GC32A-02:
Disease in a more variable and unpredictable climate

Wednesday, 17 December 2014: 10:35 AM
Taegan A McMahon1, Thomas Raffel2, Jason R Rohr3, Neal Halstead3, Matthew Venesky4 and John Romansic5, (1)Organization Not Listed, Washington, DC, United States, (2)Oakland University, Rochester, MI, United States, (3)University of South Florida, Tampa, FL, United States, (4)Allegheny college, Meadville, PA, United States, (5)H. T. Harvey & Associates, Las Gatos, CA, United States
Abstract:
Global climate change is shifting the dynamics of infectious diseases of humans and wildlife with potential adverse consequences for disease control. Despite this, the role of global climate change in the decline of biodiversity and the emergence of infectious diseases remains controversial. Climate change is expected to increase climate variability in addition to increasing mean temperatures, making climate less predictable. However, few empirical or theoretical studies have considered the effects of climate variability or predictability on disease, despite it being likely that hosts and parasites will have differential responses to climatic shifts. Here we present a theoretical framework for how temperature variation and its predictability influence disease risk by affecting host and parasite acclimation responses. Laboratory experiments and field data on disease-associated frog declines in Latin America support this framework and provide evidence that unpredictable temperature fluctuations, on both monthly and diurnal timescales, decrease frog resistance to the pathogenic chytrid fungus Batrachochytrium dendrobatidis (Bd). Furthermore, the pattern of temperature-dependent growth of the fungus on frogs was inconsistent with the pattern of Bd growth in culture, emphasizing the importance of accounting for the host–parasite interaction when predicting climate-dependent disease dynamics. Consistent with our laboratory experiments, increased regional temperature variability associated with global El Niño climatic events was the best predictor of widespread amphibian losses in the genus Atelopus. Thus, incorporating the effects of small-scale temporal variability in climate can greatly improve our ability to predict the effects of climate change on disease.