scholarly journals Investigating Spatial and Vertical Patterns of Wetland Soil Organic Carbon Concentrations in China’s Western Songnen Plain by Comparing Different Algorithms

2020 ◽  
Vol 12 (3) ◽  
pp. 932 ◽  
Author(s):  
Yongxing Ren ◽  
Xiaoyan Li ◽  
Dehua Mao ◽  
Zongming Wang ◽  
Mingming Jia ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Land Surface ◽  
Environmental Variables ◽  
Support Vector ◽  
Wetland Soil ◽  
Songnen Plain ◽  
Attribute Importance ◽  
Organic Carbon Concentration ◽  
Different Depths

Investigating the spatial and vertical patterns of wetland soil organic carbon concentration (SOCc) is important for understanding the regional carbon cycle and managing the wetland ecosystem. By integrating 160 wetland soil profile samples and environmental variables from climatic, topographical, and remote sensing data, we spatially predicted the SOCc of wetlands in China’s Western Songnen Plain by comparing four algorithms: random forest (RF), support vector machine (SVM) for regression, inverse distance weighted (IDW), and ordinary kriging (OK). The predicted results of the SOCc from the different algorithms were validated against independent testing samples according to the mean error, root mean squared error, and correlation coefficient. The results show that the measured SOCc values at depths of 0–30, 30–60, and 60–100 cm were 15.28, 7.57, and 5.22 g·kg−1, respectively. An assessment revealed that the RF algorithm was most accurate for predicting SOCc; its correlation coefficients at the different depths were 0.82, 0.59, and 0.51, respectively. The attribute importance from the RF indicates that environmental variables have various effects on the SOCc at different depths. The land surface temperature and land surface water index had a stronger influence on the spatial distribution of SOCc at the depths of 0–30 and 30–60 cm, whereas topographic factors, such as altitude, had a stronger influence within 60–100 cm. The predicted SOCc of each vertical depth increased gradually from south to north in the study area. This research provides an important case study for predicting SOCc, including selecting factors and algorithms, and helps with understanding the carbon cycles of regional wetlands.

scholarly journals Soil-Organic-Carbon Concentration and Storage under Different Land Uses in the Carrizal-Chone Valley in Ecuador

2018 ◽  
Vol 9 (1) ◽  
pp. 45
Author(s):  
Lizardo Reyna-Bowen ◽  
Lenin Vera-Montenegro ◽  
Lizardo Reyna
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Profile ◽  
Soil Management ◽  
Livestock Grazing ◽  
Total Carbon ◽  
Silty Clay ◽  
Important Indicator ◽  
Organic Carbon Concentration ◽  
Different Depths

Soil organic carbon (SOC) is an important indicator of soil quality; an elevated percentage of SOC indicates very high-quality soil, physically as well as chemically. As such, the principal objective of the present study was to determine the concentration of SOC at different depths, as well as its accumulation through the entire soil profile. The Carrizal-Chone system (SCCH) area was stratified by agricultural use. Sixty-three soil samples were taken from different depths of up to a maximum of 150 cm. The physical and chemical properties of the soil were determined. SOC was determined by the Walkley and Black method. The following results are highlighted: (1) 21 different varieties of soil management were identified; (2) the largest area was livestock grazing land, which had the greatest concentration of SOC; (3) the type of soil with the greatest SOC sequestration capacity was silty clay loam; (4) the area cultivated with corn presented the highest accumulation of total carbon; and (5) the highest concentration of SOC was found in the top 40 cm, with a tendency to decrease with depth. It is concluded that soil management influences the concentration and accumulation of SOC in the topsoil layers and the entire soil profile.

scholarly journals Combining Artificial Neural Network and Ordinary Kriging to Predict Wetland Soil Organic Carbon Concentration in China’s Liao River Basin

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7005
Author(s):  
Yingdong Kang ◽  
Xiaoyan Li ◽  
Dehua Mao ◽  
Zongming Wang ◽  
Mingxuan Liang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
River Basin ◽  
Carbon Concentration ◽  
Ordinary Kriging ◽  
Wetland Soil ◽  
Organic Carbon Concentration ◽  
Artificial Neural

