From 1 - 10 / 12
  • Categories    

    This dataset contains spatial layers describing Forest Canopy Extent from 1995-2019 in NSW Regional Forest Agreements (RFA) Areas along the eastern coast. Forest Canopy Extent is the likelihood that a certain area has forest at any given time. Forest Canopy is defined in accordance with the National State of the Forests Report which defines forests as containing as a minimum, a mature or potentially mature stand height exceeding 2 metres, stands dominated by trees usually having a single stem, where the mature or potentially mature stand component comprises 20% canopy coverage using a Crown Projective Cover (CPC) measure. <br> These have been based off the National Greenhouse Gas Inventory (NGGI) National Carbon Accounting System (NCAS) National Forest and Sparse Woody Vegetation Data grids (ABARES, 2020). These base grids are Landsat in origin and have a resolution of 25m. <br> To calculate forest canopy extent, these base grids have been processed through a series of land use and vegetation type exclusion masking and a through a fuzzy-logic based certainty analysis to reflect a forest cover extent coverage for NSW that is reflective of past and current coverage.<br> Read more about the project on the Natural Resources Commission website:<br> https://www.nrc.nsw.gov.au/fmip-baselines-ecosystem-health-projectfe1<br> This dataset is superseded by 'NSW Forest Monitoring and Improvement Program State-Wide Historic Forest Canopy Cover Extent - 1995 to 2020'

  • Categories    

    This dataset contains spatial layers describing Forest Connectivity from 1995-2019, in NSW Regional Forest Agreements (RFA) Areas along the eastern coast. Forest Connectivity accounts for the general quality of terrestrial habitats supporting biodiversity at each location, the fragmentation of habitat within its neighbourhood and how its position in the landscape contributes to connectivity among the habitats across a region. <br> These have been based off the National Greenhouse Gas Inventory (NGGI) National Carbon Accounting System (NCAS) National Forest and Sparse Woody Vegetation Data grids (ABARES, 2020). These base grids are Landsat in origin and have a resolution of 25m. <br> Forest Connectivity, including canopy cover connectivity and fragmentation is concerned and linked to forest condition. Concepts applied are to be aligned with definitions as found in the NSW Biodiversity Indicator Program (BIP) and the Spatial Links methodology for calculating connectivity.<br> Base cover extent grids used are from the NSW RFA Historic Forest Canopy Cover Extent – 1995 to 2019 product. <br> Read more about the project on the Natural Resources Commission website:<br> https://www.nrc.nsw.gov.au/fmip-baselines-ecosystem-health-projectfe1<br> This dataset is superseded by 'NSW Forest Monitoring and Improvement Program State-Wide Historic Forest Connectivity - 1995 to 2020'

  • Categories    

    The spatial layers in this dataset detail forest connectivity over NSW. Forest Connectivity accounts for the general quality of terrestrial habitats supporting biodiversity at each location, the fragmentation of habitat within its neighbourhood and how its position in the landscape contributes to connectivity among the habitats across a region. <br> Forest canopy cover connectivity and fragmentation is concerned and linked to forest condition. Concepts applied are to be aligned with definitions as found in the Biodiversity Indicator Program (BIP) and the Spatial Links methodology for calculating connectivity. <br> Base cover extent grids used are from the NSW Forest Monitoring and Improvement Program Statewide Historic Forest Cover Extent – 1995 to 2020 product. These have been processed through a series of land use and vegetation type exclusion masking and a through a fuzzy-logic based certainty analysis to reflect a forest cover extent coverage for NSW that is reflective of past and current coverage.<br> Read more about the project on the Natural Resources Commission website:<br> https://www.nrc.nsw.gov.au/fmip-baselines-ecosystem-health-projectfe1<br> This dataset supersedes "NSW Forest Monitoring and Improvement Program RFA Historic Forest Connectivity – 1995 to 2019". https://portal.tern.org.au/metadata/23696.

