Conservation Genetics

, Volume 12, Issue 1, pp 223–241 | Cite as

Comparative landscape genetic analysis of three Pacific salmon species from subarctic North America

  • Jeffrey B. Olsen
  • Penelope A. Crane
  • Blair G. Flannery
  • Karen Dunmall
  • William D. Templin
  • John K. Wenburg
Research Article


We examined the assumption that landscape heterogeneity similarly influences the spatial distribution of genetic diversity in closely related and geographically overlapping species. Accordingly, we evaluated the influence of watershed affiliation and nine habitat variables from four categories (spatial isolation, habitat size, climate, and ecology) on population divergence in three species of Pacific salmon (Oncorhynchus tshawytscha, O. kisutch, and O. keta) from three contiguous watersheds in subarctic North America. By incorporating spatial data we found that the three watersheds did not form the first level of hierarchical population structure as predicted. Instead, each species exhibited a broadly similar spatial pattern: a single coastal group with populations from all watersheds and one or more inland groups primarily in the largest watershed. These results imply that the spatial scale of conservation should extend across watersheds rather than at the watershed level which is the scale for fishery management. Three independent methods of multivariate analysis identified two variables as having influence on population divergence across all watersheds: precipitation in all species and subbasin area (SBA) in Chinook. Although we found general broad-scale congruence in the spatial patterns of population divergence and evidence that precipitation may influence population divergence in each species, we also found differences in the level of population divergence (coho > Chinook and chum) and evidence that SBA may influence population divergence only in Chinook. These differences among species support a species-specific approach to evaluating and planning for the influence of broad-scale impacts such as climate change.


Landscape genetics Pacific salmon Population structure Subarctic 



Funding for this study was provided by the Arctic Yukon Kuskokwim Sustainable Salmon Initiative through project number 45490, and the US Fish and Wildlife Service (USFWS) Alaska Region Conservation Genetics Laboratory. Tyler Grossheusch developed the ArcGIS version 9.2 data layers for each species. Doug Molyneaux (Alaska Department of Fish and Game) organized sample collections from the Kuskokwim River. The data layers used in this study can be downloaded from a companion web map at The findings and conclusions in this article are those of the authors and do not necessarily represent the views of the USFWS.

Supplementary material

10592_2010_135_MOESM1_ESM.doc (1.3 mb)
Supplementary material 1 (DOC 1296 kb)


