The ACEAS working group has developed a framework to evaluate the extent to which fire regimes are driven by climate and other environmental variables, and whether these fire and environment relationships concord with: (a) predictions of the group of conceptual models recently developed; and (b) predictions of process-based models. The dataset provides a distribution of major fire regimes niches throughout Australia ordered according to decreasing annual net primary productivity. The dataset published is the distribution of major fire regimes niches throughout Australia.

This product provides locations of areas affected by fire including the approximate day of burning. Inputs are daily day time observations from MODIS sensors on Terra and Aqua. Observations are atmospherically corrected and the resulting time series is investigated for sudden changes in reflectance, persistent over multiple days. Variations in observation and illumination geometry are taken into account through application of a kernel driven Bidirectional Reflectance Distribution Function (BRDF) model.

The dataset consists of species identity and projective foliage cover (PFC) of ground layer vascular plants from five sites located near Mareeba, in northern Queensland. The sites are located in eucalypt communities with altitudes ranging from 380 to 840 m. Data have been collected annually since 1992, in April and May, i.e. during the annual peak of plant species richness. At each site, data collection is carried out using ten 0.5 m² quadrats deployed within a permanently marked 50 x 10 m plot. For each quadrat, all plant species visible above ground are identified and sampled. PFC data for each species from the ten quadrats are averaged. Any additional species occurring within the 50 x 10 m plot is also recorded and assigned a PFC of 0.1% (Neldner and Butler, 2021).

The dataset describes the occurrence of bird species at sites within a burnt woodland. These sites comprise the following design: 5 replicate block. each with 2 large patch sites, 2 small patch sites and 2 matrix sites. One site of each pair was relatively more isolated than the other (surrounded by a higher proportion of unburnt vegetation). In addition, there are also 6 sites located beyond the extent of the fire. The data-set also lists vegetation attributes at each of these sites.

This data set is a collection of Highly Important Papers in Ecology (HIPE). Three files are included: VoteArticles.final.csv : a comma-delimited text file with the vote assessments on the relative quality of the submitted papers (Top 10, Between 11-25, Between 26-100 or Not in the top "100") and an indication of how well each voter knew the paper (Read it, Know it or Don't know it) HIP.refs.txt : tab-delimited text file with all paper bibliographic information citation.csv : a comma-delimited text file with the citation data (Google Scholar, Web of Knowledge) for each paper and each journal (Impact Factor).

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.

This data contains the visual assessment of fuel layers in fire-sensitive <em>Eucalyptus salubris</em> woodlands using Vesta methods across 24 sites in a multi-century (10 to 260+ years since fire) time-since-fire sequence derived from growth ring-size relationships.

The forest fuel survey dataset comprises site-level summary data from the well-designed fuel load surveys across 48 AusPlots Forests- 1-ha monitoring plots across Australia. Data presented here includes data on the surface, near-surface, and elevated fuel loads for each of the Forest Ausplots. It includes iButton data on 1) temperature and humidity, 2) data on litterfall and 3) decomposition rates. We also provide additional information on soil nutrient data, species composition of the understorey and midstorey, and panorama photos from the plot centre. This dataset is the second version of the <i> AusPlots Forest Fuel Survey site-level data summary, 2014 - 2015. Version 1.0.0. Terrestrial Ecosystem Research Network.</i> (dataset). <em>https://doi.org/10.25901/efnh-sk06</em>

<p>The dataset comprises well-designed survey data from the first fuel load survey across 192 transects within the 48 AusPlots Forests, 1-ha monitoring plots across Australia. Data includes: [1] Site identifiers (ID and Site Name) and site- or transect- specific notes from the fuel survey campaign; [2] Transect survey dates; [3] Transect photograph numbers and attributes (Bearing, Slope and Aspect); [4] Fuel measurements (Grass and Litter height; Duff depth; Fine Woody fuel counts and Coarse Woody fuel counts and diameter; Projective cover for biomass components (Grass, Litter, Herbs, Vines and Shrubs), and Mass of biomass components (Grass, Litter, Herbs and Vines)); [5] Moisture content for biomass components (Grass, Litter, Herbs and Vines).</p> Descriptions of the data and coding protocols used in the database are explained in (a) the database itself; (b) the explanatory file attached to this dataset and (c) the Ausplots Forest Monitoring Network Manual. The protocols and coding used in this module are drawn directly from international forest fuel survey protocols and are consistent with other Australian forest fuel inventory methodologies.</p> For site-level aggregation of the data, please see the following record: &nbsp;<a data-fr-linked="true" href="https://portal.tern.org.au/metadata/TERN/1dd61f70-7fc8-495f-8c88-823e2834b10b">https://portal.tern.org.au/metadata/TERN/1dd61f70-7fc8-495f-8c88-823e2834b10b</a></p>

This data set is a compilation of individual tree and shrub above-ground biomass (dry weight), stem diameter, height, and associated auxiliary information about the sites from which the trees or shrubs were sampled. The data were derived from numerous different projects over the last 5 decades. However, the project under which support was given to collate these datasets was Australia's Department of the Environments Methodology Development Program's Complex Wood System Project (MDP-CWS). The objective of the MDP-CWS project was to develop tools and information to underpin increased land manager participation in the domestic carbon market; the Emissions Reduction Fund (ERF). However, the intention is that this database will be expanded over time and have much greater use than just supporting carbon accounting methodologies. See publication for details: "Keryn I. Paul, John Larmour, Alison Specht, Ayalsew Zerihun, Peter Ritson, Stephen H. Roxburgh, Stan Sochacki, Tom Lewis, Craig V.M. Barton, Jacqueline R. England, Michael Battaglia, Anthony O'Grady, Elizabeth Pinkard, Grahame Applegate, Justin Jonson, Kim Brooksbank, Rob Sudmeyer, Dan Wildy, Kelvin D. Montagu, Matt Bradford, Don Butler, Trevor Hobbs, Testing the generality of below-ground biomass allometry across plant functional types, Forest Ecology and Management. 432: 102-114. https://doi.org/10.1016/j.foreco.2018.08.043. Paul, K.I., Larmour, J., Specht, A., Zerihun, A., Ritson, P., Roxburgh, S.H., Sochacki, S., Lewis, T., Barton, C.V.M., England, J.R., Battaglia, M., O’Grady, A., Pinkard, E., Applegate, G., Jonson, J., Brooksbank, K., Sudmeyer, R., Wildy, D., Montagu, K.D., Bradford, M., Butler, D., Hobbs, T., 2019. Testing the generality of below-ground biomass allometry across plant functional types. Forest Ecology and Management 432, 102–114. https://doi.org/10.1016/j.foreco.2018.08.043