This is a series comprises of vegetation condition predictions for biodiversity for the bioregions of Queensland. The datasets were created using a gradient boosting decision tree (GBDT) model based on 10 vegetation-specific remote sensing (RS) datasets and 7,938 training sites of known vegetation community and condition state across Southeast Queensland, Brigalow Belt and Central Queensland Coast bioregions. Condition score was modelled as a function of distance in the remote sensing (RS) space within homogeneous vegetation communities. The product is intended to represent predicted BioCondition for 2021 rather than any singe date. This series includes information relating the version 2.0 products of Spatial BioCondition, which have superseded the version 1.0 products (https://portal.tern.org.au/metadata/TERN/40990eec-5cef-41fe-976b-18286419da0c, https://portal.tern.org.au/metadata/TERN/2c33325c-1dd5-4674-918a-1cd5bfc1a6e3). Spatial BioCondition is not suitable for the measurement of changes in condition over time, and direct comparisons of predictions between versions 1.0 and 2.0 are not advised.

High quality passive infrared wildlife cameras were used to acquire information on faunal biodiversity at the site. Two cameras were deployed from July to Dec 2018 and between March and May 2019. <br /><br /> The Gingin Banksia Woodland SuperSite was established in 2011 and is located in a natural woodland of high species diversity with an overstorey dominated by Banksia species. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/gingin-banksia-woodland-supersite/. <br /> Other images collected at the site include digital cover photography, phenocam time-lapse images taken from fixed under and overstorey cameras and ancillary images of flora.

High quality passive infrared wildlife cameras were used to acquire information on faunal biodiversity at the Robson Creek site. Two camera traps were deployed at the site between 17-03-2018 and 25-07-2018. The first camera located in proximity to the acoustic sensor SM2/SM4 which is around 100m from the flux tower and at a height of 1.5 meter above ground, on a star picket. The second camera located for a short while near the tower (10 meter) and was attached on a bungy cord tied to a tree, at a height of 0.3 meter above ground.<br><br> The Robson Creek site lies on the Atherton Tablelands in the wet tropical rain forests of Australia at 680-740 m elevation. It is situated in Danbulla National Park within the Wet Tropics World Heritage Area. The Wet Tropics Bioregion of Australia is situated on the north-eastern coast of Queensland, between Cooktown to the north and Townsville to the south. Approximately 40% (7200 km2) of the region is covered by rain forest. Features of the region include very high plant and animal endemism, characteristics of both Gondwanan and Indo-Malaysian forests, and frequent cyclonic disturbance. The site includes core 1 ha plot (100 m x 100 m) which is located within the fetch of the flux tower and is the focal site of recurrent monitoring, and 25 ha vegetation survey plot. The vegetation survey plot has been set up for inclusion in the Smithsonian Tropical Research Institute’s Center for Tropical Forest Science – Forest Global Earth Observatory (CTFS-ForestGEO) global network of forest research plots. <br><br> For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/robson-creek-rainforest-supersite/ . <br /><br /> Other images collected at the site include time-lapse images taken from 3 phenocams (above canopy). <br /><br /> <iframe allow="autoplay; encrypted-media" allowfullscreen="" frameborder="0" src="https://www.youtube.com/watch?v=WW-cpPMhMz4" title="TERN Robson Creek SuperSite Wildlife 2017" style="height:248px;width:462px;"></iframe> <br />Camera trap results for the TERN FNQ Rainforest SuperSite - Robson Creek, Jan - Feb 2017.

This collection contains the data used in the Multi-Criteria Analysis Shell for Spatial Decision Support (MCAS-S) software tool. From the Data menu, explore and download individual supplementary layers, or download the entire datapack. The Multi-Criteria Analysis Shell for Spatial Decision Support (MCAS-S) is a software tool developed by the Australian Bureau of Agricultural and Resource Economics and Sciences that enables multi-criteria analysis (MCA) using spatial data. It is a powerful, easy-to-use and flexible decision-support tool that promotes: - framework for assessing options <br> - common metric for classifying, ranking and weighting of the data <br> - tools to compare, combine and explore spatial data <br> - live-update of alternative scenarios and trade-offs. <br>

<p>Digital Hemispherical Photography (DHP) upward-looking images were collected annually to capture vegetation and crown cover at Daintree Rainforest SuperSite. These images are used to estimate Leaf Area Index (LAI). </p><p> The site is located at the Daintree Rainforest Observatory in Lowland Complex Mesophyll Vine Forest near Cape Tribulation. Flux monitoring was established in 2001 with additional monitoring capabilities added over time. The site has more than 80 species including canopy trees belonging to the <em>Arecaceae, Euphorbiaceae, Rutaceae, Meliaceae, Myristicaceae and Icacinaceae</em> families. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/daintree-rainforest-supersite/. </p><p> Other images collected at the site include photopoints, phenocam time-lapse images taken from fixed under and overstorey cameras and ancilliary images of fauna and flora. </p>

