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Ecosystem-based management approaches require an understanding of how environmental conditions interact with living ecosystem components to influence the productivity of harvested species. This project is structured around the central hypothesis that the intensity, duration, and spatial extent of hypoxia will have important and measurable effects on the benthic invertebrate community that anchors much of the Chesapeake Bay demersal food web and contributes to the diet of many economically and ecologically important fishery species. In addition to this central hypothesis, we will evaluate the ecological trade-offs resulting from simultaneous stimulation of food availability and habitat loss (e.g., hypoxia) associated with nutrient loading. We expect that there will be generally positive relationships between 1) local primary production and benthic biomass (trophic fertilization), and 2) local primary production and prevalence of hypoxia (eutrophication), likely resulting in non-linear and spatially- and temporally-dependent relationships between hypoxia, primary production, and benthic productivity. We will combine machine learning, statistical and numerical modeling tools necessary to test and explore these hypotheses. While some of these tools already exist, such as the Chesapeake Bay Program’s 3-D water quality model (ROMS model), this project will include the development of new model-based applications (e.g., hypoxia network model, Benthos-ROMS model). The knowledge gained through completing this project will contribute to a more holistic understanding of how food availability and hypoxia interact to alter the foraging landscape for ecologically and economically important predator fish and will provide new predictive tools to link these factors to coastal food webs.