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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Aim Examining the biogeography of body size is crucial for understanding how animal communities are assembled and maintained. In tetrapods, body size varies predictably with temperature, moisture, productivity seasonality and topographical complexity. Although millennial‐scale human pressures are known to have led to the extinction of primarily large‐bodied tetrapods, human pressure history is often ignored in studies of body size that focus on extant species. Here, we analyse 11,377 tetrapod species of the Western Hemisphere to test whether millennial‐scale human pressures have left an imprint on contemporary body mass distributions throughout the tetrapod clade. Location Western Hemisphere. Time period Contemporary. Major taxa studied Tetrapods (birds, mammals, amphibians and reptiles). Methods We mapped the distribution of assemblage‐level median tetrapod body mass at a resolution of 110 km across the Western Hemisphere. We then generated multivariate models of median body mass as a function of temperature, moisture, productivity seasonality and topographical complexity, as well as two variables capturing the history of human population density and human‐induced land conversion over the past 12,000 years. We controlled for both spatial and phylogenetic autocorrelation effects on body mass–environment relationships. Results Human pressures explain a small but significant portion of geographical variation in median body mass that cannot be explained by ecological constraints alone. Overall, the median body mass of tetrapod assemblages is lower than expected in areas with a longer history of high human population density and land conversion, but there are important differences among tetrapod classes. Main conclusions At this broad scale, the effect of human pressure history on tetrapod body mass is low relative to that of ecology. However, ignoring spatial variation in the history of human pressure is likely to lead to bias in studies of the present‐day functional composition of tetrapod assemblages, at least in areas that have long been influenced by humans.

Human land use causes major changes in species abundance and composition, yet native and exotic species can exhibit different responses to land use change. Native populations generally decline in human-impacted habitats while exotic species often benefit. In this study, we assessed the effects of human land use on exotic and native reptile diversity, including functional diversity, which relates to the range of habitat use strategies in biotic communities. We surveyed 114 reptile communities from localities that varied in habitat structure and human impact level on two Caribbean islands, and calculated species richness, overall abundance, and evenness for every plot. Functional diversity indices were calculated using published trait data, which enabled us to detect signs of trait filtering associated with impacted habitats. Our results show that environmental variation among sampling plots was explained by two Principal Component Analysis (PCA) ordination axes related to habitat structure (i.e., forest or nonforest) and human impact level (i.e., addition of man-made constructions such as roads and buildings). Several diversity indices were significantly correlated with the two PCA axes, but exotic and native species showed opposing responses. Native species reached the highest abundance in forests, while exotic species were absent in this habitat. Human impact was associated with an increase in exotic abundance and species richness, while native species showed no significant associations. Functional diversity was highest in nonforested environments on both islands, and further increased on St. Martin with the establishment of functionally unique exotic species in nonforested habitat. Habitat structure, rather than human impact, proved to be an important agent for environmental filtering of traits, causing divergent functional trait values across forested and nonforested environments. Our results illustrate the importance of considering various elements of land use when studying its impact on species diversity and the establishment and spread of exotic species.

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 model-based 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 lack of accessible tools allowing ecologists to t phylogenetic species distribution models easily. . To ll this gap, the R package phyr (pronounced re) 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. . phyr can t 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.. The functions and model formula syntax we propose in phyr serves as a simple and uni ed framework that ignites the use of phylogenies to address a variety of ecological questions.

BackgroundEcological research often involves sampling and manipulating non-model organisms that reside in heterogeneous environments. As such, ecologists often adapt techniques and ideas from industry and other scientific fields to design and build equipment, tools, and experimental contraptions custom-made for the ecological systems under study. Three-dimensional (3D) printing provides a way to rapidly produce identical and novel objects that could be used in ecological studies, yet ecologists have been slow to adopt this new technology. Here, we provide ecologists with an introduction to 3D printing.ResultsFirst, we give an overview of the ecological research areas in which 3D printing is predicted to be the most impactful and review current studies that have already used 3D printed objects. We then outline a methodological workflow for integrating 3D printing into an ecological research program and give a detailed example of a successful implementation of our 3D printing workflow for 3D printed models of the brown anole, Anolis sagrei, for a field predation study. After testing two print media in the field, we show that the models printed from the less expensive and more sustainable material (blend of 70% plastic and 30% recycled wood fiber) were just as durable and had equal predator attack rates as the more expensive material (100% virgin plastic).ConclusionsOverall, 3D printing can provide time and cost savings to ecologists, and with recent advances in less toxic, biodegradable, and recyclable print materials, ecologists can choose to minimize social and environmental impacts associated with 3D printing. The main hurdles for implementing 3D printing—availability of resources like printers, scanners, and software, as well as reaching proficiency in using 3D image software—may be easier to overcome at institutions with digital imaging centers run by knowledgeable staff. As with any new technology, the benefits of 3D printing are specific to a particular project, and ecologists must consider the investments of developing usable 3D materials for research versus other methods of generating those materials.Electronic supplementary materialThe online version of this article (10.1186/s12898-018-0190-z) contains supplementary material, which is available to authorized users.