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

11 record(s)

 

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From 1 - 10 / 11
  • [This dataset is embargoed until December 31, 2020]. Data set presents results from fish biometry field work within four lakes in Japan (Suzuuchi, Funazawa, Kashiramori, Abakuma). Data comprise sampling location, fish species, sex, length, weight (total fish, gonad and liver weight). Fish were sampled during May 2017; target species included crucian carp, common carp and smallmouth bass. For the health and reproductive status assessment, fish of similar weight and total length were collected. Gill nets (20 m length and 21 mm mesh size) were employed to ensure capture of homogeneous groups of mature fish. The work described here was conducted under the TREE project (http://tree.ceh.ac.uk/) funded by the Natural Environment Research Council, Environment Agency and Radioactive Waste Management Ltd. Full details about this dataset can be found at https://doi.org/10.5285/07347484-5d35-4335-bdbe-ac9d7b33c84f

  • 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).

  • [This dataset is embargoed until January 24, 2021]. 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 https://doi.org/10.5285/d01084b2-c3b1-4187-b2e7-b0827c738855

  • 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 https://doi.org/10.5285/6ab0ee70-96f8-41e6-a3e3-6f4c31fa5372

  • 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 https://doi.org/10.5285/22b3d41e-7c35-4c51-9e55-0f47bb845202

  • These data describe the results of a three year (2011-2013) factorial experiment using plant-soil mesocosms testing the effects of biochar on soil biodiversity and soil carbon fluxes. The experimental design comprised three treatments: (1) biochar (absence or presence at 2% w/w); (2) plant type (barley, perennial ryegrass, or unvegetated); and (3) soil texture (sandy clay, sandy silt loam, clay loam). Ecosystem responses measured were net ecosystem exchange of carbon (NEE) & ecosystem respiration (both g CO2 m-2 h-1) and plant biomass (g aboveground and root). Soil biological responses measured were estimates of microbial community structure (fungal-to-bacterial ratio, total phospho-lipid fatty acid (PFLA) nmol g-1 soil) and densities (g-1 soil) of nematode worms and soil microarthropods (Collembola, Acari). The experiment was done at the Centre for Ecology & Hydrology in Penicuik, near Edinburgh in Scotland (UK). Soils used in the experiment were taken from the top 20 cm of the soil profile, from the James Hutton Institute’s Balruderry Farm near Dundee, Scotland, UK (56° 27’ N, 3° 4’ W). This research was funded by a Natural Environment Research Council Open CASE PhD studentship grant (NE/HO18085/1). Full details about this dataset can be found at https://doi.org/10.5285/130369e1-d9c7-436c-bd0c-1ccde4844576

  • [This dataset is embargoed until July 17, 2020]. 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 https://doi.org/10.5285/acf464dc-be75-41b8-9688-f2ba4037ef53

  • 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 https://doi.org/10.5285/1e9993ae-add7-497a-b54b-745b0fc6a7ca

  • 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 https://doi.org/10.5285/1957166d-7523-44f4-b279-aa5314163237

  • [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 https://doi.org/10.5285/71e5b799-fc4d-4a44-8860-a5e358c807fd