How beech ecophysiology shapes temperate forest gross primary productivity – Part 1: A wavelet-based framework for extracting seasonal dynamics

Bitton, Jonathan; Charles, Catherine; Longdoz, Bernard; Heinesch, Bernard

doi:10.5194/bg-23-6465-2026

Articles | Volume 23, issue 18

https://doi.org/10.5194/bg-23-6465-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-23-6465-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 23, issue 18

Research article

|

17 Sep 2026

Research article |

| 17 Sep 2026

How beech ecophysiology shapes temperate forest gross primary productivity – Part 1: A wavelet-based framework for extracting seasonal dynamics

Jonathan Bitton, Catherine Charles, Bernard Longdoz, and Bernard Heinesch

Supplement

https://doi.org/10.5194/bg-23-6465-2026-supplement

Data sets

FR-Hes dataset (1997–2020) Jonathan Bitton https://doi.org/10.5281/zenodo.21111957

Fluxnet Archive Product from Hainich, 2000-2024 A. Knohl et al. 11676/rOKIh2gg8tEExEelC67ZCp9q

Warm winter 2020 ecosystem eddy covariance flux product from Soroe A. Ibrom et al. https://doi.org/10.18160/X4DF-R4S2

Model code and software

Continuous wavelet transform toolkit with Wavelet Area Interpretation (WAI) Jonathan Bitton https://doi.org/10.5281/zenodo.21111957

Short summary

Seasonal changes in forest behavior are often hard to detect in carbon data. We developed a wavelet‑based approach to uncover how three beech forests grow and absorb carbon through seasons. The forests showed distinct spring growth, summer slowdowns and long‑term trends. All forests were carbon sinks with managed forests strengthening over time while the old forest weakened. We show how seasonal dynamics explain long‑term changes and offer a new tool for tracking forest responses to climate.