***This record contains a subset of benthic habitat data from https://doi.org/10.25959/E4S6-GE74 (NESP MaC Project 3.6) rehosted for the purposes of the Seamap Australia collaborative project.*** Seagrass beds are a dominant marine ecosystem of Tayaritja (the Furneaux Group of Islands) in the north-eastern waters off Tasmania. Historical coarse mapping has indicated extensive beds of Posidonia, Amphibolis, Heterozostera, and Zostera species, potentially comprising some of the largest and deepest seagrass extents found in temperate Australian waters. However, limited data on the distribution and ecological value of these seagrass habitats represents a significant knowledge gap in understanding Australia's wetland natural assets. This project mapped the extent, ecological composition, population structure, and blue carbon value of seagrass beds around Tayaritja, in partnership with the Tasmanian Aboriginal Centre, as part of NESP Marine and Coastal Hub Project 3.6. The study area focused on the coastal waters surrounding Flinders Island in the western Furneaux Group, with mapping extending from the high tide line to the depth limit of reliable optical detection (approximately 30 m), based on analysis of field data and satellite imagery capabilities in the region. This metadata record specifically describes the benthic mapping component of the study. A combination of close-range remote sensing methods was used to map the extent and ecological values of seagrass beds. High-resolution satellite imagery from Sentinel-2 (10 m) sensors, combined with bathymetric LiDAR data and oceanographic variables, was used to map baseline seagrass extent and composition. A field campaign deployed a Benthic Observation Survey System (BOSS) and unBaited Remote Underwater stereo-Video system (stereo-uBRUV) at approximately 400 locations to validate remote sensing outputs, collecting field photo quadrats and rhizome cores. From these data, maps were produced showing the extent and coverage of seagrass, sand, and macroalgae, and where possible, seagrass species composition, subject to water depth and clarity constraints. See the "Lineage" section of this record for full methodology.

Seagrass beds are a dominant marine ecosystem of Tayaritja (the Furneaux Group of Islands) in the north-eastern waters off Tasmania. Historical coarse mapping has indicated extensive beds of Posidonia, Amphibolis, Heterozostera, and Zostera species, potentially comprising some of the largest and deepest seagrass extents found in temperate Australian waters. However, limited data on the distribution and ecological value of these seagrass habitats represents a significant knowledge gap in understanding Australia's wetland natural assets. This project mapped the extent, ecological composition, population structure, and blue carbon value of seagrass beds around Tayaritja, in partnership with the Tasmanian Aboriginal Centre. The study area focused on the coastal waters surrounding Flinders Island in the western Furneaux Group, with mapping extending from the high tide line to the depth limit of reliable optical detection (approximately 30 m), based on analysis of field data and satellite imagery capabilities in the region. The field validation component of this study involved deployment of benthic video platforms to capture imagery of seagrass beds and associated ecosystems. A field campaign deployed a Benthic Observation Survey System (BOSS) and unBaited Remote Underwater stereo-Video system (stereo-uBRUV) at approximately 400 locations to collect photoquadrats and validate remote sensing outputs. Imagery annotation was conducted in the SQUIDLE+ platform. See dataset https://doi.org/10.25959/e4s6-ge74 for habitat maps derived from field validation and remote sensing inputs. The approach developed through this study contributed to the creation of the NESP Standard Operating Procedure (SOP) for Seagrass Mapping using Optical Remote Sensing (https://sustainabledevelopmentreform.github.io/nesp-sop-seagrass-mapping).. See the "Lineage" section of this record for full methodology of field collection techniques.

Seagrass beds are a dominant marine ecosystem of Tayaritja (the Furneaux Group of Islands) in the north-eastern waters off Tasmania. Historical coarse mapping has indicated extensive beds of Posidonia, Amphibolis, Heterozostera, and Zostera species, potentially comprising some of the largest and deepest seagrass extents found in temperate Australian waters. However, limited data on the distribution and ecological value of these seagrass habitats represents a significant knowledge gap in understanding Australia's wetland natural assets. This project mapped the extent, ecological composition, population structure, and blue carbon value of seagrass beds around Tayaritja, in partnership with the Tasmanian Aboriginal Centre. The study area focused on the coastal waters surrounding Flinders Island in the western Furneaux Group, with mapping extending from the high tide line to the depth limit of reliable optical detection (approximately 30 m), based on analysis of field data and satellite imagery capabilities in the region. This record specifically describes the benthic mapping component of the study. See https://doi.org/10.25959/WRXK-KV06 for imagery annotation data from the field validation campaigns. A combination of close-range remote sensing methods was used to map the extent and ecological values of seagrass beds. The approach developed through this study contributed to the creation of the NESP Standard Operating Procedure (SOP) for Seagrass Mapping using Optical Remote Sensing (https://sustainabledevelopmentreform.github.io/nesp-sop-seagrass-mapping).. High-resolution satellite imagery from Sentinel-2 (10 m) sensors, combined with bathymetric LiDAR data and oceanographic variables, was used to map baseline seagrass extent and composition. A field campaign deployed a Benthic Observation Survey System (BOSS) and unBaited Remote Underwater stereo-Video system (stereo-uBRUV) at approximately 400 locations to validate remote sensing outputs. From these data, maps were produced showing the extent and coverage of seagrass, sand, and macroalgae, and where possible, seagrass species composition, subject to water depth and clarity constraints. See the "Lineage" section of this record for full methodology. Three key types of mapping products were developed: ---Occurrence probability maps--- Continuous probability surfaces (0-100%), modelled from presence/absence data, indicating the likelihood of habitat presence at each pixel for: • Seagrass (all morphologies; > 5% cover observed in underwater field imagery) • Macroalgae species/assemblages • Sand ---Habitat percentage cover maps--- Quantitative estimates of percent cover for each habitat category: • Seagrass (all morphologies) • Macroalgae species/assemblages • Sand ---Derived products--- • Baseline binary presence/extent maps derived from optimised probability thresholds:     ○ Seagrass:     sgprob > 0.5 & sgprob > macroprob & sandcover < 0.9     ○ Macroalgae: macroprob > 0.5 & macroprob > sgprob & sandcover < 0.9     ○ Sand:           sandprob > 0.5 & sandcover < 0.2 • Predicted seagrass species composition of binary extent map. • Fractional cover visualisation: combining cover percentages of multiple habitats into a single composite product • Composite habitat maps: combining binary habitat extents and delineating mixed habitat classes These complementary products serve different purposes: probability maps provide confidence measures, extent maps delineate habitat boundaries, percent cover maps support quantitative analysis of habitat density patterns, and composite habitat maps represent the diversity of mixed habitat classes. Together, they provide a comprehensive understanding of seagrass and associated habitat distribution across the study area.

