University of Reading
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This dataset consists of behaviour and distribution data of Lepidoptera at the Stonehenge World Heritage Site in Wiltshire, UK, between 2010-2011. A long term landscape scale grassland restoration and re-creation project has been underway at the site since 2000. 200m long transects were located in the centre of different grassland re-creation fields of different ages, arable land, chalk grassland fragments on slopes and on ancient burial mounds, and semi-improved pasture. Transects were surveyed on three occasions spread across the field season (June to September), and throughout the day and were selected ad-hoc for survey in order to minimise the effect that the time of year and day would have on results. During the survey, the transect was walked at a slow, steady pace allowing five minutes for each 20m section of transect and the number and species of Lepidoptera present 5m either side and ahead were recorded. If Lepidoptera were observed feeding, then the nectar plant species was also recorded. Habitat quality, defined in terms of vegetation characteristics and nectar resources, was quantified throughout each transect by sampling quadrats in each 20m segment of the transect. Vegetation characteristics were measured as vegetation height and density and the percentage cover of bare ground and dead vegetation. Nectar resources were measured in terms of the number and percentage coverage of flowering units, the total number of nectar flowering units and of relevant families (Dipsacaceae, Fabaceae and Asteraceae). The data were collected as part of a PhD project funded by the Natural Environment Research Council and the National Trust. Full details about this dataset can be found at https://doi.org/10.5285/a384bdfb-0bf2-4c3e-80ab-e171f38d503d
This dataset consists of behaviour and distribution data of Lepidoptera from chalk grassland fragments at the Stonehenge World Heritage Site in Wiltshire, UK, in 2011. The landscape consists of small fragments of ancient chalk grassland on slopes and groups of burial mounds (barrows) which have retained many of the characteristic chalk grassland plant and butterfly species. Surveys were located at four of these chalk grassland fragments. At each chalk grassland fragment, four 20 m long survey boundaries, were set up on boundaries with adjacent land cover of either arable land or new grassland re-creation sown in the years 2009 or 2010. Control surveys were also carried out in areas of continuous habitat within the chalk grassland fragment and in the adjoining land cover type. Surveys of Lepidoptera behaviour were carried out from May to July between 10am and 4pm and effort was taken to survey the same site at different times of the day in order to minimise the effect of survey time on behaviour. Standing at the chalk grassland fragment edge the flight path of individual Lepidoptera was tracked in the survey area for up to three minutes. Measures of vegetation characteristics and nectar flower availability were recorded for each plot. Vegetation characteristics were measured as vegetation height and density and the percentage cover of bare ground and dead vegetation. Nectar resources were measured in terms of the number and percentage coverage of flowering units, the total number of nectar flowering units and of relevant families (Dipsacaceae, Fabaceae and Asteraceae). The data were collected as part of a PhD project funded by the Natural Environment Research Council and the National Trust. Full details about this dataset can be found at https://doi.org/10.5285/61561232-3307-470a-b8dc-a923b25e1641
his dataset consists of behaviour and distribution data of Lepidoptera from mown chalk grassland boundaries at the Stonehenge World Heritage Site in Wiltshire, UK, between July and August 2012. The landscape consisted of a mosaic of chalk grassland fragments on ancient burial mounds (barrows) and slopes, grassland re-creation fields of different ages since sowing, semi-improved pasture, arable farmland and woodland. In one of the grassland re-creation fields, two large areas were mown and eight 20 m long survey boundaries were set up. Four of these were set up on the edge of one of two mown areas and four were set up in areas of continuous un-mown grass which had dummy 'boundaries' parallel to the mown boundaries. The survey was conducted from the survey boundary and the flight path of individual Lepidoptera was tracked in the area 10 m either side of the survey boundary. Each individual Lepidoptera flight path was surveyed for three minutes. Each boundary was surveyed for a total of 20 minutes on three occasions over a five week period. The sequence of boundaries surveyed was chosen randomly and equal survey effort was allocated to visually searching both sides of the boundary. The order and time of day for surveying each survey area was random so to spread surveys throughout the survey period and throughout the day. Measures of vegetation characteristics and nectar flower availability were recorded for survey areas. Recorded vegetation characteristics included vegetation height and density. Nectar flower availability was measured as the number of flowering units of nectar flowers and numbers of those in the Asteraceae, Fabaceae and Dipsacaceae families. The data were collected as part of a PhD project funded by the Natural Environment Research Council and the National Trust. Full details about this dataset can be found at https://doi.org/10.5285/e3598268-22d7-4913-a736-890728ea858b
