Ticks and tick-borne microbes identified through passive and active surveillance in Alaska.

Rapid environmental change in Alaska and other regions of the Arctic and sub-Arctic has raised concerns about increasing human exposure to ticks and the pathogens they carry. We tested a sample of ticks collected through a combination of passive and active surveillance from humans, domestic animals, and wildlife hosts in Alaska for a panel of the most common tick-borne pathogens in the contiguous United States to characterize the diversity of microbes present in this region. We tested 189 pooled tick samples collected in 2019-2020 for Borrelia spp., Anaplasma spp., Ehrlichia spp., and Babesia spp. using a multiplex PCR amplicon sequencing assay. We found established populations of Ixodes angustus Neumann (Acari: Ixodidae), Ixodes uriae White (Acari: Ixodidae), and Haemaphysalis leporispalustris Packard (Acari: Ixodidae) in Alaska, with I. angustus found on a variety of hosts including domestic companion animals (dogs and cats), small wild mammals, and humans. Ixodes angustus were active from April through October with peaks in adult and nymphal activity observed in summer months (mainly July). Although no known human pathogens were detected, Babesia microti-like parasites and candidatus Ehrlichia khabarensis were identified in ticks and small mammals. The only human pathogen detected (B. burgdorferi s.s.) was found in a tick associated with a dog that had recently traveled to New York, where Lyme disease is endemic. This study highlights the value of a combined passive and active tick surveillance system to detect introduced tick species and pathogens and to assess which tick species and microbes are locally established.

The calm during the storm: Snowfall events decrease the movement rates of grey wolves (Canis lupus).

Mammalian predators encounter unique hunting challenges during the winter as snow increases the cost of locomotion and influences predator-prey interactions. Winter precipitation may also affect predators' ability to detect and pursue prey. We investigated the effects of snowfall events on grey wolves (Canis lupus) in a boreal forest ecosystem in northeastern Alberta, Canada. We predicted that wolves would respond to snowfall events by reducing their travel speed and the time they spent travelling. Over the course of two winters, we used remote cameras to identify localized snowfall events and estimate snow depth. We used telemetry data from 17 wolves to calculate travel speed and time spent travelling versus resting. Data were categorized by time of day (night versus day) and time since snowfall events, and analyzed using linear and logistic regression mixed-effects models. We found that wolves were less likely to travel on dates of snowfall events than any date prior to or after an event. Wolves also travelled slower during snowfall events, but only when compared to their travel speed 24 hours before. Effects were most pronounced at night, when movements appeared to be consistent with hunting behavior, and activity levels resumed within 24 hours of a snowfall event. Including snow depth as a variable did not improve model fit. Collectively, our findings suggest that wolves' response is not driven by increased hunting success or by energetic considerations resulting from increased snow depth. Instead, we propose that wolves reduce their activity levels because precipitation dampens hunting success. Snowfall events may impact wolves' ability to detect prey and changes in prey behavior could also lead to decreased encounter rates. We encourage scientists to further investigate the effects of short-term weather events on movement rates and predator-prey interactions.