<p>This database contains occurrence data for vertebrates across the Australian Wet Tropics. Species occurrence point data has been collected during field intensive surveys using a variety of sampling methods as well as from the literature and institutional databases. The records are divided into two tables: Misc_records and STD_records. The first contains records collated opportunistically, as well as records collected from literature. The latter is a collection of standardized surveys conducted by Steve E. Williams (JCU). </p> <p> All occurrences were vetted for positional and taxonomic accuracy, and for sensitivity at the state and national levels. Sensitive species records are withheld or have their location generalised following sensitive species rules for processing these records. </p>

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/innov). 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.

Schools Weather and Air Quality (SWAQ) is a citizen science project funded by the Department of Industry, Innovation and Science as part of its Inspiring Australia - Citizen Engagement Program. SWAQ is equipping public schools across Sydney with research-grade meteorology and air quality sensors, enabling students to collect and analyse research quality data through curriculum-aligned classroom activities. The network includes twelve automatic weather stations and seven automatic air quality stations, stretched from -33.5995° to -34.0421° latitude and from 150.6913° to 151.2708° longitude. The average spacing is 10.2 km and the average installation height is 2.5 m above ground level. Optimum site allocation was determined by undertaking a multi-criteria weighted overlay analysis to ensure data representativeness and quality. Six meteorological parameters (dry-bulb temperature, relative humidity, barometric pressure, rain, wind speed, and wind direction) and six air pollutants (SO2, NO2, CO, O3, PM2.5, and PM10) are recorded. Observations and metadata are available from September 2019 for WXT536 + AQT420 stations and from October 2019 for WXT536 stations (refer to Table 1 of the Dataset Guide), thus encompassing the Black Summer bushfire and the COVID-19 lockdown period. Data routinely undergo quality control, quality assurance and publication.

This data release consists of flux tower measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer in semi-arid eucalypt woodland using eddy covariance techniques. It been processed using PyFluxPro (v3.3.0) as described in Isaac et al. (2017), <a href="https://doi.org/10.5194/bg-14-2903-2017">https://doi.org/10.5194/bg-14-2903-2017</a>. PyFluxPro takes data recorded at the flux tower and process this data to a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER). For more information about the processing levels, see <a href="https://github.com/OzFlux/PyFluxPro/wiki">https://github.com/OzFlux/PyFluxPro/wiki</a>. <br /> <br /> The Arcturus greenhouse gas (GHG) monitoring station was established in July 2010, 48 km southeast of Emerald, Queensland, with flux tower measurements starting in June 2011 until early 2014. The station was part of a collaborative project between Geoscience Australia (GA) and CSIRO Marine and Atmospheric Research (CMAR). Elevation of the site was approximately 170m asl and mean annual precipitation was 572mm. The tower bordered 2 land use types split N-S: To the west lightly forested tussock grasslands; To the east crop lands, cycling through fallow periods.The instruments were installed on a square lattice tower with an adjustable pulley lever system to raise and lower the instrument arm. The tower was 5.6m tall with the instrument mast extending a further 1.1m above, totalling a height of 6.7m. Fluxes of heat, water vapour, methane and carbon dioxide were measured using the open-path eddy flux technique. Supplementary measurements above the canopy included temperature, humidity, windspeed, wind direction, rainfall, and the 4 components of net radiation. Soil heat flux, soil moisture and soil temperature measurements were also collected. <br /> For additional site information, see http://www.ozflux.org.au/monitoringsites/arcturus/index.html.<br /><br />

This data release consists of flux tower measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer in semi-arid eucalypt woodland using eddy covariance techniques. It been processed using PyFluxPro (v3.3.0) as described in Isaac et al. (2017), <a href="https://doi.org/10.5194/bg-14-2903-2017">https://doi.org/10.5194/bg-14-2903-2017</a>. PyFluxPro takes data recorded at the flux tower and process this data to a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER). For more information about the processing levels, see <a href="https://github.com/OzFlux/PyFluxPro/wiki">https://github.com/OzFlux/PyFluxPro/wiki</a>. <br /> <br /> The flux station was established in August 2011 while the site supported tropical savanna. The site was part of a deforestation experiment measuring greenhouse gas exchange during conversion of forest to farmland. The land was being cultivated for watermelon production from 2013.<br /><br />

