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1 December 2008 Genetic Inventory of Anadromous Pacific Salmonids of the Elwha River Prior to Dam Removal
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Abstract

We genetically characterized seven species of Pacific salmonids in the Elwha River and in selected neighboring rivers prior to the impending removal of two dams. Monitoring the genetics of recolonization of the watershed by remnant native, hatchery, and/or adjacent watershed populations is a critical element to further our understanding of ecosystem restoration. By pooling data from independent studies, we assessed intraspecific diversity for pink salmon (Oncorhynchus gorbuscha), chum salmon (O. keta), coho salmon (O. kisutch), sockeye salmon (O. nerka), Chinook salmon (O. tshawytscha), rainbow trout (O. mykiss) and bull trout (Salvelinus confluentus). Levels and patterns of genetic variability within and among collections were evaluated at 6–15 microsatellite (mSAT) loci per species. Each species had 3–8 loci with 20 or more alleles. In all species, an Elwha collection was statistically different from one or more nearest-neighbor population. In addition, the native in-river collections of Chinook salmon and steelhead (anadromous rainbow trout) were distinguishable from existing in-river hatchery stocks. In most species, Elwha populations contained similar levels of genetic diversity as observed in neighboring river systems. In O. mykiss, variability at an evolutionarily adaptive major histocompatibility complex (MHC) gene paralleled the mSAT variation. Given the various levels of distinctiveness of Elwha populations, we discuss the use of these data as a genetic ruler to manage and monitor the genetic aspects of recolonization of the Elwha River, and the importance of tissue archives for new genetic techniques.

Introduction

A plan for monitoring the ecological response of the Elwha River watershed to dam removal includes a genetic assessment of Pacific salmonids (McHenry and Pess 2008). We are interested in the current genetic status of the extant stocks in the river (native and hatchery) and in neighboring rivers that may be sources of recolonizing populations. The assessment of genetic variability within and among populations within the Elwha River and in neighboring populations prior to dam removal is important to our ability to evaluate and monitor the dynamics of population genetics of upriver recolonization once dams are removed. This paper outlines a preliminary characterization of intraspecific diversity in seven species of Pacific salmonids, pink salmon (Oncorhynchus gorbuscha), chum salmon (O. keta), coho salmon (O. kisutch), sockeye salmon (O. nerka), Chinook salmon (O. tshawytscha), rainbow trout (O. mykiss) and bull trout (Salvelinus confluentus). Previously unpublished data from several independent studies are summarized here. Allelic variation at microsatellite (mSAT) loci is assumed to be evolutionarily neutral and is used to describe the patterns of connectivity and levels of genetic diversity among salmonid gene pools in the Elwha watershed and along the Strait of Juan de Fuca. Databases developed in this study will be used to assess the relative contributions of the populations sampled here to up-river colonization after dam removal.

Mainstem hydroelectric dams were constructed on the Elwha River in 1913 and 1925 without fish passage facilities. These actions severely impacted native salmon populations and confined anadromous salmonids to the lower 8 km of the river. An overview of the current-day status of Elwha salmonids is presented in Table 1. Each of these species has been reviewed by NOAA Fisheries or USFWS in the last ten years with regard to status under the U.S. Endangered Species Act (ESA) (see Waples et al. 2001). These comprehensive reviews compiled genetic, life history, and ecological information in order to group geographic populations into conservation units termed evolutionarily significant units (ESUs) for Pacific salmon or distinct population segments (DPSs) for bull trout. In general, Elwha River populations straddle or are close to an ESU boundary delimiting a Puget Sound ESU and a Washington Coast/Olympic Peninsula ESU, e.g., for coho and Chinook salmon, and steelhead (anadromous rainbow trout)(Weitkamp et al. 1995, Busby et al. 1996, Myers et al. 1998). Seriously reduced populations in the Elwha River include Chinook salmon, steelhead, and bull trout (Table 1). Other Elwha populations such as pink and chum salmon are critically depressed, but nested within stronger regional populations. Bull trout in the Elwha are included as part of the Puget Sound/Olympic Peninsula DPS (USFWS 1999).

TABLE 1.

