50 urn:ogc:def:uom:EPSG::9001

17 record(s)


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  • This dataset contains 7-month monitoring of weather conditions at Durleigh Reservoir in Somerset, England, during 2018. A Delta T WS-GP1 weather station was installed ~ 4 m above the surface of the reservoir between 5 April and 5 October 2018. Full details about this dataset can be found at

  • This dataset contains water temperature measurements at 2 different locations in Durleigh Reservoir in Somerset, England. Water temperatures were measured using RBR SoloT thermistors (measured in °C) and HOBO TidbiT v2 loggers (measured in °F). The dataset consists of water temperature measurements from 2 locations at Durleigh reservoir between 22 February 2018 and 5 October 2018. Measurements were taken at 10 minute intervals. Full details about this dataset can be found at

  • This dataset is part of Integrated Hydrometric Units (IHU) of the UK. Hydrometric Areas are used to organise river flow measurement and hydrometric data collection in the UK. Hydrometric Areas are either integral river catchments having one or more outlets to the sea or tidal estuary, or they may include several contiguous river catchments having topographical similarity but separate tidal outlets. In mainland Britain they are numbered from 1 to 97 in clockwise order around the coast commencing in north east Scotland. The larger islands and groups of islands are numbered from 100-108. Ireland has a unified numbering system from 1 to 40 commencing with the River Foyle catchment and circulating clockwise; not all Irish Hydrometric Areas, however, have an outlet to the coast. Only those Hydrometric Areas covering Great Britain and Northern Ireland are included in this dataset. The boundaries between hydrometric areas correspond to catchment boundaries as digitally-derived from CEH Integrated Hydrological Digital Terrain Model (IHDTM) using a catchment definition program. It should be noticed that the Northern Ireland data are clipped to its political boundary so not every Hydrometric Area in this region is completely represented. The naming and numbering convention for the hydrometric areas in Great Britain was originally defined by the Inland Water Survey Committee (and first published in the Surface Water Year-Book of Great Britain 1936-37). For Northern Ireland the system was developed by a multi-agency working group in the 1970s (and first published in Surface Water: United Kingdom 1971-73. Note that full citations of those two publications are provided as additional information source. This dataset represent the same entities as the IHU Hydrometric Areas of the UK without Coastline, however, the outer boundaries of the units follow coastline published by the Ordnance Survey (Meridian 2), rather than the boundaries of the CEH Integrated Hydrological Digital Terrain Model. Full details about this dataset can be found at

  • This dataset consists of tick sampling and microclimate data from Exmoor, Richmond and New Forest study sites; as well as ARCGIS risk maps that model tick abundance driven by climate surfaces and host abundance. Tick sampling data (91 files, each representing a day of sampling) indicate tick abundance (distinguishing larvae, nymphs, adult males and adult females), vegetation height, soil moisture, temperature and relative humidity. Static risk map files indicate modeled tick abundance: 251 landcover files for the three sites, as well as 36 ArcView map files. The study is part of the NERC Rural Economy and Land Use (RELU) programme. Many people take pleasure from activities in forests and wild lands in the UK and others are being encouraged to participate. Unfortunately, there are risks and one of the most insidious is the possibility (albeit tiny) of acquiring a disease from wild animals; for example, ticks can be vectors of the bacterial infection leading to Lyme Disease. Both diagnosis and treatment can be problematic so prevention of acquiring such disease is highly desirable. Surprisingly little is known about how best to warn countryside users about the potential for disease without scaring them away or spoiling their enjoyment. Answering such questions was the goal of this project, and required the integration of a diverse set of scientific skills, and an understanding of the views of those who manage countryside, those who have contracted zoonotic diseases and those who access the land. This project combined knowledge from three strands of work, namely risk assessment, risk perception and communication, and scenario analysis. The study sites were selected to provide a range of environmental conditions and countryside use. Peri-urban parkland, accessible lowland forest and heath and remote upland forest were chosen as represented by Richmond Park on the fringe of Greater London, the New Forest in Southern England, and Exmoor in South West England. The following additional data from this same research project are available at the UK Data Archive under study number 6892 (see online resources): Lyme disease risk perception data resulting from tick imagery vignette experiments, Lyme disease patient interviews and surveys, residents and countryside staff focus groups, forest manager interviews, and multiple scoring procedures of animal social representation; as well as Lyme and tick risk communication data resulting from interviews with organisations and content analysis of risk warning information leaflets, Further documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see online resources).

