Mycorrhizas and the terrestrial carbon cycle: roles in global carbon sequestration and plant community composition

2009 ◽  
pp. 161-184 ◽  
Author(s):  
Jonathan R. Leake
Keyword(s):  
Carbon Sequestration ◽  
Carbon Cycle ◽  
Community Composition ◽  
Plant Community ◽  
Plant Community Composition ◽  
Terrestrial Carbon ◽  
Terrestrial Carbon Cycle ◽  
Global Carbon

scholarly journals Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

2017 ◽  
Author(s):  
Marko Scholze ◽  
Michael Buchwitz ◽  
Wouter Dorigo ◽  
Luis Guanter ◽  
Shaun Quegan
Keyword(s):  
Data Assimilation ◽  
Carbon Cycle ◽  
Global Carbon Cycle ◽  
Full Description ◽  
Model Data ◽  
Terrestrial Carbon ◽  
Carbon Cycle Model ◽  
Terrestrial Carbon Cycle ◽  
Uncertainty Estimates ◽  
Global Carbon

Abstract. The global carbon cycle is an important component of the Earth system and it interacts with the hydrological, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification 5 of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by model-data fusion or data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation, and systematic and 10 well error-characterized observations relevant to the carbon cycle. Relevant observations for assimilation include various in-situ measurements in the atmosphere (e.g. concentrations of CO2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties).We briefly review the different existing data assimilation techniques and contrast them to model 15 benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current 20 observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al. (2005) emphasising the rapid advance in relevant space-based observations.

scholarly journals Consequences of Considering Carbon–Nitrogen Interactions on the Feedbacks between Climate and the Terrestrial Carbon Cycle

2008 ◽  
Vol 21 (15) ◽  
pp. 3776-3796 ◽  
Author(s):  
Andrei P. Sokolov ◽  
David W. Kicklighter ◽  
Jerry M. Melillo ◽  
Benjamin S. Felzer ◽  
C. Adam Schlosser ◽  
...  
Keyword(s):  
Carbon Sequestration ◽  
Carbon Cycle ◽  
Carbon Emissions ◽  
Terrestrial Ecosystems ◽  
Co2 Concentration ◽  
Nitrogen Dynamics ◽  
Carbon Uptake ◽  
Terrestrial Carbon ◽  
Surface Warming ◽  
Terrestrial Carbon Cycle

Abstract The impact of carbon–nitrogen dynamics in terrestrial ecosystems on the interaction between the carbon cycle and climate is studied using an earth system model of intermediate complexity, the MIT Integrated Global Systems Model (IGSM). Numerical simulations were carried out with two versions of the IGSM’s Terrestrial Ecosystems Model, one with and one without carbon–nitrogen dynamics. Simulations show that consideration of carbon–nitrogen interactions not only limits the effect of CO2 fertilization but also changes the sign of the feedback between the climate and terrestrial carbon cycle. In the absence of carbon–nitrogen interactions, surface warming significantly reduces carbon sequestration in both vegetation and soil by increasing respiration and decomposition (a positive feedback). If plant carbon uptake, however, is assumed to be nitrogen limited, an increase in decomposition leads to an increase in nitrogen availability stimulating plant growth. The resulting increase in carbon uptake by vegetation exceeds carbon loss from the soil, leading to enhanced carbon sequestration (a negative feedback). Under very strong surface warming, however, terrestrial ecosystems become a carbon source whether or not carbon–nitrogen interactions are considered. Overall, for small or moderate increases in surface temperatures, consideration of carbon–nitrogen interactions result in a larger increase in atmospheric CO2 concentration in the simulations with prescribed carbon emissions. This suggests that models that ignore terrestrial carbon–nitrogen dynamics will underestimate reductions in carbon emissions required to achieve atmospheric CO2 stabilization at a given level. At the same time, compensation between climate-related changes in the terrestrial and oceanic carbon uptakes significantly reduces uncertainty in projected CO2 concentration.

scholarly journals Vegetation distribution and terrestrial carbon cycle in a carbon-cycle configuration of JULES4.6 with new plant functional types

