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    <p>This data set provides the photosynthetic pathways for 2428 species recorded across 541 plots surveyed by Australia’s Terrestrial Ecosystem Research Network (TERN) between 2011 and 2017 (inclusive). TERN survey plots are 1 ha (100 x 100 m) permanently established sites located in a homogeneous area of terrestrial vegetation. At each plot, TERN survey teams record vegetation composition and structural characteristics and collect a range of plant samples using a point-intercept method. Species were assigned a photosynthetic pathway using literature and carbon stable isotope analysis of bulk tissue collected by TERN at the survey plots. </p><p>The data set is comprised of two data tables and one data descriptor that defines the values in the two data tables. The first table contains a list of each species and its photosynthetic pathway. The second table includes a list of all the peer-reviewed sources used to create this data set. </p><p>This data set will be updated on an annual basis as TERN’s plot network expands and new information becomes available. </p>

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    This collection contains the data used in the Multi-Criteria Analysis Shell for Spatial Decision Support (MCAS-S) software tool. From the Data menu, explore and download individual supplementary layers, or download the entire datapack. The Multi-Criteria Analysis Shell for Spatial Decision Support (MCAS-S) is a software tool developed by the Australian Bureau of Agricultural and Resource Economics and Sciences that enables multi-criteria analysis (MCA) using spatial data. It is a powerful, easy-to-use and flexible decision-support tool that promotes: - framework for assessing options <br> - common metric for classifying, ranking and weighting of the data <br> - tools to compare, combine and explore spatial data <br> - live-update of alternative scenarios and trade-offs. <br>

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    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.

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    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".

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    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'

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    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.

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    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.

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    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'

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    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'

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    <p>Digital Hemispherical Photography (DHP) upward-looking images were collected annually to capture vegetation and crown cover at Daintree Rainforest SuperSite. These images are used to estimate Leaf Area Index (LAI). </p><p> The site is located at the Daintree Rainforest Observatory in Lowland Complex Mesophyll Vine Forest near Cape Tribulation. Flux monitoring was established in 2001 with additional monitoring capabilities added over time. The site has more than 80 species including canopy trees belonging to the <em>Arecaceae, Euphorbiaceae, Rutaceae, Meliaceae, Myristicaceae and Icacinaceae</em> families. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/daintree-rainforest-supersite/. </p><p> Other images collected at the site include photopoints, phenocam time-lapse images taken from fixed under and overstorey cameras and ancilliary images of fauna and flora. </p>