DOI: 10.5061/dryad.f78r6
title: Data from: Habitat-based species distribution modelling of the Hawaiian deepwater snapper-grouper complex

description: 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.
description: Predicted probability of
 occurrence of Etelis coruscans in the main Hawaiian
 IslandsThe
 “Etelis_coruscans.zip” file contains two files: an asci raster grid file
 of predicted probability of occurrence of Etelis coruscans as a proportion
 (0.0-1.0) across the main Hawaiian Islands between 50 and 400 m depth
 (“Etelis_coruscans.txt”) and an associated projection file
 (Etelis_coruscans.prj). The asci file includes a six-line header section
 with data in 10315 columns (“ncols”) and 6394 rows (“nrows”) georegistered
 to 326589.18933012 and 2083866.5021671 at the lower left corner of the
 grid (“xllcorner”, “yllcorner”). Grid cell size is 60 m and no data values
 are -9999. Fish presence/absence data were collected from BRUV (BotCam)
 surveys collected between 2007-2015 and was modelled using boosted
 regression trees with various benthic habitat variables including depth,
 slope, rugosity, and bathymetric position index. The optimal model was
 used to predict Etelis coruscans probability of occurrence across the
 entire spatial domain. Further details on methodology and results are
 contained in Oyafuso et al. (2017) Habitat-based species distribution
 modelling of the Hawaiian deepwater snapper-grouper complex. Fisheries
 Research, 195:19-27.
 https://doi.org/10.1016/j.fishres.2017.06.011Etelis_coruscans.zipPredicted probability of occurrence of Etelis carbunculus in the main Hawaiian IslandsThe “Etelis_carbunculus.zip” file contains two files: an asci raster grid file of predicted probability of occurrence of Etelis carbunculus as a proportion (0.0-1.0) across the main Hawaiian Islands between 50 and 400 m depth (“Etelis_carbunculus.txt”) and an associated projection file (Etelis_carbunculus.prj). The asci file includes a six-line header section with data in 10315 columns (“ncols”) and 6394 rows (“nrows”) georegistered to 326589.18933012 and 2083866.5021671 at the lower left corner of the grid (“xllcorner”, “yllcorner”). Grid cell size is 60 m and no data values are -9999. Fish presence/absence data were collected from BRUV (BotCam) surveys collected between 2007-2015 and was modelled using boosted regression trees with various benthic habitat variables including depth, slope, rugosity, and bathymetric position index. The optimal model was used to predict Etelis carbunculus probability of occurrence across the entire spatial domain. Further details on methodology and results are contained in Oyafuso et al. (2017) Habitat-based species distribution modelling of the Hawaiian deepwater snapper-grouper complex. Fisheries Research, 195:19-27. https://doi.org/10.1016/j.fishres.2017.06.011Etelis_carbunculus.zipPredicted probability of occurrence of Aphareus rutilans in the main Hawaiian IslandsThe “Aphareus_rutilans.zip” file contains two files: an asci raster grid file of predicted probability of occurrence of Aphareus rutilans as a proportion (0.0-1.0) across the main Hawaiian Islands between 50 and 400 m depth (“Aphareus_rutilans.txt”) and an associated projection file (Aphareus_rutilans.prj). The asci file includes a six-line header section with data in 10315 columns (“ncols”) and 6394 rows (“nrows”) georegistered to 326589.18933012 and 2083866.5021671 at the lower left corner of the grid (“xllcorner”, “yllcorner”). Grid cell size is 60 m and no data values are -9999. Fish presence/absence data were collected from BRUV (BotCam) surveys collected between 2007-2015 and was modelled using boosted regression trees with various benthic habitat variables including depth, slope, rugosity, and bathymetric position index. The optimal model was used to predict Aphareus rutilans probability of occurrence across the entire spatial domain. Further details on methodology and results are contained in Oyafuso et al. (2017) Habitat-based species distribution modelling of the Hawaiian deepwater snapper-grouper complex. Fisheries Research, 195:19-27. https://doi.org/10.1016/j.fishres.2017.06.011Aphareus_rutilans.zipPredicted probability of occurrence of Hyporthodus quernus in the main Hawaiian IslandsThe “Hyporthodus_quernus.zip” file contains two files: an asci raster grid file of predicted probability of occurrence of Hyporthodus quernus as a proportion (0.0-1.0) across the main Hawaiian Islands between 50 and 400 m depth (“Hyporthodus_quernus.txt”) and an associated projection file (Hyporthodus_quernus.prj). The asci file includes a six-line header section with data in 10315 columns (“ncols”) and 6394 rows (“nrows”) georegistered to 326589.18933012 and 2083866.5021671 at the lower left corner of the grid (“xllcorner”, “yllcorner”). Grid