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Limited predictability of tree-level responses to drought across European forests: Drivers of tree-level drought resilience

Diego I. Rodríguez-Hernández*, Fabian J. Fischer, Duncan A. O’Brien, Martin De Kauwe, Bo Wang, Olivier Bouriaud, Tommaso Jucker

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Climate change is increasing the frequency, duration and severity of extreme events such as heatwaves and droughts, pushing trees near or beyond their ecophysiological limits. Understanding what governs variability in how trees respond to drought – such as intrinsic factors related to their size, age, and species, or extrinsic factors shaped by their local competitive environment – is critical for predicting long-term forest resilience to climate change and developing climate-smart forest management strategies. Here, we use tree ring data from 2909 trees belonging to sixteen species distributed across Europe’s major forest types to comprehensively assess what factors contribute most to a tree’s ability to withstand and recover from extreme drought events. We found that trees with larger living crowns generally exhibited higher post-drought growth recovery and resilience, while trees exposed to lower drought intensities showed greater resistance. Conversely, neither the density nor the diversity of a tree’s local competitive neighbourhood had any clear influence on its response to drought. More generally, we found that our ability to predict whether a tree would exhibit drought resilience was low (R2 = 0.13–0.21) and was largely driven by species-specific responses and topographic variation across forest types, rather than by tree- and stand-level attributes. These findings highlight that drought responses are inherently complex to predict and strongly influenced by heterogeneous responses among species, shaped by forest type. Thus, integrating tree-ring, physiological, remote-sensing and fine-scale climatic data with mechanistic models represents a promising avenue for improving forecasts of future forest resilience to climate change.
Original languageEnglish
Article number123899
Number of pages11
JournalForest Ecology and Management
Volume616
Early online date15 May 2026
DOIs
Publication statusE-pub ahead of print - 15 May 2026

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