  • Categories    

    The spatial layers in this dataset detail forest cover extent over NSW. They have been created for the NSW Natural Resources Commission to detail historic baseline and trends of forest cover extent coverage for NSW for all land tenures, including all RFAs and IFOAs. <br> These have been based off the National Greenhouse Gas Inventory (NGGI) National Carbon Accounting System (NCAS) National Forest and Sparse Woody Vegetation Data grids (ABARES, 2021). These base grids are Landsat in origin and have a resolution of 25m. <br> These base grids have been processed through a series of land use and vegetation type exclusion masking and a through a fuzzy-logic based certainty analysis to reflect a forest cover extent coverage for NSW that is reflective of past and current coverage. <br> These grids cover the years from 1995 to 2020. The year gaps are triennial or biennial data layers from 1995 to 2004. 1996,1997,1999,2001,2003 years missing as these were not assessed in original applied database. From 2004 to 2020 data layers become annualised.<br> Read more about the project on the Natural Resources Commission website:<br> https://www.nrc.nsw.gov.au/fmip-baselines-ecosystem-health-projectfe1<br> This dataset supersedes "NSW Forest Monitoring and Improvement Program RFA Historic Forest Cover Extent – 1995 to 2019". https://portal.tern.org.au/metadata/23696.

  • Categories    

    The NSW Carbon Monitoring project is a collaboration between the Natural Resources Commission of NSW and Mullion Group to develop a spatial time-series dataset of forest carbon history for the state of NSW at ~25m resolution. The project used FLINTpro software to integrate historical environmental and land management data to model carbon stock and fluxes. Aboveground biomass refers to the amount of carbon stored within aboveground forest components (pools) which includes leaves, branches, bark and stems. Belowground biomass refers to the amount of carbon stored within belowground forest components (pools) which includes coarse and fine roots. Dead Organic Matter refers to the amount of carbon stored within dead forest components (pools) which includes leaf litter, branch litter, bark litter, stem litter, and dead roots. Carbon stored within soil and harvested wood products is not included within any of these datasets.

  • Categories    

    This dataset contains spatial layers describing Forest Loss and Recovery from 1998-2020 in NSW. For this dataset product and the processing of metrics, aspects of canopy loss and disturbances in the forest estate were investigated. Measures of canopy loss and recovery are seen as one of the multiple indicators of forest health. This is related to agents or pressures that affect the capacity of native forests and commercial operations to maintain normal ecosystem functions and sustainably provide productive capacity. <br> To attribute disturbances, as a driver of change, a Multiple Lines of Evidence (MLE) approach was used that leveraged available spatial datasets. This allowed for a project-wide disturbance and disturbance context layer to be generated. This information can be interpreted back against forest cover extent change outputs, in particular the differences between individual years, to identify the areas of change and the likely reasons why. Therefore, landscape trends in forest loss can be potentially assigned or at the very least investigated. <br> The time taken, in terms of years, for areas to recover from losses in forest cover extent can has also been determined. This process identifies the time taken for a patch of forest to return to a 20% canopy cover threshold, and other characteristics such as the forest type and likely disturbance or loss event.<br> Base cover extent grids used are from the NSW State-wide Historic Forest Cover Extent – 1995 to 2020 product. These have been processed through a series of land use and vegetation type exclusion masking and a through a fuzzy-logic based certainty analysis to reflect a forest cover extent coverage for NSW that is reflective of past and current coverage. <br> Read more about the project on the Natural Resources Commission website:<br> https://www.nrc.nsw.gov.au/fmip-baselines-ecosystem-health-projectfe1<br> This dataset supersedes "NSW Forest Monitoring and Improvement Program RFA Historic Forest Loss and Recovery – 1998 to 2019".

  • Categories    

    This dataset contains spatial layers describing Forest Canopy Loss and Recovery from 1998-2019 in NSW Regional Forest Agreements (RFA) Areas along the eastern coast. <br> These have been based off the National Greenhouse Gas Inventory (NGGI) National Carbon Accounting System (NCAS) National Forest and Sparse Woody Vegetation Data grids (ABARES, 2020). These base grids are Landsat in origin and have a resolution of 25m. <br> For this dataset product and the processing of metrics, aspects of canopy loss and disturbances in the forest estate were investigated. Measures of canopy loss and recovery are seen as one of the multiple indicators of forest health. This is related to agents or pressures that affect the capacity of native forests and commercial operations to maintain normal ecosystem functions and sustainably provide productive capacity. <br> To attribute disturbances, as a driver of change, a Multiple Lines of Evidence (MLE) approach was used that leveraged available spatial datasets. This allowed for a project-wide disturbance and disturbance context layer to be generated. This information can be interpreted back against forest cover extent change outputs, in particular the differences between individual years, to identify the areas of change and the likely reasons why. Therefore, landscape trends in forest loss can be potentially assigned or at the very least investigated. <br> The time taken, in terms of years, for areas to recover from losses in forest canopy cover extent can has also been determined. This process identifies the time taken for a patch of forest to return to a 20% canopy cover threshold, and other characteristics such as the forest type and likely disturbance or loss event. <br> Forest Canopy Loss and Recovery uses measures of canopy loss and disturbances which can be interpreted back against forest cover extent change outputs, in particular the differences between individual years, to identify the areas of change and the likely reasons why. Therefore, landscape trends in forest canopy loss can be potentially assigned or at the very least investigated. Time taken in years for areas to recover for losses has also been determined, as-well as other characteristics such as forest type and likely disturbance/loss event. <br> Base cover extent grids used are from the NSW RFA Historic Forest Canopy Cover Extent – 1995 to 2019 product. Read more about the project on the Natural Resources Commission website:<br> https://www.nrc.nsw.gov.au/fmip-baselines-ecosystem-health-projectfe1<br> This dataset is superseded by 'NSW Forest Monitoring and Improvement Program State-Wide Historic Forest Canopy Loss and Recovery - 1998 to 2020'

