This dataset contains global dryland literature abstracts from over the last 75 years (8218 articles) to identify areas in arid ecology that are well studied and topics that are emerging.

The project brought together a group of Australian researchers and managers with a broad range of expertise to identify current and emerging economies (‘drivers’) affecting regional agricultural landscapes and to suggest beneficial transformational changes for successful adaptation. A key challenge in these landscapes is altering how we use the land for ongoing, viable production while increasing native biodiversity. The group:<ul style="list-style-type: disc;"> <li>identified the major historical influences on Australian land use and the current social and economic drivers that are likely to increase in the future</li> <li>assessed the condition of five agro-climatic regions (adapted from Williams et al., 2002 and Hobbs and McIntyre, 2005) using a Delphi method. A small (4-person) expert panel scored the impact of historical and future scenarios on ten sustainability indicators (biodiversity, water, soil, social capital, built capital, food/fibre, carbon, energy, minerals and cultural). Five regions were chosen: Southern Mediterranean, Northern tropical, Central arid, North-east subtropical, and South-east temperate. This was an iterative process whereby scores were revisited until internal consistency between regions, scenarios, and indicators was achieved</li> <li>made projections of regional condition under the four global Representative Concentration Pathways (RCPs) based on van Vuuren et al. (2011)</li> <li>developed recommendations about land use and management, institutional and policy arrangements and social processes that will assist adaptation towards a values-rich vision of Australia in 2100.</li></ul>

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.

The composition of many eastern Australian woodland and forest bird assemblages is controlled by a single, hyper-aggresive native bird, the noisy miner <em>Manorina melanocephala</em>. The "Avifaunal disarry from a single despotic species" working group harnessed diverse existing datasets and used them to develop and test models of noisy miner occupancy and impacts. Two datasets are published based on the analysis and synthesis.

This is the base geographical data for the Robson creek 25 ha plot. The data sets contain the 100 m grid, 20 m grid, 100 m points, 20 m points, major tracks and creeks. Data format is both Google earth KML and ESRI shapefile.

The record contains information on the Digital Elevation Model of the Alice Mulga site. Information an Airborne full waveform lidar and hyperspectral data in the VNIR bands was collected using the research aircraft of Flinders University – Airborne Research Australia (ARA).

This terrestrial LiDAR dataset captures detailed vegetation structural information at the Tumbarumba Wet Eucalypt site in the Bago State Forest, New South Wales, Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.

The record contains images of elevation profile of the Tumbarumba Wet Eucalypt Site obtained from Airborne full waveform lidar and hyperspectral data in the VNIR bands using the a research aircraft of Flinders University – Airborne Research Australia (ARA).

This terrestrial LiDAR dataset captures detailed vegetation structural information at the Cumblerland Plain Woodland SuperSite in Western Sydney, Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.

This terrestrial LiDAR dataset captures detailed vegetation structural information at the Robson Creek Tropical Rainforest SuperSite within Danbulla National Park, North Queensland, Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.