Habitat Suitability Modeling for the Feeding Ground of Immature Albacore in the Southern Indian Ocean Using Satellite-Derived Sea Surface Temperature and Chlorophyll Data

Abstract

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.

Variability in the Spatiotemporal Distribution Patterns of Greater Amberjack in Response to Environmental Factors in the Taiwan Strait Using Remote Sensing Data

“…However, SST is one of the important variables directly associated with species and their prey's physiological requirements [25]. The physiological constraints of species are a key driver of their spatiotemporal distributions, and temperature preferences for tuna [29,31,57,58] and marlin [59] have been established using spatiotemporal distribution models. S. dumerili distribution was widely distributed and high catch rates were predicted in the northern region of TS in summer; however, the high catch rate prediction extended toward the ECS (Figures 2 and 8b).…”

“…Environmental factors such as sea surface temperature (SST), sea surface salinity (SSS), sea surface chlorophyll-a concentration (Chl-a), sea surface height (SSH), mixed layer depth (MLD), and eddy kinetic energy (EKE) have been reported to have a considerable impact on the distribution patterns of pelagic species [22][23][24][25][26][27][28][29][30][31], but few studies have focused on these factors with S. dumerili in the TS. In addition, an assessment of the reasons for fish catch reductions and the environmental factors influencing the distribution pattern of S. dumerili with preferred habitats in response to seasonal variations is still lacking.…”

Projected climate change impact on immature albacore tuna habitats in the Indian Ocean by using sea surface temperature and chlorophyll data: Ensemble forecasting

“…Therefore, standardizing the N. CPUE has become an essential step when studying sheries management (Kim et al 2015). In our previous study, we described the habitat preferences of immature albacore tuna and its critical role (Mondal et al 2021). Extending that work, we identi ed the projected impact of climate change on the immature albacore tuna (average weight with less than 14 kg) in the present study.…”

“…Global climate change is expected to affect the properties of seawater (Gruber 2011), considerably altering the primary production of the oceans (Steinacher et al 2010). These changes directly affect the spatial distribution of particular species and indirectly affect the ocean's productivity, drastically modifying marine ecosystems (Brander 2007;Mondal et al 2021). Hence, to achieve sustainable sheries management, stakeholders must identify the dominant trends that drive changes in the spatial distribution and habitat preference of sh in relation to climate change (Brander 2010; Sumaila et al 2011), because habitat is a key feature of any ecosystem (Sumaila et al 2011).…”

“…Small sh and invertebrate graze near phytoplankton, and albacore is attracted by these secondary producers (Bakun 1997;Olson et al 1994;Polovina et al 2001). In our preliminary study (Mondal et al 2021) of immature albacore habitat modelling, we used only sea surface temperature (SST) and sea surface chlorophyll with 2 months lag (SSC2), which was focused. An AMM derived model with SST, and SSC2 was used to obtain a preliminary idea about the immature albacore distribution pattern in the Indian Ocean.…”