Responses of soil greenhouse gas fluxes to land management in forests and grasslands: A global meta-analysis.

Land management practices significantly influence soil greenhouse gas (GHG) emissions. Despite individual measurements of the impacts of forest and grassland ecosystem management practices (FGEM) on GHG emissions, a comprehensive global-scale synthesis and comparison remain absent. In this study, a global meta-analysis was conducted to analyze the responses of three key soil GHGs, including carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), to various FGEM, including forest burning (FB) and thinning (FT), grassland grazing (GG), fencing (GF), and mowing (GM) based on 1643 observations from 317 individual studies. Moderator factors and the underlying mechanisms driving these responses were also explored. Results revealed that in managed forests, FB significantly reduced soil CO2 and N2O emissions, while FT decreased soil CH4 uptake capacity without affecting CO2 and N2O emissions. In managed grasslands, GG reduced soil CO2 emission, while GF increased it; both had neutral impacts on soil CH4 and N2O fluxes. GM did not affect GHG fluxes. Overall, forest management decreased soil CO2 emission and CH4 uptake capacity, whereas grassland management had a neutral effect on soil GHG fluxes. Temporal analysis revealed diminishing effects of FGEM on CO2 emissions over the long term. Soil CH4 uptake exhibited divergent responses over time, and soil N2O emissions remained relatively constant. Compared to managed grassland, soil GHG fluxes in managed forests were more sensitive to aridity conditions, with forest management generally restraining soil CO2 and N2O emissions and CH4 uptake in humid regions. Meta-regression analysis highlighted carbon content, soil temperature, and soil moisture as primary drives of changes in soil CO2 and CH4 fluxes, while soil N2O fluxes were more susceptible to soil organic carbon and microbial biomass nitrogen. The dependence of soil GHG fluxes on climate zones and management duration should be integrated into Earth system models for more accurate predictions of the impact of human interference.