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The data represent predicted habitat suitability for several taxa of deep-sea corals. Predictions were modeled using a statistical machine-learning algorithm called maximum entropy (MaxEnt). NOAA National Centers for Coastal Ocean Science (NCCOS) combined databases of known deep-sea coral locations provided by the NOAA Deep-Sea Coral Research and Technology Program (DSCRTP) and other contributors with environmental and oceanographic data to generate the predictive models of deep-sea coral distribution. These models are used to produce regional maps of deep-sea coral habitat. In these regions, deep-sea coral occurs on the continental shelves and slopes, at ocean depths of approximately 50 to greater than 2,000 meters. Model predictions are organized into five hierarchical categories to be able to compare the data across coral taxa and across regions. The categories correspond to the predicted likelihood of suitable deep sea coral habitat occurring. Includes all Scleractinians not included in Group 5, except Oculina spp., and unidentified Scleractinians.