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Genetic-Based Estimates of Adult Chinook Salmon Spawner Abundance from Carcass Surveys and Juvenile Out-Migrant Traps

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Genetic-Based Estimates of Adult Chinook Salmon Spawner Abundance from Carcass Surveys and Juvenile Out-Migrant Traps Transactions of the American Fisheries Society 143:55–67, 2014 C American Fisheries Society 2014 ISSN: 0002-8487 print / 1548-8659 online DOI: 10.1080/00028487.2013.829122 ARTICLE Genetic-Based Estimates of Adult Chinook Salmon Spawner Abundance from Carcass Surveys and Juvenile Out-Migrant Traps Daniel J. Rawding, Cameron S. Sharpe,1 and Scott M. Blankenship*2 Washington Department of Fish and Wildlife, 600 Capitol Way North, Olympia, Washington 98501-1091, USA Abstract Due to the challenges associated with monitoring in riverine environments, unbiased and precise spawner abun- dance estimates are often lacking for populations of Pacific salmon Oncorhynchus spp. listed under the Federal Endangered Species Act. We investigated genetic approaches to estimate the 2009 spawner abundance for a popu- lation of Columbia River Chinook Salmon Oncorhynchus tshawytscha via genetic mark–recapture and rarefaction curves. The marks were the genotyped carcasses collected from the spawning area during the first sampling event. The second sampling event consisted of a collection of juveniles from a downstream migrant trap located below the spawn- ing area. The parents that assigned to the juveniles through parentage analysis were considered the recaptures, which was a subset of the genotypes captured in the second sample. Using the Petersen estimator, the genetic mark–recapture spawner abundance estimates based on the binomial and hypergeometric models were 910 and 945 Chinook Salmon, respectively. These results were in agreement with independently derived spawner abundance estimates based on redd counts, area-under-the-curve methods, and carcass tagging based on the Jolly–Seber model. Using a rarefaction curve approach, which required only the juvenile offspring sample, our estimate of successful breeders was 781 fish. Our genetic-based approaches provide new alternatives to estimate adult Pacific salmon abundance in challenging environmental conditions or for populations with poor or unknown estimates of precision. Many populations of Pacific salmon Oncorhynchus spp. from ate the merits of regulatory decisions and conservation efforts. southern California to northern Washington are listed for pro- Despite considerable effort being directed toward Pacific salmon tection under the U.S. Endangered Species Act 1973 (ESA). In monitoring activities, reported population abundance estimates the area of ESA Pacific salmon population recovery planning, often do not meet NOAA’s guidelines for unbiased estimates Downloaded by [Dr Scott M. Blankenship] at 08:56 11 December 2013 the National Oceanic and Atmospheric Administration (NOAA) with a coefficient of variation (CV) of less than 15% (Crawford has provided guidance for status and trends monitoring based on and Rumsey 2011); thus, the development of alternative meth- Viable Salmonid Population (VSP) indictors (McElhany et al. ods to estimate abundance in the fisheries field is warranted. 2000; Crawford and Rumsey 2011). The VSP indicators include In Pacific salmon population assessment and management, adult spawner abundance, productivity, spatial distribution, and the most common abundance metric used is spawner abundance diversity. The legal statutes mandating protective action and or escapement (i.e., the number of fish returning to spawn after the monitoring recommendations associated with these actions harvest) (Hilborn and Walters 1992; Good et al. 2007; Crawford highlight the need for reliable population information to evalu- and Rumsey 2011). In contrast, conservation biology refers to *Corresponding author: scott.blankenship@fishsciences.net 1Present address: Oregon Department of Fish and Wildlife, Corvallis Research Laboratory, 28655 Highway 34, Corvallis, Oregon 97333, USA. 2Present address: Cramer Fish Sciences, GENIDAQS Division, 3300 Industrial Way, Suite 100, West Sacramento, California 95691, USA. Received December 7, 2012; accepted July 17, 2013 55 56 RAWDING ET AL. the number of adults present in the population as the census method has been extended to estimate the number of individ- size (i.e., Nc) (Luikart et al. 2010). For the methods described in uals in a population (Kohn et al. 1999; Eggert et al. 2003). this study, we defined Nc as the number of adult salmon present This approach involves fitting the cumulative number of exam- at the time of spawning, which is consistent with the above ined genotypes to the number of unique genotypes within an definitions of abundance. Another measure of abundance is the identified population to estimate the asymptote of the curve, number of successful breeders (Nb), which is defined as the which is