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1 urn:ogc:def:uom:EPSG::9001

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  • The DiGMap Plus dataset is a series of GIS layers describing the engineering properties of materials from the base of pedological soil down to c. 3m depth (ie the uppermost c.2m of geology). These deposits display a variable degree of weathering, but still exhibit core engineering characteristics relating to their lithologies. The 'Strength' dataset covers England, Scotland and Wales and characterises the material lithology, and its strength (for field description purposes) as outlined in documentation relating to BS5930 (1999 and 2003 and Eurocode7).

  • The data comprise water quality measurements taken from streams and rivers in the Conwy catchment and its estuary from March 2013 to October 2016. Depending on water type and sampling location the data consist of concentrations of major cations and anions, pH, conductivity, alkalinity, suspended material and coliforms. Samples were collected manually or by automatic sampler. Analysis was carried out at the Centre for Ecology & Hydrology (CEH) Bangor, CEH Lancaster and Bangor University laboratories. The data were collected provide information on the relationship between stream water quality, primarily macronutrient concentrations, and catchment and hydrological characteristics. The data are used to drive a catchment scale water quality model, and to investigate nutrient ratios and limitation with respect to land cover and management. All sampling and analysis was carried out by trained members of staff from the Centre for Ecology & Hydrology and Bangor University. This data was assembled under the NERC project 'The Multi-Scale Response of Water quality, Biodiversity and Carbon Sequestration to Coupled Macronutrient Cycling from Source to Sea' (Turf2Surf). Full details about this dataset can be found at https://doi.org/10.5285/32392c33-8cbe-434a-a582-ab8425a5062c

  • This dataset is a model output from the JULES land surface model driven with the Watch Forcing Data methodology applied to Era-Interim (WFDEI) data. It provides monthly global methane emissions from natural wetlands on 0.5 x 0.5 degree grid between 1980-2014. It includes the following variables: - fch4_wetl: modelled methane flux from natural wetland, in mg CH4 m-2 day-1 - fwetl: fraction of wetland - cs: soil carbon in each of these four soil carbon pools: decomposable plant material, resistant plant material, microbial biomass and humus), in kg m-2 - t_soil: sub-surface temperature of the four modelled soil layers (0-0.1 m, 0.1-0.35 m, 0.35-1.0 m and 1.0-2.0 m), in K Full details about this dataset can be found at https://doi.org/10.5285/6ce61e91-6912-4fe2-a095-12136af86347

  • Half-hourly data from eight eddy covariance towers deployed in the Sevilleta Refuge (New Mexico, USA). The main sensors deployed were sonic anemometer, relative humidity sensor and carbon dioxide concentration sensor . They were deployed and maintained by Fabio Boschetti and Andrew Cunliffe (University of Exeter). The data were collected to test the new design of eddy covariance towers and investigate the spatial variability of fluxes. Data were collected from 2018-11-01 to 2019-11-01. The data contains very few small gaps due to maintenance. Half-hourly data were gap-filled using code published on GitHub. The research was funded through NERC grant reference NE/R00062X/1 - "Do dryland ecosystems control variability and recent trends in the land CO2 sink?" Full details about this dataset can be found at https://doi.org/10.5285/e96466c3-5b67-41b0-9252-8f8f393807d7

  • The data presented are growth and physiological measurements from an ozone exposure experiment, during which grassland forbs, Leontodon hispidus and Succisa pratensis were exposed to low, medium and high ozone treatments over three growing seasons, using an outdoor Free Air Ozone Enrichment system, and with and without the addition of nitrogen during the first year. The plants were planted in April 2016 and were exposed to Low, Medium and High ozone treatments over three growing seasons (May to September 2016-2018). Measurements were taken of light-saturated photosynthesis, stomatal conductance, chlorophyll index, number of flowering stems, leaf ground cover, and the dried weight of litter. All measurements were made by members of the project. The experiments were carried out in the UKCEH Bangor Air Pollution Facility. Work was funded by the UK Centre for Ecology & Hydrology under the Natural Environment Research Council (UK) grant/award NEC05574. For L. hispidus a lower leaf cover was observed with elevated ozone, and there was an increase in litter with added nitrogen. For S. pratensis, elevated ozone reduced flowering and increased foliar damage. Increased litter and accelerated winter die-back with both ozone and nitrogen were also recorded for S. pratensis. These effects have implications for inter- and intra-specific competition, seed establishment, nutrient cycling, as well as the provision of general pollinator resources and highlight the need for concerted action to reduce pre-cursor ozone emissions to go alongside habitat management efforts to protect biodiversity. Full details about this dataset can be found at https://doi.org/10.5285/382baaf2-7795-4aa8-a434-56c9e6bd1516

