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While most food and feeding research in fisheries emphasize the feeding habits and diet components of the fish, the aim of the present work was to assess any change in the diet composition of Indian mackerel Rastrelliger kanagurta (Cuvier, 1816) and identify the role of climate change in effecting it. Non-parametric statistical technique, the Generalized Additive Model (GAMs) was used for modeling the causal link of diet changes in relation to climate change using mgcv package of R software. Monthly Index of Relative Importance (IRI) was calculated for 36 months from January 2013 to December 2015 and major prey items in the diet were identified. Climatic variables - Sea Surface Temperature (SST), precipitation (Pr), Chlorophyll a (Chl a), salinity and Ekman transport or coastal upwelling index (CUI)) pertaining to the study area were extracted for the period. Length-wise IRI was compared to check the existing patterns in the feeding habits of the fish. The dominant prey items observed in the gut of Indian mackerel during the study period were diatoms ( Fragillaria sp., Nitzchia sp., Thalassiothrix sp., Thalassiosira sp. and Coscinodiscus sp.), dinoflagellates (Ceratium sp., Ornothocercus sp., Dinophysis sp. and Prorocentrum sp.), copepods (Calanoida, Cyclopoida and Harpacticoida), decapods (Acetes) and tintinnids (Tintinnopsis sp., Codenellopsis sp. and Flavella sp). GAM models were fitted with monthly IRI of the major prey items (copepods, diatoms, dinoflagellates, Acetes and tintinnids) in the gut and climatic variables. Model selection was done in terms of sharpening the relation between the predictors and the response variable using Akaike information criterion, R-squared and F-statistics. GAM model results revealed that occurrence of prey items in the diet of Indian mackerel were influenced by environmental variables. An increase in the relative importance of dinoflagellates, Acetes and tintintids in the diet over the historic period was observed. The study also revealed a shift in the diet composition of younger fishes. The results of the current study provide a more in-depth assessment of the nonlinear relationship between climatic variables and diet composition of Indian mackerel.

Comparison of chlorophyll data of three sets of CMIP5 models for RCP 4.5 (MPI-ESM-MR, HadGEM2-ES and GFDL-ESM2M) and RCP 6.0 (IPSL-CM5A-LR, HadGEM2-ES and GFDL-ESM2M) were done with satellite derived data (OC-CCI) for the period of 1998–2017 along four Indian coastal regions. The monthly, yearly and zone-wise seasonal comparison between model and satellite data were carried out. Analysis of monthly variations of chlorophyll during 1998–2017 reveals that the satellite data show maximum value of 0.53 mg/m3 in September, whereas all other models show maximum in August. Yearly analysis indicates maximum satellite data in the year 2004, while minimum was observed in 2015. HadGEM2-ES exhibited maximum model value and the lowest was found for IPSL-CM5A-LR. It was observed that the maximum chlorophyll value of 2.56 mg/m3 for satellite data was in the monsoon season and the lowest value of 0.14 mg/m3 was in the pre-monsoon. Seasonal analysis reveals no clear match among model and satellite values in any of the coastal regions. In northwest and northeast regions, the satellite values were found higher than the model values in most of the years, whereas in other regions, the model values were found fluctuating with the satellite values. Owing to the mismatch of the model and the satellite values, the work cautions to apply biases or corrections on usage of RCP model data for regional marine climate change research.

The Indian mackerel Rastrelligerkanagurta(Cuvier, 1816) is one of the most important marine fishery resources along the south-eastern Arabian Sea along the coast of Kerala, south India. The effect of selected environmental variables on the Relative effort (Effort) and weighted catch per unit effort (cpue)of the fish were investigated using simple correlation and Path analysis. Six major oceanographic variables, namely sea surface temperature (SST), sea surface chlorophyll-a concentration (SSC), sea surface salinity (SSS), Precipitation (Pr) Indian Ocean Dipole (IOD) and Southern Oscillation Index (SOI) (ENSO index) were selected for the present study. Among these SST had the highest direct negative effect (-0.282, p SSC >SSS.

