青藏高原3m深度土壤碳库的格点数据（2019）

本数据集是基于青藏高原多年冻土分布区1114个样点的土壤调查数据，重点考虑了古气候在估算青藏高原土壤碳储量中的重要作用，在综合了气候（古气候和现代气候条件）、植被、土壤（土层厚度和土壤理化属性等）和地形等因素后，通过机器学习算法重新评估得到的青藏高原3m深度土壤碳储量。结果集表明当前陆地生态系统模型普遍低估了青藏高原冻土碳库大小，模型中缺乏对古气候影响的考虑是导致模拟偏差的重要原因。因此，未来模型模拟土壤碳循环应该将古气候的作用考虑在内。

This dataset is constructed using soil survey data from 1114 sampling sites across the permafrost distribution regions of the Qinghai-Tibet Plateau (QTP). With a focus on the critical role of paleoclimate in estimating soil carbon stocks of the QTP, we re-estimated the 3-meter-depth soil carbon stocks of the plateau via machine learning algorithms after incorporating multiple factors including climate (both paleoclimate and modern climatic conditions), vegetation, soil properties (e.g., soil layer thickness, soil physical and chemical attributes) and topography. The results show that current terrestrial ecosystem models generally underestimate the size of the permafrost carbon pool on the QTP, and the lack of consideration for paleoclimate impacts in these models is a major cause of simulation biases. Therefore, future soil carbon cycle simulations should incorporate the effects of paleoclimate.