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<p>In the context of climate warming, compound dry-hot (CDH), dry-cold (CDC), wet-hot (CWH), and wet-cold (CWC) events have become increasingly frequent and widespread in recent decades, causing severe but disproportionate impacts on terrestrial vegetation. However, the understanding of how vegetation vulnerability responds to these compound climate events (CCEs) is still limited. Here, we developed a multivariate copula conditional probabilistic model integrating the Standardized Precipitation Index (SPI), Standardized Temperature Index (STI), and Normalized Difference Vegetation Index (NDVI) together to quantify the vegetation response to each of CDH, CDC, CWH and CWC events under diverse climates in mainland China. Results show that CDC has a greater likelihood of causing vegetation loss relative to other CCEs, with the probability of NDVI ≤ 40th being 4.8–13.0% (0.5–2.6%) higher than individual dry (cold) events, while CWH causes the lowest vegetation loss probability, with the probability of NDVI ≤ 40th being 5.6–6.9% (4.2–5%) lower than individual wet (hot) events. Vegetation in arid and semi-arid regions is highly susceptible to CDC and CDH events, while that in northeastern China and southern humid regions is more vulnerable to CWC and CWH events. Among vegetation types, Shrubland, grassland and cropland exhibit higher vulnerability to CDC and CDH events, while deciduous (evergreen) forests are more vulnerable to CWC (CWH) events, which may be related to vegetation physiological characteristics, survival strategies, and climatic adaptations. This study enhances the understanding of the response of various vegetation types to different CCEs and highlights the necessity of simultaneously considering vegetation types and regional climate conditions when formulating adaptive vegetation management strategies.</p>

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Assessing the response lag and vulnerability of terrestrial vegetation to various compound climate events in mainland China under different vegetation types

  • 期刊论文

  • 发表日期：

    2025年4月7日

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  • Tian Yao,
  • Chuanhao Wu,
  • Pat J.-F. Yeh,
  • Bill X. Hu,
  • Yufei Jiao

摘要

In the context of climate warming, compound dry-hot (CDH), dry-cold (CDC), wet-hot (CWH), and wet-cold (CWC) events have become increasingly frequent and widespread in recent decades, causing severe but disproportionate impacts on terrestrial vegetation. However, the understanding of how vegetation vulnerability responds to these compound climate events (CCEs) is still limited. Here, we developed a multivariate copula conditional probabilistic model integrating the Standardized Precipitation Index (SPI), Standardized Temperature Index (STI), and Normalized Difference Vegetation Index (NDVI) together to quantify the vegetation response to each of CDH, CDC, CWH and CWC events under diverse climates in mainland China. Results show that CDC has a greater likelihood of causing vegetation loss relative to other CCEs, with the probability of NDVI ≤ 40th being 4.8–13.0% (0.5–2.6%) higher than individual dry (cold) events, while CWH causes the lowest vegetation loss probability, with the probability of NDVI ≤ 40th being 5.6–6.9% (4.2–5%) lower than individual wet (hot) events. Vegetation in arid and semi-arid regions is highly susceptible to CDC and CDH events, while that in northeastern China and southern humid regions is more vulnerable to CWC and CWH events. Among vegetation types, Shrubland, grassland and cropland exhibit higher vulnerability to CDC and CDH events, while deciduous (evergreen) forests are more vulnerable to CWC (CWH) events, which may be related to vegetation physiological characteristics, survival strategies, and climatic adaptations. This study enhances the understanding of the response of various vegetation types to different CCEs and highlights the necessity of simultaneously considering vegetation types and regional climate conditions when formulating adaptive vegetation management strategies.