 1985, 

LF, SM, GM 0 fish.

111-40-012 Vanderbilt 

Creek 32C Juneau UR, GM, LF 50 fish counted in 1984

111-40-015 Salmon Creek 32C Juneau UR, DDE, Possible introgression of hatchery fish. 

PCB

111-40-089 Lawson Creek 33C Douglas UR, RD, CH, 12 fish in 1984, only count. 

SM

111-50-060 Duck Creek 32C Juneau UR, PP, LF, High count 80 fish in 1992. Possible hatchery 

CH, RD, LD fish 

113-41-017 Granite Creek 311C Sitka UR, GM 2 fish in 1981.

115-32-091 Sawmill Creek NA Haines UR, ST, CH, 20 fish in 1976, 1 fish in 1979, no counts since. 

SM, RD

Suspected water bodies

101-45-016 White River 748K Ketchikan TH Small run, < 40 fish.

101-47-025 Ketchikan 

Creek 751K Ketchikan UR, IN, SE Very variable counts.

102-70-058 Thorne Bay 586K Thorne Bay IN, UR, SE, Poorly documented. High count 63 fish in 1986.

SM

103-60-059 Port St. 

Nicholas Creek NA Craig TH, UR Variable; high count 200 fish in 1982.

103-90-030 Staney Creek 588K Prince of TH Variable; 1,114 fish in 1986, 37 fish in 1988. 

Wales Mean USBF weir count 1929-32, 9,101 fish.

111-40-007 Switzer Creek 32C Juneau UR, DDT Variable run strength up to 227 fish in 1991.

111-50-052 Montana Creek 27C Juneau UR Run expanding, 2,208 fish in 1992.

111-50-062 Jordan Creek 27C Juneau UR, LD Variable run, 785 fish in 1992.

112-65-024 Greens Creek 144C Hawk Inlet PP Small, poorly documented, run. Three fish in 

1989.
Age structure—Mean freshwater age of juveniles did not show a clear pattern of

variation among watershed types (fig. 11). Some interior mainland rivers had very

low juvenile MFWAs, especially the Dudidontu (MFWA = 0.02 years). The low MFWA

may be attributed to immigration of nomad fry from upstream habitats (Chapman

1962). Low fry-to-juvenile (age 1.x) survival is likely in main stream habitats (Bryant

1985a).

The MFWA of lake smolts (N = 5 stocks) was typically higher than that of stream (N =

3) or river (N = 2) smolts (fig. 11B). Twenty to fifty percent of smolts in lake systems

spent at least 3 years rearing in fresh water, but only 2 to 13 percent of stream

smolts and 0 to 21 percent of river smolts spent 3 years in fresh water. The Nahlin

River had the lowest smolt MFWA (1.12 years), with 88 percent of the smolt cohort

emigrating after 1 freshwater year. The MFWA of Nahlin River returning adults was

higher than that of smolts and juveniles, however (table 8). The Nahlin is a tributary

of the Taku, and the juveniles from the Nahlin may have moved downstream into the

Taku River drainage rather than emigrating to salt water. Older and larger smolts

may experience better ocean survival, which could account for the high MFWA of

adults relative to smolts (Holtby and others 1990). This pattern observed for the

Nahlin stock was based on single samples for each life history stage, and the samples do not correspond to a single cohort. 

In contrast to the Nahlin River stock, MFWA of smolts was greater than that of adults

(sexes combined for comparison of life history stages) in 15 of 24 cases in which the

MFWA of an emigrating smolt cohort could be compared to the MFWA of that same

cohort when it returned to spawn (Elliott and others 1989). Such changes may indicate that differential survival among age classes occurred during the period between

samples (specifically, better survival for younger smolts), or there were sampling

errors.

36

Table 7—Coho salmon stocks in impaired or suspected water bodies (continued)

Stream Location

Pollutant

Number Name VCUa General source typesb Comments

113-41-021 Sawmill Creek 318C Sitka LF Poorly documented. High count 100 fish in

1985. 

113-72-002 Klag Bay 271C Klag Bay MI, TA, Poorly documented. High count 2,000 fish in 

metals 1963, only 2 fish in 1980.

115-20-007 Johnson Creek 16C Berners Bay TA Small, poorly documented run. High count of 

28 fish in 1984

NA = not available.

a VCU = USDA, Forest Service value comparison unit; approximately equivalent to a watershed; K = Ketchikan Area; 

S = Stikine Area; and C = Chatham Area.

b Pollutant source types:

CH = channelized stream IN = industrial PCB = polychlorinated biphenyls

DDE = dichlorodiphenylchloroethane LD = land development PP = petroleum products 

DDT = dichlorodiphenyltrichloroethane LF = landfill RD = road runoff

GM = gravel mining MI = mining

SE = sewage discharge TA = tailings

SM = streambank or shoreline modification TH = timber harvest

ST = septic tanks UR - urban runoff

Source: ADEC 1992; ADF&G computerized escapement database.
37

Figure 11—Mean freshwater ages (MFWA) by life history stage and habitat

type: (A) rearing juveniles, (B) smolts, and (C) adults. Horizontal lines denote

medians, boxes enclose ± 25 percent of distributions, and bars indicate

ranges. Boxes enclose entire range when sample sizes are very small.
38

Table 8—Summary of age distributions of coho salmon escapement samples

Stream Males Females

Age classes Age classes

Number Name No. 1.0 2.0 1.1 2.1 3.1 4.1 MFWAa No. 2.0 1.1 2.1 3.1 4.1 MFWAa MFWAa

-------------------Percent b------------------ Years --------------------Percent b--------------------- Years

101-30-075 Hugh Smith 

Lake 1,326 0 4 24 57 14 1 1.92 1,672 0 18 62 18 1 2.03 1.93

101-80-068 McDonald 

Lake 64 0 0 70 27 3 0 1.33 95 0 65 31 3 1 1.40 1.37

101-90-050 Naha River 166 0 0 16 58 23 3 2.13 183 0 15 63 19 3 2.11 1.96

102-30-067 Kegan Lake 110 0 0 42 58 0 0 1.58 93 0 44 56 0 0 1.56 1.57

102-60-087 Karta River 514 0 0 43 52 5 0 1.62 340 0 40 56 4 0 1.65 1.64

103-15-027 Klakas Lake 426 0 0 72 27 0 0 1.28 528 0 73 34 0 0 1.43 1.36

103-80-031 Warm Chuck 

Lake 556 6 3 70 21 0 0 1.28 638 0 70 26 0 0 1.25 1.26

103-90-010 Sarkar Lake 35 0 0 43 54 3 0 1.60 84 0 57 43 0 0 1.43 1.48

106-41-010 Salmon Bay 

Lake 480 0 3 12 52 25 6 2.26 484 4 9 49 33 7 2.39 2.34

108-70-002 Stikine River 119 2 1 62 34 0 0 1.36 48 0 44 54 2 0 1.58 1.39

109-20-013 Falls Lake 187 0 1 26 70 3 0 1.76 171 0 32 67 2 0 1.70 1.73

111-17-010 King Salmon 

River 17 0 0 65 29 6 0 1.41 20 0 50 40 5 5 1.65 1.54

111-32-032 Taku River 3,582 0 0 45 52 2 0 1.57 2,295 0 40 57 2 0 1.62 1.57

111-32-066 Yehring 

Creek 1,026 0 0 16 81 2 0 1.85 1,140 0 13 86 2 0 1.89 1.87

111-32-260 Hackett River 117 0 0 42 53 5 0 1.63 81 0 35 62 4 0 1.69 1.67

111-32-270 Nahlin River 229 0 0 9 90 2 0 1.93 162 0 4 96 0 0 1.96 1.94

111-33-034 Speel Lake 715 0 6 34 59 1 0 1.64 683 0 29 69 1 0 1.72 1.68

111-50-042 Auke Lake 825 0 13 17 54 10 1 1.95 691 0 16 69 13 1 1.99 1.97

111-50-052 Montana 

Creek 45 0 0 29 47 24 0 1.96 57 0 30 60 9 2 1.82 1.88

111-50-056 Steep Creek 20 0 0 25 65 10 0 1.85 20 0 40 45 15 0 1.75 1.79

112-50-010 Pavlof Lake 42 0 0 36 64 0 0 1.64 28 0 32 61 7 0 1.75 1.69

113-22-008 Politofski 

Lake 335 1 11 33 51 4 0 1.67 234 0 34 62 3 0 1.70 1.68

113-41-032 Salmon Lake 781 1 21 9 34 18 5 2.29 492 3 10 53 27 6 2.31 2.30

113-41-043 Redoubt Lake 859 1 8 20 55 12 5 2.01 705 0 13 56 20 10 2.30 2.09

113-62-005 Eagle River 25 0 0 0 96 4 0 2.04 26 0 0 88 12 0 2.12 2.08

113-73-003 Ford Arm 

Lake 1,225 0 6 10 43 24 5 2.30 1,042 0 12 42 32 6 2.35 2.32

115-20-010 Berners River 1,335 0 0 35 63 2 0 1.68 827 0 29 69 3 0 1.74 1.71

115-32-032 Chilkat Lake 303 5 0 20 79 1 0 1.81 282 0 14 83 3 0 1.89 1.84

115-33-020 Chilkoot Lake 358 0 0 18 77 5 0 1.87 377 0 20 77 3 0 1.82 1.84

182-30-020 Klukshu River 40 0 0 98 3 0 0 1.03 43 0 98 2 0 0 1.02 1.02

192-42-020 Tsiu River 26 0 0 85 15 0 0 1.15 15 0 53 47 0 0 1.47 1.27

Total mean 0.5 2.5 36.3 52.3 6.7 0.8 1.7 0.2 33.5 56.9 7.8 1.4 1.8

Total SD 1.4 4.9 24.5 21.4 8.1 1.8 0.3 0.9 22.8 19.4 9.7 2.6 0.3

Total CV 275.6 197.7 68.1 41.3 121.5 219.7 18.5 394.4 68.5 34.4 125.3 194.5 18.4 18.1

a MFWA = mean freshwater age. MFWA calculations do not include jacks or jills.

b Percentages may not add up to 100 because rare age classes have been omitted and because of rounding.
Adult MFWAs showed no clear differences among watershed types (fig. 11C), in 

contrast to the smolts. Variation in age structure among stocks was substantial, and

roughly equivalent, for both sexes (table 8). 

No stock had either a single-sex or a combined MFWA that was an outlier from the

distribution of all stocks sampled. The Tsiu River (N = 46 fish in 1 sample year) and

Redoubt Lake (N = 1,564 fish during 7 sampling years) stocks had distinctive differences between sexes in MFWA, with females spending, on average, nearly 4 months

longer in fresh water than males (fig. 12).

Adult MFWA increased through time in two of four testable stocks (Hugh Smith Lake

and Redoubt Lake; table 9). Both systems have been exposed to increased nutrient

inputs, through lake fertilization programs. Suburban development around Auke Lake

may account for the nearly significant increase (P = 0.08). The Salmon Lake stock

did not show a significant trend in MFWA for either adults or smolts.

Because MFWA analysis can obscure unusual bimodal age distributions, we conducted outlier analyses on the proportions of individuals found in predominant age classes. The Klukshu River stock had distinctively high proportions of age 1.1 individuals,

and correspondingly low proportions of age 2.1 individuals, for both sexes (fig. 13).

However, the Klukshu River has been sampled for age distribution for only one year,

and that sample consisted of only 83 individuals. The Eagle River stock had a 

distinctively high proportion of age 2.1 males, based on a sample of 25 fish from a

single year (fig. 13).

Sex ratio—Three lake stocks (of 13 stocks sampled at weirs) in southern southeast

Alaska had escapement sex ratios significantly skewed in favor of females (Hugh

Smith Lake, Klakas Lake, and Warm Chuck Lake; table 10). The large sample sizes

for these three stocks made a nonsignificant result unlikely. Yehring Creek (one of

two stream stocks sampled at a weir) also had a sex ratio significantly skewed in 

39

Figure 12—Frequency distribution, outlier plot, and normal quantile plot for MFWA differences between males and females in coho salmon escapements, N = 31. The Tsiu River

and Redoubt Lake stocks have distinctively high levels of sexual differences, with females

remaining in fresh water, on average, nearly 4 months longer than males. The sample

from the Tsiu River consists of only 46 fish from a single year, but the Redoubt Lake 

sample includes over 1,500 fish sampled during 7 years.
40

Figure 13—Frequency distributions, outlier plots, and normal quantile plots for proportions of individuals in escapement samples by age

and sex class: (A) age 1.1 males, (B) age 2.1 males, (C) age 1.1 females, and (D) age 2.1 females; N = 31 for all distributions. The

Klukshu River stock has distinctively high proportions of age 1.1 males and females and distinctively low proportions of age 2.1 individuals. The Eagle River stock has a distinctively high proportion of age 2.1 males in escapement samples. The sample sizes for both the

Klukshu and Eagle Rivers are small, N = 83 and 51 fish, respectively.

Table 9—Regression analyses of trends across years in mean freshwater age

(MFWA) of coho salmon stocks

Stream Regression

Adult (AD) or No. years

Number Name smolt (SM) sampled R-squared Slope P-value Trenda

101-30-075 Hugh Smith Lake AD 6 0.87 0.93 0.006 **

SM 6 0.14 0.38 0.46 NS

111-50-042 Auke Lake AD 6 0.58 0.76 0.08 NS

SM 15 0.16 -0.40 0.14 NS

113-41-032 Redoubt Lake AD 6 0.74 0.86 0.03 *

SM 6 0.39 0.63 0.19 NS

113-41-032 Salmon Lake AD 6 0.09 0.31 0.56 NS

SM 6 0.01 0.09 0.87 NS

a * = 0.05 > P > 0.01; ** = 0.01 > P > 0.001; and NS = not statistically significant.
41

Table 10—Analysis of escapement sex ratios for coho salmon stocks sampled

at weirs

Stream

Proportion Chi-square Fisher exact

Number Name Sex No. males Sex ratioa value P-valueb test P-valueb

101-30-075 Hugh Smith Lake M 1,324 0.44 1:1.27 19.84 < 0.001 *** < 0.001***

F 1,668

(jacks excluded) M 1,262 0.43 1:1.33 26.47 < 0.001 *** < 0.001 ***

F 1,654

103-15-027 Klakas Lake M 426 0.45 1:1.22 5.47 0.02 * 0.02 *

F 528

103-80-031 Warm Chuck Lake M 556 0.47 1:1.13 2.82 0.09 NS 0.1 NS

F 638

(jacks excluded) M 503 0.44 1:1.27 8.01 0.005 ** 0.005 **

F 638

106-41-010 Salmon Bay Lake M 259 0.49 1:1.04 0.14 0.71 NS 0.76 NS

F 271

(jacks excluded, M 244 0.47 1:1.13 0.66 0.42 NS 0.45 NS

1987 only) F 270

109-20-013 Falls Lake M 127 0.51 1:0.96 0.02 0.89 NS 0.93 NS

(1983 and 1984 only) F 124

111-32-066 Yehring Creek M 152 0.40 1:1.50 8.42 0.004 ** 0.005 **

(1988 only) F 232

111-32-260 Hackett River M 117 0.59 1:0.69 3.30 0.07 NS 0.09 NS

F 81

111-32-270 Nahlin Riverc M 229 0.59 1:0.69 5.78 0.02 * 0.02 *

F 162

111-33-034 Speel Lake M 714 0.51 1:0.96 0.34 0.56 NS 0.57 NS

F 683

(jacks excluded) M 668 0.50 1:1.00 0.04 0.85 NS 0.88 NS

F 678

111-50-042 Auke Lakec M 825 0.54 1:0.85 5.93 0.02 * 0.02 *

F 691

(jacks excluded) M 684 0.50 1:1.00 0.02 0.89 NS 0.91 NS

F 691

113-22-008 Politofski Lake M 331 0.59 1:0.82 8.38 0.004 ** 0.004 **

F 234

(jacks excluded) M 290 0.55 1:1.22 3.11 0.08 NS 0.08 NS

F 233

113-41-032 Salmon Lakec M 781 0.61 1:0.64 33.22 < 0.0001 *** < 0.0001 ***

F 492

(jacks excluded) M 520 0.52 1:0.92 0.97 0.32 NS 0.35 NS

F 476

113-41-043 Redoubt Lake M 507 0.55 1:0.82 4.92 0.03 * 0.03 *

F 412

(jacks excluded) M 433 0.51 1:0.96 0.34 0.56 NS 0.59 NS

F 409

113-62-005 Eagle River M 25 0.49 1:1.04 0.01 0.92 NS 1 NS

F 26

113-73-003 Ford Arm Lakec M 1,224 0.54 1:0.85 7.24 0.007 ** 0.007 **

F 1,043

(jacks excluded) M 995 0.49 1:1.04 0 0.49 NS 0.51 NS

F 1,039

115-32-032 Chilkat Lake M 282 0.51 1:0.96 0.04 0.83 NS 0.86 NS

(1987 only) F 275

115-33-020 Chilkoot Lake M 358 0.49 1:1.04 0.25 0.62 NS 0.64 NS

F 377

a Male portion of ratio standardized to 1.

b * = 0.05 > P > 0.01; ** = 0.01 > P < 0.001; *** = 0.001 > P; and NS = not statistically significant.

c Jacks are counted thoroughly.
favor of females. Both the Nahlin and Hackett River stocks had sex ratios skewed in

favor of males, and for the Nahlin River the skew was significant, and jacks were rare

(table 10). In contrast, in other samples that included all age classes and in which

significant deviations from a 1:1 sex ratio were found, removal of jacks yielded sex

ratios that did not differ from 1:1.

The proportion of jacks in different stocks ranged widely, with lake stocks generally

having greater jack proportions than other watershed types (see footnote 3), but jacks

are not thoroughly counted in most locations. In the few systems studied, the 

frequency of jacks is usually very low (less than 1 percent), but jacks comprised an

average of nearly 30 percent (SE = 0.79 percent) of the total annual run at Auke Lake 

from 1971 through 1988.8

42

Figure 14—Estimated rate of survival until return of coho salmon stocks by life

history stage and habitat: (A) estimates for rearing juveniles, and (B) estimates

for smolts. Plotted values are means of estimates for all years. Bars give standard errors of these means. The Nahlin River and Tatsamenie Lake stocks are

in interior habitats. No estimates of smolt survival from river stocks were available.

8 Taylor, S.G. 1989. Life-history characteristics of coho salmon,

Oncorhynchus kisutch, in the Auke Creek system, southeastern

Alaska. Unpublished manuscript-53. [Pages unknown]. On file

with: Pacific Northwest Research Station, Forestry Sciences

Laboratory, 2770 Sherwood Lane, Juneau, AK 99801.
Juvenile-to-adult survival—Juvenile survival was lowest for river stocks, because 

of the very low value for the Nahlin River (fig. 14A). The two interior stocks (Nahlin

River and Tatsamenie Lake) had lower juvenile survival rates than all coastal stocks

(table 11). Smolt survival tended to be lower in stream stocks than in lake stocks (fig.

14B).

43

Table 11—Estimates of coho salmon survival and exploitation rates

Stream Mean survival ratea

Mean

Year exploitation

Number Name tagged Juvenile Smolt ratea Source

--------------Percent--------------

101-29-006 Vallenar Creek 1988 5.0 Elliott and Sterritt 1990

101-30-075 Hugh Smith Lake 1980-1988 8.3 (2) 10.4 (8) 62.1 (8) Elliott and Sterritt 1990, Shaul

1990, Shaul and Koerner 1988, 

Shaul and others 1991

103-15-027 Klakas Lake 3.3 (2) 72.7 (2) Elliott and Sterritt 1990, Shaul 

and Koerner 1988, Shaul and 

others 1991

103-80-031 Warm Chuck Lake 4.3 (3) 37.7 (3) Shaul and others 1991

106-41-010 Salmon Bay Lake 57.3 (1) Shaul and Koerner 1988

111-32-066 Yehring Creek 5.3 (1) 11.3 (2) 81.5 (5) Elliott and Sterritt 1990, 1991; 

Gray and others 1978; Shaul 

1990

111-32-203 Wilms Creek 6.5 (1) Elliott and Sterritt 1990

111-32-254 Tatsamenie River 2.5 (3) 73.7 (2) Elliott and others 1989; Shaul 

1989, 1990

111-32-270 Nahlin River 1.5 (1) 57.1 (1) Shaul 1989

111-33-034 Speel Lake 5.6 (5) 55.9 (5) Josephson 1985, Shaul 1989, 

Shaul and others 1991

111-50-042 Auke Lake 16.5 (8) 42.8 (12) Elliott and others 1989; Elliott 

and Sterritt 1990, 1991; Shaul 

and others 1987; Shaul and 

others 1991

113-22-008 Politofski Lake 3.5 (2) 30.6 (2) Shaul and others 1991

113-41-032 Salmon Lake 1983-1989 9.1 (7) 52.6 (7) Elliott and others 1989; Schmidt 

1985, 1986, 1987, 1988, 1990; 

Schmidt and DerHovanisian 

1991

113-41-043 Redoubt Lake 1987 9.1 (1) 43.0 (1) Elliott and others 1989

113-62-005 Eagle River 1988-1989 3.7 (2) 54.4 (2) Schmidt 1990, Schmidt and 

DerHovanisian 1991

113-73-003 Ford Arm Lake 1980-1986 8.9 (6) 51.4 (7) Shaul 1990, Shaul and Koerner 

1988, Shaul and others 1991

115-20-010 Berners River 1974, 1980- 4.9 (7) 76.5 (8) Gray and others 1978, Shaul 

1987 Koerner 1988, Shaul 1990

115-32-032 Chilkat Lake 8.5 (3) 80.2 (1) Shaul and others 1986, Shaul 

and others 1991

115-32-032 Chilkat River 8.9 (1) Gray and others 1978

115-33-020 Chilkoot Lake 7.0 (1) 85.0 (3) Elliott and Kuntz 1988, Shaul 

and others 1991

a Number in parentheses is number of sample years.
Hugh Smith Lake, Salmon Lake, and Berners River stocks all showed nonsignificant,

negative temporal trends in survival from 1980 to 1989 (Hugh Smith Lake, b = -0.42,

P = 0.30 NS; Salmon Lake, b = - 0.55, P = 0.20 NS; Berners River, b = - 0.28, 

P = 0.50 NS). Auke Lake showed an increasing trend (b = 0.58, P = 0.10 NS). Only

for these four stocks were there enough annual records to allow evaluation of longitudinal trends in survivorship.

Exploitation rates—Exploitation rates did not differ consistently among watershed

types (fig. 15), but watershed types were less likely to affect exploitation rates than

were geographic location and migratory pattern. Exploitation rates on coho stocks

from islands were significantly lower than on mainland and interior stocks (KruskalWallis, P = 0.04). Stocks in the Lynn Canal, stocks in the Taku region with normal run

timing (except Auke Lake), and stocks in extreme southern southeast Alaska had the

highest exploitation rates. Stocks on the outer coast generally had the lowest exploitation rates. There was no significant correlation between exploitation rate and juvenile-to-adult survival.

From 1983 to 1989, exploitation rates increased significantly (R2

= 0.76, b =0.87, 

P = 0.01) for the Salmon Lake stock. Significant trends in exploitation rates were not

observed for the Hugh Smith Lake, Auke Lake, Ford Arm Lake, and Berners River

stocks.

The following stocks were discussed briefly in reports or were mentioned in discussions with fisheries biologists as having distinctive biological characteristics. These

stocks are mentioned here to call attention to their potentially distinctive characteristics and to promote further research. The Hasselborg River coho salmon rear in a

salt lake rather than freshwater habitats and apparently attain high growth rates. Use

of estuarine habitats by juveniles has also been reported for Ford Arm Lake and

Kadake Creek (Schmidt 1986, Shaul and others 1986). In the latter two cases, large

44

Figure 15—Estimated exploitation rates for coho salmon stocks by habitat.

Plotted values are means of estimates for all years. Bars give standard

errors of these means.

Anecdotal Reports
juveniles were caught moving upstream into fresh water in the fall, and these juveniles showed signs that they had been in salt water: they were sensitive to handling

and lost scales easily (see footnote 6). Lucky Cove, south of Ketchikan (see footnote

3), Reflection Lake on the upper Cleveland Peninsula,9 Hamilton Creek south of Kake

(see footnote 6), and Ward Creek on west Admiralty Island (see footnote 3) are 

considered to have early run timing and partial migration barriers. Weir counts for the

Karta River suggest that an early run of coho begins to enter this system in late June.

The run continues through September. Early and prolonged migration timing, 

combined with the presence of two lakes and a partial migration barrier in this 

system, suggest two separate stocks may be present (see footnote 3).

Patterns of variation in biological variables were generally hard to discern with a high

level of confidence. Variation in the data resulted from natural variation, differences

in methods of collection, and small, often poorly distributed samples, which either

precluded statistical analysis or contributed to considerable loss of power for statistical tests. A few trends nevertheless warrant further consideration. The weakness of

the database clearly emphasizes the need for more rigorous and specific studies on

the status and ecology of coho salmon stocks.

One of the clearest habitat-related patterns to emerge was the distinction between

interior and coastal coho salmon stocks by age structure, sex ratio, and fry-to-juvenile

survival. Studies of coho salmon stocks in British Columbia have established several

heritable morphologic, physiological, and behavioral differences between interior and

coastal stocks (Rosenau and McPhail 1987; Taylor and McPhail 1985a, 1985b,

1985c; see also McGeer and others 1991). Similar patterns for these biological characteristics may occur in southeast Alaska stocks. Interior spawning stocks that pass

through southeast Alaska represent important components of regional coho salmon

diversity.

Body length—Fry that were rearing in streams tended to be smaller than fry from

other watershed types, but no differences were apparent for other age classes of

juveniles. Swain and Holtby (1989) found no differences in body length in their comparison of lake- and tributary-stream-rearing coho in British Columbia. These authors

did find, however, morphological differences in body depth, fin coloration and placement, and aggressive behavior among coho from different watersheds. Heritable 

differences in body depth, head length, and fin size also have been found between

juveniles rearing in interior versus coastal streams in British Columbia (Taylor and

McPhail 1985b), but standard length was not an important variable in the discriminant

function analysis derived in this study. Similar differences may be found among

southeast Alaska stocks, because juveniles of these stocks commonly spend at least

1 more year in fresh water than do British Columbia populations. The extended period in fresh water might emphasize morphological differences among juveniles reared

in different watershed types.

45

Discussion

Evaluation of Results

9 Personal communication. 1996. C. Denton, fisheries biologist,

Alaska Department of Fish and Game, 2030 Sea Level Drive,

Suite 215, Ketchikan, AK 99901.
46

The size of coho smolts is considered relatively consistent throughout the range of

the species (Sandercock 1991). We found, however, an apparent trend for stream

smolts to be smaller than smolts from rivers and lakes and that the difference in body

length between watershed types tended to increase with increasing smolt age. This

pattern suggested that stream-rearing coho typically emigrate soon after reaching the

length threshold for smolting. Slow growth rates of stream-rearing coho also may

contribute to reducing the proportion of jacks produced in this watershed type,

because smolt size is positively correlated with the rate of jack return (Bilton and 

others 1982, Iwamoto and others 1984). Across all watersheds, larger coho salmon

smolts tended to emigrate later in the spring.

Mortality rates of juvenile coho salmon in different watershed types may be more

important than growth rates in determining duration of freshwater residence (see footnote 3). Differences in habitat stability and productivity patterns may influence tradeoffs between growth and mortality rates for rearing coho among rearing habitats.

Mortality rates are likely to be higher in streams subject to increased variation in environmental variables, such as temperature and flow regimes, than in systems offering

refuge in lakes that buffer environmental fluctuations. Higher freshwater survival in

lake-containing systems may favor individuals that stay in the freshwater environment

longer and migrate to sea at a larger size and thus survive better when they reach

salt water (Holtby and others 1990). 

Female coho salmon tend to be larger than males. Female body size is positively

related to fecundity and competitive ability, but these characteristics do not necessarily confer enhanced reproductive success in all situations (Fleming and Gross 1989;

Holtby and Healey 1986, 1990; van den Berghe and Gross 1989). Selective harvest

of large males could contribute to the observed size differences. The significant 

difference between the body sizes of age x.1 males and females may reflect a weakly

bimodal distribution of male body sizes (see footnote 3). Most age x.1 male coho

salmon in escapements have a size distribution similar to that of females, but a small

proportion of age x.1 males tend to be smaller than all females, thus reducing the

male mean body size. The causes and consequences of small size in some age x.1

males are unknown. 

Increasing freshwater age was associated with greater body size in females but not

in males. This result may reflect the tendency for the largest male smolts, typically

the oldest, to return as jacks. Female fecundity increases greatly with increasing

body size, but the same relation may not hold for males; in some situations small

males or jacks can have high reproductive success (Holtby and Healey 1986, 1990).

Males may forage in ways that reduce their risk of mortality rather than maximize

their rate of growth, resulting in a size-at-age distribution that is skewed to smaller

sizes relative to females (Holtby and Healey 1990) .

Although Wood (1992) discusses a decline in body weight for coho salmon from 1983

to 1987 in troll, seine, gill-net, and Canadian inriver fisheries, we found no significant

long-term temporal trends in body length for fish sampled from escapements for the

eight stocks tested (table 4). 
47

Variance-component analysis indicated that about 90 percent of total variation in adult

body length was found among individuals within stocks, and that among-stock variation made a negligible contribution to overall variability. This result is surprising given

the wide range of watershed types used by stocks included in this analysis. No

stocks with particularly early or late run timing, however, could be included in this

analysis. 

The small body size of the Pavlof Lake stock is distinctive among studied stocks and

reflects the positive relation between body size and run timing for southeast Alaska

stocks. This stock returns to fresh water in July and August rather than in fall. The

smaller body size of summer-run stocks may be the result of the loss of 2 additional

months in the ocean. Growth rates in the final months of ocean existence are

extremely rapid, up to a 10-percent increase in body mass per week in some stocks

(Gray and others 1981; see footnote 3). The positive association between body

length and mean migration date supports this interpretation. Small body size per se

may not be favored in these stocks, but rather may be a contingent result of an early

run, which is advantageous (see “Timing,” below).

Timing—Three stocks (Pavlof Lake, Salt Chuck-George Inlet, Plotnikof Lake) have

substantial migration barriers during low flow (see footnotes 3 and 6) and have early

run timing. Early run timing might be favored in these stocks to take advantage of

flow rates that facilitate passage by the barriers (see Gray and Marriott 1986 for 

discussion of Plotnikof Lake). A similar situation may occur in the Nahlin and

Dudidontu River stocks. Both stocks return and spawn early in the upper Taku River

drainage, above difficult passages in the Inklin River (see footnote 6). In addition to

migration barriers, these interior stocks also may be responding to the relatively cold

thermal regimes of their spawning streams. The Nahlin and Dudidontu drainages do

not contain lakes that could serve as thermal buffers. Early spawning dates may be

required to enable eggs to accumulate the thermal units necessary for development

and hatching (Tang and others 1987; see footnote 3).

Because early-run stocks may depend on critical flow conditions to circumvent difficult obstacles, any disruptions to watersheds that alter hydrologic characteristics of

these streams could have a detrimental effect on these stocks. Run-timing differences can be effective reproductive isolating mechanisms. Therefore, coho salmon

stocks with early return timing could show unusual patterns of genetic variation. Not

only are these stocks valuable as a potential source of genetic variation, but they also

have important fisheries values. These stocks have been favored for the development of hatchery brood stocks (see footnote 9) because early returning coho, both

hatchery and wild, provide important sport fishing opportunities between the end of 

chinook runs and the onset of typical coho runs in the autumn. Enhancement 

projects that circumvent existing barriers may compromise the integrity of early-run

stocks.

Adults of some coho salmon stocks that inhabit systems containing large lakes are

summer-run fish that return early and hold in fresh water for 1 to 4 months before

spawning (e.g., Hugh Smith Lake; see footnote 3). This behavioral characteristic also

could serve to isolate populations reproductively, if they spawn at a different time than

later returning fish. Observations from Margaret Lake populations show that summerrun fish tend to spawn earlier than fall-run fish, but individuals from both runs spawn
together.10 The late-spawning strategy offers some clear advantages in terms of egg

and alevin survival because late fall and winter freshets that cause bedload movement or scouring of the substrate can be avoided. However, the relative probabilities

of adult mortality in fresh versus salt water are not known. Early movement into fresh

water also implies foregone opportunity for growth. Finally, this strategy is probably

constrained to systems with relatively high water temperatures that will produce rapid

development of eggs once they are spawned. Further investigation of the distribution

of this behavioral strategy, as well as its ecological correlates and evolutionary consequences, would be valuable. 

Demography, declining stocks—No overall geographic pattern was present among

the declining stocks, but three stocks were located on Mitkof Island, and the other

two stocks on Mitkof Island that had an adequate number of escapement records for

analysis also showed nearly significant declines in escapement. Mitkof Island stocks

may reflect the synergistic negative effects of habitat degradation due to logging and

road building, overexploitation associated with Crystal Lake hatchery operations, and

an active local fishing community. Indian and Bear Harbor Creeks and Port Banks

(Plotnikof Lake) are in pristine areas. Data quality was only fair for all these stocks

owing to inconsistencies in the frequency, timing, and methods used to survey

escapements.

Six of seven declining stocks are in stream systems and, with the exception of the

Indian Creek stock, have relatively small escapements (mean escapement counts

less than 250 fish). These small stream stocks are considered most susceptible 

to population declines (Elliott and Kuntz 1988). Small escapements caused by poor

ocean survival or overharvest, or both, combined with the relative instability of stream

habitats, which can cause high rates of egg or juvenile mortality, all contribute to the

heightened potential for declines in small stream stocks. Estimates of juvenile production per spawner in two coastal stream stocks are highly variable (Schmidt and

DerHovanisian 1991).

Age structure—The age structure of lake stocks tends to include more freshwater

age classes and more individuals in older age classes than river or stream stocks

(table 8). Lake-containing systems may support a mixture of different genetic morphs

with different growth patterns. Studies of juvenile coho salmon in lakes and streams

in British Columbia have revealed differences in morphology and behavior between

juveniles that rear in stream versus lake habitats (Swain and Holtby 1989). These

differences were found to persist when juveniles of both types were raised in a common laboratory environment, which suggests a genetic basis to these traits.

Phenotypic plasticity could not be conclusively ruled out based on the experiments

conducted. Determining the cause of variation in biological characteristics of coho

juveniles in different habitats is important for understanding the dynamics of these

populations (Swain and Holtby 1989). Adaptive differences may enhance productivity

by reducing intraspecific competition (Swain and Holtby 1989). If genetic differentiation occurs among coho salmon stocks spawning in different segments of the same

drainage, optimal productivity from that drainage may depend on maintaining the

existing polymorphism. 

48

10 Bryant, M.D.; Frenette, B.J. Manuscript in preparation.

Colonization of the Margaret Lake watershed by anadromous

salmonids. Available from: M.D. Bryant, Pacific Northwest

Research Station, Forestry Sciences Laboratory, 2770 Sherwood

Lane, Juneau, AK 99801.
49

The relatively high proportion of cases (62.5 percent) in which MFWA declined

between smolt and adult samples from the same cohort was unexpected, in view of

the expected positive relation among smolt age, size, and ocean survival. We propose several hypotheses to explain this unexpected pattern. (1) In watersheds with

both lake (rapid juvenile growth) and stream (slow growth) habitats, stream-reared

smolts may be both older and in less robust condition than lake-reared smolts, and

enhanced survival of the lake-reared smolts could explain a system-wide decline in

MFWA from smolts to adults. (2) Older and larger smolts may be more likely to

return as jacks (Bilton and others 1984, Schmidt 1987), and returning jacks are

undersampled or not sampled at most locations. At Auke Lake, where jacks are

accurately enumerated at a weir, a nearly significant correlation exists between the

difference in MFWA from smolt to adult and the proportion of jacks that occur in the

escapement for a given year (r = 0.79, P = 0.06). (3) Errors in aging either adult or

juvenile coho by scales11 could produce spurious patterns. (4) Older, larger smolts

may, in fact, experience reduced ocean survival (Holtby and Healey 1986). (5)

Commercial and sport fishing could selectively remove the largest and oldest adults.

Experiments are underway to test these alternative hypotheses.

Increases in MFWA of adults through time is difficult to explain, given that smolt

MFWA did not show a parallel pattern in all systems. Possibly ocean conditions are

changing to increasingly favor the survival of older smolts. The trend of increasing

adult MFWA also has been detected in harvest from all fisheries (Wood 1992; Wood 

and Van Alen 1987, 1990). Where smolt MFWA also is increasing, cold winter temperatures are probably responsible for slow growth that results in a longer freshwater

rearing period (Wood and Van Alen 1987). 

Sex ratio—The sex ratio of stocks in interior rivers is unusual, in that the Nahlin and

Hackett River samples are skewed in favor of males and jacks are virtually absent.

Coastal stocks show either a female-biased sex ratio or a high incidence of jacks that

result in a male-biased sex ratio. The latter form of sex-ratio bias could result from

very few jacks being taken in commercial fisheries (see Wood and Van Alen 1987). 

It is also possible that the apparent difference between interior and coastal stocks is

actually the result of errors in determining the sex of returning coho (see footnote 3).

It is relatively difficult to accurately determine the sex of sexually immature fish returning to coastal systems, compared to fish handled at weirs near interior spawning 

tributaries (see footnote 3).

Survival and exploitation rates—The low juvenile-to-adult survival rates of interior

stocks compared to coastal stocks may reflect differences in the fish communities

present in interior versus coastal systems (Shaul 1990). Juvenile coho rearing in

interior systems face increased predation pressure from abundant resident populations of northern pike (Esox lucius), burbot (Lota lota), and lake (Salvelinus namaycush) and rainbow trout (O. mykiss) as well as competition for rearing habitat and

food resources from juvenile chinook salmon, Dolly Varden (S. malma), rainbow trout,

grayling (Thymallus articus), and lake chub (Couesius plumbeus) (Shaul 1988; see

footnote 3). Increased predation risk and competition may exclude many coho juveniles from the best foraging habitats.

11 Personal communication. 1996. S.G. Taylor, fishery biologist,

National Marine Fisheries Service, Auke Bay Laboratory, 11305

Glacier Highway, Juneau, AK 99801.
50

The current ADF&G guideline for the maximum long-term average exploitation rate

for coho salmon stocks is 70 percent (Shaul 1994). Hugh Smith Lake, the indicator

stock for southern inside waters, and some Lynn Canal stocks are consistently

exploited at rates near this target (table 11). In general, stocks that pass through the

most fisheries during their spawning migrations incur the highest exploitation rates

(Shaul and others 1991). Small stocks are particularly vulnerable to high exploitation

rates (Hilborn 1985), which may or may not be sustainable (Elliott and Kuntz 1988).

Four topics regarding the evolution and ecology of coho salmon populations are 

discussed: (1) population genetic structure and the effects of straying rates of adults

and movements of juveniles; (2) community ecology of rearing salmonids, especially

the interspecific interactions of juvenile coho salmon with juveniles of other salmonid

species; (3) body size, sex ratio, and hypotheses of coho salmon life history evolution; and (4) the possible evolutionary and ecological consequences of landslides for

salmonid populations and communities.

Population genetic structure—In general, genetic divergence among populations is

inhibited by migration and consequent gene flow. If, however, a population is sufficiently large and selection favoring an allele different from that carried by migrants is

strong and stable, the homogenizing effects of gene flow can be counteracted, and

genetic differentiation among populations can occur. Very little allozyme variation has

been detected in coho salmon populations (Bartley and others 1992, Wehrhahn and

Powell 1987), and coho show the lowest mean heterozygosity of the five major

Pacific salmon species (Allendorf and Utter 1979). Coho salmon from southern

British Columbia were much less polymorphic than Oregon coho, but this analysis

(Wehrhahn and Powell 1987) omitted the highly polymorphic transferrin locus.

Wehrhahn and Powell hypothesized that this difference is due to a severe population

bottleneck for British Columbia coho salmon during postglacial recolonization. The

estimated number of migrants for the wild stocks studied was about six per spawning

population (Wehrhahn and Powell 1987). This estimate is significant, because it suggests that a spawning population of 1,000 individuals could diverge if their local allele

confers a selective advantage in heterozygotes of 0.005. Wehrhahn and Powell

(1987) conclude that coho spawning populations of greater than 1,000 individuals are

evolutionarily significant even if they exhibit no obviously unique characters, because

these populations have increased potential for diversification.

Coho salmon straying rates are thought to be low in undisturbed populations (Labelle

1992, reviewed in Sandercock 1991). Strays typically accounted for less than 1 percent of returning adults in 14 stocks studied on Vancouver Island (Labelle 1992). The

mean straying distance reported by Labelle (1992) was 15.7 km, and more than 50

percent of strays originated in streams within 7 km. Genetic factors, exposure to 

foreign water sources during rearing, flow rates, and interactions among these factors

were important predictors of straying rates. In one system, strays accounted for over

40 percent of the escapement, probably due to enhancement procedures in an adjacent river (Labelle 1992). Four of the stocks had escapements in excess of 1,000

individuals, and the estimated straying rate for these stocks was 1.3 percent.

Although the population genetic structure of coho salmon in southeast Alaska is

unknown, it may differ substantially from that described for other regions. We present

two reasons why greater genetic diversity may occur in southeast Alaska coho populations. (1) Coho salmon in southeast Alaska rear for a longer period in fresh water.

Conceptual Issues
51

This may enhance the accuracy of homing and might reduce straying rates.

Reduced straying (gene flow) increases the potential for evolutionary diversification.

Furthermore, many populations in southeast Alaska have escapements in excess of

1,000 individuals and are pure wild stocks that have not been subject to enhancement or water diversions. (2) The source populations that colonized southeast

Alaska after the last ice age may have been different or more diverse than those that

colonized more southerly regions. Gharrett and others (1987) believe chinook

salmon recolonized southeast Alaska from both northern refugia in the Yukon River

basin and the Pacific Northwest. If coho salmon followed a similar pattern, greater

genetic diversity among the founders may contribute to higher current levels of variability. 

On the other hand, there are two reasons why diversity may be lower in stocks in

southeast Alaska. (1) The landscape in southeast Alaska is younger than areas to

the south, and glacial retreat is continuing to open new habitats. This young landscape may favor straying as an alternative life history tactic (Quinn 1984). Furthermore, in this young landscape, sufficient time may not have passed since colonization to permit genetic divergence among stocks. (2) Several cases of unusual

juvenile movements have been documented in southeast Alaska. One juvenile

female, tagged in the lower Berners River, was captured at Auke Lake, after movement across about 50 km of salt water (see footnote 3). Juvenile coho tagged in

Wilms Creek, across the Canadian boundary in the Taku River drainage, have been

captured in smolt traps on Yehring Creek nearly 20 km distant (Elliott and Sterritt

1990). Juvenile coho also have been found in streams having no apparent spawning

habitat. Whether there are any population genetic effects of movements by nomadic

juveniles is unknown. 

Community ecology—Competitive and predatory interactions among coho and other

salmonids, including resident trout and char, all having prolonged freshwater rearing

periods, are complex. Habitat displacement of coho salmon juveniles may occur in

the presence of abundant chinook salmon in the Nahlin River (see footnote 3). In

addition, because juvenile coho in southeast Alaska use lakes as rearing habitat,

competitive and predatory interactions can occur with sockeye salmon fry even

though some habitat partitioning occurs. They may compete for food resources

where they overlap, and coho salmon that are rearing in lakes may prey extensively

on recently emerged sockeye (Ruggerone and Rogers 1992). Understanding predator-prey relations among rearing salmonids could help to explain productivity patterns;

for example, sockeye production per spawner is higher in Chilkoot Lake than in

Chilkat Lake, perhaps because the clearer waters of Chilkat Lake facilitate predation

by coho salmon and other predators. Chilkat Lake coho salmon juveniles were the

largest juveniles of all systems for which data were available, implying exploitation of

a rich food resource. Chilkat Lake sockeye salmon are known, furthermore, to exhibit

very prolonged spawning and emergence periods, which could serve to make 

emerg ing sockeye salmon available to predators for a substantial portion of their

rearing period.

Interactions of coho salmon with pink and chum salmon, which do not have extended

rearing periods, also may be important. The observed correlation between the

strength of coho and pink salmon returns to southeast Alaska (Gaudet 1989) may 

be explained, in part, by coho smolts preying on emigrating pink salmon fry; coho

salmon selectively prey on juvenile pink salmon (Hargreaves and LeBrasseur 1985).
52

If feeding on abundant pink salmon fry results in enhanced early ocean growth for

coho smolts, greater ocean survival could be expected (Holtby and others 1990). 

A strong positive relation between biomass of pink salmon carcasses and recruitper-spawner ratios of coho salmon was reported in the Skagit River, possibly

because mass spawning by pink salmon produced more invertebrate drift, and 

juvenile coho can feed directly on eggs and adult carcasses of pink salmon (Michael

1995). These enhanced feeding opportunities could lead to increased coho salmon

smolt size and associated increases in marine survival. 

Life history evolution—Several studies have found that large body size confers a

significant reproductive advantage to female coho, chinook, and sockeye salmon

(Fleming and Gross 1989; Gross 1984, 1985; Healey and Heard 1984; van den

Berghe 1984; van den Berghe and Gross 1984). Despite the apparent advantages of

large body size, wide variation in female sizes occurs both within and among coho

salmon populations. Broad variation may represent an evolutionarily stable strategy,

with several interacting environmental factors and frequency-dependent selection

causing females of different sizes to achieve equal fitness (Holtby and Healey 1986).

Elaborating on this hypothesis, van den Berghe and Gross (1989) and Fleming and

Gross (1989) argue that breeding competition among female coho salmon can select

for increased body size, and that the effects of this selection may be tempered by

abiotic selection factors such as the relative arduousness of spawning migration.

They claim that differences in morphology reflect heritable responses to varied and

fluctuating selection pressures.

Landslides and salmonid evolutionary and community ecology—The abundance

and species composition of juvenile salmonids in the Dudidontu River differed profoundly from the Nahlin River (Shaul 1988), although both rivers are interior tributaries of the Taku River. In the Dudidontu River, juvenile anadromous salmonids were

less abundant, and resident species, particularly Dolly Varden, were more numerous.

Frequent blockages along the Dudidontu may favor resident life history strategies

over anadromous strategies for some species (Shaul 1988). Intermittent spawning

by anadromous salmonids resulting from frequent blockages and flow restrictions

might temporarily release juveniles of resident salmonids from competition and perhaps allow them to colonize a broad range of rearing habitats. Although coho salmon

are generally successful competitors, predation by dense populations of adult residents could delay successful recolonization by anadromous populations.

Although current data indicate that coho salmon stocks in southeast Alaska generally

have stable abundance trends, several risk factors raise concerns about the future

status of coho salmon in the region. The following list is not comprehensive but outlines what we consider to be the most significant risk factors for southeast Alaska

coho salmon stocks. 

1. A lack of stock-specific information is both a risk factor in itself and increases the

problems generated by other risk factors. Stock-specific information is not available

for over 90 percent of the coho salmon stocks in the region. Existing evidence indicates considerable biological variation among coho populations, but an adequate

assessment of biological characteristics and stock status cannot be achieved by

extrapolating from a historical sample of only 2 percent of all populations, especially

because that sample is not drawn proportionately from the range of freshwater habitat types used by coho salmon. 

Risk Factors
53

Current management of coho stocks in southeast Alaska is based on data collected

primarily from lake-containing systems, but other habitats account for a significant

proportion of the coho salmon harvested in southeast Alaska (Elliott and Kuntz 1988).

Because lakes tend to buffer fluctuations in environmental conditions, production of

coho salmon from lakes tends to be more stable than production from other, more

dynamic, habitats. Management decisions based on lake production may fail to

account for greater variation in coho salmon production in streams and rivers than in

systems with lakes; therefore, the potential for overexploitation of stream and river

stocks is higher. Small streams with small populations are the most sensitive to the

threat of overexploitation (Elliott and Kuntz 1988, Hilborn 1985) and thus may be 

useful as indicators for management strategies. Insufficient information was available

to determine if the range of variation in ocean survival and resulting run strength of

indicator stocks are representative of stocks in other habitat types, such as streams.

If stream stocks have greater variation in ocean survival, as they do in freshwater 

survival, management strategies based on the run strength of lake-inhabiting indicator stocks could expose stream stocks to unsustainable exploitation levels. Most data

on the population dynamics of coho salmon stocks have been collected during a 

period of exceptionally high marine survival. During periods when marine survival is

near normal, coho salmon stocks may not be capable of sustaining high exploitation

rates without experiencing declines in abundance. 

Patterns of coho salmon migration in southeast Alaska complicate management

(Shaul and others 1986). Conservation of weak stocks by time and area closures

may not be an option for most stocks because they pass through numerous fisheries

over an extended period en route to their spawning streams. The ongoing trend of

greater proportions of the total coho salmon harvest coming from early-season,

mixed-stock troll fisheries exacerbates this situation. Interior spawning stocks are of

special concern in this regard. In particular, the sustainability of the extremely high

exploitation rates estimated for Hugh Smith Lake (southern inside area) in recent

years and for Lynn Canal stocks is questionable. Long-term declines have occurred

in coho salmon stocks from Georgia Strait, British Columbia, that had exploitation

rates ranging from 75 to 80 percent (Canada Department of Fish and Oceans 1990,

cited in Shaul 1994). Caution is advisable in view of limitations on management 

prescriptions for rescuing declining stocks.

Fisheries for other salmonid species often harvest a substantial incidental catch of

coho salmon. Run timing thus becomes an important biological trait influencing 

vulnerability. Declines in the early-run coho salmon stocks in the Skeena River may

be caused by overharvest of coho salmon by the fishery directed at a large sockeye

run (Sprout and Kadowaki 1987). A similar threat faces early-run Taku drainage

stocks, such as those found in the Nahlin River. Coho salmon from Lynn Canal

stocks that have relatively late runs also are harvested in a fishery directed at large,

late chum salmon runs to the Chilkat River. 
2. Habitat degradation continues to be a major threat. Over the long term, a growing

human population and increasing global demands for natural resources will lead to

increasing habitat destruction or disruption. Degradation of habitat quality over large

areas of the Pacific Northwest has contributed to the decline in abundance of coho

salmon in that region (e.g., Nehlsen and others 1991). In the Pacific Northwest, habitat degradation initially occurred in scattered locations across the landscape (Frissell

1993), and observable effects of the problem were delayed. Similar events may be

occurring in southeast Alaska; for example, the loss of wood and the subsequent

effects on stream habitat continue to be observed in watersheds logged more than 

30 years ago (Bryant 1980; 1985a).

The effects of land uses on salmonid habitat is reviewed in Meehan (1991); problems

arise from changes in stream structure, sediment production, and thermal regimes.

Vulnerability to changes in thermal regimes probably differs with watershed type.

Many coho salmon populations in southeast Alaska inhabit stream watersheds

unbuffered by lakes, and they often use tributary streams for spawning and rearing

(Gray and Marriott 1986). The thermal regimes of small stream habitats may be 

particularly sensitive to disruption, and coho salmon populations, like those of other

species of Pacific salmon, show population specific patterns of variation in incubation

rate, growth, and development that appear to be adaptations to local thermal regimes

(Beacham and Murray 1990, Konecki and others 1995). Furthermore, small-stream

systems offer fewer refuges for residents when habitats are disrupted. 

3. Artificial enhancement of salmon stocks through hatcheries has the potential to

adversely affect natural runs via overexploitation (artificially raising the number of 

harvestable fish, followed by increased harvests that take both hatchery and natural

runs) and genetic introgression from hatchery stock to wild runs. These concerns are

amplified by the geographic location of hatcheries and release sites; for example, the

Neets Bay and Whitman Lake hatcheries are located along the migration pathway of

Behm Canal stocks. Currently, coho salmon stocks in southeast Alaska do not

appear to be experiencing the potentially deleterious effects of artificial enhancement

on a broad scale. Were coho salmon production increased at several hatcheries, the

situation could change, however. 

Coho salmon can spawn and rear in a wide range of habitats, and coho are capable

of passing obstacles that are barriers to the migration of other anadromous salmon.

Consequently, an estimated 2,300 coho salmon stocks are found throughout the

study region. Sampling for biological characteristics was limited to 48 (2.1 percent) 

of these stocks, and 129 stocks (5.6 percent) were represented by sufficient escapement survey data to permit regression analysis of abundance trends. The late run

timing of coho salmon and the logistical problems that accompany poor weather and

high stream flows generally diminished the quality of biological data and escapement

survey estimates for coho salmon in the region. The potential biases associated with

limited data also should be taken into account when evaluating the results presented

here. We compared stocks inhabiting 27 lake, 10 river, and 11 stream watersheds

and 5 interior and 43 coastal locations to look for patterns of variation among these

watershed types. The clearest watershed-related pattern to emerge was the distinction between interior and coastal coho salmon stocks: interior stocks had low

MFWAs, sex ratios skewed in favor of males with jacks virtually absent, and low survival rates compared to coastal stocks. Interior-spawning stocks that pass through

southeast Alaska represent important components of regional coho salmon diversity.

54

Conclusions
55

Smolts from streams tend to be smaller than smolts from lakes or rivers. Stocks rearing in lake watersheds had higher MFWAs and contained more age classes than

stocks found in other watershed types. Lake stocks also tended to have higher survival-to-return rates than river or stream stocks. Across all watersheds, adult females

were significantly larger than males, and female body size increased significantly with

increasing freshwater age. Nearly 90 percent of total variation in adult body size,

among six stocks analyzed, occurred among individuals within stocks. Small body

size, early run timing, and presence of a partial barrier to migration were associated

among several stocks in the region.

No biochemical, genetic, or scale pattern analysis data were available for separating

stock groups of coho salmon. Interior stocks, especially those in the upper Nahlin

and Hackett Rivers, that make long and arduous migrations and stocks that inhabit

systems with migration barriers were likely to show genetic divergence because of

reduced probability of gene flow and the presence of unusual selection pressures.

Interpretation of results of outlier analyses depends on whether sampled stocks are

considered representative of the range of variation present in the region. Nine stocks

had distinctive characteristics based on outlier analyses (see fig. 16 for approximate

locations). Relatively extensive data sets were available for the following stocks:

• Redoubt Lake—High MFWA differences between males and females (0.3 year,

based on 7 years of sampling and over 1,500 aged individuals).

• Tsiu River—Unusually large escapement magnitude (mean survey estimate

exceeds 22,000 across 26 years of sampling).

The following stocks show distinctive characteristics based on limited sampling.

These results should be considered preliminary.

• Salt Chuck, George Inlet—Early run timing based on escapement survey dates.

• Falls Lake—Early run timing based on mean dates at the weir.

• Pavlof Lake—Early run timing based on escapement survey dates and small body

size of age 1.1 and 2.1 females.

• Port Banks (Plotnikof Lake)—Early run timing based on escapement survey dates.

• Eagle River—High proportion of age 2.1 males in escapements. 

• Klukshu River—High proportions of age 1.1 males and females in escapements

and correspondingly low proportions of age 2.1 individuals.

• Tsiu River—Large MFWA differences between males and females.

• Tsiu-Tsivat River system—Large escapements.