  1. Anderson MJ (2003) DISTLM forward: a FORTRAN computer program to calculate a distance-based multivariate analysis for a linear model using forward selection. Department of Statistics, University of Auckland, New Zealand.
  2. Balkenhol N, Waits LP, Dezzani RJ (2009) Statistical approaches in landscape genetics: an evaluation of methods for linking landscape and genetic data. Ecography 32:818–830CrossRefGoogle Scholar
  3. Beacham TD, Jonsen KL, Supernault J, Wetklo M, Deng L, Varnavskaya N (2006) Pacific Rim population structure of Chinook salmon as determined from microsatellite analysis. Trans Am Fish Soc 135:1604–1621CrossRefGoogle Scholar
  4. Bohonak AJ (2002) IBD (isolation by distance); a program for analysis of isolation by distance. J Hered 93:153–154CrossRefPubMedGoogle Scholar
  5. Brannian LK, Evenson MJ, Hilsinger JR (2006) Escapement goal recommendations for select Arctic-Yukon-Kuskokwim region salmon stocks, 2007. Alaska Department of Fish and Game, Fishery Manuscript No. 06-07, Anchorage.
  6. Carmichael LE, Krizan J, Nagy JA, Fuglei E, Dumond M, Johnson D, Veitch A, Berteaux D, Strobeck C (2007) Historical and ecological determinants of genetic structure in arctic canids. Mol Ecol 16:3466–3483CrossRefPubMedGoogle Scholar
  7. Crane P, Molyneaux D, Lewis C, Wenburg J (2007) Genetic variation among coho salmon populations from the Kuskokwim Region and application to stock-specific harvest estimation. Alaska Fisheries Technical Report No. 96, U.S. Fish and Wildlife Service, Anchorage.
  8. Dillane E, McGinnity P, Coughlan JP, Cross MC, Eyto ED, Kenchington E, Prodöhl P, Cross TF (2008) Demographics and landscape features determine intrariver population structure in Atlantic salmon (Salmo salar L.): the case of the River Moy in Ireland. Mol Ecol 17:4786–4800CrossRefPubMedGoogle Scholar
  9. Dionne M, Caron F, Dodson JJ, Bernatchez L (2008) Landscape genetics and hierarchical genetic structure in Atlantic salmon: the interaction of gene flow and local adaptation. Mol Ecol 17:2382–2396CrossRefPubMedGoogle Scholar
  10. Dupanloup I, Schneider S, Excoffier L (2002) A simulated annealing approach to define the genetic structure of populations. Mol Ecol 11:2571–2581CrossRefPubMedGoogle Scholar
  11. Ecological Stratification Working Group (1996) A National Ecological Framework for Canada. Agriculture and Agri-Food Canada, Research Branch, Centre for Land and Biological Resources Research and Environment Canada, State of Environment Directorate, Ottawa/Hull, 125 pp.
  12. Excoffier L, Laval G, Schneider S (2005) Arlequin ver. 3.0: an integrated software program for population genetic data analysis. Evol Bioinform Online 1:47–50PubMedGoogle Scholar
  13. Flannery B, Beacham T, Wetklo M, Smith C, Templin B, Antonovich A, Seeb L, Miller S, Schlei O, Wenburg JK (2006) Run timing, migratory patterns, and harvest information of Chinook salmon stocks within the Yukon River. Alaska Fisheries Technical Report No. 92, U.S. Fish and Wildlife Service.
  14. Foll M, Gaggiotti O (2006) Identifying the environmental factors that determine the genetic structure of populations. Genetics 174:875–891CrossRefPubMedGoogle Scholar
  15. Gagnon M, Angers B (2006) The determinant role of temporary proglacial drainages on the genetic structure of fishes. Mol Ecol 15:1051–1065CrossRefPubMedGoogle Scholar
  16. Gallant AL, Binnian EF, Omernik JM, Shasby MB (1995) Ecoregions of Alaska US Geological Survey Professional Paper 1567, 73 pp.
  17. Gharrett AJ, Shirley SM, Tromble GR (1987) Genetic relationships among populations of Alaskan chinook salmon (Oncorhynchus tshawytscha). Can J Fish Aquat Sci 44:765–774Google Scholar
  18. Goudet J (2001) FSTAT, a program to estimate and test gene diversities and fixation indices (version 2.9.3).
  19. Groot C, Margolis L (1991) Pacific salmon life histories. University of British Columbia Press, Vancouver, BCGoogle Scholar
