Allozymes and Mitochondrial DNA Discriminate Asian and North American Populations of Chum Salmon in Mixed-Stock Fisheries along the South Coast of the Alaska Peninsula

Seeb, Lisa W.; Crane, Penelope A.

doi:10.1577/1548-8659(1999)128<0088:aamdda>2.0.co;2

Cited by 50 publications

(31 citation statements)

References 30 publications

(59 reference statements)

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“…The accuracy of GSI is assessed on the basis of how close the average value of b i is to 100%. Such 100% mixture simulations may not be a particularly realistic way of assessing the utility of a set of markers for GSI, but they have been used numerous times in the literature (for example, see Seeb and Crane (1999), Smith et al (2005b), Habicht et al (2007), etc.). We simulated one-hundred 100% mixtures of size N = 200 for each of the 166 populations in the baseline.…”

Section: Analysis Of Empirical Datamentioning

confidence: 99%

An improved method for predicting the accuracy of genetic stock identification

Anderson

Waples

Kalinowski

2008

Can. J. Fish. Aquat. Sci.

219

277

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Estimating the accuracy of genetic stock identification (GSI) that can be expected given a previously collected baseline requires simulation. The conventional method involves repeatedly simulating mixtures by resampling from the baseline, simulating new baselines by resampling from the baseline, and analyzing the simulated mixtures with the simulated baselines. We show that this overestimates the predicted accuracy of GSI. The bias is profound for closely related populations and increases as more genetic data (loci and (or) alleles) are added to the analysis. We develop a new method based on leave-one-out cross validation and show that it yields essentially unbiased estimates of GSI accuracy. Applying both our method and the conventional method to a coastwide baseline of 166 Chinook salmon (Oncorhynchus tshawytscha) populations shows that the conventional method provides severely biased predictions of accuracy for some individual populations. The bias for reporting units (aggregations of closely related populations) is moderate, but still present.Résumé : L'estimation de la précision de l'identification du stock génétique (« GSI ») qu'on peut espérer, étant donné une banque de données de base récoltée antérieurement, nécessite des simulations. La méthode courante comprend des simulations répétées de mélanges par ré-échantillonnage de la banque de données de base, des simulations de nouvelles banques de données de base en ré-échantillonnant la banque de données et l'analyse des mélanges ainsi simulés à l'aide des banques de données de base simulées. Nous montrons que cette méthode surestime la précision prédite de GSI. L'erreur est importante dans les populations fortement apparentées et elle augmente à mesure que de nouvelles données génétiques (locus et (ou) allèles) sont ajoutées à l'analyse. Nous mettons au point une nouvelle méthode basée sur une validation croisée de type « leave-one-out » (avec retrait d'un élément) et nous montrons qu'elle produit essentiellement des estimations non erronées de la précision de GSI. L'application de notre méthode et de la méthode courante à une banque de données de base provenant de 166 populations de saumons chinook (Oncorhynchus tshawytscha) réparties sur toute la côte montre que la méthode courante fournit des prédictions de la précision qui sont grandement faussées pour certaines populations individuelles. L'erreur dans le cas des unités d'évaluation (des rassemblements de populations fortement apparentées) est peu importante, mais réelle.[Traduit par la Rédaction]

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Section: Analysis Of Empirical Datamentioning

confidence: 99%

An improved method for predicting the accuracy of genetic stock identification

Anderson

Waples

Kalinowski

2008

Can. J. Fish. Aquat. Sci.

219

277

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“…The genetic population structure of the Pacific salmon has been clarified using various methods such as allozyme (Winans et al 1994), mitochondrial DNA (mtDNA; Seeb and Crane 1999), and microsatellite DNA (msDNA; Beacham et al 2006). The mtDNA and msDNA methods are powerful tools for genealogical identification, despite limitations of analytical precision (Zhang and Hewitt 2003).…”

Section: Introductionmentioning

confidence: 99%

The genetic population structure of lacustrine sockeye salmon, Oncorhynchus nerka, in Japan as the endangered species

et al. 2011

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“…Fisheries managers use this method extensively to estimate the proportional contribution of stocks to mixed-stock fisheries. This is especially true on the west coast of North America, where mixed-stock analysis has been routinely used for decades on all Pacific salmon species (Seeb and Crane, 1999;Habicht et al, 2010;Beacham et al, 2011Beacham et al, , 2012Small et al, 2015). Assessments of the utility of MSA in Canadian Arctic fisheries are only recently emerging (but see Harris and Taylor, 2010).…”

