This dataset consists of measures of topsoil (0-15 cm) physico-chemical properties from soils sampled from 105 x 1-km squares across Great Britain in 2024 as part of a rolling soil and vegetation monitoring program of 500 1-km squares repeated every 5 years, where 2024 is the first year of a new monitoring cycle. The properties included are: pH, soil organic matter (loss on ignition, LOI), derived carbon concentration and carbon stock (soil organic carbon, SOC), soil group, soil bulk density of fine earth, soil moisture of wet soil, fine earth volumetric water content (dry), nitrogen concentration and stock, and Olsen-phosphorus concentration. These samples are co-located with a botanical survey as part of the integrated monitoring approach, which is also available on the EIDC. The UKCEH Countryside Survey is a unique study or 'audit' of the natural resources of the UK's countryside. The sample sites are chosen from a stratified random sample, based on a 15 by 15 km grid of GB. Previous monitoring cycles have been carried out in 1978, 1984, 1990, 1998, 2007and 2019-2023 by the UK Centre for Ecology & Hydrology (UKCEH) and predecessors, with repeated visits to most of the squares each monitoring cycle. The countryside is sampled and surveyed using rigorous scientific methods, allowing us to compare new results with those from previous surveys. In this way, we can detect the gradual and subtle changes that occur in the UK's countryside over time. In addition to soil data, vegetation species data are also gathered by the current phase of the UKCEH Countryside Survey. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability and through the UKCEH National Capability for UK Challenges Programme NE/Y006208/1. Full details about this dataset can be found at https://doi.org/10.5285/cab9f36c-075e-4359-8781-24a8488641c3

[This dataset is embargoed until June 1, 2027]. The dataset contains single nucleotide polymorphism (SNP) genotyping data for 323 diverse wheat accessions from Pakistan, Mexico, and Australia. DNA was extracted from 21-day-old seedlings grown in a glasshouse at Rothamsted Research, UK, and genotyped using the commercially available TaNG v1.1 Affymetrix Axiom array at the Bristol Genomics Facility, University of Bristol. The genotypic data are provided in HapMap double-bit format. This work aimed to improve nitrogen use efficiency (NUE) in wheat as part of efforts toward sustainable yield enhancement and global food security. Genetic dissection of key agronomic traits presents a viable strategy for developing high-yielding, nitrogen-efficient wheat cultivars. The data support a genome-wide association study (GWAS) that related NUE traits to potential genetic markers. The research was funded by the Natural Environment Research Council (Grant NE/S009019/1). Full details about this dataset can be found at https://doi.org/10.5285/291ca8d7-6178-4e6f-98a5-f59225d884cd

The dataset contains information of Diameter at Breast Height (DBH) of 8,729 trees. These trees are distributed in 29 RAINFOR network forest plots across the Brazilian Amazon, comprising the states of Acre, Mato Grosso and Pará. All the plot censuses are located in terra-firme non-flooded lowland forests. The measurements were collected between 2017 and 2019. The Amazon Forest Inventory Network is a long-term, international collaboration to understand the dynamics of Amazon ecosystems. Since 2000 they have developed a framework for systematic monitoring of forests from the ground-up, centred on plots that track the fate of trees and species, and includes soil and plant biogeochemical records, as well as intensive monitoring of carbon cycle processes at some sites. RAINFOR works with partners across the nations of Amazonia to support and sustain forest monitoring and help develop new generations of Amazon ecologists. The work of RAINFOR is currently supported by funding agencies in Brazil, the UK, and the EU. Full details about this dataset can be found at https://doi.org/10.5285/63d4b774-4e03-4db2-95ad-dcca18f0d681

This is part of a long-term monitoring dataset from fortnightly sampling at the North Basin of Windermere in Cumbria, England. The data have been collected by the UK Centre for Ecology & Hydrology (UKCEH). The data available to download comprise hypolimnion temperature (TEMP) in degree Celsius, and hypolimnion dissolved oxygen concentration (DO) in mg per litre. All data have been measured in a depth of 60 to 62 m. All data are from January 2005 until the end of 2009. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/83aece7c-6ff0-4414-87ce-71ba27083b92

