Multiscale modelling of European beech decline: the role of interannual climate variability and local environmental factors.
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| Title: | Multiscale modelling of European beech decline: the role of interannual climate variability and local environmental factors. |
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| Authors: | Lemaire, Jean1 (AUTHOR) jean.lemaire@cnpf.fr, Vennetier, Michel2 (AUTHOR) michel.vennetier@inrae.fr, Prévosto, Bernard2 (AUTHOR) bernard.prevosto@inrae.fr, Cailleret, Maxime2 (AUTHOR) maxime.cailleret@inrae.fr |
| Source: | European Journal of Forest Research. Jun2025, Vol. 144 Issue 3, p421-441. 21p. |
| Subject Terms: | *Forests & forestry, *European beech, *Life sciences, *Statistical models, *Multiscale modeling |
| Abstract: | Fagus sylvatica L. is a main forest tree species in Europe but has been subjected to massive decline events over the last decades. This phenomenon has been mainly attributed to the increase in drought frequency and intensity, but it is unclear how the local specificities in stand structure, climatic, soil and topographic conditions interact, and if statistical models are able to capture the high spatial and temporal variability in tree decline. To address this challenge, we measured 5380 Fagus sylvatica trees from 308 plots distributed in four regions of France with contrasting environmental conditions, and designed models predicting decline at both regional and national scales. These models aimed at assessing the percentage of stems by plot with at least 50% crown biomass loss based on 229 dendrometric, topographic, soil and climatic variables. The climatic factors explained most of the variability in stand decline, especially the interannual climate variability from the 30-years mean in maximal temperature and in hydric deficit. Regional models were the most efficient in predicting beech decline in their calibration areas (Q2 Stone-Geisser coefficient varied from 0.26 to 0.42) as they better consider the local environmental factors. They were less effective in the other regions, and the national model was an acceptable compromise on a larger scale. These statistical models provide valuable insights for forest managers and could be improved through a more detailed temporal stand monitoring to control the effects of management and decline dynamics. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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