Florian Hartig Theoretical Ecology & Ecological Data Science

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Assessing the response of forest productivity to climate extremes in Switzerland using model–data fusion

Volodymyr Trotsiuk, Florian Hartig, Maxime Cailleret, Flurin Babst, David I. Forrester, Andri Baltensweiler, Nina Buchmann, Harald Bugmann, Arthur Gessler, Mana Gharun, Francesco Minunno, Andreas Rigling, Brigitte Rohner, Jonas Stillhard, Esther Thürig, Peter Waldner, Marco Ferretti, Werner Eugster, Marcus Schaub

Global Change Biology, 26(4), 2463–2476 (2020)
Cite this
@article{trotsiuk2020assessing,
  author = {Volodymyr Trotsiuk and Florian Hartig and Maxime Cailleret and Flurin Babst and David I. Forrester and Andri Baltensweiler and Nina Buchmann and Harald Bugmann and Arthur Gessler and Mana Gharun and Francesco Minunno and Andreas Rigling and Brigitte Rohner and Jonas Stillhard and Esther Thürig and Peter Waldner and Marco Ferretti and Werner Eugster and Marcus Schaub},
  title = {Assessing the response of forest productivity to climate extremes in Switzerland using model–data fusion},
  journal = {Global Change Biology},
  volume = {26},
  number = {4},
  pages = {2463–2476},
  year = {2020},
  doi = {10.1111/gcb.15011},
}

DOI: 10.1111/gcb.15011
Cited by 111 (Google Scholar) · 116 (OpenAlex), as of 07 September 2026

View article (DOI)

Abstract

The response of forest productivity to climate extremes strongly depends on ambient environmental and site conditions. To better understand these relationships at a regional scale, we used nearly 800 observation years from 271 permanent long-term forest monitoring plots across Switzerland, obtained between 1980 and 2017. We assimilated these data into the 3-PG forest ecosystem model using Bayesian inference, reducing the bias of model predictions from 14% to 5% for forest stem carbon stocks and from 45% to 9% for stem carbon stock changes. We then estimated the productivity of forests dominated by Picea abies and Fagus sylvatica for the period of 1960-2018, and tested for productivity shifts in response to climate along an elevational gradient and in extreme years. Simulated net primary productivity (NPP) decreased with elevation for both species. During warm-dry extremes, simulated NPP for both species increased at higher and decreased at lower elevations, with reductions in NPP of more than 25% for up to 21% of the potential species distribution range in Switzerland; reduced plant water availability had a stronger effect on NPP than temperature during these extremes. Importantly, cold-dry extremes had negative impacts on regional forest NPP comparable to warm-dry extremes. Overall, our calibrated model suggests that the response of forest productivity to climate extremes is more complex than a simple shift toward higher elevation.

What the paper shows and why it matters (AI-generated)

Assimilating nearly 800 site-years of Swiss forest monitoring data into the 3-PG growth model — cutting prediction bias for stem carbon stocks from 14% to 5% in the process — the authors find that warm-dry and cold-dry climate extremes push forest productivity in opposite directions depending on elevation, not uniformly downward as the simple story would predict. That complicates any forecast assuming climate extremes are bad for forests everywhere: the same drought year can help a high-elevation stand while hurting a low-elevation stand of the same species.