Akhiljith, P.J.; Liya, V.B.; Rojith, G.; Zacharia, P.U.; Grinson, G.; Ajith, S.; Lakshmi, P.M.; Sajna, V.H., and Sathianandan, T.V., 2019. Climatic projections of Indian ocean during 2030,...

Joseph, D.; Liya, V.B.; Rojith, G.; Zacharia, P.U., and Grinson, G., 2019. Time series analysis of CMIP5 model and observed sea surface temperature anomaly along Indian coastal zones. In: ...

Najmudeen, T.M.; Febna, M.A.A.; Rojith, G., and Zacharia, P.U., 2019. Characterisation of biochar from water hyacinth Eichhornia crassipes and the effects of biochar on the growth of fish ...

Ajith, S.; Rojith, G.; Zacharia, P.U.; Nikki, R.; Sajna, V.H.; Liya, V.B., and Grinson, G., 2019. Production, characterization and observation of higher carbon in Sargassum wightii biochar from Indian coastal waters. In: Jithendran, K.P.; Saraswathy, R.; Balasubramanian, C.P.; Kumaraguru Vasagam, K.P.; Jayasankar, V.; Raghavan, R.; Alavandi, S.V., and Vijayan, K.K. (eds.), BRAQCON 2019: World Brackishwater Aquaculture Conference. Journal of Coastal Research, Special Issue No. 86, pp. 193–197. Coconut Creek (Florida), ISSN 0749-0208.Seaweed farming gains significance as a climate resilient strategy owing to significant carbon sequestration potential and research advances to valorize products from seaweed resources. Conversion of seaweeds to biochar enhances further carbon sequestration. In this study Sargassum wightii, belonging to brown algae has been converted into biochar under different conditions of pyrolysis for possible application in aquaculture sector. The prepared biochar was subjected to elemental (CHNS) analysis to assess the nutrient profile. Further, comparative analysis has been done on raw seaweed and biochar based on the structural characterization using SEM, XRD and FTIR spectra. Functional group changes were evidenced from FTIR and XRD spectra, whereas surface modifications were elucidated by SEM analysis. The optimum temperature for biochar pyrolysis of S. wightii to yield higher carbon content has been identified. A significant observation is that seaweeds in Indian coastal waters are capable of higher carbon sequestration than in other waters.

Sajna, V.H.; Zacharia P.U.; Liya, V.B.; Rojith, G.; Somy, K.; Joseph, D., and Grinson, G., 2019. Effect of climatic variability on the fishery of Indian Oil sardine along Kerala coast. In: Jithendran, K.P.; Saraswathy, R.; Balasubramanian, C.P.; Kumaraguru Vasagam, K.P.; Jayasankar, V.; Raghavan, R.; Alavandi, S.V., and Vijayan, K.K. (eds.), BRAQCON 2019: World Brackishwater Aquaculture Conference. Journal of Coastal Research, Special Issue No. 86, pp. 184–192. Coconut Creek (Florida), ISSN 0749-0208.Indian oil sardine (IOS), the commercially and ecologically important pelagic fish of the Kerala coast is susceptible to climatic variation. The study analyzes the impact of climate change on the catch of Sardinella longiceps along the Kerala coast and tries to predict the catch trend under the two RCP scenarios 4.5 and 6.0 for the period 2020-2100. Monthly catch of IOS by major gears for the period 1990-2016 was collected and Relative effort (Effort) and Weighted CPUE (cpue) were accordingly estimated. The climatic variables Sea Surface Temperature (SST), Precipitation (Pr), Chlorophyll a (SSC) and Salinity (SSS) were obtained from NOAA/NASA. The relationship of cpue and Effort of IOS to environmental variables were explored by Generalized Additive Model. The best fit model was selected using lowest Akaike information criterion (AIC) value, Deviance and F statistic. Predictions of cpue and Effort under RCP 4.5 and RCP 6.0 were done and the catch of IOS was estimated. The GAM model revealed the variations in the catch of IOS in relation to climate change. The SST, SSS and Pr showed a negative relation whereas SSC was found to be positively related to the catch of IOS. The results of the study indicate a decreasing trend of cpue and catch and an increasing trend of Effort towards 2100 under both climate change scenarios.