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Optimization of the Monitoring and Management of the North American Gypsy MothEPA Grant Number: F5C30583
Title: Optimization of the Monitoring and Management of the North American Gypsy Moth
Investigators: Bogich, Tiffany L
Institution: Pennsylvania State University
EPA Project Officer: Zambrana, Jose
Project Period: August 1, 2004 through May 1, 2006
Project Amount: $73,338
RFA: STAR Graduate Fellowships (2005) RFA Text | Recipients Lists
Research Category: Academic Fellowships
A tremendous amount of effort is put into the detection and eradication of invasives, but not necessarily in the most economically or biologically efficient manner. In my research, I am using optimization with Stochastic Dynamic Programming (SDP) as a tool to examine the best spatial strategy of attack on a particular invasive species, the gypsy moth (Lymantria dispar)- a non-native forest pest that has caused wide-spread damage to both natural and managed systems.
My research is aimed at developing a useful mathematical tool to optimize the plan of attack for the control of the gypsy moth.
Using historical data on spread rates and management costs from the United States Department of Agriculture (USDA), I will apply quantitative methods, specifically Stochastic Dynamic Programming (SDP), to the question of optimal management, adding increasingly more realistic and complex dimensions to the model. The SDP algorithm will lead to the set of strategies that will result in the 'least invasive' state of the system within a defined time frame.
The initial mathematical model will yield answers to fundamental questions of management based on strategies of pesticide application to control gypsy moth populations. I expect that the best management strategy will be highly dependent on the initial state of the system, that is, the current state of invasion by the gypsy moth. The final model will be a useful decision making tool in managing the spread of the gypsy moth in North America while also considering the possibility of invasion by a potentially more devastating Asian relative of the current invader.