Exploring effects of hypoxia on fish and fisheries in the northern Gulf of Mexico using a dynamic spatially explicit ecosystem model
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Exploring effects of hypoxia on fish and fisheries in the northern Gulf of Mexico using a dynamic spatially explicit ecosystem model

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  • Journal Title:
    Ecological Modelling
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  • Description:
    The formation of an extensive hypoxic area off the Louisiana coast has been well publicized. However, determining the effects of this hypoxic zone on fish and fisheries has proven to be more difficult. The dual effect of nutrient loading on secondary production (positive effects of bottom-up fueling, and negative effects of reduced oxygen levels) impedes the quantification of hypoxia effects on fish and fisheries. The objective of this study was to develop an ecosystem model that is able to separate the two effects, and to evaluate net effects of hypoxia on fish biomass and fisheries landings. An Ecospace model was developed using Ecopath with Ecosim software with an added plug-in to include spatially and temporally dynamic Chlorophyll a (Chl a) and dissolved oxygen (DO) values derived from a coupled physical–biological hypoxia model. Effects of hypoxia were determined by simulating scenarios with DO and Chl a included separately and combined, and a scenario without fish response to Chl a or DO. Fishing fleets were included in the model as well; fleets move to cells with highest revenue following a gravitational model. Results of this model suggest that the increases in total fish biomass and fisheries landings as a result of an increase in primary production outweigh the decreases as a result of hypoxic conditions. However, the results also demonstrated that responses were species-specific, and some species such as red snapper (Lutjanus campechanus) did suffer a net loss in biomass. Scenario-analyses with this model could be used to determine the optimal nutrient load reduction from a fisheries perspective.
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    Ecological Modelling, 331, 142-150
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  • ISSN:
    0304-3800
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    CC BY
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    Library
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