This dataset provides understorey herbaceous biomass, ground cover and overstorey woody cover response to different fire regimes over a twenty year period at a grassland and open woodland in the tropical savannas of northern Australia. BOTANAL was used to assess understorey herbaceous biomass. Woody canopy cover was derived from digital analysis of oblique aerial imagery taken from a helicopter at the site in 1995 and again in 2013. Woody cover (tree basal area and canopy cover) was also assessed using a bitterlich gauge on BOTANAL ground based transects in 2009. The data could be used to calibrate models of herbaceous growth and woody cover change in response to long term fire. It may be useful for assessing climate change impacts on aboveground carbon sequestration. The fire regimes tested were of varying frequency (every 2, 4 and 6 years) and season (June vs. October) of fire compared to unburnt controls on woody cover and pasture composition. Sites were open to grazing by cattle.

<p>The dataset contains raw records on the frequency and % cover of Australian plant species stored in TERN's AEKOS as at 23 February 2017. There is information on basal area data in addition.The data includes plant records for the following datasets: [1] Australian Ground Cover Reference Sites Database, [2] Biological Survey of South Australia - Vegetation Survey - Biological Database of South Australia, [3] Atlas of NSW database: VIS flora survey module, [4] Queensland CORVEG Database, [5] TERN AusPlots Rangelands, [6] Transects for Environmental Monitoring and Decision Making (TREND) (2013-present) and the [7] TREND-Biome of Australia Soil Environments (BASE). </p> Soil samples for physical structure and chemical analysis (14 sites) throughout Australia were also incorporated in addition (starting 2013). The sites were: [1] AusCover Supersites SLATS Star Transects, [2] Biological Survey of the Ravensthorpe Range (Western Australia), [3] Biological Survey of South Australia - Roadside Vegetation Survey, [4] Biological Database of South Australia, [5] South-Western Australian Transitional Transect (SWATT), [6] Koonamore Vegetation Monitoring Project (1925-present), [7] Desert Ecology Research Group Plots (1990-2011) and Long Term Ecological Research Network (2012-2015), Simpson Desert, [8] Western Queensland, Australia (plants only) and [9] the TERN AusPlots Forest Monitoring Network - Large Tree Survey - 2012-2015. In total, 97,035 sites were extracted and downloaded for individual and population levels. The download package contains site location files, separate data files for individual and population levels, citation details for individual surveys and notes on how to interpret the download.

River sites were sampled during the summers of 2008/09 and 2009/10 in a survey designed to identify correlations between commonly used river condition variables and grazing land-use. Potential stream sites in northern Tasmania were screened by catchment size, northing and slope, and according to attributes aimed at minimising confounding variables, maintaining broad consistency in landscape and geomorphological context, and promoting independence among sites. A set of 27 survey sites was selected across a gradient from low to high proportion of land under grazing in their upstream catchments. Catchment sizes varied from 20-120 km2 and proportion grazing from 0-80%. Macroinvertebrates were sampled using Surber sampler. All macroinvertebrates within a 20% sub-sample identified to family and counted, with individuals from the insect orders Ephemeroptera, Plecoptera and Trichoptera identified to genus/species (by Laurie Cook, UTAS). Algal abundance was estimated at each site as the proportion of algal cover and as areal density of benthic chlorophyll a. Physical data variables collected were: water temperature, conductivity, turbidity, pH, total alkalinity, nitrate+nitrate, dissolved reactive phosphorus, total nitrogen, total phosphorus, overhead shading, the proportion of fine sediments within the sampled riffle zone, accumulated abstraction index and accumulated regulation index. For more information see: See Magierowski RH, Read SM, Carter SJB, Warfe DM, Cook LS, Lefroy EC and Davies PE. Inferring landscape-scale land-use impacts on rivers using data from mesocosm experiments and artificial neural networks. PLOS ONE.