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COMPARISON OF SIMPLE AND MULTIMETRIC DIATOM‐BASED INDICES FOR GREAT LAKES COASTLINE DISTURBANCE 1
Author(s) -
Reavie Euan D.,
Kireta Amy R.,
Kingston John C.,
Sgro Gerald V.,
Danz Nicholas P.,
Axler Richard P.,
Hollenhorst Thomas P.
Publication year - 2008
Publication title -
journal of phycology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.85
H-Index - 127
eISSN - 1529-8817
pISSN - 0022-3646
DOI - 10.1111/j.1529-8817.2008.00523.x
Subject(s) - diatom , watershed , water quality , ecology , environmental science , wetland , plankton , biology , computer science , machine learning
Because diatom communities are subject to the prevailing water quality in the Great Lakes coastal environment, diatom‐based indices can be used to support coastal‐monitoring programs and paleoecological studies. Diatom samples were collected from Great Lakes coastal wetlands, embayments, and high‐energy sites (155 sites), and assemblages were characterized to the species level. We defined 42 metrics on the basis of autecological and functional properties of species assemblages, including species diversity, motile species, planktonic species, proportion dominant taxon, taxonomic metrics (e.g., proportion Stephanodiscoid taxa), and diatom‐inferred (DI) water quality (e.g., DI chloride [Cl]). Redundant metrics were eliminated, and a diatom‐based multimetric index (MMDI) to infer coastline disturbance was developed. Anthropogenic stresses in adjacent coastal watersheds were characterized using geographic information system (GIS) data related to agricultural and urban land cover and atmospheric deposition. Fourteen independent diatom metrics had significant regressions with watershed stressor data; these metrics were selected for inclusion in the MMDI. The final MMDI was developed as the weighted sum of the selected metric scores with weights based on a metric’s ability to reflect anthropogenic stressors in the adjacent watersheds. Despite careful development of the multimetric approach, verification using a test set of sites indicated that the MMDI was not able to predict watershed stressors better than some of the component metrics. From this investigation, it was determined that simpler, more traditional diatom‐based metrics (e.g., DI Cl, proportion Cl‐tolerant species, and DI total phosphorus [TP]) provide superior prediction of overall stressor influence at coastal locales.