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Large-scale soil organic carbon mapping based on multivariate modelling: The case of grasslands on the Loess Plateau
Land Degradation & Development ( IF 4.7 ) Pub Date : 2017-11-21 22:06:39 , DOI: 10.1002/ldr.2833
Yinyin Wang 1, 2 , Lei Deng 3 , Gaolin Wu 3 , Kaibo Wang 4 , Zhouping Shangguan 1, 2
Affiliation  

The Loess Plateau is considered one of the world's regions with severe soil erosion. Grasslands are widely distributed on the Loess Plateau, accounting for approximately 40% of the total area. Soil organic carbon (SOC) plays an important role in the terrestrial carbon cycle in this region. We compiled more than 1,000 measurements of plant biomass and SOC content derived from 223 field studies of grasslands on the Loess Plateau. Combined with meteorological factors (precipitation and air temperature) and the photosynthetically active radiation factor, the topsoil SOC contents of grasslands were predicted using the random forest (RF) regression algorithm. Predicted grassland SOC content (1.70–40.34 g kg−1) decreased from the southeast to the northwest of the Loess Plateau, with approximately 1/5 of the grassland exhibiting values lower than 4 g kg−1. Observed SOC content was positively correlated with observed plant biomass, and for predicted values, this correlation was strong in the desert steppe and the steppe desert of rocky mountains. Air temperature was the most important factor affecting SOC contents in the RF model. Moreover, the residual error of observations and predictions increased as the grazing intensity varied from none to very severe in the temperate desert steppe, and this RF model may not perform well in plains. The use of the RF model for SOC prediction in Loess Plateau grasslands provides a reference for C storage studies in arid and semi-arid regions, and aboveground biomass and temperature should receive more attention due to increasing C sequestration.

中文翻译:

基于多元建模的土壤有机碳大规模制图:以黄土高原草地为例

黄土高原被认为是世界土壤侵蚀严重的地区之一。黄土高原上草原分布广泛,约占总面积的40%。土壤有机碳(SOC)在该地区的陆地碳循环中起着重要作用。我们对来自黄土高原地区223处草地的田间研究得出的植物生物量和SOC含量进行了1000多次测量。结合气象因素(降水,气温)和光合有效辐射因子,采用随机森林(RF)回归算法对草原表层土壤有机碳含量进行了预测。预测的草地SOC含量(1.70–40.34 g kg -1)从黄土高原的东南部到西北部减少,大约1/5的草地显示出低于4 g kg -1的值。观察到的SOC含量与观察到的植物生物量呈正相关,对于预测值,这种相关性在沙漠草原和落基山草原沙漠中很强。空气温度是影响RF模型中SOC含量的最重要因素。此外,随着放牧强度在温带荒漠草原上的放牧强度从无变化到非常严重,观测和预测的残留误差增加,并且该RF模型在平原上的表现可能不佳。利用RF模型预测黄土高原草地的SOC,为干旱和半干旱地区的碳储量研究提供了参考,由于碳固存增加,地上生物量和温度应引起更多关注。
更新日期:2017-11-22
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