Based on anecdotal reports the following stocks may have distinctive characteristics:

• Hasselborg River, Ford Arm Lake, Kadake Creek—Coho salmon rear in saltwater

rather than freshwater habitats and apparently attain high growth rates.

• Lucky Cove, Reflection Lake, Hamilton and Ward Creeks—Early run timing to 

systems with partial migration barriers.

• Karta River—Early and prolonged run timing; possibly two stocks present.
56

Figure 16—Approximate geographic locations in the study area of coho salmon stocks exhibiting distinctive

characteristics. Stocks 1 and 2 were sampled relatively thoroughly. Stocks 3 to 8 were represented by

limited samples (results are preliminary). Anecdotal reports suggested stocks 9 to 16 may have distinctive

characteristics, but few or no quantitative data were available for these stocks. Stocks that spawn in interior tributaries of the Taku River have low MFWAs, sex ratio bias favoring males with virtually no jacks present, and low survival rates compared to coastal stocks.
57

Figure 17—Approximate geographic locations in the study area of coho stocks with significantly declining

escapement trends.
Seven of 129 (5.4 percent) stocks evaluated showed significant declines (see fig. 17

for approximate locations). Six of seven declining stocks inhabit streams, and the

only declining lake stock (Plotnikof Lake) has distinctive run timing. In four cases, a

combination of suspected factors may be responsible for declines, and in three

cases, possible causative factors are unknown. No clear relation exists between

water quality and population status, but many stocks in impaired or suspected water

bodies have not been adequately surveyed to permit analysis of escapement trends,

or insufficient postimpact surveys have been conducted to detect an effect.

Escapement survey data for coho salmon were more unreliable for determining

trends in abundance than data for other species, thereby increasing the possibility

that significant declines may be either generated or hidden by inconsistent surveys.

Existing data suggested the wild coho salmon resource in the region is in stable 

condition. Lack of sufficient information is the most pervasive risk factor threatening

sustainable management of coho salmon stocks in the region. Additional risk factors

include habitat disruption of watersheds associated with natural resource extraction

and urbanization, and the potentially negative effects of increasing artificial enhancement on wild stocks. Wild coho salmon stocks have proven to be resilient in the face

of high levels of exploitation, when high-quality spawning and rearing habitat are

available. The effects of habitat degradation, artificial enhancement, and overexploitation are synergistic and can lead to rapid decline of productivity of wild stocks,

as they did in the Pacific Northwest.

D. Aho, J. Carol, J. Christner, F. Cole, J. Franzel, G. Killinger, R. Sainz, and 

V. Starostka provided helpful information regarding the interpretation of escapement

surveys and the history of enhancement projects. Statistical advice and technical

assistance were provided by D. Bachman, K. Frangos, and T. Max. The ADF&G documents that provided nearly all the biological data for this report were provided by 

G. Karcz Alexander, G. Gunstrom, M. Harris, S. McGhee, and K. Savikko. C. Casipit,

R. Dunlap, and V. Starostka supported the work in various and sometimes extraordinary ways. Incisive review of a previous draft by J.H. Clark greatly improved this

work, as did the input and advice of J. Seeb. S. Elliott, R. Josephson, and A.

Schmidt gave generously of their time and insights about coho salmon biology and

management. We appreciate the guidance provided by L. Talley and S. Johnson on

the ADF&G's Integrated Fishery Database and for retrieving indispensable information we requested from that database. We are especially grateful to L. Shaul for his

thoughtful and thorough review of a previous draft and for sharing his expertise on

coho salmon in southeast Alaska. 

Alaska Department of Environmental Conservation. 1992. Alaska water quality

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Alaska Department of Fish and Game, Habitat Division. 1994. Catalog of waters

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Southeast Region, Resource Management Region I. 195 p.

Allendorf, F.W.; Utter, F.M. 1979. Population genetics of fish. In: Hoar, W.; Randall,

D.; Brett, R., eds. Fish physiology. New York: Academic Press. Vol. 8.

58

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67

Stocks of chinook salmon (Oncorhynchus tshawytscha) that spawn in southeast

Alaska and adjoining areas of British Columbia and the Yukon Territory are valuable

biological, commercial, and recreational resources. Stock-specific information on various biological characteristics including body length, run timing, age structure, and

temporal trends in escapement was analyzed for geographic patterns and presence

of distinctive stocks. Stocks from the southern portion of the region have larger mean

body length, later run timing, and younger mean ages at maturation than northern

stocks. Stocks having distinctive biological characteristics include the Situk River

stock and nearby stocks from the Yakutat Forelands, the only ocean-type stocks in

the region, and the King Salmon River stock, which spawns in an island drainage.

Most stocks in the region have stable escapement trends, with 25 percent (15 stocks)

showing significant increases, and 5 percent (3 stocks) showing significant declines

from 1960 to 1993. Risk factors for chinook stocks in the region include habitat disruption from glacial advances, landslides, and human activities and potential overexploitation, especially of small stocks. Chinook stocks are well studied and monitored

compared to coho salmon.

Keywords: Chinook salmon, Oncorhynchus tshawytscha, southeast Alaska, age 

distribution, run timing, body size, intraspecific diversity, population status.

1 Janice K. Troyer coauthored this chapter. She was a biological

technician at the time this work was done, U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station,

2770 Sherwood Lane, Juneau, AK 99801.

Chinook Salmon 

(Oncorhynchus tshawytscha)

1

Abstract
Chinook salmon are distributed throughout southeast Alaska, from the Keta and

Marten Rivers in Misty Fjords National Monument to the Situk River on the Yakutat

Forelands. Most are found in large mainland river systems, but four stocks occur in

island systems: King Salmon River, Wheeler, and Greens Creeks on Admiralty Island,

and in Carroll Creek on Revillagigedo Island, where the chinook salmon are from an

introduced stock. Most stocks are found from the Stikine River south. Chinook

spawning populations range from less than 100 in many watersheds to more than

50,000 fish on the Taku River (McPherson and others 1996, 1997; Pahlke and

Bernard 1996). Most spawning populations in southeast Alaska consist of less than

1,000 individuals (based on recent escapement counts). Larger populations are

found in tributaries of large transboundary rivers, the Taku, Stikine, and Alsek Rivers.

Most juvenile chinook salmon in southeast Alaska rear in freshwater habitats for a

year or more after emergence before emigrating to sea (“stream-type” stocks). In

contrast, “ocean-type” juvenile chinook salmon emigrate from fresh water soon after

emergence or after a freshwater feeding period of 2 to 3 months. Ocean-type life 

history patterns are more common in chinook stocks of coastal rivers south of 56° N.

lat. (Taylor 1990). Stream-type chinook salmon also tend to have (1) more extensive

oceanic migrations than ocean-type chinook; (2) return migrations to natal spawning

streams that occur in spring and summer, several months before spawning, compared to the fall return timing of ocean-type chinook; and (3) the occasional occurrence of males that mature precociously without ever going to sea (Healey 1991).

Considerable variation exists, however, within these life history characteristics; for

example, the chinook salmon stock in the Situk River near Yakutat has ocean-type

juvenile emigration timing, but stream-type return and spawning timing2 (Johnson 

and others 1992b).

Most chinook salmon in southeast Alaska return to spawn after 3 or 4 years in the

ocean (i.e., x.3 or x.4). The proportion of jacks or males that mature at ages x.1 and

x.2 differs greatly among stocks, sometimes exceeding 50 percent of all males (e.g.,

Hard and others 1985). The typical size of age 1.3 and 1.4 spawners in southeast

Alaska is about 850 mm, mideye-to-fork length. Males usually outnumber females in

current spawning populations, in part owing to the number of jacks. Females generally mature at older ages. Most spawning occurs in clearwater tributaries of large,

glacial rivers. For most chinook populations in the region, peak spawning occurs

from the last week in July to late August. In general, stocks in southern southeast

Alaska spawn later than stocks in northern southeast Alaska. This trend reflects the

pattern found throughout the geographic range of chinook salmon in which spawning

occurs earlier at more northerly latitudes (Healey 1991).

In a review of the early life history of chinook salmon, Healey (1991) reports that eggs

hatch in 7 to 9 weeks and alevins overwinter in the spawning redds. Emergence

from the gravel occurs in spring, and fry attain fork lengths between 50 and 70 mm by

October. Chinook juveniles tend to rear in areas with faster current, such as channel

edges, including mainstem channels. The highest densities of rearing juveniles are

found in braided areas, especially near rootwads or other large woody debris. Fry

overwinter in close association with the stream substrate or dense cover. Fry resume

a more active existence in early spring, and develop into smolt by late spring. Smolt

typically emigrate from fresh water from early April to mid-June in most systems.

68

Introduction

Life History

2 Personal communication. 1996. P. Kissner, fisheries biologist

(retired), Alaska Department of Fish and Game, 802 3d Street,

Douglas, AK 99824.
Estuaries are important rearing areas for juvenile ocean-type chinook salmon (Levy

and Northcote 1982). Ocean-type juveniles often rear in estuaries for several months

(Healey 1991, Pearcy 1992), but stream-type juveniles in the Pacific Northwest typically spend a brief period near the estuary mouth before moving offshore (Healey

1991). Use of estuarine habitats by chinook salmon in southeast Alaska has not

been well investigated. Likewise, little is known about the early marine distribution 

of juvenile chinook salmon from southeast Alaska, largely because of their low abundance relative to other species (about 1 percent of total seine catches; Jaenicke and

Celewycz 1994).

Oceanic migration patterns of specific chinook salmon stocks are not well known

(Healey 1991). In southeast Alaska, data from coded-wire tagging indicate that some

chinook from southern southeast Alaska stocks (Chickamin and Unuk Rivers) as well

as fish from Chilkat and King Salmon Rivers in northern southeast Alaska remain in

near-shore waters for extended periods, possibly for the duration of their marine existence3 (Mecum and Kissner 1989, Pahlke and Mecum 1990). Most chinook salmon

from the Taku and Stikine River systems appear to move quickly through the nearshore waters and into the Gulf of Alaska (Hubartt and Kissner 1987). Migratory pathways of returning fish moving through inside waters can differ within drainages; for

example, two different migratory paths are followed by chinook salmon returning to

the Taku drainage. The pathway used by most fish is through Icy Strait, and then

south past Juneau to Taku Inlet. The second pathway, used by fewer fish, passes

around the southern tip of Baranof Island and proceeds north through Frederick

Sound and Stephens Passage to the Taku River (Kissner and Hubartt 1986).

Chinook salmon show latitudinal trends in biological characteristics (Healey 1991),

and chinook salmon in the southern portion of their range have life history differences

associated with freshwater migration distance. Based on these differences, we 

compared (1) northern and southern stock groups from the study region to look for

latitudinal patterns of variation in biological characteristics, and (2) coastal (outside)

and interior stocks to look for variation patterns associated with migration distance. 

Before the 1970s, chinook fisheries in the region were not closely managed (ADF&G

1992). The current phase of chinook salmon management began in the mid-1970s,

when most chinook stocks in the region were considered depressed relative to historical abundance levels (ADF&G 1981). The ADF&G imposed restrictions on terminal

and near-terminal gill-net fisheries for chinook salmon, closed coho salmon troll fisheries that intercepted large numbers of chinook salmon, and established size limits

on chinook salmon caught in sport fisheries (ADF&G 1992). In 1981, the ADF&G

began an expanded 15-year (three chinook life cycles) rebuilding program for all

transboundary river systems as well as for the Keta, Blossom, King Salmon, and

Situk Rivers (ADF&G 1992). An important component of this program was the establishment of regionwide catch ceilings for all gear types. These ceilings were largely

responsible for the relative consistency of commercial harvests of chinook salmon

during the last decade (fig. 18). The purpose of the rebuilding program was to achieve

higher spawning escapements by 1995. Escapement goals were established in 1981

and set at the historical escapement count. Insufficient data were available for spawner-recruit analyses, thereby precluding calculation of optimum escapement levels.

69

Management

3 Personal communication. 1996. S. McPherson, fisheries biologist, Alaska Department of Fish and Game, 802 3d Street,

Douglas, AK 99824.
70

The rebuilding program begun in 1981 was incorporated into the U.S./Canada Pacific

Salmon Treaty, ratified in 1985, that established the legislative basis for recent management of chinook salmon. A primary goal of the treaty was to rebuild depressed

natural chinook stocks throughout the eastern Pacific range of the species over a 

15-year period, or by 1998 (ADF&G 1992). The treaty established annual all-gear

catch ceilings that could be exceeded by “add-ons” of hatchery produced chinook

(Denton and Holland 1986).

Of the 11 index stocks in southeast Alaska used to monitor the success of the

rebuilding program, Andrew and King Creeks and Situk, Chilkat, and Stikine Rivers

have consistently exceeded escapement goals. Several stocks in southern southeast

Alaska (Unuk, Chickamin, and Blossom River stocks) initially responded well to the

rebuilding program but have declined since 1987. Mixed results have been observed

for the Alsek, King Salmon, and Keta Rivers. The Blossom and Chickamin Rivers

have had escapements below goals in recent years (McPherson and Carlile 1997,

Pahlke 1991a).

For operational purposes, the ADF&G has divided chinook systems in southeast

Alaska into three categories based on the estimated magnitude of total returns

(Kissner 1977). Minor systems have total returns of less than 1,500 individuals,

medium systems have total returns between 1,500 and 10,000 individuals, and major

systems have more than 10,000 individuals returning (on average). These categories

and their associated population estimates are based on complete drainages rather

than individual tributaries. Thirty-four systems are categorized in this system: 22

minor, 9 medium, and 3 major (table 12). Management research in the region is

directed toward refining escapement estimation and gathering information on the 

population biology of stocks useful in spawner-recruit analyses and determination of

optimal escapement goals.

Figure 18—Annual commercial harvest of chinook salmon in southeast Alaska, 1893 to 1991

(data from Rigby and others 1991).
71

Table 12—Location of spawning streams and types of data available for chinook salmon

stocks in the study region

Stream Location

Coastal North ADF&G

Number Name N. latitudea W. longitudea VCUb or interior or south mgmt. class Datac

101-30-030 Keta River 55°20 ́11 ̋ 130°28 ́24 ̋ 842K C S Mediumd B, E

101-30-060 Marten River 55°09 ́30 ̋ 130°31 ́47 ̋ 838K Minor E

101-45-078 Carroll Creek 55°39 ́04 ̋ 131°21 ́23 ̋ 744K Established? B, E

101-55-200 Wilson River 55°24 ́09 ̋ 130°36 ́25 ̋ 817K Minor E

101-55-040 Blossom River 55°24 ́10 ̋ 130°36 ́22 ̋ 815K & 818K C S d B, E

101-60-015 Rudyerd Creeke 55°39 ́47 ̋ 130°38 ́17 ̋ 802K & 798K Minor

101-60-030 Big Goat Creekf 55°45 ́00 ̋ 130°40 ́00 ̋ 802K Minor E

101-71-028 Walker Creeke 55°59 ́29 ̋ 131°50 ́32 ̋ 724K Minor

101-71-040 Chickamin River 55°49 ́26 ̋ 130°55 ́20 ̋ 793K & 794K C S Mediumd B, E

101-71-04A Barrier Creek 55°51 ́13 ̋ 130°37 ́50 ̋ 794K & 797K C S Medium B, E

101-71-04B Butler Creekf 56°03 ́00 ̋ 130°45 ́00 ̋ 795K C S Medium B, E

101-71-04C Clear Falls Creekf 55°59 ́00 ̋ 130°40 ́00 ̋ 795K E

101-71-04H Humpy Creek 55°50 ́55 ̋ 130°52 ́21 ̋ 793K B, E

101-71-04I Indian Creek 55°59 ́26 ̋ 130°39 ́19 ̋ 796K C S B, E

101-71-04K King Creek 55°50 ́28 ̋ 130°50 ́59 ̋ 793K B, E

101-71-04L Leduc River 55°54 ́23 ̋ 130°47 ́13 ̋ 794K & 795K E

101-71-04S South Fork 55°52 ́32 ̋ 130°44 ́23 ̋ 796K C S B, E

101-75-005 Herman Creeke f 55°59 ́00 ̋ 131°18 ́00 ̋ 730K Minor

101-75-010 Grant Creek 56°02 ́21 ̋ 131°12 ́45 ̋ 782K & 783K Minor E

101-75-015 Eulachon River 56°05 ́08 ̋ 131°05 ́17 ̋ 786K C S B, E

101-75-050 Klahini River 56°03 ́17 ̋ 131°02 ́54 ̋ 790K Minor E

101-75-030 Unuk River 56°04 ́38 ̋ 131°04 ́31 ̋ 786K Mediumd

101-75-30C Clear Creekf 56°07 ́ 130°57 ́ 786K C S B, E

101-75-30G Gene’s Lake 56°12 ́ 130°52 ́ 786K C S B, E

Creekf

101-75-30K Kerr Creekf 56°10 ́ 130°55 ́ Canada E

101-75-30L Lake Creek 56°08 ́03 ̋ 130°58 ́03 ̋ 786K & 789K E

101-75-30Q Cripple Creek 56°16 ́06 ̋ 130°47 ́47 ̋ 788K C S B, E

101-75-30S Sawmill Slough 786K E

107-20-001 Anan Creeke 56°10 ́47 ̋ 131°53 ́09 ̋ 522S

107-40-024 Aaron Creekf 56°22 ́ 131°55 ́ 503S Minor E

107-40-025 Oerns Creek 56°22 ́45 ̋ 131°57 ́57 ̋ 503S

107-40-047 Tom Lake Creek 56°13 ́10 ̋ 131°40 ́21 ̋ 510S Minor E

107-40-049 Harding River 56°12 ́18 ̋ 131°37 ́08 ̋ 511S C S Medium B, E

107-40-052 Bradfield River, 56°14 ́06” 131°27 ́16 ̋ 514S Medium E

North Fork

107-40-053 Bradfield River 56°13 ́58 ̋ 131°30 ́06 ̋ 517S E

East Fork

107-40-055 Eagle River 56°09 ́18 ̋ 131°35 ́13 ̋ 519S Minor E

(Bradfield)

108-40-015 Stikine River 56°38 ́20 ̋ 132°19 ́29 ̋ 493S Majord B, E

108-40-010 North Arm Creek 56°41 ́06 ̋ 132°18 ́19 ̋ 493S B, E

108-40-016 Kikahe River 56°38 ́43 ̋ 131°53 ́49 ̋ 500S E

108-40-017 Goat Creek 56°39 ́58 ̋ 131°58 ́12 ̋ 495S E

108-40-020 Andrew Creek 56°40 ́13 ̋ 132°15 ́04 ̋ 498S C S d B, E

108-40-024 Government 56°38 ́43 ̋ 132°17 ́07 ̋ 497S E

Creek

108-40-13A West of Hot 56°41 ́ 132°06 ́ E

Springsf

108-40-080 Shakes Creek 56°42 ́49 ̋ 132°06 ́17 ̋ 495S B, E

108-70-011 Katete River Canada E

108-80-100 Tahltan River Canada I N B, E
72

Table 12—Location of spawning streams and types of data available for chinook salmon

stocks in the study region (continued)

Stream Location

Coastal North ADF&G

Number Name N. latitudea W. longitudea VCUb or interior or south mgmt. class Datac

108-80-115 Beatty Creek Canada E

108-80-120 Little Tahltan Canada I N B, E

River

108-60-030 Muddy Rivere 56°54 ́15 ̋ 132°49 ́41 ̋ 489S Minor

110-14-007 Farragut River 57°09 ́42 ̋ 133°08 ́46 ̋ 90S C N Minor B, E

110-32-009 Chuck River 57°34 ́42 ̋ 133°21 ́00 ̋ 69C Minor E

111-17-010 King Salmon River 58°02 ́36 ̋ 134°20 ́18 ̋ 142C C N Minord B, E

111-32-032 Taku River 58°25 ́32 ̋ 133°58 ́25 ̋ 41C & 46C Majord B, E

111-32-210 King Salmon Canada

Creek

111-32-220 Nakina River Canada I N B, E

111-32-240 Kowatua Creek Canada I N B, E

111-32-254 Little Tatsamenie 58°25 ́ 132°20 ́ Canada I N B, E

Lakef

111-32-255 Tatsamenie River Canada I N B, E

111-32-260 Hackett River Canada I N B

111-32-270 Nahlin Riverf 58°48 ́ 132°01 ́ Canada I N B, E

111-32-275 Tseta Creek Canada I N B, E

111-32-280 Dudidontu Riverf 58°47 ́ 132°03 ́ Canada I N B, E

112-16-030 Wheeler Creekf 58°03 ́ 134°47 ́ 146C

112-65-024 Greens Creekf 58°05 ́ 134°45 ́ 144C

115-32-025 Chilkat River 59°13 ́33 ̋ 135°30 ́54 ̋ NA Mediumd B, E

115-32-046 Klehini Riverf 59°24 ́ 135°58 ́ NA B

115-32-054 Big Boulder Creek 59°25 ́43 ̋ 136°11 ́37 ̋ NA E

115-32-055 Little Boulder 59°25 ́27 ̋ 136°07 ́55 ̋ NA E

Creek

115-32-064 Kelsall River 59°31 ́53 ̋ 136°02 ́03 ̋ NA B

115-32-301 Stonehouse Canada E

Creek

115-32-068 Tahini River 59°36 ́57 ̋ 135°59 ́03 ̋ NA C N B, E

182-10-010 Doame Rivere f 59°03 ́ 138°17 ́ National Park Minor

182-20-010 East Alsek River 59°05 ́43 ̋ 138°25 ́37 ̋ National Park Minor

182-30-010 Alsek River 59°09 ́58 ̋ 138°33 ́21 ̋ National Park Majord B

Canada

182-30-020 Klukshu River Canada B, E

182-30-042 Tatshenshini Canada B

River

182-30-043 Takhanni River Canada E

182-30-045 Goat Creek Canada E

182-30-050 Blanchard River Canada E

182-40-010 Akwe River 59°16 ́59 ̋ 139°02 ́50 ̋ 379C Minor E

182-50-010 Italio Rivere 59°19 ́49 ̋ 139°14 ́21 ̋ 379 & 380C Minor

182-60-010 Dangerous Rivere f 59°23 ́ 139°17 ́ 377C Minor

182-70-010 Situk River 59°26 ́47 ̋ 139°33 ́58 ̋ 366C C N Mediumd B, E

182-80-010 Lost Rivere 59°27 ́11 ̋ 139°36 ́33 ̋ 367C Minor

183-50-010 Ankau Creeke f 59°30 ́ 139°45 ́ 369C Minor

NA = not available. 

a Latitude and longitude reported for river mouths.

b VCU = USDA, Forest Service value comparison unit; approximately equivalent to a watershed. K = Ketchikan Area; S = Stikine Area; and C = Chatham

Area.

c Data types included in this review: B = biological characteristics, E = escapement survey counts.

d Index system for management. 

e Small escapements reported, but no evidence of successful spawning.

f Approximate latitude and longitude interpolated from topographic maps.

Sources: ADF&G 1992, Kissner 1977, Pahlke 1991a.
73

Most chinook salmon in southeast Alaska are harvested in mixed-stock fisheries. 

The mixed-stock commercial harvest in southeast Alaska may include fish from other

regions; e.g., an estimated 57.9 percent of all chinook salmon harvested in 1987

were of non-Alaska origin (Olsen 1992). Chinook salmon from British Columbia

south of Dixon Entrance are taken most frequently in inside waters, and chinook from

the Pacific Northwest are caught in outside waters. For chinook salmon originating in

rivers that flow through southeast Alaska, differences in migratory pattern have important consequences for the exposure of different stocks to troll and drift gill-net fisheries, the fisheries that account for most of the southeast Alaska catch of chinook

salmon (ADF&G 1992). Stocks from southern southeast Alaska that are exposed to

fisheries for extended periods have exploitation rates that range from 16 percent for

the Unuk stock to 40 to 60 percent for the Chickamin stock, with a high of 65 percent

calculated for age 1.3 fish from the Chickamin River caught in 19894 (McPherson and

Carlile 1997). Since the mid-1970s, when the start of the troll season was delayed,

exploitation rates on the chinook stocks in the Taku and Stikine drainages (which

move offshore quickly) have been less than 10 to 20 percent (see footnote 3). These

stocks have been exposed to increasing exploitation by sport fisheries in recent

years, but the effect of these fisheries is believed to be small compared to the effects

of a directed commercial troll fishery (see footnote 3).

Recreational fisheries for chinook salmon are growing rapidly throughout southeast

Alaska. From 1977 to 1984, the estimated average annual sport catch of chinook

salmon was about 20,300 fish (ADF&G 1992). The estimated sport harvests in 1990

and 1991 were 51,200 and 68,400, respectively (ADF&G 1992). In these years,

recreational fisheries took about 20 percent of the all-gear catch ceilings instituted

under the Pacific Salmon Treaty. About 60 percent of the sport catch taken from

1977 to 1989 occurred in the Ketchikan and Juneau areas. In 1990, that declined to

45 percent as sport fisheries expanded in Petersburg-Wrangell, Sitka, and other

areas (ADF&G 1992). Management of recreational fisheries is becoming an increasingly important component of overall chinook salmon management across southeast

Alaska.

Development of ocean-type chinook runs was the goal of early enhancement efforts

that involved transfers of chinook salmon eggs into Alaska from Washington and

Oregon (Roppel 1982). This goal was apparently motivated by the expectation that

ocean-type chinook would be able to use the abundant small-stream habitats found

throughout southeast Alaska. The failure of these transplants was thought to be due

to the low productivity of Alaska streams. Greater stream productivity at lower latitudes may permit the short freshwater residence of ocean-type chinook salmon

(Taylor 1990). Hatchery production of ocean-type chinook salmon began in southeast Alaska in 1923 at the Ketchikan territorial hatchery, near the current site of the

4 Recent studies have confirmed that chinook populations in southeast Alaska differ in extent of ocean migration: Stikine, Taku,

Alsek, and Situk River stocks, as well as other Yakutat Foreland

stocks, migrate quickly to outside waters and spend most of their

ocean life in the Gulf of Alaska; the remainder of stocks spend

most of their ocean life in coastal waters. We have not conducted

analyses comparing characteristics of stock groups exhibiting

these different ocean life patterns.

Enhancement
74

Deer Mountain hatchery on Ketchikan Creek. In 1923, nearly 1 million chinook fry

were released into Ketchikan Creek (Roppel 1982). Half of the eggs hatched to produce these fry were from the Columbia River, and the other half were from unknown

sites in Oregon (Roppel 1982). The chinook program at the Ketchikan territorial

hatchery continued until 1927, with nearly 2 million fry released each year. After the

initial shipment from Oregon, all subsequent transferred eggs were derived from

stocks in Washington (Roppel 1982). Because funding for the territorial hatchery program was terminated in 1927, little information exists on returns from these early

enhancement activities on Ketchikan Creek.

The next significant attempt to establish ocean-type chinook production occurred in

the early 1950s with transfers of eyed chinook eggs from Washington that were planted in two streams near Juneau (Parker and Kirkness 1950). From 1950 to 1953, four

shipments of eyed chinook eggs from Soos Creek, Washington (and possibly other

sources), were planted in Montana and Spring Creeks near Juneau, resulting in a

total transfer of at least 160,000 eggs (the number of eggs in the final shipment is

unknown; Roppel 1982). As was the case with operations at the Ketchikan territorial

hatchery, no systematically collected data are available on returns from these efforts.

Deer Mountain hatchery in Ketchikan began chinook operations in 1955 with another

attempt to establish ocean-type runs with eggs from Soos Creek, Washington. After

releasing over 200,000 fry hatched from Soos Creek eggs during 4 years, sufficient

returns to the hatchery occurred in 1960 to continue the program with egg-takes at

the hatchery (Roppel 1982). This program continued until 1967. No subsequent

transfers of ocean-type eggs were pursued.

Egg transfers for chinook brood stock ended in the 1960s for several reasons: 

(1) low return rates from hatchery releases; (2) the possibility of importing infectious

hematopoietic necrosis virus (IHNV), which is common in chinook from Washington

and Oregon but is not present in native chinook stocks in southeast Alaska; and 

(3) concerns about potentially negative genetic effects of cultured fish from distant

sources on native stocks. Infection of local wild stocks with IHNV as a result 

of egg transfers seemingly did not occur. The genetic effects of all early egg transfers on native stocks are unknown. Although straying rates of the transferred fish

were probably high (Quinn 1993, Reisenbichler 1988), the probability of successful

spawning and recruitment were probably low owing to differences in migration and

spawning timing, rearing ecology, and a variety of other life history characteristics.

The current phase of enhancement for chinook salmon, which began in 1975 with 

a program to establish a chinook salmon brood stock from southeast Alaska, was

another response to the depressed status of southeast Alaska chinook stocks as well

as other stocks harvested incidentally in southeast Alaska. Chinook eggs were taken

from the Unuk, Chickamin, Stikine (Andrew Creek), King Salmon, and Taku drainages

(Moberly and Kaill 1977). Unuk and Chickamin River eggs were cultured separately

at the Little Port Walter research hatchery, and eggs from the other sources were cultured at the Crystal Lake hatchery on Mitkof Island; most of these eggs were from the

Andrew Creek chinook stock. Other hatcheries were located at Deer Mountain,
75

Table 13—Hatchery programs producing chinook salmon in southeast Alaskaa

Annual

egg-take

Hatchery Management Location Brood stock sources Release sites goal

Whitman Lake SSRAAb Herring Bay, George Chickamin River Whitman Lake 3,000,000

Inlet, South Neets Bay

Revillagigedo Island Carroll Inlet

Earl West Cove

Deer Mountain Ketchikan Indian Corp. Ketchikan Unuk River Ketchikan Creek 133,000

Thorne Bay

Big Salt Lake

Neets Bay SSRAAb Neets Creek, Neets Chickamin River Neets Bay 1,500,000

Bay, North Unuk River before

Revillagigedo Island 1994

Bell Islandc American Aquaculture Bell Island, West Behm Unuk River Bell Island Creek

Corp. Canal

Port Armstrongd Armstrong-Keta, Inc. Jetty Lake, South Unuk River (1985-91) Armstrong Bay 1,100,000

Baranof Island King Salmon River

Farragut River

Crystal Lake ADF&Ge Crystal Lake, Blind Andrew Creek Crystal Creek 2,500,000

Slough, Mitkof Island Ohmer Creek to11111

Earl West Cove 4,000,000

Medvejie Creek

Farragut River Farragut River

Little Port U.S. Dept. of Commerce, Little Port Walter, Chickamin River Little Port Walter

Walter NMFS Sashin Creek, South Unuk River Port Armstrong

Baranof Island King Salmon River Gastineau Channel

Snettisham ADF&Ge Speel Arm, Port Andrew Creek Speel Arm No longer

Snettisham Situk River producing

chinook

salmon

King Salmon River Auke Creek

Fish Creek 

(Douglas Island)

Montana Creek

Sheep Creek 

(Juneau)

Redoubt Lake

Gastineau Channel

Indian River 

(Tenakee)

Little Port Walter

Unuk River Port Armstrong

DIPACf Douglas Island Pink and Salmon and Sheep Andrew Creek Gastineau Channel 700,000

Chum, Inc. Creeks, Gastineau King Salmon River Sheep Creek

Channel, Juneau Fish Creek

(Douglas Island)

Auke Creek

Medvejie Creek

Tahini River Tahini River

Big Boulder Creek Big Boulder Creek

a Tamgas hatchery (Annette Island, Unuk River brood stock), Hidden Falls hatchery (northeast Baranof Island, Tahini River brood stock) and

Medvejie hatchery (Sitka, Andrew Creek brood stock) also have chinook salmon production programs.

b SSRAA = Southern Southeast Regional Aquaculture Association.

c This program is relatively small and is currently in the brood stock development stage.

d A brood stock change to either King Salmon River, or possibly Farragut River, is anticipated in 1995.

e ADF&G = Alaska Department of Fish and Game.

f In transition to King Salmon River brood stock.

Source: Information primarily from hatchery management plans provided by S. McGhee, ADF&G Division of Commercial Fisheries, 1255 West

8th Street, Juneau, AK 99802.
Neets Bay, and Whitman Lake. After several years of relatively small releases, the

hatchery program for chinook salmon grew quickly in the early 1980s and achieved a

peak release of 9 million age-1 smolts in 1988. With the advent of catch ceilings for

wild chinook associated with signing of the Pacific Salmon Treaty in 1985, hatchery

chinook were expected to play an important role in compensating for reduced harvest 

of wild fish. One goal of the hatchery chinook program was to add 100,000 chinook

salmon to the troll catch (ADF&G 1992). In 1991, 79,546 hatchery-produced chinook

salmon were caught in southeast Alaska (ADF&G 1992). Most hatchery production

programs for chinook salmon that were ongoing in 1994 are summarized in table 13.

The chinook salmon plan for southeast Alaska (Holland and others 1983) identified

numerous sites with potential for structural enhancements, lake and stream stocking

projects, or rehabilitation programs for chinook salmon. Relatively few of these

enhancement activities have occurred in the region. The following summary is not a

comprehensive list, but rather a representative sample of habitat enhancement 

projects throughout the region. Carroll Creek has been stocked with chinook fry

(Chickamin River origin) from various hatcheries since 1982. A small run also was

established in the Chilkoot River (see footnote 3). Chinook fry or smolts of Andrew

Creek origin have been released at Ohmer Creek and at numerous locations in the

Juneau area (future releases in the Juneau area probably will be of King Salmon

River origin). The NMFS experimentally stocked chinook fry into Larry and Tranquil

Lakes (both have barriers to anadromous migrations). Although the experiment produced chinook salmon, it was not as successful as coho salmon production. Fry 

outplant programs have been conducted in the Farragut, Harding, and Tahini Rivers.

Chinook salmon were stocked in Indian River, Tenakee Inlet in 1986, 1989, and 1993

(Killinger 1994). Upstream access is blocked by a barrier falls; a spawning population therefore was not established. Big Boulder Creek was stocked with fry outplants,

and an incubation box was installed at the creek following habitat disruptions associated with bridge building and road repair (see Parry and others 1993).

Enhancement efforts for chinook salmon have declined since the late 1980s, and in

recent years, nearly all state-run enhancement programs have been terminated or

transferred to private, nonprofit hatcheries. Brood stocks derived from the King

Salmon, Unuk, and Chickamin Rivers and Andrew Creek currently dominate hatchery

production throughout the region. Although a large amount of straying has not been

observed among some rivers, such as the Taku, Stikine, Chilkoot, and Situk, release

of these brood stocks throughout southeast Alaska may have increased gene flow

among chinook stocks.

Differences in morphology and scale patterns have not proven particularly effective

for separating southeast Alaska chinook stocks. Rowland (1963) was unsuccessful in

finding morphologic characteristics that permitted reliable identifications. Attempts to

employ scale analysis permitted separation of Alaska versus non-Alaska fish but

were unsuccessful for individual river systems owing to overlap in circuli counts

(Kissner 1977, Van Alen 1988). Biochemical and genetic techniques have not yielded 

appreciably better results. Mitochondrial DNA analysis of chinook from south-central

Alaska and British Columbia revealed the presence of regional mitochondrial 

76

Stock Discrimination
77

maternal lines, but overall sequence divergence among populations was less than 1

percent (Wilson and others 1987). Electrophoretic techniques have been useful for 

separating chinook stocks over broad geographic areas (Gall and others 1992).

Gharrett and others (1987) found, however, that low levels of allozyme variability

among Alaska stocks limited the resolution of this technique. In 1989, additional tissue samples were collected from southeast Alaska populations for genetic stock identification by using a more comprehensive selection of allozymes (Pahlke and Mecum

1990); but analysis of these samples was not complete as of 1994.5 Recent studies of

chinook stocks in the Snake and Klamath Rivers in the Pacific Northwest demonstrate that analysis of additional polymorphic loci can greatly enhance the ability of

electrophoresis to resolve genetic differences between stocks (Utter and others

1992). In view of this result, Utter and others (1992) recommend a cautious interpretation of electrophoretic data that do not identify genetic differences between stocks

that have little potential for interbreeding. Their work suggests that further analysis of

existing samples from southeast Alaska stocks may detect genetic divergence where

previously none had been found.

Using data up to 1991, we subdivided the 34 chinook systems designated by the

ADF&G to the level of tributaries within drainage systems. This subdivision yielded

85 reported or known chinook stocks in southeast Alaska and in transboundary 

systems of adjoining areas of British Columbia and the Yukon Territory (table 12). Of

the 85 stocks, we found at least a single element of biological data, usually escapement counts, for 70. Of these 70 stocks, 39 had data sufficient to permit their inclusion in analyses of biological variables other than escapement. We sought to identify

stocks with distinctive biological characteristics from the subsample of 39 stocks.

Most of the 39 stocks for which data were available were from tributaries of major

systems, with large, commercially significant, returns. Only 7 of 22 minor systems

were included in our analyses.

We conducted our analyses primarily on data from escapement sampling of returning

adults. Limited young of the year (YOY) and smolt fork-length data also were evaluated. Eight chinook salmon stocks in the region were sampled for biological characteristics at weirs (including the Nakina carcass weir). 

Methods used for obtaining, analyzing, and evaluating data for chinook stocks corresponded to those presented in the “General Introduction,” with minor modifications as

follows. Stocks were included in variance component analysis on the basis of having

at least 4 years of data on adult mideye-to-fork length with at least 10 individuals

sampled of each sex. For evaluations of run timing, we used mean dates calculated

from peak escapement surveys rather than the peak spawning dates reported by

Kissner (1982) and Mecum and Kissner (1989). These measures of run timing were

very strongly correlated (r = 0.83, P < 0.001), and our index based on survey dates

could be calculated for a larger number of stocks. Run-timing statistics also were 

calculated for seven stocks enumerated at weirs (excluding the Nakina carcass weir).

Our evaluation of temporal variation in sex ratios included six chinook stocks with the

Methods

Data Analysis

Procedures

5 Personal communication. 1996. C. Noll, fishery biologist, National

Marine Fisheries Service, Auke Bay Laboratory, 11305 Glacier

Highway, Juneau, AK 99801.
78

largest numbers of individuals sampled for length or age for the most years. Two of

these six, the Cripple Creek and Tahini River stocks, were not sampled at a weir or

fishwheel; therefore, more sources of sampling bias may have affected sex ratio 

estimates in these stocks.

Compared to other species of Pacific salmon in the region, relatively long time-series

of escapement surveys are available for most chinook stocks in the region; however,

the types of spawning habitats used by chinook salmon are very difficult to survey

accurately for escapements. Although continuing research is refining escapement

estimation procedures (e.g., Johnson and others 1992a), existing escapement survey

data provided only an index of actual abundance levels. In the absence of more 

reliable data, we used these to compare the interannual variability of abundance and

distribution of the escapement survey analysis (Olsen 1992). Trends identified from

these analyses should be interpreted cautiously.

We used multivariate analysis of variance (MANOVA) to look for geographic patterns

in biological characteristics of chinook stock groups. Based on patterns present in

other species, we included two geographic comparisons: (1) coastal versus interior,

and (2) northern versus southern stocks. Dependent variables in the complete model

were adult mideye-to-fork length and mean saltwater age (MSWA) for both sexes,

sexual dimorphism in mideye-to-fork length, MSWA sexual differences, and mean 

survey index dates. To determine which characteristics contributed the greatest

effects to the complete MANOVA, we conducted post hoc analyses that included only

one type of biological data (e.g., mideye-to-fork length variables alone). Significance

tests for these analyses used the approach based on greatest characteristic roots

described by Harris (1985). Samples from the mainstem Taku and Stikine Rivers

were excluded from analysis because fishwheels selectively catch smaller fish.

Interior stocks were defined as those that experience a more continental climate

because they spawn in tributaries of the Stikine, Taku, and Alsek Rivers that are north

and east of the Coast Mountains. The mouth of the Stikine River was used as the

boundary between northern and southern stock groups. Stocks in these groups have

different oceanic migration patterns (see footnote 4) and experience small differences

in freshwater climatic regimes. Stocks that spawn in interior tributaries of the Stikine

River were considered northern stocks in our analyses (see table 12).

Because insufficient data were available to include YOY fork lengths and mean

migration dates and variances at weirs in MANOVA analyses, we used graphic methods to look for geographic patterns in these characteristics.

The complete model that included all dependent variables (mideye-to-fork length,

MSWA, mean survey index date, and sexual dimorphism) was significant (Roy's maximum root F-ratio, P = 0.04) when both coastal-versus-interior and north-versus-south

effects were included. The interaction effect could not be tested because interior

stocks are not present in the southern half of the region. The coastal-versus-interior

effect alone was not significant (Roy's maximum root, P = 0.34). Examining the 

contributions of separate biological characteristics to the overall difference between

northern and southern stocks, we found that differences in body lengths were the

strongest contributors (Roy's maximum root, F = 10.56, Fcrit.= 5.1, P < 0.01), with

Results

Geographic Patterns
79

southern stocks having greater body lengths in all four age and sex classes included

in the analysis (fig. 19). Southern stocks also tended to have lower MSWAs, less

age difference between the sexes, and later survey index dates. 

Graphic analysis of geographic patterns in chinook salmon fry (YOY) and smolt fork

lengths, and mean dates of return migration and duration of return migration, showed

no clear trends.

The chinook salmon YOY in the Situk and Tahini Rivers appeared to be larger than

others in southeast Alaska, based on outlier analysis of fork lengths (fig. 20). The

number of stocks sampled and number of samples taken from each stock were small.

We attempted to standardize the comparison of different stocks by using fork lengths

measured in October, but for the Situk River, only August fork lengths were available.

The mean fork length of the YOY in the Situk River in August exceeded the mean

October fork lengths of other stocks in the region, indicating the ocean-type juvenile

growth pattern of this stock.

Mean mideye-to-fork lengths showed considerable variation for all age and sex classes (table 14), but no stocks in the region had mean body lengths for any age or sex

class that were outliers. Data for male and female mideye-to-fork length were analyzed separately because significant differences were observed between the sexes 

in adult body size (paired t-test: age 1.3, P = 0.002; age 1.4, P = 0.0001). Age 1.3

males, on average, were smaller than same-age females, but age 1.4 males were

larger than age 1.4 females. Male and female body sizes within a stock were weakly

correlated for the 1.3 age class (r = 0.11, P = 0.39) but strongly correlated for age

class 1.4 (r = 0.63, P < 0.001). Three stocks showed distinctive patterns of sexual

Body Length

Figure 19—Mideye-to-fork lengths of adult chinook salmon from

escapements by stock group, sex, and age class. Sample sizes

were 12 and 15 for the southern and northern stock groups, respectively. Height of columns indicates grand mean for all stocks in that

group across all sample years. Error bars give standard errors. See

text for MANOVA results. Stock-specific length summaries are 

presented in table 14.
80

dimorphism: Keta River, Barrier Creek, and Indian Creek (fig. 21), but this was based

on small samples sizes of 31, 35, and 36 fish, respectively. In the Keta River stock,

age 1.3 females were over 150 mm smaller than same-age males, contrary to the

general trend in the region, but the mean mideye-to-fork length of age 1.3 females in

Barrier Creek stock were larger than males by 146 mm. The 1.4 age class females

in the Keta River stock did not contradict the prevailing pattern of dimorphism and

were over 200 mm smaller than 1.4 males (fig. 21B). In contrast, the Indian Creek

age 1.4 females were 31 mm larger than males, a pattern of dimorphism opposite the

one prevailing among most stocks.

Variance-component analysis indicated that over 90 percent of total variation in male

body length, but only 45 percent of female body length variation, were attributable to

differences among individuals within the three stocks evaluated (table 15). Among

females, variation among stocks accounted for 53 percent of the total variation

observed, suggesting a higher level of stock-specific specialization in female chinook

than in males (and considerably higher than all other species of Pacific salmon 

analyzed by this method). Interannual variation within stocks accounted for a small

proportion of overall variance and was twice as great in males (5.6 percent) as in

females (2.2 percent).

Adult body sizes of southeast Alaska chinook stocks have tended to decrease

through time. Analyses were conducted separately on mideye-to-fork lengths of 1.3

and 1.4 age-class males and females (table 16). All regression slopes for males and

half of the slopes for females were negative. Only the Cripple Creek age 1.3 males

yielded a significantly negative regression (P < 0.05). The mean rate of decline for all

sex and age classes (mean of the regression coefficients) was -4.22 mm/year. The

high standard deviation (6.65) associated with this mean reflected the high variability

and small number of stocks included in this analysis. Cripple Creek, Nahlin River,

and Tahini River chinook salmon were the only stocks with enough years of data to

analyze. These stocks had the longest series of length data available, but even

these series were short (≤ 7 records).

Figure 20—Frequency distribution, outlier plot, and normal quantile

plot for October fork lengths of chinook salmon young of the year

(YOY) from 14 stocks (Situk River lengths were measured in

August). The YOY from the Situk and Tahini River stocks were distinctively large. This distribution was significantly nonnormal by the

Wilks test (P = 0.002) but became acceptably normal (P = 0.82)

when the Situk and Tahini points were removed.
81

Table 14—Summary of mean mideye-to-fork lengths (in millimeters) from chinook salmon

escapement samples

Males Females

Sexual

dimorphism age

Stream Age classes Age classes classes

Number Name No. 1.1 1.2 1.3 1.4 1.5 No. 1.2 1.3 1.4 1.5 1.3a 1.4b

101-30-030 Keta River 6 610.0 860.0 942.5 25 707.5 742.4 -152.5 200.1

101-55-040 Blossom River 26 752.7 853.8 950.7 24 930.0 811.3 919.0 -42.5 31.7

101-71-040 Chickamin River 77 427.0 587.1 794.7 922.0 976.0 144 760.0 843.8 924.5 939.0 49.1 -2.5

101-71-04A Barrier Creek 24 430.0 552.5 734.5 990.0 11 880.0 943.8 145.5 46.2

101-71-04B Butler Creek 37 375.6 610.0 788.6 943.3 44 831.0 897.5 42.4 45.8

101-71-04I Indian Creek 18 405.0 609.0 835.0 955.0 18 851.0 986.0 16.0 -31.0

101-71-04K South Fork 112 400.0 590.0 788.0 1,002.0 70 876.0 954.0 963.0 88.0 48.0

101-75-015 Eulachon River 100 397.1 616.1 788.3 963.4 1,070.0 127 849.3 942.6 930.0 61.0 20.8

101-75-30C Clear Creek 144 393.0 593.1 808.1 943.8 93 861.4 922.7 980.0 53.3 21.1

101-75-30G Gene’s Lake 206 379.8 590.3 730.5 922.5 117 740.0 814.5 915.6 1,022.5 84.0 6.9

Creek

101-75-30Q Cripple Creek 881 359.1 574.7 791.0 963.7 945.0 608 717.5 828.3 914.7 946.5 37.3 49.0

107-40-049 Harding River 16 702.9 851.4 1,030.0 9 875.0 951.7 23.6 78.3

108-70-002 Stikine Riverc 96 374.5 510.0 723.2 863.6 705.0 29 528.7 797.8 824.0 74.6 39.6

108-40-020 Andrew Creekd 375 356.9 540.4 701.1 859.2 905.0 282 688.0 783.9 852.5 857.2 82.8 6.7

108-80-100 Tahltan River 91 397.7 490.3 793.9 922.5 126 738.0 773.2 859.0 913.0 -20.7 63.5

108-80-120 Little Tahltan 451 362.9 501.9 766.7 903.3 897.0 533 711.6 797.2 866.6 936.3 30.5 36.7

Riverd

110-14-007 Farragut River 113 599.0 569.5 768.5 941.4 983.2 39 710.0 825.6 889.1 900.4 57.1 52.3

111-17-010 King Salmon 140 455.0 604.6 753.7 892.3 890.0 119 620.0 809.9 871.6 893.2 56.2 20.7

Riverd

111-32-032 Taku River c 1,646 371.5 529.6 737.1 841.4 972.0 881 583.1 756.0 841.4 877.8 18.9 0.0

111-32-220 Nakina Riverd 5,896 334.6 515.2 722.7 883.0 953.5 2,168 737.5 775.6 849.7 892.1 52.9 33.3

111-32-240 Kowatua Creek 776 354.3 558.8 753.8 888.7 945.0 317 785.3 867.5 900.2 31.5 21.2

111-32-254 Little 591 349.8 567.8 747.1 870.7 981.0 288 534.7 752.1 841.0 926.0 5.0 29.7

Tatsamenie

Laked

111-32-255 Tatsamenie 534 344.0 558.8 752.2 859.4 937.0 288 662.1 771.9 843.4 897.0 19.7 16.0

River

111-32-260 Hackett Riverd 108 372.1 531.0 739.0 882.5 25 691.9 776.0 858.8 886.3 37.0 23.7

111-32-270 Nahlin River 825 369.3 578.5 757.8 871.3 951.2 896 647.0 759.2 842.8 896.5 1.4 28.5

111-32-275 Tseta Creek 52 555.0 656.7 768.0 909.8 61 650.0 813.5 842.6 930.0 45.5 67.2

111-32-280 Dudidontu 47 375.0 567.5 770.9 922.8 910.0 45 776.0 852.4 5.1 70.4

River

115-32-068 Tahini River e 610 423.2 636.0 767.6 914.4 914.0 151 670.0 842.0 893.0 960.0 74.4 21.4

182-70-010 Situk River 20 643.3 765.0 861.0 37 680.0 845.0 871.0 80.0 -10.0

Total mean 398.5 584.4 772.8 917.8 933.4 684.2 809.3 882.1 922.4 36.5 35.7

Total SE 12.3 10.8 7.5 8.7 18.8 20.4 7.9 9.4 8.8 9.7 7.5

Total CV 15.6 10.0 5.3 5.2 8.2 13.1 5.3 5.8 4.3 7,143.8 113.6

a Age 1.3 sexual dimorphism calculated as (female - male).

b Age 1.4 sexual dimorphism calculated as (male - female).

c Samples primarily from fishwheels.

d Samples primarily from a weir; Nakina River has a carcass weir.

e Samples primarily from gill nets.
82

The mean date for chinook stocks to return to weirs seems to be consistent among

years (McGregor and Clark 1989, 1990; Olsen 1992; Pahlke 1991a; Van Alen and

Olsen 1986; Van Alen and others 1987, 1990; see footnote 6). The largest coefficient

of variation (CV) for mean date at a weir was 3.77 percent for 16 years of sampling

on the Klukshu River. The variances associated with these mean dates differed

greatly, indicating large interannual differences in the duration of runs; CVs ranged

from 25 to 112 percent. Regression analysis revealed no trends across years in run

duration.

Figure 21—Frequency distributions, outlier plots, and normal quantile

plots for sexual dimorphism in mideye-to-fork lengths of (A) age class

1.3, N = 27, and (B) age class 1.4, N = 27. Note that age 1.3 females

are typically larger than males, but age 1.4 males are typically larger

than females. In the Keta River stock, females in both age classes

were distinctively smaller than males. Age 1.3 males from Barrier Creek

were distinctively smaller than females, and age 1.4 females from

Indian Creek were distinctively larger than males. Both distributions

were significantly nonnormal by the Wilks test but became acceptably

normal when the outliers were removed. Data are presented in table

14.

Timing

6 Alaska Department of Fish and Game, unpublished data. On file

with: Alaska Department of Fish and Game, 802 3d Street,

Douglas, AK 99824.
83

Table 15—Variance component analysis of age 1.3 chinook salmon mideye-tofork lengths from escapement samplesa b

Source Degrees Type 1

of of sum of Error Expected mean Variance Percentage

variation freedom squares F-test term square component of total

Males

Total 804 3,633,999.5 4,519.90 4,618.32 100

Stocks 2 125,278.99 3.36 Years 62,639.49 145.25 3.15

Years 9 168,009.88 4.43 Error 18,667.76 260.32 5.64

Error 793 3,340,710.7 4,212.75 4,212.75 91.22

Females

Total 656 2,136,977.6 3,257.59 4,325.72 100

Stocks 2 832,829.74 64.28 Years 416,414.87 2,299.66 53.16

Years 9 58,300.18 3.35 Error 6,477.80 94.51 2.18

Error 645 1,245,847.70 1,931.55 1,931.55 44.65

a Variance components computed from means, standard errors, and sample sizes.

b Stocks included in the analysis:

101-75-30Q Cripple Creek

111-32-270 Nahlin River

115-32-068 Tahini River

Table 16—Regression analyses of trends across years in mideye-to-fork

lengths for chinook salmon escapement samplesa

Stream Regression

No. years R- SigNumber Name Sex Age sampled squared Slope P-value nificancea

101-75-30Q Cripple Creek M 1.3 6 0.67 -16.66 0.02<P<0.05 *

M 1.4 6 0.27 -6.45 0.2<P<0.4 NS

F 1.3 5 0.28 2.92 0.2<P<0.4 NS

F 1.4 6 0.09 4.17 0.5<P<0.9 NS

111-32-270 Nahlin River M 1.3 7 0.41 -11.33 0.1<P<0.2 NS

F 1.3 7 0.05 -3.95 0.5<P<0.9 NS

115-32-068 Tahini River M 1.3 7 0.14 -0.86 0.4<P<0.5 NS

M 1.4 7 0.19 -8.32 0.2<P<0.4 NS

F 1.3 7 0.07 -3.60 0.5<P<0.9 NS

F 1.4 7 0.13 1.91 0.4<P<0.5 NS

* = 0.05 > P > 0.01; NS = not statistically significant.

a All samples taken from 1982 to 1990.
84

Figure 22—Frequency distributions, outlier plots, and normal quantile plots for

index dates based on the timing of peak escapement survey counts. (A) When

all stocks (N = 58) in the region were evaluated together, the stocks from the

King Salmon, Chuck, Situk, and Nahlin Rivers had distinctively early run timing.

When northern (panel B, N = 21) and southern (panel C, N = 37) stock groups

were evaluated independently, no stocks had distinctive run timing.
85

The grand mean survey index date for all stocks in the region was 11 August. The

grand means for northern and southern stock groups were 7 August and 14 August,

respectively. Outlier analysis of index dates for all stocks combined indicated that the

Chuck, Nahlin, King Salmon, and Situk River stocks had earlier run timing but not

necessarily spawning time than other stocks (fig. 22A). The Nahlin River was the

only interior stock in this group. Separate outlier analysis of northern and southern

stock groups found no stocks with distinctive index dates (fig. 22B and C).

Geographic distribution—Of more than 85 identified stocks in southeast Alaska,

chinook salmon from King Salmon River, Wheeler Creek, and Greens Creek on

Admiralty Island and Carroll Creek on Revillagigedo Island were the only stocks

found in island drainages. All were smaller watersheds than those used by chinook

salmon in mainland systems. The small drainage of the island systems seemed to

limit the size of these populations, which increases both demographic risk and potential for rapid evolutionary divergence. For example, Kissner (1975) reports that the

King Salmon River stock begins to mature in salt water rather than in the river, a

characteristic not found in other southeast Alaska stocks. No biological data were

available for either the Wheeler or Greens Creek stocks. The population size of the

Wheeler Creek stock was considered to be very small.7 8 The Carroll Creek stock is

considered to be an introduced stock.9 If any native fish are present, the integrity of

the wild stock is further compromised by stocking of Chickamin River fry and high

straying rates of chinook from the Deer Mountain hatchery.

