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NCCOS spatial modeling of threatened Caribbean corals: presence-only modeling for threatened Orbicella species from the nearshore to the mesophotic from 2007-01-01 to 2018-12-31 (NCEI Accession 0241110)

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This dataset is a compilation of modeled spatial distributions of Threatened corals, Orbicella annularis (lobed star coral) and Orbicella faveolata (mountainous star coral)/Orbicella franksi (boulder star coral). in the shallow and upper mesophotic waters (0 – 60 meters depth) on the eastern Puerto Rico shelf (encompassing St. Thomas and St. John, U.S. Virgin Islands and the partial waters around Culebra and Vieques, Puerto Rico). Models for O. faveolata/O. franksi were combined into one model. All three Orbicella spp. area listed as Threatened under the U.S. Endangered Species Act. The raster datasets contain predicted probability of occurrence and prediction uncertainty for O. annularis and O. faveolata/O. franksi at four different model extents:
• 0 – 60 meter depth model: Orbicella spp. models encompassing the entire modeling region, both shallow and mesophotic depths from 0 to 60 meters (capped at 60 meters for Orbicella spp. known depth range in this region)
• 0 – 60 meter depth south shore only model: Orbicella spp. models of the south shore only removal of the mesophotic depths of the north shore, north of St. Thomas and St. John, USVI
• Shallow only model (0 – 30 meter depth): Orbicella spp. models of the shallow waters only, removal of the mesophotic depths
• Mesophotic only model (30 – 60 meter depth: Models of O. faveolata/O. franksi at mesophotic depths only remove of the shallow depths

Models were conducted using a presence/background sample model, which involves the use of presence-only data. Maximum entropy modeling was used specifically, initiated through the Java software program, MaxEnt.
  • Cite as: Egan, Katharine; Viehman, Shay; Holstein, Daniel; Poti, Matthew; Groves, Sarah; Smith, Tyler (2021). NCCOS spatial modeling of threatened Caribbean corals: presence-only modeling for threatened Orbicella species from the nearshore to the mesophotic from 2007-01-01 to 2018-12-31 (NCEI Accession 0241110). [indicate subset used]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.25921/t8h6-rb47. Accessed [date].
gov.noaa.nodc:0241110
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Distributor NOAA National Centers for Environmental Information
+1-301-713-3277
NCEI.Info@noaa.gov
Dataset Point of Contact NOAA National Centers for Environmental Information
ncei.info@noaa.gov
Time Period 2007-01-01 to 2018-12-31
Spatial Bounding Box Coordinates
West: -66.01531
East: -64.571651
South: 17.891265
North: 18.732052
Spatial Coverage Map
General Documentation
Associated Resources
  • Identifying suitable locations for mesophotic hard corals offshore of Maui, Hawai’i
  • Predicting the distribution of threatened orbicellid corals in shallow and mesophotic reef ecosystems
  • A statistical explanation of MaxEnt for ecologists
  • DEM Surface Tools for ArcGIS 10
  • Calculating landscape surface area from digital elevation models
  • A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter
  • Opening the black box: an open-source release of Maxent
  • Maximum entropy modeling of species geographic distributions
  • A maximum entropy approach to species distribution modeling
  • Equivalence of MAXENT and Poisson Point Process Models for Species Distribution Modeling in Ecology: Equivalence of MAXENT and Poisson Point Process Models
  • Calculating wave-generated bottom orbital velocities from surface-wave parameters
  • Benthic Habitat Maps for the Insular Shelf South of St. Thomas and St. John
  • Physical drivers of community structure and growth among mesophotic coral reef ecosystems surrounding St. Thomas, U.S. Virgin Islands
  • Benthic structure and cryptic mortality in a Caribbean mesophotic coral reef bank system, the Hind Bank Marine Conservation District, U.S. Virgin Islands
  • The United States Virgin Islands. In: Loya, Y., K.A. Puglise, and T.C.L. Bridge [eds.] Mesophotic coral ecosystems
  • Potential structuring forces on a shelf edge upper mesophotic coral ecosystem in the US Virgin Islands
  • Caribbean mesophotic coral ecosystems are unlikely climate change refugia
  • NASA Multi-scale Ultra-high resolution Sea Surface Temperature
  • Caribbean Coastal Ocean Observing System Nearshore Wave Models
  • NOAA NCEI Coastal Lidar Archive
  • Battista, Tim; National Oceanic and Atmospheric Administration (2015). Water depth and acoustic backscatter data collected from NOAA Ship Nancy Foster in Caribbean Sea, Northeast Grand Reserve, Puerto Rico from 2013-03-05 to 2013-03-29 (NCEI Accession 0131855). NOAA National Centers for Environmental Information. Dataset. https://www.ncei.noaa.gov/archive/accession/0131855.
