ISSN: 2577-4050
Authors: Nader H*
From May 2023 to September 2024, a total of 270 random samples of Katsuwonus pelamis were collected from the waters off the coast of Syria. Sophisticated analytical methods, including artificial neural networks and fuzzy logic, were utilized to examine these samples. The largest specimen recorded had a fork length of 85 cm and was estimated to be 8 years old. The von Bertalanffy growth equation derived from the fork length data (FLt = 140.72 (1-e-0.09 (t + 2.378))) shed light on the growth dynamics of this Katsuwonus pelamis population, indicating a trend of positive allometric growth, with a growth coefficient (b) of 3.29. The index of growth performance (Φ’) was calculated at 3.24, reflecting efficient growth rates. Estimates of mortality rates for Katsuwonus pelamis showed total mortality (Z) at 1.07 y⁻¹, fishing mortality (F) at 0.85 y⁻¹, natural mortality (M) at 0.22 y⁻¹, and exploitation ratio (E) at 0.79 y⁻¹, resulting in a survival coefficient (S) of 0.34 y⁻¹. The analysis indicated a large population growth (FP) of 56.6, while also revealing a high vulnerability to fishing (58.6 FV), which poses a considerable risk to the species. These findings underscore the necessity for conservation strategies aimed at sustainable management of the species, enhancing our understanding of the growth, mortality, and fishing vulnerability of Katsuwonus pelamis, and informing future research and management efforts.
Keywords: Artificial Neural Network; Exploitation; Fussy Logic; Skipjack Tuna
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