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Samples from subdivided populations yield biased estimates of effective size that overestimate the rate of loss of genetic variation.

Ryman N, Allendorf FW, Jorde PE, Laikre L, Hössjer O - Mol Ecol Resour (2013)

Bottom Line: Many empirical studies estimating effective population size apply the temporal method that provides an estimate of the variance effective size through the amount of temporal allele frequency change under the assumption that the study population is completely isolated.We studied how gene flow affects estimates of effective size obtained by the temporal method when sampling from a population system and provide analytical expressions for the expected estimate under an island model of migration.This phenomenon might partially explain the frequently reported unexpectedly low effective population sizes of marine populations that have raised concern regarding the genetic vulnerability of even exceptionally large populations.

View Article: PubMed Central - PubMed

Affiliation: Division of Population Genetics, Department of Zoology, Stockholm University, SE-106 91, Stockholm, Sweden.

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Simulated estimates of variance effective size when measuring allele frequency shifts over T = 1–10 generations and sampling the one and same (k = l = 1, top, a and b) or the same four (k = l = 4, bottom, c and d) subpopulations in population systems comprising s = 2, 10 or 500 subpopulations with migration rates m = 0.1 (left, a and c) and m = 1 (right, b and d). Within each panel, the curves are labelled with respect to s. The number of individuals sampled in each generation is n = 100 in (a) and (b), and n = 800 in c and d (cf. Fig.2). Note the different scales of the y-axes, and that four subpopulations cannot be sampled when s = 2 (bottom, c and d).
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fig03: Simulated estimates of variance effective size when measuring allele frequency shifts over T = 1–10 generations and sampling the one and same (k = l = 1, top, a and b) or the same four (k = l = 4, bottom, c and d) subpopulations in population systems comprising s = 2, 10 or 500 subpopulations with migration rates m = 0.1 (left, a and c) and m = 1 (right, b and d). Within each panel, the curves are labelled with respect to s. The number of individuals sampled in each generation is n = 100 in (a) and (b), and n = 800 in c and d (cf. Fig.2). Note the different scales of the y-axes, and that four subpopulations cannot be sampled when s = 2 (bottom, c and d).

Mentions: The dependence of on global effective size introduces a bias when estimating local effective size and measuring genetic change over multiple generations. Our analytical results on the expected estimate of NeV refer to estimates obtained when measuring allele frequency changes in consecutive generations, and we used computer simulations to assess the effect of estimating NeV from changes accumulated over multiple generations. Similar to Fig.2, we set local effective size to NeV = N = 50 and simulated the sampling of the same (k = l = 1) and the same four (k = l = 4) subpopulations T = 1–10 generations apart, mimicking different sizes of the global population by setting the total number of subpopulations to s = 2, 10, and 500 with migration rates m = 0.1 and m = 1 (Fig.3).


Samples from subdivided populations yield biased estimates of effective size that overestimate the rate of loss of genetic variation.

Ryman N, Allendorf FW, Jorde PE, Laikre L, Hössjer O - Mol Ecol Resour (2013)

Simulated estimates of variance effective size when measuring allele frequency shifts over T = 1–10 generations and sampling the one and same (k = l = 1, top, a and b) or the same four (k = l = 4, bottom, c and d) subpopulations in population systems comprising s = 2, 10 or 500 subpopulations with migration rates m = 0.1 (left, a and c) and m = 1 (right, b and d). Within each panel, the curves are labelled with respect to s. The number of individuals sampled in each generation is n = 100 in (a) and (b), and n = 800 in c and d (cf. Fig.2). Note the different scales of the y-axes, and that four subpopulations cannot be sampled when s = 2 (bottom, c and d).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
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getmorefigures.php?uid=PMC4274017&req=5

fig03: Simulated estimates of variance effective size when measuring allele frequency shifts over T = 1–10 generations and sampling the one and same (k = l = 1, top, a and b) or the same four (k = l = 4, bottom, c and d) subpopulations in population systems comprising s = 2, 10 or 500 subpopulations with migration rates m = 0.1 (left, a and c) and m = 1 (right, b and d). Within each panel, the curves are labelled with respect to s. The number of individuals sampled in each generation is n = 100 in (a) and (b), and n = 800 in c and d (cf. Fig.2). Note the different scales of the y-axes, and that four subpopulations cannot be sampled when s = 2 (bottom, c and d).
Mentions: The dependence of on global effective size introduces a bias when estimating local effective size and measuring genetic change over multiple generations. Our analytical results on the expected estimate of NeV refer to estimates obtained when measuring allele frequency changes in consecutive generations, and we used computer simulations to assess the effect of estimating NeV from changes accumulated over multiple generations. Similar to Fig.2, we set local effective size to NeV = N = 50 and simulated the sampling of the same (k = l = 1) and the same four (k = l = 4) subpopulations T = 1–10 generations apart, mimicking different sizes of the global population by setting the total number of subpopulations to s = 2, 10, and 500 with migration rates m = 0.1 and m = 1 (Fig.3).

Bottom Line: Many empirical studies estimating effective population size apply the temporal method that provides an estimate of the variance effective size through the amount of temporal allele frequency change under the assumption that the study population is completely isolated.We studied how gene flow affects estimates of effective size obtained by the temporal method when sampling from a population system and provide analytical expressions for the expected estimate under an island model of migration.This phenomenon might partially explain the frequently reported unexpectedly low effective population sizes of marine populations that have raised concern regarding the genetic vulnerability of even exceptionally large populations.

View Article: PubMed Central - PubMed

Affiliation: Division of Population Genetics, Department of Zoology, Stockholm University, SE-106 91, Stockholm, Sweden.

Show MeSH