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

Lead Research Organisation: Imperial College London
Department Name: The Centre for Environmental Policy

Abstract

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.

Planned Impact

The foremost impact from this project will be that best available information regarding the impact of different arable land management practices on greenhouse gas flux will be available to decision makers, in order to inform the revision of agricultural subsidies. Working with stakeholders and through reviewing the scoping work of NERC's Environmental Evidence for the Future the topic has been identified of high importance and relevance in the context of the UK's decision to leave the EU.

Impact will be assured not only through addressing a question of high importance to policy and practice decision makers but as a result of engagement throughout the project. A representative from the UK and Devolved Administrations will be invited to join the Technical Advisory Group to which the Review Team will report regularly. This will ensure the policy relevance of the map and enable bilateral knowledge exchange can occur during its production which will maximise the impact of the work.

The outputs of the project will also support the impact of the work. The report of the Systematic Map (SM) will be as an Open Access paper in Environmental Evidence, so that access to all who are interested is not restricted by paywalls. Additionally the creation of a briefing note, making use of infographics, to help the communication of the work to a wider audience. The SM database will be provided as an Open Access document and shared with representatives of the UK and Devolved Administrations, meaning that the results of the work can be used in decision making after the project has been completed. This, along with the creation of an interactive GIS map of the results and a 'living' evidence map that will automatically identify newly published relevant work, will enable the map to stay up to date so decision makers can have access to current information in order to inform polices, ensuring continued impact and a legacy after the project is completed.

Additionally a range of stakeholders will be engaged in the mapping activities in order to maximise the impact of the work. Stakeholder will be engaged through discussing and developing the proposal with them and requesting their input for relevant academic and grey literature, this will help to increase the saliency and legitimacy of the work which has been shown to improve impact with stakeholders. We will also request and respond to user feedback in the development of the report, GIS map and online interface, this will help to ensure that the resource produced are as applicable as possible to encourage widespread use and adoption. Stakeholders will also be invited to discuss the implications of the findings of the SM for research, policy and practice so that these are as comprehensive as possible. Together this will not only ensure that the map is of policy and practice relevancy but that the outputs can provide impacts to decision makers.

Finally, engagement with the IPCC through the inclusion of senior scientists on the IPCC Working Group on Mitigation of Climate Change will enable bilateral knowledge exchange, both on the topic of land management and GHG emissions and also on the application of systematic methods. This will inform the IPCC's understanding of the potential use of systematic mapping to their activities and help to inform future practices.

Publications

10 25 50
 
Description Using established methods for systematic mapping in environmental sciences we searched for, collated and catalogued research studies relating to the impacts of farming in temperate systems on greenhouse gas emissions. We searched 7 bibliographic databases using a tested search string, and handed search a web-based search engine and a list of organisational web sites. Search results were then be screened for relevance at title, abstract and full text levels according to a predefined set of eligibility criteria. Relevant studies were then subjected to coding and meta-data extraction, which were used to populate a systematic map database describing each relevant study's settings, methods and measured outcomes. A total of 38,825 potentially relevant records were identi?ed across all resources searched. A total of 25,683 unique records was screened for eligibility, with 347 eligible records following full text screening. The ?nal systematic map database contains 538 studies from 357 articles. A total of 296 out of 538 studies examined multiple interventions together. The top three most frequently studied single intervention types were chemical fertiliser (n = 100), tillage (n = 70), and organic fertiliser (n = 30). Across all intervention types, the top three most frequently studied were: 1) chemical fertiliser (n = 312); 2) organic fertiliser (n = 176); 3) tillage (n = 158); 4) nitri?cation inhibitor (n = 72); and, 5) cover crops (n = 62). The most common measures green house gas was Nitrous oxide (n= 441) Carbon dioxide (n=208) Methane (n=106). the total number of measured green house gases across all investigated interventions shows the prominence of nitrous oxide in research on fertilisers and nitri?cation inhibition.
Exploitation Route The map highlights knowledge clusters and gaps. The knowledge clusters identify where further meta-analysis could be undertaken, i.e. nitrous oxide from chemical and organic fertilisers. The knowledge gaps identify where further research would be the most beneficial e.g. cover crops, crop rotation and biochar application.
Sectors Agriculture, Food and Drink,Environment,Government, Democracy and Justice

URL https://farming4climate.github.io/
 
Description Canadian Centre for Evidence-Based Conservation, Carleton University 
Organisation Carleton University
Country Canada 
Sector Academic/University 
PI Contribution Imperial College and Carleton University are working together to deliver a systematic map on GHG emissions from arable agriculture
Collaborator Contribution Imperial College and Carleton University are working together to deliver a systematic map on GHG emissions from arable agriculture
Impact A systeramtic map protocol with full systeamtic map to follow early next year
Start Year 2019
 
Description The Stockholm Environment Institute and The Eppi Centre, UCL 
Organisation Stockholm Environment Institute (SEI)
Country Sweden 
Sector Academic/University 
PI Contribution Imperial College, The Stockholm Environment Institute and the Eppi centre have been working together to investigate the use of machine learning in the delivery of systematic maps. Imperial has been using experience of applying systematic approaches to provide input into how machine learning could be applied and we are coordinating its use in the systematic map of GHG emissions
Collaborator Contribution The Stockholm Environment Institute and the Eppi centre are using their expertise in machine learning to develop tools and approaches that can be applied in the systematic map in order to test appropriability and value
Impact In progress
Start Year 2019
 
Description The Stockholm Environment Institute and The Eppi Centre, UCL 
Organisation University College London
Country United Kingdom 
Sector Academic/University 
PI Contribution Imperial College, The Stockholm Environment Institute and the Eppi centre have been working together to investigate the use of machine learning in the delivery of systematic maps. Imperial has been using experience of applying systematic approaches to provide input into how machine learning could be applied and we are coordinating its use in the systematic map of GHG emissions
Collaborator Contribution The Stockholm Environment Institute and the Eppi centre are using their expertise in machine learning to develop tools and approaches that can be applied in the systematic map in order to test appropriability and value
Impact In progress
Start Year 2019