title: Accounting for regional variation in both natural environment and human disturbance to improve performance of multimetric indices of lotic benthic diatoms.
abstract: Regional variation in both natural environment and human disturbance can influence performance of ecological assessments. In this study we calculated 5 types of benthic diatom multimetric indices (MMIs) with 3 different approaches to account for variation in ecological assessments. We used: site groups defined by ecoregions or diatom typologies; the same or different sets of metrics among site groups; and unmodeled or modeled MMIs, where models accounted for natural variation in metrics within site groups by calculating an expected reference condition for each metric and each site. We used data from the USEPA's National Rivers and Streams Assessment to calculate the MMIs and evaluate changes in MMI performance. MMI performance was evaluated with indices of precision, bias, responsiveness, sensitivity and relevancy which were respectively measured as MMI variation among reference sites, effects of natural variables on MMIs, difference between MMIs at reference and highly disturbed sites, percent of highly disturbed sites properly classified, and relation of MMIs to human disturbance and stressors. All 5 types of MMIs showed considerable discrimination ability. Using different metrics among ecoregions sometimes reduced precision, but it consistently increased responsiveness, sensitivity, and relevancy. Site specific metric modeling reduced bias and increased responsiveness. Combined use of different metrics among site groups and site specific modeling significantly improved MMI performance irrespective of site grouping approach. Compared to ecoregion site classification, grouping sites based on diatom typologies improved precision, but did not improve overall performance of MMIs if we accounted for natural variation in metrics with site specific models. We conclude that using different metrics among ecoregions and site specific metric modeling improve MMI performance, particularly when used together. Applications of these MMI approaches in ecological assessments introduced a tradeoff with assessment consistency when metrics differed across site groups, but they justified the convenient and consistent use of ecoregions.
authors.affiliation: State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China; Center for Water Sciences, Department of Integrative Biology, Michigan State University, East Lansing, MI 48824, USA.
authors.forename: Tao
authors.initials: T
authors.lastname: Tang
authors.affiliation: Center for Water Sciences, Department of Integrative Biology, Michigan State University, East Lansing, MI 48824, USA. Electronic address: rjstev@msu.edu.
authors.forename: R Jan
authors.initials: RJ
authors.lastname: Stevenson
authors.affiliation: Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA.
authors.forename: Dana M
authors.initials: DM
authors.lastname: Infante
mesh_terms: D044822:Biodiversity; D017377:Diatoms / Q000145:classification*; D004784:Environmental Monitoring / Q000379:methods*; D008962:Models, Theoretical; D045483:Rivers; D014481:United States; D014484:United States Environmental Protection Agency; D060753:Water Quality
keywords: Bioassessment; Biological condition; Biological typology; Ecoregions; Multimetric index