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Environmental Management

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    Habitats serve a variety of functions on the North West Shelf (NWS). They support the life history stages of a diverse suite of tropical species including commercially harvested ones. In addition to natural disturbance regimes, habitats are altered in response to the sectoral uses, which in turn affects the distribution and life histories of species. Habitats thus serve as the nexus linking species with uses and natural disturbance, and different habitats serve different purposes at various stages of the life history of a species. A detailed understanding of habitats, at least at the structural level, is thus a prerequisite for a more comprehensive understanding of ecological structure and functions on the North West Shelf. This component of the North West Shelf Joint Environmental Management Study (NWSJEMS) aimed to collate and integrate data on habitats for the region of the North West Shelf extending from North West Cape to Port Hedland and from the coast to the 200 m isobath. The three main activities of the study were: Development of an integrated collection of information on habitats of the North West Shelf, including expert information; Application of the CSIRO Habitat Classification Framework to the data to determine the spatial nesting and structuring of habitat units on the North West Shelf; and Provision of the habitat structure classification for input into other models developed within NWSJEMS. This record describes data of key benthic marine ecosystems and habitats. These maps and descriptions of their component attributes were designed to assist the process modelling of the ecosystem and impacts of uses, as well as directly supporting planning and management by Western Australian agencies and industries.

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    This spatial polygon dataset is derived from the 2001 mapping of mud crab (Scylla serrata) habitats along the NT and Queensland coastal wetlands. The polygons were derived from Landsat imagery and verified with field work and is suitable for use at scale 1:100,000. The information can be used in many ways to assist the management of these habitats. It provides a suitable baseline dataset for monitoring broad scale changes in area and composition of coastal wetland communities. Additionally, it provides information required by managers for choosing representative habitats for protection.

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    This is a high resolution survey (1:5,000 scale dataset) describing mapped vegetation communities for the Ludmilla Creek catchment area (within the City of Darwin, Northern Territory). (Vegetation Unit - A reasonably homogeneous part of the land surface, distinct from surrounding terrain with constant properties in landform and vegetation) This vegetation survey was undertaken in 1996. This dataset represents the vegetation on the ground at the time of the survey and reflects the data and methods used to create the mapped polygons. The dataset has been revised in 2015 to include community descriptions but has not been updated to reflect the vegetation on the ground. The Darwin Remnant Vegetation Survey is considered a more up-to-date representation of vegetation for this area.

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    This is a collection of polygons outlining signficant seagrass meadows around Arnhem Land, Kakadu and Gulf of Carpentaria coastal waters for the Northern Australia Marine Biodiversity Survey (NAMBS) project between 2003 and 2005. Data was collected from imagery and ground truthed by observers from helicopter and insitu sample grabs.

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    This dataset provides mapping of water bodies and wetland regional ecosystems at 1:100,000 scale across Queensland.

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    This polygon spatial dataset describes the mangrove communities for Bynoe Harbour and its environs. The original field survey was undertaken in 1998 at a mapping scale of 1:25,000. The associated report notes an area of approximately 24,000 hectares of mangroves in Bynoe Harbour and describes ten main mangrove associations or communities. The data provides a basis for identifying the extent and distribution of mangrove communities for Bynoe Harbour and its environs. Mangrove mapping was updated over this area in a 2016 survey. See metadata record for Mangrove Community Mapping - Charles Point to Gunn Point. www.ntlis.nt.gov.au/metadata/export_data?type=html&metadata_id=87F656131848A609E050CD9B214417E1

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    This polygon spatial dataset describes the mangrove communities for Darwin Harbour and its environs and was surveyed at a mapping scale of 1:25 000. The associated report notes an area of approximately 20,400 hectares of mangroves in Darwin Harbour and describes ten main mangrove associations or communities. The data provides a basis for identifying the extent and distribution of mangrove communities for Darwin Harbour and its environs.

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    This dataset displays the reefs and shoals within Queensland maritime waters. The data has been compiled from numerous sources to produce a state wide coverage. Attributes within the data describe the source and reliability of the data. Data sources include: - The Great Barrier Reef Base Map - Geoscience Australia 1:250000 Topographic Mapping

  • The Marine Futures Project was designed to benchmark the current status of key Western Australian marine ecosystems, based on an improved understanding of the relationship between marine habitats, biodiversity and our use of these values. Approximately 1,500 km2 of seafloor were mapped using hydroacoustics (Reson 8101 Multibeam), and expected benthic habitats "ground-truthed" using towed video transects and baited remote underwater video systems. Both sources of information were then combined in a spatial predictive modelling framework to produce fine-scale habitat maps showing the extent of substrate types, biotic formations, etc. Surveys took place across 9 study areas, including the Capes region of southwest Western Australia. The area is one of the most diverse temperate marine environments in Australia. Warm, tropical waters of the Leeuwin Current mingle with the cool waters of the Capes Current, resulting in high finfish diversity, including tropical and temperate species, as well as internationally significant seagrass diversity with meadows occurring at depths greater than 40 metres. The region's geomorphology is complex with an array of intertidal and subtidal reef environments. Many marine plants and animals are endemic to the southern coast of Australia due to its long geographical isolation, with seagrass, algae and estuarine habitats functioning as spawning, nursery and feeding grounds for a wide range of invertebrates and fish. Significant numbers of marine mammals also frequent the area, including the blue whale, the largest of all marine creatures.

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    The spatial and temporal dynamics of seagrasses have been studied from the leaf to patch (100 m**2) scales. However, landscape scale (> 100 km**2) seagrass population dynamics are unresolved in seagrass ecology. Previous remote sensing approaches have lacked the temporal or spatial resolution, or ecologically appropriate mapping, to fully address this issue. This paper presents a robust, semi-automated object-based image analysis approach for mapping dominant seagrass species, percentage cover and above ground biomass using a time series of field data and coincident high spatial resolution satellite imagery. The study area was a 142 km**2 shallow, clear water seagrass habitat (the Eastern Banks, Moreton Bay, Australia). Nine data sets acquired between 2004 and 2013 were used to create seagrass species and percentage cover maps through the integration of seagrass photo transect field data, and atmospherically and geometrically corrected high spatial resolution satellite image data (WorldView-2, IKONOS and Quickbird-2) using an object based image analysis approach. Biomass maps were derived using empirical models trained with in-situ above ground biomass data per seagrass species. Maps and summary plots identified inter- and intra-annual variation of seagrass species composition, percentage cover level and above ground biomass. The methods provide a rigorous approach for field and image data collection and pre-processing, a semi-automated approach to extract seagrass species and cover maps and assess accuracy, and the subsequent empirical modelling of seagrass biomass. The resultant maps provide a fundamental data set for understanding landscape scale seagrass dynamics in a shallow water environment. Our findings provide proof of concept for the use of time-series analysis of remotely sensed seagrass products for use in seagrass ecology and management.