Lead Researcher: Eric Wolstenholme-Schmidt | Principal Investigator: Sandra Macdougall

——————————————————————————————————————

Introduction

Moose (Alces alces) are a large terrestrial ungulate present across the Northern Hemisphere. Historically, moose are known to inhabit boreal habitats, but since the early 1980s, moose have begun to colonize the Parkland and Grasslands regions of Alberta (Bjorge et al., 2018). This shift, particularly in the Parkland region, has increased the likelihood of human-moose interactions (Welch et al., 2025). These interactions are more frequent due to the higher levels of anthropogenic activity in the Parkland and Grassland Regions compared to the Boreal Region, which are generally more remote (Young et al., 2006).

Many of Alberta’s major cities are in the Parkland and Grassland Regions and are intersected by rivers that serve as vital ecosystems for moose (Hall et al., 2024). For example, the City of Red Deer in Central Alberta features a landscape where urban development accompanies vegetatively dense riverine natural areas. Across natural landscapes in Alberta, ongoing urban development has reduced natural moose habitat, driving them to reside in urban centres. The behaviours of moose in rural areas are well researched, but in urban areas, moose behaviour remains minimally studied (Hansen et al., 2024). This limited understanding of moose displacement, their movements and behaviours within urban areas such as cities makes efforts to mitigate human-moose conflicts challenging. Thus, the objective of this study was to investigate yearly urban moose occurrence and temporal activity in the City of Red Deer. To achieve this, we deployed a remote camera array throughout the natural areas of Red Deer for three years. Our study provides valuable insights that can inform future projects aimed at improving human-wildlife coexistence in urban landscapes such as cities.

Methods

Camera Deployment

Remote Cameras (Reconyx HyperFire II) were placed onto dead trees (deciduous and coniferous with a minimum diameter of eight inches) near wildlife hotspots. Wildlife hotspots were determined by doing presence surveys looking for abundance of wildlife trails, fur, tracks, browsing, grazing, and rubs. Areas with minimal anthropogenic disturbance were also selected for based on human trails, trash, roads, housing, and industrial development. The cameras were placed 2.75m high from the base of the tree and angled towards the area of interest. Camera enclosures were secured to trees using lag bolts, with a minimum of three leg bolts per enclosure. The cameras were then locked into the enclosure using a steel python lock and set to record. The array was built throughout the natural areas of Red Deer in a stratified random sampling methodology with a total count of 20 deployed cameras as of December 31st, 2025. Camera placement avoided small pockets of natural areas within heavily urbanized areas due to heavy levels of interference, vandalism, and theft. Every two months, battery levels were checked and changed if needed, SD cards swapped, and data from SD cards uploaded and tagged in WildTrax. The SD card ID, date of removal, and any notes were recorded every time a camera was checked. A copy of the photos was also stored in an off-site solid-state drive.

Moose Tagging

Photos of moose were tagged with their age (adult or calf), sex (male or female), and coupling (cow and calf). Photos of people were automatically blurred, and photos of other species were saved for future studies/applications. Age of moose was based on several factors outlined in Table 1, with calves being defined as moose under the age of one. Sex of moose was based on several factors outlined in Table 2. Calves were not assigned sex classes due to definitive features being unexpressed until adulthood. Captures of moose with unidentifiable sex class were tagged with unknown sex.

Table 1. Morphological differences between adult moose (Alces alces) and calves.

Feature	Adult	Calf
Head shape	Elongated and rectangular	Compressed and triangular
Spring coat	Dark Brown	Reddish brown
Leg length	Uniform with body	Elongated and dominant

Table 2. Morphological differences between male and female moose (Alces alces).

