Numerical Ecology with R
This new edition of Numerical Ecology with R guides readers through an applied exploration of the major methods of multivariate data analysis, as seen through the eyes of three ecologists. It provides a bridge between a textbook of numerical ecology and t
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Daniel Borcard François Gillet Pierre Legendre
Numerical Ecology with R
Second Edition
Use R! Series Editors Robert Gentleman
Kurt Hornik
Giovanni Parmigiani
More information about this series at http://www.springer.com/series/6991
Daniel Borcard • François Gillet • Pierre Legendre
Numerical Ecology with R Second Edition
Daniel Borcard Université de Montréal Département de sciences biologiques Montréal, Québec, Canada H3C 3J7
François Gillet Université Bourgogne Franche-Comté UMR Chrono-environnement Besançon, France
Pierre Legendre Université de Montréal Département de sciences biologiques Montréal, Québec, Canada H3C 3J7
ISSN 2197-5736 ISSN 2197-5744 (electronic) Use R! ISBN 978-3-319-71403-5 ISBN 978-3-319-71404-2 (eBook) https://doi.org/10.1007/978-3-319-71404-2 Library of Congress Control Number: 2017961342 © Springer International Publishing AG, part of Springer Nature 2011, 2018 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by the registered company Springer International Publishing AG part of Springer Nature. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
Ecology is sexy. Teaching ecology is therefore the art of presenting a fascinating topic to well-predisposed audiences. It is not easy: the complexities of modern ecological science go well beyond the introductory chapters taught in high schools or the marvellous movies about ecosystems presented on TV. But well-predisposed audiences are ready to make the effort. Numerical ecology is another story. For some unclear reasons, a majority of ecology-oriented people are strangely reluctant when it comes to quantifying nature and using mathematical tools to help understand it. As if nature was inherently non-mathematical, which it is certainly not: mathematics is the common language of all sc
