Tracking capelin spawning migration -- Integrating environmental data and Individual-based modeling ...

• Main Authors: Alrabeei, Salah, Subbey, Sam, Rahman, Talal
• Format: Report
• Language: unknown
• Published: arXiv 2023
• Subjects: Populations and Evolution q-bio.PE; Neural and Evolutionary Computing cs.NE; FOS Biological sciences; FOS Computer and information sciences; I.2; I.3; I.6; J.2; J.9; H.3; 92D25, 92C05, 68T05, 68U10; Barents Sea; Northern Norway
• Online Access: https://dx.doi.org/10.48550/arxiv.2311.00424; https://arxiv.org/abs/2311.00424

This paper presents a modeling framework for tracking the spawning migration of the capelin, which is a fish species in the Barents Sea. The framework combines an individual-based model (IBM) with artificial neural networks (ANNs). The ANNs determine the direction of the fish's movement based on local environmental information, while a genetic algorithm and fitness function assess the suitability of the proposed directions. The framework's efficacy is demonstrated by comparing the spatial distributions of modeled and empirical potential spawners. The proposed model successfully replicates the southeastward movement of capelin during their spawning migration, accurately capturing the distribution of spawning fish over historical spawning sites along the eastern coast of northern Norway. Furthermore, the paper compares three migration models: passive swimmers, taxis movement based on temperature gradients, and restricted-area search, along with our proposed approach. The results reveal that our approach ... : 17 pages ...