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Changes in soil carbon stock predicted by a process-based soil carbon model (Yasso07) in the Yanhe watershed of the Loess Plateau

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Abstract

Contex

Soil carbon sequestration is an ecosystem process that can provide important ecosystem services such as climate regulation and mitigation of global warming. Spatiotemporal variation in the soil organic carbon (SOC) stock is the basic information needed for landscape management and determination of regional carbon budgets.

Objectives

The objective of this study was to evaluate the effect of ecological restoration on SOC stocks and determine the influences of multiple factors in the Yanhe watershed of the Loess Plateau.

Methods

We coupled the Yasso07 soil carbon model with remote sensing indices as model input. The model performance was evaluated by uncertainty and sensitivity analyses as well as validation against field measurement.

Results

The modeling captured the spatial pattern of SOC variability across the landscape generally well. Net primary productivity (NPP) was the foremost factor that affecting the spatiotemporal variation of SOC density. Converting cropland to grassland was the most efficient restoration type in soil carbon sequestration in the study period. Land use change influenced the spatial correlation between NPP and SOC density by altering both litter quantity and quality. The changes in land use area tended to have higher contributions to the changes in SOC stock than did the changes in SOC density for different land use types.

Conclusions

The overall effect of ecological restoration on soil carbon sequestration was dependent on the main vegetation restoration type and the time of recovery. Human-derived land use changes could have more substantial effects on soil carbon budgets compared to natural factors in a short period of time.

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Acknowledgments

This study is financially supported by the National Natural Science Foundation of China (Nos. 41230745, 41201182), the Chinese Academy of Sciences (Nos. XDA05050602-05-01 and GJHZ1215), and the Academy of Finland (No. 256231). We thank the three anonymous reviewers for their constructive comments and suggestions.

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Authors and Affiliations

  1. State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-environmental Sciences (RCEES), Chinese Academy of Sciences, Beijing, 100085, China

    Nan Lu, Xing Wu, Xiaoming Feng & Bojie Fu

  2. Ecosystem Processes, Natural Environment Centre, Finnish Environment Institute (SYKE), P.O. Box 140, 00251, Helsinki, Finland

    Anu Akujärvi, Jari Liski & Maria Holmberg

  3. State Key Laboratory of Soil Erosion and Dryland Farming on Loess Plateau, Northwest A&F University, Yangling, Shaanxi, China

    Zhongming Wen

  4. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100101, China

    Yuan Zeng

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  1. Nan Lu
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  2. Anu Akujärvi
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  3. Xing Wu
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  4. Jari Liski
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  5. Zhongming Wen
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  6. Maria Holmberg
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  7. Xiaoming Feng
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  8. Yuan Zeng
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  9. Bojie Fu
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Correspondence to Nan Lu.

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Lu, N., Akujärvi, A., Wu, X. et al. Changes in soil carbon stock predicted by a process-based soil carbon model (Yasso07) in the Yanhe watershed of the Loess Plateau. Landscape Ecol 30, 399–413 (2015). https://doi.org/10.1007/s10980-014-0132-x

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