Bayesian Prediction of Multivariate Ecology from Phenotypic Data Yields New Insights into the Diets of Extant and Extinct Taxa.

AbstractMorphology often reflects ecology, enabling the prediction of ecological roles for taxa that lack direct observations, such as fossils. In comparative analyses, ecological traits, like diet, are often treated as categorical, which may aid prediction and simplify analyses but ignores the multivariate nature of ecological niches. Furthermore, methods for quantifying and predicting multivariate ecology remain rare. Here, we ranked the relative importance of 13 food items for a sample of 88 extant carnivoran mammals and then used Bayesian multilevel modeling to assess whether those rankings could be predicted from dental morphology and body size. Traditional diet categories fail to capture the true multivariate nature of carnivoran diets, but Bayesian regression models derived from living taxa have good predictive accuracy for importance ranks. Using our models to predict the importance of individual food items, the multivariate dietary niche, and the nearest extant analogs for a set of data-deficient extant and extinct carnivoran species confirms long-standing ideas for some taxa but yields new insights into the fundamental dietary niches of others. Our approach provides a promising alternative to traditional dietary classifications. Importantly, this approach need not be limited to diet but serves as a general framework for predicting multivariate ecology from phenotypic traits.

Rules of teeth development align microevolution with macroevolution in extant and extinct primates.

Macroevolutionary biologists have classically rejected the notion that higher-level patterns of divergence arise through microevolutionary processes acting within populations. For morphology, this consensus partly derives from the inability of quantitative genetics models to correctly predict the behaviour of evolutionary processes at the scale of millions of years. Developmental studies (evo-devo) have been proposed to reconcile micro- and macroevolution. However, there has been little progress in establishing a formal framework to apply evo-devo models of phenotypic diversification. Here we reframe this issue by asking whether using evo-devo models to quantify biological variation can improve the explanatory power of comparative models, thus helping us bridge the gap between micro- and macroevolution. We test this prediction by evaluating the evolution of primate lower molars in a comprehensive dataset densely sampled across living and extinct taxa. Our results suggest that biologically informed morphospaces alongside quantitative genetics models allow a seamless transition between the micro- and macroscales, whereas biologically uninformed spaces do not. We show that the adaptive landscape for primate teeth is corridor like, with changes in morphology within the corridor being nearly neutral. Overall, our framework provides a basis for integrating evo-devo into the modern synthesis, allowing an operational way to evaluate the ultimate causes of macroevolution.

Extant species fail to estimate ancestral geographical ranges at older nodes in primate phylogeny.

A clade's evolutionary history is shaped, in part, by geographical range expansion, sweepstakes dispersal and local extinction. A rigorous understanding of historical biogeography may therefore yield insights into macroevolutionary dynamics such as adaptive radiation. Modern historical biogeographic analyses typically fit statistical models to molecular phylogenies, but it remains unclear whether extant species provide sufficient signal or if well-sampled phylogenies of extinct and extant taxa are necessary to produce meaningful estimates of past ranges. We investigated the historical biogeography of Primates and their euarchontan relatives using a novel meta-analytical phylogeny of over 900 extant (n= 419) and extinct (n = 483) species spanning their entire evolutionary history. Ancestral range estimates for young nodes were largely congruent with those derived from molecular phylogeny. However, node age exerts a significant effect on ancestral range estimate congruence, and the probability of congruent inference dropped below 0.5 for nodes older than the late Eocene, corresponding to the origins of higher-level clades. Discordance was not observed in analyses of extinct taxa alone. Fossils are essential for robust ancestral range inference and biogeographic analyses of extant clades originating in the deep past should be viewed with scepticism without them.