Environmental regulations should be based on technically sound and legally defensible data analyses that are interpreted using the best available science. This tutorial compares mathematical deterministic process models with stochastic statistical models to answer regulatory decision-making questions.
The models used to support environmental regulations under conditions of uncertainty have not kept pace with our increased understanding of ecosystems and their responses to human industrial activities, nor to advances in statistics that fit the unique attributes of environmental data.
The result is that environmental regulators lack the insight they need to make effective decisions under conditions of change and uncertainty.
This tutorial examines four common deterministic models applied to aquatic ecosystems and compares them to advanced statistical models for supporting environmental regulatory decisions.