Vegetation dynamics are affected not only by the concurrent climate but also by memory-induced lagged responses. For example, favourable climate in the past could stimulate vegetation growth to surpass the ecosystem carrying capacity, leaving an ecosystem vulnerable to climate stresses. This phenomenon, known as structural overshoot, could potentially contribute to worldwide drought stress and forest mortality but the magnitude of the impact is poorly known due to the dynamic nature of overshoot and complex influencing timescales. Here, we use a dynamic statistical learning approach to identify and characterize ecosystem structural overshoot globally and quantify the associated drought impacts. We find that structural overshoot contributed to around 11% of drought events during 1981–2015 and is often associated with compound extreme drought and heat, causing faster vegetation declines and greater drought impacts compared to non-overshoot related droughts. The fraction of droughts related to overshoot is strongly related to mean annual temperature, with biodiversity, aridity and land cover as secondary factors. These results highlight the large role vegetation dynamics play in drought development and suggest that soil water depletion due to warming-induced future increases in vegetation could cause more frequent and stronger overshoot droughts.

植被动态不仅受到同时期气候的影响，还受到记忆引起的滞后反应的影响。例如，过去有利的气候可能会刺激植被生长超过生态系统的承载能力，从而使生态系统容易受到气候压力的影响。这种被称为结构性超调的现象可能会导致全球干旱胁迫和森林死亡，但由于超调的动态性质和复杂的影响时间尺度，其影响的严重程度尚不清楚。在这里，我们使用动态统计学习方法来识别和表征全球生态系统结构超调，并量化相关的干旱影响。我们发现，结构性超调导致了 1981 年至 2015 年期间约 11% 的干旱事件，并且通常与极端干旱和高温复合相关，与非超调相关的干旱相比，导致植被更快衰退和更大的干旱影响。与超调相关的干旱比例与年平均温度密切相关，生物多样性、干旱和土地覆盖是次要因素。这些结果凸显了植被动态在干旱发展中发挥的重要作用，并表明由于变暖引起的未来植被增加而导致的土壤水分枯竭可能会导致更频繁和更严重的过度干旱。