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Amphibian Research and Monitoring Initiative

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Disease


Cave Bd sampling
Left to Right: Tabby Cavendish (Great Smoky Mountains NP), Brian Gregory (USGS), and Jamie Barichivich (ARMI) swabbing salamanders for Batrachochytrium dendrobatidis (Bd) in Rockhouse Cave, Wheeler NWR, Alabama. Photo by: Alan Cressler.

ARMI conducts original research on various amphibian diseases in the lab and field. Our research has included estimating the impacts of diseases on the growth of populations, developing and testing potential treatments, affects of stressors on susceptibility to disease, how diseases are transmitted in the wild, and how to model disease distributions and spread.

ARMI disease research is conducted throughout the country, but ARMI pathologist Dr. David Green is based at the National Wildlife Health Center in Madison, Wisconsin, and coordinates the health screenings and investigations of amphibian mortalities (e.g., identification, pathology) in addition to collaborating on many disease research projects.

Amphibians at our long-term monitoring sites are periodically screened for diseases and we investigate mass mortality events.

Resources

National Wildlife Health Center - ARMI

ARMI Products on Disease

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This is an ARMI Product. Identifying Species Conservation Strategies to Reduce Disease-Associated Declines
Authors: Gerber B, Converse S, Muths E, Crokett H, Mosher B, Larissa B
Emerging infectious diseases (EIDs) are a salient threat to many animal taxa, causing local and global extinctions, altering communities and ecosystem function. The EID chytridiomycosis is a prominent driver of amphibian declines, which is caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd). To guide conservation policy, we developed a predictive decision-analytic model that combines empirical knowledge of host-pathogen metapopulation dynamics with expert judgment regarding effects of management actions, to select from potential conservation strategies. We apply our approach to a boreal toad (Anaxyrus boreas boreas) and Bd system, identifying optimal strategies that balance tradeoffs in maximizing toad population persistence and landscape-level distribution, while considering costs. The most robust strategy is expected to reduce the decline of toad breeding sites from 53% to 21% over 50 years. Our findings are incorporated into management policy to guide conservation planning. Our online modeling application provides a template for managers of other systems challenged by EIDs.

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This is an ARMI Product. Early action to address an emerging wildlife disease
Authors: Adams MJ, Harris MC, Grear DA | Date: 2017-02 | Outlet: USGS Fact Sheet | Format: .PDF
Although not yet detected in the United States, the emergence of Bsal (a fungal pathogen) could threaten the salamander population, which is the most diverse in the world. The spread of Bsal likely will lead to more State and federally listed threatened or endangered amphibian species, and associated economic effects. Because of concern expressed by resource management agencies, the U. S. Geological Survey has made Bsal and similar pathogens a priority for research.

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This is an ARMI Product. Inferential biases linked to unobservable states in complex occupancy models
Authors: Mosher BA, Bailey LL, Hubbard BA, Huyvaert KP | Date: 2017-02 | Outlet: Ecography DOI: 10.1111/ecog.02849 | Format: .PDF
Our work is motivated by the impacts of the emerging infectious disease chytridiomycosis, a disease of amphibians that associated with declines of many species worldwide. Using this host-pathogen system as a general example, we first illustrate how misleading inferences can result from failing to incorporate pathogen dynamics into the modeling process, especially when the pathogen is difficult or impossible to survey in the absence of a host species. We found that traditional modeling techniques can underestimate the effect of a pathogen on host species occurrence and dynamics when the pathogen can only be detected in the host, and pathogen information is treated as a covariate. We propose a dynamic multistate modeling approach that is flexible enough to account for the detection structures that may be present in complex multistate systems, especially when the sampling design is limited by a species’ natural history or sampling technology.


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