scholarly journals Surface Soil Organic Carbon Sequestration Under Post Agricultural Grasslands Offset by Net Loss at Depth

2021 ◽  
Author(s):  
Yi Yang ◽  
Terrance Loecke ◽  
Johanness Knops
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Surface Soil ◽  
C Sequestration ◽  
The United States ◽  
Soil Profiles ◽  
Continental Scale ◽  
C Dynamics ◽  
Subsurface Soil ◽  
Soc Stock

Abstract Post agricultural grasslands are considered to accumulate soil organic carbon (SOC) after cultivation cessation. The Conservation Reserve Program (CRP) in the U.S. is a wide scale, covering approximately 8.9 Mha as of 2020, example of row-crop to grassland conversion. To date, SOC sequestration rates, and potential, in CRP has mostly been evaluated at local scales and focused on the surface 20–30 cm of the soil profile. Thus, we lack knowledge of C sequestration rates in CRP lands on a continental scale and of C dynamics in the subsurface soil after agricultural cessation. The Rapid Carbon Assessment (RaCA) project is the most recent effort by the United States Department of Agriculture (USDA) to systematically quantify C stock in the 0-100 cm soil profiles across the conterminous US. Here we analyze data from RaCA to evaluate the C stocks of the CRP on a continental scale of both surface and subsurface soil. We found there was no difference in SOC stock between croplands and CRP lands when comparing the 0-100 cm soil profiles, which indicates that the C sequestration in CRP lands is insignificant overall. We did find that SOC accumulated in the surface soil (0–5 cm) in CRP lands. However, theses C gains in surface (0–5 cm) soil were offset by the lower SOC stock in the subsurface (30–100 cm) of the CRP. We also found that the C: N ratio in the subsurface soil in CRP lands is lower than that of croplands, indicating a lack of labile organic matter inputs in the subsoil. Whether the lower SOC in the subsurface of CRP is caused by legacy effects or is a result of C losses needs to be verified by long-term repeated sampling in both surface and subsurface soil. This analysis highlights the importance of examining C dynamics in subsurface soil after agricultural cessation to accurately measure and improve C sequestration rates in CRP lands.

scholarly journals Estimating soil organic carbon stocks of Swiss forest soils by robust external-drift kriging

2014 ◽  
Vol 7 (3) ◽  
pp. 1197-1210 ◽  
Author(s):  
M. Nussbaum ◽  
A. Papritz ◽  
A. Baltensweiler ◽  
L. Walthert
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Near Infrared ◽  
Likelihood Method ◽  
Standard Errors ◽  
Soil Profiles ◽  
Near Infrared Reflectance ◽  
Soc Stock ◽  
Soc Stocks ◽  
External Drift

Abstract. Accurate estimates of soil organic carbon (SOC) stocks are required to quantify carbon sources and sinks caused by land use change at national scale. This study presents a novel robust kriging method to precisely estimate regional and national mean SOC stocks, along with truthful standard errors. We used this new approach to estimate mean forest SOC stock for Switzerland and for its five main ecoregions. Using data of 1033 forest soil profiles, we modelled stocks of two compartments (0–30, 0–100 cm depth) of mineral soils. Log-normal regression models that accounted for correlation between SOC stocks and environmental covariates and residual (spatial) auto-correlation were fitted by a newly developed robust restricted maximum likelihood method, which is insensitive to outliers in the data. Precipitation, near-infrared reflectance, topographic and aggregated information of a soil and a geotechnical map were retained in the models. Both models showed weak but significant residual autocorrelation. The predictive power of the fitted models, evaluated by comparing predictions with independent data of 175 soil profiles, was moderate (robust R2 = 0.34 for SOC stock in 0–30 cm and R2 = 0.40 in 0–100 cm). Prediction standard errors (SE), validated by comparing point prediction intervals with data, proved to be conservative. Using the fitted models, we mapped forest SOC stock by robust external-drift point kriging at high resolution across Switzerland. Predicted mean stocks in 0–30 and 0–100 cm depth were equal to 7.99 kg m−2 (SE 0.15 kg m−2) and 12.58 kg m−2 (SE 0.24 kg m−2), respectively. Hence, topsoils store about 64% of SOC stocks down to 100 cm depth. Previous studies underestimated SOC stocks of topsoil slightly and those of subsoils strongly. The comparison further revealed that our estimates have substantially smaller SE than previous estimates.

