gov.noaa.nodc:0286986 eng utf8 model NOAA National Centers for Environmental Information ncei.info@noaa.gov https://www.ncei.noaa.gov/contact HTTPS NOAA Contact Information Information for contacts at NCEI. information custodian 2025-12-16T13:15:36Z ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) NCCOS Assessment: An Aquaculture Opportunity Atlas for the Southern California Bight (NCEI Accession 0286986) 2024-02-01 publication 2024-01-08 creation International DOI Foundation (IDF) 10.25921/x1c5-2191 NOAA National Centers for Environmental Information gov.noaa.nodc:0286986 NCEI Archive Management System 0286986 NOAA National Centers for Environmental Information ncei.info@noaa.gov https://www.ncei.noaa.gov/contact HTTPS NCEI Contact Information Information for contacts at NCEI. information publisher NOAA National Centers for Coastal Ocean Science (NCCOS) https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information resourceProvider Kenneth Riley NOAA National Centers for Coastal Ocean Science (NCCOS) ken.riley@noaa.gov https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information principalInvestigator Kenneth Riley NOAA National Centers for Coastal Ocean Science (NCCOS) ken.riley@noaa.gov https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information pointOfContact NOAA National Centers for Coastal Ocean Science (NCCOS) NCCOS Data Manager nccos.data@noaa.gov https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information pointOfContact Lisa Wickliffe NOAA National Centers for Coastal Ocean Science (NCCOS) https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information collaborator Jonathan Jossart NOAA National Centers for Coastal Ocean Science (NCCOS) https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information collaborator Jonathan MacKay NOAA National Centers for Coastal Ocean Science (NCCOS) https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information collaborator Alyssa Randall NOAA National Centers for Coastal Ocean Science (NCCOS) https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information collaborator James Morris, Jr. NOAA National Centers for Coastal Ocean Science (NCCOS) https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information collaborator James Morris, Jr. NOAA National Centers for Coastal Ocean Science (NCCOS) james.morris@noaa.gov https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information principalInvestigator James Morris, Jr. NOAA National Centers for Coastal Ocean Science (NCCOS) james.morris@noaa.gov https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information pointOfContact Morris, Jr., James A. NOAA National Centers for Coastal Ocean Science https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information author MacKay, Jonathan K. NOAA National Centers for Coastal Ocean Science https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information author Jossart, Jonathan A. NOAA National Centers for Coastal Ocean Science https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information author Wickliffe, Lisa C. NOAA National Centers for Coastal Ocean Science https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information author Randall, Alyssa L. NOAA National Centers for Coastal Ocean Science https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information author Riley, Kenneth L. NOAA National Centers for Coastal Ocean Science https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information author NOAA National Centers for Coastal Ocean Science (NCCOS) https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information contributor tableDigital Shapefiles of the Aquaculture Opportunity Area (AOA) study developed during 2021 for the Southern California Bight. Included in this dataset are: (1) Study areas in the Southern California Bight developed based on depth and jurisdictional boundaries. Four study areas were identified (North, Central North, Central South, South). (2) Suitability modeling results for the North, Central North, Central South, and South Southern California Bight study areas are presented as categories (“Unsuitable,” “Low,” “Moderate,” “High”) (3) High-High clusters (HH) from the Aquaculture Opportunity Atlas for Southern California. Clusters were identified within each of the four study areas (North, Central North, Central South, and South). (4) Refined High-High clusters (HH) from the Aquaculture Opportunity Atlas for Southern California. Clusters were identified within