Escapement—Trends in escapement from 1960 to 1993 were evaluated for 59 

chinook salmon stocks with more than 7 years of escapement records. The Little

Tatsamenie Lake stock was the only one evaluated by weir counts. Escapement estimates from both surveys and weirs were available for five stocks. Of all stocks analyzed, 15 (25 percent) were increasing significantly and three (5 percent; North Arm

Creek, Big Boulder Creek, and King Salmon River) were declining significantly (table

17). Because the 1962 count of 800 fish for North Arm Creek seemed to be anomalous, we reanalyzed the escapement trend for this stock, but excluded this count.

The result of this reanalysis was a marginally nonsignificant decline (P = 0.065). The

King Salmon River stock showed a significant decline based on weir counts (9 years)

but was stable based on intensive surveys (24 years). Increasing stocks were clustered in the Boca de Quadra and in the interior tributaries of the Taku River. No

stocks in the region have distinctively large escapements based on outlier analysis of

mean escapement estimates.

7 Personal communication. 1996. M. Laker, fisheries biologist/

ecologist, U.S. Department of Agriculture, Forest Service, Tongass

National Forest, Admiralty National Monument, 8461 Old Dairy

Road, Juneau, AK 99801.

8 Personal communication. 1996. A. Wertheimer, fishery biologist,

National Marine Fisheries Service, Auke Bay Laboratory, 11305

Glacier Highway, Juneau, AK 99801.

9 Personal communication. 1996. K. Pahlke, fisheries biologist,

Alaska Department of Fish and Game, 802 3d Street, Douglas, AK

99824.

Demography
86

Age structure—Age structure of chinook escapements was evaluated in terms of

MSWA and proportions of individuals in each age and sex class (table 18). Jacks

were excluded from MSWA analysis because sampling effort was consistent neither

among stocks nor among years within stocks (see footnote 9). Outlier analyses were

conducted separately on males and females because females have significantly higher MSWAs than males (paired t-test, P < 0.001). No stocks in the region were distinctive based on outlier analysis of MSWA for either sex.

Sampling for age structure has been conducted on the Nakina and Klukshu Rivers for

enough years to permit regression analysis of trends in MSWA across years. Both

males and females in the Nakina River showed significant trends of increasing

MSWA across years, while both sexes of the Klukshu River stock showed nonsignificant trends of decline in MSWA (table 19).

Table 17—Results of regression analysis on escapement survey estimates of

chinook salmon abundance from 1960 to 1993

Stream Regression

No. of Mean

survey escape- SE R- Test

Number Name years ment Slope slope Change squared statistic Probability value Trend

Percent

101-30-030 Keta River 25 389.16 22.67 5.63 5.83 0.41 4.03 P<0.001 +++

101-30-060 Marten River 18 123.17 8.25 2.75 6.70 0.36 3.00 0.001<P<0.01 ++

101-45-078 Carroll Creek 12 211.58 38.64 14.50 18.26 0.42 2.67 0.02<P<0.05 +

101-71-004 Chickamin River 14 371.86 47.10 9.28 12.67 0.68 5.08 P<0.001 +++

101-71-04K King Creek 22 164.09 6.94 3.10 4.23 0.20 2.24 0.02<P<0.05 +

101-75-30C Clear Creek-Unuk 15 87.20 6.93 3.05 7.95 0.28 2.28 0.02<P<0.05 +

River

107-40-053 Bradfield River East 12 129.92 13.83 4.60 10.65 0.48 3.01 0.01<P<0.02 +

Fork

108-40-010 North Arm Creek 22 109.23 -7.72 3.06 -7.06 0.24 -2.53 0.01<P<0.02 -

108-40-020 Andrews Creek 29 341.66 15.67 4.54 4.59 0.31 3.45 0.001<P<0.01 +

108-80-120 Little Tahltan River 21 1,791.86 93.60 24.17 5.22 0.44 3.87 0.001<P<0.01 ++

111-32-255 Tatsamenie River 24 694.67 43.67 6.29 6.29 0.69 6.95 P<0.001 +++

111-32-270 Nahlin River 28 885.71 44.23 10.98 4.99 0.38 4.03 P<0.001 +++

111-32-275 Tseta Creek 22 199.55 7.82 2.78 3.92 0.28 2.81 0.01<P<0.02 +

111-32-280 Dudidontu River 26 295.62 16.48 5.71 5.57 0.26 2.89 0.001<P<0.01 ++

115-32-054 Big Boulder Creek 20 102.15 -5.72 1.81 -5.60 0.36 -3.17 0.001<P<0.01 —

182-30-020 Klukshu River 15 506.40 31.95 10.74 6.31 0.40 2.97 0.01<P<0.02 +

(Canada)

182-30-050 Blanchard Creek 9 237.56 27.08 8.84 11.40 0.57 3.06 0.01<P<0.02 +

(Canada)

Systems with weirs:

111-17-010 King Salmon River 9 262.11 -18.47 7.44 -7.04 0.47 -2.48 0.02<P<0.05 -

Total stocks analyzed 59

Total stocks increasing 

significantly 15 25.0%

Total stocks decreasing 

significantlya 3 5.0%

+ = increasing trend with 0.05 > P > 0.01; ++ = increasing trend with 0.01 > P > 0.001; +++ = increasing trend with 0.001 > P; - = decreasing

trend with 0.05 > P > 0.01; and — = decreasing trend with 0.01 > P > 0.001.

a The King Salmon River shows no decline based on survey counts and a significant decline based on weir counts.
87

A high proportion of jacks was observed for many populations. Eleven stocks had 50

percent or more of male escapement samples consisting of age 1.1 and 1.2 males,

including three of four stocks in the Unuk River drainage. Andrew Creek had the

highest proportion of jacks (81 percent) from only 1 year of sampling. Two stocks

had male age distributions dominated by age 1.1 males (Genes Lake Creek, 47 perTable 18—Summary of age distributions of chinook salmon escapement

samplesa b

Males Females

Stream Age classes Age classes

Number Name 1.1 1.2 1.3 1.4 1.5 1.2 1.3 1.4 1.5

No. ---------------Percent--------------- No. ---------------Percent--------------

101-30-030 Keta River 7 0 14 57 29 0 10 0 30 70 0

101-55-040 Blossom River 28 0 43 32 25 0 24 4 50 42 0

101-71-040 Chickamin River 77 11 17 45 23 4 144 1 31 62 5

101-71-04A Barrier Creek 24 4 33 42 21 0 11 0 64 36 0

101-71-04B Butler Creek 37 46 16 30 8 0 45 0 76 24 0

101-71-04I Indian Creek 18 6 44 39 11 0 18 0 61 39 0

101-71-04K South Fork 113 19 49 28 4 0 70 0 49 49 3

101-75-015 Eulachon River 101 18 27 37 17 1 127 0 46 52 2

Unuk River drainage

101-75-30C Clear Creek 145 32 41 19 9 0 93 0 38 61 1

101-75-30G Gene’s Lake Creek 208 47 34 14 4 0 119 3 56 39 2

101-75-30Q Cripple Creek 884 27 46 19 8 0 608 0 42 56 0

108-70-002 Stikine River 74 19 57 12 11 1 22 18 41 41 0

108-40-020 Andrew Creek 170 16 65 14 2 0 14 0 29 57 14

108-80-080 Shakes Creek 23 13 13 57 13 0 26 19 62 19 0

108-80-100 Tahltan River 14 14 7 57 21 0 24 8 75 17 0

108-80-120 Little Tahltan River 600 11 20 27 42 1 722 1 36 60 2

110-14-007 Farragut River 114 11 18 35 27 4 40 3 30 55 13

111-17-010 King Salmon River 140 1 30 43 26 1 119 3 10 79 8

111-32-032 Taku River 1,653 22 42 24 9 0 883 11 49 35 3

111-32-220 Nakina River 43,676 37 40 16 7 0 10,832 0 38 61 1

111-32-240 Kowatua Creek 767 19 18 34 22 3 316 0 26 69 4

111-32-254 Little Tatsamenie 542 15 30 43 9 1 251 3 63 31 2

Lake

111-32-255 Tatsamenie River 536 24 22 30 22 1 291 7 26 69 1

111-32-260 Hackett River 110 28 24 25 24 0 25 4 24 68 4

111-32-270 Nahlin River 1,156 5 25 43 24 2 1,085 1 40 55 1

111-32-275 Tseta Creek 53 2 11 43 19 0 61 2 44 38 3

111-32-280 Dudidontu River 42 2 24 36 36 2 42 0 48 52 0

115-32-068 Tahini River 616 4 31 49 15 1 156 0 33 61 2

182-30-020 Klukshu River 1,330 1 20 57 22 0 967 2 77 21 0

182-70-010 Situk River 18 0 11 6 50 0 33 0 3 67 0

Total mean 15.1 29.1 33.8 18.7 0.7 3.0 43.2 49.5 2.4

Total SE 2.5 2.7 2.6 2.1 0.2 0.9 3.4 3.1 0.7

Total CV 88.7 50.4 43.1 61.3 161.2 168.4 42.5 34.3 152.0

a Percentages may not add to 100 because rare age classes have been omitted and because of rounding.

b Summary statistics calculated from untransformed percentages.
88

cent; Butler Creek, 46 percent). Female age distributions were not strongly skewed

toward younger age classes (table 18). Nonetheless, two stocks had greater than 15

percent of their average female escapement consisting of age 1.2 individuals

(Shakes Creek, 19 percent; Stikine River, 18 percent).

Sex ratio—Most observations of sex ratios were from small samples often taken 

during short periods in the run or from observations during stream surveys. Samples

taken at weirs or fishwheels are considered to be least biased but were available

from only eight stocks. Tahini River samples, taken by gill net, may not be comparable to weir and foot survey samples from other stocks.

Of 30 stocks evaluated, 18 had sex ratios favoring males (table 20); however, 21 of

30 stocks had less than 50 percent males in the 1.3 and 1.4 age classes, which suggested that for those stocks having more males, the increased number was due to

jacks. Four stocks had total sex ratios greater than or equal to four males for every

female (Nakina River, Kowatua Creek, and Hackett River in the Taku drainage and

the Tahini River in the Chilkat drainage). The skewed sex ratios also were present in

Kowatua Creek and Farragut, Hackett, and Tahini River stocks when only the 1.3 and

1.4 age classes were considered. All data from Hackett River and some from

Kowatua Creek were collected at weirs.

Both overall sex ratios and sex ratios of 1.3 and 1.4 age classes differed among

years within stocks. For stocks sampled for several years at weirs or fishwheels, the

coefficient of variation among years for sex ratio (expressed as a percentage of

males) ranged from a low of 9 percent for the King Salmon River to a high of 25 percent for the Little Tahltan River (table 20). For the combined 1.3 and 1.4 age classes,

the range was higher, from 17.4 percent to 29 percent for the King Salmon and Taku

Rivers, respectively. Only the Nakina River stock had a data set spanning enough

years to test for temporal trends in sex ratio. Although no consistent trend was

apparent in the Nakina River sex ratio, available data suggested cyclic fluctuations

with about a 5-year period (fig. 23).

The most complete survey of biochemical or genetic characteristics of chinook

salmon to date is by Gharrett and others (1987), who used gel electrophoresis to

examine variation in 28 loci among chinook salmon from 13 drainages throughout

Alaska. They examined stocks from the Unuk, Farragut, Stikine (mainstem), Little

Tahltan, King Salmon, Taku (mainstem), Nakina, Nahlin, and Tahini Rivers and

Table 19—Regression analyses of trends across years in mean saltwater age of

chinook salmon stocks

Stream Regression

No. years

Number Name Sex sampled R-squared Slope P-value Trend

111-32-220 Nakina River M 19 0.21 0.006 0.05 +

F 19 0.36 0.01 0.01 ++

182-30-020 Klukshu River M 13 0.16 -0.02 0.18 NS

F 13 0.08 -0.02 0.33 NS

+ = increasing trend with 0.05 > P > 0.01; ++ = increasing trend with 0.01 > P > 0.001; and NS = not 

statistically significant.

Genetic Surveys
89

Table 20—Sex ratios of chinook salmon escapement samplesa

Stream Complete sampleb 1.3 age class 1.4 age class 1.3 & 1.4 combined

Number Name Sampling No. Per- Ratio No. Per- Ratio No. Per- Ratio No. Per- Ratio

years cent cent cent cent

male male male male

101-30-030 Keta River 1982, 84 31 19 1:4.26 13 23 1:3.35 17 12 1:7.33 30 18 1:4.71

101-55-040 Blossom River 1985 52 54 1:0.85 21 43 1:1.33 17 41 1:1.44 38 42 1:1.38

101-71-040 Chickamin 1985, 89 221 35 1:1.86 79 44 1:1.27 106 16 1:5.25 185 30 1:2.33

River

101-71-04A Barrier Creek 1986 35 69 1:0.45 17 59 1:0.69 9 56 1:0.79 26 58 1:0.74

101-71-04B Butler Creek 1986, 87 82 45 1:1.22 45 24 1:3.17 14 21 1:3.76 59 23 1:3.35

101-71-04I Indian Creek 1987 36 50 1:1.00 18 39 1:1.56 9 22 1:3.55 27 31 1:2.28

101-71-04S Chickamin 1987 183 62 1:0.61 66 48 1:1.08 39 3 1:6.70 105 31 1:2.28

River 

(South Fork)

101-75-015 Eulachon River 1986, 87, 89 228 44 1:1.27 96 39 1:1.56 84 21 1:3.76 180 30 1:2.33

101-75-30C Clear Creek 1986, 87, 89 238 61 1:0.64 62 44 1:1.27 70 19 1:4.26 132 32 1:2.17

101-75-30G Genes Lake 1984-87, 89 327 64 1:0.56 97 31 1:2.23 56 16 1:5.25 153 24 1:3.17

Creek

101-75-30Q Cripple Creek 1984-87, 89 1,492 59 1:0.69 422 39 1:1.56 412 17 1:4.88 834 28 1:2.57

108-40-015 Stikine River 1982-85 125 77 1:0.30 21 52 1:0.92 25 56 1:0.79 46 54 1:0.85

108-40-020 Andrew Creek 1982-84 657 57 1:0.75 158 50 1:1.00 284 33 1:2.03 442 42 1:1.41

108-80-080 Shakes Creek 1983 49 47 1:1.13 29 45 1:1.22 8 38 1:1.63 37 42 1:1.41

108-80-100 Tahltan River 1982-84 217 42 1:1.38 51 45 1:1.22 148 40 1:1.50 199 43 1:1.35

108-80-120 Little Tahltan 1982-87 1,496 45 1:1.22 407 47 1:1.13 858 33 1:2.03 1,265 40 1:1.50

River

110-14-007 Farragut River 1983-85 154 74 1:0.35 52 77 1:0.30 53 58 1:0.72 105 68 1:0.47

111-17-010 King Salmon 1983-87 259 54 1:0.85 72 83 1:0.20 130 28 1:2.57 202 56 1:0.80

River

111-32-032 Taku River 1983-87, 89, 2,536 65 1:0.65 826 48 1:1.08 457 32 1:2.13 1,283 42 1:1.38

90

111-32-220 Nakina River 1956-59, 5,450 80 1:0.25 1,115 70 1:0.43 9,516 31 1:2.23 2,066 51 1:0.96

73-81

83-87, 89 8 3 9

111-32-240 Kowatua Creek 1983, 89, 90 1,083 80 1:0.25 345 76 1:0.31 387 44 1:1.27 732 59 1:0.69

111-32-254 Little Tatsamenie 1985, 89 879 67 1:0.49 455 59 1:0.69 146 38 1:1.63 601 49 1:1.00

Lake

111-32-255 Tatsamenie 1983-85 827 65 1:0.54 236 68 1:0.47 320 38 1:1.63 556 50 1:2.03

River

111-32-260 Hackett River 1985-86 135 81 1:0.23 33 82 1:0.22 43 60 1:0.67 76 71 1:0.41

111-32-270 Nahlin River 1983-86, 88, 2,241 52 1:0.92 924 53 1:0.89 882 32 1:2.13 1,806 43 1:1.35

89

111-32-280 Dudidontu 1990 84 50 1:1.00 35 43 1:1.33 37 41 1:1.44 72 42 1:1.41

River

111-32-275 Tseta Creek 1983, 89 114 46 1:1.17 50 46 1:1.17 33 30 1:2.33 83 38 1:1.63

115-32-068 Tahini River 1983-87, 772 80 1:0.25 353 85 1:0.18 185 49 1:1.04 538 67 1:0.49

89-90

182-30-020 Klukshu River 1983, 85-87 802 47 1:1.13 543 40 1:1.50 173 48 1:1.08 716 44 1:1.27

182-70-010 Situk River 1985, 88 57 35 1:1.86 4 50 1:1.00 31 29 1:2.45 35 40 1:1.53

a Complete sample size includes all age classes for all years.

b Data derived from escapement age or length samples; the larger of these samples is presented here.
90

Andrew and King Salmon (Taku drainage) Creeks from southeast Alaska. The stocks

from southeast Alaska showed greater genetic divergence than stocks from western

Alaska. The Tahini River stock was most divergent from other stocks in southeast

Alaska, and based on cluster analysis, branched from stocks from southern British

Columbia and Washington (Gharrett and others 1987). Significant allelic heterogeneity also was found between the Andrew Creek stock in the lower Stikine and the Little

Tahltan stock in the upper Stikine, indicating that genetic divergence had occurred

within the Stikine drainage (Gharrett and others 1987). No significant temporal 

heterogeneity was found within stocks among years.

Anecdotal reports about chinook stocks deal primarily with the historic presence of

chinook stocks that are currently of unknown status and potentially distinctive characteristics of chinook stocks in addition to those evaluated above. Most anecdotal

reports are from brief mentions of chinook stocks in unpublished reports or from 

discussions with fisheries biologists. Possible extinctions of chinook populations

have been reported for the Muddy, Nakwasina, and Black Rivers and for Big Goose

and Greens Creeks (Holland and others 1983). All these, except the Muddy River,

are island drainages. Recent surveys of Greens Creek indicate that a few wild chinook have recolonized and spawned successfully in this drainage (see footnote 8).

Chinook salmon were consistently counted at the USBF weir on Anan Creek from

Figure 23—Temporal variation in sex ratio of the Nakina River stock, which has the

longest time series in the region. Data were collected at a carcass weir. Both total sex

ratio and the sex ratio of combined nonprecocious age classes appear to oscillate with a

frequency of about 5 years. The causes and consequences of this apparent pattern are

unknown.

Anecdotal Reports

10 Personal communication. 1996. W. Heard, program manager,

National Marine Fisheries Service, Auke Bay Laboratory, 11305

Glacier Highway, Juneau, AK 99801.

11 Personal communication. 1996. A. Moles, fishery biologist,

National Marine Fisheries Service, Auke Bay Laboratory, 11305

Glacier Highway, Juneau, AK 99801.
91

1925 to 1932 (Rosier and others 1965). The mean escapement of chinook salmon

during this period was 62 fish. We found no subsequent surveys or records of 

chinook salmon in this system. Two Alaska populations are infected with IHNV, the

Situk and the Karluk River stocks.10 11 The Situk chinook also have been reported to

have particularly red spawning coloration (see footnote 2). King Salmon River 

chinook return to the river in ripe condition and spawn soon after entering fresh water

and may spawn in tidally influenced areas (see footnote 2).

Northern and southern stock groups show the clearest differences in biological characteristics of chinook salmon in southeast Alaska. These groups differ most strongly

in body length, but they also differ in MSWA, run timing, and oceanic migration patterns. Differences between mainland and island drainages may be important also;

but data on biological characteristics of island stocks are available only from the King

Salmon River. This stock has early run timing and also has the unusual characteristics of arriving at fresh water in nearly ripe condition and spawning in tidally influenced portions of the river (Kissner 1975; see footnote 2). Both characteristics are

unusual for chinook salmon. If the unusual characteristics of the King Salmon River

stock represent heritable responses to environmental factors found in an island

drainage, then this island stock, as well as others, may represent valuable elements

of genetic diversity in the region.

The chinook salmon stocks in the Yakutat Forelands, which include the Situk, Akwe,

and Italio Rivers, are probably the most distinctive stocks in the region owing to the

large proportion of smolts that emigrate at age-0. Chinook salmon in southeast

Alaska are predominantly stream-type stocks having a small proportion of individuals

that emigrate as age-0 smolts (based on readings of adult scales). Up to 98 percent

of Situk smolts emigrate from fresh water in the same year as emergence occurs

(Johnson and others 1992b). The chinook stock in the Deshka River in south-central

Alaska is the only other Alaska population in which a large proportion of juveniles 

outmigrate at age-0 (Delaney and others 1982); however, in the Deshka system emigrating juveniles may rear for a year in the mainstem Susitna River (see footnote 2).

Early emergence and a long growing season are the environmental factors likely

enabling Situk chinook to reach a size adequate for adaptation to seawater as age-0

fish. Taylor (1990) suggests that geographic differences in “growth opportunity” drove

the disruptive selection that led to the development of stream- and ocean-type life 

histories. Outlier analysis of YOY fork lengths indicated that Situk River YOY were 

distinctively large. The Situk stock was also unusual in having (1) an ocean-type juvenile life history pattern and stream-type run and spawning timing (Johnson and others

1992b), (2) endemic infection with IHNV (see footnotes 10 and 11), and (3) spawning

coloration of a deeper, brighter red than the norm (see footnote 2). The presence of

IHNV may be a consequence of spawning in unusually close association with large

numbers of sockeye salmon, which generally carry this virus (see footnote 2). Bright

red coloration is not characteristic of ocean-type stocks and may represent a specialized local adaptation of the Situk stock.

Biological and demographic data for most small populations of chinook salmon are

limited, and several of these small populations are geographically isolated. Even

though the economic significance of small stocks may not be large, some of their 

distinct characteristics, such as those of the King Salmon River stock, may represent

genetic divergence from larger mainland stocks, but this is speculative at present.

Discussion
92

Body length—Chinook stocks from the southern region had greater body lengths

than stocks in the northern region, but this result does not correspond to a general

latitudinal trend throughout the range of chinook salmon in North America (Roni and

Quinn 1995). Among North American stocks of chinook salmon, only the body

lengths of age 1.3 males were negatively correlated with latitude, but no latitudinal

trends were apparent for other age and sex classes (Roni and Quinn 1995). When

population mean lengths that included all age classes were evaluated, a positive 

correlation between length and latitude was present for females, but no relation was

apparent for males (Roni and Quinn 1995). Those authors also found significant 

negative relations between body size and migration distance for some age and sex

classes, but this was not consistent.

The regional pattern of body lengths we observed may reflect differences in marine

migration patterns and the combined influences of latitude and freshwater migration

distance. Southern stocks spend more time during their ocean life in near-shore

waters, which tend to be more productive but where fish may have greater risk of 

predation than in the Gulf of Alaska where northern interior-spawning stocks spend

most of their ocean life. These factors may contribute to more rapid growth in southern stocks (in addition to greater body length, southern stocks have lower MSWAs 

for both sexes, which suggests that rate of growth is more rapid). Following from the

hypothesized association between migration pattern and body size, if freshwater 

mortality rates are similar, we predict that spawner-recruit ratios in southern stocks

should tend to be lower than in northern stocks that have a less “risky” marine life 

history. We could not investigate statistically the interaction of latitude and migration

distance because all southern stocks have short coastal migrations. However, interaction effects may be important because the majority of northern stocks in our analyses spawned in interior drainages. 

Differences in lengths occurred between male and female chinook but lengths of

each sex were generally correlated within stocks. This relation may be a result of

selection by environmental factors for certain optimal body sizes in different habitats

(Taylor and McPhail 1985). Some environmental selection pressures on body size,

such as migration length and stream gradient, should operate similarly for both

sexes. 

Sexual dimorphism during marine residence reverses between the 1.3 and 1.4 age

classes; age 1.3 females are 37 mm longer than males, but age 1.4 males are 36

mm longer than females on average. The pattern of length dimorphism is consistent

among most stocks in the region, as is the tendency for higher proportions of males

to return at age 1.3 rather than at age 1.4. Males and females feeding in the ocean

may have different size or condition thresholds that trigger the onset of maturation

and return migration. Female thresholds may be higher because females produce

more energetically expensive gametes than males, high fecundity is required to have

any probability of successful reproduction, and female fecundity is correlated with

body size. Females with slow growth that do not achieve the required threshold for

return at age 1.3 remain at sea for an additional year of feeding. The growth increment achieved by these females during the additional ocean year may be less than

that achieved by males owing to higher investment of energy in eggs. In combination, these factors suggest that the tradeoffs between the fitness benefits of increased

Evaluation of Results
93

size and the risks of mortality imposed by an additional year at sea are different for

age 1.3 and 1.4 male and female chinook salmon. The selective mechanisms underlying these differences are likely to include the potential for males, but not females, to

pursue noncompetitive reproductive strategies and the advantages of large female

body size in terms of redd construction and defense (see Healey and Heard 1984).

Variance component analysis indicated that female chinook salmon show a higher

level of stock-specific variation in body length than any other species of Pacific

salmon in the region. Only three stocks were included in this analysis, which raises

the possibility that stocks with an unrepresentative level of divergence were included.

However, results for male chinook do not support this explanation because a very low

level of among stock variation was found for males. An evolutionary explanation for

the observed pattern is that spawning females face stronger selection for local 

adaptation in body size owing to habitat characteristics affecting successful redd 

construction, such as substrate particle size, average scour depth, and the need to

defend the redd from excavation by other females. Local adaptation in body length

has occurred in about 20 generations (roughly 100 years) among several chinook

salmon stocks in New Zealand descended from a common founder stock (Quinn and

Unwin 1993). These authors did not evaluate male and female lengths independently,

however.

The YOY fork lengths of the Situk River stock and the juvenile fork lengths of Tahini

River stock (Chilkat drainage) were larger than other stocks. The YOY from the

Tahini River had a mean fork length of 73.4 mm based on samples collected from

early August to early October 1990, but presmolts measured in the mainstem Chilkat

in April 1990 had a mean fork length of 67.4 mm (Pahlke 1991b). The 95-percent

confidence intervals for both samples do not overlap. The Tahini River provides

spawning habitat for about 33 percent of the total Chilkat chinook run (Johnson and

others 1992a). The Kelsall River, the other major source of Chilkat smolts (54 percent of the Chilkat run), also produces large YOY (1990 mean of 70.3 mm). Because

these two stocks should contribute the majority of smolts sampled in the lower

Chilkat, we would not expect the mean body size of presmolts caught in the mainstem Chilkat in spring to be smaller than that of those captured during the previous

fall. Other than sampling error, possible explanations include (1) Tahini and Kelsall

juveniles may not have begun outmigrating and may not have been present in the

mainstem Chilkat during presmolt sampling (see footnote 2), (2) a large interannual

variation in juvenile growth rates (Pahlke 1991b), and (3) some part of the largest

Tahini River chinook juveniles may migrate into Lynn Canal without spending a winter

in fresh water. The accepted size at which juvenile chinook can tolerate seawater is

70 mm (Weisbart 1967). This speculative possibility is circumstantially supported by

the genetic similarity of Chilkat chinook to ocean-type stocks in Washington (Gharrett

and others 1987), but it is not supported by the physical characteristics of Tahini

River YOY or by age data from returning individuals; however, Johnson and others

(1992b) question the reliability of scale aging data for detecting age-0 chinook smolts.

Timing—Chinook salmon in northern latitudes tend to spawn earlier than those in

southern latitudes (Healey 1991). Chinook stocks in southeast Alaska conformed to

this trend. Stocks in northern southeast Alaska had a mean survey index date that

was about a week earlier than stocks in southern southeast Alaska. Across the
94

region, peak escapement counts for chinook salmon typically occurred from the last

week in July to late August. Earlier spawning may be related to water temperature

and egg and embryo development time, with longer development time required 

in increasingly cold environments.

The low level of variation among years in mean dates of migration past weirs may be

related to stable temperature regimes of larger watersheds. The influence of temperature regime on run timing is likely through incubation and development schedules of

eggs (Brannon 1987). Miller and Brannon (1982) propose a general model of salmonid life history evolution that suggests temperature regimes may be responsible for

ecological isolation of stocks. In accord with this model, Burger and others (1985)

hypothesize that strong selection generated by predictable thermal regimes has critically adjusted timing of spawning runs in the Kenai River drainage. If the riverine

habitats used for spawning by chinook salmon in southeast Alaska also have relatively low levels of interannual variation in temperature regime, then consistent thermal

regimes could indirectly select for consistent run timing that optimizes timing of hatching or emergence. Time of hatching may be critical if redds are consistently at risk of

flood or ice scour; late-hatching eggs suffer increased mortality because redds are

disrupted before the alevins can burrow more deeply into the gravel. As do other

species of Pacific salmon, chinook salmon show plasticity in development rate in

response to temperature changes (Beacham and Murray 1990), but the relative

amount of plasticity present among different species is not known.

Escapement—Analysis of escapement trends showed that 25 percent of all chinook

stocks evaluated were increasing, but many stocks may have been depleted before

1960, the earliest date for which stock-specific escapement data were available. 

As a result, population estimates after 1960 may not provide a sound biological basis

for evaluating historical abundance. A result that indicates no significant change 

from 1960 to 1993 may reflect either a healthy, stable population or a persistently

depressed population. The trends for many stocks appear to be either bell- or Ushaped, but data series were too short to permit nonlinear analysis of trends. The

stocks in the Blossom River and several tributaries in the Chickamin system showed

pronounced bell-shaped escapement patterns.

North Arm Creek (Stikine drainage), Big Boulder Creek (Chilkat drainage), and King

Salmon River were the only three stocks showing significantly declining trends. 

North Arm and Big Boulder stocks were represented by at least 20 years of surveys 

between 1960 and 1993, but because of inconsistencies among years in survey

methods, timing, and distance, data quality for both systems was rated as fair. For

the King Salmon River, data from 24 escapement survey counts were considered

good, and yielded a stable regression outcome; 9 years of weir counts from 1983 to

1991 indicated a significant decline. Because data from weir counts are generally

more reliable than data from helicopter surveys, and because of the distinctive 

nature of the King Salmon River stock, we considered this stock to have a significant

decline. Possible causes of declines in the North Arm Creek are unknown.

Potentially adverse impacts on the Big Boulder stock included hydrologic changes in

the adjoining Klehini River and road-building activities, which temporarily disrupted

spawning gravel (Mecum and Kissner 1989). The combination of adverse natural

conditions and human-caused disturbance may have contributed to the decline of this

stock. The Big Boulder stock historically has shown high variability in escapement

Demography
95

counts. The high variation may reflect a combination of environmental instability and

the tendency of spawners to arrive in groups that have a brief residence time in this

short, swift tributary (see footnote 3). Ongoing enhancement efforts in the form of fry

outplants and a streamside incubation box may help to rebuild this stock. Decline in

the King Salmon River stock may be associated with weir operations, including egg

takes, as well as increased sport catches.

Age structure—Although age structure of chinook stocks was based on small sample sizes and inconsistent sampling methods, some general patterns were apparent.

For nearly all stocks in the region, male MSWA was less than female MSWA, if age

classes 1.1 and 1.2 were excluded from the analysis. Significant differences between

the nonjack MSWA of males and females probably reflects differences in life-history

tradeoffs, as discussed above.

For the two stocks with long-time series of age data, regression analysis did not

reveal any consistent trends in MSWA across years, but decreasing size and age

trends are documented for chinook salmon caught in southeast Alaska troll fisheries

(Ricker 1980, 1981) and sport fisheries (Fagen 1988).

Sex ratio—Overall escapement sex ratios are expected to favor males in chinook

salmon because jacks should survive better than adult females.12 One cause of differential mortality may be selective removal by fisheries governed by a minimum total

length limit, such as the 28-inch (about 700-mm) limit for southeast Alaska commercial troll, terminal gill-net, and sport fisheries. The effects and importance of this 

artificial selection on sex ratios are unknown because the sex ratio of fish caught in

commercial and sport fisheries is not known, and the effects of size-selective fisheries on populations often are not straightforward (see Miller and Kapuscinski 1994).

Differential mortality associated with differing maturation patterns cannot account for

male-biased sex ratios in specific nonprecocious age classes. The sex ratio of age

1.3 and 1.4 individuals from escapements was strongly biased in favor of males in 

the Farragut River, Hackett River, Kowatua Creek, and Tahini River in northern southeast Alaska. These uneven sex ratios may be the result of biased sampling procedures (see footnotes 2 and 9). For example, estimates derived from “carcass weirs”

that capture moribund fish drifting downstream tend to be biased toward males

(McPherson and others 1997). 

Holtby and Healey (1990) propose that male-biased sex ratios in salmonid populations may be the result of increased susceptibility of females to predation. Holtby and

Healey (1990) suggest that differential female mortality for coho salmon is a consequence of more risky foraging tactics necessitated by sex-specific constraints on

reproductive size. Fishing mortality also may contribute to biases in age-specific

escapement sex ratios, but the relation between susceptibility to natural predation

and susceptibility to fisheries is unclear.

12 Personal communication. 1996. D. Eggers, chief fisheries 

scientist, Alaska Department of Fish and Game, 1255 W. 8th

Street, Juneau, AK 99801.
96

Fecundity—In general, chinook are characterized by high levels of variation in fecundity at both intrapopulation and interpopulation levels (Healey and Heard 1984), but

few data were available for stocks from southeast Alaska. The data available for

southeast Alaska stocks agreed with the overall positive relation between fecundity

and latitude plotted by Healey (1991). This relation reflects the generally higher

fecundity of stream-type stocks relative to ocean-type stocks.

Several important aspects of chinook life history were identified through anecdotal

reports; presence and prevalence of parasites, spawning behavior, freshwater rearing

ecology, ocean distribution, straying patterns, and flesh color could not be reviewed 

at a stock-specific level because of a lack of information. Although these observations could be useful for identifying distinctive stocks, they have not been examined

systematically to determine their significance to the freshwater ecology and evolutionary biology of chinook stocks. 

Decreasing body size and age—Decreasing body size and an increase in the number of jacks may be interrelated, and these two characteristics may have genetic and

evolutionary consequences. Decreasing size and age may be the result of increasing

exploitation rates. Using data from the southeast Alaska troll fishery, Ricker (1980)

found a significant decrease in weight of chinook (r = -0.560, P < 0.05, yielding a

mean rate of decrease of 0.14 kg/yr) between 1960 and 1974. Ricker evaluates a

series of alternative hypotheses for this decline and argues that artificial selection by

fisheries, especially troll fisheries, changed the genetic basis for maturation of chinook at older ages, which results in an earlier maturation and a reduction in adult

size. Intense artificial selection in past decades, especially by gill nets targeting large

fish, may have changed the equilibrium ratios of jack- and adult-type spawners in

many of southeast Alaska's chinook stocks (see Gross 1991; Kissner 1975, 1976).

Ongoing low levels of artificial selection may be sufficient to maintain these altered

age-structure equilibria, thereby counteracting natural selection favoring preexploitation ratios.

Because some southeast Alaska chinook stocks may spend long periods of their

ocean life in near-shore waters, they are susceptible to fisheries for extended times.

No accurate estimates of exploitation rates of chinook in southeast Alaska are available for years before the current rebuilding program. Since the mid-1970s, exploitation rates on chinook stocks from southeast Alaska have typically been less than 40

percent, although exploitation estimates for some stocks from southern southeast

Alaska have occasionally been as high as 69 percent (Pahlke and Mecum 1990).

The results of our regression analyses indicated that a trend toward decreasing size

may be occurring in several southeast Alaska stocks, but only one stock showed a

significant trend (Cripple Creek, a Unuk River stock that may spend extended periods

in coastal waters). Our analyses were conducted on short time-series, and all data

were collected subsequent to the rebuilding program that represented a relaxation of

artificial selection from fisheries. Fagen (1988), using more extensive datasets and

more sophisticated analytical techniques, also found declining trends in chinook body

size in two of four southeast Alaska sport fisheries.

In southeast Alaska, high rates of jacks occur in many stocks (Hard and others 1985,

Kissner 1975). Experimental crosses of chinook salmon from the Elk River hatchery

in Oregon demonstrated high heritability of age of maturity in this stock, (estimates 

of heritability [h2

] ranged from 0.49 to 0.57 for males and 0.39 to 0.41 for females;

Conceptual Issues
97

Hankin and others 1993). Hankin and others (1993) tentatively propose that the 

heritable mechanism underlying variation in age at maturity is variation in minimum

threshold sizes necessary to trigger maturation. Wild populations of chinook salmon

introduced to New Zealand have diverged in age at maturity, both among and within

drainages, in roughly 20 generations, indicating relatively rapid response to environmental selection pressures (Quinn and Unwin 1993). Thus, increases in the proportion of jacks in a population also could contribute to size declines in all age classes

by reducing the frequency in the population of alleles that contribute to larger size

thresholds for maturation.

The biological significance of declining body size and increasing numbers of jacks

may lie in their effects on reproductive success (Roni and Quinn 1995). In coho

salmon, there is a positive correlation between female body size and redd depth 

(van den Berghe and Gross 1984). Redd depth may be locally adjusted by selection

imposed by redd superimposition or scouring from floods (Hankin and McKelvey

1985), and smaller body sizes could lead to higher egg losses. In chum salmon, a

strong positive relation exists between adult body size and survival of juveniles (Helle

1979). Although no comparable data are available for chinook salmon, the possibility

of a similar relation may exist for chinook. If this is the case, then the decline in adult

chinook body size may decrease reproductive success.

Increased proportions of jacks also may have consequences in mate selection and

productivity. Baxter (1991) found that larger male chinook salmon have greater

spawning success than small males, and that female chinook salmon display significantly more courting behavior to equal-sized or larger males and more aggressive

behavior toward smaller males. In three other studies investigating patterns of mate

selection in Pacific salmon, one each for sockeye (Hanson and Smith 1967), chum

(Schroder 1981), and pink salmon (Keenleyside and Dupuis 1988), spawning females

preferred to mate with males of similar or larger body size. In chum salmon, redd

construction by females was prolonged when males were smaller than females

(Schroder 1981). Females also might express their preference in the number of eggs

laid in a spawning bout (Brown 1981). A net decline in productivity of a population

could result from female spawning with less preferred males, but female mate-choice

behavior may select for large body size, counteracting artificial selection by fisheries

that favors small body size (Baxter 1991).

Precocious parr—The occurrence of precocious parr has been reported for the

Nahlin River stock, a headwater tributary of the Taku River13 (also see footnote 2).

These fish were less than 100 mm in fork length and expressed milt when handled

for tagging purposes. The occurrence of this form of extremely precocious maturation has been documented previously in stream-type stocks in headwater tributaries

(Burck 1967, Foote and others 1991, Gebhards 1960, Rich 1920, Robertson 1957,

Taylor 1989). Fifty-six percent of hatchery-reared chinook salmon from the Nicola

River (British Columbia) matured as parr (Foote and others 1991). Taylor (1989)

raised juvenile chinook salmon from several British Columbia stocks in a common

laboratory environment and found that stocks that spawned in interior drainages

showed a higher propensity for precocious maturation than coastal stocks, suggesting a genetic component to this trait.

13 Personal communication. 1996. L. Shaul, fisheries biologist,

Alaska Department of Fish and Game, 802 3d Street, Douglas, AK

99824.
98

Maturing parr had more rapid rates of overall weight gain in early spring than nonmaturing fish, but this pattern reversed in late spring when the precocious parr began to

show a rapid increase in gonad weight (Foote and others 1991). Gonad weight of

precocious males in July accounted for 8 percent of average body weight, compared

to 0.005 percent for nonmaturing males (Foote and others 1991). Furthermore, precocious parr showed declining seawater adaptability during spring when nonmaturing

individuals were reaching the peak of their seawater tolerance (Foote and others

1991), but experiments were not continued to determine if precocious parr regained

their ability to adapt to seawater. Gebhards (1960) suggested that precocious parr in

an Idaho population emigrated to sea the year after achieving sexual maturity. In

Atlantic salmon, some precocious parr reabsorb gonadal tissue and migrate to sea

the year after initial maturation and later return as full-sized adults (Lundqvist and

others 1988). Chinook salmon are semelparous, however, and Kissner (see footnote

2) has noted dead precocious parr during spawning ground surveys of the Nahlin

River. The high proportion of body weight devoted to gonads and low adaptability to

seawater of chinook precocious parr suggest these individuals probably never go to

sea. The proportion of males in the Nahlin stock that mature as precocious parr, their 

contribution to reproduction, and the proportion of other stocks in southeast Alaska in

which this maturation pattern occurs are unknown.

Relative to other species of Pacific salmon in the region, the large body size, small

population size, and restricted habitat-use characteristics of chinook salmon render

them more susceptible to endangerment or local extinction. In the Pacific Northwest,

64 populations of chinook salmon are considered at risk of extinction, more than any

other species (Nehlsen and others 1991). From the perspective of managing chinook

salmon diversity in southeast Alaska, a risk for minor chinook stocks in the region is 

a general lack of information. Some of these small populations have highly variable

escapements and are subject to exploitation in mixed-stock fisheries. These populations, when faced with additional factors that generally reduce survival rates, such as

declining ocean productivity, may suffer disproportionately severe declines in abundance. Because the status of some of these populations is not monitored regularly,

declines could go unnoticed for several years, thereby increasing the probability that 

stochastic events could extirpate these small stocks. In southeast Alaska, the lack of

human disturbance in most watersheds that support chinook salmon provides a margin of safety.

Thermal regimes, silt loads, and flood intensity of rivers may be the most significant

habitat features affecting chinook salmon productivity. The thermal environment of

spawning areas may play an important role in the local adaptation of Pacific salmon 

stocks (Burger and others 1985, Miller and Brannon 1982, Taylor 1990). Changes to

thermal regimes may alter development and fry emergence times, which in turn may

adversely affect fry survival (Burger and others 1985). Increased water temperatures

also can contribute to rapid progression of infections and higher than average mortality rates from disease (Fryer and Pilcher 1974). Increased siltation may reduce pool

depths and fill interstitial spaces in gravel, which will reduce both living space and

invertebrate production. Hillman and others (1987) found significantly higher densities of juvenile chinook in areas where cobble substrate was added to a streambed

heavily embedded with fine sediment. Lloyd and others (1987) review the generally

negative effects of increasing turbidity, which is correlated with suspended sediments,

on all life history stages of salmonids in Alaska waters. Rapid siltation from natural

processes has changed the structure of Dry Bay in recent decades (Gmelch 1982).

Risk Factors

Habitat Factors
99

These changes may have reduced the capacity of the lower Alsek and Dry Bay to

serve as rearing habitat for juvenile chinook (Mecum and Kissner 1989). Floods can

have both positive and negative effects on salmon habitats. Negative effects include

scouring spawning gravels and creating debris jams that can impede salmon migration, while benefits can include the creation of new rearing or overwintering habitat

(Swanston 1991). Few debris jams are actual blocks to migration and more often

contribute to habitat complexity and increase rearing habitat (Bisson and others

1987).

Landslides can be of natural origin or the result of management activities (i.e., road

failure, logging) and move inorganic (sediment) and organic material into rivers and

streams. Obvious negative effects include increased siltation and, in extreme cases,

blocks to migration. Both the Dudidontu River in the Taku drainage and the Little

Tahltan River in the Stikine drainage have experienced serious blockages from 

landslides in the last 30 years. Both blockages cleared and chinook populations

recovered, but recovery depended on downstream recruitment or recruitment from

subbasins within the larger watersheds. In smaller watersheds, such as the King

Salmon River, the consequences of a blockage from a landslide, either natural or

human-caused, may be more severe and threaten the existence of the stock.

At various points during the Pleistocene, glaciers blocked large rivers in Alaska, and

about 10,000 years BP, the Copper River was blocked by a glacier (Ferrians and

Nichols 1955). More recently, the Hubbard Glacier has had the potential to dam

Russell Fjord, which would inundate the present Situk River basin and dramatically

alter the physical characteristics of the river (Thedinga and others 1993). Although

the actual effects are mostly speculative, the changes likely would reduce the area of

spawning and rearing habitat (Thedinga and others 1993). These changes would

alter the demographic structure of the chinook population in the Situk River basin.

Glacial movements that could block the main channels of the Taku and Alsek Rivers

also represent potential risk factors to the many chinook salmon populations in those

drainages.

Logging and mining are the human activities having the most widespread potential for

adversely affecting temperature regimes, silt loads, and flood intensity of habitats

used by chinook salmon in the region. The effects on aquatic environments are

reviewed by Chamberlin and others (1991), Meehan (1991), and Nelson and others

(1991). Anecdotal reports suggest that aggressive logging in the Bradfield River

drainage during the 1950s may have contributed to a temporary decline in chinook

stocks in this drainage.1415 Illegal fishing practices also may have been a contributing

factor16 (Moberly and Kaill 1977).

14 Personal communication. 1996. F. Everest, research fisheries

biologist, U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station; located at Tongass-Chatham Area,

204 Siginaka Way, Sitka, AK 99835.

15 Personal communication. 1996. C. Casipit, regional fisheries 

program leader, U.S. Department of Agriculture, Forest Service,

Tongass National Forest, Regional Office, P.O. Box 21628,

Juneau, AK 99801.

16 Personal communication. 1996. A. Kimbell, forest supervisor,

U.S. Department of Agriculture, Forest Service, Tongass National

Forest, Stikine Area, P.O. Box 309, Petersburg, AK 99833.
100

Chinook salmon have high economic value in both commercial and sport fisheries,

which tend to be mixed-stock fisheries in southeast Alaska. The economic value of

chinook to the commercial fishery and their popularity in the sport fishery creates a

high demand that can lead to overexploitation, particularly for stocks with small

escapements, such as those in King Salmon River on Admiralty Island, in mixedstock fisheries. Since 1985, all-gear catch ceilings have been regulated by the

US/Canada Pacific Salmon Treaty, and escapement goals have been set by ADF&G

as part of their program to rebuild chinook salmon stocks. The result has been

exploitation rates on the major index streams that range from 10 to 24 percent for the

Unuk River to 40 to 65 percent for the Situk River stocks (Pahlke 1995; see footnote

9). Although these studies address larger and more economically important stocks,

smaller runs are assumed to follow the same patterns of exploitation.

Migration pathways and marine residence patterns can affect exploitation rates.

Stocks exposed to both sport and commercial fisheries for prolonged periods, such

as those in southern southeast Alaska, have an increased potential for overexploitation. The greatest potential risk is to small stocks, which are neither monitored nor

consistently sampled. These stocks may require stock-specific protective measures

or enhancement programs.

Overexploitation risks posed by enhancement activities for chinook salmon result 

primarily from having hatcheries and release sites along the migration pathways of

wild stocks. The hatchery add-on provision, which allows ceilings on the annual

allowable catch imposed by the Pacific Salmon Treaty to be exceeded by harvesting

fish produced through enhancement activities (Denton and Holland 1986), may be a

possible risk factor, if hatchery fish are not readily identified in the fishery.

About 85 chinook salmon stocks in the region occur in large river habitats in mainland

drainages. All but the Situk River and Yakutat Foreland stocks have stream-type life

histories. The Situk River is small and its chinook salmon stock has an ocean-type

juvenile rearing life history but stream-type adult migration and spawning timing.

Currently only three wild stocks occur in island drainages, and these are found on

north Admiralty Island (Wheeler and Greens Creeks and King Salmon River). The

Carroll Creek stock on Revillagigedo Island was established through stocking. Island

populations tend to be small. The largest chinook salmon stocks spawn in interior

clearwater tributaries of the Stikine, Taku, and Alsek Rivers.

Analyses of biological characteristics were based on a sample of 32 stocks from

major and medium producing drainages and 7 stocks from smaller producing

drainages. Thirty stocks were represented by samples of adult lengths and ages, 

and 58 stocks had adult migration timing indices. The group of chinook stocks found

south of the Stikine River had greater mideye-to-fork lengths, lower MSWA, and later

run-timing index dates than the group of stocks from northern southeast Alaska.

Variance-component analysis indicated that over 90 percent of total variation in male

body length, but only 45 percent of female body length variation, was attributable to

differences among individuals within the three stocks evaluated. Among females,

variation among stocks accounted for 53 percent of the total variation observed,

thereby suggesting a higher level of stock-specific specialization in female chinook

than in any other species of Pacific salmon analyzed by this method. Adult body

sizes of southeast Alaska chinook stocks have tended to decrease through time.

Fishing Pressure

Conclusions 
101

Run-timing statistics from weirs indicated that chinook stocks are generally consistent

among years in mean date of return, another unusual characteristic among species of

Pacific salmon in the region. Several stocks in the region seemed to have high proportions of jacks or few females in escapements, but these results may have been

artifacts of biased sampling. Tagging returns indicated that some stocks from the

Chickamin and Unuk Rivers in the south, Andrew Creek in the Stikine watershed, 

and King Salmon and Chilkat Rivers in the north may spend prolonged periods of

their ocean life in near-shore waters (see footnote 4).

The following stocks had distinctive characteristics based on the most reliable data

(see fig. 24 for approximate locations):

• Situk River (and Yakutat Foreland rivers)—Ocean-type juvenile life history (Johnson

and others 1992b), and early-run timing; also the only stock in the region infected

with IHNV. Anecdotal reports of unusual spawning coloration. Potentially threatened by flooding from Russel Fjord. 

• King Salmon River—Inhabits an island drainage and has distinctively early run 

timing. Anecdotal reports that this stock enters fresh water in ripe condition and

that some spawning occurs in tidally influenced areas.

• Wheeler and Greens Creeks—Not well studied, but inhabit island drainages.

• Tahini River—Unusual allozyme frequencies indicating a relation with chinook

stocks from southern British Columbia and Washington. Limited data suggest this

stock produces distinctively large YOY and that this stock may feed for prolonged

periods in Lynn Canal and Icy Strait.

The following stocks showed distinctive characteristics based on limited sampling.

These results should be considered preliminary:

• Keta River—Unusual pattern of sexual dimorphism based on small samples.

• Barrier Creek—Extreme level of sexual dimorphism in age 1.3 individuals.

• Indian Creek (Chickamin River)—Extreme level of sexual dimorphism in age 1.4

individuals.

• Chuck River—Early run timing (based on index dates) at the regional level, but not

distinctive within the northern stock group.

• Nahlin River—Early run timing (based on index dates) at the regional level, but not

distinctive within the northern stock group.

Escapement survey estimates of abundance were made from 59 stocks. Of the 59

stocks analyzed for escapement trends, 15 (25 percent) were increasing significantly

and 3 (5 percent; North Arm Creek, Big Boulder Creek, and King Salmon River) were

declining significantly (see fig. 25 for approximate geographic locations). The apparent decline in the North Arm Creek stock may have been the result of an erroneously

high count in 1962. The King Salmon River stock showed a significant decline based

on weir counts but was stable based on surveys. Increasing stocks were clustered 

in the Boca de Quadra and in the Taku River drainage. Available data indicated that 

the status of chinook stocks in the region is generally stable or increasing. Historical 

levels of abundance are not well known, however, and anecdotal reports suggest 

that as many as four small stocks may have been extirpated.
102

Figure 24—Approximate geographic locations in the study area of chinook salmon stocks that have distinctive characteristics. Stocks 1 through 5 were considered to have distinctive characteristics based on relatively reliable data. The distinctive nature of characteristics of stocks 6 through 10 were detected based on

limited samples and data should be considered preliminary. The Nahlin and Chuck Rivers have distinctive

run timing at the regional level but not within the northern stock group.
103

Figure 25—Approximate geographic locations in the study area of chinook stocks that have significantly

declining escapement trends.
104

In comparison to stocks elsewhere in the Pacific Northwest, chinook stocks in southeast Alaska do not face serious risks so long as pristine habitats are maintained and

conservative harvest strategies are pursued. Increasing human populations will

increase habitat disruption and pressure to harvest more fish; overexploitation is a

potential risk. Overexploitation could result from a combination of factors, including

(1) lack of adequate information about population dynamics leading to management

uncertainty about sustainable catch levels, (2) rapid and unpredictable growth of

sport fisheries that complicates management and could exacerbate allocation conflicts among gear groups, and (3) interception of wild stocks mixed with hatchery

returns. Natural risk factors include glacial advances and major landslides that may

block large river systems. Such events have occurred in the recent (10,000 years)

geological past, but stocks have repopulated areas under natural conditions.

Recovery depends on adjacent stocks and long time intervals.

R. Armstong, H. Jaenicke, C. Riley, and G. Snyder provided helpful suggestions 

and supported this project in its early stages. G. Karcz Alexander, G. Gunstrom, 

M. Harris, and R. Johnson supplied ADF&G documents that were the foundation of

this report. Information retrieval from various sources was facilitated by R. Betit, 

P. DeSloover, L. Erbs, P. Johnson, and L. Petershoare. L. Talley and S. Johnson

retrieved essential data from the ADF&G Integrated Fisheries Database. D. Eggers,

A. Gharrett, W. Heard, R. Medel, J. Seeb, V. Starostka, P. Sucanek, A. Wertheimer,

and B. Wright shared their insights and expertise, which greatly enhanced this report.

J.H. Clark's review of an early draft led to significant revisions of this manuscript and

a more refined approach to the project. S. Marshall provided access to the vast information resources of the ADF&G and criticism that helped to sharpen our focus. We

are especially grateful to P. Kissner, K. Pahlke, and S. McPherson who reviewed, and

improved, early drafts of this manuscript, contributed unpublished data, and offered

many ideas and insights based on their experience studying chinook salmon. 

Alaska Department of Fish and Game. 1981. Proposed management plan for

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of Fish and Game, Division of Commercial Fisheries.

Alaska Department of Fish and Game, Habitat Division. 1992. Catalog of waters

important for spawning, rearing or migration of anadromous fishes. Juneau, AK:

Alaska Department of Fish and Game, Southeast Region, Resource Management

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University. [Pages unknown]. M.S. thesis.

Beacham, T.D.; Murray, C.B. 1990. Temperature, egg size, and development of

embryos and alevins of five species of Pacific salmon: a comparative analysis.

Transactions of the American Fisheries Society. 119: 927-945.

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112
We reviewed patterns of intraspecific variation in the biological characteristics of 85

sockeye salmon (Oncorhynchus nerka) stocks sampled from the roughly 200 stocks

present in southeast Alaska and adjacent areas of British Columbia and the Yukon

Territory. Escapement trends were evaluated for 107 stocks. Most stocks in the

region had lake-type life histories, but 24 stocks also showed either river- or sea-type

life history patterns. Fourteen sockeye salmon stocks (16.5 percent) had distinctive

characteristics based on comparatively good data. This high proportion of distinctive

sockeye stocks, relative to other species reviewed, may reflect reduced gene flow,

high phenotypic plasticity, or more thorough sampling. Sixteen additional stocks may

have unusual characteristics based on limited sampling (10) or anecdotal reports (6).

Three stocks also have unusual allozyme frequencies. Most stocks in the region

have stable escapement trends, with 4 percent (4 stocks) showing significant increases, and 7.5 percent (8 stocks) showing significant declines from 1960 to 1992. Risk

factors for sockeye salmon include lack of information about small stocks and the

possibility that the high commercial value of this species may promote enhancement

of fisheries programs that are detrimental to wild stocks.