Current and historical status of Pacific Salmonids and bull trout in the Elwha River (unpublished data, M. McHenry).

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We provide descriptions of preliminary genetic data sets based on 6–15 mSAT loci. Our goal is to genetically characterize populations that currently exist in the river and to describe their genetic similarity with their nearest geographic neighbors and, when relevant, with hatchery stocks used in the river or in out-planting programs. Within this framework, we were also interested in estimating relative levels of genetic diversity within population samples. We expect that additional evaluation and analyses will ensue prior to dam removal as more detailed data sets—genetic and phenetic—are developed.

Methods and Materials

Tissues were collected in a variety of independent tribal, state, and federal programs associated with population assessments, hatchery supplementation, and/or genetic surveys. Adult and juvenile collections were made during spawning surveys, smolt trapping, seining, via electrofishing, and/or at hatcheries. Laboratory analyses were conducted at six separate facilities. Microsatellite analyses followed standard protocols as previously described, e.g., for coho salmon (Van Doornik et al. 2007), chum salmon (Small et al. 2006), rainbow trout (Small et al. 2007), steelhead (Winans et al. 2004), and bull trout (Neraas and Spruell 2001, DeHaan and Ardren 2005). Procedures used for assaying rainbow trout for the class II B1 locus at the major histocompatability complex (MHC) are found in Miller et al. (2001). Genetic diversity in a collection was estimated using two measures: allelic richness, which standardizes the number of alleles per locus to a common sample size (see Goudet 2001), and Nei's unbiased gene diversity (Nei 1987). To evaluate overall among-sample variability at a locus, we calculated observed and expected heterozygosity and Hardy Weinberg equilibrium (HWE) assuming all fish originated from one collection. Loci that deviate from HWE over all populations are more powerful among-collection discriminators. These basic statistical analyses were performed using GENEPOP (Raymond and Rousset 1995). Relationships among collections were estimated as neighbor-joining trees with PHYLIP (Felsenstein 1993) based on Cavalli-Sforza and Edwards chord distances (Cavalli-Sforza and Edwards 1967). Genetically similar collections are grouped together in the tree where branch lengths reflect genetic differences. The level of among group differences was estimated with Wright's FST statistic (Wright 1978) and evaluated for significance with 1000 permutations using FSTAT (Goudet 2001). A factorial correspondence analysis was conducted on allele frequency data to provide an independent assessment of among-collection variability for Chinook salmon using GENETIX (Belkhir et al. 2001).

Results

Pink Salmon

Fall- and summer-run collections of pink salmon from the Elwha were compared to neighboring populations in the Dungeness River (fall and summer run) and Morse Creek (summer run) (Figure 1; Table 2). Moderate levels of variability were observed in 13 mSAT loci with 3 loci exhibiting > 20 alleles per locus (Table 3). There was little variability among samples in the estimates of genetic diversity (Table 2). Eight of the 13 loci were out of HWE (Table 3). Fall-run fish from the Dungeness and Elwha clustered together in the dendrogram (Figure 2); the FST value between the collections was statistically significant (Figure 2).

Figure 1.

Location of collection sites where LEKT is Lower Elwha Klallam Tribe, Ch. is channel, and WDFW is Washington Department of Fish and Wildlife.

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Figure 2.

Consensus neighbor-joining tree of CSE chord distances between pink salmon collections based on 13 mSAT loci. Numbers at the nodes indicate the percentage of 1000 trees in which collections grouped together. FST values (× 1000) for select comparisons against the principal Elwha collection are statistically significant.

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TABLE 2.

Summary of collections by species for adult samples except where noted. BY04=brood year 2004, etc; hat=hatchery; WDFW=Washington Department of Fish and Wildlife, LEKT=Lower Elwha Klallam Tribe.

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TABLE 3.

Levels of genetic diversity estimated by the percentage of observed (Ho) and expected (He) heterozygosity, Hardy-Weinberg Equilibrium (HWE) calculated over all collections, number of observed alleles, and allele size range.

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TABLE 3 Continued.

