Non‐parametric multivariate analyses of changes in community structure

TLDR

In the early 1980s, a strategy for graphical representation of multivariate abundance data was introduced into marine ecology. The study aims to identify the most useful elements of this strategy for assessing community change from pollution and to evaluate how methodological evolution has improved its consistency and comprehensiveness. The authors propose a unified framework that combines clustering and ordination of samples, species‑responsibility identification, multivariate rank‑based tests for spatial and temporal differences, and linkage of community changes to environmental patterns. The key finding is that a biologically relevant rank‑based similarity definition underpins non‑parametric techniques that minimize statistical assumptions and are broadly applicable, and practical experience—especially with marine benthos—shows these methods are valuable for environmental impact studies.

Abstract

Abstract In the early 1980s, a strategy for graphical representation of multivariate (multi‐species) abundance data was introduced into marine ecology by, among others, Field, et al. (1982). A decade on, it is instructive to: (i) identify which elements of this often‐quoted strategy have proved most useful in practical assessment of community change resulting from pollution impact; and (ii) ask to what extent evolution of techniques in the intervening years has added self‐consistency and comprehensiveness to the approach. The pivotal concept has proved to be that of a biologically‐relevant definition of similarity of two samples, and its utilization mainly in simple rank form, for example ‘sample A is more similar to sample B than it is to sample C’. Statistical assumptions about the data are thus minimized and the resulting non‐parametric techniques will be of very general applicability. From such a starting point, a unified framework needs to encompass: (i) the display of community patterns through clustering and ordination of samples; (ii) identification of species principally responsible for determining sample groupings; (iii) statistical tests for differences in space and time (multivariate analogues of analysis of variance, based on rank similarities); and (iv) the linking of community differences to patterns in the physical and chemical environment (the latter also dictated by rank similarities between samples). Techniques are described that bring such a framework into place, and areas in which problems remain are identified. Accumulated practical experience with these methods is discussed, in particular applications to marine benthos, and it is concluded that they have much to offer practitioners of environmental impact studies on communities.