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Bangor University

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  • This dataset contains pH, turbidity, conductivity and viral concentration information in river and estuarine water, wastewater, sediment and mussel samples collected in the Conwy River and estuary. The aim of data collection was to monitor wastewater contamination in the freshwater-marine continuum. Samples were collected by trained members of staff from Bangor University at four weekly between March 2016 and August 2017. Treated and untreated wastewater samples were collected at four wastewater treatment plants along the Conwy River. Surface water samples were collected at four sites, sediments at three sites and mussels at two sites. The VIRAQUA project was funded by the Natural Environment Research Council (NERC) under the Environmental Microbiology and Human Health (EMHH) Programme (NE/M010996/1) Full details about this dataset can be found at https://doi.org/10.5285/5d19f6e2-1383-41ed-92d2-138d95bf4c72

  • The dataset contains annual soil greenhouse gas emissions following sheep urine (real and artificial) applications to a semi-improved upland grassland in North Wales, UK, across two seasons (spring and autumn) within the year 2016-2017. Soil greenhouse gas data were collected using a combination of automated chambers and manually sampled chambers, both analysed via gas chromatography. Supporting data include meteorological data, soil chemistry and above ground biomass data collected on a time-series throughout the study, following urine application. The data were used to calculate sheep urine patch nitrous oxide emission factors from an upland environment, to improve estimates of greenhouse gas emissions from extensively grazed agroecosystems. Full details about this dataset can be found at https://doi.org/10.5285/0434c74c-4a8e-45b8-a187-13e422c0ed0f

  • [This nonGeographicDataset is embargoed until December 1, 2020]. This dataset contains the answers gathered from the 806 participants who successfully finished an on-line survey on risk perception of environment-associated risks. The survey was launched on the 15th of February 2018 and ran for five days. The survey contained best worst scaling (BWS) to understand people’s perceptions to certain risks. In this study 16 risks were included in the BWS including four air-, food- and waterborne illnesses and 12 other hazards. The BWS was run in two blocks to consider two factors: first the respondents selected which risk they fear the most/least and in the second block they selected the risk they believed they had the most/least control. The survey also contained a detailed questionnaire on the participants eating habits and health status. Participants were also asked about their knowledge on enteric pathogens and whether they have ever sought or would consider seeking advice on the symptoms. Respondents were also asked whether they have experienced the hazards described in the BWS and whether they have done anything to reduce the risks in their life. The data were collected to gather information on people perceptions on environment-associated risks. This was done to understand the common knowledge on environment-associated pollutants and enlighten issues regarding risk management and mitigation. The data were collected as part of the VIRAQUA project was funded by the Natural Environment Research Council (NERC) under the Environmental Microbiology and Human Health (EMHH) Programme (NE/M010996/1). Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/0869d961-99ca-4946-9192-f35afccdda38

  • This dataset contains pH, turbidity and viral concentration information in untreated and treated wastewater samples at wastewater discharge points and wastewater treatment plants along the Conwy River. The aim of the data collection was to investigate diurnal changes in enteric virus concentrations in wastewater and to investigate any correlation with wastewater pH and turbidity. Untreated wastewater samples were collected at one wastewater treatment plant for two events. Treated wastewater samples were collected at two wastewater discharge points for two and three sampling events, respectively. All the sampling took place between July 2016 and March 2017. During a sampling events, samples were collected every two hours for 72 hours using autosamplers. Samples were collected by trained members of staff from Bangor University and Centre for Ecology & Hydrology (CEH). The data were collected as part of the VIRAQUA project was funded by the Natural Environment Research Council (NERC) under the Environmental Microbiology and Human Health (EMHH) Programme (NE/M010996/1). Full details about this dataset can be found at https://doi.org/10.5285/61640ba9-ffdd-4eda-9e83-dafc01ba8cc7

  • The dataset contains greenhouse gas fluxes (N2O, CO2 and CH4) following artificial and real sheep urine applied to organic soils within the Carneddau mountain range (556 m a.s.l.) in Snowdonia National Park, North Wales, UK. The study was conducted across two contrasting seasons (summer and autumn). Soil greenhouse gas emission data was collected using a combination of automated chambers and manually sampled chambers, with gas samples analysed via gas chromatography. Supporting data include characterisation of the soil properties at each site, meteorological data, soil moisture and soil chemistry on a time-series following treatment application. The data were used to calculate sheep urine patch N2O-N emission factors, to improve estimates of greenhouse gas emissions from sheep urine deposited to extensively grazed montane agroecosystems. Full details about this dataset can be found at https://doi.org/10.5285/01811fce-1e0f-43be-8649-336b5c51d6cf

