title: How stressor specific are trait-based ecological indices for ecosystem management?
abstract: Using macroinvertebrates as ecological indicators for different stressors has a long tradition. However, when applied to field data, one often observes correlations between different macroinvertebrate indices that can be attributed to both correlations of stressors and inherent correlations due to the sensitivity of taxa to different stressors. Ignoring the source of any given correlation leads to ambiguous conclusions about the impact of different stressors. Here, we demonstrate how to distinguish the causes of correlation by means of Monte Carlo simulations. We assessed to which degree trait-based indices are stressor-specific and whether this depends on the pool of taxa and its taxonomic resolution. Therefore, we (1) analysed the frequencies of "sensitive" and "insensitive" taxa for pairwise combinations of different indices, (2) analysed the inherent correlation of indices with random samples from different taxon pools derived from field samples and from a complete species list of a whole ecoregion, and (3) compared this inherent correlation with the actual correlation of the field samples. We exemplified this approach by analysing two existing indices (SPEARpesticides, Saprobic Index) and new indices for temperature, flow and pH stress. We used these new indices to illustrate our approach while in-depth testing of their applicability was not the focus of our study. We found strong correlations between several indices in our study area at the Swiss Plateau. The probability that this correlation is only due to inherent correlation in the taxa sensitivities was low (maximum of 0.34). The problem of inherent correlation between indices is more severe for the smaller taxon pool with lower taxonomic resolution. Correlation in the sensitivity of different taxa to different stressors leads to an inherent correlation in trait-based indices, which weakens their explanatory power. Our results highlight the importance of correlation analyses when using trait-based indices to guide ecosystem-management, especially in regions with reduced biodiversity.
authors.affiliation: Eawag: Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland. Electronic address: nele.schuwirth@eawag.ch.
authors.forename: Nele
authors.initials: N
authors.lastname: Schuwirth
authors.affiliation: Eawag: Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland. Electronic address: mira.kattwinkel@eawag.ch.
authors.forename: Mira
authors.initials: M
authors.lastname: Kattwinkel
authors.affiliation: Eawag: Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland. Electronic address: christian.stamm@eawag.ch.
authors.forename: Christian
authors.initials: C
authors.lastname: Stamm
mesh_terms: D000818:Animals; D003247:Conservation of Natural Resources / Q000379:methods*; D004784:Environmental Monitoring / Q000379:methods*; D013045:Species Specificity; D013312:Stress, Physiological
keywords: Bioassessment; Macroinvertebrates; Monte Carlo simulations; Multiple stressors; River management; Trait-based indices