Description: This group of layers show the presence (1) and absence (0) of 22 DSCS taxa in PMNM. These records were obtained from the NOAA’s Deep-Sea Coral Research and Technology Program (DSCRTP) National database and from University of Hawaii’s Hawaii Undersea Research Laboratory (HURL). They were formatted and binned into 360x360 m cells. Local experts then selected 22 DSCS taxonomic groups that were representative of a range of depths, habitats, ecological significance, as well as economic and cultural importance in PMNM.
Copyright Text: NOAA DSCRTP: https://www.ncei.noaa.gov/maps/deep-sea-corals/mapSites.htm and UH HURL: https://www.soest.hawaii.edu/HURL/
Description: This group of layers show the predicted occurrence and associated precision for 22 DSCS taxa in PMNM. Three modeling techniques, including Boosted Regression Trees (BRT), Generalized Additive Models (GAM) and Maximum Entropy (MaxEnt), were used to predict the spatial distribution of these 22 taxa. Non-parametric bootstrapping was used to calculate a mean probability of occurrence and estimate precision for each taxonomic group and modelling technique. The BRT, GAM and MaxEnt predictions were then integrated to produce single, ensemble mean predictions and precision surfaces. These ensemble predictions and precision surfaces were qualitatively reviewed by local deep-sea coral and sponge experts for completeness and accuracy. For more information see, https://coastalscience.noaa.gov/project/predicting-and-characterizing-deep-sea-coral-habitats-within-the-papahanaumokuakea-marine-national-monument/
Description: This layer shows the predicted probability of occurrence (0-1) for Acanella in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Acanella prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Acanthogorgia in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Acanthogorgia prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Anthomastus in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Anthomastus prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Bathypathes in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Bathypathes prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Bolosoma in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Bolosoma prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Candidella in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Candidella prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Caulophacus in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Caulophacus prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Chrysogorgia in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Chrysogorgia prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Name: Enallopsammia rostrata - Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This layer shows the predicted probability of occurrence (0-1) for Enallopsammia rostrata in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Name: Enallopsammia rostrata - Coefficent of Variation
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This layer shows the precision of the Enallopsammia rostrata prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Hemicorallium in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Hemicorallium prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Iridogorgia in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Iridogorgia prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Name: Isidella trichotoma - Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This layer shows the predicted probability of occurrence (0-1) for Isidella trichotoma in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Name: Isidella trichotoma - Coefficent of Variation
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This layer shows the precision of the Isidella trichotoma prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Name: Kulamanamana haumeaae - Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This layer shows the predicted probability of occurrence (0-1) for Kulamanamana haumeaae in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Name: Kulamanamana haumeaae - Coefficent of Variation
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This layer shows the precision of the Kulamanamana haumeaae prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Metallogorgia in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Metallogorgia prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Narella in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Narella prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Paragorgia in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Paragorgia prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Pleurocorallium in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Pleurocorallium prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Poliopogon in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Poliopogon prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Name: Rhodaniridogorgia - Probability of Occurrence
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This layer shows the predicted probability of occurrence (0-1) for Rhodaniridogorgia in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Rhodaniridogorgia prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Stauropathes in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Stauropathes prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Tretopleura in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Tretopleura prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the predicted probability of occurrence (0-1) for Walteria in PMNM.
These values range from 0 to 1 with higher numbers indicating taxa are more likely to be present. They are an ensemble, representing the average predicted value for all boostraps and modeling techniques combined.
Description: This layer shows the precision of the Walteria prediction.
Precision is reported as the coefficient of variation (CV). CV is the ratio of the standard deviation to the mean. Lower CV values indicate higher precision and less uncertainty. These values are an ensemble, representing the precision for all boostraps and modeling techniques combined.
Description: This layer shows the number of taxa (out of the 22 taxa selected) observed within 360x360 m cells inside PMNM.
Relative taxonomic richness values range from 0 (where no taxa were observed) to 18 (where 18/22 taxa were observed). It was developed by summarizing the deep-sea coral and sponge presences and absences obtained from the NOAA’s Deep-Sea Coral Research and Technology Program (DSCRTP) National database (NOAA DSCRTP) and the University of Hawaii’s Hawaii Undersea Research Laboratory (HURL) in PMNM.
Copyright Text: NOAA DSCRTP: https://www.ncei.noaa.gov/maps/deep-sea-corals/mapSites.htm and UH HURL: https://www.soest.hawaii.edu/HURL/
Description: This layer shows predicted, relative taxonomic richness in PMNM.
Relative taxonomic richness was predicted by summing the ensemble mean probability of occurrence predictions for all 22 DSCS taxa together. Values range from 0 (where all taxa are absent) to 15 (where up to 15 taxa are likely to occur).
Description: This layer shows seafloor depths (in meters) within PMNM.
It was created by combining several readily-available depth surfaces in PMNM. For more information, please see: https://coastalscience.noaa.gov/project/predicting-and-characterizing-deep-sea-coral-habitats-within-the-papahanaumokuakea-marine-national-monument/