research

My interests generally fall into two facets, motivated by their potential to improve decision-making on policies relevant to ecosystem health.

using ecological and evolutionary theory to understand variation in individual, population, or community responses to perturbations, including emerging infectious disease
developing computational tools that increase accessibility to and breadth of ecological data

previous work

sex-biased infections scale to population impacts for an emerging wildlife disease

Host sex is a source of within-population variation in disease that can affect transmission and impacts.

In this study, we found that females across all host species of a fungal pathogen had higher prevalence and infection severity, which reduced the proportion of females in populations through invasion years.

mating strategies explain sex-biased infection in an emerging fungal disease

Mating dynamics can be key determinants of how species respond to global changes.

In this study, we showed that differences in mating phenology between females and males can contribute to seasonal female-biased disease.

ongoing projects

an R-based pipeline for working with PIT tag data

New technology, including PIT tag systems, are allowing for the passive monitoring of individuals that can provide fine-scale information on movement, behavior, survival, etc.

We are developing a replicable workflow and complementary R package to assemble, manipulate, and analyze the big datasets generated from PIT tag systems. The new R package will increase accessibility of the systems and broaden their use by diverse stakeholders, expanding the information collected and potential use in conservation strategies.

population responses to pathogen invasion under sex-biased mortality

My previous work showed that females suffer from more severe disease than males, which resulted in the restructuring of disease-impacted populations through higher female mortality.

This project uses a population modeling approach to examine the degree to which female-biased mortality from disease can affect future population trajectories and recovery pathways.