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    The record contains information on the moth assemblages at canopy and ground level at five sites within a 25 ha plot, at Robson Creek Site, Far North Queensland. Data on moth taxonomic information and the number of individuals sampled from the ground and canopy are provided for the sampling years, 2009, 2010 and 2011.

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    TERN (funded by NCRIS and EIF) has been developing coherent community-wide management structures for several of the required key data streams, so the relevant data are no longer unmanaged. eMAST builds on this infrastructure, by generating products that integrate the different streams of data e.g. water use and other ecosystem functions. The eMAST ANUClimate climate surfaces will be the first, continental 0.01 degree (nominal 1km) resolution climate surfaces generated using the Hutchinson et al. (ANU) methodology. Combined with the ancillary bioclimatic, ecosystem variables and indices derived from these data, this will be the first complete collection of its kind made publically available as a single resource. This collection of datasets, is a resource for the ecosystem science community and enhances the capacity for research. For example the development of an advanced benchmarking system for terrestrial ecosystem models (i.e. PALS). In addition, the data will be made accessible through the SPEDDEXES web-interface at the NCI, making the data sets conveniently available to a wide audience/community. The datasets generated within the scope of eMAST focus on Australia ecosystems, but are expected to encourage global as well as national interests, because of the universal data formats use. The project is thus expected to facilitate ecosystem modellers to perform comparative analyses of model performance; build new connections between Australian and overseas researchers, and between different research communities in Australia; and accelerate the development, testing and optimization of terrestrial ecosystem models. Working towards the next generation of robust, process based ecosystem models; we are synthesizing observations of plant biophysical and physiological traits, developing gridded surfaces of these traits, and working with TERN MultiScale Plot Network to improve national coverage of trait measurements. Working in collaboration with international collaborators from NEON and NCAR; eMAST are demonstrating and developing Australia capacity for making models utilise these information rich collections. More information about this collection can be found at http://www.emast.org.au

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    <p>This dataset contains audio files for Calperum Mallee SuperSite. The site was established in 2010 and is located on Calperum Station, near Renmark, in South Australia. The property was a pastoral grazing lease for nearly 150 years, and suffered grazing-induced modifications to its ecosystems that are now being actively restored following removal of sheep in 1994. The area includes mallee woodlands and riverine vegetation. A significant amount of the mallee woodlands was burnt in January 2014. The mallee species are multi-stemmed eucalyptus trees (<em>Eucalyptus dumosa</em>, <em>E. incrassata</em>, <em>E. oleosa</em> and <em>E. socialis</em>) while the sparsely distributed mid-storey species come from <em>Eremophila</em>, <em>Hakea</em>, <em>Olearia</em>, <em>Senna</em> and <em>Melaleuca</em> genera. The spaced understory is predominately clumps of spiny grass (<em>Triodia spp.</em>). For additional site information, see <a href="https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/calperum-mallee-supersite">Daintree Rainforest SuperSite</a></p> <p>In 2019 four acoustic recorders were set up to collect audio data continuously as part of the Australian Acoustic Observatory (A2O) project. Two recorders were placed in relatively wet habitats and two in relatively dry habitats.</p>

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    Evaporation, Transpiration, and Evapotranspiration Products for Australia based on the Maximum Entropy Production model (MEP). This record is an introduction of a method into the MEP algorithm of estimating the required model parameters over the entire continent of Australia through the use of pedotransfer function, soil properties and remotely sensed soil moisture data. The algorithm calculates the evaporation and transpiration over Australia on daily timescales at the 0.05 degree (5 km) resolution for 2003 – 2013. The MEP evapotranspiration (ET) estimates were validated using observed ET data from 20 Eddy Covariance (EC) flux towers across 8 land cover types in Australia and compared the MEP-ET at the EC flux towers with two other ET products over Australia; MOD16 and AWRA-L products. The MEP model outperformed the MOD16 and AWRA-L across the 20 EC flux sites, with average root mean square errors (RMSE), 8.21, 9.87 and 9.22 mm/8 days respectively. The average mean absolute error (MAE) for the MEP, MOD16 and AWRA-L were 6.21, 7.29 and 6.52 mm/8 days, the average correlations were 0.64, 0.57 and 0.61, respectively. The percentage bias of the MEP ET was within 20% of the observed ET at 12 of the 20 EC flux sites while the MOD16 and AWRA-L ET were within 20% of the observed ET at 4 and 10 sites respectively. The analysis showed that evaporation and transpiration contribute 38% and 62%, respectively, to the total ET across the study period which includes a significant part of the “millennium drought” period (2003 – 2009) in Australia. File naming conventions: E – Evaporation T – Transpiration ET – Evapotranspiration For the 8 day ET, Daily T and ET, the suffix nnn indicates day of year, for example: 001 for January 1, 145 for May 25 (leap year) or 26, etc. While for the daily E, the suffix is in the format mmdd (month,day) for example 0101 for January 1, 0525 for May 25.

