Rafaela Ferraz Molina , Waldssimiler Teixeira de Mattos , Sandra Furlan Nogueira , Cristiano Alberto de Andrade , Lucas Ferreira Penteado , Cristina Maria Pacheco Barbosa , Luciana Gerdes
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引用次数: 0
Abstract
In Brazil, land use changes, particularly in the Atlantic Forest biome, significantly impact soil carbon dynamics. Conservation practices, such as no-till farming and integrated systems, can mitigate GHG emissions by enhancing soil organic carbon (SOC) sequestration. This study aims to assess changes in SOCS resulting from three distinct LUC pathways: from natural vegetation (NV) to extensive pasture (EP); from EP to a crop-livestock-forest integration system (iCLF); and from extensive pasture to no-till soybean monoculture (NT). Areas with similar soil types (Oxisol) but different land uses were evaluated: NV, EP, iCLF, and NT. SOC stocks, C-accumulation rates, and isotopic composition (δ13C) were analyzed. The conversion of NV to EP increased carbon stocks in the 0–30 cm layer, with δ13C indicating pasture contribution. The transition from EP to iCLF further promote SOC accumulation across all depths, with δ13C suggesting contributions from both C3 and C4 plants. In contrast, converting EP to NT did not significantly affect SOC stocks. The annual SOC accumulation rates (0–100 cm) were 0.34, 5.38, and 2.35 Mg C ha−1 year−1 for NV to EP, EP to iCLF, and EP to NT, respectively. The corresponding SOC change factors were 1.24, 1.52, and 1.03. These findings highlight the potential of integrated systems to enhance soil carbon sequestration compared to conventional pasture and no-till practices.
期刊介绍:
Agriculture, Ecosystems and Environment publishes scientific articles dealing with the interface between agroecosystems and the natural environment, specifically how agriculture influences the environment and how changes in that environment impact agroecosystems. Preference is given to papers from experimental and observational research at the field, system or landscape level, from studies that enhance our understanding of processes using data-based biophysical modelling, and papers that bridge scientific disciplines and integrate knowledge. All papers should be placed in an international or wide comparative context.