Predicted Likelihood of Suitable Habitat for Alcyonacea in the U.S. Northeast Atlantic and Mid-Atlantic (Thresholded Categories)

Metadata:

• Identification_Information
• Data_Quality_Information
• Spatial_Data_Organization_Information
• Spatial_Reference_Information
• Entity_and_Attribute_Information
• Distribution_Information
• Metadata_Reference_Information

Identification_Information:

Citation:

Citation_Information:

Originator:

Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Centers for Coastal Ocean Science (NCCOS), Center for Coastal Monitoring and Assessment (CCMA), Biogeography Branch

Publication_Date: 20130809

Title:

Predicted Likelihood of Suitable Habitat for Alcyonacea in the U.S. Northeast Atlantic and Mid-Atlantic (Thresholded Categories)

Geospatial_Data_Presentation_Form: vector digital data

Online_Linkage: <http://coastalscience.noaa.gov/projects/detail?key=35>

Description:

Abstract:

This dataset depicts the predicted likelihood of suitable habitat for deep-sea corals in the order Alcyonacea in the U.S. Northeast Atlantic and Mid-Atlantic as coral habitat suitability likelihood classes derived from a categorical reclassification of the logistic output of a maximum entropy (MaxEnt) model derived from coral presence locations and environmental predictor variables at 370.65m resolution. The reclassification used calibrated thresholds based on different hypothetical scenarios of the false positive:false negative cost ratio, that is, the relative cost of false positive versus false negative errors. Thresholds were chosen to minimize error rates when tested on data left out of the model-fitting process (cross-validation datasets), after weighting false positive and false negative error rates by the indicatd cost ratio. The thresholds were then used to create coral habitat suitability likelihood classes depicting several categories of predicted likelihood of habitat suitability. Coral habitat suitability likelihood classes can be qualitatively described as follows: Low Likelihood (Category 0, FP:FN cost ratio < 1:1, Medium-Low Likelihood (Category 1, FP:FN cost ratio > 1:1 but less than 2:1), Medium Likelihood (Category 2, FP:FN cost ratio > 2:1 but less than 5:1), High Likelihood (Category 5, FP:FN cost ratio > 5:1 but less than 10:1), Very High Likelihood (Category 10, FP:FN cost ratio > 10:1). MaxEnt is a type of statistical model. The outputs depicted here represent statistical model predictions, and as such may vary greatly in their accuracy, and may or may not reflect actual conditions at any given location. This information is provided as-is for research and evaluation purposes.

Purpose:

Deep-sea corals are of particular conservation concern due to their slow growth rates and vulnerability to disturbance. Predictive modeling of deep-sea coral habitat can aid conservation planning, inform management of offshore activities affecting the seafloor, and guide exploration. Modeling can also lend insights into the environmental factors driving the distribution of deep-sea corals, helping to build our understanding of how these unique ecosystems function. This downloadable data package is an experimental product made available to the research community and interested individuals and organizations for research and evaluation purposes. The National Oceanic and Atmospheric Administration assumes no responsibility for the use of these data.

Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 20130809

Currentness_Reference: publication date

Status:

Progress: Complete

Maintenance_and_Update_Frequency: None planned

Spatial_Domain:

Bounding_Coordinates:

West_Bounding_Coordinate: -76.747533

East_Bounding_Coordinate: -62.765207

North_Bounding_Coordinate: 44.910660

South_Bounding_Coordinate: 35.550919

Keywords:

Theme:

Theme_Keyword_Thesaurus: None

Theme_Keyword: deep-sea corals

Theme_Keyword: species distribution

Theme_Keyword: habitat suitability

Theme_Keyword: predictive models

Theme_Keyword: marine spatial planning

Theme:

Theme_Keyword_Thesaurus: ISO 19115 Topic Category

Theme_Keyword: environment

Theme_Keyword: oceans

Theme:

