# Change in Marine Communities

An Approach to Statistical Analysis and Interpretation, 3rd edition

by

K R Clarke, R N Gorley, P J Somerfield & R M Warwick

(2014)

#### Introduction and acknowledgements

#### 0.1 Introduction

Third edition The third edition of this unified framework for non-parametric analysis of multivar...

#### 0.2 Acknowledgements

Any initiative spanning quite as long a period as the PRIMER software represents (the first recog...

#### 0.3 Citing this book

Please use the following to cite this book or any of its content: Clarke KR, Gorley RN, Somerfiel...

#### Chapter 1: A framework for studying changes in community structure

#### 1.1 Introduction

The purpose of this opening chapter is twofold: a) to introduce some of the data sets which are u...

#### 1.2 Univariate techniques

For diversity indices and other single-variable extractions from the data matrix, standard statis...

#### 1.3 Example: Frierfjord macrofauna

The first example is from the IOC/GEEP practical workshop on biological effects of pollutants (),...

#### 1.4 Distributional techniques

Table 1.3. Distributional techniques. Summary of analyses for the four stages. A less condense...

#### 1.5 Example: Loch Linnhe macrofauna

Table 1.4. Loch Linnhe macrofauna {L}. Abundance/biomass matrix (part only); one (pooled) set o...

#### 1.6 Example: Garroch Head macrofauna

describe the sampling of a transect of 12 sites across the sewage-sludge disposal ground at Garr...

#### 1.7 Multivariate techniques

Table 1.5 summarises some multivariate methods for the four stages, starting with three descripti...

#### 1.8 Example: Nutrient enrichment experiment, Solbergstrand

Table 1.7. Nutrient enrichment experiment, Solbergstrand mesocosm, Norway {N}. Meiofaunal abund...

#### 1.9 Summary

A framework has been outlined of three categories of technique (univariate, graphical/distributio...

#### Chapter 2: Simple measures of similarity of species ‘abundance’ between samples

#### 2.1 Similarity for quantitative data matrices

Data matrix The available biological data is assumed to consist of an array of p rows (species) a...

#### 2.2 Example: Loch Linnhe macrofauna

A trivial example, used in this and the following chapter to illustrate simple manual computation...

#### 2.3 Presence/absence data

As discussed at the beginning of this chapter, quantitative uncertainty may make it desirable to ...

#### 2.4 Species similarities

Starting with the original data matrix of abundances (or biomass, area cover etc), the similarity...

#### 2.5 Dissimilarity coefficients

The converse concept to similarity is that of dissimilarity, the degree to which two samples are ...

#### 2.6 More on resemblance measures

On the grounds that it is better to walk before you try running, discussion of comparisons betwee...

#### Chapter 3: Clustering methods

#### 3.1 Cluster analysis

The previous chapter has shown how to replace the original data matrix with pairwise similarities...

#### 3.2 Hierarchical agglomerative clustering

The most commonly used clustering techniques are the hierarchical agglomerative methods. These u...

#### 3.3 Example: Bristol Channel zooplankton

perform hierarchical cluster analyses of zooplankton samples, collected by double oblique net ha...

#### 3.4 Recommendations

Hierarchical clustering with group-average linking, based on sample similarities or dissimilari...

#### 3.5 Similarity profiles (SIMPROF)

Given the form of the dendrogram in Fig. 3.3, with high similarities in apparently tightly define...

#### 3.6 Binary divisive clustering

All discussion so far has been in terms of hierarchical agglomerative clustering, in which sample...

#### 3.7 k-R clustering (non-hierarchical)

Another major class of clustering techniques is non-hierarchical, referred to above as flat clust...

#### Chapter 4: Ordination of samples by principal components analysis (PCA)

#### 4.1 Ordinations

An ordination is a map of the samples, usually in two or three dimensions, in which the placement...

#### 4.2 Principal components analysis

The starting point for PCA is the original data matrix rather than a derived similarity matrix (t...

#### 4.3 Example: Garroch Head macrofauna

Fig. 4.1 shows the result of applying PCA to square-root transformed macrofaunal biomass data fro...

#### 4.4 PCA for environmental data

The above example makes it clear that PCA is an unsatisfactory ordination method for biological d...

#### 4.5 Example: Dosing experiment, Solbergstrand mesocosm

An example of this final point for a real data set can be seen in Fig. 4.2. This is of nematode ...

#### Chapter 5: Ordination of samples by multi-dimensional scaling (MDS)

#### 5.1 Other ordination methods

Principal Co-ordinates Analysis The two main weaknesses of PCA, identified at the end of Chapter ...

#### 5.2 Non-metric multidimensional scaling (MDS)

The method of non-metric MDS was introduced by and , for application to problems in psychology; ...