scholarly journals Modeling soil organic carbon dynamics and its driving factors in global main cereal cropping systems

2017 ◽  
Author(s):  
Guocheng Wang ◽  
Wen Zhang ◽  
Wenjuan Sun ◽  
Tingting Li ◽  
Pengfei Han
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Crop Residue ◽  
Retention Rate ◽  
C Sequestration ◽  
The United States ◽  
Soil C ◽  
C Input ◽  
Soil C Sequestration ◽  
Residue Retention

Abstract. The net fluxes of carbon dioxide (CO2) between the atmosphere and agricultural systems are mainly characterized by the changes in soil carbon stock, which is determined by the balance between carbon input from organic materials and output through soil C decomposition. The spatiotemporal changes of cropland soil organic carbon (SOC) in response to different carbon (C) input management and environmental conditions across the global main cereal systems were studied using a modeling approach. We also identified the key variables driving SOC changes at a high spatial resolution (0.1° × 0.1°) and long time scale (54 years from 1961 to 2014). The widely used soil C turnover model (RothC) and the state-of-the-art databases of soil and climate were used in the present study. The model simulations suggested that, on a global average, the cropland SOC density increased at an annual rate of 0.22, 0.45 and 0.69 MgC ha−1 yr−1 under a crop residue retention rate of 30 %, 60 % and 90 %, respectively. Increased quantity of C input could enhance the soil C sequestration or reduce the soil C loss rate, depending largely on the local soil and climate conditions. Spatially, under a certain crop residue retention rate, a relatively higher soil C sink were generally found across the central parts of the United States, western Europe, northern regions of China, while a relatively smaller soil C sink generally occurred in regions at high latitudes of both northern and southern hemisphere, and SOC decreased across the equatorial zones of Asia, Africa and America. We found that SOC change was significantly influenced by the crop residue retention rate (linearly positive), and the edaphic variable of initial SOC content (linearly negative). Temperature had weakly negative effects, and precipitation had significantly negative impacts on SOC changes. The results can help target carbon input management for effectively mitigating climate change through cropland soil C sequestration on a global scale.

Spatial heterogeneity and environmental controllers of soil organic carbon stocks in a boreal forest

2020 ◽  
Author(s):  
Udaya Vitharana ◽  
Nora Casson ◽  
Darshani Kumaragamage ◽  
Geoff Gunn ◽  
Scott Higgins ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Spatial Variability ◽  
Boreal Forest ◽  
Spatial Heterogeneity ◽  
Surface Soil ◽  
Local Scale ◽  
Gravel Content ◽  
Soc Stock ◽  
Soc Stocks

