R. K. Plowright

The paper uses explainable AI to predict food shortages in Eastern Australian flying foxes, identifying environmental and bat-level features that predict nutritional stress with high accuracy.

This paper introduces a Bayesian multilevel model to estimate prevalence dynamics from pooled and individual wildlife samples, accounting for dilution effects and false negatives.

The paper shows that periodic increases in viral load during high prevalence periods in bats correlate with spillover events, suggesting viral load is a better predictor of transmission risk than prevalence alone.

The paper investigates Nipah virus shedding in bat roosts near human cases in Bangladesh, finding that viral RNA can be detected up to 52 days post-exposure, supporting targeted sampling for better viral ecology understanding.

The paper examines factors driving Nipah virus spillover in Bangladesh, finding winter temperature explains 53% of annual spillover variation and linking land use changes to bat behavior and viral transmission risk.

This study integrates evaporative water loss into a hibernation model to assess how host and pathogen traits influence survival in white-nose syndrome.

This paper introduces Phylofactorization, a graph-partitioning algorithm to identify phylogenetic scales in ecological data, and demonstrates its application to mammalian body mass and gut microbiome studies.