each of the four study areas (North, Central North, Central South, and South). (5) Options from the Aquaculture Opportunity Atlas for Southern California. Options were identified within two of the study areas, North and Central North. Planning and siting for marine aquaculture operations requires thorough synthesis and spatial analyses of critical environmental data and ocean space use conflicts. This dataset is to aid with visualization of aquaculture opportunity areas (AOAs) suitability model in the Southern California Bight. (1) Study Areas: Study areas (North, Central North, Central South, South) were needed due to the geographical breaks and so AOA options could be identified. Study areas were developed based on depth and jurisdictional boundaries. (2) Suitability Models: This dataset is to aid with visualization of aquaculture opportunity areas (AOAs) suitability model in the Southern California Bight. (3) High-High Clusters: This dataset is an intermediate product used to set the bounds for further analysis to identify options of potential aquaculture opportunity areas (AOAs) in the Southern California Bight. A cluster analysis was performed for each of the four study areas (North, Central North, Central South, and South) and only those clusters larger than 500 acres (the minimum size for an AOA) are presented here. (4) High-High Clusters Refined: This dataset is an intermediate product used to set the bounds for further analysis to identify options of potential aquaculture opportunity areas (AOAs) in the Southern California Bight. A cluster analysis was performed for each of the four study areas (North, Central North, Central South, and South) and only those clusters larger than 500 acres (the minimum size for an AOA) and can accommodate a square 500 acre site are presented here. (5) AOA Options: This dataset is the options of potential aquaculture opportunity areas (AOAs) in the Southern California Bight. Options between 500 and 2,000 acres were identified through the spatial planning process and will be further analyzed in a NEPA process. Funding Agency: NOAA Office of Aquaculture Funding Agency: US DOE; Advanced Research Projects Agency-Energy (ARPA-e), Macroalgae Research Inspiring Novel Energy Resources (MARINER) Funding Agency: NOAA National Centers for Coastal Ocean Science NCCOS Partners: NOAA NMFS Office of Aquaculture NCCOS Project: Tool to Forecast the Effect of Waves on Waterbodies and Shorelines completed historicalArchive NOAA National Centers for Environmental Information ncei.info@noaa.gov https://www.ncei.noaa.gov/contact HTTPS NCEI Contact Information Information for contacts at NCEI. information pointOfContact asNeeded https://www.ncei.noaa.gov/access/metadata/landing-page/bin/gfx?id=gov.noaa.nodc:0286986 Preview graphic PNG 0286986 NCEI ACCESSION NUMBER 2023-03-03 publication DEPTH - OBSERVATION harmful algal blooms (HABs) theme NODC DATA TYPES THESAURUS visual analysis instrument NODC INSTRUMENT TYPES THESAURUS model output theme NODC OBSERVATION TYPES THESAURUS NOAA National Centers for Coastal Ocean Science dataCentre NODC COLLECTING INSTITUTION NAMES THESAURUS NOAA National Centers for Coastal Ocean Science dataCentre NODC SUBMITTING INSTITUTION NAMES THESAURUS Coastal Waters of California North Pacific Ocean place NODC SEA AREA NAMES THESAURUS oceanography theme WMO_CategoryCode 2012-09-15 publication DOC/NOAA/NOS/NCCOS > National Centers for Coastal Ocean Science, National Ocean Service, NOAA, U.S. Department of Commerce dataCentre Global Change Master Directory (GCMD) Data Center Keywords 2026 revision 24 Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA) Greenbelt MD https://forum.earthdata.nasa.gov/app.php/tag/GCMD%2BKeywords HTTPS GCMD Keyword Forum Page Global Change Master Directory (GCMD). 2025. GCMD Keywords, Version 21. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords information custodian NCCOS Project: An Aquaculture Opportunity Area Atlas for the Southern California Bight NCCOS Project:Aquaculture Opportunity Areas for Federal Waters of the United States Exclusive Economic Zone project NCCOS Project Names EARTH SCIENCE > OCEANS > AQUATIC SCIENCES > AQUACULTURE EARTH SCIENCE > OCEANS > WATER QUALITY > ALGAL BLOOMS > HARMFUL ALGAL BLOOM (HABs) theme Global Change Master Directory (GCMD) Science Keywords 2026 revision 24 Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA) Greenbelt MD https://forum.earthdata.nasa.gov/app.php/tag/GCMD%2BKeywords HTTPS GCMD Keyword Forum Page Global Change Master Directory (GCMD). 