Gulf Coral & Hardbottom (Southeast Blueprint Indicator)

Reason for Selection Hardbottom provides an anchor for important seafloor habitats such as deep-sea corals, plants, and sponges. Hardbottom is also sometimes associated with chemosynthetic communities that form around cold seeps or hydrothermal vents. In these unique ecosystems, micro-organisms that convert chemicals into energy form the base of complex food webs (Love et al. 2013). Hardbottom and associated species provide important habitat structure for many fish and invertebrates (NOAA 2018). Hardbottom areas serve as fish nursery, spawning, and foraging grounds, supporting commercially valuable fisheries like snapper and grouper (NCDEQ 2016). According to Dunn and Halpin (2009), “hardbottom habitats support high levels of biodiversity and are frequently used as a surrogate for it in marine spatial planning.” Artificial reefs arealso known to provide additional habitat that is quickly colonized to provide a suite of ecosystem services commonly associated with naturally occurring hardbottom (Wu et al. 2019). We did not include active oil and gas structures as human-created hardbottom. Although they provide habitat, because of their temporary nature, risk of contamination, and contributions to climate change, they do not have the same level of conservation value as other artificial structures. Input Data * [Southeast Blueprint 2024 extent] * [Southeast Blueprint 2024 subregions] Coral & hardbottom * [usSEABED Gulf of America sediments], accessed 12-14-2023; [download the data]; view and read more about the data on the National Oceanic and Atmospheric Administration (NOAA) [Gulf Data Atlas] (select Physical --> Marine geology --> 1. Dominant bottom types and habitats) * Bureau of Ocean Energy Management (BOEM) Gulf of America, [seismic water bottom anomalies], accessed 12-20-2023 * The Nature Conservancy’s (TNC)[South Atlantic Bight Marine Assessment](SABMA); chapter 3 of [the final report] provides more detail on the seafloor habitats analysis * NOAA deep-sea coral and sponge locations, accessed 12-20-2023 on the [NOAA Deep-Sea Coral & Sponge Map Portal] * [Florida coral and hardbottom habitats], accessed 12-19-2023 Shipwrecks & artificial reefs * [NOAA wrecks and obstructions layer], accessed 12-12-2023 on the [Marine Cadastre] * [Louisiana Department of Wildlife and Fisheries (LDWF) Artificial Reefs]: Inshore Artificial Reefs, Nearshore Artificial Reefs, Offshore and Deepwater Artificial Reefs (Google Earth/KML files), accessed 12-19-2023 * [Texas Parks and Wildlife Department (TPWD) Artificial Reefs], accessed 12-19-2023; download the data from[The Artificial Reefs Interactive Mapping Application](direct download from interactive mapping application) * [Mississippi Department of Marine Resources (MDMR) Artificial Reef Bureau]: Inshore Reefs, Offshore Reefs, Rigs to Reef (lat/long coordinates), accessed 12-19-2023 * [Alabama Department of Conservation and Natural Resources (ADCNR) Artificial Reefs]: Master Alabama Public Reefs v2023 (.xls), accessed 12-19-2023 * Florida Fish and Wildlife Conservation Commission (FWC):[Artificial Reefs in Florida](.xlsx), accessed 12-19-2023 Defining inland extent & split with Atlantic * Marine Ecoregions Level III from the Commission for Environmental Cooperation North American Environmental Atlas, accessed 12-8-2021 * 2023 [NOAA coastal relief model]: volumes 2 (Southeast Atlantic), 3 (Florida and East Gulf of America), 4 (Central Gulf of America), and 5 (Western Gulf of America), accessed 3-27-2024 * 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 (NCCOS) ([matthew.poti@noaa.gov]) * [Predictive Modeling and Mapping of Hardbottom Seafloor Habitats off the Southeast U.S]: unpublished NOAA data and[draft final report entitled Assessment of Benthic Habitats for Fisheries Management]provided on 1-28-2021 by Matt Poti with NOAA NCCOS ([matthew.poti@noaa.gov]) Mapping Steps Note: Most of the mapping steps were accomplished using the graphical modeler in QGIS 3.34. Individual models were created to combine data sources and assign ranked values. These models were combined in a single model to assemble all the data sources and create a summary raster. * Create a seamless vector layer to constrain the extent of the Atlantic coral and hardbottom indicator to marine and estuarine areas <1 m in elevation. This defines how far inland it extends. * Merge together all coastal relief model rasters (.nc format) using the create virtual raster tool in QGIS. * Save the merged raster to .tif format and import it into ArcPro. * Reclassify the NOAA coastal relief model data to assign a value of 1 to areas from deep marine to 1 m elevation. Assign all other areas (land) a