Predict the potential distribution of an invasive tick in North America

Dr. Krisztian Magori is the next speaker in our meeting on 27 October. Details of his presentation are given below. Hope to see you all on the 27th.

Title: Using R to predict the potential distribution of an invasive tick in North America

The Asian longhorned tick is an invasive livestock pest in Asia and Australia that can reproduce parthenogenetically, i.e. the females can reproduce without males, leading to infestions of thousands of ticks on a single sheep or cattle. This tick has been found for the first time in North America in August 2017 on a sheep on a farm in New Jersey. Since then, it has been found across 9 states in 44 counties in the Eastern US, going back to 2010, with a potential for further spread. In order to determine the potential geographic range of this tick in North America, I adopted a published ecological rule-based niche model from New Zeeland, and applied it to North America, using R. After predicting the potential range of this tick, I obtained data on livestock production in the US by county in order to identify the counties most likely to experience significant economic losses due to this tick in the future. I published these results as a pre-print. Because the tick was spreading further during my project, I had to adjust my model and results multiple times, so I created my pre-print in R Markdown in order to easily update and revise it. In this presentation, after a brief introduction to this tick, I aim to show you how I did the modeling and the updating process in R and R Markdown, and highlight the benefits of preprints in general.

Speaker: Krisztian Magori Ph.D., is the Assistant Professor of Biostatistics at the Department of Biology at Eastern Washington University. He teaches both undergraduate and graduate biostatistics classes using R, and consults many students and faculty in the same. He is also a disease ecologist investigating the ecological relationships between hosts, pathogens, and vectors, such as ticks and mosquitoes and their environment.