The model is applied to mono-specific field crops and forest stands. For high-density crops at full cover, the model is shown to be equivalent to the classical equation of field crop production (Howell and Musick, 1985, in Les besoins en eau des cultures; Paris: INRA Editions). However, our method is more accurate at the early stages of growth (before cover) or in the case of intermediate densities. It may potentially account for local effects, such as uneven spacing, variation in the time of plant emergence or variation in seed biomass. The application of the model to trees illustrates the expression of plant plasticity in response to competition for light. Density strongly impacts on tree architectural development through interactions with the source-sink balances during growth. The effects of density on tree height and radial growth that are commonly observed in real stands appear as emerging properties of the model.
We built a simple tree growth model for Norway spruce (Picea abies (L.) Karst.) that describes the biomass and stem radial growth of one tree in a stand. Growth is controlled by an external height growth function that accounts for site quality. Crown recession is represented by an empirical function that accounts for the limitation to crown development caused by mechanical contacts with neighboring trees. The model describes biomass growth based on carbon budget (photosynthesis, respiration and senescence) and carbon partitioning between foliage, stem and root compartments. An internal regulation is introduced based on a functional balance between crown and root development. Stem annual growth is distributed along the stem by means of an empirical rule. Stem profile is the final output of the model and can be used to check the overall consistency of the model and as an aid in wood quality studies. The underlying assumptions of the model are described.
Abstract. The development of functional-structural plant models has opened interesting perspectives for a better understanding of plant growth as well as for potential applications in breeding or decision aid in farm management. Parameterization of such models is however a difficult issue due to the complexity of the involved biological processes and the interactions between these processes. The estimation of parameters from experimental data by inverse methods is thus a crucial step. This paper presents some results and discussions as first steps towards the construction of a general framework for the parametric estimation of functional-structural plant models. A general family of models of Carbon allocation formalized as dynamic systems serves as the basis for our study. An adaptation of the 2-stage Aitken estimator to this family of model is introduced as well as its numerical implementation, and applied in two different situations: first a morphogenetic model of sugar beet growth with simple plant structure, multi-stage and detailed observations, and second a tree growth model characterized by sparse observations and strong interactions between functioning and organogenesis. The proposed estimation method appears robust, easy to adapt to a wide variety of models, and generally provides a satisfactory goodness-of-fit. However, it does * Corresponding author. E-mail: paul-henry.cournede@ecp. Some parameter estimation issues in plant growth modelling not allow a proper evaluation of estimation uncertainty. Finally some perspectives opened by the theory of hidden models are discussed.
-A set of compatible models are established to simulate the profile and internal structure of stems: ring distribution, bark and sapwood profiles. First, models are built tree by tree; they are then generalized by establishing relationships between the estimates of treewise model parameters and the individual tree characteristics. The residuals are examined against the relative height or distance from the apex. Using an independent sample of 4 trees, the observed stem and annual increment profiles are compared to the modelled profiles, firstly using a stem profile model and secondly using a ring profile established previously [10]. Generally, each model proves to be more accurate when used directly to predict the type of profile -stem or increment -for which it has been calibrated. In the lower part of the tree, the ring profile model gives less biased and more accurate estimates of ring width and tree diameter than the stem profile models. stem profile / growth ring profile / bark profile / sapwood profile / Cedrus atlantica
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