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  • Collated indices are a relative measure of butterfly abundance across monitored sites in the UK, calculated from data collected by the UK Butterfly Monitoring Scheme (UKBMS). Collated indices are calculated annually for each individual butterfly species that has been recorded on five or more sites in that year. Based on this criterion collated indices have been calculated for the entire UKBMS time series from 1976 to the current year for the majority of species. For some rarer species the time series starts in a later year due to lack of data. Collated indices are calculated using a statistical model that accounts for missing data. The number of sites for each species ranges from 5 to several hundred and varies from year to year. Since 2008 more than 1,000 sites have been monitored across the UK each year. Collated indices are calculated so that we can determine how butterfly populations are changing over time across the UK. This data can be used, for example, to determine where to target conservation efforts and to measure the condition of the UK countryside. Butterflies are recognised as important indicators of biodiversity and environmental change (e.g. as official UK Biodiversity Indicators), and have been used in numerous research studies to understand the impacts of changes in climate and the extent and condition of habitats. Although the UK Centre for Ecology & Hydrology (UKCEH) and Butterfly Conservation (BC) are responsible for the calculation and interpretation of the Collated indices, the collection of the data used in their creation is ultimately reliant on a large volunteer community. The UKBMS is funded by a consortium of organisations led by the Joint Nature Conservation Committee (JNCC). This dataset is updated annually and more recent versions of the UKBMS collated indices are available. Full details about this dataset can be found at https://doi.org/10.5285/31f301f5-5374-45c5-8db5-37ea43422b8d

  • This dataset contains greenhouse gas flux data and vegetation survey data from an experiment based at Parsonage Down, UK. The vegetation survey comprises total species percentage cover and species richness data from four 50 cm by 50 cm quadrats. The greenhouse gas flux data comprises net ecosystem carbon dioxide exchange, photosynthesis and respiration data measured with an Infra-red Gas Analyser (IRGA); methane, carbon dioxide and nitrous oxide data measured using gas chromatography; and nitrate and ammonium from soil samples extracted with potassium chloride. The experiment investigated the effect of different plant groups on soil carbon stores and nutrient cycling, by using a mixture of hand weeding and herbicide spot spraying to create different plant communities on the species rich grassland at Parsonage Down. The resulting carbon and nutrient cycling rates were compared to the characteristics of the plant groups. The experiment ran from 2013 to 2015 and this dataset contains data from 2014 only. This experiment was part of the Wessex BESS project, a six-year (2011-2017) project aimed at understanding how biodiversity underpins the ecosystem functions and services that landscapes provide. Full details about this dataset can be found at https://doi.org/10.5285/e05b350f-3cf4-4f8d-aa3c-24d562ca756b

  • [THIS DATASET HAS BEEN WITHDRAWN]. This dataset contains vegetation survey data from an upland heath site in the Clocaenog Forest. Vegetation was surveyed in the experimental plots at the Climoor site in 1998, 1999, 2000, 2002, 2003, 2007, 2008, 2009, 2010, 2011 and 2012. The vegetation at the site is a typical UK upland heathland, dominated by Calluna vulgaris, with Vaccinium myrtillus and Empetrum nigrum also being present in the vegetation understory. In each year, measurements were taken at a time period of maximum growth, which was late August/early September. This was done by pin point methodology, and data includes both pin hits as well as measurements converted into plant biomass. Individual species can be examined, as well as the different components of the higher plants (i.e. leaf, stem, flower). Full details about this dataset can be found at https://doi.org/10.5285/143e1a69-d4d7-4ae0-9650-6ffad9fd75b2

  • The dataset comprises hourly water temperature data of an experimental mesocosm facility as well as air temperatures from beginning of July to end of September 2022. The experiment aimed to investigate the effect of different nutrient regimes on Taste and Odour issues. Mesocosms were filled with reservoir water and water temperature was measured by platinum resistance thermometers (PRT) shaded by a plastic cover, sited around mid-depth, radially offset by 30 cm from the mesocosm's side wall and logged by a Campbell Scientific Data Logger. Air temperature was measured at a weather station within the mesocosm compound (Vaisala weather transmitter WXT520) at around 2.7m height. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/2858a0e9-9b20-4c2c-892c-4a99fe49e315

