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Investigating the timing of origin and evolutionary processes shaping regional species diversity: Insights from simulated data and neotropical butterfly diversification rates
Author(s) -
MatosMaraví Pável
Publication year - 2016
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.12960
Subject(s) - biology , diversification (marketing strategy) , macroevolution , extinction (optical mineralogy) , extant taxon , divergence (linguistics) , biodiversity , genetic algorithm , evolutionary biology , ecology , butterfly , pleistocene , null model , phylogenetics , paleontology , biochemistry , linguistics , philosophy , marketing , business , gene
Different diversification scenarios have been proposed to explain the origin of extant biodiversity. However, most existing meta‐analyses of time‐calibrated phylogenies rely on approaches that do not quantitatively test alternative diversification processes. Here, I highlight the shortcomings of using species divergence ranks, which is a method widely used in meta‐analyses. Divergence ranks consist of categorizing cladogenetic events to certain periods of time, typically to either Pleistocene or to pre‐Pleistocene ages. This approach has been claimed to shed light on the origin of most extant species and the timing and dynamics of diversification in any biogeographical region. However, interpretations drawn from such method often confound two fundamental questions in macroevolutionary studies, tempo (timing of evolutionary rate shifts) and mode (“how” and “why” of speciation). By using simulated phylogenies under four diversification scenarios, constant‐rate, diversity‐dependence, high extinction, and high speciation rates in the Pleistocene, I showed that interpretations based on species divergence ranks might have been seriously misleading. Future meta‐analyses of dated phylogenies need to be aware of the impacts of incomplete taxonomic sampling, tree topology, and divergence time uncertainties, as well as they might be benefited by including quantitative tests of alternative diversification models that acknowledge extinction and diversity dependence.

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