#### 5.3 Diagnostics: Adequacy of MDS representation

Is the stress value small? By definition, stress reduces with increasing dimensionality of the ...

#### 5.4 EXAMPLE: Dosing experiment, Solbergstrand

The nematode abundance data from the dosing experiment {D} at the GEEP Oslo Workshop was previous...

#### 5.5 Example: Celtic Sea zooplankton

In situations where the samples are strongly grouped, as in Figs. 5.4 and 5.5, both clustering an...

#### 5.6 Example: Amoco-Cadiz oil spill, Morlaix

Benthic macrofaunal abundances of 251 species were sampled by at 21 times between April 1977 and ...

#### 5.7 MDS strengths and weaknesses

MDS strengths MDS is simple in concept. The numerical algorithm is undeniably complex, but it ...

#### 5.8 Further nMDS/mMDS developments

Higher dimensional solutions MDS solutions can be sought in higher dimensions and we noted previo...

#### 5.9 Example: Okura estuary macrofauna

describe macrofauna samples from the Okura estuary {O}, on the northern fringes of urban Aucklan...

#### 5.10 Example: Messolongi lagoon diatoms

sampled 17 lagoons in E Central Greece for diatom communities (193 species), and also recorded a...

#### 5.11 Recommendations

Non-metric MDS can be recommended as the best general ordination technique available (e.g. ). Im...

#### Chapter 6: Testing for differences between groups of samples

#### 6.1 Univariate tests and multivariate tests

Many community data sets possess some a priori defined structure within the set of samples, for e...

#### 6.2 ANOSIM for the one-way layout

Fig.6.3 displays the MDS based only on the 12 samples (4 replicates per site) from the B, C and D...

#### 6.3 Example: Frierfjord macrofauna

The rank similarities underlying Fig. 6.3 are shown in Table 6.2 (note that these are the similar...

#### 6.4 Example: Indonesian reef-corals

examined data from 10 replicate transects across a single coral-reef site in S. Tikus Island, Th...

#### 6.5 ANOSIM for two-way layouts

Three types of field and laboratory designs are considered here: a) the 2-way nested case can ari...

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

analysed meiobenthic communities from three putatively polluted (P) areas of the Firth of Clyde ...

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

An example of a two-way crossed design is given in and is introduced more fully here in Chapter ...

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

Although the above test may still function if a few random cells in the 2-way layout have only a ...

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

A final example demonstrates a positive outcome to such a test, in a common case of a 2-way layou...

#### 6.10 ANOSIM for ordered factors

Generalised ANOSIM statistic for the 1-way case Now return to the simple one-way case of page 6.2...

#### 6.11 Example: Ekofisk oil-field macrofauna

studied the soft-sediment macrobenthos at 39 sites at different distances (100m to 8km) and diff...

#### 6.12 Two-way ordered ANOSIM designs

Under the non-parametric framework adopted in this manual (and in the PRIMER package) three forms...

#### 6.13 Example: Phuket coral-reef time series

These data are discussed more fully in Chapters 15 and 16; sampling of coral assemblages took pla...

#### 6.14 Three-way ANOSIM designs

Table 6.4 details all viable combinations of 3 factors, A, B, C, in crossed/nested form, ordered/...

#### 6.15 Example: King Wrasse fish diets, WA

We begin the 3-factor examples with a fully crossed design A$\times$B$\times$C of the composition...

#### 6.16 Example: NZ kelp holdfast macrofauna

We now consider the fully nested design, C(B(A)). In north-eastern New Zealand, examined assembl...

#### 6.17 Example: Tees Bay macrofauna

The final example in this chapter is of a mixed nested and crossed design B$\times$C(A), for a to...

#### 6.18 Recommendations

For typical species abundance matrices, it is much preferable to use a non-parametric ANOSIM-ty...

#### Chapter 7: Species analyses

#### 7.1 Species clustering

Chapter 2 (page 2.4) describes how the original data matrix can be used to define similarities be...

#### 7.2 Type 2 and type 3 SIMPROF tests

describe in full detail a range of useful SIMPROF tests, which they classify as Types 1, 2 and 3...

#### 7.3 Example: Amoco-Cadiz oil spill

A second example of deriving sets of coherent species curves, this time temporal rather than spat...

#### 7.4 Shade plots

An alternative to line plots, and a technique that can often be even more useful, in terms of the...

#### 7.5 Example: Bristol Channel zooplankton

This example, last seen in Chapter 3, consists of 24 (seasonally-averaged) zooplankton net sample...

#### 7.6 Example: Garroch Head macrofauna

An example where the biotic sample axis could have sensibly been ordered according to an a prior...

