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Assessing conservation risks to populations of an anadromous Arctic salmonid, the northern Dolly Varden (Salvelinus malma malma), via estimates of effective and census population sizes and approximate Bayesian computation | SpringerLink

Conservation Genetics

, Volume 18, Issue 2, pp 393–410 | Cite as

Assessing conservation risks to populations of an anadromous Arctic salmonid, the northern Dolly Varden (Salvelinus malma malma), via estimates of effective and census population sizes and approximate Bayesian computation

  • Les N. Harris
  • Friso P. Palstra
  • Robert Bajno
  • Colin P. Gallagher
  • Kimberly L. Howland
  • Eric B. Taylor
  • James D. Reist
Research Article


Census population size (Nc) is crucial to the development of resource management strategies, however, monitoring the effective population size (Ne) of managed populations has proliferated because of this parameter’s relationship to the short-term impacts of genetic stochasticity and long-term population viability. Thus, having a sound understanding of both Nc and Ne, including population connectivity, provides valuable insights into both the demographic and genetic risks to extinction. Here, we assessed microsatellite DNA variation in four (of five known) anadromous northern Dolly Varden (NDV, Salvelinus malma malma) populations from Canada’s western Arctic region, to estimate Ne using both temporal-based and single-sample estimators and to test for associations between Ne and Nc. We also employed approximate Bayesian computation (ABC) to evaluate several evolutionary scenarios that have potentially shaped contemporary population structure in this species, focusing particularly on population size and connectivity. We found evidence for moderate to large contemporary and historical Ne, suggesting that short- and long-term extinction risks are low for these populations. Estimates of contemporary and long-term Ne were variable within and among populations and overall estimates could not be reliably linked with Nc or available spawning habitat. The overall estimate of Ne/Nc, was 0.152 and ranged from 0.024 to 0.442 when including errors around the estimate of Ne and Nc. Finally, ABC analyses suggest that NDV had a common origin followed by divergence in isolation while maintaining large effective sizes, but also that these populations were bottlenecked in the past, likely the result of post-glacial colonization processes. These results corroborate indications of limited gene flow at present, indicating independent demographic and evolutionary trajectories that imply NDV is best managed on a per-river-population basis. Overall, the results of this study further our general understanding of Ne, Ne/Nc and demographic independence in NDV, and provide a comprehensive and quantitative assessment of the potential genetic and demographic risk status of Arctic anadromous salmonids, including baselines for future monitoring.


Effective population size Census population size Northern Dolly Varden Approximate Bayesian computation Conservation 

Supplementary material

10592_2016_915_MOESM1_ESM.docx (1.5 mb)
Supplementary material 1 (DOCX 1561 kb)


  1. Allendorf FW, Luikart GH, Aitken SN (2013) Conservation and the genetics of populations. Wiley, HobokenGoogle Scholar
  2. Beaumont MA (2003) Estimation of population growth or decline in genetically monitored populations. Genetics 164:1139–1160PubMedPubMedCentralGoogle Scholar
  3. Beaumont MA, Zhang W, Balding DJ (2002) Approximate Bayesian computation in population genetics. Genetics 162:2025–2035PubMedPubMedCentralGoogle Scholar
  4. Belmar-Lucero S, Wood JL, Scott S et al (2012) Concurrent habitat and life history influences on effective/census population size ratios in stream-dwelling trout. Ecol Evol 2:562–573PubMedPubMedCentralCrossRefGoogle Scholar
