4.3 Article

Indirect Estimates of Natal Dispersal Distance from Genetic Data in a Stream-Dwelling Fish (Mogurnda adspersa)

Journal

JOURNAL OF HEREDITY
Volume 104, Issue 6, Pages 779-790

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/jhered/est055

Keywords

BAPS; effective density; isolation by distance; kMeans; Mogurnda adspersa; natal dispersal; SAMOVA

Funding

  1. Griffith School of Environment
  2. Australian Rivers Institute, Griffith University

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Recent work has highlighted the need to account for hierarchical patterns of genetic structure when estimating evolutionary and ecological parameters of interest. This caution is particularly relevant to studies of riverine organisms, where hierarchical structure appears to be commonplace. Here, we indirectly estimate dispersal distance in a hierarchically structured freshwater fish, Mogurnda adspersa. Microsatellite and mitochondrial DNA (mtDNA) data were obtained for 443 individuals across 27 sites separated by an average of 1.3 km within creeks of southeastern Queensland, Australia. Significant genetic structure was found among sites (mtDNA (ST) 0.508; microsatellite F-ST 0.225, F-ST 0.340). Various clustering methods produced congruent patterns of hierarchical structure reflecting stream architecture. Partial mantel tests identified contiguous sets of sample sites where isolation by distance (IBD) explained F-ST variation without significant contribution of hierarchical structure. Analysis of mean natal dispersal distance () within sets of IBD-linked sample sites suggested most dispersal occurs over less than 1 km, and the average effective density (D-e) was estimated at 11.5 individuals km(1); indicating sedentary behavior and small effective population size are responsible for the remarkable patterns of genetic structure observed. Our results demonstrate that Roussets regression-based method is applicable to estimating the scale of dispersal in riverine organisms and that identifying contiguous populations that satisfy the assumptions of this model is achievable with genetic clustering methods and partial correlations.

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