Keywords: Sockeye salmon, Oncorhynchus nerka, southeast Alaska, age distribution,

run timing, body size, sexual selection, intraspecific diversity, population status.

The available data for the sockeye salmon stocks in southeast Alaska stocks were

used to identify patterns of intraspecific variation, stocks with distinctive characteristics, and trends in stock abundance. More than 200 sockeye salmon stocks occur in

southeast Alaska, including 31 that spawn in Canadian waters. Escapement-index

data were available for 97 stocks and biological data for 85 stocks. This database,

assembled for management purposes, was more comprehensive than those available

for other Pacific salmon species in the region. Sockeye salmon displayed considerable variation in all biological variables evaluated. 

Sockeye salmon are able to exploit a broad range of habitat types. They typically

spawn in rivers or streams associated with lakes, or sometimes along lake shores.

About 70 percent of the sockeye populations we reviewed spawned in areas with

lakes. They usually spend 1 to 3 years in lakes as juveniles (lake-type), but some

rear for a short period (1 to 2 months) in rivers and estuaries and then migrate to the

113

Sockeye Salmon 

(Oncorhynchus nerka)

Abstract

Introduction

Life History
114

ocean (sea-type). Sea-type individuals that emigrate without overwintering in fresh

water do not develop a freshwater annulus on their scales (often referred to as “zerocheck”). A few river-type sockeye spawn in rivers and streams without lakes and rear

in the river (Wood and others 1987). In the Taku River, 55 percent of mainstem fish

spawned in side-channel habitats. A smaller percentage spawned in slough and tributary habitats (Eiler and others 1992). In all habitats, areas of upwelling groundwater

are preferred for spawning (Foerster 1968, Lorenz and Eiler 1989). 

Most sockeye stocks in southeast Alaska are lake-type fish and most juveniles rear 

in lakes for 1 year, with a smaller proportion spending 2 years in fresh water before

smolting. Few individuals of any stock remain in fresh water for 3 years. Several

stocks in southeast Alaska either rear in rivers or migrate as zero-check fish. These

stocks include mainstem spawners in the Stikine, Taku, Lace-Gilkey, and Chilkat

drainages and several stocks in the Yakutat region, of which the largest is from the

East Alsek River. Fry from river-type stocks that overwinter in fresh water typically

rear in sloughs, off-channel pools, beaver ponds, or tributaries to the main river

where spawning occurs (Heifetz and others 1987, McPherson and others 1990).

Sea-type sockeye often rear in estuarine habitats where warmer temperatures and

abundant food contribute to rapid growth (Birtwell and others 1987). 

Most sockeye salmon return to near-shore marine waters of southeast Alaska in June

and July. Mean dates of freshwater migration usually are from late July through early

to mid-August. No pattern of latitudinal variation in run timing is apparent in the 

region. Spawning typically occurs in August and September but is known to continue

until as late as March in some systems (McPherson and others 1990). Systematic

data on time of spawning were not available for most southeast Alaska stocks.

Stream temperature, which can vary considerably over a local area, is likely to 

have a strong influence on time of migration (Brannon 1987).

Surveys of genetic differentiation among populations of sockeye salmon indicate

great precision in homing behavior in this species (Varnavskaya and others 1994).

Subpopulations within lake systems often show significant genetic heterogeneity: 

the greatest differentiation is associated with run timing and spawning habitat

(Varnavskaya and others 1994). These genetic results are supported by tagging and

parasite-prevalence studies (Quinn and others 1987), as well as studies of spawningsite selection (Hendry and others 1995).

The incubation period for sockeye salmon eggs varies widely, depending on water

temperature (Burgner 1991). For most southeast Alaska stocks, eggs overwinter in

the gravel, and hatching and emergence occur in spring. Timing of emergence generally coincides with the onset of spring zooplankton blooms in the lacustrine rearing

habitat (Godin 1982).

Smolt emigration timing for sockeye stocks is not well studied in southeast Alaska.

Like most other life history characteristics of sockeye salmon, existing data indicate

emigration timing is highly variable. In the Naha River, emigration historically

occurred in late May and early June (Chamberlain 1907). Emigration from Chilkat

and Chilkoot Lakes typically occurred in June (Bergander 1988). Emigration of

smolts from the Stikine River is completed before the end of May (Wood and others

1987), while emigration of Taku River sockeye smolts peaked in June (Meehan and
115

Siniff 1962), but zero-check fish emigrated about 1 month later (Murphy and others

1989). In contrast, zero-check sockeye were found in the estuary of the Situk River

from April to July, and age 1.x and 2.x smolts were present only in May and June

(Heifetz and others 1989). Mean body size of smolts at the time of emigration also is

highly variable. The fork length of most sockeye salmon smolt from southeast Alaska

ranges from 60 to 120 mm.

Sockeye salmon from southeast Alaska stocks typically spend 2 to 3 years in salt

water before returning to fresh water to spawn. After leaving inshore waters, they

migrate in a generally northwesterly direction (Burgner 1991). No stock-specific information on oceanic migration is available. Generalized models of oceanic distribution

suggest that southeast Alaska sockeye undertake circular annual migrations in the

Gulf of Alaska north of about 46° N. lat. (Burgner 1991). Return migrations generally

follow a reverse direction, but some stocks on the outer coast appear to return directly from the open ocean rather than follow the coastline south (Hoffman and others

1984). Migration through inside waters tends to be relatively direct, although exceptions to this pattern are known to occur. For example, some southern stocks migrate

south to Dixon Entrance before returning north through Clarence Strait to mainland

spawning areas (Hoffman 1987, Hoffman and others 1984).

The body length of returning adult sockeye differs significantly by sex, but no general

geographic or temporal trends in body length or weight are apparent. Throughout

southeast Alaska, the mean mideye-to-fork length of age 1.3 males in escapements

is 577 mm, and the mean length of females is 556 mm (paired t-test, N = 77 stocks, 

t = -16.24, P < 0.001). Estimates of mean body weights of commercially harvested

sockeye salmon in southeast Alaska from 1958 to 1985 differ considerably but not

consistently in any direction (Marshall and Quinn 1988). Sex-specific body-weight

data for commercially caught sockeye salmon are not available.

The age structure of sockeye runs typically changes during the season, particularly in

large returns with prolonged run timing. Fish with higher freshwater ages (2.x) and

lower saltwater ages (x.2) tend to return later in runs (McGregor and others 1991, 

McPherson and McGregor 1986, McPherson and others 1990). The river- and seatype stocks in both the Stikine and Taku Rivers increase in proportional abundance

late in both runs (Jensen and Frank 1989, McGregor and Jones 1989). The abundance of precociously maturing males (jacks) also tends to increase later in runs

(McGregor and Jones 1989).

Jacks are present in most sockeye stocks, but the relative abundance of jacks is generally unknown, because they are small and difficult to capture and sample proportionately. In 1982, the highest proportion of jacks reported for any system where fish

were sampled at a weir was 1.42 percent (Salmon Bay Lake). Where sampling was

conducted with beach seines or by carcass collection, 10 systems had more than 

10 percent jacks in the sample, with a maximum of 45.2 percent jacks in Petersburg

Lake (McGregor 1983). Jacks dominated escapements to Klawock and Kutlaku

Lakes in 1990,1 and fishwheel catches on the Taku River in 1988 and 1989 consisted

1 McPherson, S.A.; Rowse, M.L. 1992. Abundance, age, sex, and

size of sockeye salmon catches and escapements in southeast

Alaska in 1990. 53 p. Unpublished report. On file with: USDA

Forest Service, Pacific Northwest Research Station, Forestry

Sciences Laboratory, 2770 Sherwood Lane, Juneau, AK 99801.
116

Figure 26—Sockeye harvest from the Naha River, 1887-1900 (data from Chamberlain 1907).

Figure 27—Annual commercial harvest of sockeye salmon in southeast Alaska, 1880-1991

(data from Rigby and others 1991).
117

of 6.8 percent and 3.4 percent jacks, respectively (McGregor and others 1991).

Controversy persists regarding whether the proportion of jacks in escapements is

most strongly influenced by inheritance or environmental factors.

Sockeye salmon stocks have the longest history of intense commercial exploitation of

all anadromous salmonid species in southeast Alaska. Sockeye salmon were harvested by aboriginal populations in the region. Hewes (1957, cited in Cooley 1963)

conservatively estimated the annual harvest of sockeye salmon at 2 267 962 kg.

Commercial catches by Russian fishermen are believed to have begun at Redoubt

Lake between 1812 and 1818.2 Redoubt Lake, along with Whale Bay and Gut Bay,

were among the first locations reported “denuded” of salmon by stream-fencing practices (Moser 1899, Tingle 1897). The first annual record of sockeye commercial harvest by U.S. fishermen was 108,000 fish harvested in 1883 (Rigby and others 1991),

the year a saltworks was constructed in the outlet lagoon of the Naha River (Roppel

1982). By 1889, 12 canneries operated throughout southeast Alaska (Bean 1889),

and the recorded commercial catch had increased to 738,000 sockeye. During this

period of commercial expansion, the destructive use of barricades and malicious

competition among canneries led to growing concern that some stocks in southeast

Alaska had been “fatally over fished” (Cobb and Kutchin 1907). Chamberlain (1907)

reported stock-specific harvests before 1900 from the Naha River system and adjacent streams. The record from the Naha River is most complete and illustrates early

patterns of over-exploitation (fig. 26). Severe depletion of runs during this period typically led to relocation of fishing effort, which allowed subsequent recovery of overexploited stocks. The questionable accuracy of records and differences between past

and current fishing strategies make it difficult to estimate and compare the size of

past runs to recent run size in these heavily exploited streams.

The maximum commercial harvest of sockeye salmon from southeast Alaska was

about 3,500,000 fish taken in 1914. Harvest declined steadily after that, to a minimum decade average of 642,000 fish per year during the 1970s—a harvest roughly

equivalent to that obtained by the relatively undeveloped fishery of 1889 (fig. 27;

Rigby and others 1991). Commercial harvest rebounded sharply during the 1980s,

averaging over 1,200,000 fish per year. This increasing trend has continued in the

1990s with harvests exceeding 2,000,000 fish annually. Favorable ocean conditions

in recent years have probably contributed to increasing harvests.

Because sockeye populations tend to fluctuate greatly in run strength, and because

mixed-stock exploitation prevails, the preferred management approach for sockeye

stocks is the use of escapement goals. Insufficient information is available, however,

to permit formal escapement goals to be set for all commercially exploited stocks in

the region. Most small stocks are fundamentally unmanaged. Sockeye salmon management in regulatory districts 101, 104, 106, and 111 and the Alsek River (fisheries

that catch transboundary or Canadian stocks) is governed by the U.S./Canada Pacific

Salmon Treaty, which sets harvest limits and allocates catch proportions (Ingledue

1987). Scale-pattern analysis is currently being used to separate stocks harvested 

in these districts and in Lynn Canal. Improved stock-separation technology has enhanced inseason management and compliance with treaty requirements. Inseason

management decisions are based mainly on abundance as a function of time during

2 Personal communication. 1996. R.H. DeArmond, historian. Sitka

Pioneer’s Home, 120 Katlian Avenue, Sitka, AK 99835.

Management History

Current Management
118

migration of stocks through fisheries. Selective time and area closures have proven

effective management tools for achieving escapement goals in areas where stocks

can be readily separated (e.g., Lynn Canal). The only remaining interception fisheries for sockeye salmon in the region are the district 104 purse seine fishery off

Noyes Island and the district 101 gill-net fishery off Tree Point (Pacific Salmon Commission 1991). Both fisheries intercept sockeye bound for spawning streams in southeast Alaska and British Columbia—especially the Nass and Skeena River systems.

Drift gill nets and purse seines take roughly equal proportions of the commercial harvest of sockeye salmon in southeast Alaska. Sport fisheries take a small proportion

of the total regional catch but are concentrated on stocks near roads, such as Windfall Lake on the Juneau road system. Subsistence harvest also is a small proportion

of the total regional harvest, but a few stocks are harvested relatively intensively for

this use (e.g., Karta and Klawock Rivers; Sarkar, Hetta, Sitkoh, and Kanalku Lakes).

Substantial inriver catches are taken from the Stikine and Taku Rivers; the mean 

harvests in these systems from 1979 to 1994 were 22,229 and 19,079 fish, respectively (Pacific Salmon Commission 1997). Differing numbers of sockeye salmon are

harvested in pink salmon purse-seine fisheries. The incidental catch of sockeye

salmon in the pink salmon purse-seine fishery differs annually, but 60,488 fish were

caught in 1990 (see footnote 1). The magnitude of the incidental catch of sockeye

salmon is related to the strength of the pink salmon run and fishing pressure on pink

salmon (McPherson and McGregor 1986). Limiting early-season fishing for pink

salmon has controlled the incidental take of sockeye salmon (Ingledue 1987).

Southern southeast Alaska districts have contributed about 70 percent of the total

regional harvest in recent years (McPherson and McGregor 1986; also see footnote

1). District 104 consistently harvests the most fish, but up to 84 percent of this harvest can be fish destined for the Skeena and Nass systems in Canada (see footnote

1). Although most of the harvest is taken from southern stocks, fewer data are available for those stocks than for northern ones. 

Current estimates of exploitation rates were available for only a few stocks in the

region. The mean estimated exploitation rate for all these stocks combined for 1985

to 1989 was 66 percent. This estimate does not include Canadian interception of

southern stocks or incidental, sport, or subsistence catches. Wild sockeye salmon

stocks in southeast Alaska have shown great resilience in the face of intense exploitation for over a century. Undoubtedly this resilience depends on the presence of

high-quality spawning and rearing habitats. Recent increases in commercial harvest

can be sustained only if the quality of freshwater habitats is maintained.

Between 1901 and 1906, a law required commercial fisheries operators to establish

hatcheries that would produce at least four times the number of adult sockeye harvested (Roppel 1982). The few hatcheries that were constructed seldom produced

fry in the required 4-to-1 ratio. In one example cited by Roppel (1982), two hatcheries operated by the Alaska Packers Association released 52,500,000 fry and caught

16,587,097 adults, a ratio of 3:1. From 1892 through 1933, six hatcheries operated

for various lengths of time in southern southeast Alaska. In 1933, the last of these

hatcheries was closed by the commissioner of fisheries, Frank T. Bell, who stated,

“The salmon will reproduce naturally if a sufficient number are allowed to reach their

spawning grounds. If we find that any district is threatened with depletion, we will

Enhancement
119

restrict the gear or the fishing period and permit it to build up by natural propagation

rather than try to do it artificially” (as cited in Roppel 1982). Renewed interest in

hatcheries revived during the 1950s, and a hatchery at Deer Mountain near

Ketchikan was constructed. Significant production of sockeye salmon occurs currently at the Beaver Falls, Klawock, and Snettisham hatcheries.

Brood stock for the early sockeye salmon hatcheries in southeast Alaska were generally taken from the stream where the hatchery was located. This tended to preserve

to some degree the genetic integrity of the hatchery stock, but eggs and fry from the

early hatcheries were outplanted to various locations, some of which are reported by

Roppel (1982). Barren lakes were common targets for stocking of sockeye eggs and

fry. Introduction of fry to barren lakes continued through the 1950s up to the present

and often was accompanied by the construction of a fish ladder to provide access to

the lake. 

Hatcheries are a part of current enhancement efforts for sockeye salmon in southeast

Alaska, but other methods include lake fertilization, construction of fish ladders, fry

stocking, and remote releases of fry, presmolts, and smolts. Lake fertilization is

intended to increase the primary productivity of lakes in which sockeye production is

thought to be “forage-limited” (Koenings and others 1989). In some instances,

growth and production of sockeye salmon increased. Fertilization at McDonald Lake

was followed by an estimated increase in production from 84,000 to over 300,000

returning adults (Zadina and others 1995). Smolt size in Falls and Redoubt Lakes

increased significantly after fertilization (Burkett and others 1989), but fertilization had

little effect on sockeye smolts in Hugh Smith Lake (Burkett and others 1989).

Sockeye fry from Beaver Falls and Klawock hatcheries were stocked in Salmon Lake,

Hugh Smith Lake, and Klawock River from eggs taken from their respective nursery

areas. Fertilized eggs from the Tahltan, Speel, Crescent, Sweetheart, Little Trapper,

Little Tatsamenie, and Chilkat Lakes were incubated in the Snettisham hatchery and

returned to their sources in northern southeast Alaska. Fry from the Beaver Falls

hatchery of McDonald Lake brood stock have been stocked in George Inlet, Virginia

Lake, Margaret Lake, and Shrimp Bay. Hugh Smith Lake brood stock incubated at

Beaver Falls was used to stock the Bakewell-Badger Lakes system after fishpass

reconstruction (Bibb 1987). Sockeye production at the Klawock hatchery is directed

toward enhancing the depressed Klawock River stock. The Snettisham hatchery is

used primarily for incubation of sockeye eggs for fry plants in several lakes in southeast Alaska and British Columbia. Snettisham hatchery is also developing brood

stock from Speel Lake for smolt releases near the hatchery.

Simpson (1969) estimated that 128 systems in southeast Alaska produce sockeye

salmon, including 14 systems in the Yakutat region. More recent reports from the

ADF&G put the total count of sockeye-producing systems at about 114 (e.g., Bergander 1989). Baker and others (1996) identified 206 spawning aggregates in the

region. Based on the criterion of escapement survey counts of at least 20 fish, we

found about 230 systems supporting sockeye salmon in southeast Alaska and adjacent areas of British Columbia and the Yukon Territory. 

Methods

Stock Discrimination
120

Geographic location (watershed) and run timing provide the most direct approach for

defining sockeye stocks and describing intraspecific diversity and for identifying 

populations with distinctive biological characteristics. Several other stock-separation

methods have been successfully applied to manage sockeye salmon fisheries in

southeast Alaska. Scale-pattern analysis (Marshall and others 1987), prevalence of

the brain parasite Myxobolus neurobius (Moles and others 1990), and egg diameter

(Craig 1985, Lynch and others 1990) have been used to determine the origin of fish

caught in mixed-stock fisheries. Genetic stock identification based on allozyme 

frequencies suggests the presence of subpopulation structure within several sampled

populations (Guthrie and others 1994). The objectives of most of these efforts were to

identify stocks originating from a specific watershed and to provide a method to

determine catch-and-escapement goals. In addition, results from these methods may

be used to identify potential gene flow or isolation among stocks and differences in 

environmental characteristics of rearing habitats.

Escapement sampling provided most of the data for our analysis of adult length, 

population age structure, and adult migratory timing. More information is available for

large sockeye stocks than for small stocks. Methods used to identify trends in stock 

abundance and distinctive stocks followed those described in the “General Introduction.” Grand means from all sample years were used for most analyses of biological

characteristics. The number of stocks compared for each characteristic differed,

because of limitations in the availability and quality of data.

The variance-component analysis of adult fork lengths was based on 15 stocks with

at least 6 years of sampling and a sample size of at least 15 individuals of each sex

in the 1.3 age class, the only age class evaluated. Similar selection criteria were

used to include stocks in all analyses of temporal trends. Temporal trends were analyzed only for age classes with the largest sample size.

Postorbit-to-hypural (POH) plate lengths, used in many Canadian stocks, were converted to mideye-to-fork lengths (MEF) by using the conversion equations provided 

in the source document. Equations were not provided for the 1984 sample from Little

Trapper Lake and the 1985 sample from the Klukshu River, and the lengths were 

converted with the following equations:

for Little Trapper Lake—

MEF = (1.0877 x POH) + 23.83 ,

and for Klukshu River—

MEF = (1.097 x POH) + 23.039 .

The former was derived from length-conversion equations for 1986 to 1990. The

Klukshu River sample was converted by using a generalized equation for converting

lengths of ocean-caught sockeye salmon in southeast Alaska (Pahlke 1989b).

Data Analysis

Procedures
121

Migratory timing characteristics were evaluated for 28 stocks with daily weir counts

and 97 stocks for which our run-timing index (defined in “General Introduction”) could

be calculated. Seventeen of the systems with weirs also were included in the runtiming index sample. Most survey counts of sockeye salmon in southeast Alaska are

made during surveys directed at pink salmon, and these may be too early to identify

migration peaks for sockeye stocks. The timing index calculated from these data 

provided only comparative differences in timing among sockeye salmon stocks. We

did not compile any information on emigration timing of sockeye smolts. We compared run-timing characteristics of stocks from island, mainland, coastal, and interim

drainages to look for geographic patterns. Only stocks monitored at weirs were

included in this comparison.

Mean freshwater age (MFWA), mean saltwater age (MSWA), and proportions of

escapements in each age and sex class were analyzed for 79 sockeye stocks. Two

major factors influenced the interpretation of sockeye age data. (1) The growth rate

of juvenile sockeye was density dependent in many lakes, which can lead to cycles 

of weak and strong brood years. In southeast Alaska, these cycles seemed to have 

a period of about 5 years; therefore, MFWA calculations based on less than 5 return

years may be influenced by weak or strong brood years.3 4 (2) Changes in run composition through the season complicate the evaluation of the age structure and sex ratio

(McPherson and McGregor 1986). The typical method of collecting age data from

escapements consists of a single, brief sampling visit to each run. This sampling

regime cannot detect seasonal shifts in age structure or sex ratio. Although shortterm sampling may be adequate for small stocks with relatively brief runs, serious

bias can result from a few days of sampling from large stocks with protracted runs

(see footnotes 3 and 4). The most reliable age-structure and sex-ratio data come

from stocks sampled throughout their runs at weirs. Interannual variation in MFWA

and MSWA and sex ratios were examined only for stocks sampled at weirs. Sex

ratios were derived from samples taken for age-structure analysis.

River- and sea-type life histories were identified in 24 stocks from accounts in the literature or by the presence of at least 10 percent zero-check individuals of each sex

in the x.3 age class. For analyses of biological characteristics, we combined the

river- and sea-type stocks into a single group (river-sea-type) and evaluated them

separately from the lake-type stocks. Although all three life history patterns occur in

the Situk River (Thedinga and others 1993), we treated this as a lake-type stock.

Samples taken at the Taku fishwheel were analyzed as river—sea-type, although 

this undoubtedly was a mixture of lake- and river-sea-type fish.

Adult body-length data from escapements of 84 stocks showed significant differences

between body lengths of males from lake- versus river-sea-type stocks, but not

between females of each type of stock (table 21). Therefore, outlier analyses of body

length were conducted separately for males of each type of stock, but stock types

were pooled for females. Five stocks (Essowah Lake, Julian, Coffee, Chuunk Mountain, and Honakta Sloughs) were not included in body-length analyses, because 

sample sizes were too small (N ≤ 60 fish). 

3 Personal communication. 1996. M. Haddix, limnologist, Alaska

Department of Fish and Game, 2030 Sea Level Drive, Suite 215,

Ketchikan, AK 99901.

4 Personal communication. 1996. T. Zadina, fisheries biologist,

Alaska Department of Fish and Game, 2030 Sea Level Drive,

Suite 215, Ketchikan, AK 99901.

Results

Body Length
122

Both types of sockeye stocks showed significant levels of sexual dimorphism in all

age classes tested (table 21), but the direction of the difference was not consistent.

Males were larger than females in the 1.3 and 2.3 age classes, but females were

larger than males in the 1.2 age class (fig. 28). Differences between males and

females were greater in river-sea-type stocks than lake-type stocks in the 1.3 age

class (table 21). Furthermore, age 0.3 fish from river-sea-type stocks were significantly more dimorphic in body length than age 1.3 fish from lake-type stocks (table

21). Outlier analysis for degree of sexual dimorphism therefore was conducted separately on lake- and river-sea-type stocks. Although significant sexual dimorphism

exists, male and female body lengths were highly correlated throughout the region

(fig. 28). Freshwater age did not have a significant effect on adult body length

(males, T = 0.37, P = 0.71 NS; females, T = 2.79, P = 0.07 NS), but age 1.3 individuals tended to be larger than age 2.3 individuals (table 21).

Adult body length increased over time in four of the 32 stocks tested (table 22). The

specific stocks and age classes were (1) Petersburg Lake age 1.3 females, but not

males; (2) Thoms Lake age 2.3 males and females; (3) Speel Lake age 1.3 males;

and (4) Crescent Lake age 1.3 males. Sample sizes have been small in recent years

from both Petersburg and Thoms Lakes. Speel and Crescent Lakes have weirs, and

large samples of body lengths for age 1.3 individuals were available. Regression

coefficients were positive in 45 of 64 tests (70 percent), suggesting a weak trend of

increasing body size with time throughout the region. Our database did not contain

sufficient recent data to detect any changes in body size in systems where lake fertilization has occurred.

Table 21—Mideye-to-fork length comparisons between lake-type and river—seatype sockeye salmon stocks, and between age 1.3 and 2.3 lake-type sockeye

salmon

Lake-type River-sea-type

Age and sex class t-value P-value Mean SDa N Mean SDa N

Age 1.2 females 0.43 0.67 492.6 16.68 46 490.3 16.48 13

Age 1.2 males 3.68 <0.01 485.3 24.96 47 462.7 17.39 20

Age 1.3 males 3.01 <0.01 572.5 20.86 54 587.1 15.32 23

Age 1.3 females 0.97 0.34 554.3 19.57 54 558.8 16.32 23

Age 1.2 sexual dimorphism 2.54 0.01 -6.5 21.39 46 -22. 15.75 13

Age 1.3 sexual dimorphism 3.63 <0.01 18.2 11.91 54 28.3 8.80 23

Age 1.3 vs. 0.3 dimorphism 3.52 <0.01 18.2 11.91 54 29.0 13.55 24

Comparisons of lake-type age classes

Age 1.3 Age 2.3

Mean SDa N Mean SDa N

Age 1.3 vs. 2.3 males 0.37 0.71 572.5 20.9 54 570.3 24.7 44

Age 1.3 vs. 2.3 females 2.79 0.07 554.3 19.6 54 551.1 21.1 43

a SD = standard deviation.
123

Figure 28—Male versus female sockeye salmon mideye-to-fork lengths: (A)

age 1.2, N = 58, (B) age 1.3, N = 77, (C) age 2.3, N = 46. Each point represents mean lengths for one stock. Means calculated for escapement

samples across all years. Diagonal line represents equal lengths for both

sexes.
124

Table 22—Regression analysis of trends across years in mideye-to-fork lengths from sockeye salmon

escapements

Stream Males Females

Age No. years R- RNumber Name class sampled squared Slope P-valuea squared Slope P-valuea

101-30-075 Hugh Smith Lake 1.3 8 0.01 1.35 0.5<P<0.9 0.22 1.09 0.2<P<0.4

101-80-068 McDonald Lake 1.3 8 0.15 2.66 0.2<P<0.4 0.06 1.16 0.5<P<0.9

101-90-050 Naha River 1.3 8 0.12 3.23 0.2<P<0.4 0.11 2.74 0.4<P<0.5

101-90-084 Helm Lake 1.2 7 0.26 2.87 0.2<P<0.4 0.01 0.45 0.5<P<0.9

102-30-067 Kegan Lake 1.3 8 0.01 1.01 0.5<P<0.9 0.00 -0.28 P>0.9

102-60-087 Karta River 1.3 8 0.10 2.43 0.4<P<0.5 0.08 1.06 0.5<P<0.9

103-15-027 Klakas Lake 1.3 7 0.01 0.63 0.5<P<0.9 0.42 -3.96 0.1<P<0.2

103-25-047 Hetta Lake 1.3 7 0.02 1.19 0.5<P<0.9 0.01 0.42 0.5<P<0.9

103-60-047 Klawock Lake 1.3 6 0.03 1.29 0.5<P<0.9 0.02 0.65 0.5<P<0.9

103-90-014 Sarkar Lake 2.2 7 0.01 1.04 0.5<P<0.9 0.14 -3.83 0.4<P<0.5

106-30-051 Luck Lake 1.3 7 0.00 0.03 P>0.9 0.01 -1.17 0.05<P<0.9

106-41-010 Salmon Bay Lake 1.3 8 0.08 2.24 0.4<P<0.5 0.00 0.27 0.5<P<0.9

106-41-030 Red Bay Lake 1.3 7 0.19 1.69 0.2<P<0.4 0.01 -0.26 0.5<P<0.9

106-44-060 Petersburg Lake 1.3 8 0.03 1.42 0.5<P<0.9 0.57 8.89 0.02<P<0.05 *

107-30-030 Thoms Lake 2.3 8 0.54 5.28 0.02<P<0.05* 0.58 3.72 0.02<P<0.05 *

109-20-013 Falls Lake 1.3 6 0.02 -0.43 0.5<P<0.9 0.01 -0.30 0.5<P<0.9

109-52-035 Kutlaku Lake 1.3 8 0.06 -1.03 0.5<P<0.9 0.09 1.41 0.4<P<0.5

109-62-013 Alecks Lake 1.3 6 0.03 1.10 0.5<P<0.9 0.01 0.41 0.5<P<0.9

111-32-032 Taku River 1.3 7 0.48 2.13 0.05<P<0.1 0.36 1.81 0.1<P<0.2

111-32-235 Kuthai Lake 1.3 7 0.07 -2.81 0.5<P<0.9 0.05 -1.93 0.5<P<0.9

111-32-245 Little Trapper Lake 1.3 8 0.25 -4.45 0.2<P<0.4 0.21 -4.35 0.2<P<0.4

111-32-254 Little Tatsamenie 1.3 6 0.31 -8.62 0.2<P<0.4 0.28 -8.18 0.2<P<0.4

Lake

111-33-034 Speel Lake 1.3 8 0.66 4.92 0.01<P<0.02** 0.44 4.64 0.5<P<0.1

111-35-007 Crescent Lake 1.3 8 0.76 6.19 0.001<P<0.01*** 0.30 3.78 0.1<P<0.2

111-50-042 Auke Lake 2.3 8 0.38 2.04 0.1<P<0.2 0.40 2.91 0.05<P<0.1

111-50-056 Steep Creek 1.3 8 0.03 -1.06 0.5<P<0.9 0.02 -0.68 0.5<P<0.9

113-41-043 Redoubt Lake 2.2 8 0.09 1.56 0.4<P<0.5 0.06 0.84 0.5<P<0.9

113-73-003 Ford Arm Lake 1.3 8 0.11 2.54 0.4<P<0.5 0.00 0.16 P>0.9

115-32-025 Chilkat River 0.3 7 0.00 -0.14 P>0.9 0.05 0.95 0.5<P<0.9

115-32-032 Chilkat Lake 2.3 8 0.00 -0.03 P>0.9 0.00 -0.01 P>0.9

115-33-020 Chilkoot Lake 1.3 8 0.14 0.79 0.2<P<0.4 0.29 1.34 0.1<P<0.2

182-20-010 East Alsek River 0.3 6 0.35 3.33 0.2<P<0.4 0.44 3.07 0.1<P<0.2

a * = 0.05 > P > 0.01; ** = 0.01 > P > 0.001; and *** = P < 0.001.
125

Variance-component analysis of lake-type stocks indicated that nearly 81 percent of

total variation in male body length was attributable to variation among individuals

within stocks, and 8 percent was accounted for by differences among stocks (table

23). Females were less variable within stocks (68 percent) and more variable among

stocks (20 percent). Interannual variation within stocks was about equal for both

sexes (males 11 percent, females 12 percent). No river-sea-type stocks were included in this analysis, because of the requirement for balanced data and relatively large

samples of age 1.3 individuals. Given the highly variable nature of the rearing 

habitats used by river-sea-type stocks, these stocks also may have high levels of

within-stock variance in body length.

Adults in all age-sex classes from both the Karta and Naha Rivers were near or at

the top of their respective size distributions. Age 1.2 males in the Karta system are

larger than other stocks in the group (fig. 29A). The Karta River on Prince of Wales 

Island and the Naha River on Revillagigedo Island both drain large, low-gradient

watersheds containing numerous lakes. Insufficient information is available to determine if smolts from these populations are particularly large. No other stocks had 

distinctive adult body size.

Table 23—Variance component analysis of age 1.3 sockeye salmon mideye-to-fork

lengths from escapementsa b

Degrees

Source of of Type 1 sum Error Expected Variance Percentage

variation freedom of squares F-test term mean square component of total

Males

Total 31,972 55,076,640 1,722.65 1,741.92

Stocks 14 5,452,334 7.17 Years 389,452.42 144.07 8.27

Years 90 4,887,491 38.68 Error 54,305.45 194.04 11.14

Error 31,868 44,736,816 1,403.82 1,403.82 80.59

Females

Total 34,218 42,045,441 1,228.75 1,254.26

Stocks 14 8,998,098 13.99 Years 642,721.28 254.10 20.26

Years 90 4,135,193 54.21 Error 45,946.59 152.64 12.17

Error 34,114 28,912,150 847.52 847.52 67.57

a Variance components computed from means, standard errors, and sample sizes.

b Stocks included in the analysis:

101-30-075 Hugh Smith Lake 111-33-034 Speel Lake 106-41-010 Salmon Bay Lake

101-80-068 McDonald Lake 111-35-007 Crescent Lake 109-52-035 Kutlaku Lake

101-90-050 Naha River 111-50-056 Steep Creek 111-32-245 Little Trapper Lake

102-30-067 Kegan Lake 113-41-043 Redoubt Lake 115-32-032 Chilkat Lake

102-60-087 Karta River 113-73-003 Ford Arm Lake 115-33-020 Chilkoot Lake
126

The sockeye stock that spawns in Benzeman Lake and is harvested in Necker Bay

has long been recognized as consisting of unusually small individuals (Moser 1899).

Body lengths of fish caught in Necker Bay are the smallest of all sampled commercial

fisheries (McPherson and McGregor 1986). The commercial sockeye harvest from

Necker Bay is dominated by age 2.2 individuals (McGregor and others 1984,

McPherson and McGregor 1986). No data were available from escapements regarding body lengths in this stock.

Figure 29—Frequency distributions, outlier plots, and normal quantile plots for

(A) mideye-to-fork lengths of age 1.2 males from lake-type stocks, N = 47, and

(B) sexual dimorphism of age 1.3 individuals from lake-type stocks, N = 55.

Age 1.2 males in the Karta River stock are distinctively large. In the Pavlof and

Lake Anna stocks, males are distinctively larger than females, and in Luck Lake

females average nearly 6 mm longer than males in mideye-to-fork length.
127

Differences in the body lengths between age 1.3 males and females in the Pavlof,

Anna, and Luck Lake stocks were greater than those observed for the other stocks

(fig. 29B). Males in the Pavlof and Lake Anna populations averaged 56 and 51 mm

greater in mideye-to-fork length, respectively, than females. The Pavlof Lake result

was based on a sample of 27 males and 35 females from a single year, and the Lake

Anna sample consisted of 47 males and 26 females. In contrast, Luck Lake females

were larger (average 6 mm) than males in a sample size of 123 males and 416

females during a 7-year period. No outliers were found for river-sea-type stocks. 

The grand mean date of adult freshwater migration for 30 stocks inhabiting systems

monitored with weirs or fishwheels was 7 August. The mean date of migration for

individual stocks ranged from 4 July to 3 September. Interior stocks tended to have

later mean migration dates (Kruskal-Wallis test, P = 0.11 NS; table 24), which was

expected, given that most weirs were located near outlets of nursery lakes, far from

the sea. No relation existed between the mean date of migration and body length of

age 1.3 sockeye (N = 25 stocks; males, r = 0.12, P = 0.56; females, r = 0.06, P =

0.79).

Variance in migration timing is an index of run duration, because it reflects the dispersion of the migratory time-density function at the weir (Mundy 1984). Actual run 

duration was more protracted than estimates at weirs show, because weirs frequently

were not operated for the full duration of runs. Variance (days squared) ranged from

30.75 for the Nakina River stock to 752.26 for the Chilkat Lake stock. Interior stocks

had more compact run timing than island or coastal-mainland stocks (table 24). 

Run duration and mean escapement count were weakly correlated (N = 25, r = 0.33,

P = 0.1). Based on a comparison of coefficients of variation, run duration and

escapement magnitude were more variable among years than was the mean migration date. Coefficients of variation for mean migration date ranged from 1 to 8 percent, and coefficients of variation for variance (run duration) and escapement ranged

from 10 to 80 percent and 10 to 140 percent, respectively. No geographic pattern

was apparent in the degree of variability of these characteristics.

Historic and current weir counts were available for Klawock and Redoubt Lakes, but

only Klawock Lake was sampled for enough years to permit comparison of timing

characteristics between the historic and current periods. The mean date of migration

was significantly earlier (Wilcoxon test, P = 0.001) and the duration of migration was

Timing

Table 24—Run timing summary statistics by habitat for sockeye salmon stocks

monitored with weirs or fishwheels

Mean date Variance (duration) Escapement

Mean Mean

N (Julian Mean N (days Mean N Mean Mean

Habitats (stocks) date) CV (stocks) squared) CV (stocks) (no. of fish) CV

Percent Percent Percent

Island 10 212.1 4.4 10 222.1 54.2 11 17,407 74.3

Coastal 10 217.1 3.1 10 259.8 43.6 10 35,964 60.0

Interior 7 229.1 2.0 7 120.0 48.9 7 9,139 51.4
significantly greater than they are currently (Wilcoxon test, P = 0.03). Differences in

mean date of migration may be partially attributed to significantly larger historic runs

(Wilcoxon test on mean escapements, P = 0.001), because mean date of migration

and escapement count were correlated in this stock (r = 0.58, P = 0.01). Run duration and escapement magnitude were not strongly correlated (r = 0.38, P = 0.12).

Thirteen sockeye stocks in the region had sufficiently long series of weir counts to

permit evaluation of contemporary trends across years in mean date of migration

(table 25). Three of these 13 stocks showed significant changes in mean migration

date. Both Klawock River and Chilkat Lake stocks had trends toward later run timing,

and the Tahltan Lake stock showed a trend toward earlier run timing.

The mean index (peak number of fish counted) date for the 97 stocks evaluated was

21 August, about 2 weeks later than the grand mean migration date for systems with

weirs. For the 17 stocks for which weir mean date and timing-index date could be

calculated, the mean difference between calculated values was 15.59 days (SE =

3.33, range -13 to 33), with index dates generally being later than weir dates. At

Redfish and Redoubt Lakes, weir mean dates were later than index dates by 13 and

5 days, respectively. At Falls Lake the dates were the same. One explanation for

these discrepancies is that all three systems are very near salt water, and the short

length of visible stream led to unreliable abundance estimates from surveys.

No stocks showed distinctive timing characteristics. Run duration of the Chilkat Lake

stock was much more protracted than for other stocks in the region, but this difference did not meet the outlier criterion. Five other stocks also had relatively protracted runs; Klukshu, Sitkoh, Kegan, Hugh Smith, and Chilkoot Lakes. The Klukshu

Lake stock was unusual among these because it is the only interior stock, and interior

stocks tend to have relatively compact runs.

128

Table 25—Regression analyses of trends across years in sockeye salmon mean

migration dates for stocks counted at weirs

Stream Regression

No. years

Number Name sampled Years R-squared Slope P-valuea

103-60-047 Klawock Lake 10 1968-88 0.72 1.66 0.001<P<0.01**

106-41-010 Salmon Bay Lake 10 1965-88 0.14 0.41 0.2<P<0.4

108-80-110 Tahltan Lake 32 1959-91 0.22 -0.48 0.001<P<0.01**

109-20-013 Falls Lake 9 1981-89 0.02 0.55 0.5<P<0.9

111-32-245 Little Trapper Lake 9 1983-91 0.00 0.07 P>0.9

111-32-254 Little Tatsamenie Lake 7 1985-91 0.36 1.00 0.1<P<0.2

111-33-034 Speel Lake 10 1983-92 0.27 -0.68 0.1<P<0.2

111-35-007 Crescent Lake 12 1977-92 0.21 0.60 0.1<P<0.2

113-41-043 Redoubt Lake 11 1982-92 0.05 0.35 0.5<P<0.9

115-32-032 Chilkat Lake 26 1967-92 0.27 0.95 0.001<P<0.01**

115-33-020 Chilkoot Lake 17 1976-92 0.03 0.30 0.5<P<0.9

182-30-020 Klukshu Lake 16 1976-91 0.08 0.47 0.2<P<0.4

182-70-010 Situk River 14 1971-92 0.03 0.13 0.5<P<0.9

a ** = 0.01 > P > 0.001.
Escapement—Escapement trends for the period 1960 through 1992 could be evaluated for 107 stocks: 14 (13 percent) showed significant trends. Four stocks were

increasing significantly and 10 were declining significantly (table 26). No geographic

pattern was apparent for either the increasing or declining stocks. The significant

declines detected for the Shipley Bay-Lake Creek, Auke Lake, and Pavlof Lake

stocks are of particular note, given the distinctive characteristics of these populations

(see “Age Structure,” below). Declines detected in the Sitkoh Lake and Situk River

populations were probably attributable, respectively, to inappropriately early surveys

and a reduced escapement goal. When surveys conducted before 15 August were

omitted from the Sitkoh Lake analysis, the decline became nonsignificant. The

decline in escapements to the Situk River probably resulted, in part, from the

increase in exploitation rate that followed a reduction of the management escapement goal in 1987 for this system from 80,000-100,000 to 40,000-55,000 fish

(McPherson and others 1987). The Sitkoh and Situk stocks were not included in the

list of declining stocks.

Both weir counts and survey counts were available for seven stocks, allowing a limited comparison of these data types. In five of seven cases, both data types yielded

regression lines of escapement trends with slopes of the same sign. Falls and

Redoubt Lakes both had negative slopes, based on aerial survey counts, and positive

slopes, based on weir counts, but the aerial survey counts were unreliable for the

short outlet streams from these deep lakes. The Situk stock showed a significant

decline based on weir counts but a nonsignificant decline based on survey counts.

This difference is probably due to the low degree of overlap in the timing of survey

(1960 to 1975) and weir (1971 to 1992) counts.

129

Table 26—Sockeye salmon stocks with significantly declining escapement trends 

Stream Location Data

quality

Number Name VCUa General Land useb rating Possible factors

103-11-017 Hunter Bay 699K Prince of Wales Wilderness Fair Unknown

103-15-027 Klakas Lake 687K Prince of Wales Wilderness Fair Unknown

105-43-002 Lake Creek- 541K Kosciusko Island LUD II (legislated) Fair Unknown

Shipley Bay FS cabin

109-20-007 Gut Bay 332C Baranof (south) Wilderness Fair Unknown

111-50-042 Auke Lake 29C Auke Bay, LUD III Good Habitat degradation;

Juneau Private hatchery manipulations;

gravel mining

112-50-010 Pavlof River 218C Chichagof LUD III Good Habitat degradation; fish

Timber harvest pass effects (?)

113-52-004 Hanus Bay 295C Baranof LUD II Fair Unknown

FS cabin and trail

115-32-060 Mosquito Lake NA Haines Private and State Fair Habitat degradation; 

(campground) sport harvest (?)

NA = not available.

a VCU = USDA, Forest Service value comparison unit; approximately equivalent to a watershed; K = Ketchikan Area; and 

C = Chatham Area.

b LUD = Land use designation:

LUD II = roadless areas

LUD III = multiple use

LUD IV = intensive resource use (especially logging)

Demography
130

McDonald, Chilkat, and Chilkoot Lakes, and the Situk River, which were monitored

with weirs, had large sockeye populations (fig. 30A). Among stocks for which escapment survey counts were available, the Situk and East Alsek Rivers and Hatchery

Creek (McDonald Lake) stocks also had particularly large runs (fig. 30B). Total run

size for the East Alsek River stock has been estimated to be as high as 180,000

sockeye.5 The East Alsek stock was also the only large stock in the region in which

the zero-check life history pattern predominated.

5 Personal communication. 1996. F. Bergander, fisheries biologist,

Alaska Department of Fish and Game, 802 3d Street, Douglas, AK

99824.

Figure 30—Frequency distributions, outlier plots, and normal quantile plots for

mean escapement magnitude of (A) stocks enumerated at weirs, N = 30, and

(B) stocks included in escapement surveys, N = 97. All named stocks are 

distinctively large. Hatchery Creek is an inlet stream to McDonald Lake.
131

Water quality and demographic status—Ward Cove is the only “impaired” water body

inhabited by a sockeye population; four additional “suspected” water bodies contain

sockeye populations (Alaska Department of Environmental Conservation 1992) (table

27). Ward Cove, Montana Creek, and Thorne Bay contain small populations, with maximum escapement counts of less than 300 individuals. The Klag Bay population was of

intermediate size with a maximum escapement survey count of 6,000 fish in 1976 and a

mean survey count of 1,597 fish (based on 24 surveys between 1962 and 1992) but no

significant temporal trend in population size. The Ward Creek stock, surveyed eight

times between 1975 and 1989, did not show a significant population trend. Both the

Thorne Bay and Montana Creek stocks have been surveyed only three times at intermittent intervals. Incidental observations of sockeye spawning at various locations in the

Thorne River drainage suggested annual escapements may have been as high as

5,000 fish for 1983 to1993.6 Catch reports from the subsistence fishery on the Thorne

River ranged between 6 and 131 fish for the same period (see footnote 6). The last survey for Thorne Bay counted 10 fish in 1982.

Table 27—Sockeye salmon stocks in impaired or suspected water bodies

Stream Location Pollutant

source

Number Name VCUa General typesb Comments

Impaired water bodies

101-47-015 Ward Cove 749K Ketchikan IN, DO Small run; maximum count of 290 fish

Debris in 1982

Suspected water bodies

102-70-058 Thorne Bay 586K Thorne Bay IN, UR, Only 3 escapement surveys conducted:

SE, SM 200 fish in 1963, 2 fish in 1979,

10 fish in 1982

111-50-052 Montana Creek 27C Juneau UR Only 3 escapement surveys conducted: 

210 fish in 1983, 10 fish in 1989,

2 fish in 1992

113-72-002 Klag Bay 271C Klag Bay Metals Moderate sized run; maximum count of 

MI, TA 6,000 fish in 1976; no significant

population trend

115-33-020 Lutak Inlet NA Haines As, PAH Large population; mean annual weir 

escapement count of 81,538 fish, 

from 1976 to 1992. No significant

population trend

NA = not available

a VCU = USDA, Forest Service value comparison unit; approximately equivalent to a watershed; K = Ketchikan Area;

and C = Chatham Area.

b Pollutant source types:

As = Arsenic MI = Mining SM = Streambank or shoreline modification

DO = Dissolved oxygen PAH = Poly aromatic hydrocarbons TA = Tailings

IN = Industrial SE = Sewage discharge UR = Urban runoff

Source: ADEC 1992

6 Personal communication. 1996. E. Johnston, staff officer, USDA

Forest Service, Tongass National Forest, Thorne Bay Ranger

District, P.O. Box 1, Thorne Bay, AK 99919.
132

The largest stock using a suspected water body is the Chilkoot Lake stock. Lutak

Inlet is listed as a suspected water body and serves as a secondary rearing area for

Chilkoot Lake sockeye smolts (McPherson 1990). Chilkoot Lake sockeye smolts emigrate at comparatively small sizes (65 to 75 mm; McPherson 1990). The time spent

rearing in Lutak Inlet therefore may be critical to the relatively high productivity of this

stock (McPherson 1990). The Chilkoot Lake sockeye stock is one of the largest

southeast Alaska stocks.

Age structure—Age structure data were available for the same 84 stocks for which

body-length data were available. Male and female MFWA were correlated within

sockeye stocks (fig. 31A). However, MFWA differed among stocks over a wide

range, extending from 0.01 to over 2 years. The grand mean MFWA for the region

was 1.07 years. A relatively large number of river-sea-type stocks with low MFWA

occurred in the Yakutat area, the northern-most area included in this review. Riversea-type stocks do not occur south of the Stikine River.

Figure 31—Relation between the age structures of males and females in sockeye

stocks: (A) mean freshwater age (MFWA), N = 79, and (B) mean saltwater age

(MSWA), N = 79. Line (c) indicates equal male and female MSWA; line (b), a 

difference of 6 months between male and female MSWA; and line (a) a 1-year 

difference in MSWA. Fillmore, Luck, and Petersburg Lakes have high proportions

of returning jacks, resulting in low male MSWA.
133

Tahltan, Crescent, and Chilkoot Lake stocks showed significant trends of increasing

male MFWA of the 14 stocks with 6 or more years of data (table 28). Despite the tight

correlation between male and female MFWA (fig. 31A), only Tahltan Lake females

showed a significantly increasing trend. Females in the Crescent and Chilkoot stocks

had increasing MFWAs, but the increases were not statistically significant.

Shipley Lake sockeye had a higher MFWA for both sexes than all other lake-type

stocks (fig. 32, A and B). Most Shipley Lake sockeye spend at least 2 years in fresh

water before emigrating to the ocean, but only 197 fish sampled over 2 years were

in the sample. No river—sea-type stocks (N = 24) had a distinctive MFWA. The

Hasselborg, East Alsek, Akwe, and Ahrnklin River stocks exhibited MFWAs ≤ 0.20

years, which suggests that large proportions of these populations were zero-check

individuals. The Hasselborg and Ahrnklin stocks both were sampled for age composition for only 1 year (1989 and 1987, respectively).

Four lake-type stocks have distinctive levels of sexual difference in MFWA; in

Christina and Kah Sheets Lakes, females spent more time in fresh water than did

males, and in Shipley Lake and Buschmann Creek the opposite pattern was present

(fig. 32C). Among these four populations, the Kah Sheets sample had 415 fish sampled over 5 years, but the others had less than 2 years of data. Two river—sea-type

stocks, Chum Salmon Slough (Taku River) and Lost River, also had distinctive levels

of MFWA difference (fig. 32D). Although Chum Salmon Slough has been sampled for

only 2 years, in both cases females spent less time in fresh water than did males.

Table 28—Regression analyses of trends across years in mean freshwater age (MFWA) and mean saltwater

age (MSWA) of sockeye salmon stocksa

MFWA MSWA

Stream Males Females Males Females

No.

years R- R- R- RNumber Name sampled squared Slope P-value squared Slope P-value squared Slope P-value squared Slope P-value

101-30-075 Hugh Smith 9 0.03 -0.01 0.5<P<0.9 0.07 -0.01 0.5<P<0.9 0.01 0.01 0.5<P<0.9 0.00 -0.00 P>0.9

Lake

102-60-087 Karta River 6 0.07 0.01 0.5<P<0.9 0.30 0.01 0.2<P<0.4 0.31 -0.05 0.2<P<0.4 0.38 -0.05 0.1<P<0.2

106-41-010 Salmon Bay 6 0.00 -0.00 P>0.9 0.37 -0.01 0.1<P<0.2 0.07 -0.03 0.5<P<0.9 0.27 -0.07 0.2<P<0.4

Lake

108-80-110 Tahltan Lake 8 0.65 0.01 0.01<P<0.02 * 0.75 0.02 0.001<P<0.01 ** 0.09 -0.01 0.5<P<0.9 0.15 -0.03 0.2<P<0.4

109-20-013 Falls Lake 7 0.30 -0.06 0.2<P<0.4 0.13 -0.03 0.4<P<0.5 0.30 -0.06 0.2<P<0.4 0.22 0.03 0.2<P<0.4

111-32-245 Little Trapper 6 0.40 0.02 0.1<P<0.2 0.50 0.03 0.1<P<0.2 0.29 -0.02 0.2<P<0.4 0.11 -0.01 0.5<P<0.9

Lake

111-33-034 Speel Lake 7 0.25 0.01 0.2<P<0.4 0.56 0.01 0.5<P<0.1 0.10 0.02 0.4<P<0.5 0.00 -0.00 0.5<P<0.9

111-35-007 Crescent Lake 7 0.59 0.02 0.02<P<0.05 * 0.02 0.00 0.5<P<0.9 0.20 0.06 0.2<P<0.4 0.20 0.02 0.2<P<0.4

111-50-042 Auke Lake 8 0.14 -0.01 0.2<P<0.4 0.02 -0.01 0.5<P<0.9 0.03 -0.03 0.5<P<0.9 0.01 -0.01 0.5<P<0.9

113-41-043 Redoubt Lake 8 0.26 0.04 0.2<P<0.4 0.24 0.04 0.2<P<0.4 0.37 -0.05 0.1<P<0.2 0.55 -0.05 0.02<P<0.05*

115-32-032 Chilkat Lake 9 0.01 0.01 0.5<P<0.9 0.02 0.01 0.5<P<0.9 0.06 0.02 0.5<P<0.9 0.04 0.01 0.5<P<0.9

115-33-020 Chilkoot Lake 9 0.52 0.03 0.02<P<0.05 * 0.40 0.03 0.05<P<0.1 0.05 0.00 0.5<P<0.9 0.38 0.01 0.05<P<0.1

182-30-020 Klukshu Lake 6 0.12 0.01 0.4<P<0.5 0.00 -0.00 P>0.9 0.24 -0.03 0.2<P<0.4 0.60 -0.22 0.05<P<0.1

182-70-010 Situk River 6 0.28 -0.04 0.2<P<0.4 0.02 -0.01 0.5<P<0.9 0.43 0.06 0.1<P<0.2 0.00 -0.00 P>0.9

a * = 0.05 > P > 0.01; ** = 0.01 > P > 0.001.
134

The annual variation of MFWA was high in the Falls Lake stock. Male MFWA ranged

from 1.12 for the 1988 return to 1.86 for the 1984 return, and female MFWA ranged

from 1.10 in 1988 to 1.93 in 1985. Falls Lake was fertilized from 1983 to 1985

(Burkett and others 1989), but data were not collected in enough years to determine

if MFWA was highly variable before lake fertilization. Studies of Falls Lake in 1981

and 1982, before fertilization, found 40 percent and 83 percent, respectively, of age

2.0 smolts emigrating from this system (Koenings and others 1984). The extended

rearing period was probably the result of forage limitations (Koenings and others

1984), and successful enhancement of lake productivity could account for the

decrease in MFWA seen recently. Alternatively, high interannual variation in age

structure could reflect run-strength cycles and the overlap of weak and strong brood

years. Outlier analysis was not conducted on degree of interannual variation

because only 14 stocks had sufficient data for inclusion.

Figure 32—Frequency distributions, outlier plots, and normal quantile plots for mean freshwater age (MFWA) characteristics.

(A) Lake-type males and (B) lake-type females. Shipley Lake males and females spend an average of 2.2 and 2.1 years in

fresh water prior to emigration; both distinctively high MFWAs. Despite transformation these distribution were very nonnormal; N = 55. (C) Lake-type and (D) river—sea-type sexual differences in MFWA. All named stocks in (C) and (D) had distinctive 
The same set of stocks was used to evaluate MSWA. Sex-specific MSWA and

MFWA were negatively correlated, significantly so for females (females, r = -0.47, 

P < 0.001; males, r = -0.15, P = 0.17). Because males return to spawn precociously

at a much higher frequency than females, male and female MSWAs were not tightly

correlated (fig. 31B). Distinctive levels of sexual differences in MSWA were present

in Fillmore, Luck, and Petersburg Lakes (fig. 31B), but the Fillmore Lake stock was 

sampled for only 2 years. In the extreme cases of the Fillmore and Luck Lake

stocks, female MSWAs were a year older than for males. High proportions (45 percent and 29 percent) of age 1.1 males in the escapement of these stocks may

account for the difference between male and female MSWA. Escapement samples

with > 20 percent jacks occurred in Trumpeter, Kutlaku, and Ford Arm Lake stocks,

but these lakes also had high proportions of x.3 males or x.2 females, which reduced

the overall difference in MSWA between males and females. Because age structure

results involving jacks may have been strongly influenced by sampling methodology,

these results should be interpreted cautiously.

