Combining paleoecology and modeling to explore cascading disturbances in forest ecosystems

Research output: Contribution to journal › Research article › Contributed › peer-review

Contributors

  • Cécile C. Remy - , University Of Franche-comté (Author)
  • Matthew D. Hurteau - , University of New Mexico (Author)
  • Sarah Le Berre - , Chair of Silviculture (Author)
  • Dominik Thom - , Chair of Silviculture (Author)
  • Rupert Seidl - , Technical University of Munich, Berchtesgaden National Park (Author)
  • Laurent Millet - , University Of Franche-comté (Author)
  • Damien Rius - , University Of Franche-comté (Author)

Abstract

Climate-induced cascading disturbance interactions pose a major challenge to the sustainable provision of forest ecosystem services to society. Developing a deeper understanding and enhanced capacity to simulate these interactions is essential for identifying disturbance-induced tipping points in forest ecosystems, and for improving management in response to such changes. This forum paper highlights opportunities to anticipate future forest disturbance trajectories by integrating paleoecology and modeling. Recent advances in forest landscape models (FLMs) and in the paleoecology of disturbances provide novel opportunities for hindcast simulations that account for multiple interacting disturbances. FLM simulations informed by paleoecological reconstructions could be mutually beneficial for both the modeling and paleoecological research communities. This integrative approach would enable the testing of previously unexplored causal hypotheses to explain discrepancies between reconstructed and simulated vegetation trajectories, while also evaluating model performance across long temporal scales and under changing climatic conditions. To integrate paleoecological data into FLMs, priority should be given to multi-proxy paleoecological reconstructions across multiple forest ecosystems to generate the data needed to inform and refine models. These new research avenues may advance projections of ecosystem change, thereby strengthening the scientific basis for guiding adaptive forest policy and management.

Details

Original languageEnglish
Article numbere08722
JournalEcography
Volume2026
Issue number10
Early online date28 Jul 2026
Publication statusPublished - Oct 2026
Peer-reviewedYes

External IDs

ORCID /0000-0001-8091-6075/work/226153785

Keywords

Sustainable Development Goals

Keywords

  • climate change, ecology, environmental archives and proxies, forest landscape models, hindcast, interacting disturbances