Dynamics of a fishery with nonlinear harvesting: control, price variation, and MSY

In this paper, we construct and analyse a new fishing mathematical model, which describes the time evolution of a fish stock, which is harvested by a fishing fleet, described by its fishing effort.  We consider that the price, which is given by the difference between supply and demand, is varying with respect to time.  For the harvesting function, we use the Holling II function.  On the other hand, we consider two different time scales: a fast one for the price variation and a slow one for fish stock and fishing effort variations.  We use an "aggregation of variables" method to get the aggregated model that governs fish biomass and fishing effort in the slow time.  By analyzing this reduced model, and under some conditions, we prove that three interesting equilibria can occur.  Furthermore, we show how one can control the model to avoid the undesirable situations and to reach the stable equilibrium.  Another interesting aspect given in this manuscript is the possibility of the implementation of Marine Protected Areas (MPAs).  We show how that MPAs permits us to contribute significantly to the rehabilitation of depleted fish populations.  This is achieved by disrupting the state of "Fish Extinction" equilibrium, and establishing a stable one.

  1. Clark C. W.  Mathematical Bioeconomics: The optimal management of renewable resources.  Wiley, New York (1990).
  2. Mchich R., Auger P., El Abdlaoui A.  Méthode d'agrégation des variables appliquée à la dynamique des populations.  Revue Africaine de Recherche en Informatique et Math{\'e}matiques Appliquées.  5, 26–32 (2005).
  3. Mchich R., Auger P., Brochier T., Brehmer P.  Interactions Between the Cross-Shore Structure of Small Pelagic Fish Population, Offshore Industrial Fisheries and Near Shore Artisanal Fisheries: A Mathematical Approach.  Acta Biotheoretica.  64, 479–493 (2016).
  4. Bazykin A. D.  Nonlinear Dynamics of Interacting Populations.  World Scientific, Singapore (1998).
  5. Edelstein-Keshet L.  Mathematical Models in Biology.  Random House, New York (1998).
  6. Barbier E. B., Strand I., Sathirathai S.  Do open access conditions affect the valuation of an externality? Estimating the welfare effects of mangrove-fishery linkages.  Environmental and Resource Economics.  21, 343–367 (2002).
  7. El Hakki I., Mchich R., Bergam A., Charouki N., El Harrak A.  Effect of a nonlinear demand function on the dynamics of a fishery.  Mathematical Modeling and Computing.  10 (4), 1143–1153 (2023).
  8. Auger P., Mchich R., Raïssi N., Kooi B.  Effects of market price on the dynamics of a spatial fishery model: Over-exploited fishery/traditional fishery.  Ecological Complexity.  7 (1), 13–20 (2010).
  9. Brochier T., Auger P., Thiao D., Bah A., Ly S., Nguyen-Huu T., Brehmer P.  Can overexploited fisheries recover by self-organization? Reallocation of fishing effort as an emergent form of governance.  Marine Policy.  95, 46–56 (2018).
  10. Ly S., Balde M., Mansal F., Nguyen-Huu T., Auger P.  A Model of a Multi-Site Fishery with Variable Price: from Over-Exploitation to Sustainable Fisheries.  Mathematical Modelling of Natural Phenomena.  8, 130–142 (2014).
  11. Mchich R., Auger P., Bravo de la Parra R., Raïssi N.  Dynamics of a fishery on two fishing zones with fish stock dependent migrations: aggregation and control.  Ecological Modelling.  158 (1–2), 51–62 (2002).
  12. Schaefer M. B.  Some considerations of population dynamics and economics in relation to the management of the commercial marine fisheries.  Journal of the Fisheries Board of Canada.  14, 669–681 (1957).
  13. Ly S., Auger P., Balde M.  A bioeconomic model of a multi-site fishery with nonlinear demand function: number of sites optimizing the total catch.  Acta Biotheoretica.  62 (3), 371–384 (2014).
  14. Moussaoui A., Auger P.  A bioeconomic model of a fishery with saturated catch and variable price: Stabilizing effect of marine reserves on fishery dynamics.  Ecological Complexity.  45, 100906 (2021).