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Published online 17 May 2007
Published in Vadose Zone J 6:269-281 (2007)
DOI: 10.2136/vzj2006.0067
© 2007 Soil Science Society of America
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Root Functional Architecture: A Framework for Modeling the Interplay between Roots and Soil

Alain Pierreta,*, Claude Doussanb, Yvan Capowiezc, François Bastardiec and Loïc Pagèsd

a Inst. de Recherche pour le Developpement–Int. Water Management Inst.–Natl. Agric. and Forestry Res. Inst., c/o Ambassade de France BP 06, Vientiane, Lao PDR
b Inst. Natl. de la Recherche Agron.–Unité Climat, Sol et Environ., Domaine Saint Paul, Site Agroparc, 84914 Avignon Cedex 9, France
c Inst. Natl. de la Recherche Agron., Lab. de Toxicologie Environ., UMR INRA/UAPV, Domaine Saint Paul, Site Agroparc, 84914 Avignon Cedex 9, France
d Inst. Natl. de la Recherche Agron., Unité Production et Systèmes Horticoles, Domaine Saint Paul, Site Agroparc-84914 Avignon Cedex 9, France


Figure 1
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FIG. 1. Comparison of the rooting patterns of (A) a perennial monocotyledon (Lolium multiflorum and (B) a perennial dicotyledon species (Achillea millefolium) (from Kutschera, 1960).

 

Figure 2
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FIG. 2. Effects of localized (i) nutrient supply and (ii) physical constraint on the root system architecture of a monocotyledon and a dicotyledon. Root system architecture of a barley plant (Hordeum vulgare cv. Proctor) (A) uniformly supplied with nitrate or (B) supplied with nitrate through a banded treatment. The banded treatment triggered root proliferation in the zone of nitrate supply (Drew, 1975). Comparison of the architectures of two Lupinus angustifolius root systems: (C) physically unconstrained growth conditions, and (D) taproot growth stopped by a physical obstacle at an early developmental stage.

 

Figure 3
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FIG. 3. (A) Root impact map illustrating soil exploration by roots in compacted soil horizons in which cracks represent paths of least resistance preferentially explored by roots (Tardieu and Katerji, 1991). (B) A model for relative root elongation rate as a function of matric potential, at different levels of soil strength Qp (MPa), measured by a penetrometer (Dexter, 1987): as soil strength increases and soil is drier, relative root elongation (R/Rmax) decreases.

 

Figure 4
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FIG. 4. Simulation of the influence of different degrees of basal root gravitropism on the exploitation of P by bean (Phaseolus vulgaris L.) root systems. The depletion zone of P is represented by diffusion of P to the root with time (Diffusion coefficient 10–8 cm2 s–1). (A) Bean root systems simulated with different rooting patterns (shallow; Carioca, a cultivar, and deep). (B) Volume of the overlapping exploited zones for the three root system types. (C) P uptake by the three simulated root systems at the end of simulation (320 h), in the case of a stratified soil profile of P (P concentration is higher in the first 20 cm of soil) (from Ge et al., 2000).

 

Figure 5
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FIG. 5. Simulated three-dimensional root architecture (coupled with water and nitrate transfer and uptake by the root system) with corresponding root density and nitrate concentration distribution for (A) continuous supply of nitrogen by drippers and (B) the same amount of nitrogen, but supplied at the beginning of the simulation period (from Somma et al., 1998).

 

Figure 6
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FIG. 6. Simulation of nitrate uptake efficiency with an architecture model taking into account both inflow and morphological plasticity of the root system. Nitrate is distributed in the soil as small patches. The efficiency of uptake with plasticity is relative to the same root system with no plasticity response. Root systems are (A) herringbone system and (B) dichotomous system. In the dynamic supply case, the nutrient patches are randomly redistributed in space, which is not the case for static supply (from Dunbabin et al., 2001).

 

Figure 7
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FIG. 7. Simulation of maize (Zea mays L.) root system architecture interacting with the environment. A plow pan layer impedes root growth at 35 cm depth. (A) General morphology of the simulated maize plant. (B) Simulated (+) and observed (·) root profiles, obtained by counting the number of colonized cells (2 x 2 cm) on vertical grids. The horizontal bar represents one standard deviation (from Pagès, 1999). (C) A simple example of simulated root growth around mechanical obstacles (rocks) in a homogeneous soil (from Prusinkiewicz, 1998).

 

Figure 8
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FIG. 8. Modeling of the interactions between roots and soil structure. (A) Comparison between two 100-d-old maize (Zea mays L.) root systems, the first one (left-hand side) grown in a homogeneous soil volume and the second (right-hand side) grown in a structured soil consisting of a 25-cm-thick tilled layer with distributed dense clods, a 3-cm plow layer and a ~1.2-m-deep subsoil with biopores (earthworm burrows). In the case of the structured soil, the interactions between growing roots and soil structure have led to reduced rooting depth and lateral expansion of the root system. This is largely due to the trapping of roots in macropores at certain soil depths (50–55 cm in particular), as shown by (B) the high occurrence of root-to-macropore distances less than the voxel size (1 cm) .

 

Figure 9
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FIG. 9. Distribution of water uptake fluxes within a simulated maize (Zea mays L.) root system. Water uptake is simulated by taking into account the variability of the root hydraulic conductance in the root system (from Doussan et al., 1999).

 

Figure 10
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FIG. 10. Simulation of the propagation of a water uptake front across the root system of a 50-d-old narrowleaf lupin (Lupinus angustifolius) with a fibrous root system, growing in a sandy rhizotron. Length scale in centimeters. Distribution of calculated water uptake within the root system 1.5, 5, 7, 9, and 11.5 h after the beginning of an uptake experiment. The rates are expressed as flux density (i.e., volumetric flow rate normalized to the root surface area [cm3 cm–2 s–1]). The red lines show the downwardly moving zone of active water uptake. The green color shows negative flux rates, that is, water exsorption by roots (from Doussan et al., 2006).

 





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