Molecules, morphology and minute hooded beetles: a phylogenetic study with implications for the evolution and classification of Corylophidae (Coleoptera: Cucujoidea)

The recent development of Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) techniques has facilitated the exploration of parameter-rich evolutionary models. At the same time, stochastic models have become more realistic (and complex) and have been extended to new types of data, such as morphology. Based on this foundation, we developed a Bayesian MCMC approach to the analysis of combined data sets and explored its utility in inferring relationships among gall wasps based on data from morphology and four genes (nuclear and mitochondrial, ribosomal and protein coding). Examined models range in complexity from those recognizing only a morphological and a molecular partition to those having complex substitution models with independent parameters for each gene. Bayesian MCMC analysis deals efficiently with complex models: convergence occurs faster and more predictably for complex models, mixing is adequate for all parameters even under very complex models, and the parameter update cycle is virtually unaffected by model partitioning across sites. Morphology contributed only 5% of the characters in the data set but nevertheless influenced the combined-data tree, supporting the utility of morphological data in multigene analyses. We used Bayesian criteria (Bayes factors) to show that process heterogeneity across data partitions is a significant model component, although not as important as among-site rate variation. More complex evolutionary models are associated with more topological uncertainty and less conflict between morphology and molecules. Bayes factors sometimes favor simpler models over considerably more parameter-rich models, but the best model overall is also the most complex and Bayes factors do not support exclusion of apparently weak parameters from this model. Thus, Bayes factors appear to be useful for selecting among complex models, but it is still unclear whether their use strikes a reasonable balance between model complexity and error in parameter estimates.

Beetles represent almost one-fourth of all described species, and knowledge about their relationships and evolution adds to our understanding of biodiversity. We performed a comprehensive phylogenetic analysis of Coleoptera inferred from three genes and nearly 1900 species, representing more than 80% of the world's recognized beetle families. We defined basal relationships in the Polyphaga supergroup, which contains over 300,000 species, and established five families as the earliest branching lineages. By dating the phylogeny, we found that the success of beetles is explained neither by exceptional net diversification rates nor by a predominant role of herbivory and the Cretaceous rise of angiosperms. Instead, the pre-Cretaceous origin of more than 100 present-day lineages suggests that beetle species richness is due to high survival of lineages and sustained diversification in a variety of niches.

Ants are the world's most diverse and ecologically dominant eusocial organisms. Resolving the phylogeny and timescale for major ant lineages is vital to understanding how they achieved this success. Morphological, molecular, and paleontological studies, however, have presented conflicting views on early ant evolution. To address these issues, we generated the largest ant molecular phylogenetic data set published to date, containing approximately 6 kb of DNA sequence from 162 species representing all 20 ant subfamilies and 10 aculeate outgroup families. When these data were analyzed with and without outgroups, which are all distantly related to ants and hence long-branched, we obtained conflicting ingroup topologies for some early ant lineages. This result casts strong doubt on the existence of a poneroid clade as currently defined. We compare alternate attachments of the outgroups to the ingroup tree by using likelihood tests, and find that several alternative rootings cannot be rejected by the data. These alternatives imply fundamentally different scenarios for the early evolution of ant morphology and behavior. Our data strongly support several notable relationships within the more derived formicoid ants, including placement of the enigmatic subfamily Aenictogitoninae as sister to Dorylus army ants. We use the molecular data to estimate divergence times, employing a strategy distinct from previous work by incorporating the extensive fossil record of other aculeate Hymenoptera as well as that of ants. Our age estimates for the most recent common ancestor of extant ants range from approximately 115 to 135 million years ago, indicating that a Jurassic origin is highly unlikely.