Underground decision making; where to grow, when to branch

Abstract

In this thesis we study decision making in plant roots specifically for the cases of prepattering of lateral root competent sites and directional root growth by using multi-level computational models. Using these models we aim to understand how the combination of root architecture, developmental processes and hormone production and transport can drive decision making in plant roots and furthermore how environmental factors can impinge on the decision making process. Through using visualization techniques that allow interpretation of a combination of temporal and spatial information it was possible to elucidate the highly dynamic nature of lateral root priming and halotropism respectively. The results of this thesis showed that the dynamics of the plant hormone auxin act as an information integrator for both lateral root priming and halotropism, the results show a vital role for the auxin reflux loop as an integrator of the information flow. Additionally, plant root architecture, cell sizes, shapes and growth processes play a vital role in spatial location of a signal and timing of the information flow. Together the studies in this thesis highlight the importance of dynamic spatial explicit models as a valuable, independent research tool particularly for the unravelling of highly complex, emergent properties for which available experimental tools are limited.