Transient dynamics of terrestrial carbon storage: Mathematical foundation and numeric examples

Luo, Yiqi; Shi, Zheng; Lu, Xingjie; Xia, Jianyang; Liang, Junyi; Wang, Ying; Smith, Matthew J.; Jiang, Lifen; Ahlstrom, Anders; Chen, Benito; Hararuk, Oleksandra; Hastings, Alan; Hoffman, Forrest; Medlyn, Belinda; Niu, Shuli; Rasmussen, Martin; Todd-Brown, Katherine; Wang, Ying -Ping

doi:10.5194/bg-2016-377

Title: Transient dynamics of terrestrial carbon storage: Mathematical foundation and numeric examples

Full Record
Other Related Research

Abstract

Terrestrial ecosystems absorb roughly 30% of anthropogenic CO₂ emissions since preindustrial era, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling, experimental, and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under climate 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, 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 ofmore »« less

Authors:

Luo, Yiqi ^[1]; Shi, Zheng ^[2]; Lu, Xingjie ^[3]; Xia, Jianyang ^[4]; Liang, Junyi ^[2]; Wang, Ying ^[2]; Smith, Matthew J. ^[5]; Jiang, Lifen ^[2]; Ahlstrom, Anders ^[6]; Chen, Benito ^[7]; Hararuk, Oleksandra ^[8]; Hastings, Alan ^[9]; Hoffman, Forrest ^[10]; Medlyn, Belinda ^[11]; Niu, Shuli ^[12]; Rasmussen, Martin ^[13];

^[14]; Wang, Ying -Ping ^[3]

Univ. of Oklahoma, Norman, OK (United States); Tsinghua Univ., Beijing (China)
Univ. of Oklahoma, Norman, OK (United States)
CSIRO Oceans and Atmosphere, Aspendale, VIC (Australia)
East China Normal Univ., Shanghai (China)
Microsoft Research, Cambridge (United Kingdom)
Stanford Univ., Stanford, CA (United States); Lund Univ., Lund (Sweden)
Univ. of Texas, Arlington, TX (United States)
Canadian Forest Service, Victoria, BC (Canada)
Univ. of California, Davis, CA (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Western Sydney Univ., Penrith, NSW (Australia)
Chinese Academy of Sciences (CAS), Beijing (China)
Imperial College, London (United Kingdom)
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Publication Date:: Fri Sep 16 00:00:00 EDT 2016

Research Org.:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: USDOE Office of Science (SC)

OSTI Identifier:: 1327772

Grant/Contract Number:: AC05-00OR22725

Resource Type:: Accepted Manuscript

Journal Name:: Biogeosciences Discussions (Online)

Additional Journal Information:: Journal Name: Biogeosciences Discussions (Online); Journal Volume: 2016; Journal ID: ISSN 1810-6285

Publisher:: European Geosciences Union

Country of Publication:: United States

Language:: English

Subject:: 54 ENVIRONMENTAL SCIENCES

Citation Formats


                    Luo, Yiqi, Shi, Zheng, Lu, Xingjie, Xia, Jianyang, Liang, Junyi, Wang, Ying, Smith, Matthew J., Jiang, Lifen, Ahlstrom, Anders, Chen, Benito, Hararuk, Oleksandra, Hastings, Alan, Hoffman, Forrest, Medlyn, Belinda, Niu, Shuli, Rasmussen, Martin, Todd-Brown, Katherine, and Wang, Ying -Ping. Transient dynamics of terrestrial carbon storage: Mathematical foundation and numeric examples.  United States: N. p., 2016. 
Web.  doi:10.5194/bg-2016-377.

Copy to clipboard


                    Luo, Yiqi, Shi, Zheng, Lu, Xingjie, Xia, Jianyang, Liang, Junyi, Wang, Ying, Smith, Matthew J., Jiang, Lifen, Ahlstrom, Anders, Chen, Benito, Hararuk, Oleksandra, Hastings, Alan, Hoffman, Forrest, Medlyn, Belinda, Niu, Shuli, Rasmussen, Martin, Todd-Brown, Katherine, & Wang, Ying -Ping. Transient dynamics of terrestrial carbon storage: Mathematical foundation and numeric examples.  United States.  https://doi.org/10.5194/bg-2016-377

Copy to clipboard


                    Luo, Yiqi, Shi, Zheng, Lu, Xingjie, Xia, Jianyang, Liang, Junyi, Wang, Ying, Smith, Matthew J., Jiang, Lifen, Ahlstrom, Anders, Chen, Benito, Hararuk, Oleksandra, Hastings, Alan, Hoffman, Forrest, Medlyn, Belinda, Niu, Shuli, Rasmussen, Martin, Todd-Brown, Katherine, and Wang, Ying -Ping. Fri .  
"Transient dynamics of terrestrial carbon storage: Mathematical foundation and numeric examples".  United States.  https://doi.org/10.5194/bg-2016-377.  https://www.osti.gov/servlets/purl/1327772.

