Creation year

2014

764 record(s)
 
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    High quality digital site reference images are captured for the core 1 hectare (ha) 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 will be 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 /><br /> The Tumbarumba Flux site was established in 2000 and started measuring in 2001. The 1 ha plot was established in 2015. Preliminary images have been captured since 2000 using various sampling strategies and protocols. The overstorey is dominated by <em>Eucalyptus delegatensis</em> and <em>Eucalyptus dalrympleana</em>. For additional site information, see https://www.tern.org.au/tern-observatory/tern-ecosystem-processes/tumbarumba-wet-eucalypt-supersite/.<br /><br/> Other images collected at the site include digital cover photography, phenocam time-lapse images taken from fixed under and overstorey cameras, and ancillary images of fauna and flora.

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    The record contains information on litterfall data from four 1-hectare plots from the Great Western Woodlands site collected in 2014. Data on total litter weights from fifteen litter traps in each of four 1-ha study plots and crown canopy cover percent is provided.

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    The MODIS Land Condition Index (LCI) is an index of total vegetation cover (green and non-photosynthetic vegetation ), and so is also an index of soil exposure. The LCI is a normalised difference index based on MODIS bands in the mid-infrared portion of the spectrum. The index is produced from 500-m MODIS nadir BRDF adjusted reflectance (NBAR) data. As with all products derived from passive remote sensing imagery, this product represents the world as seen from above. Therefore, the cover recorded by this product represent what would be observed from a birds-eye-view. Therefore, dense canopy may prevent observation of significant soil exposure.

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    Seedling surveys were conducted at the Cumberland Plain site in 2014. The identity and height of all seedlings were recorded along six 20 m x 1 m transects in the core 1 ha plot.

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    The dataset provides information on soil chemistry from a 10 year chronosequence sample of restoration in southern Australia. The parameters include: A) Physical properties- Soil moisture (%), Gravel (%) - ( >2.0 mm), Soil Texture, i.e.Course Sand (%) (200-2000 µm), Fine Sand (%) - (20-200 µm), Sand (%), Silt (%) (2-20 µm), Clay (%) (<2 µm), and B) Chemical properties- such as, Ammonium Nitrogen (mg/Kg), Nitrate Nitrogen (mg/Kg), Phosphorus Colwell (mg/Kg), Potassium Colwell (mg/Kg), Sulphur (mg/Kg), Organic Carbon (%), Conductivity (dS/m), pH (CaCl2), pH (H2O), DTPA Copper (mg/Kg), DTPA Iron (mg/Kg), DTPA Manganese (mg/Kg), DTPA Zinc (mg/Kg), Exc. Aluminium (meq/100g), Exc. Calcium (meq/100g), Exc. Magnesium (meq/100g), Exc. Potassium (meq/100g), Exc. Sodium (meq/100g) and Boron Hot CaCl2 (mg/Kg). This data would have application for land managers. The soil chemistry data is also related to the eDNA OTU table published on "https://doi.org/10.4227/05/5878480a91885", titled "Revegetation rewilds the soil bacterial microbiome of an old field. Part 1: OTU raw data matrix", and as such it would have an appeal to researchers undertaking a meta-analysis on eDNA and restoration outcomes.

