<br>This dataset lists the plant communities from Rangeland sites across Australia described by the TERN Surveillance Monitoring team, using standardised AusPlots methodologies. <br /> <br> For each plant community, species richness, relative species abundance, vegetation condition as well as the spatial extent of the community, are described using AusPlots Point intercept, Species richness, Relative species abundance, and Plot and Physical Descriptions methods. Plant species are identified at every site as part of the AusPlots Vegetation vouchering method. The specimen data is updated with the identification date and authority details when species identification is confirmed by the Herbaria.<br />

Data is provided from three survey types: nocturnal drive-by monitoring; ground counts; and exit counts. The nocturnal drive-by monitoring dataset provides information on species presence/absence at 124 sites across Christmas Island. The ground count dataset provides information on numbers of bats observed roosting in trees at known camp sites; while the exit count dataset records counts of bats exiting from the respective camp sites.

The dataset accompanies the paper by Zemunik et al. (2016), which used the Jurien Bay dune chronosequence to investigate the changes in the plant community diversity and turnover in response to long-term soil development. The Jurien Bay chronosequence is located in the Southwest Australian biodiversity hotspot, in an area with an extremely rich regional flora. The dataset consists of both flora and soil data that allows all analyses presented in the paper (Zemunik et al. 2016) to be independently investigated. The dataset is an update to that previously supplied for a prior study (Zemunik et al. 2015; DOI 10.4227/05/551A3DDE8BAF8). The study used a randomised stratified design, stratifying the dune system of the chronosequence into six stages, the first three spanning the Holocene (to ~6.5 ka) and oldest spanning soil development from the Early to Middle Pleistocene (to ~2 Ma). Floristic surveys were conducted in 60 permanent 10 m × 10 m plots (10 plots in each of six chronosequence stages). Each plot was surveyed at least once between August 2011 and March 2012, and September 2012. To estimate canopy cover and number of individuals for each plant species within the 10 m × 10 m plots, seven randomly-located 2 m × 2 m subplots were surveyed within each plot. Within each subplot, all vascular plant species were identified, the corresponding number of individuals was counted and the vertically projected vegetation canopy cover was estimated. Surface (0-20 cm) soil from each of the 420 subplots was collected, air dried and analysed at the Smithsonian Tropical Research Institute in Panama, for a range of chemical and physical properties: total and resin soil phosphorus; total nitrogen and dissolved organic nitrogen; soil total and organic carbon; exchangeable calcium (Ca), iron (Fe), potassium (K), magnesium (Mg), manganese (Mn) and sodium (Na); Mehlich-III extractable iron, magnesium, copper (Cu) and zinc (Zn); and pH (measured in H20 and CaCl2). Nutrient-acquisition strategies were determined from the literature, where known, and from mycorrhizal analyses of root samples from species with poorly known strategies. Most of the currently known nutrient-acqusition strategies were found in the species of the chronosequence. Previous studies in the Jurien Bay chronosequence have established that its soil development conforms to models of long-term soil development first presented by Walker and Syers (1976); the youngest soils are N-limiting and the oldest are P-limiting (Laliberté et al. 2012). However, filtering of the regional flora by high soil pH on the youngest soils has the strongest effect on local plant species diversity (Laliberté et al. 2014). The update involved modification to species names due to taxonomic changes and the inclusion of additional soil analyses, not present in Zemunik et al. (2015). The additional soil variables (additional to DOI 10.4227/05/551A3DDE8BAF8) were exchangeable Ca, K, Al, Mg, Mn and Na, measured for all 420 subplots; and Cu, Fe, Mn and Zn, extracted in Mehlich III solution, for each of the 60 plots. References Laliberté, E., Turner, B.L., Costes, T., Pearse, S.J., Wyrwoll, K.H., Zemunik, G. & Lambers, H. (2012) Experimental assessment of nutrient limitation along a 2-million-year dune chronosequence in the south-western Australia biodiversity hotspot. Journal of Ecology, 100, 631-642. Walker, T.W. & Syers, J.K. (1976) The fate of phosphorus during pedogenesis. Geoderma, 15, 1-19. Zemunik, G., Turner, B.L., Lambers, H. & Laliberté, E. (2015) Diversity of plant nutrient-acquisition strategies increases during long-term ecosystem development. Nature Plants 1, Article number: 15050, 1-4. Zemunik, G., Turner, B.L., Lambers, H. & Laliberté, E. (2016) Increasing plant species diversity and extreme species turnover accompany declining soil fertility along a long-term chronosequence in a biodiversity hotspot. Journal of Ecology.

Experimental sites were established in the northern wheat-growing district of western Australia (Lat -29.66°, Long 116.18°) in August 2017, and monitored through to November 2019. We selected five planted old field sites with similar soil types and vegetation composition. Old fields were planted with York gum (Eucalyptus loxophleba Benth.) and dominant shrubs as understorey. At the time of sampling in 2017, vegetation age ranged from 8–13 years and distance from remnant measured 279 m (± 162 m). We established two control and two treatment plots, each measuring 5 m x 5 m, in the interrows of five planted old field sites. Both treatments were randomly assigned to plots within each site. Between August and early November 2017, we measured a total of 30 response variables at each of the control and treatment plots. Response variables included soil physical and chemical properties (bulk density, penetration resistance, soil moisture, nitrogen and carbon pools), microbial biomass, decomposition rate of roiboos and green tea as per the standardized Tea Bag Index (TBI) protocol, herbaceous vegetation cover and richness, and ant abundance and richness, as well as abundance and richness of ant functional groups.

The QBEIS survey database (formerly CORVEG) contains ecosystem physical and vegetation characteristics, including structural and floristic attributes as well as descriptions of landscape, soil and geologic features, collected at study locations across Queensland since 1982. The resulting survey database provides a comprehensive record of areas ground-truthed during the regional ecosystems mapping process and a basis for future updating of mapping or other relevant work such as species modelling.<br /><br /> Only validated survey data is made publicly available and all records of confidential taxa have been masked from the dataset. Data is accessible from the TERN Data Infrastructure, which provides the ability to extract subsets of vegetation, soil and landscape data across multiple data collections and bioregions for more than 100 variables including basal area, crown cover, growth form, stem density and vegetation height.

<p> AusPlots is a collection of ecological data and samples gathered from a network of plots and transects across Australia by the TERN Surveillance Monitoring team, using standardised methodologies. </p> <p>The AusPlots collection provides the ecological infrastructure to: </p> <ul><li>quantify the richness and cover of plant species (including weeds); </li><li>quantify the diversity and abundance of soil biodiversity; </li><li>assess the state, spatial heterogeneity and structural complexity of vegetation, including life-stage; </li><li>record vegetation and soil parameters that assist with the validation of remotely sensed ecological products;</li><li>analyse vegetation structure and change based on a series of photo reference images; </li><li>better estimate soil carbon and nutrient stocks; </li><li>conduct taxonomic validation studies based on collected plant voucher specimens; </li><li>conduct DNA barcoding and population genetic profiling based on collected tissue samples. </li></ul> <p> Overall this information will progress understanding of ecosystem processes, structure and function, and more generally progress understanding of the response to disturbance and longer-term environmental change of rangeland ecosystems, which underpins sustainable management practice.</p>.