Accurate prediction of wetland soil organic carbon concentration and an understanding of its controlling factors are important for studying regional climate change and wetland carbon cycles; with that knowledge mechanisms can be put in place that are conducive to sustainable ecosystem management for environmental health. In this study, a hybrid approach combining an artificial neural network and ordinary kriging and 103 soil samples at three soil depth ranges (0–30, 30–60, and 60–100 cm) were used to predict wetland soil organic carbon concentration in China’s Liao River Basin. The model evaluation indicated that a combination of artificial neural network and ordinary kriging and limited soil samples achieved good performance in predicting wetland soil organic carbon concentration. Wetland soil organic carbon concentration in the Liao River Basin has apparent spatial and vertical heterogeneities with values decreasing from southeast to northwest and concentrates present mainly in the topsoil (0–30 cm). Mean wetland soil organic carbon concentration values at the three soil depths were 10.43 ± 0.38, 7.93 ± 0.25, and 7.61 ± 0.22 g/kg, respectively, which are smaller than those over other wetland regions in Northeast China. Terrain aspect contributed the most in predicting wetland soil organic carbon concentration at each of the three soil depths, followed by normalized difference vegetation index at 0–30 cm and mean annual precipitation at 30–60 and 60–100 cm. This study provides a framework method and baseline to quantify the soil organic carbon concentration dynamics in response to climatic and anthropogenic drivers.

Long-term (47 yr) effects of tillage and frequency of summerfallow on soil organic carbon in a Dark Brown Chernozem soil in western Canada

2016 ◽  
Vol 96 (4) ◽  
pp. 347-350 ◽  
Author(s):  
Elwin G. Smith ◽  
H. Henry Janzen ◽  
Lauren Scherloski ◽  
Francis J. Larney ◽  
Benjamin H. Ellert
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Concentration ◽  
Western Canada ◽  
Conservation Value ◽  
Chernozem Soil ◽  
No Till ◽  
Organic Carbon Concentration ◽  
Annual Changes

After 47 yr of no-till and reduced summerfallow at Lethbridge, Alberta, soil organic carbon concentration and stocks increased 2.14 g kg−1 and 2.22 Mg ha−1, respectively, in the surface 7.5 cm layer. These findings confirmed the conservation value of reducing tillage and summerfallow. The annual changes were relatively small.

scholarly journals Australian net (1950s–1990) soil organic carbon erosion: implications for CO<sub>2</sub> emission and land–atmosphere modelling

2014 ◽  
Vol 11 (18) ◽  
pp. 5235-5244 ◽  
Author(s):  
A. Chappell ◽  
N. P. Webb ◽  
R. A. Viscarra Rossel ◽  
E. Bui
Keyword(s):  
Soil Erosion ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Land Surface ◽  
Total Carbon ◽  
Catchment Scale ◽  
European Settlement ◽  
Surface Models ◽  
Management Context ◽  
Land Use And Management

Abstract. The debate remains unresolved about soil erosion substantially offsetting fossil fuel emissions and acting as an important source or sink of CO2. There is little historical land use and management context to this debate, which is central to Australia's recent past of European settlement, agricultural expansion and agriculturally-induced soil erosion. We use "catchment" scale (∼25 km2) estimates of 137Cs-derived net (1950s–1990) soil redistribution of all processes (wind, water and tillage) to calculate the net soil organic carbon (SOC) redistribution across Australia. We approximate the selective removal of SOC at net eroding locations and SOC enrichment of transported sediment and net depositional locations. We map net (1950s–1990) SOC redistribution across Australia and estimate erosion by all processes to be ∼4 Tg SOC yr−1, which represents a loss of ∼2% of the total carbon stock (0–10 cm) of Australia. Assuming this net SOC loss is mineralised, the flux (∼15 Tg CO2-equivalents yr−1) represents an omitted 12% of CO2-equivalent emissions from all carbon pools in Australia. Although a small source of uncertainty in the Australian carbon budget, the mass flux interacts with energy and water fluxes, and its omission from land surface models likely creates more uncertainty than has been previously recognised.

scholarly journals The use of radiocarbon <sup>14</sup>C to constrain carbon dynamics in the soil module of the land surface model ORCHIDEE (SVN r5165)

2018 ◽  
Author(s):  
Marwa Tifafi ◽  
Marta Camino-Serrano ◽  
Christine Hatté ◽  
Hector Morras ◽  
Lucas Moretti ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon ◽  
Land Surface ◽  
Carbon Stock ◽  
Land Surface Model ◽  
Carbon Dynamics ◽  
Total Carbon ◽  
Soil Parameters ◽  
Surface Model

