ArticleAnnals of botany2011
A stochastic model of tree architecture and biomass partitioning: application to Mongolian Scots pines.
Article in Annals of botany, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Improving the 3D representation of plant architecture and parameterization efficiency of functional-structural tree models using terrestrial LiDAR data.AoB PLANTS · 2025Article
- Functional-Structural Plant Model "GreenLab": A State-of-the-Art Review.Plant phenomics (Washington, D.C.) · 2024Article
- Two decades of research with the GreenLab model in agronomy.Annals of botany · 2021Review
- Internal trophic pressure, a regulator of plant development? Insights from a stochastic functional-structural plant growth model applied to Coffea trees.Annals of botany · 2020Article
- Stochastic modelling of tree architecture and biomass allocation: application to teak (Tectona grandis L. f.), a tree species with polycyclic growth and leaf neoformation.Annals of botany · 2018Article
- Estimating Sink Parameters of Stochastic Functional-Structural Plant Models Using Organic Series-Continuous and Rhythmic Development.Frontiers in plant science · 2018Article
- Multiscale digital Arabidopsis predicts individual organ and whole-organism growth.Proceedings of the National Academy of Sciences of the United States of America · 2014Article
- Article
- Plant growth and architectural modelling and its applications. Preface.Annals of botany · 2011Article
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8 authors.
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Abstract
BACKGROUND AND
aimsMongolian Scots pine (Pinus sylvestris var. mongolica) is one of the principal species used for windbreak and sand stabilization in arid and semi-arid areas in northern China. A model-assisted analysis of its canopy architectural development and functions is valuable for better understanding its behaviour and roles in fragile ecosystems. However, due to the intrinsic complexity and variability of trees, the parametric identification of such models is currently a major obstacle to their evaluation and their validation with respect to real data. The aim of this paper was to present the mathematical framework of a stochastic functional-structural model (GL2) and its parameterization for Mongolian Scots pines, taking into account inter-plant variability in terms of topological development and biomass partitioning.
methodsIn GL2, plant organogenesis is determined by the realization of random variables representing the behaviour of axillary or apical buds. The associated probabilities are calibrated for Mongolian Scots pines using experimental data including means and variances of the numbers of organs per plant in each order-based class. The functional part of the model relies on the principles of source-sink regulation and is parameterized by direct observations of living trees and the inversion method using measured data for organ mass and dimensions. KEY
resultsThe final calibration accuracy satisfies both organogenetic and morphogenetic processes. Our hypothesis for the number of organs following a binomial distribution is found to be consistent with the real data. Based on the calibrated parameters, stochastic simulations of the growth of Mongolian Scots pines in plantations are generated by the Monte Carlo method, allowing analysis of the inter-individual variability of the number of organs and biomass partitioning. Three-dimensional (3D) architectures of young Mongolian Scots pines were simulated for 4-, 6- and 8-year-old trees.
conclusionsThis work provides a new method for characterizing tree structures and biomass allocation that can be used to build a 3D virtual Mongolian Scots pine forest. The work paves the way for bridging the gap between a single-plant model and a stand model.
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