  • The dataset contains 5-day of water velocities at Durleigh Reservoir in Somerset, England. A Nortek Vector acoustic doppler velocimeter (ADV) was used to collect the dataset. The ADV was deployed between 20 August 2018 (15:00) and 24 August 2018 (09:15), located ~ 30 m north of the surface mixers in Durleigh reservoir. The surface mixers were operating when the ADV was deployed and were switched off between 07:17 on 22 August and 16:42 on 23 August 2018. Full details about this dataset can be found at

  • This dataset contains water chemistry and phytoplankton cell counts collected from 3 different depths at 3 different sites in Durleigh Reservoir in Somerset, England, during 2018. Water samples were collected on 22 Feb, 5 Apr, 20 Apr, 30 May, 13 Jun, 27 Jun, 9 Jul, 24 Jul, 20 Aug, 21 Aug, 22 Aug, 23 Aug, 24 Aug, and 5 Oct 2018. The data available to download includes phytoplankton cell counts (cells/ml), turbidity (NTU), pH, Ammonia (mg/l), total oxidised nitrogen (mg/l) nitrite (mg/l), nitrate (mg/l), ammonium (mg/l), orthophosphate (mg/l), silica (mg/l), Potassium (mg/l), Calcium (mg/l), Geosmin (ng/l), 2-MIB (ng/l), total and soluble manganese, iron, copper, magnesium, zinc, and aluminium (all: mg/l). Full details about this dataset can be found at

  • [This dataset is embargoed until December 31, 2020]. This dataset contains time series observations of surface-atmosphere exchanges of net ecosystem carbon dioxide exchange (NEE), sensible heat (H) and latent heat (LE), and momentum (τ) measured at a at a Miscanthus x. giganteus Greef et Deu (hereafter Miscanthus) plantation in Lincolnshire, UK. Turbulent flux densities were monitored using the micrometeorological eddy covariance (EC) technique between 4 July 2013 and 25 November 2017. The dataset includes ancillary weather and soil physics observations, as well as variables describing atmospheric turbulence and the quality of the turbulent flux observations. 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

  • This dataset consists of invertebrate abundance data and associated ecosystem measurements (Including leaf litter depth and mass, seedlings, soil moisture and nutrients, and rainfall) measured within an area of lowland, old growth dipterocarp rainforest in the Maliau Basin Conservation Area, Sabah, Malaysia between 2015 and 2016. Data were collected during a collaborative project which was included in the NERC Human-modified tropical forest (HMTF) programme. Full details about this dataset can be found at

  • Data comprise radionuclide deposition, radioactivity dose measurements, radioactive particle activity and physical characteristic information from soil samples collected within and around the Chernobyl Exclusion Zone (CEZ) following the Chernobyl nuclear accident in 1986. Data include radiocaesium, radiostrontium and soil chemistry parameters from soils collected in 1997, plutonium isotope measurements in soil samples and soil layers collected in 2000 and 2001, 'Hot particle' dataset presenting radionuclide activity and some physical characteristics of 'hot particles' extracted from soils collected in the Ukraine and Poland between 1995 and 1997; and Ivankov region data (radionuclide activity concentrations and natural background dose measurements) from a survey of the Ivankov region, immediately to the south of the CEZ conducted in 2014. Funding for preparing this data set was provided by the EU COMET project ( and TREE ( project funded by the NERC, Environment Agency and Radioactive Waste Management Ltd. under the RATE programme. Full details about this dataset can be found at

  • This dataset contains a list of all known birds, bryophytes, fungi, invertebrates, lichens and mammals that use oak (Quercus petraea and Quercus robur) in the UK. In total 2300 species are listed in the dataset. For each species we provide a level of association with oak, ranging from obligate (only found on oak) to cosmopolitan (found on a wide range of other tree species). Data on the ecology of each oak associated species is provided: part of tree used, use made of tree (feeding, roosting, breeding), age of tree, woodland type, tree form (coppice, pollarded, or natural growth form) and season when the tree was used. Data on use or otherwise by each of the 2300 species of 30 other alternative tree species (Acer campestre, Acer pseudoplatanus, Alnus glutinosa, Betula pendula, Betula pubescens, Carpinus betulus, Castanea sativa, Fagus sylvatica, Fraxinus excelsior, Ilex aquifolium, Larix spp, Malus sylvestris, Picea abies, Pinus nigra ssp. laricio, Pinus sylvestris, Populus tremula, Prunus avium, Pseudotsuga menziesii, Quercus cerris, Quercus rubra, Sorbus aria, Sorbus aucuparia, Sorbus torminalis, Taxus baccata, Thuja plicata, Tilia cordata, Tilia platyphyllos, Tilia vulgaris, Tsuga heterophylla, Ulmus glabra) was also collated. A complete list of data sources is provided. Full details about this dataset can be found at