Abstract

Albacore tuna (Thunnus alalunga) is one of the important commercial species of the longline fishery in the southern Indian Ocean (SIO). The satellite-based oceanographic data of net primary production (NPP), sea-surface temperature (SST), sea surface salinity (SSS), mixed layer depth (MLD), sea-surface height (SSH) and eddy kinetic energy (EKE), were used to evaluate the effects of oceanographic conditions on the hotspot habitat for Albacore tuna and to explore the spatial variability of these features in the SIO using the generalized additive model (GAM) and maximum entropy models (MaxEnt). The results from the Maxent and GAM revealed its potential for predicting the spatial distribution of Albacore tuna and highlight the use of multispectral satellite images for describing habitats. In these two models, the spatial habitat patterns were explained predominantly by SST (17–21°C) and indicated that SST is the most influential factor in the geographic distribution of Albacore tuna. Hoptspot habitat formation were also possibly related to the MLD (60–120 m), NPP (250–450 mg C/m2d1) and SSH (0.4–0.6 m).

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.