Theme_Keyword_Thesaurus: NOS Data Explorer Topic Category

Theme_Keyword: Environmental Monitoring

Place:

Place_Keyword_Thesaurus: None

Place_Keyword: U.S. Northeast Atlantic

Place_Keyword: U.S. Mid-Atlantic

Access_Constraints: None

Use_Constraints:

Please acknowledge "NOAA/NOS National Centers for Coastal Ocean Science (NCCOS)" when using these data in a report or peer reviewed publication, and where possible use the following citation: Kinlan BP, Poti M, Drohan A, Packer DB, Nizinski M, Dorfman D, Caldow C. 2013. Digital data: Predictive models of deep-sea coral habitat suitability in the U.S. Northeast Atlantic and Mid-Atlantic regions. Downloadable digital data package. Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Centers for Coastal Ocean Science (NCCOS), Center for Coastal Monitoring and Assessment (CCMA), Biogeography Branch. Released August 2013. Available at: <http://coastalscience.noaa.gov/projects/detail?key=35>. Knowledge of how this dataset has been of use and which organizations are utilizing it is of great benefit for ensuring information products like this continue to meet the needs of the management and research communities. Therefore it is requested, but not mandatory, that any user of this data supply this information to the principal investigator, Brian Kinlan (Brian.Kinlan@noaa.gov). This downloadable data package is an experimental product made available to the research community and interested individuals and organizations for research and evaluation purposes. The National Oceanic and Atmospheric Administration assumes no responsibility for the use of these data.

Point_of_Contact:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization:

Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Centers for Coastal Ocean Science (NCCOS), Center for Coastal Monitoring and Assessment (CCMA), Biogeography Branch

Contact_Address:

Address_Type: mailing and physical address

Address: 1305 East-West Highway, SSMC4, N/SCI-1

City: Silver Spring

State_or_Province: MD

Postal_Code: 20910-3278

Country: United States

Contact_Voice_Telephone: 301-713-3028

Data_Set_Credit:

Brian Kinlan, Matthew Poti, Dan Dorfman, Chris Caldow (NOAA/NOS/NCCOS/CCMA Biogeography Branch); Amy Drohan, Dave Packer, Martha Nizinski (NOAA/NMFS Northeast Fisheries Science Center)

Data_Quality_Information:

Attribute_Accuracy:

Attribute_Accuracy_Report:

The outputs depicted here represent statistical model predictions, and as such may vary greatly in their accuracy, and may or may not reflect actual conditions at any given location. This information is provided as-is for research and evaluation purposes.

Logical_Consistency_Report:

These data are believed to be logically consistent. Users should independently analyze the dataset according to their own needs and standards to determine data usability.

Completeness_Report:

For more information on selection criteria, generalizations, definitions used, and other rules used to derive the dataset, please see: Kinlan BP, Poti M, Drohan A, Packer DB, Nizinski M. 2012. Habitat Suitability Modeling for Deep-Sea Corals in the Northeast and Mid-Atlantic Regions (poster presentation). Proceedings of the 2nd National Habitat Assessment Workshop: Fisheries Science to Support NOAA’s Habitat Blueprint, Seattle, WA, USA, September 5-7, 2012. Available from NOAA Fisheries Office of Science and Technology or by emailing author: Brian.Kinlan@NOAA.gov.

Lineage:

Source_Information:

Source_Citation:

Citation_Information:

Originator:

Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), Deep-Sea Coral Research and Technology Program (DSCRTP)

Publication_Date: Unpublished Material

Title: NOAA National Deep-Sea Coral Geodatabase Records

Geospatial_Data_Presentation_Form: spreadsheet

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 1873

Ending_Date: 2002

Source_Currentness_Reference: ground condition

Source_Citation_Abbreviation: DSCDB

Source_Contribution:

Deep-sea coral presence records in the U.S. Northeast Atlantic and Mid-Atlantic were acquired from the NOAA National Deep-Sea Coral Geodatabase (updated as of 20111202). These records were used in the spatial predictive models of deep-sea coral habitat suitability.

