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新书资源(2010年11月)

Data analysis in vegetation ecology / Otto Wildi. — Oxford : Wiley-Blackwell, 2010. – (58.851/W673)

Contents

    Contents
    
    Preface
    List of Figures
    List of Tables
    1 Introduction
    2 Patterns in Vegetation Ecology
    2.1 Pattern recognition
    2.2 Interpretation of patterns
    2.3 Sampling for pattern recognition
    3 Transformation
    3.1 Data types
    3.2 Scalar transformation and the species enigma
    3.3 Vector transformation
    3.4 Example: Transformation of plant cover data
    4 Multivariate Comparison
    4.1 Resemblance in multivariate space
    4.2 Geometric approach
    4.3 Contingency testing
    4.4 Product moments
    4.5 The resemblance matrix
    4.6 Assessing the quality of classifications
    5 0rdinaUon
    5.1 Why ordination?
    5.2 Principal component analysis (PCA)
    5.3 Principal coordinates analysis (PCOA)
    5.4 Correspondence analysis (CA)
    5.5 The horseshoe or arch effect
    5.6 Ranking by orthogonal components
    6 Classification
    6.1 Group structures
    6.2 Linkage clustering
    6.3 Minimum-variance clustering
    6.4 Average-Linkage clustering: UPGMA, WPGMA, UPGMC and WPGMC
    6.5 Forming groups
    6.6 Structured synoptic tables
    7 3oining Ecological Patterns
    7.1 Pattern and ecological response
    7.2 Analysis of variance
    7.3 Correlating resemblance matrices
    7.4 Contingency tables
    7.5 Constrained ordination
    8 Static Explanatory Modelling
    8.1 Predictive or explanatory?
    8.2 The Bayes probability model
    8.3 Predicting wetland vegetation (example)
    9 Assessing Vegetation Change in Time
    9.1 Coping with time
    9.2 Rate of change and trend
    9.3 Markov models
    9.4 Space-for-time substitution
    9.5 Dynamics in pollen diagrams (example)
    10 Dynamic Modelling
    10.1 Simulating time processes
    10.2 Including space processes
    10.3 Processes in the Swiss National Park (SNP)
    11 Large Data Sets: Wetland Patterns
    11.1 Large data sets differ
    11.2 Phytosociology revisited
    11.3 Suppressing outliers
    11.4 Replacing species with new attributes
    11.5 Large synoptic tables?
    12 Swiss Forests: A Case Study
    12.1 Aim of the study
    12.2 Structure of the data set
    12.3 Methods
    12.4 Selected questions
    12.5 Conclusions
    Appendix A On Using Software
    A.1 Spreadsheets
    A.2 Databases
    A.3 Software for multivariate analysis
    Appendix B Data Sets Used
    References
    Index