Background/Question/Methods
Previous tick-borne disease studies in the U.S. have focused on the association between fragmentation and increased disease risk mediated by habitat loss and reduced host biodiversity. However, fragmentation can impact disease risk through altering host mobility. In the case of extreme fragmentation, such as urban environments, isolated habitat patches may reduce host habitat or dispersal and slow down tick establishment and persistence. We hypothesize a non-linear relationship between forest fragmentation and Lyme disease infection risk driven by urban patch connectivity and the movement of white-tailed deer (Odocoileus virginianus), the main tick dispersal host. Individual host responses to the permeability of the landscape matrix can scale up to population distribution patterns that in turn shape that of ticks and their pathogens and drive human infection risk heterogeneity. Animal habitat selection determines movement decisions and their willingness to utilize patches and corridors. Further, resource provisioning by humans may attract hosts to visit isolated habitat patches. Thus, integrating animal movement is essential to determine if individual behavior and resulting population distribution relates to the risk of human exposure to infected ticks in urban environments.
We examine how the movement patterns and resource utilization by deer determine the distribution of blacklegged ticks (Ixodes scapularis) which depend on this host for dispersal in the highly fragmented New York City borough of Staten Island. We use utilization distributions to identify spatial overlap between high deer use areas and high-density tick clusters in public parks and residential areas. We examine the impact of landscape connectivity for deer movement on tick densities and Borrelia burgdorferi infection. We use fine-scale GPS location data from Staten Island deer to examine movement responses to the urban landscape through step selection analysis to construct a risk map incorporating the landscape covariates most predictive of deer movement.
Results/Conclusions
Results show that regions of high habitat use within individual home ranges and overlapping home ranges of multiple deer correlate with areas of high I. scapularis densities. This identifies clusters where the likelihood of human exposure to infected tick vectors is highest. We show that deer habitat use is clustered around urban parks but extends to residential and urban areas. We will next be identifying covariates that predict resource selection and movement within, and surrounding, each park using step selection analysis. Our results emphasize that patch connectivity and host movement is a neglected factor that is critical to consider in urban tick-borne disease systems.