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近40年中国植被绿度对干旱胁迫的响应及其驱动因素OACHSSCD

Sensitivity of vegetation greenness to drought stress and its driving factors over the past four decades in China

中文摘要英文摘要

全球变暖背景下,极端天气事件增多导致中国干旱事件频发,引起植被显著变化,成为中国生态系统风险管理中的突出问题.基于此,集成归一化植被指数(NDVI)、土地利用和ERA5—Land数据集,运用线性回归、游程理论、植被敏感性指标和随机森林模型,探讨了植被绿度对干旱胁迫的敏感性及其驱动因素.研究揭示了过去40年中国植被绿度的时空动态变化,确定了表征干旱事件的最优时间尺度,量化了植被对干旱胁迫的敏感性,并探究了干旱时期关键驱动因素对植被绿度敏感性的影响.结果表明:(1)过去40年间,中国植被整体呈恢复趋势,NDVI年变化率介于-0.0140/a至0.0088/a之间,东南地区改善明显,西北部呈现恢复与退化并存的格局;(2)在最优干旱时间尺度上,植被对干旱胁迫的响应呈现"西北长期—东南短期"的空间异质性格局.全国大多数地区经历了频繁且严重的干旱事件,最长可持续达24个月,严重度最高可达33.50;(3)植被异常和敏感度呈明显的"东南低—西北高"的梯度变化特征,高敏感性(均值达1.15)与低异常值集中在西北干旱区、青藏高原等生态脆弱区,稀疏植被和超旱地区对干旱响应尤为敏感;(4)植被对干旱事件的敏感性主要受降水(26.61%)、太阳辐射(25.00%)和土壤水分(17.36%)影响,在青藏高原表现出多因子复合影响,且干旱与驱动因子同步发生时产生的生态冲击远超单一事件的累积效应.因此,在植被敏感性研究中,除考虑干旱事件的时间尺度外,还应关注干旱与驱动因子的复合胁迫效应.将这些复合胁迫因子纳入植被风险评估框架,有助于提升干旱敏感性预测精度,为中国气候适应和生态系统管理提供科学依据.

In the context of global warming,the increasing frequency of extreme weather events has led to more frequent and intense droughts in China,intensifying vegetation changes and emerging as a prominent issue in ecosystem risk management.Persistent droughts have profoundly influenced vegetation dynamics,carbon cycling,and ecosystem stability,emphasizing the urgent need to better understand vegetation sensitivity to climatic stressors.To address this,the Normalized Difference Vegetation Index(NDVI),land use,and ERA5—Land datasets were integrated,and linear regression,run theory,the vegetation sensitivity index,and a random forest model were employed to comprehensively investigate the sensitivity of vegetation greenness to drought stress and its driving factors.The analysis revealed the spatiotemporal dynamics of vegetation greenness over the past four decades across China and identified the optimal time scale for characterizing drought events.It further quantified vegetation sensitivity to drought stress and examined the effects of key biophysical drivers during drought periods.The results showed that vegetation in China generally exhibited a restorative growth trend over the past 40 years,with annual NDVI change rates ranging from-0.0140 to 0.0088/a.The southeastern region demonstrated clear improvement,whereas the northwestern region displayed a mixed pattern of recovery and degradation,reflecting the combined influences of climate change and human activities.At the optimal drought time scale,vegetation responses to drought stress exhibited a spatially heterogeneous pattern of"long—term in the northwest and short—term in the southeast."Most regions experienced frequent and severe drought events,with durations lasting up to 24 months and maximum severity values reaching 33.50,indicating persistent hydroclimatic stress in arid and semi—arid zones.Vegetation anomalies and sensitivity showed a distinct southeast—northwest gradient.High sensitivity values(mean up to 1.15)and low anomaly values were concentrated in ecologically fragile areas such as the arid northwest and the Tibetan Plateau,where sparse vegetation and hyper—arid ecosystems were particularly sensitive to drought stress.Vegetation sensitivity was mainly influenced by precipitation(26.61%),solar radiation(25.00%),and soil moisture(17.36%).On the Tibetan Plateau,compound impacts of multiple climatic drivers were evident,and the synchronous occurrence of drought and these factors caused ecological impacts far exceeding the cumulative effects of single events.These findings highlight the necessity of integrating temporal drought characteristics and compound stress interactions into vegetation risk assessment frameworks.This integration can improve the accuracy of drought sensitivity prediction and provide scientific guidance for climate adaptation and sustainable ecosystem management in China.

吴光明;徐筱雯;李奇锦;何湘铃;姜亮亮

重庆师范大学地理与旅游学院,重庆 401331||重庆师范大学地理信息系统应用研究重庆市高校重点实验室,重庆 401331重庆师范大学地理与旅游学院,重庆 401331||重庆师范大学地理信息系统应用研究重庆市高校重点实验室,重庆 401331重庆师范大学地理与旅游学院,重庆 401331||重庆师范大学地理信息系统应用研究重庆市高校重点实验室,重庆 401331重庆师范大学地理与旅游学院,重庆 401331重庆师范大学地理与旅游学院,重庆 401331||重庆师范大学地理信息系统应用研究重庆市高校重点实验室,重庆 401331

干旱事件最优尺度植被敏感性驱动因素中国

drought eventsoptimal scalevegetation sensitivitydriving factorsChina

《生态学报》 2026 (7)

3489-3504,16

国家自然科学基金(42201124)重庆市自然科学基金创新发展联合(CSTB2025NSCQ-LZX0118)中国博士后科学基金(2023M740433)重庆市自然科学基金创新发展联合(CSTB2024NSCQ-LZX0064)

10.20103/j.stxb.202506121484

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