COMPARING APPLES WITH APPLES: USE OF LIMITING ENVIRONMENTAL DIFFERENCES TO MATCH REFERENCE AND STRESSOR-EXPOSURErnSITES FOR BIOASSESSMENT OF STREAMS

摘要

Human impacts on freshwater biota are often assessed by comparisons with regional reference sites judged to be free or nearly free from the influence of stressors of concern. These comparisons may involve predictive models that extrapolate from reference-site data to estimate the biota that would occur at each assessment site in the absence of the stressors. This extrapolation often involves selection or weighting of data from particular reference sites, but it is seldom demonstrated whether this process results in a more accurate, precise and sensitive assessment than would be achieved from comparison with a simple unweighted combination of data from all reference sites, that is a null model. In addition, predictive models often rely on additive combinations of environmental predictor variables, but such combinations may poorly represent the natural control of spatial variation in biological communities by multiple limiting factors. In this paper, we describe a different type of reference-site approach, based on the concept of limiting environmental differences (LEDs) as natural constraints on biological similarity among sites. In this method, an assessment site is compared with a sub-set of environmentally matched reference sites selected by application of LED criteria to individual environmental variables. We illustrate this approach by its application to a potentially subtle impact: the effect of water abstraction on fish assemblages in unregulated streams in northeastern New South Wales, Australia. We compared (1) a LED-based predictive model, (2) a null model and (3) a model based on cluster analysis and multiple discriminant analysis in the style of the widely followed River Invertebrate Prediction and Classification System (RIVPACS). The LED-based model was about as accurate as the RIVPACS-type model and the most precise and sensitive of the three, being best able to distinguish sites where fish assemblages departed from reference status.