An understanding of the spatial distribution of Ixodes scapularis is a fundamental component in defining Lyme disease risk in North America. Because of the clear relationship between climate and I .scapularis habitat suitability, climate forecasting can be used to predict tick populations in future years. Therefore, a spatially predictive logistic model for the establishment of I. scapularis in North America was first developed using ground-observed environmental data. The logistic regression showed that both temperature and vapour pressure significantly contribute towards establishment (P<0.0001). Model accuracy evaluated using the receiver operating characteristics plot was 97% (P<0.0001). This logistic model provided the basis for forecasting the contribution of climate change in the future patterns of I. scapularis establishment throughout North America. Global Climate Model (GCM) scenarios for each climatic variable were provided by the UK Hadley Centre for Climate Prediction and Research (HadCM2). Experiments forced with changes in greenhouse gas concentrations alone and those forced with greenhouse gas and sulphate aerosol changes resulting from anthropogenic effects were considered. Data on the change of each climate variable from present conditions was acquired for 3 mean 30-year time points: the 2020's (2010-2039), the 2050's (2040-2069) and the 2080's (2070-2099). The logistic model was extrapolated in time according to the different GCM's and used to predict the future probabilities of establishment for I. scapularis across North America. The final result was a series of habitat suitability maps that provide the expected change in distribution of I. scapularis, clearly defining future areas of Lyme disease risk.
Species 1: Acari Ixodidae Ixodes scapularis (Black-legged tick, Deer tick)
Keywords: Lyme disease, GIS
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