2025. GCMD Keywords, Version 21. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords information custodian Marine Spatial Ecology > Coastal Aquaculture Siting and Sustainability theme NCCOS Research Areas Geospatial theme NCCOS Research Data Types Aquaculture Marine aquaculture Marine spatial planning Offshore aquaculture Option Location and Areal Extent Spatial planning theme Provider Keywords Models/Analyses > Data Analyses > Environmental Modeling instrument Provider Instruments OCEAN > PACIFIC OCEAN > NORTH PACIFIC OCEAN place Global Change Master Directory (GCMD) Location Keywords 2026 revision 24 Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA) Greenbelt MD https://forum.earthdata.nasa.gov/app.php/tag/GCMD%2BKeywords HTTPS GCMD Keyword Forum Page Global Change Master Directory (GCMD). 2025. GCMD Keywords, Version 21. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords information custodian Waterbodies > Pacific Ocean place NCCOS Regions of Study Santa Barbara Channel Santa Monica Bay Southern California Bight place Provider Place Names U3LNX6 Send2NCEI Submission Package ID accessLevel: public otherRestrictions Cite as: Morris, Jr., James A.; MacKay, Jonathan K.; Jossart, Jonathan A.; Wickliffe, Lisa C.; Randall, Alyssa L.; Riley, Kenneth L. (2024). NCCOS Assessment: An Aquaculture Opportunity Atlas for the Southern California Bight (NCEI Accession 0286986). [indicate subset used]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.25921/x1c5-2191. Accessed [date]. Distribution liability: NOAA and NCEI make no warranty, expressed or implied, regarding these data, nor does the fact of distribution constitute such a warranty. NOAA and NCEI cannot assume liability for any damages caused by any errors or omissions in these data. If appropriate, NCEI can only certify that the data it distributes are an authentic copy of the records that were accepted for inclusion in the NCEI archives. otherRestrictions Use liability: NOAA and NCEI cannot provide any warranty as to the accuracy, reliability, or completeness of furnished data. Users assume responsibility to determine the usability of these data. The user is responsible for the results of any application of this data for other than its intended purpose. NCCOS Project: An Aquaculture Opportunity Area Atlas for the Southern California Bight 2023 publication https://coastalscience.noaa.gov/data_reports/an-aquaculture-opportunity-area-atlas-for-the-southern-california-bight/ https://coastalscience.noaa.gov/data_reports/an-aquaculture-opportunity-area-atlas-for-the-southern-california-bight/ HTTPS https://coastalscience.noaa.gov/data_reports/an-aquaculture-opportunity-area-atlas-for-the-southern-california-bight/ NCCOS Project Page information crossReference Tool to Forecast the Effect of Waves on Waterbodies and Shorelines 2005 publication https://coastalscience.noaa.gov/project/tool-forecast-effect-waves-waterbodies-shorelines/ HTTPS https://coastalscience.noaa.gov/project/tool-forecast-effect-waves-waterbodies-shorelines/ National Centers for Coastal Ocean Science (NCCOS) project page information NOAA National Centers for Coastal Ocean Science (NCCOS) https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information publisher documentDigital crossReference project Aquaculture Opportunity Areas for Federal Waters of the United States Exclusive Economic Zone 2020 publication https://coastalscience.noaa.gov/project/aquaculture-opportunity-areas-for-federal-waters-of-the-united-states-exclusive-economic-zone/ HTTPS https://coastalscience.noaa.gov/project/aquaculture-opportunity-areas-for-federal-waters-of-the-united-states-exclusive-economic-zone/ National Centers for Coastal Ocean Science (NCCOS) project page information NOAA National Centers for Coastal Ocean Science (NCCOS) https://coastalscience.noaa.gov/ HTTPS NOAA National Centers for Coastal Ocean Science (NCCOS) website Institution web page information publisher documentDigital crossReference project Morris Jr, J. A. (2021). An Aquaculture Opportunity Area Atlas for the Southern California Bight. National Centers for Coastal Ocean Science (U.S.). https://doi.org/10.25923/tmx9-ex26 2021 publication International DOI Foundation (IDF) https://doi.org/10.25923/tmx9-ex26 https://doi.org/10.25923/tmx9-ex26 HTTPS https://doi.org/10.25923/tmx9-ex26 Cited Publication information Morris Jr, James A. author National Centers for Coastal Ocean Science (U.S.) publisher documentDigital National