Probabilistic historical biogeography: new models for founder-event speciation, imperfect detection, and fossils allow improved accuracy and model-testing

By N. Matzke. 2013

957 citations recorded by the source corpus.

Historical biogeography has been characterized by a large diversity of methods and unresolved debates about which processes, such as dispersal or vicariance, are most important for explaining distributions. A new R package, BioGeoBEARS, implements many models in a common likelihood framework, so that standard statistical model selection procedures can be applied to let the data choose the best model. Available models include a likelihood version of DIVA (“DIVALIKE”), LAGRANGE’s DEC model, and BAYAREA, as well as “+J” versions of these models which include founder-event speciation, an important process left out of most inference methods. I use BioGeoBEARS on a large sample of island and non-island clades (including two fossil clades) to show that founder-event speciation is a crucial process in almost every clade, and that most published datasets reject the non-J models currently in widespread use. BioGeoBEARS is open-source and freely available for installation at the Comprehensive R Archive Network at http://CRAN.R-project.org/package=BioGeoBEARS. A step-by-step tutorial is available at http://phylo.wikidot.com/biogeobears.

Subfields: Ecological Modeling, Nature and Landscape Conservation, Paleontology

View Paper: https://www.semanticscholar.org/paper/77c59b585cea7f7030b6a639778c424647f82e6e

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Citations in the corpus

Evaluating the influence of connectivity and distance on biogeographical patterns in the south‐western deserts of North America (2016, methodology): “For biogeographical analyses, we used the R package BioGeoBEARS (Matzke, 2013).”
Evolution, Diversification, and Biogeography of Grasshoppers (Orthoptera: Acrididae) (2018, methodology): “We used the package BioGeoBEARS (Biogeography with Bayesian [and Likelihood] Evolutionary Analysis in R Scripts) (Matzke 2013) within R (R Core Team 2017) to infer biogeographical patterns during the diversification of different lineages within Acrididae.”
In and out of the Qinghai‐Tibet Plateau: divergence time estimation and historical biogeography of the large arctic‐alpine genus Saxifraga L. (2017, methodology): “Methods Using a total of 420 taxa (321 ingroup taxa) comprising more than 60% of extant Saxifraga species, we studied the evolutionary history of Saxifraga by performing phylogenetic analyses (maximum likelihood and Bayesian inference on nuclear ITS and plastid trnL–trnF, matK sequences), divergence”
A dated molecular perspective of eucalypt taxonomy, evolution and diversification (2019, methodology): “A properly coded and detailed biogeographic analysis of the eucalypts, incorporating well resolved and substantiated phylogenies that allows for more 30 robust dating estimates, and newer methods such as BioGeoBears (Matzke 2013) could assist with interpreting the eucalypt spread.”
A tale of worldwide success: Behind the scenes of Carex (Cyperaceae) biogeography and diversification (2019, methodology): “Ancestral area reconstruction (AAR) was conducted using the R package “ BioGeoBEARS ” (Matzke, 2013, 2014a).”