<p>The knowledge of spatial heterogeneity and environmental controllers of soil organic carbon (SOC) stocks is essential for upscaling and predicting SOC dynamics under changing land use and climatic conditions.  This study investigated the spatial variability and intrinsic and extrinsic controllers of SOC stocks in a boreal forest catchment (320 ha) at the International Institute for Sustainable Development Experimental Lakes Area in Ontario, Canada. Forty-seven surface soil (0-30 cm) samples, representative of the spatial variability of topography, surface water flow patterns and vegetation distribution, were obtained within the catchment. Air dried soil samples were sieved to separate gravel (>2 mm) and fine-earth (<2 mm) fractions and were analyzed for SOC concentration using the loss-on-ignition method. Core sample method was used to determine the soil bulk density. SOC concentrations in surface soils showed a large spatial variability (1.2% to 50.4%, CV= 111.3%). Thick organic soil layers in the wetlands of the sub-catchment showed the highest SOC concentrations. The surface soil SOC stocks ranged between 14.5 to 240.5 Mg ha-1 with an average stock of 101.5 Mg ha-1. Spatial autocorrelations of SOC stocks were modelled by calculating relevant variograms. The variability of SOC stocks (sill = 834) was dominated by the random variability (nugget=275) whereas the variability of SOC concentration (sill = 2.5) was dominated by the spatially structured variability (nugget = 0). We found a strong spatial autocorrelation of the SOC concentrations within the catchment, but the SOC stocks were less spatially correlated. This was largely due to the heterogeneity in the thickness of the surface soil layer (10 cm - 30 cm) and in the gravel content (0-28.9%). We found that a large over-estimation of SOC stocks (52.5%) could result if these intrinsic factors are not considered. Extrinsic controllers were generally not significantly related to the SOC stock; Spearman’s rank correlation analysis on the entire dataset showed non-significant relationships between the SOC stock and extrinsic controllers, namely NDVI (r = 0.04) elevation (r = 0.2), slope (r = -0.1) and topographic indices, stream power index (r = -0.1), relative position index (r=-0.2) and plan curvature (r = -0.1). However, regression tree analysis revealed local-scale effects of aspect, NDVI, elevation, and distance to ridge on the SOC stocks. Many forest soil databases lack information of gravel content and soil depth. Thus, upscaling boreal forest SOC stocks without these two key intrinsic controllers can lead to higher uncertainties in  SOC stock estimates. Further, the impacts of extrinsic controllers may vary across heterogenous landscapes. Machine learning-based digital soil mapping techniques such as Random Forest models are more appropriate for incorporating local-scale impacts of extrinsic controllers when upscaling SOC stocks of boreal forest soils. </p>

scholarly journals Soil organic carbon stocks under different land uses in Chure region of Makawanpur district, Nepal

2019 ◽  
Vol 16 (2) ◽  
pp. 13-23 ◽  
Author(s):  
P Ghimire ◽  
B Bhatta ◽  
B Pokhrel ◽  
G Kafle ◽  
P Paudel
Keyword(s):  
Land Use ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Management Practices ◽  
C Sequestration ◽  
Organic Carbon Content ◽  
Degraded Forest ◽  
Degraded Land ◽  
Soil C ◽  
Soc Stock

Soil C sequestration through enhanced land use is a good strategy to mitigate the increasing concentration of atmospheric CO2. A study was conducted in Chhatiwan VDC of Makawanpur District to compare soil organic carbon (SOC) stocks of four main land use types such as forest, degraded forest, Khet and Bari land. Stratified random sampling method was used for collecting soil samples. Organic carbon content was determined by Walkley and Black method. Total SOC stock of different types of land followed the order: as Forest (110.0 t ha-1) > Bari (96.5 t ha-1) > Khet (86.8 t ha-1) > Degraded land (72.0 t ha-1). The SOC% declined with soil depths. The SOC% at 0–20 cm depth was highest (1.26 %) that recorded in the forest soils and lowest (0.37%) at 80- 100cm depth in degraded forest land. Thus, the SOC stock varied with land use systems and soil depths. The study suggests a need for appropriate land use strategy and sustainable soil management practices to improve SOC stock. SAARC J. Agri., 16(2): 13-23 (2018)

High organic carbon input can accelerate global warming in rice paddy soil: increase unprotected soil organic carbon and CH4 emission

2021 ◽  
Author(s):  
Hyeonji Song ◽  
Snowie Galgo ◽  
Ronley Canatoy ◽  
Hogyeong Chae ◽  
Pil Joo Kim
Keyword(s):  
Global Warming ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Rice Paddy ◽  
C Sequestration ◽  
Soil C ◽  
Saturation Degree ◽  
Soil Saturation ◽  
Soc Stock ◽  
Soil C Sequestration