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    This data contains stem diameter, height measurements, basal area and above ground living biomass calculations for the Gingin Banksia Woodlands in Western Australia.

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    Experimental sites were established in the northern wheat-growing district of western Australia (Lat -29.66°, Long 116.18°) in August 2017, and monitored through to November 2019. We selected five planted old field sites with similar soil types and vegetation composition. Old fields were planted with York gum (Eucalyptus loxophleba Benth.) and dominant shrubs as understorey. At the time of sampling in 2017, vegetation age ranged from 8–13 years and distance from remnant measured 279 m (± 162 m). We established two control and two treatment plots, each measuring 5 m x 5 m, in the interrows of five planted old field sites. Both treatments were randomly assigned to plots within each site. Between August and early November 2017, we measured a total of 30 response variables at each of the control and treatment plots. Response variables included soil physical and chemical properties (bulk density, penetration resistance, soil moisture, nitrogen and carbon pools), microbial biomass, decomposition rate of roiboos and green tea as per the standardized Tea Bag Index (TBI) protocol, herbaceous vegetation cover and richness, and ant abundance and richness, as well as abundance and richness of ant functional groups.

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    This dataset consists of images of fauna, flora, fungi or general scenery or events captured at the site on an ad-hoc basis and may provide the researcher with information regarding the species that occupy, frequent or traverse this site.<br /> <br /> 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/ .<br /> <br /> Other images collected at the site include digital hemispherical photography and digital cover photography.

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    <p>This dataset contains audio files for Boyagin Wandoo Woodland SuperSite. The site was established in 2017 at the Boyagin Nature Reserve with research plots located in Wandoo woodland (<em>Eucalypt sp.</em>). The core 1&nbsp;ha plot is located in dense eucalypt woodland. For additional site information, see <a href="https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/boyagin-wandoo-woodland-supersite/">Boyagin Wandoo Woodland SuperSite</a></p> <p>In 2019 four acoustic recorders were set up to collect audio data continuously as part of the Australian Acoustic Observatory (A2O) project. Two recorders were placed in relatively wet habitats and two in relatively dry habitats.</p>

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    The record contains information on leaf chemistry studied on co-occurring tropical mountaintop restricted tree species from various mountaintop sites in Far North Queensland in 2019. Data on leaf stable carbon and nitrogen isotope concentrations, and elemental chemistry such as carbon, nitrogen, phosphorous, calcium, magnesium, potassium, sodium, copper, boron, sulfur, zinc and manganese are provided.

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    The Australian Phenology Product is a continental data set that allows the quantitative analysis of Australia’s phenology derived from MODIS Enhanced Vegetation Index (EVI) data using an algorithm designed to accommodate Australian conditions, described in Xie et al. 2023. The product can be used to characterize phenological cycles of greening and browning and quantify the cycles’ inter and intra annual variability from 2003 to 2018 across Australia. Phenological cycles are defined as a period of EVI-measured greening and browning that may occur at any time of the year, extend across the end of a year, skip a year (not occur for one or multiple years) or occur more than once a year. Multiple phenological cycles within a year can occur in the form of double cropping in agricultural areas or be caused by a-seasonal rain events in water limited environments. Based on per-pixel greenness trajectories measured by MODIS EVI, phenological cycle curves were modelled and their key properties in the form of phenological curve metrics were derived including: the first and second minimum point, peak, start and end of cycle; length of cycle, and; the amplitude of the cycle. Integrated EVI under the curve between the start and end of the cycle time of each cycle is calculated as a proxy of productivity.