The study of eco-evolutionary dynamics, i.e. of the inter-twinning between ecological and evolutionary processes when they occur at comparable time scales, is of growing interest in the current context of global change (Carroll, Hendry, Reznick, & Fox, 2007; Govaert et al., 2019). Demo-genetic agent-based models (DG-ABMs) have gained popularity to address this issue because of their abilities to consider feedback loops between ecological and evolutionary processes and to track populations of interacting individuals with adaptive traits variations (Berzaghi et al., 2019; Lamarins et al., 2022). This type of individual- and process-based simulation modelling where interindividual variation in fitness and hence opportunities for selection emerge from demography, which in turn affects the genetic composition of the population over successive generations (feedback loop), is only beginning to be applied to forest trees (Oddou-Muratorio, Hendrik, & Lefèvre, 2020). Examples include studies investigating the dispersal capacity of transgenes in forest landscapes using spatially explicit DG-ABMs with different demographic rates for transgenic and wild-type trees (DiFazio, Slavov, Burczyk, Leonardi, & Strauss, 2004; Kuparinen & Schurr, 2007), the effect of assortative mating and selection on genetic and plastic differentiation along environmental gradients (Soularue et al., 2023) or the interactions and feedback between tree thinning, genetic evolution, and forest stand dynamics, eventually in the context of drought-induced disturbances (Fririon, Davi, Oddou‐Muratorio, Ligot, & Lefèvre, 2024; Godineau et al., 2023).

In this study, Devresse et al. (2025) extend the current DG-ABM framework for forest trees by incorporating interspecific interactions within diverse, uneven-aged forests. To this end, they adapted an existing multi-species, process-based forest dynamics model—ForCEEPS (Morin et al., 2021)—enabling the evolution of selected tree functional traits across generations. Their work focuses on three quantitative traits: drought tolerance, shade tolerance, and maximal growth rate. Using this enhanced DG-ABM, the authors investigate the conditions under which evolutionary rescue might occur in a mixed beech-fir forest facing climate change. Their results demonstrate that greater trait variability and higher heritability can mitigate short-term (century-scale) forest cover loss under climate warming. The study also shows that assisted gene flow facilitates species adaptation to climate change, while the introduction of pre-adapted species (assisted migration) may enhance post-disturbance recovery but simultaneously constrain the evolutionary rescue of local species.

This work represents a major interdisciplinary advancement in forest ecology and nicely illustrates how integrating evolutionary processes into ecology-focused models can offer novel insights into forest dynamics. The implementation of genetic variability and inheritance via the infinitesimal model of quantitative genetics, along with its limitations, is described in detail, and the various research questions explored using the coupled DG‑ABM are presented as proof of concept for this successful integration. Beyond its methodological contribution, the study highlights the importance of more integrated approaches to understanding forest responses to climate change—approaches that account for both within- and between-species diversity and that promote nature-based solutions. It also underscores the urgent need for experimental studies exploring the genetic variation and architecture of adaptive traits in forest species to better anticipate and support their adaptive potential in a rapidly changing environment.

References

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Devresse, L., Way, F., Postic, T., de Coligny, F. & Morin, X. (2025) Evolutionary rescue in a mixed beech-fir forest: insights from a quantitative-genetics approach in a process-based model. HAL, ver.4 peer-reviewed and recommended by PCI Ecology https://hal.science/hal-04575070

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