scholarly journals Simulating Grassland Carbon Dynamics in Gansu for the Past Fifty (50) Years (1968–2018) Using the Century Model

2021 ◽  
Vol 13 (16) ◽  
pp. 9434
Author(s):  
Meiling Zhang ◽  
Stephen Nazieh ◽  
Teddy Nkrumah ◽  
Xingyu Wang
Keyword(s):  
Soil Carbon ◽  
Management Practices ◽  
Correlation Coefficients ◽  
Gansu Province ◽  
Century Model ◽  
Soil C ◽  
Soil Carbon Stock ◽  
C Dynamics ◽  
Sequestration Rate ◽  
Soc Density

China is one of the countries most impacted by desertification, with Gansu Province in the northwest being one of the most affected areas. Efforts have been made in recent decades to restore the natural vegetation, while also producing food. This has implications for the soil carbon sequestration and, as a result, the country’s carbon budget. Studies of carbon (C) dynamics in this region would help to understand the effect of management practices on soil organic carbon (SOC) as well as aboveground biomass (ABVG), and to aid informed decision-making and policy implementation to alleviate the rate of global warming. It would also help to understand the region’s contribution to the national C inventory of China. The CENTURY model, a process-based model that is capable of simulating C dynamics over a long period, has not been calibrated to suit Gansu Province, despite being an effective model for soil C estimation. Using the soil and grassland maps of Gansu, together with weather, soil, and reliable historical data on management practices in the province, we calibrated the CENTURY model for the province’s grasslands. The calibrated model was then used to simulate the C dynamics between 1968 and 2018. The results show that the model is capable of simulating C with significant accuracy. Our measured and observed SOC density (SOCD) and ABVG had correlation coefficients of 0.76 and 0.50, respectively, at p < 0.01. Precipitation correlated with SOCD and ABVG with correlation coefficients of 0.57 and 0.89, respectively, at p < 0.01. The total SOC storage (SOCS) was 436.098 × 106 t C (approximately 0.4356% of the national average) and the average SOCD was 15.75 t C/ha. There was a high ABVG in the southeast and it decreased towards the northwest. The same phenomenon was observed in the spatial distribution of SOCD. Among the soils studied, Hostosols had the highest SOC sequestration rate (25.6 t C/ha) with Gypsisols having the least (7.8 t C/ha). Between 1968 and 2018, the soil carbon stock gradually increased, with the southeast experiencing the greatest increase.

Spatially Explicit Simulation of Soil C Dynamics with the Century Model

2008 ◽  
Author(s):  
Carlos Gustavo Tornquist ◽  
Joao Mielnickzuk ◽  
Philip Walter Gassman
Keyword(s):  
Spatially Explicit ◽  
Century Model ◽  
Soil C ◽  
C Dynamics ◽  
Explicit Simulation

scholarly journals Influence of climate change factors on carbon dynamics in northern forested peatlands

2006 ◽  
Vol 86 (Special Issue) ◽  
pp. 269-280 ◽  
Author(s):  
C. C. Trettin ◽  
R. Laiho ◽  
K. Minkkinen ◽  
J. Laine
Keyword(s):  
Climate Change ◽  
Organic Matter ◽  
Management Practices ◽  
Atmospheric Temperature ◽  
Soil C ◽  
Altered Hydrology ◽  
Biogeochemical Models ◽  
C Dynamics ◽  
C Balance ◽  
C Cycle

Peatlands are carbon-accumulating wetland ecosystems, developed through an imbalance among organic matter production and decomposition processes. Soil saturation is the principal cause of anoxic conditions that constrain organic matter decay. Accordingly, changes in the hydrologic regime will affect the carbon (C) dynamics in forested peatlands. Our objective is to review ecological studies and experiments on managed peatlands that provide a basis for assessing the effects of an altered hydrology on C dynamics. We conclude that climate change influences will be mediated primarily through the hydrologic cycle. A lower water table resulting from altered precipitation patterns and increased atmospheric temperature may be expected to decrease soil CH4 and increase CO2 emissions from the peat surface. Correspondingly, the C balance in forested peatlands is also sensitive to management and restoration prescriptions. Increases in soil CO2 efflux do not necessarily equate with net losses from the soil C pool. While the fundamentals of the C balance in peatlands are well-established, the combined affects of global change stressors and management practices are best considered using process-based biogeochemical models. Long-term studies are needed both for validation and to provide a framework for longitudinal assessments of the peatland C cycle. Key words: Peatland, carbon cycle, methane, forest, wetland.

