Using similarity measures in benthic impact assessments

Abstract

Eleven similarity measures were used to assess the impacts of clam digging on the infauna of one intertidal mud-flat. When the similarity matrices were clustered using a divisive polythetic algorithm two different conclusions were possible from the dendograms produced. Dendograms generated by 3 coefficients indicated digging had an impact on areas dug more than once, while the 8 others did not. In addition, existing data from an impact analysis of a power plant effluent were re-analyzed using 5 different coefficients. In this case, three of the five coefficients gave results which indicated that the benthic community at the effluent pipe was different from that present at the control. Two coefficients gave the opposite conclusion - the populations were not different.These results indicate that the objectivity of cluster analysis, as it has come to be used in impact studies, is only apparent, not real. Too many subjective choices are made in selecting algorithms and methods of interpretation. Objective criteria need to be developed for the choices made, based on the intrinsic and ecological properties of the quantitative methods. Some criteria that have been developed are discussed, and used to determine which coefficients are best suited for the two data sets analyzed. To reduce the number of subjective choices made an analysis of variance of the similarity matrix is presented as an alternative to clustering.