scholarly journals Global Sequestration Potential of Increased Organic Carbon in Cropland Soils

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Robert J. Zomer ◽  
Deborah A. Bossio ◽  
Rolf Sommer ◽  
Louis V. Verchot
2021 ◽  
Author(s):  
Sylvia Vetter ◽  
Michael Martin ◽  
Pete Smith

<p>Reducing greenhouse gas (GHG) emissions in to the atmosphere to limit global warming is the big challenge of the coming decades. The focus lies on negative emission technologies to remove GHGs from the atmosphere from different sectors. Agriculture produces around a quarter of all the anthropogenic GHGs globally (including land use change and afforestation). Reducing these net emissions can be achieved through techniques that increase the soil organic carbon (SOC) stocks. These techniques include improved management practices in agriculture and grassland systems, which increase the organic carbon (C) input or reduce soil disturbances. The C sequestration potential differs among soils depending on climate, soil properties and management, with the highest potential for poor soils (SOC stock farthest from saturation).</p><p>Modelling can be used to estimate the technical potential to sequester C of agricultural land under different mitigation practices for the next decades under different climate scenarios. The ECOSSE model was developed to simulate soil C dynamics and GHG emissions in mineral and organic soils. A spatial version of the model (GlobalECOSSE) was adapted to simulate agricultural soils around the world to calculate the SOC change under changing management and climate.</p><p>Practices like different tillage management, crop rotations and residue incorporation showed regional differences and the importance of adapting mitigation practices under an increased changing climate. A fast adoption of practices that increase SOC has its own challenges, as the potential to sequester C is high until the soil reached a new C equilibrium. Therefore, the potential to use soil C sequestration to reduce overall GHG emissions is limited. The results showed a high potential to sequester C until 2050 but much lower rates in the second half of the century, highlighting the importance of using soil C sequestration in the coming decades to reach net zero by 2050.</p>


PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245040
Author(s):  
Feng Zhang ◽  
Shihang Wang ◽  
Mingsong Zhao ◽  
Falv Qin ◽  
Xiaoyu Liu

Soil organic carbon content has a significant impact on soil fertility and grain yield, making it an important factor affecting agricultural production and food security. Dry farmland, the main type of cropland in China, has a lower soil organic carbon content than that of paddy soil, and it may have a significant carbon sequestration potential. Therefore, in this study we applied the CENTURY model to explore the temporal and spatial changes of soil organic carbon (SOC) in Jilin Province from 1985 to 2015. Dry farmland soil polygons were extracted from soil and land use layers (at the 1:1,000,000 scale). Spatial overlay analysis was also used to extract 1282 soil polygons from dry farmland. Modelled results for SOC dynamics in the dry farmland, in conjunction with those from the Yushu field-validation site, indicated a good level of performance. From 1985 to 2015, soil organic carbon density (SOCD) of dry farmland decreased from 34.36 Mg C ha−1 to 33.50 Mg C ha−1 in general, having a rate of deterioration of 0.03 Mg C ha−1 per year. Also, SOC loss was 4.89 Tg from dry farmland soils in the province, with a deterioration rate of 0.16 Tg C per year. 35.96% of the dry farmland its SOCD increased but 64.04% of the area released carbon. Moreover, SOC dynamics recorded significant differences between different soil groups. The method of coupling the CENTURY model with a detailed soil database can simulate temporal and spatial variations of SOC at a regional scale, and it can be used as a precise simulation method for dry farmland SOC dynamics.


2013 ◽  
Vol 20 (2) ◽  
pp. 653-665 ◽  
Author(s):  
Martin Wiesmeier ◽  
Rico Hübner ◽  
Peter Spörlein ◽  
Uwe Geuß ◽  
Edzard Hangen ◽  
...  

Soil Research ◽  
2014 ◽  
Vol 52 (5) ◽  
pp. 463 ◽  
Author(s):  
Zhongkui Luo ◽  
Enli Wang ◽  
Jeff Baldock ◽  
Hongtao Xing

The diversity of cropping systems and its variation could lead to great uncertainty in the estimation of soil organic carbon (SOC) stock across time and space. Using the pre-validated Agricultural Production Systems Simulator, we simulated the long-term (1022 years) SOC dynamics in the top 0.3 m of soil at 613 reference sites under 59 representative cropping systems across Australia’s cereal-growing regions. The point simulation results were upscaled to the entire cereal-growing region using a Monte Carlo approach to quantify the spatial pattern of SOC stock and its uncertainty caused by cropping system and environment. The predicted potential SOC stocks at equilibrium state ranged from 10 to 140 t ha–1, with the majority in a range 30–70 t ha–1, averaged across all the representative cropping systems. Cropping system accounted for ~10% of the total variance in predicted SOC stocks. The type of cropping system that determined the carbon input into soil had significant effects on SOC sequestration potential. On average, the potential SOC stock in the top 0.3 m of soil was 30, 50 and 60 t ha–1 under low-, medium- and high-input cropping systems in terms of carbon input, corresponding to –2, 18 and 26 t ha–1 of SOC change. Across the entire region, the Monte Carlo simulations showed that the potential SOC stock was 51 t ha–1, with a 95% confidence interval ranging from 38 to 64 t ha–1 under the identified representative cropping systems. Overall, predicted SOC stock could increase by 0.99 Pg in Australian cropland under the identified representative cropping systems with optimal management. Uncertainty varied depending on cropping system, climate and soil conditions. Detailed information on cropping system and soil and climate characteristics is needed to obtain reliable estimates of potential SOC stock at regional scale, particularly in cooler and/or wetter regions.


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