  5. Bernos TA, Fraser DJ (2016) Spatiotemporal relationship between adult census size and genetic population size across a wide population size gradient. Mol Ecol 25:4472–4487PubMedCrossRefGoogle Scholar
  6. Bertorelle G, Benazzo A, Mona S (2010) ABC as a flexible framework to estimate demography over space and time: some cons, many pros. Mol Ecol 19:2609–2625PubMedCrossRefGoogle Scholar
  7. Blum MG, François O (2010) Non-linear regression models for approximate Bayesian computation. Stat Comput 20:63–73CrossRefGoogle Scholar
  8. Caballero A (1994) Developments in the prediction of effective population size. Heredity 73:657–679PubMedCrossRefGoogle Scholar
  9. Cavalli-Sforza Ll, Edwards AWF (1967) Phylogentic analysis models and estimation procedures. Am J Hum Genet 19:233–257PubMedPubMedCentralGoogle Scholar
  10. Charlier J, Palmé A, Laikre L, Andersson J, Ryman N (2011) Census (NC) and genetically effective (Ne) population size in a lake-resident population of brown trout Salmo trutta. J Fish Biol 79:2074–2082PubMedCrossRefGoogle Scholar
  11. Consuegra S, Verspoor E, Knox D, de Leaniz CG (2005) Asymmetric gene flow and the evolutionary maintenance of genetic diversity in small, peripheral Atlantic salmon populations. Conserv Genet 6:823–842CrossRefGoogle Scholar
  12. Cook J, Brochmann C, Talbot S (2013) Genetic perspectives on Arctic biodiversity. In: Meltofte H et al (eds) Arctic biodiversity assessment. Status and trends in Arctic biodiversity. Conservation of Arctic Flora and Fauna, Akureyri, pp 459–483Google Scholar
  13. COSEWIC (2010) COSEWIC assessment and status report on the Dolly Varden Salvelinus malma malma (Western Arctic populations) in Canada. Committee on the Status of Endangered Wildlife in Canada. Ottawa. p x + 65. (
  14. Crow JF, Kimura M (1970) An introduction to population genetics theory. Harper & Row, New YorkGoogle Scholar
  15. Csillery K, Francois O, Blum MGB (2012) Abc: an R package for approximate Bayesian computation (ABC). Method Ecol Evol 3:475–479CrossRefGoogle Scholar
  16. Csillery K, Blum MG, Gaggiotti OE, François O (2010) Approximate Bayesian computation (ABC) in practice. Trends Ecol Evol 25:410–418PubMedCrossRefGoogle Scholar
  17. Depaulis F, Mousset S, Veuille M (2003) Power of neutrality tests to detect bottlenecks and hitchhiking. J Mol Evol 5:S190–S200CrossRefGoogle Scholar
  18. DFO (2003) Big fish river Dolly Varden. DFO Science Stock Status Report D5—60 (2002)Google Scholar
  19. Do C, Waples RS, Peel P, Macbeth GM, Tillett BJ, Ovenden JR (2014) NEESTIMATOR v2: re-implementation of software for the estimation of contemporary effective population size (N e) from genetic data. Mol Ecol Res 14(1):209–214CrossRefGoogle Scholar
  20. Estoup A, Jarne P, Cornuet JM (2002) Homoplasy and mutation at microsatellite loci and their consequences for population genetic analysis. Mol Ecol 11:1591–1604PubMedCrossRefGoogle Scholar
  21. Excoffier L, Laval G, Schneider S (2005) Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evol Bioinform 1:47–50Google Scholar
  22. Excoffier L, Foll M (2011) Fastsimcoal: a continuous-time coalescent simulator of genomic diversity under arbitrarily complex evolutionary scenarios. Bioinformatics 27(9):1332–1334PubMedCrossRefGoogle Scholar
  23. Felsenstein J (2009) PHYLIP (Phylogeny Inference Package) version 3.6.9. Distributed by the author. Department of Genome Sciences, University of Washington, SeattleGoogle Scholar
  24. Fontaine MC, Roland K, Calves I et al (2014) Postglacial climate changes and rise of three ecotypes of harbour porpoises, Phocoena phocoena, in western Palearctic waters. Mol Ecol 23:3306–3321PubMedCrossRefGoogle Scholar
  25. Frankham R (1995) Effective population size/adult population size ratios in wildlife: a review. Genet Res 66:95–107CrossRefGoogle Scholar
