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Home » Incorporating fish in Earth system predictions

Incorporating fish in Earth system predictions

.Living marine resources (LMRs) are exquisitely sensitive to climate variability and change, displaying dramatic fluctuations on seasonal-to-decadal scales and significant vulnerability to anthropogenic warming, deoxygenation, and acidification trends. The ability to predict the response of fisheries to climate variations is essential to sound LMR management. Earth system models (ESMs) are an important tool in this context and have demonstrated predictive skill for physical and biogeochemical variables on seasonal to decadal time scales. ESM predictions have not directly simulated fish, however, thereby precluding a dynamical representation of feedbacks and nonlinear interactions. Our objective is to extend ESM predictions to include fish explicitly. We will couple an existing Fisheries Size and Functional Type model (FEISTY) to the MOM6 ocean general circulation model (OGCM), thereby enabling direct simulation and prediction of potential fish catch, fish distributions, and food web structure in the Geophysical Fluid Dynamics Laboratory (GFDL) and National Center for Atmospheric Research (NCAR) ESMs. Rationale. There is a compelling need for projections of future fisheries yields with accurate estimates of uncertainty; current projections suggest changes could be large, but uncertainties are also very large. Uncertainty arises from climate scenarios, internal climate variability, and structural differences in ESM frameworks. The recent adoption of NOAA’s MOM6 ocean model by the two major US modeling centers (NCAR and GFDL) provides an opportunity to accelerate research into large-scale fisheries responses to climate variability and change and the associated uncertainties. Summary of work. We will couple FEISTY to MOM6. We will evaluate and understand the dependencies and interactions between the higher trophic levels in FEISTY and the lower trophic levels (phytoplankton, zooplankton, etc.) represented in the underlying ocean biogeochemistry model. We will tune and optimize solutions, relying on empirical datasets constraining distributions of biogeochemical tracers and algal, zooplankton and fish biomass. Our ultimate scientific product will be analysis of global ocean-sea-ice hindcast integrations of MOM6 that include prognostic biogeochemistry and explicitly simulate spatiotemporal variability in potential fish catch, fish distributions, and food web structure—as well as interactions coupling higher trophic level dynamics explicitly down through nutrient and oxygen cycling. This project will open extensive possibilities for future work, including fully-coupled ESM predictions and regional simulations.
Broader impacts and relevance. The proposed work comprises an essential step in developing explicit representations of linkages connecting large-scale climate dynamics to ecosystems sustaining LMRs. This work will enable scientists and resource managers to leverage improving ESM predictions, inclusive of explicit higher-trophic level forecasts. Ultimately, this work builds towards a comprehensive framework for integrated ecosystem assessment, inclusive of uncertainties stemming from structural differences in models, internal climate variability, and differences in climate scenarios.

Climate Risk Area: Marine Ecosystems

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