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Environment

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  • [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

  • 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 following dataset contains information on saplings of woody plant species in invaded subtropical mountain forests (Yungas) over three years. The forests were located in the Horco Molle Experimental Reserve and Parque Sierra de San Javier, Tucumán, Argentina. The data was collected as part of an experiment to investigate the impact of management control on the invasion of non-native species such as Ligustrum lucidum, and other less abundant non-native species, on the dynamics of the woody community. The experiment was conducted between June 2020 and November 2023. This work was carried out as part of NERC grant NE/S011641/1 “Optimising the long-term management of invasive species affecting biodiversity and the rural economy using adaptive management”. Full details about this dataset can be found at https://doi.org/10.5285/4311fa93-fdcc-43bd-bb2e-185118c06ed7

  • This dataset describes hourly time series of discharge and suspended sediment flux at four sites in the Vietnamese Mekong Delta (Chau Doc, Tan Chau, Can Tho and My Thaun) for the period 2005 – 2015. This data was calculated from historic Acoustic Doppler Current Profiler (aDcp)data obtained as part of routine flood monitoring conducted by the Vietnamese Hydrological Agency. The data were collated by the authors. The data were processed to back out sediment fluxes through the delta through calibration of the acoustic backscatter signal to suspended sediment concentrations collected in Chau Doc (May 2017) and Can Tho (September 2017). For each aDcp instrument acoustic backscatter signal was calibrated to observed suspended sediment concentrations (SSCs). These concentrations values were then matched to measured acoustic backscatter values (dB) from the depth at which each sample was taken to generate power law calibration curves. To generate daily fluxes, the point specific ADCP fluxes were used to generate sediment ratings curves between sediment flux (kg/s) and discharge (m3/s). These ratings curves were then propagated over recorded daily discharge values measured by the Vietnamese hydrological agency to provide daily fluxes over the period of record. The work was funded through NERC grant reference NE/P008100/1 - Deciphering the dominant drivers of contemporary relative sea-level change: Analysing sediment deposition and subsidence in a vulnerable mega-delta. Full details about this dataset can be found at https://doi.org/10.5285/ac5b28ca-e087-4aec-974a-5a9f84b06595

  • Audible and ultrasound recordings in Panama for the purpose of monitoring bird and bat calls. The recordings were taken across 4 sites in Barro Colorado Island and the Gamboa forest region around sunrise and sunset hours between the 21st and the 26th of January 2023. Audible recordings were made using SM4 song meter, whilst ultrasound was recorded using a SM4BAT song meter. The Parties involved in data collection are listed in the author section. No data are missing. Full details about this dataset can be found at https://doi.org/10.5285/eeb7c6dc-2ad8-4375-ad86-523a6e570170

  • The dataset contains borehole groundwater levels and physico-chemical parameters for the period May 2017 to June 2018 including; (1) near-monthly measurements of water table depth, groundwater temperature, pH, electrical conductivity and total dissolved solids obtained from manual sampling of 22 boreholes; and (2) higher temporal resolution (5-min time-step) timeseries of water table depth, groundwater temperature and electrical conductivity obtained from automatic dataloggers in 3 of the abovementioned boreholes. Full details about this dataset can be found at https://doi.org/10.5285/40a80d95-5a8a-4586-aa24-d6c87f9968b6

  • The dataset provides transcripts from focus groups in Salima, Mangochi and Zomba (Malawi). The focus groups' discussions focused on important monthly agricultural activities in association with the climate services and extreme weather events. This outlined how climatic factors affected agricultural decision-making. The data were produced as part of NERC Program Science for Humanitarian Emergencies and Resilience (SHEAR). Grant reference - Improving Preparedness to Agro-Climatic Extremes in Malawi (IPACE-Malawi). Full details about this dataset can be found at https://doi.org/10.5285/199b0046-79a3-4e74-8152-17f10c376671

  • This dataset contains data recording kinetics of the spherulite growth in poly(hydroxybuterate)-based systems with various amounts of copolymer and additive (plasticiser and/or filler). The experiments were performed using polarised light microscopy. The experiments were conducted at the University of Strathclyde. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/1c2fe14e-0aa4-4f4a-b827-57b96deeda0d

  • This dataset presents predicted soil erosion rates (t ha-1 yr-1) and its impact on topsoils, including lifespans (yr) assuming erosion rates remain constant and there is no replacement of soil; flux rates of soil organic carbon via erosion (t SOC ha-1 yr-1); flux rates of soil nitrogen via erosion (t N ha-1 yr-1); and flux rates of soil phosphorous via erosion (t P ha-1 yr-1). The dataset comes in the form of three multi-band raster GeoTiff files, structured as follows: LC16_Results.tif: Model predictions generated under the 2016 Copernicus Land Cover Map at 30-metre resolution (five bands) Mitigation_scenarios.tif: Predicted reductions in erosion rates in the event of implementing mitigation scenarios described in sixteen different scenarios (sixteen bands). PNV_Results.tif: Same structure as LC16_Results.tif, but stores predictions generated under the Potential Natural Vegetation cover map for East Africa at 30-metre resolution (five bands) Full details about this dataset can be found at https://doi.org/10.5285/86d07d98-2956-4395-8b02-29dd5d98e6be

  • This datasets contains Electrical Resistivity Tomography surveys taken in the Makutapora Basin, Central Tanzania, using an AGI SuperSting R8 (STING) resistivity meter. Survey geometry, parameters and coordinates are also included. Full details about this dataset can be found at https://doi.org/10.5285/1998da32-a978-41a4-8a66-81df1e625cca