The MSWA of females in 26 of 79 stocks ranged from 2.9 to 3.0, indicating very few

females returned precociously. Bakewell and Leask Lake females had the lowest

MSWAs, although Leask Lake was sampled only 1 or a few days each season.

Bakewell Lake stock, which was established from stocked fry, was sampled throughout

the course of its run, but for only 2 years. In both of these cases, the low female

MSWA was attributable to high proportions of 2-ocean-year fish (age classes 1.2, 2.2,

and 3.2). Assuming that 2-ocean-year females were large enough to be sampled proportionately, the low MSWA of these stocks may reflect distinctive maturation characteristics.

Year-to-year variation in MSWA was about the same as in MFWA, with no apparent

relation between year-to-year variation in MSWA and MFWA. Mean saltwater age 

differed more for males than females in 11 of the 14 stocks. Redoubt Lake was the

only stock showing a significant temporal trend in MSWA; female MSWA was decreasing significantly (table 28). Male MSWA was also decreasing in this stock but not 

significantly.

Outlier analyses of proportions of individuals in major age classes provided results

similar to the MFWA and MSWA analyses. Because the separate age-class

approach was more fine-grained, this technique identified a few additional stocks 

with unusual age-structure characteristics (figs. 33 and 34). Among lake-type stocks,

Bakewell Lake had distinctively high proportions of age 1.2 males and females, Leask

Lake had higher proportions of age 2.2 males and females than all other stocks, and

Shipley and Auke Lakes had distinctively high proportions of age 2.3 females.

Among river-sea-type stocks, the East Alsek and Lost Rivers had distinctively high

proportions of 0.2 females, and the Ahrnklin River had higher proportions of 0.3

males 

(fig. 34).

Sex ratio—Sockeye stocks did not show the wide range of sex ratios seen in chinook

and coho salmon stocks. Sex ratios (expressed as a percentage of males) for entire

populations (all age classes) ranged from 0.37 for the Ford Arm Lake stock to 0.68

for the Hackett River stock (weir-sampled populations, throughout their runs; N = 25; 

fig. 35). These sex-ratio estimates typically did not account accurately for jacks. 

The sex ratios of the predominant age classes of these stocks had a similar range,

135
136

from 0.25 for Ford Arm Lake to 0.68 for Hackett River. The Hackett River stock was

the only river-sea-type stock included in the evaluation of sex ratios, so whether a

sex ratio skewed in favor of males was a general characteristic of zero-check stocks

is unknown. The distribution of sex ratios for stocks in the region demonstrates that

population sex ratios cluster near 1:1 (fig. 35). A similar pattern holds for the sex

ratio of predominant age classes within populations.

The Hackett and Karta River systems had distinctive sex ratios in which males predominate, and the Ford Arm Lake sex ratio was skewed in favor of females (fig. 35).

Figure 33—Frequency distributions, outlier plots, and normal quantile plots for proportions of individuals by age and sex classes in laketype escapements. N = 51 for (A) age 2.2 males, (B) age 2.2 females, and (D) age 2.3 females; N=53 for (C) age 2.3 males. All distributions are very nonnormal despite transformation. All named stocks have distinctively high proportions of age 2.x individuals in

escapements. Auke and Leask Lakes are represented by relatively large samples.
137

A survey of electrophoretic diversity of 52 sockeye populations throughout the region

identified three geographic groupings that differed in allele frequencies (Guthrie and

others 1994). These groups corresponded to the southern inside waters, the far

southeastern islands including Prince of Wales Island, and inside waters of northern

and central southeast Alaska. Two further groups, northern coastal and northern

island, may exist but require additional sampling to confirm (Guthrie and others

1994). Analysis of stock groupings by migration entry routes yielded significant 

differences in total heterogeneity among entry route groups, but F-tests comparing

heterogeneity within and among entry routes were not significant (P =0.10; Guthrie

and others 1994). Rearing habitat (i.e., lake versus river-sea) did not affect the

underlying geographic patterns of genetic divergence (Guthrie and others 1994,

Wood and others 1994).

Genetic Surveys

Figure 34—Frequency distributions, outlier plots, and normal quantile plots for

proportions of individuals by age and sex classes in river-sea-type escapements: (A) age 0.3 males, N = 22; (B) age 0.2 females, N = 16. Both distributions are nonnormal despite transformation. Named stocks have distinctively

high proportions of the respective age and sex classes in escapements.

Samples from the East Alsek and Lost Rivers are relatively large.
138

Principal-component analysis and neighbor-joining trees suggested that the Tahltan

and Sitkoh Lake stocks have unusual allele frequencies. Several other stocks

diverged to a lesser degree (Shipley Creek, Galea Lake, and Juneau area stocks

may have been influenced by the egg transfer from Afognak Lake). In their survey of

British Columbia sockeye stocks, Wood and others (1994) found that fish from the

Stikine and Taku drainages cluster with those from the Nass and Skeena Rivers to

the south. The Klukshu Lake stock from the Alsek River drainage clustered with

southern river stocks including the Fraser and Columbia (Wood and others 1994).

Six locations showed temporal heterogeneity in allele frequencies (McDonald Lake,

Karta River, Salmon Bay Lake, Yehring Creek, Tatsamenie Lake, and the Chilkat

drainage), thereby suggesting genetic substructure in these populations.

Seven stocks may have distinctive biological characteristics, but they were not included in the analyses because data were limited either in quantity or quality or the

spawning location was uncertain.

• Excursion Inlet—Purse seine harvest is dominated by age 2.3 fish (McGregor and

McPherson 1986). The predominance of this age class suggests a particularly high

MFWA. Spawning location is unknown.

• Redfish Bay—Harvest is dominated by age 2.3 fish (McGregor 1983, McGregor and

McPherson 1986). Again, the predominance of this age class suggests a particularly high MFWA. There has been a long exploitation history (Roppel 1982). Current

management is based on annual determination of run strength in the bay and a 

limited purse seine fishery is allowed if adequate fish are present (see footnote 5).

• Essowah Lakes—Fish of small body size.7 Data from 1 year of sampling do not 

support this contention.

Anecdotal Reports

Figure 35—Frequency distribution, outlier plot, and normal quantile plot for proportion of males in escapements. Named stocks all have distinctive sex ratios, and all

are represented by large samples collected at weirs.

7 Personal communication. 1996. P. Peyton, consultant, P.O. Box

22871, Juneau, AK 99802.
139

• Kanalku Lake—Small body size and early migration timing.8 A fish pass constructed

in the early 1970s was destroyed by high water within a few years of installation

(Bibb 1987).

• Virginia Lake—May have small body size or low MSWA associated with flow limiting

barriers (see footnotes 3 and 4). Fish passes, lake fertilization, and fry stocking

have occurred at Virginia Lake, beginning in 1989 (Parry and others 1993).

• Mahoney Creek—May have small body size or low MSWA associated with flow limiting barriers (see footnotes 3 and 4).

• Kook Lake—Outlet stream passes underground in karst topography; some spawning occurs within the cave.9

Among river—sea-type stocks, the Hasselborg River stock deserves comment. This

stock is thought to consist entirely of stream spawners, with juveniles rearing in a salt

chuck rather than a freshwater lake.10 The Hasselborg River stock is also noteworthy

in being located in a small clearwater stream on Admiralty Island while all other riversea-type stocks are located on the mainland. Outside southeast Alaska, zero-check

sockeye stocks are typically found in large glacial mainland systems (Wood and others 1987).

Body length—The Speel and Crescent Lake stocks were the only stocks showing

well-defined changes in body size; both stocks are increasing significantly in body

length. Both stocks were considered to be depressed, relative to their former abundance, and were the object of time and area closures designed to allow rebuilding

(McGregor 1985). Despite these restrictions, exploitation rates on these stocks have

remained at about 55 percent, the mean estimated exploitation rate for 1983 to 1989

(Jensen and others 1990, McGregor and Jones 1989). The reduction in exploitation

rates of these stocks or a partial shift from gill-net to purse-seine harvest may have

contributed to an increase in the body size of fish in escapements (McPherson and

McGregor 1986). Older and larger fish are known to be harvested differentially in gillnet fisheries (Jensen 1991, McGregor 1986, McPherson 1989). Increasing male size

in the Speel and Crescent Lake stocks may have been the result of reduced selective

removal of large fish.

There was a weak regionwide trend of increasing body length, particularly in males.

Mathisen (1962) and Simpson (1969) suggest that large male sockeye are selectively

harvested by gill nets in comparison to females. The switch to purse-seine harvesting may have accounted for the increase in the size of males.

8 Personal communication. 1996. M. Laker, fisheries biologist/ecologist, USDA Forest Service, Tongass National Forest, Admiralty

National Monument, 8461 Old Dairy Road, Juneau, AK 99801.

9 Personal communication. 1996. V. Starostka, fishery and wildlife

staff assistant, USDA Forest Service, Tongass National Forest,

Chatham Area, 204 Siginaka Way, Stika, AK 99835.

10 Personal communication. 1996. S. McPherson, fisheries biologist, Alaska Department of Fish and Game, 801 3d Street,

Douglas, AK 99824.

Discussion

Evaluation of Results
140

Alternatively, favorable ocean conditions in recent years may have contributed to 

the increases in male body length. There is some evidence of recent high ocean 

productivity (Brodeur and Ware 1993), but the interacting effects of ocean productivity

and density-dependent competition on body size is unclear and possibly variable

(McKinnell 1995; Peterman 1984, 1985; Rogers and Ruggerone 1993).

Timing—Interior stocks in southeast Alaska and in the Copper River (Merritt and

Roberson 1986) have more compact runs than coastal stocks. Several factors may

contribute to this pattern. The coastal climate is generally less variable than the continental climate of the interior, which may reduce the intensity of selection for precise

timing of spawning, emergence, and emigration. Compact run timing also may be

associated with compact emergence timing, possibly keyed to food resources or flow

conditions. Flow rates also can contribute to compact run timing by creating temporary velocity blocks to spawner migrations. An example is on the Stikine River for

stocks spawning in Tahltan Lake, an interior spawning area more than 300 km from

saltwater (Richardson and Johnston 1966). The Tahltan Lake stock has compact run

timing compared to other stocks in the area (Jensen and Frank 1988); however,

results from Stikine River test fisheries indicate that the Tahltan Lake stock also has

more compact run timing through nearshore waters than non-Tahltan stocks (coastal

and interior) (Jensen and Frank 1988). Thus, both flow conditions and adaptive factors may contribute to compact run timing in the Tahltan Lake stock.

Analysis of trends in the mean migration dates of 13 stocks revealed that the two

stocks with the longest data series, Tahltan and Chilkat Lakes, had significant

changes in their mean migration dates. The Tahltan Lake stock is returning progressively earlier and the Chilkat Lake stock is returning progressively later. Fisheries

probably selectively remove later fish in the Tahltan Lake stock, because this stock

migrates through existing fisheries earlier than other stocks in its region (Jensen and

Frank 1988). In contrast, fisheries are likely to remove early returning fish from the

Chilkat run, because that run is later than other Lynn Canal runs. The Chilkat run 

has two distinct run segments, however; the later migration date may be due to

strengthening of the later run segment relative to the early segment. The data were

consistent with expectations based on fisheries effects, but other factors also may be

influencing timing trends of the Chilkat stock.

The duration of the Chilkat run was longer than that of any other stock. Two distinct

populations may be present in Chilkat Lake (Guthrie and others 1994, McPherson

1990). Currently, the late stock tends to be more abundant than the early stock.

McPherson (1990) describes the spawning time of the early stock as extending from

15 July to 31 August and the late stock from 1 September to 15 February. The late

return of the late stock is the primary cause of the extended run duration to Chilkat

Lake. Both early and late stocks spawn along lake beaches as well as tributary

streams. Juveniles resulting from late spawning are believed to emerge late and

consequently show a 2.x or even a 3.x life history pattern. This difference in rearing

time was reflected in the age structure of returning adults. The early component of

the run to Chilkat Lake consists primarily of 1.x fish, and the late portion of the run

consists primarily of 2.x fish.
141

Causes of potential divergence among stocks in Chilkat Lake are unknown, but two

possible explanations are presented: (1) fisheries practices may selectively remove

the central portion of the run, thereby imposing disruptive selection on run timing; and

(2) flow reversals between Chilkat Lake and the Tsirku River may separate the

stocks. When lake levels are low, or during high river flow conditions, river water

from the Tsirku flows into Chilkat Lake; this flow reversal occurs regularly and is considered normal (Bergander and others 1988). Fish do not enter the lake during flow

reversals. If flow reversals occur consistently and are sufficiently prolonged, they

may impose a substantial gap in the migratory timing of fish into Chilkat Lake.

Differences in run timing may in turn serve to reproductively isolate early and late

populations to the degree necessary for genetic divergence. Prolonged flow reversals could have the effect of retarding the phenology of late-spawned juveniles and

account for the higher proportion of age 2.x individuals in the late stock. In addition,

unrecorded stocking or fry transfers cannot be excluded.

Chilkoot Lake also had relatively prolonged run timing. This lake also is believed to

be inhabited by two distinct sockeye populations (McPherson 1990). Early and late

migrating stocks in Chilkoot Lake overlap to a greater extent than the two stocks in

Chilkat Lake; the spawning dates of the early and late stocks were defined by

McPherson (1990) as 1 July to 15 August and 1 August to 15 October, respectively.

The early stock spawns primarily in small tributaries and the later stock spawns in the

mainstem of the Chilkoot River and on lake beaches (McPherson 1990). Both stocks

in Chilkoot Lake are dominated by age 1.x individuals, with smolts leaving the lake at

a comparatively small size (see footnote 10). The late stock is more abundant than

the early stock, as is the case in Chilkat Lake.

The presence of two stocks in Chilkoot Lake may be the result of a transfer of 2 million eggs from Chilkat Lake in 1917 (Roppel 1982). Alternatively, natural colonization

of Chilkoot Lake by sockeye from Chilkat Lake is certainly possible, given the proximity of these systems in upper Lynn Canal. The late runs in the two lakes differ in duration of spawning, location of spawning, duration of freshwater rearing period, and size

at outmigration. Bimodal run timing also could be due to fisheries practices or habitat

segregation.

Hugh Smith and Kegan Lakes are other locations having prolonged migrations and

some indications, not statistically significant, of genetic divergence within the population (Guthrie and others 1994). No transfers of eggs from other stocks are known to

have occurred to either of these stocks. Escapements to Hugh Smith Lake in some

years show bimodality in run timing (Bergander 1972). Two streams are the primary

spawning locations for Hugh Smith Lake sockeye; Cobb Creek spawners have 

compact run timing, and Buschmann Creek spawners have protracted run timing 

(see footnotes 3 and 4). Historically, very heavy fishing pressure (Kutchin 1903, cited

in Roppel 1982) may have reduced the population to a few fish. In addition, hatchery

operations and lake fertilization (Peltz and Koenings 1989, Roppel 1982) may have

influenced run timing. Hatchery-incubated fry were stocked in Hugh Smith Lake from

1986 through 1992 in numbers ranging from 250,000 to 1,480,800 (see footnotes 3

and 4). The potential effects of enhancement activities on run timing have been

demonstrated by recent fry plants: fry hatched from eggs taken from Buschmann

Creek during a brief segment of the run were replanted into Hugh Smith Lake, and

corresponding changes in run timing were noted (see footnotes 3 and 4).
142

Among interior stocks in the Taku River, the Little Tatsamenie Lake system stock has

protracted run timing past the Canyon Island fish wheel (McGregor and others 1991).

This stock also shows genetic heterogeneity (Guthrie and others 1994), providing another example of a potential association between run duration and genetic structure

of sockeye populations. The run duration of the Klukshu Lake stock is over twice that

of any other interior stock and, like other stocks with prolonged runs, is likely to exhibit within-population heterogeneity in allozyme frequencies.

Demography, declining stocks—The eight stocks having significant population

declines showed no apparent patterns in terms of geographic location or stock size.

Five of these stocks were found in systems having minimal known human impacts on

spawning habitats (Hunter Bay, Klakas Lake, Lake Creek-Shipley Bay, Gut Bay, and

Situk River). Declines in these stocks may be due to natural variability, changes in the

capability of the habitat to support sockeye salmon, or changes in harvest patterns.

Three declining stocks were found in systems with differing degrees of human

impacts on spawning habitats. The Auke Lake stock is monitored at a weir. Pavlof

Lake stocks are counted during foot surveys, and those at Mosquito Lake have

changed from foot surveys to boat survey to fixed wing aerial surveys.

Among causes thought to be responsible for the decline of the Auke Lake stock are

(1) alteration of spawning habitat, including gravel removal from and road building

near Lake Creek, the primary spawning tributary; (2) limnological changes caused by

wastewater effluent entering the lake; and (3) experimental manipulations, which

involved smolt trapping and ensuing high smolt mortality (Taylor 1987). A drought in

summer 1993 caused the outlet stream to Auke Lake to dry up, and sockeye were

mechanically transported to Auke Lake for part of the run. Low water also led to

spawning in suboptimal habitats. These factors may contribute to further declines in

the Auke Lake stock. Sport-fishing restrictions have been instituted in Auke Bay to

protect returning sockeye.

If counts completed by the USFWS from 1953 to 1959 are included in the regression

analysis for the Pavlof Lake stock, the decline becomes nonsignificant (0.1 < P <

0.2); however, historical escapements up to 50,000 sockeye were reported before

1900 (Moser 1902, cited in Bibb 1987). A step-pool fishway was completed in 1935

to circumvent a 4.3-m waterfall at tidewater. This fishway was replaced with a more

effective fish pass in 1974; an additional fish pass was added at a 2.8-m falls above

Pavlof Lake in 1987.11 Increased competition with other salmonids due to access 

provided by these fishways, heavy subsistence harvest, and changes in habitat 

quality due to road building and timber harvest may be contributing factors to sockeye population decline in this system.

The mean escapement survey count was 119 sockeye salmon for Mosquito Lake.

Habitat degradation, caused by residential development around the lake, and the

potential for high sport harvest as a result of easy lake access are possible contributors to the decline of this stock.

11 Personal communication. 1996. C. James, biological technician,

USDA Forest Service, Tongass National Forest, Hoonah Ranger

District, P.O. Box 135, Hoonah, AK 99829.
143

Escapement magnitude—McDonald Lake is the only exceptionally large sockeye

stock remaining in the southern half of southeast Alaska. It also has been extensively manipulated. Nutrients have been added to the lake in recent years. Eggs and fry

were stocked from Afognak (Litnik) Lake decades ago (Roppel 1982). In addition,

hatchery operations, predator control, releases of brook trout, lake fertilization

(Burkett and others 1989), and heavy harvests (Roppel 1982) may have modified

stock composition.

Harvest of sockeye salmon in the East Alsek system have increased dramatically in

recent years, from an average of 13,798 fish in 1960-79 to 83,532 fish in 1980-88,

which probably reflects expansion of the stock, as well as an increase in fishing effort

(Rowse 1990). In contrast to the McDonald Lake stock, the East Alsek stock 

does not have a long history of manipulation and exploitation but was exposed to

substantial recent changes in stream-channel morphology. Migration of the Alsek

River channel and ground-water upwelling through gravel deposits resulted in the 

formation of the East Alsek River in the 1960s (McPherson 1987). The East Alsek

River is relatively short (about 12 km), is of low gradient, and has no available lake

for rearing habitat, which may account for the high incidence of zero-check individuals. The high proportion of gill-net harvest of this stock may be contributing to the

high proportion of age 0.2 fish in escapements. The East Alsek River currently supports the largest sockeye fishery in the Yakutat region (Pahlke 1989a, Rowse 1990). 

Age structure—Exploitation rates on older and larger fish tend to be higher (e.g.,

Jensen 1991, McGregor 1986, McPherson 1989), and the expected effect of selective

removal of large fish by gill nets is a decrease in age in escapements. In general,

fish harvested by purse seine tend to be younger and more variable in age than fish

taken by gill net (McPherson and McGregor 1986). The only significant trends in age

structure we found were for increasing age, which may reflect an increasing trend in

the proportion of the catch taken by purse seines. Other factors that might contribute

to the weak trend of increasing age are ocean conditions favorable to growth in

recent years and dramatic differences in the recruitment strength of certain yearclasses (see footnote 1). If the progeny of a very strong year-class were to dominate

returns for several years, this would result in a progressive increase in age for a stock

over the course of a 5- to 10-year time series.

The MFWA of sockeye in Shipley, Auke, and Leask Lakes was greater than other

stocks in southeast Alaska (figs. 32 and 33). The estimate of MFWA of the Shipley

Lake came from a small sample in only 2 years. A hatchery operated for 1 year,

1903, at Shipley Lake and 1,700,000 fry were planted in the lake during this year

(Roppel 1982). Presumably the fry planted were the result of eggs being taken from

Shipley Lake. Auke Lake sockeye showed a high proportion of age 2.3 individuals in

escapements. More than 5 million sockeye eggs were transferred from Afognak Lake

to Auke Lake in 1922 (Roppel 1982), but this transfer is unlikely to explain the unusual age structure, because age 2.3 individuals made up less than 15 percent of

escapements to Afognak Lake from 1985 to 1989 (White and others 1990). Furthermore, survival of the transferred eggs is thought to have been very low (Roppel

1982). Leask Lake had an exceptionally high proportion of age 2.2 individuals in

escapements. Usually only a small segment of the run was sampled each year and

the sample dates differed among years, but high proportions of age 2.2 individuals

were found in samples from all years.
144

The Leask Lake sockeye stock had a relatively low female MSWA, compared to other

lake stocks in the region (in addition to having a high MFWA). Abbreviated ocean

residence by the Leask Lake stock may be associated with a small barrier to migration that is negotiable only by smaller fish (see footnotes 3 and 4). For sockeye

salmon, returning after 2 ocean years may be functionally equivalent to the early 

season returns seen in coho salmon that inhabit locations with flow barriers. Early

returns are not associated with particularly rapid ocean growth: 2-ocean-year

females from Leask Lake return at sizes similar to those of 2-ocean-year females

from other stocks.

The decreasing trend in MSWA in the Redoubt Lake stock may be related to lake fertilization. A significant increase in smolt size has occurred since fertilization of this

lake began in 1984 (Burkett and others 1989), and larger smolts tend to spend less

time in the ocean (Bradford and Peterman 1987; but see also Koenings and others

1993). Hyatt and Stockner (1985) suggest that less time in the ocean reduces exposure to marine predators and may increase marine survival, which in combination

with the predator-avoidance advantages of larger smolts, may contribute to a positive

relation between smolt size and marine survival. When lake-fertilization programs

increase the number of returning fish, body size often decreases (Hyatt and Stockner

1985), but this trend was not evident at Redoubt Lake. Although the number of sockeye returning to Redoubt Lake is increasing nearly significantly, body-length data 

from 1982 to 1989 showed no significant trend in body size for age 2.2 individuals

(table 22). 

Sex ratio—The sex ratio tends to be close to 1:1 for most sockeye salmon stocks.

This may be the result of nonselective purse-seine harvests that do not differentially

remove larger (male) sockeye. Only Speel and Crescent Lakes showed high levels

of interannual variation in sex ratio, for unknown reasons. At Crescent Lake this variation might be due to fish escaping through the weir, which would prevent proportional sampling (see footnote 5).

The comparisons used to identify distinctive sockeye stocks were regionwide in

scope. The geographic framework was based on political boundaries rather than biological criteria. Analysis of genetic divergence among sockeye populations indicated

that genetic variability within the region clusters into three geographically definable

groups.12 The process of identifying distinctive stocks therefore might be more appropriately conducted at smaller geographic scale of these genetic groups. As techniques for genetic characterization of populations improve, and additional data allow

refinement of methods used to discriminate phenotypically distinctive stocks, comparative analyses at smaller scales should be considered. Large drainage basins that

contain numerous sockeye populations, such as the Taku River basin, constitute a

biologically meaningful lower limit of geographic scale for conducting the sort of 

comparative phenotypic analyses presented here.

Sexual selection—Sexual selection in Pacific salmon has not been well studied,

despite several life history attributes that render these species particularly suitable

subjects for studies of reproductive behavior and the evolution of sexual dimorphism

(Quinn and Foote 1994). The intense competition associated with semelparity and a

relatively short peak spawning season, facilitate the determination of factors that may

12 Personal communication. 1996. C. Guthrie, fishery biologist,

National Marine Fisheries Service, Auke Bay Laboratory, 11305

Glacier Highway, Juneau, AK 99801.

Conceptual Issues
145

be responsible for differences in morphology and reproductive behavior (Quinn and

Foote 1994). Among Pacific salmon, sockeye are noted for high levels of sexual

dimorphism and particularly bright spawning coloration.

The typical pattern of age 1.3 and 2.3 males being larger than females may be the

result of competition among males for access to females. Large size may provide an

advantage in this competition (Hanson and Smith 1967, Quinn and Foote 1994; but

see Healey 1987; Holtby and Healey 1986, 1990; Schroder 1981). The greater level

of sexual dimorphism found in river-sea-type stocks suggests that sexual selection

may be more intense in these stocks. Competition for access to females could be

intensified by a high level of synchronization in spawning or by sex ratios biased in

favor of males (e.g., Schroder 1982). Increased sexual dimorphism also could result

from relaxation of selection for large body size on females (if spawning habitat is not

limited) or intensified selection by abiotic factors for reduced female size (Fleming

and Gross 1989, Healey 1987).

The strong correlation between length and fecundity in females may constrain possible female body lengths to a more narrow range than that for male body lengths.

These constraints could produce the observed pattern of female sockeye salmon 

having a higher level of stock-specificity in body length than males, as seen in our

variance component analysis. Male body size may be subject to a more complicated

suite of selection pressures that has the net effect of increasing variability. For

instance, sexual selection may favor larger body size in males that pursue a competitive reproductive strategy, but the potential for successfully pursuing alternate reproductive strategies, such as returning as jacks, could maintain genetic diversity for

small size (Gross 1985, 1991).

Body size and shape, especially hump size, were good predictors of male breeding

success among beach-spawners in Iliamna Lake (Quinn and Foote 1994). Lake

spawners are most likely to show the greatest hump development, and perhaps the

least length dimorphism, compared to river or stream spawners. Energetic costs

associated with increased hump size may limit development of this characteristic in

river spawners, especially those using interior rivers. Increased length dimorphism in

river-sea-type stocks may be permitted by reduced energetic investment in hump

development. In stream spawners, bear predation as well as water depth and current

are likely to limit hump development (Quinn and Foote 1994).

Sea-type sockeye stocks, and life history evolution—Phylogenetic relationships

among sockeye, pink, and chum salmon are subject to debate. Evidence from studies of morphology (Smith and Stearley 1989), biochemistry (Utter and others 1973),

and nuclear DNA support a sister group relationship between sockeye and pink

salmon. Life history (Smith and Stearley 1989) and mtDNA (Thomas and others

1986) data support a sister group relationship between pink and chum salmon. One

derived life-history characteristic used to support the close relationship between pink 

and chum salmon is the reduced freshwater phase, with juveniles ready to emigrate

as they emerge from the gravel (Smith and Stearley 1989). This capacity can be

viewed as the current endpoint in an evolutionary trend toward decreasing reliance

on freshwater spawning and rearing habitats. Studies of zero-check sockeye in the

Situk River indicate that some sockeye begin moving to estuarine environments at a
146

small size (about 50 mm in fork length) and the timing of emigration for some sockeye in these populations is similar to that of pink and chum stocks in the system

(Heifetz and others 1989, Thedinga and others 1993). This work suggests that the

emigration behavior of sea-type sockeye is intermediate between that of the pinkchum group and the chinook-coho group. Information on the emigration behavior of

other sea-type sockeye stocks is needed to determine the usefulness of this characteristic for testing phylogenetic hypotheses. The relatively numerous sea-type sockeye stocks found in southeast Alaska could be useful in this context.

The East Alsek River stock could provide an opportunity for investigating the pace of

adaptation for freshwater rearing period. The East Alsek River separated from the

mainstem Alsek during the 1960s. The main Alsek River is not known to have a large

sea-type component in its sockeye population (McBride and Bernard 1984; Rowse

1990). The development of a large sea-type stock in the East Alsek may have resulted from (1) colonization of the East Alsek River by the relatively rare sea-type fish

from the Alsek River stock preadapted to the novel conditions encountered in the

East Alsek; (2) colonization by strays from nearby systems with similar habitat characteristics and dominated by sockeye stocks with sea-type life histories; (3) a rapid,

environmentally induced (phenotypic) shift in life history by lake- or river-type

colonists from the Alsek River; or (4) an extremely rapid adaptive (genotypic) shift in

life history. Genetic techniques that permit relatively fine-grained discrimination of

stocks may permit a test of these hypotheses by helping to determine the source or

sources of East Alsek River colonists.

Most sea-type stocks occur in morphologically active river systems, with shifting

channels and high sediment loads. Many river systems in southeast Alaska have

active glaciers and may have been blocked by recent movement of these glaciers

(e.g., Ferrians and Nichols 1955). As a result, access to lake spawning and rearing

areas may have been blocked, thereby leaving no alternative for fry except for a seatype life history. Landslides also can block access to upstream lakes, and sea-type

sockeye observed in the Fraser River by Birtwell and others (1987) may be the result

of the landslide that occurred at Hell’s Gate in 1913 (Foerster 1968). River blockages

also contribute to the development of strictly freshwater populations of sockeye 

(kokanee).

Parasites—At least 42 different species of parasites and numerous bacterial and

viral pathogens infect sockeye salmon (Margolis 1963, cited in Foerster 1968). Most

work on the parasitology of sockeye salmon has been on using parasites for stock

separation or to investigate aspects of life history, such as migratory behavior

(Konovalov 1995, Quinn and others 1987). In a recent review of sockeye life history,

Burgner (1991) refers to parasites only in terms of prespawning mortalities in Fraser

River runs and as a possible factor in Skeena River population cycles. Relatively little research has been conducted on the effects of parasites on the ecology and population dynamics of sockeye stocks, despite their potential importance. Garnick and

Margolis (1990), for example, report that helminth parasites may have detrimental

effects on the ability of sockeye smolts to orient properly. Detrimental effects of parasites are generally more severe in juvenile life stages, but these critical stages are

the least studied.
147

In southeast Alaska, the presence of Myxobolus neurobius has been widely investigated as a biological marker for separating stocks (Moles 1987, Moles and others

1990), but the pathology caused by this parasite is not well understood. The pathology of infectious hematopoietic necrosis virus (IHNV) is better studied, because of its

detrimental effects on hatchery production of sockeye (Saft and Pratt 1986). The

effects of this nearly ubiquitous virus on wild stocks in southeast Alaska are unknown.

Epizootic outbreaks of this virus have been reported from British Columbia (e.g.,

Williams and Amend 1976). Because of the usefulness of parasites in sockeye stock

separation, more information is available on the parasites of sockeye stocks than for

stocks of other Pacific salmon in the region. This parasite-distribution information

sets the stage for studies of the ecological and evolutionary effects of parasites on

sockeye populations. Myxobolus neurobius, for example, was found in all sampled

populations in southeast Alaska except Steep Creek, Chilkat, and Chilkoot Lakes

(Moles 1987), but why these populations are not parasitized is unknown. Experimental infections can be used to determine if absence of certain parasites indicates

resistance or lack of exposure. Parasite resistance is a component of intraspecific

diversity with important ramifications for enhancement programs.

Variation in run strength and cyclic patterns—Sockeye salmon runs are highly

variable and often show little relation between escapement and recruitment (Foerster

1968). Eggers and Rogers (1987) ascribe fluctuations to depensatory fishing, but

Walters and Woodey (1992) suggest that cyclic fluctuations are natural. Numerous

factors in both freshwater and saltwater environments probably contribute to fluctuations in run size, but one of the goals of management is to maintain constant ”optimum” escapement numbers to major sockeye salmon producing systems. The 

ecological effects of modifying cyclical escapements of sockeye salmon are largely

unknown. 

Long-term ecological consequences of sockeye salmon cycles include effects on

nutrient budgets, predator-prey interactions, juvenile salmonid survival and growth,

and zooplankton populations. Large escapements of sockeye salmon deliver nutrient

pulses to stream and lake ecosystems (Kline and others 1990, 1993; Mathisen 1972; 

Richey and others 1975), which increases productivity of the aquatic ecosystem.

Large populations of sockeye fry are capable of overgrazing their zooplankton forage

base (Koenings and Burkett 1987), and size-selective predation by juvenile sockeye

salmon can alter zooplankton population structure (Stockner 1987). Density-dependent effects decrease juvenile sockeye salmon growth and increase freshwater residence time, resulting in higher predation rates by juvenile coho salmon or other

species that prey on sockeye fry (Ruggerone and Rogers 1992). 

Although few sockeye stocks in southeast Alaska seem to be declining, several

potential risk factors exist, including fishing pressure, enhancement activities, and

habitat degradation. None seems to offer immediate threats to most stocks in southeast Alaska, but risk to smaller stocks or localized stocks may be greater than for

other larger stocks that are more closely monitored.

Risks from fishing pressure derive from overexploitation and harvest of mixed stocks.

Sockeye salmon are among the most economically valuable of salmon species harvested in the region, which can lead to increased harvest demands. Consequently,

managers are likely to face increasing pressure from fishers to increase quotas,

Risk Factors
148

decrease escapement goals, or produce more fish. Mixed-stock management increases the vulnerability of small stocks (e.g., Hilborn 1985). Escapements of small

stocks often are not well monitored and management of them often is lumped with

larger stocks. Subsistence fishing on localized sockeye stocks may be substantial

and harvest rates can be difficult to manage.

Lake fertilization is one of the more common enhancement efforts to increase sockeye salmon production. Although lake fertilization can increase the number of sockeye salmon available for harvest, potential risks include overexploitation of natural

stocks mixed with artificially enhanced stocks, changes in biological characteristics 

of stocks, and changes in ecosystem dynamics resulting from increased sockeye fry

numbers and lake productivity.

Fertilization tends to be successful in increasing the harvestable biomass of sockeye

stocks. When fertilization increases the number of sockeye salmon, the fishery usually expands, which can lead to overharvest of other stocks with lower productivity

that pass through the fishery (see Hilborn 1985). The most obvious management

remedy is to increase harvest effort on the harvest area nearest the enhanced stock.

If fertilization is discontinued, the new harvest levels must be established to avoid

overexploiting stocks producing at prefertilization levels. Although fertilization may

increase the number of harvestable fish, the size of returning fish decreased in some

Canadian populations after fertilization (Hyatt and Stockner 1985). Lake fertilization

may produce responses in zooplankton populations and lake ecology similar to those

suggested during cyclic patterns of sockeye escapement, such as changes in zooplankton species composition and cyclic patterns of zooplankton productivity.

Stocks in particular habitats or locations may be vulnerable to habitat alterations,

either natural or human-caused. Sockeye stocks with high proportions of stream

spawners may have more variable productivity than stocks dominated by lake spawners. The Auke Lake stock, for example, has a high proportion of stream spawners

and unstable fry production, caused by fall freshets that scour redds and low winter

flows that leave redds without enough water (Taylor 1987). Urban development

around Lake Creek, the primary spawning area of the Auke Lake stock, contributes to

increased sediment load to the spawning area. Stream-spawning sockeye stocks are

more likely than lake spawners to be adversely affected by land-use activities that

disrupt the hydrology and flow regimes of watersheds or increase sediment loads.

The potential for the Hubbard Glacier to block Russell Fjord and divert its water

through the channel of the Situk River is a unique risk factor. Most sea-type sockeye

that spawn in the Situk system use the Old Situk River, the channel that would be

most heavily affected by flooding (Thedinga and others 1993). Furthermore, the Old

Situk channel provides important winter habitat for river-type sockeye in the Situk 

system (Thedinga and others 1993). New habitat would be created following the flow

alterations, but habitats and population would be unstable for an unknown period of

time.
149

About 200 populations of sockeye salmon are relatively evenly distributed throughout

the study region. At least 7 years of escapement data are available for 97 of these

stocks, and data on biological characteristics are available from at least 1 year of 

sampling for 85 stocks. Most stocks in the region have a lake-type life history, but at

least 24 stocks have relatively large proportions of individuals that have either a riveror sea-type life history, including most stocks on the Yakutat forelands.

Age 1.3 individuals tended to be larger than age 2.3 individuals, indicating that the

extra year in fresh water does not lead to larger adult size. Body size of sockeye

salmon showed a generally increasing trend, in contrast to the decreasing trends

present in other species of Pacific salmon in the region. Run timing of interior stocks

was significantly more compact than timing of island or coastal-mainland stocks. 

Surveys of electrophoretic allele frequencies indicated strong geographic patterning,

and at least three geographic clusters have been recognized (southern inside, southeastern island, and inside north and central). 

A larger proportion of sockeye stocks have distinctive characteristics than do other

species of Pacific salmon evaluated. This may reflect a combination of higher level

of homing fidelity attributed to sockeye salmon, which reduces gene flow among populations, high levels of phenotypic plasticity in response to differing environmental

conditions, or the superior quantity and quality of data available for sockeye stocks. 

The following stocks had distinctive biological characteristics, based on relatively

large samples (see fig. 36 for approximate geographic locations):

• Leask Lake—high proportions of age 2.2 individuals of both sexes in escapements.

• McDonald Lake (Hatchery Creek)—large population size (possibly artificially maintained by lake fertilization); high proportion of stream spawners; possibly two stocks

present.

• Karta River—distinctively large age 1.2 males. This stock is near or at the top of 

the size distribution for all other sex and age classes. Sex ratio skewed in favor of

males.

• Luck Lake—reverse sexual size difference, and high level of sexual difference in

MSWA (high jack proportion).

• Kah Sheets Lake—high level of sexual difference in MFWA (females remain in fresh

water longer).

• Petersburg Lake—high level of sexual difference in MSWA (high proportion of

jacks).

• Hackett River—river-type stock with a sex ratio skewed toward males.

• Auke Lake—high proportions of age 2.3 females in escapements; also a declining

population.

• Ford Arm Lake—lake-type stock with a sex ratio skewed toward females.

• Chilkat Lake—large population size; two separate stocks probably present; 

prolonged run duration.

• Chilkoot Lake—large population size; two separate stocks probably present.

• East Alsek River—high proportion of age 0.2 individuals in escapements of this 

distinctively large sea-type stock (mean escapements > 30,000 fish).

Conclusions
150

Figure 36—Approximate geographic locations in the study area of sockeye salmon stocks that have distinctive characteristics. Stocks 1 to 14 have been sampled relatively thoroughly. Stocks 15 to 24 are preliminary results based on limited samples. Stocks 25 to 27 have distinctive allele frequencies based on

surveys by Guthrie and others (1994) and Wood and others (1994).
151

• Situk River—large population size; lake-, river-, and sea-type life histories all in the

same system.

• Lost River—high level of sexual difference in MFWA (males remain in fresh water

longer); high proportion of age 0.2 females in escapements.

The following stocks show distinctive characteristics based on limited sampling (these

results are preliminary):

• Fillmore Lake—large sexual difference in MSWA (high proportion of jacks).

• Buschmann Creek—large sexual difference in MFWA.

• Bakewell Lake—high proportion of age 1.2 individuals of both sexes; an artificial

population.

• Shipley Lake—high MFWA, high proportions of age 2.3 females in escapements;

large sexual difference in MFWA; also a declining population.

• Christina Lake—large sexual difference in MFWA.

• Pavlof Lake—large sexual difference in body length of age 1.3 individuals; also a

declining population.

• Hasselborg River—zero-check life history predominates; only island stock having

this life-history pattern; stream spawning with juveniles rearing in salt chuck.

• Lake Anna—large sexual difference in body length of age 1.3 individuals.

• Benzeman Lake-Necker Bay—small adult body size (in harvest); age 2.2 and 2.3

fish predominate (in harvest). 

• Ahrnklin River—high proportion of age 0.3 males.

The following stocks have unusual electrophoretic allozyme frequencies, based on

existing surveys:

• Tahltan Lake—interior lake in the Stikine River drainage; this stock also may produce smaller eggs than other Stikine stocks (Craig 1985).

• Sitkoh Lake—only Chichagof Island stock included in the analysis.

• Klukshu Lake—interior lake in the Alsek River drainage; clusters with southern

British Columbia stocks.

Based on anecdotal reports the following stocks may have distinctive characteristics:

• Excursion Inlet—purse-seine harvest in the inlet dominated by age 2.3 fish; the predominance of this age class suggests a particularly high MFWA; spawning location

unknown. 

• Redfish Bay—harvest dominated by age 2.3 fish; the predominance of this age

class suggests a particularly high MFWA.

• Kanalku Lake—small body size and early migration timing.

• Mahoney Creek—may have small body size or low MSWA associated with flowlimiting barrier.

• Virginia Lake—possible small body size or low MSWA associated with historic 

barrier; effects of fish pass and intensive enhancement activities on native 

population unknown.

• Kook Lake—karst topography, cave spawning.
152

Figure 37—Approximate geographic locations in the study area of sockeye stocks with significantly declining escapement trends (stocks 1 to 8), or that inhabit “impaired” (Ward Cove, stock 9) or “suspected”

water bodies (stocks 10 to 13).
153

Significantly declining escapement trends were found for eight sockeye salmon populations (8 percent of those evaluated; see fig. 37 for approximate geographic locations). Only two of the eight stocks were represented by relatively good data.

Distinctive characteristics were present in three of the declining populations. Five

declining populations were in relatively undisturbed watersheds. Of the six sockeye

stocks inhabiting impaired or suspected water bodies, four were surveyed enough

times to permit evaluation of population trends; three were stable, and one (Auke

Lake) was declining significantly. Lutak Inlet, a suspected water body, may serve as 

a rearing area for the distinctively large and commercially important Chilkoot Lake

stock.

The overall status of sockeye populations in southeast Alaska is good, but potential

risks include (1) increased demand for this commercially valuable species; (2) overexploitation of small, artificially enhanced, or weak stocks in mixed-stock fisheries; 

(3) heavy and poorly monitored subsistence harvests; and (4) lack of adequate 

information about small populations.

L. Talley and S. Johnson provided professional assistance in accessing the information contained in the ADF&G Integrated Fishery Database. G. Gunstrom, M. Harris,

S. McPherson, and K. Savikko provided ADF&G documents that were the foundation

of this report, and J. Helle provided important documents from the Pacific Salmon

Commission and the National Marine Fisheries Service. S. Marshall provided both

access to the information resources of the ADF&G and criticism that improved this

project. F. Bergander and S. McPherson shared their insights and expertise regarding sockeye salmon biology. J. Christner, J. Franzel, E. Johnston, R. Medel, and 

V. Starostka commented on specific aspects of a previous draft. Both the content 

and format of this report were improved by the input provided by F. Bergander and 

P. Porter. Special thanks to M. Haddix and T. Zadina for their thorough review of a

previous draft.

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Bergander, F.E. 1988. Sockeye salmon stock assessment and evaluation in southeast Alaska, 1983-84. Reg. Inf. Rep. 1J88-36. Juneau, AK: Alaska Department of

Fish and Game, Division of Commercial Fisheries. 36 p.

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164
165

There are over 6,000 populations of pink salmon in southeast Alaska (odd- and evenyear lines in over 3,000 streams). Stock groups in northern and southern parts of

southeast Alaska (separated at Sumner Strait) differ in migratory pathways and rarely

interbreed. Because of these patterns of temporal and spatial separation, outlier

analyses of biological characteristics were conducted separately on southern even-,

southern odd-, northern even-, and northern odd-year stock groups. Adult run timing

and escapement magnitude are the only biological data available for many stocks of

pink salmon. Nineteen southern populations have distinctively early run timing.

Seven streams across the region show large differences in timing between even- and

odd-year lines, suggesting alternate responses by each line to the same freshwater 

environment. Exceptionally large escapements occur in eight populations, but only

two locations have large escapements of both lines. One population is unique in the

region for traveling far upstream to spawn in the interior. Most pink salmon populations in the region that can be analyzed have stable escapement trends, with 18 

percent (240 populations) showing significant increases, and 1.6 percent (21 

populations) showing significant declines from 1960 to 1993. 

Keywords: Pink salmon, Oncorhynchus gorbuscha, southeast Alaska, run timing,

population status, intraspecific diversity.

Pink salmon inhabit rivers north of 40° N. lat. around the Pacific Rim of Asia and

North America. Spawning generally occurs in the lower reaches of coastal rivers,

and pink salmon rarely ascend beyond 500 km from the sea (Neave 1966). A substantial portion of spawning, up to 74 percent in regions such as Prince William

Sound, takes place in intertidal areas (Noerenberg 1963). Intertidal spawning is

indicative of the general pattern of pink salmon life history, which deemphasizes

reliance on fresh-water habitat. Pink salmon fry begin migrating to sea within hours

of emergence, and most fry spend less than a week in fresh water. This life history

pattern may have originated in the small, unproductive streams in far northerly

regions during interglacial times (Miller and Brannon 1982). Pink salmon also are

characterized by a simplified, and virtually fixed, 2-year life span. Eggs are deposited

in redds from July to October and hatch during winter; fry emerge and immediately

migrate to salt water in early spring. After about 16 months at sea, adults return to

Pink Salmon 

(Oncorhynchus gorbuscha)

Abstract

Introduction
spawn and die (Sheridan 1962). Two consequences of this accelerated life history

are that even- and odd-year lines are reproductively isolated, and pink salmon are

distinguished from other Pacific salmon by their small adult size (averaging 1 to 2.5

kg) (Heard 1991). 

Southeast Alaska is near the center of the North American distribution of pink salmon;

consequently, populations are numerous, well distributed, and often large. Pink

salmon inhabit over 3,000 streams in the region (ADF&G, Habitat Division 1994), and

at least 200 of these populations have mean escapements in excess of 10,000 individuals. Pink salmon are the most abundant of the five species of Pacific salmon in

the region, with total catches exceeding 30 million annually during the early 1990s

(Hofmeister 1994). Pink salmon tend to inhabit smaller streams, with occasional

large populations in large rivers (Heard 1991). The only large transboundary population of pink salmon in the study area is in the Taku River drainage, where spawning

occurs primarily in the Nakina River (McGregor and Clark 1990). In contrast to

Prince William Sound, less than 20 percent of pink salmon spawning is estimated to

occur in the intertidal zone in southeast Alaska.

We reviewed information on 650 even-year and 684 odd-year runs of pink salmon in

southeast Alaska. Even- and odd-year lines inhabiting the same stream were treated

separately, because they are reproductively isolated. Estimates of run timing and of

escapement magnitude, both based on stream surveys or weir counts, were the basis

of virtually all evaluations and analyses presented here. Data available for other biological characteristics, such as body size, were inadequate to permit worthwhile comparisons at the population level of analysis. These characteristics are discussed in

this “Introduction” in an effort to describe basic pink salmon biology and trends present in southeast Alaska. More general reviews of pink salmon biology are available

(Bonar and others 1989, Heard 1991, Raleigh and Nelson 1985), including one

focused on southeast Alaska (Alexandersdottir 1987). Furthermore, the extensive

body of literature on pink salmon biology has been compiled recently into an electronic bibliography (Johnson and others 1994).

Pink salmon stocks in southeast Alaska often are divided into stock groups based on

the geographic location of spawning streams or on run timing. Sumner Strait serves

as the approximate boundary between the geographically defined northern and

southern groups. Pink salmon that spawn in streams of northern southeast Alaska

generally enter through Icy Strait or northern Chatham Strait; southern populations

move to inside waters through Dixon Entrance and Sumner Strait. Tagging studies

indicate that, after adults move inshore, very little intermingling occurs between pink

salmon from each geographic area (reviewed in Hoffman and others 1984). Timing 

of peak spawning is used to separate pink salmon populations into early (before 15

August), middle (15 August-15 September), and late (after 15 September) stock

groups (Royce 1962, Sheridan 1962). Run-timing groups are generally believed to

be determined by the temperature regime of spawning streams; early run timing is

typical of populations that spawn in cooler streams. Pink salmon in southeast Alaska

spawn in water temperatures ranging from 7 to 18 °C (Sheridan 1962). Because

mainland streams throughout the region tend to be cooler than island streams, runtiming groups show some degree of geographic separation along a mainland-island

axis. Much overlap and many exceptions to this temperature-based run-timing pattern occur, however. The large population in the Wilson River, for example, has

166

Spawning and

Freshwater Life

History
167

waves of spawning that correspond to all three timing segments (Hofmeister and

Dangel 1989). Historically, the overall pattern of run timing in the region may have

been earlier, but artificial selection by fisheries that removed early portions of runs is

thought to have caused a change in run timing, particularly for runs with intermediate

timing (Alexandersdottir 1987, Alexandersdottir and Mathisen 1982). Timing of

spawning in odd-year Auke Creek pink salmon is moderately heritable (males h2 = 0.2

± 0.16 SE; females h2 = 0.4 ± 0.20 SE) (Smoker and others 1991), thereby confirming that this trait can respond readily to selection. Both the northern and southern

stock groups have populations that fall into all three run-timing categories, but in

accord with trends in water temperature, northern populations tend to have earlier 

run timing than southern populations (Heard 1991). Both even- and odd-year lines

conform to similar stock grouping patterns based on geography and run timing.

Males generally return to spawning streams before females, but by the time runs are

completed, the overall sex ratio generally approaches 1:1 (Dangel and Jones 1988,

Heard 1991, Hofmeister and Dangel 1989). The spawning period for pink salmon

populations typically lasts from 1 to 1.5 months. Within this spawning period, runs

often are subdivided into early and late components (Taylor 1980). The factors

responsible for the origin of these timing components are unclear, but segregation

may be maintained, once established, by shock-induced mortality of eggs of early

spawners resulting from redd superimposition by later spawners (Joyce 1986). Pink

salmon eggs are susceptible to mortality due to mechanical shock for 15 to 30 days

(depending on water temperatures) after deposition (Joyce 1986). This period corresponds roughly to the time interval between early and late spawning peaks. 

Stream life is an important variable in pink salmon reproductive success because, for

females, successful defense of a redd may limit egg losses due to superimposition

and, for males, extended stream life can provide additional spawning opportunities.

Stream life was highly variable among streams, years in the same stream, stream

segments, and timing segments of the run (table 29).

Table 29—Duration of pink salmon stream-life in southeast Alaska

Mean Range

stream (individual fish or

Stream name Year lifea weekly mean) Source

- - - - - -Days- - - - - - -

Salmon Creek 1983 15 4.0 - 38 Thomason and Jones 1984

Starrigavan Creek 1983 30 6 - 55 Thomason and Jones 1984

Kadashan Creek 1986 12.4 10.6 - 12.7b Dangel and Jones 1988

a Mean number of days between tagging and recovery, weighted by the number of fish recovered.

b Range of mean stream life values computed weekly throughout the spawning season.
168

One consistent finding in stream-life studies is that stream life decreases as the run

proceeds (Dangel and Jones 1988, Helle and others 1964, Thomason and Jones

1984). Of the many environmental variables suggested as potential causes of differences in duration of stream life, current velocity is likely to be most important; swift

currents impose the greatest energetic demands on spawning and holding fish, 

thereby resulting in shorter stream life (Heard 1991). Predation rates, particularly by

bears, also can affect mean stream life (Dangel and Jones 1988).

Pink salmon prefer spawning habitat with shallower riffles and more rapid flow than

habitats preferred by other Pacific salmon. The two critical habitat variables for

spawning are water depth and current velocity (Semko 1954, cited in Heard 1991).

Preferred water depths are in the range of 20 to 25 cm, with virtually all redds

between 10 and 140 cm (reviewed in Heard 1991). Average current velocities above

redds range from 30 to 140 cm/second with averages between 60 and 80 cm/second

(reviewed in Heard 1991). Although other species of Pacific salmon rely on upwelling

groundwater to deliver oxygen to developing eggs and alevins, pink salmon rely more

heavily on penetration of surface water into the gravel (Kobayashi 1968, Semko

1954, both cited in Heard 1991). None of the studies reviewed by Heard (1991) was

based on data collected in southeast Alaska; however, the studies reviewed covered

nearly the entire geographic distribution of pink salmon and therefore the values provided are likely to apply to most populations in southeast Alaska. 

Egg and alevin mortality may drive pink salmon population dynamics. Pink salmon

catches in southeast Alaska cycle with a periodicity of about 20 years, apparently

tracking cyclic changes in sea surface and winter air temperatures (Hofmeister 1994):

low catches correspond with periods of low temperatures. Very cold temperatures in

late fall or early winter, before eggs hatch, can cause mortality when ice formation

reduces intergravel flow (Reiser and Bjornn 1979). Once eggs have hatched, alevins

can burrow deeply into gravel to escape freezing, but unusually severe winter cold

may increase alevin mortality. 

Timing of emigration is another factor influencing juvenile survivorship. Fry emergence and emigration tend to be highly synchronous. Coordinated emigration may 

be favored by predator swamping or other antipredator benefits to individuals of being

in a group. Emergence and migration take place almost entirely at night (Sheridan

1962), and bright moonlight inhibits migration (Pritchard 1944, cited in Heard 1991),

suggesting that visually oriented predators have been an important force of natural

selection shaping migratory behavior. Migration timing is thought to coincide with

optimal “windows of opportunity” in the saltwater environment (Miller and Brannon

1982, Smoker and others 1991). For pink salmon stocks these windows may be

defined by onset of zooplankton blooms that provide forage for fry, optimal saltwater

temperature for growth, or avoidance of predators (Pearcy 1992, Sheridan 1962).

Selection favoring appropriate timing of emigration may be stronger for pink and

chum salmon, because these species rely more heavily on plankton than do other

anadromous species such as coho salmon (Pearcy 1992). Strong selection to optimize the emigration timing could lead to differentiation among stocks in response to

thermal characteristics of natal streams (Beacham and Murray 1986, Heard 1991). 
Warm stream temperatures can result in early emigration of pink salmon fry, causing

fry to arrive in salt water before plankton blooms. This sort of inappropriate timing is

thought to result in poor adult returns in southern southeast Alaska (Hofmeister and

others 1988). Few data are available regarding the timing of emigration for populations in southeast Alaska. The date by which 50 percent emigration had occurred

from Sunny Creek (Prince of Wales Island) ranged from 21 April to 26 May for the

odd-year line, and from 2 May to 24 May for the even-year line (Hofmeister and 

others 1988).

Mortality resulting from emigration timing “errors” are a manifestation of fluctuating

selection pressures imposed by a changeable environment. This fluctuating selection

can preserve genetic variation in characters exposed to selection, or it can favor

genotypes with appropriate reaction norms (Stearns 1992). Variation maintained by

fluctuating selection may be critical to long-term stock productivity in a changeable

environment (Smoker and others 1991). Maintenance of genetic variation does not

preclude local adaptation. Theoretical work suggests that if environmental variation

among spawning sites is greater than temporal variation within sites, then differences

in environmental selection pressures along a gradient can result in local adaptation

(Lynch and Gabriel 1987). In pink salmon, local adaptations to thermal regimes can

occur within segments of a stream. Hebert (1994) found that differences in developmental rate compensate for differences in spawning timing of different run components in Auke Creek. Individuals in the late component of the run show heritable

developmental acceleration that enables eggs to hatch with about 15 percent fewer

thermal units than the early spawning component in this stream (Hebert 1994, Joyce

1986). 

