Model-assisted integration of physiological and environmental constraints affecting the dynamic and spatial patterns of root water uptake from soils

Abstract

Due in part to recent progress in root genetics and genomics, increasing attention is being devoted to root system architecture (RSA) for the improvement of drought tolerance. The focus is generally set on deep roots, expected to improve access to soil water resources during water deficit episodes. Surprisingly, our quantitative understanding of the role of RSA in the uptake of soil water remains extremely limited, which is mainly due to the inherent complexity of the soil-plant continuum. Evidently, there is a need for plant biologists and hydrologists to develop together their understanding of water movement in the soil-plant system. Using recent quantitative models coupling the hydraulic behaviour of soil and roots in an explicit 3D framework, this paper illustrates that the contribution of RSA to root water uptake is hardly separable from the hydraulic properties of the roots and of the soil. It is also argued that the traditional view that either the plant or the soil should be dominating the patterns of water extraction is not generally appropriate for crops growing with a sub-optimal water supply. Hopefully, in silico experiments using this type of model will help explore how water fluxes driven by soil and plant processes affect soil water availability and uptake throughout a growth cycle and will embed the study of RSA within the domains of root hydraulic architecture and sub-surface hydrology.

A Hydraulic Model Is Compatible with Rapid Changes in Leaf Elongation under Fluctuating Evaporative Demand and Soil Water Status

“…In a wet soil (20.01 MPa), plant hydraulic conductance is lower than soil hydraulic conductance, thereby making the major contribution to limiting water movements. This is not the case at 20.15 MPa (Draye et al, 2010).…”

3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture

“…This knowledge gap exists primarily because of the difficulties in imaging root systems and in identifying relevant quantitative phenotypes from complex topologies (3,4,41,42). Computer simulations supported by empirical field work can suggest ideal root architectures, or ideotypes, that are best suited to a particular environment (10,(43)(44)(45)(46). Moreover, root allocation tradeoffs may limit certain RSA combinations, such as between root growth in the topsoil versus deep soil horizons (3,10,47,48), and these tradeoffs may have a genetic basis.…”

Analyzing Lateral Root Development: How to Move Forward

“…Models can test and validate biological hypotheses, and models can be inverted to determine the hidden parameters of a system (Dupuy et al, 2010). Models can also integrate complex environmental and developmental variables, including, for example, response to water and nutrient supply (Dunbabin et al, 2002;Draye et al, 2010), various phosphorus concentrations (Fang et al, 2009), root adaptation to low nitrogen soil under carbon flux modifications (Brun et al, 2010), and the formation of root cortical aerenchyma in response to soil nutrient status (Postma and Lynch, 2011). Software packages are also available to facilitate the (re)construction of root systems, such as SimRoot (Lynch et al, 1997).…”

“…Software packages are also available to facilitate the (re)construction of root systems, such as SimRoot (Lynch et al, 1997). Recent progress in elucidating the biological, chemical, and physical processes affecting root growth in soil allows models to be constructed that integrate fundamental regulatory mechanisms into powerful mathematical frameworks incorporating both variability and plasticity (de Dorlodot et al, 2007;Draye et al, 2010). Taken together, these tools will help understanding the system and knowledge gaps and/or capture and predict the relevant properties of a root system.…”