Article
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Dynamics of Sustainable Fisheries: A Mathematical Approach using Lotka-Volterra Equations
Version 1
: Received: 18 September 2023 / Approved: 19 September 2023 / Online: 20 September 2023 (02:44:49 CEST)
How to cite: WUSU, A.; Olabanjo, O. Dynamics of Sustainable Fisheries: A Mathematical Approach using Lotka-Volterra Equations. Preprints 2023, 2023091296. https://doi.org/10.20944/preprints202309.1296.v1 WUSU, A.; Olabanjo, O. Dynamics of Sustainable Fisheries: A Mathematical Approach using Lotka-Volterra Equations. Preprints 2023, 2023091296. https://doi.org/10.20944/preprints202309.1296.v1
Abstract
This study delves into the intricate dynamics of sustainable fisheries through the lens of mathematical modeling, specifically employing the Lotka-Volterra equations. The Lotka-Volterra equations, originally conceived to understand predator-prey interactions, offer a potent framework to model and predict fish population dynamics within aquatic ecosystems. The aim of this research is to demonstrate the applicability and efficacy of the Lotka-Volterra equations in understanding the delicate balance of fish populations and aiding sustainable fisheries management. Through this mathematical approach, we seek to provide a structured methodology and present results that showcase the potential of this model in predicting and managing fish populations. In our analysis, we adjust the parameters of the Lotka-Volterra equations to simulate various scenarios, enabling a comprehensive understanding of sustainable fishing practices. Our findings underscore the significance of mathematical models, particularly the Lotka-Volterra equations, in informing strategies to maintain fish populations in a sustainable and ecologically balanced manner, thereby ensuring the longevity of marine ecosystems and the fisheries thatrely upon them.
Keywords
Sustainable; Fisheries; Predator; Prey; Lotka-Volterra Equations
Subject
Biology and Life Sciences, Aquatic Science
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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