Introduction and Background
White-tailed deer are severely abundant in North America. It is estimated that the population of white-tailed deer has increased from 500,000 animals to 20 million animals from 1900 to 1995 (Cook and Daggett, 1995). As the population of white-tailed deer has increased, so have transportation networks and volumes of traffic (Hubbard et al., 2000). Car accidents involving white-tailed deer pose a serious threat to road safety and deer welfare, as well as financial costs for society, as half a million deer-vehicle accidents occur annually in North America (Hubbard et al., 2000). Deer density and movement are correlated with deer-vehicle accidents (Oosenburg et al.,1991). Studies suggest patterns in deer-vehicle accidents are driven by deer-related behavior on seasonal and diurnal scales (Hothorn et al., 2015). Therefore, studying white-tailed deer feeding behavior and how they respond to changes in vegetation is a foundational part in understanding their foraging patterns and spatial dispersion1. White-tailed deer foraging patterns and spatial dispersion in response to changes in vegetation can be correlated with the frequency of car accidents involving white-tailed deer. Understanding these spatial and temporal patterns can help educate individuals about road safety and push for changes that can help promote highway safety and reduce loss of human and deer life.
Methods
In order to study the correlation between deer foraging patterns and deer-vehicle patterns I had to design a method inspired by previous studies on these two topics. In one study, global positioning system (GPS) collars were used to track white-tailed deer movement in an 8,300 km2 area from February 2006-April 2008 (Williams et al., 2012). The area in this study is similar to the area in mine, consisting of wooded land surrounded by agricultural crops. These GPS collars were programmed to record the position of the deer every five hours in order to track their movement. Using these methods, it was found that the deer’s movement in this area varied in relation to changes in vegetation. My study was conducted similar to this study by recording movement using trail cameras instead of GPS collars. In another study, white-tailed deer were radio collared and tagged in order to track and record movement (Tierson et al., 1985). Researchers monitored these radio collared deer and compared their range sizes across seasons to study the behavior of deer. Sparrowe and Springer conducted a study using visual markers and minimal radiotelemetry to monitor the movement of deer (Sparrowe & Springer, 1970). These researchers would actively patrol the study area and record locations of the marked deer. For nighttime data collection, they installed a spotlight on their vehicle. These studies inspired me to use the method of tracking white-tailed deer. Due to budget and time restraints I had to conduct the tracking portion of my study using trail cameras. The tracking of deer provides a way to accurately record the different times of peak movement.
The area I chose to conduct my study is located in Hayden, Indiana which is in southeastern Indiana. I chose this area due to the convenience of data collection and the supposed abundance of white-tailed deer in this area of the Midwest. The area of study consisted of 31 acres of wooded property surrounded by crop fields. These crop fields are bordered by low-traffic county roads. Data collection will take place from late August through late November, capturing the later part of the vegetation life cycle. Four trail cameras were placed on the perimeter of the wooded property—one on each North, South, East, and West side of the property. These cameras are placed to capture when the deer exit and enter the wooded property. These trail cameras are inconspicuously mounted to a tree at a height that can sense the movement of deer. Trail cameras work by capturing an image and time stamping it when the motion sensors are triggered. I monitored the four trail cameras every during the duration of the study, averaging the daily times that deer appeared to travel in and out of the wooded property. The forage quality and quantity declines as the seasons change from warmer to colder. Warmer seasons have higher-quality forage, so there are more leaves and flowers which are tender and favorable to white-tailed deer. However, in colder seasons these favorable parts of plants are limited, and the nutritional value of these plants has decreased. In colder seasons there are less leaves and tender matter and more thorns and dry matter. Therefore, the field and forage conditions were also be monitored weekly to link whether or not changes in forage impacted the movement and behavior of the deer.
I also added a more journalistic approach to my study to gather more relevant data. I distributed an anonymous survey to various residents in the Hayden, IN area to gain a better understanding of the relationship between deer and motor vehicle traffic in that area. The survey questions were in the format of a Google Forms questionnaire, and sent out to 20 Hayden, IN residents. The Google Forms survey included the following questions:
- In what road setting do you find yourself driving most?
- County Roads
- Highways
- Interstates
- City Roads
- How often do you drive weekly?
- 1-5 times per week
- 6-10 times per week
- 11-15 times per week
- 15+ times per week
- How often do you drive between 5:00 am and 8:00 am weekly?
- 1-2 times per week
- 3-4 times per week
- 5+ times per week
- How often do you drive between 3:00 pm and 7:00 pm weekly?
- 1-2 times per week
- 3-4 times per week
- 5+ times per week
- Have you ever been in a deer-vehicle accident?
- Yes
- No
- OPTIONAL: If you have been in a deer-vehicle accident, describe it below and add photos if possible.
- What time of day do you see the most deer?
