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Temporal variability in the thermal requirements for vegetation phenology on the Tibetan plateau and its implications for carbon dynamics

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Abstract

Static thermal requirements (T req ) are widely used to model the timing of phenology, yet may significantly bias phenological projections under future warming conditions, since recent studies argue that climate warming will increase T req for triggering vegetation phenology. This study investigates the temporal trend and inter-annual variation of T req derived from satellite-based spring and autumn phenology for the alpine and temperate vegetation on the Tibetan Plateau from 1982 to 2011. While we detected persistent warming in both spring and autumn across this time period, we did not find a corresponding long-term increase in T req for most of the study area. Instead, we found a substantial interannual variability of T req that could be largely explained by interannual variations in other climatic factors. Specifically, the number of chilling days and fall temperature were robust variables for predicting the dynamics of T req for spring onset and autumn senescence, respectively. Phenology models incorporating a dynamic T req algorithm performed slightly better than those with static T req values in reproducing phenology derived from SPOT-VGT NDVI data. To assess the degree to which T req variation affects large-scale phenology and carbon cycling projections, we compared the output from versions of the Terrestrial Ecosystem Model that incorporated static and dynamic T req values in their phenology algorithms. Under two contrasting future climate scenarios, the dynamic T req setting reduced the projected growing season length by up to 1–3 weeks by the late twenty-first century, leading to a maximum reduction of 8.9 % in annual net primary production and ~15 % in cumulative net ecosystem production for this region. Our study reveals that temporal dynamics of T req meaningfully affect the carbon dynamics on the Tibetan Plateau, and should thus be considered in future ecosystem carbon modeling.

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Acknowledgments

We thank Zhiyao Tang, Shilong Piao and Yue Shi for helpful comments on the manuscript. This research is supported with a NSF project (DEB- #0919331), the NSF Carbon and Water in the Earth Program (NSF-0630319), the NASA Land Use and Land Cover Change program (NASA-NNX09AI26G), Department of Energy (DE-FG02-08ER64599), and the NSF Division of Information & Intelligent Systems (NSF-1028291), funded to Q.Z.

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Authors and Affiliations

  1. Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, CIVIL 550 Stadium Mall Drive, West Lafayette, IN, 47907-2051, USA

    Zhenong Jin, Qianlai Zhuang & Min Chen

  2. Department of Agronomy, Purdue University, West Lafayette, Indiana, 47907, USA

    Qianlai Zhuang

  3. Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN, 47907, USA

    Jeffrey S. Dukes

  4. Department of Biological Sciences, Purdue University, West Lafayette, IN, 47907, USA

    Jeffrey S. Dukes

  5. Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, 810008, China

    Jin-Sheng He

  6. Department of Ecology, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China

    Jin-Sheng He

  7. Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA

    Andrei P. Sokolov

  8. Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA

    Tonglin Zhang

  9. Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100085, China

    Tianxiang Luo

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  1. Zhenong Jin
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  2. Qianlai Zhuang
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  4. Jin-Sheng He
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  6. Min Chen
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Correspondence to Qianlai Zhuang.

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Jin, Z., Zhuang, Q., Dukes, J.S. et al. Temporal variability in the thermal requirements for vegetation phenology on the Tibetan plateau and its implications for carbon dynamics. Climatic Change 138, 617–632 (2016). https://doi.org/10.1007/s10584-016-1736-8

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  • DOI: https://doi.org/10.1007/s10584-016-1736-8

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