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

2017 ◽  
Vol 14 (1) ◽  
pp. 145-161 ◽  
Author(s):  
Yiqi Luo ◽  
Zheng Shi ◽  
Xingjie Lu ◽  
Jianyang Xia ◽  
Junyi Liang ◽  
...  
Keyword(s):  
Residence Time ◽  
Storage Capacity ◽  
Rate Of Change ◽  
Transient Dynamics ◽  
Mathematical Framework ◽  
Time Step ◽  
C Storage ◽  
C Cycle ◽  
Storage Potential ◽  
C Input

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. 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.

scholarly journals Transient Dynamics of Terrestrial Carbon Storage: Mathematical foundation and Numeric Examples

2016 ◽  
Author(s):  
Yiqi Luo ◽  
Zheng Shi ◽  
Xingjie Lu ◽  
Jianyang Xia ◽  
Junyi Liang ◽  
...  
Keyword(s):  
Residence Time ◽  
Storage Capacity ◽  
Net Primary Production ◽  
Rate Of Change ◽  
Transient Dynamics ◽  
Time Step ◽  
C Storage ◽  
C Cycle ◽  
Storage Potential ◽  
C Input

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 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 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.

scholarly journals Carbon-nitrogen coupling under three schemes of model representation: Traceability analysis

2018 ◽  
Author(s):  
Zhenggang Du ◽  
Ensheng Weng ◽  
Jianyang Xia ◽  
Lifen Jiang ◽  
Yiqi Luo ◽  
...  
Keyword(s):  
Land Surface ◽  
Storage Capacity ◽  
N Uptake ◽  
C:N Ratio ◽  
Land Surface Models ◽  
Plant N Uptake ◽  
Coupled Models ◽  
C Storage ◽  
C Cycle ◽  
Surface Models

Abstract. The interaction between terrestrial carbon (C) and nitrogen (N) cycles has been incorporated into more and more land surface models. However, the scheme of C-N coupling differs greatly among models, and how these diverse representations of C-N interactions will affect C-cycle modeling remains unclear. In this study, we explored how the simulated ecosystem C storage capacity in the terrestrial ecosystem (TECO) model varies with three different commonly-used schemes of C-N coupling. The three schemes (SM1, SM2, and SM3) have been used in three different coupled C-N models (i.e., TECO-CN 2.0, CLM 4.5, and O-CN, respectively). They differ mainly in the stoichiometry of C and N in vegetation and soils, plant N uptake strategies, pathways of N import, and the competition between plants and microbes for soil mineral N. We incorporated them into the C-only version of TECO model, and evaluated their impacts on the C cycle with a traceability framework. Our results showed that all of the three C-N schemes resulted in significant reductions in steady-state C storage capacity compared with the C-only version, but the magnitude varied with −23 %, −30 % and −54 % for SM1, SM2, SM3, respectively. The reduced C storage capacity is the combination of decreases in net primary productivity (NPP) by −29 %, −15 % and −45 % with changes of mean C residence time (MRT) by 9 %, −17 % and −17 % for SM1, SM2, and SM3, respectively. The divergent NPP are mainly attributed to the different assumptions on plant N uptake, plant tissue C:N ratio, down-regulation photosynthesis, and biological N fixation. In comparison, the alternative representations of the plant and microbe competition strategy and the plant N uptake, combining with the flexible C:N ratio in vegetation and soils, led to a notable spread MRT. These results highlight that the diverse assumptions on N process representation among different C-N coupled models could cause additional uncertainty to land surface models. Understanding their difference can help us to improve the capability of models to predict future biogeochemical cycles on land.

scholarly journals Carbon–nitrogen coupling under three schemes of model representation: a traceability analysis

2018 ◽  
Vol 11 (11) ◽  
pp. 4399-4416 ◽  
Author(s):  
Zhenggang Du ◽  
Ensheng Weng ◽  
Lifen Jiang ◽  
Yiqi Luo ◽  
Jianyang Xia ◽  
...  
Keyword(s):  
Land Surface ◽  
Storage Capacity ◽  
N Uptake ◽  
N Fixation ◽  
Land Surface Models ◽  
Plant N Uptake ◽  
Coupled Models ◽  
C Storage ◽  
C Cycle ◽  
Surface Models

