Akshay Seetharam

Thesis Advisor: Dr. Christina Edholm (Scripps College - Department of Mathematics)

Second Reader: TBD

Contact: aseetharam@hmc.edu

Abstract Description of project here

Diaprepes abbreviatus, commonly known as the cirtrus root weevil or sugarcane rootstock borer weevil, is a species of beetle native to the Caribbean and is now an invasive pest in agriculture across the United States, with a range stretching from Southern California to Florida. Nematodes, which act as parasites against beetles, are commonly used as a method of biological control to minimize the growth of Diaprepes populations. Many different strategies for this control (i.e. how many nematodes to introduce, and when to change tactics in response to a responsively changing Diaprepes population) have been developed; two in particular are adaptive and optimal control. Previous work with Dr. Edholm has determined that adaptive control tends to outperform optimal control (minimizing costs while maximizing Diaprepes death) in most cases, but the precise conditions upon which optimal control might do better are not well understood. Furthermore, stochasticity due to climate change and other mathematical models of control have not been explored in detail. This project will first aim to incorporate a linear programming–based mathematical structure, and later consider possibilities for incorporating stochasticity and strategy-switching to combat the weevil scourge.