Fleurant C, Duchesne J, Raimbault P
Landscape Laboratory, National Institute of Horticulture, 2 rue Le Nôtre, 49045 Angers cedex 01, France.
J Theor Biol. 2004 Mar 7;227(1):137-47. doi: 10.1016/j.jtbi.2003.10.014.
This paper presents a general mathematical model for the morphometric description of trees. This model is based on the introduction of fractal theory, and more particularly of the concept of self-similarity, into a statistical physics rationale. Fractal theory provides the necessary tools to describe the complexity of tree structure. Statistics, when applied to physics, makes it possible to explain the properties of complex objects starting from their components. The combination of both tools allowed us to develop a theoretical model that is the probability density function of the morphometric lengths of trees. An example of validation of this law is given here: the theoretical model of morphometric lengths is compared with experimental data of Cupressocyparis.
本文提出了一种用于树木形态测量描述的通用数学模型。该模型基于将分形理论，更具体地说是自相似性概念，引入统计物理原理。分形理论提供了描述树木结构复杂性的必要工具。统计学应用于物理学时，使得从其组成部分出发解释复杂物体的特性成为可能。这两种工具的结合使我们能够开发出一个理论模型，即树木形态测量长度的概率密度函数。这里给出了该定律的一个验证示例：将形态测量长度的理论模型与柳杉的实验数据进行比较。