Source_Information:

Source_Citation:

Citation_Information:

Originator:

Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data, and Information Service (NESDIS), National Geophysical Data Center (NGDC)

Publication_Date: 1999

Title: U.S. Coastal Relief Model - Northeast Atlantic

Geospatial_Data_Presentation_Form: raster digital data

Online_Linkage: <http://www.ngdc.noaa.gov/mgg/coastal/crm.html>

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 1999

Source_Currentness_Reference: publication date

Source_Citation_Abbreviation: NOAA NE CRM

Source_Contribution:

Gridded bathymetry data (3 arc-second) from the U.S. Coastal Relief Model (CRM) were downloaded and projected to WGS 1984 UTM Zone 18N with bi-linear resampling to 92.6625m horizontal grid resolution. The projected bathymetry dataset was then used to create a 370.65m horizontal grid resolution bathymetry dataset and to derive a suite of additional terrain metric datasets at several spatial scales. The 370.65m horizontal grid resolution bathymetry dataset and the derived terrain metric datasets were used as potential environmental predictors in the spatial predictive models of deep-sea coral habitat suitability.

Source_Information:

Source_Citation:

Citation_Information:

Originator:

Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data, and Information Service (NESDIS), National Geophysical Data Center (NGDC)

Publication_Date: 1999

Title: U.S. Coastal Relief Model - Southeast Atlantic

Geospatial_Data_Presentation_Form: raster digital data

Online_Linkage: <http://www.ngdc.noaa.gov/mgg/coastal/crm.html>

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 1999

Source_Currentness_Reference: publication date

Source_Citation_Abbreviation: NOAA SE CRM

Source_Contribution:

Gridded bathymetry data (3 arc-second) from the U.S. Coastal Relief Model (CRM) were downloaded and projected to WGS 1984 UTM Zone 18N with bi-linear resampling to 92.6625m horizontal grid resolution. The projected bathymetry dataset was then used to create a 370.65m horizontal grid resolution bathymetry dataset and to derive a suite of additional terrain metric datasets at several spatial scales. The 370.65m horizontal grid resolution bathymetry dataset and the derived terrain metric datasets were used as potential environmental predictors in the spatial predictive models of deep-sea coral habitat suitability.

Source_Information:

Source_Citation:

Citation_Information:

Originator: United States Geological Survey (USGS)

Publication_Date: 2005

Title:

usSEABED Atlantic Coast Offshore Surficial Sediment Data Release, version 1.0

Geospatial_Data_Presentation_Form: vector digital data

Other_Citation_Details:

Data described in Reid, JM, Reid, JA, Jenkins, CJ, Hastings, ME, Williams, SJ, and Poppe, LJ. 2005. usSEABED: Atlantic coast offshore surficial sediment data release: U.S. Geological Survey Data Series 118, version 1.0.

Online_Linkage: <http://pubs.usgs.gov/ds/2005/118/htmldocs/data_cata.htm>

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 2005

Source_Currentness_Reference: publication date

Source_Citation_Abbreviation: usSEABED Atlantic

Source_Contribution:

The usSEABED Atlantic Coast Offshore Surficial Sediment Data Release, version 1.0 parsed and extracted databases contain seabed survey data that provide a variety of information about seafloor sediment characteristics. These seabed survey point data were filtered to extract surficial sediment data, which were then used to produce 370.65m horizontal grid resolution continuous gridded datasets for predicted surficial sediment mean grain size, percent mud, percent sand, and percent gravel using geostatistical methods. These derived datasets were used as potential environmental predictors in the spatial predictive models of deep-sea coral habitat suitability.

