BSc - MSc (Integ.)

ENSO events exert an enormous influence on the global weather pattern. El Nino has become very visible in recent years as a dominant source of interannual climate variability around the world. ENSO episodes are known to change the environmental characteristics of coastal waters which are the major habitats for the fish resources that are harvested all along the Indian coasts. The effects of various ENSO episodes from 2007-2020 on Gujarat’s marine fish resources were studied. The monthly catch of major pelagic fish resources like Gold spotted grenadier anchovy (Coilia dussumieri), Bombay duck (Harapadon nehereus), Ribbon fish, Torpedo scad (Megalaspis cordyla), Long tail tuna (Thunnus tonggol), Kawakawa (Euthynnus offinis), Yellowfin tuna (Thunnus albacares); demersal fishes like Croakers, Threadfin bream, and Greater lizard fish (Saurida tumbil); crustacean fishes like Crabs, Stomatopods, Lobsters and Penaeus spp.; and molluscans like Sepia pharonis, Octopus spp., Sepia spp and squids by major gears for the period 2007-2020 were collected and the catch per unit effort (CPUE) was estimated. The ENSO indices like Nino 1+2, Nino 4, Nino 3.4, ONI, MEI, SOI, EMI, DMI, TNI, and ocean-atmospheric parameters such as Chlorophyll a (CHL_A), Salinity (SALT), Sea Surface Height (SSH), Sea Surface Temperature (SST), Local Temperature Anomaly (LTA), Rainfall (RF), Ocean Current Direction (OCD) and Ocean Current Velocity (OCV) were analyzed. GAM (Generalized Additive Model) was used to study the influence of the ENSO phenomenon on different ocean-atmospheric parameters by considering ocean-atmospheric parameters as the response variables and the different ENSO indices as predictors. GAM model results indicated that the ENSO could explain 47.5% of the deviance in local temperature anomaly (R2.adj=0.41), 45.6% of the deviance in SALT (R2.adj=0.39), 45.5% of the deviance in SST(R2.adj=0.38), 41.8%of the deviance in monthly Rainfall (R2.adj=0.33), 35.5% of the deviance in Sea Surface Height (R2. Aj = 0.3) and 31.2% of the deviance in Chla. The ENSSO episodes could explain 39.6% deviance in the abundance of Ribbon fish, 33.3%, 22.9% and 21.8% deviance in the abundance of tuna species such as Thunnus tonggol, Euthynnus affinis, and Thunnus albacares respectively, 34.6% deviance in the abundance of Croakers. 26.6% deviance in the abundance of Threadfin breams, 53.8% deviance in the abundance of Stomatopods and 29.9% deviance in the abundance of Sepia pharonis. The combined model explained 66.6% deviance of Ribbon fish (R2.adj=0.58), 74.1% deviance of Saurida tumbil (R2.adj=0.75), 79% deviance of Stomatopods (R2.adj=0.71) and 75.1% deviance of Sepia spp (R2.adj=0.64). The ENSO episodes alone could explain 32.8% of deviance (R2.adj=0.27) and combination of ENSO and ocean-atmospheric parameters could explain 76.3% of the deviance (R2.adj=0.64) in the abundance of total fish resources the over the Gujarat coast.