bioRxivEcologyPreprint
Mapping diversification metrics in macroecological studies: Prospects and challenges
Abstract
The intersection of macroecology and macroevolution is one of the most active research areas today. Macroecological studies are increasingly using phylogenetic diversification metrics to explore the role of evolutionary processes in shaping present-day patterns of biodiversity. Evolutionary explanations of species richness gradients are key for our understanding of how diversity accumulated in a region. For instance, the present-day diversity in a region can be a result of in situ diversification, extinction, or colonization from other regions, or a combination of all of these processes. However, it is unknown whether these metrics capture well these diversification and dispersal processes across geography. Some metrics (e.g., mean root distance -MRD-; lineage diversification-rate -DR-; evolutionary distinctiveness -ED-) seem to provide very similar geographical patterns regardless of how they were calculated (e.g., using branch lengths or not). The lack of appropriate estimates of extinction and dispersal rates in phylogenetic trees can limit our conclusions about how species richness gradients emerged. With a review of the literature and complemented by an empirical comparison, we show that phylogenetic metrics by itself are not capturing well the speciation, extinction and dispersal processes across the geographical gradients. Furthermore, we show how new biogeographic methods can improve our inference of past events and therefore our conclusions about the evolutionary mechanisms driving regional species richness. Finally, we recommend that future studies include several approaches (e.g., spatial diversification modelling, parametric biogeographic methods) to disentangle the relative the role of speciation, extinction and dispersal in the generation and maintenance of species richness gradients.
- research focus: ecology & biodiversity
- research focus: benchmarking
- approach: comparative / phylogenetic analysis
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