The early marine stage of the life cycle may represent a critical period profoundly

influencing return rates. Parker (1962, 1968) examined mortality schedules for pink

salmon and estimated that the highest mortality rates occur during the first 40 days in

the coastal ocean. Predation by coho salmon smolts may be a significant cause of

pink salmon mortality in the near-shore environment, particularly when the abundance of pink salmon fry is low (Hargreaves and LeBrasseur 1985, Hofmeister and

others 1988).

Schooling and rapid growth may be considered additional elements of a predator

avoidance strategy in the early life history of pink salmon. Once in the marine environment, pink salmon fry form large schools and either forage along shorelines and in

estuaries for several weeks (Bailey and others 1975, Healey 1967) or move relatively

rapidly out to sea (Healey 1967, Neave 1966). Growth rate of pink salmon fry during

early marine life in Tenakee Inlet was 0.30 mm/day in length, and 15.3 mg/day in

weight (Hofmeister and others 1988). These rates are somewhat lower than Parker's

(1964) estimate of 0.87 mm/day for Bella Coola River fry and perhaps reflect differences in marine productivity. Though the Tenakee Inlet rates are slower, the observed 6-percent/day increase in weight is still an impressively rapid growth rate.

Marine migration routes and chronology for southeast Alaska pink salmon (both

adults and juveniles) are fairly well studied. Major offshore migrations of juvenile pink

salmon occur through the straits of southeast Alaska in July and August (Martin

1966). In general, the area of the north Pacific traversed by pink salmon from southeast Alaska extends from about 44° N. lat. off the coasts of Oregon and Washington,

169

Marine Life History
170

north and west to the south coast of the Alaska Peninsula (Takagi and others 1981).

During the first summer at sea, migration proceeds in a generally northwesterly direction along the Alaska coast, followed by a southeasterly migration across the open

sea between 44° N. lat. and 50° N. lat. during fall and winter (Takagi and others

1981). In the second spring and summer at sea, pink salmon follow various migratory pathways that bring them back to the coastal waters of southeast Alaska (Takagi

and others 1981). Tagging studies have revealed many details of the inshore migrations of pink salmon to fishing districts in the region (Hoffman 1982, Hoffman and others 1984). For most districts, returning pink salmon enter through at least two different straits and often follow indirect paths to their natal streams (Hoffman 1982,

Hoffman and others 1984). Highly mixed-stock fisheries are one consequence of this

complicated migratory pattern in southeast Alaska. 

In many areas throughout their range, pink salmon abundance fluctuates dramatically

between even- and odd-year lines (Ricker 1962). Many hypotheses have been

offered to explain the origin and maintenance of line dominance, and it is likely that

the phenomenon results from the interaction of several factors (Ricker 1962); for

example, density-independent mortality due to severe climatic conditions may initiate

line dominance that is subsequently preserved by depensatory mortality. At present

in southeast Alaska, no clear pattern of line dominance is apparent in either the

northern or southern region. Line dominance at smaller spatial scales is possible, 

but it is not well documented.

In British Columbia, in conjunction with a general pattern of odd-year dominance,

odd-year pink salmon tend to be larger than even-year fish (Ricker 1962). Based on

the weight data compiled by Marshall and Quinn (1988), odd-year pink salmon also

are significantly larger than even-year fish in southeast Alaska (t = 2.26, P = 0.03).

This difference in weight may be attributable either to genetic differences in growth

rate or differences in ocean productivity in the areas used by each line (Ricker 1962).

Body size of pink salmon also tends to increase with decreasing latitude (Heard

1991).

Body size decreased significantly through time in both even- and odd-year lines in

British Columbia (McAllister and others 1992, Ricker 1981). Ricker (1981) attributes

this decline in size to the selectivity of gill net and troll gear for larger fish, resulting in

artificial selection that favors individuals with heritable small size characteristics; however, alternative hypotheses such as changes in oceanographic conditions (Healey

1986), increased competition (Healey 1986), or selective depletion of stocks with

large mean body size (Nelson and Soulé 1987) could not be rigorously tested

(McAllister and others 1992). Linear regression analysis of trends in pink salmon

body size using the weight estimates of Marshall and Quinn (1988) revealed a significant decline in body size in both even- and odd-year lines across years (fig. 38; even,

N = 35, R2 = 0.20, T= -2.86, P = 0.01; odd, N = 36, R2 = 0.28, T= -3.6, P < 0.01).

Because most pink salmon in southeast Alaska currently are harvested with purseseine gear, which is considered nonselective, the observed decline in body size may

be due to other factors, such as persistent effects of historical selection including

high-seas drift netting, ongoing weak gear selection, or any of the alternative

hypotheses given above (e.g., see Ishida and others [1993] on chum size declines).

This result also may reflect the negative relation between pink salmon run strength

and body size of individuals (Heard 1991), given that run strength generally increased

from 1916 to 1984. 
171

Commercial fisheries for pink salmon were started in southeast Alaska with the construction in 1878 of salmon canneries at Klawock and at Turner's Point in Sitka (Bean

1887). Although these facilities were built primarily for processing sockeye salmon,

the destructive fishing practices, such as stream barricades, used to catch sockeye

for the canneries undoubtedly had detrimental effects on pink salmon populations.

Stream barricades were first outlawed and periods closed to fishing were established

by the Alaska Salmon Act of 1896 (Royce 1962). The USBF first recorded pink

salmon commercial catch data for the 1889 season, when a total catch of 92,000 fish

was recorded. Subsequently, a continuous record of regional catch data has been

maintained for each year through the present (Rigby and others 1991; see fig. 39).

The pink salmon industry grew slowly from its inception until 1910 and then expanded rapidly from 1910 to 1920, as sockeye populations near canneries were depleted

(Vaughan 1942). Salmon traps were the principle gear type used during this period,

and the number of traps operated expanded from 57 in 1908 to 472 in 1920 (Alexandersdottir 1987). Economic conditions prompted severe curtailment of commercial

fishing effort in 1921 and 1922, and again from 1931 to 1933 (Vaughan 1942).

During the intervening period, rebuilding of the fishery was slowed by passage of the

White Act in 1924, which required 50 percent of annual returns be allowed to spawn

and established numerous closed areas in southeast Alaska (Royce 1962). This law

reflected increasing concern about the management of salmon fisheries in Alaska

and was accompanied by an increase in the number of enforcement personnel hired.

The White Act was never applied to pink salmon, however, and because it was typically impossible to attribute catches to particular streams, the regulation was generally unenforceable (Royce 1962).

Figure 38—Trends in body weight for pink salmon harvested commercially in southeast Alaska, 1915-85. Linear regression, even years, N = 35, R2 = 0.20, T = -2.86, 

P = 0.01; odd years, N = 36, R2 = 0.28, T = -3.6, P < 0.01. See Marshall and Quinn

(1988) for details of data compilation methods.

Management History
172

1 Personal communication. 1996. K. Hofmeister, fisheries biologist,

Alaska Department of Fish and Game, 802 3d Street, Douglas, AK

99824.

Catches during the 1930s and 1940s were high but showed a steadily declining

trend, which suggests a gradual decline in productivity or overexploitation, or both.

This decline in catches occurred despite an increase in fishing effort (Alexandersdottir

and Mathisen 1982). Salmon traps were discouraged during this time in favor of

seines and gill nets. Throughout this period, enforcement efforts by the USFWS in

southeast Alaska declined1 (Royce 1962). Nearly three decades of relatively meager

catches and escapements followed. 

Figure 39—Annual commercial harvest of pink salmon in southeast Alaska: (A) even

years, 1892-1990; and (B) odd years, 1893-1991 (data from Rigby and others 1991).
173

The State of Alaska assumed responsibility for fisheries management in 1960. The

management strategy adopted by the state was based on obtaining constant (optimal)

escapements. Attainment of this goal was monitored by surveys of selected streams

throughout the region. Estimation of optimal escapement is a complex and imprecise

process, and estimates gradually were adjusted upward as pink salmon catches remained depressed. During the 1970s, the ADF&G began a rebuilding program based

on increasing escapements throughout the region. This rebuilding program and favorable oceanic conditions (Lawson 1993, Pearcy 1992; see footnote 1) contributed to

average commercial catches in the 1980s that exceeded catches in any prior decade

(Rigby and others 1991; see fig. 39). This trend has continued, with commercial

catches of pink salmon during the early 1990s reaching record high levels.

Current management of the pink salmon fishery is based on attempting to obtain optimal escapements to index streams throughout the region. Recent analyses of the

relation between brood-year escapement index and catch of pink salmon indicates

that the optimum escapement index for the region is at least 12 million fish (Hofmeister 1994). The regional escapement index is the sum of indices for each district.

District escapement indices are calculated by summing the highest escapement

count made for each stream surveyed in the district and adjusting for the number of

index streams not surveyed during that season. The number of index streams in

each district is defined as all streams for which an escapement count was available

at least once from 1960 to the brood year of the returning run. Adjustment for unsurveyed streams involves multiplying the number of streams not surveyed by the average escapement count for all streams within that district having a peak escapement

count of less than 10,000 pink salmon. To complete the district index, the adjustment

is simply added to the sum of counts from surveyed streams. Roughly 700 streams

are surveyed annually, the majority of which are in southern districts. This level of

survey effort represents about a 50-percent sample of index streams and a 25-percent sample of all pink salmon populations in the region. The regional escapement

index is not designed to provide an estimate of total escapement to the region

(Hofmeister 1994); however, the design of the index does provide an easy means for

monitoring attainment of escapement goals at the district level.

In recent years, most districts have consistently achieved escapement goals while

supporting record catches. Districts 105-108, in the southern part of southeast

Alaska, are exceptions to this pattern, consistently failing since 1988 to meet escapement goals (Hofmeister and Dangel 1989, Hofmeister and others 1988, Pacific

Salmon Commission 1991). Whether this represents a problem of stock decline 

(perhaps due to interceptions in districts 102 and 104 [Hofmeister and others 1988])

or unrealistically high escapement goals is unclear.

Preseason forecasting and inseason management are important components of the

current sustained-yield strategy for pink salmon. A tremendous amount of management research effort has been invested to generate models that reliably predict pink

salmon run strength (e.g., Hoffman 1963; Hofmeister and Dangel 1989; Jones and

Dangel 1981, 1985; Jones and others 1988). These efforts have been valuable in

terms of learning about the influence of environmental factors on freshwater survivorship. To date these models have had mixed predictive success, however. Potentially

high variability in marine survival may reduce the accuracy of forecasts derived from

models built around freshwater variables (see Hofmeister and Dangel 1989).

Current Management
174

Inseason assessment of run strength is accomplished by combining data from 

harvest, sex composition of the catch, and escapement surveys in multiple regression

models developed from historical data (Pacific Salmon Commission 1991). Inseason

assessments of run strength have been effectively implemented through delegation of

authority for time and area closures to district managers.

Proportions of the total catch taken by different gear types differ considerably by 

district throughout the region, but in general the purse seine fleet catches over 85

percent of the total pink salmon taken in southern southeast Alaska. The gillnet 

fishery takes the next largest proportion (about 5 to 10 percent) followed by the troll

fleet (1 to 10 percent) (Pacific Salmon Commission 1991). 

Hatchery production of pink salmon in southeast Alaska has never been extensive.

The Fortmann hatchery (1901 to 1927) on the Naha River system, and the Yes Bay

hatchery (1905 to 1933) near McDonald Lake were the first hatcheries to produce

pink salmon in the region (Roppel 1982). Pink salmon also have been produced at

Ketchikan Creek since 1924, with releases occurring at Ketchikan Creek and in saltwater ponds off Gravina and Duke Islands (Roppel 1982). The Ketchikan Creek

hatchery was the only early facility devoted to enhancement of pink salmon in the

region. The contribution of these early enhancement efforts to commercial harvests

cannot be determined. Operations at these early hatcheries led to transfers of eggs

among several sites in the region. Fry from eggs taken from Fish Creek (Thorne

Arm), Ward Cove, and Lucky Cove were released at Ketchikan Creek or the Duke

Island ponds. Eggs from Ketchikan Creek and Smeaton Bay were moved to Yes 

Bay, and eggs from Eva Lake were planted by A.J. Sprague of the Territorial Fish

Commission in Portage Bay, Cascade Bay Lakes, Saginaw Bay, Tebenkof Bay,

Hamilton River, and Johns Harbor (Roppel 1982). The success of these transfers is

unknown. Sprague also transferred eggs from Chilkat Lake to Chilkoot Lake from

1917 to 1920, which apparently did yield some returns (Roppel 1982). During the

same period, Sprague made numerous poorly documented transfers of pink salmon

eggs from several streams (including Anan Creek) to streams in the Juneau area

(including Auke Creek), Douglas and Admiralty Island streams, and Lake Baranof

(Roppel 1982). Little is known of the outcome of these numerous transfers.

Small-scale hatcheries on Sashin Creek and Auke Creek have been operated by the

NMFS to conduct research on pink salmon ecology, population biology, and genetics.

One transfer associated with these hatcheries involved moving adult pink salmon

from Bear Harbor on Kuiu Island to Sashin Creek in an attempt to replace the evenyear line at Sashin Creek that had been experimentally eradicated (Smedley and

McNeil 1966). The purpose of this experiment was to determine the feasibility of

establishing pink salmon populations in new locations by transplanting adults

(Smedley and McNeil 1966). Although the transplant was successful, the technique

of moving adults never achieved widespread application. The Sashin and Auke

Creek hatcheries continue to make considerable contributions to our understanding of

pink salmon biology, although they are not large contributors to commercial fisheries.

Currently, pink salmon are produced on a large scale by (1) Burnett Inlet hatchery on

Etolin Island in southern southeast Alaska, (2) Armstrong-Keta hatchery on southern

Baranof Island, and (3) Douglas Island Pink and Chum (DIPAC) hatchery near

Juneau. Burnett Inlet brood stock was derived from McHenry Inlet, Mosman Inlet,

Enhancement
175

Black Bear Creek, and Anan Creek. Release sites are at the hatchery and in Anita

Bay. Brood stock for Armstrong-Keta was derived from Lovers and Coras Coves and

Sashin Creek. Releases occur at the hatchery. Brood stock for DIPAC is derived

from Fish Creek (Douglas Island) and Kadashan Creek stocks. Pink salmon from

DIPAC are released near the hatchery in Gastineau Channel. Production from these

hatcheries make important contributions to local fisheries but a relatively minor contribution (<10 percent) to the total commercial catch of pink salmon throughout the

region. We did not attempt to document the operations of several small-scale pink

salmon hatcheries in the region. 

The localized nature of pink salmon enhancement in southeast Alaska has minimized

the sorts of conservation problems developing for wild stocks in Prince William Sound

(see Geiger 1994). Given the importance to effective management of inseason runstrength assessments, large hatchery returns, if indistinguishable from wild fish, can

lead to overexploitation of wild stocks (Pacific Salmon Commission 1991). The prevailing cautious policy toward enhancement and new technological developments for

marking hatchery fish, such as thermally induced otolith marks (Hagen and Munk

1994) and genetic markers (Utter and Ryman 1993), may reduce conflicts between

hatchery programs and conservation of wild stocks. These new developments in

marking technology cannot reduce high straying rates among hatchery fish, but they

do provide a means for identifying these strays. Surveys of streams along Gastineau

Channel have revealed that up to 70 percent of fish sampled from escapements were

DIPAC strays with thermally marked otoliths.2

Installation of fish passes and other enhancement activities in the region have been

reviewed by Bibb (1987) and Parry and others (1993). The only enhancement project

directed explicitly at pink salmon was the fish pass at Anan Creek; however, pink

salmon undoubtedly have benefited from projects undertaken for other species (see

Bibb 1987, Sullivan 1980). 

A large body of data indicates distinct genetic separation between even- and 

odd-year pink salmon stocks inhabiting the same stream (e.g., Aspinwall 1974).

Consequently, we evaluated even- and odd-year lines separately.

Within the odd- and even-year runs, the definition of a stock is complicated by an

unknown degree of straying among streams. A fairly widespread perception exists

that pink salmon tend to stray more often, and more widely, than other species of

Pacific salmon (Quinn 1984), but few data are available to support this. To the 

contrary, both tagging and biochemical evidence suggest generally low straying rates

among pink salmon populations (reviewed in Heard 1991). Since Heard's review,

Gharrett and others3 (1993) report that genetically marked pink salmon spawning in

Auke Creek show exceedingly precise homing, resulting in genetic infrastructure within the spawning area of this small stream. In contrast, coded-wire-tagged wild and

hatchery pink salmon from Prince William Sound showed high straying rates; for

example, 53 percent of wild fish marked at Herring Creek were recovered in 14 

2 Personal communication. 1996. E. Volk, Douglas Island Pink and

Chum, 2697 Channel Drive, Juneau, AK 99824.

3 Gharrett, A.J.; Lane, S.; McGregor, A.J.; Taylor, S.G. 1993. Use 

of a genetic marker to examine genetic interaction among subpopulations of pink salmon (Oncorhynchus gorbuscha). Unpublished 

document. On file with: University of Alaska Southeast, 11120

Glacier Highway, Juneau, AK 99801.

Methods

Stock Discrimination
176

4 Personal communication. 1996. A. Gharrett, professor of fisheries, University of Alaska Southeast, 210 Anderson Building,

11120 Glacier Highway, Juneau, AK 99801. Preliminary results

from: Gharrett, A.J.; Wilson, R.B.; Baker, B.M. [and others]. 1990.

Preliminary report on genetic diversity of southern southeast

Alaskan pink salmon populations. NWAFC Proc. Rep. 909-03.

Auke Bay, AK: National Marine Fisheries Service, Alaska Fisheries

Science Center. 50 p.

different streams up to 38 km away (Sharp and others 1994). Studies of homing and

straying are susceptible to many confounding factors, such as the effects of (1) marking procedures on homing behavior, (2) run strength, (3) spawning location (e.g.,

intertidal vs. upstream), and (4) environmental variation, such as oil contamination 

in Prince William Sound. Nonetheless, the bulk of available data support the generalization offered by Ricker (1962) that straying “probably rarely exceeds 10% for 

indigenous stocks.” 

Genetic surveys of pink salmon in 16 streams in both southern and northern southeast Alaska (McGregor 1983) and 19 streams in southern southeast Alaska found

high overall levels of genetic similarity among populations that precluded local-scale

geographic discrimination of stocks.4 At a larger geographic scale, populations from

western Prince of Wales, adjacent to the Gulf of Alaska, were found to differ significantly from populations originating from streams flowing into the inside waters of

southeast Alaska. If straying is infrequent, then the lack of local geographic divergence may reflect relatively recent founding of these populations. Furthermore, the

close proximity of streams suitable for pink salmon in southeast Alaska may promote

gene flow, and many relatively small populations may make low levels of gene flow

sufficient to prevent divergence at allozyme loci.

The divergence between western Prince of Wales populations and inside populations

may be a consequence of colonization from different glacial refugia (see Kondzela

and others 1994). The hypothesis of colonization from alternative glacial refugia also

has been invoked as a possible explanation for the dramatic genetic differences

between even- and odd-year lines of pink salmon (Aspinwall 1974).

As described above, for management purposes only two large stock groups of pink

salmon are recognized in the study area; the northern and southern groups divide

approximately along Sumner Strait (Smedley and Seibel 1967). This division 

corresponds to management districts 101-108 in the southern group, and districts

109-115, 182, and 183 in the northern group.

Stock groups of pink salmon may contain more fine-grained geographic separation.

For instance, Alexandersdottir and Mathisen (1982) recognized 16 stocks in their

classification for southeast Alaska based on geographical location, spawning time,

and migration route. In addition, intertidal spawners and upstream spawners in the

same stream have been considered separate stocks owing to differences in timing,

physical and chemical environment, and line dominance (Royce 1962). In view of the

ongoing controversy, for operational purposes we defined individual stocks of pink

salmon based on geographic location (i.e., spawning streams), as was done throughout this paper.
177

Because the types of data on biological characteristics of pink salmon populations

were limited, analyses in this paper were confined to timing characteristics, geography, escapement magnitude, escapement trends, and water quality. These analyses

were conducted on data collected from escapement surveys and daily weir counts

and were compiled into computerized data files by the ADF&G, Division of Commercial Fisheries. The ADF&G escapement survey database for pink salmon 

is very extensive, and readers interested in detailed records for particular locations

should contact the Southeast Regional Office of ADF&G in Douglas, AK. No data

from catches were included in our analyses. Weir counts for pink salmon collected

historically by the USBF also were not included in this paper. 

We conducted analyses of timing and escapement characteristics on a sample of 

650 even-year and 684 odd-year pink salmon stocks. This sample represented over

20 percent of the approximately 6,000 even- and odd-year lines present in the region.

These stocks were well distributed throughout the region, and for many stocks the

data collection period extended over 30 years (from 1960 to 1992). All stocks included in our analyses were represented in the ADF&G database by at least 7 years of

survey data. 

Run-timing analyses are based on the timing index described in the “General Introduction.” The usefulness of this index is enhanced for many pink salmon populations

by multiple surveys per year, which permit fine resolution of the date when peak

abundance of spawners occurred. Because of the many stocks for which timing

indices could be calculated, and the low number of stocks for which daily weir counts

were available for evaluating run timing, our analyses of run timing relied on index

dates.

Data were available to calculate run-timing statistics for 27 of 45 even-year pink

salmon stocks enumerated at weirs and 26 of 42 odd-year populations. Most of

these weirs were operated primarily for other species with counts of pink salmon

made incidentally. The numerous possible sources of bias associated with these

data rendered them unsuitable for detailed analysis of run timing. Weirs at Sashin,

Auke, and Kadashan Creeks targeted pink salmon and yielded more complete and

reliable data. 

Our estimate of escapement magnitude was calculated by taking the largest escapement survey estimate from each year and computing the mean of these maxima.

Survey counts were not expanded to estimate total escapement.

We analyzed the effects of geographic region (northern or southern) and line (even or

odd) on timing index and escapement magnitude by using a fixed-effects ANOVA

model (Beacham and Murray 1988);

Yijk + μ + Ri + Lj + RLij + eijk ,

where

Yijk = observed timing index or escapement,

μ = mean,

Ri = region, and

l

j = line.

Data Analysis

Procedures
178

The regression procedures described in the “General Introduction” were used to evaluate escapement trends for pink salmon populations. Even- and odd-year lines were

evaluated separately, meaning that escapement surveys had to be conducted over a

span of 14 years before a population could be included in the analysis.

At systems with weirs, even- and odd-year lines showed a similar range of grand

mean freshwater migration dates. These dates ranged, for even-year stocks, from 

2 August for Kadashan East, to 10 September for Sashin Creek. Among odd-year

lines, Sashin Creek again showed relatively late run timing with a grand mean freshwater migration date (based on data from 1935 to 1963) of 4 September. The

Kadashan East pink salmon population was relatively early with a grand mean date 

of 30 July.

Kadashan Creek stocks showed no trends across years in migration timing for evenor odd-year lines, but historical data (1935-63) from the odd-year line at Sashin Creek

showed a nearly significant trend (0.05 < P < 0.1 ) toward earlier run timing. This

trend becomes less strong if the datum from 1987 (the only value we obtained for

recent years) was included in the analysis. Experimental manipulations at Sashin

and Auke Creeks and hatchery operations at Auke Creek may have altered natural

run timing patterns.

Even-year runs were later than odd-year runs at both Kadashan River sites and at

Sashin Creek, but the difference in mean migration date was significant only at

Sashin Creek (paired t-test, N = 15, P = 0.01). The East and West Kadashan Creek

stocks did not differ in run timing (N = 9, P = 0.3). The most that can be inferred from

these analyses is a suggestion of the range of run timing in the region. Clearly, these

limited data from weirs were insufficient for evaluating regional patterns of pink

salmon run timing.

Pink salmon migration timing in the Taku River is about a month earlier than other

runs in northern southeast Alaska. The calculated mean migration dates from samples taken at the Canyon Island fishwheel ranged from an early date of 18 July in

1989 to the latest date of 27 July in 1986 (McGregor and others 1991). These dates

suggest that both even- and odd-year pink salmon from the Taku River have particularly early run timing relative to other stocks in the region. The primary spawning

area of Taku River pink salmon is in the clearwater reach of the Nakina River

(McGregor and others 1991), nearly 100 km upstream from Taku Inlet. The early run

timing of this stock is probably related to the exceptionally long freshwater migration

these fish undertake.

Analysis of timing index dates revealed highly significant effects of both region 

(F = 116.12, P < 0.01) and line ( F = 76.37, P < 0.01), but no significant interaction

effects. Tukey pairwise comparisons indicated that all comparisons except one were

highly significant (P < 0.01); the only nonsignificant difference was between evenyear northern stocks and odd-year southern stocks (P = 0.48). Within both regions,

odd-year lines had significantly earlier index dates than even-year lines. The difference was about 4 days in both regions (table 30). The variance of index dates was

significantly heterogeneous among the four stock groups (Fmax test, P < 0.05; Sokal

and Rohlf 1981), with southern stock groups showing less variability in timing than

northern groups for both even- and odd-year runs. The variances of even- and oddResults

Timing
179

year lines within regions were quite similar (table 30). The observed heterogeneity in 

variance probably did not adversely affect the results of ANOVA, because significance tests in ANOVA are relatively robust with regard to deviations from the

assumption of equal variances (Sokal and Rohlf 1981).

Within each stock group defined by the ANOVA (southern even, southern odd, northern even, and northern odd), we plotted frequency distributions to look for outliers

(fig. 40). Eleven populations in the southern even early group and two populations in

the southern odd, early group had distinctly early run timing (table 31). Four odd-year

late populations in the southern region had conspicuously late run timing (table 31).

No clear timing outliers were present in either line in the northern region. The 

frequency distributions for the northern region were relatively flat and suggested

bimodality or multimodality, which probably accounts for the lack of apparent outliers

(fig. 40). 

The validity of the early index dates from southern southeast Alaska is suspect,

because of the possible influences of early surveys for chinook or sockeye salmon in

some of these systems (noted in table 31); however, not all systems with early runs

of chinook and sockeye also yielded early timing indices for pink salmon, and some

of the stocks with early index dates are found in streams that do not support populations of these other species (e.g., Swift Creek, Valentine Creek).

The mean date of the run-timing index was earlier for odd-year lines than for evenyear lines, and this pattern also was conspicuous within a number of particular

streams. Nineteen locations in northern southeast Alaska had odd-year lines with a

timing index more than 10 days earlier than even-year lines (table 32); Indian River

(Sitka), Wheeler Creek (Admiralty), Phonograph Creek (Chichagof), and Althorp

Creek (Chichagof) were outliers from the distribution (table 32, fig. 41).

Patterns of run-timing index within a stream did not always conform to the pattern of

stock group means. Even-year lines had earlier timing indices, by at least a week

(table 32), than odd-year lines in six streams in the southern part of southeast Alaska.

Two of these streams (Clear and Grant Creeks in the Chickamin River drainage) had

timing-index differences that were outliers from the overall distribution (fig. 41), with

Table 30—Descriptive statistics for pink salmon run-timing index, summarized

by region and line

South North

Statistic Even years Odd years Even years Odd years

Na 359 367 291 317

Mean (Julian day) 237.5 233.4 232.5 228.7

Variance 59.7 46.1 87.2 79.3

SDb 7.7 6.8 9.3 8.9

Minimum 215 212 206 207

Maximum 256 254 253 251

a

N = number.

b

SD = standard deviation.
180

even-year returns occurring 13 and 9 days earlier than odd-year returns. In the

northern part of southeast Alaska, Lake Kathleen Creek (Admiralty Island) was conspicuous in having an even-year index date that preceded the odd-year date by 25

days (fig. 41).

The geographic distribution of stocks, escapement magnitude, and escapement

trends were the variables we evaluated to characterize pink salmon demographics.

We also reviewed the effects of diminished water quality on pink salmon escapements. Age structure and sex ratio could not be evaluated owing to a lack of data

(see Olson and McNeil [1967] and Vallion and others [1981] for sex-ratio data from

Sashin Creek). The age composition of all stocks was assumed to be entirely 0.1,

although rare deviations from this pattern, in duration of both freshwater (Heard 1991)

and saltwater residence (Anas 1959, Foster and others 1981), are known from other

regions.

Figure 40—Frequency distributions, outlier plots, and normal quantile plots for run-timing index dates plotted by line and region: (A)

even-year lines, southern region, N = 359; (B) even-year lines, northern region, N = 291; (C) odd-year lines, southern region, N = 367;

and (D) odd-year lines, northern region, N = 317. See table 31 for specific stocks in the tails of each distribution.

Demography
181

Table 31—Pink salmon stocks with early or late run timing, based on index date

and evaluated by region and line

Stream Survey

Mean Mean

Julian Mean Number First Last escapeNumber Name date date of years year year ment

Southern southeast, even-year lines, early stocks

• 101-11-100 Swift Creek 215 03-Aug 7 64 90 381.4

• 101-60-025 Valentine Creek 215 03-Aug 13 64 92 17,517.7

• 101-71-04C Clear Creek 215 03-Aug 12 66 92 3,125.0

• 101-71-028 Walker Creek 217 05-Aug 17 60 92 23,176.5

• 101-75-010 Grant Creeka 217 06-Aug 16 60 92 21,360.3

• 101-71-025 Walker Cove Lower 219 07-Aug 10 70 92 9,700.8

Head

• 101-71-063 Portage Creek 219 07-Aug 17 60 92 30,027.3

• 101-75-080 Robinson Creek 219 07-Aug 7 72 88 5,300.0

• 101-71-04K King Creeka 220 08-Aug 17 60 92 28,399.9

• 101-75-015 Eulachon Rivera 220 08-Aug 17 60 92 18,739.6

• 101-75-050 Klahini Rivera 220 08-Aug 17 60 92 16,391.5

• 101-30-030 Keta Rivera 221 09-Aug 17 60 92 93,394.1

• 101-60-016 Rudyard Creek 221 09-Aug 16 60 92 9,089.0

Southern southeast, even-year lines, late stocks

• 101-23-094 Crab Bay 256 13-Sep 7 64 92 2,735.7

• 102-60-087 Karta River 255 12-Sep 15 60 92 53,785.0

• 105-43-001 Shipley Bay North 255 12-Sep 7 68 86 1,075.9

Head

• 102-30-065 Kugel Creek 254 11-Sep 12 68 92 6,259.3

• 102-30-067 Kegan Cove 254 11-Sep 12 64 92 11,206.4

• 103-40-067 Coco Harbor Head 254 11-Sep 12 64 92 3,480.1

• 102-40-015 Kitkun Bay 253 10-Sep 9 66 92 1,447.2

Southeast Side

• 102-40-060 Lagoon Creek 253 10-Sep 17 60 93 26,320.6

• 103-60-047 Klawock River 253 10-Sep 12 60 92 112,345.8

• 106-10-030 Eagle Chuck Luck 253 10-Sep 16 62 92 36,426.8

Lake

• 106-10-034 Luck Creek Luck 252 09-Sep 7 78 92 1,551.9

Lake

• 103-21-018 Keete Inlet North 252 09-Sep 17 60 86 1,741.2

Arm Head

• 101-23-087 Kwain Bay 252 09-Sep 8 64 92 2,956.3

• 102-30-017 Johnson Cove 251 08-Sep 14 62 92 7,167.3

Creek

• 102-40-047 West of 251 08-Sep 10 72 92 4,460.0

Disappearance

• 102-40-011 Lancaster Cove 250 07-Sep 7 72 90 5,464.3

East

• 106-30-080 108 Creek Whale 250 07-Sep 13 60 92 78,781.5

Pass

• 106-30-082 Squaw Creek Whale 250 07-Sep 14 66 92 8,608.9

Pass
182

Table 31—Pink salmon stocks with early or late run timing, based on index date

and evaluated by region and line (continued)

Stream Survey

Mean Mean

Julian Mean Number First Last escapeNumber Name date date of years year year ment

Southern southeast, odd-year lines, early stocks

• 101-60-025 Valentine Creek 212 31-Jul 11 73 93 18,038.2

• 101-75-080 Robinson Creek 215 03-Aug 13 73 93 27,069.2

• 101-30-030 Keta Rivera 218 06-Aug 17 61 93 47,126.5

Southern southeast, odd-year lines, late stocks

• 106-30-080 108 Creek Whale 254 11-Sep 13 61 93 70,143.1

Pass

• 102-60-087 Karta River 253 10-Sep 14 61 93 28,402.6

• 103-60-047 Klawock River 253 10-Sep 13 61 93 120,560.8

• 106-10-030 Eagle Creek Luck 253 10-Sep 17 61 93 41,427.6

Lake

• 102-30-041 Frederick Creek 251 08-Sep 13 67 93 12,716.9

• 103-30-040 Grace Harbor Creek 251 08-Sep 13 73 93 3,279.1

• 101-47-025 Ketchikan Creek 250 07-Sep 7 75 89 11,738.4

• 102-40-011 Lancaster Cove 250 07-Sep 9 67 93 5,598.9

East

• 103-21-018 Keete Inlet North 250 07-Sep 8 61 81 2,712.5

Arm Head

• 101-41-067 Nadzaheen Creek 249 06-Sep 13 61 87 10,695.2

• 103-30-043 Vesta Bay 248 05-Sep 12 65 93 626.6

• 106-10-010 Ratz Harbor Creek 248 05-Sep 16 61 93 16,696.6

Northern southeast, even-year lines, early stocks

• 112-42-025 Kadashan Creek 206 25-Jul 7 60 92 33,004.6

• 112-48-023 West Bay Head 210 29-Jul 10 62 92 6,941.2

Creek

• 112-47-010 Long Head Bay 212 31-Jul 16 62 92 32,158.2

Northern southeast, even-year lines, late stocks

• 113-41-019 Indian River, Sitka 253 10-Sep 11 62 90 3,417.6

• 113-44-005 Katlian Bay South 251 08-Sep 16 60 92 8,509.4

Fork

• 113-43-002 Nakwasina River 260 07-Sep 14 60 92 6,628.6

• 112-17-026 Lake Florence 249 06-Sep 14 60 92 13,119.3

Creek

• 112-73-017 Hood Bay South 249 06-Sep 9 64 92 1,008.6

Arm Head North

• 113-62-006 Sukoi Inlet West 249 06-Sep 13 62 90 3,719.2

Side

• 109-62-012 Elena Bay Head 248 05-Sep 14 62 92 3,171.6

• 109-62-018 Goose Trap Creek 248 06-Sep 13 66 92 6,160.4

• 113-65-005 Fish Bay South Side 248 05-Sep 14 60 92 2,535.7

Head
183

Table 31—Pink salmon stocks with early or late run timing, based on index date

and evaluated by region and line (continued)

Stream Survey

Mean Mean

Julian Mean Number First Last escapeNumber Name date date of years year year ment

Northern southeast, even-year lines, late stocks

• 109-52-035 Kutlaku Creek 247 04-Sep 16 62 92 11,820.0

• 109-62-024 Petrof Bay West 247 04-Sep 15 62 92 3,755.5

Head

• 112-17-050 Thayer Creek 247 04-Sep 16 60 92 4,272.3

• 113-66-002 East of Kane Island 247 04-Sep 7 64 78 2,928.6

• 114-25-012 East Homeshore 247 04-Sep 9 66 92 2,536.7

Creek

Northern southeast, odd-year lines, early stocks

• 112-16-030 Wheeler Creek 207 26-Jul 17 61 93 18,967.6

• 112-42-025 Kadashan Creek 211 30-Jul 7 61 93 57,857.1

• 112-48-019 Little Goose Creek 211 30-Jul 10 73 93 4,495.0

• 111-17-010 King Salmon River 212 31-Jul 13 61 93 18,205.0

• 114-23-080 Goose Creek 212 31-Jul 9 65 93 1,903.9

• 112-48-015 Big Goose Creek 213 01-Aug 17 61 93 26,785.3

Northern southeast, odd-year lines, late stocks

• 112-48-035 Tenakee Inlet Head 215 03-Aug 16 61 93 12,701.9

• 112-67-060 Kanalku Lake Creek 251 08-Sep 9 69 93 6,433.3

• 113-44-005 Katlian Bay South 251 08-Sep 17 61 93 51,458.8

Fork

• 113-41-011 Port Krestof Sound 248 05-Sep 7 63 91 428.6

• 109-45-013 Salt Chuck-Security 247 04-Sep 17 61 93 7,587.2

• 109-62-018 Goose Trap Creek 247 04-Sep 11 65 93 5,048.9

• 114-25-012 East Homeshore 247 04-Sep 8 69 91 2,043.8

Creel

• 109-62-012 Elena Bay Head 246 03-Sep 14 61 93 3,859.9

• 109-62-013 Alecks Creek 245 02-Sep 17 61 93 28,163.2

• 109-62-020 Petrof Bay 245 02-Sep 16 61 93 3,069.3

Southeast Head

• 112-12-025 Kook Lake Outlet 245 02-Sep 13 61 93 6,511.9

• 113-62-006 Sukoi Inlet West 245 02-Sep 15 63 93 6,200.0

• = outlier.

a Index date may be affected by early season escapement surveys targeting chinook salmon in which pink

salmon are counted incidentally.
184

Table 32—Pink salmon streams with large timing differences between even and

odd-year lines

Stream Number of survey years

Timing Mean

Number Name differencea Even Odd escapement

Days

Southern southeast, negative differences

• 101-71-04C Clear Creek -13 12 7 3,125.0

• 101-75-010 Grant Creek -9 16 16 21,360.3

• 103-30-040 Grace Harbor Creek -8 13 13 4,911.5

• 105-10-010 North of Louise Cove -8 11 11 1,992.0

• 103-80-056 Inside St. Phillips Island -7 11 14 7,590.9

• 108-60-003 Bear Creek Frederick Sound -7 10 9 4,569.4

Southern southeast, positive differences

• 102-30-067 Kegan Cove 15 12 16 11,206.4

• 103-60-011 Shinaku Inlet North Side 16 7 7 9,070.0

• 102-60-068 Kina Creek 14 12 13 10,490.8

• 102-60-038 Dog Salmon Creek 13 13 15 4,448.5

• 102-60-082 Harris River 13 17 16 74,168.3

• 103-11-035 Little Datzkoo Head 13 10 8 2,611.5

• 102-30-040 Moira South Arm Head 13 8 10 13,131.3

Southwest

• 102-40-015 Kitkun Bay Southeast Side 12 9 14 1,447.2

• 103-11-041 Datzkoo Harbor Head 12 11 9 5,268.5

• 103-15-023 Klakas Right Head 12 17 17 33,751.2

• 103-60-037 Big Salt Lake Southwest Side 12 7 8 5,522.1

• 106-22-014 Burnett Inlet Northeast Head 12 7 8 186.3

• 101-30-095 Vixen Bay Head 11 13 15 5,354.8

• 101-45-094 Spit Creek 11 8 11 4,324.8

• 102-30-089 Miller Lake Creek 11 10 10 5,530.0

• 102-60-042 Cabin Creek Polk Inlet 11 10 13 5,565.0

• 103-90-028 Slow Creek 11 9 7 6,522.2

• 105-10-019 Kathleen Creek 11 12 12 8,600.6

• 107-40-055 Eagle River Bradfield 11 17 17 42,573.5

Northern southeast, negative differences

• 112-17-012 Lake Kathleen Creek -25 15 16 5,825.7

• 112-80-028 Chaik Bay Creek -6 17 17 20,195.4

• 109-42-030 Kadake Creek -5 17 16 18,884.7

• 110-22-004 Amber Creek North Arm -5 17 17 14,667.9

Pybus

• 110-34-010 Walter Island Creek -5 8 7 615.5

• 112-42-025 Kadashan Creek -5 7 7 33,004.6

• 112-67-060 Kanalku Lake Creek -5 11 9 2,322.7

• 113-41-042 Kizhuchia Creek Red Bay -5 10 13 1,622.0
185

Geographic distribution—The Nakina River pink salmon stock is unique among

stocks in southeast Alaska in having a freshwater migration that extends up to 100

km. We do not know of any other transboundary pink salmon stocks in the region

that ascend this far into fresh water. 

Pink salmon stocks appeared to be sparsely distributed in Lynn Canal and along the

northern outer coast, but this appearance may reflect a lack of data on the relatively

small pink salmon populations found in these areas. Within this context, the pink

salmon stock in the Situk River was unusual, because of its large mean escapements

(see table 33 and next section).

Escapement magnitude—Escapement magnitude differed significantly between

regions (F = 13.9, P < 0.01) but not between lines. Tukey (1977) pairwise comparisons indicated that southern even- and odd-year lines had significantly greater mean

escapements than the northern even-year line (table 34).

Table 32—Pink salmon streams with large timing differences between even- and

odd-year lines

Stream Number of survey years

Timing Mean

Number Name differencea Even Odd escapement

Days

Northern southeast, positive differences

• 113-41-019 Indian River, Sitka 30 11 13 3,417.6

• 112-16-030 Wheeler Creek 17 16 17 3,601.6

• 113-95-004 Phonograph Creek Lisianski 16 12 16 833.3

Inlet

• 114-50-020 Althorp Creek 16 17 17 6,855.9

• 109-52-008 Rowan Bay East Head 15 17 17 9,123.5

• 113-54-007 Rodman Creek 14 17 17 29,805.9

• 109-20-007 Gut Bay Head 13 11 10 2,131.8

• 112-12-046 Gypsum Creek 13 14 14 950.2

• 113-57-005 Patterson Bay West Head 13 17 17 24,247.1

• 113-96-002 Saltery River Stag 13 17 17 6,900.0

• 109-52-050 Pillar Bay Southwest Side 12 8 11 1,123.8

• 113-95-006 Lisianski River 12 17 16 12,894.1

• 114-40-035 Trail River 12 17 16 3,251.5

• 109-52-055 Kwatahein Creek Pillar 11 10 14 3,255.2

• 112-12-034 North of Basket Bay 11 17 16 5,292.5

• 112-17-050 Thayer Creek 11 16 17 4,272.3

• 113-42-002 Limit Creek Nakwasina Point 11 15 16 3,857.5

• 113-58-002 Hoonah Sound North Arm 11 15 16 4,317.1

West

• 113-81-011 Black River 11 16 17 6,375.0

• = outlier

a Timing difference calculated as (even index date) - (odd index date).
186

Distinctively large mean escapements occur in six drainages in the southern region

and only one (Chuck River, even years only) in the northern region (table 33; fig. 42).

Only the Wilson River and Anan Creek in the southern region have distinc-tively large

runs of both lines. Not surprisingly, these large escapements occur in relatively large

drainages on the mainland or on Prince of Wales Island (fig. 43). Taku River pink

salmon escapement, estimated by using mark-recapture methods, indicated that this

system is a major pink salmon producer in northern southeast Alaska (McGregor and

Clark 1990). Estimated abundance ranges from 340,000 to nearly 500,000, depending on the recovery data included in the analysis (McGregor and others 1991). It was

not included in the outlier analysis because a different method was used.

Figure 41—Frequency distributions, outlier plots, and normal quantile plots

for differences in run-timing index between even- and odd-year lines for

the (A) southern (N = 323) and (B) northern (N = 275) regions. Difference

calculated as mean even-year index date minus mean odd-year index

date. See table 32 for summary data for stocks occupying the tails of the

distributions.
187

Differences in magnitude of the largest stocks are indicative of the general differences in population size between southern and northern regions. For example, the

odd-year line of the Nakina River stock had a mean escapement estimate of about

100,000 fish, which was the highest estimate for any stock in the northern region.

The Wilson River and Anan Creek stocks were the largest in the southern region and

both have mean escapement estimates over 150,000 fish.

Escapement trends—The great majority of pink salmon stocks analyzed have stable

escapements across years, and among stocks showing significant changes, increasing trends were far more common than decreasing trends. Among even-year lines,

115 stocks showed a significant trend, with 101 stocks (15.5 percent) increasing significantly and 14 (2.2 percent) decreasing significantly. The pattern was similar for

odd-year stocks but with an even more pronounced increasing trend; 147 stocks

Table 33—Pink salmon stocks with large mean escapements

Stream

Maximum Number

Mean number of of years

Number Name escapement fish surveyed

Even-year lines, southern region

• 101-30-083 Humpback Creek 107,259 300,000 17

• 101-55-020 Wilson River 183,686 660,000 17

• 103-60-047 Klawock River 112,346 350,000 12

• 107-20-015 Anan Creek 157,439 338,000 17

Even-year lines, northern region

• 110-32-009 Chuck River Windham Bay 86,047 259,000 17

• 110-34-008 Sanborn Creek 63,266 125,000 17

• 182-70-010 Situk River 62,000 175,000 9

Odd-year lines, southern region

• 101-30-083 Humpback Creek 102,165 295,000 17

• 101-55-020 Wilson River 158,719 388,000 17

• 103-21-008 Nutkwa Creek 102,468 202,000 17

• 103-60-047 Klawock River 120,561 350,000 13

• 103-90-030 Staney Creek 101,247 310,000 17

• 107-20-015 Anan Creek 157,439 338,000 17

Odd-year lines, northern region

• 109-20-016 Red Bluff Bay South Head 77,063 195,000 16

• 110-32-009 Chuck River Windham Bay 72,474 209,000 17

• 110-34-003 Rusty River 60,741 229,000 11

• 110-34-008 Sanborn Creek 61,420 153,950 17

• 111-32-220 Nakina River 96,978 750,000 9

• 113-64-001 Deep Bay Head 74,235 150,000 17

• 113-95-006 Lisianski River 78,988 220,000 16

• = outlier.
188

(21.5 percent) showed a significant trend, with 140 (20.5 percent) increasing significantly and only 7 (1 percent) decreasing significantly. Only one stream, Thetis Bay—

southwest head, showed significant declines of both lines (table 35 and fig. 44). In

systems with weirs, only five even-year stocks were evaluated and one was increasing significantly. This was the Sashin Creek stock, which was recovering from the

eradication and transplant experiment (Smedley and McNeil 1966). Weir counts from

six odd-year stocks were sufficient for analysis, and three of these were increasing 

significantly.

The only geographic pattern apparent among declining stocks was a cluster of three

even-year stocks in Seymour Canal (fig. 44). This set of three included Pack Creek, 

a popular brown bear observation site. Pack Creek and Windfall Creek were both

represented by relatively good data sets; both were surveyed more than once annually for all 17 even years from 1960 to 1992. Only seven surveys were available for

the last significantly declining stock, in an unnamed creek opposite south Tiedeman

Island (111-14-038). Two additional stocks in Seymour Canal showed nearly significant declines (0.05 < P < 0.1), and 10 of 11 even-year stocks had negative slopes.

This general pattern was not present in Seymour Canal in the odd-year line.

The large number of pink salmon stocks in the region assures that many will be

found in impaired and suspected water bodies (table 36). Ten water bodies classified

as “impaired” by the Alaska Department of Environmental Conservation are inhabited

by stocks of pink salmon (table 36). Only five of these water bodies were surveyed

for pink salmon escapement with sufficient regularity to permit escapement-trend

analysis. Three of these five showed significantly increasing trends in escapement,

and the remaining two were stable. Salmon Creek (Juneau) is one of the significantly

increasing stocks, and this likely is due to hatchery operations (the DIPAC Gastineau

Channel hatchery is at the mouth of Salmon Creek and uses the creek as its water

source). 

Twenty-five pink salmon populations were found in suspected water bodies (table

36). None of the 25 showed a significant decline. Seven stocks (28 percent)

increased significantly. 

Table 34—Descriptive statistics for pink salmon escapement estimates summarized by region, and even and odd years

South North

Statistic Even years Odd years Even years Odd years

Na 359 367 291 317

Mean (survey count) 13,406.3 13,013.4 8,296.5 10,952.0

Variance 431,647,000.0 418,203,000.0 126,119,000.0 198,073,000.0

SDb 20,776.1 20,450.0 11,230.0 14,073.8

Minimum 159.5 60.7 118.6 298.6

Maximum 183,685.9 159,684.1 86,047.0 96,977.8

a

N = number.

b

SD = standard deviation.

Water Quality
189

At this time, only preliminary surveys of allozyme frequencies have been conducted

on pink salmon stocks in southeast Alaska. McGregor (1983) surveyed 12 streams in

northern southeast Alaska and four in southern southeast Alaska, and Gharrett and

others reported on 19 populations in southern southeast Alaska (see footnote 4).

Significant differences in allele frequencies are present between northern and 

southern regions (McGregor 1983), but both surveys found that differences within

regions were small. Among the stocks surveyed in the southern region, Anan Creek

and Black Bear Creek differed from all others in cluster analyses. Because of the

limited extent of the survey, results of additional analyses are necessary to confirm

the genetic distinctiveness of these populations.

Figure 42—Frequency distributions, outlier plots, and normal quantile plots of mean pink salmon escapement magnitude based on

escapement surveys, by line and region. Panel letters and sample sizes as in fig. 40. Table 33 presents summary data for specific

stocks with large escapements.

Genetic Surveys
190

Figure 43—Approximate locations of southeast Alaska pink salmon stocks with large mean escapements.

Sashin and Auke Creeks are considered to have special scientific value owing to the long histories of

research conducted at these sites.
191

Table 35—Pink salmon stocks with significantly declining escapement trends

Stream Location

Data

quality

Number Name VCUa General Land useb rating Possible factors

Even-year lines

101-15-012 Halibut Bay Northwest Head 846K Misty Fiords National Wilderness Good Unknown

Monument

103-11-035 Little Datzkoo Head 663K Dall Island LUD IV Poor Unknown

107-20-020 Canoe Pass West Side 474S Etolin Island Wilderness Fair Unknown

107-20-071 Fools Inlet Head East 480S Wrangell Island LUD IV Fair Habitat? 

380 ha logged 

1953-90

107-30-070 Snake Creek, Olive Cove 469S Etolin Island LUD IV, state Good Habitat?

land 186 ha logged 

1941-80

108-40-007 Stikine North Arm Mouth 492S Stikine River Wilderness Poor Unknown

109-30-017 Curtiss Creek 181C Admiralty Island Wilderness Fair Unknown

109-62-030 Thetis Bay Southwest Head 407S Kuiu Island Wilderness Fair Unknown

109-62-036 Neal Creek 406S Kuiu Island Wilderness Fair Unknown

110-11-003 Twelvemile Creek, Frederick 446S Kupreanof Island LUD III Good Unknown

Sound

111-14-038 Opposite South Tiedeman 140C Admiralty Island Wilderness Poor Unknown

111-15-020 Windfall Creek 151C Admiralty Island Wilderness Good Unknown

111-15-030 Pack Creek 152C Admiralty Island Wilderness Good Unknown

112-50-032 Bay Head Creek 243C Chichagof Island LUD IV Fair Unknown

Odd-year lines

101-43-029 Pop Creek 756K Revillagigedo Island LUD III Poor Habitat? 

472 ha logged 

1955-81

101-90-060 Wolf Creek 743K Revillagigedo Island LUD III Poor Unknown

106-22-14B Burnett Inlet Southeast Head 468S Etolin Island LUD III Poor Hatchery effects?

109-62-030 Thetis Bay Southwest Head 407S Kuiu Island Wilderness Good Unknown

112-17-025 Lake Florence Creek 150C Admiralty Island Wilderness; Good Habitat?

native corp. Timber harvest

114-23-035 Chicken Creek Icy Strait 196C Chichagof Island LUD IV Fair Unknown

114-31-009 Gartina Creek 205C Chichagof Island LUD IV; native Poor Habitat?

corp.

a VCU = USDA Forest Service value comparison unit; approximately equivalent to a watershed; K = Ketchikan Area; S = Stikine Area;

and C = Chatham Area.

b LUD = land use designations:

LUD III = multiple use

LUD IV = intensive resource use (especially logging)
192

Figure 44—Approximate locations of southeast Alaska pink salmon stocks with significantly declining

escapements; see table 35 for summary data including possible factors contributing to apparent declines.
193

Table 36—Pink salmon stocks in impaired or suspected water bodies

Stream Location

Pollutant

Number Name VCUa General sourcesb Comments

Impaired water bodies

101-45-038 Salt Chuck 747K Carroll Inlet TH, RC Even-year runs increasing significantly

George Inlet Odd-year runs show no significant trend

101-47-015 Ward Cove 749K Ketchikan IN, DO, Even years—3 surveys from 1982-88, max. 

Debris 3,277 fish, min. 390 fish

Odd years—3 surveys from 1981-89, max. 

905 fish, min. 27 fish

109-52-007 Rowan Bay 402S Kuiu Island TH Even-year runs increasing significantly

Odd-year runs increasing significantly

110-33-009 Hobart Bay 75C Near Juneau TH, IN, SM, Even years—only 1 survey, 30 fish in 1986

RC Odd years—2 surveys, 16 fish in 1971, 4,200 

fish in 1991

111-40-010 Lemon Creek 32C Juneau UR, PP, MI Odd years only—2 surveys, 11 fish in 1981, 80

LF, SM, GM fish in 1985

111-40-012 Vanderbilt Creek 32C Juneau UR, GM, LF Even years—only 1 survey, 941 fish in 1990

Odd years—only 1 survey, 2 fish in 1983, 

survey too late

111-40-015 Salmon Creek 32C Juneau UR, DDE, Even- and odd-year runs both increasing 

PCB significantly

Hatchery operation; status of wild stock 

unknown

111-40-089 Lawson Creek 33C Douglas UR, RD, CH, Even years—5 surveys from 1968-92, highly 

SM variable

Odd years—10 surveys from 1969-93, no 

significant trend

113-41-017 Granite Creek 311C Sitka UR, GM Even years—7 surveys from 1978-92, no 

significant trend

Odd years—5 surveys from 1981-91, max. 

7,000 fish, min. 500 fish

113-41-028 Bear Creek 318C Sitka IN, DO, Even years—3 surveys, 0 fish in

Silver Bay Debris 1978, 76 fish in 

1980, 2,500 fish in 1990 

Odd years—4 surveys, max. 8,000 fish,

min. 1,000 fish 

Suspected water bodies

101-45-024 White River 748K Ketchikan TH Even-year runs increasing significantly

Odd-year runs show no significant trend

101-47-017 Carlanna Creek 750K Ketchikan UR, IN, SE Odd years only—210 fish in 1969, 34 fish in 

1977, 491 fish in 1979

101-47-025 Ketchikan Creek 751K Ketchikan UR, IN, SE Even and odd years—a moderate-sized run 

showing no significant trend

102-40-033 Dora Lake Creek 677K Prince of Wales TH Even years—5 surveys from 1966-86, max. 

13,000 fish, min. 0 fish

Odd years—6 surveys from 1963-93, max. 