Source_Information:

Source_Citation:

Citation_Information:

Originator:

Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Marine Fisheries Service (NMFS), Northeast Fisheries Science Center (NEFSC)

Publication_Date: Unpublished Material

Title: NOAA NEFSC Bottom Temperature/Salinity Database Records

Geospatial_Data_Presentation_Form: spreadsheet

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 19710309

Ending_Date: 20091118

Source_Currentness_Reference: ground condition

Source_Citation_Abbreviation: NOAA NEFSC T/S

Source_Contribution:

Near-bottom temperature and salinity point data from NOAA Northeast Fisheries Science Center (NEFSC) trawl surveys were used to produce 370.65m horizontal grid resolution continuous gridded datasets for predicted long-term climatologies of bottom temperature and bottom salinity using geostatistical methods. These derived datasets were used as potential environmental predictors in the spatial predictive models of deep-sea coral habitat suitability.

Source_Information:

Source_Citation:

Citation_Information:

Originator:

Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Marine Fisheries Service (NMFS), Northeast Fisheries Science Center (NEFSC)

Publication_Date: Unpublished Material

Title:

Marine Resources Monitoring, Assessment, and Prediction (MARMAP) Bottom Temperature Data

Geospatial_Data_Presentation_Form: spreadsheet

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 19770213

Ending_Date: 19930513

Source_Currentness_Reference: ground condition

Source_Citation_Abbreviation: MARMAP

Source_Contribution:

Near-bottom temperature point data from Marine Resources Monitoring, Assessment, and Prediction (MARMAP) surveys were used to produce a 370.65m horizontal grid resolution continuous gridded dataset for a predicted long-term climatology of bottom temperature using geostatistical methods. This derived dataset was used as a potential environmental predictor in the spatial predictive models of deep-sea coral habitat suitability.

Source_Information:

Source_Citation:

Citation_Information:

Originator: Woods Hole Oceanographic Institute

Publication_Date: Unknown

Title:

Wood Hole Hydrographic Station Bottom Temperature and Bottom Salinity Data

Geospatial_Data_Presentation_Form: spreadsheet

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 19770213

Ending_Date: 19871210

Source_Currentness_Reference: ground condition

Source_Citation_Abbreviation: whHydro

Source_Contribution:

Near-bottom temperature and salinity data from Woods Hole Oceanographic Institute (WHOI) hydrographic station surveys were used to produce 370.65m horizontal grid resolution continuous gridded datasets for predicted long-term climatologies of bottom temperature and bottom salinity using geostatistical methods. These derived datasets were used as potential environmental predictors in the spatial predictive models of deep-sea coral habitat suitability.

Source_Information:

Source_Citation:

Citation_Information:

Originator:

Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data, and Information Service (NESDIS), National Oceanographic Data Center (NODC)

Publication_Date: 2009 (but including updates through 201112)

Title:

World Ocean Database 2009, online version, incorporating all monthly updates through 201112

Geospatial_Data_Presentation_Form: spreadsheet

Other_Citation_Details:

The World Ocean Database 2009 has been updated monthly every month since its release in 2009.

Online_Linkage: <http://www.nodc.noaa.gov/OC5/SELECT/dbsearch/dbsearch.html>

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 18640111

Ending_Date: 20090906

Source_Currentness_Reference: ground condition

Source_Citation_Abbreviation: WOD09

Source_Contribution:

Ocean Station Data (OSD) were downloaded from the World Ocean Database (WOD) using WOD select (<http://www.nodc.noaa.gov/OC5/SELECT/dbsearch/dbsearch.html>) on 2012024 (temperature), 20120224 (salinity), and 20120106 (dissolved oxygen). These data were filtered to extract near-bottom surveys, which were then used to produce 370.65m horizontal grid resolution continuous gridded datasets for predicted long-term climatologies of bottom salinity, bottom temperature, and bottom dissolved oxygen using geostatistical methods. These derived datasets were used as potential environmental predictors in the spatial predictive models of deep-sea coral habitat suitability.