  • The data consist of general physical, biological and chemical parameters for soil samples taken in the Conwy catchment in North West Wales. Samples were collected between 2013 and 2014 across a land use intensification gradient ranging from semi-natural peatlands, acid grasslands to improved grasslands and arable fields. Soil cores were taken to a depth of 1 metre and divided into 15 centimetre (cm) depth increments. General soil physical and chemical parameters were measured at each depth increment for most of the sites. Biological (root and fine root biomass) parameters were assessed in the topsoil 0-15 cm in 5 cm intervals. Soil parameters were tested across a land use intensification gradient to detect parameters that can predict aboveground biomass production across different land management types. Data were used to enhance the predictions of biomass production in the Joint UK Land Environment Simulator model (JULES). Measurements informed the improvement of the nitrogen cycle component in the model. Measurements were undertaken by trained members of staff from Bangor University, the Centre for Ecology & Hydrology and Exeter University. This data was collected for the NERC project 'The Multi-Scale Response of Water quality, Biodiversity and Carbon Sequestration to Coupled Macronutrient Cycling from Source to Sea' (NE/J011991/1). The project is also referred to as Turf2Surf. Full details about this dataset can be found at https://doi.org/10.5285/6566a706-9c55-4f7f-b33d-27bc29c73274

  • Time series data of carbon release in disintegrations per minute are presented for different nitrogen and phosphorus treatments with a high glucose concentration substrate added as a carbon source to soil samples from six depths (0-15, 15-30, 50-100, 100-150, 150-200 and 250-300 centimetres). Soil cores were collected from a field experiment in the Conwy catchment in July 2016 and returned the laboratories of the School of Environment, Natural Resources and Geography, Bangor University. A high molecular weight substrate was added as a carbon source to the samples and the rate of 14C-substrate mineralization measured. All the work was carried out by trained members of staff from Bangor University and the Centre for Ecology & Hydrology. The measurements were taken to improve understanding of the relationship between microbial activity and soil properties and depth of sampling, under differing nutrient availability. The data were collected for the NERC project 'The Multi-Scale Response of Water quality, Biodiversity and Carbon Sequestration to Coupled Macronutrient Cycling from Source to Sea' (NE/J011991/1). The project is also referred to as Turf2Surf. Full details about this dataset can be found at https://doi.org/10.5285/a15c35d7-0247-4ea3-820b-f6f20cc5ffed

  • Data are presented showing grass productivity as grammes per 100 square centimetres under four different nutrient treatments (water, nitrogen, phosphorus and nitrogen & phosphorus combined). An experimental hillslope in the Conwy catchment was selected in August 2016. Three transects, were identified across the hillslope. Along each transect, a 1 x 1 square metre quadrat was used to delineate randomly selected sampling areas. Within each quadrat 5 individual 10 x 10 x 10 centimetre (cm) swards were collected using a spade and transported to the laboratory in Bangor University for the nutrient addition. Three different harvests at different stages (initial cut, first harvest, second harvest) were conducted in order to measure grass productivity. Harvest included removal of all vegetation within the quadrat down to approximately 1 cm in height. The data were collected to identify the nutrient limitations within the hillslope by trained members of staff from Bangor University and the Centre for Ecology & Hydrology. The data were collected for the NERC project 'The Multi-Scale Response of Water quality, Biodiversity and Carbon Sequestration to Coupled Macronutrient Cycling from Source to Sea' (NE/J011991/1). The project is also referred to as Turf2Surf. Full details about this dataset can be found at https://doi.org/10.5285/6e395915-ab5c-43f4-b4de-c9a3c5c1b956

  • 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

  • The dataset comprises the spider and beetle abundance sampled by suction sampling in each 1metre (m) x 1m quadrat. Sampling was conducted at six salt marsh sites at four spatial scales: 1 m (the minimal sampling unit) nested within a hierarchy of increasing scales of 1-10 m, 10-100 m and 100-1000 m. Three of the sites were in Morecambe Bay, North West England and three of the sites were in Essex, South East England. All samples were taken during the winter and summer of 2013. This data was collected as part of Coastal Biodiversity and Ecosystem Service Sustainability (CBESS): NE/J015644/1. The project was funded with support from the Biodiversity and Ecosystem Service Sustainability (BESS) programme. BESS is a six-year programme (2011-2017) funded by the UK Natural Environment Research Council (NERC) and the Biotechnology and Biological Sciences Research Council (BBSRC) as part of the UK's Living with Environmental Change (LWEC) programme. Full details about this dataset can be found at https://doi.org/10.5285/aff42a31-c314-444e-bdff-2275a8ee93da