*U.S. Dept Commerce/NOAA/NMFS/NWFSC/Publications*

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**NOAA F/NWC-187 - Status and Future of Spring Chinook Salmon in the Columbia River Basin—Conservation and Enhancement**

**STOCK STRUCTURE AND GENE CONSERVATION INCOLUMBIA RIVER SPRING CHINOOK SALMON**

Robin S. Waples

National Marine Fisheries ServiceNorthwest Fisheries Science Center2725 Montlake Boulevard EastSeattle, Washington 98112

Three major races of chinook salmon, *Oncorhynchus tshawytscha* (spring, summer, and fall run fish), arerecognized in the Columbia River Basin. These races are fairly distinct with respect to life history features, suchas time of entry into fresh water and age and timing of outmigration, but somewhat less so if other characters areused. For example, Utter et al. (1989) found that fish from the same stream with different run times were typicallymore similar genetically than were fish of the same run time from different streams. They suggested that eachrace was probably polyphyletic, with life history divergence occurring within some streams after colonization byfish of a single run time.    

Regardless of whether this hypothesis is true, considerable geographic structure can be identified among springchinook salmon populations. Figure 1 shows a dendrogram. of genetic relationships based on electrophoretic datafor 15 polymorphic gene loci. Although it is easy to overinterpret such dendrograms, several points emerge froman examination of the figure. First, the major groupings fall out along geographic lines and generally arecompatible with those identified by Schreck et al. (1986) using meristic, morphological, and genetic data. There isa major distinction between spring chinook salmon from west of the Cascades (group A, Willamette River andgroup B, lower Columbia River) and those farther east. Second, mid- to upper Columbia River stocks (group C)cluster very tightly together, as do those from the Snake River system (group D). It is interesting to note thatKooskia Hatchery, which is in Idaho but has been stocked with Carson fish, clusters with the Columbia Riverstocks rather than the other Snake River stocks. Finally, stocks in group C do not differ substantially from thosein group D; this probably reflects the origin of the Carson-Leavenworth hatchery stock, which was started withupriver fish intercepted at Bonneville Dam.    

Further insight regarding stock structure in spring chinook salmon is gained by considering averageheterozygosity, a measure of overall genetic variability within individuals or populations. Winans (1989) reportedmuch lower levels of heterozygosity in upriver spring chinook salmon than is found in lower river spring chinookor fall chinook from throughout the basin (Table 1). The cause of this pattern is not clear, but one possibility isthat upriver spring chinook salmon stocks have experienced severe (or repeated) bottlenecks in population sizeduring which homozygosity increased through inbreeding (matings between individuals of similar genotype).Low heterozygosity does not necessarily imply reduced fitness, as little detectable genetic variation has beenfound in a number of apparently healthy species. However, data for a variety of organisms provide evidence for arelationship between population bottlenecks, reductions in genetic variability, and increased susceptibility todisease (O'Brien and Evermannn 1988). A plausible explanation for this relationship is suggested by theobservation that immune and disease response systems in vertebrates are typically controlled by extremelypolymorphic genetic systems; that is, a large number of alleles occur in a population, with few individuals sharingany one genotype. Such a population is much less susceptible to decimation by a newly evolved viral or bacterialpathogen than is a largely monomorphic population. In this regard, it is interesting to note that problems causedby bacterial kidney disease ars, most severe in upriver spring chinook salmon, which have the lowest levels ofgenetic variability of any spring or fall stocks (Table 1).    

This simple relationship by no means represents conclusive evidence for a causal relationship, but it does serve toillustrate the point that the erosion of genetic variability can have serious, and often unforeseen, consequences. Insome respects, the extinction of rare alleles may be of more importance than the loss of heterozygosity per se (seeAllendorf 1986). As shown in Figure 2, which depicts results from a series of computer simulations modelling therate of loss of genetic variability from chinook salmon populations (Waples, in press), a substantial percentage oflow frequency alleles can be permanently lost before there is an appreciable decline in heterozygosity. In chinooksalmon, as in most species, rare alleles are more common than any other class of alleles (Fig. 3), so large numbersof rare alleles are subject to rapid extinction in small populations. It is not clear what immediate adaptive valuethis large class of rare alleles has, but it is certain that they represent the bulk of the raw material upon whichnatural selection might act. Permanent loss of a substantial portion of such alleles may compromise the ability ofa population to respond to challenges presented by changing environmental conditions.    

The rate of loss of genetic variability is a function of effective population size (Ne). If sex ratio of spawners isunequal or if the variance among families in reproductive success is large, Ne is less than the census number, andperhaps a great deal less. Given that spawning escapement to many upriver stocks is already seriously low (e.g.,Williams 1989), reduced Ne is a very real concern for spring chinook salmon. Evaluating effective populationsize, however, is particularly difficult with Pacific salmon. Even if spawning is carefully monitored, smoltmortality after outmigration may be 99% or more, making it difficult to estimate the variance among families innumber of progeny returning to spawn. Furthermore, because of the complex life history features of chinooksalmon, it is not apparent what relationship the effective number of breeders each year (Nb) has to the morefamiliar concept of effective population size per generation (Ne).    