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Chum Salmon

Chum salmon collections from Puget Sound, Hood Canal, and the Strait of Juan de Fuca were compared to an Elwha River collection (Figure 1; Table 2). Seven of the 13 loci contained >20 alleles (Table 3). The highest levels of diversity were found in the Elwha collection. Allelic richness at Jimmycomelately Creek was approximately 50% the value of the Elwha collection (Table 2). Five of the 13 loci were out of HWE and FST values were generally low (Figure 3). Populations grouped by locale and by run timing (Figure 3); the fall-run fish from the Elwha River formed a branch off the Puget Sound fall-run group (Figure 3).

Figure 3.

Consensus neighbor-joining tree of CSE chord distances between chum salmon collections based on 13 mSAT loci. Numbers at the nodes indicate the percentage of 1000 trees in which collections grouped together. FST values (× 1000) for select comparisons against the principal Elwha collection are statistically significant. Ellipses enclose collections by group for illustrative purposes.

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Figure 4.

Consensus neighbor-joining tree of CSE chord distances between coho salmon collections based on 11 mSAT loci. Numbers at the nodes indicate the percentage of 1000 trees in which collections grouped together. FST values (× 1000) for select comparisons against the principal Elwha collection are statistically significant.

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Coho Salmon

Coho salmon were collected from six sites along the Strait of Juan de Fuca and compared to an Elwha River collection site at 11 mSAT loci (Figure 1; Table 2). Five loci had >20 alleles and 6 loci were out of HWE. Allelic and gene diversity measures were similar over all sites (Table 2). The relationships among samples did not follow a geographic pattern (Figure 4). For example, Deep and Salt creeks, which are found on either side of East and West Twin Creeks, grouped together. Elwha grouped with the Dungeness collection even though the two collections have statistically different allele frequencies (overall chi-square P=0.000; FST=0.173). As a group these collections clustered with coho salmon from the northern Washington coast (as opposed to exhibiting a Puget Sound affinity) (VanDoornik et al. 2007).

Rainbow Trout

Three collections of resident rainbow trout above the Elwha Dam were compared to a wild and a hatchery collection of steelhead from the lower river (Figure 1; Table 2). Five of 15 mSAT loci contained 20 or more alleles (Table 3). There was considerable variability in the estimates of genetic diversity. The wild steelhead collection from the lower Elwha River had the largest values of allelic richness and gene diversity, whereas a collection of rainbow trout from the South Branch Little River had 40–50% less at both estimates of allelic richness and gene diversity (Table 2). Allelic richness and gene diversity were higher in two resident trout collections (Griff and Madison creeks) than in the hatchery steelhead collections. All the loci departed significantly from HWE (Table 3) and FST values were moderate, e.g., FST between the wild and the brood year 2006 hatchery collection was 0.035 (P<0.001) (Figure 5a). It is worth noting that the wild fish were significantly different from the hatchery fish at all loci. The resident rainbow trout formed a separate branch from the wild and hatchery steelhead collections on the mSAT tree (Figure 5a).

Figure 5a.

Consensus neighbor-joining tree of CSE chord distances between rainbow trout and steelhead collections based on 14 mSAT loci. Numbers at the nodes indicate the percentage of 1000 trees in which collections grouped together. FST values (× 1000) for select comparisons against the principal Elwha collection are statistically significant. Ellipses enclose collections by group for illustrative purposes.

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Figure 5b.

Consensus neighbor-joining tree of CSE chord distances between rainbow trout and steelhead collections based on variability at the class II B1 locus at the major histocompatability complex (MHC). FST values (× 1000) for select comparisons against the principal Elwha collection are statistically significant.

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Similar patterns of genetic variability were seen at the MHC locus for which 9–18 alleles were seen in the various collections (Table 2). The largest values of genetic variability were seen in the wild steelhead collection, the smallest values were seen in the rainbow trout from South Branch Little River, and reduced levels were seen in the hatchery collections (Table 2). The level of differentiation at this locus as estimated by FST was roughly twice that of the mSATs (Figures 5a and 5b).

