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Introduction
This new edition of Numerical Ecology with R guidesreaders through an applied exploration of the major methods of multivariatedata analysis, as seen through the eyes of three ecologists. It provides abridge between a textbook of numerical ecology and the implementation of thisdiscipline in the R language. The book begins by examining some exploratoryapproaches. It proceeds logically with the construction of the key buildingblocks of most methods, i.e. association measures and matrices, and thensubmits example data to three families of approaches: clustering, ordinationand canonical ordination. The last two chapters make use of these methods toexplore important and contemporary issues in ecology: the analysis of spatialstructures and of community diversity. The aims of methods thus range fromdescriptive to explanatory and predictive and encompass a wide variety ofapproaches that should provide readers with an extensive toolbox that canaddress a wide palette of questions arising in contemporary multivariateecological analysis. The second edition of this book features a completerevision to the R code and offers improved procedures and more diverseapplications of the major methods. It also highlights important changes in themethods and expands upon topics such as multiple correspondence analysis,principal response curves and co-correspondence analysis. New features includethe study of relationships between species traits and the environment, andcommunity diversity analysis.
This book is aimed at professional researchers,practitioners, graduate students and teachers in ecology, environmental scienceand engineering, and in related fields such as oceanography, molecular ecology,agriculture and soil science, who already have a background in general andmultivariate statistics and wish to apply this knowledge to their data usingthe R language, as well as people willing to accompany their disciplinarylearning with practical applications. People from other fields (e.g. geology,geography, paleoecology, phylogenetics, anthropology, the social and educationsciences, etc.) may also benefit from the materials presented in this book.Users are invited to use this book as a teaching companion at the computer. Allthe necessary data files, the scripts used in the chapters, as well as extra Rfunctions and packages written by the authors of the book, are available online(URL: http://adn.biol.umontreal.ca/~numericalecology/numecolR/).
Keywords
Numerical Ecology R Language R Code EcologyEnvironmental Science Data Analysis Cluster Analysis Unconstrained OrdinationCanonical Ordination Spatial Analysis Multiple Correspondence AnalysisPrinciple Response Curves
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