Evaluating AUSRIVAS predictive model performance for detecting simulated eutrophication effects on invertebrate assemblages

Abstract

AbstractConfidence in any bioassessment method is related to its ability to detect ecological improvement or impairment. We evaluated Australian River Assessment (AUSRIVAS)-style predictive models built using reference-site data sets from the Australian Capital Territory (ACT), the Yukon Territory (YT; Canada), and the Laurentian Great Lakes (GL; North America) area. We evaluated model performance as ability to correctly assign reference condition with independent reference-site data. Evaluating model ability to detect human disturbance is generally more problematic because the actual condition of test sites is usually unknown. Independent reference-site data underwent simulated impairment by varying the proportions of sensitive, intermediate, and tolerant taxa to simulate degrees of eutrophication. Model performance was related to differences in data sets, such as number and distribution of invertebrate taxa. Sensitive taxa tended to have lower expected probabilities of occurrence than more-tolerant taxa...