Controls and variability of soil respiration temperature sensitivity across China

被引:9
|
作者
Yang, Zhihan [1 ,2 ]
Luo, Xinrui [2 ]
Shi, Yuehong [2 ]
Zhou, Tao [2 ]
Luo, Ke [2 ]
Lai, Yunsen [2 ]
Yu, Peng [2 ]
Liu, Liang [2 ]
Olchev, Alexander [3 ]
Bond-Lamberty, Ben [4 ]
Hao, Dalei [5 ]
Jian, Jinshi [6 ]
Fan, Shaohui [7 ]
Cai, Chunju [7 ]
Tang, Xiaolu [1 ,8 ]
机构
[1] Chengdu Univ Technol, State Key Lab Geohazard Prevent & Geoenvironm Prot, Chengdu 610059, Peoples R China
[2] Chengdu Univ Technol, Coll Earth Sci, Chengdu 610059, Sichuan, Peoples R China
[3] Lomonosov Moscow State Univ, Fac Geog, Dept Meteorol & Climatol, GSP 1, Moscow 119991, Russia
[4] Univ Maryland, Joint Global Change Res Inst, Pacific Northwest Natl Lab, 5825 Univ Res Court,Suite 3500, College Pk, MD 20740 USA
[5] Pacific Northwest Natl Lab, Atmospher Sci & Global Change Div, Richland, WA 99352 USA
[6] Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess Pl, Yangling 712100, Peoples R China
[7] Int Ctr Bamboo & Rattan, Key Lab Bamboo & Rattan, Beijing 100102, Peoples R China
[8] Chengdu Univ Technol, Coll Ecol & Environm, Chengdu 610059, Sichuan, Peoples R China
基金
美国国家科学基金会;
关键词
Soil respiration; Temperature sensitivity; Soil organic carbon; Vegetation activity; FOREST ECOSYSTEMS; HETEROTROPHIC RESPIRATION; CARBON; CLIMATE; VEGETATION; ROOTS; PRECIPITATION; FEEDBACKS; PATTERNS; DATABASE;
D O I
10.1016/j.scitotenv.2023.161974
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Understanding the temperature sensitivity (Q10) of soil respiration is critical for benchmarking the potential intensity of regional and global terrestrial soil carbon fluxes-climate feedbacks. Although field observations have demonstrated the strong spatial heterogeneity of Q10, a significant knowledge gap still exists regarding to the factors driving spatial and temporal variabilities of Q10 at regional scales. Therefore, we used a machine learning approach to predict Q10 from 1994 to 2016 with a spatial resolution of 1 km across China from 515 field observations at 5 cm soil depth using climate, soil and vegetation variables. Predicted Q10 varied from 1.54 to 4.17, with an area-weighted average of 2.52. There was no significant temporal trend for Q10 (p = 0.32), but annual vegetation production (indicated by normalized difference vegetation index, NDVI) was positively correlated to it (p < 0.01). Spatially, soil organic car-bon (SOC) was the most important driving factor in 62 % of the land area across China, and varied greatly, demonstrat-ing soil controls on the spatial pattern of Q10. These findings highlighted different environmental controls on the spatial and temporal pattern of soil respiration Q10, which should be considered to improve global biogeochemical models used to predict the spatial and temporal patterns of soil carbon fluxes to ongoing climate change.
引用
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页数:9
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