Sockeye salmon

The Elwha watershed has a population of landlocked sockeye salmon (kokanee) in Lake Sutherland (Figure 1), although occasional adult sockeye strays have been observed in the lower Elwha River. Two kokanee collections from Lake Sutherland were compared with Lake Ozette sockeye salmon (the nearest sockeye salmon stock in Washington) and with Lake Whatcom kokanee (historically, the most frequently outplanted kokanee in western Washington; Figure 1, Table 2). Over 13 loci, there were moderate levels of variability, with 5 loci containing 20 or more alleles (Table 3). The Ozette sockeye salmon collection had low values of genetic diversity compared to the other samples (Table 2). None of the loci were in HWE over all collections. The three collections were strongly differentiated (Figure 6).

Figure 6.

Consensus neighbor-joining tree of CSE chord distances between sockeye salmon/kokanee collections based on 13 mSAT loci. Numbers at the nodes indicate the percentage of 1000 trees in which collections grouped together. FST values (× 1000) for select comparisons against the principal Elwha collection are statistically significant. Ellipses enclose collections by group for illustrative purposes.

i0029-344x-82-sp1-128-f06.gif

Chinook Salmon

Tissues of Elwha River Chinook salmon were analyzed from collections taken from the Washington Department of Fish and Wildlife hatchery, a spawning site at Hunt's Road Channel, and a screw trap (rkm 0.5) sampling of 0-age non-hatchery Chinook salmon (Figure 1; Table 2). These were compared to a collection from the Dungeness River. Eight of the 13 mSAT loci screened for the chinook collections had 20 or more alleles. Allelic and gene diversity measures were similar over all sites (Table 2). Ten of the 13 loci were in HWE (Table 3), indicating a low level of differentiation among collections. The Hunt's Road Channel fish were distinctive in the mSAT dendrogram (Figure 7a). The same relationship was seen using Nei's genetic distance (Nei 1978). However, these results were not consistent with FST values among the collections, e.g., the FST value between Hunt's Road Channel and the hatchery was not significantly different from zero, whereas all other pair-wise comparisons with the Dungeness collection were statistically significant. For an independent view of collection variability, we viewed the data in a factorial correspondence analysis. The first three axes explained 85.3% of the variance (Figure 7b). Dungeness River was set apart from the other collections on Axis 1, the screw trap collections were distinctive on Axis 2, and the hatchery was distinctive on Axis 3. The disparity in results between the dendrogram and the factorial correspondence analysis plot is partially explained by the low level of divergence among the collections.

Figure 7a.

Consensus neighbor-joining tree of CSE chord distances between Chinook salmon collections based on 13 mSAT loci. Numbers at the nodes indicate the percentage of 1000 trees in which collections grouped together. FST values × 1000 are provided for select comparisons against the principal Elwha collection and are not statistically different from zero.

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Figure 7b.

Plot of average scores of five collections of Chinook salmon along the first three axes of a factorial correspondence analysis based on 13 mSAT loci.

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Bull Trout

Bull trout in the Elwha River were compared with collections ranging from the west coast of Washington to the Hood Canal in Puget Sound (Figure 1; Table 2). The number of alleles per locus ranged from 8–19 (Table 2). There was considerable variability in gene diversity estimates between collections within watersheds, and among collections overall (Table 2). Estimates of gene diversity were smallest in two collections from the Dungeness watershed. None of the loci were in HWE over all collections. The Elwha collection was clearly differentiated from all other neighboring populations (FST=0.168; Figure 8), consistent with bull trout variability throughout its range (Spruell et al. 2003).

Figure 8.

Consensus neighbor-joining tree of CSE chord distances between bull trout collections based on 6 mSAT variability. Bootstrap values at the nodes are not available. FST values (× 1000) for select comparisons against the principal Elwha collection are statistically significant.

