Name: St. Croix Resilience Indicators & Composite Resilience Score
Display Field:
Type: Group Layer
Geometry Type: null
Description: Relative climate resilience scores (unitless) for coral reef habitats in the U.S. Virgin Islands at the 50 x 50 m resolution. Scores are derived from a suite of indicators incorporating biological, climatological, and physical attributes from St. Croix. Also included here are the 23 indicators which were compiled to develop the relative resilient index.
Copyright Text: US DOC; NOAA; NOS; National Centers for Coastal Ocean Science (NCCOS)
Description: Relative climate resilience scores (unitless) for coral reef habitats in the U.S. Virgin Islands at the 50 x 50 m resolution. Scores are derived from a suite of indicators incorporating biological, climatological, and physical attributes from St. Croix.
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: US DOC; NOAA; NOS; National Centers for Coastal Ocean Science (NCCOS)
Description: This group contains each of the Indicators selected to support a relative resilience coverage.
Several of these indicators (based on data from the National Coral Reef Monitoring Program) are reported by habitat type with raw values and indicator socres. Whereas other are reported by raw values and resilience scores.
Copyright Text: US DOC; NOAA; NOS; National Centers for Coastal Ocean Science (NCCOS)
Name: St. Croix Degree Heating Weeks (Degree Heating Weeks above Maximum Monthly Mean)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Degree Heating Weeks were calculated by summing the positive anomalies of the modeled SSTs above the NOAA CRW CoralTemp v3.1 maximum monthly mean(MMM) for each 3 month period. (warmest month of the 1985-2012 climatology,
https://coralreefwatch.noaa.gov/product/5km/description_climatology.php ).
Both the model data and the CoralTemp v3.1 data were filled where data was missing in the zonal direction using NCL’s poisson grid fill function.
These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project.
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: UNEP 2020. Projections of future coral bleaching conditions using IPCC CMIP6 models: climate policy implications, management applications, and Regional Seas summaries. United Nations Environment Programme, Nairobi, Kenya
Description: This dataset visualizes sediment runoff potential based on landcover, slope, soil characteristics, road density, erosivity, and precipitation in individual watersheds based on an analysis from the earlier US Caribbean project "Summit to Sea." A simple diffusion model determined patterns of coral exposure to runoff. Higher values are places more susceptible to runoff from sediments.
These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project.
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: National Centers for Coastal Ocean Science (NCCOS); World Resources Institute; Pittman, S. J., Poti, M., Jeffrey, C. F., Kracker, L. M., & Mabrouk, A. (2017). Decision support framework for the prioritization of coral reefs in the US Virgin Islands. Ecological Informatics.
Description: Mean Ramicrusta spp. cover for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project.
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176081], 2019 [NCEI Accession 0216069], and 2021 [NCEI Accession 0270849]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5ww7fqk. (Accessed 05 February 2022).
Description: Mean macroalgae cover for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project.
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef fish communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176080], 2019 [NCEI Accession 0224406], and 2021 [NCEI Accession 0270582]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/V5F769MM. (Accessed 05 February 2022).
Name: St. Croix Wave Energy: Wave-induced flow near the sea floor (meters/second)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Wave data were obtained from a CARICOOS SWAN wave model (SWAN_Aggregation/Best Time Series) shared on a CARICOOS OPeNDAP server (http://52.55.122.42/thredds/dodsC/swan/SWAN_Aggregation_best.ncd.html). The source data have a spatial resolution of 0.01 degrees on a geographic grid (WGS84) and temporal resolution of 3-hours from noon on 13 Oct 2012 through 1500 hours on 21 Nov 2021. There is a gap in the data between noon on day 222 of 2013 and 1500 hours on day 363 of 2014. The data extend from 64W to 68W and 17N to 19.5N.
Wave-induced flow near the sea floor (i.e., representative bottom orbital velocity) was calculated from depth and mean significant wave height and period following Wiberg and Sherwood 2008.
These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project.
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: US DOC; NOAA; NOS; National Centers for Coastal Ocean Science (NCCOS)
Description: Depth values at the 50 m resolution derived from various bathymetric layers.
These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project.
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: US DOC; NOAA; NOS; National Centers for Coastal Ocean Science (NCCOS)
Description: Structural complexity at the 50 m resolution derived from various bathymetric layers using the arc-chord ratio method described in Du Preez 2015.
These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project.
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science, 2022
Name: St. Croix Orbicella Species Abundance (Coral count per 10 m²)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Mean Orbicella species abundance for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project.
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176081], 2019 [NCEI Accession 0216069], and 2021 [NCEI Accession 0270849]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5ww7fqk. (Accessed 05 February 2022).
Name: St. Croix Acropora Species Abundance (Coral count per 10 m²)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Mean Acropora species abundance for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project.
