EARTH SCIENCE > Biosphere > Vegetation
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A hand-held Garmin GPS was used to map vegetation patches on Leonie and Anchorage Island in February 2007. Discrete patches of vegetation were walked round, and the recorded track saved. The aim of the data collection was to provide some ground truthing data for vegetation NVDI (Normalized Difference Vegetation Index) ratios calculated from satellite data. Funding: UK Natural Environment Research Council (core funding to the British Antarctic Survey).
This dataset consists of (i) 673 red-green-blue (RGB) images, (ii) precise coordinates of ground control points and harvest plot corners, (iii) the photogrammetrically reconstructed dense point cloud (comprising of 228,315,000 points with XYZ and RGB values), (iv) four normalised difference vegetation index (NDVI) maps, (v) aboveground biomass data from harvest plots, and (vi) observations of the ground surface obtained from a walkover survey with a GNSS instrument. These data were collected over the eastern part of Qikiqtaruk - Herschel Island, in the Canadian Yukon (69.5N, 138.8W). The images were collected in July and August 2016. Further details on the image processing are provided in the lineage section. This dataset was created by Andrew Cunliffe, with support from Isla Myers-Smith, Jakob Assmann, Jeffery Kerby and Gergana Daskalova (https://teamshrub.com/), in order to inform ongoing ecological monitoring studies in this area. This research was supported by the Natural Environment Research Council (NE/M016323/1), and the NERC Geophysical Equipment Facility (GEF:1063).
We present here the land cover classification across West Antarctica and the McMurdo Dry Valley produced from Landsat-8 Operational Land Imager (OLI) images of six proglacial regions of Antarctica at 30 m resolution, with an overall accuracy of 77.0 % for proglacial land classes. We conducted this classification using an unsupervised K-means clustering approach, which circumvented the need for training data and was highly effective at picking up key land classes, such as vegetation, water, and different sedimentary surfaces. This work is supported by the Leeds-York-Hull Natural Environment Research Council (NERC) Doctoral Training Partnership (DTP) Panorama under grant NE/S007458/1. The Ministry of Education, Youth and Sports of the Czech Republic project VAN 1/2022 and the Czech Antarctic Foundation funded fieldwork that contributed to part of this work.
Genetic variation on a spatial scale was assessed, using both DNA fingerprinting and sequencing-based approaches, in the Antarctic endemics Buellia frigida, Carbonia vorticosa and Amandinea petermananii, and in the bipolar species Caloplaca saxicola, Umbilicaria decussata and Cladonia galindezii. PCR-based (Polymerase Chain Reaction) molecular biology techniques, were used as they are ideal for working with lichens because little starting material is required. See Fabian et al. 2007 for further information on analyses and results.
The fieldwork involved collection of fertile lichens from a range of sites across the Antarctic Peninsula and isolation of the lichen-forming fungi into pure culture in a laboratory at Rothera. Approximately 5,600 monospore cultures were isolated, including B frigida. Approximately 400 thalli of Usnea species, and 3 O. frigida thalli have also been collected for whole thallus analysis. Logarithmic sampling transects of B frigida were conducted at Rothera (2 transects) and on Anchorage Island (one transect) to examine the genetic variation and geographic variation. All thalli of B frigida collected from the transects were successfully used to generate viable spores from four individual apothecia from each thallus. 16 spores were subcultured and maintained from each apothecium.
The Weather Research and Forecasting (WRF) model output over the whole of Peru at 12 km horizontal resolution and 3 hourly output (domain 1, d01), the Rio Santa River Basin (in the Cordillera Blanca) at 4 km horizontal resolution and hourly output (domain 2, d02), the Vilcanota-Urubamba region at 4 km horizontal resolution and hourly output (domain 3, d03) and the upper region of the Rio Santa River Basin at 800 m horizontal resolution and hourly output (domain 4, d04). Domains 1 to 3 cover the period from 1980 to 2018, domain 4 covers from 2009 to 2018. Full details of the WRF model setup can be found in Fyffe et al., (2021). These data were corrected as part of the PEGASUS (Producing EnerGy and preventing hAzards from SUrface water Storage in Peru) and Peru GROWS (Peruvian Glacier Retreat and its Impact on Water Security) projects. The datasets were created to assess past climate in the Peruvian Andes, as a basis to determine future climate in the region, and as an input for glaciological and hydrological models. The data were created using the British Antarctic Survey high performance computer. The creation of this data was conducted under the Peru GROWS and PEGASUS projects, which were both funded by NERC (grants NE/S013296/1 and NE/S013318/1, respectively) and CONCYTEC through the Newton-Paulet Fund. The Peruvian part of the Peru GROWS project was conducted within the framework of the call E031-2018-01-NERC "Glacier Research Circles", through its executing unit FONDECYT (Contract No. 08-2019-FONDECYT).