Our overarching aim is to monitor soil properties and how they change, nationally and globally. This is important because soils are the major store of terrestrial carbon that buffers climate change, and management impacts soil health, e.g. acidity, structure and nutrient delivery. Landowners and policy makers need to understand if interventions to improve soils work and need tools that enable rapid data acquisition. This proposal builds on the world leading NERC mySoil digital iphone application used by more than 50,000 people globally. mySoil provides basic soil information on an iphone and allows endusers to upload data and photos through crowd sourcing, with more than 4000 records uploaded and the past few years. In consultation with our industry partners we propose to further develop the NERC mySoil app into an industry standard, survey grade application that can collect georeferenced soil data, on and offline. Each year we fail to capture £millions of unstructured soil data which is analysed for small businesses, just 2% of which could form a substantial community resource for producing soil maps or benchmarking/comparing soil data. We will be working with the National Trust, NRM laboratories, Agricultural Industries Confederation and EU Joint Research Centre to incorporate NERC tools into their agri-environment business or monitoring and public and business outreach. Our objectives are to expand the offline capability, and develop field protocols for collecting soil information that can inform indicators of soil change. Translation into several common European languages will ensure wide accessibility. Initial data from our survey indicates that the agricultural, horticultural, conservation and education sectors are the greatest beneficiaries of information delivered through NERC digital platforms, both mySoil and the UK Soil Observatory. Our partners work with all these sectors and seek to have a tool that is freely available and can be used by both professionals and the general public. They will use their extensive resources to identify a range of end users for testing across business sectors and will help with translation. The major benefits identified from our survey of current end users are, 'increasing their knowledge and awareness of soil resources' and 'improving their outputs and processes'. This proposal focuses on improving outputs and processes by helping our partners to collect data to inform them on the state and change of soils on the lands for which they have interest. The data will support the National Trusts Land Capability assessment and the JRC/Eurostat LUCAS survey (Land Use and Coverage Area frame Survey); both of these inform policy. Moreover, companies, scientists and the public benefit from data that can be incorporated into open soil mapping projects like soilGRIDS produced by the World Soil Information Centre.

Nitrogen (N) is vital for crop productivity, however, typically half of the N we add to agricultural land is usually lost to the environment. This wastes the resource and produces threats to air, water, soil, human health and biodiversity, and generates harmful greenhouse gas (GHG) emissions. These environmental problems largely result from our inability to accurately match fertiliser inputs to crop demand in both space and time in the field. If these problems are to be overcome, we need a radical step change in current N management techniques in both arable and grassland production systems. One potential solution to this is the use of technologies that can 'sense' the amount of plant-available N present in the soil combined with sensors that can report on the N status of the crop canopy. On their own, these sensors can provide useful information on soil/crop N status to the farmer. However, they need refining if they are then to be used to inform fertiliser management decisions. This is because climate variables (e.g., temperature, rainfall, sunlight hours) and soil factors (e.g., texture, organic matter content) can have a major influence on soil processes and plant growth, independent of soil N status. These sensors therefore need to be combined with other data and improved soil-crop growth models to provide a more accurate report of how soil N relates to crop N demand at any given point in time. In this project, we are demonstrating how adoption of precision agriculture techniques (in the form of soil nitrate sensors) can be used to improve N use efficiency in both arable (wheat, oilseed rape) and grassland systems. While we are focusing on soil nitrate, as it arguably represents the key form of soil N associated with productivity and the environment, the approaches we are taking are also readily applicable to other nutrients for which sensors are currently being developed (e.g., ammonium, phosphate, potassium). We have designed our research programme in accordance with the strategic objectives of the BBSRC-SARIC programme and those recently produced by HM Government to facilitate delivery of sustainable intensification strategies. To maximise the potential for technology development, commercialisation and adoption we are working closely with a range of industry partners throughout the programme. Overall, we aim to (i) demonstrate the use of novel N sensors for the real-time measurement of soil N status; (ii) use geo-statistical methods to optimise the deployment of these in situ sensors; (iii) produce new mechanistic mathematical models which allow accurate prediction of crop N demand; (iv) validate the benefits of these sensors and models in representative grassland and arable systems from a N use and economic standpoint; and (v) explore how these new technologies can improve current fertiliser management and guidelines through enhanced industry-focused decision support tools. Ultimately, this technology shift could result in substantial savings to the farmer by both reducing costs, maximising yields and minimising damage to the environment. For example, if our technology improves N use efficiency by 10% in agricultural land where fertiliser is applied in the UK (8.2 million hectares of grassland and tilled crops), we estimate it would save 100 thousand tons of N fertiliser (equivalent to a saving of £69 million per annum to farmers). When the direct and indirect costs of nitrate pollution are considered (e.g., removing nitrate from drinking water is estimated to cost UK water companies >£20 million annually), and the reduction in direct and indirect greenhouse gas emissions from manufacture and use of 100 thousand tons of N fertiliser are accounted for, the benefits of adopting a validated precision agriculture approach are clear.

