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A bioeconomic model for a multispecies small-scale fishery system

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  • Azevedo, Eric
  • Pintassilgo, Pedro
  • Dantas, David
  • Daura-Jorge, Fábio Gonçalves

Abstract

A fishery encompasses various interconnected systems, including ecological, socioeconomic, and governing systems. Managing fisheries requires the simultaneous consideration of all these systems, making it a challenging endeavor. To address these challenges, fisheries bioeconomic models have emerged as a crucial tool. They are particularly valuable in the context of small-scale fisheries, which are often complex, overlooked and poorly understood. Thus, this paper presents a dynamic multispecies and multigear bioeconomic model that can illuminate the ecological, economic, and social dimensions of small-scale fisheries under different management scenarios. The model was applied to a small-scale fisheries system in Southern Brazil that has as a notable feature a cooperative fishing behavior between dolphins and fishers. Three scenarios were explored: the base scenario (status quo), the optimal management scenario, and the constrained optimal management scenario. The model outputs demonstrated a clear tradeoff between labour effort, species conservation, and economic rent. Shifting from the base to an optimal management scenario would result in a labour employment reduction within the system but concurrently yield higher stock levels, economic rent, and wages. These results illustrate how our model can explore critical management scenarios across the multiple dimensions of fisheries systems. In essence, this research offers a novel contribution in the form of a bioeconomic model tailored for small-scale fisheries involving multiple species.

Suggested Citation

  • Azevedo, Eric & Pintassilgo, Pedro & Dantas, David & Daura-Jorge, Fábio Gonçalves, 2024. "A bioeconomic model for a multispecies small-scale fishery system," Ecological Economics, Elsevier, vol. 226(C).
  • Handle: RePEc:eee:ecolec:v:226:y:2024:i:c:s0921800924002556
    DOI: 10.1016/j.ecolecon.2024.108358
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