Multivariate Analysis of Ecological Data with Ade4 - (Paperback)
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<p/><br></br><p><b> Book Synopsis </b></p></br></br><p>This book introduces the ade4 package for R which provides multivariate methods for the analysis of ecological data. It is implemented around the mathematical concept of the duality diagram, and provides a unified framework for multivariate analysis. The authors offer a detailed presentation of the theoretical framework of the duality diagram and also of its application to real-world ecological problems. These two goals may seem contradictory, as they concern two separate groups of scientists, namely statisticians and ecologists. However, statistical ecology has become a scientific discipline of its own, and the good use of multivariate data analysis methods by ecologists implies a fair knowledge of the mathematical properties of these methods.</p>The organization of the book is based on ecological questions, but these questions correspond to particular classes of data analysis methods. The first chapters present both usual and multiway data analysis methods. Further chapters are dedicated for example to the analysis of spatial data, of phylogenetic structures, and of biodiversity patterns. One chapter deals with multivariate data analysis graphs.<p></p>In each chapter, the basic mathematical definitions of the methods and the outputs of the R functions available in ade4 are detailed in two different boxes. The text of the book itself can be read independently from these boxes. Thus the book offers the opportunity to find information about the ecological situation from which a question raises alongside the mathematical properties of methods that can be applied to answer this question, as well as the details of software outputs. Each example and all the graphs in this book come with executable R code. <p></p><p/><br></br><p><b> From the Back Cover </b></p></br></br><p></p><p>This book introduces the ade4 package for R which provides multivariate methods for the analysis of ecological data. It is implemented around the mathematical concept of the duality diagram, and provides a unified framework for multivariate analysis. The authors offer a detailed presentation of the theoretical framework of the duality diagram and also of its application to real-world ecological problems. These two goals may seem contradictory, as they concern two separate groups of scientists, namely statisticians and ecologists. However, statistical ecology has become a scientific discipline of its own, and the good use of multivariate data analysis methods by ecologists implies a fair knowledge of the mathematical properties of these methods.</p><p>The organization of the book is based on ecological questions, but these questions correspond to particular classes of data analysis methods. The first chapters present both usual and multiway data analysis methods. Further chapters are dedicated for example to the analysis of spatial data, of phylogenetic structures, and of biodiversity patterns. One chapter deals with multivariate data analysis graphs.</p><p>In each chapter, the basic mathematical definitions of the methods and the outputs of the R functions available in ade4 are detailed in two different boxes. The text of the book itself can be read independently from these boxes. Thus the book offers the opportunity to find information about the ecological situation from which a question raises alongside the mathematical properties of methods that can be applied to answer this question, as well as the details of software outputs. Each example and all the graphs in this book come with executable R code.</p><br><p></p><p/><br></br><p><b> About the Author </b></p></br></br><b>Jean Thioulouse</b> holds a PhD (1985) and a Habilitation Thesis (1996) from the University of Lyon, France. He is the author of more than 100 scientific papers (orcid.org/0000-0001-7664-0598) and has received grants from various institutions, including the University of Lyon, the CNRS and the French National Research Agency. He is senior scientist at the CNRS, currently working in the Biometry and Evolutionary Biology Department of the University of Lyon. His research activity is focused on the development of statistical methods applied to the analysis of ecological data.<br><b>Stéphane Dray</b> holds a PhD (2003) and a Habilitation Thesis (2016) from the University of Lyon, France. He is senior scientist at the CNRS, currently working in the Biometry and Evolutionary Biology Department of the University of Lyon. He is a statistical ecologist mainly interested by the analysis of spatial and multivariate data, with a special emphasis on community ecology. He co-authored several R packages including ade4, adegraphics, adespatial and adephylo. <br><b>Anne-Béatrice Dufour</b> holds a PhD (1989) and a Habilitation Thesis (1996) from the University of Lyon, France. She is Associate Professor in the department of Biometry and Evolutionary Biology of the University of Lyon. She has over 30 years of academic and consulting experience in statistics and multivariate analysis. Her research interest is mainly focused on the methodology of multivariate analyses. She co-authored the ade4 package R.<br><b>Aurélie Siberchicot</b> is statistical and computer engineer in the Biometry and Evolutionary Biology Department of the University of Lyon. She develops, manages and maintains several R packages, resulting from collaborations within the scope of ecology, genomics, epidemiology or eco-toxicology. She is an active member of the R community, locally and nationally.<br><b>Thibaut Jombart </b>is an Associate Professor in outbreak response analytics at the London School of Hygiene and Tropical Medicine, a Lecturer in genetic analysis at Imperial College London, and the founder of the R Epidemics Consortium. His research focuses on the development of evidence synthesis tools for understanding infectious disease dynamics, with a specific focus on emergency outbreak response and humanitarian crises.<br><b>Sandrine Pavoine</b> holds a PhD in statistical ecology (2005) from the University of Lyon and a Habilitation Thesis (2014) from Paris-Sud University in France. Since 2006, she has been Associate Professor at the French National Museum of Natural History in Paris. She develops mathematical approaches that help to analyze biodiversity patterns in space and time. She studies the processes that generate patterns in species, functional and phylogenetic diversity and is also interested in human impacts on biodiversity from local to global scales. She has been awarded by several national prizes and is member of the AcademiaNet portal to Outstanding Female Academics.
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