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176081], 2019 [NCEI Accession 0216069], and 2021 [NCEI Accession 0270849]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5ww7fqk. (Accessed 05 February 2022).
Description: Mean coral cover for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project.
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176081], 2019 [NCEI Accession 0216069], and 2021 [NCEI Accession 0270849]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5ww7fqk. (Accessed 05 February 2022).
Name: St. Croix SCTLD Resistant Abundance (Coral count per 10 m²)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Mean SCTLD resistant species abundance for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project.Genera included: Acropora spp., Agaricia spp., Cladocora spp., Helioseris spp., Isophyllia spp., Madracis spp., Manicina spp., Mussa spp., Mycetophyllia spp., Porites spp., Oculina spp., Scolymia spp., and Tubastrea spp..
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176081], 2019 [NCEI Accession 0216069], and 2021 [NCEI Accession 0270849]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5ww7fqk. (Accessed 05 February 2022).
Name: St. Croix Fish Biomass: All Species (biomass kg/177 m²)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Mean fish biomass for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project.
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef fish communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176080], 2019 [NCEI Accession 0224406], and 2021 [NCEI Accession 0270582]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/V5F769MM. (Accessed 05 February 2022).
Name: St. Croix Fish Biomass: Herbivore Species (biomass kg/177m²)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Mean fish biomass of herbivore species for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project.
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef fish communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176080], 2019 [NCEI Accession 0224406], and 2021 [NCEI Accession 0270582]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/V5F769MM. (Accessed 05 February 2022).
Name: St. Croix Fish Biomass: Commercial Species (biomass kg/177m²)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Mean fish biomass of commercial species for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project.
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef fish communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176080], 2019 [NCEI Accession 0224406], and 2021 [NCEI Accession 0270582]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/V5F769MM. (Accessed 05 February 2022).
Name: St. Croix Crustose Coraline Algae Cover (% cover)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Mean crustose coralline algae (CCA) cover for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project.
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176081], 2019 [NCEI Accession 0216069], and 2021 [NCEI Accession 0270849]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5ww7fqk. (Accessed 05 February 2022).
Name: St. Croix Colpophyllia natans abundance (Coral count per 10 m²)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Mean Colpophyllia natans abundance for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project. This species was selected due to its susceptibility to Stony Coral Tissue Loss Disease (SCTLD).
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176081], 2019 [NCEI Accession 0216069], and 2021 [NCEI Accession 0270849]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5ww7fqk. (Accessed 05 February 2022).
Name: St. Croix Dendrogyra cylindrus abundance (Coral count per 10 m²)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Mean Dendrogyra cylindrus abundance for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project. This species was selected due to its susceptibility to Stony Coral Tissue Loss Disease (SCTLD).
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176081], 2019 [NCEI Accession 0216069], and 2021 [NCEI Accession 0270849]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5ww7fqk. (Accessed 05 February 2022).
Name: St. Croix Dichocoenia stokesii abundance (Coral count per 10 m²)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Mean Dichocoenia stokesii abundance for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project. This species was selected due to its susceptibility to Stony Coral Tissue Loss Disease (SCTLD).
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176081], 2019 [NCEI Accession 0216069], and 2021 [NCEI Accession 0270849]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5ww7fqk. (Accessed 05 February 2022).
Name: St. Croix Diploria labyrinthiformis abundance (Coral count per 10 m²)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Mean Diploria labyrinthiformis abundance for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project. This species was selected due to its susceptibility to Stony Coral Tissue Loss Disease (SCTLD).
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176081], 2019 [NCEI Accession 0216069], and 2021 [NCEI Accession 0270849]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5ww7fqk. (Accessed 05 February 2022).
Name: St. Croix Eusmilia fastigiata abundance (Coral count per 10 m²)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Mean Eusmilia fastigiata abundance for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project. This species was selected due to its susceptibility to Stony Coral Tissue Loss Disease (SCTLD).
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176081], 2019 [NCEI Accession 0216069], and 2021 [NCEI Accession 0270849]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5ww7fqk. (Accessed 05 February 2022).
Name: St. Croix Meandrina meandrites abundance (Coral count per 10 m²)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Mean Meandrina meandrites abundance for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project. This species was selected due to its susceptibility to Stony Coral Tissue Loss Disease (SCTLD).
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176081], 2019 [NCEI Accession 0216069], and 2021 [NCEI Accession 0270849]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5ww7fqk. (Accessed 05 February 2022).
Name: St. Croix Pseudodiploria clivosa abundance (Coral count per 10 m²)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Mean Pseudodiploria clivosa abundance for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project. This species was selected due to its susceptibility to Stony Coral Tissue Loss Disease (SCTLD).
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176081], 2019 [NCEI Accession 0216069], and 2021 [NCEI Accession 0270849]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5ww7fqk. (Accessed 05 February 2022).
