Elsevier

Ecological Modelling

Volume 206, Issues 3–4, 24 August 2007, Pages 231-249
Ecological Modelling

GRAAL-CN: A model of GRowth, Architecture and ALlocation for Carbon and Nitrogen dynamics within whole plants formalised at the organ level

https://doi.org/10.1016/j.ecolmodel.2007.03.036Get rights and content

Abstract

A functional–structural model has been developed to analyse the dynamics between morphogenetic processes and assimilate (carbon and nitrogen) management processes, the dynamics between carbon and nitrogen metabolism (acquisition and allocation) as well as the regulations of those processes during the vegetative development of individual plants. It associates models of plant morphogenesis and models simulating the growth of plant compartments as related to assimilate availability. Using object-oriented modelling methods, knowledge is formalised at the organ level (local rules of development and resource management), and the behaviour of the plant arises from interactions between those organs and the integration of the processes into the whole plant. Shoot and root organs are initiated as a function of temperature. Using the source–sink concept, organ growth is calculated from its individual potential growth and assimilate availability within the plant. Simulations using maize illustrate the capacity of the model to mimic the main features of plants in relation to development and resource allocation (e.g., dynamics of root:shoot ratio for carbon and nitrogen, changes in priority between organs as well as plant plasticity to assimilate availability). Conceptually, the model constitutes a generic framework for testing and sorting out hypotheses on functioning processes involved in plant development. In the fields of systems biology and ecology, it is a highly suitable tool for analysing the interactions between genotypic and environmental characteristics affecting plant behaviour.

Introduction

Many crop and plant models have been developed over recent years to simulate the main fluxes (e.g., CO2, water, or nitrogen) between the plant and its environment (soil and atmosphere). They aimed at studying the effects of various environmental factors on crop and forest growth, soil and groundwater quality and/or air and surface water quality (e.g., Suzuki et al., 1993, Hauhs et al., 1995, Tiktak and van Grinsven, 1995, Brisson et al., 1998, Riedo et al., 1998, Kirschbaum, 1999, Tanaka, 2001, Welch et al., 2005). For these purposes, the soil, root system, canopy, and atmosphere were considered as homogeneous in the horizontal plane, and thus all components of the model were described as one-dimensional. However, to study heterogeneous populations or competition within the population at a lower scale, it is necessary to explicitly consider the architecture of individual plants. Such a description needs to provide both (i) spatial information, which is essential for understanding plant-medium exchanges and thus inter-plant competition (see e.g., Chelle, 2005, for light interception; Caldwell, 1987, for water and nutrients uptake), and (ii) structural information making it possible to represent plant organs and thus intra-plant interactions (e.g., by using a source/sink approach, Warren-Wilson, 1972, Drouet and Pagès, 2003).

Among the numerous models of plant architecture that have been developed and published, most of them have focused on the developmental processes which combine and repeat within the plant, and lead to a complex and highly structured system (e.g., Diggle, 1988, Pagès et al., 1989, Kurth, 1994, Jourdan et al., 1995, Perttunen et al., 1996, de Reffye and Houllier, 1997, Fournier and Andrieu, 1998, Prusinkiewicz, 1999). These development-focused models simulate realistic plants, but in a narrow range of environmental conditions related to the data used to develop and calibrate the model. By producing plant mock-ups, these simulations have been shown to be useful for getting an insight into the influence of the plant architecture on various aspects of plant functioning, like resource capture (e.g., for the shoot system, Dauzat et al., 2001; for the root system, Dunbabin et al., 2003), mechanical constraints related to plant weight (Pearcy et al., 2005), interactions with other living organisms (Hanan et al., 2002) or transport within the branching system (Doussan et al., 1998, Früh and Kurth, 1999, Daudet et al., 2002).

To further develop this approach, and to give virtual plants the architectural plasticity that real plants exhibit in response to medium heterogeneity and its changes, it is necessary to model at the organ level the response of the developmental processes to their environment sensu lato. For a given individual organ, this environment has an external component (i.e., exogenous environment) and an internal component (i.e., within the plant, endogenous environment, as defined by Pagès, 2000). The former has been the subject of much experimental and modelling work on various organs, using several major variables like temperature, air vapour pressure deficit, and soil mechanical impedance (Ben Haj Salah and Tardieu, 1995, Bengough et al., 2006). The latter is much more difficult to formalise and quantify, and has received little attention.

