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

Oyafuso ZS, Drazen JC, Moore CH, Franklin EC

Date Published: August 3, 2017

DOI: http://dx.doi.org/10.5061/dryad.f78r6

 

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Title Predicted probability of occurrence of Etelis coruscans in the main Hawaiian Islands
Downloaded 1 time
Description The “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.2017.06.011
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Title Predicted probability of occurrence of Etelis carbunculus in the main Hawaiian Islands
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Description The “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.2017.06.011
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Title Predicted probability of occurrence of Aphareus rutilans in the main Hawaiian Islands
Downloaded 1 time
Description The “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.2017.06.011
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Title Predicted probability of occurrence of Hyporthodus quernus in the main Hawaiian Islands
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Description The “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.2017.06.011
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At the request of the author, this item is embargoed until the associated publication appears.
Title Predicted probability of occurrence of Pristipomoides filamentosus in the main Hawaiian Islands
Downloaded 1 time
Description The “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.2017.06.011
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At the request of the author, this item is embargoed until the associated publication appears.
Title Predicted probability of occurrence of Pristipomoides sieboldii in the main Hawaiian Islands
Downloaded 1 time
Description The “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.2017.06.011
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At the request of the author, this item is embargoed until the associated publication appears.
Title Predicted probability of occurrence of Pristipomoides zonatus in the main Hawaiian Islands
Downloaded 1 time
Description The “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.2017.06.011
Details View File Details
At the request of the author, this item is embargoed until the associated publication appears.

When using this data, please cite the original publication:

Oyafuso ZS, Drazen JC, Moore CH, Franklin EC (2017) Habitat-based species distribution modelling of the Hawaiian deepwater snapper-grouper complex. Fisheries Research 195: 19-27. http://dx.doi.org/10.1016/j.fishres.2017.06.011

Additionally, please cite the Dryad data package:

Oyafuso ZS, Drazen JC, Moore CH, Franklin EC (2017) Data from: Habitat-based species distribution modelling of the Hawaiian deepwater snapper-grouper complex. Dryad Digital Repository. http://dx.doi.org/10.5061/dryad.f78r6
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