Numerical Ecology with R

François Gillet is professor of Community Ecology and Ecological Modelling at Université de Franche-Comté, Besançon, France. Pierre Legendre is professor of Quantitative Biology and Ecology at Université de Montréal, Fellow of the Royal Society of Canada, and ISI Highly Cited Researcher in Ecology/E...

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Bibliographic Details
Main Authors: Borcard, Daniel, Gillet, Francois (Author), Legendre, Pierre (Author)
Format: eBook
Language:English
Published: New York, NY Springer New York 2011, 2011
Edition:1st ed. 2011
Series:Use R!
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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245 0 0 |a Numerical Ecology with R  |h Elektronische Ressource  |c by Daniel Borcard, Francois Gillet, Pierre Legendre 
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505 0 |a Introduction -- Exploratory data analysis -- Association measures and matrices -- Cluster analysis -- Unconstrained ordination -- Canonical ordination -- Spatial analysis of ecological data.    
653 |a Theoretical Ecology/Statistics 
653 |a Environmental monitoring 
653 |a Statistics  
653 |a Biostatistics 
653 |a Forestry 
653 |a Forestry 
653 |a Biostatistics 
653 |a Epidemiology 
653 |a Epidemiology 
653 |a Ecology  
653 |a Statistics for Life Sciences, Medicine, Health Sciences 
653 |a Monitoring/Environmental Analysis 
700 1 |a Gillet, Francois  |e [author] 
700 1 |a Legendre, Pierre  |e [author] 
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520 |a François Gillet is professor of Community Ecology and Ecological Modelling at Université de Franche-Comté, Besançon, France. Pierre Legendre is professor of Quantitative Biology and Ecology at Université de Montréal, Fellow of the Royal Society of Canada, and ISI Highly Cited Researcher in Ecology/Environment 
520 |a Numerical Ecology with R provides a long-awaited bridge between a textbook in Numerical Ecology and the implementation of this discipline in the R language. After short theoretical overviews, the authors accompany the users through the exploration of the methods by means of applied and extensively commented examples. Users are invited to use this book as a teaching companion at the computer. The travel starts with exploratory approaches, proceeds with the construction of association matrices, then addresses three families of methods: clustering, unconstrained and canonical ordination, and spatial analysis. All the necessary data files, the scripts used in the chapters, as well as the extra R functions and packages written by the authors, can be downloaded from a web page accessible through the Springer web site(http://adn.biol.umontreal.ca/~numericalecology/numecolR/).  
520 |a This book is aimed at professional researchers, practitioners, graduate students and teachers in ecology, environmental science and engineering, and in related fields such as oceanography, molecular ecology, agriculture and soil science, who already have a background in general and multivariate statistics and wish to apply this knowledge to their data using the R language, as well as people willing to accompany their disciplinary learning with practical applications. People from other fields (e.g. geology, geography, paleoecology, phylogenetics, anthropology, the social and education sciences, etc.) may also benefit from the materials presented in this book. The three authors teach numerical ecology, both theoretical and practical, to a wide array of audiences, in regular courses in their Universities and in short courses given around the world. Daniel Borcard is lecturer of Biostatistics and Ecology and researcher in Numerical Ecology at Université de Montréal, Québec, Canada.