What are the impacts of agricultural soil and crop management on greenhouse gas fluxes? - Informing post Brexit agricultural subsidy policy

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The UK's decision to leave the European Union presents an opportunity to transform the financial assistance given to farmers and other land managers, so that practices that enhance the environment and assist in the mitigation and adaption to climate can be incentivised. Different soil and crop management practices affect the flux of greenhouse gases (GHG), meaning that agricultural production can be a significant source of emissions. As a result, leveraging the mitigation potential in the agricultural sector by promoting practices known to contribute less to GHG emissions is extremely important in meeting the country's emission reduction targets and goals committed to in the Paris Agreement. Here we propose a systematic map of the evidence relating to the impact of soil and crop management of arable land in temperate regions on GHG flux, including both mineral and organic soils. Following preliminary searches and an awareness of related evidence bases we are aware that there is a suitable volume of research related to the topic to warrant systematic mapping (i.e. the evidence base is large but within the limits of that dealt with in recent systematic maps). This map will be produced using established, yet state-of-the-art methods for systematic mapping in environmental sciences and we will follow the Collaboration for Environmental Evidence (CEE) guidance and standards. During our mapping, we will search for, collate and catalogue research studies relating to the impacts of farming in temperate systems (i.e. relevant to the UK) on GHG emissions, identifying evidence for agricultural practices that mitigate against climate change and those that contribute to it. This will inform the design of reformed agricultural subsidies, enabling pubic money to be spent on activities that are the most beneficial in mitigating against climate change. The mapping will be aided by using cutting-edge machine learning, natural language processing and text-mining tools which provides an opportunity to apply these tools for the first time during the conduct of an environmental systematic map, to test their use in policy relevant reviews and to develop skills and capabilities. These technological tools will be used to support but not replace human-driven systematic mapping to increase efficiency, reduce risk and maximise legacy without affecting the rigour demanded by CEE standards (which do not currently cater for machine-driven synthesis). Additionally, an interactive visualisations platform will be produced enable users to interact with the map and select specific areas to examine in more detail. Furthermore, the development of machine learning will enable the automatic recognition of relevant newly published research so that an ongoing 'living' evidence map is created. A highly experienced review team with experts in evidence synthesis methods, agricultural policy and the application of innovative technologies will conduct the mapping. A technical advisory group will be established to support the review team with subject and methodological expertise. A representative from the UK and Devolved Administrations will be invited to join this group in order to ensure the policy relevance of the map and so that bilateral knowledge exchange can occur during its production. A larger stakeholder group will also be engaged during the project to maximise impact. Finally, all resources will be made Open Access, and the living evidence map will enable decision-makers to have access to the most up to date information to inform policies and subsidies, thus ensuring the legacy of the work after the project is completed.