Copy to clipboard


                    
@article{osti_1327772,

  title        = {Transient dynamics of terrestrial carbon storage: Mathematical foundation and numeric examples},

  author       = {Luo, Yiqi and Shi, Zheng and Lu, Xingjie and Xia, Jianyang and Liang, Junyi and Wang, Ying and Smith, Matthew J. and Jiang, Lifen and Ahlstrom, Anders and Chen, Benito and Hararuk, Oleksandra and Hastings, Alan and Hoffman, Forrest and Medlyn, Belinda and Niu, Shuli and Rasmussen, Martin and Todd-Brown, Katherine and Wang, Ying -Ping},

  abstractNote = {Terrestrial ecosystems absorb roughly 30% of anthropogenic CO2 emissions since preindustrial era, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling, experimental, and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under climate 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, 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. Furthermore, this and our other studies have demonstrated that one matrix equation can exactly 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 (3D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. Moreover, the 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. We also propose that the C storage potential be the targeted variable for research, market trading, and government negotiation for C credits.},

  doi          = {10.5194/bg-2016-377},

  journal      = {Biogeosciences Discussions (Online)},

  number       = ,

  volume       = 2016,

  place        = {United States},

  year         = {Fri Sep 16 00:00:00 EDT 2016},

  month        = {Fri Sep 16 00:00:00 EDT 2016}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (DOE)

Publisher's Version of Record

https://doi.org/10.5194/bg-2016-377

Other availability

Search WorldCat to find libraries that may hold this journal

Save / Share:

Export Metadata

Save to My Library

Similar Records in DOE PAGES and OSTI.GOV collections:

Transient dynamics of terrestrial carbon storage: mathematical foundation and its applications

Journal Article Luo, Yiqi ; Shi, Zheng ; Lu, Xingjie ; ... - Biogeosciences (Online)

Terrestrial 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.,more »« less
https://doi.org/10.5194/bg-14-145-2017
Transient dynamics of terrestrial carbon storage: Mathematical foundation and its applications

Journal Article Luo, Yiqi ; Shi, Zheng ; Lu, Xingjie ; ... - Biogeosciences (Online)

Terrestrial 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., netmore »« less
Cited by 56
https://doi.org/10.5194/bg-14-145-2017

Full Text Available
Data Synthesis and Data Assimilation at Global Change Experiments and Fluxnet Toward Improving Land Process Models

Technical Report Luo, Yiqi

The project was conducted during the period from 7/1/2012 to 6/30/2017 with three major tasks: (1) data synthesis and development of data assimilation (DA) techniques to constrain modeled ecosystem feedback to climate change; (2) applications of DA techniques to improve process models at different scales from ecosystem to regions and the globe; and 3) improvements of modeling soil carbon (C) dynamics by land surface models. During this period, we have synthesized published data from soil incubation experiments (e.g., Chen et al., 2016; Xu et al., 2016; Feng et al., 2016), global change experiments (e.g., Li et al., 2013; Shi etmore »« less
https://doi.org/10.2172/1389295

Full Text Available
Transient Traceability Analysis of Land Carbon Storage Dynamics: Procedures and Its Application to Two Forest Ecosystems

Journal Article Jiang, Lifen ; Shi, Zheng ; Xia, Jianyang ; ... - Journal of Advances in Modeling Earth Systems

Uptake of anthropogenically emitted carbon (C) dioxide by terrestrial ecosystem is critical for determining future climate. However, Earth system models project large uncertainties in future C storage. To help identify sources of uncertainties in model predictions, this study develops a transient traceability framework to trace components of C storage dynamics. Transient C storage (X) can be decomposed into two components, C storage capacity (X_c) and C storage potential (X_p). X_c is the maximum C amount that an ecosystem can potentially store and Xp represents the internal capacity of an ecosystem to equilibrate C input and output for a network ofmore »« less
Cited by 13
https://doi.org/10.1002/2017MS001004
Sources of Uncertainty in Modeled Land Carbon Storage within and across Three MIPs: Diagnosis with Three New Techniques

Journal Article Zhou, Sha ; Liang, Junyi ; Lu, Xingjie ; ... - Journal of Climate

Terrestrial carbon cycle models have incorporated increasingly more processes as a means to achieve more-realistic representations of ecosystem carbon cycling. Despite this, there are large across-model variations in the simulation and projection of carbon cycling. Several model intercomparison projects (MIPs), for example, the fifth phase of the Coupled Model Intercomparison Project (CMIP5) (historical simulations), Trends in Net Land–Atmosphere Carbon Exchange (TRENDY), and Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), have sought to understand intermodel differences. Here in this study, the authors developed a suite of new techniques to conduct post-MIP analysis to gain insights into uncertainty sources across 25more »« less
Cited by 21
https://doi.org/10.1175/jcli-d-17-0357.1

Full Text Available

Similar Records