scholarly journals Changes in soil carbon stock in Mewat and Dhar under cereal and legume based cropping systems

2019 ◽  
Author(s):  
B. Chakrabarti ◽  
S.K. Bandyopadhyay ◽  
D. Pratap ◽  
H. Pathak ◽  
R. Mittal ◽  
...  
Keyword(s):  
Soil Carbon ◽  
Carbon Stock ◽  
Management Practices ◽  
Surface Soil ◽  
Cropping Systems ◽  
Soil Layer ◽  
Cropping System ◽  
Soil Carbon Stock ◽  
Cropping Sequence ◽  
Surface Soil Layer

Soil organic carbon is strongly affected by agricultural management practices. Cropping systems can influence the amount of carbon present in soil. Increase in SOC can be related with the choice of crops present in the cropping sequence as well as on the management practices followed. The present study was undertaken to quantify the changes in soil carbon stock under different cropping systems. Two major cropping systems i.e. pearlmillet-wheat and pearlmillet-mustard were selected in Mewat, Haryana while soybean-wheat cropping systems was identified in Dhar, Madhya Pradesh. Results showed that SOC of surface soil layer decreased from 0.42% to 0.39% in pearlmillet-mustard cropping system during the study period. But in soybean-wheat cropping system it increased from 1.14% to 1.24%. Legume based cropping system showed enhancement of surface soil carbon.

 Implementation of mycorrhizal mechanism into a soil carbon model improves the prediction of long-term processes of plant litter decomposition

2021 ◽  
Author(s):  
Weilin Huang ◽  
Peter van Bodegom ◽  
Toni Viskari ◽  
Jari Liski ◽  
Nadejda Soudzilovskaia
Keyword(s):  
Soil Carbon ◽  
Litter Decomposition ◽  
Arbuscular Mycorrhizae ◽  
Plant Litter ◽  
Climate Impacts ◽  
Microbial Interactions ◽  
Soil C ◽  
Plant Litter Decomposition ◽  
C Dynamics

&lt;p&gt;Mycorrhizae, a plant-fungal symbiosis, is an important contributor to below ground-microbial interactions, and hypothesized to play a paramount role in soil carbon (C) sequestration. Ectomycorrhizae (EM) and arbuscular mycorrhizae (AM) are the two dominant forms of mycorrhizae featured by nearly all Earth plant species. However, the difference in the nature of their contributions to the processes of plant litter decomposition is still understood poorly. Current soil carbon models treat mycorrhizal impacts on the processes of soil carbon transformation as a black box. This retards scientific progress in mechanistic understanding of soil C dynamics.&lt;/p&gt;&lt;p&gt;We examined four alternative conceptualizations of the mycorrhizal impact on plant litter C transformations, by integrating AM and EM fungal impacts on litter C pools of different recalcitrance into the soil carbon model Yasso15. The best performing concept featured differential impacts of EM and AM on a combined pool of labile C, being quantitatively distinct from impacts of AM and EM on a pool of recalcitrant C.&lt;/p&gt;&lt;p&gt;Analysis of time dynamics of mycorrhizal impacts on soil C transformations demonstrated that these impacts are larger at the long-term (&gt;2.5yrs) litter decomposition processes, compared to the short-term processes. We detected that arbuscular mycorrhizae controls shorter term decomposition of labile carbon compounds, while ectomycorrhizae dominate the long term decomposition processes of highly recalcitrant carbon elements. Overall, adding our mycorrhizal module into the Yasso model greatly improved the accuracy of the temporal dynamics of carbon sequestration.&lt;/p&gt;&lt;p&gt;A sensitivity analysis of litter decomposition to climate and mycorrhizal factors indicated that ignoring the mycorrhizal impact on the decomposition leads to an overestimation of climate impacts. This suggests that being co-linear with climate impacts, mycorrhizal impacts could be partly hidden within climate factors in soil carbon models, reducing the capability of such models to mechanistically predict impacts of climate vs vegetation change on soil carbon dynamics.&lt;/p&gt;&lt;p&gt;Our results provide a benchmark to mechanistic modelling of microbial impacts on soil C dynamics. This work opens new pathways to examining the impacts of land-use change and climate change on plant-microbial interactions and their role in soil C dynamics, allowing the integration of microbial processes into global vegetation models used for policy decisions on terrestrial carbon monitoring.&lt;/p&gt;

