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  Loss of competitive strength in European conifer species under climate change

Grünig, M., Rammer, W., Baumann, M., Albrich, K., André, F., Augustynczik, A. L., Bohn, F., Bouwman, M., Bugmann, H., Collati, A., Cristal, I., Dalmonech, D., De Caceres, M., De Coligny, F., Dobor, L., Dollinger, C., Forrester, D. I., Garcia-Gonzalo, J., González-Olabarria, J. R., Hiltner, U., Hlásny, T., Honkaniemi, J., Huber, N., Huth, A., Jonard, M., Jönsson, A. M., Lagergren, F., Mina, M., Mohren, F., Moos, C., Morin, X., Muys, B., Nieberg, M., Peltoniemi, M., Reyer, C. P. O., Storms, I., Thom, D., Toigo, M., Seidl, R. (in press): Loss of competitive strength in European conifer species under climate change. - Communications Earth and Environment.

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Item Permalink: https://publications.pik-potsdam.de/pubman/item/item_34370 Version Permalink: https://publications.pik-potsdam.de/pubman/item/item_34370_1
Genre: Journal Article

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2026.02.13.705703v1.full.pdf (Preprint), 2MB
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 Creators:
Grünig, Marc1, Author
Rammer, Werner1, Author
Baumann, Martin1, Author
Albrich, Katharina1, Author
André, Frédéric1, Author
Augustynczik, Audrey L.D.1, Author
Bohn, Friedrich1, Author
Bouwman, Meike1, Author
Bugmann, Harald1, Author
Collati, Alessio1, Author
Cristal, Irina1, Author
Dalmonech, Daniela1, Author
De Caceres, Miquel1, Author
De Coligny, Francois1, Author
Dobor, Laura1, Author
Dollinger, Christina1, Author
Forrester, David I.1, Author
Garcia-Gonzalo, Jordi1, Author
González-Olabarria, José Ramón1, Author
Hiltner, Ulrike1, Author
Hlásny, Tomáš 1, AuthorHonkaniemi, Juha1, AuthorHuber, Nico1, AuthorHuth, Andreas1, AuthorJonard, Mathieu1, AuthorJönsson, Anna Maria1, AuthorLagergren, Frederik1, AuthorMina, Marco1, AuthorMohren, Frits1, AuthorMoos, Christine1, AuthorMorin, Xavier1, AuthorMuys, Bart1, AuthorNieberg, Mats2, Author                 Peltoniemi, Mikko1, AuthorReyer, Christopher P. O.2, Author                 Storms, Ilié1, AuthorThom, Dominik1, AuthorToigo, Maude1, AuthorSeidl, Rupert1, Author more..
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: Climate change is expected to alter species assemblages by affecting the outcome of competition between species. Investigating processes of competition remains challenging particularly in tree communities, as they unfold over extensive spatio-temporal scales. Here, we developed a deep-learning approach to leverage a novel database of 135 million simulated local-scale tree responses to climate across continental Europe to investigate changes in the competitiveness of nine major tree species under different scenarios of climate change. Specifically, we trained a Deep Neural Network on local process model projections to investigate climate change effects on indicators of competitive strength and species dominance. We found decreasing competitive strength for all investigated evergreen coniferous species across their distribution, while major deciduous broadleaved species such as Quercus robur and Fagus sylvatica increased in competitiveness. Changes in tree species competition with climate differed locally, but most investigated species lost competitive strength at their warm range edges. As a consequence of these changes, up to 19% of Europe’s forests could experience a change in the dominant tree species until the end of the 21st century. Our results suggest a profound climate-induced reassembly of Europe’s forests and identify areas that may require specific attention in forest policy and management.

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Language(s): eng - English
 Dates: 2024-09-222026-04-23
 Publication Status: Accepted / In Press
 Pages: 28
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: MDB-ID: No data to archive
Organisational keyword: RD2 - Climate Resilience
PIKDOMAIN: RD2 - Climate Resilience
Working Group: Forest Ecosystem Resilience
Research topic keyword: Adaptation
Research topic keyword: Biodiversity
Research topic keyword: Climate impacts
Research topic keyword: Ecosystems
Research topic keyword: Forest
Model / method: 4C
Model / method: Machine Learning
Model / method: Model Intercomparison
Regional keyword: Europe
OATYPE: Gold Open Access
 Degree: -

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Title: Communications Earth and Environment
Source Genre: Journal, SCI, Scopus, oa
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Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/communications-earth-environment
Publisher: Nature