Current issue: 55(3)
Under compilation: 55(4)
A new approach for modelling plant growth using the software AMAPpara is presented. This software takes into consideration knowledge about plant architecture which has been accumulated at the Plant Modelling Unit of CIRAD for several years, and introduces physiological concepts in order to simulate the dynamic functioning of trees. The plant is considered as a serial connection of vegetative organs which conduct water from the roots to the leaves. Another simple description of the plant as a network of parallel pipes is also presented which allows an analytical formulation of growth to be written. This recurring formula is used for very simple architectures and is useful to understand the role of each organ in water transport and assimilate production. Growth simulations are presented which show the influence of modifications in architecture on plant development.
Process-based tree growth models are recognized to be flexible tools which are valuable for investigating tree growth in relation to changing environment or silvicultural treatments. In the context of forestry, we address two key modelling problems: allocation of growth which determines total wood production, and distribution of wood along the stem which determines stem form and wood quality. Growth allocation and distribution are the outcome of carbon translocation, which may be described by the Munch theory. We propose a simpler gradient process to describe the carbon distribution in the phloem of conifers. This model is a reformulation of a carbon diffusion-like process proposed by Thornley in 1972. By taking into account the continuity of the cambium along the stem, we obtain a one-dimensional reaction-diffusion model which describes both growth allocation between foliage, stem and roots, and growth distribution along the stem. Distribution of wood along the stem is then regarded as an allocation process at a smaller scale. A preliminary sensitivity analysis is presented. The model predicts a strong relationship between morphology and foliage-root allocation. It also suggests how empirical data, such as stem analysis, could be used to calibrate and validate allocation rules in process-based growth models.