Physiological and Hyperspectral Responses of Individual European Beech Trees to Drought Stress: A Pilot Study During a Compound Drought and Heatwave Event

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Authors: Karolina Sakowska, Luca Belelli Marchesini, Michele Dalponte, Mustafa Elfahl, Mirco Rodeghiero, Francesca Ugolini, S. Pilati, Loris Vescovo, Luis Alonso Chorda, Chiara Torresan
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References: 54

Abstract

European beech is a species of both ecological and economic relevance in Europe. However, its high sensitivity to drought poses a significant risk amid increasing climate extremes. This study aimed to evaluate the physiological and spectral responses of beech to drought stress, combining in situ leaf-level measurements with hyperspectral remote sensing data. We set up the experiment in an Alpine European beech forest in northern Italy, which included three water treatments: control, water stress, and irrigation. Physiological data (i.e., leaf gas exchange and chlorophyll content), alongside airborne hyperspectral remote sensing data, were collected from 20 to 29 July 2022 during a compound drought and heatwave (CDHW) event. Water-stressed trees exhibited significantly reduced photosynthetic rates, lower photosystem II efficiency, and higher non-photochemical quenching, indicating impaired photosynthetic performance. Water-stressed beech exhibited up to 70% reduced photosynthesis and 35% lower leaf chlorophyll content under severe drought conditions. Hyperspectral vegetation indices, particularly the RENDVI, CIRE, and SPRI, successfully detected stress status. This exploratory study, based on an intensive analysis of four trees, demonstrates the feasibility of integrating physiological measurements with hyperspectral remote sensing to detect drought-stress signatures in European beech at the individual-tree level, establishing a methodological framework for more extensive future research.

Fields of Study & Subjects

Plant Water Relations and Carbon Dynamics Remote Sensing in Agriculture Plant Stress Responses and Tolerance

Publication details

Journal / source
Remote Sensing
Volume
18
Issue
3
Pages
488–488
Publication date
3 February 2026
Language
EN