Phylogeography of the dry vegetation endemic species Nephila sexpunctata (Araneae: Araneidae) suggests recent expansion of the Neotropical Dry Diagonal

Recent developments in marginal likelihood estimation for model selection in the field of Bayesian phylogenetics and molecular evolution have emphasized the poor performance of the harmonic mean estimator (HME). Although these studies have shown the merits of new approaches applied to standard normally distributed examples and small real-world data sets, not much is currently known concerning the performance and computational issues of these methods when fitting complex evolutionary and population genetic models to empirical real-world data sets. Further, these approaches have not yet seen widespread application in the field due to the lack of implementations of these computationally demanding techniques in commonly used phylogenetic packages. We here investigate the performance of some of these new marginal likelihood estimators, specifically, path sampling (PS) and stepping-stone (SS) sampling for comparing models of demographic change and relaxed molecular clocks, using synthetic data and real-world examples for which unexpected inferences were made using the HME. Given the drastically increased computational demands of PS and SS sampling, we also investigate a posterior simulation-based analogue of Akaike's information criterion (AIC) through Markov chain Monte Carlo (MCMC), a model comparison approach that shares with the HME the appealing feature of having a low computational overhead over the original MCMC analysis. We confirm that the HME systematically overestimates the marginal likelihood and fails to yield reliable model classification and show that the AICM performs better and may be a useful initial evaluation of model choice but that it is also, to a lesser degree, unreliable. We show that PS and SS sampling substantially outperform these estimators and adjust the conclusions made concerning previous analyses for the three real-world data sets that we reanalyzed. The methods used in this article are now available in BEAST, a powerful user-friendly software package to perform Bayesian evolutionary analyses.

The relative importance of local ecological and larger-scale historical processes in causing differences in species richness across the globe remains keenly debated. To gain insight into these questions, we investigated the assembly of plant diversity in the Cerrado in South America, the world's most species-rich tropical savanna. Time-calibrated phylogenies suggest that Cerrado lineages started to diversify less than 10 Mya, with most lineages diversifying at 4 Mya or less, coinciding with the rise to dominance of flammable C4 grasses and expansion of the savanna biome worldwide. These plant phylogenies show that Cerrado lineages are strongly associated with adaptations to fire and have sister groups in largely fire-free nearby wet forest, seasonally dry forest, subtropical grassland, or wetland vegetation. These findings imply that the Cerrado formed in situ via recent and frequent adaptive shifts to resist fire, rather than via dispersal of lineages already adapted to fire. The location of the Cerrado surrounded by a diverse array of species-rich biomes, and the apparently modest adaptive barrier posed by fire, are likely to have contributed to its striking species richness. These findings add to growing evidence that the origins and historical assembly of species-rich biomes have been idiosyncratic, driven in large part by unique features of regional- and continental-scale geohistory and that different historical processes can lead to similar levels of modern species richness.