Abstract. The interaction between terrestrial carbon (C) and nitrogen (N) cycles has been incorporated into more and more land surface models. However, the scheme of C–N coupling differs greatly among models, and how these diverse representations of C–N interactions will affect C-cycle modeling remains unclear. In this study, we explored how the simulated ecosystem C storage capacity in the terrestrial ecosystem (TECO) model varied with three different commonly used schemes of C–N coupling. The three schemes (SM1, SM2, and SM3) have been used in three different coupled C–N models (i.e., TECO-CN, CLM 4.5, and O-CN, respectively). They differ mainly in the stoichiometry of C and N in vegetation and soils, plant N uptake strategies, downregulation of photosynthesis, and the pathways of N import. We incorporated the three C–N coupling schemes into the C-only version of the TECO model and evaluated their impacts on the C cycle with a traceability framework. Our results showed that all three of the C–N schemes caused significant reductions in steady-state C storage capacity compared with the C-only version with magnitudes of −23 %, −30 %, and −54 % for SM1, SM2, and SM3, respectively. This reduced C storage capacity was mainly derived from the combined effects of decreases in net primary productivity (NPP; −29 %, −15 %, and −45 %) and changes in mean C residence time (MRT; 9 %, −17 %, and −17 %) for SM1, SM2, and SM3, respectively. The differences in NPP are mainly attributed to the different assumptions on plant N uptake, plant tissue C : N ratio, downregulation of photosynthesis, and biological N fixation. In comparison, the alternative representations of the plant vs. microbe competition strategy and the plant N uptake, combined with the flexible C : N ratio in vegetation and soils, led to a notable spread in MRT. These results highlight the fact that the diverse assumptions on N processes represented by different C–N coupled models could cause additional uncertainty for land surface models. Understanding their difference can help us improve the capability of models to predict future biogeochemical cycles of terrestrial ecosystems.

scholarly journals A traceability analysis system for model evaluation on land carbon dynamics: design and applications

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Jian Zhou ◽  
Jianyang Xia ◽  
Ning Wei ◽  
Yufu Liu ◽  
Chenyu Bian ◽  
...  
Keyword(s):  
Residence Time ◽  
Model Evaluation ◽  
Earth System ◽  
Ecological Processes ◽  
System Models ◽  
C Storage ◽  
C Cycle ◽  
Traceability Analysis ◽  
Analysis System ◽  
Earth System Models

Abstract Background An increasing number of ecological processes have been incorporated into Earth system models. However, model evaluations usually lag behind the fast development of models, leading to a pervasive simulation uncertainty in key ecological processes, especially the terrestrial carbon (C) cycle. Traceability analysis provides a theoretical basis for tracking and quantifying the structural uncertainty of simulated C storage in models. Thus, a new tool of model evaluation based on the traceability analysis is urgently needed to efficiently diagnose the sources of inter-model variations on the terrestrial C cycle in Earth system models. Methods A new cloud-based model evaluation platform, i.e., the online traceability analysis system for model evaluation (TraceME v1.0), was established. The TraceME was applied to analyze the uncertainties of seven models from the Coupled Model Intercomparison Project (CMIP6). Results The TraceME can effectively diagnose the key sources of different land C dynamics among CMIIP6 models. For example, the analyses based on TraceME showed that the estimation of global land C storage varied about 2.4 folds across the seven CMIP6 models. Among all models, IPSL-CM6A-LR simulated the lowest land C storage, which mainly resulted from its shortest baseline C residence time. Over the historical period of 1850–2014, gross primary productivity and baseline C residence time were the major uncertainty contributors to the inter-model variation in ecosystem C storage in most land grid cells. Conclusion TraceME can facilitate model evaluation by identifying sources of model uncertainty and provides a new tool for the next generation of model evaluation.

