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Confidently identifying the correct K value using the ΔK method: When does K = 2?
Cullingham, Catherine I; Miller, Joshua M; Peery, Rhiannon M; Dupuis, Julian R; Malenfant, René M; Gorrell, Jamieson C; Janes, Jasmine K.
Affiliation
  • Cullingham CI; Department of Biology, Carleton University, Ottawa, ON, Canada.
  • Miller JM; Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada.
  • Peery RM; Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada.
  • Dupuis JR; Department of Entomology, University of Kentucky, Lexington, KY, USA.
  • Malenfant RM; Department of Biology, University of New Brunswick, Fredericton, NB, Canada.
  • Gorrell JC; Biology Department, Vancouver Island University, Nanaimo, BC, Canada.
  • Janes JK; Biology Department, Vancouver Island University, Nanaimo, BC, Canada.
Mol Ecol ; 29(5): 862-869, 2020 03.
Article in En | MEDLINE | ID: mdl-32034821
ABSTRACT
Populations delineated based on genetic data are commonly used for wildlife conservation and management. Many studies use the program structure combined with the ΔK method to identify the most probable number of populations (K). We recently found K = 2 was identified more often when studies used ΔK compared to studies that did not. We suggested two reasons for this hierarchical population structure leads to underestimation, or the ΔK method does not evaluate K = 1 causing an overestimation. The present contribution aims to develop a better understanding of the limits of the method using one, two and three population simulations across migration scenarios. From these simulations we identified the "best K" using model likelihood and ΔK. Our findings show that mean probability plots and ΔK are unable to resolve the correct number of populations once migration rate exceeds 0.005. We also found a strong bias towards selecting K = 2 using the ΔK method. We used these data to identify the range of values where the ΔK statistic identifies a value of K that is not well supported. Finally, using the simulations and a review of empirical data, we found that the magnitude of ΔK corresponds to the level of divergence between populations. Based on our findings, we suggest researchers should use the ΔK method cautiously; they need to report all relevant data, including the magnitude of ΔK, and an estimate of connectivity for the research community to assess whether meaningful genetic structure exists within the context of management and conservation.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Conservation of Natural Resources / Genetics, Population / Models, Genetic Type of study: Prognostic_studies Limits: Animals Language: En Journal: Mol Ecol Journal subject: BIOLOGIA MOLECULAR / SAUDE AMBIENTAL Year: 2020 Document type: Article Affiliation country: Canadá

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Conservation of Natural Resources / Genetics, Population / Models, Genetic Type of study: Prognostic_studies Limits: Animals Language: En Journal: Mol Ecol Journal subject: BIOLOGIA MOLECULAR / SAUDE AMBIENTAL Year: 2020 Document type: Article Affiliation country: Canadá
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