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The permafrost carbon inventory on the Tibetan Plateau: a new evaluation using deep sediment cores

机译:青藏高原的多年冻土碳库:使用深部沉积物芯的新评估

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The permafrost organic carbon (OC) stock is of global significance because of its large pool size and the potential positive feedback to climate warming. However, due to the lack of systematic field observations and appropriate upscaling methodologies, substantial uncertainties exist in the permafrost OC budget, which limits our understanding of the fate of frozen carbon in a warming world. In particular, the lack of comprehensive estimates of OC stocks across alpine permafrost means that current knowledge on this issue remains incomplete. Here, we evaluated the pool size and spatial variations of permafrost OC stock to 3m depth on the Tibetan Plateau by combining systematic measurements from a substantial number of pedons (i.e. 342 three-metre-deep cores and 177 50-cm-deep pits) with a machine learning technique (i.e. support vector machine, SVM). We also quantified uncertainties in permafrost carbon budget by conducting Monte Carlo simulations. Our results revealed that the combination of systematic measurements with the SVM model allowed spatially explicit estimates to be made. The OC density (OC amount per unit area, OCD) exhibited a decreasing trend from the south-eastern to the north-western plateau, with the exception that OCD in the swamp meadow was substantially higher than that in surrounding regions. Our results also demonstrated that Tibetan permafrost stored a large amount of OC in the top 3m, with the median OC pool size being 15.31 Pg C (interquartile range: 13.03-17.77Pg C). 44% of OC occurred in deep layers (i.e. 100-300cm), close to the proportion observed across the northern circumpolar permafrost region. The large carbon pool size together with significant permafrost thawing suggests a risk of carbon emissions and positive climate feedback across the Tibetan alpine permafrost region.
机译:永久冻土有机碳(OC)库由于其巨大的库规模以及对气候变暖的潜在积极反馈而具有全球意义。但是,由于缺乏系统的现场观测和适当的放大方法,多年冻土超滤预算中存在大量不确定性,这限制了我们对变暖世界中冷冻碳命运的了解。尤其是,缺乏对整个高山多年冻土地区OC储量的综合估计,这意味着当前关于此问题的知识仍然不完整。在这里,我们通过结合大量脚架(即342个三米深的岩心和177个50cm深的矿坑)的系统测量值,评估了青藏高原多年冻土OC储量到3m深度的库大小和空间变化,机器学习技术(即支持向量机,SVM)。通过进行蒙特卡洛模拟,我们还量化了多年冻土碳收支的不确定性。我们的结果表明,系统测量值与SVM模型的结合使得可以进行空间上明确的估计。 OC密度(每单位面积的OC量,OCD)从东南高原到西北高原呈下降趋势,但沼泽草甸的OCD明显高于周围地区。我们的结果还表明,西藏多年冻土层在前3m储藏了大量的OC,OC池中位数为15.31 Pg C(四分位数范围:13.03-17.77Pg C)。 OC的44%发生在较深的层(即100-300cm),接近于北部环极多年冻土地区的比例。较大的碳库规模以及显着的多年冻土融化表明藏族高山多年冻土地区存在碳排放和积极的气候反馈的风险。

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