Centers for Coastal Ocean Science (U.S.) crossReference Bovee, K.D. Development and evaluation of habitat suitability criteria for use in the instream flow incremental methodology.https://pubs.er.usgs.gov/publication/70121265 1986 publication https://pubs.er.usgs.gov/publication/70121265 https://pubs.er.usgs.gov/publication/70121265 HTTPS https://pubs.er.usgs.gov/publication/70121265 Cited Publication information Bovee, K.D. author U.S. Fish and Wildlife Service publisher documentDigital Instream Flow Information Paper 21, Report 86(7) crossReference Bwadi, B. E., Mustafa, F. B., Ali, M. L., & Bhassu, S. (2018). Spatial analysis of water quality and its suitability in farming giant freshwater prawn (Macrobrachium rosenbergii) in Negeri Sembilan region, Peninsular Malaysia. Singapore Journal of Tropical Geography, 40(1), 71–91. https://doi.org/10.1111/sjtg.12250 2018-07-10 publication International DOI Foundation (IDF) https://doi.org/10.1111/sjtg.12250 https://doi.org/10.1111/sjtg.12250 HTTPS https://doi.org/10.1111/sjtg.12250 Cited Publication information Bwadi, Benjamin Ezekiel Department of Geography University of Malaya Malaysia author Mustafa, Firuza Begham Department of Geography University of Malaya Malaysia author Ali, Mohammad Lokman Institute of Biological Science, Division of Genetics and Molecular Biology and Centre of Biotechnology for Agriculture, CEBAR University of Malaya Malaysia author Bhassu, Subha Institute of Biological Science, Division of Genetics and Molecular Biology and Centre of Biotechnology for Agriculture, CEBAR University of Malaya Malaysia author Wiley publisher documentDigital Singap J Trop Geogr 40(1) ISSN 0129-7619, ISSN 1467-9493, pp. 71-91 crossReference Gimpel, A., Stelzenmüller, V., Töpsch, S., Galparsoro, I., Gubbins, M., Miller, D., Murillas, A., Murray, A. G., Pınarbaşı, K., Roca, G., & Watret, R. (2018). A GIS-based tool for an integrated assessment of spatial planning trade-offs with aquaculture. Science of The Total Environment, 627, 1644–1655. https://doi.org/10.1016/j.scitotenv.2018.01.133 2018-06 publication International DOI Foundation (IDF) https://doi.org/10.1016/j.scitotenv.2018.01.133 https://doi.org/10.1016/j.scitotenv.2018.01.133 HTTPS https://doi.org/10.1016/j.scitotenv.2018.01.133 Cited Publication information Gimpel, Antje author Stelzenmüller, Vanessa author Töpsch, Sandra author Galparsoro, Ibon author Gubbins, Matthew author Miller, David author Murillas, Arantza author Murray, Alexander G. author Pınarbaşı, Kemal author Roca, Guillem author Watret, Robert author Elsevier BV publisher documentDigital Science of The Total Environment 627 ISSN 0048-9697, pp. 1644-1655 crossReference Kapetsky, J.M., J. Aguilar-Manjarrez, and J. Jenness. 2013. A global assessment of potential for offshore mariculture development from a spatial perspective. FAO Fisheries and Aquaculture Technical Paper No. 549. Rome: FAO. https://www.fao.org/3/i3100e/i3100e.pdf 2013 publication https://www.fao.org/3/i3100e/i3100e.pdf https://www.fao.org/3/i3100e/i3100e.pdf HTTPS https://www.fao.org/3/i3100e/i3100e.pdf Cited Publication information Kapetsky, J.M. author Aguilar-Manjarrez, J. author Jenness, J. author documentDigital FAO Fisheries and Aquaculture Technical Paper No. 549. Rome: FAO. crossReference Longdill, P. C., Healy, T. R., & Black, K. P. (2008). An integrated GIS approach for sustainable aquaculture management area site selection. Ocean & Coastal Management, 51(8–9), 612–624. https://doi.org/10.1016/j.ocecoaman.2008.06.010 2008-01 publication International DOI Foundation (IDF) https://doi.org/10.1016/j.ocecoaman.2008.06.010 https://doi.org/10.1016/j.ocecoaman.2008.06.010 HTTPS https://doi.org/10.1016/j.ocecoaman.2008.06.010 Cited Publication information Longdill, Peter C. author Healy, Terry R. author Black, Kerry P. author Elsevier BV publisher documentDigital Ocean & Coastal Management 51(8-9) ISSN 0964-5691, pp. 612-624 crossReference Muñoz-Mas, R., Martínez-Capel, F., Schneider, M., & Mouton, A. M. (2012). Assessment of brown trout habitat suitability in the Jucar River Basin (SPAIN): Comparison of data-driven approaches with fuzzy-logic models and univariate suitability curves. Science of The Total Environment, 440, 123–131. https://doi.org/10.1016/j.scitotenv.2012.07.074 2012-12 publication International DOI Foundation (IDF) https://doi.org/10.1016/j.scitotenv.2012.07.074 https://doi.org/10.1016/j.scitotenv.2012.07.074 HTTPS https://doi.org/10.1016/j.scitotenv.2012.07.074 Cited Publication information Muñoz-Mas, Rafael author Martínez-Capel, Francisco author Schneider, Matthias author Mouton, Ans M. author Elsevier BV publisher documentDigital Science of The Total Environment 440 ISSN 0048-9697, pp. 123-131 crossReference Radiarta, I. N., Saitoh, S.