This dataset contains the number (count) of dingo, red fox and feral cat photographs from remote camera traps in the Simpson Desert. Note, spatial location for the sites has been desensitized. Please contact the data author for site details.

Evaluation of the morphological variation within the genus <em>Polyosma</em> (<em>Escalloniaceae</em>) of Australia, New Caledonia and Papuasia based on herbarium specimens to clarify the taxonomy of the recognized species in this genus. These data also identified several previously unpublished species that are new to science.

This map gives a modelled estimate of the spatial distribution of Pedogenon soil classes across Australia.<br><br> Pedogenon mapping is a method for stratifying the landscape (similar to soil-landscape units), which can be used to assess past soil change with a space-for-time substitution approach.<br><br> Pedogenon classes are a conceptual taxa that aim to define groups of homogeneous environmental variables. These groups are created applying unsupervised classification to a set of state variables, proxies of the soil-forming factors for a given reference time. The assumption is that the soil-forming processes within these classes (i.e., pedogenons) have been relatively similar over pedogenetic time and thus have developed soils with similar properties. Pedogenon classes can afterwards be divided into subclasses along a gradient from less (i.e., remnant pedogenons) to more anthropogenic pressure on soils (i.e., pedophenons), in an analogous way to the concept of genoform and phenoform (Rossiter and Bouma, 2018). The assessment of changes in soil condition can be done with a space for time substitution within and across pedogenon classes. The conceptualization and methodology for pedogenon mapping and using the classes as basis to assess changes in soil condition are explained with more detail in two publications (Román Dobarco et al., 2021a; Román Dobarco et al., 2021b).<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>Period (temporal coverage; approximately): 1950-2022;</li> <li>Spatial resolution: 3 arc seconds (approx 90&nbsp;m);</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>

The lesser hairy-footed dunnart (<i>Sminthopsis youngsoni, Dasyuridae</i>) is a generalist marsupial insectivore in arid Australia, but consumes wolf spiders (<i>Lycosa spp., Lycosidae</i>) disproportionately often relative to their availability. This project tested the hypothesis that this disproportionate predation is a product of frequent encounter rates between the interactants due to high overlap in their diets and use of space and time. This data set focuses on overlap in the diel acttivity patterns wolf spiders (<i>Lycosa spp.</i>) and the lesser hairy-footed dunnart (<i>Sminthopsis youngsoni</i>) in the Simpson Desert, south-western Queensland Australia. To quantify the temporal activity of lycosids, spotlight surveys were conducted in October 2016 every hour between dusk (19:30 h) and dawn (05:30 h) over three nights. Additionally, remote camera traps were deployed to further quantify patterns in the activity of lycosids and S. youngsoni. Twenty-four Reconyx PC800 HyperfireTM cameras were deployed on 7th July 2016 at Main Camp and left until 12th October 2016 (98 days, or 2352 h of deployment). Images were tagged with camera location, position, angle, camera ID number, species and confidence and date and time data were extracted from each image. This data was used to identify mean activity times for each species (with confidence intervals) and to assess overlap in nocturnal activity patterns between lycosids and S. youngsoni, and thus the potential for competition and predation using the Overlap v 0.2.7 package in R. This data presents a useful example for investigating how the 'Overlap' package works and the benefits it provides.

This is Version1 of the Australian Soil Organic Carbon product of the Soil and Landscape Grid of Australia at 30&nbsp;m resolution.<br /><br /> The map gives a modeled estimate of the spatial distribution of total organic carbon 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- 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).</p> 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: Mass fraction of carbon by weight in the < 2 mm soil material as determined by dry combustion at 900 Celsius;</li> <li>Units: %;</li> <li>Period (temporal coverage; approximately): 1970-2021;</li> <li>Spatial resolution: 1 arc seconds (approx 30&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>Target data standard: GlobalSoilMap specifications;</li> <li>Format: Cloud Optimised GeoTIFF.</li></ul>

This dataset contains global dryland literature abstracts from over the last 75 years (8218 articles) to identify areas in arid ecology that are well studied and topics that are emerging.