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An Integrated Ecological Modeling System for Assessing Impacts of Multiple Stressors on Stream and Riverine Ecosystem Services within River Basins.
Johnston, John M; Barber, M Craig; Wolfe, Kurt; Galvin, Mike; Cyterski, Mike; Parmar, Rajbir.
Afiliação
  • Johnston JM; USEPA/ORD/NERL, 960 College Station Rd., Athens, GA 30605.
  • Barber MC; USEPA/ORD/NERL, 960 College Station Rd., Athens, GA 30605.
  • Wolfe K; USEPA/ORD/NERL, 960 College Station Rd., Athens, GA 30605.
  • Galvin M; USEPA/ORD/NERL, 960 College Station Rd., Athens, GA 30605.
  • Cyterski M; USEPA/ORD/NERL, 960 College Station Rd., Athens, GA 30605.
  • Parmar R; USEPA/ORD/NERL, 960 College Station Rd., Athens, GA 30605.
Ecol Modell ; 354: 104-114, 2017 06 24.
Article em En | MEDLINE | ID: mdl-28966433
ABSTRACT
We demonstrate a novel, spatially explicit assessment of the current condition of aquatic ecosystem services, with limited sensitivity analysis for the atmospheric contaminant mercury. The Integrated Ecological Modeling System (IEMS) forecasts water quality and quantity, habitat suitability for aquatic biota, fish biomasses, population densities, productivities, and contamination by methylmercury across headwater watersheds. We applied this IEMS to the Coal River Basin (CRB), West Virginia (USA), an 8-digit hydrologic unit watershed, by simulating a network of 97 stream segments using the SWAT watershed model, a watershed mercury loading model, the WASP water quality model, the PiSCES fish community estimation model, a fish habitat suitability model, the BASS fish community and bioaccumulation model, and an ecoservices post-processer. Model application was facilitated by automated data retrieval and model setup and updated model wrappers and interfaces for data transfers between these models from a prior study. This companion study evaluates baseline predictions of ecoservices provided for 1990 - 2010 for the population of streams in the CRB and serves as a foundation for future model development.
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Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Ecol Modell Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Ecol Modell Ano de publicação: 2017 Tipo de documento: Article