To address these questions, a computer simulation model was developed that incorporates the pattern ofoverlapping year classes and one-time reproduction typical of chinook salmon. Results (Waples, in press) indicatethat generation length in chinook salmon can be defined as the average age at reproduction and that effectivepopulation size per generation is equivalent to the generation length times the effective number of breeders peryear. Thus, for a chinook salmon population with average age at spawning of 4 years, Ne» 4Nb. This relationshipallows us to apply the large body of theory developed for population and conservation genetics directly toproblems of concern to spring chinook salmon. A method has also been developed to estimate Nb fromyear-to-year changes in allele frequency, and this approach can be used to identify hatcheries (or wildpopulations) in which Nb is lower than expected; remedial actions can be taken before serious problemsassociated with inbreeding develop.    

**References**

Allendorf, F. W. 1986. Genetic drift and the loss of alleles versus heterozygosity, Zoo Biol. 5:181-190.    

Nei, M. 1978. Estimation of average heterozygosity and genetic distance from a small number of individuals.Genetics 89:583-590.    

O'Brien, S. J., and J. F. Evermann. 1988. Interactive influence of infectious disease and genetic diversity innatural populations. Trends Ecol. Evol. 3:254-259.    

Schreck, C. B., H. W. Li, R. C. Hjort, and C. S. Sharpe. 1986. Stock identification of Columbia River chinooksalmon and steelhead trout. Final Report of Research to Bonneville Power Administration, Portland, Oregon.(Available from Oregon State University, Corvallis, OR 97331.)

Utter, F., G. Milner, G. Stahl, and D. Teel. 1989. Genetic population structure of chinook salmon in the Pacificnorthwest. Fish. Bull., U.S. 87:239-263.

Waples, R. S. In press. Conservation genetics of Pacific salmon. II. Effective population size and the rate of lossof genetic variability. J. Heredity 81(4):267-276.

Williams, J. G. 1989. Snake River spring and summer chinook salmon: can they be saved? Regul. Rivers 4:17-26.

Winans, G. 1989. Genetic variability in chinook salmon stocks from the Columbia River Basin. N. Am. J. Fish.Manage. 9:47-52.    

**QUESTIONS AND ANSWERS**

- Q:
- How can you attribute changes to reduced numbers of breeders?

- A:
- It is difficult to sort out genetic drift from rate of change of allele frequency. One needs to have a closedpopulation—if you measure different parts of a run in different years, it is even more difficult. Thus would be agreater potential to see this in hatchery stocks. Preliminary data us available for 20-30 hatchery populations overmany years. It seems that there is a much lower N. than we would hope for.

- Q:
- If heterozygosity of Snake River populations is low, what are we to do, and how are we to protect the integrity ofSnake River stocks?

- A:
- Some have suggested hybridization; this is a possibility but it is not recommended. This might result in theopposite of what is wanted. The wild fish have migrated for thousands of years, ~ one shouldn1 interfere withtheir genetic makeup. We should leave them alone while not doing anything to further reduce this component.Some species, defined through electrophoresis, are doing even worse, although this does not imply reducedfitness.

- Q:
- Might hatchery practices decrease genetic variability—for example, culling for disease?

- A:
- Yes. Hatcheries might also take only one part of the run, or use a small number of males for a relatively largenumber of females. This would mean that a few individuals would have a large contribution to the subsequentpopulation. Even females may show a disproportionate contribution; this should be discouraged. BonnevillePower Administration (BPA) has expressed interest in practical approaches for doing something about this.

- Q:
- Were the stated heterozygosity values for hatchery or wild fish? And is there more life history variability, andtherefore higher heterozygosity, in the lower river? We see some curious migration timing there.

- A:
- Both hatchery and wild fish are included in the values. I don't know about life history variability in the lowerriver. It may be true that there has been loss of this variability in the Snake River, since there seems to be such anarrow window for migration timing.

- Q:
- If life history behavior becomes less diverse, might the window be even further reduced?

- A:
- Yes; good point.

Figure 1. Dendrogram of genetic relationships among 25 populations of spring chinook salmon. Dendrogram was constructed using electrophoretic data for 15 gene loci gathered by National Marine Fisheries Service, Seattle, and Washington Department of Fisheries, Olympia; clustering strategy was unweighted pain-group method analysis using Nei's (1978) genetic distance. A number of loci known or suspected to be monomorphic were not included in the analysis, so values shown are relative rather than unbiased estimates of true genetic distance. Major geographic groupings: **A**: Willamette River; **B**: Lower Columbia River (plus Klickitat); **C**: Mid- to upper Columbia River (Washington); **D**: Snake River (plus Yakima); **E**: Mid-Columbia (Oregon). Samples from wild/naturally spawning populations are indicated by an asterisk (*); others are hatchery samples.

Figure 2. Proportion of initial genetic variability remaining in a simulated chinook salmon population after periods of time up to 100 years. Large numbers of alleles with low initial frequency (P0) can be lost before an appreciable cange in heterozygosity is detected. Nb is the effective number of breeders per year.

Figure 3. Distribution of alleles at various frequencies found in samples from 177 chinook salmon populations in the Pacific Northwest.

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Table 1. Average heterozygosity valuesa for spring and fall chinook salmon from the Columbia River Basin. Regional values are means based on the number of stocks indicated in parentheses.

aBased on data for 33 gene loci reported by Winans (1989). A number of loci known or suspected to be monomorphic were not included in the analysis, so values shown are relative rather than unbiased estimates of total heterozygosity.

bExcluding Kooskia Hatchery.

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