Browsing by Author "Van Vuuren, Brian John"
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- ItemAn agent-based model of Eldana Saccharina Walker(Stellenbosch : Stellenbosch University, 2016-12) Van Vuuren, Brian John; Potgieter, Linke; Bekker, James; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: An agent-based simulation model is formulated in this dissertation in order to simulate the population dynamics of Eldana saccharina Walker infestation in sugarcane. The simulation model comprises four distinct building blocks, namely a graphical user interface, the implementation of the life cycle and associated influence of temperature on E. saccharina, the mating process of E. saccharina and the oviposition and dispersal of E. saccharina. These building blocks are based on existing literature pertaining to the biology and behaviour of the pest and, in cases where the relevant literature is insu cient or non-existent, expert opinion and careful assumption. In order to select areas from existing sugarcane farms on which to execute location-speci c experiments, functionality which allows Geographic Information Systems (GIS) data importation is included as a platform on which to run the simulation model. These data inform the model in respect of the shape and characteristics of the underlying sugarcane elds in which the simulated E. saccharina population interacts. The model interacts and operates within an AnyLogic simulation software environment and, in so doing, aims to emulate the behaviour of a population of E. saccharina moths in sugarcane. It is anticipated that the model implementation may serve as a basis for facilitating future design and testing of control measures in order to suppress the pest and its consequent detrimental e ect to sugarcane through infestation and feeding on interior stalk nutrients. Numerous working mathematical models of the pest exist in the literature, but, in all previous cases, intricate aspects of the stalk borer's biology have been aggregated on a population level and average population changes have been a ected at discrete time steps. The resulting analyses therefore yield conclusions that do not necessarily re ect the continuous, changing nature of E. saccharina on a localised level. Using agent-based modelling, however, the pest's behaviour may be modelled in more detail so as to facilitate more thorough investigation of potential control strategies and their expected e cacy on the pest at di erent points in its life cycle. The agent-based simulation model designed in this dissertation is subjected to a number of veri cation and validation techniques. Furthermore, a pilot sensitivity analysis is conducted to identify the most in uential parameters in the simulation model. These parameters are then considered further in a comprehensive parameter variation analysis in order to illustrate the exibility and diversity of the model in terms of the variety of scenarios pertaining to E. saccha- rina population behaviour that it can accommodate. In some cases, simpli ed implementations of control measures are also imposed on the pest within the model in order to further illustrate its implementation capabilities, as anticipated for future model development and use. In light of this exibility, the model is also presented as a computerised decision support and analysis tool, including the ability to upload and recreate a speci c user's own sugarcane farm shape le, as well as to alter a set of available parameters. This may aid in simulating speci c behaviour in a simulation run in accordance with what has typically been observed by the user, or of hypothetical scenarios which require investigation. In turn, as the model is further developed and detailed control measures are included as part of the simulation execution, it is believed that an appropriate response pertinent to the characteristics of the geographical area under consideration and the corresponding E. saccharina population present in this area may be predicted, allowing for control measure alteration and redesign so as to optimise the associated parameters or actions prior to in- eld implementation. In order to further re ne the model and improve its accuracy, as well as ensure agreement between the existing modelling approaches and actual biological processes in nature, the entire simulation model of E. saccharina is subjected to an expert panel discussion. The experts comprising the panel encompass some of the key researchers pertaining to E. saccharina and other moth behaviour and population dynamics, both in South Africa and internationally. The simulation model is updated or adjusted according to suggestions made and new information shared by the expert panel in an attempt to simulate the pest as accurately as possible in accordance with the body of knowledge currently available. Although several other approaches to modelling E. saccharina populations have been adopted in the past, no existing models implement such a low level of abstraction with respect to the biology of the pest. In addition, previous models are often case-speci c, investigating speci c control measures that are imposed on an aggregate level on a population of the pest. By actively simulating E. saccharina's biological decision-making processes, intricate aspects pertaining to one or a number of interacting control strategies, as well as the manner in which they alter the pest's biology or behaviour, may easily be incorporated using an agent-based simulation modelling approach. Adopting a low level of abstraction also requires extensive information pertaining to the pest and, as such, areas where little understanding still exists with respect to the behaviour of E. saccharina have been highlighted and, consequently, may be prioritised for future entomological research by experts in the eld. Finally, numerous options for future investigation into this problem, including model re nement, control measure design and testing and comparison to existing models, pose positive possibilities for the eventual establishment of a functional, integrated pest management programme for E. saccharina.