A multidecadal study of the Malabar upwelling system influencing Indian Mackerel landings along the coasts of Karnataka and Kerala, south-east Arabian Sea

Abstract

Indian Mackerel (Rastrelliger kanagurta) is an essential small pelagic fishery resource, contributing to nearly 30 % of India's total marine fish landing. However, this species' life cycle and stock status are poorly understood and data deficient. Ocean mesoscale events are also known to influence their landing, besides the environmental factors like- salinity, chlorophyll, and sea surface temperature, affecting these small pelagic fishes' availability, migration, feeding, and reproductive activity. The Malabar upwelling region (southwest coast of India) is a significant upwelling system where upwelling occurs during the monsoon months. The nutrient-rich water increases the productivity of surface water, leading to plankton abundance. This productivity sustains a fishery for several commercially important fishes, mainly small pelagics such as sardines, mackerels, and anchovies, supporting India's most significant coastal pelagic fishery. For understanding the relationship between the target fish and the oceanographic events, in the present study, Pearson's correlation has been estimated between Indian Mackerel landing, rainfall, Sea water temperature at 0, 10, 20, 30, 45, and 50 m depths, mixed layer depth (MLD), their anomalies and occurrences of potential fishing zone (PFZ) lines along the Malabar upwelling region and corresponding coasts of Karnataka and Kerala. Mackerel landing time series showed a significant autocorrelation in four-quarter lag, correlation with rainfall anomaly in one-quarter lag, with PFZ line and MLD in three-quarter lag, and with SWT@50 (Seawater temperature@50 m depth) and SST anomaly in two-quarter lag both in Karnataka and Kerala. Upwelling events, as indicated by the presence of PFZ lines, were found to significantly impact the landings of Indian mackerel along the Karnataka and Kerala coasts. Polynomial equations were used to model the relationship between mackerel landings and these environmental factors, effectively capturing the influence of these parameters on mackerel catch trends.