High quality passive infrared wildlife cameras were used to acquire information on faunal biodiversity at the site. Two cameras were deployed from July to Dec 2018 and between March and May 2019. <br /><br /> The Gingin Banksia Woodland SuperSite was established in 2011 and is located in a natural woodland of high species diversity with an overstorey dominated by Banksia species. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/gingin-banksia-woodland-supersite/. <br /> Other images collected at the site include digital cover photography, phenocam time-lapse images taken from fixed under and overstorey cameras and ancillary images of flora.

This dataset consists of measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer in arid tussock grassland using eddy covariance techniques. <br /> <br /> The flux station is located at Rosebank Station, approximately 11 km south-east of Longreach in Queensland. The site is arid tussock grassland with a variety of grass species including <em>Astrebla lappacea</em> and <em>Astrebla squarrosa</em> over black vertosol soil that supports sheep and beef cattle grazing. Traditional owners at this site are the Iningai people. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/mitchell-grass-rangeland-supersite/ .<br /><br />This data is also available at http://data.ozflux.org.au .

<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 flux station is located at Rosebank Station, approximately 11&nbsp;km south-east of Longreach in Queensland. The site is arid tussock grassland with a variety of grass species including <em>Astrebla lappacea</em> and <em>Astrebla squarrosa</em> over black vertosol soil that supports sheep and beef cattle grazing. Traditional owners at this site are the Iningai people.

The dataset contains maps of total % C₃ and C₄ plant cover, proportional C₃ and C₄ vegetation (relative to combined C₃ and C₄ cover), and vegetation &delta;¹³C isoscape (stable carbon isotope values) across Australia. Data are centered on year 2015. We used vegetation and land-use rasters to categorize grid-cells (100 m²) into woody (C₃), native herbaceous (C₃ and C₄), and herbaceous cropland (C₃ and C₄) cover. TERN Ecosystem Surveillance field surveys and environmental factors were regressed to predict native C₄ herbaceous cover. These layers were combined and a &delta;¹³C mixing model was used to calculate site-averaged &delta;¹³C values.

Digital Hemispheric Photography (DHP) upward-looking images are collected up to three times per year to capture vegetation cover at Boyagin Wandoo Woodland SuperSite. These images can be used to estimate Leaf area index (LAI), Crown Cover or Foliage Projective Cover (FPC). The Boyagin Wandoo Woodland SuperSite was established in 2017 in Wandoo Woodland, which is surrounded by broadacre farming. About 80% of the overstorey cover is <em>Eucalyptus accedens</em>. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/boyagin-wandoo-woodland-supersite/ . Digital Cover Photography was also collected at Boyagin from 2019.

This product provides locations of areas affected by fire including the approximate day of burning. Inputs are daily day time observations from MODIS sensors on Terra and Aqua. Observations are atmospherically corrected and the resulting time series is investigated for sudden changes in reflectance, persistent over multiple days. Variations in observation and illumination geometry are taken into account through application of a kernel driven Bidirectional Reflectance Distribution Function (BRDF) model.

<p>This dataset contains audio files for TERN Boyagin Wandoo Woodland SuperSite. Long-term recordings of the environment can be used to identify sound sources of interest, characterise the soundscape, aid in the assessment of fauna biodiversity, monitor temporal trends and track environmental changes.</p> <p>The site was established in 2017 at the Boyagin Nature Reserve with research plots located in Wandoo woodland (<em>Eucalypt sp.</em>). The core 1&nbsp;ha plot is located in a dense eucalypt woodland. For additional site information, see <a href="https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/boyagin-wandoo-woodland-supersite/">Boyagin Wandoo Woodland SuperSite</a></p> <p>In 2018 an acoustic recorder was set up to collect audio data for a total of 12 hours per day, split between six hours around dawn and six hours around dusk. The recording schedule aimed at capturing morning and evening bird choruses while minimizing memory and battery requirements. A long-term spectrogram has been generated for each audio file to aid in data exploration.</p> <p>Data are made available through the data link. For downloading large amount of data, please follow these instructions <a href="https://ternaus.atlassian.net/wiki/spaces/TERNSup/pages/2530148353/How+to+download+TERN+s+acoustic+data+in+bulk">How to download TERN's acoustic data in bulk</a></p>

This data contains a once-off general structural description according to the National Vegetation Information System (NVIS) level 5 for the core 1 hectare plot in the Mitchell Grass Rangeland site in 2018. Dominant growth form, cover, height and species (up to 5 species in order of dominance) for up to 3 sub-stratum per traditional strata (Ground, Mid and Upper).

This data contains a list of all vascular plants surveyed in the Gingin Banksia Woodlands site in 2018.

For some time, Remote Sensing Sciences, has produced Foliage Projective Cover (FPC) using a model applied to Landsat surface reflectance imagery, calibrated by field observations. An updated model was developed which relates field measurements of FPC to 2-year time series of Normalized Difference Vegetation Index (NDVI) computed from Landsat seasonal surface reflectance composites. The model is intended to be applied to Landsat and Sentinel-2 satellite imagery, given their similar spectral characteristics. However, due to insufficient field data coincident with the Sentinel-2 satellite program, the model was fitted on Landsat imagery using a significantly expanded, national set of field data than was used for the previous Landsat FPC model fitting. The FPC model relates the field measured green fraction of mid- and over-storey foliage cover to the minimum value of NDVI calculated from 2-years of Landsat seasonal surface reflectance composites. NDVI is a standard vegetation index used in remote sensing which is highly correlated with vegetation photosynthesis. The model is then applied to analogous Sentinel-2 seasonal surface reflectance composites to produce an FPC image at Sentinel-2 spatial resolution (i.e. 10&nbsp;m) using the radiometric relationships established between Sentinel-2 and Landsat in Flood (2017). This is intended to represent the FPC for that 2-year period rather than any single date, hence the date range in the dataset file name. The dataset is generally expected to provide a reasonable estimate of the range of FPC values for any given stand of woody vegetation, but it is expected there will be over- and under-estimation of absolute FPC values for any specific location (i.e. pixel) due to a range of factors. The FPC model is sensitive to fluctuations in vegetation greenness, leading to anomalies such as high FPC on irrigated pastures or locations with very green herbaceous or grass understoreys. A given pixel in the FPC image, represents the predicted FPC in the season with the least green/driest vegetation cover over the 2-year period assumed to be that with the least influence of seasonally variable herbaceous vegetation and grasses on the more seasonally stable woody FPC estimates. The two-year period was used partly because it represents a period relative to tree growth but was also constrained due to the limited availability of imagery in the early Sentinel-2 time series. The FPC dataset is constrained by the woody vegetation extent dataset for the FPC year.