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Discussion

A basic tenant of conservation genetics is that natural genetic diversity, as estimated in some cases by molecular markers, enhances the probability of a population's survival over ecological and evolutionary time (Avise 1994). In our synopsis of several independent and preliminary studies, collections within the Elwha river system generally exhibited moderate levels of genetic diversity, levels that were similar with those from neighboring sites (Table 2). These estimates do not guarantee rates or levels of recolonization success; rather, they indicate an absence of genetically impoverished groups of populations in the set of collections noted here. Two findings deserve extra comment. Among the three resident rainbow trout collections, the South Branch Little River had substantially reduced values of allelic richness and heterozygosity at both mSAT and MHC loci (Table 2). This population differs from the other two collections because it is isolated above a barrier in the upper Little River. A simple explanation therefore is that it has experienced periodic fluctuations in population numbers. Based on protein genetic data, Phelps et al. (2001) concluded that the South Branch Little River may be closely related to coastal winter steelhead, a finding not corroborated with our preliminary data. We (G. Winans, J. Baker, and K. Miller) are also investigating whether genetic introgression with non-native hatchery trout has occurred in the above-dam resident trout populations, including the South Branch Little River. The Elwha hatchery steelhead and the Lake Ozette sockeye salmon collection also exhibited a moderate reduction in genetic diversity (Table 2). The latter result was previously observed in a protein genetic survey (Winans et al. 1996). It is also worth noting that the Elwha chum salmon collection contained relatively higher levels of genetic diversity. This may be due in part to the hatchery transfers of chum salmon from Hood Canal (the Quilcene National Fish Hatchery) in the 1970's and 1980's to the Lower Elwha Klallam Tribal Hatchery (Nick Lampsakis, The Point No Point Treaty Council, personal communication).

In general, patterns of genetic similarity (Figures 2–8) follow patterns of differentiation that have been seen in more far-ranging investigations for each species. For example, nearest neighbors of chum salmon are genetically similar, whereas the pattern of differentiation in sockeye and coho salmon is more mosaic-like (see Waples et al. 2001). Two particular findings are worth emphasizing however. The collection of wild steelhead was clearly different from the hatchery stock (Figure 5a and 5b). This result was anticipated as the hatchery fish have an out-of-basin origin and spawn in December and January, whereas the wild Elwha population spawns from May to July. Less clear are the results for the Chinook salmon. The hatchery stock of Chinook salmon is based on local fish returning to the hatchery, although fish are ‘mined’ from the local stretch of the river in some years to meet egg-take goals (Michael L. McHenry, personal observation). In spite of this periodic mining and the proximity of the two sites, there is some indication that the hatchery stock may be dissimilar from the Hunt's Road Channel (Figure 7b). Further, the screw trap data indicate the possible presence of more populations in the river (Figure 7b). These preliminary results will be reevaluated as we collect more temporal and spatial data.

These baselines are all work-in-progress data sets requiring additional sampling to broaden the geographic coverage and to statistically confirm relationships. For example, Fraser River and southern Vancouver Island populations are needed for both the pink and sockeye salmon baselines, as recolonization to the Elwha River may involve strays from these large Northwest stocks. We (G. Winans, J. Baker, and K. Miller) are in the process of analyzing upper Elwha resident rainbow trout, as well as non native hatchery rainbow trout stocks (which were planted into the upper Elwha; Brenkman et al. 2008), to complete our genetic and phenetic survey of O. mykiss in the basin. We recognize that collections of chum salmon and steelhead are needed from the Dungeness River; and the late fall-run chum salmon from adjacent populations along the Strait of Juan de Fuca are missing in the baseline.

We also recognize that other character sets are needed to more completely understand local adaptation and, therefore, the characteristics of fish stocks that may successfully recolonize a reopened river. For rainbow trout, MHC variability is being used in conjunction with neutral markers (mSATs) to help dissect levels of adaptability with respect to disease challenges (Miller et al. 2001). We are also evaluating multivariate morphometrics for kokanee, coloration of juvenile rainbow trout, and morphometrics for juvenile and adult rainbow trout (see Winans et al. 2003). Other data that are useful for defining populations but are difficult to collect in a large river system such as the Elwha River include run timing, spawn timing, and ocean age.

As these genetic data sets are expanded for each species, we will be in a position to monitor the population composition of recolonization of the upper Elwha River. Mixture analysis of outmigrating juveniles and/or returning adults is essentially a genetic stock identification (GSI) procedure, where mixture genotypes are compared against a population baseline to estimate population proportions (Shaklee et al. 1999). We describe a range in the levels of population differentiation, from low FST values in pink and Chinook salmon to high values for sockeye salmon and bull trout. These values are well within the range of FST estimates that simulation studies have used to demonstrate accurate GSI applications (Beacham et al. 2000, Winans et al. 2004, Van Doornik et al. 2007).