Name: St. Croix Pseudodiploria strigosa abundance (Coral count per 10 m²)
Display Field: HABITAT
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: Mean Pseudodiploria strigosa abundance for major habitat categories derived from the National Coral Reef Monitoring Program (NCRMP) St. Croix sampling missions. These data were used to calculate resilience scores for the US Virgin Islands Coral Reef Resilience Prioritization project. This species was selected due to its susceptibility to Stony Coral Tissue Loss Disease (SCTLD).
The US Virgin Islands (USVI) Coral Reef Resilience Prioritization project identified coral reefs and underwater habitats in the USVI that may have high resilience properties and potential to withstand current and forecasted climate change conditions, such as thermal stress, increased wave action, and coral disease outbreaks. To learn more, visit https://coastalscience.noaa.gov/project/u-s-virgin-islands-coral-reef-resilience-prioritization/
Copyright Text: NOAA National Centers for Coastal Ocean Science and NOAA Southeast Fisheries Science Center. 2021. National Coral Reef Monitoring Program: Assessment of coral reef benthic communities in the U.S. Virgin Islands. Data subsets 2013-2015 [NCEI Accession 0224205], 2017 [NCEI Accession 0176081], 2019 [NCEI Accession 0216069], and 2021 [NCEI Accession 0270849]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5ww7fqk. (Accessed 05 February 2022).
Description: A bathymetry dataset for the USVI was created by integrating historical sounding data from hydrographic surveys with more recently collected higher resolution bathymetric data from multibeam sonar and LiDAR. A unified point dataset was generated from the multibeam sonar, LiDAR, and sounding data, quality checked and interpolated to predict a continuous, 20 x 20 m gridded bathymetry dataset and corresponding uncertainty estimates.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: These data visualize the major and detailed structural features and biological cover of the benthos in existing benthic habitat maps for St. Croix in the U.S. Virgin Islands.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: Buck Island Reef National Monument Benthic Habitat Map (Deep)
Display Field: Zone
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: This feature class visualizes the major and detailed structural features and biological cover of the benthos in deep depths around Buck Island Reef National Monument.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: Buck Island Reef National Monument Benthic Habitat Map (Moderate)
Display Field: Zone
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: This feature class visualizes the major and detailed structural features and biological cover of the benthos in moderate depths around Buck Island Reef National Monument.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: Buck Island Reef National Monument Benthic Habitat Map (Shallow)
Display Field: Zone
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: This feature class visualizes the major and detailed structural features and biological cover of the benthos in shallow depths of Buck Island Reef National Monument.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: This data layer represents a 2001 benthic habitat map visualizing the major and detailed structural features and biological cover of the benthos for St. Croix.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: The MPA Inventory is a comprehensive catalog that provides detailed information for existing marine protected areas in the United States. The inventory provides geospatial boundary information (in polygon format) and classification attributes that seek to define the conservation objectives, protection level, governance and related management criteria for all sites in the database. The comprehensive inventory of federal, state and territorial MPA sites provides governments and stakeholders with access to information to make better decisions about the current and future use of place-based conservation. The information also will be used to inform the development of the national system of marine protected areas as required by Executive Order 13158. This group also includes the boundary for the Queen Conch seasonal closure area from the National Marine Fisheries Service Southeast Regional Office.
Copyright Text: NOAA Marine Protected Areas Center in joint effort with the US Department of the Interior; National Marine Fisheries Service Southeast Regional Office
Description: Marine Park subset of the MPA Inventory. The MPA Inventory is a comprehensive catalog that provides detailed information for existing marine protected areas in the United States. The inventory provides geospatial boundary information (in polygon format) and classification attributes that seek to define the conservation objectives, protection level, governance and related management criteria for all sites in the database. The comprehensive inventory of federal, state and territorial MPA sites provides governments and stakeholders with access to information to make better decisions about the current and future use of place-based conservation. The information also will be used to inform the development of the national system of marine protected areas as required by Executive Order 13158. This layer visualizes managed areas designated as Marine Park in St. Croix.
Copyright Text: NOAA Marine Protected Areas Center in joint effort with the US Department of the Interior
Name: National Historic Park and Ecological Preserve
Display Field: Site_Name
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: National Hestoric Pack subset of the MPA Inventory. The MPA Inventory is a comprehensive catalog that provides detailed information for existing marine protected areas in the United States. The inventory provides geospatial boundary information (in polygon format) and classification attributes that seek to define the conservation objectives, protection level, governance and related management criteria for all sites in the database. The comprehensive inventory of federal, state and territorial MPA sites provides governments and stakeholders with access to information to make better decisions about the current and future use of place-based conservation. The information also will be used to inform the development of the national system of marine protected areas as required by Executive Order 13158. This layer visualizes managed areas designated as National Historic Park and Ecological Preserve in St. Croix.