value of 0. * Convert the raster produced above to vector using the raster to polygon tool. * Clip to the 2024 Blueprint subregions using the pairwise clip tool. * Hand-edit to remove terrestrial polygons (one large terrestrial polygon and the Delmarva peninsula). * Dissolve the resulting data layer to produce a seamless polygon defining marine and estuarine areas <1 m in elevation. * Hand-edit to select all but the main marine polygon and delete. * Define the extent of the Gulf version of this indicator to separate it from the Atlantic. This split reflects the extent of the different datasets available to represent coral and hardbottom habitat in the Atlantic and Gulf, rather than a meaningful ecological transition. * Use the select tool to select the Florida Keys class from the Level III marine ecoregions (“NAME_L3 = "Florida Keys"“). * Buffer the “Florida Keys” Level III marine ecoregion by 2 km to extend it far enough inland to intersect the inland edge of the <1 m elevation layer. * Reclassify the two NOAA Atlantic hardbottom suitability datasets to give all non-NoData pixels a value of 0. Combine the reclassified hardbottom suitability datasets to define the total extent of these data. Convert the raster extent to vector and dissolve to create a polygon representing the extent of both NOAA hardbottom datasets. * Union the buffered ecoregion with the combined NOAA extent polygon created above. Add a field and use it to dissolve the unioned polygons into one polygon. This leaves some holes inside the polygon, so use the eliminate polygon part tool to fill in those holes, then convert the polygon to a line. * Hand-edit to extract the resulting line between the Gulf and Atlantic. * Hand-edit to use this line to split the <1 m elevation layer created earlier in the mapping steps to create the separation between the Gulf and Atlantic extent. * From the BOEM seismic water bottom anomaly data, extract the following shapefiles: anomaly_confirmed_relic_patchreefs.shp, anomaly_Cretaceous.shp, anomaly_relic_patchreefs.shp, seep_anomaly_confirmed_buried_carbonate.shp, seep_anomaly_confirmed_carbonate.shp, seep_anomaly_confirmed_organisms.shp, seep_anomaly_positives.shp, seep_anomaly_positives_confirmed_gas.shp, seep_anomaly_positives_confirmed_oil.shp, seep_anomaly_positives_possible_oil.shp, seep_anomaly_confirmed_corals.shp, seep_anomaly_confirmed_hydrate.shp. * To create a class of confirmed BOEM features, merge anomaly_confirmed_relic_patchreefs.shp, seep_anomaly_confirmed_organisms.shp, seep_anomaly_confirmed_corals.shp, and seep_anomaly_confirmed_hydrate.shp and assign a value of 6. * To create a class of predicted BOEM features, merge the remaining extracted shapefiles and assign a value of 3. * From usSEABED sediments data, use the field “gom_domnc” to extract polygons: rock (dominant and subdominant) receives a value of 2 and gravel (dominant and subdominant) receives a value of 1. * From the wrecks database, extract locations having “high” and “medium” confidence (positionQuality = “high” and positionQuality = “medium”). Buffer these locations by 150 m and assign a value of 4. The buffer distance used here, and later for coral locations, follows guidance from the Army Corps of Engineers for setbacks around artificial reefs and fish havens (Riley et al. 2021). * Merge artificial reef point locations from FL, AL, MS and TX. Buffer these locations by 150 m. Merge this file with the three LA artificial reef polygons and assign a value of 5. * From the NOAA deep-sea coral and sponge point locations, select all points. Buffer the point locations by 150 m and assign a value of 7. * From the FWC coral and hardbottom dataset polygon locations, fix geometries, reproject to EPSG=5070, then assign coral reefs a value of 7, hardbottom a value of 6, hardbottom with seagrass a value of 6, and probable hardbottom a value of 3. Hand-edit to remove an erroneous hardbottom polygon off of Matagorda Island, TX, resulting from a mistake by Sheridan and Caldwell (2002) when they digitized a DOI sediment map. This error is documented on page 6 of the Gulf of Mexico Fishery Management Council’s[5-Year Review of the Final Generic Amendment Number 3]. * From the TNC SABMA data, fix geometries and reproject to EPSG=5070, then select all polygons with TEXT_DESC = "01. mapped hard bottom area" and assign a value of 6. * Union all of the above vector datasets together—except the vector for class 6 that combines the SABMA and FL data—and assign final indicator values. Class 6 had to be handled separately due to some unexpected GIS processing issues. For overlapping polygons, this value will represent the maximum value at a given location. * Clip the unioned polygon dataset