Classical individual assignments versus mixture modeling to estimate stock proportions in Atlantic salmon (Salmo salar) catches from DNA microsatellite data

Canadian Journal of Fisheries and Aquatic Sciences

Volumn 62, Issue 9, 2005, Pages 2143-2158

  Koljonen, Marja Liisa ^a   Pella, Jerome J ^b   Masuda, Michele ^b  

^a FINNISH FOREST RESEARCH INSTITUTE   (Finland)

^b NATIONAL MARINE FISHERIES SERVICE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DNA FINGERPRINTING; SALMONID FISHERY; STOCK ASSESSMENT; STOCK IDENTIFICATION;

ATLANTIC OCEAN; BALTIC SEA;

SALMO SALAR;

EID: 29144527027     PISSN: 0706652X     EISSN: None     Source Type: Journal    
DOI: 10.1139/f05-128     Document Type: Article

References (58)

1. Anonymous. 2003. Report of the Baltic Salmon and Trout Assessment Working Group. International Council for the Exploration of the Sea, Advisory Group on Fishery Management, ICES CM 2003/ACFM: 20, 2-11 April 2003, Karlskrona, Sweden.
2. Anonymous. 2004. Report of Working Group on Assessment of Baltic Salmon and Trout. International Council for the Exploration of the Sea, Advisory Group on Fishery Management, ICES CM 2004/ACFM: 22, 21-30 April 2004, Tarto, Estonia.
3. Banks, M.B., and Eichert, W. 2000. WHICHRUN (version 3.2): a computer program for population assignment of individuals based on multilocus genotype data. J. Hered. 91: 87-89.
4. Beacham, T.D., and Wood, C.C. 1999. Application of microsatellite DNA variation to estimation of stock composition and escapement of Nass River sockeye salmon (Oncorhynchus nerka). Can. J. Fish. Aquat. Sci. 56: 297-310.
5. Beacham, T.D., Pollard, S., and Le, K.D. 1999. Population structure and stock identification of steelhead in southern British Columbia, Washington, and the Columbia River based on microsatellite DNA variation. Trans. Am. Fish. Soc. 128: 1068-1084.
6. Begg, G.A., Friedland, K.D., and Pearce, J.B. 1999. Stock Identification - Its Role in Stock Assessment and Fisheries Management: A Selection of Papers Presented at a Symposium of the 28th Annual Meeting of the American Fisheries Society in Hartford, Conn., 23-27 August 1998. Fish. Res. 43: 1-3.
7. Cadrin, S.X., Friedland, K.D., and Waldman, J.R. 2005. Stock identification methods. Applications in fishery science. Elsevier Academic Press, Burlington, Mass.
8. Cornuet, J.-M., Piry, S., Luikart, G., Estoup, A., and Solignac, M. 1999. New methods employing multilocus genotypes to select or exclude populations as origins of individuals. Genetics, 153: 1989-2000.
9. Davies, N., Villablanca, F.X., and Roderick, G.K. 1999. Determining the source of individuals: multilocus genotyping in nonequilibrium population genetics. Trends Ecol. Evol. 14: 17-21.
10. Dawson, K.J., and Belkhir, K. 2001. A Bayesian approach to the identification of panmictic populations and the assignment of individuals. Genet. Res. Camb. 78: 59-77.
11. Debevec, E.M., Gates, R.B., Masuda, M., Pella, J., Reynolds, J., and Seeb, L.W. 2000. SPAM (version 3.2): statistics program for analyzing mixtures. J. Hered. 91: 509-510.
12. Fournier, D.A., Beacham, T.D., Riddell, B.E., and Busack, C.A. 1984. Estimating stock composition in mixed stock fisheries using morphometric, meristic, and electrophoretic characters. Can. J. Fish. Aquat. Sci. 41: 400-408.
13. Gelman, A., and Rubin, D.B. 1992. Inference from iterative simulation using multiple sequences. Stat. Sci. 7: 457-511.
14. Guinand, B., Scribner, K.T., Topchy, A., Page, K.S., Punch, W., and Burnham-Curtis, M.K. 2004. Sampling issues affecting accuracy of likelihood-based classification using genetical data. Environ. Biol. Fishes, 69: 245-259.
15. Guo, S.W., and Thompson, E.A. 1992. Performing the exact test of Hardy-Weinberg proportions for multiple alleles. Biometrics, 48: 361-372.
16. Hand, D.J. 1981. Discrimination and classification. John Wiley & Sons, New York.