The main means by which architectural models have linked individual organ growth and development to other plant parts is through carbohydrate availability (Thaler and Pagès, 1998, Balandier et al., 2000, Drouet and Pagès, 2003, Yan et al., 2004, Allen et al., 2005, Eschenbach, 2005). If carbohydrate availability has often been shown to be a limiting factor or a signal for root growth (Bingham and Stevenson, 1993, Thaler and Pagès, 1996, Freixes et al., 2002), there is nevertheless little evidence of its prominent influence for determining shoot or leaf growth under usual, not extreme, conditions. Other resources, or other signalling substances, like nitrogen metabolism products, should also be considered for representing the variations of development in a whole plant model, as proposed in the pioneer work of Thornley (1972). Using various species, experimental work has shown the impact of nitrogen nutrition on leaf growth (e.g., Gastal and Nelson, 1994, Vos et al., 1996, Fricke et al., 1997). Furthermore, resources (carbon and nitrogen especially) interact through several functions: acquisition, transport, and utilisation for growth. It is worth evaluating the impact of these interactions on organ and plant behaviour.

We pursue this modelling approach, integrating both architectural development and resource management, hereafter carbon (C) and nitrogen (N). For this purpose, we consider the shoot and root systems with the same amount of detail and represent for the organs of each system the main processes regarding C and N management. These processes are explicitly described as functions of external factors (temperature, light, nitrogen supply) and endogenous factors (carbon and nitrogen availability within the plant). The present model, called GRAAL-CN, follows up and generalises the work of Drouet and Pagès (2003), which considered carbon assimilates alone. GRAAL-CN is founded upon dynamics between organ development and assimilate partitioning for C and N as well as interactions between C and N metabolism within the whole plant. After a detailed description of the model, we focus on its conceptual advances based on simulations of the architectural plasticity of virtual plants in relation to varying C and N inputs.

Section snippets

General principles

GRAAL-CN associates two aspects of plant functioning: (i) morphogenetic processes that determine the initiation of new organs and plant topology as well as (ii) resource acquisition (carbon and nitrogen) and assimilate exchange between organs that modulate their extension and growth in assimilate mass (see e.g., Lemaire and Millard, 1999). Both assimilates, carbon and nitrogen, have the same status within the plant: they interact symmetrically and regulate both resource acquisition and

Conditions for the simulations

The simulations were carried out on maize using the parameter values summarised in Table 1. The time step of the model was 1 day. Day length was 12 h. To simplify the analysis of the results, air (resp. soil) temperature was kept constant: 20 °C (resp. 18 °C) for all the simulations. The duration of each simulation was 80 days, corresponding to 960 degree days after sowing (silking stage). The growing conditions involved two contrasting and homogeneous nutrient supplies (0.5 mmol l−1 under the ‘low N

Discussion

From a conceptual point of view, GRAAL-CN uses an ascending (i.e., bottom-up) modelling approach to integrate processes from the organ level to the whole plant level through aggregated levels of organisation (organs, axes as well as root and shoot systems). It simultaneously uses a top-down approach that helps sort out elementary processes and identify robust parameters through sensitivity analyses. GRAAL-CN mimics plant developmental plasticity to environmental and endogenous factors (carbon

Conclusion

Based on the GRAAL model developed for maize growth and carbon partitioning (Drouet and Pagès, 2003), GRAAL-CN has been developed to be more generic with concepts and structure (Fig. 2) transposable to various species and to assimilates other than carbon (e.g., nitrogen). By using a bottom-up approach (i.e., an ascending modelling process), the analysis of a system from its objects makes a direct parallel between the functional–structural properties of the real plant and the organisation of the

Acknowledgement

We wish to thank Suzette Tanis-Plant for editorial advice in English.

References (104)

  • G.O. Edmeades et al.

    Genomics and the physiologist: bridging the gap between genes and crop response

    Field Crops Res.

    (2004)
  • C. Eschenbach

    Emergent properties modelled with the functional structural tree growth model ALMIS: computer experiments on resource gain and use

    Ecol. Model.

    (2005)
  • C. Fournier et al.

    A 3D architectural and process-based model of maize development

    Ann. Bot.

    (1998)
  • T. Früh et al.

    The hydraulic system of trees: theoretical framework and numerical simulation

    J. Theor. Biol.

    (1999)
  • J. Hanan et al.

    Simulation of insect movement with respect to plant architecture and morphogenesis

    Comput. Electron. Agric.

    (2002)
  • M. Hauhs et al.

    A model relating forest growth to ecosystem-scale budgets of energy and nutrients

    Ecol. Model.

    (1995)
  • F. Hoffmann

    FAGUS, a model for growth and development of beech

    Ecol. Model.

    (1995)
  • M.U.F. Kirschbaum

    CenW, a forest growth model with linked carbon, energy, nutrient and water cycles

    Ecol. Model.

    (1999)
  • W. Kurth

    Morphological models of plant growth: possibilities and ecological relevance

    Ecol. Model.

    (1994)
  • R.L. McCown et al.

    APSIM: a novel software system for model development, model testing and simulation in agricultural systems research

    Agric. Syst.

    (1996)
  • L.B. Pachepsky et al.

    An adequate model of photosynthesis. I. Parametrization, validation and comparison of models

    Agric. Syst.

    (1996)
  • J. Perttunen et al.

