A suite of models will enable managers to assess fishing community vulnerability under climate change, with important policy implications for management of scallop fisheries in the Northeastern U.S.
The Atlantic sea scallop fishery has grown to be one of the most important fisheries in the Northeastern U.S., averaging around $500 million in annual catch revenue in recent years, compensating for declining yields of historically important finfish like cod, haddock, and flatfish.
The current scallop management program rotates access for scallop fishers between open and closed areas. When resource managers detect high abundances of small scallops in an area, that area can be closed to fishing to allow the scallops to grow larger. This increases value through more abundant catches and higher prices associated with the bigger scallops.
To ensure the sustainability and effectiveness of the area management program, it is essential to be aware of climate-driven changes in the scallops’ habitat—including both biological (e.g., food availability and predation risks) and physicochemical (e.g., temperature and pH) conditions. It is also critical to be able to use these changes in environmental conditions as predictors of scallop fishers’ behavior, such as choice of fishing routes and harvest locations.
To better understand the socioeconomic impacts of a changing ocean on the sea scallop industry, WHOI biologist Rubao Ji and colleagues, in collaboration with scientists from NOAA’s National Marine Fisheries Service and UMass Dartmouth, used new data on scallop catches and scallop spatial distributions (stocks) to model the relationship between catch per unit effort and scallop stocks. They are also developing economic models to describe how scallop fishers’ expectations of stock abundance, anticipated revenues, historical fishing patterns, vessel characteristics, season, management, and other drivers affect their choice of routes and harvest locations. Rubao and his team are also using models that link scallop biology and conditions in their habitat to predict potential changes in fishing revenue at a given port in response to changing resource conditions there.
Together, this suite of models will enable managers to assess fishing community vulnerability under climate change, with important policy implications for the area management program.
Rubao Ji is a scientist in WHOI’s Biology Department with over 20 years of experience in developing numerical models that link fluid dynamics and marine biology. Among other applications, Ji has used models to predict the effects of ocean currents on nutrients and marine life and the impacts of climate change on ocean food webs.