文献类型：期刊文献

英文题名：Spatial and temporal patterns of global soil heterotrophic respiration in terrestrial ecosystems

作者：Tang, Xiaolu[1,2] Fan, Shaohui[3] Du, Manyi[4] Zhang, Wenjie[5,6] Gao, Sicong[6] Liu, Shibin[1] Chen, Guo[1] Yu, Zhen[7,8] Yang, Wunian[1]

第一作者：Tang, Xiaolu

通信作者：Yang, WN[1];Fan, SH[2]|[a000544a2d11f077bd3d5]范少辉;

机构：[1]Chengdu Univ Technol, Coll Earth Sci, Chengdu 610059, Peoples R China;[2]Chengdu Univ Technol, State Environm Protect Key Lab Synerget Control &, Chengdu 610059, Peoples R China;[3]Int Ctr Bamboo & Rattan, Key Lab Bamboo & Rattan, Beijing 100102, Peoples R China;[4]Chinese Acad Forestry, Expt Ctr Forestry North China, Beijing 102300, Peoples R China;[5]Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China;[6]Univ Technol Sydney, Sch Life Sci, Ultimo, NSW 2007, Australia;[7]Nanjing Univ Informat Sci & Technol, Sch Appl Meteorol, Nanjing 210044, Peoples R China;[8]Iowa State Univ, Dept Ecol Evolut & Organismal Biol, Ames, IA 50011 USA

年份：2020

卷号：12

期号：2

起止页码：1037-1051

外文期刊名：EARTH SYSTEM SCIENCE DATA

收录：;Scopus(收录号：2-s2.0-85084838453);WOS:【SCI-EXPANDED(收录号:WOS:000531862700001)】；

基金：This research was supported by the National Natural Science Foundation of China (grant nos. 31800365 and 41671432); Fundamental Research Funds of International Centre for Bamboo and Rattan (grant nos. 1632017003 and 1632018003); Fundamental Research Funds of Public Welfare of Central Institutes (grant no. CAFYBB2018MA002); the State Key Development Program of National "Thirteenth Five-year" plan of China (grant no. 2018YFD0600105); Innovation funding of Remote Sensing Science and Technology of Chengdu University of Technology (grant no. KYTD201501); Starting Funding and Foundation for University Key Teacher of Chengdu University of Technology (grant nos. 10912-2018KYQD-06910 and 10912-2019JX-06910); and Open Funding from Key Laboratory of Geoscience Spatial Information Technology of the Ministry of Land and Resources (Chengdu University of Technology).

语种：英文

摘要：Soil heterotrophic respiration (RH) is one of the largest and most uncertain components of the terrestrial carbon cycle, directly reflecting carbon loss from soils to the atmosphere. However, high variations and uncertainties of RH existing in global carbon cycling models require RH estimates from different angles, e.g., a data-driven angle. To fill this knowledge gap, this study applied a Random Forest (RF) algorithm (a machine learning approach) to (1) develop a globally gridded RH dataset and (2) investigate its spatial and temporal patterns from 1980 to 2016 at the global scale by linking field observations from the Global Soil Respiration Database and global environmental drivers (temperature, precipitation, soil water content, etc.). Finally, a globally gridded RH dataset was developed covering from 1980 to 2016 with a spatial resolution of half a degree and a temporal resolution of 1 year. Globally, the average annual RH was 57.2 +/- 0.6 PgC a(-1) from 1980 to 2016, with a significantly increasing trend of 0.036 +/- 0.007 PgC a(-2). However, the temporal trend of the carbon loss from RH varied in climate zones, and RH showed a significant and increasing trend in boreal and temperate areas. In contrast, such a trend was absent in tropical regions. Temperature-driven RH dominated 39% of global land and was primarily distributed at high-latitude areas. The areas dominated by precipitation and soil water content were mainly semiarid and tropical areas, accounting for 36% and 25% of global land area, respectively, suggesting variations in the dominance of environmental controls on the spatial patterns of RH. The developed globally gridded RH dataset will further aid in the understanding of the mechanisms of global soil carbon dynamics, serving as a benchmark to constrain terrestrial biogeochemical models.2019a