6.825 fish, min. 0 fish
194

Table 36—Pink salmon stocks in impaired or suspected water bodies (continued)

Stream Location

Pollutant

Number Name VCUa General sourcesb Comments

102-40-035 Dora Bay West 677K Prince of Wales TH Even years—1 survey in 1986, 13,000 fish

Odd years—3 surveys, 4,965 fish in 1985, 

2,000 fish in 1987, 100 fish in 1993

102-70-058 Thorne Bay 588K Prince of Wales IN, UR, SE, Even years—no significant trend

SM Odd years—increasing significantly

103-60-029 Steelhead Creek 595K Prince of Wales TH, RD Even years—14 surveys 1960-92; no 

significant trend

Odd years—increasing significantly

103-60-059 Port St. Nicholas NA Craig TH, UR Even years—no significant trend

Creek Odd years—increasing significantly

103-90-030 Staney Creek 588K Prince of Wales TH Even years—no significant trend

Odd years—increasing significantly

106-44-001 Hammer Slough 447S Petersburg UR, SE Even years—1 survey in 1984, 10 fish

Odd years—2 surveys, 6 fish in 1983, 20 fish 

in 1985

111-40-007 Switzer Creek 32C Juneau UR, DDT Odd years—3 surveys; max. 45 fish in 1991

Possible hatchery strays

111-50-035 Auke Nu Creek 27C Juneau UR Even years—2 surveys, 25 fish in 1968, 2 fish 

in 1988

Odd years—2 surveys, 1,828 fish in 1983, 42 

fish in 1987

111-50-037 Wadleigh Creek 27C Juneau UR, SE Even years—8 surveys, 1968-92, no 

significant trend

Odd years—5 surveys 1983-93, max. 2,000 

fish in 1985, min. 50 fish in 1993

111-50-042 Auke Creek 27C Juneau HA, UR, SE, Even and odd years—no significant trend

PP, LD, RE Research and hatchery effects

111-50-052 Montana Creek 27C Juneau UR Even years—2 surveys, both < 20 fish

Odd years—mean escapement 346 fish, 

no significant trend

112-13-006 False Bay 210C Chichagof TH Even years—no significant trend

Island Odd years—increasing significantly

112-42-016 Corner Bay 236C Tenakee Inlet TH Even and odd years—no significant trend

Fish pass present

112-65-015 Hawk Inlet Head 128C Hawk Inlet Metals Even years—6 surveys from 1970-92, max. 

2,000 fish in 1990, min. 100 fish in 1974

No odd-year surveys

112-65-025 Greens Creek 144C Admiralty PP Even years—increasing significantly

Island Odd years—no significant trend

113-41-012 Sitka Harbor 311C Sitka UR, HA, PP, Even and odd years—no significant trend

(Indian River) STP

113-41-021 Sawmill Creek 318C Sitka LF Odd-year surveys only—4 surveys, max. 

8,000 fish in 1985, min. 1,000 fish in 1979

113-54-007 Rodman Creek 292C North of Sitka TH Even and odd years—no significant trend

113-72-002 Klag Bay 271C Klag Bay Metals, MI, Even years—6 surveys, range 0-500 fish

TA Odd years—9 surveys 1961-91, no 

significant trend
195

Timing—Large differences occurred in the run timing of even- and odd-year lines

returning to certain streams in the region. The relation between these line differences

in spawning timing and fry emigration timing is unknown. Spawn-timing differences

of a similar magnitude have been reported previously (Aro and Shepard 1967, Skud

1958), but the mechanisms underlying these within-stream differences have not been

investigated. These mechanisms are of interest because both lines are exposed to

similar selective environments in fresh water, and timing differences can be viewed

as alternative solutions to the problem of reproducing successfully in a particular

environment. In our survey, all streams showing large between-line timing differences were on or near the outer coast, except for Lake Kathleen Creek on the west

side of Admiralty Island.

Another outcome of our analysis of run timing was that odd-year lines in both southern and northern regions were typically earlier than even-year lines. This result 

provided additional circumstantial support for the consistent finding that differences

between even- and odd-year lines are greater than differences within lines over large

geographic areas (Beacham and others 1985). The causes of pervasive differences

between even- and odd-year lines are unknown, but hypotheses include (1) founding

of even- and odd-year lines from genetically divergent stocks dispersing from different

glacial refugia; (2) heritable differences in development, growth, and maturation rate

preserved as coadapted complexes; and (3) heritable differences in migration route

(possibly due to item (1), above).

Stocks occupying the tails of the timing distribution for each analysis group are good

candidates for biochemical tests of genetic divergence. Analysis of run timing at a

fine geographic scale might reveal stocks temporally isolated from others in their 

area. If water temperature is a critical variable determining run timing (Sheridan

1962), then stocks from systems in karst terrain or with large lakes that buffer temperature fluctuations are likely to diverge in timing from nearby systems lacking these

Table 36—Pink salmon stocks in impaired or suspected water bodies (continued)

Stream Location

Pollutant

Number Name VCUa General sourcesb Comments

114-32-036 Eight Fathom 202C Chichagof TH Odd years only—2 surveys, 250 fish in 

Bight Creek Island 1965, 40 fish in 1969

115-33-020 Lutak Inlet NA Haines As, PAH Possibly an established population

a VCU = USDA Forest Service value comparison unit; approximately equivalent to a watershed; K = Ketchikan Area; S = Stikine Area;

and C = Chatham Area.

b Pollutant source types:

As = arsenic LD = land development RE = recreation

CH = channelized stream LF = landfill SE = sewage discharge

DDE = dichlorodiphenylchloroethane MI = mining SM = streambank or shoreline modification

DDT = dichlorodiphenyltrichloroethane PAH = poly-aromatic hydrocarbons TA = tailings

DO = dissolved oxygen PCB = polychlorinated biphenyls TH = timber harvest

GM = gravel mining PP = petroleum products UR = urban runoff

HA = harbor RC = road construction

IN = industrial RD = road runoff

Sources: Alaska Department of Fish and Game computerized escapement files. Available from: Alaska Department of Fish and Game,

802 3d Street, Douglas, AK 99824; ADEC 1992.

Discussion

Evaluation of Results
196

attributes. For example, 108 Creek (Whale Pass) is in an area of low-relief karst 

terrain on Prince of Wales Island and had exceptionally late run timing, and four

north-facing drainages in Tenakee Inlet (including Kadashan Creek, noted for its cold

water temperatures) had very early run timing (table 31). 

Escapement magnitude—Escapement magnitude results from habitat characteristics, such as the size of the available spawning habitat (see Swanston and others

1977) and spawning productivity per unit area, as well as ocean conditions and the

size of the harvest. Nonetheless, as population size increases, the intensity of natural selection necessary to counteract genetic drift or the homogenizing effects of gene

flow declines, and genetic differentiation among populations in response to selection

can occur more readily (Chakraborty and Leimar 1987, Wehrhahn and Powell 1987).

Reduced gene flow due to spatial isolation can further enhance the potential for

divergence of large populations. Pink salmon stocks spawning in large rivers in

British Columbia have diverged morphologically from populations in smaller rivers;

they generally have proportionately larger heads, thicker caudal peduncles, and larger fins than those spawning in small rivers (Beacham and others 1988).

We identified large breeding populations of pink salmon in eight locations in southeast Alaska, including the Taku River. The Taku River stock is estimated to have an

annual escapement of 350,000 to 500,000 fish (McGregor and others 1991), most of

them bound for the Nakina River spawning grounds far upstream. The Nakina River

population has the characteristics associated with high potential for genetic divergence: it is large, it is isolated from gene flow by the distance of freshwater migration, and its spawning environment (in the interior) may impose selection pressures

different from those on the coast. 

Managers have sometimes attempted to increase escapement size by installing fish

passes to bypass migration barriers and increase access to spawning areas. For

example, the Anan Creek stock was estimated to support historical harvests of 2 to 

3 million and still have escapements of several hundred thousand, making this one of

the world's largest pink salmon-producing systems (see footnote 1). Mean escapements for even- and odd-year lines during USBF weir operations (1925-32) were

253,413 and 285,210 fish, respectively (Rosier and others 1965). The ADF&G

installed a fish pass in 1967 to circumvent a waterfall in the tidal area that was a

velocity barrier to pink salmon migration during periods of high water flow (Bibb 

1987). Washouts and other problems prevented proper function of the fish pass, and

in winter 1975-76, the fish pass was removed. High water in 1976 prompted an airlift

of 129,000 pink salmon over the falls. In 1977, a replacement fish ladder was installed by the ADF&G and USDA Forest Service. This ladder was supposed to provide access in all flow conditions and increase pink salmon escapements to numbers

nearer the estimated optimal escapement value of 320,000 fish (USDA, n.d., cited in

Bibb 1987). Thorough analyses of the success of this project have not been conducted. Based on escapement-survey counts, we found no significant difference in

escapements among the periods before fish pass construction (1960-66), during

attempted installation (1967-77), and after construction of the ladder (1978-93)

(Kruskal-Wallis, even-years, N = 16, airlift year excluded, P = 0.62; odd-years, N =

17, P = 0.59). Comparison of only before and after samples also yielded no significant differences (Wilcoxon, even-years, N = 12, P = 0.47; odd-years, N = 14, P =
197

0.99). Subsequent to fish pass construction, even-year mean annual escapement

survey counts declined by over 20,000, and in odd years, survey counts increased by

over 10,000 fish. The fish pass has had no clear effect, positive or negative, on Anan

Creek pink salmon escapements.

Escapement trends—Over 18 percent of pink salmon stocks evaluated had significantly increasing trends. In contrast, the number of pink salmon stocks in the region

showing declining escapement trends was exceptionally small (21 of 1,334 stocks

analyzed, or less than 2 percent). The probability is high of obtaining this many

declining stocks purely by chance, even if all stocks were in fact stable or increasing.

Using a different method for evaluating trends, Baker and others (1996) found nearly

40 percent increasing and 3 percent declining or precipitously declining pink salmon

spawning aggregates in the region. The predominantly positive trend in pink salmon

escapements reflects ADF&G's successful implementation of efforts to rebuild pink

salmon stocks by increasing escapements. The success of this program was assisted by generally favorable ocean conditions and winter temperatures from 1980

through 1990 (Hofmeister 1994). Another factor contributing to success of the

rebuilding effort possibly was the generally pristine quality of spawning habitat in 

the region.

Ten of the declining stocks are in designated wilderness areas. Of the 11 stocks in

locations where commodity extraction or other potentially disruptive land uses are

possible, five locations have not had any development activities. Though the number

of stocks involved is small, the pattern suggests that fishing pressure may be the

most important factor contributing to declines. Twice as many stocks are declining in

even years as in odd years. Given that even-year lines tend to be lower in abundance than odd-year lines, even-year lines may experience proportionately heavier

fishing mortality. Three even-year stocks are declining in Seymour Canal, and data

quality is good for two of these stocks: Pack Creek and Windfall Creek. The high

value of Pack Creek as a brown bear observation venue increases the significance of

the decline at this location and suggests an attempt should be made to determine

factors contributing to the decline (such as the impact of bear predation and possible

disruption of spawning associated with bear-viewing activities). Of the 35 pink

salmon stocks spawning in water bodies designated as “impaired” or “suspected” by

ADEC (1992) and with adequate data to permit analysis of escapement trends, none

is declining and 10 show a significant increase. This surprising result suggests pink

salmon are relatively resilient in regard to diminished water quality, especially pollution resulting from urban development (the most frequently cited source of pollution).

The general lack of data on biological characteristics of pink salmon and the lack of

an accepted biological basis for stock discrimination at more refined geographic

scales than northern and southern regions were pervasive difficulties that hindered

our efforts to identify distinctive stocks and evaluate population status. Two pink

salmon systems in southeast Alaska, Sashin and Auke Creeks, are very well studied.

We considered these populations to have particular scientific value owing to the longterm databases available from each. Throughout the natural sciences, detailed longterm databases are gaining recognition as invaluable resources because they permit

thorough analysis of variation and cyclic trends. But for virtually all the remaining

stocks in the region, relatively little is known about their biology. 
198

Two central issues in pink salmon biology are the definition of stocks and the degree

to which local adaptation occurs in quantitative traits. One insight provided by the

work of Gharrett, Smoker, and coworkers is that, although between-stock variation in

allozyme frequencies measured electrophoretically is often limited, variation in quantitative traits, such as life history characteristics, is nonetheless present and potentially

critical to the long-term fitness of salmon populations (reviewed in Smoker and others

1991). Related to the issue of local adaptation are the matters of straying and gene

flow. High rates of straying in Prince William Sound relative to other locations may

reflect recent geologic instability in the sound. The earthquake of 27 March 1964 

produced widespread habitat disruption (Noerenberg and Ossiander 1964). Much of

this disruption occurred in the intertidal zone of streams, and Prince William Sound is

noted for having a large proportion of intertidal spawners (Noerenberg 1963, Roys

1971). A high level of straying was likely among returning pink salmon that found

natal streams no longer accessible. Given the general similarity of the intertidal

spawning environment, this straying was likely to result in successful gene flow.

Fifteen generations may not be an adequate amount of time for straying rates to

return to an equilibrium level after such a significant disruption (see footnote 3).

Furthermore, the relative lack of specific homing cues in the intertidal environment

may tend to increase background straying rates (Baker and others 1996).

The degree of ecological interaction among different species of Pacific salmon

deserves additional attention. Currently, predator-prey interactions are somewhat

better understood than competitive or mutualistic interactions; for example, coho

salmon smolts are known to be major predators on pink salmon fry, but chinook

salmon smolts caught in similar locations consume very few pink salmon (Hofmeister

and others 1988). Coho smolts also are known to preferentially prey on pink salmon

fry even when chum fry are more abundant (Hargreaves and LeBrasseur 1985,

Jones and others 1988). 

Interspecific competition is believed to play a significant role in driving abundance

cycles between pink and chum salmon (reviewed in Salo 1991), but experimental

tests of this hypothesis have not been conducted. Pink and chum salmon are likely 

to compete while spawning, as fry in the early marine environment (Gallagher 1979,

cited in Salo 1991), and possibly during the ocean feeding stage (Beacham and Starr

1982). In areas where strong line dominance occurs in pink salmon, chum salmon

adjust their maturation schedule to spawn in greater numbers in years when pink

salmon are less abundant (Gallagher 1979, cited in Salo 1991). The competitive

interaction between these species may have evolutionary implications for both, given

that fluctuations in abundance and age at maturity (in chum salmon) are probably

partly heritable (Smoker 1984). On a per-stream basis, the degree of habitat and

temporal segregation between pink and chum salmon in both freshwater and marine

environments is not well investigated. Likewise, little is known about the potential for

chum salmon to benefit from the presence of pink salmon, or if pink salmon function

as a sort of predator shield, both as fry in the marine environment and as adults in

the spawning stream (Dangel and Jones 1988). Widespread sympatric populations of

pink and chum salmon in streams in southeast Alaska make it a promising area for

investigating interspecific interactions.

Conceptual Issues
199

In southeast Alaska, considerable overlap in habitat use also occurs between pink

and sockeye salmon. Interactions between these species have not been studied.

The fertilizing effect of pink salmon carcasses (Kline and others 1990, 1993) could

have positive effects if pink salmon spawn above lakes used by rearing juvenile sockeye. Large numbers of decaying pink salmon carcasses also could have negative

effects if decomposition decreases dissolved oxygen content in sockeye rearing

lakes.

A fascinating and persistent question in pink salmon biology is, What factors are

responsible for line dominance? Line dominance is not apparent currently in southeast Alaska but has occurred historically in the southern region. The methods used

to collect data on pink salmon abundance and drainage patterns in a region may

determine how easily dominance can be detected. Dominance may be more readily

detected in areas where relatively few separate populations are taken in a fishery,

especially if the majority of the catch is derived from a few very productive systems.

In these areas, once dominance is established in the major regional stock, this pattern will be clearly reflected in catch statistics. This situation does not pertain to

southeast Alaska where there is a large number of small populations. Ricker (1962)

suggests that line dominance is the result of a variety of different factors, many 

operating locally. In southeast Alaska, alternative factors may operate on different

local stock groups, resulting in no net dominance of one line at the geographic scale

for which catch data are typically analyzed (i.e., northern and southern regions).

Evaluating this hypothesis requires reliable catch and escapement data for groups of

adjacent populations. If dominance occurs at a local scale in southeast Alaska, and 

if dominance is maintained by depensatory predation or interspecific competition

between pink and chum salmon, management efforts to maintain large populations 

of both lines may be futile (Ricker 1962). Understanding scale and underlying 

mechanisms would enable management strategies to be tailored to particular 

biological circumstances.

The final issue of considerable biological and practical interest is whether or not

overescapement is an important factor affecting pink salmon returns, and what magnitude of escapement results in diminishing returns. The conflicting hypotheses

regarding this issue are (1) very large escapements lead to both thorough seeding of

marginal habitats and thorough cleaning of spawning gravels, ultimately resulting in

increased recruitment; or (2) very high spawner densities lead to increased aggression among spawners, higher egg losses due to redd superimposition, and densitydependent reductions in fry survival, possibly by exceeding the carrying capacity of

the near-shore environment. In southeast Alaska, the 1985 and 1986 brood-year

escapement indices exceeded the estimated optimal escapement of 12 million fish

and these high escapements produced very low returns in both 1987 and 1988

(Hofmeister 1994). This small sample suggests overescapement may be reached at

about 15 million fish (Hofmeister 1994). Although it is unlikely that an adaptive management experiment will be conducted intentionally to determine what magnitude of

escapement is excessive (see McAllister and others 1992), such an experiment at a

management-district scale could provide very useful information. The basis of current

escapement goals is not well documented (Pacific Salmon Commission 1991).
200

The low number of declining stocks in the region indicated that pink salmon populations are not currently jeopardized by imminent risk factors. The following list contains some factors we consider potentially important, given the continuation of current

biological and economic trends. Heard (1991) reviews natural risk factors affecting

pink salmon populations. We focus on human-caused risks.

1. Escapement-goal management for pink salmon is certainly more appropriate than

fixed quotas, given the tremendous variation in abundance of pink salmon across

years. The application of escapement-goal management also has some potential pitfalls. One pitfall associated with pink salmon is a consequence of strong run-timing

segregation by sex, with males preceding females. If fishing is deferred until late in

the run, females may be harvested disproportionately, adversely unbalancing the 

sex ratio of escapements (Hofmeister and Dangel 1989). Sex-ratio data from weirs

on the Naha River, Hugh Smith Lake, and Karta River from 1986 to 1988 all show a

predominance of males; catches in the districts where these systems are found contain a predominance of females (Hofmeister and Dangel 1989). This risk factor is

most severe for stocks with intermediate run timing (see Alexandersdottir and

Mathisen 1982). The ADF&G uses inseason sex-ratio data to direct fishing effort at

entire runs rather than only early or late segments; however, the scale of harvest 

control may not be sufficiently precise to alleviate sex-ratio bias in the catch.

The effects of a sex ratio favoring males on stock productivity are not known, but the

obvious expectation is that productivity would decline when the sex ratio becomes 

too biased. Besides the simple reduction in numbers of eggs deposited, productivity

declines could result from intensification of competition among males for access to

females. Male pink salmon are very aggressive at the spawning ground and 

competition among males is extreme (Heard 1991, Keenleyside and Dupuis 1988).

Increased competitive interactions among large males might increase the spawning

success of small, femalelike males. If femalelike morphology in males has a genetic

basis, a decline over time in male body sizes could result (Gross 1985, 1991).

2. Although the survey of many index streams in the region suggests that management of pink salmon occurs at a relatively fine geographic scale, management decisions ultimately are based on attainment of district-wide escapement goals. It is 

possible that, at the district level, escapement goals can be exceeded while some

populations disappear. In essence, smaller or less productive populations can be

overexploited as fisheries grow and develop based on larger or more productive 

populations with similar migratory pathways or spawning destinations. The economic

and political momentum of large fisheries on productive stocks make them difficult to

slow or divert, leading to the potential depletion or extirpation of weak stocks. The

capacity of small or less productive populations to persist in a changing environment

also may be compromised indirectly, if overexploitation reduces genetic variability

(Gharrett and Smoker 1993). If small pink salmon populations are reduced or eliminated, wildlife populations relying on the pink salmon resource could be adversely

affected, and removal of salmon may compromise the integrity of entire vertebrate

communities (Willson and Halupka 1995). The significance of this risk factor depends

on the degree to which pink salmon stocks are genetically isolated and geographically distinct. At this time, it is completely unclear if the geographic scale of management districts corresponds to the biological reality of pink salmon metapopulations. 

Risk Factors
201

3. Prespawning mortality of pink salmon in southeast Alaska is primarily caused by

low water flows and large numbers of spawners, resulting in hypoxic conditions

(Davidson 1933, cited in Heard 1991; Heard 1991; Murphy 1985; Pentec Environmental, Inc. 1991). Historical surveys revealed 76 streams with prespawning mortalities from 1949 to 1989 (see footnote 5, cited in Pentec Environmental, Inc. 1991), but

undocumented die-offs are believed to be more common (Murphy 1985). The summers of 1992 and 1993 were particularly warm and dry in southeast Alaska and

numerous fish kills occurred during these years, particularly on Prince of Wales

Island.5 Prespawning mortality tends to occur in small drainages in low-elevation terrain with little buffering capacity in the form of lakes or ponds, or in confined intertidal

systems with restricted tidal exchange (Pentec Environmental, Inc. 1991). The former type of drainage also is favored for logging activities, which tend to increase

stream temperatures (reviewed by Beschta and others 1987), decrease dissolved

oxygen in surface as well as intragravel water (Chamberlin and others 1991), and in

some situations, decrease stream flow (Hicks and others 1991). These effects are all

more pronounced in small drainages, and retention of forested buffers along streams

tends to decrease them. Consequently, appropriate timber management practices

are necessary to minimize logging impacts on prespawning mortality. Prespawning

mortality events tend not to remove large portions of spawning populations (Murphy

1985), but logging can reduce the climatic buffering capacity of streams sufficiently to

increase the frequency of die-off events. Repeated die-offs could have cumulative

effects on population sizes.

4. Decreases in body size may have negative consequences on pink salmon productivity. Body size of pink salmon in southeast Alaska shows a significant decline

across years. Decreases in female body size may decrease egg number or size, or

both, and survival of eggs, alevins, and fry (Bilton 1973, cited in McAllister and others

1992). In coho salmon, larger females obtain better redd sites, dig deeper redds that

are less susceptible to scour, and defend their redd longer and more successfully,

thereby reducing the frequency of redd superimposition (van den Berghe and Gross

1989). If similar patterns apply to pink salmon, then decreasing body size can diminish stock productivity. Given that payment for catches is made by weight, not number, the obvious result of declining body size is increasing pressure to take larger

numbers of fish. This may not be an important issue if small body size continues to

be associated with strong runs.

5. Although wild coho salmon consume more pink salmon fry than do hatchery-reared

coho (Hofmeister and Dangel 1989), the very large numbers of coho smolts that can

be released by hatcheries make them a potential threat to nearby pink salmon populations. This potential risk factor is easily addressed by delaying hatchery releases

until after pink salmon fry move offshore (Hofmeister and others 1988).

5 Gibbons, D. 1989. Alaska working group on cooperative

forestry/fisheries research annual report for 1989. Unpublished

report. On file with: U.S. Department of Agriculture, Forest

Service, Wildlife and Fisheries, P.O. Box 21682, Juneau, AK

99802.

6 Personal communication. 1996. Brenda Wright, fisheries biologist, U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station, 2770 Sherwood Lane, Juneau, AK
202

Another risk associated with hatchery production of pink salmon in southeast Alaska

relates to the effects of hatchery returns on inseason management. Brood stock from

the DIPAC hatchery was derived in part from the Kadashan River, a stock with relatively early run timing. Burnett Inlet hatchery is developing Anan Creek brood stock;

Anan Creek pink salmon also have relatively early run timing for their area. Development of fisheries on these hatchery returns has the potential to increase exploitation rates on nearby wild stocks with early timing, such as the Taku River stock.

Furthermore, if the problem of disproportionate catch of females is addressed by

shifting the basis of management more toward fishery performance and away from

escapement goals, then hatchery fish can confound determination of natural stock

run strength (Pacific Salmon Commission 1991). Large, early returns of hatchery fish

could provide an erroneous impression of a strong run, if the hatchery fish are not

distinguishable from wild populations. This risk factor can be easily minimized by

requiring that hatchery fish be marked, and new, more efficient marking techniques

are being developed.

Pink salmon are immensely abundant in southeast Alaska, with populations inhabiting

over 3,000 streams. Because even- and odd-year lines are reproductively isolated by

the 2-year life cycle of pink salmon, over 6,000 separate populations are present in

the region. Spatial and temporal factors have been used to characterize these populations into stock groups. Both even- and odd-year lines are divided into northern

and southern stock groups based on differences in migratory pathways and apparent

lack of mingling across the boundary at Sumner Strait. Within the northern and

southern regions, pink salmon stock groups also have been characterized by migratory timing (early, middle, and late spawning groups). Spawning timing is related to

stream temperature regime; therefore, stock groups defined by spawning timing also

show rough geographic separation, with early stocks concentrated on the mainland

and late stocks on the outer islands. Genetic data distinguished two geographic

stock groups within the southern half of the region: inland and Prince of Wales

groups. No widespread genetic surveys of pink salmon in southeast Alaska have

been completed. Additional genetic and biological data from pink salmon escapements would be useful to define more clearly the spatial and temporal boundaries of

pink salmon stocks. Existing data suggested that stock separation may occur at

scales ranging from within streams, to groups of populations separated by hundreds

of kilometers of shoreline. The spatial extent of stocks probably differs among areas,

with finer grain separation in areas of higher habitat heterogeneity and temporal stability. Except for the populations in Sashin and Auke Creeks, relatively little is known

about the biological characteristics of individual pink salmon populations in southeast

Alaska. Spawning timing and population size were the only biological characteristics

for which large databases exist that include populations throughout the region. 

Spawning timing—Based on analysis of index dates, 12 even-year, and 2 odd-year

southern-region populations have distinctively early run timing (see fig. 45 for approximate geographic location). Four odd-year southern populations have distinctively late

run timing. No populations in the northern region have distinctive timing, probably

because the histograms for this region suggest broader bimodality than those for the

southern region. The Taku River stock appears to be conspicuously early in its run

timing, but the relation between mean date of migration calculated at a fishwheel and

our timing index was unclear. Differences in spawning timing can limit gene flow.

Conclusions

Distinctive Stocks
203

Figure 45—Approximate location of southeast Alaska pink salmon stocks, with timing index dates, that are

outliers from the overall distribution for their line and region, and stocks with timing differences between

lines that are outliers. The Taku River stock is included based on run timing calculated from fishwheel captures.
204

Timing differences—Two southern-region streams, and five northern-region streams

showed exceptional differences in timing between even- and odd-year lines, possibly

indicating alternate responses to similar selective environments by each line.

Large escapements—Six southern-region streams and two northern-region streams

had exceptionally large escapements. Wilson River and Anan Creek in the southern

region had large escapements in both even and odd years. Large populations may

be important contributors to fisheries and may diverge genetically, if the rate of gene

flow is not great enough to overcome the change in allele frequencies due to 

selection. Based on a preliminary allozyme survey, the Anan Creek population is

genetically divergent from other populations sampled in southern southeast Alaska

(see footnote 4).

Geographic location—We did not compile data on spawning migration length for pink

salmon populations throughout the region, but the pink salmon population that spawns

in the Nakina River is the only population traversing the coastal climate and spawning

in an area with a more continental climatic regime. Isolation by distance and different

selection pressures could contribute to genetic divergence of this population.

Special scientific value—The extraordinary amount of research conducted at

Sashin and Auke Creeks has resulted in a wealth of information about pink salmon

biology at these sites, as well as invaluable long-term databases. Insufficient information was available from other pink salmon populations in the region to know if the

Sashin and Auke Creek populations are biologically unique. The study of pink

salmon populations at these locations has made, and will continue to make, significant contributions to our understanding of this species.

Only seven of 21 declining stocks were represented by relatively good data. Factors

responsible for declines of well-surveyed stocks are generally unknown. Habitat disruption in the form of timber harvest has occurred in the watersheds of Snake Creek

and Lake Florence Creek.

Existing data indicated that diminished water quality does not have a clear negative

effect on pink salmon escapements. These data are scant, and additional monitoring

of populations inhabiting impaired water bodies is recommended. Ten pink salmon

populations were found in impaired water bodies.

The low percentage (about 2 percent) of declining pink salmon stocks in the region

indicated that pink salmon populations are not generally at risk in the region at the

present time. Factors that could contribute to future declines include sex-biased

catches that lead to a predominance of males in escapements, prespawning mortality, egg and alevin mortality associated with changed hydrologic and thermal regimes

of streams in logged watersheds, and an ongoing decline in pink salmon body size

that could reduce productivity.

The cooperation of L. Talley and S. Johnson greatly facilitated access to the information contained in the ADF&G Integrated Fishery Database, without which this report

would have been impossible. G. Gunstrom, M. Harris, and K. Savikko provided

essential ADF&G documents. S. Marshall provided both access to the information

resources of the ADF&G and criticism that improved this project. Lengthy conversations with B. Heard, K. Hofmeister, and H. Jaenicke introduced us to the important

Declining 

Escapement Trend

Water Quality

Risk Factors

Acknowledgments
205

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W. Smoker provided copies of unpublished theses of K. Hebert and P. Goddard. 

D. Aho provided useful comments on an earlier draft. Special thanks to A.J. Gharrett

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215

Chum salmon (Oncorhynchus keta) inhabit over 3,000 streams throughout southeast

Alaska. This review contains run-timing indices and escapement-trend evaluations

for over 400 of these populations and analysis of additional biological characteristics

for 46 populations. Throughout the region, summer chum salmon populations spawn 

primarily in mainland or northern-island drainages, and fall populations spawn 

primarily in southern-island drainages. At the subregional scale, genetic analysis of

populations in southern southeast Alaska has revealed three geographic groups that

may reflect historical colonization patterns. Differences in migratory pathways that

reduce gene flow among groups may have preserved these differences. Four chum

salmon stocks have distinctive characteristics based on reliable data, including the

Chilkat River stock, which has late run timing and large population size and is an

important resource for wildlife. Twelve additional stocks may have unusual biological

characteristics based on limited sampling (seven) or anecdotal reports (five). Twelve

populations (2.8 percent) of chum salmon had escapement trends that were increasing significantly, and 41 populations (9.5 percent) had declining escapement trends, 

a higher proportion than any other species surveyed. Risk factors that may contribute to declines in chum salmon abundance include inadequate understanding of

chum salmon population biology, logging practices that result in increased sediment

loads in spawning streams, and large-scale enhancement activities that may contribute to over exploitation of wild stocks.

Keywords: Chum salmon, Oncorhynchus keta, southeast Alaska, run timing, body

size, intraspecific diversity, population status.

Chum salmon inhabit the widest geographic range of all the Pacific salmon. In North

America, they were found from the Sacramento River in central California to the

Mackenzie and Anderson Rivers on the Arctic coast of Canada's Northwest Territories

(Bakkala 1970). Chum salmon inhabit over 3,000 streams throughout southeast

Alaska, and additional chum salmon populations are still being identified. Chum

salmon stocks are distributed more densely and evenly in southern southeast Alaska

than in northern southeast Alaska. Except for the East Alsek and Italio Rivers, relatively few chum salmon populations occur in the Yakutat region. Transboundary

chum salmon populations occur only in the Stikine and Taku Rivers in southeast

Chum Salmon 

(Oncorhynchus keta)

Abstract

Introduction
216

Alaska. We reviewed information for more than 400 chum salmon populations in

southeast Alaska, primarily evaluations of population status and run timing based on

escapement surveys. Information on biological characteristics is presented for 46 

populations.

Chum salmon populations in southeast Alaska are separated into two types that are

commonly referred to as “summer” and “fall” run populations after the designations

for Asian chum salmon by Berg (1934, cited in Salo 1991). Except for differences in

run timing, these populations do not show the same set of correlated characteristics

that Berg used to define these types (Salo 1991). Summer chum salmon in southeast Alaska are typically characterized as having larger body size and older age composition. Summer chum salmon spawn from July to September and are found primarily in northern southeast Alaska. Fall chum salmon spawn from September to

November and predominate in southern southeast Alaska, especially in Prince of

Wales Island drainages. Exceptions to this general pattern include large fall chum

salmon populations in the Chilkat, Excursion, and Taku Rivers in northern southeast

Alaska (several small runs as well; McGregor and Marshall 1982) and large summer

runs in the Tombstone and Keta Rivers, Hidden Inlet, and Fish Creek (Hyder) in

southern southeast Alaska. Both types of chum salmon runs are found in some

streams. For both summer and fall chum salmon, migratory timing differs by sex,

age, and body size; males tend to precede females (Clark and McGregor 1983),

older fish tend to precede younger fish, and larger fish in a given age class are generally found in the early portion of runs (Dangel and others 1977).

Throughout their range, chum salmon typically spawn in the lower 200 km of rivers,

sometimes using the intertidal zone. Exceptions to this pattern occur, such as populations that ascend the Yukon River over 2500 km to spawn. The inability or reluctance of chum salmon to surmount barriers (including some fish ladders) is a characteristic that limits upstream migration and determines the suitability of streams as

spawning habitat (Hale and others 1985). Like most other salmonid species, chum

salmon prefer to spawn in locations where upwelling occurs or just above areas of

turbulent flow (Salo 1991). A wide range of temperatures, water velocities, and substrates are acceptable (Hale and others 1985).

Eggs incubate in redds for 50 to 130 days, depending on water temperature (Bakkala

1970), and emergence occurs from February through May (Jones and others 1988;

Koerner 1988, 1989, 1990). Late-running stocks often select spawning areas with 

relatively warm winter temperatures. The relation among spawning timing, water 

temperature, and emigration timing probably reflects evolutionary synchronization of

these events with "windows of opportunity," such as near-shore plankton blooms, that

maximize fry survival (Holtby and others 1989, Miller and Brannon 1982). Mortality of

eggs and alevins is high; only 10 percent of eggs typically survive to emergence

(Hunter 1959). Some controversy exists over whether all newly emerged juveniles

immediately begin emigration to saltwater or if some remain to feed in freshwater for

several weeks or months (Holtby and others 1989, Mason 1974, Salo 1991). No data

are available from southeast Alaska to address this issue. Downstream migration of

fry occurs primarily at night (Hale and others 1985, Koerner 1990). During the day fry

remain near the gravel. Approximate mean dates of emigration are available for only

three stocks in southeast Alaska; roughly 8 April for Fish Creek (Hyder, early segment

Life History
217

of run missed; Koerner 1988, 1989, 1990) and 2 May for Kadashan Creek (early part

of run missed; Jones and others 1985), both of which are summer stocks, and 13

May for Sunny Creek, a fall stock near Ketchikan (Hofmeister 1990). Fry from all

three locations average just under 40 mm in length at emigration (see refs. above).

Chum salmon smolts typically remain in estuaries for 1 to several months where they

feed extensively and grow rapidly (Healey 1980, Mason 1974). Movement offshore

typically occurs when inshore food resources begin to decline and fry are large

enough to feed on larger prey and avoid predators (Salo 1991). Studies in southeast

Alaska indicate early marine predation on chum salmon smolts by coho smolts is not

nearly as intense as coho predation on pink salmon (Hofmeister and others 1988,

Jones and others 1988). Chum salmon may in fact benefit from the presence of pink

salmon, because coho selectively prey on pink salmon fry (Hargreaves and

LeBrasseur 1985).

Increasing evidence indicates chum salmon occupy a unique trophic position in the

ocean environment, relative to other salmon species. Chum salmon apparently feed

predominantly on gelatinous zooplankton (Welch and Parsons 1993), while other

salmon species are primarily piscivorous.

Little is known about stock-specific oceanic migration patterns of chum salmon from

southeast Alaska, especially in the northern half of the region. Returning adults 

typically move inshore in early July, peak in late July, and decrease rapidly in August.

Annual variation in this pattern is not well studied. District 101-11 near the mouth of

Portland Canal has been identified as an important mixing area for returning chum

salmon, including stocks from as far north as District 106—northeastern Prince of

Wales Island (Pacific Salmon Commission 1987). An extensive juvenile marking 

program in Fish Creek (Hyder) should provide information on the migratory pathways

and harvest patterns of this stock (Koerner 1990).

Chum salmon spawning populations consist of age 0.2, 0.3, and 0.4 individuals. On

average, chum salmon from southeast Alaska typically spend about 3 years in salt

water before returning to spawn (grand mean saltwater age [MSWA] = 3.24 years);

however, there is considerable variation about this mean within seasons, among

years, and among populations. In many systems in northern southeast Alaska, age

0.4 fish consistently dominate escapements. Males and females differ little in mean

age in escapements. Precociously maturing males apparently are rare among chum

salmon populations in southeast Alaska. No age 0.1 chum salmon of either sex have

been reported for systems studied in the region.

Over broad geographic areas, the body size of chum salmon decreases with increasing latitude (Salo 1991). Although the largest chum salmon in southeast Alaska are

found in the southern area, near Portland Canal, the overall trend is not readily

apparent throughout the region. Male chum salmon tend to be significantly larger

than females (regional mean male length for age 0.3 individuals = 641 mm, mean

female length = 618 mm). Body size tends to increase with age for both sexes.
218

Considerable interest exists in apparent temporal trends of decreasing size and

increasing age in chum salmon. This pattern has been found for both wild and hatchery stocks in North America and Asia1 2 (Helle 1993, Ishida and others 1993, Ricker

1980). The causes and consequences of this trend are unclear. Density-dependent

effects in the ocean have been suggested as one possible cause (Ishida and others

1993). Selective harvest may have contributed directly to increasing age and indirectly, through selection for slow growth rates, to the general trend of decreasing size

(Ricker 1980). Whatever the cause of the observed trends may be, because reproductive success in chum salmon is positively related to body size in some stocks

(Helle 1989; but see Ricker 1980), a potential consequence of decreasing body size

is decreased productivity.

No chum salmon populations in southeast Alaska are noted for having distinct patterns of interannual variation in life-history characteristics and abundance. In other

geographic areas where these oscillations occur, they are thought to result from competition between juvenile chum salmon and pink salmon for zooplankton resources, 

in conjunction with pronounced even- and odd-year cycles of pink salmon abundance

(Salo 1991). When pink salmon are abundant, chum salmon are not and vice versa.

Cycles of chum salmon abundance are not apparent in southeast Alaska, perhaps

because pink salmon in the region have not shown pronounced cycles in recent

times (Hofmeister and others 1988).

The first recorded commercial catch of chum salmon in southeast Alaska occurred in

1896 when 2,938 fish were reported caught (Rich and Ball 1933, cited in Clark and

Weller 1986). Commercial harvest increased during the next two decades, peaking 

in 1918 when 9.35 million chum salmon were harvested (Clark and Weller 1986).

Catches remained at a high level until the early 1950s, when a substantial decline

occurred. Poor harvests persisted for nearly three decades; the average annual harvest from 1971 to 1980 was 1.43 million fish. In the mid-1980s, a modest increase

began, with the average annual harvest for 1986-90 reaching 2.76 million fish (Rigby

and others 1991; fig. 46). 

An important factor associated with the decline in harvest has been a reduction in

directed fisheries for chum salmon. Currently in southeast Alaska, significant fisheries directed primarily at wild-stock chum salmon occur only for summer and fall

chum salmon in the Tree Point-Portland Canal area, and for fall chum salmon in Icy

Strait-Lynn Canal and district 102 (southeastern Prince of Wales Island). Small

directed fisheries for chum salmon occur in districts 105 and 111. The majority of

chum salmon are harvested incidentally in purse-seine fisheries for pink salmon, and

the number of chum salmon harvested is related to the duration of pink salmon 

fishing periods (Clark and Weller 1986). Chum salmon also are harvested incidentally in fisheries for sockeye (early season) and coho salmon (late season). More than

60 percent of chum salmon are harvested by purse seine, about 30 percent are

caught by gill net, and the remainder are taken in troll, trap, sport, and subsistence

fisheries.

Management

1 Personal communication. B. Bachen, Northern Southeast

Regional Aquaculture Association, 1308 Sawmill Creek Boulevard,

Sitka, AK 99835.

2 Personal communication. 1996. K. Hofmeister, fisheries biologist,

Alaska Department of Fish and Game, 802 3d Street, Douglas, AK

99824.
219

Escapement surveys are the primary management tool for chum salmon. The 

accuracy of these surveys is compromised, however, by the need to count the more

numerous pink salmon present in most of the streams where chum salmon spawn.

Fixed escapement goals have been established only for Fish Creek (Hyder) and

Disappearance Creek, both in southern southeast Alaska. Achievement of these

goals has been monitored through escapement surveys and weir counts. Few weirs

in the region are operated explicitly for the enumeration and sampling of chum

salmon populations. Because few fisheries are directed toward chum salmon, few

management research efforts are directed toward this species.

A significant proportion of the catch in recent years has been attributable to hatchery

production (e.g., Neets Bay and Whitman Lake hatcheries contribute over 192,000

chum salmon annually to the Tree Point harvest [Pacific Salmon Commission 1991],

and Hidden Falls hatchery alone contributed 725,000 fish in 1992 [see footnote 1]).

Large returns to hatcheries have required an increasing number of special time and

area openings to harvest them (Clark and Weller 1986). The need for these openings and the presence of large numbers of unmarked hatchery fish have complicated,

and in some cases confounded, the management of wild-stock fisheries (Pacific

Salmon Commission 1987).

Chum salmon stocks of southern southeast Alaska and northern British Columbia,

particularly those in Portland Canal, have been designated as stocks of special concern by the U.S./Canada Pacific Salmon Treaty (Annex IV, Chapter 2). The stocks

located on the Canadian side of Portland Canal are of greatest concern, because

they collapsed in the mid-1970s and have not recovered. Summer chum salmon

runs throughout the boundary region are depressed, relative to their historical abunFigure 46—Annual commercial harvest of chum salmon in southeast Alaska, 1890-

1991 (data from Rigby and others 1991).
220

dance (Pacific Salmon Commission 1991). Boca de Quadra fisheries have been

closed frequently in the past 25 years because of weak runs (Pacific Salmon

Commission 1991).

The limited development of tools to discriminate among stocks of chum salmon has

limited the implementation of stock-specific management strategies. Both scalepattern analysis (McGregor and Marshall 1982) and allozyme surveys (Davis and

Olito 1982; Kondzela and others 1989, 1994) can be used as effective stock separation tools for chum salmon, but neither technique has been broadly applied throughout the region. 

The “special concern” status of populations in the boundary region has motivated

extensive genetic surveys (Kondzela and others 1989, 1994). Consequently, the

genetic relationships among chum salmon populations in southern southeast Alaska

are relatively well understood compared to those of other salmon species in the

region. Chum salmon populations in the boundary region cluster into six geographically defined groups, three of which are in southeast Alaska (Kondzela and others

1994). These three groups can be roughly described as central southeast (north of

Sumner Strait), Prince of Wales Island area, and southern southeast east of Clarence

Strait. The divergence of the Prince of Wales stock group may reflect the presence

of glacial refugia on this island (Kondzela and others 1994; also see “Conceptual

Issues” below). 

The stocks sampled for genetic analysis overlap little with stocks sampled for other

biological characteristics, thereby preventing us from determining if phenotypic characteristics follow similar geographic clustering patterns as allozyme frequencies, or if

stocks exhibiting unusual phenotypes are also genotypically divergent. 

Data from escapement surveys and sampling were used for the analyses presented

in this report. Adult body length data were converted to mideye-to-fork lengths by

using equations in Pahlke (1989). Ten stocks were included in a variance-component

analysis of adult fork lengths (table 37). These stocks were selected by the criteria of

having at least 5 years of sampling with samples of at least 15 individuals of each

sex in the 0.3 age class. The years sampled were not the same for all stocks. No

other age classes were analyzed by the variance-component procedure because

insufficient data were available. Stocks with at least 6 years of sampling were selected for inclusion in analyses of temporal trends in body length and age at return.

The methods described in the “General Introduction” were used to calculate the 

timing of peak escapement. Because chum salmon surveys are typically ancillary to

pink salmon surveys, they may not reflect true timing for chum salmon. Escapement

survey data and daily weir count data were taken from computerized files maintained

by the ADF&G, Division of Commercial Fisheries.

The age structure of chum salmon stocks was evaluated in terms of MSWA and the

proportions of escapement samples in each age and sex class. Because the age

structure and sex ratio of chum salmon runs vary during the spawning season, 

evaluations of these characteristics based on “snapshot” samples from runs may be

biased. Weirs that remain in operation for the full duration of runs provide the best

Methods

Stock Discrimination

Data Analysis

Procedures
221

opportunity for sampling throughout the run and for providing accurate data on age

composition and sex ratio. Sampling for age and sex at weirs is limited to only five

streams in the region, and sampling was incomplete for at least two of these sites

because the weir was pulled before the run was complete.

Biological characteristics of summer and fall chum salmon populations were not 

analyzed separately because they form a continuum in the region and are difficult to

separate. Characteristics of stocks spawning in island versus mainland drainages

were compared with a t-test or Wilcoxon tests.

Biological data other than run timing or escapement magnitude were available for

only 46 of the 3,000 known populations. Most data were from stocks that spawn

north of Sumner Strait and the Stikine River, although most chum salmon stocks in

the region are found south of Sumner Strait. Many data sets were collected while

eggs were taken for hatchery production or incubation boxes or during development

of spawning channels. Long-term data sets were available only for the Fish Creek

Table 37—Variance component analysis of chum salmon mideye-to-fork 

lengthsa b

Source Degrees

of of Type 1 sum Error Expected Variance Percentage

variation freedom of squares F-test term mean square componentc of total

Males

Total 7,187 11,937,581.86 1,661.00 1,717.65 100.00

Stocks 9 3,147,533.40 12.16 Years 349,725.93 438.69 25.54

Years 40 1,150,283.38 26.87 Error 28,757.08 208.66 12.15

Error 7,138 7,630,765.08 1,070.29 1,070.29 62.31

Females

Total 7,004 10,099,223.55 1,441.92 1,492.35 100.00

Stocks 9 2,801,248.56 9.14 Years 311,249.84 382.11 25.60

Years 40 1,362,032.22 39.9 Error 34,050.81 256.76 17.21

Error 6,955 5,935,942.77 853.48 853.48 57.19

a Body lengths of age 0.3 fish from escapements.

b Stocks included in the analysis and years when sampling occurred:

101-15-085 Fish Creek-Hyder 1973-77

102-40-043 Disappearance Creek 1973, 1975-77, 1984

111-50-052 Montana Creek 1982-85, 1988

112-42-025 Kadashan Creek 1976-77, 1982-84

114-27-030 Spasski Creek 1984-88

114-80-020 Excursion River 1975-76, 1982-84

115-32-025 Chilkat River 1974-76, 1982-83

115-32-046 Klehini River 1976, 1982-85

115-32-048 Herman Creek 1982-85, 1987

182-20-010 East Alsek River 1983-87

c Variance components computed from means, standard errors, and sample sizes.
222

(Hyder), Disappearance Creek, Kadashan Creek, and Chilkat River stocks; all are

among the largest stocks in the region. Most of the biological information available is

not representative of the majority of chum salmon populations found in the region. In

their 1987 report, the Northern Boundary Technical Committee of the Pacific Salmon

Commission (1987) described the situation succinctly: “Our knowledge of chum

stocks is minimal.”

Adequate samples of adult lengths from escapements were available from 46 wild

stocks. Age 0.3 and 0.4 adult lengths differed significantly by sex and age (two-way

ANOVA, sex, F = 59.5, P < 0.001; age, F = 71.0, P < 0.001). Age 0.4 males were

largest and age 0.3 females smallest.

Both age 0.3 and 0.4 males showed nearly significant differences in body length

between island and mainland spawning populations; mainland spawners were larger

(age 0.3, t = 1.95, P = 0.06; age 0.4, t = 1.88, P = 0.07). For females, the same

overall pattern was present, and for age 0.4 females the difference in body length

was significant (age 0.3, t = 1.27, P = 0.21 NS; age 0.4, t = 2.10, P = 0.04).

Variance-component analysis indicated that over 62 percent of total variation in male

body length is attributable to variation among individuals within stocks, and 25.5 percent is accounted for by differences among stocks (table 37). Females were less

variable among individuals (57 percent), but interannual variation was higher (17 

percent versus 12 percent for males).

Five stocks were analyzed to determine if temporal trends in adult body length were

present. Only one stock, Herman Creek (Chilkat) showed a significant trend, with

both males and females decreasing in size (table 38). The lack of significant results

for the other stocks may be due in part to the few years for which data were available. More detailed analyses of changes in body size of chum salmon have revealed

a distinct downward inflection point beginning in the mid-1980s.3 Compared to

Herman Creek, all other stocks analyzed had fewer post-1985 samples.

Results

Adult Body Length

Table 38—Regression results for trends in chum salmon mideye-to-fork lengtha

Males Females

No. of

Stream years R- Signi- R- Signinumber Name sampled Years squared Slope P-value ficance squared Slope P-value ficance

101-15-085 Fish Creek- 6 1972-77 0.08 1.21 0.50<P<0.9 NS 0.11 2.07 0.50<P<0.9 NS

Hyder

115-32-025 Chilkat River 8 1972-84 0.13 -1.87 0.20<P<0.4 NS 0.18 -2.71 0.20<P<0.4 NS

115-32-046 Klehini River 8 1972-88 0.41 1.40 0.05<P<0.1 NS 0.00 0.05 P>0.9 NS

115-32-048 Herman 8 1982-90 0.52 -3.33 0.02<P<0.05 * 0.60 -4.33 0.02<P<0.05 *

Creek

182-20-010 East Alsek 7 1959-87 0.12 -0.41 0.40<P<0.5 NS 0.50 -1.08 0.05<P<0.1 NS

River

NS = not statistically significant; * = 0.05 > P > 0.01.

a Body lengths of age class 0.3 fish.

3 Personal communication. 1996. J. Helle, fishery biologist,

National Marine Fisheries Service, Auke Bay Laboratory, 11305

Glacier Highway, Juneau, AK 99801.
223

No chum salmon stock in the region was distinct in terms of body size. Age 0.4

female chum salmon from Fish Creek (Hyder) were over 20 mm longer, on average,

than females from other stocks in the region, but the distribution of body sizes was

relatively even and the Fish Creek population was not an outlier (fig. 47).

The West Bay Head stock showed a distinctive level of sexual dimorphism in body

size, with age 0.4 males averaging more than 70 mm longer in mideye-to-fork length

(fig. 48B), but this result was based on a small sample from a single year. The Port

Camden stocks were the only populations in which females were distinctively larger

than same-age males but, again, the sample was limited (fig. 48).

Figure 47—Frequency distributions, outlier plots, and normal quantile plots for chum salmon mean mideye-to-fork lengths: (A) age 0.3

males, N = 46; (B) age 0.4 males, N = 46; (C) age 0.3 females, N = 34; and (D) age 0.4 females, N = 34. Mean lengths calculated for

escapements from all years sampled. No outliers are present.
224

Figure 48—Frequency distributions, outlier plots, and normal quantile

plots for sexual dimorphism in chum salmon body length by age class.

Sexual dimorphism in body length calculated as male minus female mideye-to-fork lengths: (A) age 0.3, N = 46, and (B) age 0.4, N = 46.

Means calculated for escapement samples from all years. Port Camden

and West Bay Head stocks are outliers, but these stocks were sampled

for only one year.

Table 39—Summary statistics for chum salmon run timing

Survey index

Statistic Weir countsa Total Mainland Island

Number of stocks 9 428 17 23

Mean (Julian day) 214.6 234 246.1 227.6

Variance 123.4 313.7 976.4 375.7

Standard deviation 11.8 17.7 31.3 19.4

Minimum 200 200 211 200

Maximum 238 306 306 265

a Systems with at least 4 years of data.
225

Ten streams had weir data that could be used to calculate mean dates and duration

of freshwater migrations. In most streams, however, the weir was removed before the

chum salmon run was complete. The longest temporal data sets were from two

streams in the Kadashan River drainage—east and west (Tonolite Creek) branches 

of the Kadashan River, which had more than 18 years of escapement counts. No

change or trend in mean date of migration past the weir was detected for either

branch during the sample period, from 1969 through 1988. No other data sets were

sufficiently long to permit analysis of trends in mean date through time. The mean

dates of migration were 26 July for the east branch and 25 July for the west branch

(standard error was 1.1 for both); mean run duration for both branches was about 2

months for runs averaging 12,000 and 16,000 fish, respectively.

The mean of run-timing indices calculated for 428 stocks in the region was 21

August, with the range extending from 19 July to 2 November (table 39). The west

branch of Kadashan Creek had the earliest index date, 19 July, which precedes the

mean weir migration date by nearly a week. This pattern suggested that the index

date underestimates the date of peak spawning; however, because weir mean date

and index date can be compared in only one system, no conclusions were possible.

The run-timing index of island stocks was significantly earlier than for mainland stocks

(N = 40, t = 2.15, P = 0.04; table 39). This comparison included only stocks for which

body-length data were available and the result therefore was strongly influenced by

the large number of late-spawning stocks in the Chilkat drainage included in the

analysis, as well as the dearth of fall-type stocks from the islands of southern southeast Alaska. Based on an index date of 2 November, the timing of peak spawning of

the Chilkat River stock is considerably later than other stocks in the region (fig. 49).

Two other stocks in the Chilkat drainage, Porcupine Creek and Herman Creek, as

well as the Taku River and one of its tributaries, Fish Creek, all have relatively late

run timing. Peak survey counts occur in the second week in October in these systems.

Counts from escapement surveys and weirs, age structure, and sex ratio were the

data types we evaluated to examine the demographic characteristics of chum salmon

populations. Age structure and sex ratio were included in our analysis but were

based on a small, nonrandom sample of the chum salmon stocks. Adequate age

structure and sex-ratio data can be obtained only by sampling many individuals

throughout the spawning season.

Escapement—Escapement trends for 1960 through 1993 were evaluated for 433

chum salmon stocks in the region. Twelve of these stocks showed a significantly

increasing trend in escapement, and 41 were declining significantly. A cluster of five

increasing stocks was found in Cholmondeley Sound. The remainder were scattered

throughout the region. Clusters of declining stocks were located on Prince of Wales

Island, in Petrof Bay on Kuiu Island, and in Seymour Canal on Admiralty Island (see

table 40). Seven declining stocks spawn in Chichagof Island streams.

Timing

Demography 
226

Some stocks in the region showed considerable declines in abundance, but available

data were not appropriate or sufficient for regression analysis. For example, Eagle

Creek, the outlet of Luck Lake on Prince of Wales Island, was the site of a USBF weir

from 1928 to 1931. During the 4 years of weir operation, the mean chum salmon

count was 17,853 fish. This stream has not been surveyed regularly since largescale timber harvest occurred in the drainage in 1969, but the mean count of chum

salmon from four surveys conducted in 1967-68 and 1981-82 was 99 fish. These

recent surveys were conducted at times corresponding to historical peaks in the run.

We reviewed USFWS escapement surveys conducted from 1925 to 1960, in an

attempt to identify additional stocks that show conspicuous changes in abundance

(table 41). The survey methods and reporting during these early surveys cannot be

rigorously compared to later surveys; therefore, these stocks were not included in our

list of stocks showing a significant decline. Nonetheless, these stocks have shown

sufficient changes in abundance that we suspect the differences are unlikely to be

caused entirely by differences in sampling methods. Two examples are Grace Creek

where mean escapement count was 3,413 fish before 1957 and 1,255 after 1964,

and Nutkwa Creek with mean escapement of 11,145 before 1955 and 318 after 1961

(table 41). Data were not available for either stream after 1985.

