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This dataset presents the demographic monitoring (growth and survival) of 81 tree species based on repeated stem measurement data from 20, 0.5 ha (100 m x 50 m) permanent moist forest plots in northern Queensland, Australia from 1971 to 2019, as well as four additional plots of 0.1 to 1 ha whose monitoring began in the 2000s. The plots have a rainfall range of 1200 to over 6000 mm, represent eleven vegetation types, six parent materials, and range from 15 m to 1500 m above sea level. Except for minor disturbances associated with selective logging on two plots, the plots were established in old growth forest and all plots have thereafter been protected. Plots were regularly censused and at each census the diameter at breast height (DBH) of all stems ≥10 cm DBH were recorded. We only report the data for the 81 species studied in Bauman et al. 2022 (Nature), here. We also provide the climatology of these plots as well as the temperature, vapour pressure deficit, and maximum climatological water deficit of all intervals separating consecutive censuses, as used in the analyses of Bauman et al. 2022.
Data on weather conditions at the Warra Tall Eucalypt site collected between 2004 - 2012. Data includes daily maximum and minimum temperatures, wind speed, wind direction, rainfall and humidity.
A total of 53 native Australian species (52x C3, 1x C4) were sampled from 22 plant families and 7 growth forms along a transect in WA spanning 9.56 degrees latitude and 6.85 degrees longitude. Samples were collected using the nationally-accepted AusPlots Rangelands methodology. Samples were stored to preserve isotopic signatures and analysed using standard techniques for mass spectroscopy, including internationally-calibrated standards. Technical replicates of 13% showed very low drift (0.07).
This dataset contains information on vegetation at a set of field sites along with associated environmental data extracted from spatial layers and selected ecological statistics. Measurements of vascular plants include species, growth form, height and cover from 1010 point intercepts per plot as well as systematically recorded absences, which are useful for predictive modelling and validation of remote sensing applications. The derived cover estimates are robust and repeatable, allowing comparisons among environments and detection of modest change. The field plots span a rainfall gradient of 129-1437 mm Mean Annual Precipitation ranging from aseasonal to highly seasonal. The dataset consists of a processed version the AusPlots Rangelands dataset with three components: 1) a site table with locality, environmental and summary ecology statistics for each plot; 2) a set of compiled point intercept records identified by individual hits, site visits and plots and; 3) a processed species percent cover against site/visit matrix for ecological analysis. The data have re-use potential for studies on vegetation properties in the Australian rangelands or as a species presence/absence dataset for testing ecological models. The dataset also provides opportunities for generic application such as testing community ecology theories or developing or demonstrating community ecology software, whether using the raw point by point intercept data or the derived percent cover matrix.
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.