Two phylogenetic comparative methods, independent contrasts and generalized least squares models, can be used to determine the statistical relationship between two or more traits. We show that the two approaches are functionally identical and that either can be used to make statistical inferences about values at internal nodes of a phylogenetic tree (hypothetical ancestors), to estimate relationships between characters, and to predict values for unmeasured species. Regression equations derived from independent contrasts can be placed back onto the original data space, including computation of both confidence intervals and prediction intervals for new observations. Predictions for unmeasured species (including extinct forms) can be made increasingly accurate and precise as the specificity of their placement on a phylogenetic tree increases, which can greatly increase statistical power to detect, for example, deviation of a single species from an allometric prediction. We reexamine published data for basal metabolic rates (BMR) of birds and show that conventional and phylogenetic allometric equations differ significantly. In new results, we show that, as compared with nonpasserines, passerines exhibit a lower rate of evolution in both body mass and mass-corrected BMR; passerines also have significantly smaller body masses than their sister clade. These differences may justify separate, clade-specific allometric equations for prediction of avian basal metabolic rates.

One of the central questions of conservation biology is what life-history traits render a species prone to extinction. We addressed this problem by calculating extinction rates for 35 species of turtles and squamates (lizards and snakes) occurring on 87 land-bridge islands in the Mediterranean Sea. We calculated extinction rates in two ways: first, by incorporating the known sequence of historical island separations and second by ignoring history and assuming that the islands became isolated simultaneously. The second procedure is simpler and more frequently used in the literature and produces estimates of extinction rates that are similar to the first, more complex procedure. We then determined the relationship between extinction rates (calculated using both methods) and body mass, longevity, habitat specialization, and population abundance using two methods: first, by accounting for the phylogenetic relationships among species and, second, by ignoring them. Only population abundance and habitat specialization explained a significant amount of the observed variation in species extinction rates. Body mass itself did not explain variation in extinction rates, although it was strongly correlated with abundance. These conclusions were obtained using both procedures for calculating extinction rates and both procedures for correlating extinction rates with life-history traits.

Investigating the effect of biodiversity on the stability of ecological communities is complicated by the numerous ways in which models of community interactions can be formulated. This has led to differences in conclusions and interpretations of how the number of species in a community affects its stability. Here, we derive a simple, general relationship between the coefficient of variation (CV) of combined species densities and the environmentally driven variability in species' per capita population growth rates. For a given level of environmentally driven variability in per capita population growth rates, increasing the number of species in a community decreases the CV of combined species densities, provided that species do not respond to environmental fluctuations in a perfectly correlated way. Thus, a community with more species of competitors will be more stable (have lower CV in combined species densities for a given level of environmental variability) than a species-poor community, provided that the species in both communities show equal variability in per capita population growth rates and provided that species within each community do not show strongly correlated responses to environmental fluctuations. This conclusion also applies to "noninteractive" models in which there is no competition between species.

No abstract