[THIS DATASET HAS BEEN WITHDRAWN]. A spatial indicator of ecological status for valuation of biodiversity across the UK, based on species occurrence records was developed. UK species occurrence data were collated from the Biological Records Centre (BRC). The mean ecological status was calculated across all taxonomic groups for the 2000 to 2013 time period, relative to the species richness maximums from the 1970-1990 time period, showing differences as colours. Full details about this dataset can be found at https://doi.org/10.5285/f30e4fde-634b-402a-b807-b5188d21b998

This dataset contains information about planktonic bacterial quantity at the drinking water pumping stations installed in three different aquifer types of England. The aim of data collection was to assess spatial and seasonal variation of groundwater bacterioplankton distribution and their dependence on organic matter, nutrient concentration and local hydrogeology. Untreated groundwater samples were collected from the intergranular sandstone aquifer of English Midlands and East Midlands, the dual porosity chalk aquifer of South East England and the karstic limestone aquifer of the Cotswolds. For temporal variation in each aquifer, the same aquifers were sampled during pre-recharge season in September-October 2022 and post-recharge season in January-February 2023. Full details about this dataset can be found at https://doi.org/10.5285/b27ce2ee-89ee-428d-bcd5-4abd97141d62

Data comprise plot details and radionuclide activity concentrations for Sr-90, Cs-137, Am-241, Pu-238, Pu-239 and Pu-240 in ‘grassy’ vegetation and soil. These radionuclide activity concentrations have been used to make estimations of total weighted absorbed doses to grassy vegetation, deciduous trees and bacteria; no dose rate estimates for grassy vegetation have been made for those sites where grassy vegetation was absent. Radiation from the 1986 Chernobyl nuclear power plant accident killed coniferous trees in a 4-6 km2 area of forest to the west of the power plant. This area is now known as the 'Red Forest’ and it has subsequently regenerated with understorey vegetation and deciduous trees; it is the most anthropogenically contaminated radioactive ecosystem on Earth. In July 2016 a severe fire burnt (to varying degrees) c. 80 percent of the Red Forest; this presented a unique opportunity to study the impact of radiation on the recovery of forest ecosystems exposed to a secondary stressor (fire). To investigate this, in September 2017 the RED FIRE project set up sixty study plots in the Red Forest (in burnt and unburnt areas) with a further nine plots established close to Buriakivka village (approximately 8 km from the Red Forest). Vegetation samples from each plot were harvested using shears in September 2017. Each sample was sorted into ‘grassy’ and ‘other’ vegetation; these were air-dried (20-25 degrees Celsius) and the grassy vegetation samples homogenised prior to radionuclide analyses. Soil core samples collected in September 2017 were bulked, homogenised and sub-samples taken for determination of pH and percentage moisture determined by oven drying (approximately 60 degrees Celsius) to a constant mass. The remaining soil sample was used for the determination of radionuclide activity concentrations; prior to analyses, these samples were dried at approximately 80 degrees Celsius. This work was funded by the NERC, Grant Ref: NE/P015212/1 (RED FIRE: Radioactive Environment Damaged by fire: a Forest In Recovery) Full details about this dataset can be found at https://doi.org/10.5285/60782622-7bfa-4615-a9e3-0a802a9f4674

The data comprises both compositional data and growth assay data from an experiment of wild bacterial communities in Wytham Woods, Oxford. The communities live in puddles of water in tree-holes formed by the roots of beech trees. We manipulated the pH of tree-holes during the experiment for comparison with control tree-holes that were unmanipulated. Compositional data comprises the frequency of different Amplicon Sequencing Variants and derived measures of species diversity for samples taken over time (up to 12 weeks from the start of the experiment). The growth assay data comprises measurements of growth rates of community samples and isolates back in the laboratory, when grown on beech tea media manipulated to have different pHs. Full details about this dataset can be found at https://doi.org/10.5285/9d64f2bd-2918-416f-b08c-3369edbc1b30