the population estimate of successful breeders. In ge- number of spawners that produced at least one offspring during netic rarefaction curves, multiple equations may be used to esti- one reproductive season (Schmeller and Merila¨ 2007). Since mate Nb; however, different equations often lead to different re- many salmon populations in the Pacific Northwest are listed for sults (Frantz and Roper 2006). As with genetic mark–recapture protection under the ESA, the number of successful breeders studies, the genetic rarefaction approach is typically applied may be a better metric for assessing extinction probabilities due to adults, but the method has been used to estimate the num- to the loss of genetic diversity and depensation (Waples 2002; ber of Green Sturgeon Acipenser medirostris breeders in the Barrowman et al. 2003). For semelparous species such as Pacific Sacramento River based on juvenile collections (Israel and May salmon, Nc equates to the number of successful breeders (Nb) 2010). We investigated the genetic rarefaction approach in par- plus the number of spawners that produced no offspring. allel with tGMR, which we termed transgenerational genetic Juvenile Pacific salmon out-migration and adult spawner rarefaction curves (tGRC). abundance are commonly estimated, with this life-stage-specific While genetic-based approaches to estimating abundance information analyzed using spawner–recruit relationships to es- have proven successful, care must be taken in study design timate freshwater productivity and capacity (Hilborn and Wal- development, genetic analysis, use of software for matching ters 1992; Barrowman et al. 2003) or the effectiveness of habi- genetic samples or obtaining parental assignments, and appli- tat restoration for salmon populations (Bradford et al. 2005). cation to statistical models (Marucco et al. 2011). Lukacs and If adult and juvenile genetic sampling is incorporated into this Burnham (2005a) indicated that the equal capture and correct established monitoring framework, then the use of genetic ap- identification of marked and unmarked assumptions should be proaches to estimate Nc and Nb in a population can be pursued carefully examined in genetic mark–recapture studies. For ex- as alternatives to more traditional visual count methods. As each ample, individual heterogeneity in capture probabilities will lead individual in a population is characterized by a unique genetic to a violation of the equal capture assumption and can be ad- profile, often referred to as a molecular tag or genetic mark, dressed through study designs and statistical models (Lukacs DNA-based methods have been developed to determine the and Burnham 2005b; Miller at al. 2005; Marucco et al. 2011). number of animals sampled and to estimate the population size In addition, marked and unmarked individuals can be correctly using mark–recapture and rarefaction models (Lukacs and Burn- identified by ensuring the number of chosen loci has sufficient ham 2005a; Frantz and Roper 2006). The use of genetic markers power to differentiate related individuals and laboratory proce- to estimate population abundance is common in wildlife inves- dures and genetic assignment software can minimize genotyp- tigations (Marucco et al. 2011); however, adaptations of these ing and assignment errors (Mills et al. 2000; Waits and Leberg approaches to aquatic systems appear well suited for estimating 2000). Violation of genetic-based model assumptions will lead Pacific salmon population abundance. Genetic mark–recapture to biased abundance estimates (Lukacs and Burnham 2005a). approaches designed to estimate abundance are based on mark– We tested genetic-based approaches to estimate abundance recapture theory and are varied (Lukacs and Burnham 2005a). on a population of Chinook Salmon Oncorhynchus tshawytscha They may be structured to directly recapture the same individual in a well-monitored lower–Columbia River tributary system (Palsbøll et al. 1997; Taberlet et al. 1997) or recover a parent’s (Coweeman River, Washington). We compared the accuracy Downloaded by [Dr Scott M. Blankenship] at 08:56 11 December 2013 genotype through its offspring via parentage analysis (Jones and and precision of the genetics-based approaches to independent Avise 1997; Pearse et al. 2001). Here, we employed a modifica- estimates of abundance based on redd surveys (Gallagher and tion of the latter technique to estimate spawner abundance (Nc) Gallagher 2005), area-under-the-curve (AUC) methods (English via the Petersen estimator (Williams et al. 2002). We used mul- et al. 1992), and Jolly–Seber carcass tagging (Sykes and Bots- tilocus genotypes from sampled adult carcasses to establish a set ford 1986). We report the results of this comparison and describe of “marks,” with “recaptures” of parental marks accomplished and discuss the challenges of implementing genetic approaches, through parentage analysis of genotyped
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