Thermal mismatch models derived from occurrence data predict pathogen prevalence in frogs

Area of Science:

• Ecology
• Wildlife disease
• Pathogen-host interactions

Background:

• Emerging infectious diseases pose significant threats to wildlife populations.
• Pathogen impacts vary within and among host species, influenced by environmental conditions.
• The environmental tolerance mismatch hypothesis (ETMH) posits that host and pathogen performance under varying environmental conditions drives this variability.

Purpose of the Study:

• To test the ETMH by examining the relationship between thermal niche mismatch and the prevalence of the amphibian fungal pathogen *Batrachochytrium dendrobatidis* (Bd).
• To assess if thermal mismatch can predict Bd prevalence within and among Australian frog species.
• To explore the utility of species occurrence data for predicting pathogen outcomes.

Main Methods:

• Derived species realized thermal niches from occurrence data for 42 Australian frog species.
• Quantified thermal mismatch between frog hosts and the Bd pathogen.
• Analyzed the relationship between thermal mismatch and Bd prevalence within and among species.

Main Results:

• Thermal mismatch reliably predicted variation in Bd prevalence across Australian frog species.
• Within species, warmer-adapted hosts exhibited a steeper decline in Bd prevalence with increasing temperature.
• Among species, higher pathogen prevalence was associated with closer thermal affinities between hosts and the pathogen.

Conclusions:

• Findings strongly support the ETMH, demonstrating its applicability in predicting wildlife disease dynamics.
• Thermal niche mismatch, derived from occurrence data, is a robust predictor of pathogen prevalence.
• This approach offers a valuable tool for spatial and temporal prediction of pathogen impacts and can inform conservation strategies.