scholarly journals Vinasse application and cessation of burning in sugarcane management can have positive impact on soil carbon stocks

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5398 ◽  
Author(s):  
Caio F. Zani ◽  
Arlete S. Barneze ◽  
Andy D. Robertson ◽  
Aidan M. Keith ◽  
Carlos E.P. Cerri ◽  
...  
Keyword(s):  
Soil Carbon ◽  
Greenhouse Gas ◽  
Management Practices ◽  
Positive Impact ◽  
Clay Fraction ◽  
Bioenergy Crops ◽  
Soil C ◽  
Sequestration Potential ◽  
C Stocks ◽  
Management Changes

Bioenergy crops, such as sugarcane, have the potential to mitigate greenhouse gas emissions through fossil fuel substitution. However, increased sugarcane propagation and recent management changes have raised concerns that these practices may deplete soil carbon (C) stocks, thereby limiting the net greenhouse gas benefit. In this study, we use both a measured and modelled approach to evaluate the impacts of two common sugarcane management practices on soil C sequestration potential in Brazil. We explore how transitions from conventional (mineral fertiliser/burning) to improved (vinasse application/unburned) practices influence soil C stocks in total and in physically fractionated soil down to one metre. Results suggest that vinasse application leads to an accumulation of soil C of 0.55 Mg ha−1yr−1 at 0–30 cm depth and applying unburned management led to gains of ∼0.7 Mg ha−1yr−1 at 30–60 cm depth. Soil C concentration in the Silt+Clay fraction of topsoil (0–20 cm) showed higher C content in unburned management but it did not differ under vinasse application. The CENTURY model was used to simulate the consequences of management changes beyond the temporal extent of the measurements. Simulations indicated that vinasse was not the key factor driving increases in soil C stocks but its application may be the most readily available practice to prevent the soil C losses under burned management. Furthermore, cessation of burning may increase topsoil C by 40% after ∼50 years. These are the first data comparing different sugarcane management transitions within a single area. Our findings indicate that both vinasse application and the cessation of burning can play an important role in reducing the time required for sugarcane ethanol production to reach a net C benefit (payback time).

scholarly journals Soil carbon mineralization in response to nitrogen enrichment in surface and subsurface layers in two land use types

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7130
Author(s):  
Nazia Perveen ◽  
Mariam Ayub ◽  
Tanvir Shahzad ◽  
Muhammad Rashid Siddiq ◽  
Muhammad Sohail Memon ◽  
...  
Keyword(s):  
Soil Carbon ◽  
Microbial Biomass Carbon ◽  
Carbon Mineralization ◽  
N Availability ◽  
Soil C ◽  
Suppression Effect ◽  
N Level ◽  
C Dynamics ◽  
Subsurface Layers ◽  
N Enrichment

Atmospheric nitrogen (N) deposition increases N availability in soils, with consequences affecting the decomposition of soil carbon (C). The impacts of increasing N availability on surface soil C dynamics are well studied. However, subsurface soils have been paid less attention although more than 50% soil C stock is present below this depth (below 20 cm). This study was designed to investigate the response of surface (0–20 cm) and subsurface (20–40 cm and 40–60 cm) C dynamics to 0 (0 kg N ha−1), low (70 kg N ha−1) and high (120 kg N ha−1) levels of N enrichment. The soils were sampled from a cropland and a grass lawn and incubated at 25 °C and 60% water holding capacity for 45 days. Results showed that N enrichment significantly decreased soil C mineralization (Rs) in all the three soil layers in the two studied sites (p < 0.05). The mineralization per unit soil organic carbon (SOC) increased with profile depth in both soils, indicating the higher decomposability of soil C down the soil profile. Moreover, high N level exhibited stronger suppression effect on Rs than low N level. Rs was significantly and positively correlated with microbial biomass carbon explaining 80% of variation in Rs. Overall; these results suggest that N enrichment may increase C sequestration both in surface and subsurface layers, by reducing C loss through mineralization.