Data consist of field spectral reflectance measurements and surface photographs of cyanobacterial soil crusts and other surficial materials in Diamantina National Park, Queensland. Data were collected as part of project NE/K011626/1 (associated with NE/K011464/1) Multiscale Impacts of Cyanobacterial Crusts on Landscape Stability. The reflectance data and associated surface photographs are of biological and physical soil crusts developed on claypan and sand dune surfaces alongside the Diamantina River (specifically on and around Lake Constance pan and Homestead pan. Data were collected and processed by Kevin White and Ian Davenport, using a Spectra Vista Hr1024i spectrometer with a spectralon reference panel. All data were processed using SVC Hr1024i PC Data acquisition software (version 1.6.7 Beta) to remove areas of spectral overlap. Photographs taken using a range of mobile device cameras. All field photographs are in JPEG (jpg) format. Data were collected for the purpose of assessing the ability to remotely sense presence/absence of cyanobacterial soil crusts for mapping purposes. Data are organised into a directory structure based on specific field experiments, each with its own directory structure. Dataset 1: Calcrete Reflectance Spectra, Diamantina National Park. Calcrete exposures are common in Diamantina National Park, forming flat-topped hills known locally as 'Jump-Ups'. Calcretes creat false positives with the commonly used biological soil crust indices from remote sensing data, so field spectra of calcretes were collected to characterise their spectral reflectance to assist with image processing. Dataset 2: Lake Constance Pan Mapping project Field Photographs, Reflectance Spectra and field notes, Lake Constance Clay Pan, Diamantina National Park. This dataset is a repeat survey undertaken in 2015, which revisited sample points first surveyed as part of the so-called 'MAM survey' in 2000. Dataset 3: Solar Radiation Photosynthesis experiment Field Photographs and Reflectance Spectra from three locations in Diamantina National Park, Lake Constance pan, a duneflank site on ‘Crusty Inlet dune’ (where no photosynthesis could be stimulated) and Homestead pan. The Homestead pan experiment was run twice (Winter 2015 and Summer 2016). Dataset 4: Shade netting experiment Spectral Reflectance measurements of a spectralon panel were taken under the shade netting to characterise the transmissivity of the netting at different solar elevation angles. Dataset 5: Photographic cards Spectral reflectance measurements of a set of photographic reference cards, which were included in the frame of all the surface photographs collected for this project. Dataset 6: Mobile Device experiment Field Photographs taken with a range of mobile device cameras (Moto G, Nexus 6 and Samsung Galaxy Note 10.1) and two cameras (Nikon Coolpix P610 and Nikon Coolpix 950 Full Spectrum), and associated reflectance spectra data, for 5 study sites Crusty Inlet Pan Surface, Crusty Inlet Dune North Flank, Lake Constance Pan and Homestead Dune. Dataset 7: Rainfall simulator Spectral reflectance data and associated field notes of sites used in a rainfall simulator/wind tunnel experiment, Lake Constance claypan (which formed part of the associated NERC project NE/K011464/1)
This resource comprises abundance data for invertebrates, pest damage to apples, and yields from an agroforestry system subject to two different understorey management treatments, comprising an unmown flowering understorey and a mown understorey. The data was collected from an intercropped apple-arable agroforestry site in Screveton, Nottinghamshire, UK, from five experimental blocks, each block split between the two understorey management treatments. The data was collected between April and September 2020. Data was collected using (i) pitfall traps, (ii) sticky traps, (iii) visual searches of apple trees for natural enemies, pests and fruit damage from pests and disease, (iv) flower visitation counts for pollinators, (v) apple fruit yield and quality metrics, and (vi) grain yield samples. The data was collected to compare the effect of understorey management in agroforestry on functional invertebrates and associated ecosystem services. All data was collected by Tom Staton (University of Reading). Three pitfall traps were damaged and are excluded from the dataset, comprising (i) Visit 1, Block 2, Mown treatment, Position 4; (ii) Visit 4, Block 2, Mown treatment, Position 3; and (iii) Visit 4, Block 3, Unmown treatment, Position 2. The research was funded under NERC grant NE/R012229/1 Quantitative and Modelling Skills in Ecology and Evolution (QMEE) CDT Full details about this dataset can be found at https://doi.org/10.5285/83a10b11-23ef-4378-a56d-c63cce365275
