Modelling the influence of climate drivers on the spatial distribution of scads along the West Coast of India

Bright, Rose P and Varghese, Eldho and Joseph, Alphonsa and Jayasankar, J and Ratheesh Kumar, R and Gills, Reshma and Kishore, Nanda and George, Grinson and Sreenath, K R (2025) Modelling the influence of climate drivers on the spatial distribution of scads along the West Coast of India. In the context of climate change-driven oceanic shifts, understanding the spatial distribution of commercially important fish species is crucial for sustainable fisheries management. In 2022, the mainland coast of India reported marine fish landings of 3., 86. pp. 1-13. ISSN 2352-4855

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Abstract

In the context of climate change-driven oceanic shifts, understanding the spatial distribution of commercially important fish species is crucial for sustainable fisheries management. In 2022, the mainland coast of India reported marine fish landings of 3.49 million tonnes, reflecting a 14.53 % growth compared to 2021. Notably, scads contributed significantly, with landings of 1.63 lakh tonnes, emphasizing the necessity of studying their spatial distribution along the Indian coastline. This study employs Species Distribution Models (SDMs) to predict the potential habitat niches of scads along the west coast of Indian Exclusive Economic Zone (EEZ) by dividing it into 446 grids, each spanning 0.5° × 0.5° and integrating key environmental variables such as sea surface temperature, salinity, chlorophyll concentration, dissolved oxygen, pH, and bathymetry. Passive georeferencing approach was adopted to derive the probable fishing grounds of the resource, which were further combined with environmental factors to build a comprehensive spatial database. The SDMs utilized this dataset to examine the relationship between scads' presence/ absence on these grids and environmental variables. A series of SDMs were fitted to the data and compared the model efficiency in terms of TSS and AUC scores. Further, an ensemble modelling approach was adopted to enhance prediction accuracy, synthesizing outputs from multiple models. Results demonstrated a strong influence of environmental factors viz., chlorophyll (CHL) and sea surface salinity (SSS) on scads' spatial distribution and provided reliable predictions of their potential habitats. These validated models were then applied to predict the potential distribution of scads along the west coast of India under varying climatic scenarios (SSP2, SSP3 & SSP5), it is observed that in the near future, scads are projected to experience significant range loss to changing environmental conditions.

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