Copyright Text: NOAA Marine Protected Areas Center in joint effort with the US Department of the Interior
Description: National Monument subset of the MPA inventory. The MPA Inventory is a comprehensive catalog that provides detailed information for existing marine protected areas in the United States. The inventory provides geospatial boundary information (in polygon format) and classification attributes that seek to define the conservation objectives, protection level, governance and related management criteria for all sites in the database. The comprehensive inventory of federal, state and territorial MPA sites provides governments and stakeholders with access to information to make better decisions about the current and future use of place-based conservation. The information also will be used to inform the development of the national system of marine protected areas as required by Executive Order 13158. This layer visualizes managed areas designated as National Monuments in St. Croix.
Copyright Text: NOAA Marine Protected Areas Center in joint effort with the US Department of the Interior
Description: National Wildlife Refuge subset from MPA Inventory. The MPA Inventory is a comprehensive catalog that provides detailed information for existing marine protected areas in the United States. The inventory provides geospatial boundary information (in polygon format) and classification attributes that seek to define the conservation objectives, protection level, governance and related management criteria for all sites in the database. The comprehensive inventory of federal, state and territorial MPA sites provides governments and stakeholders with access to information to make better decisions about the current and future use of place-based conservation. The information also will be used to inform the development of the national system of marine protected areas as required by Executive Order 13158. This layer visualizes managed areas designated as National Wildlife Refuges in St. Croix.
Copyright Text: NOAA Marine Protected Areas Center in joint effort with the US Department of the Interior
Description: Fishery Management Area subset of the MPA Inventory. The MPA Inventory is a comprehensive catalog that provides detailed information for existing marine protected areas in the United States. The inventory provides geospatial boundary information (in polygon format) and classification attributes that seek to define the conservation objectives, protection level, governance and related management criteria for all sites in the database. The comprehensive inventory of federal, state and territorial MPA sites provides governments and stakeholders with access to information to make better decisions about the current and future use of place-based conservation. The information also will be used to inform the development of the national system of marine protected areas as required by Executive Order 13158. This layer also includes the boundary for the Queen Conch seasonal closure area from the National Marine Fisheries Service Southeast Regional Office. This layer visualizes managed areas designated as Fishery Management Areas in St. Croix.
Copyright Text: NOAA Marine Protected Areas Center in joint effort with the US Department of the Interior; National Marine Fisheries Service Southeast Regional Office
Description: This file geodatabase raster dataset is derived from sightings of hard bottom from visual surveys collected via drop camera or remotely operated vehicle video. This gridded version of the dataset was created by visualizing only those cells where at least one observation of hard bottom occured.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: St. Croix Predicted Presence of Hard Bottom (20 m)
Display Field: Dissolve
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: This feature class is the output of a presence-only predictive model used to predict how likely each 20 x 20 m grid cell is to contain hard bottom based on observed hard bottom data and environmental covariates such as bathymetry (and it's derivatives slope, slope of slope, and curvature). The model was run using MaxENT (Maximum Entropy Modeling) and a binary threshold was instituted to call cells as having hard bottom or not based on a likelihood output from the model.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: St. Croix Predicted Presence of Hard Bottom (100 m)
Display Field: Value
Type: Raster Layer
Geometry Type: null
Description: This file geodatabase raster dataset was created by aggregating predicted hard bottom from 20 x 20 m grid cells onto a 100 x 100 m grid. If the resulting 100 x 100 m grid cells contain any 20 x 20 m grid cells that were predicted to contain hard bottom, that larger cell was also denoted as containing hard bottom.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: St. Croix Predicted Percentage of Hard Bottom
Display Field: Value
Type: Raster Layer
Geometry Type: null
Description: This file geodatabase raster dataset was created by aggregating predicted hard bottom from 20 x 20 m grid cells onto a 100 x 100 m grid. If the resulting 100 x 100 m grid cells contain any 20 x 20 m grid cells that were predicted to contain hard bottom, that larger cell was also denoted as containing hard bottom.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: These data visualize the slope of slope of the seafloor, a rugosity analog, around St. Croix in the U.S. Virgin Islands.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS); Pittman, S. J., Poti, M., Jeffrey, C. F., Kracker, L. M., & Mabrouk, A. (2017). Decision support framework for the prioritization of coral reefs in the US Virgin Islands. Ecological Informatics.
Description: This file geodatabase raster dataset visualizes the slope of slope of the seafloor around St. Croix. Slope of slope is analagous to curvature or rugosity. The layer was derived from a 20 x 20 m bathymetry grid layer for St. Croix. The slope of the bathymetry layer was obtained using the spatial analyst slope tool. The output from that tool was fed back into the spatial analyst slope tool to obtain a second derivative of the bathymetry surface representing the rate of slope change between neighboring cells.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS); Pittman, S. J., Poti, M., Jeffrey, C. F., Kracker, L. M., & Mabrouk, A. (2017). Decision support framework for the prioritization of coral reefs in the US Virgin Islands. Ecological Informatics.
