An environmental classification developed in conjunction with the NSW Marine Parks Authority Research Committee. For more information see: Breen D.A. and R.P. Avery. (2002). Broad-scale biodiversity assessment of the Manning Shelf marine bioregion. Draft final report for the NSW Marine Parks Authority. Copies of the report may be borrowed from the library: Environment Australia, GPO Box 787, Canberra ACT 2601 Australia. This coverage is intended for used in regional level marine conservation assessment. It was prepared using very low cost techniques (ie. unrectified API) and should not be relied upon for navigation purposes. This record describes the environmental classification of the four ocean ocean ecosystems classified by depth. The full study also describes classes for each of the five major estuary ecosystems, and nine habitat surrogates.

An environmental classification developed in conjunction with the NSW Marine Parks Authority Research Committee. For more information see: Breen D.A. and R.P. Avery. (2002). Broad-scale biodiversity assessment of the Manning Shelf marine bioregion. Draft final report for the NSW Marine Parks Authority. Copies of the report may be borrowed from the library: Environment Australia, GPO Box 787, Canberra ACT 2601 Australia. This coverage is intended for used in regional level marine conservation assessment. It was prepared using very low cost techniques (ie. unrectified API) and should not be relied upon for navigation purposes. This represents an historic dataset providing transparency on the 2002 marine park systematic planning process. This product is one of three related datasets used in the assessment process: "NSW Ocean Ecosystems 2002", "NSW Estuarine Ecosystems 2002" & "NSW Marine Habitats 2002" This record describes classes for each of the five major estuary ecosystems. The full study also describes the environmental classification of the four ocean ocean ecosystems classified by depth, and nine habitat surrogates.

An environmental classification developed in conjunction with the NSW Marine Parks Authority Research Committee. For more information see: Breen D.A. and R.P. Avery. (2002). Broad-scale biodiversity assessment of the Manning Shelf marine bioregion. Draft final report for the NSW Marine Parks Authority. Copies of the report may be borrowed from the library: Environment Australia, GPO Box 787, Canberra ACT 2601 Australia. This coverage is intended for used in regional level marine conservation assessment. It was prepared using very low cost techniques (ie. unrectified API) and should not be relied upon for navigation purposes. This represents an historic dataset providing transparency on the 2002 marine park systematic planning process. This product is one of three related datasets used in the assessment process: "NSW Ocean Ecosystems 2002", "NSW Estuarine Ecosystems 2002" & "NSW Marine Habitats 2002" This record describes the environmental classification of nine habitat surrogates (mangrove, seagrass, saltmarsh, subtidal sediment, beach, intertidal rocky shore, subtidal reef and island). The full study also describes classes for each of the five major estuary ecosystems, and the four ocean ecosystems classified by depth.

In order to design a representative network of high seas marine protected areas (MPAs), an acceptable scheme is required to classify the benthic bioregions of the oceans. Given the lack of sufficient biological information to accomplish this task, we used a multivariate statistical method with 6 biophysical variables (depth, seabed slope, sediment thickness, primary production, bottom water dissolved oxygen and bottom temperature) to objectively classify the ocean floor into 11 different categories, comprised of 53,713 separate polygons, that we have termed "seascapes". Validation of the seascape classification was carried out by comparing the seascapes with an existing map of seafloor geomorphology, and by GIS analysis of the number of separate polygons and perimeter/area ratio. We conclude that seascapes, derived using a multivariate statistical approach, are biophysically meaningful subdivisions of the ocean floor and can be expected to contain different biological associations, in as much as different geomorphological units do the same. Our study illustrates how the identification of potential sites for high seas marine protected areas can be accomplished by GIS analysis of seafloor geomorphic and seascape classification maps. Using this approach, maps of seascape and geomorphic heterogeneity were generated in which heterogeneity hot-spots identify themselves as MPA candidates. The use of computer-aided mapping tools removes subjectivity in the MPA design process and provides greater confidence to stakeholders that an unbiased result has been achieved.

In order to design a representative network of high seas marine protected areas (MPAs), an acceptable scheme is required to classify the benthic bioregions of the oceans. Given the lack of sufficient biological information to accomplish this task, we used a multivariate statistical method with 6 biophysical variables (depth, seabed slope, sediment thickness, primary production, bottom water dissolved oxygen and bottom temperature) to objectively classify the ocean floor into 11 different categories, comprised of 53,713 separate polygons, that we have termed "seascapes". Validation of the seascape classification was carried out by comparing the seascapes with an existing map of seafloor geomorphology, and by GIS analysis of the number of separate polygons and perimeter/area ratio. We conclude that seascapes, derived using a multivariate statistical approach, are biophysically meaningful subdivisions of the ocean floor and can be expected to contain different biological associations, in as much as different geomorphological units do the same. Our study illustrates how the identification of potential sites for high seas marine protected areas can be accomplished by GIS analysis of seafloor geomorphic and seascape classification maps. Using this approach, maps of seascape and geomorphic heterogeneity were generated in which heterogeneity hot-spots identify themselves as MPA candidates. The use of computer-aided mapping tools removes subjectivity in the MPA design process and provides greater confidence to stakeholders that an unbiased result has been achieved.

