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Tree mortality during long-term droughts is lower in structurally complex forest stands

Author

Listed:
  • Qin Ma

    (Nanjing Normal University
    Ministry of Education
    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application)

  • Yanjun Su

    (Chinese Academy of Sciences
    China National Botanical Garden
    University of Chinese Academy of Sciences)

  • Chunyue Niu

    (Chinese Academy of Sciences
    China National Botanical Garden
    University of Chinese Academy of Sciences)

  • Qin Ma

    (Chinese Academy of Sciences
    China National Botanical Garden
    University of Chinese Academy of Sciences)

  • Tianyu Hu

    (Chinese Academy of Sciences
    China National Botanical Garden
    University of Chinese Academy of Sciences)

  • Xiangzhong Luo

    (National University of Singapore)

  • Xiaonan Tai

    (New Jersey Institute of Technology)

  • Tong Qiu

    (Pennsylvania State University)

  • Yao Zhang

    (Peking University)

  • Roger C. Bales

    (University of California)

  • Lingli Liu

    (Chinese Academy of Sciences
    China National Botanical Garden
    University of Chinese Academy of Sciences)

  • Maggi Kelly

    (University of California
    University of California)

  • Qinghua Guo

    (Peking University
    Peking University)

Abstract

Increasing drought frequency and severity in a warming climate threaten forest ecosystems with widespread tree deaths. Canopy structure is important in regulating tree mortality during drought, but how it functions remains controversial. Here, we show that the interplay between tree size and forest structure explains drought-induced tree mortality during the 2012-2016 California drought. Through an analysis of over one million trees, we find that tree mortality rate follows a “negative-positive-negative” piecewise relationship with tree height, and maintains a consistent negative relationship with neighborhood canopy structure (a measure of tree competition). Trees overshadowed by tall neighboring trees experienced lower mortality, likely due to reduced exposure to solar radiation load and lower water demand from evapotranspiration. Our findings demonstrate the significance of neighborhood canopy structure in influencing tree mortality and suggest that re-establishing heterogeneity in canopy structure could improve drought resiliency. Our study also indicates the potential of advances in remote-sensing technologies for silvicultural design, supporting the transition to multi-benefit forest management.

Suggested Citation

  • Qin Ma & Yanjun Su & Chunyue Niu & Qin Ma & Tianyu Hu & Xiangzhong Luo & Xiaonan Tai & Tong Qiu & Yao Zhang & Roger C. Bales & Lingli Liu & Maggi Kelly & Qinghua Guo, 2023. "Tree mortality during long-term droughts is lower in structurally complex forest stands," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-43083-8
    DOI: 10.1038/s41467-023-43083-8
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    References listed on IDEAS

    as
    1. Nathan L. Stephenson & Adrian J. Das, 2020. "Height-related changes in forest composition explain increasing tree mortality with height during an extreme drought," Nature Communications, Nature, vol. 11(1), pages 1-4, December.
    2. Atticus E. L. Stovall & Herman Shugart & Xi Yang, 2019. "Tree height explains mortality risk during an intense drought," Nature Communications, Nature, vol. 10(1), pages 1-6, December.
    3. Silvia Ferrari & Francisco Cribari-Neto, 2004. "Beta Regression for Modelling Rates and Proportions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(7), pages 799-815.
    4. Michael J. Koontz & Andrew M. Latimer & Leif A. Mortenson & Christopher J. Fettig & Malcolm P. North, 2021. "Cross-scale interaction of host tree size and climatic water deficit governs bark beetle-induced tree mortality," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    5. Pretzsch, Hans & Forrester, David I. & Rötzer, Thomas, 2015. "Representation of species mixing in forest growth models. A review and perspective," Ecological Modelling, Elsevier, vol. 313(C), pages 276-292.
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