snail-learning

Predicting the spatial distribution of an invasive apple snail

Snail-learning was my Statistical Machine Learning (ABE6933) final project in Fall 2018 and will be further refined into my senior thesis in Spring 2019. With an invasive apple snail (Pomacea maculata) dispersing quickly throughout the southeastern US, it is important to understand the extent of its range in order to predict the distribution and success of the endangered Florida snail kite population. Machine learning methods were employed to identify which environmental variables best predicted the spread of the snail and to build a predictive model of its distribution.