Feature	Male	Female
Antlers	Yes	No
Antler scar	Yes	No
Vaginal patch – white	No	Yes
Face colour	Darker	Lighter
Bell size/shape	Enlarged and robust	Recessed and thin
Genitalia	Penis/testicles	Vagina/teats

Occurrence and temporal data graphs:

Moose detections were lumped into ten-day bins for 2024 and 2025, with each year beginning on January 1st. To prevent over-amplification within the occurrence and temporal graphs, individual events were determined using a sixty-second thirty-minute rule. Events captured within sixty seconds of each other were lumped together until the time between detections was greater than sixty seconds. Within the lumped detections, only one detection was counted every thirty minutes. For example, if there was one individual in front of the camera for one hour, and all the captures were within sixty seconds of each other, then this would count as two counts (one every thirty-minutes) in the occurrence graph. This is to ensure over-amplification is limited but also prevent under-amplification of moose activity when exhibiting lumped behaviour. If multiple individuals were captured, then the highest number of individuals was taken. For example, if two moose were in multiple captures, all taken within sixty seconds of each other for a total of thirty minutes, this would count as two detections. If the pair were there for one hour, it would count as four detections (one per individual every thirty minutes).  If an individual triggered the camera and then retriggered the camera more than sixty seconds after the last detection, then the sixty-second thirty-minute rule did not apply, and these detections were not lumped together.

To account for differing numbers of cameras between weeks across the two years, the number of captured events was normalized against the number of deployed cameras for each respective week.  Total ten-day detections assumed by the sixty-second thirty-minute rule were then cross-referenced to the original data set to ensure accuracy and validity of the rule. Occurrence graphs for all, male, and female moose were created. Temporal graphs were broken down into three seasons: winter (December 1 to March 31), summer (April 1 to August 31), and fall (September 1 to November 30). All graphs were built using the data set from January 1, 2024, to December 31, 2025, and were made in RStudio using the R package ‘activity.’

Current findings

Overall, both sexes of moose have increased movements during the later calving season. The later calving season is the time during June/July when most calves have been born and when calves are no longer dependent on lactation. The later calving season is also the time when vegetation growth for many plant species peaks, and moose will increase foraging efforts with the rise of vegetative growth (Boone et al., 2025). Females with calves will also increase movements during this time as energy needed for lactation can now be utilized on movement (Van Ballenberghe & Miquelle, 1990). Movements may also increase in response to calves’ vulnerability to predators (Van Ballenberghe & Miquelle, 1990). Bulls have heightened occurrence levels during the rut and later calving season. Cows have slightly increased levels of occurrence during the rut; however, their occurrence levels are highest during the later calving season. Winter is the time of lowest occurrence across both sex classes. Late summer (August), during the hottest times of the year, occurrence levels plummet. A drop in winter occurrence is likely due to moose reducing their movements to maximize energy expenditure by limiting movement and focusing foraging efforts (Risenhoover, 1986). Moose are extremely sensitive to higher temperatures; to compensate for this, moose will limit movement, decreasing occurrence levels (Risenhoover, 1986). Temporal activity of moose in the winter follows a skewed crepuscular pattern, with one lesser activity peak at dawn and a dominant peak at dusk. In the summer, moose exhibit a uniform twin-peak crepuscular structure at dawn and dusk. Fall has a less uniform crepuscular activity structure with increased activity during the night, but reduced activity during the day, compared to winter and summer temporal activity patterns.

Figure 1. Yearly Occurrence of moose (Alces alces) in the City of Red Deer, Alberta, from January 1^st, 2024, to December 31^st, 2025, lumped into ten-day bins starting on January 1st of each year. Individual captures were sorted using a sixty-second thirty-minute rule. All captures taken within sixty seconds of each other were lumped together and then only one detection was counted every thirty minutes. Captures were than normalized against the number of cameras deployed per ten days. Events captured using Reconynx HyperFire II. Remote cameras were deployed throughout the natural areas of Red Deer using a stratified random methodology. Made using Rstudio.

Figure 2. Yearly Occurrence of female moose (Alces alces) in the City of Red Deer, Alberta, from January 1^st, 2024, to December 31^st, 2025, lumped into ten-day bins starting on January 1st of each year. Individual captures were sorted using a sixty-second thirty-minute rule. All captures taken within sixty seconds of each other were lumped together and then only one detection was counted every thirty minutes. Captures were than normalized against the number of cameras deployed per ten days. Events captured using Reconynx HyperFire II. Remote cameras were deployed throughout the natural areas of Red Deer using a stratified random methodology. Made using Rstudio.

