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This chapter explains how to build a phylogeny for a certain set of species. A phylogenetic tree is a representation of species interrelatedness and conveys information about which taxa share recent common ancestors, which evolutionary groups (clades) species belong to, and the distances (time, genetic, or character differences) separating species. The chapter first considers two R packages called ape and picante for use in analysis of the R phylogenetic object (referred to as a phylo object type), along with a few other packages, before discussing the steps in reconstructing phylogenetic relationships. It also evaluates some tree-building approaches that are easily implemented in R, including distance-based methods and maximum likelihood methods. Finally, it describes ways of finding and adapting available phylogenetic trees, together with tree scaling and rate smoothing.

This chapter explains how phylogenetic information can be used to make better conservation decisions. Evidence shows that human-caused climate change is likely to be the dominant cause of extinction in the near future. Phylogeny can provide a powerful tool for aiding decision making in species conservation. The chapter first considers the importance of preserving evolutionary history by focusing on the tree of life, the phylogenetic tree connecting all living organisms that provides a powerful metaphor for conservation biology. It then examines phylogenetically based metrics for quantifying evolutionary history, including phylogenetic diversity for evaluating sites and evolutionary distinctiveness for comparing species. It also discusses the integration of evolutionary history with extinction probabilities for conservation prioritization using relative extinction risk to weight evolutionary distinctiveness, or EDGE (evolutionarily distinct and globally endangered). Finally, it describes how to prioritize biodiversity hotspots of evolutionary distinctiveness and how to apply metrics to conservation prioritization.

This chapter examines a variety of methods for detecting the patterns of evolution of a certain trait. It first considers common metrics for evaluating phylogenetic signal and compares fit of alternative evolutionary models. When trait data deviates significantly from assumptions of Brownian motion (BM), the phylogenetic distances separating taxa on a time-calibrated tree might not accurately capture phenotypic distance between species. If we are able to identify the correct model of trait evolution, we can transform the branch lengths on the phylogenetic tree to match. Nevertheless, we might still favor using the untransformed tree because complex evolutionary models might not generalize across traits. The chapter also reviews alternative models of trait evolution, including a model of constrained evolution, multirate and multioptima models, speciational models, and white noise model. Finally, it looks at some of the common models for reconstructing ancestral states for discrete and continuous data.

This chapter examines how phylogenetic approaches can address both ecological character displacement and community-wide character displacement. In ecological character displacement, selection might drive the divergence of ecological phenotypes by negative antagonistic interactions that reduce competition between sympatric populations utilizing the same resource base. In community-wide character displacement, ecological divergence occurs in allopatry, and competition filters species into communities based upon their trait values. The geographic distribution of a species reflects multiple factors, including its strength of phylogenetic niche conservatism and the geography of present day climate, its dispersal ability, and the history of speciation. This chapter considers the effect of competition in the native range, focusing on a scenario in which the evolution of species traits may itself be a product of species interactions. It shows that phylogenetic methods can additionally provide insights into how species interactions might shape trait evolution and even illuminate the process of speciation itself.

This chapter examines how phylogenetic diversity changes across spatial and temporal gradients. Spatial ecophylogenetic patterns can reveal how different processes shape ecological communities. Metacommunity ecology reinvigorated the search for general mechanisms that create diversity and structural differences among communities, and by using phylogenetic patterns we can understand how shared traits and evolution inform community differences. The chapter first considers phylobetadiversity as a measure of phylogenetic turnover before discussing two types of phylobetadiversity metrics, diversity partitioning and pairwise distances. It also analyzes the influence of spatial scale on phylogenetic patterns, focusing on the scale dependency of phylogenetic patterns, and concludes with an overview of phylogenetic diversity–area relationships.

This chapter examines the logic of null modeling for phylogenetic tests. Developing null expectations for community phylogenetic patterns from randomization procedures is the cornerstone for many ecophylogenetic analysis. The chapter advocates an approach that explicitly considers multiple randomizations to better understand what aspects of community and phylogenetic structure determine observed patterns. It first provides a brief historical overview of randomization tests in ecology, focusing on two important academic conflicts that highlight the need for using randomizations in ecological analysis: the first relates to species–genus ratios and competition between close relatives, and the second deals with co-occurrence patterns and competitive coexistence. It then explains how community data and phylogenetic data can be randomized, taking into account randomizations to test trait data, altering the phylogenetic tree, and other randomizations and inference issues. It also discusses some important considerations for constructing the species pool to be used in the randomization tests.