-I., & Miyazono, A. (2008). GIS-based multi-criteria evaluation models for identifying suitable sites for Japanese scallop (Mizuhopecten yessoensis) aquaculture in Funka Bay, southwestern Hokkaido, Japan. Aquaculture, 284(1–4), 127–135. https://doi.org/10.1016/j.aquaculture.2008.07.048 2008-11 publication International DOI Foundation (IDF) https://doi.org/10.1016/j.aquaculture.2008.07.048 https://doi.org/10.1016/j.aquaculture.2008.07.048 HTTPS https://doi.org/10.1016/j.aquaculture.2008.07.048 Cited Publication information Radiarta, I Nyoman author Saitoh, Sei-Ichi author Miyazono, Akira author Elsevier BV publisher documentDigital Aquaculture 284(1-4) ISSN 0044-8486, pp. 127-135 crossReference Silva, C., Ferreira, J. G., Bricker, S. B., DelValls, T. A., Martín-Díaz, M. L., & Yáñez, E. (2011). Site selection for shellfish aquaculture by means of GIS and farm-scale models, with an emphasis on data-poor environments. Aquaculture, 318(3–4), 444–457. https://doi.org/10.1016/j.aquaculture.2011.05.033 2011-08 publication International DOI Foundation (IDF) https://doi.org/10.1016/j.aquaculture.2011.05.033 https://doi.org/10.1016/j.aquaculture.2011.05.033 HTTPS https://doi.org/10.1016/j.aquaculture.2011.05.033 Cited Publication information Silva, C. author Ferreira, J.G. author Bricker, S.B. author DelValls, T.A. author Martín-Díaz, M.L. author Yáñez, E. author Elsevier BV publisher documentDigital Aquaculture 318(3-4) ISSN 0044-8486, pp. 444-457 crossReference Anselin, L. (1995). Local Indicators of Spatial Association—LISA. Geographical Analysis, 27(2), 93–115. https://doi.org/10.1111/j.1538-4632.1995.tb00338.x 1995-04 publication International DOI Foundation (IDF) https://doi.org/10.1111/j.1538-4632.1995.tb00338.x https://doi.org/10.1111/j.1538-4632.1995.tb00338.x HTTPS https://doi.org/10.1111/j.1538-4632.1995.tb00338.x Cited Publication information Anselin, Luc author Wiley publisher documentDigital Geographical Analysis 27(2) ISSN 0016-7363, ISSN 1538-4632, pp. 93-115 crossReference Esri. 2021a. ArcGIS Pro: Release 2.8.0. Redlands, CA: Environmental Systems Research Institute.https://www.esri.com/about/newsroom/announcements/esri-releases-arcgis-pro-book-updated-for-version-2-8/ 2021 publication https://www.esri.com/about/newsroom/announcements/esri-releases-arcgis-pro-book-updated-for-version-2-8/ https://www.esri.com/about/newsroom/announcements/esri-releases-arcgis-pro-book-updated-for-version-2-8/ HTTPS https://www.esri.com/about/newsroom/announcements/esri-releases-arcgis-pro-book-updated-for-version-2-8/ Cited Publication information Esri publisher crossReference Esri. 2021b. What is a z-score? What is a p-value? Esri ArcGIS Pro online. https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-statistics/what-is-a-z-score-what-is-a-p-value.htm 2021 publication https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-statistics/what-is-a-z-score-what-is-a-p-value.htm https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-statistics/what-is-a-z-score-what-is-a-p-value.htm HTTPS https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-statistics/what-is-a-z-score-what-is-a-p-value.htm Cited Publication information Esri publisher crossReference NCCOS Assessment: An Aquaculture Opportunity Atlas for the U.S. Gulf of Mexico. 2023. Riley, Kenneth L., Wickliffe, Lisa C., Jossart, Jonathan A., MacKay, Jonathan K., Randall, Alyssa L., Morris, Jr., James A. NOAA National Centers for Coastal Ocean Science. Dataset. https://coastalscience.noaa.gov/data_reports/an-aquaculture-opportunity-area-atlas-for-the-u-s-gulf-of-mexico/ 2023 publication https://coastalscience.noaa.gov/data_reports/an-aquaculture-opportunity-area-atlas-for-the-u-s-gulf-of-mexico/ HTTPS https://coastalscience.noaa.gov/data_reports/an-aquaculture-opportunity-area-atlas-for-the-u-s-gulf-of-mexico/ Data Source information Riley, Kenneth L. author Wickliffe, Lisa C. author Jossart, Jonathan A. author MacKay, Jonathan K. author Randall, Alyssa L. author Morris, Jr., James A. author NOAA National Centers for Environmental Information publisher crossReference eng; USA utf8 environment oceans -120.450994 -117.183297 32.518165 34.422305 2021-10-01 2021-10-18 Methods: (1) Study Areas: Study areas (North, Central North, Central