Modeling the impacts of fishing regulations in a tropical Indian estuary using Ecopath with Ecosim approach

• Published in: Environment, development and sustainability Vol. 23; no. 12; pp. 17745 - 17763
• Main Authors: Sreekanth, G. B., Chakraborty, S. K., Jaiswar, A. K., Zacharia, P. U., Mohamed, K. S.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01-12-2021; Springer Nature B.V
• Subjects: Bans; Commercial fishing; Direct reduction; Earth and Environmental Science; Ecology; Economic Geology; Economic Growth; Ecosystems; Environment; Environmental Economics; Environmental Management; Estuaries; Fish; Fisheries; Fishery policy; Fishing; Functional groups; Recovery; Regulation; Regulations; Sustainable Development; Trophic levels; Simulation; Fishing regulation; Indiscriminate fishing; Zuari estuary; Ecopath with Ecosim
• ISSN: 1387-585X; 1573-2975
• DOI: 10.1007/s10668-021-01410-3

In this study, we measured the impacts of an effective fishing regulation on the sustainability of fisheries in Zuari estuary, a tropical estuary situated along western coast of India through an Ecosim approach. Ecosystem indicators for 2016 and 2031 (for each Ecosim scenario) were measured to compare and contrast the decadal changes in the status of the ecosystem between these two periods. Four different hypothetical fishing patterns were simulated to explore the best suited management scenario. The ecosystem indices of 2031 ecosystem were compared with that obtained for 2016 to evaluate the possible effects of fishing regulations. The functional groups showed a decline in their biomass when no fishing regulations are implemented (S1). The direct fishing effort reductions of all the fleets (S4) and ban/reduction of indiscriminate fishing fleets (S2-immediate ban and S3-gradual reduction) showed a more or less similar trend for recovery of fish stocks through diverse fisheries policies. A complete ban of indiscriminate fishing seems to slightly more advantageous than the direct reductions in the fishing effort for all the fleets in terms of stock recovery (130%), Q statistic (1.15), Shannon diversity (1.43), mean trophic level of ecosystem (2.98), mean trophic level of the catch (2.91) and fish catch in the gillnet fleet (200%). The simulations have also suggested that a complete control for mechanized fishing fleets will be the best possible management strategy for the recovery of fish stocks in the ecosystem.