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The development of a spatially-explicit, individual-based, disease model for frogs and the chytrid fungus
Citation:
Xie, G. Y., N. H. SCHUMAKER, A. F. BROOKES, AND A. Blaustein. The development of a spatially-explicit, individual-based, disease model for frogs and the chytrid fungus. Presented at Ecological Society of America, Portland, OR, August 05 - 10, 2012.
Impact/Purpose:
The fungal pathogen, Batrachochytrium dendrobatidis (BD), has been associated with amphibian population declines and even extinctions worldwide.
Description:
Background / Question / Methods The fungal pathogen, Batrachochytrium dendrobatidis (BD), has been associated with amphibian population declines and even 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. Although fungi are conventionally considered microparasites, experimental and field research has demonstrated that BD also exhibits macroparasitic characteristics. 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, Cheryl Briggs and colleagues have developed the only model to date that addresses the dose-dependency properties of these particular fungal infections. But the Briggs model is non-spatial and has limited ability to explain the dynamics of the BD epidemic at landscape scales. Here we describe a spatially-explicit analog to the Briggs model that we have developed using HexSim. 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 hypothesized 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.