17. Hansen, M.H., Kenchington, E., and Nielsen, E.E. 2001. Assigning individual fish to populations using microsatellite DNA markers. Fish Fish. 2: 93-112.
18. Hastie, T., Tibshirani, R., and Friedman, J. 2001. The elements of statistical learning. Data mining, inference, and prediction. Springer-Verlag, New York.
19. King, T.L., Kalinowski, S.T., Schill, W.B., Spidle, A.P., and Lubinski, B.A. 2001. Population structure of Atlantic salmon (Salmo salar L.): a range wide perspective from microsatellite DNA variation. Mol. Ecol. 10: 807-821.
20. Koljonen, M.-L., and McKinnell, S. 1996. Assessing seasonal changes in stock composition of Atlantic salmon catches in the Baltic Sea with genetic stock identification. J. Fish Biol. 49: 1-21.
21. Koljonen, M.-L., and Pella, J.J. 1997. The advantage of using smolt age with allozymes for assessing wild stock contributions to Atlantic salmon catches in the Baltic Sea. ICES J. Mar. Sci. 54: 1015-1030.
22. Koljonen, M.-L., Jansson, H., Paaver, T., Vasin, O., and Koskiniemi, J. 1999. Phylogeographic lineages and differentiation pattern of Atlantic salmon in the Baltic Sea with management implications. Can. J. Fish. Aquat. Sci. 56: 1766-1780.
23. Koljonen, M.-L., Tähtinen, J., Säisä, M., and Koskiniemi, J. 2002. Maintenance of genetic diversity of Atlantic salmon (Salmo salar) by captive breeding programmes and the geographic distribution of microsatellite variation. Aquaculture, 212: 69-93.
24. Koskinen, M.T. 2003. Individual assignment using microsatellite DNA reveals unambiguous breed identification in the domestic dog. Anim. Genet. 34: 297-301.
25. Luikart, G., and England, P.R. 1999. Statistical analysis of microsatellite DNA data. Trends Ecol. Evol. 14: 253-256.
26. Manel, A., Berthier, P., and Luikart, G. 2002. Detecting wildlife poaching: Identifying the origin of individuals with Bayesian assignment tests and multilocus genotypes. Conserv. Biol. 16: 650-659.
27. Manel, A., Gaggiotti, O., and Waples, R.S. 2005. Assignment methods: matching biological questions with appropriate techniques. Trends Ecol. Evol. 20: 136-142.
28. Masuda, M., Nelson, S., and Pella, J. 1991. User's manual for GIRLSEM, GIRLSYM and CONSQRT. The computer programs for computing conditional maximum likelihood estimates of stock compositions from discrete characters. Personal computer version. USA-DOC-NOAA-NMFS Auke Bay Laboratory, Auke Bay, Alaska.
29. McConnell, S.K., O'Reilly, P., Hamilton, L., Wright, J.N., and Bentzen, P. 1995. Polymorphic microsatellite loci from Atlantic salmon (Salmo salar): genetic differentiation of North American and European populations. Can. J. Fish. Aquat. Sci. 52: 1863-1872.
30. McConnell, S.K., Ruzzante, D., O'Reilly, T.O., and Hamilton, L. 1997. Microsatellite loci reveal highly significant genetic differentiation among Atlantic salmon (Salmo salar L.) stocks from east coast of Canada. Mol. Ecol. 6: 1075-1089.
31. Millar, R.B. 1987. Maximum likelihood estimation of mixed stock fishery composition. Can. J. Fish. Aquat. Sci. 44: 583-590.
32. Nei, M. 1973. Analysis of gene diversity in subdivided populations. Proc. Natl. Acad. Sci. U.S.A. 70: 3321-3323.
33. Nei, M., Tajima, F., and Tateno, Y. 1983. Accuracy of estimated phylogenetic trees from molecular data. J. Mol. Evol. 19: 153-170.
34. Nielsen, E.E., Hansen, M.M., and Loeschke, V. 1999. Genetic variation in time and space: microsatellite analyses of extinct and extant populations of Atlantic salmon. Evolution, 53: 261-268.
35. Norris, A.T., Bradley, D.G., and Cunningham, E.P. 1999. Microsatellite genetic variation between and within farmed and wild Atlantic salmon (Salmo salar) populations. Aquaculture, 180: 247-2634.
36. O'Reilly, P.T., Hamilton, L.C., McConnell, S.K., and Wright, J.M. 1996. Rapid analysis of genetic variation in Atlantic salmon (Salmo salar) by PCR multiplexing of dinucleotide and tetranucleotide microsatellites. Can. J. Fish. Aquat. Sci. 53: 2292-2298.