to the buffered marine subregions. * Convert both the unioned polygon dataset and the separate vector layer for class 6 using GDAL “rasterize”. * Fill NoData cells in both rasters with zeroes and, using Extract by Mask, mask the resulting raster with the Gulf indicator extent. Adding zero values helps users better understand the extent of this indicator and to make this indicator layer perform better in online tools. * Use the raster calculator to evaluate the maximum value among the two rasters described above (one for class 6 and one for all other classes). * Export the final dataset as an unsigned 8-bit integer raster to ArcPro. Create the raster attribute table using the legend values below. * As a final step, clip to the spatial extent of Southeast Blueprint 2024. 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: 7 = Confirmed hardbottom-associated species (e.g., corals, sponges, patch reef, chemosynthetic communities) 6 = Confirmed natural hardbottom 5 = Artificial reefs 4 = Shipwrecks 3 = Probable natural hardbottom (fine resolution) 2 = Rock (coarse resolution) 1 = Gravel (coarse resolution) 0 = Not identified as hardbottom Known Issues * While active oil and gas platforms also provide artificial hardbottom habitat that supports diverse marine life (Claisse et al. 2014), we did not include active drilling sites in this version of the indicator. This decision reflects an attempt to balance the positive structural habitat value of oil and gas platforms with the negative impacts of climate change caused by fossil fuel combustion (e.g., coral bleaching and ocean acidification) (NOAA 2023) and the negative impacts of a potential oil spill (Daley 2019). We intend to further investigate these tradeoffs in future revisions. * The shipwrecks class does not account for variation in the condition of submerged structures, such as “black reef” phenomena caused by pollution and invasive species growth around contaminated shipwrecks (Degnarain 2020). * This indicator may underprioritize hardbottom and coral habitat in the eastern Gulf of America due to limited data availability. According to the Florida State University Marine Lab, “Most deep-sea research in the Gulf of America has targeted areas important to the oil and gas industry...This research has resulted in significant contributions to the discovery and in some cases the protection of hard bottom and deep-sea reefs. In contrast, the eastern Gulf of America remains relatively unexplored. In fact, it is perhaps the least explored region of the Gulf. Therefore, there is a limited amount of data on their distributions...” This issue particularly impacts the confirmed hardbottom-associated species and predicted fine-resolution hardbottom classes because the BOEM seismic anomalies dataset is limited to the BOEM central and western planning areas in the Gulf of America. As a result, this dataset does not cover state and federal waters around Florida, or other state waters across the Gulf. * This indicator underrepresents coral and hardbottom habitat within three Gulf deepwater coral Habitat Areas of Particular Concern (Steamboat Lumps, The Edges, Madison Swanson) where finer scale data on coral and hardbottom is lacking. We hope to improve coverage within these HAPCs in future updates. * While this layer has a 30 m resolution, the usSEABED dataset is coarser than that. We downsampled 2 km grid cells to 30 m. 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 Alabama Department of Conservation and Natural Resources. Artificial Reefs 2023. Microsoft Excel file. Accessed December 19, 2023. [[https://www.outdooralabama.com/saltwater-fishing/artificial-reefs]]. Claisse JT, Pondella DJ, Love M, Zahn LA, Williams CM, Williams JP, Bull AS (2014) Oil platforms off California are among the most productive marine fish habitats globally. Proc Natl Acad Sci USA 111: 15462−15467 [[https://www.pnas.org/doi/10.1073/pnas.1411477111]]. Commission for Environmental Cooperation. 2009. Marine Ecoregions of North America, 2008.Vector digital data. Montréal, Québec, Canada. [[https://www.cec.org/north-american-environmental]­atlas/marine-ecoregions-level-iii/]. Conley, M.F., M.G. Anderson, N. Steinberg, and A. Barnett, eds. 2017. The South Atlantic Bight Marine Assessment: Species, Habitats and Ecosystems. The Nature Conservancy, Eastern Conservation Science. [[https://easterndivision.s3.amazonaws.com/Marine/SABMA/SABMA_Report_11April2018.pdf]]. Daley, Jason. Deepwater Horizon Site is Now a Sticky Wasteland Populated by Sickly Crabs. September 19, 2019. Smithsonian Magazine. [[https://www.smithsonianmag.com/smart-news/deepwater-horizon-site-wasteland-populated-sickly-crabs-180973181/]]. Deep Sea Coral Research and