Multivariate Analysis of Ecological Communities PDF Download

Author: P.G.N. Digby
Publisher: Springer Science & Business Media
ISBN: 9400931352
Category : Science
Languages : en
Pages : 215

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Author: Hugh G. Gauch
Publisher: Cambridge University Press
ISBN: 9780521282406
Category : Mathematics
Languages : en
Pages : 320

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Book Description
A full description of computer-based methods of analysis used to define and solve ecological problems. Multivariate techniques permit summary of complex sets of data and allow investigation of many problems which cannot be tackled experimentally because of practical restraints.

Author: Bruce McCune
Publisher: Mjm Software Design
ISBN: 9780972129008
Category : Biotic communities
Languages : en
Pages : 300

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Book Description
Analysis of Ecological Communities offers a rationale and guidance for selecting appropriate, effective, analytical methods in community ecology. The book is suitable as a textbook and reference book on methods for multivariate analysis of ecological communities and their environments. The book covers distance measures, data transformation, outlier analysis, coordination, cluster analysis, PCA RA, CA, DCA, NMS, NMS, CCA, Bray-Curtis, MRPP, Mantel test, discriminant analysis, twinspan, classification and regression trees, structural equation modeling, and more. It also includes brief treatments of community sampling and diversity measures. The 304 page book is richly illustrated. It provides many examples from the literature and demonstrations of basic principles with simulated and real data sets.

Author: Jan Lepš
Publisher: Cambridge University Press
ISBN: 9780521891080
Category : Computers
Languages : en
Pages : 296

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Table of contents

Author: Michael Greenacre
Publisher: Fundacion BBVA
ISBN: 8492937505
Category : Ecology
Languages : es
Pages : 336

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Book Description
La diversidad biológica es fruto de la interacción entre numerosas especies, ya sean marinas, vegetales o animales, a la par que de los muchos factores limitantes que caracterizan el medio que habitan. El análisis multivariante utiliza las relaciones entre diferentes variables para ordenar los objetos de estudio según sus propiedades colectivas y luego clasificarlos; es decir, agrupar especies o ecosistemas en distintas clases compuestas cada una por entidades con propiedades parecidas. El fin último es relacionar la variabilidad biológica observada con las correspondientes características medioambientales. Multivariate Analysis of Ecological Data explica de manera completa y estructurada cómo analizar e interpretar los datos ecológicos observados sobre múltiples variables, tanto biológicos como medioambientales. Tras una introducción general a los datos ecológicos multivariantes y la metodología estadística, se abordan en capítulos específicos, métodos como aglomeración (clustering), regresión, biplots, escalado multidimensional, análisis de correspondencias (simple y canónico) y análisis log-ratio, con atención también a sus problemas de modelado y aspectos inferenciales. El libro plantea una serie de aplicaciones a datos reales derivados de investigaciones ecológicas, además de dos casos detallados que llevan al lector a apreciar los retos de análisis, interpretación y comunicación inherentes a los estudios a gran escala y los diseños complejos.

Author: Jean Thioulouse
Publisher: Springer
ISBN: 1493988506
Category : Medical
Languages : en
Pages : 334

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Book Description
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. 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. 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.

Author: Petr Šmilauer
Publisher: Cambridge University Press
ISBN: 110769440X
Category : Mathematics
Languages : en
Pages : 375

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Book Description
An accessible introduction to the theory and practice of multivariate analysis for graduates, researchers and professionals dealing with ecological problems.

Author: JeriLynn E. Peck
Publisher:
ISBN:
Category : Biotic communities
Languages : en
Pages : 192

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Book Description

Author: Mark Gardener
Publisher: Pelagic Publishing Ltd
ISBN: 1907807632
Category : Science
Languages : en
Pages : 553

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Book Description
Interactions between species are of fundamental importance to all living systems and the framework we have for studying these interactions is community ecology. This is important to our understanding of the planets biological diversity and how species interactions relate to the functioning of ecosystems at all scales. Species do not live in isolation and the study of community ecology is of practical application in a wide range of conservation issues. The study of ecological community data involves many methods of analysis. In this book you will learn many of the mainstays of community analysis including: diversity, similarity and cluster analysis, ordination and multivariate analyses. This book is for undergraduate and postgraduate students and researchers seeking a step-by-step methodology for analysing plant and animal communities using R and Excel. Microsoft's Excel spreadsheet is virtually ubiquitous and familiar to most computer users. It is a robust program that makes an excellent storage and manipulation system for many kinds of data, including community data. The R program is a powerful and flexible analytical system able to conduct a huge variety of analytical methods, which means that the user only has to learn one program to address many research questions. Its other advantage is that it is open source and therefore completely free. Novel analytical methods are being added constantly to the already comprehensive suite of tools available in R. Mark Gardener is both an ecologist and an analyst. He has worked in a range of ecosystems around the world and has been involved in research across a spectrum of community types. His knowledge of R is largely self-taught and this gives him insight into the needs of students learning to use R for complicated analyses.

Author: Daniel Borcard
Publisher: Springer
ISBN: 331971404X
Category : Mathematics
Languages : en
Pages : 444

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Book Description
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 the implementation of this discipline in the R language. The book begins by examining some exploratory approaches. It proceeds logically with the construction of the key building blocks of most methods, i.e. association measures and matrices, and then submits example data to three families of approaches: clustering, ordination and canonical ordination. The last two chapters make use of these methods to explore important and contemporary issues in ecology: the analysis of spatial structures and of community diversity. The aims of methods thus range from descriptive to explanatory and predictive and encompass a wide variety of approaches that should provide readers with an extensive toolbox that can address a wide palette of questions arising in contemporary multivariate ecological analysis. The second edition of this book features a complete revision to the R code and offers improved procedures and more diverse applications of the major methods. It also highlights important changes in the methods and expands upon topics such as multiple correspondence analysis, principal response curves and co-correspondence analysis. New features include the study of relationships between species traits and the environment, and community diversity analysis. 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. Users are invited to use this book as a teaching companion at the computer. All the necessary data files, the scripts used in the chapters, as well as extra R functions and packages written by the authors of the book, are available online (URL: http://adn.biol.umontreal.ca/~numericalecology/numecolR/).