There is no life without soil to provide food, feed, fibre and wood. Understanding how soils are changing in response to land use management, climate change, and pollution is at the forefront of environmental research to reduce degradation and deliver vital functions such as, food production, transforming and recycling waste, and storing carbon. We have identified an important market failure that results in the loss of high quality strategic soil data for industry and policy. Farmers collect soil samples every year that they have analysed in commercial laboratories, this data lacks basic location information and is generally collected through paper based systems inhibiting data flows that would stimulate new business opportunities. Therefore, we will turn farmer's soil analysis into 'smart soil data' to unlock the secrets of the soil. More than 0.5 million soil samples, collected by the farming industry every year are without location information and digitally undiscoverable. 'smart soil data' is digital, discoverable, with gps positioning and accredited laboratory analysis. By making soil data smart we can begin to address the questions for which we need big data, such as why have we reached a yield plateau, and why does yield decline follow crop rotation, is soil carbon stock declining? In order to unlock these secrets we need 'smart soil data'. MySoil sample will address this, a web and app based digital data capture system built on the tried and tested NERC iRecord platform. We will: i) build a digital data hub for owners to privately store or share industry data, making anonymized data discoverable and interoperable. ii) a web and smartphone soil sample data collection system with GPS, and iii) create anonymous digital data pipelines to interpretive benchmarking portals for industry. This will open up new markets and business opportunities for collecting and using high level anonymized, 'smart soil data'. We call our system 'mySoil-sample', which builds on our success in crowdsourcing soil data using 'mySoil' (4000+ records) and wildlife data using 'iRecord' (50,000+ records). The new data acquisition system will provide a strategic data resource that will add value to data and inform both industry and policy makers. This is now vital, as Brexit may pose a range of new challenges for farmers and agri-business to remain competitive. There has never been more need to understand how our natural resources can respond to this economic and societal challenge. We will use the power of the crowd (farming and conservation communities), combined with tried and tested NERC digital crowdsourcing data acquisition systems, both web and app based to support industry and policy.

There is no life without soil to provide food, feed, fibre and wood. Understanding how soils are changing in response to land use management, climate change, and pollution is at the forefront of environmental research to reduce degradation and deliver vital functions such as, food production, transforming and recycling waste, and storing carbon. We have identified an important market failure that results in the loss of high quality strategic soil data for industry and policy. Farmers collect soil samples every year that they have analysed in commercial laboratories, this data lacks basic location information and is generally collected through paper based systems inhibiting data flows that would stimulate new business opportunities. Therefore, we will turn farmer's soil analysis into 'smart soil data' to unlock the secrets of the soil. More than 0.5 million soil samples, collected by the farming industry every year are without location information and digitally undiscoverable. 'smart soil data' is digital, discoverable, with gps positioning and accredited laboratory analysis. By making soil data smart we can begin to address the questions for which we need big data, such as why have we reached a yield plateau, and why does yield decline follow crop rotation, is soil carbon stock declining? In order to unlock these secrets we need 'smart soil data'. MySoil sample will address this, a web and app based digital data capture system built on the tried and tested NERC iRecord platform. We will: i) build a digital data hub for owners to privately store or share industry data, making anonymized data discoverable and interoperable. ii) a web and smartphone soil sample data collection system with GPS, and iii) create anonymous digital data pipelines to interpretive benchmarking portals for industry. This will open up new markets and business opportunities for collecting and using high level anonymized, 'smart soil data'. We call our system 'mySoil-sample', which builds on our success in crowdsourcing soil data using 'mySoil' (4000+ records) and wildlife data using 'iRecord' (50,000+ records). The new data acquisition system will provide a strategic data resource that will add value to data and inform both industry and policy makers. This is now vital, as Brexit may pose a range of new challenges for farmers and agri-business to remain competitive. There has never been more need to understand how our natural resources can respond to this economic and societal challenge. We will use the power of the crowd (farming and conservation communities), combined with tried and tested NERC digital crowdsourcing data acquisition systems, both web and app based to support industry and policy.

