Background/Question/Methods There is increasing recognition that many aspects of human well-being are linked to functions of healthy ecosystems and the services they provide to society at local to global scales. Societal pressures can contaminate habitats, reduce their area, alter community composition, and otherwise degrade ecosystems in ways that may ultimately result in adverse human impacts. This research explored the role of forest fragmentation in Lyme disease. Previous studies have shown that highly fragmented forests are unable to support native predators and competitors of disturbance-tolerant species that are the most competent reservoirs for the bacterial agent of Lyme disease. Therefore, fragmentation may degrade the natural pest regulation service of intact forest ecosystems. We sought to quantify landscape design parameters that may reduce forest degradation and associated human risk of environmental exposure to arthropod-borne disease. We modeled disease incidence rate from landcover pattern metrics across 12 Maryland counties. Observed rates derived from passive surveillance data on 2137 cases during 1996-2000. We used major roads to delineate 514 landscape analysis units from 0.002 to 580 km2. We quantified fragmentation metrics using 30-meter resolution satellite imagery and a geographic information system.

Results/Conclusions The parameter that explained the most variation in incidence rate was the percent of habitat edge represented by forest adjoining lawn and other herbaceous cover (R2 = 0.75; rate ratio = 1.34 [1.26, 1.43], p < 0.0001). Also highly significant was percent of the landscape in forest cover (cumulative R2 = 0.82), which exhibited a quadratic relationship with incidence rate. Modeled relationships applied throughout the range of landscape sizes. Our model suggests that contact between humans, the vector tick, and its wild hosts is facilitated in landscapes with high forest-herbaceous interspersion as opposed to those with clustered forest and herbaceous cover. Landscapes with sufficient high-density development to preclude a large percentage of forest-herbaceous edge would also limit exposure. Results indicate that risk reduction may be most effective at the community, rather than the individual, level. Model validation is currently underway in Pennsylvania, New York, and Wisconsin to determine the model’s predictive utility across endemic landscapes under alternative development scenarios.