  • Categories    

    Microsatellite genotype data for 3 eucalypt species. Data include progeny and adults from across a gradient of habitat fragmentation. These microsatellite data could be further used in additional analyses, e.g. genetic diversity. Samples collected from stands on eucalypts as follows: non-neighbouring adult trees had leaf and seeds collected. Leaf was used to genotype the adults. Seeds were germinated, tissue then collected, and the same microsatellites genotyped - i.e. open-pollinated progeny arrays. The dataset is possibly useful for meta-analysis or review of effects of habitat fragmentation on plants (e.g. mating system, genetic diversity etc).

  • Categories    

    This dataset presents the demographic monitoring (growth and survival) of 81 tree species based on repeated stem measurement data from 20, 0.5 ha (100 m x 50 m) permanent moist forest plots in northern Queensland, Australia from 1971 to 2019, as well as four additional plots of 0.1 to 1 ha whose monitoring began in the 2000s. The plots have a rainfall range of 1200 to over 6000 mm, represent eleven vegetation types, six parent materials, and range from 15 m to 1500 m above sea level. Except for minor disturbances associated with selective logging on two plots, the plots were established in old growth forest and all plots have thereafter been protected. Plots were regularly censused and at each census the diameter at breast height (DBH) of all stems ≥10 cm DBH were recorded. We only report the data for the 81 species studied in Bauman et al. 2022 (Nature), here. We also provide the climatology of these plots as well as the temperature, vapour pressure deficit, and maximum climatological water deficit of all intervals separating consecutive censuses, as used in the analyses of Bauman et al. 2022.

  • Categories    

    These datasets consist of soil maps generated to assess baselines, drivers and trends for soil health and stability within the NSW Regional Forest Agreement (RFA) regions. <br> The maps are organised into empirical soil maps, digital soil maps, and data cube maps. <br> Empirical soil maps consists of four products. Maps include topsoil pH, carbon, Emerson Aggregate Stability and Soil Profile Quality Confidence. Each map consists of 2,162 units. Maps were generated using the most representative soil profile for each unit available within the Soil and Land Information System (SALIS). The 2008 woody vegetation coverage was used as baseline. Maps reflect values when the sampling occurred with temporal changes not being accounted for. Locations with missing or of poor quality data are identified, providing a confidence rating map as part of the evaluation process.<br> Digital soil maps include map products of key soil condition indicators covering the Regional Forest Agreement regions of eastern NSW. Raster maps of key soil indicators, such as soil carbon, pH, bulk density, hillslope erosion and others, were created at 100 m resolution. For each key soil indicator, maps include baseline (approximately 2008) levels as well as trends of change resulting from different human and natural disturbances such as forest harvesting, uncontrolled stock grazing, climate change and bush fire. <br> Data cube maps include time series of soil organic carbon (SOC) between January 1990 and December 2020 for the Regional Forest Agreement regions of eastern NSW. Products provide estimates of SOC concentrations and associated trends through time. Modelling was carried out using a data cube platform incorporating machine learning space-time framework and geospatial technologies. Important covariates required to drive this spatio-temporal modelling were identified using the Recursive Feature Elimination algorithm (RFE). <br> A web mapping application on the NSW Spatial Collaboration Portal depicts these datasets. Access the webapp through the link below:<br> https://portal.spatial.nsw.gov.au/portal/home/item.html?id=af9c71935f024f4a8f64cb39f5eba007