#### 7.7 Example: Ekofisk oil-field macrofauna

The 39 sites sampled for benthic infauna at different distances from an oil-field in the N Sea we...

#### 7.8 Species contributions to sample (dis)similarities – SIMPER

Dissimilarity breakdown between groups The fundamental information on the multivariate structure ...

#### 7.9 Example: Tasmanian meiofauna

Another clear generalisation is to a 2-way rather than 1-way layout, illustrated by the 16 meiofa...

#### 7.10 Bubble plots (plus examples)

Bubble plots Abundance (or density, biomass, area cover etc) for a particular species can be show...

#### Chapter 8: Diversity measures, dominance curves and other graphical analyses

#### 8.1 Univariate measures

A variety of different statistics (single numbers) can be used as measures of some attribute of c...

#### 8.2 Graphical/distributional plots

The purpose of graphical/distributional representations is to extract information on patterns of ...

#### 8.3 Examples: Garroch Head and Ekofisk macrofauna

Plots of geometric abundance classes along a transect across the Garroch Head {G} sewage-sludge d...

#### 8.4 Examples: Loch Linnhe and Garroch Head macrofauna

ABC curves for the macrobenthos at site 34 in Loch Linnhe, Scotland {L} between 1963 and 1973 are...

#### 8.5 Multivariate tools used on univariate data

Ekofisk macrofauna: testing dominance curves Fig. 8.5b compares the averaged community samples fo...

#### 8.6 Example: Plymouth particle-size data

Fig. 8.15 is from Coulter Counter data of particle-size distributions for estuarine water samples...

#### 8.7 Multiple diversity indices

A large number of different diversity measures can be computed from a single data set and it is r...

#### Chapter 9: Transformations and dispersion weighting

#### 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 ...

#### Chapter 10: Species aggregation to higher taxa

#### 10.1 Species aggregation

Fig. 10.1a repeats the multivariate ordination (nMDS) seen in Fig. 1.7 for the macrofaunal data f...

#### 10.2 Examples

Multivariate examples Nutrient-enrichment experiment In the soft-bottom mesocosms at Solbergstr...

#### 10.3 Recommendation

Clearly the operational taxonomic level for environ¬mental impact studies is another factor to be...

#### Chapter 11: Linking community analyses to environmental variables

#### 11.1 Introduction

Approach In many studies, the biotic data is matched by a suite of environmental variables measur...

#### 11.2 Example: Garroch Head macrofauna

For the 12 sampling stations (Fig. 8.3) across the sewage-sludge dump ground at Garroch Head {G},...

#### 11.3 Linking biota to univariate environmental measures (and examples)

Univariate community measures If the biotic data are best summarised by one, or a few, simple uni...

#### 11.4 Linking biota to multivariate environmental patterns

The intuitive premise adopted here is that if the suite of environmental variables responsible fo...

#### 11.5 Further ‘BEST’ variations

Entering variables in groups In some contexts, it makes good sense to utilise an a priori group s...

#### 11.6 Linkage trees (and example)

The idea of linkage trees¶ is most easily understood in the context of a particular example, so F...

#### 11.7 Concluding remarks

For this chapter as a whole, two final points need to be made. The topic of experimental and fiel...

#### Chapter 12: Causality - community experiments in the field and laboratory

#### 12.1 Introduction

In Chapter 11 we have seen how both the univariate and multivariate community attributes can be c...

#### 12.2 `Natural experiments’

It is doubtful whether so called natural experiments deserve to be called ‘experiments’ at all, a...

#### 12.3 Field experiments

Field manipulative experiments include, for example, caging experiments to exclude or include pre...

#### 12.4 Laboratory experiments

More or less natural communities of some components of the biota can be maintained in laboratory ...

#### 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...

#### Chapter 14: Relative sensitivities and merits of univariate, graphical/distributional and multivariate techniques

#### 14.1 Introduction

Two communities with a completely different taxonomic composition may have identical univariate o...

#### 14.2 Examples 1, 2 and 3

Example 1: Macrobenthos from Frierfjord/Langesundfjord, Norway As part of the GEEP/IOC Oslo Works...

#### 14.3 Examples 4, 5, 6 and 7

Example 4: Fish communities from coral reefs in the Maldives In the Maldive islands, compared ree...

#### 14.4 General conclusions and recommendations

General conclusions Three general conclusions emerge from these examples: The similarity in com...

#### Chapter 15: Multivariate measures of community stress and relating to models

#### 15.1 Introduction

We have seen in Chapter 14 that multivariate methods of analysis are very sensitive for detecting...

#### 15.2 Meta-analysis of marine macrobenthos

This method was initially devised as a means of comparing the severity of community stress betwee...