Source_Information:

Source_Citation:

Citation_Information:

Originator:

Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Centers for Coastal Ocean Science (NCCOS), Center for Coastal Monitoring and Assessment (CCMA), Coastal Oceanographic Assessment and Trends Branch

Originator:

Department of Commerce (DOC), National Aeronautics and Space Administration (NASA), Goddard Space Flight Center (GSFC)

Publication_Date: Unknown

Title: SeaWiFS Surface Chlorophyll-a

Geospatial_Data_Presentation_Form: raster digital data

Online_Linkage: <http://oceancolor.gsfc.nasa.gov/SeaWiFS/>

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 1998

Ending_Date: 2006

Source_Currentness_Reference: ground condition

Source_Citation_Abbreviation: SeaWiFS Chl-a

Source_Contribution:

High-resolution (approx. 1.1km) monthly composite satellite data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS; <http://oceancolor.gsfc.nasa.gov/SeaWiFS/>) instrument on the SeaStar spacecraft, processed using standard NASA ocean biology group processing (OBGP) algorithms to produce estimates of sea surface chlorophyll-a concentration, were obtained from the NOAA Coastal Oceanographic Asssessment and Trends (COAST) Branch (NOAA/NOS/NCCOS/CCMA/COAST) and used to produce a 370.65m horizontal grid resolution dataset for mean annual sea surface chlorophyll-a concentration. This dataset was used as a potential environmental predictor in the spatial predictive models of deep-sea coral habitat suitability.

Source_Information:

Source_Citation:

Citation_Information:

Originator:

Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Centers for Coastal Ocean Science (NCCOS), Center for Coastal Monitoring and Assessment (CCMA), Coastal Oceanographic Assessment and Trends Branch

Originator:

Department of Commerce (DOC), National Aeronautics and Space Administration (NASA), Goddard Space Flight Center (GSFC)

Publication_Date: Unknown

Title: SeaWiFS Remote Sensing Reflectance at 670nm

Geospatial_Data_Presentation_Form: raster digital data

Online_Linkage: <http://oceancolor.gsfc.nasa.gov/SeaWiFS/>

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 1998

Ending_Date: 2006

Source_Currentness_Reference: ground condition

Source_Citation_Abbreviation: SeaWiFS Rrs670

Source_Contribution:

High-resolution (approx. 1.1km) monthly composite satellite data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS; <http://oceancolor.gsfc.nasa.gov/SeaWiFS/>) instrument on the SeaStar spacecraft, processed using standard NASA ocean biology group processing (OBGP) algorithms to produce estimates of water-leaving radiance at 670nm (a proxy for sea surface turbidity), were obtained from the NOAA Coastal Oceanographic Asssessment and Trends (COAST) Branch (NOAA/NOS/NCCOS/CCMA/COAST) and used to produce a 370.65m horizontal grid resolution dataset for mean annual sea surface turbidity. This dataset was used as a potential environmental predictor in the spatial predictive models of deep-sea coral habitat suitability.

Process_Step:

Process_Description:

