ASSESSING HYPOXIA EFFECTS ON
the Northern gulf FISHERY

NGOMEX 2016: Synthesis and Integrated Modeling of Long-Term Data Sets to Support Fisheries and Hypoxia Management in the Northern Gulf of Mexico.

This project began in September 2016 and is projected to be completed in September 2022

Over the past three decades, an enormous amount of data has been collected in the Northern Gulf of Mexico to study hypoxia and its impacts on coastal ecosystems and associated fisheries. These data have been collected by multiple governmental and academic institutions during monitoring cruises conducted at various spatial scales with frequencies ranging from bi-weekly to annually. While the individual data products from these cruises have been made available through scientific publications and online data repositories, there has been limited progress in synthesizing these data within a common analysis framework. The proposed study will systematically integrate existing datasets using probabilistic, data-centric modeling approaches to more fully evaluate the spatiotemporal dynamics of hypoxia and to understand and forecast effects on fisheries and ecosystem impacts. Components of this work focused on hypoxia dynamics include (1) geostatistical modeling of all available dissolved oxygen data, (2) parsimonious biophysical modeling of hypoxia dynamics, (3) and fusion of geostatistical and mechanistic modeling results to develop optimal estimates of hypoxia through time and over multiple sections of the Louisiana-Texas Shelf. Leveraging these new hypoxia estimates, additional study components will focus on (4) evaluating the effects of hypoxia on regional fisheries (penaeid shrimp, Gulf menhaden), as well as (5) relationships to metrics currently being developed or used to monitor the state of and potential future changes to the Gulf ecosystem (i.e., “ecological indicators”) within the context of other ecosystem stressors. The improved hypoxia and ecosystem prediction capabilities will be leveraged to develop enhanced fisheries forecasts that explicitly consider recent and future (forecasted) hypoxic conditions on the shelf. This study will provide a rich, data-centric approach to understanding hypoxia and its consequences that will both compliment and contrast with more mechanistically complex hydrodynamic and ecosystem models. The proposed approach outlined here will focus on data-driven inference of factors driving hypoxia and fisheries dynamics, rigorous uncertainty quantification, and parsimonious forecasting methodologies that can be readily operationalized in the Gulf and other coastal areas.