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The dataset contains carbon dioxide and methane emissions, as well as resorufin production (as a proxy for microbial metabolic activity) and dissolved oxygen concentrations, resulting from laboratory incubation experiments of streambed sediments. The sediments were collected from the upper 10 centimetres of the streambed in the River Tern and the River Lambourn in September 2015, with three samples collected from each river. These samples were collected from three areas: silt-dominated sediment underneath vegetation (fine), sand-dominated sediment from unvegetated zones (medium) and gravel-dominated sediment from unvegetated zones (coarse). The sediment was used in laboratory incubation experiments to determine the effect of temperature, organic matter content, substrate type and geological origin on streambed microbial metabolic activity, and carbon dioxide and methane production. The work was carried out as part of a Natural Environment Research Council (NERC) funded PhD (NERC award number 1602135). The work was also part funded through the Seventh Framework Programme (EU grant number 607150). Full details about this dataset can be found at https://doi.org/10.5285/3a0a5132-797c-4ed5-98b9-1c17eaa2f2b7
The meteorological data describes the air and soil temperatures, net radiation balance, down-welling photosynthetically active radiation, wind speed, wind direction and the vapour pressure deficit. Data collection was carried out at Cartmel Sands marsh from the 31st of May 2013 till the 26th of January 2015. The Cartmel Sands site is in Morecambe, North West England, and the meteorological tower was situated in the middle of the marsh. 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/b1e2fb9c-8c34-490a-b6ae-2fdf6b460726
[THIS DATASET HAS BEEN WITHDRAWN]. 1 km gridded estimates of daily and monthly rainfall for Great-Britain and Northern Ireland (together with approximately 3000 km2 of catchment in the Republic of Ireland) from 1890 to 2014. The rainfall estimates are derived from the Met Office national database of observed precipitation. To derive the estimates, monthly and daily (when complete month available) precipitation totals from the UK rain gauge network are used. The natural neighbour interpolation methodology, including a normalisation step based on average annual rainfall, was used to generate the daily and monthly estimates. The estimated rainfall on a given day refers to the rainfall amount precipitated in 24 hours between 9am on that day until 9am on the following day. The CEH-GEAR dataset has been developed according to the guidance provided in BS 7843-4:2012. Full details about this dataset can be found at https://doi.org/10.5285/f2856ee8-da6e-4b67-bedb-590520c77b3c
This dataset includes the transcript of discussion group activities on Human Wildlife conflict, conducted with ten rural communities in Marrupa District, Niassa (Northern Mozambique). It also comprises the results of semi-structured interviews conducted individually in three of the ten selected communities. The ten villages were selected from a forest cover gradient running from villages with a higher forest cover to those within degraded forest areas and consequently low cover. The villages had similar infrastructure, soils, rainfall, and vegetation types. The dataset contains information on the occurrence of conflict with both vertebrate and invertebrate wild species, mitigation strategies, conflict seasonality and trends, but also its impact on agricultural production and livestock rearing. The discussion groups were conducted with six to ten people and the presence of the leader of each village, between May and July 2015. Data were collected as part of a project funded under the Ecosystem Services for Poverty Alleviation (ESPA) programme. Full details about this dataset can be found at https://doi.org/10.5285/7bd2e230-c219-4017-9914-b5cfd83a4eae
[THIS DATASET HAS BEEN WITHDRAWN]. The European Monitoring and Evaluation Program Unified Model for the UK (EMEP4UK) simulates the year 2001 to 2014 UK daily average atmospheric composition at a horizontal resolution of 5 x 5 km2. The species included in this dataset are surface daily average concentrations of: nitric oxide (NO), nitrogen dioxide (NO2), particulate matter (PM10 and PM2.5), ammonia (NH3), nitric acid (HNO3), sulphur dioxide (SO2), ammonium (NH4+), nitrate (NO3-), sulphate (SO42-), PM2.5 organic matter, and ground level ozone (O3). The EMEP4UK model framework consists of an atmospheric chemistry transport model (ACTM) which simulates hourly to annual average atmospheric composition and deposition of various pollutants and the weather research and forecast model (WRF). Pollutants simulated include fine particulate matter (PM10, PM2.5), secondary organic aerosols (SOA), elemental carbon (EC), secondary inorganic aerosols (SIA), sulphur dioxide (SO2), ammonia (NH3), nitrogen oxides (NOx), and ground level ozone (O3). Dry and wet deposition of pollutants are also generated by the EMEP4UK. WRF is used to calculate the required meteorological input data for the ACTM. The version of EMEP4UK used to model the 2001-2014 dataset available here is based on the EMEP Meteorological Synthesizing Centre West (MSC-W) model version rv4.4. Notes: Only the simulations for the years between 2002-2012 include data for from forest fire. The emissions used for simulating the years 2013 and 2014 are the same as the year 2012 (updated date will be made available as soon as 2013 and 2014 national emission inventory data have been processed). The calculated year 2001-2012 use a different version of the WRF model, moreover for the year 2013 and 2014 the WRF model setup was changed as the specific Humidity is no longer nudged with re-analysis in the WRF simulation.
