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Updated: Oct 6, 2025

Author Spotlight: Leaf Trait Analysis for Climate and Ecology Reconstruction in Modern and Ancient Plant Communities
Published on: October 25, 2024
Consistent temperature-dependent patterns of leaf lifespan across spatial and temporal gradients for deciduous trees
Xingli Xia1, Yingji Pan2, Mingyang Chang1
1School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China.
Abstract:
Temperature affects leaf lifespan (LL) across either space or time, driving long-term adaptation and short-term thermal acclimation, respectively. However, a comprehensive understanding of the phenomenon and the underlying phenological mechanisms remain poorly understood. The present study investigated the relationship between LL and temperature in six common deciduous trees across both spatial and temporal gradients, then explained the LL variation patterns based on phenological shifts. Using long-term (1971-2000) phenological records of six deciduous tree species at 54 sites across central Europe, we analyzed spatial and temporal variations of LL and leaf phenology along temperature gradients. We assessed the relative contribution of phenological shifts to LL variations by comparing absolute changes in leaf-out and leaf fall. We reported positive LL-temperature relationships across all observations along both spatial (+3.32 days/°C) and temporal (+4.43 days/°C) gradients. The paired t-test of the six deciduous tree species showed no significant difference in regression slopes of LL- temperature between the two gradients (t = -1.50, df = 5, P = 0.194). Prolonged LL can be explained mainly by earlier leaf-out induced by warmer temperatures both spatially (-3.22 days/°C) and temporally (-4.08 days/°C). The converging temperature-dependent patterns of LL across time and space indicate that short-term thermal acclimation keeps pace with long-term genetic adaptation for deciduous trees in Europe. Earlier leaf-out is the key force shaping the LL-temperature relationship. These results provide insights for predicting future vegetation dynamics under global warming.
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