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    This data release consists of flux tower 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. It been processed using PyFluxPro (v3.3.3) as described in Isaac et al. (2017), <a href="https://doi.org/10.5194/bg-14-2903-2017">https://doi.org/10.5194/bg-14-2903-2017</a>. PyFluxPro takes data recorded at the flux tower and process this data to a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER). For more information about the processing levels, see <a href="https://github.com/OzFlux/PyFluxPro/wiki">https://github.com/OzFlux/PyFluxPro/wiki</a>. <br /><br /> The Great Western Woodlands (GWW) comprise a 16 million hectare mosaic of temperate woodland, shrubland and mallee vegetation in south-west Western Australia. The region has remained relatively intact since European settlement, owing to the variable rainfall and lack of readily accessible groundwater. The woodland component is globally unique in that nowhere else do woodlands occur at as little as 220 mm mean annual rainfall. Further, other temperate woodlands around the world have typically become highly fragmented and degraded through agricultural use. The Great Western Woodlands Site was established in 2012 in the Credo Conservation Reserve. The site is in semi-arid woodland and was operated as a pastoral lease from 1907 to 2007. The core 1 ha plot is characterised by <em>Eucalyptus salmonophloia</em> (salmon gum), with <em>Eucalyptus salubris</em> and <em>Eucalyptus clelandii</em> dominating other research plots. The flux station is located in Salmon gum woodland. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/great-western-woodlands-supersite/ . <br /><br />

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    This data release consists of flux tower 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. It been processed using PyFluxPro (v3.3.3) as described in Isaac et al. (2017), <a href="https://doi.org/10.5194/bg-14-2903-2017">https://doi.org/10.5194/bg-14-2903-2017</a>. PyFluxPro takes data recorded at the flux tower and process this data to a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER). For more information about the processing levels, see <a href="https://github.com/OzFlux/PyFluxPro/wiki">https://github.com/OzFlux/PyFluxPro/wiki</a>. <br /> <br /> <em>Eucalyptus obliqua</em> forests dominate the vegetation below 650 m where they exist as fire-maintained communities. On fertile soils these forests attain mature heights in excess of 55m: the tallest <em>E. obliqua</em>reaches a height of 90m. The flux station is installed in a stand of tall, mixed-aged <em>E.obliqua</em> forest (77 and >250 years-old) with a rainforest understorey and a dense man-fern (<em>Dicksonia antarctica</em>) ground-layer, on a small flat of elevation 100 m adjacent to the Huon River. The understorey vegetation progresses from wet sclerophyll (dominated by <em>Pomaderris apatala</em> and <em>Acacia dealbata</em>) to rainforest (dominated by <em>Nothofagus cunninghamii</em>, <em>Atherosperma moschatum</em>, <em>Eucryphia lucida</em> and <em>Phyllocladus aspleniifolius</em>) with increasing time intervals between fire events. The site supports prodigous quantities of coarse woody debris as is characteristic of these fire-maintained eucalypt forests on fertile sites in southern Tasmania. <br />The soil at the flux site is derived from Permian mudstone and has a gradational profile with a dark brown organic clayey silt topsoil overlying a yellow brown clay. <br />The climate of Warra is classified as temperate with a mild summer and no dry season. Mean annual precipitation is 1700 mm with a relatively uniform seasonal distribution. Summer temperatures peak in January (min. 8.4°C – max 19.2°C) with winter temperatures reaching their lowest in July (min 2.6°C – max 8.4°C).<br /><br />The instruments are mounted at the top of an 80m tall guyed steel lattice tower. Supplementary measurements above the canopy include temperature, humidity, windspeed, wind direction, rainfall, incoming and reflected shortwave radiation and net radiation. An open-path gas analyser (EC150) was replaced by a closed-path gas analyser (EC155) at the end of Jan 2015.Soil moisture content is measured using Time Domain Reflectometry, while soil heat fluxes and temperature are also measured. Micro-meteorology (CO2, H2O, energy fluxes), meteorology (temp, humidity, wind speed and direction, rainfall) taken from the Warra Flux Site from 2013 to late 2016. Data incomplete due to ongoing problems since changing the open-path IRGA to a closed path system (CPEC200) during 2015. Soil data (moisture, heat flux, temp) complete for time period. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/warra-tall-eucalypt-supersite/ .<br><br>

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    This data release consists of flux tower 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. It been processed using PyFluxPro (v3.5.0) as described in Isaac et al. (2017), <a href="https://doi.org/10.5194/bg-14-2903-2017">https://doi.org/10.5194/bg-14-2903-2017</a>. PyFluxPro takes data recorded at the flux tower and process this data to a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER). For more information about the processing levels, see <a href="https://github.com/OzFlux/PyFluxPro/wiki">https://github.com/OzFlux/PyFluxPro/wiki</a>. <br /> <br /> The site was identified as tropical pasture dominated by species <em>Chamaecrista rotundifolia</em> (Round-leaf cassia cv. Wynn), <em>Digitaria milijiana</em> (Jarra grass) and <em>Aristida sp.</em> standing at approximately 0.3m tall. The soil at the site was a mixture of red kandosol and deep sand. Elevation of the site was close to 70m and mean annual precipitation at a nearby Bureau of Meteorology site was 1250mm. Maximum temperatures ranged from 37.5°C (in October) to 31.2°C (in June), while minimum temperatures ranged from 12.6°C (in July) to 23.8°C (in January). Maximum temperatures varied on a seasonal basis between 6.3°C while minimum temperatures varied by 11.2°C. <br /> <br /> The instrument mast was 15 meters tall. Heat, water vapour and carbon dioxide measurements were taken using the open-path eddy flux technique. Temperature, humidity, wind speed, wind direction, rainfall, incoming and reflected shortwave radiation and net radiation were measured. <br />Ancillary measurements taken at the site included LAI, leaf-scale physiological properties (gas exchange, leaf isotope ratios, N and chlorophyll concentrations), vegetation optical properties and soil physical properties. Airborne based remote sensing (Lidar and hyperspectral measurements) was carried out across the transect in September 2008. <br /> The site was destroyed by fire in September 2013. <br />

