1. Monitoring questing winter tick abundance on traditional moose hunting lands.
- Author
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Berube, Juliana A., Sirén, Alexej P. K., Simpson, Benjamin D., Klingler, Kelly B., and Wilson, Tammy L.
- Subjects
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MOOSE , *IXODIDAE , *WINTER , *TICKS , *WILDLIFE refuges , *DERMACENTOR , *MOUNTAIN forests - Abstract
An important symbolic and subsistence animal for many Native American Tribes, the moose (Alces alces; mos in Algonquin, Penobscot language) has been under consistent threat in the northeastern United States because of winter tick (Dermacentor albipictus) parasitism over the past several decades, causing declines in moose populations throughout the region. This decline has raised concern for Tribes and agencies that are invested in moose. Given this concern, it is increasingly important to effectively monitor and develop strategies to manage winter ticks to address consistent population declines of moose due to winter ticks. The Penobscot Nation developed a novel strategy to sample questing winter ticks (i.e., ticks that are actively seeking hosts) using a plot‐based sampling protocol that may be suitable for heterogeneous habitats. We deployed this protocol in the northeastern United States in 2022 during the tick questing period (Sep–Dec) on Penobscot Nation sovereign trust lands, the White Mountain National Forest and Umbagog National Wildlife Refuge, and western‐central Massachusetts, USA. We analyzed the data using occupancy and N‐mixture models. Detection probability peaked during mid‐October and tick occupancy and abundance were greatest at sites with intermediate understory vegetation height. The sampling protocol was successful at sampling ticks in Massachusetts, where abundances were expected to be low, indicating that it may be useful for studies planning to monitor winter tick distribution and abundance in areas with sub‐optimal moose habitat and where winter tick abundance is expected to be low. This approach may also benefit managers or researchers intending to monitor many species of hard ticks, and where imperfect detection is expected. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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