This dataset contains daily soil moisture estimates using prototype cosmic ray neutron sensors. The sensors were deployed in a centre-pivot irrigation site in the state of Bahia, Brazil, and measurements were taken hourly between June and December, 2023. The dataset includes daily averages of volumetric water containment, which have been corrected for environmental effects. This dataset was created to study the potential for using distributed cosmic ray sensors to support data driven irrigation optimisation and is supported by NERC (NE/W004364/1). Full details about this dataset can be found at https://doi.org/10.5285/a2c87e47-6f85-4bee-9a54-ecb1bb5b3573

This dataset contains total nitrogen (N) deposition at a 1km x 1km resolution in the UK, annually from 1990 to 2017. N deposition is presented as reduced N (NHx) and oxidised N (NOy), both of which are split into wet and dry portions. Values are given for forest and moorland land cover, as well as a weighted mean to each grid cell (‘grid average’). Full details about this dataset can be found at https://doi.org/10.5285/9b203324-6b37-4e91-b028-e073b197fb9f

This dataset contains information relating to the survival and persistence of Salmonella spp. on plastic and glass, under conditions simulant of a peri-urban waste pile. The data encompass bacterial strain identity, material type, timepoints (days), temperature (°C), bacterial concentration (CFU/ml), survival percentages, and regression parameters. Data were sampled over a 28-day period using culture-based approaches; and the ability of isolates to cause disease following their recovery was determined through the use of a Galleria mellonella model. This work was supported by the UKRI Natural Environment Research Council (NERC) as part of the GCRF SPACES project [grant number NE/V005847/1] and the Plastic Vectors project, “Microbial hitch-hikers of marine plastics: the survival, persistence & ecology of microbial communities in the ‘Plastisphere’” [grant number NE/S005196/1]. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/9c3a1ae5-65d7-45c6-b6f3-1a955b17abff

This dataset includes stream and rainfall hydrochemistry of the Plynlimon (Pumlumon in Welsh) research catchments in Mid Wales. The data cover the period from March 2024 to March 2025. Sampling was carried out every four weeks by a team of researchers from UK Centre for Ecology & Hydrology. Stream samples were taken using a grab technique and filtered in the field. Rain samples were collected using bulk precipitation collectors. Data are presented for major anions and cations, pH, conductivity, alkalinity and in-situ measurements for the water temperature and stream flow for the six stream locations and air temperature and volume for the rainfall sites. Full details about this dataset can be found at https://doi.org/10.5285/bb431417-01e8-43e7-bfe5-e48441b2e091

This dataset contains information relating to the survival and persistence of Salmonella spp. on plastic and glass, under conditions simulant of environmental UV exposure. The data encompass bacterial strain identity, material type, timepoints (days), temperature (°C), bacterial concentration (CFU/ml), survival percentages, and regression parameters. Data were sampled over a 21-day period using culture-based approaches; and the ability of isolates to cause disease following their recovery was determined through the use of a Galleria mellonella model. This work was supported by the UKRI Natural Environment Research Council (NERC) as part of the GCRF SPACES project [grant number NE/V005847/1] and the Plastic Vectors project, “Microbial hitch-hikers of marine plastics: the survival, persistence & ecology of microbial communities in the ‘Plastisphere’” [grant number NE/S005196/1]. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/57ef148f-8cfb-4ba6-b673-114b22b21613

This dataset comprises water chemistry data (dissolved organic carbon (DOC), total dissolved nitrogen (TdN), particulate organic carbon (POC), total phosphorus (TP), soluble reactive phosphorus (SRP), absorbance at 254nm (Abs 254), specific ultraviolet absorbance (SUVA), and dissolved CH4, CO2, N2O) collected bi-weekly from peatland streams near Penicuik, Scotland, in 2022 and 2023. Data were obtained via collection of water samples in situ, and concentrations were derived via subsequent sample processing and analysis. The objective of this dataset is to provide background data to characterise differences in the baseline period before restoration at the sampling site occurs. Full details about this dataset can be found at https://doi.org/10.5285/a48c07c0-ae32-4df1-8e32-5eec44c683b3