AUTHOR=Alizadeh Ashrafi Tannaz , Ersdal Anne Mai , Nordli Anders Samuelsen TITLE=A Multi-Region and Multi-Period Harvest Schedule of the Trawl Fleet JOURNAL=Frontiers in Marine Science VOLUME=8 YEAR=2022 URL=https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2021.738912 DOI=10.3389/fmars.2021.738912 ISSN=2296-7745 ABSTRACT=

Under the individual vessel quota regulations, the expected economic return of a multi species fishery is influenced by an array of a multi-component choice such as targeted species, landings per haul, harvesting time and its location. The components of effort allocation decisions are further complicated by changes in the market conditions and the constant movements of fish between spawning and feeding habitats. Migratory behavior influences the dispersal of species, relative availability of fish and its composition, and the bycatch likelihood across different locations over the course of a fishing year. The objective of this article is to investigate the optimal allocation of fishing effort in the Norwegian bottom-trawl fleet within economically important species; cod, saithe, and haddock across three heavily trawled areas—including southern and northern parts of the west coast of Norway, and the high sea areas of the Arctic—to achieve maximum expected economic return, with respect to the individual vessel quota constraints and bycatch considerations. The results from a mixed integer non-linear optimization problem evidence that the spawning migration of Northeast Arctic cod along the northwest coast, effort allocation behavior of coastal fleet, together with institutional regulations necessitate the substitution of fishing effort across different fishing locations within the fishing season to maximize expected return. The results of our study further reveal that the Arctic region to target cod is the biggest contributor to annual fishing revenue. By contrast, conducting saithe fishery in the southwest of the Norwegian coast has the lowest economic contribution. The results from Monte Carlo simulation demonstrate that the proposed model is effective and applicable for effort allocation decision analysis.