  • Battista, Tim; National Oceanic and Atmospheric Administration (2016). Water depth and acoustic backscatter data collected from NOAA Ship Nancy Foster in Caribbean Sea, from 2015-03-18 to 2015-04-07 (NCEI Accession 0131859). NOAA National Centers for Environmental Information. Dataset. https://www.ncei.noaa.gov/archive/accession/0131859.
  • Battista, Timothy; Stecher, Michael; Costa, Bryan; Sautter, Will; National Oceanic and Atmospheric Administration (2017). Water Depth and acoustic backscatter data collected from NOAA Ship Nancy Foster in the US Caribbean/ Puerto Rico and St. Thomas from 2016-04-07 to 2016-04-26 (NCEI Accession 0157612). NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5rx9945.
  • USVI TCRMP
  • Costa, Bryan; Kracker, Laura; Battista, Tim; Sautter, Will; Mabrouk, Ayman; Edwards, Kimberly; Taylor, Chris; Ebert, Erik (2018). NCCOS Assessment: Benthic Habitat Map for the Insular Shelf South of St. Thomas and St. John, U.S. Virgin Islands (NCEI Accession 0170098). NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5930rfv.
  • National Centers for Coastal Ocean Science, 2017: NCCOS Assessment: Underwater Video for Ground Validation and Accuracy Assessment of Benthic Habitat Maps of the Insular Shelf South of St. Thomas and St. John, U.S. Virgin Islands, 2010-03-20 to 2017-02-10, https://www.fisheries.noaa.gov/inport/item/50381.
  • NOAA National Centers for Coastal Ocean Science (2018). National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in the U.S. Virgin Islands. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5ww7fqk.
  • NOAA National Centers for Coastal Ocean Science; NOAA Southeast Fisheries Science Center (2018). National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in Puerto Rico. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5pg1q23.
  • Chen, Yi-Hsiu; Viehman, Shay; Shertzer, Kyle; Egan, Katharine; Groves, Sarah (2020). NCCOS spatial modeling of threatened Caribbean corals: process-based models for Acropora palmata (elkhorn coral) distributions in the U.S. Virgin Islands (NCEI Accession 0220087). NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.25921/61by-cw46.
  • Spatial Predictive Modeling of Threatened ESA Corals in the U.S. Atlantic and Caribbean
  • Seafloor Characterization of the U.S. Caribbean
  • Developing A Benthic Habitat Map for the Insular Shelf South of St. Thomas and St. John
  • National Coral Reef Monitoring Program Implementation: Biological and Socioeconomic Monitoring
  • NOAA’s National Coral Reef Monitoring Program
Publication Dates
  • publication: 2021-09-24
Data Presentation Form Digital table - digital representation of facts or figures systematically displayed, especially in columns
Dataset Progress Status Complete - production of the data has been completed
Historical archive - data has been stored in an offline storage facility
Data Update Frequency As needed
Supplemental Information
Submission Package ID: MNKXUJ
Purpose Orbicellid corals (genus: Orbicella) are primary reef-building corals throughout the Caribbean in shallow and mesophotic coral ecosystems, and the three species in this genus are also listed as Threatened under the U.S. Endangered Species Act. There is a poor understanding of where they occur, which limits population monitoring and management. Orbicella spp. can also be used as a proxy for identifying mesophotic coral reef habitat (> 30 meter depth), as they are abundant in these ecosystems throughout the Caribbean. The probability of occurrence for Orbicella annularis and Orbicella faveolata/Orbicella franksi (combined) from shallow to mesophotic depths (0 – 60 meters) on the eastern Puerto Rico shelf was predicted using maximum entropy models, a presence/background sample modeling technique. The goals of our study were 1) to predict probability of occurrence for Orbicella spp. along the eastern Puerto Rico shelf and 2) to identify how abiotic environmental factors constrain that habitat based on varying model extents. The data in this accession were funded by the Virgin Islands Experimental Program to Stimulate Competitive Research under award NSF #0814417 to the University of the Virgin Islands; and the National Science Foundation Scholarship in Science, Technology, Engineering, and Mathematics under award NSF #1356632 to the University of the Virgin Islands.