  26. Frankham R (1996) Relationship of genetic variation to population size in wildlife. Conserv Biol 10:1500–1508CrossRefGoogle Scholar
  27. Franklin IR (1980) Evolutionary change in small populations. Conservation biology: an evolutionary-ecological perspective. Sinauer Associates, Sunderland, MA, pp 135–149Google Scholar
  28. Franklin I, Frankham R (1998) How large must populations be to retain evolutionary potential? Anim Conserv 1:69–70CrossRefGoogle Scholar
  29. Fraser DJ, Hansen MM, Ostergaard S et al (2007) Comparative estimation of effective population sizes and temporal gene flow in two contrasting population systems. Mol Ecol 16:3866–3889PubMedCrossRefGoogle Scholar
  30. Fraser DJ, Calvert AM, Bernatchez L, Coon A (2013) Multidisciplinary population monitoring when demographic data are sparse: a case study of remote trout populations. Ecol Evol 3:4954–4969PubMedPubMedCentralCrossRefGoogle Scholar
  31. Gallagher CP, Howland KL, Harris LN, Bajno R, Sandstrom S, Loewen T, Reist J (2013) Dolly Varden (Salvelinus malma malma) from the Big Fish River: abundance estimates, effective population size, biological characteristics, and contribution to the coastal mixed-stock fishery. DFO Can Sci Advis Sec Res Doc 2013/059. p v + 46Google Scholar
  32. Gallagher CP, Roux M-J, Howland KL, Tallman, RF (2012) Synthesis of biological and harvest information used to assess populations of northern form Dolly Varden (Salvelinus malma malma) in Canada. Part III: Comparison among populations. DFO Can Sci Advis Sec Res. Doc 2011/128. p vi + 81Google Scholar
  33. Garza J, Williamson E (2001) Detection of reduction in population size using data from microsatellite loci. Mol Ecol 10:305–318PubMedCrossRefGoogle Scholar
  34. Goldstein DB, Linares AR, Cavilla-Sforza LL, Feldman MW (1995) An evaluation of genetic distances for use with microsatellites. Genetics 139:463–471PubMedPubMedCentralGoogle Scholar
  35. Goudet J (2002) FSTAT: a program to estimate and test gene diversities and fixation indices [online]. Version Available from
  36. Hansen MM, Ruzzante DE, Nielsen EE, Bekkevold D, Mensberg KLD (2002) Long-term effective population sizes, temporal stability of genetic composition and potential for local adaptation in anadromous brown trout (Salmo trutta) populations. Mol Ecol 11:2523–2535PubMedCrossRefGoogle Scholar
  37. Hansen MM, Limborg MT, Ferchaud A-L, Pujolar J-M (2014) The effects of Medieval dams on genetic divergence and demographic history in brown trout populations. BMC Evol Biol 14:122PubMedPubMedCentralCrossRefGoogle Scholar
  38. Hare M, Nunney L, Schwartz MK, Ruzzante DE, Burford M, Waples RS, Ruegg K, Palstra FP (2011) Understanding and estimating effective population size for practical application in marine conservation and management. Conserv Biol 25(3):438–439PubMedCrossRefGoogle Scholar
  39. Harris LN, Taylor EB, Tallman RF, Reist JD (2012) Gene flow and effective population size in two life-history types of broad whitefish Coregonus nasus from the Canadian Arctic. J Fish Biol 81:288–307PubMedCrossRefGoogle Scholar
  40. Harris LN, Moore J-S, Galpern P, Tallman R, Taylor E (2014) Geographic influences on fine-scale, hierarchical population structure in northern Canadian populations of anadromous Arctic Char (Salvelinus alpinus). Environ Biol Fish 97:1233–1252CrossRefGoogle Scholar
  41. Harris LN, Bajno R, Gallagher CP et al (2015) Life-history characteristics and landscape attributes as drivers of genetic variation, gene flow, and fine-scale population structure in northern Dolly Varden (Salvelinus malma malma) in Canada. Can J Fish Aquat Sci 72:1477–1493CrossRefGoogle Scholar
  42. Heath DD, Busch C, Kelly J, Atagi DY (2002) Temporal change in genetic structure and effective population size in steelhead trout (Oncorhynchus mykiss). Mol Ecol 11:197–214PubMedCrossRefGoogle Scholar
