Fish and Fisheries · 2020 · 15 citations · 67 references
Natural ResourcesFisheriesNatural Resource EconomicsFisheries EconomicsFisheries ManagementMarine FisheriesFisheries SubsidiesFishery BioeconomicsFishery Management EconomicsFishery Resource EconomicsFishing Effort ManagementMarine Fisheries EconomicsBenefit Transfer In FisheriesBioeconomic Effort ModelsCapacity-building SubsidiesFisheries Subsidy PolicyFishery Bioeconomic ModelingFishing Effort OptimizationProfit ReallocationTuna Fisheries
Abstract The western and central Pacific Ocean (WCPO) tuna fishery is one of the world's largest in terms of both catch volume and value, providing over half of global tuna catch with a landed value of US $5.84 billion in 2017. Fishing is conducted by both large‐ and small‐scale fleets, with fisheries subsidies disproportionately benefiting the former. The primary objective of this study was to determine the optimal distribution of effort between two large‐scale fisheries (LSF) and two small‐scale fisheries (SSF) in the WCPO under three scenarios: to maximize industry benefits, minimize subsidization or maximize food supply. The objective was approached using a bioeconomic game‐theoretic model. Results indicate opposite distributions of effort to maximize industry benefits (all fishing conducted by LSF) or to minimize subsidization (all fishing by SSF), with more balanced effort distributions to maximize food supply. Total value of capacity‐enhancing subsidies in optimal scenarios ranged from $1.4 billion when industry benefits were maximized to $0.2 billion when subsidization was minimized. Investigation of suboptimal scenarios reveals the flexibility of these results, with wide ranges in outputted state variables for a given goal. Difficulty was encountered in modelling the SSF sector due to data deficiencies, a well‐recognized issue in managing SSF. Investments towards “data equity” to help ensure that management decision‐making can properly account for the SSF sector would be useful. This study has implications for the objectives we set in fisheries management, and the potential trade‐offs, often value‐driven in nature, that we must make explicit in that management.
67
R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
John F. Nash · Annals of Mathematics · 1951 · 6.6K citations
John C. Nash · Econometrica · 1953 · 3.2K citations
On the Dynamics of Exploited Fish Populations
Raymond J. H. Beverton, Sidney J. Holt · Copeia · 1958 · 2.7K citations
The State of World Fisheries and Aquaculture 2026
FAO eBooks · 2013 · 2K citations · Full text