I am a quantitative ecologist interested in disease dynamics, community and population ecology, and species conservation.

To mimic natural hierarchical systems, I develop hierarchical Bayesian models, and I exploit data collected over space and time to separate ecological and observational processes to answer ecological questions.

My research program focuses on unifying ecological and evolutionary theory to address fundamental questions in disease ecology using field, experimental, and quantitative approaches. 

Research program

Population & Community ecology

Broadly, I am interested in understanding how disturbance impacts population dynamics and community composition. 

​One type of disturbance are disease outbreaks. In this case, we might expect that different species would respond differently to disease infection, where differences are reflected in population dynamics; and that there may be some commonalities across species-responses at the community level.
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Read more:

• Tadpole community disassembly following a Bd outbreak (DiRenzo et al. 2016)
• Persistence of amphibians following outbreak  (DiRenzo et al. 2019)
• Trophic cascades due to amphibian loss (Zipkin et al. 2020)

Advanced quantitative approaches

​Broadly, I am interested in understanding how imperfect host detection influences parameter estimation and inference, while taking advantage of commonly collected data (i.e., data from populations where individuals are not individually marked).
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I develop novel Bayesian hierarchical models using detection/non-detection or count data to accurately and precisely estimate parameters that are comparable to estimates generated from data collected by marking individuals, which can be costly and labor-intensive.

​Read more:

• ​​​Imperfect pathogen detection (DiRenzo et al. 2018)
• Multi-state generalized N-mixture model (DiRenzo et al. 2018)
• Quantitative approaches in disease ecology (DiRenzo & Grant 2019)

Disease ecology
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Species do not occur in isolation, and their interactions likely contribute to their disease dynamics. For example, species with high infection intensities, abundance, or prevalence may contribute disproportionately to community disease dynamics.

I use lab experiments and field data to test hypotheses relating to variation in transmission and reservoirs. 

Read more:​

• External re-infection (DiRenzo et al. 2018)
• Atelopus zeteki, a potential acute supershedder (DiRenzo et al. 2014)
• Chytrid viability shed from two endandered tropical amphibians (Maguire et al. 2016)