Application of the GreenLab model to simulate and optimize wood production and tree stability: a theoretical study
Qi R., Letort V., Kang M., Cournède P.-H., Reffye P. d., Fourcaud T. (2009). Application of the GreenLab model to simulate and optimize wood production and tree stability: a theoretical study. Silva Fennica vol. 43 no. 3 article id 201. https://doi.org/10.14214/sf.201
Abstract
The GreenLab model was used to study the interaction between source-sink dynamics at the whole tree level, wood production and distribution within the stem, and tree mechanical stability through simulation and optimization. In this first promising numerical attempt, two GreenLab parameters were considered in order to maximize wood production: the sink strength for cambial growth and a coefficient that determines the way the biomass assigned to cambial growth is allocated to each metamer, through optimization and simulation respectively. The optimization procedure that has been used is based on a heuristic optimization algorithm called Particle Swarm Optimization (PSO). In the first part of the paper, wood production was maximized without considering the effect of wood distribution on tree mechanical stability. Contrary to common idea that increasing sink strength for cambial growth leads to increasing wood production, an optimal value can be found. The optimization results implied that an optimal source and sink balance should be considered to optimize wood production. In a further step, the mechanical stability of trees submitted to their self weight was taken into account based on simplified mechanical assumptions. Simulation results revealed that the allocation of wood at the stem base strongly influenced its global deformation. Such basic mechanical criterion can be an indicator of wood quality if we consider further the active biomechanical processes involved in tree gravitropic responses, e.g. formation of reaction wood.
Keywords
wood quality;
optimization;
biomechanics;
FSPM;
Particle Swarm Optimization;
source-sink dynamics;
biomass allocation
Received 2 June 2008 Accepted 14 May 2009 Published 31 December 2009
Views 4720
Available at https://doi.org/10.14214/sf.201 | Download PDF