Using the presence-only coral location data and a suite of environmental/oceanographic predictor variables, we built high-resolution regional predictive coral habitat suitability models. To extract the maximum amount of information possible from presence-only data, we used MaxEnt (version 3.3.3k, available at: <http://www.cs.princeton.edu/~schapire/maxent/>) and ENMTools software (version 1.3, available at: <http://enmtools.blogspot.com/>) to implement a stepwise model selection process. A combination of cross-validation area-under-curve (AUC) statistics and Akaike’s information criterion (AICc) were used to identify models that balanced predictive power with complexity. Model accuracy and relative importance of predictor variables were evaluated through bootstrap, cross-validation, and jackknife statistics. The logistic output from MaxEnt was reclassified into categories of predicted likelihood of habitat suitability using calibrated thresholds based on different hypothetical scenarios of the false positive:false negative cost ratio, that is, the relative cost of false positive versus false negative errors. Thresholds were chosen to minimize error rates when tested on data left out of the model-fitting process (cross-validation datasets), after weighting false positive and false negative error rates by the indicatd cost ratio. Thresholds corresponding to false positive:false negative cost ratios of 1:1, 2:1, 5:1, and 10:1 were calculated using the 'ROCR' package in the R statistical software (version 2.15, available at: <http://cran.us.r-project.org/>). The thresholds were then used to create coral habitat suitability likelihood classes ranging from 0 (low likelihood of suitable coral habitat; predicted false positive to false negative cost ratio < 1:1) to 10 (very high likelihood of suitable coral habitat; predicted false positive to false negative cost ratio > 10:1). For additional details of the modeling process, please see: Kinlan BP, Poti M, Drohan A, Packer DB, Nizinski M. 2012. Habitat Suitability Modeling for Deep-Sea Corals in the Northeast and Mid-Atlantic Regions (poster). Proceedings of the 2nd National Habitat Assessment Workshop: Fisheries Science to Support NOAA’s Habitat Blueprint, Seattle, WA, USA, September 5-7, 2012. Available from NOAA Fisheries Office of Science and Technology or by emailing author: Brian.Kinlan@NOAA.gov.

Process_Date: 20120501

Spatial_Data_Organization_Information:

Direct_Spatial_Reference_Method: Vector

Point_and_Vector_Object_Information:

SDTS_Terms_Description:

SDTS_Point_and_Vector_Object_Type: G-polygon

Point_and_Vector_Object_Count: 11597

Spatial_Reference_Information:

Horizontal_Coordinate_System_Definition:

Planar:

Grid_Coordinate_System:

Grid_Coordinate_System_Name: Universal Transverse Mercator

Universal_Transverse_Mercator:

UTM_Zone_Number: 18N

Transverse_Mercator:

Scale_Factor_at_Central_Meridian: 0.9996

Longitude_of_Central_Meridian: -75.0

Latitude_of_Projection_Origin: 0.0

False_Easting: 500000.0

False_Northing: 0.0

Planar_Coordinate_Information:

Planar_Coordinate_Encoding_Method: coordinate pair

Coordinate_Representation:

Abscissa_Resolution: 0.001

Ordinate_Resolution: 0.001

Planar_Distance_Units: meters

Geodetic_Model:

Horizontal_Datum_Name: WGS 1984

Ellipsoid_Name: WGS 1984

Semi-major_Axis: 6378137.0

Denominator_of_Flattening_Ratio: 298.257223563

Entity_and_Attribute_Information:

Detailed_Description:

Entity_Type:

Entity_Type_Label: ALCY

Entity_Type_Definition:

This dataset depicts the predicted likelihood of suitable coral habitat as coral habitat suitability likelihood classes derived from a categorical reclassification of the logistic transformation of the raw output of a maximum entropy (MaxEnt) model derived from coral presence locations and environmental predictor variables. The reclassification used calibrated thresholds based on different hypothetical scenarios of the false positive:false negative cost ratio, that is, the relative cost of false positive versus false negative errors. Thresholds were chosen to minimize error rates when tested on data left out of the model-fitting process (cross-validation datasets). after weighting false positive and false negative error rates by the indicated cost ratio. Thresholds corresponding to false positive:false negative cost ratios of 1:1, 2:1, 5:1, and 10:1 were calculated using the 'ROCR' package in the R statistical software (version 2.15). The thresholds were then used to create coral habitat suitability likelihood classes. Coral habitat suitability likelihood classes can be qualitatively described as follows: Low Likelihood (Category 0, FP:FN cost ratio < 1:1, Medium-Low Likelihood (Category 1, FP:FN cost ratio > 1:1 but less than 2:1), Medium Likelihood (Category 2, FP:FN cost ratio > 2:1 but less than 5:1), High Likelihood (Category 5, FP:FN cost ratio > 5:1 but less than 10:1), Very High Likelihood (Category 10, FP:FN cost ratio > 10:1).