Name: St. Croix Maximum Seafloor Slope of Slope (100 m)
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This file geodatabase raster dataset was created by aggregating the slope of slope data from 20 x 20 m grid cells onto a 100 x 100 m grid. Each 100 x 100 m grid cell can have up to 25 20 x 20 m grid cells within it, and each 100 x 100 m grid cell was given the value of the 20 x 20 m grid cell with the highest slope of slope value.
Slope of slope data was generated by taking the slope of the bathymetry layer was obtained using the spatial analyst slope tool. The output from that tool was fed back into the spatial analyst slope tool to obtain a second derivative of the bathymetry surface representing the rate of slope change between neighboring cells.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS); Pittman, S. J., Poti, M., Jeffrey, C. F., Kracker, L. M., & Mabrouk, A. (2017). Decision support framework for the prioritization of coral reefs in the US Virgin Islands. Ecological Informatics.
Name: St. Croix Masked Maximum Seafloor Slope of Slope
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This file geodatabase raster dataset was created by aggregating the slope of slope data from 20 x 20 m grid cells onto a 100 x 100 m grid. Each 100 x 100 m grid cell can have up to 25 20 x 20 m grid cells within it, and each 100 x 100 m grid cell was given the value of the 20 x 20 m grid cell with the highest slope of slope value. The resulting grid was then masked using a raster dataset of predicted hard bottom whereby areas that were not predicted to be hard bottom were clipped out.Slope of slope data was generated by taking the slope of the bathymetry layer was obtained using the spatial analyst slope tool. The output from that tool was fed back into the spatial analyst slope tool to obtain a second derivative of the bathymetry surface representing the rate of slope change between neighboring cells.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS); Pittman, S. J., Poti, M., Jeffrey, C. F., Kracker, L. M., & Mabrouk, A. (2017). Decision support framework for the prioritization of coral reefs in the US Virgin Islands. Ecological Informatics.
Name: St. Croix Maximum Slope of Slope (200 m radius)
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This file geodatabse raster dataset was created by taking the maximum slope of slope value within a 200 m circular neighborhood around each pixel in order to highlight areas that are near places with high slopes. This layer can be informative for marine species with home ranges of certain sizes that may not have to be on rugose or complex seafloor, but must be nearby such areas. Slope of slope data was generated by taking the slope of the bathymetry layer was obtained using the spatial analyst slope tool. The output from that tool was fed back into the spatial analyst slope tool to obtain a second derivative of the bathymetry surface representing the rate of slope change between neighboring cells.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS); Pittman, S. J., Poti, M., Jeffrey, C. F., Kracker, L. M., & Mabrouk, A. (2017). Decision support framework for the prioritization of coral reefs in the US Virgin Islands. Ecological Informatics
Description: Data on Coral Percent Cover from National Coral Reef Monitoring Program and preceding efforts. Collected from in-situ surveys. Suveys conducted: 2001-2019.
Copyright Text: National Center for Coastal Ocean Science (NCCOS)
Description: These data visualize point locations where Acropora cervicornis and Acropora palmata colonies were observed during field operations and areas where these coral species are predicted to occur based on environmental covariates. The data was compiled from various sources including the National Coral Reef Monitoring Program.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: This feature class visualizes point locations where Acropora cervicornis colonies were observed during field operations. The data was compiled from various sources including the National Coral Reef Monitoring Program.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: St. Croix Minimum Predicted Acropora cervicornis Presence
Display Field: Value
Type: Raster Layer
Geometry Type: null
Description: This raster dataset visualizes the output of MaxENT (Maximum Entropy Modeling) models used to predict the presence of Acropora cervicornis based on observations from field operations and associated environmental covariates such as depth, slope of slope, and rugosity. The minimum prediction based on a set of 10 model runs was used so that places that were predicted to have the highest likelihood of containing suitable habitat were mapped.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: St. Croix Mean Predicted Acropora cervicornis Presence
Display Field: ClassDesc
Type: Raster Layer
Geometry Type: null
Description: This raster dataset visualizes the output of MaxENT (Maximum Entropy Modeling) models used to predict the presence of Acropora cervicornis based on observations from field operations and associated environmental covariates such as depth, slope of slope, and rugosity. The average of the 10 model runs was taken for each pixel. Each pixel was binned into 1 of 5 classes ranging from low to very high based on the ratios of false positive error to false negative error. The likelihood of finding suitable habitat for Acropora cervicornis in a particular pixel increases from low to very high in the bin classes.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: This feature class visualizes point locations where Acropora palmata colonies were observed during field operations. The data was compiled from various sources including the National Coral Reef Monitoring Program.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: St. Croix Minimum Predicted Acropora palmata Presence
Display Field: Value
Type: Raster Layer
Geometry Type: null
