Wolves and Snow

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.

Although travel in deep snow imposes high energetic costs, animals can mitigate these costs through behavioural adaptations. For example, they can select habitats with shallower or more supportive snow. It is less well known, however, if animals select for favourable snow conditions at the scale of the step, i.e., along the travel paths themselves. We snow-tracked grey wolves (Canis lupusL., 1758) over 187 km and used a paired design to compare snow conditions on travel paths to snow 1 m and 10 m away. Snow on travel paths was 3.2 cm shallower than measurements 1 m away, except when wolves travelled on linear features recently compacted by humans. In those cases, the mean difference in snow depth increased to 17.5 cm. Our analyses suggest that, under natural snow conditions, wolves are limited in the fine-scale differences they can achieve along their travel paths. By creating areas with highly favourable snow conditions, anthropogenic activities drastically change the winter land-scape, with potential implications for energetics and predator–prey dynamics.

In the winter, snow can presents major challenge to large mammals by impeding locomotion, limiting food availability, and imposing additional energetic costs during travel. This thesis examines the effects of snow conditions on the fine-scale movement patterns of grey wolves (Canis lupus)in a boreal forest ecosystem in northern Alberta. In my first chapter, Iuse traditional snow tracking to quantify the difference in snow depth and sinking depth between wolf travel paths and measurements 1m and 10 m off-path.I compare these results to snow depths recorded at a landscape scale using remote cameras that were deployed across my study area. Wolves’ choice of shallow snow conditions was not consistent across all spatial scales, as snow depth measured by remote cameras was slightly less than the average snow depth10m off-path.However, at fine spatial scales, snow depth and sinking depth were consistently lowest on wolf travel paths, and highest10m off-path. The difference in depth that wolves were able to achieve through travel path choices was highly dependent on substrate type.Linear features, and ploughed linear features in particular, were associated with sinking depths and snow depths that were far lower than any other substrate type. Whereas sinking depth for travel paths on natural, uncompacted substrates was 1.1cm less than measurements 1m away, sinking depth for travel paths on ploughed linear features was 4.5cm less than measurements 1m away. Thus, travelling on ploughed linear features may be highly advantageous for wolves, especially as local snow conditions increase. Based on published leg length measurements, we estimated that wolves would start to become impeded by snow conditions when sinking depth reached 18cm (equivalent to 50% sternum height). Over our study, these high sinking depths were encountered 37% of the time. As most of these sinking depths were recorded when wolves were travelling on natural substrates, linear features may provide energetic advantages, especially when wolves are
iii covering large distances or travelling at high speeds. However, although the effects of ploughed linear features may be important in deep snow environments with high levels of industrial or recreational activity, they are unlikely to have an overwhelming impact on locomotion or energetics in the moderate snow conditions that are characteristic of where most wolves in North America are found.In my second chapter, I use remote cameras to identify localized snowfall events, and examine the effects of these events on wolf movements. The effects of snowfall were most noticeable the night of a snowfall event.Relative to my controls, travel speed decreased from 28.1m/min to 20.6m/min the night of a snowfall event.Similarly, the proportion of time spent travelling decreased by 30% compared to controls, from 0.35 to 0.24. The effect of snowfall on movement did not translate into a significant reduction in daily distance travelled; however, relative to controls, wolves travelled nearly 4km less on days of a snowfall event.Because Idid not find evidence for persistent effects, I propose that wolves reduce their movements during a snowfall because it is more difficult for them to detect prey, as snowfall can affect wolves’ ability to detect odour trails, in addition to limiting visibility and insulating sound.This thesis further sour understanding of the grey wolves’ winter ecology in a boreal forest ecosystem that is representative of a large part of the ir geographic distribution in North America. To my knowledge, this is also the first time that a study has investigated the effects of snowfall events on animal movemen tin a natural setting. Understanding wolves’ response to snow is important not only for wolf biology, but also for predator-prey interactions. Through their influence on predator movements, snow conditions have the potential to influence encounter rates, predation risk, and kill rate.

To study factors important to the success of wolves, Canis lupus, hunting moose, Alces alces, we analysed data from more than 4000 km of snow tracking of wolves during 1998–2003 in Scandinavia. We used two methods to estimate hunting success for 17 wolf territories from 185 observations of wolf attacks on moose. On average, hunting success was estimated at 45 and 64% for the two methods, respectively. We used a smaller data set (N = 142) to examine the effect of age of breeding wolves, hunting group size, snow depth and moose density on hunting success. Multiple logistic regression showed that age of breeding males was the only variable significantly related to hunting success, with maximum hunting success at 4.5–5.5+ years of age. We also studied prey selection of radiocollared adult wolves over successive winters in two wolf packs that lost one of the breeding wolves. Whereas the surviving adult female switched to prey on Roe deer, Capreolus capreolus, the surviving adult male continued mainly to select moose. Our results suggest that the positive effect of male age on hunting success reflects both increased experience of attacking prey and possibly the greater size of adult male wolves (25–30%) compared to adult female wolves.

Survival of 203 yearling and adult White-tailed deer (Odocoileus virginianus) was monitored for 23,441 deer days from January through April 1975-85 in northeastern Minnesota. Gray wolf (Canis lupus) predation was the primary mortality cause, and from year to year during this period, the mean predation rate ranged from 0.00 to 0.29. The sum of weekly snow depths/month explained 51% of the variation in annual wolf predation rate, with the highest predation during the deepest snow.