<p>This cloud mask collection was generated for daytime Himawari-8/9 imagery using a newly developed algorithm by CSIRO (Commonwealth Scientific and Industrial Research Organisation), collaboratively among research teams, for the Australian continent and surrounding waters. The product was extensively validated against space-borne LiDAR to ensure its quality. The product is provided here in a regular latitude/longitude grid. It is also available in the original Himawari (geostationary) projection (WGS84, sub-satellite longitude = 140.7&deg;E and satellite altitude = 35785863 meters). Please contact the authors for accessing the data, which is located on the Australian National Computational Infrastructure (NCI). Currently, a near-real-time algorithm/processor is being developed to improve data availability, and to extend production to Himawari-10 (2028-2045).</p>

This dataset comprises a comprehensive collection of plant tissue samples representing vascular plants sampled from TERN Ecosystem Surveillance monitoring plots across Australia. Derived from the plant voucher specimens, these tissue samples are critical for accurate species identification and verification, supporting a complete inventory of vascular plant species at each plot. They also serve as reference material for DNA barcoding and stable isotope analyses. Collected following the standardised Ecosystem Surveillance methodology, the dataset includes over 76,000 archived samples housed at the TERN Australia Soil and Herbarium Collection, located at the University of Adelaide's Waite Campus.<br></br> Each record includes detailed metadata such as voucher barcode, site and visit information and sampling details. Plant tissue samples are accessible and available for loan upon request through the EcoPlots Samples portal via an Expression of Interest.

This dataset comprises a comprehensive collection of plant voucher specimens representing vascular plants sampled from TERN Ecosystem Surveillance monitoring plots across Australia. These specimens are essential for accurate species identification and verification, providing a complete inventory of vascular plant species present at each plot. Collected following the standardised Ecosystem Surveillance methodology, the dataset includes over 57,000 accessioned vascular plant specimens housed at the TERN Australia Soil and Herbarium Collection, located at the University of Adelaide's Waite Campus.<br></br> Each record includes detailed metadata such as voucher barcode, site and visit information, sampling details, and digitised images where available. Plant voucher specimens are accessible and available for loan upon request through the EcoPlots Samples portal via an Expression of Interest.

The data set contains information on the soil water content at various depths in the Samford Ecological Research Facility (SERF), Samford Peri-Urban Site. Information on soil water content is provided from two sensors, i.e., 1) Sentek Solo, for high frequency sampling and 2) Sentek Diviner, for coarser resolution sampling.

This data contains vegetation cover, ground cover, tree density and stand basal area data across a multi-century time-since-fire sequence derived from growth ring-size relationships in fire-sensitive <em>Eucalyptus salubris</em> woodlands.

The dataset contains records of Robber Crab (<i>Birgus latro</i>) mortality across Christmas Island, including location co-ordinates and details of sex and thoracic length. To manage the impact of road mortality on the species, this monitoring project is designed to assess spatial variation in road mortality. Basic data are collected at the site (sex, size, date, coordinates).

The record contains information on beetle succession in decaying <i>Eucalyptus obliqua</i> logs, from 1999-2009. Data on beetle species identification, field sampling notes, and collection details from eucalyptus logs across the decade range from 1999 - 2009 are provided.