Description: This raster dataset visualizes the output of MaxENT (Maximum Entropy Modeling) models used to predict the presence of Acropora palmata based on observations from field operations and associated environmental covariates such as depth, slope of slope, and rugosity. The minimum prediction based on a set of 10 model runs was used so that places that were predicted to have the highest likelihood of containing suitable habitat were mapped.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: St. Croix Mean Predicted Acropora palmata Presence
Display Field: ClassDesc
Type: Raster Layer
Geometry Type: null
Description: This raster dataset visualizes the output of MaxENT (Maximum Entropy Modeling) models used to predict the presence of Acropora palmata based on observations from field operations and associated environmental covariates such as depth, slope of slope, and rugosity. The average of the 10 model runs was taken for each pixel. Each pixel was binned into 1 of 5 classes ranging from low to very high based on the ratios of false positive error to false negative error. The likelihood of finding suitable habitat for Acropora palmata in a particular pixel increases from low to very high in the bin classes.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: These data visualize aggregated seagrass or mangrove classed polygons from available benthic habitat maps and the National Oceanic and Atmospheric Administration's (NOAA) Coastal Change Analysis Program and where hard bottom is predicted to occur near either seagrass or mangrove habitats.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: This feature class was created by aggregating the seagrass classed polygons from available benthic habitat maps and the National Oceanic and Atmospheric Administration's (NOAA) Coastal Change Analysis Program and dissolving them into a single map of seagrass presence in St. Croix.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: St. Croix Predicted Presence of Hard Bottom Near Seagrass
Display Field: Value
Type: Raster Layer
Geometry Type: null
Description: This raster dataset depicts areas predicted to be hard bottom that are near patches of seagrass (aggregated from benthic habitat maps). Pixels where hard bottom was predicted to occur were denoted as "near" seagrass patches if the pixel was witin 300 m of seagrass.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: This raster dataset visualizes the Euclidean distance from hard bottom areas to the nearest seagrass polygon. This dataset is built on the same extent and resolution as the 20 x 20 m bathymetry dataset.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: This feature class was created by aggregating the mangrove classed polygons from available benthic habitat maps and the National Oceanic and Atmospheric Administration's (NOAA) Coastal Change Analysis Program and dissolving them into a single map of mangrove presence in St. Croix.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: St. Croix Predicted Presence of Hard Bottom Near Mangroves
Display Field: Value
Type: Raster Layer
Geometry Type: null
Description: This raster dataset depicts areas predicted to be hard bottom that are near patches of mangrove (aggregated from benthic habitat maps). Pixels where hard bottom was predicted to occur were denoted as "near" mangrove patches if the pixel was witin 300 m of mangrove
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: This raster dataset visualizes the Euclidean distance from hard bottom areas to the nearest mangrove polygon. This dataset is built on the same extent and resolution as the 20 x 20 m bathymetry dataset
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: These data represent point data obtained from visual underwater surveys conducted by the National Coral Reef Monitoring Program (NCRMP) between 2001 and 2015. Additionally, fish species richness is predicted throughout the St. Croix study area and masked by hard bottom presence.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: This feature class represents fish species richness point data obtained from visual underwater surveys conducted by the National Coral Reef Monitoring Program (NCRMP) between 2001 and 2017.
From 2001 to 2015, the method for counting fish species richness was a single diver observing a 25m x 4m belt transect. After 2015, the method for observation was a stationary point count with a radius of 7.5m. Two divers are used and results are averaged.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: This shapefile represents total fish abundance summarized by site and survey date collected during National Coral Reef Monitoring Program surveys from 2001 - 2017.
From 2001 to 2015, the method for counting fish abundance was a single diver observing a 25m x 4m belt transect. After 2015, the method for observation was a stationary point count with a radius of 7.5m. Two divers are used and results are averaged.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: St. Croix Mean Predicted Fish Species Richness
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This raster dataset represents the mean prediction of fish species richness in 20 x 20 m grid cells. The boosted regression tree model used point data obtained from National Coral Reef Monitoring Program field efforts and environmental covariates such as bathymetry and terrain complexity.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: St. Croix Maximum of Mean Predicted Fish Species Richness (100 m)
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This raster dataset represents the max of the mean prediction of fish species richness in 20 x 20 m grid cells. The 20 x 20 m grid cells were aggregated onto a 100 x 100 m grid wherein the 20 x 20 m pixel with the highest value was used as the value of the 100 x 100 m cell containing it. The boosted regression tree model used point data obtained from National Coral Reef Monitoring Program field efforts and environmental covariates such as bathymetry and terrain complexity.