Sheep Creek near Juneau had a small native population of chum salmon before

hatchery development (Huizer and others 1970a). The fate of this wild stock in the

presence of large hatchery returns is unknown, but it is possible that the wild stock

has been extirpated (see footnote 3). Similarly, the effects of hatchery operations on

nearby native populations of chum salmon in Kowee, Salmon, and Peterson Creeks

near Juneau are unknown. The brood stock used to produce the fry released into

creeks in the Juneau area was an amalgam derived from at least four populations in

the region, including Kadashan, Sawmill, Montana, and Salmon Creeks.

Figure 49—Frequency distribution, outlier plot, and normal quantile plot for run timing

index calculated from timing of escapement surveys, N = 428. The Chilkat River stock

has exceptionally late run timing.
227

Table 40—Chum salmon stocks with significantly declining escapement trends

Stream Location

Data

quality

Number Name VCUa General Land useb rating Possible factors

101-11-101 Hidden Inlet 850K Misty Fiords National Wilderness Good Unknown (harvest)

Monument

101-71-026 Walker Cove 799K Misty Fiords National Wilderness Fair Unknown (harvest)

River Head Monument

101-90-039 Margeruite Creek 738K Revillagigedo Island LUD IV Fair Habitat degradation; 

fish pass

102-60-072 Twelvemile Creek 621K Prince of Wales LUD IV Fair Habitat degradation

Uskabd

103-62-013 Shinaku Creek 594K Prince of Wales LUD IV Fair Unknown (hatchery)

Island

103-90-027 Gutchie Creek 571K Prince of Wales LUD IV Fair Habitat degradation

Island

103-90-030 Staney Creek 588K Prince of Wales LUD IV Fair Habitat degradation

Island

103-90-042 Shaheen Creek 589K Prince of Wales LUD IV Fair Habitat degradation

Island

105-10-032 Kell Bay Creek 411S Kuiu Island LUD III Good Unknown

105-42-010 Wolf Creek North El 536K Prince of Wales LUD IV Fair Habitat degradation

Capitan Island

106-44-031 Crystal Creek 451S Mitkof Island LUD III Good Hatchery?

107-10-020 Vixen Inlet Creek 720K Cleveland Peninsula LUD IV Fair Unknown

107-10-070 Kudays Creek South 473S Etolin Island Wilderness Fair Unknown

Etolin

107-10-072 South Etolin 473S Etolin Island Wilderness Good Unknown

Island East

107-40-047 Tom Lake Creek 510S Bradfield Canal LUD IV Good Unknown

109-30-001 Woewodski Harbor 180C Admiralty Island Wilderness Fair Unknown

109-62-020 Petrof Bay Southeast 407S Kuiu Island Wilderness Good Unknown

Head

109-62-024 Petrof Bay West Head 407S Kuiu Island Wilderness Good Unknown

109-62-028 WIlliam Creek 407S Kuiu Island Wilderness Good Unknown

Thetis East

111-12-005 Pleasant Bay Creek 168C Admiralty Island Wilderness Good Unknown

(Seymour Canal)

111-13-010 Mole River 156C Admiralty Island Wilderness Good Unknown

(Seymour Canal)

111-15-024 Windfall Harbor 151C Admiralty Island Wilderness Good Unknown

West Side (Seymour Canal)

111-15-030 Pack Creek 152C Admiralty Island Wilderness Good Unknown

(Seymour Canal)

111-16-035 Swan Cove 152C Admiralty Island Wilderness Good Unknown

South Creek (Seymour Canal)

111-16-040 Swan Cove Creek 152C Admiralty Island Wilderness Good Unknown

(Seymour Canal)

111-17-010 King Salmon River 143C Admiralty Island Wilderness Good Unknown

(Seymour Canal)

111-17-028 Portage Creek 135C Admiralty Island Wilderness Fair Unknown

(Seymour Canal)
228

Table 40—Chum salmon stocks with significantly declining escapement trends 

(continued)

Stream Location

Data

quality

Number Name VCUa General Land useb rating Possible factors

111-35-020 Sweetheart Creek 57C Snettisham LUD III Poor Hatchery effects

112-42-008 Indian River- 220C Chichagof Island LUD III Fair Habitat degradation

(?) 

Tenakee (Tenakee Inlet) harvest

112-43-012 Crab Bay Head 233C Chichagof Island LUD IV Good Habitat degradation; 

(Tenakee Inlet) harvest

112-45-032 Eaton Creek 230C Chichagof Island LUD IV Fair Habitat degradation; 

(Tenakee Inlet) harvest

112-50-030 Freshwater Creek 215C Chichagof Island LUD IV Good Habitat degradation; 

(Tenakee Inlet) harvest

113-53-003 Saook Bay 294C Baranof Island (NE) LUD IV Fair Habitat degradation; 

West Head harvest

113-57-005 Patterson Bay 283C Chichagof Island (S) LUD II Fair Unknown

West Head

113-58-003 Granite Creek 284C Chichagof Island (S) Wilderness Fair Unknown

North Arm

113-62-005 Krestof Sound 303C Kruzof Island LUD III Poor Unknown

Sukoi South 2

114-25-035 West Swanson 118C Pt. Couverden LUD III Good Habitat degradation

Creek

114-27-030 Spasski Creek 207C Chichagof Island Native Land Good Habitat degradation

(NE)

114-80-020 Excursion River NA Glacier Bay National National Park Good Harvest

Park

115-10-065 Beardslee River 107C Lynn Canal LUD III Fair Unknown

115-20-052 Sawmill Creek 17C Lynn Canal LUD II Good Unknown 

Berners Bay (Berners Bay) (egg take?)

a VCU = USDA, Forest Service value comparison unit; approximately equivalent to a watershed. K = Ketchikan Area; S = Stikine

Area; and C = Chatham Area.

b LUD = Land use designation:

LUD II = roadless areas

LUD III = multiple use

LUD IV = intensive resource use (especially logging)

The Chilkat River run of chum salmon is the largest chum salmon population in the

region, with a mean survey estimate of over 54,000 fish (fig. 50). Returns of this population have been depressed in recent years (see footnote 2). The next largest run,

based on escapement surveys, spawns in the Harding River and has a mean count

of nearly 16,000 fish. Disappearance Creek is the largest chum salmon population

monitored at a weir with a mean escapement count of 26,336. This is a minimum

estimate of the true mean because, in later years, the weir on Disappearance Creek

was removed once the management escapement goal of 30,000 fish was reached.
229

Table 41—Comparison of historical and current survey counts for selected chum salmon

stocks

Stream Historical surveysa Current surveys

VCU

Number Name Year Count Year Count numberb Land use Comments

101-71-050 Grace Creek 1947 3,000 1964 4,000 776K Wilderness Many surveys per year for

1949 5,300 1972 100 historical counts improve

1950 9,000 1983 36 data quality. “Grace Creek

1951 1,800 1985 886 is a very productive salmon

1952 950 stream for its size. During

1953 1,080 recent years of low relative

1954 2,500 abundance, its production

1955 1,500 has been better than other

1956 6,000 streams in Behm Canal.”

1957 3,000 (Martin 1959).

Mean 3,413 1,255.5

101-80-003 Cow Creek 1949 6,000 12 counts 781K Wilderness Located at the apex of Behm

1950 1,900 1964-85 Canal. Site of Fisheries

1951 1,800 Research Institute studies

1952 805 begun in 1948.

1953 420

Mean 2,185 140

102-30-089 Miller Lake 1940 3,000 1985 600 682K LUD IV

Creek 1942 4,000 Native

1947 700 corporation

1948 4,000

1953 2,000

1956 4,500

1957 9,000

Mean 3,885.7 600

102-60-080 Indian Creek 1948 120 No recent 622K State Extensive timber harvest

1949 106 counts LUD IV 1959-65. Small run may

1950 10 have been extirpated.

1951 485

1952 42

1953 20

1956 60

1957 22

1958 0

1959 0

1960 0

Mean 78.6

103-21-008 Nutkwa 1929 8,500 1961 86 K27a Native 

Creek 1931 18,763 1962 24 corporation

1944 6,500 1966 1,000 LUD IV

1945 5,000 1972 700

1946 20,000 1973 400

1948 25,000 1984 6

1949 400 1985 16

1955 5,000

Mean 11,145.4 318.9
230

Table 41—Comparison of historical and current survey counts for selected chum salmon

stocks (continued)

Stream Historical surveysa Current surveys

VCU

Number Name Year Count Year Count numberb Land use Comments

103-25-015 Deer Creek 1940 3,000 10 years 673K Native Recent surveys too early.

1943 8,000 1960-85 corporation

1944 16,000

1945 21,000

1947 22,500

1948 20,000

1949 1,450

Mean 13,135.7 304.1

105-42-005 Calder Creek 1930 27,516 28 years 531K LUD IV Both weir and survey counts

1931 17,125 1961-93 during historic period.

1951 20,400 Moderate timber harvest

1952 2,270 during 1970s.

1953 3,100

1955 650

1956 10,000

1957 20,000

1958 17,500

Mean 13,173.4 1,007.6

106-30-080 108 Whale 1929 5,728 1972 0 538K LUD IV Also called Big Creek, this

Pass 1930 7,542 1981 5 stream flows underground

1931 68,617 1984 1 for about 100 m.

1961 8,215 1993 100 Extensive timber harvest

1962 1,357 1966-89. Recent surveys

1963 723 too early.

1964 981

Mean 13,309 26.5

106-10-030 Eagle Creek 1928 1,982 1967 300 581K LUD IV Historic weir counts

Luck Lake 1929 5,066 1968 1 of chums incomplete.

1930 23,224 1981 24 Extensive timber harvest

1931 50,772 1982 72 beginning in 1969.

Mean 20,261 99.3

109-42-030 Kadake 13 years 15 years

Creek 1940-59 1962-93 421S LUD IV Extensive timber harvest

beginning in 1965.

Mean 8,390 372.1

a USBF or USFWS weir present. 

b VCU = USDA, Forest Service value comparison unit; approximately equivalent to a watershed. K = Ketchikan Area; S = Stikine Area; and

C = Chatham Area.

Sources for historical data: Martin 1959, Orrell and Klinkhart 1963, Orrell and others 1963, Rosier and others 1965.
231

Figure 50—Frequency distribution, outlier plot, and normal quantile plot for mean

chum salmon escapement magnitude based on escapement survey counts, N =

428. The Chilkat River stock has exceptionally large runs for the region. 

Age structure—We included 46 stocks in our evaluation of escapement age composition (table 42). Age structure was evaluated both in terms of MSWA and proportions of individuals found in each sex and age class (table 42, fig. 51). No geographic trend in MSWA was apparent. Island and mainland stocks did not differ significantly in MSWA (males, t = 1.13, P = 0.27 NS; females, t = -1.52, P = 0.13 NS), but for

both sexes the trend was for island stocks to be older. Male MSWA ranged from 2.65

years (East Alsek River) to 3.65 years (an unnamed creek near Snettisham), and

female MSWA ranged from 2.71 (East Alsek River) to 3.68 (Gartina Creek). The only

stock showing a distinctive age structure was the East Alsek River, which had an

unusually low MSWA (fig. 52A) because of a high proportion of age 0.2 spawners.

Throughout the region, male and female MSWA were highly correlated within stocks

(r = 0.95, P < 0.001). The Nakwasina River and Gravel Creek stocks were unusual in

showing different MSWA between male and female fish (fig. 52B). In the Nakwasina

River females were older than males (fig. 52B), and in Gravel Creek males were

older. These results were based on limited sampling from 2 and 3 years, respectively.

Significant temporal trends in MSWA were apparent only in the Herman Creek and

East Alsek stocks (table 43). In the Herman Creek stock, only females showed a 

significant increase in MSWA with time, but the male trend was nearly significant

(0.05 < P < 0.1). Both sexes showed a significant increase in the East Alsek stock,

due largely to samples from 1959 and 1962 that had an exceptionally high proportion

of age 0.2 fish. Age sampling of this stock was not resumed until 1982, and no subsequent samples have shown such a high proportion of age 0.2 fish. The exceptional

1959 sample has been attributed to an extraordinarily weak year class in 1955

(Mattson and Thorsteinson 1976). These authors offer no explanation for this weak

year class, or for the recurrence of the unusual age-composition pattern in 1962.

Results of these analyses of temporal trends must be considered preliminary, given

the few samples for each stock and the caveats regarding representative sampling of

age distributions provided above.
232

Table 42—Summary of chum salmon age distributions and mean saltwater ages (MSWA)

Stream Males Females

Sample Sample

Number Name sizea 0.2 0.3 0.4 0.5 MSWAb sizea 0.2 0.3 0.4 0.5 MSWAb

Percent Years Percent Years

101-15-085 Fish Creek 1,194 10 78 11 3.01 1,210 8 80 11 3.03

(Hyder)

101-15-090 Marx Creek 68 3 81 16 3.13 110 5 81 14 3.08

(Hyder)

101-90-029 Traitors Creek 154 5 90 6 3.01 190 2 93 4 3.02

102-40-043 Disappearance 1,413 17 69 14 <1 2.97 1,129 13 69 17 <1 3.05

Creek

108-70-002 Stikine River 478 5 83 12 3.06 255 7 84 10 3.03

(Kakwan)

108-70-00? Stikine (Great 105 2 86 11 1 3.11 59 85 14 2 3.17

Glacier)

109-43-006 Port Camden 68 43 53 4 3.62 105 40 59 1 3.61

West Head

109-43-008 Port Camden 105 75 24 1 3.26 42 67 33 3.33

109-45-01? Security Bay 31 16 84 2.84 55 9 89 2 2.93

110-14-007 Farragut River 39 3 77 21 3.18 9 89 11 3.11

111-32-032 Taku River 2,372 <1 78 21 <1 3.21 1,872 <1 78 21 <1 3.21

111-33-010 Prospect Creek 25 96 4 3.04 23 4 83 13 3.09

Speel

111-33-020 Crater Creek 128 1 56 42 1 3.43 96 2 57 40 1 3.40

111-33-025 Gravel Creek 114 6 60 34 3.28 90 4 77 19 3.14

111-34-010 (not named) 40 35 65 3.65 58 36 64 3.64

111-40-065 Middle Point 176 1 97 2 3.01 196 2 97 2 3.00

Creek

111-41-005 Admiralty Creek 95 3 92 5 3.02 171 3 92 5 3.02

111-50-052 Montana Creek 974 3 43 52 2 3.53 1,086 2 44 52 1 3.53

111-50-069 Fish Creek 692 <1 44 55 1 3.57 632 <1 49 48 2 3.52

(Douglas

Island)

111-90-005 Limestone Inlet 141 1 74 24 3.23 160 1 78 21 3.19

112-21-005 Clear River-Kelp 261 3 73 24 3.21 253 2 75 24 3.22

Bay

112-42-025 Kadashan Creek 914 6 57 36 1 3.32 969 2 54 44 1 3.43

112-42-025 Kadashan West 246 2 33 65 1 3.64 233 1 36 62 <1 3.61

112-48-023 West Bay Head 208 <1 88 11 3.11 271 86 14 3.14

Creek

112-80-028 Chaik Bay Creek 529 3 88 9 3.06 511 3 87 10 3.06

113-41-032 Salmon Lake 172 6 54 35 5 3.38 153 6 48 45 1 3.41

113-41-040 Sandy Cove 216 <1 93 6 3.06 350 <1 91 8 3.08

113-43-002 Nakwasina River 348 1 78 16 4 3.24 366 1 54 28 17 3.61

113-44-005 Katlian Bay 391 4 85 11 3.07 365 2 82 15 3.13

South Fork

113-72-005 Sister Lake 172 5 94 1 2.96 198 4 96 1 2.97

113-81-011 Black River 79 9 80 11 3.03 65 9 68 23 3.14

114-27-030 Spasski Creek 849 <1 51 47 2 3.50 902 <1 43 55 1 3.57

114-31-009 Gartina Creek 769 1 44 53 2 3.56 982 1 33 65 1 3.68
233

Table 42—Summary of chum salmon age distributions and mean saltwater ages (MSWA)

(continued)

Stream Males Females

Sample Sample

Number Name sizea 0.2 0.3 0.4 0.5 MSWAb sizea 0.2 0.3 0.4 0.5 MSWAb

Percent Years Percent Years

114-31-013 Game Creek 424 42 55 3 3.60 413 <1 39 58 3 3.63

114-33-023 Neka River 451 1 87 12 <1 3.12 455 <1 86 13 <1 3.13

114-34-010 Humpback 281 1 67 32 1 3.33 445 1 65 33 1 3.34

Creek

114-80-020 Excursion Inlet 1,185 3 78 17 2 3.19 1,124 2 70 25 3 3.27

115-20-020 Lace River 99 3 89 8 3.05 115 1 82 17 3.17

(Berners Bay)

115-20-052 Sawmill Creek 226 1 81 15 2 3.19 174 1 76 21 2 3.24

(Berners Bay)

115-32-025 Chilkat River 1,382 8 79 13 <1 3.05 1,061 5 82 13 3.09

115-32-046 Klehini River 1,922 5 79 17 <1 3.12 1,937 2 76 22 <1 3.20

115-32-048 Herman Creek 1,144 4 73 22 1 3.19 1,327 2 74 24 <1 3.23

115-32-048S Spawning 685 8 77 14 <1 3.07 416 6 74 20 3.13

Channel

115-32-057 31 Mile Creek 374 1 53 44 2 3.46 324 1 44 52 2 3.56

115-32-059 25 Mile Creek 94 2 76 22 3.20 110 2 66 30 2 3.32

182-20-010 East Alsek River 1,317 44 48 9 2.65 1,465 37 54 9 2.71

Total stocks 46 46

Total mean 503.3 3.21 489.8 3.24

Total SE 80.4 0.03 74.9 0.03

Total median 3 77.5 16.5 2 74.5 21

a Cumulative sample size for all years.

b MSWA may not equal value expected based on percentages because MSWA is calculated from numbers of individuals in each age

class, not percentages, and because of rounding.

The historical samples from the East Alsek decreased the grand MSWA of this stock

enough that it appeared to be distinct from other populations in the region (fig. 51A).

No other chum salmon stocks were unusual in either MSWA or the proportions of

individuals found in each age class. 

Sex ratio—While male chum salmon predominate early in runs and females late, 

the overall ratio of males to females for the entire spawning season is believed to 

balance near 1:1 (Bakkala 1970). To minimize the effects of sample timing on

results, only cumulative sex ratios for all sampling years were evaluated (table 44).

The cumulative sex ratios of chum salmon populations in southeast Alaska ranged

from 1:1.8 to 1:0.23 (males:females) (fig. 53). Like most sex-ratio values that deviated appreciably from 1:1, the distinctive values from the Port Camden West and

Farragut River stocks resulted from relatively small samples or samples from single

years, or both, and may not represent the true sex ratio of these populations. The

sex ratios of the majority age classes in escapements were similar to those of entire

populations, largely because the number of age classes found in chum salmon populations was low (table 44).
234

Figure 51—Frequency distributions, outlier plots, and normal quantile

plots for (A) male mean saltwater age (MSWA), and (B) sexual differences in MSWA. For both plots, N = 46. (A) The East Alsek River stock

has a distinctly low male MSWA. (B) Females in the Nakwasina River

stock are markedly older than males, but sampling is limited to one year.

Gravel Creek females are distinctly younger than males, but again 

sampling is limited to 204 individuals in three years.

Given the large number of chum salmon stocks found in the region, it is not surprising that many are in impaired and suspected water bodies (table 45). Eight stocks

inhabit water bodies considered impaired by the Alaska Department of Environmental

Conservation (1992). Only one of these populations is surveyed regularly (Rodman

Creek), and this population shows no significant trend in abundance. Eighteen chum

salmon populations are found in suspected water bodies. One of these populations,

Staney Creek, shows a significant decline in number of fish based on escapement

survey counts. Eleven of the populations in suspected water bodies had fewer than

20 survey years from 1960 to 1993, indicating that they are not surveyed regularly;

five populations were surveyed fewer than seven times and could not be analyzed for

trends in abundance.

Three chum populations analyzed by Kondzela and others (1989, 1994) show unusual genetic characteristics. The Port Real Marina stock from Prince of Wales Island

shows greater genetic affinity to Queen Charlotte Island stocks than do other Prince

of Wales Island stocks. Lover's Cove Creek chum salmon from south Baranof Island

Water Quality

Genetic Surveys
235

Figure 52—Age composition of 46 chum salmon stocks in the region: (A) male age distributions, and (B)

female age distributions. Percentages do not sum to 100 in many cases because rare age classes (0.5,

0.6) are not included. Note the high proportion of age 0.2 individuals in the East Alsek River stock.
236

Table 43—Regression analysis for trends across years in chum salmon mean saltwater ages

(MSWA)

Stream Males Females

No. of

years R- Signi- R- SigniNumber Name sampled Years squared Slope P-value ficance squared Slope P-value ficance

101-15-085 Fish Creek- 6 1972-77 0.18 -0.06 0.4<P<0.5 NS 0.18 -0.06 0.4<P<0.5 NS

Hyder

102-40-043 Disappearance 6 1973-84 0.15 0.04 0.4<P<0.5 NS 0.16 0.04 0.4<P<0.5 NS

Creek

112-42-025E Kadashan 6 1976-85 0.00 -0.00 P>0.9 NS 0.02 -0.01 P>0.9 NS

Creek

114-80-020 Excursion Inlet 6 1975-84 0.09 0.03 0.5<P<0.9 NS 0.05 0.02 0.5<P<0.9 NS

115-32-025 Chilkat River 8 1972-84 0.01 0.00 0.5<P<0.9 NS 0.00 0.00 0.5<P<0.9 NS

115-32-046 Klehini River 8 1972-88 0.20 0.01 0.2<P<0.4 NS 0.42 0.02 0.05<P<0.1 NS

115-32-048 Herman Creek 8 1982-90 0.48 0.03 0.05<P<0.1 NS 0.71 0.04 0.01<P<0.001 **

182-20-010 East Alsek 8 1959-87 0.94 0.04 P<0.001 *** 0.94 0.04 P<0.001 ***

River

NS = not statistically significant; ** = 0.01 > P > 0.001; and *** = P < 0.001.

are distinct from all other central-southeast Alaska stocks, but no other Baranof Island

stocks were sampled. The chum salmon population in Herman Creek (Chilkat River

drainage) is divergent from other stocks in the northern area, showing genetic similarity to stocks in central British Columbia. The Herman Creek stock also is the only

population with significant interannual heterogeneity, indicating the possibility of 

subpopulation genetic structure in this stock.

Several chum salmon stocks may be distinctive or occupy unusual habitats but have

no quantitative data. J. Helle (see footnote 3) has suggested that the chum salmon

stocks in Disappearance and Lagoon Creeks should be considered unique in productivity per unit area. Disappearance Creek is a stream in karst topography that originates in two limestone caves. The Tombstone River and Hidden Inlet stocks, like the

Fish Creek (Hyder) stock, are summer populations with highly protracted escapement

timing that extends from June to October (Pacific Salmon Commission 1991). The

Tombstone River stock also may have fish with an exceptionally large body size (see

footnote 3). Kook Lake Creek passes underground and fish swim through caves in

karst terrain to reach spawning areas, with some spawning occurring in the cave

reaches.4

Biological information on chum salmon stocks is generally inadequate to assess patterns of variation and to identify distinctive populations throughout the region. Adult

length, run-timing index, and demographic characteristics of escapements were the

only biological variables that could be analyzed for 46 populations out of over 3,000

in the region, and data for many of these populations were limited. Virtually no information was available about migratory behavior, juvenile life-stage characteristics, and

stock-recruitment relations, as well as other factors useful for fisheries management

Anecdotal Reports

Discussion

Evaluation of Results

4 Personal communication. V. Starostka, fishery and wildlife staff

assistant, U.S. Department of Agriculture, Forest Service, Tongass

National Forest, Chatham Area, 204 Siginaka Way, Sitka, AK

99835.
237

Table 44—Sex ratios of chum salmon stocks

Entire sample Age class 0.3 or 0.4b

Stream Sample size Sample size

Proportion Sex ratio Proportion Sex ratio

Number Name Males Females male male:femalea Males Females male male:femalea

101-15-085 Fish Creek-Hyder 1,194 1,210 0.50 1:1.01 936 972 0.49 1:1.04

101-15-090 Marx Creek-Hyder 68 110 0.38 1:1.62 55 89 0.38 1:1.62

101-90-029 Traitors Creek 154 190 0.45 1:1.23 138 177 0.44 1:1.28

102-40-043 Disappearance 1,413 1,129 0.56 1:0.80 968 779 0.55 1:0.80

Creek

108-70-002 Stikine River- 478 255 0.65 1:0.53 397 213 0.65 1:0.54

Kakwan

108-70-00? Stikine-Great 105 59 0.64 1:0.56 90 50 0.64 1:0.56

Glacier

109-43-006 Port Camden South 68 105 0.39 1:1.54 29 42 0.41 1:1.45

Head

109-43-008 Port Camden West 105 42 0.71 1:0.40 79 28 0.74 1:0.35

Head

109-45-01? Security Bay 31 55 0.36 1:1.77 26 49 0.35 1:1.88

110-14-007 Farragut River 39 9 0.81 1:0.23 30 8 0.79 1:0.27

111-32-032 Taku River 2,372 1,872 0.56 1:0.79 1,855 1,469 0.56 1:0.79

111-33-010 Prospect Creek 25 23 0.52 1:0.92 24 19 0.56 1:0.79

Speel

111-33-020 Crater Creek 128 96 0.57 1:0.75 72 55 0.57 1:0.76

111-33-025 Gravel Creek 114 90 0.56 1:0.79 68 69 0.50 1:1.01

111-34-010 (not named) 40 58 0.41 1:1.45 14 21 0.40 1:1.50

111-40-065 Middle Point Creek 176 196 0.47 1:1.11 171 190 0.47 1:1.11

111-41-005 Admiralty Creek 95 171 0.36 1:1.80 87 158 0.36 1:1.82

111-50-052 Montana Creek 974 1,086 0.47 1:1.11 422 481 0.47 1:1.14

111-50-069 Fish Creek (Douglas 692 632 0.52 1:0.91 303 312 0.49 1:1.03

Island)

111-90-005 Limestone Inlet 141 160 0.47 1:1.13 105 125 0.46 1:1.19

112-21-005 Clear River-Kelp Bay 261 253 0.51 1:0.97 190 189 0.50 1:0.99

112-42-025 Kadashan Creek 914 969 0.49 1:1.04 521 519 0.50 1:0.99

112-42-025W Kadashan Westb 246 233 0.51 1:0.95 159 144 0.52 1:0.91

112-48-023 West Bay Head 208 271 0.43 1:1.30 184 234 0.44 1:1.27

Creek

112-80-028 Chaik Bay Creek 529 511 0.51 1:0.97 468 446 0.51 1:0.95

113-41-032 Salmon Lake 172 153 0.53 1:0.89 93 74 0.56 1:0.80

113-41-040 Sandy Cove 216 350 0.38 1:1.62 201 320 0.39 1:1.59

113-43-002 Nakwasina River 348 366 0.49 1:1.05 273 197 0.58 1:0.72

113-44-005 Katlian Bay South 391 365 0.52 1:0.93 332 300 0.53 1:0.90

Fork

113-72-005 Sister Lake 171 198 0.46 1:1.16 161 190 0.46 1:1.18

113-81-011 Black River 79 65 0.55 1:0.82 63 44 0.59 1:0.70

114-27-030 Spasski Creekb 849 902 0.48 1:1.06 402 499 0.45 1:1.24

114-31-009 Gartina Creekb 769 982 0.44 1:1.28 409 642 0.39 1:1.57

114-31-013 Game Creekb 424 413 0.51 1:0.97 234 239 0.49 1:1.02

114-33-023 Neka River 451 455 0.50 1:1.01 393 392 0.50 1:1.00

114-34-010 Humpback Creek 281 445 0.39 1:1.58 187 290 0.39 1:1.55

114-80-020 Excursion Inlet 1,185 1,124 0.51 1:0.95 928 791 0.54 1:0.85
238

Table 44—Sex ratios of chum salmon stocks

Entire sample Age class 0.3 or 0.4b

Stream Sample size Sample size

Proportion Sex ratio Proportion Sex ratio

Number Name Males Females male male:femalea Males Females male male:femalea

115-20-020 Lace River (Berners 99 115 0.46 1:1.16 88 94 0.48 1:1.07

Bay)

115-20-052 Sawmill Creek 226 174 0.57 1:0.77 184 132 0.58 1:0.72

(Berners Bay)

115-32-025 Chilkat River 1,382 1,061 0.57 1:0.77 1,092 868 0.56 1:0.79

115-32-046 Klehini River 1,922 1,937 0.50 1:1.01 1,509 1,472 0.51 1:0.98

115-32-048 Herman Creek 1,144 1,327 0.46 1:1.16 840 979 0.46 1:1.17

115-32-048S Spawning Channel 685 416 0.62 1:0.61 529 308 0.63 1:0.58

115-32-057 31 Mile Creek 374 324 0.54 1:0.87 200 144 0.58 1:0.72

115-32-059 25 Mile Creek 94 110 0.46 1:1.17 71 73 0.49 1:1.03

182-20-010 East Alsek River 1,317 1,465 0.47 1:1.11 626 792 0.44 1:1.27

N 46 46

Minimum 0.36 0.35

Maximum 0.81 0.79

Median 0.50 0.50

a Male component of ratio standardized to 1 for comparative purposes.

b Data for the age class that predominates in escapements are presented. Stocks in which the 0.4 age class predominates are noted.

Figure 53—Frequency distribution, outlier plot, and normal quantile plot for sex ratio

(expressed as the proportion of males) of chum salmon escapements. Mean sex

ratios for all age classes for all years of sampling are presented. Outliers from the

distribution are based on small samples from single years and may not be representative of the true escapement sex ratios of these populations. Data are presented in

table 44.
239

Table 45—Chum salmon stocks in impaired or suspected water bodies

Stream Location

Pollutant

source

Number Name VCUa General typesb Comments

Impaired water bodies

101-45-038 Salt Chuck-George 747K Carroll Inlet TH, RC 3 years of surveys: 860 fish in 1972.

Inlet

101-47-015 Ward Cove 749K Ketchikan IN, DO, 6 years of escapement surveys, 1981-88.

Debris Maximum count, 341 fish in 1984, 

minimum count, 2 fish in 1988.

109-52-007 Rowan Bay 402S Kuiu Island TH Moderate sized run, mean escapement of 

1,064 fish. No population trend with 24 

survey years, 1962-93.

110-33-009 Hobart Bay 75C Near Juneau TH, IN, Only 1 survey; 1,950 fish in 1991.

SM, RC

111-40-010 Lemon Creek 32C Juneau UR, PP, MI 6 survey years from 1968-89; highly

LF, SM, GM variable.

111-40-015 Salmon Creek 32C Juneau UR, DDE, Hatchery operation; status of wild stock

PCB unknown.

111-40-089 Lawson Creek 32C Douglas UR, RD, 5 survey years; considerable increase

CH, SM in 1990 and 1991.

113-41-028 Bear Creek 318C Sitka IN, DO, 5 survey years; highly variable.

Silver Bay Debris

Suspected water bodies

101-45-024 White River 748K Ketchikan TH Moderate sized stock, mean escapement 

1,026 fish. Nonsignificant declining trend, 

12 survey years.

102-70-058 Thorne Bay 588K Thorne Bay IN, UR, Four survey years; 1,500 fish in 1961,

SE, SM less than 100 fish from 1982-86.

103-60-059 Point St. Nicholas NA Craig TH, UR Moderate sized stock; mean escapement 

Creek 1,000 fish. Nonsignificant decline, 

16 survey years, 1960-92.

103-90-030 Staney Creek 588K Prince of TH Highly significant decline.

Wales

111-40-007 Switzer Creek 32C Juneau UR, DDT Small stock; mean survey count of 84 fish.

No population trend, 18 survey years.

111-50-037 Wadleigh Creek 27C Juneau UR, SE Small stock; mean survey count of 44 fish.

No population trend with 9 survey years.

111-50-042 Auke Creek 27C Juneau HA, UR, SE Small population with hatchery effects.

PP, LD, RE

111-50-052 Montana Creek 27C Juneau UR Moderate sized stock; mean survey count

664 fish. Nonsignificant increasing trend, 

20 survey years.

112-13-006 False Bay 210C NE Chichagof TH Small run; no population trend,

Island 14 years surveyed.

112-42-016 Corner Bay 236C Tenakee Inlet TH Small stock; nonsignificant decline with 

26 survey years (1960-92); fish pass

present.
240

Table 45—Chum salmon stocks in impaired or suspected water bodies

Stream Location

Pollutant

source

Number Name VCUa General typesb Comments

112-65-015 Hawk Inlet Head 128C Hawk Inlet Metals Moderate sized stock; mean survey count

605 fish. No population trend with 

12 survey years.

112-65-025 Greens Creek 144C Admiralty PP Moderate sized stock; mean escapement

Island 2,188 fish. No population trend with 31 

survey years (1960-93).

113-41-012 Sitka Harbor 311C Sitka UR, HA, 6 survey years; highly variable.

(Indian River) PP, STP

113-54-007 Rodman Creek 292C North of Sitka TH Moderate sized stock; mean survey count 

2,293 fish. No population trend, 

23 survey years.

113-72-002 Klag Bay 271C Klag Bay Metals, One survey in 1973; 4,000 fish.

MI, TA

114-32-036 Eight Fathom 202C Chichagof TH 5 survey years 1963-78; highly variable.

Bight Creek Island

115-20-007 Johnson Creek 16C Berners Bay TA One survey in 1974; 50 fish.

115-33-020 Lutak Inlet NA Haines As, PAH Mean annual weir escapement count of 

421 fish from 1976 to 1993.

a VCU = USDA, Forest Service value comparison unit; approximately equivalent to a watershed. K = Ketchikan Area; S = Stikine Area;

and C = Chatham Area.

b Pollutant source types:

As = Arsenic IN = Industrial RD = Road runoff

CH = Channelized stream LD = Land development RE = recreation

DDE = Dichlorodiphenylcholorethane LF = Landfill SE = Sewage discharge

DDT = Dichlorodiphenyltrichloroethane MI = Mining SM = Streambank or shoreline

DO = Dissolved oxygen PAH = Poly-aromatic hydrocarbons modification

GM = Gravel mining PCB = Polychlorinated biphenyls TH = Timber harvest

HA = Harbor PP = Petroleum products TA = Tailings

RC = Road construction UR = Urban runoff

Source: ADEC 1992.

and the identification of potentially distinctive stocks. The inadequacy of existing data

was exacerbated by the geographic distribution and timing of data collection for the

baseline. Most information on chum salmon populations is for northern southeast

Alaska, while the majority of stocks are in southern southeast Alaska. Most biological

data were collected from the late 1970s to the late 1980s during a period of improving ocean survival. Ocean survival rates of hatchery stocks reached unprecedented

highs during this period (from a typical expectation of 2 to 3 percent, ocean survival

has increased up to 16 percent at Medvejie Creek and 8 percent for 1980 brood at

Hidden Falls [see footnote 1]), and survival of wild stocks probably increased as well.

The short duration of the data set (< 15 years) and improved ocean survival may

overestimate long-term stock conditions. 
241

Body length—Chum salmon showed pronounced sexual size dimorphism; males

were larger than females in all age classes. The consistency of this pattern (fig. 47)

suggests that sexual selection favoring large size in males is a general characteristic

of chum salmon populations (Schroder 1981). Older fish also were larger, but the

increment between successive age classes decreased with increasing age, indicating

diminishing returns for prolonged ocean life. Differences in body size between island

and mainland stocks may be due to factors that include run timing, egg size, and the

physical characteristics of drainages (Beacham and Murray 1987).

Several potential factors have been implicated to explain decreasing body size

including oceanic density-dependence, selective fisheries effects, and changes in

physical characteristics of the ocean environment (Helle 1993, Ishida and others

1993, Kaeriyama 1989, Ricker 1980). The prevailing hypothesis offered to explain

the decline is based on the presence of density-dependent limitation of growth in the

ocean (Kaeriyama 1989). Perhaps the gelatinous planktonic forms fed on by chum

salmon (Welch and Parsons 1993) are more prone to concentration in the marine

environment by abiotic factors than the piscine prey of other salmon species. Spatial

concentration of prey can intensify intraspecific competition for food resources.

Furthermore, large-scale enhancement operations, in both Japan and the west, have

contributed enormous numbers of fish having relatively homogeneous genetic characteristics to the ocean population of chum salmon. If these enhanced stocks move

en masse to relatively circumscribed areas, determined in part by inherited migratory

routes, the opportunity for local resource depletion is also increased. Ishida and others (1993) calculate that density-dependent effects could account only for about 35

percent of variability in chum salmon body weight. Other factors undoubtedly are

involved. Selection by fisheries against large individuals is unlikely to be a pervasive

factor, because most chum salmon are harvested with seine gear, which does not

selectively remove large individuals. In British Columbia (Ricker 1980) and southeast

Alaska (Clark and others 1984), age 0.2 fish are more common in harvests than in

escapements, thereby suggesting that fisheries are selectively removing small individuals. Ricker (1980) argues that this pattern of harvest may effectively select against

rapid growth rate and thereby contribute to declines in both age and size. Increased

sedimentation of streams selects against larger fry (Scrivener and Brownlee 1989),

and this mortality factor also could contribute to selection for reduced growth rate.

Changes in ocean temperature may be yet another factor contributing to the

observed changes (Ricker 1980). Our inability to detect trends in body size through

time for several stocks may be due to lack of recent data. Estimated body weights of

chum salmon harvested commercially in southeast Alaska from 1958 to 1985

(Marshall and Quinn 1988) do not show a declining trend, and this result also is possibly due to a lack of estimates from recent years. Body weights of several Asian

chum salmon populations are decreasing (Ishida and others 1993), but the one

Canadian population (Fraser River) included in the Ishida study did not show a

decreasing trend in characters correlated with body weight.

Variance-component analysis of chum salmon body lengths indicated a greater proportion of variability among populations and less variability within populations than

was shown by other species of Pacific salmon (see other chapters in this paper).

This result suggested an increased level of local body-size adaptation in chum

salmon. Chum salmon stocks in British Columbia showed a high level of local adaptation in morphology as well as other characteristics, such as meristic counts, egg size,
242

and development pattern (Beacham and Murray 1987). Substrate grain size and

variability of flow regime are two environmental factors that may have important

selective consequences for body size in chum salmon (Beacham and Murray 1987;

see footnote 3).

The presence of local adaptations within stocks suggests that straying between

stocks is limited. The few existing studies of marked individuals indicate that the

straying rate of wild fish is low (Salo 1991). Geographic distance among stocks is

correlated with genetic distance between stocks (Davis and Olito 1982, Kijima and

Fujio 1982, Scribner and others 1998). Some hatchery stocks of chum salmon show

considerable local straying (McNair 1985).

Helle (1984) notes the large size of chum salmon spawning in Fish Creek near

Hyder. Although this stock is among the largest in each sex and age category we

analyzed, it is not an outlier; however, our analysis was based on mideye-to-fork

lengths and not weights. Stock-specific weight data were not available for other

stocks in the region.

Timing—Run timing is a central component of local adaptation of chum salmon

stocks in other regions (Beacham and Murray 1987, Miller and Brannon 1982). In

British Columbia, timing of spawning had a marked effect on fry emergence timing

and age of maturity. Within geographic areas, early-spawning stocks have later times

of fry emergence and higher proportions of older chum salmon than late-spawning

stocks (Beacham and Murray 1987). Early spawning is associated with cold water

systems (Holtby and others 1989). Cold water temperatures retard development and

increase the development time of egg and alevins.

In southeast Alaska, Kadashan River has the earliest run timing of any system surveyed, and winter water temperatures in this system are consistently below 1°C (see

footnote 1). The Kadashan River stock also showed relatively compact run timing

despite its considerable size. This suggests a relation between water temperatures,

which affect embryo and alevin development, and run duration. We are unaware of

any discussion in the literature of a relation between compact run timing and cold

incubation temperatures. A compact early run may result from a combination of

opposing selection pressures; developmental delays imposed by cold water on eggs

and alevins would favor early spawning so fry can emigrate at an appropriate time to

take advantage of high marine productivity, but delaying adult entry into fresh water

as much as possible would provide the benefit of more time to feed in the marine 

environment resulting in larger body size and higher fecundity.

In contrast, the Fish Creek (Hyder) stock has a protracted run duration and some

spawning occurs in warm upwelling areas (see footnote 3). Availability of these

spawning habitats, which permit more rapid development, could contribute to a more

protracted run duration.

The effects of warm upwelling water in spawning areas on mean date of return migration are more apparent than effects on run duration. The timing of the Chilkat run,

which occurs in October and November, is probably influenced by warm upwelling

water (Bugliosi 1988). We suspect that the late runs in Porcupine Creek and in the

Taku River drainage also may be associated with warm upwelling water. 
243

Local timing adaptations of salmon populations can have important consequences for

wildlife species that prey on salmon (Willson and Halupka 1995). The late timing and

large magnitude of the Chilkat River chum salmon run attracts aggregations of bald

eagles exceeding 3,000 individuals, the largest aggregation of bald eagles in the

world (Hansen and others 1986). The strength of the late chum run in the Chilkat

may influence the reproductive success of bald eagles over a wide geographic area

(Hansen 1987).

Daily weir counts are available from USFWS weirs operated for various years

between 1929 and 1966 at Keete Inlet (103-21-018), Klawock River, Staney Creek

(Orrell and others 1963), Kook Lake, and Hood Bay (112-73-024) (Huizer and others

1970b). At all these locations, counts showed distinctly bimodal run timing suggesting that both summer and fall chum runs may be present. Favorite Creek (112-67-

080) in Kootznahoo Inlet is also reported to have both summer and fall runs, but no

supporting data are available (Huizer and others 1970b). Throughout the region, 

the frequency of sympatric runs of summer and fall chum in the same stream is

unknown, but maintenance of clear timing differences suggests reproductive isolation

and possible genetic differences between early and late spawners.

Demography, declining stocks—Relatively good survey data were available for 9 of

the 12 chum salmon stocks in the region that showed a significant increase in abundance, and for 21 of the 41 declining stocks (table 40). Of the 21 declining stocks

with the best data, 14 spawned in drainages with minimal human disturbance to 

habitat (wilderness areas, roadless areas, and national parks and preserves). Eight

of these spawning streams empty into Seymour Canal on Admiralty Island. The relatively large number of declining populations in this area is a source of concern, and

the causes of decline are unknown. Declines in areas where timber harvests have

occurred were not surprising in view of results from the Carnation Creek experimental

watershed, which demonstrated the sensitivity of chum salmon to increased sedimentation (Scrivener and Brownlee 1989).

Age structure—The frequency distributions of male and female MSWAs for the

region appeared to be bimodal, with a primary peak at about 3.1 years and a secondary peak near 3.5 years (fig. 52A). All stocks in the secondary peak were from northern southeast Alaska, but too few summer stocks have been sampled from southern

southeast Alaska to determine if older fish are restricted to northern areas. Older age

is generally considered a characteristic of summer chum, which are more widely

found in northern southeast Alaska.

As was the case for temporal changes in length, detection of temporal changes in

MSWA was inhibited by insufficient data. Only the Herman Creek and East Alsek

stocks showed significant changes in age (both increasing). This result paralleled the

results of other investigators, who have found trends of increasing age and decreasing lengths in a wide range of chum salmon stocks (Ishida and others 1993, Ricker

1980; see footnote 3). 

Chum salmon from the Queen Charlotte Islands form two distinct stock groups,

based on genetic analysis (Kondzela and others 1994). Allele frequencies in both

groups diverge from those of mainland British Columbia populations. This pattern of

genetic divergence is consistent with geologic evidence indicating that the Queen

Conceptual Issues
244

Charlotte Islands were ice free during the height of the Wisconsin glaciation (Warner

and others 1982). Divergence between the mainland and island populations also

suggests that postglacial colonization of mainland streams tended to occur from

mainland source populations rather than from island populations. Similarly, the allele

frequencies of chum salmon stocks from Prince of Wales Island are distinct when

compared to those from stocks inhabiting the area east of Clarence Strait, which suggests that a similar pattern of glacial refugia and subsequent colonization occurred in

southeast Alaska. This interpretation is supported by geologic and botanic evidence

indicating that portions of Prince of Wales Island were ice free during the most recent

glacial maxima.5 6

We agree with Kondzela and others (1994) that further genetic surveys of stocks in

northern southeast Alaska could improve understanding of postglacial colonization

patterns. Based on allozyme analysis of chinook salmon throughout Alaska, Gharrett

and others (1987) suggest that some similarities between Yukon River and southeast

Alaskan chinook could be due to colonization via headwater capture of the Taku and

Stikine Rivers. Because chum salmon also currently spawn near the headwaters of

the Yukon River and may have persisted in the Bering refugium during glacial periods, colonization of northern southeast Alaska by chum salmon could have followed a 

similar route.

As was found for the other salmon species reviewed in this paper, a relatively small

proportion (9.5 percent) of chum salmon stocks we evaluated had declining escapement trends. This was, however, the highest percentage for any species in the

region. Several factors may be contributing to these declines and have the potential

to cause further declines in chum salmon abundance and diversity throughout southeast Alaska. We do not consider the following list complete, but it contains those factors that are most pervasive and therefore have the potential to affect large numbers

of chum salmon populations.

1. Benign neglect may be the most insidious threat to chum populations in southeast

Alaska. Stock-specific information is limited for chum populations on the biological

characteristics critical to effective management, such as stock-recruit relations,

exploitation rates, or migratory timing and pathways. The current low level of

research and monitoring effort probably reflects the low economic interest in chum

salmon, relative to other salmon species in the region. Because few fisheries are

directed at chum salmon, management effort is correspondingly reduced. Although

few fisheries are directed at chum salmon, large numbers of them are being harvested incidentally in fisheries for sockeye, pink, and coho salmon. This high proportion

of incidental harvest increases the potential for unsustainable harvest of particular

stocks that overlap in route and timing with very productive runs of other species, and

it increases the likelihood of artificial selection through fishery effects, because management decisions are not made with regard for the migratory timing or productivity 

5 Personal communication. 1996. J. Baichtal, geologist, U.S.

Department of Agriculture, Forest Service, Tongass National

Forest, Thorne Bay Ranger District, P.O. Box 19001, Thorne Bay,

AK 99919.

6 Personal communication. 1996. A. Harris (retired), U.S.

Department of Agriculture, Forest Service, Pacific Northwest

Research Station, 2770 Sherwood Lane, Juneau, AK 99801.

Risk Factors
245

of chum salmon populations. Without monitoring, the status of populations could

decline to crisis levels before notice is taken. Even if monitoring indicated severe

declines in chum salmon populations, the great economic value of fisheries for other

species severely limit the possibility of attempting to protect weak chum salmon

stocks with time and area closures.

The threat posed by benign neglect is exacerbated by the unrepresentative nature of

existing baseline data. Most baseline information is for large chum salmon populations, the majority of which are in northern southeast Alaska, but the majority of chum

salmon populations are small and found in southern southeast Alaska streams.

Furthermore, most baseline data for chum salmon populations in the region have

been collected during a period of favorable ocean conditions. A downturn in ocean

conditions is highly probable; only the time of its onset is uncertain. If current political

and policy trends continue, it seems unlikely that large amounts of additional baseline

information on chum salmon will be collected. Reductions in weir operations and

other field monitoring programs suggest that the ADF&G is choosing to devote less of

its dwindling financial and personnel resources to data collection and more to management of existing data. In our opinion, a lack of economic incentive and insufficient

funding of management research are contributing to a tenuous management situation

for chum salmon in southeast Alaska.

2. Chum salmon are sensitive to changes in streams that result from timber harvest,

such as changes in flow dynamics, increased temperature, and increased sediment

loads (Holtby and others 1989, Murphy 1985, Scrivener and Brownlee 1989).

Several declining populations in the region are in areas of intensive timber harvest.

Proper implementation of improved land-management programs may reduce the

magnitude of this threat. The extensive scale of planned timber-harvest activities in

some areas are nonetheless likely to contribute to further declines of chum salmon

populations. 

3. Chum salmon enhancement projects tend to be large in scale. A few hatcheries in

the region can produce enormous numbers of chum salmon fry and correspondingly

large returns of mostly unmarked adults, which cannot be identified as hatchery fish

in mixed stock fisheries. For those relying on harvest statistics to assess the health

of a fish resource, the success of enhancement efforts has the potential to obscure

widespread declines in wild stocks. The confused perceptions resulting from simultaneously increasing harvests (of hatchery-produced fish) and declining wild stocks can

delay development of the consensus necessary to take action to protect relatively

unproductive stocks. This represents a particular threat to chum salmon stocks, 

given the management situation described above.

At a local level, the detrimental effects of large-scale enhancement efforts on wild

stocks have been reviewed by numerous authors (e.g., Goodman 1990). A few wild

stocks of chum salmon have probably experienced some of these detrimental effects,

and at least one (Sheep Creek) may have been extirpated. Further development of

large-scale hatchery production should be critically evaluated, and the potential use

of hatcheries to augment weak stocks should be explored (Kapuscinski and

Jacobson 1987). 
246

Figure 54—Approximate geographic location of southeast Alaska chum salmon stocks with distinctive biological characteristics.
247

4. Little information is available on the degree to which roe-stripping of chum salmon

occurs in southeast Alaska. The relatively high value of chum salmon roe relative to

whole fish may provide incentive for roe-stripping. Underreported or unreported

catches of chum salmon associated with roe-stripping could contribute to population

declines.

At the regional level, chum salmon diversity in southeast Alaska can be characterized

along the axes of run timing (summer and fall runs) and island-versus-mainland

spawning locations. Both axes may be correlated with water-temperature regime during egg incubation. At the subregional level, genetic analysis of chum salmon populations in southern southeast Alaska cluster into geographically defined groupings.

The three genetically defined groups identified to date are Prince of Wales Island

area, inside areas east of Clarence Strait and south of Sumner Strait, and centralsoutheast Alaska from Sumner Strait to Frederick Sound. These geographic clusters

may reflect historical colonization patterns and may be preserved by differences in

migratory pathways that reduce gene flow among groups. We expect that similar

genetic analyses for chum salmon populations in northern southeast Alaska will

reveal a similar geographic pattern. Based on our analyses conducted at the level of

individual populations, and on studies of genetic characteristics, the following chum

salmon stocks have distinctive characteristics (see fig. 54 for approximate geographic

locations):

• Chilkat River stock has late run timing, large population size, and is an important

resource for wildlife.

• Herman Creek stock has a genetic affinity to populations in central British Columbia

and may exhibit subpopulation genetic structure; significant declines in size and age

were detected in this stock.

• Port Real Marina stock has a genetic affinity to Queen Charlotte Island stocks, as

well as other Prince of Wales Island stocks.

• Lover's Cove Creek stock has unusual allele frequencies, but no other stocks in its

geographic area were sampled; further genetic sampling of northern southeast

Alaska stocks is required.

The following stocks showed distinctive characteristics based on limited sampling.

These results need to be confirmed.

• East Alsek River stock has a high proportion of age 0.2 spawners in some years

and low MSWA.

• Port Camden females are larger than same-age males—a sexual size-difference

that is the reverse of most other stocks in the region.

• West Bay Head Creek stock appears to have an extreme sexual size-difference in

age 0.4 fish; males are over 70 mm longer than females in mideye-to-fork length.

• Nakwasina River stock appears to have an extreme sexual difference in MSWA;

female MSWA is over 3 months greater than male’s.

• Gravel Creek stock appears to have sexual size-difference in MSWA with females

younger than males—the reverse of most stocks in the region.

• Farragut River stock appears to have sex ratio skewed in favor of males.

• Port Camden West stocks appear to have sex ratio skewed in favor of males.

Conclusions
248

Figure 55—Approximate geographic location of southeast Alaska chum salmon stocks with significantly

declining escapements and relatively high-quality escapement survey data.
249

Based on anecdotal reports and professional judgment, the following stocks may

have distinctive characteristics. Lack of adequate comparative data prevented 

evaluation of these reports.

• Fish Creek (Hyder) stock has prolonged run duration and large body size.

• Hidden Inlet stock has prolonged run duration.

• Tombstone River stock has prolonged run duration and potentially large body size.

• Disappearance Creek stock has high productivity per unit area and large population

size.

• Kook Lake stock swims through karst caves to reach spawning grounds, and some

fish spawn in cave reaches.

Eight chum salmon populations are found in impaired water bodies and 18 spawn in

or migrate through suspected water bodies, but only one of these shows a significant

decline in escapement.

A higher proportion of chum salmon stocks have declining escapement trends than

stocks of other species surveyed. Forty-one stocks (9.5 percent) show significant

declines, and 21 of these stocks have relatively good escapement data (table 40).

Declining stocks are clustered in Seymour Canal on Prince of Wales Island and the

Petrof Bay area of Kuiu Island (fig. 55). Risk factors that may be contributing to

these declines, and that have the greatest potential to cause future declines, include

minimal management research leading to inadequate understanding of chum salmon 

biology, logging practices resulting in increased sediment loads, and large-scale

enhancement activities possibly contributing to overexploitation of wild stocks.

The assistance of S. Johnson and L. Talley in accessing the ADF&G Integrated

Fisheries Database was indispensable. G. Gunstrom, M. Harris, and K. Savikko 

provided ADF&G documents that were the foundation of this report, and J. Helle 

provided documents from the Pacific Salmon Commission and the National Marine

Fisheries Service. S. Marshall provided both access to the information resources 

of the ADF&G and criticism that improved this project. Indepth discussions with B.

Bachen, J. Helle, and K. Hofmeister provided a wealth of insights about chum salmon

biology and management. B. Lorenz and V. Starostka commented on specific

aspects of a previous draft. K. Kondzela's careful review greatly improved this manuscript.

Alaska Department of Environmental Conservation. 1992. Alaska Water Quality

Assessment 1992. Juneau, AK. Water Quality Management Section. 88 p.

Bakkala, R.G. 1970. Synopsis of biological data on the chum salmon, Oncorhynchus

keta (Walbaum) 1792. FAO Species Synop. 41. Washington, DC: U.S. Department

of the Interior, Fish and Wildlife Service, Bureau of Commercial Fisheries. 89 p.

Beacham, T.D.; Murray, C.B. 1987. Adaptive variation in body size, age, morphology,

egg size, and developmental biology of chum salmon (Oncorhynchus keta) in

British Columbia. Canadian Journal of Fisheries and Aquatic Sciences. 44: 

244-261.

Acknowledgments

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When you know: Multiply by: To find:

Millimeters (mm) 0.04 Inches

Centimeters (cm) 0.39 Inches

Meters (m) 3.28 Feet

Kilometers (km) 0.62 Miles

Milligrams (mg) 0.000035 Ounces

Kilograms (kg) 2.21 Pounds

Hectares (ha) 2.47 Acres

Celcius (°C) (°C x 1.8) + 32 Fahrenheit

255

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(voice and TDD). USDA is an equal opportunity provider and

employer.

Pacific Northwest Research Station, 333 S.W. First Avenue, 

P.O. Box 3890, Portland, Oregon 97208-3890.