  20. Gustafson RG, Winans GA (1999) Distribution and population genetic structure of river- and sea-type sockeye salmon in western North America. Ecol Freshw Fish 8:181–193CrossRefGoogle Scholar
  21. Hassol SJ, Berner J, Callaghan TV, Fox S, Furgal C, Hoel AH et al (2005) Arctic climate impact assessment. Cambridge University Press, Cambridge.
  22. Heginbottom JA, Brown J, Melnikov ES, Ferrians OJ Jr (1993) Circum-arctic map of permafrost and ground ice conditions. In: Proceedings of the sixth international conference on Permafrost, Wushan, vol 2. South China University Press, Guangzhou, China, pp 1132–1136.
  23. Hendry AP, Castric V, Kinnison MT, Quinn TP (2004) The evolution of philopatry and dispersal: homing versus straying in salmonids. In: Hendry AP, Stearns S (eds) Evolution illuminated: Salmon and their relatives. Oxford University Press, Oxford, pp 52–91Google Scholar
  24. Holderegger R, Wagner HH (2008) Landscape genetics. Bioscience 58:199–207CrossRefGoogle Scholar
  25. Jones SH, Fahl CB (1994) Magnitude and frequency of floods in Alaska and conterminous basins of Canada. US Geological Survey Water-Resources Investigations Report, 93-4197, 122 pp.
  26. Jørgensen HBH, Hansen MM, Bekkevold D, Ruzzante DE, Loeschcke V (2005) Marine landscapes and population genetic structure of herring (Clupea harengus L.) in the Baltic Sea. Mol Ecol 14:3219–3234CrossRefPubMedGoogle Scholar
  27. Kalinowski ST (2005) HP-RARE 1.0: a computer program for performing rarefaction on measures of allelic richness. Mol Ecol Notes 5:187–189CrossRefGoogle Scholar
  28. Kaufman DS, Manley WF (2004) Pleistocene maximum and late Wisconsin glacier extents across Alaska, U.S.A. In: Ehlers J, Gibbard PL (eds) Quarternary glaciations extent and chronology, part II: North America. Elsevier, Amsterdam, 440 ppGoogle Scholar
  29. Kittlein MJ, Gaggiotti OE (2008) Interactions between environmental factors can hide isolation by distance patterns: a case study of Ctenomys rionegrensis in Uruguay. Proc R Soc Lond B 275:2633–2638CrossRefGoogle Scholar
  30. L’Abáe-Lund JH, Vøllestad LA (1985) Homing precision of roach Rutilus rutilus in Lake Arungen, Norway. Environ Biol Fish 13:235–239CrossRefGoogle Scholar
  31. Lapointe M, Eaton B, Driscol S, Latulippe C (2000) Modeling the probability of salmonid egg pocket scour due to floods. Can J Fish Aquat Sci 57:1120–1130CrossRefGoogle Scholar
  32. Le Corre V, Kremer A (2003) Genetic variability at neutral markers, quantitative trait loci and trait in a subdivided population under selection. Genetics 164:1205–1219PubMedGoogle Scholar
  33. Lindsey CC, McPhail JD (1986) Zoogeography of fishes of the Yukon and Mackenzie basins. In: Hocutt CH, Wiley EO (eds) The zoogeography of North American freshwater fishes. Wiley, New York, pp 639–674Google Scholar
  34. MacLean R, Oswood MW, Irons JG, McDowell WH (1999) The effect of permafrost on stream biogeochemistry: a case study of two streams in the Alaskan (U.S.A.) taiga. Biogeochemistry 47:239–267CrossRefGoogle Scholar
  35. Manel S, Schwartz MK, Luikart G, Taberlet P (2003) Landscape genetics: combining landscape ecology and population genetics. TREE 18:189–197Google Scholar
  36. Manier MK, Arnold SJ (2006) Ecological correlates of population genetic structure: a comparative approach using a vertebrate metacommunity. Proc R Soc Lond B 273:3001–3009CrossRefGoogle Scholar
  37. Manni F, Guerard E, Heyer E (2004) Geographic patterns of (genetic, morphologic, linguistic) variation: how barriers can be detected by using Monmonier’s algorithm. Hum Biol 76:173–190CrossRefPubMedGoogle Scholar
  38. Marten A, Brändle M, Brandl R (2006) Habitat type predicts genetic population differentiation in freshwater invertebrates. Mol Ecol 15:2643–2651CrossRefPubMedGoogle Scholar
  39. Olsen JB, Flannery BG, Beacham TD, Bromaghin JF, Crane PA, Lean CF, Dunmall KM, Wenburg JK (2008) The influence of hydrographic structure and seasonal run timing on genetic diversity and isolation-by-distance in chum salmon (Oncorhynchus keta). Can J Fish Aquat Sci 65:2026–2042CrossRefGoogle Scholar