Carbon Storage and Carbon Dioxide Sequestration of Banana Plants at Different Growth Stages

2014 ◽  
Vol 1010-1012 ◽  
pp. 662-665
Author(s):  
Mu Qiu Zhao ◽  
Ming Li ◽  
Yun Feng Shi
Keyword(s):  
Carbon Dioxide ◽  
Vegetative Growth ◽  
Hainan Island ◽  
Growth Stages ◽  
Maturity Stage ◽  
C Storage ◽  
C Cycle ◽  
Fruit Growing ◽  
Storage Structures ◽  
Different Growth Stages

Large annual herbaceous plants such as banana (Musa spp.) have a very impressive carbon (C) storage and carbon dioxide (CO2) sequestration in agroecosystems, and play a certain role in global C cycle, climate regulation and reducing global warming. In this paper, we systematically studied C storage on the different growth stages, CO2sequestration and distribution, and mathematical models for predicting CO2sequestration by bananas which were planted in western Hainan island, China. The results showed that C content of dry matter in different structures of banana plants was 45-50% in line with the current results, and in fruit reached the highest, in stems and roots followed, while that in leaves were the lowest. C storage in different structures of banana plants increased exponentially during banana growing process (vegetative growth and bud stage), stems were the major storage structures of C, and roots and leaves also had considerable C storage. C fixed by banana plants was mainly distributed in fruit at fruit growing stage. CO2sequestration was 16.3, 41.1 and 80.0t/ha at vegetative growth, bud and fruit maturity stage separately, and power function model can be applied with stem diameter (D) or composite parameter (D2H) as independent variables to predict.

Post-thinning soil organic matter evolution and soil CO2 effluxes in temperate radiata pine plantations: impacts of moderate thinning regimes on the forest C cycle

2012 ◽  
Vol 42 (11) ◽  
pp. 1953-1964 ◽  
Author(s):  
Irene Fernandez ◽  
Juan Gabriel Álvarez-González ◽  
Beatríz Carrasco ◽  
Ana Daría Ruíz-González ◽  
Ana Cabaneiro
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Radiata Pine ◽  
Soil Samples ◽  
Mitigation Strategies ◽  
Change Scenario ◽  
Soil C ◽  
C Storage ◽  
C Cycle ◽  
C And N

Forest ecosystems can act as C sinks, thus absorbing a high percentage of atmospheric CO2. Appropriate silvicultural regimes can therefore be applied as useful tools in climate change mitigation strategies. The present study analyzed the temporal changes in the effects of thinning on soil organic matter (SOM) dynamics and on soil CO2 emissions in radiata pine ( Pinus radiata D. Don) forests. Soil C effluxes were monitored over a period of 2 years in thinned and unthinned plots. In addition, soil samples from the plots were analyzed by solid-state 13C-NMR to determine the post-thinning SOM composition and fresh soil samples were incubated under laboratory conditions to determine their biodegradability. The results indicate that the potential soil C mineralization largely depends on the proportion of alkyl-C and N-alkyl-C functional groups in the SOM and on the microbial accessibility of the recalcitrant organic pool. Soil CO2 effluxes varied widely between seasons and increased exponentially with soil heating. Thinning led to decreased soil respiration and attenuation of the seasonal fluctuations. These effects were observed for up to 20 months after thinning, although they disappeared thereafter. Thus, moderate thinning caused enduring changes to the SOM composition and appeared to have temporary effects on the C storage capacity of forest soils, which is a critical aspect under the current climatic change scenario.

scholarly journals Through enhanced tree dynamics carbon dioxide enrichment may cause tropical forests to lose carbon

2004 ◽  
Vol 359 (1443) ◽  
pp. 493-498 ◽  
Author(s):  
Christian Körner
Keyword(s):  
Tropical Forests ◽  
Forest Dynamics ◽  
Forest Inventories ◽  
C Storage ◽  
Theoretical Approaches ◽  
C Cycle ◽  
Net Uptake ◽  
And Storage ◽  
Biodiversity Effects

The fixation and storage of C by tropical forests, which contain close to half of the globe's biomass C, may be affected by elevated atmospheric CO 2 concentration. Classical theoretical approaches assume a uniform stimulation of photosynthesis and growth across taxa. Direct assessments of the C balance either by flux studies or by repeated forest inventories also suggest a current net uptake, although magnitudes sometimes exceed those missing required to balance the global C cycle. Reasons for such discrepancies may lie in the nature of forest dynamics and in differential responses of taxa or plant functional types. In this contribution I argue that CO 2 enrichment may cause forests to become more dynamic and that faster tree turnover may in fact convert a stimulatory effect of elevated CO 2 on photosynthesis and growth into a long–term net biomass C loss by favouring shorter–lived trees of lower wood density. At the least, this is a scenario that deserves inclusion into long–term projections of the C relations of tropical forests. Species and plant functional type specific responses (‘biodiversity effects’) and forest dynamics need to be accounted for in projections of future C storage and cycling in tropical forests.

