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    <p>Digital Cover Photography (DCP) upward-looking images are collected three times per year to capture vegetation cover at Gingin Banksia Woodland SuperSite. These images can be used to estimate Leaf Area Index (LAI). </p> <p> 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. </p><p> Other images collected at the site include digital hemispherical photography (DHP), photopoints, phenocam time-lapse images taken from fixed under and overstorey cameras, and ancillary images of fauna and flora. </p>

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    This terrestrial LiDAR dataset captures detailed vegetation structural information at the Tumbarumba Wet Eucalypt site in NSW, 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.

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    <p>Digital Hemispherical Photography (DHP) upward-looking images are collected three times per year to capture vegetation and crown cover at the Gingin Banksia Woodland SuperSite. These images are used to estimate Leaf area index (LAI). </p> <p> 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/. </p><p> Other images collected at the site include digital cover photography (DCP), photopoints, phenocam time-lapse images taken from fixed under and overstorey cameras and ancillary images of fauna and flora. </p>

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    The dataset includes three csv files: [1] effects of pre-inhabitation and viruses on the feeding behavior of <i>Rhopalosiphum padi</i> and <i>R. maidis</i> (min). [2] Effects of pre-inhabitation and viruses on the fecundity of<i> R. padi</i> and <i>R. maidis</i> (total offspring in laboratory and field). [3] Effect of pre-inhabitation and viruses on the host plant nutrient content (amino acids, total sterols, and simple sugars-mg/g). These data might be used by researchers studying positive interactions, effects of viruses on host plants and vectors, phytochemistry of the wheat plant, and feeding behavior of phloem-feeders.

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    <p>Ground lidar, also known as Terrestrial Laser Scanning (TLS), is a ranging instrument that provides detailed 3D measurements directly related to the quantity and distribution of plant materials in the canopy. This dataset contains raw instrument data and ancillary data for numerous sites across northern and eastern Australia from 2012 onwards. Scans have been collected using two Riegl VZ400 waveform recording TLS instruments. One is co-owned and operated by the Remote Sensing Centre, Queensland Department of Environment and Science (DES) and the TERN Auscover Brisbane Node, University of Queensland. The second is owned and operated by Wageningen University, Netherlands.</p> <p>Data can be accessed from https://field.jrsrp.com/ by selecting the combinations Field, Ground Lidar. Raw data are accessible by selecting individual locations on the map and then clicking on the TLS scan directory link on the right hand site of the screen. </p>

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    This dataset is a collection of drone RGB and multispectral imagery from plots across Australia (AusPlots, SuperSites, Cal/Val sites to be established in the future). Standardised data collection and data processing protocols are used to collect drone imagery and to generate orthomosaics. The protocols developed in 2022 are based on the DJI Matrice 300 (M300) RTK drone platform. DJI Zenmuse P1 and MicaSense RedEdge-MX/Dual sensors are used with M300 to capture RGB and multispectral imagery simultaneously. The data is georeferenced using the DJI D-RTK2 base station and onboard GNSS RTK. In the processing workflow, the multispectral image positions (captured with navigation-grade accuracy) are interpolated using image timestamp and RGB image coordinates. Dense point clouds and the fine-resolution RGB smoothed surface were used to generate co-registered RGB (1 cm/pixel) and multispectral (5 cm/pixel) orthomosaics. Mission-specific metadata for each plot is provided in the imagery/metadata folder. The Drone Data Collection and RGB and Multispectral Imagery Processing protocols can be found at <em> https://www.tern.org.au/field-survey-apps-and-protocols/ </em>.

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    This dataset is a collection of drone lidar data from plots across Australia (AusPlots, SuperSites, Cal/Val sites to be established in the future). The aim of these drone surveys is to capture vegetation structure. The standardised data collection and data processing protocols developed in 2022 are based on the DJI Matrice 300 (M300) RTK drone platform. Lidar sensor DJI Zenmuse L1 is used with DJI Matrice 300 (M300) RTK platform to capture RGB colourised 3D point clouds. The data is georeferenced using the onboard GNSS in M300 and the D-RTK 2 base station. DJI Terra software was used to generate 3D point clouds from the raw lidar data. The protocols include flight planning and data collection guidelines for a 100 x 100 m TERN plot, and the processing workflow used on DJI Terra. Mission-specific metadata for each plot is provided in the imagery/metadata folder (please refer to the imagery collection). The Drone Data Collection and Lidar Processing protocols can be found at <em> https://www.tern.org.au/field-survey-apps-and-protocols/ </em>.

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    Microsatellite genotype data for 3 eucalypt species. Data include progeny and adults from across a gradient of habitat fragmentation. These microsatellite data could be further used in additional analyses, e.g. genetic diversity. Samples collected from stands on eucalypts as follows: non-neighbouring adult trees had leaf and seeds collected. Leaf was used to genotype the adults. Seeds were germinated, tissue then collected, and the same microsatellites genotyped - i.e. open-pollinated progeny arrays. The dataset is possibly useful for meta-analysis or review of effects of habitat fragmentation on plants (e.g. mating system, genetic diversity etc).

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    The acquisition of sunphotometer measurements are critical to capture vital data on atmospheric properties during airborne hyperspectral imaging campaigns as well as for measurements coinciding with the overpass of satellite sensors. The atmospheric properties measured are used in atmospheric correction of the remotely sensed image data. This data is primarily for input into atmospheric correction systems. It may also prove of use in validation of aerosol products such as MOD04 and the reflectance change method developed as part of CRC-SI project 4.1 which may be integrated into the Auscover 19 band reflectance product processing. It can also be used to check methods that produce water vapour directly from the data (SODA). The MicroTops instruments referred to here capture solar radiance data in 5 wavelengths which are used to extract information on aerosol optical thickness and water vapour content. These two key parameters of interest are used as inputs for the atmospheric correction of remotely sensed image data.

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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>