An assessment methodology for successional systems. II. Statistical tests and specific examples

This paper presents a dynamic framework for environmental assessment when the system under study is undergoing successional change. Successional differences between sites for which one wishes to detect a difference because of a treatment are essentially confounding factors. We show how successional changes over the study period or resulting from differences in study site plot ages can be factored out by developing a null model of expected behavior over time. The null model for change in state with time is characterized in terms of a stochastic envelope around a nominal trajectory. Specific tests for the detection of trends associated with succession are described and illustrated on example data. It is concluded that the methods developed work particularly well for laboratory microcosm data.