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ISBN 10: 1786394243
ISBN 13: 9781786394224
Author: Otto Wildi
1 Introduction
1.1 Epistemology
1.2 Paradigms ruling analysis
2 Patterns in vegetation ecology
2.1 Pattern recognition
2.2 Multivariate pattern analysis
2.3 Sampling for pattern recognition
2.3.1 Getting a sample
2.3.2 Organizing the data
2.4 Pattern recognition in R
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
3.5 Which transformation?
4 Multivariate comparison
4.1 Resemblance in multivariate space
4.2 Geometric approach
4.3 Contingency measures
4.4 Product moments
4.5 The resemblance matrix
4.6 Assessing the quality of classifications
4.7 Which resemblance function?
5 Classification
5.1 The legacy of vegetation classification
5.2 Group structures
5.3 Agglomerative clustering
5.3.1 Linkage clustering
5.3.2 Average linkage clustering revisited
5.3.3 Minimum-variance clustering
5.4 Divisive clustering
5.5 Forming groups
5.6 Silhouette plot and fuzzy representation
5.7 Revising classifications
5.8 Which classification method?
6 Ordination
6.1 Why ordination?
6.2 Principal component analysis
6.2.1 Operational steps
6.2.2 Interpretation by example
6.3 Principal coordinates analysis
6.4 Correspondence analysis
6.5 Heuristic ordination
6.5.1 The horseshoe or arch effect
6.5.2 Flexible shortest path adjustment
6.5.3 Nonmetric multidimensional scaling
6.5.4 Detrended correspondence analysis
6.6 How to interpret ordinations
6.7 Ranking by orthogonal components
6.7.1 RANK method
6.7.2 A sampling design based on RANK (example)
6.8 Which ordination method?
7 Ecological patterns
7.1 Pattern and ecological response
7.2 Evaluating groups
7.2.1 Variance testing
7.2.2 Variance ranking
7.2.3 Ranking by indicator values
7.2.4 Analysis of concentration
7.3 Correlating spaces
7.3.1 The Mantel test
7.3.2 Correlograms
7.3.3 More trends: `Schlaenggli' data revisited
7.4 Constrained ordination
7.5 Nonparametric multiple analysis of variance
7.5.1 Method and example
7.5.2 Data transformation revisited
7.5.3 Clustering revisited
7.6 Synoptic vegetation tables
7.6.1 The aim of ordering tables
7.6.2 Steps involved in sorting tables
7.6.3 Example: ordering Ellenberg's data
8 Traits and indicators
8.1 Vegetation beyond the species concept
8.2 Analytical framework
8.3 Matrix operations in a nutshell
8.4 Schlaenggli data example
8.4.1 Preparing data matrices
8.4.2 Deriving and projecting new data spaces
8.4.3 Measuring convergence
8.5 Rebuilding community ecology?
9 Static predictive modelling
9.1 Predictive or explanatory?
9.2 Evaluating environmental predictors
9.3 Generalized linear models
9.4 Generalized additive models
9.5 Classification and regression trees
9.6 Testing and building scenarios
9.7 Modelling vegetation types
9.8 Expected wetland vegetation (example)
10 Vegetation change in time
10.1 Coping with time
10.2 Temporal autocorrelation
10.3 Detecting trend
10.4 Rate of change
10.5 Early succession: Vraconnaz revisited
10.6 Markov models
10.6.1 Method an example
10.6.2 Limitations and practice
10.7 Space-for-time substitution
10.7.1 Principle and method
10.7.2 Swiss National Park succession (example)
10.8 Dynamics in pollen diagrams
11 Dynamic modelling
11.1 Principles of systems
11.2 Simulating exponential growth
11.3 Logistic growth
11.4 The Lotka–Volterra model
11.5 Simulating space processes
11.6 Processes in the Swiss National Park
11.6.1 The temporal model
11.6.2 The spatial model
12 Revising classifications
12.1 Beyond statistical analysis
12.2 Wetland data
12.3 Preprocessing data
12.3.1 Suppressing outliers
12.3.2 Selecting groups
12.4 Evaluating classification revisions
12.5 Carry-over nomenclature?
12.6 Step by step in R
12.7 Revising classification - or data?
13 Swiss forests: a case study
13.1 Aim of the study
13.2 Structure of the data set
13.3 Selected questions
13.3.1 Is the similarity pattern discrete or continuous?
13.3.2 Is there a scale effect from plot size?
13.3.3 Which factors reflect vegetation pattern?
13.3.4 Is tree species distribution man-made?
13.3.5 Is the tree species pattern expected to change?
13.4 Conclusions
data analysis in vegetation ecology
what is vegetation in ecology
vegetation description and data analysis
what is vegetation analysis
vegetation data analysis
Tags: Otto Wildi, Data Analysis, Vegetation Ecology
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