As a quantitative ecologist and evolutionary biologist, I use computational modeling to address diverse questions. Currently, I am a postdoctoral researcher in the Kramer lab at the University of South Florida. We are using machine learning models to determine whether increased spatial resolution of satellite imagery improves predictions of invasive Aedes aegypti mosquito occurrence and abundance in California. I received my Ph.D. in the Biology department at the University of Vermont with the help of my advisor, Dr. Nicholas Gotelli. My dissertation focused on the effect of host ecology and evolutionary biology on the pathogen dynamics of Ranavirus, an emerging infectious amphibian disease.
In my postdoctoral research, I use XGBoost classification models to predict mosquito occurrence and abundance using nearly 10,000 trap site data across California. We assess how increasingly fine spatial resolution (1 km to 30 m) of remotely sensed climate and vegetation data — including temperature, precipitation, humidity, and NDVI — affects model accuracy.
2024 - presentI worked with large climate datasets to map and forecast distributions of invasive pest species in New England under different climate scenarios. Built automated model pipelines and visualizations as part of an NSF EPSCoR grant to create a pest atlas.
2023I received my doctorate through the Biology department at University of Vermont. My dissertation was titled "The Effect of Amphibian Host Ecology and Evolution on the Pathogen Dynamics of Ranavirus"
Aug. 2022I taught as a Visiting Assistant Professor at Middlebury College: Reproducible Biology in R (a course I created) and Ecology and Evolution for 1 semester each. As an Assistant Laboratory Professor, I taught Cell Biology and Genetics labs (2 years) and Ecology and Evolution labs (1 semester).
2021 - 2024I collected 4 Wood Frog egg masses from 10 locations and experimentally infected 5 tadpoles per egg mass with Ranavirus (and included 5 controls). I amplified the Major Histocompatibility Complex (MHC) gene in the experimental Wood Frog tadpoles most susceptible and most resistant to infection to identify any genetic differences and signatures of selection. Manuscript in prep.
2018 - 2022I investigated whether amphibian diversity is related to Ranavirus prevalence and viral load. A positive relationship would be an example of the amplification effect, while a negative relationship would be an example of the dilution effect. Manuscript in prep.
2019 - 2022I collected liver tissue from Bullfrog (Lithobates catesbeianus) and Amazonian anuran species to analyze whether the presence and abundance of Ranavirus is associated with the presence and abundance of anuran macroparasites. Published in the International Journal for Parasitology: Parasites and Wildlife (2024) doi:10.1016/j.ijppaw.2024.100924.
2019 - 2022Over my 6 years of teaching as a GTA I taught: Computational Biology laboratory to graduate and advanced undergraduate students for 5 semesters; Ecology and Evolution to sophomore-senior undergraduate Biology majors for 7 semesters; and Exploring Biology to freshman-sophomore Biology majors for 2 semesters.
2015 - 2022Overall, I collected and tested 1,927 amphibian toe and tail tissue samples from 31 sites across Vermont.
Summers 2016 - 2019I started my doctorate degree at the University of Vermont, advised by Dr. Nicholas Gotelli.
Aug. 2015I graduated UCL with a Master of Research in Biodiversity, Evolution, and Conservation, completing two species distribution modeling projects during that time. My work using support vector machine (SVM) modeling to predict seaweed community classification was published in Aquatic Conservation (2018) doi:10.1002/aqc.2905.
Sep. 2014I graduated from UF with a Bachelor of Science in Wildlife Ecology and Conservation.
May 2012R
GIS
Species Distribution Modeling
qPCR
DNA isolation
Unix
Field work
This study investigated co-infection patterns between Ranavirus and helminth parasites in invasive bullfrogs in Brazil’s Atlantic Forest. The repository includes raw data and analysis code for the peer-reviewed publication.
As part of an NSF EPSCoR project, this atlas uses high-resolution environmental data and species distribution models to map and forecast the spread of agricultural and forest pests in New England.
© 2025 Dr. Lauren V. Ash