Copyright Text: National Oceanic and Atmospheric Administration (NOAA) National Coral Reef Monitoring Program (NCRMP)
Name: St. Croix Masked Maximum of Mean Predicted Fish Species Richness (100 m)
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This raster dataset represents the max of the mean prediction of fish species richness in 20 x 20 m grid cells. The 20 x 20 m grid cells were aggregated onto a 100 x 100 m grid wherein the 20 x 20 m pixel with the highest value was used as the value of the 100 x 100 m cell containing it. The resulting grid was then masked by the predicted hard bottom map whereby areas that were not predicted to contain hard bottom were removed. The boosted regression tree model used point data obtained from National Coral Reef Monitoring Program field efforts and environmental covariates such as bathymetry and terrain complexity.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: These data represent known fish spawning aggregation areas around St. Croix in the U.S. Virgin Islands.
Copyright Text: Nemeth, R.S., 2012. Ecosystem aspects of species that aggregate to spawn. In: Reef Fish Spawning Aggregations: Biology, Research and Management. Springer, Netherlands, pp. 21–55
Description: This feature class represents an area known to coincide with fish spawning aggregations.
Copyright Text: Nemeth, R.S., 2012. Ecosystem aspects of species that aggregate to spawn. In: Reef Fish Spawning Aggregations: Biology, Research and Management. Springer, Netherlands, pp. 21–55
Description: Data used to produce this layer were collected in 2014 by NOAA’s National Centers for Coastal Ocean Science (NCCOS). Data were collected from the population of occupational SCUBA divers in the U.S. Virgin Islands (n=87) on the value of particular reef areas, as well as the status of these reefs in terms of ecological health. Survey respondents provided spatial information on: 1) the presence of significant ecological and biological features on familiar reefs; 2) the influence of common ecological stressors on familiar reefs; and 3) the best reef areas for diving tourism, personal diving and research activities.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: Data used to produce this layer were collected in 2014 by NOAA’s National Centers for Coastal Ocean Science (NCCOS). Data were collected from the population of occupational SCUBA divers in the U.S. Virgin Islands (n=87) on the value of particular reef areas, as well as the status of these reefs in terms of ecological health. Survey respondents provided spatial information on: 1) the presence of significant ecological and biological features on familiar reefs; 2) the influence of common ecological stressors on familiar reefs; and 3) the best reef areas for diving tourism, personal diving and research activities. Multiple data layers were created to summarize spatial data provided by survey respondents. These data were collected with the purpose of incorporation into a model to be used for prioritization of coral reefs in the U.S. Virgin Islands.This particular resource contains the Index of Reef Quality as perceived by professional SCUBA divers in the USVI. The reefs are classed either A or B depending upon the number of four different reef features/characteristics that a given cell contains. The four reef features are: Large Variety of Coral Species; Large Variety of Fish Species; Large Amount of Coral Cover; and, Large Amount of Physical Reef Structure.
Copyright Text: NOAA’s National Centers for Coastal Ocean Science (NCCOS)
Description: These data visualize long term monitoring sites, reef tourism service values, observed and predicted mature fish biomass, and high quality reef sites selected by local SCUBA divers around St. Croix in the U.S. Virgin Islands.
Copyright Text: Territorial Coral Reef Ecosystem Monitoring Program (TCRMP); van Zanten, B. T., Van Beukering, P. J., & Wagtendonk, A. J. (2014). Coastal protection by coral reefs: A framework for spatial assessment and economic valuation. Ocean & coastal management, 96, 94-103.; National Centers for Coastal Ocean Science (NCCOS)
Description: This data layer visualizes the point locations of long term monitoring sites for the Territorial Coral Reef Ecosystem Monitoring Program (TCRMP). Approximately 39 reef cells (32 TCRMP & 7 National Park Service) were identified as valuable ‘sentinel sites’ because of the presence of long-term permanent scientific monitoring sites used for territorial and national reporting of coral reef status and trends to inform adaptive management. Data collection at these sites represents a substantial strategic investment for Federal and Territorial government agencies tasked with coral reef conservation, which qualifies these coral reefs as offering a monitoring service to society.
Copyright Text: Territorial Coral Reef Ecosystem Monitoring Program (TCRMP)
Description: The tourism-associated economic value attributed to shallow-water coral reefs (< 35 m) based on beach use, proximity to hotels and snorkeling and diving was used to map total reef tourism value (US$) with the premise that coral reefs closer to recreational sites are more valuable.
Copyright Text: van Zanten, B. T., Van Beukering, P. J., & Wagtendonk, A. J. (2014). Coastal protection by coral reefs: A framework for spatial assessment and economic valuation. Ocean & coastal management, 96, 94-103.