37. Ota, T. 1993. DISPAN: genetic distance and phylogenetic analysis. Institute of Molecular Evolutionary Genetics, Pennsylvania State University, Penn., USA.
38. Paetkau, D., Calvert, W., Stirling, I., and Strobeck, C. 1995 Microsatellite analysis of population structure in Canadian polar bears. Mol. Ecol. 4: 347-354.
39. Pella, J., and Masuda, M. 2001. Bayesian methods for analysis of stock mixtures from genetic characters. Fish. Bull. 99: 151-167.
40. Pella, J., and Masuda, M. 2005. Classical discriminant analysis, classification of individuals, and source population composition of mixtures. In Stock identification methods: applications in fishery science. Edited by S. Cadrin, K. Friedland, and J. Waldman. Academic Press, New York. pp. 517-552.
41. Pella, J.J., and Milner, G.B. 1987. Use of genetic marks in stock composition analysis. In Population genetics and fisheries management. Edited by N. Ryman and F. Utter. University of Washington Press, Seattle, Wash. pp. 247-276.
42. Potvin, C., and Bernatchez, L. 2001. Lacustrine spatial distribution of landlocked Atlantic salmon populations assessed across gen-erations by multilocus individual assignment and mixed-stock analysis. Mol. Ecol. 10: 2375-2388.
43. Pritchard, J.K., Stephens, M., Rosenberg, N.A., and Donnelly, P. 2000. Inference of population structure using multilocus genotype data. Genetics, 155: 945-959.
44. Rannala, B., and Mountain, J.L. 1997. Detecting immigration by using multilocus genotypes. Proc. Natl. Acad. Sci. U.S.A. 94: 9197-9221.
45. Raymond, M., and Rousset, F. 1995. GENEPOP (version 1.2): population genetics software for exact test and ecumenicism. J. Hered. 86: 248-249.
46. Rice, W.R. 1989. Analyzing tables of statistical tests. Evolution, 43: 223-225.
47. Roques, S., Duchesne, P., and Bernatchez, L. 1999. Potential of microsatellites for individual assignment: the North Atlantic redfish (genus Sebastes) species complex as a case study. Mol. Ecol. 8: 1703-1717.
48. Säisä, M., Koljonen, M.-L., and Tähtinen, J. 2003. Genetic changes in Atlantic salmon stocks since historical times and the effective population sizes of the long-term captive breeding programmes. Conserv. Genet. 4: 613-627.
49. Säisä, M., Koljonen, M.-L., Gross, R., Nilsson, J., Tähtinen, J., Koskiniemi, J., and Vasemägi, A. 2005. Population genetic structure and postglacial colonization of Atlantic salmon (Salmo salar) in the Baltic Sea area based on microsatellite DNA variation. Can. J. Fish. Aquat. Sci. 62: 1887-1904.
50. Saitou, N., and Nei, M. 1987. The neighbor joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4: 406-425.
51. Shaklee, J.B., Beacham, T.D., Seeb, L., and White, B.A. 1999. Managing fisheries using genetic data: case studies from four species of Pacific salmon. Fish. Res. 43: 45-78.
52. Slettan, A., Olsaker, I., and Lie, O. 1995. Atlantic salmon, Salmo salar, microsatellites at the SSOSL25, SSOSL85, SSOSL311, SSOSL417 loci. Anim. Genet. 26: 277-285.
53. Slettan, A., Olsaker, I., and Lie, O. 1996. Polymorphic Atlantic salmon (Salmo salar) microsatellites at the SSOSL438, SSOSL439, and SSOSL444 loci. Anim. Genet. 27: 57-58.
54. Smouse, P.E., Waples, R.S., and Tworek, J.A. 1990. A genetic mixture analysis for use with incomplete source population data. Can. J. Fish. Aquat. Sci. 47: 620-634.
55. Taggart, J.B., Hynes, R.A., Prodöhl, P.A., and Ferguson, A. 1992. A simplified protocol for routine total DNA isolation from salmonid fishes. J. Fish Biol. 40: 963-965.
56. Waples, R.S. 1990. Temporal changes of allele frequency in Pacific salmon: implications for mixed-stock fishery analysis. Can. J. Fish. Aquat. Sci. 47: 968-976.
57. Weir, B.C., and Cockerham, C.C. 1984. Estimating F-statistics for the analysis of population structure. Evolution, 38: 1350-1370.
58. Wood, C.C., McKinnell, S., Mulligan, T.J., and Fournier, D.A. 1987. Stock identification with the maximum-likelihood mixture model: sensitivity analysis and application to complex problems. Can. J. Fish. Aquat. Sci. 44: 866-881.