[This dataset is embargoed until October 1, 2026]. This dataset reports concentrations of six antibiotics—oxytetracycline, ciprofloxacin, enrofloxacin, sulfamethazine, ofloxacin, and norfloxacin—measured in surface water and wastewater from two catchments in India: Dera Bassi (Punjab) and Bhiwadi (Rajasthan). Samples were collected at four time points between May 2022 and June 2023 from the River Ghaggar and wastewater effluent sites. Full details about this dataset can be found at https://doi.org/10.5285/1a4588b8-7145-49ce-8bd5-0895d385932d

Bat species data from the UK Environmental Change Network (ECN) terrestrial sites. The count of individual species is recorded. These data are collected while walking a defined transect using a bat detector at ECN's terrestrial sites using a standard protocol. They represent continuous records (the transects are walked four times each year) from 1993 to 2015. ECN is the UK's long-term environmental monitoring programme. It is a multi-agency programme sponsored by a consortium of fourteen government departments and agencies. These organisations contribute to the programme through funding either site monitoring and/or network co-ordination activities. These organisations are: Agri-Food and Biosciences Institute, Biotechnology and Biological Sciences Research Council, Cyfoeth Naturiol Cymru - Natural Resources Wales, Defence Science & Technology Laboratory, Department for Environment, Food and Rural Affairs, Environment Agency, Forestry Commission, Llywodraeth Cymru - Welsh Government, Natural England, Natural Environment Research Council, Northern Ireland Environment Agency, Scottish Environment Protection Agency, Scottish Government and Scottish Natural Heritage. Full details about this dataset can be found at https://doi.org/10.5285/2588ee91-6cbd-4888-86fc-81858d1bf085

This dataset consists of a range of ecological measurements collected from a set of arable fields, each sown with a combination of genetically modified and conventional maize crops. Measurements include species counts in the following areas: weed seedbank, vegetation in the crop, field edge vegetation, invertebrates. The data were collected as part of the Farm Scale Evaluations (FSEs), a four-year programme of research by independent researchers aimed at studying the effect that the management practices associated with Genetically Modified Herbicide Tolerant (GMHT) crops might have on farmland wildlife, when compared with weed control used with non-GM crops. Data were collected by a consortium of: the Institute of Terrestrial Ecology (now the Centre for Ecology &Hydrology), the Institute of Arable Crops Research (now Rothamsted Research) and the Scottish Crop Research Institute (now the James Hutton Institute). Data were collected for four crops overall (Beet, Maize, Spring-sown Oilseed Rape and Winter-sown oilseed Rape). Full details about this dataset can be found at https://doi.org/10.5285/ca6752ed-3a22-4790-a86d-afadaedda082

Data are presented from an ozone exposure experiment performed on five African crops. The crops (Beans, cowpea, finger millet, pearl millet and wheat) were exposed to three different levels of ozone in the UK CEH Bangor solardomes. Wheat was grown at UK ambient temperature, whereas the solardomes were heated for the other crops to better mimic tropical conditions. The experiment ran from May 2017 to September 2017. The crop plants were grown from seed in pots in solardomes. The aim of the experiment was to investigate the impact of ozone exposure on the crop yield and plant health. The dataset comprises of manually collected data on plant physiology, biomass and yield. In addition the automatically logged data of ozone concentration and meteorological variables in the solardomes are presented. Plant physiology data is stomatal conductance of individual leaves, measured on an ad-hoc basis. The dataset includes the associated data measured by the equipment (relative humidity, leaf temperature, photosynthetically active radiation). Soil moisture of the pots was always measured at the same time, and chlorophyll content of the measured leaf was usually, but not always, determined at the same time. Yield was determined for each plant, in addition to yield-related metrics including mass per bean and 100 grain weight. For finger millet and pearl millet yield is expressed as weight of seed heads and number of seed heads, rather than explicitly as seed weight. The ozone and meteorological dataset is complete, but with some gap-filling for short periods when the computer was not logging data. The work was carried out as part of the NERC funded SUNRISE project (NE/R000131/1). Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/f38beff1-993f-4785-8a97-1de21e3e19c0

