imulating plant functional acclimation and trait evolution using an eco-evolutionary vegetation model (PlantFATE)

Hofhansl, F. ORCID: https://orcid.org/0000-0003-0073-0946, Singh, S., Stefaniak, E. ORCID: https://orcid.org/0000-0003-2998-5619, Maxwell, T., & Joshi, J. (2025). imulating plant functional acclimation and trait evolution using an eco-evolutionary vegetation model (PlantFATE). DOI:10.5194/egusphere-egu25-11302. In: EGU General Assembly 2025, 27 April-02 May 2025, Vienna.

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Abstract

In the face of ongoing global crises, such as climate change and biodiversity loss, we urgently need to understand dynamic and complex responses of global forest ecosystems. To do so, we need to develop modeling frameworks that account for multiple temporal and organizational scales, and therefore capture functional adaptations of individuals, species, and ecosystems in response to the environment.

Here we present Plant-FATE (Plant Functional Acclimation and Trait Evolution) an eco-evolutionary vegetation model that embodies functional diversity by representing plant life-history strategies, and adaptations by accounting for short-term physiological acclimation, mid-term demographic shifts, and long-term trait evolution.

Tested with data obtained from an hyperdiverse site in the Amazon Forest, our model predicts a nonlinear response of tropical forests to increasing atmospheric CO2 due to diverse aspects of the growth-mortality tradeoff. At moderately elevated CO2, we found that evolution towards higher wood density increases vegetation C sequestration. By contrast, under highly elevated CO2 levels, a darkening understorey rather triggers lower wood densities, thus reversing gains from the proposed CO2 fertilization effect.

Our results suggest that competition for resources may modulate community-level eco-evolutionary dynamics of forest ecosystems, such that competition-induced changes in wood density may render forests more vulnerable to future climatic extreme events. Our study highlights the importance of accounting for eco-evolutionary dynamics when simulating the functional response of forest ecosystems to projected climate change.

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