The woody vegetation extent for Queensland is attributed with an estimated age in years since the last significant disturbance. The method uses a sequential Conditional Random Fields classifier applied to Landsat time series starting 1988 to predict woody cover over the time period. A set of heuristic rules is used to detect and track regrowing woody vegetation in the time series of woody probabilities and record the approximate start and end dates of the most recent regrowth event. Regrowth detection is combined with the Statewide Land and Trees Study (SLATS) Landsat historic clearing data to provide a preliminary estimate of age since disturbance for each woody pixel in the woody extent. The 'last disturbance' may be due to a clearing event or other disturbance such as fire, flood, drought-related death etc. Note that not all recorded disturbances may result in complete loss of woody vegetation, so the estimated age since disturbance does not always represent the age of the ecosystem. The age since disturbance product is derived from multiple satellite image sources and derived products which represent different scales and resolutions: Landsat (30&nbsp;m), Sentinel-2 (10&nbsp;m) and Earth-i (1&nbsp;m).

The physical drivers of ecosystem formation – macroclimate, lithology and landform – along with vegetation structural formations are key determinants of current ecosystem type. Each combination of these ecosystem drivers – each ‘ecological facet’ – provides a unique set of opportunities and challenges for life. <br> Management and conservation should seek to understand and take in to account these drivers of ecosystem formation. By understanding the unique combinations of these drivers management strategies can plan for their full range of variation, and conservation efforts can ensure that unique ecosystems are not lost. Unfortunately, there is currently no Australia-wide standardized map of ecological facets at management-appropriate scales. <br> By understanding the magnitude and distribution of unique combinations of these drivers, management strategies can plan for their full range of variation, and conservation efforts can ensure that unique ecosystems are not lost. Additionally, by improving our understanding of the past and present conditions that have given rise to current ecological facets this dataset could facilitate future predictive environmental modelling. Finally, this data could assisting biodiversity conservation, climate change impact studies and mitigation, ecosystem services assessment, and development planning <br> Further information about the dataset can be found at <a href="https://ternaus.atlassian.net/wiki/spaces/TERNSup/pages/2276130817/GEOSS+Ecosystem+Map">GEOSS Ecosystem Map,TERN Knowledge Base </a> .

Digital Cover Photography (DCP) upward-looking images will be collected up to twice per year to capture vegetation cover at Boyagin Wandoo Woodland SuperSite. These images can be used to estimate Leaf area index (LAI), Crown Cover or Foliage Projective Cover (FPC). The Boyagin Wandoo Woodland SuperSite was established in 2017 in Wandoo Woodland, which is surrounded by broadacre farming. About 80% of the overstorey cover is <em>Eucalyptus accedens</em>. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/boyagin-wandoo-woodland-supersite/ . Digital Hemispheric Photography (DHP) has also been collected at Boyagin SuperSite.

The spatial layers in this dataset detail forest connectivity over NSW. Forest Connectivity accounts for the general quality of terrestrial habitats supporting biodiversity at each location, the fragmentation of habitat within its neighbourhood and how its position in the landscape contributes to connectivity among the habitats across a region. <br> Forest canopy cover connectivity and fragmentation is concerned and linked to forest condition. Concepts applied are to be aligned with definitions as found in the Biodiversity Indicator Program (BIP) and the Spatial Links methodology for calculating connectivity. <br> Base cover extent grids used are from the NSW Forest Monitoring and Improvement Program Statewide Historic Forest Cover Extent – 1995 to 2020 product. These have been processed through a series of land use and vegetation type exclusion masking and a through a fuzzy-logic based certainty analysis to reflect a forest cover extent coverage for NSW that is reflective of past and current coverage.<br> Read more about the project on the Natural Resources Commission website:<br> https://www.nrc.nsw.gov.au/fmip-baselines-ecosystem-health-projectfe1<br> This dataset supersedes "NSW Forest Monitoring and Improvement Program RFA Historic Forest Connectivity – 1995 to 2019". https://portal.tern.org.au/metadata/23696.

<p>Digital Cover Photography (DCP) upward-looking images were collected annually to capture vegetation cover at the TERN Karawatha Peri-Urban SuperSite. These images can be used to estimate Leaf area index (LAI), Crown Cover or Foliage Projective Cover (FPC). </p><p> The Karawatha Peri-Urban SuperSite was established in 2007 and decommissioned in 2018. The site was located in Eucalypt forest at Karawatha Forest. For additional site information, see https://deims.org/f15bc7aa-ab4a-443b-a935-dbad3e7101f4 . </p><p> Other images collected at the site include photopoints and ancilliary images of fauna and flora. </p>