An evaluation of new parsimony‐based versus parametric inference methods in biogeography: a case study using the globally distributed plant family Sapindaceae

摘要: Aim Recently developed parametric methods in historical biogeography allow researchers to integrate temporal and palaeogeographical information into the reconstruction of biogeographical scenarios, thus overcoming a known bias parsimony-based approaches. Here, we compare method, dispersal-extinction-cladogenesis (DEC), against dispersal-vicariance analysis (DIVA), which does not incorporate branch lengths but accounts for phylogenetic uncertainty through Bayesian empirical approach (Bayes-DIVA). We analyse benefits limitations each method using cosmopolitan plant family Sapindaceae as case study. Location World-wide. Methods Phylogenetic relationships were estimated by inference on large dataset representing generic diversity within Sapindaceae. Lineage divergence times penalized likelihood over sample trees from posterior distribution phylogeny account dating reconstructions. compared scenarios between Bayes-DIVA two different DEC models: one with no geological constraints another that employed stratified model dispersal rates scaled according area connectivity across four time slices, reflecting changing continental configuration last 110 million years. Results Despite differences underlying model, inferred similar scenarios. The main were: (1) timing events - sometimes conflicts information, (2) lower frequency terminal DEC. Uncertainty estimations influenced both ancestral ranges decisiveness an can be assigned node. Main conclusions By considering lineage times, gives more accurate reconstructions are agreement evidence. In contrast, showed highest unequivocally reconstructing ranges, probably its ability uncertainty. Care should taken defining because possibility overestimating extinction events, or inferring outside extant species owing enforced model. wide-spanning spatial proposed here could prove useful testing large-scale patterns plants.