Just as valuable as these descriptions of population differences using mSATs are the tissues used to collect the data. As pointed out by Shaklee et al. (1999), DNA-based techniques represent an “evolving technology.” As mSAT baselines have supplemented and then replaced protein genetic baselines for salmon population genetic work (Beacham et al. 1998b, Small et al. 1998), so to will other genetic markers be developed that will be as (or more) discriminating, cheaper, or more objective to score than mSATs. For example, laboratory techniques to score large numbers of single nucleotide polymorphisms are being developed for salmon that meet the above desired attributes of a new technology (Smith et al. 2005, Elfstrom et al. 2006). Thus, an important challenge for collaborators in the field is the proper archiving of baseline tissue samples. When mSAT data are no longer the technology of choice and incorporated into a newer, more advanced molecular technique (see Avise 1994), archived tissues from our studies will be extremely valuable to maintain pertinent genetic baselines and to extend our gene inventory/GSI work started here on salmon recolonization in the Elwha River.

There are several other difficult management and conservation issues that can be addressed with these data. Hatchery Chinook salmon are slated for outplanting into various reaches of the Elwha River (Ward et al. in press). Our data suggest that Elwha Chinook salmon may not consist of one interbreeding population. The early-returning fish at Hunt's Road Channel may represent a unique population. The screw trap data suggest there may be other unrecognized populations in the river. If either of these findings is true, after additional sampling and analyses, how will hatchery outplanting effect these populations? There have also been suggestions to move steelhead above the dams prior to dam removal. Here we show high levels of differentiation at the mSAT and MHC loci between resident trout and below-dam steelhead. Resident trout are different from steelhead, but we know little about the role of rainbow trout in steelhead adaptability and evolution, and vice versa. For example, in sympatry, low but steady genetic contributions of trout to steelhead populations may be important in the population genetic stability of steelhead (Araki et al. 2007). And in one case, rainbow trout crosses made from a population isolated in allopatry for about 80 years were able to produce smolts (in a hatchery environment), but the adults returned in very small percentages (Thrower et al. 2004). If steelhead are not passed upstream prior to dam removal, it is feasible that these data can be used to monitor the interactions of the various gene pools and study the characteristics of recolonization. We recognize that preserving natural processes associated with recolonization may be as important as recognizing and protecting natural biological diversity (Avise 1994).

The success of reestablishing sustainable populations will vary by species (Pess et al. 2008) and dam sites. It will vary due to factors such as species composition, habitat quality and quantity, the number and biological fitness of available gene pools, the number and strength of neighboring populations and hatcheries, and, to some degree, the extent of management involvement. Some of us (G. Winans, J. Baker, and K. Miller) are presently involved in monitoring O. mykiss in five dam recolonization efforts in the Pacific Northwest. Our goal is to provide a “genetic ruler” that assesses relevant gene pools prior to dam removal. This ruler will be used in the future as part of a multivariable evaluation of recolonization success. As more dam sites are reconsidered for removal (McHenry and Pess 2008), our accumulated information on the genetics of recolonization will help guide these events. The genetic data provided here are the first such data that will be used as a genetic ruler in an attempt to manage and conserve Pacific salmonids in the Elwha River recolonization program.

Acknowledgments

Chum salmon tissues and mSAT data for Chi-nook salmon from the Dungeness River were provided by the Washington Department of Fish and Wildlife genetics laboratory. Field and laboratory assistance was provided by Mel Elofson, Raymond Moses, Larry Ward, Delia Patterson, Sam Brenkman, and Piper Schwenke. Sandy Slover provided the map.

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Gary A. Winans, Michael L. McHenry, Jon Baker, Anna Elz, Alisha Goodbla, Eric Iwamoto, David Kuligowski, Kristi M. Miller, Maureen P. Small, Paul Spruell, and Don Van Doornik "Genetic Inventory of Anadromous Pacific Salmonids of the Elwha River Prior to Dam Removal," Northwest Science 82(sp1), 128-141, (1 December 2008). https://doi.org/10.3955/0029-344X-82.S.I.128
Published: 1 December 2008
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