Abstract

Predicting the emergence and spread of infectious diseases is critical for the effective conservation of biodiversity. White-nose syndrome (WNS), an emerging infectious disease of bats, has resulted in high mortality in eastern North America. Because the fungal causative agent Pseudogymnoascus destructans is constrained by temperature and humidity, spread dynamics may vary by geography. Environmental conditions in the southern part of the continent are different than the northeast, where disease dynamics are typically studied, making it difficult to predict how the disease will manifest. Herein, we modelled WNS pathogen spread in Texas based on cave densities and average dispersal distances of hosts, projecting these results out to 10 years. We parameterized a predictive model of WNS epidemiology and its effects on bat populations with observed cave environmental data. Our model suggests that bat populations in northern Texas will be more affected by WNS mortality than southern Texas. As such, we recommend prioritizing the preservation of large overwintering colonies of bats in north Texas through management actions. Our model illustrates that infectious disease spread and infectious disease severity can become uncoupled over a gradient of environmental variation and highlight the importance of understanding host, pathogen and environmental conditions across a breadth of environments.

Highlights

  • Emerging infectious diseases of wildlife are increasing in number and threatening several species with extinction [1,2,3]

  • Because the fungal causative agent Pseudogymnoascus destructans is constrained by temperature and humidity, spread dynamics may vary by geography

  • We focused on using information available on bat species known to hibernate in Texas as only hibernating species are affected by White-nose syndrome (WNS)

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Summary

Introduction

Emerging infectious diseases of wildlife are increasing in number and threatening several species with extinction [1,2,3]. We modelled WNS pathogen spread in Texas based on cave densities and average dispersal distances of hosts, projecting these results out to 10 years. We parameterized a predictive model of WNS epidemiology and its effects on bat populations with observed cave environmental data.

Results
Conclusion

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