Résumé
The genetic composition of forest stands dynamically evolves driven by the combination of natural processes and management practices. Evolution-oriented forest management consists in understanding and stewarding these combined processes to enhance short-term adaptation and productivity while maintaining long-term evolvability.Silviculture is a sequence of practices, each having multiple possible genetic impacts, depending one on the other. Moreover, silvicultural practices interact with demographic changes due to other natural causes like environment changes. All these dependencies and interactions make an analytical approach of the resulting evolutionary dynamics, based on quantitative genetics, very complex. Here, we developed a demo-genetic simulation approach of this issue.Previous demo-genetic models in forest systems mainly focused on the possible impacts of silviculture on the overall (neutral) gene diversity. Here we focus on the selection effects on growth. We coupled a quantitative genetics model to a growth dynamics model calibrated for Cedrus atlantica, and simulated various scenarios of silviculture, using the CAPSIS simulation platform (http://capsis.cirad.fr/capsis/help_en/luberon2).We compared the effect of various management practices on (i) the growth, (ii) the genetic quality and (iii) the evolutionary potential of the stand. We show that different silviculture sequences may result in very different levels of selection intensity for growth, which have different impacts on the dynamics of genetic means and variances from one generation of trees to the next. We also show the importance of all stages of interventions, including those in the juvenile stage, on the final genetic impacts. Finally, we show that the effective genetic impacts of a given silviculture guideline are highly influenced by pragmatic choices in the forest and by local disturbance regimes.This work should be considered as a “proof of concept” showing that demo-genetic models coupling forest dynamics, quantitative genetics, silviculture practices and natural disturbances are feasible. Such models provide a powerful approach to investigate the potential genetic impacts of silviculture and guide evolution-oriented forest management. We are currently extending this approach to other species and other contexts. ONLINE VIDEO: https://youtu.be/Y-pzxWo0zF8?list=PLA8HUi4yh9-w9Lg0Tc2YgFmzHxRwhPBe6