South, South) in the Southern California Bight were needed due to the geographical breaks so Aquaculture Opportunity Area (AOA) options could be identified. Study areas were developed based on depth and jurisdictional boundaries. Step 1.1: Federal waters off Southern California, south of Point Conception to the U.S. and Mexico border, were selected as one of the first regions for AOA evaluation because of preexisting spatial data availability, previous analyses in the region, and industry interest in developing sustainable offshore aquaculture operations. Step 1.2: NOAA further narrowed the AOA site selection criteria in Southern California using a combination of spatial mapping approaches, scientific review, and stakeholder input. As described above, the Southern California AOA area of interest includes federal waters between 5.6 km (3.0 nautical miles [nm]) and 46.3 km (25.0 nm) offshore within the EEZ at depths ranging between 10 m (32.8 ft) and 150 m (492.1 ft). (2) Suitability Models: Planning and siting for marine aquaculture operations requires thorough synthesis and spatial analyses of critical environmental data and ocean space use conflicts (Kapetsky et al. 2013). This dataset is to aid with visualization of aquaculture opportunity areas (AOAs) suitability model in the Southern California Bight. A gridded relative suitability analysis, commonly used in a Multi-Criteria Decision Analysis (MCDA), was performed to identify the grid cells with the highest suitability for aquaculture development in the study areas (Longdill et al. 2008; Radiarta et al. 2008; Gimpel et al. 2015; Bwadi et al. 2019). Spatial data layers included in the suitability analysis identify space-use conflicts and environmental constraints such as active national security areas, maritime navigation, ocean industries, and natural resource management. We utilized a submodel structure to capture ocean use and conservation concerns including national security; natural and cultural resources; industry, navigation, and transportation; and aquaculture and fishing. Data layers with no compatibility with aquaculture development (e.g., shipping fairways) were captured in the list of incompatible constraints and removed from further analysis due to known incompatibility with aquaculture. This model structure ensures that each submodel is given equal representation in the overall suitability model regardless of how many data layers are present in each submodel. The geometric mean of the four submodels (i.e., national security; industry, navigation, and transportation; natural and cultural resources; fishing and aquaculture) was used to calculate an overall suitability score. The geometric mean #(Equation 1) was chosen because it grants equal importance to each variable (Bovee 1986; Longdill et al. 2008; Silva et al. 2011; Muñoz-Mas et al. 2012). Furthermore, all data layers and submodels had equal weight within the suitability model. Equation 1. Step 2.1: 1. A suitability polygon with a 4.05 ha (10 ac) hexagonal grid was created using the extent of the created study area polygons (North, Central North, Central South, South; see Step 1.2), which was only in the US Federal waters of the Southern California Bight and at depths between 10 and 150 m. Step 2.2: Each data layer was scored on a 0 to 1 scale, with scores approaching 0 representing low suitability and 1 representing high suitability relative to the other grid cells for aquaculture. Any grid that contained a data layer with a 0 score (i.e., constraints data layer) was deemed unsuitable for aquaculture, and not considered further in the analysis. Next, an overall suitability score was calculated for each submodel (i.e., national security; industry, navigation, and transportation; natural and cultural resources; fishing and aquaculture) by taking the geometric mean of all scores within each grid cell. Scoring rationale for both categorical and continuous data can be seen in Appendix C of Riley et al. 2021. The geometric mean of the four submodels was used to calculate an overall suitability score. Step 2.3: Suitability scores are presented as categories (“Unsuitable,” “Low,” “Moderate,” “High”) grouped by quantiles of the calculated scores, with all scores of 0 being in the “Unsuitable” category and represented by the color red. Within the suitability submodel and overall model maps, standardized colors were used to depict categories, with orange representing “Low,” yellow “Moderate,” and blue “High” suitability and