<p>Soil C sequestration is widely regarded as the most reasonable way to mitigate global warming. Traditionally, a high amount of organic carbon (OC) input is strongly recommended to increase soil organic carbon (SOC) stocks in croplands. However, according to the whole-soil saturation theory, stable SOC (mineral-associated SOC) accumulation can be limited at a certain point, relying on silt and clay contents. Most studies based on the theory were conducted in aerobic soil condition. This relationship is still uncertain in a rice paddy that makes up 10.8% of total arable land and has an anaerobic soil environment. In this study, we investigated high OC addition can enhance soil C sequestration in a rice paddy. We added different OC levels (0.5, 2.0, 2.9, and 4.6 Mg C ha<sup>-1</sup> yr<sup>-1</sup>) in rice paddy by incorporating cover crop biomass for nine years. SOC stock and soil saturation degree were determined. Unprotected, sand-associated, silt-associated, and clay-associated SOC were separated via density and size fractionation. Respired C losses (CO<sub>2</sub>-C and CH<sub>4</sub>-C) were monitored using the static closed chamber method. SOC stock did not linearly increase with higher amount of OC input. The carbon sequestration efficiency (i.e. the increase of SOC per unit of OC input) decreases with the amount OC added. Higher OM input significantly increased unprotected labile SOC content. Unprotected SOC (<1.85 g cm<sup>-3</sup>) exponentially increased as the SOC saturation degree was higher. On the other hand, stable SOC content did not exhibit a linear relationship with the SOC saturation degree. The higher OC addition level exponentially increased respired C loss. In particular, C loss via CH<sub>4</sub> was more sensitive to high OC addition. We conclude that higher OC addition in rice paddy without consideration in terms of SOC stock saturation point can accelerate global warming by increasing labile SOC accumulation and CH<sub>4</sub> emission.</p>

scholarly journals Estimating soil organic carbon stocks of Swiss forest soils by robust external-drift kriging

2013 ◽  
Vol 6 (4) ◽  
pp. 7077-7116
Author(s):  
M. Nussbaum ◽  
A. Papritz ◽  
A. Baltensweiler ◽  
L. Walthert
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Near Infrared ◽  
Likelihood Method ◽  
Standard Errors ◽  
Soil Profiles ◽  
Near Infrared Reflectance ◽  
Soc Stock ◽  
Soc Stocks ◽  
External Drift

Abstract. Accurate estimates of soil organic carbon (SOC) stocks are required to quantify carbon sources and sinks caused by land use change at national scale. This study presents a novel robust kriging method to precisely estimate regional and national mean SOC stocks, along with truthful standard errors. We used this new approach to estimate mean forest SOC stock for Switzerland and for its five main ecoregions. Using data of 1033 forest soil profiles, we modelled stocks of two compartments (0–30, 0–100 cm depth) of mineral soils. Lognormal regression models that accounted for correlation between SOC stocks and environmental covariates and residual (spatial) auto-correlation were fitted by a newly developed robust restricted maximum likelihood method, which is insensitive to outliers in the data. Precipitation, near-infrared reflectance, topographic and aggregated information of a soil and a geotechnical map were retained in the models. Both models showed weak but significant residual autocorrelation. The predictive power of the fitted models, evaluated by comparing predictions with independent data of 175 soil profiles, was moderate (robust R2 = 0.34 for SOC stock in 0–30 cm and R2 = 0.40 in 0–100 cm). Prediction standard errors (SE), validated by comparing point prediction intervals with data, proved to be conservative. Using the fitted models we mapped forest SOC stock by robust external-drift point kriging at high resolution across Switzerland. Predicted mean stocks in 0–30 cm and 0–100 cm depth were equal to 7.99 kg m−2 (SE 0.15 kg m−2) and 12.58 kg m−2 (SE 0.24 kg m−2), respectively. Hence, topsoils store about 64% of SOC stocks down to 100 cm depth. Previous studies underestimated SOC stocks of topsoil slightly and those of subsoils strongly. The comparison further revealed that our estimates have substantially smaller SE than previous estimates.

