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

Luo, Yiqi; Shi, Zheng; Lu, Xingjie; Xia, Jianyang; Liang, Junyi; Jiang, Jiang; Wang, Ying; Smith, Matthew J.; Jiang, Lifen and Ahlström, Anders LU , et al. (2017) In Biogeosciences 14(1). p.145-161
Abstract

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., net primary production, NPP) and residence time.... (More)

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., 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.

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published
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Biogeosciences
volume
14
issue
1
pages
17 pages
publisher
Copernicus Publications
external identifiers
  • scopus:85009436138
  • wos:000393893500001
ISSN
1726-4170
DOI
10.5194/bg-14-145-2017
language
English
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yes
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19f979a1-afc0-47a7-8001-bbf492547213
date added to LUP
2017-03-03 09:42:12
date last changed
2018-01-07 11:53:51
@article{19f979a1-afc0-47a7-8001-bbf492547213,
  abstract     = {<p>Terrestrial ecosystems have absorbed roughly 30 % of anthropogenic CO<sub>2</sub> 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.</p>},
  author       = {Luo, Yiqi and Shi, Zheng and Lu, Xingjie and Xia, Jianyang and Liang, Junyi and Jiang, Jiang and Wang, Ying and Smith, Matthew J. and Jiang, Lifen and Ahlström, Anders and Chen, Benito and Hararuk, Oleksandra and Hastings, Alan and Hoffman, Forrest and Medlyn, Belinda E. and Niu, Shuli and Rasmussen, Martin and Todd-Brown, Katherine E. O. and Wang, Ying-Ping},
  issn         = {1726-4170},
  language     = {eng},
  month        = {01},
  number       = {1},
  pages        = {145--161},
  publisher    = {Copernicus Publications},
  series       = {Biogeosciences},
  title        = {Transient dynamics of terrestrial carbon storage : Mathematical foundation and its applications},
  url          = {http://dx.doi.org/10.5194/bg-14-145-2017},
  volume       = {14},
  year         = {2017},
}