coinciding with each proportion of quantile values. With all suitability maps, relative categories still represent values ranging from 0 to 1, with the “Low” category representing the lowest quantile of the data, “Moderate” the middle quantile, and “High” the upper quantile. Presenting categories rather than actual suitability scores simplified interpretation of results and provided optimal contrast among categories. Distribution of scores varies among the suitability submodels (e.g., number of data layers, score range of data distribution depicted); for example, in one submodel a score of 0.5 could be classified as “High,” while in another submodel or region a score of 0.5 could be “Low” because the scores are relative. Thus, suitability scores among the different study areas and different submodels should not be compared, as the score is unique to each study area and submodel. (3) High-High Clusters: Step 3.1: A Local Index of Spatial Association (LISA) analysis, which identifies statistically significant clusters and outliers, was performed on the final relative suitability modeling results (Anselin 1995). All grid cells with a score of 0 were not included in the cluster analysis, as these areas are unsuitable for aquaculture and are not considered further. The ArcGIS Pro Cluster and Outlier Analysis tool was used to implement the LISA analysis (Esri 2021a). The fixed-distance spatial conceptualization was utilized within this analysis as it allows the identification of localized clusters. The function inputs were a 250-m search distance and 9,999 iterations with row standardization and a false discovery rate correction applied to allow for more conservative results by estimating the number of false positives for a given confidence level, adjusting the critical p-value accordingly (Esri 2021b). Statistically significant clusters (p < 0.05) of the highest suitable scores (i.e., high-high clusters) were identified, with any clusters smaller than 202 ha (500 ac) excluded, as this was the minimum AOA target size. Anselin L. 1995. Local Indicators of Spatial Association—LISA. Geog Anal. 27(2):93–115. Esri. 2021a. ArcGIS Pro: Release 2.8.0. Redlands, CA: Environmental Systems Research Institute. Esri. 2021b. What is a z-score? What is a p-value? Esri ArcGIS Pro online. Available from: https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-statistics/what-is-a-z-score-what-is-a-p-value.htm (4) Refined High-High Clusters: Step 4.1: A Local Index of Spatial Association (LISA) analysis, which identifies statistically significant clusters and outliers, was performed on the final relative suitability modeling results (Anselin 1995). All grid cells with a score of 0 were not included in the cluster analysis, as these areas are unsuitable for aquaculture and are not considered further. The ArcGIS Pro Cluster and Outlier Analysis tool was used to implement the LISA analysis (Esri 2021a). The fixed-distance spatial conceptualization was utilized within this analysis as it allows the identification of localized clusters. The function inputs were a 250-m search distance and 9,999 iterations with row standardization and a false discovery rate correction applied to allow for more conservative results by estimating the number of false positives for a given confidence level, adjusting the critical p-value accordingly (Esri 2021b). Statistically significant clusters (p < 0.05) of the highest suitable scores (i.e., high-high clusters) were identified, with any clusters smaller than 202 ha (500 ac) excluded, as this was the minimum AOA target size. Next multiple iterations of a 500 acre square site were fit within this shape and dissolved to create the final shape used for the precision siting model. Anselin L. 1995. Local Indicators of Spatial Association—LISA. Geog Anal. 27(2):93–115. Esri. 2021a. ArcGIS Pro: Release 2.8.0. Redlands, CA: Environmental Systems Research Institute. Esri. 2021b. What is a z-score? What is a p-value? Esri ArcGIS Pro online. Available from: https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-statistics/what-is-a-z-score-what-is-a-p-value.htm (5) AOA Options: Step 5. 