In order to design a representative network of high seas marine protected areas (MPAs), an acceptable scheme is required to classify the benthic bioregions of the oceans. Given the lack of sufficient biological information to accomplish this task, we used a multivariate statistical method with 6 biophysical variables (depth, seabed slope, sediment thickness, primary production, bottom water dissolved oxygen and bottom temperature) to objectively classify the ocean floor into 11 different categories, comprised of 53,713 separate polygons, that we have termed "seascapes". Validation of the seascape classification was carried out by comparing the seascapes with an existing map of seafloor geomorphology, and by GIS analysis of the number of separate polygons and perimeter/area ratio. We conclude that seascapes, derived using a multivariate statistical approach, are biophysically meaningful subdivisions of the ocean floor and can be expected to contain different biological associations, in as much as different geomorphological units do the same. Our study illustrates how the identification of potential sites for high seas marine protected areas can be accomplished by GIS analysis of seafloor geomorphic and seascape classification maps. Using this approach, maps of seascape and geomorphic heterogeneity were generated in which heterogeneity hot-spots identify themselves as MPA candidates. The use of computer-aided mapping tools removes subjectivity in the MPA design process and provides greater confidence to stakeholders that an unbiased result has been achieved.

In order to design a representative network of high seas marine protected areas (MPAs), an acceptable scheme is required to classify the benthic bioregions of the oceans. Given the lack of sufficient biological information to accomplish this task, we used a multivariate statistical method with 6 biophysical variables (depth, seabed slope, sediment thickness, primary production, bottom water dissolved oxygen and bottom temperature) to objectively classify the ocean floor into 11 different categories, comprised of 53,713 separate polygons, that we have termed "seascapes". Validation of the seascape classification was carried out by comparing the seascapes with an existing map of seafloor geomorphology, and by GIS analysis of the number of separate polygons and perimeter/area ratio. We conclude that seascapes, derived using a multivariate statistical approach, are biophysically meaningful subdivisions of the ocean floor and can be expected to contain different biological associations, in as much as different geomorphological units do the same. Our study illustrates how the identification of potential sites for high seas marine protected areas can be accomplished by GIS analysis of seafloor geomorphic and seascape classification maps. Using this approach, maps of seascape and geomorphic heterogeneity were generated in which heterogeneity hot-spots identify themselves as MPA candidates. The use of computer-aided mapping tools removes subjectivity in the MPA design process and provides greater confidence to stakeholders that an unbiased result has been achieved.

The Seamap Australia spatial data layer is a nationally synthesised data product of seafloor marine habitat data. Australian continental shelf benthic habitat layers in GIS format were collected from various stakeholders around the country. Through compiling all of these data sets, we established a controlled vocabulary, reviewed by ANDS and external independent assessors, to produce a national classification of marine habitats. This national marine habitat classification scheme complements work undertaken by the National Environmental Science Program (NESP) Marine Biodiversity Hub (Theme D). The Seamap Australia product is of national importance and highlights the diversity of benthic habitats around our marine estate. This is the first edition of a seafloor marine habitat data layer that seamlessly brings together data from each of Australia’s state and territory marine habitat databases. Seamap Australia is a constantly evolving product as we continuously improve our skills in standardising, collating and sharing marine spatial data. This record describes a static version of the Seamap Australia national data layer as of 28/11/2018. The most current version of the data is available from the Seamap Australia website [http://seamapaustralia.org/map]. We envisage that the 'live' product will be constantly developed and updated as future surveys continue to improve our knowledge of our vast marine estate.

These data provide a baseline inventory of submerged aquatic vegetation within Long Island's South Shore bays. The data were derived from conventional-color metric film diapositives obtained in June 2002 from the New York Department of State's Division of Coastal Resources. Benthic classifications follow the System for Classification of Habitats in Estuarine and Marine Environments (SCHEME). The study area spans approximately 443 square kilometers, extending from the west end of Long Beach Island in Nassau County eastward to Heady Creek at the east end of Shinnecock Bay in Suffolk County. The creation of this baseline inventory was a critical need identified in the Comprehensive Management Plan for the Long Island South Shore Estuary Reserve. Established following the state legislature's passage of the Long Island South Shore Estuary Reserve Act in 1993, the management plan aimed to protect and improve the estuary's ecosystem, enhance public access, and support sustainable economic activities. Ultimately, the goal was to sustain existing high-quality habitats and restore degraded areas to support the productivity of commercially and ecologically important estuarine species. The management plan also mandated a long-term monitoring program to evaluate progress toward estuarine resource improvement goals, building upon this foundational benthic habitat data. The layers available within the data download include biotic, geoform, and substrate. Partners: New York Department of State's Division of Coastal Resources