Fisheries management as a Stackelberg Evolutionary Game: Finding an evolutionarily enlightened strategy

Monica Salvioli*, Johan Dubbeldam, Katerina Stankova, Joel S. Brown

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Fish populations subject to heavy exploitation are expected to evolve over time smaller average body sizes. We introduce Stackelberg evolutionary game theory to show how fisheries management should be adjusted to mitigate the potential negative effects of such evolutionary changes. We present the game of a fisheries manager versus a fish population, where the former adjusts the harvesting rate and the net size to maximize profit, while the latter responds by evolving the size at maturation to maximize the fitness. We analyze three strategies: i) ecologically enlightened (leading to a Nash equilibrium in game-theoretic terms); ii) evolutionarily enlightened (leading to a Stackelberg equilibrium) and iii) domestication (leading to team optimum) and the corresponding outcomes for both the fisheries manager and the fish. Domestication results in the largest size for the fish and the highest profit for the manager. With the Nash approach the manager tends to adopt a high harvesting rate and a small net size that eventually leads to smaller fish. With the Stackelberg approach the manager selects a bigger net size and scales back the harvesting rate, which lead to a bigger fish size and a higher profit. Overall, our results encourage managers to take the fish evolutionary dynamics into account. Moreover, we advocate for the use of Stackelberg evolutionary game theory as a tool for providing insights into the eco-evolutionary consequences of exploiting evolving resources.

Original languageEnglish
Article number0245255
Number of pages20
JournalPLOS ONE
Volume16
Issue number1
DOIs
Publication statusPublished - 20 Jan 2021

Keywords

  • RAPID EVOLUTION
  • FISH STOCKS
  • SIZE
  • CONSEQUENCES
  • POPULATIONS
  • MATURATION
  • PATTERNS
  • LOBSTER
  • SHIFTS
  • YIELDS

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