This dataset contains daily automated weather station (AWS) data from the Climoor field site in Clocaenog forest, North East Wales. The data are air temperature (mean, minimum and maximum), rainfall, net radiation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction. The dataset has been quality checked, and incorrect or missing values removed, data has not been infilled. Data runs from 12/6/1999 until 30/06/2015, no data was collected March 2006 and June 2008. Air temperature, rainfall and wind speed and direction were recorded since June 1999. Measurements of relative humidity, air pressure, net and solar radiation and PAR started in June 2008. Since June 2008, data are recorded in minute intervals, averaged to hourly, then to daily means that are reported here. The Climoor field experiment intends to answer questions regarding the effects of warming and drought on ecosystem processes. The reported data are collected to monitor site specific environmental conditions and their development with time. These data are important to interpret results that are collected from the climate change manipulations imposed in the field. Full details about this dataset can be found at https://doi.org/10.5285/7f2a4935-a9e8-47dc-b126-93d9e19496bd
The dataset contains instantaneous fluxes of carbon dioxide, methane and nitrous oxide from intact lysimeters in agricultural grasslands in the Hampshire Avon catchment (UK). Manipulations of soil temperature, soil water saturation, additions of nitrogen, phosphorus and of nitrogen and phosphorus were made at three orthogonal experiments in three sub-catchments of contrasting geology (chalk, clay and greensand). Fluxes of carbon dioxide were directly measured continuously during 2014 and 2015 using automated chamber approach, and fluxes of methane and nitrous oxide were measured in 'campaign' mode. Flux measurements consisted of chamber closure for 180 seconds, except when in 'campaign' mode when measurement periods were extended to 300 seconds. Full details about this dataset can be found at https://doi.org/10.5285/8031c2c1-7032-4958-b314-7664d747b988
These data show the presence/absence and identification of Cryptosporidium species from the results of a molecular survey of various upland river biota aquatic invertebrates, biofilms, mammal droppings and fish guts, gills and faeces. Samples were collected from various upland influenced sites from around Wales between 2012 and 2015 and were collected. Additionally, otter samples from UK-wide project were also tested. Sample collection was primarily undertaken by DURESS researchers at Cardiff University. Sample testing and analysis was performed at the Cryptosporidium Reference Unit, Public Health Wales Microbiology, Swansea. DNA was extracted using a commercially available kit (Gentra PureGene), Qiagen stool and tissue DNA kits for the fish and mammal samples. These data were collected to provide new information required for the production of a catchment pathogen model to inform ecosystems (dis)services analysis of land use change scenarios for the Diversity in Upland Rivers for Ecosystem Service Sustainability (DURESS) project, part of the NERC Biodiversity and Ecosystem Service Sustainability (BESS) BESS Programme. Full details about this dataset can be found at https://doi.org/10.5285/84242834-dc78-49a6-83cb-951edac65d18
The dataset is a subset of the BGS borehole material database, created on August 1st 2015 covering only the Bowland-Hodder geological unit (as defined and mapped by Andrews et al., 2013). It shows all boreholes (name, location and registration details) for which BGS hold borehole material (drillcore, cuttings, samples and their depth ranges). This data will add value to existing NERC (Natural Environment Research Council) data by allowing a simple route for users to identify borehole material from the Bowland-Hodder interval.
This data set provides a spatial stratification of forest cover into discrete vegetation classes according to the High Carbon Stock (HCS) Approach. The data set covers the Stability of Altered Forest Ecosystems (SAFE) project site located in Sabah, Malaysian Borneo. Data were collected in 2015 during a 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/10.5285/81cad1ef-b5cc-4592-a71f-204a5d04b700