The Value of Incorporating Seasonal Climate Forecasts into a Harvest Guideline Control Rule for Pacific Sardine

Desiree Tommasi , Princeton University/NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ
Charles Stock , Climate and Ecosystems Group, NOAA Geophysical Fluid Dynamics Lab
State of the art dynamical global forecast systems now exists that allow for projections of climate variables at a seasonal scale. More specifically, we demonstrate that both the NOAA's Geophysical Fluid Dynamics Laboratory (GFDL CM 2.5-FLOR) and the National Center for Environmental Prediction (NCEP CFSv2) climate forecast systems produce skillful projections of sea surface temperature (SST) both at a temporally “fishery relevant” scale, monthly to inter-annual, and at a spatially “fishery relevant” scale, the coastal shelf. Since it is well established that environmental fluctuations affect the productivity of numerous fish stocks, incorporation of such projections into the fisheries management framework has the potential to produce more effective management targets.

We explore the value of future climate information for the fishery management process using the case study of Pacific sardine (Sardinops sagax caerulea). This species was selected as it is one of the only fisheries that already incorporates environmental information into the management framework, through an SST dependent harvest guideline, and for which there is a strong recruitment-SST relationship. We quantify the effectiveness of management, namely stable long-term catches, under four different scenarios: status quo, perfect future information, dynamic forecast future information, and persistence forecast future information.