第一作者: | Ren, Yongxing |
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英文第一作者: | Ren, Yongxing |
联系作者: | Mao, Dehua |
英文联系作者: | Mao, Dehua |
发表年度: | 2023 |
卷: | |
摘要: | PurposeAs a huge natural carbon storage, wetlands play an important role in the global carbon cycle. However, the spatial pattern and storage of soil organic carbon (SOC) in wetland ecosystems remain largely uncertain due to large spatial heterogeneity and insufficient field observations.MethodsIn this study, we predict the spatial pattern of SOC density and estimated SOC storage in wetlands of Northeast China based on 819 field samples and multiple geospatial data using random forest algorithm.ResultsThe SOC density of wetlands at different depths was affected differently by environmental factors and the SOC density in the surface layer (0-30 cm) was more susceptible to climatic change. The correlation coefficients (r) between the SOC density predicted by the random forest model and the measured SOC density were 0.86, 0.77 and 0.73 in 0-30, 30-60 and 60-100 cm soil depths, respectively. Our estimation showed that Northeast China holds huge wetland SOC storage in the amount of 3.40 +/- 0.13 Pg C. The average wetland SOC density was 44.30 +/- 1.72 kg C m(-2), which decreased gradually from north to south in the study area.ConclusionThe wetland SOC density in Northeast China decreased with soil depth, and the influence of environmental factors on wetland SOC gradually decreased. Surface wetland SOC may be more sensitive to global climate change. Our results examined the relationship between wetland SOC and environmental factors, which benefits the understanding of the responses of wetland SOC to climate change. |
刊物名称: | PLANT AND SOIL |
参与作者: | Ren, YX (Ren, Yongxing) [1] , [2] ; Li, XY (Li, Xiaoyan) [2] ; Mao, DH (Mao, Dehua) [1] ; Xi, YB (Xi, Yanbiao) [3] ; Wang, ZM (Wang, Zongming) [1] |
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Northeast China holds huge wetland soil organic carbon storage: an estimation from 819 soil profiles
本站小编 Free考研考试/2024-01-13
Northeast China holds huge wetland soil organic carbon storage: an estimation from 819 soil profiles and random forest algorithm