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Développement d’un modèle de dynamique forestière à grande échelle pour simuler les forêts françaises dans un contexte non-stationnaire

Abstract : Context. Since the industrial revolution, European forests have shown expansion of their area and growing stock. This expansion, together with climate change, drive changes in the processes of forest dynamic. The emergence of a European bioeconomy strategy suggests new developments of forest management strategies at European and national levels. Simulating future forest resources and their management with large-scale models is therefore essential to provide strategic planning support tools. In France, forest resources show high diversity as compared with other European countries' forests. The MARGOT forest dynamic model (MAtrix model of forest Resource Growth and dynamics On the Territory scale), was developed by the national forest inventory (IFN) in 1993 to simulate French forest resources from data of this inventory, but has been the subject of restricted developments, and simulations remain limited to a time horizon shorter than 30 years, under “business as usual” management scenarios, and not taking into account non-stationary forest and environmental contexts.Aims. The general ambition of this thesis was to consent a significant development effort on MARGOT model, in order to tackle current forestry issues. The specific objectives were: i) to assess the capacity of MARGOT to describe French forest expansion over a long retrospective period (1971-2016), ii) to take into account the heterogeneity of forests at large-scale in a holistic way, iii) to account for the impacts of forest densification in demographic dynamic processes, iv) to encompass external climatic forcing in forest growth, v) in a very uncertain context, to be able to quantify NFI sampling uncertainty in model parameters and simulations with respect to the magnitude of other trends considered. The development of forest management scenarios remained outside the scope of this work.Main results. A generic method for forest partitioning according to their geographic and compositional heterogeneity has been implemented. This method is intended to be applied to other European forest contexts. A method of propagating sampling uncertainty to model parameters and simulations has been developed from data resampling and error modelling approaches. An original approach to integrating density-dependence in demographic processes has been developed, based on a density metric and the reintroduction of forest stand entities adapted to the model. A strategy for integrating climate forcing of model demographic parameters was developed based on an input-output coupling approach with the process-based model CASTANEA, for a subset of French forests including oak, beech, Norway spruce, and Scots pine forests. All of these developments significantly reduced the prediction bias of the initial model.Conclusions. These developments make MARGOT a much more reliable forest resource assessment tool, and are based on an original modeling approach that is unique in Europe. The use of ancient forest statistics will make it possible to evaluate the model and simulate the carbon stock of French forests over a longer time horizon (over 100 years). Intensive simulations to assess the performance of this new model must be done.
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Submitted on : Thursday, February 24, 2022 - 3:48:21 PM
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Timothée Audinot. Développement d’un modèle de dynamique forestière à grande échelle pour simuler les forêts françaises dans un contexte non-stationnaire. Ecologie, Environnement. Université de Lorraine, 2021. Français. ⟨NNT : 2021LORR0179⟩. ⟨tel-03587619⟩



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