  • The data comprise outcomes from questionnaire surveys conducted with greenspace users on their perceptions of experimentally manipulated urban meadows (varying levels of diversity and vegetation height of sown wildflower meadows), and associated socio-economic data of respondents to the questionnaire surveys. The experimental meadows were located in Bedford and Luton. Data was collected by the data authors, and participants gave informed consent before completing the questionnaires. The work was initially completed under the Fragments, functions and flows NERC BESS project in 2014. The scaling of biodiversity and ecosystem services in urban ecosystems was funded by grant NE/J015369/1 from the Biodiversity and Ecosystem Service Sustainability (BESS) programme. Subsequent analysis was carried out under the NERC grant ‘Location, Configuration, Distribution: the Role of Landscape Pattern and Diversity in Ecosystem Services’ (NE/K015508/1). Full details about this dataset can be found at https://doi.org/10.5285/29d6345f-9f53-4894-8f60-80843f49c017

  • The dataset details the locations and attributes of canopy disturbances in Nyungwe National Park, Rwanda, that were suspected to have been caused by lightning strikes. Disturbances were located by surveying 23 km of trails and assessing whether disturbances (clusters of dead or damaged trees) had damage signatures consistent with lighting. Only disturbances that were thought to potentially have been caused by lightning were recorded. As well as providing a qualitative assessment of the confidence that the damage was caused by lightning, the dataset contains the number of dead and damaged trees in different size classes, as well as the taxonomic identity and degree of crown damage experienced by canopy trees within the putative strike. Photographs of a subset of strikes are also provided. Data were collected as part of the project Lightning in African tropical forests: from tree mortality to carbon dynamics (NE/W003872/1). Full details about this dataset can be found at https://doi.org/10.5285/d47e78bc-2227-4bc7-90ae-9ec871c52bec

  • This data resource provides plot-level plant occurrence data for the first eight years (2015-2022) of the National Plant Monitoring Scheme (covering the UK, the Channel Islands, and the Isle of Man). Data consist of individual observations of plants, and other habitat characteristics, at the metre-scale; observations are accompanied by percentage cover information recorded according to the Domin frequency-abundance scale commonly used in plant community ecology. Other information provided includes the plot type (size, shape, according to the NPMS classification), the volunteer-recorded NPMS habitat, the date of sampling, and information regarding the spatial location of the plot. Information contained within the metadata file should allow users to reconstruct the sampling history (including gaps) of any plot that has been sampled within the NPMS scheme between 2015 and 2022. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Please be aware that this dataset is updated annually and that more recent versions exist. Full details about this dataset can be found at https://doi.org/10.5285/f7ef2dc5-2bce-4436-8f65-90f7a99acff2

  • This dataset contains carbon and nitrogen data from soils and vegetation from 13 calcareous grassland, 13 heathland and 12 woodland sites within Dorset, UK. The sites were selected to represent a range of habitat types across a condition gradient as measured by levels of degradation from the original habitat. The original habitats were identified as being calcareous grassland, heathland or woodland from a survey conducted in the 1930s. Within each site, 15cm deep soil cores were taken and analysed for total nitrogen, total carbon and bulk density. Within the same area for each site, vegetation samples were taken from five 50cm quadrats and separated into herbacous or shrub layers before analysis for total carbon, total nitrogen and dry weight. Heathland and calcareous grassland sites were visited in summer 2017 and woodland sites were visited in summer 2018. Full details about this dataset can be found at https://doi.org/10.5285/ea43c2d1-88f5-4692-a09d-0ef4d96e0f35

  • These data are GIS shapefiles which contain geospatial information describing the location and condition of bridges, buildings and roads in Chamoli District, Uttarakhand, India, following the 7th February 2021 avalanche and debris flow hazard cascade (the so-called ‘Chamoli event’). The dataset also contains a GIS shapefile which contains polygon outlines supporting geomorphological analysis of change in river valleys between the avalanche source and the town of Joshimath. The latter is designed to be used in conjunction with the other data resources contained in this data collection. Full details about this dataset can be found at https://doi.org/10.5285/a763e254-c249-4934-b0fb-c3b808b37db6