From 1 - 10 / 31
  • Categories    

    The dataset provides information on the Specific Leaf Area (SLA) measurements of the species <i>Dodonaea viscosa</i> from the TERN AusPlots.

  • Categories    

    <br>Tropical rainforests play a powerful role in mediating the global climate through the exchange and storage of carbon and water. Climate change is expected to generate higher atmospheric water demand in many areas, potentially increasing the rate of evaporation. In this study, we show that higher evaporative demand may in fact lead to lower fluxes of water from tropical rainforests and a reduced capacity of these forests to store carbon.</br> The record contains meteorological and forest inventory data in addition to data on soil water potential, sapflow measurements and tree hydraulic vulnerability measures from Robson Creek and Cow Bay study sites in Far North Queensland. The measurements occurred over a period of two years form 2019 to 2020.

  • Categories    

    This data contains leaf area index calculated from Digital Cover Photography images taken at the core 1-ha plot within the Tumbarumba Wet Eucalypt site in 2014.

  • Categories    

    This data contains leaf area index calculated from Digital Hemispheric Photography images taken at the core 1-ha plot within the Whroo Dry Eucalypt site between 2014 - 2016.

  • Categories    

    There are presence absence records for vegetation and matched hydrological data from 687 1 x 1 m quadrats recorded from 11 wetlands and wetland complexes (28 sampled hydrological gradients (referred to as transects) across the upper and lower southeast of South Australia. Plant data were collected in spring 2013. Hydrological monitoring data at each site consisted of continuous (6 hourly) surface water level data from a state agency monitoring network. Observed water levels at the monitoring instrument on the day of monitoring were related to the observed depth of water at each quadrat, assuming a flat, level water surface and obtain a datum for each quadrat relative to the monitoring instrument. The continuous monitoring record was then used to calculate a range of different hydrological predictors indicating the variation at each quadrat. The hydrological dataset provided are the univariate summary statistics recording different aspects of surface water dynamics for each quadrat. Hydrological predictors (sum-exceedance value, hydroperiod and maximum inundation depth) were calculated for annual and seasonal periods in the three-years prior to plant data collection. See metadata and relevant publication for additional details on calculation. Hydrological predictors for each quadrat are provided in a single matrix of sites by predictors, with relevant location details for the quadrat (xy coordinates, site, transect). Included is a single electrical conductivity class for each transect (ordinal variable - low moderate, high - see metadata). Vegetation data are provided as a single matrix (quadrats x plant functional group) showing presence absence of each functional group in each quadrat. There is also a lookup table giving the assignment of each plant species to a plant functional group.

  • Categories    

    This data contains leaf area index calculated from Digital Cover Photography images taken at the Samford Peri-Urban site between 2014 - 2016

  • Categories    

    This data contains leaf area index calculated from Digital Cover Photography images taken at four 1-ha plots within the Great Western Woodlands site between 2013 - 2015

  • Categories    

    This data contains leaf area index calculated from Digital Cover Photography images taken at the Calperum Mallee core 1-ha site between 2013 - 2015.

  • Categories    

    This data contains leaf area index calculated from Digital Hemispheric Photography images taken at the core 1-ha plot within the Robson Creek Rainforest site in 2014.

  • Categories    

    This data contains leaf area index calculated from Digital Hemispheric Photography images taken at the core 1-ha plot within the Warra Tall Eucalypt site in 2015.