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    This dataset lists land surface substrate characteristics observed in Rangeland sites across Australia by the TERN Surveillance Monitoring team, using standardised AusPlots methodologies. <br /> Land surface substrate observations are collected at each site as part of the AusPlots Point intercept method. At each site, observations on the substrate type (e.g. rock, coarse woody debris, litter) are recorded on transect laid out on the plots. These records form the basis for ground cover derivation, see the AusPlots Ground cover and Point intercept methods below.<br />

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    <br>This release consists of flux tower measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer using eddy covariance techniques. Data were processed using PyFluxPro (v3.4.7) as described by Isaac et al. (2017). PyFluxPro produces a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER).</br><br> The Loxton site was established in August 2008 and decommissioned in June 2009. The orchard was divided into 10&nbsp;ha blocks (200&nbsp;m by 500&nbsp;m with the long axis aligned north–south) and the flux tower was situated at 34.47035&nbsp;°S and 140.65512&nbsp;°E near the middle of the northern half of a block of trees. The topography of the site was slightly undulating and the area around the tower had a slope of less than 1.5&nbsp;°. The orchard was planted in 2000 with an inter-row spacing of 7&nbsp;m and a within row spacing of 5&nbsp;m. Tree height in August 2008 was 5.5&nbsp;m. The study block consists of producers, Nonpareil, planted every other row, and pollinators planted as alternating rows of Carmel, Carmel and Peerless, and Carmel and Price. All varieties were planted on Nemaguard rootstock. All but 31&nbsp;ha of the surrounding orchard was planted between 1999 and 2002. Nutrients were applied via fertigation. Dosing occurred between September and November and in April with KNO<sub>3</sub>, Urea, KCl, and NH<sub>4</sub>NO<sub>3</sub> applied at annual rates of 551, 484, 647, and 113&nbsp;kg/ha, respectively. The growth of ground cover along the tree line was suppressed with herbicides throughout the year. Growth in the mid-row began in late winter and persisted until herbicide application in late November. The research was supported with funds from the National Action Plan for Salinity via the Centre for Natural Resource Management, and the River Murray Levy.

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    The woody vegetation extent for Queensland is attributed with an estimated age in years since the last significant disturbance. The method uses a sequential Conditional Random Fields classifier applied to Landsat time series starting 1988 to predict woody cover over the time period. A set of heuristic rules is used to detect and track regrowing woody vegetation in the time series of woody probabilities and record the approximate start and end dates of the most recent regrowth event. Regrowth detection is combined with the Statewide Land and Trees Study (SLATS) Landsat historic clearing data to provide a preliminary estimate of age since disturbance for each woody pixel in the woody extent. The 'last disturbance' may be due to a clearing event or other disturbance such as fire, flood, drought-related death etc. Note that not all recorded disturbances may result in complete loss of woody vegetation, so the estimated age since disturbance does not always represent the age of the ecosystem. The age since disturbance product is derived from multiple satellite image sources and derived products which represent different scales and resolutions: Landsat (30&nbsp;m), Sentinel-2 (10&nbsp;m) and Earth-i (1&nbsp;m).

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    Tree demographic, tree biomass and shrub count data for two Ausplots adjacent to Credo Flux tower (Salmon Gum, SG100E and Gimlet, Gim100W). Floristic survey data and 1000 points of cover. Tree demographics was measured using a tape at 130cm for diameter and 2 different laser height finders. These gave consistently different measures and both are presented. Plot biomass was calculated from allometric regression published by Jonson and Freudenberger (2011). All shrubs with mature heights of over 0.5m were measured in ten, 10m wide by 100m transects to ensure all shrubs in the one hectare plots were counted. Floristic survey was undertaken and 1000 point intercepts recorded along 10 lines (5 north-south, 5 east-west with one point per meter) for SG100W according to Ausplots methodology (Foulkes et al., 2011)

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    This data package comprises fire severity scores from Kakadu in 2014. A total of 220 permanent monitoring plots (40&nbsp;m x &nbsp;20 m) were established across three parks (Kakadu, Litchfield and Nitmiluk) in 1994-1995 to monitor biotic change. Of these, 132 plots are located in Kakadu. These sample a variety of landform and vegetation type/habitat conditions. A substantial proportion of plots were positioned deliberately at sites likely to reveal environmental dynamics, especially at ecotones and in patches of fire-sensitive vegetation. For example stands of <i>Callitris</i>, sandstone heaths. As well, many plots are located at, or in the near vicinity of, intensively managed sites such as camp-grounds and other tourist destinations. A synopsis of related data packages which have been collected as part of the Three Park Savanna Fire-effects Plot Network’s full program is provided at <a href="http://www.ltern.org.au/index.php/ltern-plot-networks/three-parks-savanna ">LTERN</a>

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    Seedling surveys were conducted at the Cumberland Plain site in 2014. The identity and height of all seedlings were recorded along six 20 m x 1 m transects in the core 1 ha plot.

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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 linear seasonal persistent green trend is derived from analysis of the seasonal persistent green product over time. The current version is based on the 1987-2014 period. <br> Seasonal persistent green cover is derived from seasonal fractional cover using a weighted smooth spline fitting routine. This weights a smooth line to the minimum values of the seasonal green cover. This smooth minimum is designed to represent the slower changing green component, ideally consisting of perennial vegetation including over-storey, mid-storey and persistent ground cover. The seasonal persistent green is then summarized using simple linear regression, and the slope of the fitted line is captured in this product. The original units are percentage points per year. Values are later truncated and scaled.

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    This product has been superseded and will not be processed from early 2023. Please find the updated version 3 of this product at https://portal.tern.org.au/metadata/24071. Long term temporal statistic products derived from the seasonal ground cover product for each fraction. Statistics include: 5th percentile minimum, mean, median, 95th percentile maximum, standard deviation and observation count. There is one raster image for each season and each bare and green fraction for the full time series of imagery available. Min/max (5th and 95th percentile) products are also made for each fraction using all seasonal ground cover images available.

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    1. Restoration of degraded landscapes has become increasingly important for conservation of species and their habitats owing to habitat destruction and rapid environmental change. An increasing focus for restoration activity are old-fields as agricultural land abandonment has expanded in the developed world. Studies examining outcomes of ecological restoration predominantly focus on vegetation structure and plant diversity, and sometimes vertebrate fauna. Fewer studies have systematically investigated effects of restoration efforts on soil chemical and biophysical condition or ground-dwelling invertebrates and there is limited synthesis of these data. 2. This dataset comprised data for a global meta-analysis of published studies to assess the effects on soil properties and invertebrates of restoring land that was previously used for agriculture. Studies were included if the site had been either cropped or grazed, restoration was either active (planting) or passive (abandonment, fencing) and if adequate data on soil chemical or physical properties or invertebrate assemblages were reported for restored, control (cropped/grazed) or reference sites. 3. The dataset includes 42 studies, published between 1994 and 2019 that met the inclusion criteria, covering 16 countries across all continents. More studies assessed passive restoration approaches than active planting, and native species were more commonly planted than exotic species.