The UK is committed to quantifying and managing its emissions of greenhouse gases (GHG, i.e. CO2, CH4, N2O) to reduce the threat of dangerous climate change. Sinks and sources of GHGs vary in space and time across the UK because of the landscape's mosaic of managed and semi-natural ecosystems, and the varying temporal sensitivities of each GHG's emissions to meteorology and management. Understanding spatio-temporal patterns of biogenic GHG emissions will lead to improvements in flux estimates, allow creation of inventories with greater sensitivity to management and climate, and advance the modelling of feedbacks between climate, land use and GHG emissions. Addressing Deliverable C of the NERC Greenhouse Gas Emissions and Feedbacks Research Programme, we will use extensive existing UK field data on GHG emissions, supplemented with targeted new measurements at a range of scales, to build accurate GHG inventories and improve the capabilities of two land surface models (LSMs) to estimate GHG emissions. Our measurements will underpin state-of-the-art temporal and spatial upscaling frameworks. The temporal framework will evaluate diurnal, seasonal and inter-annual variation in emissions of CO2, CH4 and N2O over dominant UK land-covers, resolving management interventions such as ploughing, fertilizing and harvesting, and the effects of weather and climate variability. The spatial framework will evaluate landscape heterogeneity at patch (m), field (ha) and landscape (km2) scales, in two campaigns combining chambers, tower and airborne flux measurements in arable croplands of eastern England, and grazing and forest landscapes of northern Britain. For modelling, we will update two LSMs - JULES and CTESSEL- so that each generates estimates of CO2, CH4 and N2O fluxes from managed landscapes. The models will be updated to include the capabilities to represent changes in land use over time, to represent changes in land management over time (crop sowing, fertilizing, harvesting, ploughing etc), and the capacity to simulate forest rotations. With these changes in place, we will determine parameterisations for dominant UK land-covers and management interventions, using our spatio-temporal data. The work is organized in five science work-packages (WP). WP1: Data assembly and preliminary analysis. We will create a database of GHG flux data and ancillary data for major UK landcovers/landuses in order to calibrate and evaluate the LSMs' capabilities, and generate spatial databases of environmental and management drivers for the models. WP2. GHG measurement at multiple scales. We will deploy advanced technology to generate new information on spatial GHG processes from simultaneous measurement from chamber (<1 m) to landscape (40 km) length scales, and on temporal flux variation from minutes to years. WP3. Earth observation (EO) to support upscaling. EO data will provide: i) driving data for LSM upscaling, from flux tower to aircraft campaign scales; and ii) spatial data for testing LSM outputs at these larger scales. WP4 Upscaling GHG processes. Firstly, the two LSMs will be updated to allow the impacts of management activities on GHG emissions to be simulated, with calibration against an array of temporal flux data. Then, we will use the LSMs to model the fluxes of GHGs at larger spatial scales, based on a rigorous understanding of how the nonlinearity of responses and the non-Gaussian distribution of environmental input variables interact, for each GHG, using all available field data at finer scales. WP5 Application at the regional scale. The LSMs will upscale GHG emissions for both campaign regions (E. England, N. Britain) using 1-km2 resolution simulations with a focus on the airborne campaign periods of 4 weeks. We will determine how regional upscaling error can be reduced with intensive spatial soil and land management data.