The dataset includes information on antibiotic-resistance and resistance genes in bacteria (Escherichia coli) from humans, poultry and the environment in rural households, poultry farms and urban food markets. The rural households and poultry farms (broiler chickens) were located in Mirzapur, Tangail district; and urban food markets were located in Dhaka city, Bangladesh. Environmental samples were collected from surface water, water supply, wastewater, soil, animal faeces (poultry and cattle) and solid waste between February 2017 and October 2018 . DNA samples from antibiotic-resistant bacteria found in all samples were analysed for quantitative assessment of two resistance genes. Trained staff from the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) undertook sample collection and laboratory analysis. The aim of the study was to assess the prevalence and abundance of antibiotic-resistant bacteria and associated genes among humans, poultry and environmental compartments in Bangladesh. The survey was part of a wider research project, Spatial and Temporal Dynamics of Antimicrobial Resistance Transmission from the Outdoor Environment to Humans in Urban and Rural Bangladesh. The research was funded by NERC/BBSRC/MRC on behalf of the Antimicrobial Resistance Cross-Council Initiative award NE/N019555/1. Full details about this dataset can be found at https://doi.org/10.5285/0239cdaf-deab-4151-8f68-715063eaea45

A spatial indicator of ecological status for valuation of biodiversity across the UK, based on species occurrence records for eleven taxonomic groups (Bees, Birds, Bryophytes, Butterflies, Carabidae, Hoverflies, Isopoda, Ladybirds, Moths, Orthoptera and Vascular plants) was developed. UK species occurrence data were collated from the Biological Records Centre (BRC). The mean ecological status was calculated across all taxonomic groups for the 2000 to 2013 time period, relative to the species richness maximums from the 1970-1990 time period. This version supersedes the dataset "UK ecological status map". Full details about this dataset can be found at https://doi.org/10.5285/58b248a8-6e34-4ffb-ae32-3744566399a2

Data on the carbon and nitrogen cycling in soils from different geologies within the Hampshire Avon catchment, UK. The dataset also includes functional gene data, anion and cation concentrations, methane production and oxidation potential, and nitrification, denitrification and mineralization rates. Data were collected between February 2013 and November 2014. Data were collected to address the hypotheses of how the functional microbial community involved in carbon and nitrogen cycling changed seasonally and with geology. Data were collected as part of the project "The role of lateral exchange in modulating the seaward flux of C, N, P", funded under NERC's Macronutrients Cycles research programme. Full details about this dataset can be found at https://doi.org/10.5285/83f83414-f644-4684-ad5b-e1237fb12fc5

Data on the carbon and nitrogen cycling in sediments from rivers within the Hampshire Avon catchment, UK. The dataset includes functional gene data, anion and cation concentrations, methane production and oxidation potential, carbohydrates concentrations, pigment data, and particle size data. Data were collected between February 2013 and November 2014. Data were collected to address the hypotheses of how the functional microbial community involved in carbon and nitrogen cycling changed seasonally and with geology. Data were collected as part of the project "The role of lateral exchange in modulating the seaward flux of C, N, P", funded under NERC's Macronutrients Cycles research programme. Full details about this dataset can be found at https://doi.org/10.5285/976602b3-a58d-460c-a52d-088d0bb09989

This dataset contains in-stream measurements of sediment porewater nutrients, nitrification rates (and the fraction which is either fully oxidised to nitrate or reduced to N2 gas), and the abundance of microbial 16S rRNA and specific N-cycling genes and transcripts. Sediments were sampled in winter (February 2018) and summer (July 2018), from 12 UK rivers with permeable beds (sand or chalk geology) and a gradient of P concentrations, in the Hampshire Avon catchment, Kent, and Essex. Methods included measurements of porewater nutrients using Skalar SAN++AutoAnalyser, nitrification rates from in-situ ‘push-pull’ injections of 15N-labelled ammonia and -nitrite, and sediment microbial gene and transcript abundance by DNA extraction and qPCR. The work was supported by the Natural Environment Research Council (Grants NE/P01142X/1, NE/P011624/1; A new dynamic for Phosphorus in RIverbed Nitrogen Cycling - PRINCe Full details about this dataset can be found at https://doi.org/10.5285/d432d96c-7aff-45a5-9d4b-37e4065afdd7