Technology Program (DSCRTP) (2016). Observations of Deep-Sea Coral and Sponge Occurrences from the NOAA National Deep-Sea Coral and Sponge Database, 1842-Present, version 20230620-0 (NCEI Accession 0145037). NOAA National Centers for Environmental Information. Dataset. [[https://www.ncei.noaa.gov/archive/accession/0145037]]. Accessed December 20, 2023. Degnarain, Nashan. Black Reef Risk: How Sunken Metal Shipwrecks Attract Coral-Destroying Invasive Species. August 20, 2020. Forbes. [[https://www.forbes.com/sites/nishandegnarain/2020/08/20/black-reef-risk-how-sunken-metal-shipwrecks-attract-coral-destroying-invasive-species/?sh=55ae49c4129d]]. Dunn DC, Halpin PN (2009) Rugosity-based regional modeling of hard-bottom habitat. Marine Ecology Progress Series 377:1-11. [[https://doi.org/10.3354/meps07839]]. Florida Fish and Wildlife Conservation Commission-Fish and Wildlife Research Institute. Coral and Hard Bottom Habitats Florida. Vector digital data. Published March 12, 2015. Accessed December 19, 2023. [[https://geodata.myfwc.com/datasets/myfwc::coral-and-hard-bottom-habitats-in-florida/about]]. Florida Fish and Wildlife Conservation Commission. Artificial Reefs: Download Reef Locations. Microsoft Excel file. Accessed December 19, 2023. [[https://myfwc.com/fishing/saltwater/artificial-reefs/locate/]]. Florida State University Marine Lab. Coleman and Koenig Research: Hard Bottom Reefs of the West Florida Shelf. “Oil Platforms in the Gulf of Mexico.” Accessed March 20, 2024. [[https://marinelab.fsu.edu/labs/coleman/research/shelf-edge/]]. Jenkins C. Dominant Bottom Types and Habitats In Gulf of Mexico Data Atlas [Internet]. Stennis Space Center (MS): National Centers for Environmental Information; 2011. [5 screens]. [[https://gulfatlas.noaa.gov]]. Louisiana Department of Wildlife and Fisheries. Artificial Reefs: Inshore Artificial Reefs, Nearshore Artificial Reefs, Offshore and Deepwater Artificial Reefs. Google Earth/KML files. Accessed December 19, 2023. [[https://www.wlf.louisiana.gov/page/artificial-reefs]]. Love, M., Baldera, A., Yeung, C. & Robbins C. (2013). The Gulf of Mexico Ecosystem: A Coastal and Marine Atlas. New Orleans, LA: Ocean Conservancy, Gulf Restoration Center. [[https://oceanconservancy.org/wp-content/uploads/2017/05/gulf-atlas.pdf]]. Mississippi Department of Marine Resources. Artificial Reef Bureau. Inshore Reefs, Offshore Reefs, Rigs to Reef. Lat/long coordinates. Accessed December 19, 2023. [[https://dmr.ms.gov/artificial-reef/]]. National Oceanographic and Atmospheric Administration. Deep Sea Coral Research and Technology Program 2018 Report to Congress. December 2018. [[https://www.ncei.noaa.gov/data/oceans/coris/library/NOAA/DSCRTP/Other/Reports_To_Congress/2018/DSCRTP2018_Report_to_Congress.pdf]]. National Oceanographic and Atmospheric Administration. How does climate change affect coral reefs? National Ocean Service website. Last updated January 20, 2023. Accessed August 9, 2023. [[https://oceanservice.noaa.gov/facts/coralreef-climate.html]]. National Oceanographic and Atmospheric Administration. Unpublished Draft: Assessment of Benthic Habitats for Fisheries Management. May 2015. [[https://secassoutheast.org/pdf/DRAFT_Benthic-Habitats-for-Fisheries-Management-Final-Report-April-2015-with-MP-additions.pdf]]. NOAA National Centers for Environmental Information. (2023). Coastal Relief Models (CRMs) [Data set]. NOAA National Centers for Environmental Information. [[doi: 10.25921/5ZN5-KN44]]. NCDEQ (North Carolina Department of Environmental Quality) 2016. North Carolina Coastal Habitat Protection Plan Source Document. Morehead City, NC. Division of Marine Fisheries. 475 p. [[https://deq.nc.gov/media/26813/open]]. Office for Coastal Management, 2023: Wrecks and Obstructions. NOAA National Centers for Environmental Information. [[https://www.fisheries.noaa.gov/inport/item/70439]]. 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]]. Riley, K.L., Wickliffe, L.C., Jossart, J.A., MacKay, J.K., Randall, A.L., Bath, G.E., Balling, M.B., Jensen, B.M., and Morris, J.A. Jr. 2021. An Aquaculture Opportunity Area Atlas for the U.S. Gulf of Mexico. NOAA Technical Memorandum NOS NCCOS 299. Beaufort, NC. 545 pp. [[https://doi.org/10.25923/8cb3-3r66]]. Texas Parks and Wildlife Department. The Artificial Reefs Interactive Mapping Application. Accessed December 19, 2023. [[https://tpwd.maps.arcgis.com/apps/webappviewer/index.html?id=644a45d5b75b4881b1fbb6c42bdd09d4]]. Wu, Zhongin, James R. Tweedley, Neil R. Loneragan, Xiumei Zhang. 2019. Artificial reefs can mimic natural habitats for fish and macroinvertebrates in temperate coastal waters of the Yellow Sea. Ecological Engineering, vol 139. [[https://doi.org/10.1016/j.ecoleng.2019.08.009]].