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The number of markers and samples needed for detecting bottlenecks under realistic scenarios, with and without recovery: a simulation‐based study
Author(s) -
Hoban Sean M.,
Gaggiotti Oscar E.,
Bertorelle Giorgio
Publication year - 2013
Publication title -
molecular ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.619
H-Index - 225
eISSN - 1365-294X
pISSN - 0962-1083
DOI - 10.1111/mec.12258
Subject(s) - bottleneck , biology , power (physics) , sampling (signal processing) , task (project management) , population bottleneck , computer science , component (thermodynamics) , sample size determination , statistics , evolutionary biology , ecology , microsatellite , mathematics , genetics , physics , engineering , allele , telecommunications , systems engineering , quantum mechanics , detector , gene , embedded system , thermodynamics
Detecting bottlenecks is a common task in molecular ecology. While several bottleneck detection methods exist, evaluations of their power have focused only on severe bottlenecks (e.g. to Ne ~10). As a component of a recent review, Peery et al . ([Peery MZ, 2012]) analysed the power of two approaches, the M‐ratio and heterozygote excess tests, to detect moderate bottlenecks (e.g. to Ne ~100), which is realistic for many conservation situations. In this Comment, we address three important points relevant to but not considered in Peery et al . Under moderate bottleneck scenarios, we test the (i) relative advantage of sampling more markers vs. more individuals, (ii) potential power to detect the bottleneck when utilizing dozens of microsatellites (a realistic possibility for contemporary studies) and (iii) reduction in power when postbottleneck recovery has occurred. For the realistic situations examined, we show that (i) doubling the number of loci shows equal or better power than tripling the number of individuals, (ii) increasing the number of markers (up to 100) results in continued additive gains in power, and (iii) recovery after a moderate amount of time or gradual change in size reduces power, by up to one‐half. Our results provide a practical supplement to Peery et al . and encourage the continued use of bottleneck detection methods in the genomic age, but also emphasize that the power under different sampling schemes should be estimated, using simulation modelling, as a routine component of molecular ecology studies.