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These datasets consist of soil maps generated to assess baselines, drivers and trends for soil health and stability within the NSW Regional Forest Agreement (RFA) regions. <br> The maps are organised into empirical soil maps, digital soil maps, and data cube maps. <br> Empirical soil maps consists of four products. Maps include topsoil pH, carbon, Emerson Aggregate Stability and Soil Profile Quality Confidence. Each map consists of 2,162 units. Maps were generated using the most representative soil profile for each unit available within the Soil and Land Information System (SALIS). The 2008 woody vegetation coverage was used as baseline. Maps reflect values when the sampling occurred with temporal changes not being accounted for. Locations with missing or of poor quality data are identified, providing a confidence rating map as part of the evaluation process.<br> Digital soil maps include map products of key soil condition indicators covering the Regional Forest Agreement regions of eastern NSW. Raster maps of key soil indicators, such as soil carbon, pH, bulk density, hillslope erosion and others, were created at 100 m resolution. For each key soil indicator, maps include baseline (approximately 2008) levels as well as trends of change resulting from different human and natural disturbances such as forest harvesting, uncontrolled stock grazing, climate change and bush fire. <br> Data cube maps include time series of soil organic carbon (SOC) between January 1990 and December 2020 for the Regional Forest Agreement regions of eastern NSW. Products provide estimates of SOC concentrations and associated trends through time. Modelling was carried out using a data cube platform incorporating machine learning space-time framework and geospatial technologies. Important covariates required to drive this spatio-temporal modelling were identified using the Recursive Feature Elimination algorithm (RFE). <br> A web mapping application on the NSW Spatial Collaboration Portal depicts these datasets. Access the webapp through the link below:<br> https://portal.spatial.nsw.gov.au/portal/home/item.html?id=af9c71935f024f4a8f64cb39f5eba007
We investigated recovery of soil chemical properties after restoration in semi-arid Western Australia, hypothesising that elevated nutrient concentrations would gradually decline post planting, but available phosphorus (P) concentrations would remain higher than reference conditions. We used a space-for-time substitution approach, comparing 10 planted old field plots with matched fallow cropland and reference woodlands. Sampling on planted old fields and reference woodland plots was stratified into open patches and under tree canopy to account for consistent differences between these areas. Soil samples to 10 cm depth were collected at 20 points across 30 plots. Ten samples were randomly collected and combined from locations beneath trees and a further 10 samples collected in gaps and combined, resulting in one soil sample for beneath tree canopy and another one for gap areas. Sampling occurred in autumn 2017 to capture potentially high concentrations of soil nitrate following the seasonal die-back of exotic annual plants typical of this Mediterranean-climate region. Samples were stored at 4 °C in plastic zip-lock bags until delivery to the CSBP Limited (Bibra Lake, WA) laboratories. Chemical parameters measured were plant available P (Colwell), plant available N (nitrate and ammonium), total N, plant available potassium (Colwell) and plant available sulphur (KCl 40). Lastly, electrical conductivity, pH (H2O, CaCl2), and soil texture were quantified as differences among plots could affect nutrient availability and soil chemistry. Soil available nutrients were also measured using Plant Root Simulator (PRS)TM resin probes (Western Ag Innovations, 2010, https://www.westernag.ca/inn). Probes contain anion or cation exchange membranes within a plastic stake. The membranes act as a sink for collecting nutrients and continuously absorb ions during deployment. Four anion and cation probes were placed vertically in the top 15 cm of soil at each stratification. Probes were left in the ground for three months during the growing season, from August to November 2017. This period was deemed suitable for semi-arid regions to achieve sufficient nutrient uptake but not too long to saturate probes. After removal, probes were cleaned with deionized water and sent to Western Ag Innovations (Canada) for analysis. All soil chemical analyses were conducted under laboratory conditions using standard test procedures. PRS probe nutrients are reported as micrograms/10cm2/time.
This data contains soil physico-chemical characteristics collected at the Daintree Rainforest, Cow Bay site between 2011 - 2014.
This data contains soil physico-chemical characteristics collected at the Robson Creek Rainforest site between 2011 - 2014.
Leaf trait associations with environmental variation in the wide-ranging shrub Dodonaea viscosa subsp. angustissima (Sapindaceae) Part 1: Latitude
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 TREND (PSRF)- Terrestrial Ecosystems project initiated a landscape-scale monitoring transect along the Adelaide Geosyncline region in southern Australia, initially spanning approximately 550 km. The aim was to examine spatial drivers of species composition and to isolate the influence of climate on whole vegetation community composition and therefore inform on-going monitoring of the impact of climate change. Specific questions were: 1. What are the most important spatial drivers of species and phylogenetic composition along landscape-scale environmental gradients? 2. Can the answer to Question 1. inform selection of suitable spatial analogues for climate change? 3. How can a framework for assessing spatial drivers be used to monitor and interpret shifts in species composition due to climate change? The dataset consists of site and species records (see attachments) for plots established along the Adelaide Geosyncline for the TREND project. Data consist of vascular plant species composition (presence-abundance/absence) within 900m<sup>2</sup> plots plus site data, including aspect and soil properties. Data have been used to analyze changes in composition with geographic and environmental differences and as a baseline for monitoring.
This data contains soil physico-chemical characteristics collected at the Daintree Rainforest, Cape Tribulation site between 2007 - 2015.
Soil collection and analysis of chemical and physical attributes was carried out at the Great Western Woodlands site to provide contextual data for the Biomes of Australian Soil Environments (BASE) soil microbial diversity project.
This data contains soil physico-chemical characteristics collected at the Whroo Dry Eucalypt site in 2015.
This data contains soil physico-chemical characteristics collected at the Cumberland Plain site in 2013.