Data from: Habitat-based species distribution modelling of the Hawaiian deepwater snapper-grouper complex

Deepwater snappers and groupers are valuable components of many
subtropical and tropical fisheries globally and understanding the habitat
associations of these species is important for spatial fisheries
management. Habitat-based species distribution models were developed for
the deepwater snapper-grouper complex in the main Hawaiian Islands (MHI).
Six eteline snappers (Pristipomoides spp., Aphareus rutilans, and Etelis
spp.) and one endemic grouper (Hyporthodus quernus) comprise the species
complex known as the Hawaiian Deep Seven Bottomfishes. Species occurrence
was recorded using baited remote underwater video stations deployed
between 30 and 365 m (n = 2381) and was modeled with 12 geomorphological
covariates using GLMs, GAMs, and BRTs. Depth was the most important
predictor across species, along with ridge-like features, rugosity, and
slope. In particular, ridge-like features were important habitat
predictors for E. coruscans and P. filamentosus. Bottom hardness was an
important predictor especially for the two Etelis species. Along with
depth, rugosity and slope were the most important habitat predictors for
A. rutilans and P. zonatus, respectively. Models built using GAMs and BRTs
generally had the highest predictive performance. Finally, using the BRT
model output, we created species-specific distribution maps and
demonstrated that areas with high predicted probabilities of occurrence
were positively related to fishery catch rates.