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    High quality digital site reference images are captured for the core 1 hectare vegetation plot of the site on an annual basis to provide context for researchers to understand the general layout and vegetation of the study site, and as a visual reference to monitor any changes over time. Photopoints are taken annually using the five point photopoint method. The set of images for each year usually consists of twenty images: four images taken at each corner of the plot facing each of the four cardinal points, and four images taken from the centre of the plot facing each corner. <br /> The Litchfield Savanna SuperSite was established in 2013 in Litchfield National Park. Site selection was influenced by the history of long-term monitoring work undertaken in this area by the Darwin Centre for Bushfire Research (formerly Bushfires NT). The core 1ha plot is dominated by <em>Eucalyptus miniata</em>. The site is representative of the dominant ecosystem type across northern Australia: frequently burnt tropical savanna in high rainfall areas. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/litchfield-savanna-supersite/ . <br /> Phenocam images are also collected at the site.

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    High quality passive infrared wildlife cameras were used to acquire information on faunal biodiversity at the site. Two camera traps were deployed within the one hectare core plot between 11/04/2017 and 06/05/2017. The first camera (Reconyx UltraFire WR6) was attached to a tree at one metre high and the second camera (Reconyx Hyperfire HC600) was attached to a tree at 0.3 metres high. The cameras were first deployed for two weeks, then data were downloaded before redeploying the cameras at two other sites within the one hectare plot for a further one week period.<br /> Individuals from 10 species were observed during the study time frame.<br /><br /> The Samford Peri-Urban SuperSite was established in 2010 in remnant fringe eucalypt forest, near urban development in the Samford Valley. The upper storey is dominated by <em>Corymbia intermedia</em>, <em>Eucalyptus siderophloia</em> and <em>Lophostemon suaveolens</em>. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/samford-peri-urban-supersite/ . <br /><br /> Other images collected at the site include digital cover photography, phenocam time-lapse images taken from fixed overstorey cameras, panoramic landscape and photopoints. <br /><br /> <iframe allow="autoplay; encrypted-media" allowfullscreen="" frameborder="0" src="https://www.youtube.com/embed/1OIGPufjPK8" title="Camera trap trial (Hyperfire) at Samford 2017" style="height:248px;width:462px;"></iframe> <br />Camera trap trial (Hyperfire) at Samford 2017

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    The Daintree Rainforest SuperSite comprises two sites (a) the Daintree Rainforest Observatory at Cape Tribulation, comprising a long-term monitoring sites, canopy crane, and extensive researcher and teaching infrastructure and (b) research facilities at the Daintree Discovery Centre at Cow Bay, an award winning ecotourism interpretive centre featuring a canopy tower, aerial walkway and scientific monitoring. This dataset contains high quality passive infrared wildlife cameras were used to acquire information on faunal biodiversity at the Daintree Discovery Centre at Cow Bay. One camera trap was deployed adjacent to the 1 ha core plot between 22/01/2017 and 08/06/2017. The core plot is located within the fetch of the flux tower and is the focal site of recurrent monitoring. The camera (Reconyx HC600 HyperFire) was attached to a tree at 0.5 metre high. <br> The forest is classed as complex mesophyll vine forest (type 1a) and has an average canopy height of 25m. The dominant canopy trees belong to the Arecaceae, Euphorbiaceae, Rutaceae, Meliaceae, Myristicaceae and Icacinaceae families. It is continuous for several kilometres around the Cow Bay Tower except for an area 600m north-east of the flux tower, which is cleared agricultural land used for a cattle farm. For additional information on the Daintree Rainforest SuperSite, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/daintree-rainforest-supersite/ <br /><br /> Other images collected at the site include digital cover photography, phenocam time-lapse images (3 above canopy, 1 under canopy), panoramic landscape and photopoints. <br /><br /> <iframe frameborder="0" src="https://www.youtube.com/embed/7VkIFIWfrkQ" title="Camera trap results for the Daintree Discovery Centre between January and April 2017" style="height:248px;width:462px;"></iframe> <br />Camera trap results for the Daintree Discovery Centre between January and April 2017.

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    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>

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    This dataset consists of measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer in dry eucalypt woodland using eddy covariance techniques. <br /> <br /> The Collie flux station was located approximately 10km southeast of Collie, near Perth, Western Australia. It was established in August 2017 and stopped measuring in November 2019. <br /><br /> This data is also available at http://data.ozflux.org.au .

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    The monthly fractional cover product shows representative values for the proportion of bare ground, green and non-green ground cover across a month. It is a spatially explicit raster product, which predicts vegetation cover at medium resolution (30 m per-pixel) for each month. This dataset consists of medoid-composited monthly fractional cover created from a combined Landsat 8 and Sentinel-2 time series.

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    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> .

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    This dataset consists of measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer in semi-arid eucalypt woodland using eddy covariance techniques. <br /> <br /> The flux station was established in 2017 in Wandoo Woodland, which is surrounded by broadacre farming. About 80% of the overstorey cover is <em>Eucalyptus accedens</em> Climate information comes from the nearby Pingelly BoM AWS station 010626 (1991 to 2016) and shows mean annual precipitation is approximately 445 mm with highest rainfall in June and July of 81 mm each month. Maximumum and minuimum annual rainfall is 775 and 217 mm, respectively. Maximum temperatures range from 31.9°C (in Jan) to 15.4°C (in July), while minimum temperatures range from 5.5°C (in July) to 16.0 °C (in Feb). The Noongar people are the traditional owners at Boyagin. <br />For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/boyagin-wandoo-woodland-supersite/ . <br /><br />This data is also available at http://data.ozflux.org.au .

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    Foliage Projective Cover (FPC) is the percentage of ground area occupied by the vertical projection of foliage. The Remote Sensing Centre FPC mapping is based on regression models applied to dry season (May to October) Landsat-5 TM, Landsat-7 ETM+ and Landsat-8 OLI imagery for the period 1988-2014. An annual woody spectral index image is created for each year using a multiple regression model trained from field data collected mostly over the period 1996-1999. A robust regression of the time series of the annual woody spectral index is then performed. The estimated foliage projective cover is the prediction at the date of the selected dry season image for 2014. Where this deviates significantly from the woody spectral index for that date, further tests are undertaken before this estimate is accepted. In some cases, the final estimate is the woody spectral index value rather than the robust regression prediction. The product is further masked to remove areas classified as non-woody.

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    The seasonal dynamic reference cover method images are created using a modified version of the dynamic reference cover method developed by <a href="https://doi.org/10.1016/j.rse.2012.02.021">Bastin et al (2012) </a>. This approach calculates a minimum ground cover image over all years to identify locations of most persistent ground cover in years with the lowest rainfall, then uses a moving window approach to calculate the difference between the window's central pixel and its surrounding reference pixels. The output is a difference image between the cover amount of a pixel's reference pixels and the actual cover at that pixel for the season being analysed. Negative values indicate pixels which have less cover than the reference pixels. <br/> The main differences between this method and the original method are that this method uses seasonal fractional ground cover rather than the preceding ground cover index (GCI) and this method excludes cleared areas and certain landforms (undulating slopes), which are considered unsuitable for use as reference pixels.