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

25 record(s)
 
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  • 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 https://doi.org/10.5285/f5f85f15-8f3a-474c-ae58-7cdeab2a53ca

  • This dataset presents plant percentage cover by species, average plant cover and species richness for sites along the foredune area of sites distributed between Cape Canaveral (Florida) and Tybee Island (Georgia), USA. Plant cover by species was sampled on three occasions using 0.5 x 0.5m quadrats distributed along 3 transects at up to 28 sites. Observations were conducted in February 2018, July 2018, and January 2019. The coastline was impacted by Hurricane Irma in October 2017 and the data were collected to look at plant composition in coastal foredunes undergoing recovery from the hurricane. The data were collected as part of NERC grant NE/R016593/1, Resilience of a coastal ecosystem following hurricane Irma. Full details about this dataset can be found at https://doi.org/10.5285/100af68f-78e2-4b9d-86b9-5777a5ef38fa

  • 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

  • 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 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 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 https://doi.org/10.5285/c2587e20-ba4a-4444-8ce9-ccdec15b0aa3

  • 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 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

  • The dataset contains the leaf area index (LAI) (m2/ m2 ) collected with the LAI-2200 C (plant canopy analyzer), that was computed with 5, 4 and 3 rings using the FV2200 software. Additionally, it has the x and y coordinates (m) of the points collected inside the plots and the time of collection (hour: min: sec). This research was collected in a field site approximately 80 km north of Manaus, in the state of Amazonas, Brasil. The campaigns were carried out in October 2017, March 2018, August 2018 and October 2018. Full details about this dataset can be found at https://doi.org/10.5285/6e70665f-b558-4949-b42a-49fbaec7e7cc

  • The dataset contains the radiocarbon age of soil organic matter fractions collected along grassland-to-forest conversion chronosequences across Scotland. Soil samples were collected in summer 2018. In summer 2019, soil samples were fractionated and the radiocarbon age of bulk soil and soil fraction samples determined by accelerator mass spectrometry. Full details about this dataset can be found at https://doi.org/10.5285/0dd45f6f-0536-4ee3-9932-58bac019d2c6