  40. Petren K, Grant PR, Grant BR, Keller L (2005) Comparative landscape genetics and the adaptive radiation of Darwin’s finches: the role of peripheral isolation. Mol Ecol 14:2943–2957CrossRefPubMedGoogle Scholar
  41. Primmer CR, Veselov AJ, Zubchenko A, Poututkin A, Bakhmet I, Koskinen MT (2006) Isolation by distance within a river system: genetic population structuring of Atlantic salmon, Salmo salar, in tributaries of the Varzuga River in northwest Russia. Mol Ecol 15:653–666CrossRefPubMedGoogle Scholar
  42. Quinn TP (2005) The behavior and ecology of Pacific salmon and trout. University of Washington Press, Seattle, WAGoogle Scholar
  43. Quinn T, Tallman R (1987) Seasonal environmental predictability and homing in riverine fishes. Environ Biol Fish 18:155–159CrossRefGoogle Scholar
  44. Rice WR (1989) Analyzing tables of statistical tests. Evolution 43:223–225CrossRefGoogle Scholar
  45. Rousset F (2008) Genepop’007: a complete re-implementation of the genepop software for Windows and Linux. Mol Ecol Res 8:103–106CrossRefGoogle Scholar
  46. Sandercock FK (1991) Life history of coho salmon. In: Groot C, Margolis L (eds) Pacific salmon life histories. University of British Columbia Press, Vancouver, BC, pp 392–446Google Scholar
  47. Seeb LW, Crane PA (1999) High genetic heterogeneity in chum salmon in western Alaska, the contact zone between northern and southern lineages. Trans Am Fish Soc 128:58–87CrossRefGoogle Scholar
  48. Seeb LW, Antonovich A, Banks MA, Beacham TD, Bellinger MR, Blankenship SM et al (2007) Development of a standardized DNA database for Chinook salmon. Fisheries 32:540–552CrossRefGoogle Scholar
  49. Short AEZ, Caterino MS (2009) On the validity of habitat as a predictor of genetic structure in aquatic systems: a comparative study using California water beetles. Mol Ecol 18:403–414CrossRefPubMedGoogle Scholar
  50. Smith CT, Nelson RJ, Wood CC, Koop BF (2001) Glacial biogeography of North American coho salmon (Oncorhynchus kisutch). Mol Ecol 10:2775–2785CrossRefPubMedGoogle Scholar
  51. Smouse PE, Long JC, Sokal RR (1986) Multiple regression and correlation extensions of the Mantel test matrix correspondence. Syst Zool 35:627–632CrossRefGoogle Scholar
  52. Storfer A, Murphy MA, Evans JS et al (2006) Putting the ‘landscape’ in landscape genetics. Heredity 98:128–142CrossRefPubMedGoogle Scholar
  53. Utter FM, McPhee MV, Allendorf FW (2009) Population genetics and the management of Arctic-Yukon-Kuskokwim salmon populations. In: Krueger CC, Zimmerman CE (eds) Pacific salmon: ecology and management of western Alaska’s populations. American Fisheries Society, Symposium 70, Bethesda, MD, pp 97–123Google Scholar
  54. Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38:1358–1370CrossRefGoogle Scholar
  55. Whiteley AR, Spruell P, Allendorf F (2004) Ecological and life history characteristics predict population genetic divergence of two salmonids in the same landscape. Mol Ecol 13:3675–3688CrossRefPubMedGoogle Scholar
  56. Wilmot RL, Everett RJ, Spearman WJ, Baccus R, Varnavskaya NV, Putivkin SV (1994) Genetic stock structure of Western Alaska chum salmon and a comparison with Russian far east stocks. Can J Fish Aquat Sci 51:84–94Google Scholar
  57. Wright S (1943) Isolation by distance. Genetics 28:114–138PubMedGoogle Scholar

Copyright information

© US Government 2010

Authors and Affiliations

  • Jeffrey B. Olsen
    • 1
  • Penelope A. Crane
    • 1
  • Blair G. Flannery
    • 1
  • Karen Dunmall
    • 2
  • William D. Templin
    • 3
  • John K. Wenburg
    • 1
  1. 1.Conservation Genetics LaboratoryU.S. Fish & Wildlife ServiceAnchorageUSA
  2. 2.Fisheries DepartmentKawerak, Inc.NomeUSA
  3. 3.Alaska Department of Fish and Game, Division of Commercial FisheriesGene Conservation LaboratoryAnchorageUSA

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