| Literature DB >> 29685579 |
Jeet Sukumaran1, L Lacey Knowles2.
Abstract
The development of process-based probabilistic models for historical biogeography has transformed the field by grounding it in modern statistical hypothesis testing. However, most of these models abstract away biological differences, reducing species to interchangeable lineages. We present here the case for reintegration of biology into probabilistic historical biogeographical models, allowing a broader range of questions about biogeographical processes beyond ancestral range estimation or simple correlation between a trait and a distribution pattern, as well as allowing us to assess how inferences about ancestral ranges themselves might be impacted by differential biological traits. We show how new approaches to inference might cope with the computational challenges resulting from the increased complexity of these trait-based historical biogeographical models.Keywords: computational models; historical biogeography; trait-dependent dispersal
Mesh:
Year: 2018 PMID: 29685579 DOI: 10.1016/j.tree.2018.03.010
Source DB: PubMed Journal: Trends Ecol Evol ISSN: 0169-5347 Impact factor: 17.712