This dataset contains information on the soil particle size distribution, electrical conductivity, total carbon, and inorganic carbon in the form of CaCO3 for the topsoil (0-15cm) from the Countryside Survey monitoring programme spanning the years 2018 to 2023. This period includes the five years, along with the pilot year, required to finalize the sampling across the geography of Great Britain. Additionally, it includes the aggregate size distribution and stability for the CS2019. UKCEH Countryside Survey is the longest integrated national monitoring programme of the countryside for Great Britain, which began in 1978. The results provide a unique insight into how our plants, soil, woodlands and small water bodies have changed over time. Full details about this dataset can be found at https://doi.org/10.5285/6893097f-f504-4b77-96c8-8daa5da6a09d

Estimates of annual loads of phosphorus, sediment, nitrogen and faecal coliform from non-agricultural sources to rivers in Scotland, reported at Water Framework Directive (WFD) catchment scale. The sources of pollutants include: urban, woodland, montane areas, river bank erosion, septic tanks and sewage treatment works. Loads are estimated based upon available data (e.g. septic tank licences) and modelling (bank erosion). The values specify phosphorous, nitrogen or sediment losses in kilograms per year and faecal coliform in 10^6 colony forming units (cfu) per year. Full details about this dataset can be found at https://doi.org/10.5285/eb73ca31-7eb9-479c-96be-6063e29c8a7f

This dataset contains palaeolimnological data from sediment cores taken from five Arctic lakes. Two lakes located in Alaska were cored in July 2013, one lake located in Greenland was cored in April 2013, and two lakes located in Norway were cored in March 2014. The data includes macrofossil, chironomids and Cladocera analysis at 2 cm resolution; and loss on ignition, diatoms, biogenic silica, nitrogen and carbon isotopes, algal photosynthetic pigments and pollen analyses at 1 cm resolution. All cores were subject to X-Ray Fluorescence scanning analysis at 200 or 400 micrometer resolution before subsampling. The data were collected as part of the Lakes and Arctic Carbon project, funded under NERC's Arctic Research Programme. Full details about this dataset can be found at https://doi.org/10.5285/e48aa7ca-e8af-482a-bebd-45291de9584f

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

This data describes the recovering and isolation processes of Bacteroides spp. strains from human and cattle faecal sources from rural areas in Siaya County (Kenya), and occurred between 7th and 28th of June 2018. The data also includes the detection of bacteriophages (infecting these Bacteroides spp. host strains) in conjunction with traditional faecal indicator organisms in water sources from Kisumu and Siaya County (Kenya) occurring between June 18th 2018 and June 13th 2019. Exact location (coordinates) of the sample points are also described in the data set. A microbiological technique using Bile Esculin Bacteroides (BBE) agar was used for the recovering and isolation processes of Bacteroides spp. strains. Standard ISO (7899-2, 9308-1, 10705-2 and 10705-4) techniques, such as membrane filtration and the double-agar-layer methods, were used for the detection of bacteriophages and traditional faecal indicator organisms. The purpose of data collection was to develop new markers that could identify cattle and/or human sources of faecal contamination, which could be used as part of a Microbial Source Tracking (MST) tool box. Technicians and researchers from the University of Brighton (UK), University of Southampton (UK), from the Victoria Institute for Research on Environment and Development (VIRED) (KE) and from the Kenya Medical Research Institute (KEMRI) (KE) were responsible for the collection and interpretation of data. Full details about this dataset can be found at https://doi.org/10.5285/02c8a6b0-e59e-4278-b9a2-9958cd5a2c3c

The data comprise water quality measurements taken from streams and rivers in the Conwy catchment and its estuary from March 2013 to October 2016. Depending on water type and sampling location the data consist of concentrations of major cations and anions, pH, conductivity, alkalinity, suspended material and coliforms. Samples were collected manually or by automatic sampler. Analysis was carried out at the Centre for Ecology & Hydrology (CEH) Bangor, CEH Lancaster and Bangor University laboratories. The data were collected provide information on the relationship between stream water quality, primarily macronutrient concentrations, and catchment and hydrological characteristics. The data are used to drive a catchment scale water quality model, and to investigate nutrient ratios and limitation with respect to land cover and management. All sampling and analysis was carried out by trained members of staff from the Centre for Ecology & Hydrology and Bangor University. This data was assembled under the NERC project 'The Multi-Scale Response of Water quality, Biodiversity and Carbon Sequestration to Coupled Macronutrient Cycling from Source to Sea' (Turf2Surf). Full details about this dataset can be found at https://doi.org/10.5285/32392c33-8cbe-434a-a582-ab8425a5062c