Section: Introductionmentioning

confidence: 99%

Genetic Stock Identification and Relative Contribution of Arctic Char (<i>Salvelinus alpinus</i>) from the Hornaday and Brock Rivers to Subsistence Fisheries in Darnley Bay, Northwest Territories + Supplementary Appendix Tables S1 to S4 (See Article Tools)

Harris¹,

Boguski²,

Gallagher³

et al. 2016

ARCTIC

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ABSTRACT. Where anadromous fishes occur in the Canadian Arctic, they provide the mainstay of local subsistence fisheries of varying intensities. Many of these fisheries harvest a mixture of stocks at discrete locations and it is often not known which stocks, specifically, are being harvested and to what extent. In the Darnley Bay area of the Northwest Territories, Arctic char, Salvelinus alpinus, in particular have long provided an important subsistence resource to residents of Paulatuk, and char from two systems (the Hornaday and Brock Rivers) are thought to contribute to the coastal fishery for this species. Genetic mixed-stock analysis (GMA) is routinely applied for resolving stock contributions to such fisheries, yet studies incorporating GMA to understand specifically which stocks are being harvested in the Canadian Arctic, and to what extent, are relatively scarce. In this study, we assayed microsatellite DNA variation among 987 Arctic char from two important coastal subsistence fisheries and several inland sampling locations in the Darnley Bay area to (1) assess the degree of genetic structuring between the Hornaday and Brock Rivers and (2) resolve the proportional contributions of these stocks to coastal mixed-stock fisheries in the region using GMA. Overall, genetic differentiation was relatively high and significant (θ = 0.117; 95% C.I. = 0.097-0.142) among baseline sampling locations. Overall patterns of genetic stock structure also support previous hypotheses that additional life history types (e.g., landlocked or freshwater-resident char, or both) exist in the Hornaday system, as indicated by elevated levels of genetic differentiation between some of our sampling locations. The GMA suggested that, while both river systems contribute to the coastal fishery, catches were dominated by Arctic char from the Hornaday River, which highlights the importance of this system. All told, our results may be relevant to the management of the subsistence fishery in Darnley Bay and for furthering the collective understanding of char biodiversity and life history variation in the Canadian Arctic.Key words: Arctic char; Salvelinus alpinus; mixed-stock fishery; genetic mixed-stock analysis; subsistence harvest; Darnley Bay RÉSUMÉ. Dans les milieux de l'Arctique canadien où l'on trouve des poissons anadromes, ceux-ci sont à la base de pêcheries de subsistance locales d'intensités variées. Grand nombre de ces pêcheries permettent de récolter un mélange de stocks à différents endroits et nous ne savons souvent pas quels stocks en particulier sont récoltés et jusqu'à quel point. Dans la région de la baie Darnley, dans les Territoires du Nord-Ouest, l'omble chevalier, Salvelinus alpinus, en particulier, a longtemps fourni une ressource de subsistance importante aux résidents de Paulatuk, et des ombles de deux réseaux (les rivières Hornaday et Brock) semblent contribuer à la pêche de cette espèce en eaux côtières. La méthode de l'analyse génétique de stocks mélangés est souvent employée pour déterminer les contributions de d...

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Allozymes and Mitochondrial DNA Discriminate Asian and North American Populations of Chum Salmon in Mixed-Stock Fisheries along the South Coast of the Alaska Peninsula

Cited by 50 publications

References 30 publications

An improved method for predicting the accuracy of genetic stock identification

An improved method for predicting the accuracy of genetic stock identification

The genetic population structure of lacustrine sockeye salmon, Oncorhynchus nerka, in Japan as the endangered species

Genetic Stock Identification and Relative Contribution of Arctic Char (<i>Salvelinus alpinus</i>) from the Hornaday and Brock Rivers to Subsistence Fisheries in Darnley Bay, Northwest Territories + Supplementary Appendix Tables S1 to S4 (See Article Tools)

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