- Around sunrise
- Around sunset
- Middle of the day
- Nighttime
Offering an anonymous survey about deer-vehicle accidents provides qualitative data for me to compare to other research studies about this topic. Limiting my survey to only Hayden, IN residents allows me to gather valuable data on deer-vehicle accidents specifically in that area. This survey was distributed towards the end of my data collection period, late November. Choosing to distribute this towards the end of my study allowed the chance for the participants to potentially obtain more data relevant to the survey questions. I sent out 25 surveys and received 19 responses. Data from my quantitative and qualitative research was compared to findings from similar studies in order to help support the overall connection and importance of my findings.
Results
Vegetation Changes
The changes in vegetation around the study area were documented throughout the data collection period. Vegetation in August through September stayed relatively consistent. There were lush amounts of green vegetation for the deer to consume.
Figure 2: Photo from September 17 displaying the amount of green vegetation present.
As we entered October, I saw the vegetation begin to discolor and die off. This is consistent with normal vegetation patterns as the weather begins to cool and stray from an environment suitable to support these plants.
Figure 3: Photo depicting the vegetation status on October tenth.
Towards the end of October most of the vegetation had discolored and appeared to have a harder and coarser texture than they previously did in August and September.
Figure 4: Photo depicting vegetation status October twenty-third.
The vegetation in November was very scarce and from what I observed, the vegetation that was present had a hard texture and was very spread out. A lot of the vegetation that was still alive had thorns and other sharp parts, which are harder to consume than the easily digestible lush greens.
Figure 5: Photo depicting vegetation status November seventeenth.
Deer Movement
The temporal pattern of the movement of deer appeared to be relatively stable from late August to late September. Deer movement would increase around the hours of sunrise and then decrease until the hours around sunset. At sunset the movement would again increase. As seen in Table 1, the peak deer movement times for the months of August and September were around sunrise and sunset hours. A daily average of three deer would be captured on the trail cameras around 6:00 am and approximately two deer daily around 7:00 am. There was relatively no daily average deer movement from the midday hours of 8:00 am to 3:00 pm. Deer movement would then increase again around the time of sunset. Approximately one deer would be captured daily by the camera around 7:00 pm and three deer on average would be captured at 8:00 pm. The data gathered for these months is slightly different than the data gathered for the months of October and November. In the months of October and November, the average daily highest peaks stayed consistent at sunrise and sunset. However, there was a slight peak of movement midday around noon. In almost all of the pictures of deer captured at that time the deer were facing towards the trail camera as if they were returning from their morning food venture. Daily on average there are three deer who are captured by the trail cameras around 7:00 am and on average two captured on camera around 8:00 am. This is similar to the peak times in table 1, as these hours are still around sunrise. The sunset peaks have shifted as well, with only one at 5:00 pm. In both Table 1 and Table 2 there is a fairly consistent timeframe of daily deer movement with only small amounts of variation.
Table 1: Table 1 depicts the daily average number of deer that cross the perimeter at a given time in the months of August and September.
Table 2: Table 2 depicts the daily average number of deer that cross the perimeter at a given time in the months of October and November.
Deer-vehicle Survey
The anonymous survey provided useful qualitative data about deer-vehicle interactions. As stated before, I sent out twenty-five surveys and received nineteen responses.
For Question 1 it was determined that most people in the Hayden area spend most of their time driving on highways and interstates.
Table 3: Table 3 depicts results for Question 1
For Question 2 it was determined that most people drive eleven times or more weekly.
Table 4: Table 4 depicts results for Question 2
It was determined in Question 3 that most people who took the survey drive between the hours of 5:00 am and 8:00 am more than five times a week.
Table 5: Table 5 depicts the results from Question 3
The results of question 4 show that most people drive between the hours of 3:00 pm and 7:00 pm more than five times a week.
Table 6: Table 6 depicts the results from Question 4.
For Question 5, it was determined that two of the nineteen participants had been in an accident involving a white-tailed deer. They both provided descriptions of their accidents.
Person 1 stated that their accident occurred around 6:00 am during the month of September as they were driving along a country road that is not traveled often. This person also provided images of their vehicle after the accident. It should be noted that the images were taken several hours after the accident occurred. As seen in the pictures, the bumper is damaged and the individual stated that it cost $650 to fix.
Figures 6 and 7: These figures depict the result of a deer-vehicle accident.
Person 2 stated that their accident occurred around 8:00 pm during the month of October on a highway that is frequently traveled. This person did not provide photos, however the front right side of the bumper of the car was damaged and cost around $500 to fix.
Question 7 shows that most people who took the survey tend to see deer around sunset and sunrise, which are typical movement times for deer.
Table 7: Table 7 depicts the results from Question 7.
Discussion
In my research project it was found that white-tailed deer are at peak movement around the hours of sunrise and sunset. According to Volk et al., this is accurate for the warmer months as temperatures are lower at those times than they are around midday (Volk et al., 2007). The times of day with lower temperatures are optimal for foraging food to limit energy expenditure (Ortega-Santos & Fullbright, 2013). My findings for the colder months were also accurate in the sunrise and midday aspect. Volk et al. states that diurnal activity in winter peaks at dawn and dusk due to the need to regulate their temperature, specifically in more northern populations of white-tailed deer (Volk et al., 2007).
