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Functional and phylogenetic ecology in R. (English) Zbl 1300.92008

Use R!. New York, NY: Springer (ISBN 978-1-4614-9541-3/pbk; 978-1-4614-9542-0/ebook). xii, 212 p. (2014).
This book is structured in nine interlinked chapters, covering aspects from handling phylogenetic data in R, to quantifying and understanding phylogenetic and functional diversity, partitioning the environmental and spatial components of community diversity, and integrating R with other phylogenetic and functional trait analytical software.
The first chapter explains why phylogenetics and functional traits should be used in ecology, and why R is a good environment for this type of studies; it concludes with a “how to use this book” section.
The second chapter focuses on the management of phylogenetic data in R. The author provides functions and extensive examples from the {ape} library for constructing and plotting phylogenetic trees. Some procedures to manipulate trees and calculate additional information are also discussed. The third chapter deals with phylogenetic diversity. Commencing with background notions on the topic, it makes use of publicly available datasets to discuss tree-based measures, the Faith index and the evolutionary heritage metric. It continues with an extended discussion of distance-based measures of phylogenetic diversity with emphasis on pairwise measures and nearest neighbor measures. The chapter concludes with a set of approaches for comparing metrics, for which the R commands and the graphical outputs on the discussed datasets are included.
The fourth chapter discusses functional diversity with emphasis on quantifying the functional composition of communities, using moments of the trait distributions like the kurtosis, the skewness, the mean and the standard deviation. Next, for measuring the functional diversity, the dendrogram-based and the Euclidean distance-based approaches are compared using generated trait distances matrices and dendrograms. The phylogenetic diversity is computed using either the pairwise and the nearest neighbor measures or ranges and convex hulls. The chapter concludes with the comparison of metrics of functional diversity.
The fifth chapter focuses on phylogenetic and functional beta diversity, described using tree-based measures such as UniFrac or the phylogenetic Soreson’s index. The discussion of distance-based measures includes the pairwise and nearest neighbor measures. The author also presents other metrics such as the Rao’s index and concludes with a comparison of the proposed approaches.
The sixth chapter discusses the use of null models for the diversity analysis. Following a set of arguments to support the use of null models for phylogenetic and functional analyses, the author presents the theoretical side of calculating the standardized effect size, the quantiles and \(p\)-values. Next, the classes of null models are presented and the use of constrained and unconstrained randomizations for these models is discussed. The author also includes randomization approaches for functional trait data and for alpha and beta diversity.
The seventh chapter introduces comparative methods for the quantification of the phylogenetic signal and includes trait correlations based on independent constraints, generalized least squares, eigenvector regression and test such as the Mantel test, Blomberg’s \(K\) and significance test, Pagel’s \(\lambda\) and standardized contrast variance, unstandardized contrast means and randomization tests. The chapter concludes with the notions of timing and magnitude quantification of the trait divergences.
The eighth chapter explains approaches for partitioning phylogenetic, functional, environmental and spatial components of community diversity. First the author describes the partitioning of functional alpha diversity, using multiple regression and distance matrices or principal coordinates of neighbor matrices and forward selection. Next, the variance partitioning is introduced and similar approaches are presented for beta diversity. The chapter concludes with an example on the role of abiotic filtering.
In the ninth chapter the author reviews other phylogenetic and functional trait analytical software that could be integrated with R. Phylocom detailed examples for the notions introduced in the previous chapters are presented and discussed.
Each chapter is built in a lecture-style incremental manner and does not assume an extensive previous knowledge of R. All chapters conclude with a series of exercises that consolidate the presented notions. This approach makes the book suitable for undergraduates and postgraduates, as well as researchers with an interest in the field. Its structure and detailed examples supported with exercises make it a timely addition for the scientific community.

MSC:

92-02 Research exposition (monographs, survey articles) pertaining to biology
92D15 Problems related to evolution
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