    LIGNUM: a tree model based on simple structural units

    Ann. Bot.

    (1996)
  • M. Riedo et al.

    A pasture simulation model for dry matter production, and fluxes of carbon, nitrogen, water and energy

    Ecol. Model.

    (1998)
  • M. Suzuki et al.

    Simplified dynamic model on carbon exchange between atmosphere and terrestrial ecosystems

    Ecol. Model.

    (1993)
  • F. Tabourel-Tayot et al.

    MecaNiCAL, a supply–demand model of carbon and nitrogen partitioning applied to defoliated grass. 1. Model description and analysis

    Eur. J. Agron.

    (1998)
  • A. Tiktak et al.

    Review of sixteen forest-soil-atmosphere models

    Ecol. Model.

    (1995)
  • M.T. Allen et al.

    Using L-systems for modelling source–sink interactions, architecture and physiology of growing trees: the L-PEACH model

    New Phytol.

    (2005)
  • P. Balandier et al.

    SIMWAL: a structural–functional model simulating single walnut tree growth in response to climate and pruning

    Ann. For. Sci.

    (2000)
  • A.G. Bengough et al.

    Root responses to soil physical conditions; growth dynamics from field to cell

    J. Exp. Bot.

    (2006)
  • H. Ben Haj Salah et al.

    Temperature affects expansion rate of maize leaves without spatial distribution of cell length

    Plant Physiol.

    (1995)
  • N. Bernstein et al.

    Growth and development of sorghum leaves under conditions of NaCl stress: possible role of some mineral elements in growth inhibition

    Planta

    (1995)
  • N. Bertin et al.

    Evaluation d’un modèle dynamique de croissance et de développement de la tomate (Lycopersicon esculentum Mill.), TOMGRO, pour différents niveaux d’offre et de demande en assimilats

    Agronomie

    (1993)
  • I.J. Bingham et al.

    Control of root growth—effects of carbohydrates on the extension, branching and rate of respiration of different fractions of wheat roots

    Physiol. Plant.

    (1993)
  • A.J. Bloom et al.

    Root respiration associated with ammonium and nitrate absorption and assimilation by barley

    Plant Physiol.

    (1992)
  • T.J. Bouma et al.

    Analysis of root respiration of Solanum tuberosum as related to growth, ion uptake and maintenance of biomass

    Plant Physiol. Biochem.

    (1996)
  • N. Brisson et al.

    STICS: a generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn

    Agronomie

    (1998)
  • G.H. Buck-Sorlin et al.

    Barley morphology, genetics and hormonal regulation of internode elongation modelled by a relational growth grammar

    New Phytol.

    (2005)
  • M.M. Caldwell

    Plant architecture and resource competition

  • R. Cardenas-Navarro et al.

    Modelling nitrate influx in young tomato (Lycopersicon esculentum Mill.) plants

    J. Exp. Bot.

    (1999)
  • P. Chartier

    Assimilation nette d’une culture couvrante. II. La réponse de l’unité de surface de feuille

    Ann. Physiol. Vég.

    (1969)
  • M. Chelle

    Phylloclimate or the climate perceived by individual plant organs: What is it? How to model it? What for?

    New Phytol.

    (2005)
  • D.J. Connor et al.

    Effect of nitrogen content on the photosynthetic characteristics of sunflower leaves

    Aust. J. Plant Physiol.

    (1993)
  • T.M. DeJong et al.

    Seasonal relationships between leaf nitrogen content (photosynthetic capacity) and leaf canopy light exposure in peach (Prunus persica)

    Plant Cell Environ.

    (1985)
  • P. Delhon et al.

    Diurnal regulation of NO3 uptake in soybean plants. 4. Dependence on current photosynthesis and sugar availability to the roots

    J. Exp. Bot.

    (1996)
  • S. Demotes-Mainard et al.

    Effect of mutual shading on the emergence of nodal roots and the root/shoot ratio of maize

    Plant Soil

    (1992)
  • P. de Reffye et al.

    Modelling plant growth and architecture: some recent advances and applications to agronomy and forestry

    Curr. Sci.

    (1997)
  • de Wit, C.T., 1965. Photosynthesis of leaf canopies. Agric. Res. Rept. no. 663. Center for Agric. Publ. Doc,...
  • A.J. Diggle

    ROOTMAP: a model in three-dimensional coordinates of the growth and structure of fibrous root systems

    Plant Soil

    (1988)
  • M. Dingkuhn et al.

    Environmental and genetic control of morphogenesis in crops: towards models simulating phenotypic plasticity

    Aust. J. Agric. Res.

    (2005)
  • M.C. Drew et al.

    Nutrient supply and the growth of the seminal root system in barley. II. Localized, compensatory increases in lateral root growth and rates of nitrate uptake when nitrate supply is restricted to only part of the root system

    J. Exp. Bot.

    (1975)
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