Abstract. Despite the importance of soil as a large component of the terrestrial ecosystems, the soil compartments are not well represented in the Land Surface Models (LSMs). Indeed, soils in current LSMs are generally represented based on a very simplified schema that can induce a misrepresentation of the deep dynamics of soil carbon. Here, we present a new version of the IPSL-Land Surface Model called ORCHIDEE-SOM, incorporating the 14C dynamic in the soil. ORCHIDEE-SOM, first, simulates soil carbon dynamics for different layers, down to 2 m depth. Second, concentration of dissolved organic carbon (DOC) and its transport are modeled. Finally, soil organic carbon (SOC) decomposition is considered taking into account the priming effect. After implementing the 14C in the soil module of the model, we evaluated model outputs against observations of soil organic carbon and 14C activity (F14C) for different sites with different characteristics. The model managed to reproduce the soil organic carbon stocks and the F14C along the vertical profiles. However, an overestimation of the total carbon stock was noted, but was mostly marked on the surface. Then, thanks to the introduction of 14C, it has been possible to highlight an underestimation of the age of carbon in the soil. Thereafter, two different tests on this new version have been established. The first was to increase carbon residence time of the passive pool and decrease the flux from the slow pool to the passive pool. The second was to establish an equation of diffusion, initially constant throughout the profile, making it vary exponentially as a function of depth. The first modifications did not improve the capacity of the model to reproduce observations whereas the second test showed a decrease of the soil carbon stock overestimation, especially at the surface and an improvement of the estimates of the carbon age. This assumes that we should focus more on vertical variation of soil parameters as a function of depth, mainly for diffusion, in order to upgrade the representation of global carbon cycle in LSMs, thereby helping to improve predictions of the future response of soil organic carbon to global warming.

scholarly journals Soil organic carbon stabilization mechanisms and temperature sensitivity in old terraced soils

2021 ◽  
Vol 18 (23) ◽  
pp. 6301-6312
Author(s):  
Pengzhi Zhao ◽  
Daniel Joseph Fallu ◽  
Sara Cucchiaro ◽  
Paolo Tarolli ◽  
Clive Waddington ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Temperature Sensitivity ◽  
Land Surface ◽  
C:N Ratio ◽  
Temperature Sensitive ◽  
Organic C ◽  
Fraction Composition ◽  
Soil Burial ◽  
C Cycle

Abstract. Being the most common human-created landforms, terrace construction has resulted in an extensive perturbation of the land surface. However, our mechanistic understanding of soil organic carbon (SOC) (de-)stabilization mechanisms and the persistence of SOC stored in terraced soils is far from complete. Here we explored the factors controlling SOC stability and the temperature sensitivity (Q10) of abandoned prehistoric agricultural terrace soils in NE England using soil fractionation and temperature-sensitive incubation combined with terrace soil burial-age measurements. Results showed that although buried terrace soils contained 1.7 times more unprotected SOC (i.e., coarse particulate organic carbon) than non-terraced soils at comparable soil depths, a significantly lower potential soil respiration was observed relative to a control (non-terraced) profile. This suggests that the burial of former topsoil due to terracing provided a mechanism for stabilizing SOC. Furthermore, we observed a shift in SOC fraction composition from particulate organic C towards mineral-protected C with increasing burial age. This clear shift to more processed recalcitrant SOC with soil burial age also contributes to SOC stability in terraced soils. Temperature sensitivity incubations revealed that the dominant controls on Q10 depend on the terrace soil burial age. At relatively younger ages of soil burial, the reduction in substrate availability due to SOC mineral protection with aging attenuates the intrinsic Q10 of SOC decomposition. However, as terrace soil becomes older, SOC stocks in deep buried horizons are characterized by a higher temperature sensitivity, potentially resulting from the poor SOC quality (i.e., soil C:N ratio). In conclusion, terracing in our study site has stabilized SOC as a result of soil burial during terrace construction. The depth–age patterns of Q10 and SOC fraction composition of terraced soils observed in our study site differ from those seen in non-terraced soils, and this has implications when assessing the effects of climate warming and terrace abandonment on the terrestrial C cycle.

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