The K = 2 conundrum |
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Authors: | Jasmine K. Janes Joshua M. Miller Julian R. Dupuis René M. Malenfant Jamieson C. Gorrell Catherine I. Cullingham Rose L. Andrew |
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Affiliation: | 1. School of Environmental and Rural Sciences, The University of New England, Armidale, NSW, Australia;2. Biology Department, Vancouver Island University, Nanaimo, BC, Canada;3. Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA;4. Department of Plant and Environmental Protection Sciences, University of Hawai'i at M?noa, Honolulu, HI, USA;5. Department of Biology, University of New Brunswick, Fredericton, NB, Canada;6. Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada |
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Abstract: | Assessments of population genetic structure have become an increasing focus as they can provide valuable insight into patterns of migration and gene flow. structure , the most highly cited of several clustering‐based methods, was developed to provide robust estimates without the need for populations to be determined a priori. structure introduces the problem of selecting the optimal number of clusters, and as a result, the ΔK method was proposed to assist in the identification of the “true” number of clusters. In our review of 1,264 studies using structure to explore population subdivision, studies that used ΔK were more likely to identify K = 2 (54%, 443/822) than studies that did not use ΔK (21%, 82/386). A troubling finding was that very few studies performed the hierarchical analysis recommended by the authors of both ΔK and structure to fully explore population subdivision. Furthermore, extensions of earlier simulations indicate that, with a representative number of markers, ΔK frequently identifies K = 2 as the top level of hierarchical structure, even when more subpopulations are present. This review suggests that many studies may have been over‐ or underestimating population genetic structure; both scenarios have serious consequences, particularly with respect to conservation and management. We recommend publication standards for population structure results so that readers can assess the implications of the results given their own understanding of the species biology. |
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Keywords: | clustering methods conservation delta K management optimal K population genetic structure |
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