1: The first step in the precision siting model evaluated the high-high cluster output from the LISA cluster analysis and refined each cluster to accommodate at minimum a square option that is 500 ac (i.e., the minimum AOA size requirement). For each of those clusters, an iterative process was developed, where the first iteration was to identify every possible location accommodating a square that is 2,000 ac. Next, all remaining areas within that cluster were examined to determine if additional square options less than 2,000 ac could be placed. Using 500-ac increments, three further iterations were run using 1,500 ac, 1,000 ac, and 500 ac to identify any additional areas within each cluster. Larger size options were prioritized over smaller options, as increased size would support more farms, space to optimally configure farming locations, and maximum flexibility in mooring configurations. However, it is important to note that size was not considered when ranking the options in the next parts of the precision siting model. All potential options identified within a single high-high cluster were ranked using the within-cluster model, which is structured to identify the highest suitable option according to closest proximity to an inlet, lowest relative fishing effort, and lowest relative vessel traffic. The data within these three submodels of the within-cluster model were rescaled using a 0 to 1 range, with 0 being less suitable for aquaculture and 1 being more suitable for aquaculture. This is the same method used in the suitability model; however, it is important to note that the rescaling is performed for the data in each individual cluster in the within-cluster model. File Information: 10.8 MB total, 79 files in 9 folders (unzipped) Data File Format(s): ShapeFile .SHP and ancillary files Data File Compression: none Data File Resolution: none GIS Projection: Projected Coordinate System: NAD 1983 (2011) California (Teale) Albers (Meters) WKID 6414 / Geographic Coordinate System: NAD 1983 (2011) WKID 6318 and WGS 1984 WKID 4326 NOAA National Centers for Environmental Information +1-301-713-3277 ncei.info@noaa.gov pointOfContact In most cases, electronic downloads of the data are free. However, fees may apply for custom orders, data certifications, copies of analog materials, and data distribution on physical media. Contact NCEI for other distribution options and instructions. Shapefile 5.444 https://doi.org/10.25921/x1c5-2191 HTTPS Web browser NCEI Dataset Landing Page Navigate directly to the URL for a descriptive web page with download links. information https://www.ncei.noaa.gov/archive/accession/oas/286986 HTTPS Web browser Descriptive Information Navigate directly to the URL for a descriptive web page with download links. information https://www.ncei.noaa.gov/archive/accession/download/286986 HTTPS Web browser HTTPS Navigate directly to the URL for data access and direct download. download ftp://ftp-oceans.ncei.noaa.gov/nodc/archive/arc0222/0286986/ FTP Any FTP client FTP These data are available through the File Transfer Protocol (FTP). FTP is no longer supported by most internet browsers. You may copy and paste the FTP link to the data into an FTP client (e.g., FileZilla or WinSCP). download dataset NCEI Accession 0286986 v1.1 was published. 2024-02-01T19:10:58Z NCEI Accession 0286986 v1.1 publication https://www.ncei.noaa.gov/archive/accession/0286986/1.1 HTTPS NCEI Accession 0286986 v1.1 published 2024-02-01T19:10:58Z download model Parameter or Variable: Option Location and Areal Extent (measured); Units: acre; Observation Category: model output; Sampling Instrument: Models/Analyses > Data Analyses > Environmental Modeling; Sampling and Analyzing Method: Federal waters off Southern California, south of Point Conception to the U.S. and Mexico border, were selected as one of the first regions for AOA evaluation because of preexisting spatial data availability, previous analyses in the region, and industry interest in developing sustainable offshore aquaculture operations. NOAA further narrowed the AOA site selection criteria in Southern California using a combination of spatial mapping approaches, scientific review, and stakeholder input. As described above, the Southern California AOA area of interest includes federal waters between 5.6 km (3.0 nautical miles [nm]) and 46.3 km (25.0 nm) offshore within the EEZ at depths ranging between 10 m (32.8 ft) and 150 m (492.1 ft).; Data Quality Method: For more details, see Riley et al. 2021. asNeeded Metadata are developed, maintained and distributed by NCEI. Updates are performed as needed to maintain currentness. NOAA National Centers for Environmental Information custodian visual analysis visual analysis visual analysis and measurement of sample materials use visual analysis with observation types of visual estimate and/or visual observation