scholarly journals Spatial heterogeneity and environmental predictors of permafrost region soil organic carbon stocks

2021 ◽  
Vol 7 (9) ◽  
pp. eaaz5236 ◽  
Author(s):  
Umakant Mishra ◽  
Gustaf Hugelius ◽  
Eitan Shelef ◽  
Yuanhe Yang ◽  
Jens Strauss ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Spatial Heterogeneity ◽  
Surface Air Temperature ◽  
Spatially Explicit ◽  
Soil Profiles ◽  
Permafrost Region ◽  
Environmental Predictors ◽  
Soil Organic Carbon Stocks ◽  
Soc Stocks

Large stocks of soil organic carbon (SOC) have accumulated in the Northern Hemisphere permafrost region, but their current amounts and future fate remain uncertain. By analyzing dataset combining >2700 soil profiles with environmental variables in a geospatial framework, we generated spatially explicit estimates of permafrost-region SOC stocks, quantified spatial heterogeneity, and identified key environmental predictors. We estimated that 1014−175+194 Pg C are stored in the top 3 m of permafrost region soils. The greatest uncertainties occurred in circumpolar toe-slope positions and in flat areas of the Tibetan region. We found that soil wetness index and elevation are the dominant topographic controllers and surface air temperature (circumpolar region) and precipitation (Tibetan region) are significant climatic controllers of SOC stocks. Our results provide first high-resolution geospatial assessment of permafrost region SOC stocks and their relationships with environmental factors, which are crucial for modeling the response of permafrost affected soils to changing climate.

scholarly journals Soil Organic Carbon Dynamics in Semi-Arid Irrigated Cropping Systems

Agronomy ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 484
Author(s):  
Andrew M. Bierer ◽  
April B. Leytem ◽  
Robert S. Dungan ◽  
Amber D. Moore ◽  
David L. Bjorneberg
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Empirical Data ◽  
Cropping Systems ◽  
C Sequestration ◽  
Conventional Tillage ◽  
Dndc Model ◽  
Application Timing ◽  
Winter Triticale ◽  
Semi Arid

Insufficient characterization of soil organic carbon (SOC) dynamics in semi-arid climates contributes uncertainty to SOC sequestration estimates. This study estimated changes in SOC (0–30 cm depth) due to variations in manure management, tillage regime, winter cover crop, and crop rotation in southern Idaho (USA). Empirical data were used to drive the Denitrification Decomposition (DNDC) model in a “default” and calibrated capacity and forecast SOC levels until 2050. Empirical data indicates: (i) no effect (p = 0.51) of winter triticale on SOC after 3 years; (ii) SOC accumulation (0.6 ± 0.5 Mg ha–1 year–1) under a rotation of corn-barley-alfalfax3 and no change (p = 0.905) in a rotation of wheat-potato-barley-sugarbeet; (iii) manure applied annually at rate 1X is not significantly different (p = 0.75) from biennial application at rate 2X; and (iv) no significant effect of manure application timing (p = 0.41, fall vs. spring). The DNDC model simulated empirical SOC and biomass C measurements adequately in a default capacity, yet specific issues were encountered. By 2050, model forecasting suggested: (i) triticale cover resulted in SOC accrual (0.05–0.27 Mg ha–1 year–1); (ii) when manure is applied, conventional tillage regimes are favored; and (iii) manure applied treatments accrue SOC suggesting a quadratic relationship (all R2 > 0.85 and all p < 0.0001), yet saturation behavior was not realized when extending the simulation to 2100. It is possible that under very large C inputs that C sequestration is favored by DNDC which may influence “NetZero” C initiatives.

scholarly journals Molecular trade-offs in soil organic carbon composition at continental scale

2020 ◽  
Vol 13 (10) ◽  
pp. 687-692 ◽  
Author(s):  
Steven J. Hall ◽  
Chenglong Ye ◽  
Samantha R. Weintraub ◽  
William C. Hockaday
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Continental Scale ◽  
Trade Offs ◽  
Carbon Composition
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