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Is local selection so widespread in river organisms? Fractal geometry of river networks leads to high bias in outlier detection
Author(s) -
Fourcade Yoan,
ChaputBardy Audrey,
Secondi Jean,
Fleurant Cyril,
Lemaire Christophe
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.12158
Subject(s) - biology , local adaptation , outlier , selection (genetic algorithm) , population , adaptation (eye) , ecotype , fractal , evolutionary biology , ecology , false positive paradox , genetic structure , statistics , artificial intelligence , genetic variation , computer science , genetics , mathematics , mathematical analysis , demography , neuroscience , sociology , gene
Identifying local adaptation is crucial in conservation biology to define ecotypes and establish management guidelines. Local adaptation is often inferred from the detection of loci showing a high differentiation between populations, the so‐called F ST outliers. Methods of detection of loci under selection are reputed to be robust in most spatial population models. However, using simulations we showed that F ST outlier tests provided a high rate of false‐positives (up to 60%) in fractal environments such as river networks. Surprisingly, the number of sampled demes was correlated with parameters of population genetic structure, such as the variance of F ST s, and hence strongly influenced the rate of outliers. This unappreciated property of river networks therefore needs to be accounted for in genetic studies on adaptation and conservation of river organisms.