Use Limitations
  • accessLevel: Public
  • Distribution liability: NOAA and NCEI make no warranty, expressed or implied, regarding these data, nor does the fact of distribution constitute such a warranty. NOAA and NCEI cannot assume liability for any damages caused by any errors or omissions in these data. If appropriate, NCEI can only certify that the data it distributes are an authentic copy of the records that were accepted for inclusion in the NCEI archives.
Dataset Citation
  • Cite as: Egan, Katharine; Viehman, Shay; Holstein, Daniel; Poti, Matthew; Groves, Sarah; Smith, Tyler (2021). NCCOS spatial modeling of threatened Caribbean corals: presence-only modeling for threatened Orbicella species from the nearshore to the mesophotic from 2007-01-01 to 2018-12-31 (NCEI Accession 0241110). [indicate subset used]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.25921/t8h6-rb47. Accessed [date].
Cited Authors
Principal Investigators
Collaborators
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Points of Contact
Publishers
Acknowledgments
  • Related Funding Agency: US DOC; NOAA; NMFS; Office of Science and Technology (OST)
  • Related Funding Agency: US DOC; NOAA; National Centers for Coastal Ocean Science (NCCOS)
  • Related Funding Agency: Virgin Islands Experimental Program to Stimulate Competitive Research awarded to the University of the Virgin Islands
  • Related Funding Agency: National Science Foundation Scholarship in Science, Technology, Engineering, and Mathematics awarded to the University of the Virgin Islands
Theme keywords NODC DATA TYPES THESAURUS NODC OBSERVATION TYPES THESAURUS WMO_CategoryCode
  • oceanography
Global Change Master Directory (GCMD) Science Keywords NCCOS Research Data Type
  • NCCOS Research Data Type > Derived Data Product
  • NCCOS Research Data Type > Geospatial
  • NCCOS Research Data Type > Model
NCCOS Research Keywords
  • NCCOS Research Priority > Marine Spatial Ecology
  • NCCOS Research Topic > Ecological and Biogeographic Assessments
Provider Keywords
  • Derived Data Product
  • Ecological and Biogeographic Assessments
  • Geospatial Data
  • Marine Spatial Ecology
  • Model Data
  • Orbicella annularis
  • Orbicella faveolata
  • Orbicella franksi
  • Probability of Occurrence
  • Uncertainty
Data Center keywords NODC SUBMITTING INSTITUTION NAMES THESAURUS Global Change Master Directory (GCMD) Data Center Keywords
Platform keywords Provider Platform Names
  • NOAA Ship Nancy Foster
Instrument keywords Provider Instruments
  • Models/Analyses > Data Analyses > Environmental Modeling
Place keywords NODC SEA AREA NAMES THESAURUS Global Change Master Directory (GCMD) Location Keywords NCCOS Research Location
  • NCCOS Research Location > Region > Caribbean Sea
  • NCCOS Research Location > U.S. States and Territories > Puerto Rico
  • NCCOS Research Location > U.S. States and Territories > U.S. Virgin Islands
Provider Place Names
  • Culebra
  • Puerto Rico
  • St. John
  • St. Thomas
  • U.S. Virgin Islands
  • Vieques
Project keywords NODC PROJECT NAMES THESAURUS Provider Project Names
  • Developing A Benthic Habitat Map for the Insular Shelf South of St. Thomas and St. John
  • National Coral Reef Monitoring Program Implementation: Biological and Socioeconomic Monitoring
  • Seafloor Characterization of the U.S. Caribbean
  • Spatial Predictive Modeling of Threatened ESA Corals in the U.S. Atlantic and Caribbean
  • US Coral Reef Monitoring Data Summary 2018
Keywords NCEI ACCESSION NUMBER
Use Constraints
  • Cite as: Egan, Katharine; Viehman, Shay; Holstein, Daniel; Poti, Matthew; Groves, Sarah; Smith, Tyler (2021). NCCOS spatial modeling of threatened Caribbean corals: presence-only modeling for threatened Orbicella species from the nearshore to the mesophotic from 2007-01-01 to 2018-12-31 (NCEI Accession 0241110). [indicate subset used]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.25921/t8h6-rb47. Accessed [date].
