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Autor: Otto Wildi
ISBN-13: 9780470664964
Einband: E-Book
Seiten: 234
Sprache: Englisch
eBook Typ: PDF
eBook Format: E-Book
Kopierschutz: Adobe DRM [Hard-DRM]
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Data Analysis in Vegetation Ecology

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Evolving from years of teaching experience by one of the topexperts in vegetation ecology, Data Analysis in VegetationEcology aims to explain the background and basics ofmathematical (mainly multivariate) analysis of vegetation data.
The book lays out the basic operations involved in the analysis,the underlying hypotheses, aims and points of views. It conveys themessage that each step in the calculations has a specific,straightforward meaning and that patterns and processes known byecologists often find their counterpart in mathematical operationsand functions. The first chapters introduce the elementary conceptsand operations and relate them to real-world phenomena andproblems. Later chapters concentrate on combinations of methods toreveal surprising features in data sets. Showing how to findpatterns in time series, how to generate simple dynamic models, howto reveal spatial patterns and related occurrence probabilitymaps.

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 Ordination.

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 andWPGMC.

6.5 Forming groups.

6.6 Structured synoptic tables.

7 Joining 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.



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Autor: Otto Wildi
ISBN-13 :: 9780470664964
ISBN: 0470664967
Verlag: John Wiley & Sons
Seiten: 234
Sprache: Englisch
Auflage 1. Auflage
Sonstiges: Ebook