OOS 20-6 - The development of a spatially-explicit, individual-based, disease model for amphibians and the chytrid fungus, Batrachochytrium dendrobatidis

Tuesday, August 7, 2012: 3:20 PM
C124, Oregon Convention Center
Gisselle Yang Xie, Zoology Department, Oregon State University, OR, Nathan H. Schumaker, US EPA, Corvallis, OR, Allen Brookes, US Environmental Protection Agency, Corvallis, OR and Andrew R. Blaustein, Department of Zoology, Oregon State University, Corvallis, OR
Background/Question/Methods

The fungal pathogen, Batrachochytrium dendrobatidis (BD), has been associated with amphibian population declines and extinctions worldwide. Transmission of the fungus between amphibian hosts occurs via motile zoospores, which are produced on the infected host and released into the water column to further encyst on new hosts. Critically, the consequences of BD infection are highly dependent on the number of zoospores present on the host.  While a number of models have been formulated for the investigation of the population-level epidemiology of BD, Briggs et al. (2010, Proc. Natl. Acad. Sci. 107:9695-9700) is the only model that addresses the dose-dependent properties of Bd infections. The Briggs model focuses on pond-level Bd dynamics and does not include spatial processes of host and pathogen dispersal. Here we describe a spatially-explicit BD model built in direct reference to the Briggs et al. model and encompasses the suite of host-environment zoospore processes described therein. Our model has the ability to scale local-level processes to the landscape-level and should allow predictions of dynamics of Bd infections at large spatial scales.     

Results/Conclusions

We constructed a model for the dispersal of Batrachochytrium dendrobatidis (BD) throughout a hypothetical metapopulation of a generic aquatic Ranid amphibian using HexSim, a spatially-explicit, individual-based simulation framework. Our study investigates how likely BD is to invade and persist endemically within a population based on host reproductive rate, duration of the larval life stage, and types of dispersal vectors. Our spatially-explicit model also illustrates how landscape features influence the spread of the disease, and it facilitates the exploration of large scale mitigation strategies.