This dataset presents the results of a seafloor habitat modeling exercise for the 'Capes region' of the South-west Corner Marine Park, southern WA. The model classifies five broad habitat types (hereafter 'ecosystem components'): seagrass, macroalgae, sessile invertebrates, bare consolidated substrata, and bare unconsolidated substrata. Modeling was conducted at two spatial scales to assess the effectiveness of using broad-scale (~250 m) spatial covariates derived from bathymetry in mapping habitat classes and to compare the modelling outcomes with those obtained using finer-resolution input data. The fine-scale mapping focused on an IUCN II zone near Margaret River, using a seamless 5 m resolution multibeam bathymetry composite. The broad-scale mapping covered multiple IUCN zones, including the southwestern Geographe Australian Marine Park (AMP), the northwestern tip of the South-west Corner AMP, and the Ngari Capes WA State Marine Park. This component used the 250 m resolution 2023 AusBathyTopo grid from Geoscience Australia. Habitat maps were constructed using (1) the bathymetry data sources described above; (2) ground-truthing observations from stereo-BRUV and BOSS camera systems; and (3) Physical covariates, all smoothed to 5 m or 250 m resolution, for the fine- and broad-scale mapping, respectively. Source datasets are available from: • Geoscience Australia's eCat: https://dx.doi.org/10.26186/145281 (5 m multibeam bathymetry) and https://doi.org/10.26186/148758 (250 m DEM bathymetry) • Squidle+: http://squidle.org/geodata/explore (benthic imagery annotations - see also outputs from NESP MaC Project 2.4: https://doi.org/10.25959/6G5A-3G03) • AODN Portal: https://portal.aodn.org.au/search (IMOS oceanographic datasets). This analysis uses the modelling methodology developed in NESP Project 2.1, which extended the ecosystem component modelling to include all temperate Australian shelf waters at a resolution of 250 m (https://doi.org/10.25959/BVJ7-D984). Analysing the scale effects effects of spatial covarariate inputs was undertaken by NESP Project 2.3, along with exploration of visualisation options regarding prediction certainty in consultation with Parks Australia (management end-users). Further details on sampling design for ground-truthing observations and the modelling techniques are available in the NESP MaC Project 2.1 Final Report: https://www.nespmarinecoastal.edu.au/publication/improving-seabed-habitat-predictions-for-southern-australia. A description on this specific South-west Corner case study and the spatial scale analysis is described in the NESP MaC Project 2.3 Final Report: https://www.nespmarinecoastal.edu.au/publication/improving-knowledge-transfer-to-support-australian-marine-park-decision-making-and-management-effectiveness-evaluation. A selection of mapping (WMS) services are listed in the 'Downloads & Links' section of this record. See the 'Lineage' section for a full description of the data packages available for download, and for more visualisation options.

Redmap is a primarily a website that invites the community to spot, log and map marine species that are uncommon in their region, or along particular parts of their coast. The information collected is mapped and displayed on the site, demonstrating, in time, how species distributions may be changing. Sightings are divided into two categories – those with a photo that can be ‘verified’ by a marine biologist, and sightings without photos that we call community sightings (anecdotal). All the information collected, with and without photos, is mapped and will be used in the following years to map out a ‘story’ of changes occurring in our marine environment. The main data collected includes the species sighted (normally selected from a list comprising preselected species of interest), the location, date/time and activity being undertaken. Other optional information gathered include biological data such as sex, size and weight and environmental data such as water depth and temperature and habitat. This record is associated with live data (and will subsequently change over time). Note that the accuracy of spatial elements has been reduced for distribution purposes. This data set is also subject to a three year embargo (ie. does not contain data less than three years old). If you wish to discuss obtaining a citable, static dataset, that is current and/or contains precise spatial elements, please see Point of Contact.