Multisatellite-Based Feeding Habitat Suitability Modeling of Albacore Tuna in the Southern Atlantic Ocean

Abstract

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.

Keywords

• albacore tuna
• habitat suitability index
• longline fishery
• fisheries management
• multisatellite remote sensing data