North Indian Ocean region around India and Sri Lanka is a complex and rich coastal ecosystem undergoing various seasonal and inter-annual changes and various pressures. Hence the objective of this study was to assess the scales of coupling between chlorophyll-a concentration (chl-a) and the influencing variables and explore the nature of the spatiotemporal variability of them. The seasonal and annual variations of chl-a along the Bay of Bengal (BoB), Arabian sea (AS) and ocean region around Sri Lanka in relation to the physical and chemical oceanographic variables were analyzed using satellite observations covering the period of 2002-2018. The effects of diffuse attenuation coefficient, photosynthetically available radiation (PAR), sea surface temperature (SST), Wind speed, Eastward wind component, Nitrate, Black carbon column mass density, Sea Salt Surface Mass Concentration, Open water net downward longwave flux, Surface emissivity were considered on a monthly time scale. Wavelet analysis and the Boosted Regression Trees (BRT) were used as the main analysis and modeling methods. The peaks of chl-a, diffuse attenuation coefficient, and nitrate were observed in September. In wind speed and eastward wind it was July and in black carbon column mass density, and PAR in March. In Sea Salt Surface Mass Concentration, Open water net downward longwave flux, Surface emissivity, Diffuse attenuation coefficient for downwelling irradiance, and SST mean maximums were found in June, February, November, September, April respectively. In BRT model the estimated cross validation (cv) deviance, standard error (se), training data correlation, cv correlation, and D2 were 0.003, 0.002, 0.932, 0.949, and 0.846 respectively. According to the results, diffuse attenuation coefficient (90%), eastward wind component (3.7%) and nitrate (3%) were the most positively correlated variables with Chl-a occurrence. SST evidenced an inverse relationship with Chl-a. According to the model built <42 Einsteinm-2day-1 PAR, <0.986 surface emissivity, <70 Wm-2 open water net downward long wave flux, 28.2 -28.5 0C SST , 2 ms-1 Wind speed, 5 ms-1 - 6 ms-1 eastward wind, 4.8 x10-8 -7x10-8 kgm-3 sea salt surface mass concentration, and 0.1-0.5micromoleL-1 nitrate are favourable for the optimum level of phytoplankton occurrence. Since BRT deals robustly with non-linear relationships of the environmental variables it can be used in further studies of ecological modeling.

Swordfish (Xiphias gladius) are a highly migratory keystone species, found in tropical and temperate seas that are influenced by environmental parameters. In the Bay of Bengal, the Arabian Sea, and the ocean region around Sri Lanka, the environment is gradually changing as a result of climate change. In this study, we identified the preferable environmental conditions for swordfish using satellite-derived environmental data and in-situ fish catch data. We modeled the relationships between fish distribution and the environment changes using Boosted Regression Trees (BRT) and Generalized Additive Model (GAM) methods. The monthly mean fishing effort is comparatively high from October to March and the fish catch rates are high from September to November. Chlorophyll-a concentration has a positive relationship with catch rates while sea surface temperature (SST), sea salt surface mass concentration (SSS), and effort show negative relationships. Approximately 0.3–0.4 mgm−3 of chlorophyll-a, 28–28.5 °C SST, and (3–5)10−8 kgm−3 of SSS were significantly correlated with high swordfish catch rates. According to the optimum environmental conditions identified using the above models, the suitable environmental spatial and temporal distribution was mapped. The results show that the optimum conditions for swordfish are in the eastern region of Sri Lanka, around Thailand and Myanmar, from June to August, and around Bangladesh, Myanmar, Pakistan, the west coast of Sri Lanka, and the east coast of India during September to November.