  43. Hedrick PW, Rashbrook VK, Hedgecock D (2000) Effective population size of winter-run chinook salmon based on microsatellite analysis of returning spawners. Can J Fish Aquat Sci 57:2368–2373CrossRefGoogle Scholar
  44. Hill WG (1981) Estimation of effective population size from data on linkage disequilibrium. Genet Res 38:209–216CrossRefGoogle Scholar
  45. Holderegger R, Kamm U, Gugerli F (2006) Adaptive vs. neutral genetic diversity: implications for landscape genetics. Landsc Ecol 21:797–807CrossRefGoogle Scholar
  46. Howland K, Mochnacz N, Gallagher C, Tallman R, Ghamry H, Roux M-J, Sandstrom S, Reist J (2012) Developing strategies for improved assessment and ecosystem-based management of Canadian Northern Dolly Varden. In: Browman HI, Cochrane KL, Evans D, Jamieson GS, Livingston PA, Woodby D, Zhang CI (eds) Global progress in ecosystem-based fisheries management. Alaska Sea Grant, University of Alaska Fairbanks, Fairbanks. doi:10.4027/gpebfm.2012.09 Google Scholar
  47. Hsieh, C-H, Reiss CS, Hunter JR et al (2006) Fishing elevates variability in the abundance of exploited species. Nature 443:859–862PubMedCrossRefGoogle Scholar
  48. Jamieson IG, Allendorf FWA et al (2013) A school of red herring: reply to Frankham et al. Trends Ecol Evol 28:188–189PubMedCrossRefGoogle Scholar
  49. Johnstone DL, O’Connell MF, Palstra FP, Ruzzante DE (2013) Mature male parr contribution to the effective size of an anadromous Atlantic salmon (Salmo salar) population over 30 years. Mol Ecol 22:2394–2407PubMedCrossRefGoogle Scholar
  50. Jones OR, Wang J (2010) COLONY: a program for parentage and sibship inference from multilocus genotype data. Mol Ecol Res 10:551–555CrossRefGoogle Scholar
  51. Jorde PE, Ryman N (2007) Unbiased estimator for genetic drift and effective population size. Genetics 177:927–935PubMedPubMedCentralCrossRefGoogle Scholar
  52. 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
  53. Kalinowski ST, Waples RS (2002) Relationship of effective to census size in fluctuating populations. Conserv Biol 16:129–136CrossRefGoogle Scholar
  54. Kamath PL, Haroldson MA, Luikart G, Paetkau D, Whitman C, Manen FT (2015) Multiple estimates of effective population size for monitoring a long-lived vertebrate: an application to Yellowstone grizzly bears. Mol Ecol 24:5507–5521PubMedCrossRefGoogle Scholar
  55. Kimura M, Weiss GH (1964) The stepping stone model of population structure and the decrease of genetic correlation with distance. Genetics 49:561–576PubMedPubMedCentralGoogle Scholar
  56. Kristofferson AH, Wiswar D, Lemieux P, Marshall D, Blouw A, Hemming C, Antoniuk G, Archie W (1991) Joint Canada-USA field survey of the charr (Salvelinus) resources of the Firth River, Yukon Territory and Alaska, 1989. Can Data Rep Fish Aquat Sci 861:21Google Scholar
  57. Krueger CC, Wilmot RL, Everett RJ (1999) Stock origins of Dolly Varden collected from Beaufort Sea coastal sites of Arctic Alaska and Canada. Trans Am Fish Soc 12:49–57CrossRefGoogle Scholar
  58. Lande R (1988) Genetics and demography in biological conservation. Science 241:1455–1460PubMedCrossRefGoogle Scholar
  59. Lauck T, Clark CW, Mangel M, Munro GR (1998) Implementing the precautionary principle in fisheries management through marine reserves. Ecol App 8:S72–S78CrossRefGoogle Scholar
  60. Leberg P (2005) Genetic approaches for estimating the effective size of populations. J Wildl Manag 69:1385–1399CrossRefGoogle Scholar
  61. Lindsay 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
  62. Lohmueller KE, Bustamante CD, Clark AG (2010) The effect of recent admixture on inference of ancient human population history. Genetics 185:611–622PubMedPubMedCentralCrossRefGoogle Scholar
  63. Luikart G, Ryman N, Tallmon DA, Schwartz MK, Allendorf FW (2010) Estimation of census and effective population sizes: the increasing usefulness of DNA-based approaches. Conserv Genet 11:355–373CrossRefGoogle Scholar
