Simulating tick distributions over sub-Saharan Africa: the use of observed and simulated climate surfaces

A broad suit of climate data sets is becoming available for use in predictive species modelling. We compare the efficacy of using interpolated climate surfaces [Center for Resource and Environmental Studies (CRES) and Climate Research Unit (CRU)] or high-resolution model-derived climate data [Division of Atmospheric Research limited-area model (DARLAM)] for predictive species modelling, using tick distributions from sub-Saharan Africa.

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