Nicholas D. Stone

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

Abstract 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?’.

Generation of mechanistic variability in a process-based object-oriented plant model

Abstract A cotton crop model based on individual plant developmental behavior and variability was developed. Object-oriented simulation (OOS) provided the conceptual basis for the new model structure. The procedural model, COTSIM, provided the theoretical background for cotton plant development. Data collected during 1987 from field-grown cotton were used for model development and verification, and data from 1988 were used for model validation. The model predicted mass accretion and production of organs within the patterns and magnitudes observed in the field. The model also predicted crop development aspects that had not previously been described by procedural models. Age and size of leaves and fruit and associated developmental variability were included in the model through representation of objects and their variable behavior defined by their position on the plant and how this constrains their growth. Observed variability was the result of the aggregate behavior of components. Variability in our OOS model is an output as opposed to being an input in most procedural plant models. The model has recreated both realistic plants and populations in a mechanistic simulation. Object-oriented models are an important step towards common structures and languages for model design and the development of simulations. It was noted that increased mechanistic detail resulted in an increase of procedure calls (messages) and a five-fold increase in model run time.

A dynamically linked expert-database system for decision support in Texas cotton production

Abstract This paper describes a prototype of a farm level expert (FLEX) system providing firm-level decision support for cotton farms in central Texas. The system was developed on a Pyramid 90x computer running the UNIX operating system. The system integrates a farm and field database with simulation models and expert system to provide advice on key strategic and tactical decisions relating to cotton production throughout the calendar year. CLIPS, the C-Language Integrated Production System developed by NASA, was used as the inference engine. Modifications were made to CLIPS to provide a menu-driven user interface and frame-like knowledge representation through dynamic access to C-language structures in the database. A rudimentary model-based reasoning component was added and is being expanded to allow the system to deal with some unforeseen field situations. Currently, the program is being ported to an IBM PC/AT for delivery to the field. Components of the system are being tested in the field.

Effect of Parasitism by Varroa Jacobsoni on Morphometrics of Africanized Worker Honeybees

SummaryAfricanized bees infested with 0–5 Varroa jacobsoni mites per bee were measured for 23 lengths and 25 angles on the forewing and 3 lengths on the hind leg. Bees infested with 1–2 mites exhibited virtually no consequence. For bees infested with up to 4–5 mites, some of the measurements had a simple regression on increased mite infestation in at least one data set, but affected structures often differed in this respect between colonies and on the left and right sides of bees. All such lengths exhibited a negative regression. The net effect of parasitism on the exoskeleton appears minor in contrast to reports of substantial loss of protein, haemolymph volume, weight and reduced longevity suffered by infested bees. This is probably because differentiation of the exoskeleton occurs mainly before the most intense feeding by mites and cuticle development proceeds despite a diminishing protein reserve.

Inclusion of plant structure and fiber quality into a distributed delay cotton model to improve management and optimize profit

Abstract This research introduces a simple variation of distributed delay algorithms to solve some relevant problems in simulation of plant development. Cotton was used as a case study. An energy-based model of cotton plant growth was expanded to account for production of fruit at different main-stem nodes and fruiting branch positions. The inclusion of plant structure in a simulation model permitted more accurate estimation of projected harvest value. The implications to crop and pest management are two-fold. Higher levels of resolution in the plant structure can result in improved estimates of crop value and insect economic injury levels. More explicit representation of plant structure provides a more natural framework for integrated insect models based on organism behavior such as location and fruit size preference. An algorithm is presented to enhance the resolution of ecological applications that include developmental variability. The effects of cotton plant structure on cotton lint yield and fiber quality were determined for a short-season cultivar, TAMCOT CD3H. An existing cotton plant model, COTSIM, was used and adapted to short-season production. The cotton plant model was modified to include plant architecture. Fiber quality parameters and yield of fruit at different branch positions were determined for the test cultivar. Arrays corresponding to different fruiting branch positions and fiber property trends were constructed to better corresponde with patterns observed in field data. These patterns showed that fiber properties are closely associated with the positions on a fruiting branch. The development of fruit position-cohorts was modeled using an algorithm that simulates the distribution of growth rates with a time-distributed delay. This algorithm was extended to include arrays to represent fruit produced at different fruiting branch positions on the plant. The model predicted observed fruiting data from non-stressed plants well. The inclusion of the effects of plant structure on cotton yield and fiber quality permitted a more accurate determination of cotton prices. In addition, when linked to insect pest models, this model will simulate a dynamic, position-dependent effect of insect damage on fruiting structures and economic loss.

An expert system to elicit risks preferences: The futility of utility revisited.

Abstract An expert system, ASSESS, is presented which is designed to elicit risk preferences. ASSESS measures risk preferences inexactly with an interval measure that is easily used with Generalized Stochastic Dominance to rank alternative management strategies for risk efficiency. The literature on risk attitude assessments is reviewed and the expert system is described. The design of ASSESS is discussed in the context of the current literature on elicitation procedures. ASSESS is one component of the overall COTFLEX system being developed to help cotton producers with key management decisions in the United States.