Stratifying soils into pedogenically similar categories for modeling forest soil carbon

2008 ◽  
Vol 88 (4) ◽  
pp. 501-516 ◽  
Author(s):  
C H Shaw ◽  
E. Banfield ◽  
W A Kurz
Keyword(s):  
Soil Carbon ◽  
Forest Soil ◽  
Scientific Basis ◽  
Soil C ◽  
Orthogonal Contrasts ◽  
Carbon Modeling ◽  
Ecosystem Carbon ◽  
C Dynamics ◽  
C Stocks ◽  
Pedogenic Processes

Most forest ecosystem carbon (C) models are designed to estimate total ecosystem C including soil C stocks and fluxes. Stratification by tree species is often used in these models to reduce uncertainty, but the potential of stratification by soil taxon has received little attention. This potential can be realized only if meaningful modeling strata are identified. Therefore, the objectives of this study were: (a) to distinguish strata of soil C modeling cateogories (SCMC) on the basis of soil C stocks of taxonomic categories that are characterized by similar pedogenic processes important to C dynamics, and (b) to review the literature to test the robustness of the SCMC scheme. Carbon stocks of 1383 forest soil pedons were analyzed by multiple means comparisons for soil orders and by orthogonal contrasts between pedologically related sets of subgroups within soil orders. Eleven SCMCs were distinguished with mean total C stocks varying from 325 ± 37.2 t ha-1 for the gleyed Cryosol SCMC to 94 ± 3.9 t ha-1 for the Brunisolic Gray Luvisol SCMC. A review of the literature relevant to each SCMC demonstrated that there is a scientific basis for using these strata to model forest soil C dynamics. Key words: Forest soil, carbon, modeling, pedology, genesis

Empirical modelling of plant and soil carbon flux drivers under field conditions

2020 ◽  
Author(s):  
Chris McCloskey ◽  
Guy Kirk ◽  
Wilfred Otten ◽  
Eric Paterson
Keyword(s):  
Soil Moisture ◽  
Soil Temperature ◽  
Soil Carbon ◽  
Field Conditions ◽  
Gas Flux ◽  
Soil C ◽  
C Dynamics ◽  
Plant Respiration ◽  
Soil Temperature And Moisture

