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.

This dataset contains records of vascular plant species from selected TERN AusPlots in South Australia. Preparation from raw data involved extraction of all vouchered species from the plots, the removal of intra-specific taxa (only genus and species used to define individual taxa) and removal of duplicate records and those not determined to species. Species list has been appended in this record.

Ground layer vascular plant species identity and projective foliage cover (PFC) data were collected from four permanently marked 50x10 metre plots in north Queensland on a three monthly frequency for three years. Ten 0.5 square metre quadrats were used for sampling at each occasion at each site and the data pooled and averaged. Refer to Neldner, V.J., Kirkwood, A.B. and Collyer, B.S. (2004). Optimum time for sampling floristic diversity in tropical eucalypt woodlands of northern Queensland. The Rangeland Journal 26: 190-203 for more information. Note: Spreadsheet compiled in 2021 from original data collection records.

This product has been superseded and will not be processed from early 2023. Please find the updated version 3 of this product here <a href="https://portal.tern.org.au/metadata/24072">Seasonal dynamic reference cover method - Landsat, JRSRP algorithm version 3.0, Queensland Coverage</a>. The seasonal dynamic reference cover method images are created using a modified version of the dynamic reference cover method developed by <a href="https://doi.org/10.1016/j.rse.2012.02.021">Bastin et al (2012)</a>. This approach calculates a minimum ground cover image over all years to identify locations of most persistent ground cover in years with the lowest rainfall, then uses a moving window approach to calculate the difference between the window's central pixel and its surrounding reference pixels. The output is a difference image between the cover amount of a pixel's reference pixels and the actual cover at that pixel for the season being analysed. Negative values indicate pixels which have less cover than the reference pixels. <br> The main differences between this method and the original method are that this method uses seasonal fractional ground cover rather than the preceding ground cover index (GCI) and this method excludes cleared areas and certain landforms (undulating slopes), which are considered unsuitable for use as reference pixels.

This data set contains information on Electrical Conductivity and pH from bore water from two plots, Blackbutt and Salmongum the Great Western Woodland Site.

This dataset contains predictions of the aboveground biomass density (AGBD) for Australia for 2020. Data were generated by the Global Ecosystem Dynamics Investigation (GEDI) NASA mission, which used a full-waveform LIDAR attached to the International Space Station to provide the first global, high-resolution observations of forest vertical structure. Data include both Level 4A (~25&nbsp;m footprints) and Gridded Level 4B (1&nbsp;km x 1&nbsp;km) Version 2. The Australian portion of the data was extracted from the original global datasets <a href="https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2056">GEDI L4A Footprint Level Aboveground Biomass Density</a> and <a href="https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2299">GEDI L4B Gridded Aboveground Biomass Density</a>.

The Australian Phenology Product is a continental data set that allows the quantitative analysis of Australia’s phenology derived from MODIS Enhanced Vegetation Index (EVI) data using an algorithm designed to accommodate Australian conditions, described in Xie et al. 2023. The product can be used to characterize phenological cycles of greening and browning and quantify the cycles’ inter and intra annual variability from 2003 to 2018 across Australia. Phenological cycles are defined as a period of EVI-measured greening and browning that may occur at any time of the year, extend across the end of a year, skip a year (not occur for one or multiple years) or occur more than once a year. Multiple phenological cycles within a year can occur in the form of double cropping in agricultural areas or be caused by a-seasonal rain events in water limited environments. Based on per-pixel greenness trajectories measured by MODIS EVI, phenological cycle curves were modelled and their key properties in the form of phenological curve metrics were derived including: the first and second minimum point, peak, start and end of cycle; length of cycle, and; the amplitude of the cycle. Integrated EVI under the curve between the start and end of the cycle time of each cycle is calculated as a proxy of productivity.

The record contains information on rainfall data recorded between 1995-2011 from 17 rain gauges across the Calperum Mallee Site, Calperum Station, South Australia. Data on mean monthly and annual rainfall and standard deviation is provided for each site, along with annual rainfall totals.

Mating system and fitness data for families of <em>Eucalyptus socialis</em> grown in common garden experiments. Families collected across a fragmentation gradient. Open-pollinated progeny arrays were collected and reared in the common garden experiments. These open-pollinated progeny arrays were also genotyped at microsatellite loci to generate the mating system data. Data showed association between fragmentation on mating system, which in turn impacted fitness. Please contact owner prior to use.

This dataset comprises spatially and temporally dynamic estimates of the monthly latent heat flux (λE) and sensible heat flux (H) for all of Australia. The available energy (A, being net radiation [Rn] less the gound heat flux [G]) can be obtained by adding the λE and H datasets provided. Energy variables have been provided as hydrological equivalent units of depth, normalised to daily rates (mm/d). TERN OzFlux Surface Energy Balance (SEB) data were used to scale MODIS-based covariates of surface temperature less air temperature (Ts – Ta) and Rn using a Spatial and Temporal General Linear Model (ST-GLM) to third order. The ST-GLM SEB model was implemented across all of Australia on a 0.005° spatial grid (~ 500 m) on a monthly timestep from March 2000 through June 2023. Coefficients of the model were determined from the OzFlux network of eddy covariance flux tower data. Three flux tower sites were used to independently validate the accuracy of the model, being Calperum, SA, Howard Springs, NT, and Tumbarumba, NSW. The mean absolute difference (MAD) for λE, H and A was estimated as: 0.37, 0.39 and 0.34&nbsp;mm/d, respectively. The relative errors determined by the MAD percentage (MADP) for λE, H, and A were estimated to be: 16%, 26%, and 9%, respectively. This dataset represents a new pathway for operational regional- to global-scale estimation of dynamic SEB variables.