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5 urn:ogc:def:uom:EPSG::9001

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  • The dataset contains information on the species identity and frequency of all insect-flower interactions recorded in 10 birch (Betula spp.) woodland fragments surveyed in 2009 (May-August). The data were collected in two transects (50 x 2m; 15m apart and at least 50m from the woodland edge) randomly situated prior to the onset of flowering in the centre of each wood. Five of the woodland sites were disturbed by cattle grazing, while five were undisturbed. Landowners confirmed that livestock had been absent for at least 70-100 years in undisturbed sites. Where livestock were present, cattle grazing was light to moderate (e.g. 2007: mean = 8.4 cattle ha-1) and long term (mean = 33 years). The dataset comprises 13 columns, 2002 rows and is 218 KB. It gives the site name, geographic coordinates, whether it was disturbed by cattle grazing or not, the wind speed and temperature at time of sampling, the date of sampling, and the identity of the insect and plants interacting (binomial name or recognisable taxonomic unit). Full details about this dataset can be found at https://doi.org/10.5285/4c058d1f-6166-4606-88a2-d2feaf036a2f

  • This dataset consists of the vector version of the Land Cover Map 2000 for Great Britain, containing individual parcels of land cover (the highest available resolution). Level 2 & Level 3 attributes are available. Level 2, the standard level of detail, provides 26 LCM2000 target or ('sub') classes. This is the most widely used version of the dataset. Level 3 gives higher class detail. However, the quality of this level of detail may vary in different areas of the country, requiring expert interpretation. The dataset is part of a series of data products produced by the Centre for Ecology & Hydrology known as LCM2000. LCM2000 is a parcel-based thematic classification of satellite image data covering the entire United Kingdom. The map updates and upgrades the Land Cover Map of Great Britain (LCMGB) 1990. Like the earlier 1990 products, LCM2000 is derived from a computer classification of satellite scenes obtained mainly from Landsat, IRS and SPOT sensors and also incorporates information derived from other ancillary datasets. LCM2000 was classified using a nomenclature corresponding to the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompasses the entire range of UK habitats. In addition, it recorded further detail where possible. The series of LCM2000 products includes vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions. Full details about this dataset can be found at https://doi.org/10.5285/b79e887e-a2a7-4224-8fd7-e78066b950b3

  • This is part of an ongoing long-term monitoring dataset of surface temperature, surface oxygen, water clarity, water chemistry and phytoplankton chlorophyll a from fortnightly sampling at Blelham Tarn in Cumbria, England that began in 1945 for some variables. The data have been collected by the UK Centre for Ecology & Hydrology (UKCEH). The data available to download comprise surface temperature (TEMP) in degree Celsius, surface oxygen saturation (OXYG) in % air-saturation, Secchi depth (SECC) in metres, alkalinity (ALKA) in µg per litre as CaCO3 and pH. Ammonium (NH4N), nitrate (NO3N), soluble reactive phosphate (PO4P), total phosphorus (TOTP), dissolved reactive silicon expressed as SiO2 (SIO2) and phytoplankton chlorophyll a (TOCA) are all given in µg per litre. Water samples are based on a sample integrated from 0 to 5 m. Measurements are made from a boat at a marked location (buoy) at the deepest part of the lake. When it was not possible to visit the buoy, samples were taken from the shore, thus water samples were not integrated on these occasions, marked as Flag 2. All data are from January 2014 until the end of 2018. 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/ae8c850d-211e-4560-8b37-437b6e0e2a16

  • The data consists of faecal microbiology and moisture content taken from two separate cohorts of 30 cattle. The cattle were from the North Wyke Farm Platform, a UK national capability, located at Rothamsted Research, North Wyke in Devon. Faecal samples were collected between November 2016 and July 2018. Samples were collected and microbiologically analysed in the laboratory within 6 to 8 hours. Two cohorts of 30 cattle were selected from 90 animals, ten from each of the three farmlets. Each cohort covering the period that cattle enter the farm platform, i.e. from weaning until slaughter ca. 16 – 20 months. Full details about this dataset can be found at https://doi.org/10.5285/ec83a4ea-923a-4f02-8a9f-aeecc43d7123

