Did the end-Cretaceous mass extinction event, by eliminating non-avian dinosaurs and most of the existing fauna, trigger the evolutionary radiation of present-day mammals? Here we construct, date and analyse a species-level phylogeny of nearly all extant Mammalia to bring a new perspective to this question. Our analyses of how extant lineages accumulated through time show that net per-lineage diversification rates barely changed across the Cretaceous/Tertiary boundary. Instead, these rates spiked significantly with the origins of the currently recognized placental superorders and orders approximately 93 million years ago, before falling and remaining low until accelerating again throughout the Eocene and Oligocene epochs. Our results show that the phylogenetic 'fuses' leading to the explosion of extant placental orders are not only very much longer than suspected previously, but also challenge the hypothesis that the end-Cretaceous mass extinction event had a major, direct influence on the diversification of today's mammals.

Abstract. Analyses of life-history, ecological, and geographic trait differences among species, their causes, correlates, and likely consequences are increasingly important for understanding and conserving biodiversity in the face of rapid global change. Assembling multispecies trait data from diverse literature sources into a single comprehensive data set requires detailed consideration of methods to reliably compile data for particular species, and to derive single estimates from multiple sources based on different techniques and definitions. Here we describe PanTHERIA, a species-level data set compiled for analysis of life history, ecology, and geography of all known extant and recently extinct mammals. PanTHERIA is derived from a database capable of holding multiple geo-referenced values for variables within a species containing 100 740 lines of biological data for extant and recently extinct mammalian species, collected over a period of three years by 20 individuals. PanTHERIA also includes spatial databases of mammalian geographic ranges and global climatic and anthropogenic variables. Here we detail how the data fields are extracted and defined for PanTHERIA using a customized data input format (MammalForm); how data were collected from the literature, species names and sources tracked, error-checking and validation procedures applied, and how data were consolidated into species-level values for each variable. Tables of the consolidated species-level values are made available for each of two recent species-level taxonomic classifications of mammals, as well as associated taxonomic synonymy conversion and data-input files. This study provides a useful guide to prospective researchers on how to structure and codify life-history, ecological, geographic, and taxonomic data and methods to extract meaningful species-level traits. It also provides comprehensive information on traits like size, diet, environmental conditions, and ecology to permit macroecological and macroevolutionary analyses of this important clade.

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Many large animal species have a high risk of extinction. This is usually thought to result simply from the way that species traits associated with vulnerability, such as low reproductive rates, scale with body size. In a broad-scale analysis of extinction risk in mammals, we find two additional patterns in the size selectivity of extinction risk. First, impacts of both intrinsic and environmental factors increase sharply above a threshold body mass around 3 kilograms. Second, whereas extinction risk in smaller species is driven by environmental factors, in larger species it is driven by a combination of environmental factors and intrinsic traits. Thus, the disadvantages of large size are greater than generally recognized, and future loss of large mammal biodiversity could be far more rapid than expected.

Whereas previous studies have investigated correlates of extinction risk either at global or regional scales, our study explicitly models regional effects of anthropogenic threats and biological traits across the globe. Using phylogenetic comparative methods with a newly-updated supertree of 5020 extant mammals, we investigate the impact of species traits on extinction risk within each WWF ecoregion. Our analyses reveal strong geographical variation in the influence of traits on risk: notably, larger species are at higher risk only in tropical regions. We then relate these patterns to current and recent-historical human impacts across ecoregions using spatial modelling. The body-mass results apparently reflect historical declines of large species outside the tropics due to large-scale land conversion. Narrow-ranged and rare species tend to be at high risk in areas of high current human impacts. The interactions we describe between biological traits and anthropogenic threats increase understanding of the processes determining extinction risk.

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BackgroundAlthough it has proven to be an important foundation for investigations of carnivoran ecology, biology and evolution, the complete species-level supertree for Carnivora of Bininda-Emonds et al. is showing its age. Additional, largely molecular sequence data are now available for many species and the advancement of computer technology means that many of the limitations of the original analysis can now be avoided. We therefore sought to provide an updated estimate of the phylogenetic relationships within all extant Carnivora, again using supertree analysis to be able to analyze as much of the global phylogenetic database for the group as possible.ResultsIn total, 188 source trees were combined, representing 114 trees from the literature together with 74 newly constructed gene trees derived from nearly 45,000 bp of sequence data from GenBank. The greater availability of sequence data means that the new supertree is almost completely resolved and also better reflects current phylogenetic opinion (for example, supporting a monophyletic Mephitidae, Eupleridae and Prionodontidae; placing Nandinia binotata as sister to the remaining Feliformia). Following an initial rapid radiation, diversification rate analyses indicate a downturn in the net speciation rate within the past three million years as well as a possible increase some 18.0 million years ago; numerous diversification rate shifts within the order were also identified.ConclusionsTogether, the two carnivore supertrees remain the only complete phylogenetic estimates for all extant species and the new supertree, like the old one, will form a key tool in helping us to further understand the biology of this charismatic group of carnivores.

Phylogenetic Bootstrapping (BS) is a standard technique for inferring confidence values on phylogenetic trees that is based on reconstructing many trees from minor variations of the input data, trees called replicates. BS is used with all phylogenetic reconstruction approaches, but we focus here on the most popular, Maximum Likelihood (ML). Because ML inference is so computationally demanding, it has proved too expensive to date to assess the impact of the number of replicates used in BS on the quality of the support values. For the same reason, a rather small number (typically 100) of BS replicates are computed in real-world studies. Stamatakis et al. recently introduced a BS algorithm that is 1-2 orders of magnitude faster than previous techniques, while yielding qualitatively comparable support values, making an experimental study possible.In this paper, we propose stopping criteria, that is, thresholds computed at runtime to determine when enough replicates have been generated, and report on the first large-scale experimental study to assess the effect of the number of replicates on the quality of support values, including the performance of our proposed criteria. We run our tests on 17 diverse real-world DNA, single-gene as well as multi-gene, datasets, that include between 125 and 2,554 sequences. We find that our stopping criteria typically stop computations after 100-500 replicates (although the most conservative criterion may continue for several thousand replicates) while producing support values that correlate at better than 99.5% with the reference values on the best ML trees. Significantly, we also find that the stopping criteria can recommend very different numbers of replicates for different datasets of comparable sizes.Our results are thus two-fold: (i) they give the first experimental assessment of the effect of the number of BS replicates on the quality of support values returned through bootstrapping; and (ii) they validate