This dataset consists of landscape and agricultural management archetypes (1 km resolution) at three levels, defined by different opportunities for adaptation. Tier 1 archetypes quantify broad differences in soil, land cover and population across Great Britain, which cannot be readily influenced by the actions of land managers; Tier 2 archetypes capture more nuanced variations within farmland-dominated landscapes of Great Britain, over which land managers may have some degree of influence. Tier 3 archetypes are built at national levels for England and Wales and focus on socioeconomic and agro-ecological characteristics within farmland-dominated landscapes, characterising differences in farm management. The unavailability of several input variables for agricultural management prevented the generation of Tier 3 archetypes for Scotland. The archetypes were derived by data-driven machine learning. The three tiers of archetypes were analysed separately and not as a nested structure (i.e. a single Tier 3 archetype can occur in more than one Tier 2 archetype), predominantly to ensure that archetype definitions were easily interpreted across tiers. Full details about this dataset can be found at https://doi.org/10.5285/3b44375a-cbe6-468c-9395-41471054d0f3

The data comprises records of phenotypic traits of outbred Gryllus bimaculatus that were bred in a laboratory. Inbreeding was minimized by avoiding crossing family lines. Traits that were measured include adult body mass, development time, and lifespan. The data were collected in 2023 by researchers from the University of Glasgow to investigate the effects of parental age and temperature conditions on offspring life-history. We chose this species because we have complementary field projects on field crickets and they are easily maintained in a lab. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/085ec3ff-110d-4dbf-96da-7418ab9a7c5a

This data were created as part of the NIMFRU project and consists of 21 flood matrices. These have been completed by community members from the project target communities of Anyangabella, Agule and Kaikamosing which are all found in the Katakwi district. Five of the matrices were completed by local district officers. The data were collected in December 2020. These data were collected to understand how communities resilience had changed as a result of the NIMFRU project. Full details about this dataset can be found at https://doi.org/10.5285/463b2bcc-731a-42af-ba69-1662aa21f1bf

[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

This dataset is a product of the raw HEA (household economy approach) data that were collected in sixteen communities in the Katakwi district, and the raw IHM (individual household method) data that was collected with 42 households in the community of Anyangabella, and 51 households in the community of Kaikamosing. These data were collected in December 2020 and shows the crop calendars of the Katakwi district. These data consist of quantitative information relating to crop and fishing production timelines throughout a typical agricultural year. The data were collected to support the analysis of vulnerability levels of different to further support livelihood impact modelling, and the development of targeted policies to support resilience at household and community level. The data collection team comprised of local, Ugandan partners. All data were collected in the local language and translated into English. Full details about this dataset can be found at https://doi.org/10.5285/d91bd655-ad51-42c1-a8d0-91923246244b

This dataset is a product of the raw HEA (Household Economy Approach) data that were collected in sixteen communities in the Katakwi district, and the raw IHM (Individual Household Method) data that was collected with 42 households in the community of Anyangabella, and 51 households in the community of Kaikamosing. These data were collected in 2018, and consist of multiple aspects of household and individual income sources and expenditure in the Katakwi District. The data were collected to support the analysis of vulnerability levels to further support livelihood impact modelling, and the development of targeted policies to support resilience at household and community level. The data collection team comprised of local, Ugandan partners. All data were collected in the local language and translated into English. Full details about this dataset can be found at https://doi.org/10.5285/e736e22c-f409-49ee-930d-a415ade89e79

The number and type of natural enemies of crop pests found in winter-sown oilseed rape fields (Brassica napus L.) in relation to local plant diversity (in crop and field margin) and landscape characteristics. Natural enemies and pests were collected using two methods (suction sampling and pitfall traps). Local plant diversity was assessed using quadrats in field margins and in cropped area. The presence of hedges was also recorded. Landscape characteristics include the amount of mass flowering crops, arable land, presence of patches of different grassland types (intensive, restored and species rich) and the amount of grasslands and other semi natural habitat with up to a 3km radius of the collection points. These data were collected as part of Wessex BESS project, funded by the NERC Biodiversity and Ecosystem Service Sustainability research program. This dataset can be used in conjunction with other Wessex BESS WP4 datasets. Full details about this dataset can be found at https://doi.org/10.5285/6e2be4d6-a681-4ae5-8abf-0c3fc150365d

[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

[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 over 4000 faecally-contaminated environmental samples collected over 2 years across 53 dairy farms in England. The samples were analysed for E. coli resistance to amoxicillin, streptomycin, cefalexin, tetracycline and ciprofloxacin and detection of resistant strains is presented in the dataset as a binary result, along with mechanisms of resistance to third generation cephalosporins where relevant. In addition there is comprehensive farm management data including antibiotic usage data. Full details about this dataset can be found at https://doi.org/10.5285/c9bc537a-d1c5-43a0-b146-42c25d4e8160