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farming

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  • Data are presented from an ozone exposure experiment performed on four African crops. The crops (Beans, Cowpeas, Amaranth and Sorghum) were exposed to three different levels of ozone and two heat treatments in the UK CEH Bangor solardomes. The experiment ran from May 2018 to September 2018. The crop plants were grown from seed, in pots in solardomes. The aim of the experiment was to investigate the impact of ozone exposure on the crop yield and plant health. The dataset comprises of manually collected data on plant physiology, biomass and yield. In addition the automatically logged data of ozone concentration and meteorological variables in the solardomes are presented. Plant physiology data is stomatal conductance of individual leaves, measured on an ad-hoc basis. The dataset includes the associated data measured by the equipment (relative humidity, leaf temperature, photosynthetically active radiation – a small number of photosynthetically active radiation measurements are missing due to faulty readings). Soil moisture of the pots was always measured at the same time, and chlorophyll content of the measured leaf was usually, but not always, determined at the same time. Yield of beans and cowpeas was determined for each plant. For Amaranth, only the seed head weight was determined. Sorghum did not reach yield, therefore, total biomass at harvest is given as an alternative. Total biomass was not determined for those plants of other crop types that did reach yield. The ozone and meteorological dataset is complete, but with some gap-filling for short periods when the computer was not logging data The work was carried out as part of the NERC funded SUNRISE project (NE/R000131/1). Full details about this dataset can be found at https://doi.org/10.5285/f7da626c-f39c-474f-b2e7-8638ab26d166

  • 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 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

  • Data from 38 experimental sites across the UK and Ireland were collated resulting in 623 separate mineral fertiliser N2O emission factors (EF) estimates derived from field measurements. Data were either i) extracted from published studies in which one aim of the experimentation was to explicitly measure N2O and report EFs after a mineral fertiliser application, or ii) raw data were used from the Agricultural and Environmental Data Archive (AEDA). To find the published data, a survey of literature was conducted using Google Scholar for articles considered ‘recent’ (20 years or fewer), i.e. published after January 1998 and submitted before April 2019. The following search terms and their variations were used: N2O, nitrous oxide, emission factor, mineral fertiliser, ammonium nitrate, urea, nitrification inhibitor, nitrogen use efficiency, agriculture, greenhouse gas, grassland and arable. This search based on keywords was complemented with a search through the literature cited in the articles found and known previous research. Full details about this dataset can be found at https://doi.org/10.5285/9948d1b9-caa1-4894-93e6-cc0f4326fced

  • This dataset represents a cohort of heifers followed from birth to 18 months or first pregnancy on 37 farms in the South West of England. Faecally-contaminated environmental samples were collected over 2 years and the samples analysed for E. coli resistance to amoxicillin, cefalexin and tetracycline with detection of resistant strains presented in the dataset as a binary result. Farm-level antibiotic usage data is also given. Full details about this dataset can be found at https://doi.org/10.5285/7c3ad803-fbd4-45c3-826b-fa04c902ded8

  • 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 consists of faecally-contaminated samples taken from the environment around pre-weaned calves on 51 farms in South-West England during 2017/2018 and is a subset of a larger dataset investigating antibiotic resistance in E. coli across 53 farms. The samples were analysed for presence of E. coli resistant to amoxicillin, streptomycin, cephalexin, tetracycline and/or ciprofloxacin. Management factors deemed related to pre-weaned calves are included, including antibiotic usage data at farm level. Full details about this dataset can be found at https://doi.org/10.5285/808b2b62-14db-4483-b0e6-5f533c007eec

  • 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

  • The data consist of nitrogen gene data, soil biodiversity indices and microbial community composition for three soil depths (0-15, 15-30 and 30-60 cm) from a winter wheat field experiment located in the United Kingdom and collected between April 2017 and August 2017. The sites were Rothamsted Research at North Wyke in Devon and Bangor University at Henfaes Research Station in North Wales. At each site measurements were taken from 15 plots, organised within a randomised complete block design where 5 plots did not receive fertilizers (controls), 5 plots received food-based digestate, and 5 plots received acidified food based digestate a nitrification inhibitor. Soil samples were taken within two weeks of digestate application and shortly before winter wheat harvest. Soil chemical parameters were: soil nitrate, ammonium, dissolved organic carbon and nitrogen, amino acids and peptides, soil organic matter content as loss-on-ignition, pH, sodium, potassium, calcium, magnesium, permanganate oxdisable carbon citric acid extractable phosphorous, Olsen-P and total carbon, nitrogen and phosphorus. Soil biological measure were: microbial biomass carbon and nitrogen. Soil samples were taken by members of staff from Centre of Ecology & Hydrology (Bangor), Bangor University, School of Environment, Natural Resources & Geography Sustainable Agricultural Sciences, and Rothamsted Research North Wyke. Measurements were carried out Rothamsted Research Harpenden and the Centre of Ecology & Hydrology (Wallingford). Soil physico-chemical parameters were measured on the same soil samples and are presented in a related dataset. https://catalogue.ceh.ac.uk/id/90df9dfa-a0c8-4ead-a13d-0a0a13cda7ab Data was collected for the Newton Fund project “UK-China Virtual Joint Centre for Improved Nitrogen Agronomy”. Funded by Biotechnology and Biological Sciences Research Council (BBSRC) and NERC - Ref BB/N013468/1 Full details about this dataset can be found at https://doi.org/10.5285/391c0294-07f1-4856-b592-428bd44055ca

  • [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