This dataset includes relative surface soil moisture across the Thames Valley, between October 2015 and September 2021, using backscatter radar data collected using the ESA Sentinel-1 Constellation. Radar backscatter was normalised to 40 incidence angle, using a novel monthly normalisation parameterisation. Full details about this dataset can be found at https://doi.org/10.5285/b23d63d1-dcc5-4c49-a6b5-67154f3739b7
2 examples of Integrated Water Vapour Transport (IVT) maps generated using a new algorithm produced from the work done under the Grant. This algorithm has been published and the article can be found here: http://onlinelibrary.wiley.com/doi/10.1029/2012JD018027/abstract
This dataset includes laboratory and field measurements of carbon fluxes and spectral reflectance for peatland vegetation including Sphagnum species. It also includes satellite data relating to the development and use of a Temperature and Greenness (TG) model, and an annual Temperature, Greenness and Wetness (TGWa) model. The laboratory data includes Gross Primary Productivity (GPP) and respiration data from samples of Sphagnum capillifolium and Sphagnum papillosum which were collected from the Forsinard Flows RSPB reserve (Northern Scotland) and subjected to different rainfall simulations, including total drought, in the laboratory. Spectral reflectance of the samples was also measured throughout the experiment, and the vegetation indices calculated are recorded. The field data includes carbon fluxes and spectral reflectance measurements, in this case taken from collars located at three sites within the Forsinard Flows Reserve during the main growing season of 2017 (March to September). Associated measurements of temperature, Photosynthetically Active Radiation (PAR), and moisture content were recorded. The species composition of the collars is also given in the data. The satellite data include Land Surface Temperature (LST) and Normalised Difference Vegetation Index (NDVI) products from the Moderate Resolution Imaging Spectroradiometer (MODIS) used to develop a TG model over the Forsinard Flows reserve, and the Glencar bog in Ireland. The dataset also includes bands used to calculate the Normalised Difference Water Index (NDWI) to develop the TGWa model. The MODIS data used in the implementation of this model to assess restoration progress, and also upscaling effectiveness, are included in the dataset. The work was carried out during a PhD project part-funded by the NERC SCENARIO DTP (Grant number: NE/L002566/1) at the University of Reading, and part-funded by The James Hutton Institute. Full details about this dataset can be found at https://doi.org/10.5285/ab9f47f9-9faf-4403-a57e-25e31f581ed0
This set of data is the second set of impact interviews conducted with the target communities of the BRAVE project. The interviews are transcriptions in Microsoft word. The communities involved in the data collection were from Tomo and Poa in Burkina Faso and Jawani and Tariganga in Ghana. There are 32 interviews from Burkinabe community members, and 23 from the Ghanaian communities. Individuals were selected based on their participation in the BRAVE field activity of the Farmer Voice Radio. The data was collected between October 2019 and February 2020 by the local researchers. This data methodology was built on the initial vulnerability assessments, and include questions around behaviour change and income change based on the BRAVE communities activities of ground water measurement and water management strategies. This data shows behaviour and livelihood change within the communities and due to these activities. This is final qualitative impacts dataset from the BRAVE project. Previous linked data sets include the baseline vulnerability assessments and the first round of impact interviews. BRAVE: Building understanding of climate variability into planning of groundwater supplies from low storage aquifers in Africa BRAVE is a ‘Consortium’ research project is part of the UPGro (Unlocking the Potential of Groundwater for the Poor) programme.
This data set consists of sets of qualitative data in the form of vulnerability questionnaires (referred to as tool 1) and interviews (referred to as Tool 2) from 4 communities - 2 in Northern Ghana and 2 in Burkina Faso.