2018 ◽  
Author(s):  
Anna B. Harper ◽  
Andrew J. Wiltshire ◽  
Peter M. Cox ◽  
Pierre Friedlingstein ◽  
Chris D. Jones ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Soil Carbon ◽  
Boreal Forests ◽  
Carbon Sink ◽  
Vegetation Distribution ◽  
Terrestrial Carbon ◽  
Terrestrial Carbon Cycle ◽  
Vegetation Carbon ◽  
Global Vegetation ◽  
Global Carbon

Abstract. Dynamic global vegetation models (DGVMs) are used for studying historical and future changes to vegetation and the terrestrial carbon cycle. JULES (the Joint UK Land Environment Simulator) represents the land surface in the Hadley Centre climate models and in the UK Earth System Model. Recently the number of plant functional types (PFTs) in JULES were expanded from 5 to 9 to better represent functional diversity in global ecosystems. Here we introduce a more mechanistic representation of vegetation dynamics in TRIFFID, the dynamic vegetation component of JULES, that allows for any number of PFTs to compete based solely on their height, removing the previous hardwired dominance hierarchy where dominant types are assumed to outcompete subdominant types. With the new set of 9 PFTs, JULES is able to more accurately reproduce global vegetation distribution compared to the former 5 PFT version. Improvements include the coverage of trees within tropical and boreal forests, and a reduction in shrubs, which dominated at high latitudes. We show that JULES is able to realistically represent several aspects of the global carbon cycle. The simulated gross primary productivity (GPP) is within the range of observations, but simulated net primary productivity (NPP) is slightly too high. GPP in JULES from 1982–2011 was 133 PgC yr−1, compared to observation-based estimates between 123±8 (over the same time period) and 150–175 PgC yr−1. NPP from 2000–2013 was 72 PgC yr−1, compared to satellite-derived NPP of 55 PgC yr−1 over the same period and independent estimates of 56.2±14.3 PgC yr−1. The simulated carbon stored in vegetation is 542 PgC, compared to an observation-based range of 400–600 PgC. Soil carbon is much lower (1422 PgC) than estimates from measurements (>2400 PgC), with large underestimations of soil carbon in the tropical and boreal forests. We also examined some aspects of the historical terrestrial carbon sink as simulated by JULES. Between the 1900s and 2000s, increased atmospheric carbon dioxide levels enhanced vegetation productivity and litter inputs into the soils, while land-use change removed vegetation and reduced soil carbon. The result was a simulated increase in soil carbon of 57 PgC but a decrease in vegetation carbon by of PgC. JULES simulated a loss of soil and vegetation carbon of 14 and 124 PgC, respectively, due to land-use change from 1900–2009. The simulated land carbon sink was 2.0±1.0 PgC yr−1 from 2000–2009, in close agreement to estimates from the IPCC and Global Carbon Project.

scholarly journals Ignoring detailed fast-changing dynamics of land use overestimates regional terrestrial carbon sequestration

2009 ◽  
Vol 6 (2) ◽  
pp. 3215-3235 ◽  
Author(s):  
S. Zhao ◽  
S. Liu ◽  
Z. Li ◽  
T. L. Sohl
Keyword(s):  
Land Use ◽  
Carbon Sequestration ◽  
Land Use Change ◽  
Carbon Cycle ◽  
Global Carbon Cycle ◽  
Forest Harvesting ◽  
Terrestrial Carbon ◽  
Terrestrial Carbon Sequestration ◽  
Data Frequency ◽  
Global Carbon

Abstract. Land use change is critical in determining the distribution, magnitude and mechanisms of terrestrial carbon budgets at the local to global scales. To date, almost all regional to global carbon cycle studies are driven by a static land use map or land use change statistics with decadal time intervals. The biases in quantifying carbon exchange between the terrestrial ecosystems and the atmosphere caused by using such land use change information have not been investigated. Here, we used the General Ensemble biogeochemical Modeling System (GEMS), along with consistent and spatially explicit land use change scenarios with different intervals (1 yr, 5 yrs, 10 yrs and static, respectively), to evaluate the impacts of land use change data frequency on estimating regional carbon sequestration in the southeastern United States. Our results indicate that ignoring the detailed fast-changing dynamics of land use can lead to a significant overestimation of carbon uptake by the terrestrial ecosystem. Regional carbon sequestration increased from 0.27 to 0.69, 0.80 and 0.97 Mg C ha−1 yr−1 when land use change data frequency shifting from 1 year to 5 years, 10 years interval and static land use information, respectively. Carbon removal by forest harvesting and prolonged cumulative impacts of historical land use change on carbon cycle accounted for the differences in carbon sequestration between static and dynamic land use change scenarios. The results suggest that it is critical to incorporate the detailed dynamics of land use change into local to global carbon cycle studies. Otherwise, it is impossible to accurately quantify the geographic distributions, magnitudes, and mechanisms of terrestrial carbon sequestration at local to global scales.

