Abstract Disease ecology has focused greatly on determining how changes to biodiversity may drive infectious disease risk for humans. Fencing off experimental areas (exclosures) has been a common experimental approach to assess how removing large-bodied hosts may affect disease risk, especially with tick-borne pathogens (TBPs). However, exclosure experiments have found conflicting results based on the experiment’s scale, with smaller exclosures tending to increase tick densities inside the exclosure and larger exclosures tending to decrease tick densities inside. Previously, we have lacked a unifying theoretical framework able to reconcile the results of exclosure experiments across spatial scales. We present a spatially explicit model of TBP risk incorporating tick dispersal by small transmission-competent mammal hosts who can enter the exclosure and by large transmission-incompetent mammal hosts excluded from the exclosure. Our model reproduces the scale-dependence and spatial patterning observed in past exclosure experiments while elucidating their causal mechanisms. Specifically, the modeled exclosures produce high densities of infected ticks near their boundaries, with the densities decreasing towards the exclosure’s centre. Empirical results have found lower tick densities at the exclosure’s edge than its centre, a pattern we demonstrate can also be produced if we additionally allow ticks in their free-living questing stage to disperse.
Freedman et al. (2026) studied this question.