Anthropogenic climate change is predicted to be a major cause of species extinctions in the next 100 years. But what will actually cause these extinctions? For example, will it be limited physiological tolerance to high temperatures, changing biotic interactions or other factors? Here, we systematically review the proximate causes of climate-change related extinctions and their empirical support. We find 136 case studies of climatic impacts that are potentially relevant to this topic. However, only seven identified proximate causes of demonstrated local extinctions due to anthropogenic climate change. Among these seven studies, the proximate causes vary widely. Surprisingly, none show a straightforward relationship between local extinction and limited tolerances to high temperature. Instead, many studies implicate species interactions as an important proximate cause, especially decreases in food availability. We find very similar patterns in studies showing decreases in abundance associated with climate change, and in those studies showing impacts of climatic oscillations. Collectively, these results highlight our disturbingly limited knowledge of this crucial issue but also support the idea that changing species interactions are an important cause of documented population declines and extinctions related to climate change. Finally, we briefly outline general research strategies for identifying these proximate causes in future studies.

The mechanisms underlying the high extant biodiversity in the Neotropics have been controversial since the 19th century. Support for the influence of period-specific changes on diversification often rests on detecting more speciation events during a particular period. The timing of speciation events may reflect the influence of incomplete taxon sampling, protracted speciation, and null processes of lineage accumulation. Here we assess the influence of these factors on the timing of speciation with new multilocus data for New World noctilionoid bats (Chiroptera: Noctilionoidea). Biogeographic analyses revealed the importance of the Neotropics in noctilionoid diversification, and the critical role of dispersal. We detected no shift in speciation rate associated with the Quaternary or pre-Quaternary periods, and instead found an increase in speciation linked to the evolution of the subfamily Stenodermatinae (∼18 Ma). Simulations modeling constant speciation and extinction rates for the phylogeny systematically showed more speciation events in the Quaternary. Since recording more divergence events in the Quaternary can result from lineage accumulation, the age of extant sister species cannot be interpreted as supporting higher speciation rates during this period. Instead, analyzing the factors that influence speciation requires modeling lineage-specific traits and environmental, spatial, and ecological drivers of speciation.

Selection for divergent performance optima has been proposed as a central mechanism underlying adaptive radiation. Uncovering multiple optima requires identifying forms associated with different adaptive zones and linking those forms to performance.However, testing and modeling the performance of complex morphologies like the cranium is challenging. We introduce a three- Studies of morphological adaptation aim to link form (morphology) to biomechanical function, and biomechanical function to performance, or the ability to carry out ecological tasks that influence fitness (Arnold 1983). Selection for performance is thought to drive the evolution of underlying form. Implicit in many studies is the assumption of the existence of performance optima, or values of peak performance toward which lineages evolve. Many morphological systems contain multiple performance optima, each of which offers the opportunity to evolve into a dif- * These authors contributed equally to this work.

Morphological characters are indispensable in phylogenetic analyses for understanding the pattern, process, and tempo of evolution. If characters are independent and free of systematic errors, then combining as many different kinds of characters as are available will result in the best-supported phylogenetic hypotheses. But since morphological characters are subject to natural selection for function and arise from the expression of developmental pathways, they may not be independent, a situation that may amplify any underlying homoplasy. Here, we use new dental and multi-locus genetic data from bats (Mammalia: Chiroptera) to quantify saturation and similarity in morphological characters and introduce two likelihood-based approaches to identify strongly conflicting characters and integrate morphological and molecular data. We implement these methods to analyze the phylogeny of incomplete Miocene fossils in the radiation of Phyllostomidae (New World Leaf-nosed Bats), perhaps the most ecologically diverse family of living mammals. Morphological characters produced trees incongruent with molecular phylogenies, were saturated, and showed rates of change higher than most molecular substitution rates. Dental characters encoded variation similar to that in other morphological characters, while molecular characters encoded highly dissimilar variation in comparison. Saturation and high rates of change indicate randomization of phylogenetic signal in the morphological data, and extensive similarity suggests characters are non-independent and errors are amplified. To integrate the morphological data into tree building while accounting for homoplasy, we used statistical molecular scaffolds and combined phylogenetic analyses excluding a small subset of strongly conflicting dental characters. The phylogenies revealed the Miocene nectar-feeding †Palynephyllum nests within the crown nectar-feeding South American subfamily Lonchophyllinae, while the Miocene genus †Notonycteris is sister to the extant carnivorous Vampyrum. These relationships imply new calibration points for timing of radiation of the ecologically diverse Phyllostomidae. [Chiroptera; conflict; dentition; morphology; Phyllostomidae; saturation; scaffold; systematic error.].