scholarly journals Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

2017 ◽  
Vol 14 (14) ◽  
pp. 3401-3429 ◽  
Author(s):  
Marko Scholze ◽  
Michael Buchwitz ◽  
Wouter Dorigo ◽  
Luis Guanter ◽  
Shaun Quegan
Keyword(s):  
Data Assimilation ◽  
Carbon Cycle ◽  
Global Carbon Cycle ◽  
Ecosystem Dynamics ◽  
Full Description ◽  
Terrestrial Carbon ◽  
Carbon Cycle Model ◽  
Terrestrial Carbon Cycle ◽  
Uncertainty Estimates ◽  
Global Carbon

Abstract. The global carbon cycle is an important component of the Earth system and it interacts with the hydrology, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation and systematic and well error-characterised observations relevant to the carbon cycle. Relevant observations for assimilation include various in situ measurements in the atmosphere (e.g. concentrations of CO2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties).We briefly review the different existing data assimilation techniques and contrast them to model benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al.(2005), emphasising the rapid advance in relevant space-based observations.

scholarly journals Vegetation distribution and terrestrial carbon cycle in a carbon cycle configuration of JULES4.6 with new plant functional types

2018 ◽  
Vol 11 (7) ◽  
pp. 2857-2873 ◽  
Author(s):  
Anna B. Harper ◽  
Andrew J. Wiltshire ◽  
Peter M. Cox ◽  
Pierre Friedlingstein ◽  
Chris D. Jones ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Soil Carbon ◽  
Boreal Forests ◽  
Carbon Sink ◽  
Vegetation Distribution ◽  
Terrestrial Carbon ◽  
Terrestrial Carbon Cycle ◽  
Vegetation Carbon ◽  
Global Vegetation ◽  
Global Carbon

Abstract. Dynamic global vegetation models (DGVMs) are used for studying historical and future changes to vegetation and the terrestrial carbon cycle. JULES (the Joint UK Land Environment Simulator) represents the land surface in the Hadley Centre climate models and in the UK Earth System Model. Recently the number of plant functional types (PFTs) in JULES was expanded from five to nine to better represent functional diversity in global ecosystems. Here we introduce a more mechanistic representation of vegetation dynamics in TRIFFID, the dynamic vegetation component of JULES, which allows for any number of PFTs to compete based solely on their height; therefore, the previous hardwired dominance hierarchy is removed. With the new set of nine PFTs, JULES is able to more accurately reproduce global vegetation distribution compared to the former five PFT version. Improvements include the coverage of trees within tropical and boreal forests and a reduction in shrubs, the latter of which dominated at high latitudes. We show that JULES is able to realistically represent several aspects of the global carbon (C) cycle. The simulated gross primary productivity (GPP) is within the range of observations, but simulated net primary productivity (NPP) is slightly too high. GPP in JULES from 1982 to 2011 is 133 Pg C yr−1, compared to observation-based estimates (over the same time period) between 123 ± 8 and 150–175 Pg C yr−1. NPP from 2000 to 2013 is 72 Pg C yr−1, compared to satellite-derived NPP of 55 Pg C yr−1 over the same period and independent estimates of 56.2 ± 14.3 Pg C yr−1. The simulated carbon stored in vegetation is 542 Pg C, compared to an observation-based range of 400–600 Pg C. Soil carbon is much lower (1422 Pg C) than estimates from measurements (> 2400 Pg C), with large underestimations of soil carbon in the tropical and boreal forests. We also examined some aspects of the historical terrestrial carbon sink as simulated by JULES. Between the 1900s and 2000s, increased atmospheric carbon dioxide levels enhanced vegetation productivity and litter inputs into the soils, while land use change removed vegetation and reduced soil carbon. The result is a simulated increase in soil carbon of 57 Pg C but a decrease in vegetation carbon of 98 Pg C. The total simulated loss of soil and vegetation carbon due to land use change is 138 Pg C from 1900 to 2009, compared to a recent observationally constrained estimate of 155 ± 50 Pg C from 1901 to 2012. The simulated land carbon sink is 2.0 ± 1.0 Pg C yr−1 from 2000 to 2009, in close agreement with estimates from the IPCC and Global Carbon Project.