Access Constraints
  • Use liability: NOAA and NCEI cannot provide any warranty as to the accuracy, reliability, or completeness of furnished data. Users assume responsibility to determine the usability of these data. The user is responsible for the results of any application of this data for other than its intended purpose.
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  • In most cases, electronic downloads of the data are free. However, fees may apply for custom orders, data certifications, copies of analog materials, and data distribution on physical media.
Lineage information for: dataset
Processing Steps
  • 2021-09-24T12:29:17Z - NCEI Accession 0241110 v1.1 was published.
Output Datasets
Lineage information for: dataset
Processing Steps
  • Parameter or Variable: Probability of Occurrence (calculated); Units: unitless; Observation Category: model output; Sampling Instrument: Models/Analyses > Data Analyses > Environmental Modeling; Sampling and Analyzing Method: Probability of occurrence for Orbicella annularis and Orbicella faveolata/Orbicella franksi were calculated by averaging ten maximum entropy modeling predictions using the Java version of MaxEnt. Using environmental predictors and presence-only data of Orbicella spp., MaxEnt creates a model and produces predicted distribution maps for the species being modeled. Each grid cell of the predicted distribution map demonstrates the probability of that species (in this case, Orbicella spp.) occurring within that grid cell. The normal output is habitat suitability, but prevalence of the species within the modeled region was used as a parameter in the model, converting the grids to probability of occurrence. These data are unitless. Habitat suitability maps have values ranging from 0 – 1, but probability of occurrence maps are displayed as a percentage of 0 – 100%. For more details, see Egan et al. (2021).; Data Quality Method: Model performance was assessed via discrimination capacity, which is the ability of the model to correctly distinguish between presences and background samples. This is represented by the area under the receiver operative characteristic curve (AUC). Performance was also assessed using reliability, of the agreement between predicted and observed values. Reliability is represented by mean absolute error (MAE). Model uncertainty was quantified to provide some indication of how sampling variability and model structure may have influenced the predicted distributions Uncertainty maps for each coral group’s model replicates were created by taking the standard error among the ten replicate cloglog spatial distribution maps, and were assessed visually for areas of high uncertainty. For more details, see Egan et al. (2021)..
  • Parameter or Variable: Uncertainty (calculated); Units: unitless; Observation Category: model output; Sampling Instrument: Models/Analyses > Data Analyses > Environmental Modeling; Sampling and Analyzing Method: Uncertainty of the predicted probability of Orbicella spp. occurrence was calculated by creating a grid and taking the standard error of the ten replicate model runs. Uncertainty maps were assessed visually to determine areas of high model uncertainty between each of the replicate model runs. For more details, see Egan et al. (2021).; Data Quality Method: Uncertainty maps were reviewed by subject matter experts. Analysis methods were described and supported by reference publications. For more details, see Egan et al. (2021)..
Last Modified: 2024-06-10T13:19:58Z
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