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    <br>This release consists of flux tower measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer using eddy covariance techniques. Data were processed using PyFluxPro (v3.4.7) as described by Isaac et al. (2017). PyFluxPro produces a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER).</br> <br>The Collie flux station was located approximately 10&nbsp;km southeast of Collie, near Perth, Western Australia. It was established in August 2017 and stopped measuring in November 2019. </br>

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    This data release consists of flux tower 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. It been processed using PyFluxPro (v3.3.3) as described in Isaac et al. (2017), <a href="https://doi.org/10.5194/bg-14-2903-2017">https://doi.org/10.5194/bg-14-2903-2017</a>. PyFluxPro takes data recorded at the flux tower and process this data to a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER). For more information about the processing levels, see <a href="https://github.com/OzFlux/PyFluxPro/wiki">https://github.com/OzFlux/PyFluxPro/wiki</a>. <br /> <br /> The Cow Bay flux station was established in December 2008 and managed by James Cook University. The forest is classified as complex mesophyll vine forest, there are 94 species in the core 1Ha, and average tree height is 22m. Elevation of the site is 90m and mean annual precipitation is 3935mm. The Daintree Rainforest is one of the most biodiverse forests in Australia.The instruments are mounted on a walk-up tourist tower at 35m. Fluxes of heat, water vapour and carbon dioxide are measured using the open-path eddy flux technique. Supplementary measurements above the canopy include temperature, humidity, windspeed, wind direction, rainfall, incoming and reflected shortwave radiation and net radiation.The early years 2009 - 12 had several data gaps. Shadowing of the radiometric equipment continues to cause artifacts on the radiometers - these can be seen as reduction in downwelling radiation with solar inclination. The site is part of the FNQ Rainforest SuperSite - associated with the Daintree node, which is part of the TERN Australian SuperSite Network (ASN). <br/> For additional site information, see https://supersites.tern.org.au/supersites/fnqr-daintree .<br />

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    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).

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    <br>This release consists of flux tower measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer using eddy covariance techniques. Data were processed using PyFluxPro (v3.4.7) as described by Isaac et al. (2017). PyFluxPro produces a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER).</br> <br>The flux station site is located within an area of dryland agriculture. The surrounding area is dominated by broadacre farming practices. The vegetation cover is predominantly pasture. Elevation of the site is close to 152&nbsp;m and mean annual precipitation at a nearby Bureau of Meteorology site measures 650&nbsp;mm. Maximum temperatures range from 12.3&nbsp;°C (in July) to 29.7&nbsp;°C (in February), while minimum temperatures range from 10.4&nbsp;°C (in July) to 26.8&nbsp;°C (in February).</br> <br>The instrument mast is 4&nbsp;m tall. Heat, water vapour and carbon dioxide measurements are taken using the open-path eddy flux technique. Temperature, humidity, wind speed, wind direction, rainfall and net radiation are measured. Soil heat fluxes are measured and soil moisture content is gathered using time domain reflectometry.</br>

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    A total of 53 native Australian species (52x C3, 1x C4) were sampled from 22 plant families and 7 growth forms along a transect in WA spanning 9.56 degrees latitude and 6.85 degrees longitude. Samples were collected using the nationally-accepted AusPlots Rangelands methodology. Samples were stored to preserve isotopic signatures and analysed using standard techniques for mass spectroscopy, including internationally-calibrated standards. Technical replicates of 13% showed very low drift (0.07).

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    Mating system and fitness data for families of <em>Eucalyptus socialis</em> grown in common garden experiments. Families collected across a fragmentation gradient. Open-pollinated progeny arrays were collected and reared in the common garden experiments. These open-pollinated progeny arrays were also genotyped at microsatellite loci to generate the mating system data. Data showed association between fragmentation on mating system, which in turn impacted fitness. Please contact owner prior to use.

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    <p> The dataset aims at studying associations between mating system parameters and fitness in natural populations of trees. Fifty-eight open-pollinated progeny arrays were collected from trees in three populations. Progeny were planted in a reciprocal transplant trial. Fitness was measured by family establishment rates. We genotyped all trees and their progeny at eight microsatellite loci. Planting site had a strong effect on fitness, but seed provenance and seed provenance × planting site did not. Populations had comparable mating system parameters and were generally outcrossed, experienced low biparental inbreeding and high levels of multiple paternity. As predicted, seed families that had more multiple paternities also had higher fitness, and no fitness-inbreeding correlations were detected. Demonstrating that fitness was most affected by multiple paternities rather than inbreeding, we provide evidence supporting the constrained inbreeding hypothesis; i.e. that multiple paternity may impact on fitness over and above that of inbreeding, particularly for preferentially outcrossing trees at life stages beyond seed development. This dataset could potentially be reused for meta-analysis or review of effects of habitat fragmentation on plants (e.g. pollination, mating system, genetic diversity etc). Please contact owner prior to re-use. </p> <p>This is part of the authors' PhD at the University of Adelaide, supervised by Prof Andrew Lowe, Dr Mike Gardner and Dr Kym Ottewell. Main goals of the project were 1. Examine and quantify the impact of fragmentation and tree density on mating patterns, and how this may vary with pollinators of differing mobility 2. Determine the theoretical expectations and perform empirical tests of mating pattern-fitness relationships in trees 3. Explore the plant genetic resource management implications that arise from the observations in aims 1 and 2 </p>