cell size is 60 m and no data values are -9999. Fish presence/absence data were collected from BRUV (BotCam) surveys collected between 2007-2015 and was modelled using boosted regression trees with various benthic habitat variables including depth, slope, rugosity, and bathymetric position index. The optimal model was used to predict Hyporthodus quernus probability of occurrence across the entire spatial domain. Further details on methodology and results are contained in Oyafuso et al. (2017) Habitat-based species distribution modelling of the Hawaiian deepwater snapper-grouper complex. Fisheries Research, 195:19-27. https://doi.org/10.1016/j.fishres.2017.06.011Hyporthodus_quernus.zipPredicted probability of occurrence of Pristipomoides filamentosus in the main Hawaiian IslandsThe “Pristipomoides_filamentosus.zip” file contains two files: an asci raster grid file of predicted probability of occurrence of Pristipomoides filamentosus as a proportion (0.0-1.0) across the main Hawaiian Islands between 50 and 400 m depth (“Pristipomoides_filamentosus.txt”) and an associated projection file (Pristipomoides_filamentosus.prj). The asci file includes a six-line header section with data in 10315 columns (“ncols”) and 6394 rows (“nrows”) georegistered to 326589.18933012 and 2083866.5021671 at the lower left corner of the grid (“xllcorner”, “yllcorner”). Grid cell size is 60 m and no data values are -9999. Fish presence/absence data were collected from BRUV (BotCam) surveys collected between 2007-2015 and was modelled using boosted regression trees with various benthic habitat variables including depth, slope, rugosity, and bathymetric position index. The optimal model was used to predict Pristipomoides filamentosus probability of occurrence across the entire spatial domain. Further details on methodology and results are contained in Oyafuso et al. (2017) Habitat-based species distribution modelling of the Hawaiian deepwater snapper-grouper complex. Fisheries Research, 195:19-27. https://doi.org/10.1016/j.fishres.2017.06.011Pristipomoides_filamentosus.zipPredicted probability of occurrence of Pristipomoides sieboldii in the main Hawaiian IslandsThe “Pristipomoides_sieboldii.zip” file contains two files: an asci raster grid file of predicted probability of occurrence of Pristipomoides sieboldii as a proportion (0.0-1.0) across the main Hawaiian Islands between 50 and 400 m depth (“Pristipomoides_sieboldii.txt”) and an associated projection file (Pristipomoides_sieboldii.prj). The asci file includes a six-line header section with data in 10315 columns (“ncols”) and 6394 rows (“nrows”) georegistered to 326589.18933012 and 2083866.5021671 at the lower left corner of the grid (“xllcorner”, “yllcorner”). Grid cell size is 60 m and no data values are -9999. Fish presence/absence data were collected from BRUV (BotCam) surveys collected between 2007-2015 and was modelled using boosted regression trees with various benthic habitat variables including depth, slope, rugosity, and bathymetric position index. The optimal model was used to predict Pristipomoides sieboldii probability of occurrence across the entire spatial domain. Further details on methodology and results are contained in Oyafuso et al. (2017) Habitat-based species distribution modelling of the Hawaiian deepwater snapper-grouper complex. Fisheries Research, 195:19-27. https://doi.org/10.1016/j.fishres.2017.06.011Pristipomoides_sieboldii.zipPredicted probability of occurrence of Pristipomoides zonatus in the main Hawaiian IslandsThe “Pristipomoides_zonatus.zip” file contains two files: an asci raster grid file of predicted probability of occurrence of Pristipomoides zonatus as a proportion (0.0-1.0) across the main Hawaiian Islands between 50 and 400 m depth (“Pristipomoides_zonatus.txt”) and an associated projection file (Pristipomoides_zonatus.prj). The asci file includes a six-line header section with data in 10315 columns (“ncols”) and 6394 rows (“nrows”) georegistered to 326589.18933012 and 2083866.5021671 at the lower left corner of the grid (“xllcorner”, “yllcorner”). Grid cell size is 60 m and no data values are -9999. Fish presence/absence data were collected from BRUV (BotCam) surveys collected between 2007-2015 and was modelled using boosted regression trees with various benthic habitat variables including depth, slope, rugosity, and bathymetric position index. The optimal model was used to predict Pristipomoides zonatus probability of occurrence across the entire spatial domain. Further details on methodology and results are contained in Oyafuso et al. (2017) Habitat-based species distribution modelling of the Hawaiian deepwater snapper-grouper complex. Fisheries Research, 195:19-27. https://doi.org/10.1016/j.fishres.2017.06.011Pristipomoides_zonatus.zip