Statistical Issues in Ecological Risk Assessment

Ecological risk assessment (ERA) is concerned with making decisions about the natural environment under uncertainty. Statistical methodology provides a natural framework for risk characterization and manipulation with many quantitative ERAs relying heavily on Neyman-Pearson hypothesis testing and other frequentist modes of inference. Bayesian statistical methods are becoming increasingly popular in ERA as they are seen to provide legitimate ways of incorporating subjective belief or expert opinion in the form of prior probability distributions. This article explores some of the concepts, strengths and weaknesses, and difficulties associated with both paradigms. The main points are illustrated with an example of setting a risk-based “trigger” level for uranium concentrations in the Magela Creek catchment of the Northern Territory of Australia.