Chapter 9: Transforma... | PRIMER-e Learning Hub

9.1 Introduction

There are two distinct roles for transformations in community analyses: a) to validate statistica...

9.2 Univariate case

For purely illustrative purposes, Table 9.1 extracts the counts of a single Thyasira species from...

9.3 Multivariate case

There being no necessity to transform to attain distributional properties, transformations play a...

9.4 Recommendations

The transformation sequence in a multivariate analysis, corresponding to a progressive downweight...

9.5 Dispersion weighting

There is a clear dichotomy, in defining sample similarities, between methods which give each vari...

9.6 Example: Fal estuary copepods

and present biotic and environmental data from five creeks of the Fal estuary, SW England, whos...

9.7 Variability weighting

describe a similar idea to dispersion weighting for use when the data are continuous biological ...

0.1 Introduction

0.2 Acknowledgements

0.3 Citing this book

1.1 Introduction

1.2 Univariate techniques

1.3 Example: Frierfjord macrofauna

1.4 Distributional techniques

1.5 Example: Loch Linnhe macrofauna

1.6 Example: Garroch Head macrofauna

1.7 Multivariate techniques

1.8 Example: Nutrient enrichment experiment, Solbergstrand

1.9 Summary

2.1 Similarity for quantitative data matrices

2.2 Example: Loch Linnhe macrofauna

2.3 Presence/absence data

2.4 Species similarities

2.5 Dissimilarity coefficients

2.6 More on resemblance measures

3.1 Cluster analysis

3.2 Hierarchical agglomerative clustering

3.3 Example: Bristol Channel zooplankton

3.4 Recommendations

3.5 Similarity profiles (SIMPROF)

3.6 Binary divisive clustering

3.7 k-R clustering (non-hierarchical)

4.1 Ordinations

4.2 Principal components analysis

4.3 Example: Garroch Head macrofauna

4.4 PCA for environmental data

4.5 Example: Dosing experiment, Solbergstrand mesocosm

5.1 Other ordination methods

5.2 Non-metric multidimensional scaling (MDS)

5.3 Diagnostics: Adequacy of MDS representation

5.4 EXAMPLE: Dosing experiment, Solbergstrand

5.5 Example: Celtic Sea zooplankton

5.6 Example: Amoco-Cadiz oil spill, Morlaix

5.7 MDS strengths and weaknesses

5.8 Further nMDS/mMDS developments

5.9 Example: Okura estuary macrofauna

5.10 Example: Messolongi lagoon diatoms

5.11 Recommendations

6.1 Univariate tests and multivariate tests

6.2 ANOSIM for the one-way layout

6.3 Example: Frierfjord macrofauna

6.4 Example: Indonesian reef-corals

6.5 ANOSIM for two-way layouts

6.6 Example: Clyde nematodes (2-way nested case)

6.7 Example: Eaglehawk Neck meiofauna (two-way crossed case)

6.8 Example: Mesocosm experiment (two-way crossed case with no replication)

6.9 Example: Exe nematodes (no replication and missing data)

6.10 ANOSIM for ordered factors

6.11 Example: Ekofisk oil-field macrofauna

6.12 Two-way ordered ANOSIM designs

6.13 Example: Phuket coral-reef time series

6.14 Three-way ANOSIM designs

6.15 Example: King Wrasse fish diets, WA

6.16 Example: NZ kelp holdfast macrofauna

6.17 Example: Tees Bay macrofauna

6.18 Recommendations

7.1 Species clustering

7.2 Type 2 and type 3 SIMPROF tests

7.3 Example: Amoco-Cadiz oil spill

7.4 Shade plots

7.5 Example: Bristol Channel zooplankton

7.6 Example: Garroch Head macrofauna

7.7 Example: Ekofisk oil-field macrofauna

7.8 Species contributions to sample (dis)similarities – SIMPER

7.9 Example: Tasmanian meiofauna

7.10 Bubble plots (plus examples)

8.1 Univariate measures

8.2 Graphical/distributional plots

8.3 Examples: Garroch Head and Ekofisk macrofauna

8.4 Examples: Loch Linnhe and Garroch Head macrofauna

8.5 Multivariate tools used on univariate data

8.6 Example: Plymouth particle-size data

8.7 Multiple diversity indices

9.1 Introduction

9.2 Univariate case

9.3 Multivariate case

9.4 Recommendations