This dataset contains soil microbial and genomic analysis files of 9 soil samples from each of three plots at Fletcherview, Northern Queensland (NQ) processed by the <a href='https://agrf.org/'>Australian Genome Research Facility Ltd (AGRF) </a>. The files are available as compressed FastQ formatted sequence files.<br> For the nine Far North Queensland (FNQ) new plots (3 plots in Fletcherview and six plots at Wambiana), soil sampling additional to that done as component of plot installation by TERN have been undertaken. This is aligned with potential future exploratory work on soil eDNA proposed for WA. The protocol is a modified version of the <a href="https://doi.org/10.1186/s13742-016-0126-5">BASE sampling protocol</a>, combined with soil sampling as per <a href="https://www.tern.org.au/wp-content/uploads/TERN-Rangelands-Survey-Protocols-Manual_web.pdf">White et al. (2012)</a>. <br> DNA extracted from the soil samples and Metagenomics 10Gbp (giga base pairs) bundle as per AGRF protocol.

This data set is the result of the investigation on the response of littoral and floodplain vegetation and soil moisture flux to weir pool raising in 2015. The data was collected over 18 months between August 2015 and December 2016- before, during and after the weir pool levels were raised. The data set contains information on Tree Condition including crown extent and density, bark form, epicormic growth and state, reproduction, crown growth, leaf die off and damage, and mistletoe. Leaf Water Potential, taken predawn and in the middle of the day. Plant Area Index/Canopy Cover measurements using hemispherical photos. Soil Chemistry measurements- total soil moisture (gravimetric water content; %), soil suction (or soil matric potential), Electrical Conductivity and soil pH.

This data contains soil physico-chemical characteristics collected at the Alice Mulga site in 2013.

The Soil Moisture Integration and Prediction System (SMIPS) produces national extent daily estimates of volumetric soil moisture at a resolution of approximately 1km or 0.01 decimal degrees. SMIPS also generates an index of between 0-1 which approximates how full the 90cm metre soil moisture store is at a particular location and time. The SMIPS model itself consists of two linked soil moisture stores, a shallow quick responding 10cm upper store and a deeper, slower responding 80cm store. SMIPS is parameterised using physical properties from the <a href ='https://www.clw.csiro.au/aclep/soilandlandscapegrid/'>Soil and Landscape Grid of Australia </a>and takes a data model fusion approach for model forcing. Version 1.0 of the SMIPS model uses precipitation and potential evapotranspiration data from the Bureau of Meteorology’s <a href="http://www.bom.gov.au/water/landscape/assets/static/publications/AWRALv6_Model_Description_Report.pdf">AWRA Model</a>. In addition to version 1.0 of the model, an experimental version of the model is available for user testing. This version of the model uses precipitation data supplied by an experimental CSIRO daily rainfall surface generated using spatial data from the NASA Global Precipitation Mission as a base and enhanced using rainfall observations from the Bureau of Meteorology (BoM) rainfall gauge network, and various landscape covariates, processed using a machine learning approach. <br> To help increase model accuracy, the internal SMIPS model states are adjusted or ‘bumped’ by daily observational data from the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) satellite mission.

This data contains soil description, bulk density and soil moisture characteristics collected at the Calperum Mallee site in 2012.

We generated a total of 2,313,977 16S archaeal raw reads across the 36 replicates (64,277 ± 23,335 SD per replicate). A total of 2,299,955 archaeal sequences (63,888 ± 23,473 SD per replicate) and 1,937 archaeal OTUs (54 ± 20 SD per replicate) remained for further analysis after quality filtering. The OTU data provide information on archaeal flux at an active restoration site at Mt Bold, a water catchment reserve of the Mt Lofty Ranges in South Australia, through a stagger of years and can be used accordingly.

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

The authors analyzed a total of 3,002,411 quality-filtered bacterial 16S rRNA gene sequences in the 48 technical replicates across 8 revegetation chronosequence sites, consisting of 3,316 OTUs. Nine bacterial phyla dominated this dataset, including Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes, Gemmatimonadetes, Planctomycetes, Proteobacteria and Verrucomicrobia.The OTU data provide information on bacterial flux at this restoration site through a stagger of years and can be used accordingly.

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

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