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Morales, Ariadna_E ; Ruedi, Manuel ; Field, Kathryn ; Carstens, Bryan_C ( , Evolution)
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Carstens, Bryan C. ; Morales, Ariadna E. ; Field, Kathryn ; Pelletier, Tara A. ( , Journal of Biogeography)
Abstract Aim Our work seeks to understand the global demographical response of bat species to the climate change that occurred at the Last Glacial Maximum (
LGM ).Location All continents except Antarctica.
Methods Mitochondrial
DNA sequences were sampled from bat species throughout the planet where we could associate a georeferenced sample with a givenDNA sequence. Our investigation estimates the historical demographical response using over 12,000 samples from >300 nominal species of bats. CustomPython and R scripts were written to aggregate sequence data from GenBank, locality information fromGBIF , and to associate these records to individual samples. We conducted approximate Bayesian computation to calculate the posterior probability of demographical bottleneck and expansion responses to the end of the Pleistocene, and then collected organismal trait data to identify traits that were associated with either demographical response. We also used R to estimate current and end‐Pleistocene species distribution models (SDM) for species where >10 georeferenced samples were available.Results Analysis of the genetic data indicate that some temperate insectivores responded to the end of the Pleistocene by undergoing a demographical expansion. However, the neotropical family Phyllostomidae experienced the most dramatic response, with many of its species undergoing demographical bottlenecks. Larger bats, and those with shorter forewings, were more likely to undergo a demographical bottleneck. In contrast with the results of the genetic data analysis, the automated SDMs all predicted range expansion since the LGM.
Main conclusions Historical populations of Neotropical bats that rely on Angiosperms for resources (i.e., pollen, nectar, fruit) were negatively influenced by the climate change that occurred at the end of the Pleistocene. Our work highlights the utility of incorporating exploratory trait‐based analyses in phylogeography. It serves as an example of automated big data phylogeography, and suggests that repurposed data can lead to new insights about global biodiversity.