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The Effect of Connecting Sites in the Environment of a Harvested Population

Authors :
Rafael Bravo de la Parra
Jean-Christophe Poggiale
Pierre Auger
Universidad de Alcalá - University of Alcalá (UAH)
Institut méditerranéen d'océanologie (MIO)
Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)
Unité de modélisation mathématique et informatique des systèmes complexes [Bondy] (UMMISCO)
Université de Yaoundé I-Institut de la francophonie pour l'informatique-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Université Gaston Bergé (Saint-Louis, Sénégal)-Université Cadi Ayyad [Marrakech] (UCA)-Sorbonne Université (SU)-Institut de Recherche pour le Développement (IRD [France-Nord])
Source :
Mathematical Modelling of Natural Phenomena, Mathematical Modelling of Natural Phenomena, 2023, 18, pp.4. ⟨10.1051/mmnp/2023004⟩
Publication Year :
2023
Publisher :
HAL CCSD, 2023.

Abstract

International audience; This work presents a model of a harvested population in a multisite environment. Locally it has the shape of the Gordon-Schaefer model. This model gives rise, placing us in the case of a fishery, to an equilibrium of the stock and the fishing effort and, therefore, of the yield that is obtained per unit of time. Considering that the management of the fishery can act on the fishing costs, the yield is optimized as a function of the cost. The objective of the work is to compare the maximum obtained yield in two extreme cases: unconnected sites and connected sites with rapid movements of both the stock and the fishing effort. The analysis of the model, first in an environment with two sites and later with any number of them, makes it possible to establish the conditions for one of the two cases to be more favorable from the point of view of the yield. In this way, it is proposed towards which of the two compared cases management should be directed.

Details

Language :
English
ISSN :
09735348 and 17606101
Database :
OpenAIRE
Journal :
Mathematical Modelling of Natural Phenomena, Mathematical Modelling of Natural Phenomena, 2023, 18, pp.4. ⟨10.1051/mmnp/2023004⟩
Accession number :
edsair.doi.dedup.....27706b6ccb1ca08d333b9f8e1c42a04f