  64. Lynch M, Lande R (1998) The critical effective size for a genetically secure population. Anim Conserv 1:70–72CrossRefGoogle Scholar
  65. Mochnacz NJ, Schroeder BS, Sawatzky CD, Reist JD (2010) Assessment of northern Dolly Varden, Salvelinus malma malma (Walbaum, 1792), habitat in Canada. Can Manuscr Rep Fish Aquat Sci 2926:vi + 48Google Scholar
  66. Moore J-S, Harris LN, Tallman RF, Taylor EB (2013) The interplay between dispersal and gene flow in anadromous Arctic char (Salvelinus alpinus): implications for potential for local adaptation. Can J Fish Aquat Sci 70:1327–1338CrossRefGoogle Scholar
  67. Mousset S, Derome N, Veuille M (2004) A test of neutrality and constant population size based on the mismatch distribution. Mol Biol Evol 2:724–731CrossRefGoogle Scholar
  68. Musick JA (1999) Criteria to define extinction risk in marine fishes: the American Fisheries Society initiative. Fisheries 24:6–14CrossRefGoogle Scholar
  69. Narum SR (2006) Beyond Bonferroni: less conservative analyses for conservation genetics. Conserv Genet 7(5):783–787CrossRefGoogle Scholar
  70. Neel MC, McKelvey K, Ryman N et al (2013) Estimation of effective population size in continuously distributed populations: there goes the neighborhood. Heredity 111:189–199PubMedPubMedCentralCrossRefGoogle Scholar
  71. Nei M (1987) Molecular evolutionary genetics. Columbia University Press, New YorkGoogle Scholar
  72. Nunney L, Elam DR (1994) Estimating the effective population size of conserved populations. Conserv Biol 8:175–184CrossRefGoogle Scholar
  73. Olafsson K, Pampoulie C, Hjorleifsdottir S, Gudjonsson S, Hreggvidsson GO (2014) Present-day genetic structure of Atlantic Salmon (Salmo salar) in Icelandic rivers and ice-cap retreat models. PLoS ONE 9(2):e86809PubMedPubMedCentralCrossRefGoogle Scholar
  74. Oleinik A, Skurikhina L, Bondar E, Brykov V (2013) Phylogeography of northern Dolly Varden Salvelinus malma (Salmoniformes: Salmonidae) from Asia and North America: An analysis based on the mitochondrial DNA genealogy. J Ichthyol 53:820–832CrossRefGoogle Scholar
  75. Palstra FP, Fraser DJ (2012) Effective/census population size ratio estimation: a compendium and appraisal. Ecol Evol 2:2357–2365PubMedPubMedCentralCrossRefGoogle Scholar
  76. Palstra FP, O’Connell, MF, Ruzzante DE (2007) Population structure and gene flow reversals in Atlantic salmon (Salmo salar) over contemporary and long-term temporal scales: effects of population size and life history. Mol Ecol 16(21):4504–4522PubMedCrossRefGoogle Scholar
  77. Palstra FP, Ruzzante DE (2008) Genetic estimates of contemporary effective population size: what can they tell us about the importance of genetic stochasticity for wild population persistence? Mol Ecol 17:3428–3447PubMedCrossRefGoogle Scholar
  78. Palstra F, Ruzzante DE (2011) Demographic and genetic factors shaping contemporary metapopulation effective size and its empirical estimation in salmonid fish. Heredity 107:444–455PubMedPubMedCentralCrossRefGoogle Scholar
  79. Palstra FP, O’Connell MF, Ruzzante DE (2009) Age structure, changing demography and effective population size in Atlantic Salmon (Salmo salar). Genetics 182:1233–1249PubMedPubMedCentralCrossRefGoogle Scholar
  80. Pauls SU, Nowak C, Bálint M, Pfenninger M (2013) The impact of global climate change on genetic diversity within populations and species. Mol Ecol 22:925–946PubMedCrossRefGoogle Scholar
  81. Perrier C, Normandeau E, Dionne M, Bernatchez L (2014) Alternative reproductive tactics increase effective population size and decrease inbreeding in wild Atlantic salmon. Evol App 7:1094–1106CrossRefGoogle Scholar
  82. Poesch MS, Chavarie L, Chu C, Pandit SN, Tonn WM (2016) Climate change impacts on freshwater fishes: a Canadian perspective. Fisheries 41(7):385–391CrossRefGoogle Scholar
