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

23 record(s)


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  • This dataset contains Dissolved oxygen concentrations from 2 different locations in Durleigh Reservoir in Somerset, England. Two miniDOT oxygen loggers were fitted with miniWIPER’s and deployed at 2 locations in Durleigh on 30 May 2018. Both sensors were collected on 5 October 2018 and the raw data files are presented in this dataset. 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 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 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).

  • These data were collected from surface sediments (0-5 cm) at sites located along the Athens Riviera and Salamina coastline, Greece. The sediments came from both oil-contaminated (via Agia Zoni II oil-spill) and uncontaminated sites and were first collected between September 2017 and April 2018. For sediments taken at each site, data includes hydrocarbon concentrations (alkanes and Polycyclic Aromatic Hydrocarbons (PAHs)), absolute microbial abundance (by Quantitative Polymerase Chain Reaction (qPCR)) of Bacteria, Archaea, and Fungi, and 16S rRNA amplicon libraries of Bacteria and Archaea. Additionally, nutrient concentrations (ammonia, nitrate, nitrite, silicate, and phosphate) were measured from seawater samples taken at the same sites. This study was conducted by the University of Essex, in partnerships with Archipelagos Institute of Marine Conservation and Cranfield University, and funded by the National Environmental Research Council and EnvEast DTP. 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 is embargoed until May 12, 2021]. The dataset contains the Diameter at Breast Height (DBH) of trees > 10 cm along with botanical identification (family and species). Data were obtained via forest inventories, in annual campaigns (from 2017 to 2019) conducted in May, with exception of the first campaign, which was from June to November, due to the species identification activity. The research was conducted in a field site approximately 80 km north of Manaus, in the state of Amazonas, Brasil. The dendrometer dataset contains the distance in circumference (mm) from a window on the dendrometer band installed in the tree and measured with a digital caliper, where that distance changes when the trunk grows. Dendrometric bands data were collected from April 2018 to January 2020. Full details about this dataset can be found at

  • This dataset contains the dive times (dive start time and dive end time) and depths (maximum depth attained on a dive) of three species of auk from the Isle of May outside the seabird breeding season. Data were collected from 12 Atlantic puffin individuals (Fratercula arctica), 13 common guillemot (Uria aalge) and 13 razorbill (Alca torda). Atlantic puffin data were collected between 19th July 2008 to 3rd December 2008; common guillemot data from 20th July 2005 to 28th January 2006; razorbill data from 1st July 2008 to 24th January 2009. Full details about this dataset can be found at

  • This dataset includes measurements of litter in 20 plots (250 x 10 m each) in the Brazilian Amazon. Study plots were distributed across a gradient of forest disturbance, including: undisturbed primary forests , logged primary forests, logged-and-burned primary forests, and secondary forests. Data were collected from January 2015 until October 2018. In December 2015, during the El Niño-mediated drought, eight of our study plots were affected by understory fires. Full details about this dataset can be found at

  • The dataset contains light penetration through the water column at a Durleigh Reservoir in Somerset, England. HOBO Pendant Temperature/Light 8K Data Loggers (Onset) were positioned at 0.5 m, 1.5 m, and 2.5 m depths on a temperature chain Durleigh. The loggers were deployed between 30 May 2018 and 5 October 2018. Full details about this dataset can be found at