Sequestration of carbon in the humus layer of Swedish forests — direct measurements

2009 ◽  
Vol 39 (5) ◽  
pp. 962-975 ◽  
Author(s):  
Björn Berg ◽  
Maj-Britt Johansson ◽  
Åke Nilsson ◽  
Per Gundersen ◽  
Lennart Norell
Keyword(s):  
Layer Thickness ◽  
Forest Type ◽  
C Sequestration ◽  
Rate Of Change ◽  
Kriging Interpolation ◽  
Data Set ◽  
C Storage ◽  
Humus Layer ◽  
Sequestration Rate ◽  
Storage Rate

To determine sequestration rates of carbon dioxide (CO2) we calculated the carbon (C) storage rate in humus layers of Swedish forests with Podsolic soils, which account for 14.2 × 106 ha of the 22.7 × 106 ha of forested land in Sweden. Our data set covered 41 years of humus inventories and mean humus layer thickness in 82 513 plots. We analysed three forest types: (i) all combinations of tree species, (ii) forests dominated (>70%) by Norway spruce ( Picea abies (L.) Karst.), and (iii) forests dominated (>70%) by Scots pine ( Pinus sylvestris L.). To relate changes in humus layer thickness to land area we used the intersections in 25 km × 25 km grids and used kriging interpolation, permitting calculations for each forest type. For each intersection mean humus thickness for each year was calculated and regressed against time to obtain the rate of change. This rate, humus bulk density, and humus C concentration were used to calculate sequestration rates. The mean sequestration rate was 251 kg C·ha–1·year–1, which is higher than theoretical values. The sequestration rate was positively related to temperature sum, albeit including effects of forest management. The pine-dominated forest type had a mean rate of 283 kg C·ha–1·year–1, and the spruce-dominated had a mean rate of 239 kg C·ha–1·year–1. Under similar site conditions, pine sequestered more C than spruce (difference of 71 kg C·ha–1·year–1; p < 0.0001), showing the importance of this type of ecosystem for C sequestration.

scholarly journals Technical Note: SWIFT – a fast semi-empirical model for polar stratospheric ozone loss

2013 ◽  
Vol 13 (12) ◽  
pp. 31607-31634 ◽  
Author(s):  
M. Rex ◽  
S. Kremser ◽  
P. Huck ◽  
G. Bodeker ◽  
I. Wohltmann ◽  
...  
Keyword(s):  
Differential Equations ◽  
Stratospheric Ozone ◽  
Accurate Method ◽  
Technical Note ◽  
Rate Of Change ◽  
Polar Regions ◽  
Time Step ◽  
Ozone Loss ◽  
Semi Empirical ◽  
Loss Rates

Abstract. An extremely fast model to estimate the degree of stratospheric ozone depletion during polar winters is described. It is based on a set of coupled differential equations that simulate the seasonal evolution of vortex-averaged hydrogen chloride (HCl), nitric acid (HNO3), chlorine nitrate (ClONO2), active forms of chlorine (ClOx = Cl + ClO + 2 ClOOCl) and ozone (O3) on isentropic levels within the polar vortices. Terms in these equations account for the chemical and physical processes driving the time rate of change of these species. Eight empirical fit coefficients associated with these terms are derived by iteratively fitting the equations to vortex-averaged satellite-based measurements of HCl, HNO3 and ClONO2 and observationally derived ozone loss rates. The system of differential equations is not stiff and can be solved with a time step of one day, allowing many years to be processed per second on a standard PC. The inputs required are the daily fractions of the vortex area covered by polar stratospheric clouds and the fractions of the vortex area exposed to sunlight. The resultant model, SWIFT (Semi-empirical Weighted Iterative Fit Technique), provides a fast yet accurate method to simulate ozone loss rates in polar regions. SWIFT's capabilities are demonstrated by comparing measured and modeled total ozone loss outside of the training period.

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