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 (hereafter Miscanthus) plantation in Lincolnshire, UK. Turbulent flux densities were monitored using the micrometeorological eddy covariance (EC) technique between 4 July 2013 and 25 November 2017. 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/10.5285/71e5b799-fc4d-4a44-8860-a5e358c807fd

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

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 short rotation coppice willow plantation in Lincolnshire, UK. Turbulent flux densities were monitored using the micrometeorological eddy covariance (EC) technique between 9 January 2014 and 26 November 2017. 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/bf0d7332-4cfe-4277-bd99-3caf35332a7b

These data are from an investigation of the effects of biochar application to soil, on soil greenhouse gas emissions and N transformations within the soil. Biochar is a carbon rich substance which is being advocated as a climate mitigation tool to increase carbon sequestration and reduce nitrous oxide emissions. The data were collected during a 15N pool dilution incubation to investigate the nitrogen transformations within biochar-amended soil following the addition of 15N-labelled ammonium nitrate. Analyses included 15N content of nitrous oxide and 15N content of soil. The N transformations were then modelled using a model for calculating nitrogen fluxes in soil using 15N tracing (FLUAZ model). Full details about this dataset can be found at https://doi.org/10.5285/69d89261-b7ee-4b56-bb13-1128e3c8dd93

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 short rotation coppice willow plantation in Lincolnshire, UK. Turbulent flux densities were monitored using the micrometeorological eddy covariance (EC) technique between 13th October 2009 and 15th May 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/10.5285/9e14539e-b376-4a70-87a0-f8725f84bae9

This dataset contains counts of pollinators visiting different varieties of oilseed rape (OSR). Data were collected from four trial sites in the UK in May 2012. The trial sites comprised of 20 varieties (plots) replicated in three blocks on each farm but only 2 of the blocks at each site were used for pollinator observations. Pollinator observations were also only made where there were greater than 30 percent of OSR plants in flower in the plot and only when weather conditions were within standardised limits. For each plot per site a six minute observation period was made during which the number of pollinators within the following taxon groups were counted: bumblebees to the species level, solitary bees identified to general body forms (Lasiglossum to genus level; Osmia separated to bicolour and rufa; Andrena separated to body forms typical of dorsata, carantonica, nigroaenea, haemorrhoa, fulva, flavipies, nitida, cineraria, bicolour and minuta), large hoverflies (> 12 mm), small hoverflies (< 11 mm), and Bibionidae. Each variety was observed for two separate six minute periods to reduce the impacts of minor fluctuations in weather that may reduce pollinator observations within single six minute periods. The dataset was collected as part of a project which aimed to identify key pollinators for OSR and identify if there are feeding preferences for individual varieties. Full details about this dataset can be found at https://doi.org/10.5285/d7b25308-3ec7-4cff-8eed-fe20b815f964

Data collected during field and laboratory experiments to investigate the long-term effects of biochar application to soil on greenhouse gas emissions in a bioenergy plantation (Miscanthus X. giganteus). Analysis included monitoring of greenhouse gas emissions (carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O)), soil physical (bulk density and soil moisture ) and soil chemical analyses (total carbon (C) and nitrogen (N), extractable ammonium and nitrate). Biochar was applied to plots in a bioenergy plantation and emissions of CO2, CH4 and N2O were measured over a 2 year period. In addition a laboratory incubation experiment was conducted on soil taken from the Miscanthus field amended with field-incubated biochar to assess the effect on greenhouse gas emissions. Biochar is a carbon rich substances which is being advocated as a climate mitigation tool to increase carbon sequestration and reduce nitrous oxide emissions. Full details about this dataset can be found at https://doi.org/10.5285/e9baffd1-18ad-435e-94e2-01e49c14c547

Data from an investigation of the effects of biochar application to soil on greenhouse gas emissions using soil from a bioenergy crop (Miscanthus X. giganteus). Data include physical (bulk density) and chemical analyses of the soil (total carbon (C) and nitrogen (N), extractable ammonium and nitrate), and greenhouse gas (GHG) emissions (carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O)) during incubations. Data were collected during two incubation experiments investigating the effects of temperature, soil moisture and soil aeration on biochar induced suppression of GHG emissions. Biochar is a carbon rich substances which is being advocated as a climate mitigation tool to increase carbon sequestration and reduce nitrous oxide emissions. Full details about this dataset can be found at https://doi.org/10.5285/2757e972-a7fe-494d-92c3-c3205dfdef19

Data collected during a field experiment investigating the differences between greenhouse gas (GHG) fluxes under a bioenergy crop Miscanthus x giganteus and a conventional arable crop, barley (Hordeum vulgare) on adjacent fields. Measurements taken include soil respiration (Rs) measured using Licor automated chambers and infrared gas analyser (IRGA), from collars excluding aboveground vegetation but not roots. Ancillary measurements included meteorological variables (air temperature and solar radiation) and soil variables (soil moisture and temperature at 5 cm depth). Data were collected between May and September 2013. Full details about this dataset can be found at https://doi.org/10.5285/c397d6f4-96f4-4967-a0df-c64ef35ea572

This data collection results from abundance surveys of 7 species of weeds in ca. 500 lowland arable fields in 49 farms over three years. Each field was divided into large grids of 20x20 metre cells, and the density of seven species was estimated three times a year. The study is part of the NERC Rural Economy and Land Use (RELU) programme. In the context of changing external and internal pressures on UK agriculture, particularly those associated with the ongoing reform of the EU Common Agricultural Policy, it is imperative to determine whether all of the various dimensions of sustainability - including the relevant economic and environmental objectives as well as social and cultural values - can be integrated successfully at the farm and landscape levels. Although the ways in which economic, technological, and regulatory changes are likely to affect the profitability and management of farms of varying size are reasonably well understood, there is not the knowledge or understanding to predict the resulting effects on biodiversity. For example, the effect of changes in arable farming practices on field weeds and, in turn, on habitats and food supply required to sustain farm birds is a case in point. This knowledge is critical, however, if we are to understand the ecological consequences of changes in agricultural policy. Furthermore, it is also important if we are to design and justify changes in farming methods that can not only enhance nature conservation, but do this is ways that are practical and appealing from a farmer's point of view. This understanding is essential if we are to achieve an agriculture that is sustainable in both economic and environmental terms and is widely perceived to have social and cultural value. A consistent theme in all components of this research project is to understand the behaviour (of farmers, weeds or birds) and then use this information to produce predictive models. Whilst there have been a number of models of economic behaviour, weed populations and bird populations - including many by the research team here - the really novel component of this research is to integrate these within one framework. Farmer interviews on economic attitudes and preferences associated with and importance of different land-use objectives to lowland arable farmers are available at the UK Data Archive under study number 6728 (see online resources). Further documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see online resources).