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Modeling Carbon Fluxes Using Multi-Temporal MODIS Imagery and CO2 Eddy Flux Tower Data in Zoige Alpine Wetland, South-West China

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Abstract

An accurate and synoptic quantification of gross primary production (GPP) in wetland ecosystems is essential for assessing carbon budgets at regional or global scales. In this study, a satellite-based Vegetation Photosynthesis Model (VPM) integrated with observed eddy tower and remote sensing data was employed and adapted to evaluate the feasibility and dependability of the model for estimating GPP in an alpine wetland, located in Zoige, Southwestern China. Eddy flux data from 2-year observations showed that temperature explained most of the seasonal variability in carbon fluxes and that warming increased GPP and ecosystem respiration, and hence affected the carbon balance of alpine wetlands. The comparison between modeled and observed GPP fluxes indicated that simulated values were largely in agreement with tower-based values (P < 0.0001). 12-year long-term simulations (2000–2011) found that (1) there was significantly increasing trends at rate of 17.01 gCm−2 year−1 for annual GPP (R 2 = 0.62, P = 0.002); (2) the inter-annual variation in GPP was highly sensitive to climate warming; and (3) a warmer climate can prolong the plant growing season and, by that, increase wetland productivity. Our results demonstrated that the satellite-driven VPM model has the potential to be applied at large spatial and temporal scales for scaling-up carbon fluxes of alpine wetlands.

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Acknowledgments

This study was supported by Forestry Nonprofit Industry Scientific Research Special Project (No. 201204201), the National Science and Technology Support Program of China (2012BAC19B04), the National Youth Science Foundation of China (Grant No. 31300417), the National Natural Science Foundation of China (Grant No. 31170459), the research program ‘Climate Change: Carbon Budget and Relevant Issues’ of the Chinese Academy of Sciences (Grant No. XDA05050402) and the National Natural Science Foundation of China (No.50239020). X. Xiao was supported by a research gran from the NASA Earth Observing System (EOS) Data Analysis Program (NNX09AE93G). We thank the principal investigators of the MODIS data products as well as the Oak Ridge National Laboratory’s (ORNL) Distributed Active Archive Center (DAAC) and the Earth Observing System (EOS) Data Gateway for making these MODIS products available. We thank two anonymous reviewers for their valuable comments and suggestions on an earlier version of the manuscript.

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Authors and Affiliations

  1. Chinese Academy of Forestry, Institute of Wetland Research, Beijing, 100091, China

    Xiaoming Kang

  2. College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China

    Xiaoming Kang, Yanfen Wang, Xiaoyong Cui, Lei Zhong & Yanbin Hao

  3. Chinese Academy of Sciences, Chengdu Institute of Biology, Chengdu, 610041, China

    Huai Chen

  4. College of Forestry, Northwest Agriculture and Forest University, Yanglin, 712100, China

    Huai Chen

  5. State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China

    Jianqing Tian

  6. School of Earth and Environment, The University of Western Australia, Crawley, WA, 6009, Australia

    Yichao Rui

  7. Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, 90183, Umeå, Sweden

    Paul Kardol

  8. Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK, 73019, USA

    Xiangming Xiao

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  1. Xiaoming Kang
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Kang, X., Wang, Y., Chen, H. et al. Modeling Carbon Fluxes Using Multi-Temporal MODIS Imagery and CO2 Eddy Flux Tower Data in Zoige Alpine Wetland, South-West China. Wetlands 34, 603–618 (2014). https://doi.org/10.1007/s13157-014-0529-y

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