Abstract
Communityβlevel data, typically in the form of abundances of over 100 species, are widely collected in the context of environmental monitoring, e.g., of the effects of disposal of drilling muds in offshore oil operations. The statistical properties of the resulting abundance arrays preclude the use of βclassicalβ multivariate analyses, such as principal components and multivariate analysis of variance. One alternative is the use of nonparametric displays and tests, such as nonmetric multidimensional scaling (MDS) and variations of Mantel tests on similarity matrices. These do not require the restrictive assumptions of parametric techniques and possess a conceptual simplicity, facilitating their use and understanding by environmental managers and regulators. A monitoring example is discussed from Norwegian oil fields, for which such analyses have had a significant impact on environmental practice. The techniques are equally applicable to assessing outcomes from communityβlevel laboratory experiments and bioassays. The paper exemplifies the analysis approach taken at the Plymouth Marine Laboratory (and encapsulated in the PRIMER software) through (1) observational studies of pollution gradients in North Sea sediments and heavy metal pollutants in the Fal estuary, UK; (2) an experimental study on differential effects of metals on marine nematode communities; and (3) a bioassay approach employing a microcosm experiment on Fal estuary sediments.