Multivariate Analysis of Ecological Communities
The last ten years have seen an enormous increase in the development and application of multivariate methods in ecology; indeed the perceived importance of these methods for elucidating the complex interactions observed in community studies is shown by the number of recent books devoted to introducing the more common multivariate techniques to ecologists (Williams, 1976; Orloci, 1978; Whittaker, 1978a, b; Gauch, 1982; Legendre and Legendre, 1983; Pielou, 1984) and by the chapters added to new editions of more general texts on quantitative ecology (e.g. Greig-Smith, 1983; Kershaw and Looney, 1985). Two reasons can be put forward to explain this development. The first is undoubtedly the increasing availability of cheap computing power which makes it feasible to analyse the large data matrices involved in community studies. The second, perhaps less widely appreciated, is the change in emphasis of theoretical work on multivariate analysis, away from the development of formal statistical models and associated distribution theory towards descrip­ tive techniques for exploring pattern in data sets and providing succinct summaries and displays. This new approach, termed 'pattern analysis' by Williams (1976), has led to a range of statistical techniques which have been enthusiastically taken up by ecologists to replace the collection of ad hoc procedures developed over the years for analysing community data.
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Multivariate Analysis of Ecological Communities
The last ten years have seen an enormous increase in the development and application of multivariate methods in ecology; indeed the perceived importance of these methods for elucidating the complex interactions observed in community studies is shown by the number of recent books devoted to introducing the more common multivariate techniques to ecologists (Williams, 1976; Orloci, 1978; Whittaker, 1978a, b; Gauch, 1982; Legendre and Legendre, 1983; Pielou, 1984) and by the chapters added to new editions of more general texts on quantitative ecology (e.g. Greig-Smith, 1983; Kershaw and Looney, 1985). Two reasons can be put forward to explain this development. The first is undoubtedly the increasing availability of cheap computing power which makes it feasible to analyse the large data matrices involved in community studies. The second, perhaps less widely appreciated, is the change in emphasis of theoretical work on multivariate analysis, away from the development of formal statistical models and associated distribution theory towards descrip­ tive techniques for exploring pattern in data sets and providing succinct summaries and displays. This new approach, termed 'pattern analysis' by Williams (1976), has led to a range of statistical techniques which have been enthusiastically taken up by ecologists to replace the collection of ad hoc procedures developed over the years for analysing community data.
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Multivariate Analysis of Ecological Communities

Multivariate Analysis of Ecological Communities

Multivariate Analysis of Ecological Communities

Multivariate Analysis of Ecological Communities

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Overview

The last ten years have seen an enormous increase in the development and application of multivariate methods in ecology; indeed the perceived importance of these methods for elucidating the complex interactions observed in community studies is shown by the number of recent books devoted to introducing the more common multivariate techniques to ecologists (Williams, 1976; Orloci, 1978; Whittaker, 1978a, b; Gauch, 1982; Legendre and Legendre, 1983; Pielou, 1984) and by the chapters added to new editions of more general texts on quantitative ecology (e.g. Greig-Smith, 1983; Kershaw and Looney, 1985). Two reasons can be put forward to explain this development. The first is undoubtedly the increasing availability of cheap computing power which makes it feasible to analyse the large data matrices involved in community studies. The second, perhaps less widely appreciated, is the change in emphasis of theoretical work on multivariate analysis, away from the development of formal statistical models and associated distribution theory towards descrip­ tive techniques for exploring pattern in data sets and providing succinct summaries and displays. This new approach, termed 'pattern analysis' by Williams (1976), has led to a range of statistical techniques which have been enthusiastically taken up by ecologists to replace the collection of ad hoc procedures developed over the years for analysing community data.

Product Details

ISBN-13: 9780412246500
Publisher: Springer Netherlands
Publication date: 01/31/1987
Series: Population and Community Biology Series , #5
Pages: 206
Product dimensions: 6.10(w) x 9.25(h) x (d)
Age Range: 18 Years

Table of Contents

1 Ecological data.- 1.1 Types of data.- 1.2 Forms of data.- 1.3 Standardization and transformation of data.- 1.4 Constructing association data.- 2 Preliminary inspection of data.- 2.1 Displaying data values.- 2.2 Mapping.- 2.3 Displaying distributions of variables.- 2.4 Bivariate and multivariate displays.- 3 Ordination.- 3.1 Direct gradient analysis.- 3.2 Principal components analysis.- 3.3 Correspondence analysis.- 3.4 Ordination methods when rows or columns are grouped.- 3.5 Principal coordinates analysis.- 3.6 The horseshoe effect.- 3.7 Non-metric ordination.- 3.8 Case studies.- 4 Methods for comparing ordinations.- 4.1 Procrustes rotation.- 4.2 Generalized Procrustes analysis.- 4.3 Comparing ordination methods by multiple Procrustes analysis.- 5 Classification.- 5.1 Agglomerative hierarchical methods.- 5.2 Divisive hierarchical methods.- 5.3 Non-hierarchical classification.- 5.4 Visual displays for classification.- 5.5 Case study.- 5.6 Methods for comparing classifications.- 6 Analysis of asymmetry.- 6.1 Row and column plots.- 6.2 Skew-symmetry analysis.- 6.3 Case studies.- 6.4 A proof of the triangle-area theorem.- 7 Computing.- 7.1 Computing options.- 7.2 Examples of Genstat programs.- 7.3 Handling missing values.- 7.4 Conclusion.- 7.5 List of software.- References.- Appendix Matrix algebra.- A.1 Matrices and vectors.- A.2 Particular forms of matrices.- A.3 Simple matrix operations.- A.4 Simple geometry and some special matrices.- A.5 Matrix inversion.- A.6 Scalar functions of matrices.- A.7 Orthogonal matrices.- A.8 Matrix decompositions.- A.9 Conclusion.
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