Figure 3. Yearly Occurrence of male moose (Alces alces) in the City of Red Deer, Alberta, from January 1^st, 2024, to December 31^st, 2025, lumped into ten-day bins starting on January 1st of each year. Individual captures were sorted using a sixty-second thirty-minute rule. All captures taken within sixty seconds of each other were lumped together and then only one detection was counted every thirty minutes. Captures were than normalized against the number of cameras deployed per ten days. Events captured using Reconynx HyperFire II. Remote cameras were deployed throughout the natural areas of Red Deer using a stratified random methodology. Made using Rstudio.

Figure 4. Daily activity of moose (Alces alces) in the City of Red Deer, Alberta for winter [(December 1 to March 31)(act = 0.427, se = 0.0722, lcl = 0.304, ucl = 0.586)], summer [(April 1 to August 31)(act = 0.503, se = 0.0429, lcl = 0.409, ucl = 0.580)], and fall [(September 1 to November 30)(act = 0.648, se = 0.0687, lcl = 0.474, ucl = 0.740)], based on events captured on Reconyx HyperFire II from Jan 1, 2024 to December 31, 2025. Remote cameras were placed throughout the natural areas of Red Deer using a stratified random methodology.  Individual captures were sorted using a sixty-second thirty-minute rule. Captures taken within sixty seconds of each other were lumped together and then only one detection was counted every thirty minutes. Made using Rstudio.

References

Boone, H., Romanski, M., Kellner, K., Kays, R., Potvin, L., Roloff, G., & Belant, J. (2025). Optimal timing to estimate moose (Alces alces) demographic parameters using remote cameras. Scientific Reports, 15(1), 20493. https://www.nature.com/articles/s41598-025-05603-y

Bjorge, R. R., Anderson, D., Herdman, E., & Stevens, S. (2018). Status And Management of Moose in the Parkland and Grassland Natural Regions of Alberta. Alces, 54, 71–84. Retrieved from https://alcesjournal.org/index.php/alces/article/view/232

Hall, L. M., Sullivan, F. B., Burke, S. A., Palace, M. W., Jones, H., & Moll, R. J. (2024). Detecting unmarked moose with infrared sensors via an unoccupied aerial system and correcting for sightability. Alces, 60, 147-165. https://alcesjournal.org/index.php/alces/article/view/1881

Hansen, C. P., Kays, R., & Millspaugh, J. J. (2024). From backyard to backcountry: changes in mammal communities across an urbanization gradient. Journal of Mammalogy, 105(1), 175-191. https://doi.org/10.1093/jmammal/gyad110

Laliberté, J., & St-Laurent, M. H. (2020). In the wrong place at the wrong time: Moose and deer movement patterns influence wildlife-vehicle collision risk. Accident Analysis & Prevention, 135, 105365. https://www.sciencedirect.com/science/article/pii/S0001457519302052

Risenhoover, K. L. (1986). Winter activity patterns of moose in interior Alaska. The Journal of wildlife management, 727-734. https://www.jstor.org/stable/3800990

Van Ballenberghe, V., & Miquelle, D. G. (1990). Activity of moose during spring and summer in interior Alaska. The Journal of wildlife management, 391-396. https://www.jstor.org/stable/3809645

Welch, J. H., Barboza, P. S., Farley, S. D., & Spalinger, D. E. (2015). Nutritional value of habitat for moose on urban and military lands. Journal of Fish and Wildlife Management, 6(1), 158-175. https://meridian.allenpress.com/jfwm/article/6/1/158/203708/Nutritional-Value-of-Habitat-for-Moose-on-Urban Young, J. E., Sánchez-Azofeifa, G. A., Hannon, S. J., & Chapman, R. (2006). Trends in land cover change and isolation of protected areas at the interface of the southern boreal mixed wood and aspen parkland in Alberta, Canada. Forest Ecology and Management, 230(1-3), 151-161. https://doi.org/10.1016/j.foreco.2006.04.031