This dataset contains time series observations of surface-atmosphere exchanges of net ecosystem carbon dioxide exchange (NEE), sensible heat (H) and latent heat (LE), and momentum (τ) measured at a at a Miscanthus x. giganteus Greef et Deu plantation in Lincolnshire, UK. Turbulent flux densities were monitored using the micrometeorological eddy covariance (EC) technique between 30th April 2008 and 18th February 2013. The dataset includes ancillary weather and soil physics observations, as well as variables describing atmospheric turbulence and the quality of the turbulent flux observations. 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/10.5285/00487c70-b74e-4c91-ab0c-31735c2e3b13

The UK Centre for Ecology and Hydrology gathered a range of ecological data between 2000 and 2004. The data include vegetation, farm management and habitat information, collected from 89 pairs of organic and non-organic fields on 161 farms containing arable crops distributed throughout England. Within these farms, landscape context and farm management practices centred on 30 pairs of target spring cereal fields (in 2000) and 59 pairs of target winter wheat fields (over two seasons 2002-2004). Data were derived at different scales ranging from field to landscape scale using a range of methods. The vegetation data consists of plant records from within target fields which were sampled in 3 years (2000, 2002, 2003) with each field sampled in one of the years. Three plot types were used. (i) Crop margin plots which recorded species presence in plots extending 1 m from the ploughed edge and 100 m along the field edge. (ii) Field boundary plots which recorded presence and abundance (% cover) of species in plots extending 1 m from the centre of the uncultivated field boundary and 10 m parallel to the boundary. Berries were counted in winter from a sub-set of sites. (iii) Percent cover of within-crop plants was recorded in 0.5×0.5 m quadrats placed at distances of 2, 4, 8, 16 and 32 m from the ploughed margin on 12 transects per field. Farm management data were collected via land manager questionnaires. Farmers were asked 40 questions concerning management of the target field and the whole farm. Habitat data were summarised at the farm level from the satellite-derived UKCEH Land Cover Map 2000. Invertebrates and birds were also sampled but do not form part of this data set. The study was based on a total of 88 non-organic and 73 organic farms over three cropping seasons between 2000 and 2004. This dataset was created to investigate the benefits of organic farming for biodiversity as part of a DEFRA funded study. Full details about this dataset can be found at https://doi.org/10.5285/aa86a268-559c-4f54-8e52-6292ad7901f4

[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 provided data presents a list of greenhouse gas removal practices for soil organic carbon sequestration, which are suitable under biophysical, economic and social consideration. The list is the result of the first step in analysing the potential of agricultural soils to sequester carbon globally and is part of the NERC funded project Soils-R-GGREAT (NE/P019455/1). The work is based on literature research and expert panel and judgements. The work was supported by the Natural Environment Research Council (NE/P019455/1) Full details about this dataset can be found at https://doi.org/10.5285/e0acc105-e13e-4c1f-b275-f7518b823aad

[This dataset is embargoed until May 1, 2026]. The dataset is in csv format recording trait values measured on a subset of the Bengal and Assam Aus Panel (BAAP) of rice grown in the field at two levels of nitrogen application in four South Asian sites over at least two seasons. Traits are leaf nitrogen content (measured with a Soil Plant Analysis Development (SPAD) meter) at 45 and 60 days, days to flowering and at harvest plant height, number of tillers, straw biomass and grain yield. The purpose was to assess members of the BAAP for their response to nitrogen treatment in the field for identification of rice cultivars for high nitrogen use efficiency (NUE) plus quantitative trait loci (QTL) and candidate genes for NUE Full details about this dataset can be found at https://doi.org/10.5285/1e20a1c8-6aeb-4365-866d-71b24c497586

The data consists of faecal microbiology and moisture content taken from two separate cohorts of 30 cattle. The cattle were from the North Wyke Farm Platform, a UK national capability, located at Rothamsted Research, North Wyke in Devon. Faecal samples were collected between November 2016 and July 2018. Samples were collected and microbiologically analysed in the laboratory within 6 to 8 hours. Two cohorts of 30 cattle were selected from 90 animals, ten from each of the three farmlets. Each cohort covering the period that cattle enter the farm platform, i.e. from weaning until slaughter ca. 16 – 20 months. Full details about this dataset can be found at https://doi.org/10.5285/ec83a4ea-923a-4f02-8a9f-aeecc43d7123

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 winter-sown oilseed rape 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/10.5285/37a503da-d75c-4d72-8e8b-b11c2fdc7d92

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 spring-sown oilseed rape 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/10.5285/0023bd6e-4dd7-462c-aacf-f13083b054ab

[This dataset is embargoed until June 1, 2026]. The dataset contains 323 diverse wheat accessions under two N regimes (N100 and N50) across two environments over two consecutive years, 2021-2023. All 323 genotypes were planted in two different Locations: 1) University of Agriculture, Faisalabad (31.4396° N, 73.0768° E), and 2) National Institute of Genomics and Advanced Biotechnology (NIGAB), Islamabad (33.6736° N, 73.1240° E). The experiments were laid down for two years; Yr1) Rabi-2021-22 and Yr2) Rabi-2022-23. Alpha lattice was used as an experimental design with 4 replications at location 1 and 3 replications at location 2. Treatments were applied as 100% of the recommended N dose at a rate of 120 kg ha-1 (N100) and 50% of the recommended dose at a rate of 60 kg ha-1(N50). Urea was used as N source and applied in three splits as basal dose, at stem elongation stage and at the heading stage. Standard irrigation and crop management practices were followed for all environments. The following parameters were measured: days to flowering, flag leaf area (cm2), peduncle length (cm), spike length (cm), plant height (cm), straw yield (g), grain yield (g) and thousand grain weight (g). The work was supported by the Natural Environment Research Council (Grant NE/S009019/1). Full details about this dataset can be found at https://doi.org/10.5285/7aa32225-f277-4ff6-bc73-7fe6123748cc

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