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Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

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Front. Earth Sci.    2020, Vol. 14 Issue (1) : 13-24    https://doi.org/10.1007/s11707-019-0763-y
RESEARCH ARTICLE
Comparison and analysis of three estimation methods for soil carbon sequestration potential in the Ebinur Lake Wetland, China
Yonghui WANG1,2, Kexiang LIU1,2, Zhaopeng WU1,2, Li JIAO1,2()
1. Xinjiang Laboratory of Lake Environment and Resources in Arid Zone, Xinjiang Normal University, Urumqi 830054, China
2. College of Geography and Tourism, Xinjiang Normal University, Urumqi 830054, China
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Abstract

Based on soil under seven vegetation types, the carbon sequestration potential in the Ebinur Lake wetland was estimated using the maximum value method, the saturation value method, and the classification and grading method. Results indicated that: 1) Soil carbon sequestration results for the top 20 cm soil layer were about 1.88 Mt using the maximum value method; the middle level standard of the classification and grading method result was 1.71 Mt. 2) Soil carbon sequestration potential in the top 20 cm layer under different vegetation types, evaluated using the saturation value method and the classification-grading method, ranged from 0.45 to 0.67 Mt, accounting for about 5/16 of the ideal carbon sequestration potential. 3) Carbon sequestration potential calculated using the saturation method and the classification method (middle level standard), combining the soil organic carbon increment under different vegetation types in Ebinur Lake wetland, recorded an average growth rate of soil organic carbon around 0.7–1 kg/(hm2·a). Time required to reach its carbon sequestration potential was 41 to 144 a. These results indicate that soil organic carbon content dynamically changes, and different forms of land use affect soil organic carbon content. The potential and ability of soil carbon sequestration and its mechanism of dynamic change are investigated, providing a scientific basis for understanding regional carbon cycle and climate change in wetlands.
Keywords Ebinur Lake      wetland      soil      carbon sequestration potential     
Corresponding Author(s): Li JIAO   
Just Accepted Date: 01 August 2019   Online First Date: 30 October 2019    Issue Date: 24 March 2020
 Cite this article:   
Yonghui WANG,Kexiang LIU,Zhaopeng WU, et al. Comparison and analysis of three estimation methods for soil carbon sequestration potential in the Ebinur Lake Wetland, China[J]. Front. Earth Sci., 2020, 14(1): 13-24.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-019-0763-y
https://academic.hep.com.cn/fesci/EN/Y2020/V14/I1/13
Fig.1  Sample point distribution around Ebinur Lake
Vegetation Section number
Dry lakebed 16
Desert riparian forest 5
Halophyte shrub 3
Saline meadow 10
Desert shrub 11
Alpine coniferous forest 5
Microphanerophytes desert 57
Total 107
Tab.1  Sampling point design
Fig.2  Interval distribution of organic carbon content in the different vegetation types
Vegetation Sample SOC Max
/g/kg		 C density increment/t/hm2 Area
/hm2		 SCS/t
Dry lakebed 14 19.86 3.87 41464.33 160466.96
Desert riparian forest 4 7.59 0.50 44851.19 22425.60
Halophyte shrub 3 3.29 0.11 637.85 70.16
Saline meadow 9 322.8 42.60 11571.05 492926.73
Desert shrub 10 25.92 4.04 148134.24 598462.33
Alpine coniferous forest 4 7.82 0.69 20614.47 14223.98
Microphanerophytes desert 56 84.82 17.53 33699.9 590759.25
Total 100 69.34 1879335.01
Tab.2  Carbon sequestration potential in the different vegetation types
Fig.3  Organic carbon content and variables in the different vegetation types
Vegetation types Sample Area
/hm2		 SOC increment
/g/kg		 C density increment
/t/hm2		 SCS/t
Dry lakebed 15 41464.33 4.26 1.31 54318.27
Desert riparian forest 5 44851.19 3.04 1.06 47542.26
Halophyte shrub 4 637.85 2.42 0.8 510.28
Saline meadow 10 11571.05 34.89 15.83 183169.72
Desert shrub 11 148134.24 0.32 3.07 454772.12
Alpine coniferous forest 5 20614.47 3.87 1.32 27211.10
Microphanerophytes desert 57 33699.90 9.59 5.02 169173.50
Total 107 300973.03 58.39 28.41 936697.25
Tab.3  Estimation of different vegetation types using the saturation value method
level low lower middle higher high
Dry lakebed 26227.66 42657.61 73849.88 253729.39 321360.87
Desert riparian forest 33866.92 118236.19 233750.43 311667.24 338038.32
Halophyte shrub 309.99 2522.17 3783.25 5044.33 5333.12
Saline meadow 169813.83 232814.79 494174.88 676096.41 858017.93
Desert shrub 252510.46 653875.34 671487.45 1243015.91 1538013.22
Alpine coniferous forest 37652.13 56399.64 112799.29 162148.98 268497.19
Microphanerophytes desert 262751.62 706493.52 118116.3 1438343.95 2045644.73
Total 783132.61 1812999.26 1707961.48 4090046.21 5374905.38
Tab.4  Carbon sequestration potential of the vegetation types under different carbon sequestration levels/t
vegetation Area
/hm2		 Bulk density
/g·cm−3		 Sample SOC increment
/g/kg		 C density increment
/t/hm2		 SCS/t
Dry lakebed 41464.33 1.54 16 5.78 1.78 73849.88
Desert riparian forest 44851.19 1.74 5 15.00 5.21 233750.43
Halophyte shrub 637.85 1.65 3 18.00 5.93 3783.25
Saline meadow 11571.05 2.27 10 94.13 42.71 494174.88
Desert shrub 148134.24 1.62 11 14.00 4.53 671487.45
Alpine coniferous forest 20614.47 1.98 5 16.00 5.47 112799.29
Microphanerophytes desert 33699.90 1.68 57 66.89 35.05 118116.30
Total 300973.03 12.48 107 229.8 100.68 1707961.48
Tab.5  Carbon sequestration potential of the different vegetation types at the moderate level
Fig.4  Soil organic carbon and standard deviation with the different vegetation types
Method C density increment
/t/hm2		 SCS/t
Max Min Max Min
Maximum value method 42.60 0.11 598462.33 70.16
Saturation method 15.83 0.8 454772.12 510.28
Classification grading method (H) 74.15 7.54 2045644.73 5333.12
Classification grading method (M) 42.71 1.78 671487.45 3783.25
Classification grading method (L) 14.68 0.49 262751.62 309.99
Tab.6  Comparison of carbon sequestration potential under the different estimation methods
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