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A Comparison of some methods for analysing changes in benthic community structure

Published online by Cambridge University Press:  11 May 2009

R. M. Warwick  and
K. R. Clarke
R. M. Warwick
Affiliation:
Plymouth Marine Laboratory, Prospect Place, The Hoe, Plymouth PL 3DH
K. R. Clarke
Affiliation:
Plymouth Marine Laboratory, Prospect Place, The Hoe, Plymouth PL 3DH
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Extract

Statistical methods for analysing changes in community structure fall under the three general headings of univariate, graphical/distributional and multivariate. These methods are applied to a variety of benthic community data (macrobenthos, meiobenthos, corals, demersal fish), from a variety of localities (intertidal/subtidal, temperate/tropical) and over both spatial and temporal scales. Four general conclusions emerge from this comparative study:

(1) The similarity between sites or times based on their univariate or graphical/distributional properties is usually different from their clustering in multivariate analyses.

(2) Species dependent (multivariate) methods are much more sensitive than species independent (univariate and graphical/distributional) methods in discriminating between sites or times.

(3) In examples where more than one component of the fauna has been studied, univariate and graphical/distributional methods may give different results for different components, whereas multivariate methods tend to give the same results.

(4) By matching multivariate ordinations from subsets of environmental data to an ordination of faunistic data, the key environmental variables responsible for community change may be identified.

Type
Research Article
Information
Journal of the Marine Biological Association of the United Kingdom , Volume 71 , Issue 1 , February 1991 , pp. 225 - 244
Copyright
Copyright © Marine Biological Association of the United Kingdom 1991

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References

Austen, M.C. & Warwick, R.M. 1989. Comparison of univariate and multivariate aspects of estuarine meiobenthic community structure. Estuarine, Coastal and Shelf Science, 29, 23–42.CrossRefGoogle Scholar
Austen, M.C.Warwick, R.M. & RosadoM.C., M.C., 1989. Meiobenthic and macrobenthic community structure along a putative pollution gradient in southern Portugal. Marine Pollution Bulletin, 20, 398–405.CrossRefGoogle Scholar
Clarke, K.R. 1990. Comparisons of dominance curves. Journal of Experimental Marine Biology and Ecology, 138, 143–157.CrossRefGoogle Scholar
Clarke, K.R. & Green, R.H. 1988. Statistical design and analysis for a ‘biological effects’ study. Marine Ecology Progress Series, 46, 213–226.CrossRefGoogle Scholar
Field, J.G.Clarke, K.R. & Warwick, R.M. 1982. A practical strategy for analysing multispecies distribution patterns. Marine Ecology Progress Series, 8, 37–52.CrossRefGoogle Scholar
Follum, O.A. & Moe, K.A. 1988. The GEEP Workshop: field sampling. Marine Ecology Progress Series, 46, 7–12.CrossRefGoogle Scholar
Gray, J.S.Aschan, M.Carr, M.R.Clarke, K.R.Green, R.H.Pearson, T.H.Rosenberg, R. & Warwick, R.M. 1988. Analysis of community attributes of the benthic macrofauna of Frierfjord/Langesundfjord and in a mesocosm experiment. Marine Ecology Progress Series, 46, 151–165.CrossRefGoogle Scholar
Gray, J.S.Clarke, K.R.Warwick, R.M. & Hobbs, G. 1990. Detection of initial effects of pollution on marine benthos: an example from the Ekofisk and Eldfisk oilfields, North Sea. Marine Ecology Progress Series, 66, 285–299.CrossRefGoogle Scholar
JongmanR.H.G., R.H.G.,Terbraak, C.J.F. & Tongeren, O.F.R. van 1987. Data Analysis in Community and Landscape Ecology. Wageningen: Pudoc.Google Scholar
Kruskal, J.B. & Wish, M. 1978. Multidimensional Scaling. Beverley Hills, California: 5age Publications.CrossRefGoogle Scholar
Lambshead, P.J.D.Platt, H.M. & Shaw, K.M. 1983. The detection of differences among assemblages of benthic species based on an assessment of dominance and diversity. Journal of Natural History, 17, 859–874.CrossRefGoogle Scholar
Shannon, Ce. & Weaver, W. 1949. The Mathematical Theory of Communication. Urbana: University of Illinois Press.Google Scholar
Warwick, R.M. 1971. Nematode associations in the Exe estuary. Journal of the Marine Biological Association of the United Kingdom, 51, 439–454.CrossRefGoogle Scholar
Warwick, R.M. 1986. A new method for detecting pollution effects on marine macrobenthic communities. Marine Biology, 92, 557–562.CrossRefGoogle Scholar
WarwickR.M., R.M.,Pearson, T.H. & Ruswahyuni, 1987. Detection of pollution effects on marine macrobenthos: further evaluation of the species abundance/biomass method. Marine Biology, 95, 193–200.CrossRefGoogle Scholar
Warwick, R.M.Clarke, K.R. & Gee, J.M. 1990a. The effect of disturbance by soldier crabs Mictyris platycheles H. Milne Edwards on meiobenthic community structure. Journal of Experimental Marine Biology and Ecology, 135, 19–33.CrossRefGoogle Scholar
Warwick, R.M.Clarke, K.R. & Suharsono, 1990b. A statistical analysis of coral community responses to the 1982–83 El Niño in the Thousand Islands, Indonesia. Coral Reefs, 8, 171–179.CrossRefGoogle Scholar
Warwick, R.M.Platt, H.M.Clarke, K.R.Agard, J. & Gobin, J. 1990c. Analysis of macrobenthic and meiobenthic community structure in relation to pollution and disturbance in Hamilton Harbour, Bermuda. Journal of Experimental Marine Biology and Ecology, 138, 119–142.CrossRefGoogle Scholar