Optimal Multispecies Harvesting Targets in Biologically, Technologically, and Temporally Interdependent Fisheries
Economic and Social Sciences Research (ESSR) Program researcher Stephen Kasperski is developing multispecies bioeconomic models of groundfish in the Bering Sea. These models are designed to account for the biological interactions among species, technological interactions which result in catching multiple species, and temporal interactions between species as fishermen allocate their effort across multiple fisheries over the course of a year. Ecosystem-based approaches to fisheries management should address both the interactions that occur in the biological ecosystem as well as the larger economic system in which the harvesters operate. Single-species management of multispecies fisheries ignores these interactions and can lead to the detriment of the health of the ecosystem, fish stocks, and fishery profits.
The model developed in this study solves a dynamic optimization problem of maximizing the value from a three-species fishery and determines the optimal harvest quota of each species given the biological, technological, and temporal interactions. The model is currently being applied to the pollock, Pacific cod, and arrowtooth flounder fisheries in the Bering Sea to estimate optimal harvesting quota for each species over time. The population of each species will be simulated into the future with and without each set of interactions to isolate the impact of each type of species interactions on the sustainability and profitability of the fishery. The current theoretical results highlight the importance of including biological, technological, and temporal interactions when determining quota in a multispecies fishery.
By Stephen Kasperski
Eliminating Double Counting When Estimating Regional Economic Impacts of Harvest Changes
Demand-driven input-output (IO) models are useful in calculating the economic impact from changes in final demand, enabling analysts to examine interindustry transactions. Some previous studies, however, argue that it is more appropriate to use supply-driven models in situations where the output level (e.g., harvest level or total allowable catch (TAC)) is altered, because the change in demand is not known. In addition, for complex international sectors such as North Pacific fisheries, it is not necessarily easy to derive changes in final demand that would correspond to the initial change in output in the supply side. However, supply-driven models that calculate the forward linkage effects have been criticized due to technical theoretical issues, and economists have criticized the models in applications where they are used to explain changes in physical output arising from changes in physical factor inputs (common in fisheries applications).
To address these weaknesses and correctly estimate the economy-wide impacts of an exogenous change in productive capacity (e.g., change in harvest level or TAC), we can run the demand-driven IO model with changes in output specified as final demand changes and with regional purchase coefficients (RPCs) for all the directly impacted industries (e.g., fish harvesting and processing industries) set equal to zero. By setting the RPCs to zeroes, the model can effectively prevent other regional industries from purchasing the output from these seafood industries, and therefore, avoid the double counting problem typically encountered when demand-driven approaches are used to calculate the impacts of exogenous change in output. ESSR researcher Chang Seung is developing this type of model to improve estimates of regional economic impacts of various fishery management actions involving changes in catch of certain species or landings of certain vessel types.
