Abstract
BackgroundReducing greenhouse gas emissions is a vital step in limiting climate change and meeting the goals outlined in the COP 21 Paris Agreement of 2015. Studies have suggested that agriculture accounts for around 11% of total greenhouse gas emissions and the industry has a significant role in meeting international and national climate change reduction objectives. However, there is currently little consensus on the mechanisms that regulate the production and assimilation of greenhouse gases in arable land and the practical factors that affect the process. Practical advice for farmers is often overly general, and models based on the amount of nitrogen fertiliser applied, for example, are used despite a lack of knowledge of how local conditions affect the process, such as the importance of humus content and soil types. Here, we propose a systematic map of the evidence relating to the impact on greenhouse gas flux from the agricultural management of arable land in temperate regions.MethodsUsing established methods for systematic mapping in environmental sciences we will search for, collate and catalogue research studies relating to the impacts of farming in temperate systems on greenhouse gas emissions. We will search 6 bibliographic databases using a tested search string, and will hand search a web-based search engine and a list of organisational web sites. Furthermore, evidence will be sought from key stakeholders. Search results will then be screened for relevance at title, abstract and full text levels according to a predefined set of eligibility criteria. Consistency checking will be employed to ensure the criteria are being applied accurately and consistently. Relevant studies will then be subjected to coding and meta-data extraction, which will be used to populate a systematic map database describing each relevant study’s settings, methods and measured outcomes. The mapping process will help to identify knowledge gaps (subjects lacking in evidence warranting further primary research) and knowledge clusters (subjects with sufficient studies to allow a useful full systematic review), and will highlight best and suboptimal research methods.
Highlights
Reducing greenhouse gas emissions is a vital step in limiting climate change and meeting the goals outlined in the COP 21 Paris Agreement of 2015
Reducing greenhouse gas emissions is a vital step in attempting to reduce climate change and meet the goals outlined in the Paris Agreement resulting from the COP21 in 2015
Studies have suggested that agriculture accounts for around 11% of total greenhouse gas emissions [1] and the industry has a significant role in meeting international and national climate change reduction objectives (e.g. England and Wales’s National Union of Farmers’ goal of reaching net zero greenhouse gas emissions across the agriculture sector by 2040 [2] and targets set for the agricultural sector in The Scottish Government’s Climate Change Plan [3])
Summary
The review will follow the Collaboration for Environmental Evidence Guidelines and Standards for Evidence Synthesis in Environmental Management [12] and it conforms to ROSES reporting standards [13] (see Additional file 1). Eligible intervention(s): Any farmland management practice applied to the crop or the soil, and that could be applied to entire fields This would include, for example: fertilisation; addition of amendments (e.g. lime); different crop rotations; soil tillage. Information regarding possible sources of heterogeneity will be extracted (in the form of metadata and coding) from across the eligible articles Such variables will include: climate zone; fertiliser type; fertiliser quantity; presence of soil drainage; soil texture classification; soil physical characteristics; crop type; above-ground biomass; concurrent land management; land management history; and organic matter content. Knowledge gap and cluster identification strategy A series of heat maps (cross tabulations of key descriptors, e.g. interventions and outcomes, interventions and populations/settings) will be produced These will be compared with one another and the differences between groupings to systematically identify knowledge clusters (subtopics that are well-represented by research studies) and knowledge gaps (subtopics that are comparatively under-represented by research studies). We will aim to present the results using the EviAtlas tool [19], which will allow studies to be presented via location of the study and make use of dropdown filters so that studies relating to different soil types, interventions and GHG emissions can be identified
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