  83. R Core Team (2013) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna.
  84. Rambaut A (2009) FigTree v1. 3.1: Tree Fig. drawing tool. FigTree website Google Scholar
  85. Reist JD, Wrona FJ, Prowse TD et al (2006a) General effects of climate change on Arctic fishes and fish populations. Ambio 35:370–380PubMedCrossRefGoogle Scholar
  86. Reist JD, Wrona FJ, Prowse TD et al (2006b) An overview of effects of climate change on selected Arctic freshwater and anadromous fishes. Ambio 35:381–387PubMedCrossRefGoogle Scholar
  87. Robert CP, Cornuet J-M, Marin J-M, Pillai NS (2011) Lack of confidence in approximate Bayesian computation model choice. Proc Natl Acad Sci 10:15112–15117CrossRefGoogle Scholar
  88. Rousset F (2008) GENEPOP’ 007: a complete re-implementation of the GENEPOP software for Windows and Linux. Mol Ecol Resour 8:103–106PubMedCrossRefGoogle Scholar
  89. Sandstrom S, Harwood L, Howland K (2009) Status of anadromous Dolly Varden char (Salvelinus malma) of the Rat River, Northwest Territories, as assessed through mark-recapture and live-sampling at the spawning and overwintering site (1995–2007). Can Tech Rep Fish Aquat Sci 2842:23Google Scholar
  90. Saura M, Caballero A, Caballero P, Moran P (2008) Impact of precocious male parr on the effective size of a wild population of Atlantic salmon. Freshw Biol 53(12):2375–2384CrossRefGoogle Scholar
  91. Schwartz MK, Luikart G, Waples RS (2007) Genetic monitoring as a promising tool for conservation and management. Trends Ecol Evol 22:25–33PubMedCrossRefGoogle Scholar
  92. Seber GAF (1982) The estimation of animal abundance and related parameters, 2nd edn. London, Edward ArnoldGoogle Scholar
  93. Sherwin W, Moritz C (2000) Managing andmonitoring genetic erosion. In: Young AG, Clarke GM (eds) Genetics, demography and viability of fragmented populations. Cambridge University Press, Cambridge, pp 9–34CrossRefGoogle Scholar
  94. Shrimpton JM, Heath DD (2003) Census vs. effective population size in chinook salmon: large-and small-scale environmental perturbation effects. Mol Ecol 12:2571–2583PubMedCrossRefGoogle Scholar
  95. Smith TB, Kark S, Schneider CJ, Wayne RK, Moritz C (2001) Biodiversity hotspots and beyond: the need for preserving environmental transitions. Trends Ecol Evol 16:431CrossRefGoogle Scholar
  96. Soulé ME (1980) Thresholds for survival: maintaining fitness and evolutionary potential. Conserv Biol 111:124Google Scholar
  97. Stockwell CA, Heilveil JS, Purcell K (2013) Estimating divergence time for two evolutionarily significant units of a protected fish species. Conserv Genet 14:215–222CrossRefGoogle Scholar
  98. Tallman R, Zhu X, Janjua Y et al (2013) Data limited assessment of selected North American anadromous charr stocks. J Ichthyol 53:867–874CrossRefGoogle Scholar
  99. Tallmon DA, Luikart G, Waples RS (2004) The alluring simplicity and complex reality of genetic rescue. Trends Ecol Evol 19:489–496PubMedCrossRefGoogle Scholar
  100. Tallmon DA, Koyuk A, Luikart G, Beaumont MA (2008) ONeSAMP: a program to estimate effective population size using approximate Bayesian computation. Mol Ecol Res 8:299–301CrossRefGoogle Scholar
  101. Taylor EB, May-McNally SL (2015) Genetic analysis of Dolly Varden (Salvelinus malma) across its North American range: evidence for a contact zone in southcentral Alaska. Can J Fish Aquat Sci 72:1048–1057CrossRefGoogle Scholar
  102. Templeton AR (1994) Biodiversity at the molecular-genetic level—experiences from disparate macroorganisms. Philos Trans R Soc B 345:59–64CrossRefGoogle Scholar
  103. Thrall PH, Richards CM, McCauley DE, Antonovics J (1998) Metapopulation collapse: the consequences of limited gene flow in spatially structured populations. In: Bascompte J, Sole RV (eds) Modeling Spatiotemporal Dynamics in Ecology. Academic Press, San Diego, pp 83–104Google Scholar
  104. Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes 4(3):535–538CrossRefGoogle Scholar
  105. Wang J (2001) A pseudo-likelihood method for estimating effective population size from temporally spaced samples. Genet Res 78:243–257PubMedCrossRefGoogle Scholar
