1. Model-based approaches are increasingly popular in ecological studies. A good example of this trend is the use of joint species distribution models to ask questions about ecological communities. However, most current applications of modelbased methods do not include phylogenies despite the well-known importance of phylogenetic relationships in shaping species distributions and community composition. In part, this is due to a lack of accessible tools allowing ecologists to fit phylogenetic species distribution models easily. 2. To fill this gap, the r package phyr (pronounced fire) implements a suite of metrics, comparative methods and mixed models that use phylogenies to understand and predict community composition and other ecological and evolutionary phenomena. The phyr workhorse functions are implemented in C++ making all calculations and model estimations fast. 3. phyr can fit a variety of models such as phylogenetic joint-species distribution models, spatiotemporal-phylogenetic autocorrelation models, and phylogenetic trait-based bipartite network models. phyr also estimates phylogenetically independent trait correlations with measurement error to test for adaptive syndromes and performs fast calculations of common alpha and beta phylogenetic diversity metrics. All phyr methods are united under Brownian motion or Ornstein-Uhlenbeck models of evolution, and phylogenetic terms are modelled as phylogenetic covariance matrices. 4. The functions and model formula syntax we propose in phyr provide an easy-touse collection of tools that we hope will ignite the use of phylogenies to address a variety of ecological questions.
Abstract. Phylogenetic diversity-area curves are analogous to species-area curves and quantify the relationship between the phylogenetic diversity of species assemblages and the area over which assemblages are sampled. Here, we developed theoretical expectations of these curves under different ecological and macroevolutionary processes. We first used simulations to generate curves expected under three ecological community assembly processes: species sorting, where species have distinct environmental preferences; random placement, where species have no environmental preference but vary in their prevalence across communities; and limited dispersal, where species have no environmental preference but vary in their ability to disperse. Second, we simulated curves expected across regions (e.g., across oceanic islands) that are derived from colonization among regions, within-region speciation, and extinction. We also computed curves for two data sets, one on forest plots along an elevation gradient and the other on Caribbean island Anolis lizards. Of the three ecological processes, only species sorting produced strong relationships between phylogenetic diversity and area. The forest plot curves matched the species-sorting expectation, but only when phylogenetic repulsion (that caused closely related species to be found in similar habitats but not in the same plots) was also included in the simulation. Strong relationships between regional phylogenetic diversity and area were simulated if species were derived only from within-region speciation; colonizations among regions obscured the pattern. Similarly, larger Caribbean islands had more withinisland speciation and contained more Anolis phylogenetic diversity than smaller islands, but colonizations among islands obscured this relationship. This work furthers our understanding of the processes that govern the phylogenetic diversity of ecological communities and biogeographic regions.
Global variation in species richness is widely recognized, but the explanation for what drives it continues to be debated. Previous efforts have focused on a subset of potential drivers, including evolutionary rate, evolutionary time (maximum clade age of species restricted to a region), dispersal (migration from one region to another), ecological factors and climatic stability. However, no study has evaluated these competing hypotheses simultaneously at a broad spatial scale. Here, we examine their relative contribution in determining the richness of the most comprehensive dataset of tetrapods to our knowledge (84% of the described species), distinguishing between the direct influences of evolutionary rate, evolutionary time and dispersal, and the indirect influences of ecological factors and climatic stability through their effect on direct factors. We found that evolutionary time exerted a primary influence on species richness, with evolutionary rate being of secondary importance. By contrast, dispersal did not significantly affect richness patterns. Ecological and climatic stability factors influenced species richness indirectly by modifying evolutionary time (i.e. persistence time) and rate. Overall, our findings suggest that global heterogeneity in tetrapod richness is explained primarily by the length of time species have had to diversify.
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