Chapter 13: Data requirements for biological effects studies - which components and attributes of the marine biota to examine?

13.1 Components

The biological effects of pollutants can be studied on assemblages of a wide variety of marine or...

13.2 Plankton and fish

Plankton The advantages of plankton are that: a) Long tows over relatively large distances result...

13.3 Macrobenthos and meiobenthos

Macrobenthos The advantages of soft-bottom macrobenthos are that: a) They are relatively non-mobi...

13.4 Hard-bottom epifauna and hard-bottom motile fauna

Hard-bottom epifauna The advantages of using hard-bottom encrusting faunas, reef-corals etc. are:...

13.5 Attributes and recommendations

Attributes Species abundance data are by far the most commonly used in environmental impact studi...

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