Description: This feature class represents point data of mature fish biomass obtained from National Coral Reef Monitoring Program field surveys. This layer contains biomass data for commercially important adult fish species.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: St. Croix Mean Predicted Mature Fish Biomass
Display Field:
Type: Raster Layer
Geometry Type: null
Description: This raster dataset represents the model output of a boosted regression tree model predicting the mean fish biomass in each 20 x 20 m grid cell. The model used point data obtained from National Coral Reef Monitoring Program field efforts and environmental covariates such as bathymetry and terrain complexity.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Name: St. Croix High Quality Reefs (diver identification)
Display Field: OBJECTID
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: This data layer visualizes the number of unique SCUBA divers who denoted that particular reef sites possessed one or more metrics of high quality reefs.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)
Description: These data visualize threats and stressors such as ship traffic, land runoff exposure, thermal stress, wave height, wave power, and landscape development on or around St. Croix in the U.S. Virgin Islands.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS); United States Coast Guard; World Resources Institute; Pittman, S. J., Poti, M., Jeffrey, C. F., Kracker, L. M., & Mabrouk, A. (2017). Decision support framework for the prioritization of coral reefs in the US Virgin Islands. Ecological Informatics.; National Oceanic and Atmospheric Administration (NOAA) Coral Reef Watch; Caribbean Coastal Ocean Observing System (Miguel Canals-Silander); National Oceanic and Atmospheric Administration (NOAA) Coastal Change Analysis Program (C-CAP)
Description: This raster dataset is a gridded representation of the density for 2014 of ship traffic in waters surrounding St. Croix. This layer was created by converting Automatic Identification System (AIS) point data obtained from the US Coast Guard for individual ships into tracklines of ship traffic density in order to standardize out variation in movement of the ships. The length of the tracklines was calculated across all the ships in each 100 m grid cell, thus grid cells where ships were constantly passing across it would have more tracklines.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS); United States Coast Guard
Description: This raster dataset visualizes sediment runoff potential based on landcover, slope, soil characteristics, road density, erosivity, and precipitation in individual watersheds based on an analysis from the earlier US Caribbean project "Summit to Sea." A simple diffusion model determined patterns of coral exposure to runoff. Higher values are places more susceptible to runoff from sediments.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS); World Resources Institute; Pittman, S. J., Poti, M., Jeffrey, C. F., Kracker, L. M., & Mabrouk, A. (2017). Decision support framework for the prioritization of coral reefs in the US Virgin Islands. Ecological Informatics.
Description: This raster dataset visualizes the Pathfinder v5.2-4 km Sea Surface Temperature dataset from the National Oceanic and Atmospheric Administration's (NOAA) Coral Reef Watch program. From this dataset, thermal stress events were defined using the Degree Heating Weeks (DHW) metric wherein bleaching-level thresholds for thermal stress had been exceeded for sufficient duration to induce bleaching (DHW ≥ 4).
Copyright Text: National Oceanic and Atmospheric Administration (NOAA) Coral Reef Watch
Description: This raster dataset visualizes the average wave height from August 2012 to July 2014 around St. Croix from the Caribbean Coastal Ocean Observing System Nearshore Wave Model based on the Simulating Wave Nearshore (SWAN) model.
Copyright Text: Caribbean Coastal Ocean Observing System (Miguel Canals-Silander)
Description: This raster dataset visualizes the maximum wave height from August 2012 to July 2014 around St. Croix from the Caribbean Coastal Ocean Observing System Nearshore Wave Model based on the Simulating Wave Nearshore (SWAN) model.
Copyright Text: Caribbean Coastal Ocean Observing System (Miguel Canals-Silander)
Description: Relative exposure to waves was mapped using average wave power (Kw/m from August 2012 to July 2014 at ~ 1.1 km horizontal grid resolution from the CariCOOS (Caribbean Coastal Ocean Observing System Nearshore Wave Model (data provided by Miguel Canals-Silander) based on the Simulating WAve Nearshore SWAN model.
Copyright Text: Caribbean Coastal Ocean Observing System (Miguel Canals-Silander)
Description: This data layer visualizes classified land cover types in St. Croix based on Landsat imagery. The data was developed by NOAA;s Office of Coastal Management, Coastal Change Analysis Program (C-CAP).
Copyright Text: National Oceanic and Atmospheric Administration (NOAA) Coastal Change Analysis Program (C-CAP)
Name: St. Croix Landscape Development Intensity Index
Display Field: NAME
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: The Landscape Development Intensity Index (LDI) was calculated by assigning a weighted value to each land use type in the NOAA C-CAP land cover data (2012) to represent relative cumulative impact to runoff. Highest coefficients are assigned to impervious surfaces (e.g. paved roads) and lowest coefficients to the least developed patches of vegetation (most able to reduce runoff). The area of each land use type were then summed for sub-watersheds to calculate a relative impact for each individual sub-watershed.
Copyright Text: National Centers for Coastal Ocean Science (NCCOS)