This data release consists of flux tower measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer in semi-arid eucalypt woodland using eddy covariance techniques. It been processed using PyFluxPro (v3.3.0) as described in Isaac et al. (2017), <a href="https://doi.org/10.5194/bg-14-2903-2017">https://doi.org/10.5194/bg-14-2903-2017</a>. PyFluxPro takes data recorded at the flux tower and process this data to a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER). For more information about the processing levels, see <a href="https://github.com/OzFlux/PyFluxPro/wiki">https://github.com/OzFlux/PyFluxPro/wiki</a>. <br /> <br /> The site was classified as box woodland, dominated by two main Eucalypt species:<em>Eucalyptus microcarpa</em> (Grey Box) and <em>Eucalyptus leucoxylon</em> (Yellow Gum).<br /> Elevation of the site is close to 165 m and mean annual precipitation from a nearby Bureau of Meteorology site measured 558 mm. Maximum temperatures ranged from 29.8°C (in January) to 12.6°C (in July), while minimum temperatures ranged from 14.2°C (in February) to 3.2°C (in July). Maximum temperatures varied on a seasonal basis by approximately 17.2°C and minimum temperatures by 11.0°C.<br /><br />The instrument mast is 36m tall. Heat, water vapour and carbon dioxide measurements are taken using the open-path eddy flux technique. Temperature, humidity, wind speed, wind direction, rainfall, incoming and reflected shortwave radiation and net radiation were measured above the canopy. Soil heat fluxes were measured and soil moisture content was gathered using time domain reflectometry. <br><br>

We selected nine study sites, each incorporating three vegetation states: (a) fallow cropland, representing the restoration starting point, (b) planted old field (actively restored site), and (c) reference York gum (E. loxophleba) woodland. Plant species richness and cover All annual and perennial plant species were recorded in spring 2017 within each plot and identified to genus and species level where possible. Nomenclatures follow the Western Australian Herbarium (2017). A point intercept method previously demonstrated to provide objective and repeatable measures of cover (Godínez-Alvarez, Herrick, Mattocks, Toledo & Van Zee 2009; Prober, Standish & Wiehl 2011) was used to quantify cover of individual plant species, total vegetation cover and substrate types (i.e., bare ground, litter cover, plant cover). Ground cover, individual species, and canopy cover intercepting at every 2 m along four parallel, evenly spaced 50 m transects across each plot were recorded using a vertically placed dowel (8 mm wide, 2 m tall), resulting in 100 intercepting points per plot. For planted old fields, transects were placed parallel to planting rows, with two centred on rows and two centred between rows. This approximately represented the relative abundance of planted rows and non-planted inter-rows. If a species was recorded in the plot but did not intercept the dowel on any transect it was assigned 0.5 points. This method provided a measure of relative abundance (percentage cover) of plant species across the plot. To calculate species richness and cover across different life history and growth forms, species were classified into the following groups: total, native trees, native shrubs, native non – planted shrubs, native grasses, native perennial forbs, native annual forbs, exotic grasses and exotic annual forbs using the Western Australian Herbarium (2017) classification. Woody debris and leaf litter surveys Leaf-litter dry mass was estimated by collecting leaf-litter from five randomly placed 25 cm x 25 cm quadrats along two 50 m transects across each plot. Litter was stored in paper bags for transportation and then oven dried for 36 hours at 60 °C. The dried litter was weighed to 3 decimal points. Cover of fine and coarse woody debris and litter depth was estimated at every meter along two 20 m transects for each plot. Woody debris was classified by diameter. Length, max and min diameter was measured for all logs with a diameter greater than 10 cm.

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://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html'>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="https://awo.bom.gov.au/assets/notes/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.

We used Digital Soil Mapping (DSM) technologies combined with the real-time collations of soil attribute data from TERN's recently developed Soil Data Federation System, to produce a map of Australian Soil Classification Soil Order classes with quantified estimates of mapping reliability at a 90&nbsp;m resolution.

This data release consists of flux tower measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer in semi-arid eucalypt woodland using eddy covariance techniques. It been processed using PyFluxPro (v3.3.0) as described in Isaac et al. (2017), <a href="https://doi.org/10.5194/bg-14-2903-2017">https://doi.org/10.5194/bg-14-2903-2017</a>. PyFluxPro takes data recorded at the flux tower and process this data to a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER). For more information about the processing levels, see <a href="https://github.com/OzFlux/PyFluxPro/wiki">https://github.com/OzFlux/PyFluxPro/wiki</a>. <br /> <br /> The Wombat State Forest site is a secondary re-growth forest that was last harvested in 1980. Dominant tree species are <em>Eucalyptus obliqua</em> (messmate stringybark), <em>Eucalyptus radiata</em> (narrow leaf peppermint) and <em>Eucalyptus rubida</em> (candlebark) with an average canopy height of 25m. The understorey consists mainly of patchy grasses and the soil is a silty-clay overlying clay. The forest is managed by the Department of Sustainability and Environment and management includes selective harvesting and prescribed burning regimes. The climate of the study area is classified as cool-temperate to Mediterranean zone with cold and wet winters (May-Aug) and warm and dry summers (Dec-Feb) with a temperature range: 1-30 °C and mean annual air temperature (2001-2012): 12.1°C. Annual rainfall is approximately 871 mm (142 year long-term average). Coherent automated measurements of soil greenhouse gas fluxes (CO2, CH4 and N2O) were collected using a trailer-mounted mobile laboratory – Fourier transform infra-red (FTIR) spectrometer from 2010 to 2016. Measurement height was 30m but increased to 33m from January 2017<br /><br />