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Multidimensional divergent selection, local adaptation, and speciation
Author(s) -
White Nathan J.,
Butlin Roger K.
Publication year - 2021
Publication title -
evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.84
H-Index - 199
eISSN - 1558-5646
pISSN - 0014-3820
DOI - 10.1111/evo.14312
Subject(s) - selection (genetic algorithm) , biology , genetic algorithm , curse of dimensionality , divergence (linguistics) , ecological speciation , adaptation (eye) , evolutionary biology , local adaptation , ecological selection , incipient speciation , confounding , genetics , computer science , artificial intelligence , genetic variation , population , mathematics , statistics , gene , gene flow , linguistics , philosophy , demography , neuroscience , sociology
Divergent selection applied to one or more traits drives local adaptation and may lead to ecological speciation. Divergent selection on many traits might be termed “multidimensional” divergent selection. There is a commonly held view that multidimensional divergent selection is likely to promote local adaptation and speciation to a greater extent than unidimensional divergent selection. We disentangle the core concepts underlying dimensionality as a property of the environment, phenotypes, and genome. In particular, we identify a need to separate the overall strength of selection and the number of loci affected from dimensionality per se, and to distinguish divergence dimensionality from dimensionality of stabilizing selection. We then critically scrutinize this commonly held view that multidimensional selection promotes speciation, re‐examining the evidence base from theory, experiments, and nature. We conclude that the evidence base is currently weak and generally suffers from confounding of possible causal effects. Finally, we propose several mechanisms by which multidimensional divergent selection and related processes might influence divergence, both as a driver and as a barrier.