scholarly journals Ignoring detailed fast-changing dynamics of land use overestimates regional terrestrial carbon sequestration

2009 ◽  
Vol 6 (8) ◽  
pp. 1647-1654 ◽  
Author(s):  
S. Q. Zhao ◽  
S. Liu ◽  
Z. Li ◽  
T. L. Sohl
Keyword(s):  
Land Use ◽  
Carbon Sequestration ◽  
Land Use Change ◽  
Carbon Cycle ◽  
Global Carbon Cycle ◽  
Forest Harvesting ◽  
Terrestrial Carbon ◽  
Terrestrial Carbon Sequestration ◽  
Data Frequency ◽  
Global Carbon

Abstract. Land use change is critical in determining the distribution, magnitude and mechanisms of terrestrial carbon budgets at the local to global scales. To date, almost all regional to global carbon cycle studies are driven by a static land use map or land use change statistics with decadal time intervals. The biases in quantifying carbon exchange between the terrestrial ecosystems and the atmosphere caused by using such land use change information have not been investigated. Here, we used the General Ensemble biogeochemical Modeling System (GEMS), along with consistent and spatially explicit land use change scenarios with different intervals (1 yr, 5 yrs, 10 yrs and static, respectively), to evaluate the impacts of land use change data frequency on estimating regional carbon sequestration in the southeastern United States. Our results indicate that ignoring the detailed fast-changing dynamics of land use can lead to a significant overestimation of carbon uptake by the terrestrial ecosystem. Regional carbon sequestration increased from 0.27 to 0.69, 0.80 and 0.97 Mg C ha−1 yr−1 when land use change data frequency shifting from 1 year to 5 years, 10 years interval and static land use information, respectively. Carbon removal by forest harvesting and prolonged cumulative impacts of historical land use change on carbon cycle accounted for the differences in carbon sequestration between static and dynamic land use change scenarios. The results suggest that it is critical to incorporate the detailed dynamics of land use change into local to global carbon cycle studies. Otherwise, it is impossible to accurately quantify the geographic distributions, magnitudes, and mechanisms of terrestrial carbon sequestration at the local to global scales.

Impacts of soil hydrologial modeling on long-term terrestrial carbon cycle inferred from CCDAS (Carbon Cycle Data Assimilation System)

2020 ◽  
Author(s):  
Mousong Wu ◽  
Marko Scholze ◽  
Fei Jiang ◽  
Hengmao Wang ◽  
Wenxin Zhang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Carbon Cycle ◽  
Carbon Budget ◽  
Terrestrial Carbon ◽  
Global Carbon Budget ◽  
Terrestrial Carbon Cycle ◽  
Global Carbon ◽  
Data Assimilation System ◽  
Assimilation System

<p>The terrestrial carbon cycle is an important part of the global carbon budget due to its large gross exchange fluxes with the atmosphere and their sensitivity to climate change. Terrestrial biosphere models show large uncertainties in estimating carbon fluxes, which impacts global carbon budget assessments. The land surface carbon cycle is tightly controlled by soil moisture through plant physiological processes. In this context, accurate soil moisture data will improve the modeling of carbon fluxes in a model-data fusion framework. We employ the Carbon Cycle Data Assimilation System (CCDAS) to assimilate 36 years (1980-2015) of surface soil moisture data as provided by the ESA CCI in combination with atmospheric CO<sub>2</sub> concentration observations at global scale. We will present the methods used for assimilating long-term remotely sensed soil moisture into the terrestrial biosphere model, and demonstrate the importance of soil moisture in modeling ecosystem carbon cycle processes. We will also investigate the impacts of soil moisture on the terrestrial carbon cycle during climate extremes at various scales.</p>

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