R
Robin S. Waples
Researcher at National Oceanic and Atmospheric Administration
Publications - 207
Citations - 25146
Robin S. Waples is an academic researcher from National Oceanic and Atmospheric Administration. The author has contributed to research in topics: Population & Effective population size. The author has an hindex of 69, co-authored 195 publications receiving 22752 citations. Previous affiliations of Robin S. Waples include Scripps Institution of Oceanography & Joseph Fourier University.
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NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne ) from genetic data.
TL;DR: NeEstimator v2 includes three single‐sample estimators (updated versions of the linkage disequilibrium and heterozygote‐excess methods, and a new method based on molecular coancestry), as well as the two‐sample (moment‐based temporal) method.
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What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity.
TL;DR: It is suggested several quantitative criteria that might be used to determine when groups of individuals are different enough to be considered ‘populations’, and a simple algorithm based on a multilocus contingency test of allele frequencies in pairs of samples has high power to detect the true number of populations but requires more rigorous statistical evaluation.
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Separating the wheat from the chaff: patterns of genetic differentiation in high gene flow species
TL;DR: This article discusses strategies to maximize the signal:nolse ratio in genetic studies of marine species and suggests a quantitative method to correct for bias due to a common sampling problem.
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ldne: a program for estimating effective population size from data on linkage disequilibrium.
Robin S. Waples,Chi Do +1 more
TL;DR: Ldne is a program with a Visual Basic interface that implements a recently developed bias correction for estimates of effective population size (Ne) based on linkage disequilibrium data and introduces a jackknife method for obtaining confidence intervals that appears to perform better than parametric methods currently in use.
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Genetic monitoring as a promising tool for conservation and management
TL;DR: It is illustrated how DNA and population genetic data can provide valuable information, often unattainable via other approaches, for monitoring species of management, conservation and ecological interest.