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Stochastic modelling of development and biomass allocation: Computation applied to architecture of young mahogany trees (Khaya senegalensis Desr. A. Juss), a native African savannah emblematic agroforestry species
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International audience. The architectural plasticity forms observed in trees is a result of meristem functioning, which generates new organs and branches, and adjusts growth processes in response to heterogeneous climatic adaptations that affect biomass allocation. Analyzing this plasticity should enable the selection of adapted individuals for optimizing successful cropping systems. Mahogany tree (Khaya senegalensis) is a rhythmically growing indigenous agroforestry tree that is heavily exploited for its multiple uses. Understanding its growth characteristics, as well as the complexity of its structure (randomness, rhythmicity, etc. of Mahogany tree), could facilitate its conservation and sustainable management. This study aims to model the architecture and physiology of young mahogany trees based on field data using an organ-level structural–functional model called 'GreenLab', which is founded on source-sink relationships. Ninety trees aged 6, 12, and 24 months were measured in the field. Development was calculated using a dual-scale automaton based on the Monte Carlo process, while biomass production and its distribution to different plant organs (source and sink) were calibrated using Pressler's law using Markov chains. Meristematic activity laws, combined with organ sinks (D: Demand), photosynthesis (Q: Supply), and organic series (Q/D: Trophic pressure), were employed to simulate individual architecture. The results demonstrate that the model realistically and flexibly describes topological development and replicates biomass production and allocation processes for rhythmically growing trees. This model will enable the identification of mahogany ideotypes suited for enhancing agroforestry cropping systems based on this species and several other threatened species. These findings introduce and thus lay the groundwork for a computational plant model tailored to the needs of agroforestry from a novel perspective, offering new avenues for agronomic and forestry applications in West Africa and Côte d'Ivoire.
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