Spatially-explicit estimate of soil nitrogen stock and its implication for land model across Tibetan alpine permafrost region
作 者：Kou D, Ding JZ, Li F, Wei N, Fang K, Yang GB, Zhang BB, Liu L, Qin SQ, Chen YL, Xia JY, Yang YH*
影响因子:4.61
刊物名称:Science of The Total Environment
出版年份:2019
卷:650期: 页码:1795-1804
文章摘要:Permafrostsoils store a large amount of nitrogen (N) which could be activated under the continuous climate warming. However, compared with carbon (C) stock, little is known about the size andspatial distributionof permafrost N stock. By combining measurements from 519 pedons with twomachine learningmodels (supporting vector machine (SVM) and random forest (RF)), we estimated the size and spatial distribution of N stock across the Tibetan alpine permafrost region. We then compared these spatially-explicit N estimates with simulated N stocks from the Community Land Model (CLM). We found that N density (N amount per area) in the top three meters was 1.58 kg N m²(interquartile range: 1.40–1.76) across the study area, constituting a total of 1802 Tg N (interquartile range: 1605–2008), decreasing from the southeast to the northwest of the plateau. N stored below 1m accounted for 48% of the total N stock in the top three meters. CLM4.5 significantly underestimated the N stock on the Tibetan Plateau, primarily in areas with arid/semi-arid climate. The process of biological N fixation played a key role in the underestimation of N stock prediction. Overall, our study highlights that it is imperative to improve the simulation of N processes and permafrost N stocks in land models to better predict ecological consequences induced by rapid and widespread permafrost degradation.