#### 15.3 Increased variability

noted that, in a variety of environmental impact studies, the variability among samples collecte...

#### 15.4 Breakdown of seriation

Clear-cut zonation patterns in the form of a serial change in community structure with increasing...

#### 15.5 Model matrices & ‘RELATE’ tests

The form of the seriation statistic is simply a matrix correlation coefficient (e.g. equation 11....

#### 15.6 Examples

Example: Tees Bay macrofauna Fig. 15.7 shows the nMDS plot for the inter-annual macrofauna sample...

#### Chapter 16: Further multivariate comparisons and resemblance measures

#### 16.1 Introduction

To motivate the first method of this chapter look again at the analysis of macrobenthic samples f...

#### 16.2 Matching of ordinations

The BEST (Bio-Env) technique of Chapter 11 can be generalised in a natural way, to the selection ...

#### 16.3 Example: Amoco-Cadiz oil spill

Applying this (BVStep) procedure to the 125-species set from the Bay of Morlaix, a smallest subse...

#### 16.4 Further extensions

Both BEST Bio-Env and BVStep routines can be generalised to accommodate possibilities other than ...

#### 16.5 Second-stage MDS

It is not normally a viable sampling strategy, for soft-sediment benthos at least, to use BVStep ...

#### 16.6 Comparison of resemblance measures

S Tikus Island coral cover The use of second-stage MDS plots can be extended to also include the ...

#### 16.7 Second-stage interaction plots

Phuket coral-reef times series A rather different application of second-stage MDS¶ is motivated b...

#### 16.8 Example: Algal recolonisation, Calafuria

An example of this type (though not a classic BACI situation) is given by , for a study by . Sub-...

#### Chapter 17: Biodiversity and dissimilarity measures based on relatedness of species

#### 17.1 Species richness disadvantages

Chapter 8 discussed a range of diversity indices based on species richness and the species abunda...

#### 17.2 Average taxonomic diversity and distinctness

Two measures, which address some of the problems identified with species richness and the other d...

#### 17.3 Examples: Ekofisk oil-field and Tees Bay soft-sediment macrobenthos

The earlier Fig. 14.4 demonstrated a change in the sediment macrofaunal communities around the Ek...

#### 17.4 Other relatedness measures

The remainder of this chapter deals only with data in the form of a species list for a locality (...

#### 17.5 ‘Expected distinctness’ tests

Species master list The construction of taxonomic distinctness indices from simple species lists ...

#### 17.6 Example: UK free-living nematodes

examined 14 species lists from a range of different habitats and impacted/undisturbed UK areas (...

#### 17.7 Example: N Europe groundfish surveys

An investigation of the taxonomic structure of demersal fish assemblages in the North Sea, Englis...

#### 17.8 Variation in taxonomic distinctness, $\Lambda ^ +$

VarTD was defined in equation (17.7), as the variance of the taxonomic distances {$\omega _ {ij}$...

#### 17.9 Joint (AvTD, VarTD) analyses

The histogram and funnel plots of Figs. 17.7 and 17.8 are univariate analyses, concentrating on o...

#### 17.10 Concluding remarks on taxonomic distinctness

Early applications of taxonomic distinctness ideas in marine science can be found in for demersa...

#### 17.11 Taxonomic dissimilarity

A natural extension of the ideas of this chapter is from $\alpha$- or ‘spot’ diversity indices to...

#### 17.12 Examples

Example: Island fish species lists Fish species lists extracted from FishBase (www. fishbase.org)...

#### Chapter 18: Bootstrapped averages for region estimates in multivariate means plots

#### 18.1 Means plots

Several examples have been seen in previous chapters of the advantages of viewing ordination plot...

#### 18.2 Example: Indonesian reef corals, S. Tikus

The point is made here in Fig 18.1 for the Shannon diversity of coral community transects (% cove...

#### 18.3 ‘Bootstrap average’ regions

The idea of the (univariate) bootstrap () is that our best estimate of the distribution of values...

#### 18.4 Example: Loch Creran macrobenthos

collected a set of 256 soft-sediment macrobenthic samples along a transect in Loch Creran, Scotl...

#### 18.5 Example: Fal estuary macrofauna

The soft-sediment macrobenthic communities from five creeks of the Fal estuary, SW England, {f} w...

#### Appendices

#### Appendix 1: Index of example data

The following is a list of all (real) data sets used as examples in the text, where they are refe...

#### Appendix 2: Principal literature sources and further reading

A list of some of the core methods papers was given in the Introduction, and the source papers fo...

#### Appendix 3: Bibliography

Addison & Clark (1990) Addison, R.F. and Clarke, K.R. (1990) ‘Biological effects o...