Modelling Plant Information Flows


In days of global climate change and population growth, the demand on food production is ever increasing. In order to be able to feed the future world population, plant scientists and agronomists need to find new ways to produce more with less ressources.

Instead of having one centralised center of decision, like animals, plants have thousands of de-centralised ones, the meristems. Each one of them is capable of responding to signals in order to adapt their structure, growth, development and function. Such response is done by integrating both exogenous and endogenous factors. On the one hand, exogenous factors inform the meristems about their direct environment so they can adopt the best strategy to optimise the capture of surrounding ressources. On the other hand, the endogenous factors informs each meristem about the needs and status of the other organs (fig. 1C). Ultimately, the local integration of both leads to complex, diverse and plastic growth and developmental patterns. Such patterns are of outmost importance for the plant, as they will define its ability to survive in potentially challenging environment.

[A] At the plant level, different types of information are constantly integrated. [B] Leaf stomatas locally integrate informations from their direct exogenous such as light and Vapour-Pressure Deficit [VPD] and endogenous environments such as water pressure and abscissic acid [ABA]. [C.] Root apical meristems locally integrate local exogenous, like soil water and nutrient, and endogenous informations, such as carbon and auxin [IAA]

Information transfer is therefore at the very center of most of plant physiological processes (fig. 1A). This transfer can be of various nature. For instance, information about the water status of the plant is known to be conveyed both by physical (e.g. changes in water pressure in different plant organs, such as roots, leafs or xylem) and biochemical (e.g. production, transport and degradation of abscissic acid, ABA) processes (fig. 1B).

In 1880, Charles Darwin published the Power of Movement in Plant, a pioneer work in plant biology that explores how information transport within the plant would affect its development. Since then, with the advent of plant molecular biology techniques, much knowledge has been gained into the diversity and complexity of transport and regulation processes. Most of this knowledge has been acquired in the model plant Arabidopsis thaliana and remains, still today, mainly qualitative. This knowledge, mostly untapped by breeders and agronomists, presents a unique opportunity to design innovative solutions to the increasing food demand. However, the limiting step still remains the transfer of discrete and localised knowledge at the molecular and cell levels into functional plant responses to complex environments.

Functional-Structural Plant Models (FSPM's) have been used by scientists for severals decades. These models explicitly simulate the growth and development of single plants, together with complex physiological processes and environmental responses. They have been used, among other things, to study water dynamics in the soil-plant systems , long distance transport of signalling molecules or the response of root system development to heterogeneous nutrient supplies.

Here, we propose to use Functional-Structural Plant Modelling (i) to understand how various signals that carry information are interacting and being conveyed and integrated at the plant level and (ii) to amplify discrete physiological knowledge into functional plant processes.

Overview of the project.

Associated papers

A modeling approach to determine the importance of dynamic regulation of plant hydraulic conductivities on the water uptake dynamics in the soil-plant-atmosphere system | 2014 | Lobet G, Pagès P and Draye X | View paper

Associated presentations

First steps towards an explicit modeling of aba production and translocation in relation with the water uptake dynamics | 2013 | View on figshare

Water relations in the soil-plant system. What can we learn from functional-structural plant models | 2014 | View on figshare

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