Drainage Canals in Southeast Asian Peatlands Increase Carbon Emissions
Drainage Canals in Southeast Asian Peatlands Increase Carbon Emissions
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DOI：
10.1029/2020av000321
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发表时间：
2021-03-01
期刊：
影响因子：
8.4
通讯作者：
Konings, Alexandra G.
中科院分区：
文献类型：
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作者：
Dadap, Nathan C.;Hoyt, Alison M.;Konings, Alexandra G.
与伐木和农业相关的排水渠使热带泥炭地的有机土壤变干，从而威胁到长期碳储存的可行性，因为分解，火灾和河流运输增加了排放量。在东南亚泥炭地，经历了几十年的土地利用变化，排水渠的确切范围和空间分布是未知的。这阻碍了对排水、土地利用和碳排放之间关系的区域规模调查。在这里，我们使用高分辨率卫星图像和卷积神经网络创建了第一个排水渠区域地图。我们发现，排水是不可避免的，发生在至少65%的泥炭地和所有的土地利用类型。虽然以前的泥炭地碳排放量的估计依赖于土地利用作为排水的代理，我们的地图显示，在土地利用类型内排水密度有很大的变化。沉降率是3.2倍，在密集排水区比在非排水区，突出排水调解泥炭沉降的核心作用。占排水渠被发现，以提高30%的沉降预测模型，这表明运河包含的信息沉降不单独捕获的土地利用。因此，我们的数据集可用于改善泥炭地的沉降和相关的碳排放预测，并用于水文恢复的目标区域。
Drainage canals associated with logging and agriculture dry out organic soils in tropical peatlands, thereby threatening the viability of long-term carbon stores due to increased emissions from decomposition, fire, and fluvial transport. In Southeast Asian peatlands, which have experienced decades of land use change, the exact extent and spatial distribution of drainage canals are unknown. This has prevented regional-scale investigation of the relationships between drainage, land use, and carbon emissions. Here, we create the first regional map of drainage canals using high resolution satellite imagery and a convolutional neural network. We find that drainage is widespread-occurring in at least 65% of peatlands and across all land use types. Although previous estimates of peatland carbon emissions have relied on land use as a proxy for drainage, our maps show substantial variation in drainage density within land use types. Subsidence rates are 3.2 times larger in intensively drained areas than in non-drained areas, highlighting the central role of drainage in mediating peat subsidence. Accounting for drainage canals was found to improve a subsidence prediction model by 30%, suggesting that canals contain information about subsidence not captured by land use alone. Thus, our data set can be used to improve subsidence and associated carbon emissions predictions in peatlands, and to target areas for hydrologic restoration.