HABITAT HETEROGENEITY, DISPERSAL, AND LOCAL RISK OF EXPOSURE TO LYME-DISEASE

Spatial heterogeneity presents a fundamental challenge to conventional ecological theory. Although ecological systems are usually heterogene ous, it is not clear how often heterogeneity fundamentally alters thei r behavior. We addressed this issue with a study of the infection of t icks (Ixodes scapularis) by the causative agent of Lyme disease (the s pirochete Borrelia burgdorferi) in multiple habitats within a semirura l landscape, combining both field and modeling approaches. We sampled the densities and infection prevalences of ticks in five habitats over two years in southeastern New York. There were consistent differences among habitats in adult infection prevalence, which was unrelated to tick density, suggesting that local habitat features exert some contro l over local risk of exposure to infected ticks. Other results undersc ored the importance of processes taking place on larger scales. We obs erved a positive relationship between the change in tick density withi n a cohort from the nymphal to adult stages, and changes in prevalence over the same period. Habitats with many adults relative to the numbe r of nymphs several months earlier showed increasing prevalence of B. burgdorferi. Presumably these habitats were receiving immigrating tick s that became infected on their dispersing hosts. We designed a comput er model, patterned after the life cycle of I. scapularis, to determin e whether patterns observed in the field could be explained by dispers al among habitats differing in host species composition. The model sho wed that habitat-related variation in tick density and spirochete prev alence was maintained even with moderate dispersal, as long as the dif ferent habitats supported distinct assemblages of hosts. Dispersal pro duced nonlinear or threshold responses under many conditions, due to p ositive and negative feedbacks. Such feedback is a general feature of many ecological systems, which implies that the behavior of heterogene ous systems will very often be unpredictable from an understanding of isolated components.