Object-oriented simulation: plant growth and discrete organ to organ interactions

This paper reviews and applies new hierarchical approaches to ecological modelling. These new approaches are made possible by the development of the object-oriented paradigm. This paradigm draws upon the notion of ‘universal’ or classes dating back to early Greek philosophy. It is an intriguing approach to simulation because it is based upon the concepts of hierarchy and taxonomy, two of the basic organizing principles in ecology. Adopting an object-oriented approach to simulation can result in a reduction of mathematical and statistical abstraction. The object-oriented approach lends itself directly to incorporation of mechanisms within appropriate hierarchies. A case study is presented outlining the design steps for simulating plant growth objects (roots, stem, leaves, fruit, whole plant, etc.). The design steps are shown in graphical form to illustrate the differences between object-oriented and traditional procedural approaches. Cotton growth and development has been selected for the case study because of the large knowledge base available for the explicit representation of age and size for each organ. Inclusion of mechanisms at the level of the individual organ provides additional information for crop management. Computing fruit growth at discrete branch locations results in the ability to manage for optimum fiber yield and reduced pest vulnerabilities for individual bolls. Variability in light interception, leaf age, and resulting carbohydrate supply for leaves at specific positions leads naturally to variability in individual boll fiber yield. The goal of the model to capture the behavior of individual organs as a function of their interaction with other organs was achieved. The object-oriented paradigm facilitates the formulation of a simulation procedure in which an individual organ interacted with other organs and the crop microclimate. This led us one step closer to answering the question, ‘How do individual characteristics and behaviors result in given population patterns?’.