Using stochastic epidemiological models to evaluate conservation strategies for endangered amphibians. Issue 133 (31st August 2017)

• Record Type: Journal Article
• Authors: Drawert, Brian; Griesemer, Marc; Petzold, Linda R.; Briggs, Cheryl J.
• Is Part Of: Journal of the Royal Society interface. Volume 14:Issue 133(2017)
• Publication Date: 2017-08-31
• Subjects: chytridiomycosis -- Batrachochytrium dendrobatidis -- epidemiological models -- stochastic models; Physical sciences -- Research -- Periodicals; Life sciences -- Research -- Periodicals; Interdisciplinary research -- Periodicals; 570.5
• DOI: 10.1098/rsif.2017.0480
• Languages: English
• ISSNs: 1742-5689

Abstract

Abstract : Recent outbreaks of chytridiomycosis, the disease of amphibians caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd), have contributed to population declines of numerous amphibian species worldwide. The devastating impacts of this disease have led researchers to attempt drastic conservation measures to prevent further extinctions and loss of biodiversity. The conservation measures can be labour-intensive or expensive, and in many cases have been unsuccessful. We developed a mathematical model of Bd outbreaks that includes the effects of demographic stochasticity and within-host fungal load dynamics. We investigated the impacts of one-time treatment conservation strategies during the disease outbreak that occurs following the initial arrival of Bd into a previously uninfected frog population. We found that for all versions of the model, for a large fraction of parameter space, none of the one-time treatment strategies are effective at preventing disease-induced extinction of the amphibian population. Of the strategies considered, treating frogs with antifungal agents to reduce their fungal load had the greatest likelihood of a beneficial outcome and the lowest risk of decreasing the persistence of the frog population, suggesting that this disease mitigation strategy should be prioritized over disinfecting the environment or reducing host density.