In the current study, remotely sensed sea surface ocean temperature (SST) and sea surface chlorophyll (SSC), an indicator of tuna abundance, were used to determine the optimal feeding habitat zone of the southern Indian Ocean (SIO) albacore using a habitat suitability model applied to the 2000–2016 Taiwanese longline fishery data. The analysis showed a stronger correlation between the 2-month lag SSC and standardized catch per unit effort (CPUE) than 0-, 1-, 3-, and 4-month lag SSC. SST also exhibited a stronger correlation with standardized CPUE. Therefore, SST and SSC_2 were selected as final variables for model construction. An arithmetic mean model with SST and SSC_2 was deemed suitable to predict the albacore feeding habitat zone in the SIO. The preferred ranges of SSC_2 and SST for the feeding habitat of immature albacore were 0.07–0.09 mgm−3 and 16.5–18.5 °C, respectively, and mainly centralized at 17.5 °C SST and 0.08 mgm−3 SSC_2. The selected habitat suitability index model displayed a high correlation (R2 = 0.8276) with standardized CPUE. Overall, temperature and ocean chlorophyll were found to be essential for albacore habitat formation in the SIO, consistent with previous studies. The results of this study can contribute to ecosystem-based fisheries management in the SIO by providing insights into the habitat preference of immature albacore tuna in the SIO.

Decision strategies in fisheries management are often directed by the geographic distribution and habitat preferences of target species. This study used remote sensing data to identify the optimal feeding habitat of albacore tuna in the Southern Atlantic Ocean (SAO) using an empirical habitat suitability model applying longline fisheries data during 2009–2015. An arithmetic mean model with sea surface temperature (SST) and sea surface chlorophyll-a concentration (SSC) was determined to be suitable for defining the albacore habitat in the SAO. The optimal ranges of SST and SSC for the habitat were approximately 16.5 °C–19.5 °C and 0.11–0.33 mg/m3, respectively. The study revealed a considerable positive trend between the suitable habitat area and standardized catch per unit effort (r = 0.97; p < 0.05); due to the west-to-east and northward development of the suitable habitat, albacore schools moved to the northeast of the SAO, thus increasing catch probability in April to August in that region. Overall, the frontal structure of SST and SSC plays an essential role in the formation of potential albacore habitats in the SAO. Our findings could contribute to the establishment of regional ecosystem-based fisheries management in the SAO.

The location, effort, number of captures, and time of fishing were all used in this study to assess the geographic distribution of Parastromateus niger in the Taiwan Strait. Other species distribution models performed worse than generalized linear models (GLMs) based on six oceanographic parameters. The sea surface temperature (SST) was between 26.5 °C and 29.5 °C, the sea surface chlorophyll (SSC) level was between 0.3–0.44 mg/m3, the sea surface salinity (SSS) was between 33.4 °C and 34.4 °C, the mixed layer depth was between 10 °C and 14 °C, the sea surface height was between 0.57 °C and 0.77 °C, and the eddy kinetic energy (EKE) was between 0.603 °C. According to the statistical findings, SST is merely a small effect compared to SSS, SSC level, and EKE in terms of impacting species distribution. By combining four effective single-algorithm models with no obvious bias, an ensemble habitat model was created. The ranges of 117°E–119°E and 22°N–24°N have the highest annual distributions of S.CPUE and nominal CPUE.

In this study, we conducted long-term temporal and spatial observations of monthly, interannual, and decadal sea surface temperature (SST) variation in the Gulf of Mannar (GoM) for the period from 1870 to 2018. We obtained climatological data from the Met Office Hadley Centre, UK. The monthly time series revealed that April and August were the warmest and coolest months of the year, respectively. The mean SSTs for April and August were 29.85 ± 0.44 °C and 27.15 ± 0.49 °C, respectively. The mean annual highest and lowest SSTs were observed in 2015 and 1890 with SSTs of 28.93 ± 0.31 °C and 27.45 ± 0.31°C, respectively, and the annual time series revealed a warming SST trend of 0.004 °C. Decadal time series also revealed a warming SST trend of 0.04 °C, with the highest and lowest mean decadal SSTs being 28.56 ± 0.21 °C in 2010–2018 and 27.78 ± 0.25 °C in 1890–1889, respectively. Throughout the study period, the spatial distribution of climate trends over decades across the GoM revealed a strong spatial gradient, and the region between 6–8° N and 77–78° E was warmer than all other regions of the GoM.

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This study employed an arithmetic mean model with sea surface temperature and chlorophyll data (2-month lag) to determine the projected impact of climate change on the immature albacore tuna habitat in the Indian Ocean. Albacore tuna fishing data from Taiwanese longline fishery from 2000 to 2016 were used. Standardization of the nominal catch per unit effort data was performed to prevent bias and overestimation resulting from various temporal and spatial factors. In the Indian Ocean, potential immature albacore habitats exhibited significant habitat suitability index (HSI) changes in response to future climate change levels. As the water stratifies in a projected warm climate, low HSI areas were enlarged, and potential immature albacore habitats exhibited a net southward shift. Although the CMIP5 climate model sea surface temperature projections generated different HSI patterns for immature albacore, our results from the ensemble median immature albacore habitat forecasts provided information useful for assessing risks and adaptation strategy options for albacore fishery resources under climate change. The trends of the potential immature albacore habitat distribution could also be cautiously used to inform resource stakeholders’ decisions.