Species Distribution Models of Tropical Deep-Sea Snappers

摘要: Deep-sea fisheries provide an important source of protein to Pacific Island countries and territories that are highly dependent on fish for food security. However, spatial management these deep-sea habitats is hindered by insufficient data. We developed species distribution models using spatially limited presence data the main harvested in Western Central Ocean. used bathymetric water temperature develop presence-only commercially exploited snappers Etelis Cuvier 1828, Pristipomoides Valenciennes 1830, Aphareus 1830. evaluated performance four different algorithms (CTA, GLM, MARS, MAXENT) within BIOMOD framework obtain ensemble predicted distributions. projected predictions across Ocean produce maps potential snapper distributions 32 territories. Depth was consistently best predictor all groups models. Bathymetric slope poorest predictor. Temperature at depth a good GLM only. Model precision highest MAXENT CTA. There were strong regional patterns suitable habitat, with largest areas habitat (> 35% Exclusive Economic Zone) seven South (Fiji, Matthew & Hunter, Nauru, New Caledonia, Tonga, Vanuatu Wallis Futuna). Predicted also varied among species, proportion lowest Etelis. Despite paucity, relationship between their environments sufficiently predict large area Our results therefore baseline designing monitoring programs balance resource exploitation conservation planning, predicting future snappers.