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Transient dynamics of terrestrial carbon storage: mathematical foundation and its applications
Luo, Yiqi1,2; Shi, Zheng1; Lu, Xingjie3; Xia, Jianyang4; Liang, Junyi1; Jiang, Jiang1; Wang, Ying5; Smith, Matthew J.6; Jiang, Lifen1; Ahlstrom, Anders7,8; Chen, Benito9; Hararuk, Oleksandra10; Hastings, Alan11; Hoffman, Forrest12; Medlyn, Belinda13; Niu, Shuli14; Rasmussen, Martin15; Todd-Brown, Katherine16; Wang, Ying-Ping3
2017-01-12
Source PublicationBIOGEOSCIENCES
ISSN1726-4170
Volume14Issue:1Pages:145-161
Corresponding AuthorLuo, Yiqi(yluo@ou.edu)
AbstractTerrestrial ecosystems have absorbed roughly 30% of anthropogenic CO2 emissions over the past decades, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling and experimental and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under global change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g., net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, which is the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Moreover, this and our other studies have demonstrated that one matrix equation can replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3-D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. In addition, the physical emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. Overall, this new mathematical framework offers new approaches to understanding, evaluating, diagnosing, and improving land C cycle models.
DOI10.5194/bg-14-145-2017
WOS KeywordSOIL ORGANIC-MATTER ; NONLINEAR MICROBIAL MODELS ; EARTH SYSTEM MODELS ; DATA-ASSIMILATION ; ATMOSPHERIC CO2 ; ELEVATED CO2 ; NITROGEN MINERALIZATION ; DISTRIBUTED EXPERIMENTS ; LITTER DECOMPOSITION ; GRASSLAND SOILS
Indexed BySCI
Language英语
Funding ProjectNational Science Foundation ; US Department of Homeland Security ; US Department of Agriculture through NSF[EF-0832858] ; University of Tennessee, Knoxville ; US Department of Energy[DE-SC0008270] ; US Department of Energy[DE-SC0014085] ; US National Science Foundation (NSF)[EF 1137293] ; US National Science Foundation (NSF)[OIA-1301789]
Funding OrganizationNational Science Foundation ; US Department of Homeland Security ; US Department of Agriculture through NSF ; University of Tennessee, Knoxville ; US Department of Energy ; US National Science Foundation (NSF)
WOS Research AreaEnvironmental Sciences & Ecology ; Geology
WOS SubjectEcology ; Geosciences, Multidisciplinary
WOS IDWOS:000393893500001
PublisherCOPERNICUS GESELLSCHAFT MBH
Citation statistics
Cited Times:15[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/64886
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLuo, Yiqi
Affiliation1.Univ Oklahoma, Dept Microbiol & Plant Biol, Norman, OK 73019 USA
2.Tsinghua Univ, Dept Earth Syst Sci, Beijing, Peoples R China
3.CSIRO Oceans & Atmosphere, Aspendale, Vic, Australia
4.East China Normal Univ, Sch Ecol & Environm Sci, Shanghai, Peoples R China
5.Univ Oklahoma, Dept Math, Norman, OK 73019 USA
6.Microsoft Res, Sci Computat Lab, Cambridge, England
7.Stanford Univ, Dept Earth Syst Sci, Stanford, CA 94305 USA
8.Lund Univ, Dept Phys Geog & Ecosyst Sci, Lund, Sweden
9.Univ Texas Arlington, Dept Math, Arlington, TX 76019 USA
10.McGill Univ, Dept Nat Resource Sci, Montreal, PQ, Canada
11.Univ Calif Davis, Dept Environm Sci & Policy, One Shields Ave, Davis, CA 95616 USA
12.Oak Ridge Natl Lab, Computat Earth Sci Grp, Oak Ridge, TN 37831 USA
13.Univ Western Sydney, Hawkesbury Inst Environm, Penrith, NSW 2751, Australia
14.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China
15.Imperial Coll, Dept Math, London, England
16.Pacific Northwest Natl Lab, Biol Sci Div, Richland, WA 99352 USA
Recommended Citation
GB/T 7714
Luo, Yiqi,Shi, Zheng,Lu, Xingjie,et al. Transient dynamics of terrestrial carbon storage: mathematical foundation and its applications[J]. BIOGEOSCIENCES,2017,14(1):145-161.
APA Luo, Yiqi.,Shi, Zheng.,Lu, Xingjie.,Xia, Jianyang.,Liang, Junyi.,...&Wang, Ying-Ping.(2017).Transient dynamics of terrestrial carbon storage: mathematical foundation and its applications.BIOGEOSCIENCES,14(1),145-161.
MLA Luo, Yiqi,et al."Transient dynamics of terrestrial carbon storage: mathematical foundation and its applications".BIOGEOSCIENCES 14.1(2017):145-161.
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