This chapter reviews the history of the use of phylogenetics in ecology, beginning with a discussion of early attempts to classify the diversity of life and the development of evolutionary theory. In particular, it examines how early taxonomists, starting with Carl Linnaeus, have grouped species by similarity in their traits and how early ecologists and biologists such as Charles Darwin recognized the importance of relatedness in influencing ecological interactions and species distributions. The chapter proceeds by focusing on the introduction of the neutral theory of biodiversity into mainstream ecology and the development of the niche-based model of community assembly. It also considers how some ecologists questioned the relevance of phylogenetic corrections for ecology and concludes by analyzing the emergence of ecological phylogenetics or ecophylogenetics.

This book has explored the major methods and concepts in the field of ecophylogenetics. It has considered many of the common statistics and metrics used by ecologists when testing ecophylogenetic hypotheses at both small and large scales. The power of this approach is predicated on the assumption that phylogeny provides information on the evolutionary history of traits that cannot be inferred simply from community data. This concluding chapter reviews some of the advances that have been made in terms of predicting ecology from evolutionary patterns, combining trait and phylogenetic information, and developing a more predictive science of climate change and the biology of species invasions. It also discusses several possible trajectories for ecophylogenetic analyses in the future that will be important in moving the field forward. Finally, it looks at the benefits of a synthesis between ecology and evolution.

This is the first book to critically review the application of phylogenetic methods in ecology, and it serves as a primer to working ecologists and students of ecology wishing to understand these methods. The book demonstrates how phylogenetic information is transforming ecology by offering fresh ways to estimate the similarities and differences among species, and by providing deeper, evolutionary-based insights on species distributions, coexistence, and niche partitioning. It examines this emerging area's explosive growth, allowing for this new body of hypotheses testing. It systematically looks at all the main areas of current ecophylogenetic methodology, testing, and inference. Each chapter covers a unique topic, emphasizes key assumptions, and introduces the appropriate statistical methods and null models required for testing phylogenetically informed hypotheses. The applications presented throughout are supported and connected by examples relying on real-world data that have been analyzed using the open-source programming language, R. Showing how phylogenetic methods are shedding light on fundamental ecological questions related to species coexistence, conservation, and global change, the book will interest anyone who thinks that evolution might be important in their data.

This chapter examines the use of phylogenetic methods to explain macroevolutionary trends in speciation, extinction, and the distribution of phylogenetic diversity across space and through time. The diversity of life is unevenly distributed across the globe. Species richness tends to be higher at lower latitudes and elevations, and the distribution of life forms also varies across space. For example, Foster's rule suggests that on islands small species evolve to become bigger, while large species evolve to become smaller. Equally, the distribution of evolutionary history shows large spatial variation, reflecting the histories of speciation, extinction, and dispersal. This chapter first considers how large, global phylogenies make it possible to map the distribution of phylogenetic diversity and develop a conservation strategy to maximize coverage of the tree of life. It then discusses the variation in diversification across spatiotemporal gradients and shows that phylogenetic diversity covaries significantly with taxonomic richness.

This chapter discusses the use of phylogenetic distances to infer mechanisms of ecological assembly. Mechanisms influencing patterns of community assembly act on the ecological similarities and differences of organisms, and not on the number of species. Phylogenetic patterns of relatedness have provided an especially useful and popular approach to quantifying expected species ecological differences for examining community assembly. Over the past decade, phylogenetic information has been widely used in community assembly studies to test a basic set of hypotheses about the relatedness of co-occurring species. This chapter considers two kinds of metrics employing phylogenetic information: those that examine patterns of relatedness by measuring phylogenetic distances among species, and those that provide an index of phylodiversity within an assemblage by accounting for the distribution of or evenness in edge lengths.