&lt;p&gt;Our understanding of soil carbon (C) dynamics is limited; field measurements necessarily conflate fluxes from plant and soil sources and we therefore lack long-term field-scale data on soil C fluxes to use to test and improve soil C models. Furthermore, it is often unclear whether findings from lab-based studies, such as the presence of rhizosphere priming, apply to soil systems in the field. It is particularly important that we are able to understand the roles of soil temperature and moisture, and plant C inputs, as drivers of soil C dynamics in order to predict how changing climate and plant productivity may affect the net C balance of soils. We have developed a field laboratory with which to generate much-needed long-term C flux data under field conditions, giving near-continuous measurements of plant and soil C fluxes and their drivers.&lt;/p&gt;&lt;p&gt;The laboratory contains 24 0.8-m diameter, 1-m deep, naturally-structured soil monoliths of two contrasting C3 soils (a clay-loam and a sandy soil) in lysimeters. These are sown with a C4 grass (&lt;em&gt;Bouteloua dactyloides&lt;/em&gt;), providing a large difference in C isotope signature between C4 plant respiration and C3-origin soil organic matter (SOM) decomposition, which enables clear partitioning of the net C flux. This species is used as a pasture grass in the United States, and regular trimming through the growing season simulates low-intensity grazing. The soil monoliths are fitted with gas flux chambers and connected via an automated sampling loop to a cavity ring-down spectrometer, which measures the concentration and &lt;sup&gt;12&lt;/sup&gt;C:&lt;sup&gt;13&lt;/sup&gt;C isotopic ratio of CO&lt;sub&gt;2&lt;/sub&gt; during flux chamber closure. Depth-resolved measurements of soil temperature and moisture in each monolith are made near-continuously, along with measurements of incoming solar radiation, rainfall, and air temperature a the field site. The gas flux chambers are fitted with removable reflective backout covers allowing flux measurements both incorporating, and in the absence of, photosynthesis.&lt;/p&gt;&lt;p&gt;We have collected net ecosystem respiration data, measurements of photosynthesis, and recorded potential drivers of respiration over two growing seasons through 2018 and 2019. Through partitioning fluxes between plant respiration and SOM mineralisation we have revealed clear diurnal trends in both plant and soil C fluxes, along with overarching seasonal trends which modify both the magnitude of fluxes and their diurnal patterns. Rates of photosynthesis have been interpolated between measurement periods using machine learning to generate a predictive model, which has allowed us to investigate the effect of plant productivity on SOM mineralisation and assess whether rhizosphere priming can be detected in our system. Through regression analyses and linear mixed effects modelling we have evaluated the roles of soil temperature, soil moisture, and soil N content as drivers of variation in plant and soil respiration in our two contrasting soils. This has shown soil temperature to be the most important control on SOM mineralisation, with soil moisture content playing only a minor role. We have also used our empirical models to suggest how the carbon balance of pasture and grassland soils may respond to warming temperatures.&lt;/p&gt;

Carbon dioxide fluxes on agricultural grasslands – Uncertainty associated with gap-filling

2020 ◽  
Author(s):  
Henriikka Vekuri ◽  
Juha-Pekka Tuovinen ◽  
Mika Korkiakoski ◽  
Laura Heimsch ◽  
Liisa Kulmala ◽  
...  
Keyword(s):  
Carbon Sequestration ◽  
Soil Carbon ◽  
Eddy Covariance ◽  
Carbon Stock ◽  
Management Practices ◽  
Terrestrial Ecosystems ◽  
Carbon Markets ◽  
Gap Filling ◽  
Soil Carbon Stock ◽  
Uncertainty Estimates

&lt;p&gt;Mitigation of climate change requires &amp;#8211; besides reductions in greenhouse gas emissions &amp;#8211; actions to increase carbon sinks and storages in terrestrial ecosystems. Agricultural lands have a high potential for increased carbon sequestration through climate-smart land management and agricultural practices. However, in order to make climate-smart farming an accredited solution for climate policy, carbon markets and product footprints, reliable verification of carbon sequestration is needed. Direct measurement of the changes in soil carbon stock is slow, laborious and expensive and has significant uncertainties due to large background stocks and high spatial variability. An alternative is to infer the soil carbon stock change from measurements of the gaseous carbon fluxes between ecosystems and the atmosphere using the micrometeorological eddy covariance (EC) method.&lt;/p&gt;&lt;p&gt;Eddy covariance measures net ecosystem exchange (NEE), which is a small difference between two large components: carbon uptake by photosynthesis and losses due to plant and soil respiration. Therefore, small changes in either of them results in a large change in NEE. This sensitivity is also reflected in uncertainty estimates, which are critical for defining confidence intervals for annual carbon budget estimates and for making statistically valid comparisons of different management practices. &amp;#160;In addition, there are inevitable gaps in the data due to instrument failure, power shortages and non-ideal flow conditions. Therefore, in order to calculate daily and annual sums, the collected data must be temporally upscaled or gap-filled, which constitutes a major additional source of uncertainty. This study compares two different gap-filling methods for CO&amp;#8322; fluxes: (1) an artificial neural network and (2) non-linear regression, which uses temperature and radiation as drivers. Uncertainties associated with both methods are estimated and discussed. The analysis is based on EC flux measurements conducted at two agricultural grassland sites in Finland.&lt;/p&gt;

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