Entity_Type_Definition_Source: NOAA/NOS/NCCOS/CCMA Biogeography Branch

Attribute:

Attribute_Label: FID

Attribute_Definition: Internal feature number.

Attribute_Definition_Source: ESRI

Attribute_Domain_Values:

Unrepresentable_Domain:

Sequential unique whole numbers that are automatically generated.

Attribute:

Attribute_Label: Shape

Attribute_Definition: Feature geometry.

Attribute_Definition_Source: ESRI

Attribute_Domain_Values:

Unrepresentable_Domain: Coordinates defining the features.

Attribute:

Attribute_Label: ID

Attribute_Definition:

Sequential unique whole numbers that are automatically generated.

Attribute_Definition_Source: ESRI

Attribute_Domain_Values:

Unrepresentable_Domain:

Sequential unique whole numbers that are automatically generated.

Attribute:

Attribute_Label: GRIDCODE

Attribute_Definition:

Values indicate the coral habitat suitability likelihood class for each polygon. Coral habitat suitability likelihood classes were derived from a categorical reclassification of the logistic transformation of the raw output of a maximum entropy (MaxEnt) model derived from coral presence locations and environmental predictor variables. Coral habitat suitability likelihood classes can be qualitatively described as follows: Low Likelihood (Category 0, FP:FN cost ratio < 1:1, Medium-Low Likelihood (Category 1, FP:FN cost ratio > 1:1 but less than 2:1), Medium Likelihood (Category 2, FP:FN cost ratio > 2:1 but less than 5:1), High Likelihood (Category 5, FP:FN cost ratio > 5:1 but less than 10:1), Very High Likelihood (Category 10, FP:FN cost ratio > 10:1).

Attribute_Definition_Source: NOAA/NOS/NCCOS/CCMA Biogeography Branch

Attribute_Domain_Values:

Enumerated_Domain:

Enumerated_Domain_Value: 0

Enumerated_Domain_Value_Definition:

low likelihood of suitable coral habitat (false positive to false negative cost ratio < 1:1)

Enumerated_Domain_Value_Definition_Source: NOAA/NOS/NCCOS/CCMA Biogeography Branch

Attribute_Domain_Values:

Enumerated_Domain:

Enumerated_Domain_Value: 1

Enumerated_Domain_Value_Definition:

medium-low likelihood of suitable coral habitat (false positive to false negative cost ratio > 1:1 but < 2:1)

Enumerated_Domain_Value_Definition_Source: NOAA/NOS/NCCOS/CCMA Biogeography Branch

Attribute_Domain_Values:

Enumerated_Domain:

Enumerated_Domain_Value: 2

Enumerated_Domain_Value_Definition:

medium likelihood of suitable coral habitat (false positive to false negative cost ratio > 2:1 but < 5:1)

Enumerated_Domain_Value_Definition_Source: NOAA/NOS/NCCOS/CCMA Biogeography Branch

Attribute_Domain_Values:

Enumerated_Domain:

Enumerated_Domain_Value: 5

Enumerated_Domain_Value_Definition:

high likelihood of suitable coral habitat (false positive to false negative cost ratio > 5:1 but < 10:1)

Enumerated_Domain_Value_Definition_Source: NOAA/NOS/NCCOS/CCMA Biogeography Branch

Attribute_Domain_Values:

Enumerated_Domain:

Enumerated_Domain_Value: 10

Enumerated_Domain_Value_Definition:

very high likelihood of suitable coral habitat (false positive to false negative cost ratio > 10:1)

Enumerated_Domain_Value_Definition_Source: NOAA/NOS/NCCOS/CCMA Biogeography Branch

Overview_Description:

Entity_and_Attribute_Overview:

This dataset depicts the predicted likelihood of suitable coral habitat as coral habitat suitability likelihood classes derived from a categorical reclassification of the logistic output of a maximum entropy (MaxEnt) model derived from coral presence locations and environmental predictor variables. The reclassification used calibrated thresholds based on different hypothetical scenarios of the false positive:false negative cost ratio, that is, the relative cost of false positive versus false negative errors. Thresholds were chosen to minimize error rates when tested on data left out of the model-fitting process (cross-validation datasets). after weighting false positive and false negative error rates by the indicated cost ratio. Thresholds corresponding to false positive:false negative cost ratios of 1:1, 2:1, 5:1, and 10:1 were calculated using the 'ROCR' package in the R statistical software (version 2.15). The thresholds were then used to create coral habitat suitability likelihood classes. Coral habitat suitability likelihood classes can be qualitatively described as follows: Low Likelihood (Category 0, FP:FN cost ratio < 1:1, Medium-Low Likelihood (Category 1, FP:FN cost ratio > 1:1 but less than 2:1), Medium Likelihood (Category 2, FP:FN cost ratio > 2:1 but less than 5:1), High Likelihood (Category 5, FP:FN cost ratio > 5:1 but less than 10:1), Very High Likelihood (Category 10, FP:FN cost ratio > 10:1).

Entity_and_Attribute_Detail_Citation:

For more information please see: Kinlan BP, Poti M, Drohan A, Packer DB, Nizinski M. 2012. Habitat Suitability Modeling for Deep-Sea Corals in the Northeast and Mid-Atlantic Regions (poster). Proceedings of the 2nd National Habitat Assessment Workshop: Fisheries Science to Support NOAA’s Habitat Blueprint, Seattle, WA, USA, September 5-7, 2012. Available from NOAA Fisheries Office of Science and Technology or by emailing author: Brian.Kinlan@NOAA.gov.

Entity_and_Attribute_Detail_Citation:

Phillips, S.J., Anderson, R.P., Schapire R.E. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling 190:231-259.

Entity_and_Attribute_Detail_Citation:

R Core Team. 2012. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL <http://www.R-project.org/>.

Entity_and_Attribute_Detail_Citation:

Sing, T, Sandler, O, Beerenwinkel, N, Lengauer, T. 2005. ROCR: visualizing classifier performance in R. Bioinformatics 21(20): 3940-3941.

Distribution_Information:

Distributor:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization:

Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Centers for Coastal Ocean Science (NCCOS), Center for Coastal Monitoring and Assessment (CCMA), Biogeography Branch

Contact_Address:

Address_Type: mailing and physical address

Address: 1305 East-West Highway, SSMC4, N/SCI-1

City: Silver Spring

State_or_Province: MD

Postal_Code: 20910-3278

Country: United States

Contact_Voice_Telephone: 301-713-3028

Resource_Description: Downloadable Data

Distribution_Liability:

These data were prepared by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, make any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed in this report, or represents that its use would not infringe privately owned rights. Reference therein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. Any views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. Although all data have been used by NOAA, no warranty, expressed or implied, is made by NOAA as to the accuracy of the data and/or related materials. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by NOAA in the use of these data or related materials.

Standard_Order_Process:

Digital_Form:

Digital_Transfer_Information:

Format_Name: ESRI Shapefile

Digital_Transfer_Option:

Online_Option:

Computer_Contact_Information:

Network_Address:

Network_Resource_Name: <http://coastalscience.noaa.gov/projects/detail?key=35>

Fees: None

Metadata_Reference_Information:

Metadata_Date: 20130809

Metadata_Contact:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization:

Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Centers for Coastal Ocean Science (NCCOS), Center for Coastal Monitoring and Assessment (CCMA), Biogeography Branch

Contact_Address:

Address_Type: mailing and physical address

Address: 1305 East-West Highway, SSMC4, N/SCI-1

City: Silver Spring

State_or_Province: MD

Postal_Code: 20910-3278

Country: United States

Contact_Voice_Telephone: 301-713-3028

Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata

Metadata_Standard_Version: FGDC-STD-001-1998