This data is the fruit set and marketable fruit set (percentage and success: failure) of commercial raspberry plants under four different pollination treatments. The data also includes fruit measurements (weight in grams and length and width in mms) of these fruit and the number of seeds per fruit for a subset of the collected fruits. Full details about this dataset can be found at https://doi.org/10.5285/de5b4f33-f679-4798-8daf-51a314e78204

This dataset comprises 259 smallholder agricultural field surveys collected from twenty-six villages across three Districts in Mozambique, Africa. Surveys were conducted in ten fields in each of six villages in Mabalane District, Gaza Province, ten villages in Marrupa District, Niassa Province, and ten villages in Gurue District, Zambezia Province. Data were collected in Mabalane between May-Sep 2014, Marrupa between May-Aug 2015, and Gurue between Sep-Dec 2015. Fields were selected based on their age, location, and status as an active field at the time of the survey (i.e. no fallow fields were sampled). Structured interviews using questionnaires were conducted with each farmer to obtain information about current management practices (e.g. use of inputs, tilling, fire and residue management), age of the field, crops planted, crop yields, fallow cycles, floods, erosion and other problems such as crop pests and wild animals. The survey also includes qualitative observations about the fields at the time of the interview, including standing live trees and cropping systems. This dataset was collected as part of the Ecosystem Services for Poverty Alleviation (ESPA) funded ACES project , which aims to understand how changing land use impacts on ecosystem services and human wellbeing of the rural poor in Mozambique. Full details about this dataset can be found at https://doi.org/10.5285/78c5dcee-61c1-44be-9c47-8e9e2d03cb63

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 contains yield data for wheat, oilseed rape and field beans grown in fields under different agri-environment practices. The fields were located at the Hillesden Estate in Buckinghamshire, UK, where a randomised block experiment had been implemented to examine the effects of converting differing proportions of arable land to wildlife habitat. The fields were planted with wheat (Triticum aestivum L.) followed by break crops of either oilseed rape (Brassica napus L.) or field beans (Vicia faba L.). Three treatments were applied at random: a control ("business as usual"), Entry Level Stewardship (ELS) treatment and ELS Extra treatment. The ELS treatment involved removing 1% of land to create wildlife habitats. The ELS Extra had a greater proportion of land removed (6%) and additional wildlife habitats included. The total yield of each crop was measured at the time of harvesting using a yield meter attached to the combine harvester. From these values, yield per hectare and the ratio of crop yield to regional average yield were calculated. Full details about this dataset can be found at https://doi.org/10.5285/e54069b6-71a9-4b36-837f-a5e3ee65b4de

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 pertains to a single time point 'snapshot' spatial sampling of site characteristics, soil parameters and soil greenhouse gas emissions for two sites (Extensive and Intensive). The extensively managed site ('Extensive'; 240-340 m above sea level; a.s.l.) consisted of an 11.5 ha semi-improved, sheep-grazed pasture at Bangor University's Henfaes Research Station, Abergwyngregyn, North Wales (53°13'13''N, 4°0'34''W). The intensively managed site ('Intensive'; on average 160 m a.s.l.) was a 1.78 ha sheep-grazed pasture located in south-west England, at the North Wyke Farm Platform (NWFP), Rothamsted Research, Okehampton, Devon (50°46'10''N, 30°54'05''W). At the Extensive site soil and gas sampling was conducted on 30th November 2016. At the Intensive site soil and gas sampling was conducted on 1st August 2016. The data contains: site characteristics including elevation, slope, compound topographic index, vegetation type or manure application, and sample point grid references; soil parameters including soil bulk density, soil percentage water-filled pore space, soil moisture, soil organic matter contents, soil pH, soil nitrate nitrogen concentration, soil ammonium nitrogen concentration, soil percentage total carbon contents, soil percentage total nitrogen contents, and carbon to nitrogen content ratio; and soil greenhouse gas flux data for nitrous oxide, carbon dioxide and methane. The study was conducted as a wider part of the NERC funded Uplands-N2O project and BBSRC-supported Rothamsted Research, North Wyke Farm Platform (Grant Nos: NE/M015351/1, NE/M013847/1, NE/M013154/1, BBS/E/C/000J0100, BBS/E/C/000I0320, BBS/E/C/000I0330). Quantifying the spatial and variability of the drivers of greenhouse gas emissions and their interactions in grazing systems is critical to improve our understanding of nitrous oxide, carbon dioxide and methane fluxes, enabling better estimates of aggregated greenhouse gas emissions and associated uncertainties at the landscape scale. Full details about this dataset can be found at https://doi.org/10.5285/f3118fa8-6bec-488b-9713-2415912b8b9e

