Simulating biological impairment to evaluate the accuracy of ecological indicators

Summary 1 Biological indicators are used to measure the biological health of ecosystems. Resource managers may uncritically assume that such indicators give unbiased estimates of true biological condition, but this assumption is largely untested. Use of biased indicators could lead to ineffective and potentially damaging management. 2 We used a simulation model to compare estimated indicator values objectively with true impairment. We used the model to progressively alter the densities of 155 stream invertebrate taxa as functions of stress and taxon-specific sensitivities to stress. We applied the model to large samples collected from five reference-quality sites. After each stress event, we randomly collected 100, 300 and 600 fixed-count subsamples from the remaining assemblages and recorded the densities of all taxa in both the large sample and the fixed-count subsamples. We then examined how well two indicators, non-metric multidimensional scaling (NMDS) and sample taxa richness, detected the simulated impairment when derived from fixed-count subsamples. 3 NMDS ordinations of artificially impaired samples, and samples from reference and impaired sites, showed that the simulated impairments were realistic. NMDS further showed that impairment trajectories were evident for subsamples of 100, 300 and 600 individuals. However, the discrimination of stress levels within ordination space greatly improved with increasing sampling effort. The ordination also showed that increasing stress could cause assemblages at some sites to resemble unstressed assemblages at other sites. 4 Taxa-richness indicators were much more problematic. Estimates of taxa richness from 100- and 300-count samples often substantially underestimated true taxa loss and frequently indicated taxa gain. Apparent gains in taxa richness occurred because stress caused changes in evenness that compensated for, or even overrode, the effect of true taxa loss. Estimates of taxa loss derived from 600-count subsamples also underestimated true taxa loss, but these estimates were strongly correlated with true taxa loss. 5 Synthesis and applications. Bioassessements that rely on richness-based indicators derived from small fixed-count subsamples may substantially underestimate true biological impairment. Simulation models provide an objective means to evaluate how well different types of biotic indicators measure true biological impairment in aquatic and other types of ecosystems.