青藏高原土壤碳储量及其影响因素研究进展

生态学杂志

青藏高原土壤碳储量及其影响因素研究进展

王荔^1,2,曾辉^1,5,张扬建^2,3,4,赵广^2*,陈宁^2,6,李军祥^1,2

（¹北京大学深圳研究生院，深圳 518055； ²拉萨高原生态试验站，生态系统网络观测与模拟重点实验室，中国科学院地理科学与资源研究所，北京 100101；³中国科学院青藏高原地球科学卓越创新中心，北京 100101；⁴中国科学院大学资源与环境学院，北京 100190；⁵北京大学城市与环境学院，北京 100871；⁶中国科学院大学，北京 100190）

出版日期:2019-11-10 发布日期:2019-11-10

A review of research on soil carbon storage and its influencing factors in the Tibetan Plateau.

WANG Li^1,2, ZENG Hui^1,5, ZHANG Yang-jian^2,3,4, ZHAO Guang^2*, CHEN Ning^2,6, Li Jun-xiang^1,2

(¹Peking University Shenzhen Graduate School, Shenzhen 518055, Guangdong, China; ²Lhasa Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Nature Resources Research, Chinese Academy of Sciences, Beijing 100101, China; ³Center for Excellence in Tibetan Plateau Earth Science, Chinese Academy of Sciences, Beijing 100101, China; ⁴College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China; ⁵College of Urban and Environmental Science,Peking University, Beijing 100871, China; ⁶University of Chinese Academy of Sciences, Beijing 100190, China).

Online:2019-11-10 Published:2019-11-10

摘要/Abstract

摘要： 青藏高原是全球变化的敏感区，也是泛第三极地区气候变化的启动区。青藏高原土壤碳作为生态系统碳库的重要组成部分，对生态系统碳循环过程具有非常重要的作用。目前，对青藏高原土壤碳储量的估算仍存在很大的不确定性。为此，本文综述了近30年来关于青藏高原土壤碳储量研究，比较不同研究的土壤碳储量估算结果，以固有因子和变化因子两类影响因素作为切入点，分析了土壤碳储量时空分异规律。从估算模型和方法看，CENTURY和TEM模型综合考虑了影响土壤碳储量的多种机理过程，结果可信度高于EVI、NDVI模型以及插值估算法。青藏高原草地土壤表层（0～20 cm）有机碳储量约10 Pg C（1 Pg=10¹⁵ g）。高原冻土区土壤有机碳储量（0～200 cm）约16.5 Pg C，土壤无机碳储量（0～100 cm）约14 Pg C。青藏高原土壤碳储量沿东南向西北方向逐渐降低，而关于变化因子对青藏高原土壤碳储量的作用规律还没有一致的认识。此外，采样点选择、数据源选择、估算深度以及估算方法等影响了青藏高原土壤碳储量估算结果的精确性。未来青藏高原土壤碳储量研究应建立土壤碳储量估算标准来提高结果的可比性；同时增大采样区、采样量以及采样深度并保障采样周期的时间连贯性等，有效减少土壤碳储量估算不确定性。以期更好地理解和预测未来青藏高原生态系统对气候变化的响应。

关键词: 作物空间分配模型, 东北地区, 水稻, 空间响应, 气候变化

Abstract: The Tibetan Plateau is highly sensitive to global climate change, and is the controller for regional climate in the Pan-Third Pole region. On the Tibetan Plateau, soil carbon accounts for a high proportion of the ecosystem carbon and is extremely important for ecosystem carbon cycling. However, there are still plenty of uncertainties for current soil carbon storage estimation on the Tibetan Plateau, with different estimation methods also having great discrepancies. Here, we reviewed research progress on soil carbon storage on the Tibetan Plateau during the past 30 years, and compared the results of different studies. We also analyzed the spatial and temporal variation of soil carbon storage based on two kinds of influencing factors (inherent, such as geographical factor, soil property, vegetation type; and variable, such as climate change, human activities). In terms of estimation models and methods, the process models such as CENTURY and TEM, which consider multiple processes affecting soil carbon storage, had higher accuracy compared with the EVI and NDVI models, and interpolation estimation. Averaged across different studies, soil organic carbon storage in the top 20 cm of the alpine grasslands is about 10 Pg C (1 Pg=10¹⁵ g), and that in the top 200 cm of the alpine permafrost is approximately 16.5 Pg C. Soil inorganic carbon storage in the top 100 cm of the alpine grassland is about 14 Pg C. The soil carbon storage on the Tibetan Plateau decreases gradually from southeast to northwest. The effects of variable factors on soil carbon storage varied greatly. The estimation accuracy of soil carbon storage is affected by sampling location, data source type, estimation method, and soil depth. Future studies of soil carbon storage on the Tibetan Plateau should pay attention to establishing a common standard for soil carbon storage estimation. Under the common standard, the comparability among different studies is boosted. Meanwhile, expanding sampling area and sample size, increasing sampling depth and maintaining the temporal coherence among each sampling period can efficiently abate uncertainty in soil carbon storage estimation on the Tibetan Plateau. With these improvements, our understanding on Tibetan Plateau ecosystem responses to climate change would be advanced and our prediction on its future status be more accurate.

Key words: climate change, crop spatial allocation model, rice, spatial response, Northeast China.

王荔,曾辉,张扬建,赵广,陈宁,李军祥. 青藏高原土壤碳储量及其影响因素研究进展[J]. 生态学杂志.

WANG Li, ZENG Hui, ZHANG Yang-jian, ZHAO Guang, CHEN Ning, Li Jun-xiang. A review of research on soil carbon storage and its influencing factors in the Tibetan Plateau.[J]. cje.

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