Atlantic Deep-Sea Coral Richness (Southeast Blueprint Indicator)

Reason for Selection Many deep-sea corals form tree-like shapes and complex reefs that provide valuable three-dimensional habitat structure for many fish and invertebrate species. The presence of more coral genera typically creates more complex habitats that support more species. In tropical coral reef communities, higher levels of coral diversity and topographic complexity have been shown to promote higher diversity of fish species (Komyakova et al. 2013). Deep-sea corals support commercially important fisheries such as grouper, snapper, sea bass, rockfish, shrimp, and crab. Because most deep-sea corals grow very slowly, they are highly vulnerable to damage from trawling and energy development, as well as ocean acidification due to climate change (NOAA 2018). Input Data * [Southeast Blueprint 2023 subregions]: Marine (combined Atlantic & Gulf of America) * [Southeast Blueprint 2023 extent] * National Oceanic and Atmospheric Administration (NOAA) [Characterizing Spatial Distributions of Deep-sea Corals and Hardbottom Habitats in the U.S. Southeast Atlantic]; [read the final report]; data shared prior to official release on 2-4-2022 by Matt Poti with the NOAA National Centers for Coastal Ocean Science ([matthew.poti@noaa.gov]) This dataset provides probability models for 24 deep-sea coral genera (Eunicella, Enallopsammia, Cladocora, Chrysogorgia, Callogorgia, Bathypathes, Antipathes, Anthothela, Acanthogorgia, Acanella, Thesea, Tanacetipathes, Stylasteridae, Stichopathes, Solenosmilia, Plumarella, Paramuricea, Paragorgia, Oculina, Nicella, Muricea, Madrepora, Lophelia, Leiopathes),as well as a combined genus richness layer that counts the average number of unique genera predicted to occur in each 100 m pixel. Matt Poti provided a summarized vector version of the continuous genus richness raster layer that mirrors the way the Bureau of Safety and Environmental Enforcement displays the Gulf version of these data. This classification is based on natural breaks in the data distribution and used 10 bins. We further collapsed the bins from 10 to 5 for simplicity. Mapping Steps * Convert the categorical text descriptions in the provided genus richness shapefile into the indicator values. * Reclassify to collapse the 10 classes into 5 by combining the “0-0.5” and “0.5-1” classes and assigning a value of 1, combining the “1-1.5” and “1.5-2” classes and assigning a value of 2, combining the “2-2.5” and “2.5-3” classes and assigning a value of 3, combining the “3-3.5” and “3.5-4” classes and assigning a value of 4, and combining the “4-5” and “>5” classes and assigning a value of 5. * Convert the shapefile to a raster. * Clip to the Southeast Blueprint 2023 marine subregion. * As a final step, clip to the spatial extent of Southeast Blueprint 2023. Note: For more details on the mapping steps, code used to create this layer is available in the[Southeast Blueprint Data Download]under > 6_Code. Final indicator values Indicator values are assigned as follows: 5 = Highest predicted average genus richness (>4) 4 = High predicted average genus richness (>3-4) 3 = Medium predicted average genus richness (>2-3) 2 = Low predicted average genus richness (>1-2) 1 = Lowest predicted average genus richness (0-1) Known Issues * While this layer has a 30 m resolution, the NOAA deep-sea coral models were coarser than that. We downsampled 100 m pixels to 30 m. * This indicator underprioritizes areas with low survey effort for the variables used to predict deep-sea corals. This is especially true for seafloor geology, curvature, and aspect. Sharp linear features and shapes in this indicator, when not aligned with a shelf break, are a symptom of places with low survey effort for these variables. * The source data does not consistently cover all areas deeper than 50 m within the Blueprint marine subregion. According to the final report for the NOAA project, “The study area included waters between 50–3,500 m depth within BOEM’s Straits of Florida, South Atlantic, and Mid-Atlantic Planning Areas and extended from Florida to Delaware. Locations of underwater visual surveys used to compile the presence-absence database for this study did not span this entire depth range across the study area. Therefore, the depth range of the study area extent varied with latitude. Offshore of south Florida (the Straits of Florida, the Miami and Pourtalès Terraces, and the adjacent escarpment) presence-absence data were not located shallower than approximately 150 m, so the study area was restricted to waters from 150–3,500 m depth south of 26.5 °N latitude. Similarly, the study area was restricted to continental slope waters from 200–3,500 m depth north of 34.5 °N because presence-absence data north of Cape Lookout, North Carolina, were located only on the continental slope (in submarine canyons and inter-canyons areas) and not on the continental shelf (<200 m depth).” Other Things to Keep in Mind * Atlantic and Gulf deep-sea coral richness are intended to serve as complementary indicators and are based on very similar NOAA source data. Because of the different deep-sea coral communities present in the Atlantic and the Gulf, the data provider recommended different thresholds for what level of genus richness qualifies as highest, high, medium, etc. to ensure the Blueprint captures the most important deep-sea coral areas within each region. Disclaimer: Comparing with Older Indicator Versions There are numerous problems with using Southeast Blueprint indicators for change analysis. Please consult Blueprint staff if you would like to do this (email [hilary_morris@fws.gov]). Literature Cited Komyakova V, Munday PL, Jones GP. Relative importance of coral cover, habitat complexity and diversity in determining the structure of reef fish communities. PLoS One. 2013 Dec 13;8(12):e83178. [[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3862682/#B11]]. National Oceanographic and Atmospheric Administration. Deep Sea Coral Research and Technology Program 2018 Report to Congress. December 2018. [[https://www.fisheries.noaa.gov/resource/document/deep-sea-research-and-technology-program-2018-report-congress]]. Poti M, Goyert HF, Salgado EJ, Bassett R, Coyne M, Winship AJ, Etnoyer PJ, Hourigan TF, Coleman HM, Christensen J. 2022. Data synthesis and predictive modeling of deep-sea coral and hardbottom habitats offshore of the southeastern US: guiding efficient discovery and protection of sensitive benthic areas. New Orleans (LA): US Department of the Interior, Bureau of Ocean Energy Management. 224 p. Contract No.: M16PG00010. Report No.: OCS Study BOEM 2022- 038. [[https://espis.boem.gov/final%20reports/BOEM_2022-038.pdf]].