编号：CDUT-2022-22

标题：Spatial and temporal patterns of global soil heterotrophic respiration in terrestrial ecosystems

入藏号：WOS:000531862700001

中国科学院文献情报中心期刊分区：地学1区/TOP

本校作者：唐晓鹿，范少辉，杜满义，张文杰，高思聪，刘世宾，陈果，余振，杨武年

来源出版物：EARTH SYSTEM SCIENCE DATA  卷:12  期:2  页:1037-1051

出版年：2020

第一地址： 成都理工大学

关键词：土壤异养呼吸，时空变异，随机森林，驱动因子

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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 Pg C a−1 from 1980 to 2016,with a significantly increasing trend of 0.036 ± 0.007 Pg C 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. The dataset is publicly available at https://doi.org/10.6084/m9.figshare.8882567 (Tang et al., 2019a).

文章链接地址：https://essd.copernicus.org/articles/12/1037/2020/