In this mesocosm study, three types of wet wipes (plastic containing, and home and commercially compostable) colonised with E. coli were buried in beach sand and their degradation, tensile strength, and concentration of E. coli was quantified over 15 weeks. Wipes were firstly passed through a series of treatments to simulate their journey from the bathroom to the beach. Water characteristics (pH, salinity) of these water types were measured. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/19a8083b-afa4-40b9-91bf-7a529eea870d

This dataset contains information on the volume of nectar consumed, metabolic rate and activity of bumblebees that were exposed to environmentally relevant dose rates of ionising radiation at the University of Stirling. Data is for two connected experiments collected via direct observation in a laboratory setting. The first experiment investigates variables during and after 10-days of radiation exposure and the second investigates these variables under a dose rate gradient. Funding for this work was via the TREE project funded by the NERC, Environment Agency and Radioactive Waste Management Ltd. under the RATE programme. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/0da32d7f-eea1-4200-8fde-3a32d0d9ed05

This dataset contains the carbon and nitrogen content of soil organic matter fractions collected along grassland-to-forest conversion chronosequences. Four chronosequences of grassland-to-forest conversion were used across Scotland, from Alyth to Craik. Soil samples were collected in summer 2018. Soil samples were collected using soil corers. In 2020, soil samples were fractionated in the laboratory, and the elemental composition of bulk soil and soil fraction samples was determined. The goal of the study was to determine the changes in the quantity of soil organic carbon and nitrogen, and the form in which these carbon and nitrogen are stored. Full details about this dataset can be found at https://doi.org/10.5285/ad3d4c0a-66d5-4367-a41c-5f3cdff752f7

This dataset contains information about water quality based on faecal indicators at eighteen lakes in each of three lake districts: - Greater Glasgow conurbation, Scotland - Cumbria, NW England - Norfolk, E England. Lakes were sampled once in each of three seasons (spring, summer and autumn) in either 2016 (Norfolk) or 2017 (Cumbria and Greater Glasgow) with faecal indicators being quantified at three discrete sampling stations in each lake (>50m apart) and at three points at each station (i.e. nine samples per lake per sampling date). Faecal indicators were quantified based on standard dilution, membrane filtration and incubation, followed by colony counting. The data were collected to investigate the fine scale connectivity between Faecal Indicator Organisms (FIO) densities within water bodies and diffuse and point source inputs from the adjacent catchment and from biological vectors. They also provide an indication of the relative sources of variation in reported concentrations that is relevant for environmental regulatory purposes. The work was supported by the Natural Environment Research Council grant NE/N006437/1 (Hydroscape: connectivity x stressor interactions in freshwater habitats). Full details about this dataset can be found at https://doi.org/10.5285/5f988cd4-479d-4e35-8835-42f80ebc1698

This dataset contains information about water quality based on faecal indicators at 15 lakes in the Greater Glasgow conurbation, Scotland. Lakes were sampled in winter (2016/17) and summer (2017) with faecal indicators being quantified at high spatial resolution (up to 60 points per lake depending on water body size) in sediment and water from each lake. Faecal indicators were quantified based on standard dilution, membrane filtration and incubation for water, and incubation in bacteria-specific broth, followed by plating and incubation for sediment extracts. Contextual information about water quality, water bird densities, and land cover in different buffer sizes is also provided for each lake. The data were collected to investigate how connectivity and stressors interact to determine biodiversity and ecosystem function in freshwaters. The work was supported by the Natural Environment Research Council grant NE/N006437/1 (Hydroscape: connectivity x stressor interactions in freshwater habitats) Full details about this dataset can be found at https://doi.org/10.5285/34df30f2-3163-4c11-8743-3732e49220fb

[This dataset is embargoed until January 2, 2025]. This dataset contains characterisation data, thermotolerance data, anti-fungal drug resistance data and virulence data of Candida isolates from different types of plastic pollution. Samples were collected from marine, estuarine and freshwater environments, and screened for pathogenic species of Candida. These Candida isolates were subsequently assessed for their thermotolerance, anti-fungal drug resistance, and their pathogenicity in a Galleria model of infection. Data were collected as part of grants NE/V005847/1, Sustainable Plastic Attitudes to benefit Communities and their Environments (SPACES), and NE/S005196/1, Microbial hitch-hikers of marine plastics: the survival, persistence & ecology of microbial communities in the 'Plastisphere'. Full details about this dataset can be found at https://doi.org/10.5285/4477f77c-c1c9-44e4-baeb-3353954c8355

This resource is the raw data from a topographic survey of the Sourhope field experiment site, conducted by the Department of Environmental Science, University of Stirling in April and May 2000. The data are available to match to other data sets from the field site, or to analyse in more detail. The data were collected as part of the NERC Soil Biodiversity Thematic Programme, centred upon the intensive study of a large field experiment located at the Macaulay Land Use Research Institute (now the James Hutton Institute)'s farm at Sourhope in the Scottish Borders (Grid reference: NT8545019630). During this time, the site was monitored to assess changes in above ground biomass production (productivity), species composition and relative abundance (diversity). Full details about this dataset can be found at https://doi.org/10.5285/d5b78255-b834-485e-8aa4-590ddf604bfd

This dataset comprises co-aligned hyperspectral and LiDAR data collected of European beech (Fagus sylvatica) forest within core protected areas of the UNESCO Rhӧn Biosphere Reserve, Germany. Data was collected using the Headwall Hyperspec Nano sensor flown from a unmanned aerial vehicle (UAV) in September 2020. The dataset comprises image and LiDAR data of four sites, each approximately 8ha in size. The study forests were subject to the extreme drought event that impacted central Europe in 2018/2019 and this project sought to collect data to enable individual tree and stand level assessment of the response (canopy damage and defoliation) of European beech trees to extreme drought events. The hyperspectral images available in this dataset have approx. 5cm pixel size with an associated LiDAR dataset and are suitable for identifying individual trees and the degree of canopy damage (defoliation, discolouration, and mortality) sustained by individuals/stands within the forest. The work was supported by the Natural Environment Research Council (Grant NE/V00929X/1). Full details about this dataset can be found at https://doi.org/10.5285/23d6a61c-c1cf-4c1b-a65c-f3fe42fc0e76

This dataset comprises four RGB unmanned aerial vehicle (UAV) images collected in September 2020 of European beech (Fagus sylvatica) forest within core protected areas of the UNESCO Rhӧn Biosphere Reserve, Germany. The study forests were subject to the extreme drought event that impacted central Europe in 2018/2019 and this project sought to collect data to enable the analysis of individual tree and stand level response (canopy damage and defoliation) of European beech trees to extreme drought events. The RGB images available in this dataset have approx. 3cm pixel size with an associated 10cm pixel digital elevation model (DEM) and are suitable for identifying individual trees and the degree of canopy damage (defoliation, discolouration, and mortality) sustained by individuals/stands within the forest. The work was supported by the Natural Environment Research Council (Grant NE/V00929X/1). Full details about this dataset can be found at https://doi.org/10.5285/b2d17962-3c7f-4193-a180-cde885d1a83e

The dataset contains the radiocarbon age of soil organic matter fractions collected along grassland-to-forest conversion chronosequences across Scotland. Soil samples were collected in summer 2018. In summer 2019, soil samples were fractionated and the radiocarbon age of bulk soil and soil fraction samples determined by accelerator mass spectrometry. Full details about this dataset can be found at https://doi.org/10.5285/0dd45f6f-0536-4ee3-9932-58bac019d2c6