From Mountains to Basins: Asymmetric Ecosystem Vulnerability and Adaptation to Extreme Climate Events in Southwestern China

文献类型： 外文期刊

第一作者： Lu, Qingao

作者： Lu, Qingao;Zhang, Yuandong;Wei, Jingxuan;Xu, Kun;Sun, Wei

作者机构：

关键词： climate-ecosystem interaction; southwestern China; random forest regression; moving window analysis

期刊名称：REMOTE SENSING （ 影响因子：4.1； 五年影响因子：4.8 ）

ISSN：

年卷期： 2025 年 17 卷 3 期

页码：

收录情况： SCI

摘要： The increasing frequency of both singular and compound extreme climate events driven by global warming has profoundly impacted terrestrial ecosystems. Using machine learning-based Random Forest algorithms and moving correlation analysis, this study quantifies the impacts of extreme climate indices (ECIs) on two ecological indicators (EIs), the NDVI and GPP, from 1982 to 2019. The results reveal that singular extreme climate events exert a more pronounced influence on ecosystems across Southwestern China (SWC) than compound ones. Specifically, the NDVI and GPP exhibited strong correlations with summer days (SU) and diurnal temperature range (DTR), with SU contributing positively (weight = 0.275 for the GPP and 0.238 for the NDVI) and DTR negatively (weight = 0.107 for the GPP and 0.130 for the NDVI). Regional analyses highlighted distinct spatial patterns: in mid-high-altitude areas (>1 km), including the Hengduan Mountains (HDMs) and Yunnan-Guizhou Plateau (YGP), extreme temperatures and precipitation significantly promoted vegetation growth, with rainfall day index (RDI), frost days (FD), extreme temperature index (ETI), SU, and DTR all having a strong influence (>0.1) on the GPP and NDVI. These areas showed strong adaptability to extreme climate, benefiting overall vegetation health. In contrast, ecosystems in low-altitude areas (<1 km) showed more variable responses. The Guangxi Basin (GXB) exhibited strong resistance to ECIs, with vegetation being almost unaffected by extreme precipitation and benefiting from continuous warming. Only consecutive wet days (CWD) and FD were significantly negatively correlated with EIs (p < 0.05), and their correlation weights were low (weights = 0.043 and 0.013). However, the vegetation in the Sichuan Basin (SCB) is more susceptible to climate extremes, which have particularly strong effects on the NDVI. SU, tropical nights (TR), ETI, and growing season length (GSL), which have positive effects on EIs in mid-high-altitude areas, show extremely significant negative correlations in the SCB (p < 0.001), and their weights account for one-third of the total (weights = 0.15, 0.11, 0.061 and 0.012, respectively). These findings underscore the heterogeneous responses of ecosystems to ECIs and emphasize the need for region-specific strategies in ecosystem management and disaster prevention amid climate change.

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