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>.

<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>

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.

<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>

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.

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>.

This is a data set on the prescence of Salmonella and the exposure of flavivirus in the Australian White Ibis. The data is presented in an excel file that lists, band numbers, sample dates, age, sex, bill lengths, presence of Salmonella in gut samples, and evidence of exposure to flavivirus for 72 birds sampled in the years 2002, 2003 and 2015 in Sydney, Australia. Detailed results listed in our open accessible manuscript published in the Journal of Urban Ecology in 2019. <em> https://academic.oup.com/jue/article/5/1/juz006/5506280</em>.

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).

Leaf traits for 11 populations of <i>Dodonaea viscosa</i> subsp. <i>angustissima</i> (Sapindaceae) opportunistically collected from across an elevational gradient (300 to 800 m above sea level) in the Flinders Ranges of South Australia. We present leaf traits for 266 individuals. Traits measured include leaf area and specific leaf area, and elevation.

<br>The aim of this project is to compile land use and management practices and their observed and measured impacts and effects on vegetation condition. The results provide land managers and researchers with a tool for reporting and monitoring spatial and temporal transformations of Australia’s native vegetated landscapes due to changes in land use and management practices. Following are the details about Goorooyarroo Nature Reserve Site 2, ACT, Australia </br><br> Pre-European benchmark-analogue vegetation: The site was originally woodlands on the deeper soils of the lower slopes and flats (<em>Eucalyptus blakelyi</em> and <em>Eucalyptus melliodora</em>) (McIntrye et al 2010). </br><br> Brief chronology of changes in land use and management:<ul style="list-style-type: disc;"> <li>1819: Area managed by indigenous Ngunnawal people</li> <li>1826: Sheep grazing with shepherds commenced</li> <li>1860: Fences constructed - continuous stocking with sheep commenced</li> <li>1905: Area used for sheep grazing - continuous /set stocking</li> <li>1920: Fallen timber collected for firewood started</li> <li>1961: Mature trees on the site were ring barked to promote pasture grasses</li> <li>1973: Dead and fallen trees felled for fire wood</li> <li>1979: Bushfire burns through the area</li> <li>1994: Mulligans Flat Nature Reserve established</li> <li>1995: Continuous stocking with sheep grazing ceased</li> <li>1995: Collection of firewood ceased</li> <li>1995: Pasture improvement ceased</li> <li>1996: Kangaroo population begins to rapidly increase</li> <li>2006: Roo proof fence completed</li> <li>2006: Commenced annual removal of pest species of plants and animals</li> <li>2010: Commenced annual Kangaroo cull.</li></ul></br>