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    These datasets provide the data underlying the publication on <i>"Lines in the sand: quantifying the cumulative development footprint in the world’s largest remaining temperate woodland"</i> <em> https://link.springer.com/article/10.1007/s10980-017-0558-z. </em>. The datasets are: (A) data in csv format: [1] development footprint by sample area: Information on the 24, ~490 km^2 sample areas assessed in the study, including the different infrastructure types (roads, railways, mapped tracks, un-mapped tracks which have been manually digitized in the study using aerial imagery and hub infrastructure such as mine pits and waste rock dumps, also manually digitized in the study). Also contains some key co-variables assessed as potential explanatory variables for development footprint. The region-wide modelling of development footprint found strong positive effects of mining project density and pastoralism, as well as a highly significant negative interaction between the two. At low mining project densities, development footprints are more extensive in pastoral areas, but at high mining project densities, pastoral areas are relatively less developed than non-pastoral areas, on average. [2] Great Western Woodlands (GWW) 20 km grid: The datasets provides data for the 20x20 km grid placed over the whole GWW and used for the regional estimation of development footprint, linear infrastructure density, and linear infrastructure type based on the region-wide analysis. Data is for each cell in the grid and provides the total length of roads in that grid cell, MINEDEX mining projects, pastoral status, etc. This dateset was used to project the data from the 24 study areas across the whole of the Great Western Woodlands and calculate region-wide estimates of development footprint and linear infrastructure lengths. [3] disturbance by patch: This dataset provides the data for each patch for the analysis of patch-level drivers of development footprint, which was performed to gain further insights into the effects of other landscape variables that what could be gleaned from the region-wide analysis. For this analysis, we divided sample areas into polygonal patch types, each with a unique combination of the following categorical co-variables: pastoral tenure, greenstone lithology, conservation tenure, ironstone formation, schedule-1 area clearing restrictions, environmentally sensitive area designation, vegetation formation, and sample area. For each patch type (n=261), we calculated the following attributes: a) number of mining projects, b) number of dead mineral tenements, c) sum of duration of all live and dead tenements, d) type of tenements (exploration/prospecting tenement, mining and related activities tenement, none), e) primary target commodity (gold, nickel, iron-ore, other), f) distance to wheatbelt, and g) distance to the nearest town. [4] mapped versus digitized tracks: This dataset provides mapped and un-mapped track widths, measured using high-resolution aerial imagery at at least 20 randomly-generated locations within each of 24 sample areas. Pastoral tenure and mining intensity for each sample area are included for analysis purposes. [5] edge effect scenarios: Hypothetical edge effect zones were created, based on effect zones gleaned from the literature and arranged under three scenarios, to reflect potential risks of offsite impacts in areas adjacent to development footprints observed (see appendix 3 of article). The calculated proportion of the entire GWW within edge effect zones varied from ~3% under the conservative scenario to ~35% under the maximal scenario. Within the range of development footprints observed in this study, the proportion of a landscape that lies within edge effect zones increases hyperbolically with the number of mining projects, and approaches 100% in the maximal scenario, 60% in the moderate scenario, and ~20% under the conservative scenario. shapefiles: [6] Great Western Woodlands boundary, [7] sample areas (layer file shows sample areas by category).

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    Data is provided from three survey types: nocturnal drive-by monitoring; ground counts; and exit counts. The nocturnal drive-by monitoring dataset provides information on species presence/absence at 124 sites across Christmas Island. The ground count dataset provides information on numbers of bats observed roosting in trees at known camp sites; while the exit count dataset records counts of bats exiting from the respective camp sites.

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    In 2013 the scope of the Island-wide Survey was expanded to gather data at each survey site about scale insect assemblages. This involves a vegetation survey of twelve key tree species that play a role in YCA-scale insect mutualism. These tree species are an effective proxy for the scale species present in an area. The dataset contains vegetation transect survey data on the target twelve key tree species that play a role in YCA-scale insect mutualism, collected during the Island-wide Survey.

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    This data set contains information on Electrical Conductivity and pH from bore water from two plots, Blackbutt and Salmongum the Great Western Woodland Site.

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    We present a High-throughput eDNA dataset of fungi to track functional recovery in ecological restoration in the form of an OTU raw data matrix. We generated a total of 4,993,144 ITS fungal raw reads (118,884 ± 42,210 SD per replicate) across the 42 replicates. A total of 4,955,680 fungal sequences (117,430 ± 42,164 SD per replicate) remained for further analysis after quality filtering. The OTU data provide information on fungal flux at this restoration site through a stagger of years and can be used accordingly.