| Abstrakt: |
Background: Grasslands are essential for providing vital resources in the livestock sector and delivering invaluable ecosystem services such as biodiversity and soil carbon (C) sequestration. Despite their critical importance, these ecosystems face escalating threats from human disturbances, human degradation, and climate change, compromising their ability to effectively stock C. Restoring degraded grasslands emerges as a pragmatic and cost-effective approach to tackling climate change. However, the successful implementation of grassland management toward this goal, faces significant challenges. A systematic mapping approach will help to compile a comprehensive global inventory of studies investigating the impact of differing grassland management practices on soil carbon. In addition, the potential for trade-offs with other greenhouse gas emissions further underlines the value of a systematic assessment. This approach aims to identify knowledge clusters (i.e., well-represented subtopics that are amenable to full synthesis) for potential systematic reviews and pinpoint knowledge gaps requiring further primary research efforts, all contributing to a better understanding of the evidence surrounding this topic. Methods: Following systematic evidence synthesis standards, we developed the question to address in the systematic map protocol using the PICO framework. We established a preliminary search string by combining search terms for the Population (Grasslands), Intervention (management) and Outcome (soil carbon) categories, as well as with one additional group (Study types—to focus on farm and field experiments). We will conduct a comprehensive literature search of relevant peer-reviewed and grey literature using Web of Science, Scopus, CABI platforms, Google Scholar, and specialised websites (e.g., Agrotrop). Searches will be conducted in the English, Spanish, Portuguese, French, German, and Mongolian languages, as per the linguistic capabilities of the research team. The comprehensiveness of the search will be assessed by comparing the literature collected to a test-list of forty relevant articles. The repeatability of the literature screening process will be ensured by a list of inclusion/exclusion criteria and inter-reviewer consistency statistical tests. Data extraction will be organised into four complementary sections (article information, PICO categories, study characteristics, measurable parameters), on which we will perform queries to produce the tables, figures and evidence maps that will compose the systematic map. The results will identify and describe knowledge gaps and clusters. [ABSTRACT FROM AUTHOR] |
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