Using Agent-Based Models to Inform the Dynamics of Winter Tick Parasitism of Moose.


North American moose (Alces alces) populations along the southern extent of their range have been experiencing high levels of calf mortality in recent years. In New England, this phenomenon has been linked to extensive blood loss resulting from extreme winter tick (Dermacentor albipictus) parasitism. Moose are symbolic of the region and generate income through tourism and the auction of hunting permits; thus, successive years of greater than 50% calf mortality (epizootics) are of concern to wildlife managers and others. It is hypothesized that high localized moose density coupled with climate change are the driving forces behind moose-winter tick epizootics; however, the impact that variable combinations of these and other factors have on the occurrence and magnitude of epizootics has not been previously simulated. We, therefore, developed and implemented a spatially explicit agent-based model with two model environments, each representative of a distinct location within an ongoing field study site in northern New Hampshire that differed in the proportional availability of optimal moose habitat. Three experiments were devised to test the sensitivity of the outcome variables, calf infestation level and calf mortality, to 1) winter tick abundance, 2) winter tick aggregation, and 3) moose density, for the length of the winter tick questing period. Each experiment was conducted in both model environments. This model generated similar mortality levels to those measured in the field study under representative moose density and weather conditions. Additionally, the modeled moose agents and the radio-collared moose in the field reflect comparable habitat usage. While the infestation levels reported by calf agents are considered conservative, we believe that future versions of this model, parameterized with more accurate estimates of winter tick abundance and moose density, may be an effective tool for managing moose against winter tick parasitism.


Natural Resources and the Environment

Publication Date


Journal Title

Ecological Complexity


Elsevier B.V.

Digital Object Identifier (DOI)


Document Type



© 2020 Elsevier B.V.