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Multivariate Analysis of Ecological Data using CANOCO

$162.00 (C)

  • Authors:
  • Jan Lepš, University of South Bohemia, Czech Republic
  • Petr Šmilauer, University of South Bohemia, Czech Republic
  • Date Published: June 2003
  • availability: Available
  • format: Hardback
  • isbn: 9780521814096

$ 162.00 (C)
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About the Authors
  • Multivariate statistical methods are described in this study and advice is given on how best to apply these methods using CANOCO software. Data sets and program files for the case studies are provided on a supporting website. The book is useful to anyone studying complex ecological problems, such as the variation of biotic communities with environmental conditions or their response to experimental manipulations. It is primarily targeted at ecologists who need to analyze data resulting from field observations and experiments.

    • Written for ecologists - no background in statistics necessary
    • Contains hands-on tutorials
    • Datasets are provided
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    Reviews & endorsements

    "The book is helpful for users interested in analyses of distributions of qualitative variables." Ole Wendroth, University of Kentucky, Vadose Zone Journal

    "I sincerely recommend the book to all graduate students and scientists working with ecological data." Écoscience

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    Product details

    • Date Published: June 2003
    • format: Hardback
    • isbn: 9780521814096
    • length: 282 pages
    • dimensions: 254 x 178 x 17 mm
    • weight: 0.71kg
    • contains: 110 b/w illus.
    • availability: Available
  • Table of Contents

    1. Introduction and data manipulation
    2. Experimental design
    3. Basics of gradient analysis
    4. Using Canoco
    5. Constrained ordination and permutation tests
    6. Similarity measures
    7. Classification methods
    8. Regression methods
    9. Advanced use of ordination
    10. Visualising multivariate data
    11. Case study 1: variation in forest bird assemblages
    12. Case study 2: search for community composition patterns and their environmental correlates: vegetation of spring meadows
    13. Case study 3: separating the effects of explanatory variables
    14. Case study 4: evaluation of experiments in randomised complete blocks
    15. Case study 5: analysis of repeated observations of species composition from factorial experiment
    16. Case study 6: hierarchical analysis of crayfish community variation
    17. Case study 7: differentiating two species and their hybrids with discriminant analysis.

  • Authors

    Jan Lepš, University of South Bohemia, Czech Republic
    Dr Jan Leps is Professor of Ecology in the Department of Botany at the University of South Bohemia, Czech Republic.

    Petr Šmilauer, University of South Bohemia, Czech Republic
    Dr Petr Smilauer is Lecturer in Multivariate Statistics at the University of South Bohemia, Czech Republic.

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