  • The dataset consists of pH, Loss on ignition (Soil organic matter) measurements and soil group information taken from soil samples from plots in 103 woodland sites surveyed across Great Britain in 1971 and again over the growing seasons of 2000, 2002 and 2003 (referred to as '2001 survey'), using exactly the same field methods. Data were collected under projects managed by The Nature Conservancy (in 1971) and the Centre for Ecology & Hydrology (in 2001). Full details about this dataset can be found at https://doi.org/10.5285/fb1e474d-456b-42a9-9a10-a02c35af10d2

  • Dataset contains Terrestrial laser scanner (TLS) and CT scan data collected during fieldwork on a small gravel-bed river. TLS data show the river bed surface topography collected at five intervals between September 2014 and October 2018. CT scan data show the 3D structure of sections of the river bed. CT data has been processed to segment the images into gravel grains and fine-grained matrix. Full details about this dataset can be found at https://doi.org/10.5285/b30b4d56-f0a9-43e8-aacc-09d9b5b1f9fc

  • 3D digital elevation models of Tsho Rolpa glacier lake, Nepal, generated from unmanned aerial vehicle (UAV) imagery, with a spatial resolution of 10 centimetres. It is combined with bathymetry data so that both the lakebed elevation (DTM) and the lake surface elevation (DSM) are obtained. Full details about this dataset can be found at https://doi.org/10.5285/8e483692-3b65-41d2-a7fd-5a3cd589a71c

  • This dataset consists of the 1km raster, percentage aggregate class version of the Land Cover Map 1990 (LCM1990) for Northern Ireland. The 1km percentage product provides the percentage cover for each of 10 aggregated land cover classes for 1km x 1km pixels. This product contains one band per aggregated habitat class (producing a 10 band image). The 10 aggregate classes are groupings of the 21 target classes, which are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. The aggregate classes group some of the more specialised classes into more general categories. For example, the five coastal classes in the target class are grouped into a single aggregate coastal class. This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution. LCM1990 is a land cover map of the UK which was produced at the UK Centre for Ecology & Hydrology by classifying satellite images (mainly from 1989 and 1990) into 21 Broad Habitat-based classes. It is the first in a series of land cover maps for the UK, which also includes maps for 2000, 2007, 2015, 2017, 2018 and 2019. LCM1990 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the UK CEH web site and the LCM1990 Dataset documentation) to select the product most suited to their needs. 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. Full details about this dataset can be found at https://doi.org/10.5285/1278d7b5-da47-46b5-b1a6-049e726425a7

  • The dataset includes lists of local tree names, tree species identification and local uses of trees in seventeen different villages across three Districts in Mozambique, Africa. We collated species lists from seven villages in Mabalane District, Gaza Province, ten villages in Marrupa District, Niassa Province, and ten villages in Gurue District Zambezia Province. Data were collected in Mabalane between May-Sep 2014, Marrupa between May-Aug 2015, and Gurue between Sep-Dec 2015. Lists of local tree names were collated from several forest plots and agricultural field surveys occurring within the sampled villages, and their species identified in the field by the authors and/or from dried and pressed samples by botanists at the Universidade Eduardo Mondlane in Maputo. Tree species uses by local populations were recorded through a mixture of key informant interviews, focus group discussions, village surveys and ad-hoc observations. This dataset was collected as part of the Ecosystem Services for Poverty Alleviation (ESPA) funded ACES project , which aims to understand how changing land use impacts on ecosystem services and human wellbeing of the rural poor in Mozambique. Full details about this dataset can be found at https://doi.org/10.5285/52371ef0-855f-40c8-8567-f8965f9cbf03

  • The data comprises of dimensions of large wood pieces and the isotope composition (radiocarbon, stable carbon isotopes) of cellulose extracted from the wood samples. Large Wood (LW) samples were collected from the Mackenzie River delta region, Northwest Territories, Canada, in August 2019 and were analysed at the National Environmental Isotope Facility, UK. The scientific aims were to help constrain the source and age of wood carried by this large river system draining to the Arctic Ocean. Full details about this dataset can be found at https://doi.org/10.5285/19be1a45-c457-40af-a582-395257d7a3b0