This is Version 2 of the Australian Total Soil Nitrogen product of the Soil and Landscape Grid of Australia.<br></br> It supersedes the Release 1 product that can be found at https://doi.org/10.4225/08/546F564AE11F9<br></br> The map gives a modelled estimate of the spatial distribution of total nitrogen in soils across Australia.<br></br> 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 (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90&nbsp;m pixels). An additional measure of model reliability is through assessment of model extrapolation risk. This measure provides users a spatial depiction where model estimates are made within the domain of the observed data or not.<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: Total soil nitrogen;</li> <li>Units: % (percentage of fine soil mass);</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: 24;</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>

This data contains soil physico-chemical characteristics collected at 33 one hectare plots in the Karawatha Peri-Urban site in 2007.

Leaf traits for 101 populations of <i>Dodonaea viscosa subsp. angustissima </i>(Sapindaceae) opportunistically collected across a ~1,000 km latitudinal north-south sequence with climates grading from the arid zone to the mesic Mediterranean zone. Additionally, we present leaf traits for 266 individuals on an attitudinal gradient in the Mt Lofty Ranges, South Australia. Traits measured include leaf area and specific leaf area, as well as climatic variables associated with the collection sites. <p>Leaf area is known to be responsive to climatic conditions. This data could be combined with additional collections for Dodonaea viscosa or broader plant trait data sets to explore pant responses to environmental change.</p>

The forest fuel survey dataset comprises site-level summary data from the well-designed fuel load surveys across 48 AusPlots Forests- 1-ha monitoring plots across Australia. Data presented here includes data on the surface, near-surface, and elevated fuel loads for each of the Forest Ausplots. It includes iButton data on 1) temperature and humidity, 2) data on litterfall and 3) decomposition rates. We also provide additional information on soil nutrient data, species composition of the understorey and midstorey, and panorama photos from the plot centre. This dataset is the second version of the <i> AusPlots Forest Fuel Survey site-level data summary, 2014 - 2015. Version 1.0.0. Terrestrial Ecosystem Research Network.</i> (dataset). <em>https://doi.org/10.25901/efnh-sk06</em>

The data set contains information on plant diversity indices, species composition, vegetation cover and edaphic properties from the <i>Eucalyptus salubris</i> woodlands, Great Western Woodlands site. The data represents changes in plant diversity due to disturbance with time since fire in a chronosequence.

This data contains soil physico-chemical characteristics collected at the Samford Peri-Urban site in 2013.

This data contains soil physico-chemical characteristics collected at the Daintree Rainforest, Cape Tribulation site between 2007 - 2015.

This data contains soil physico-chemical characteristics collected at the Robson Creek Rainforest site between 2011 - 2014.

Plant material decomposition in soil was investigated using two types of tea bags (Green and Rooibos) buried to 8 cm for 80-90 days across seven TERN Ecosystem Process monitoring sites between 2016 - 2017. The sites included: Great Western Woodlands, Robson Creek Rainforest, Samford Peri-Urban, Cumberland Plain, Cape Tribulation, Warra Tall Eucalypt and Tumbarumba Wet Eucalypt sites. Weight loss of tea bags was determined and contextual data collected.

This dataset contains information on vegetation at a set of field sites along with associated environmental data extracted from spatial layers and selected ecological statistics. Measurements of vascular plants include species, growth form, height and cover from 1010 point intercepts per plot as well as systematically recorded absences, which are useful for predictive modelling and validation of remote sensing applications. The derived cover estimates are robust and repeatable, allowing comparisons among environments and detection of modest change. The field plots span a rainfall gradient of 129-1437 mm Mean Annual Precipitation ranging from aseasonal to highly seasonal. The dataset consists of a processed version the AusPlots Rangelands dataset with three components: 1) a site table with locality, environmental and summary ecology statistics for each plot; 2) a set of compiled point intercept records identified by individual hits, site visits and plots and; 3) a processed species percent cover against site/visit matrix for ecological analysis. The data have re-use potential for studies on vegetation properties in the Australian rangelands or as a species presence/absence dataset for testing ecological models. The dataset also provides opportunities for generic application such as testing community ecology theories or developing or demonstrating community ecology software, whether using the raw point by point intercept data or the derived percent cover matrix.