APPLICATION OF MULTIVARIATE ANALYSES IN STUDIES OF THE ORGANIZATION AND STRUCTURE OF FISH AND INVERTEBRATE COMMUNITIES

Ecological studies often attempt to link observed effects to multiple causal factors which may be operating simultaneously. Although in situ randomized experiments in which factor levels are controlled may be a powerful means for disentangling causal relationships, an experimenta l approach is not always feasible or even a desirable first step in th e analysis, particularly when there is insufficient background knowled ge of the system. In such cases, analysis of survey data, reflecting n atural (co)variation in the putative causal factors and their direct a nd indirect effects, can be a practical and useful alternative to expe riments. When set in the proper statistical framework, survey data can be used to assess whether a given factor has a detectable effect once the effect of other factors has been accounted for statistically (by partialling), and to estimate what proportion of the effect can be att ributed to each factor (by variance decomposition). This analysis can help establish whether a particular causal model is consistent with th e data at hand, and should be viewed as preliminary to a mechanistic a pproach, providing support and guidance for the investigation of more realistic variables. Here, we use three examples based on survey data from fish and invertebrate lacustrine communities to illustrate the ap plication of partialling and variance decomposition in a multivariate setting. The first example shows that variation in the abundance and s ize structure of cladoceran taxa is still associated with fish species composition when potentially confounding effects of abiotic variables are accounted for by partialling. In the second and third examples, v ariance decomposition is used to determine the relative contribution o f the environmental and spatial components to variation in the communi ty structure of littoral zoobenthos and in the diet of a freshwater fi sh species.