Deciphering the distribution of Indian mackerel, Rastrelliger kanagurta (Cuvier, 1817) along the Northwest coasts of India

Sahina, Akter and Nakhawa, A D and Bhendekar, S N and Lal, Dhanya M and Abidi, Zeba Jaffer and Nayak, B B and Karankumar, R (2024) Deciphering the distribution of Indian mackerel, Rastrelliger kanagurta (Cuvier, 1817) along the Northwest coasts of India. Thalassas: An International Journal of Marine Sciences. pp. 1-13. ISSN 2366-1674

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Official URL: https://link.springer.com/article/10.1007/s41208-0...

Abstract

Rastrelliger kanagurta (Cuvier, 1817), commonly known as the Indian mackerel, is found widely across the coastlines of the Indian Ocean. This study explores the applicability of the Generalized Additive Model (GAM) for predicting the habitat preferences of the Indian mackerel. Data on Indian mackerel catch and oceanographic parameters were collected from January 2017 to April 2019. Parameters such as Sea Surface Temperature (SST), Chlorophyll-a concentration (CHL), Sea Surface Height (SSH), Sea Surface Salinity (SSS), Mixed Layer Depth (MLD), and Ocean Currents (OC) were sourced from the Copernicus Marine Environment Monitoring Service (CMEMS) satellites. Initial ggpairs plot analysis showed positive correlations between Indian mackerel abundance and SSH (p < 0.01, r = 0.19), and negative correlations with SSS (p < 0.01, r = -0.23) and OC (p < 0.05, r = -0.15). GAM results indicated that CHL (p < 0.001), SSS (p < 0.001), SSH (p < 0.001), SST (p < 0.001), and MLD (p < 0.05) significantly influence Indian mackerel catch along the Northwest coast of India. The distribution map revealed high abundance in the coastal waters of Mumbai and Raigad. GAM outputs were employed to generate a spatial prediction map, suggesting the potential for increased catches beyond 50 m depth compared to coastal areas. This study highlights the usefulness of multispectral satellite images in identifying potential fishing grounds. The findings from this research can aid decision-making, reduce fuel costs related to search and fishing operations, and enhance understanding of climate change effects on Indian mackerel distribution.

Item Type: Article
Uncontrolled Keywords: Indian mackerel; Oceanographic parameters; Generalized additive model; Habitat preference; Spatial prediction
Subjects: Pelagic Fisheries > Mackerel fishery
Divisions: CMFRI-Mumbai
Depositing User: Arun Surendran
Date Deposited: 13 May 2025 11:29
Last Modified: 13 May 2025 11:29
URI: http://eprints.cmfri.org.in/id/eprint/18589

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