Functional and Structural Optimality in Plant Growth: A Crop Modelling Case Study

Abstract:

Simple mechanistic models of vegetation processes are essential both to our understanding of plant behaviour and to our ability to predict future changes in vegetation. One concept that can take us closer to such models is that of plant optimality, the hypothesis that plants aim to achieve an optimal state. Conceptually, plant optimality can be either structural or functional optimality. A structural constraint would mean that plants aim to achieve a certain structural characteristic such as an allometric relationship or nutrient content that allows optimal function. A functional condition refers to plants achieving optimal functionality, in most cases by maximising carbon gain. Functional optimality conditions are applied on shorter time scales and lead to higher plasticity, making plants more adaptable to changes in their environment. In contrast, structural constraints are optimal given the specific environmental conditions that plants are adapted to and offer less flexibility. We exemplify these concepts using a simple model of crop growth. The model represents annual cycles of growth from sowing date to harvest, including both vegetative and reproductive growth and phenology. Structural constraints to growth are represented as an optimal C:N ratio in all plant organs, which drives allocation throughout the vegetative growing stage. Reproductive phenology - i.e. the onset of flowering and grain filling - is determined by a functional optimality condition in the form of maximising final seed mass, so that vegetative growth stops when the plant reaches maximum nitrogen or carbon uptake. We investigate the plants' response to variations in environmental conditions within these two optimality constraints and show that final yield is most affected by changes during vegetative growth which affect the structural constraint.