This dataset consists of butterfly and bumblebee counts, winter bird counts, number of flowering units, and seed mass data, along with categories of soil type and quality, and temperature data. Data were collected from arable farms under the English Entry Level agri-environment Scheme (ELS) for two options: Nectar Flower Mixture option (NFM) and Wild Bird Seed Mixture (WBM). Surveys were carried out in 2007 and repeated in 2008. All data were collected using standardised protocols: butterfly and bumblebee counts were collected from transects in the NFM options during summer; flowering units were counted within quadrats along the same transects in summer; bird counts were made in winter within the whole WBM areas; seed resource was calculated for the WBM areas from seeds collected in quadrats along transects. The dataset also contains results from farmer interviews. The interviews were designed to explore farmer attitudes towards, and history of, environmental management and their perceptions and understanding of the management requirements. Three measures of farmer attitude were then calculcated from their responses: experience (4-point scale), concerns (5-point scale) and motivation (3-point scale). All data were collected as part of the FarmCAT project, the principal aim of which was to develop a holistic understanding of the social and ecological factors which lead to the successful delivery of agri-environmental schemes. This project was funded as part of the ESRC Rural Economy and Land Use (RELU) programme. Full details about this dataset can be found at https://doi.org/10.5285/d774f98f-030d-45bb-8042-7729573a13b2

This dataset contains information on soil physico-chemical characteristics and palm nutrient concentrations collected in 2019 across twenty-five smallholder oil palm farms in Perak, Malaysia. Leaf and rachis were sampled from 3 palms within each plot. Soils were sampled to 30cm depth in the palm circle of the same 3 palms and the adjacent inter-row area. These data were collected to assess the soil condition and nutritional status of oil palms across smallholder farms. This information was used to advise on best agronomic practice. The work was supported by the Natural Environment Research Council (Grant No. 355 NE/R000131/1). Full details about this dataset can be found at https://doi.org/10.5285/4d3813b6-714b-403a-aeeb-e2fa518a1520

This dataset includes values of 15 traits (total dry mass; root length to shoot length ratio; leaf mass fraction; root mass fraction; shoot mass fraction; leaf thickness; leaf force to punch; leaf area to shoot area ratio; leaf concentrations of N, P, K, Ca and Mg; leaf N: P concentration ratio; specific maximum root length) measured in February 2020 on 394 seedlings of 15 woody plant species growing in logged in the Ulu Segama Forest Reserve or unlogged forest in the Danum Valley Conservation Area, Malaysia. The purpose of this data collection was to determine whether the expression of plant functional traits differed between tree seedlings recruited into logged and unlogged forests. This information is important for understanding the drivers of variation in seedling growth and survival in response to logging disturbance, and to uncover the mechanisms giving rise to differentiation in tree seedling composition in response to logging. These data were collected as part of NERC project “Seeing the fruit for the trees in Borneo: responding to an unpredictable community-level fruiting event” (NE/T006560/1). Full details about this dataset can be found at https://doi.org/10.5285/e738e8af-554a-4940-bb56-267c7377d74d

[THIS DATASET HAS BEEN WITHDRAWN]. Modelled average percentage yield loss due to ground-level ozone pollution (per 1 degree by 1 degree grid cell) are presented for the crops maize (Zea mays), rice (Oryza sativa), soybean (Glycine max) and wheat (Triticum aestivum) for the period 2010-2012. Data are on a global scale, based on the distribution of production for each crop, according to the Food and Agriculture Organisation’s (FAO) Global Agro-Ecological Zones (GAEZ) crop production data for the year 2000. Modelled ozone data (2010-2012) needed for yield loss calculations were derived from the EMEP MSC-W (European Monitoring and Evaluation Programme, Meteorological Synthesising Centre-West) chemical transport model (version 4.16). Mapping the global crop yield losses due to ozone highlights the impact of ozone on crops and allows areas at high risk of ozone damage to be identified, which is one of the first steps towards mitigation of the problem. The yield loss calculations were done as part of the NERC funded SUNRISE project (NEC06476). Full details about this dataset can be found at https://doi.org/10.5285/181a7dd5-0fd4-482a-afce-0fa6875b5fb3