  106. Wang J (2005) Estimation of effective population sizes from data on genetic markers. Philos Trans R Soc B 360:1395–1409CrossRefGoogle Scholar
  107. Wang J, Whitlock MC (2003) Estimating effective population size and migration rates from genetic samples over space and time. Genetics 163:429–446PubMedPubMedCentralGoogle Scholar
  108. Waples RS (1989) A generalized approach for estimating effective population size from temporal changes in allele frequency. Genetics 121:379–391PubMedPubMedCentralGoogle Scholar
  109. Waples RS (2004) Salmonid insights into effective population size. In: Hendry A, Stearns S (eds) Evolution Illuminated: salmon and their relatives. Oxford University Press, New York, pp 295–314Google Scholar
  110. Waples RS (2005) Genetic estimates of contemporary effective population size: to what time periods do the estimates apply? Mol Ecol 14:3335–3352PubMedCrossRefGoogle Scholar
  111. Waples RS (2006) A bias correction for estimates of effective population size based on linkage disequilibrium at unlinked gene loci. Conserv Genet 7:167–184CrossRefGoogle Scholar
  112. Waples RS (2010) Spatial-temporal stratifications in natural populations and how they affect understanding and estimation of effective population size. Mol Ecol Res 10:785–796CrossRefGoogle Scholar
  113. Waples RS (2016) Making sense of genetic estimates of effective population size. Mol Ecol 25:4689–4691PubMedCrossRefGoogle Scholar
  114. Waples RS, Do C (2008) LDNE: a program for estimating effective population size from data on linkage disequilibrium. Mol Ecol Res 8:753–756CrossRefGoogle Scholar
  115. Waples RS, Do C (2010) Linkage disequilibrium estimates of contemporary Ne using highly variable genetic markers: a largely untapped resource for applied conservation and evolution. Ecol Appl 3:244–262Google Scholar
  116. Waples RS, Yokota M (2007) Temporal estimates of effective population size in species with overlapping generations. Genetics 175:219–233PubMedPubMedCentralCrossRefGoogle Scholar
  117. Waples RS, Luikart G, Faulkner JR, Tallmon DA (2013) Simple life history traits explain key effective population size ratios across diverse taxa. Proc R Soc Lond Ser B 280(1768):1339CrossRefGoogle Scholar
  118. Waples RS, Antao T, Luikart G (2014) Effects of overlapping generations on linkage disequilibrium estimates of effective population size. Genetics 197:769–780PubMedPubMedCentralCrossRefGoogle Scholar
  119. Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38:1358–1370CrossRefGoogle Scholar
  120. Whiteley AR, Fitzpatrick SW, Funk WC, Tallmon DA (2015) Genetic rescue to the rescue. Trends Ecol Evol 30:42–49PubMedCrossRefGoogle Scholar
  121. Willi Y, Van Buskirk J, Hoffmann AA (2006) Limits to the adaptive potential of small populations. Ann Rev Ecol Evol Syst 37:433–458CrossRefGoogle Scholar
  122. Wollebæk J, Heggenes J, Røed KH (2011) Population connectivity: dam migration mitigations and contemporary site fidelity in Arctic char. BMC Evol Biol 11:207PubMedPubMedCentralCrossRefGoogle Scholar
  123. Wright S (1931) Evolution in mendelian populations. Genetics 16:97–159PubMedPubMedCentralGoogle Scholar
  124. Wright S (1938) Size of population and breeding structure in relation to evolution. Science 87(2263):430–431Google Scholar
  125. Wright S (1969) Evolution and the genetics of populations: vol. 2. The theory of gene frequencies. University of Chicago Press, ChicagoGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Les N. Harris
    • 1
  • Friso P. Palstra
    • 2
  • Robert Bajno
    • 1
  • Colin P. Gallagher
    • 1
  • Kimberly L. Howland
    • 1
  • Eric B. Taylor
    • 3
  • James D. Reist
    • 1
  1. 1.Fisheries and Oceans CanadaWinnipegCanada
  2. 2.CNRS UMR 7206 Eco-anthropologie et Ethnobiologie, Equipe “Génétique des populations humaines”Muséum National d’Histoire NaturelleParis Cedex 05France
  3. 3.Department of Zoology, Biodiversity Research Centre and Beaty Biodiversity MuseumUniversity of British ColumbiaVancouverCanada

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