<ul><li>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. </li> <li>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.</li> <li>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.</li></ul>

This is Version 2 of the Australian Soil Bulk Density - Whole Earth product of the Soil and Landscape Grid of Australia.<br></br> It supersedes the Release 1 product that can be found at <a href="https://doi.org/10.4225/08/546EE212B0048">https://doi.org/10.4225/08/546EE212B0048</a><br></br> The map gives a modelled estimate of the spatial distribution of Bulk Density in soils across Australia.<br></br> <p>The Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5&nbsp;cm, 5-15&nbsp;cm, 15-30&nbsp;cm, 30-60&nbsp;cm, 60-100&nbsp;cm and 100-200&nbsp;cm. These depths are consistent with the specifications of the GlobalSoilMap.net project - <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf">GlobalSoilMaps</a>. The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90&nbsp;m pixels).<br></br> Detailed information about the Soil and Landscape Grid of Australia can be found at - <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html">SLGA</a><br><br> <ul style="list-style-type: disc;"><li>Attribute Definition: Bulk Density of the whole soil (including coarse fragments) in mass per unit volume by a method equivalent to the core method;</li> <li>Units: g/cm3;</li> <li>Period (temporal coverage; approximately): 1950-2021;</li> <li>Spatial resolution: 3 arc seconds (approx 90&nbsp;m);</li> <li>Total number of gridded maps for this attribute: 18;</li> <li>Number of pixels with coverage per layer: 2007M (49200 * 40800);</li> <li>Data license : Creative Commons Attribution 4.0 (CC BY);</li> <li>Target data standard: GlobalSoilMap specifications;</li> <li>Format: Cloud Optimised GeoTIFF.</li></ul>

<br>This dataset lists observations on soil samples collected in rangeland sites across Australia by the TERN Surveillance Monitoring team, using standardised AusPlots methodologies. <br/> <br>Soil samples are collected at each site as part of the AusPlots Soil Samples method. For each soil sample fine earth bulk density, gravel bulk density, wet and dry weight are estimated and coarse fragments lithology, abundance, size and shape observed as part of the AusPlots Soil Samples and Soil Bulk Density method.<br/>

The Australian cosmic-ray soil moisture monitoring network was first established in 2010 to provide Australian and global researchers with spatially distributed intermediate scale soil moisture observations. A cosmic-ray sensor (CRS) provides continuous estimates of soil moisture over an area of approximately 30 hectares by measuring naturally generated fast neutrons (energy 10–1000 eV) that are produced by cosmic rays passing through the Earth’s atmosphere. The neutron intensity above the land surface is inversely correlated with soil moisture as it responds to the hydrogen contained in the soil and to a lesser degree to plant and soil carbon compounds. The cosmic-ray technique is also passive, non-contact, and is largely insensitive to bulk density, surface roughness, the physical state of water, and soil texture. The scale of CRS measurements fills the void between point scale sensor measurements and large scale satellite observations. The depth of measurements varies with the moisture content of the soil but is typically between 10-30 cm. The depth of observations is reported as ‘effective depth’. <br> The CosmOz network is expanding as new sensors are added over time. The initial network was funded by CSIRO Land and Water but more recently TERN has funded work to maintain the network add new sensors and deliver data more efficiently. The standard CRS installation includes; a cosmic-ray neutron tube, a rain gauge (2m high), temperature and humidity sensors, and an atmospheric pressure sensor. Measures of all parameters are reported at an hourly interval. Each CRS requires an in-field calibration across the footprint of measurements to convert neutron counts to soil moisture content. The calibration includes collection of soil samples for bulk density, lattice water content and soil organic carbon.<br> The Australia CosmOz network consists of <a href="https://cosmoz.csiro.au/sites">19 stations</a>. The extent of the network and available data can be seen at the CosmOz network web page: <a href="https://cosmoz.csiro.au/">https://cosmoz.csiro.au</a>. The data is also accessible from the <a href="https://landscapes-cosmoz-api.tern.org.au/rest/doc">TERN Cosmoz REST API</a>.<br> The calibration and correction procedures used by the network are described by <a href="https://doi.org/10.1002/2013WR015138">Hawdon et al. 2014 </a>.