  • This is part of an ongoing long-term monitoring dataset of surface temperature, surface oxygen, water clarity, water chemistry and phytoplankton chlorophyll a from fortnightly sampling at Grasmere in Cumbria, England that began in 1968 for some variables. The data have been collected by the UK Centre for Ecology & Hydrology (UKCEH). The data available to download comprise surface temperature (TEMP) in degree Celsius, surface oxygen saturation (OXYG) in % air-saturation, Secchi depth (SECC) in metres, alkalinity (ALKA) in µg per litre as CaCO3 and pH. Ammonium (NH4N), nitrate (NO3N), soluble reactive phosphate (PO4P), total phosphorus (TOTP), dissolved reactive silicon expressed as SiO2 (SIO2) and phytoplankton chlorophyll a (TOCA) are all given in µg per litre. Measurements are made from a boat at a marked location (buoy) at the deepest part of the lake. When it was not possible to visit the buoy, samples were taken from the shore, thus water samples were not integrated on these occasions, marked as Flag 2. All data are from January 2014 until the end of March 2018. Unfortunately, due to funding shortages, the long-term monitoring of Grasmere ended in March 2018. 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/10.5285/86cce079-9410-4948-978a-1c92ff3d604c

  • This dataset measures the abundance of ant species at baited traps set across twelve trees in four experimental plots in lowland, tropical rainforest. Baited traps were set at 5 m vertical intervals from the ground to as high as possible in the canopy, the stratum of each trap location was recorded. At each height two pairs of baited traps were set, each pair contained one trap baited with carbohydrate (honey and oats) and the second with protein (tuna). Traps within each pair were separated by approximately 20cm were left open for 24 hours. All ants collected were identified to morphospecies level and the species abundance in each trap was recorded. Full details about this dataset can be found at https://doi.org/10.5285/62bf0251-ca8d-4288-a274-0ff6e39b3a3c

  • Data were generated to investigate the influence of bed roughness on the dynamics of large sand-bed rivers like the South Saskatchewan, Canada. The influence of roughness was investigated by using a numerical model to simulate the evolution of the river bed for a hypothetical sand-bed river modelled on the South Saskatchewan. The model generated information on the evolving river bed topography, water depth, flow velocities and sediment transport rates, over a period of 28 years as part of NERC project NE/L00738X/1 Full details about this dataset can be found at https://doi.org/10.5285/790e507c-ce99-47ca-99b4-c97a684ee8c6

  • The data set contains the Philippines bridge inventory, river migration geodatabase and source code to assess active river channel change (i.e. planform adjustments) using Landsat 5, 7 and 8 products in Google Earth Engine. The data set contains hydro-morphological and bridge characteristics for 74 bridges (> 200 m deck length) in the Philippines from 1988 to 2019 and is available in .csv and .shp format. For a given region of interest (ROI), the code will extract active river channel masks, calculate similarity coefficients between active river channel masks at decadal intervals and calculate active widths and centreline statistics. The code was used by Boothroyd et al. (in press) to investigate decadal river migration at critical bridge infrastructure in the Philippines. Full details about this dataset can be found at https://doi.org/10.5285/2efd24f9-e745-4f54-8bbd-6439b0ad93e5

  • Data are presented showing change in saltmarsh extent along 25 estuaries/embayments in six regions across Great Britain, between 1846 and 2016. Data were captured from maps and aerial photographs. Marsh extent was delineated a scale of 1:7,500 by placing vertices every 5 m along the marsh edge. Error introduced from: (i) inaccuracies in the basemap used to georeference maps and aerial photographs; (ii) the georeferencing procedure itself; (iii) the interpreter when placing vertices on the marsh edge; and (iv) map and photo distortions that occurred prior to digitisation were calculated and used to estimate the root mean square error (RMSE) in areal extent of each marsh complex. Measures of marsh extent were only recorded if maps and aerial photographs were available for the entire estuary/embayment. Data was collected as part of a study on the large-scale, long-term trends and causes of lateral saltmarsh change. The data was used in the analysis for Ladd et al. (2019). C. Ladd and M.F. Duggan-Edwards carried out the collection and processing of the saltmarsh extent data. All authors contributed to the interpretation of the data. The work was carried out under the NERC programme - Carbon Storage in Intertidal Environment (C-SIDE), NERC grant reference NE/R010846/1. Full details about this dataset can be found at https://doi.org/10.5285/03b62fd0-41e2-4355-9a06-1697117f0717

  • Erosion risk mapping showing river channel concentrations modelled using SCIMAP for the Yorkshire River Derwent, UK. Scenario mapping has been carried out and the dataset includes the following scenarios to assess variation in model output: 1) traditional land use map; 2) satellite derived land use maps; 3) long term rainfall averages; 4) integrating the artificial drainage network and 5) incorporating future climate change. Full details about this dataset can be found at https://doi.org/10.5285/331dd8ca-a4ff-40e6-b753-1b68468d8996