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Soil carbon sequestration potential with enhanced vegetation cover over NSW

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Research Data Australia2025-12-20 收录
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https://researchdata.edu.au/soil-carbon-sequestration-cover-nsw/3833992
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Digital soil maps of soil organic carbon (SOC) sequestration potential resulting from hypothetical increases in long-term vegetation cover are presented at 100-m resolution across NSW. This increase could be achieved by strategies such as revegetation, grazing management or crop residue management. By applying a 10% relative increase in vegetation cover, a mean state-wide potential increase of 5.4 t/ha over the 0-30 cm depth interval was modelled. Assuming a 20-year period of re-equilibration, this equates to an average SOC increase of 0.27 t/ha/yr.\r\nMaps and data are also derived using a 10% absolute increase in vegetation cover and a maximum potential increase in vegetation cover, being that of geographically equivalent nature reserves. The outputs can be used to identify locations of highest sequestration potential and thereby help prioritise areas and inform decisions on sequestration programs. They can provide approximate estimates of equivalent CO2 emissions avoided within the soil from these vegetation cover increases. The results could encourage formal incorporation of soil carbon sequestration in programs under Australia’s Emission Reduction Fund. \r\nThe work was undertaken as part of the NSW Government's Primary Industries Productivity and Abatement Program (PIPAP). Methods and results are fully reported in Gray et al. (2021) as provided here. \r\n

本研究提供了新南威尔士州(NSW)范围内分辨率为100米的数字土壤图谱,该图谱表征了长期植被覆盖假设性提升所带来的土壤有机碳(SOC)固碳潜力。此类植被覆盖提升可通过植被恢复、放牧管理或作物残茬管理等策略实现。通过设置10%的相对植被覆盖提升量,模型模拟得到全州0-30厘米土层的平均固碳潜力提升量为5.4吨/公顷。假设土壤碳库需要20年达到重新平衡,这相当于年均土壤有机碳提升量为0.27吨/公顷/年。 本研究还基于10%的绝对植被覆盖提升量,以及与研究区域地理条件等效的自然保护区植被覆盖最大潜在提升量,生成了对应的图谱与数据集。该输出结果可用于识别固碳潜力最高的区域,从而助力优先确定重点区域,并为固碳项目的决策提供参考依据。同时,该结果可估算植被覆盖提升所带来的土壤等效减排二氧化碳量的近似值。本研究结果可推动土壤碳固存正式纳入澳大利亚《减排基金(Emission Reduction Fund)》框架下的相关项目。 本研究系新南威尔士州政府“第一产业生产力与减排项目(Primary Industries Productivity and Abatement Program, PIPAP)”的组成部分。如本文所示,研究方法与结果已在Gray等人(2021)的研究中完整披露。
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