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Estimation of Soil Respiration by Its Driving Factors Based on Multi-Source Data in a Sub-Alpine Meadow in North China

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  • Yanan Liang

    (State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
    Institute of Loess Plateau, Shanxi University, Taiyuan 030006, China
    Beijing Engineering Research Center for Watershed Environmental Restoration & Integrated Ecological Regulation, School of Environment, Beijing Normal University, Beijing 100875, China)

  • Yanpeng Cai

    (State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
    Institute for Energy, Environment and Sustainable Communities, University of Regina, 120, 2 Research Drive, Regina, SK S4S 7H9, Canada
    Beijing Engineering Research Center for Watershed Environmental Restoration & Integrated Ecological Regulation, School of Environment, Beijing Normal University, Beijing 100875, China)

  • Junxia Yan

    (Institute of Loess Plateau, Shanxi University, Taiyuan 030006, China)

  • Hongjian Li

    (Institute of Loess Plateau, Shanxi University, Taiyuan 030006, China)

Abstract

Soil respiration ( R s ) in high-altitude areas are normally sensitive to varying climatic conditions. The objective of this research was mainly to explore temporal variations in R s rates and the corresponding controlling factors for the establishment of appropriate fitting models in a sub-alpine meadow of north China. The data was obtained through field measuring and extraction of the Moderate Resolution Imaging Spectroradiometer (MODIS) in the geographical unit of the study site over the period of 2007 to 2015. The main results were as follows: (1) seasonal variations in R s rates, soil temperature ( T s ), land surface temperature (LST), and normalized difference vegetation index (NDVI) all produced symmetrical bell type patterns, while soil moisture ( M s ) showed a fluctuating pattern, (2) a T s -exponential model could greatly capture seasonal variations of R s rates in the study site, reflecting the role of temperature as a dominant driving factor in determining R s temporal variations in alpine meadow areas, (3) there was no significant difference between the performing indicators evaluating the proposed T s -exponential model and the LST-exponential model. This indicated great potential for applying remote sensing products to estimate seasonal R s rates and 4) seasonal variations in R s rates towards temperature sensitivity (Q 10 ) showed a concave curve and dramatically decreased as the temperature increased from −1 to 11 °C. Overall, the results indicated that attention to significant effects of climatic conditions on R s , particularly in areas of low temperature, should be warranted. Also, applicability of remote sensing products for estimating R s was reflected and demonstrated.

Suggested Citation

  • Yanan Liang & Yanpeng Cai & Junxia Yan & Hongjian Li, 2019. "Estimation of Soil Respiration by Its Driving Factors Based on Multi-Source Data in a Sub-Alpine Meadow in North China," Sustainability, MDPI, vol. 11(12), pages 1-17, June.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:12:p:3274-:d:239614
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    References listed on IDEAS

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    1. Ben Bond-Lamberty & Allison Thomson, 2010. "Temperature-associated increases in the global soil respiration record," Nature, Nature, vol. 464(7288), pages 579-582, March.
    2. Eric A. Davidson & Ivan A. Janssens, 2006. "Temperature sensitivity of soil carbon decomposition and feedbacks to climate change," Nature, Nature, vol. 440(7081), pages 165-173, March.
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