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Data from: Estimating synchronous demographic changes across populations using hABC and its application for a herpetological community from northeastern Brazil

Citation

Gehara, Marcelo et al. (2017), Data from: Estimating synchronous demographic changes across populations using hABC and its application for a herpetological community from northeastern Brazil, Dryad, Dataset, https://doi.org/10.5061/dryad.789pv

Abstract

Many studies propose that Quaternary climatic cycles contracted and /or expanded the ranges of species and biomes. Strong expansion-contraction dynamics of biomes presume concerted demographic changes of associated fauna. The analysis of temporal concordance of demographic changes can be used to test the influence of Quaternary climate on diversification processes. Hierarchical approximate Bayesian computation (hABC) is a powerful and flexible approach that models genetic data from multiple species, and can be used to estimate the temporal concordance of demographic processes. Using available single-locus data we can now perform large-scale analyses, both in terms of number of species and geographic scope. Here we first compared the power of four alternative hABC models for a collection of single-locus data. We found that the model incorporating an a priori hypothesis about the timing of simultaneous demographic change had the best performance. Secondly, we applied the hABC models to a dataset of 7 squamate and 4 amphibian species occurring in the Seasonally Dry Tropical Forests (Caatinga) in Northeastern Brazil, which, according to paleoclimatic evidence, experienced an increase in aridity during the Pleistocene. If this increase was important for the diversification of associated xeric-adapted species, simultaneous population expansions should be evident at the community level. We found a strong signal of synchronous population expansion in the Late Pleistocene, supporting the expansion of the Caatinga during this time. This expansion likely enhanced the formation of communities adapted to high aridity and seasonality and caused regional extirpation of taxa adapted to wet forest.

Usage Notes

Funding

National Science Foundation, Award: DEB-1210346, DEB-1257926, DEB-1500448, CNS-0958379, CNS-0855217, ACI-1126113

Location

South America
Brazil