These datasets provide the data underlying the publication on <i>"Lines in the sand: quantifying the cumulative development footprint in the world’s largest remaining temperate woodland"</i> <em> https://link.springer.com/article/10.1007/s10980-017-0558-z. </em>. The datasets are: (A) data in csv format: [1] development footprint by sample area: Information on the 24, ~490 km^2 sample areas assessed in the study, including the different infrastructure types (roads, railways, mapped tracks, un-mapped tracks which have been manually digitized in the study using aerial imagery and hub infrastructure such as mine pits and waste rock dumps, also manually digitized in the study). Also contains some key co-variables assessed as potential explanatory variables for development footprint. The region-wide modelling of development footprint found strong positive effects of mining project density and pastoralism, as well as a highly significant negative interaction between the two. At low mining project densities, development footprints are more extensive in pastoral areas, but at high mining project densities, pastoral areas are relatively less developed than non-pastoral areas, on average. [2] Great Western Woodlands (GWW) 20 km grid: The datasets provides data for the 20x20 km grid placed over the whole GWW and used for the regional estimation of development footprint, linear infrastructure density, and linear infrastructure type based on the region-wide analysis. Data is for each cell in the grid and provides the total length of roads in that grid cell, MINEDEX mining projects, pastoral status, etc. This dateset was used to project the data from the 24 study areas across the whole of the Great Western Woodlands and calculate region-wide estimates of development footprint and linear infrastructure lengths. [3] disturbance by patch: This dataset provides the data for each patch for the analysis of patch-level drivers of development footprint, which was performed to gain further insights into the effects of other landscape variables that what could be gleaned from the region-wide analysis. For this analysis, we divided sample areas into polygonal patch types, each with a unique combination of the following categorical co-variables: pastoral tenure, greenstone lithology, conservation tenure, ironstone formation, schedule-1 area clearing restrictions, environmentally sensitive area designation, vegetation formation, and sample area. For each patch type (n=261), we calculated the following attributes: a) number of mining projects, b) number of dead mineral tenements, c) sum of duration of all live and dead tenements, d) type of tenements (exploration/prospecting tenement, mining and related activities tenement, none), e) primary target commodity (gold, nickel, iron-ore, other), f) distance to wheatbelt, and g) distance to the nearest town. [4] mapped versus digitized tracks: This dataset provides mapped and un-mapped track widths, measured using high-resolution aerial imagery at at least 20 randomly-generated locations within each of 24 sample areas. Pastoral tenure and mining intensity for each sample area are included for analysis purposes. [5] edge effect scenarios: Hypothetical edge effect zones were created, based on effect zones gleaned from the literature and arranged under three scenarios, to reflect potential risks of offsite impacts in areas adjacent to development footprints observed (see appendix 3 of article). The calculated proportion of the entire GWW within edge effect zones varied from ~3% under the conservative scenario to ~35% under the maximal scenario. Within the range of development footprints observed in this study, the proportion of a landscape that lies within edge effect zones increases hyperbolically with the number of mining projects, and approaches 100% in the maximal scenario, 60% in the moderate scenario, and ~20% under the conservative scenario. shapefiles: [6] Great Western Woodlands boundary, [7] sample areas (layer file shows sample areas by category).

<p>This dataset comprises a comprehensive archive of soil subsite samples collected from TERN Ecosystem Surveillance monitoring plots across Australia. In addition to the 1-meter soil pit, soil subsite samples are taken from nine locations across the 1-hectare monitoring plot from three depths (0-10cm, 10-20cm and 20-30cm). Each of the nine subsites are selected to represent the variation in micro habitats across the monitoring plot. Collected following the standardised Ecosystem Surveillance methodology, the dataset includes over 33,600 soil subsite samples archived in the TERN Australia Soil and Herbarium Collection, located at the University of Adelaide's Waite Campus.</p> <p>Each record includes detailed metadata such as voucher barcode for soil collected from the three depths at each of the nine subsites, site and visit information and sampling details. Soil subsite samples are accessible and available for loan upon request through the EcoPlots Samples portal via an Expression of Interest.</p>

This dataset contains the effect of stress and herbivory on the establishment of alternate provenances of a foundation tree species. This data relates to plant fitness and could be used for more broader studies in this area. We established a common garden experiment within a 238 ha restoration site owned and managed by the South Australian Water Corporation (SA Water), near the township of Clarendon (-35.0882°S, 138.6236°E). We grew ca.1500 seedlings sourced from one local and two non-local provenances of <i>Eucalyptus leucoxylon</i> to test whether local provenancing was appropriate. The three provenances spanned an aridity gradient, with the local provenance sourced from the most mesic area and the distant provenance sourced from the most arid. We explored the effect of provenance on four fitness proxies after 15 months, including survival, above-ground height, susceptibility to insect herbivory, and pathogen related stress.