The peak movement times for white-tailed deer appeared to happen around sunrise and sunset in all four seasons of the data collection period, however the peak seemed to last longer in the colder months with a slight spike in movement around midday. According to (Rodrigues et al., 2000), this is due to the deer expanding their home range in relation to the availability of forage to (Rodrigues et al., 2000). Leeuwenberg et al. (1997) discovered that seasonal variation in home range sizes is larger in the months where there is little forage available. The availability of flowers and grasses decreases in colder months, therefore deer are required to travel farther to increase their chances of finding nutritional food to (Rodrigues et al., 2000). In nutritionally inadequate habitats, white-tailed deer are far less productive (Ortega-Santos & Fullbright, 2013). Without proper nutrition female white-tailed deer’s milk supply can be reduced, ovulation and conception rates are lowered, and male deer will not meet their body mass and antler size potential (Ortega-Santos & Fullbright, 2013). In order to avoid such factors, white-tailed deer seek a diet rich in proteins, fats, vitamins, carbohydrates, and minerals (Foster, 2018). High-quality forage is ideal compared to low-quality forage because of the nutrients it contains and quick digestion time. Low-quality forages pass through the digestive tract more slowly than high-quality forage, thus reducing the amount of nutrients absorbed in the body because once the rumen capacity is reached, no more food can be eaten until more room is made (Ortega-Santos & Fullbright, 2013). The forage quality declines as the seasons change from warmer to colder. In addition to higher-quality forage, in the warmer seasons there are more leaves and flowers which are tender and favorable. However, in colder seasons these favorable parts of plants are limited and the nutritional value of these plants has decreased. In colder seasons there are less leaves and tender matter and more thorns and dry matter. The low quantity of favorable and nutritional matter causes the deer to spend more time foraging in order to find quality food, which spends more energy (Ortega-Santos & Fullbright, 2013). Ortega-Santos and Fullbright conclude that deer migrate to areas where they can find good quality food that is more accessible. They found that in the South Texas Plains where deer feed on guajillo, deer did not move as frequently when the plant was lush in the spring. When the plant began to mature and die off, deer movement picked up and home range size increased due to searching for that plant or similar plants in that area.
Williams et al., found similar results in their study. They concluded that white-tailed deer home range size, migration, and dispersal distances are a product of the deer responding to the landscape (Williams et al., 2012). The deer responded to selective pressures in their environment like low quantities of food by moving to areas where nutritional resources were more abundant (Williams et al., 2012).
Hammerstrom and Blake (1939) also concluded in their study that the result of inadequate nutritional food supply causes white-tailed deer to migrate. They studied a population of white-tailed deer through multiple cycles of all four seasons, they found that deer density is correlated with food shortage. During winter deer density was lower, which means the deer had moved to find sources of food.
DeYoung studied the effects on deer density related to changes in vegetation. In the study, two deer populations were studied in different areas, either a natural-nutrition area or an enhanced-nutrition area. In the enhanced-nutrition area, the deer did not shift movement much and stayed relatively close to the enhanced food area (DeYoung, 2019). In the natural-nutrition area the deer were rarely around, meaning they were off looking for food resources (DeYoung, 2019). This study shows how deer are less likely to migrate away from areas where food quantity is abundant.
These results align with what I gather from my research data. In my warmer month data, deer movement peaks from about 5:00 am to 6:00 am and from 6:00 pm to 8:00 pm or later. The colder months have a similar pattern in respect to time of day, however the peak movement times are from 6:00 am to 9:00 am and 4:00 pm to 8:00 pm. This suggests that in the warmer months the deer are sticking around and close having a small home range. While in the colder months, their peak movement times are longer in duration, suggesting that they are traveling longer distances and coming back later. In the warmer months I observed the vegetation to be more abundant, therefore the deer did not have to travel far for food. As the weather became colder, I noticed the vegetation eventually died off leaving low supplies of hard, unfavorable food that is not as nutritious.
It appears that changes in white-tailed deer foraging behavior correlates with deer-vehicle accident frequency. Allen and McCullough (1976) found that higher rates of deer-car collisions occurred in the early morning around sunrise and before sunset. This was concluded to happen because deer movement for forage increases around this time (Allen & McCullough, 1976).
Hubbard et al., found that deer behavior is an important variable in deer-vehicle accidents. They found that green-up of vegetation along highways is related to an increase in accidents (Hubbard et al., 2000). Areas of deer habitat that at the center were greater than 50 m from the edge of a road had higher rates of accidents (Hubbard et al., 2000). As the seasons began to get colder, the deer would increase their home range. This caused them to cross surrounding roads and increase the risk of being involved in an accident with a vehicle (Hubbard et al., 2000). Similar findings are stated by Finder et al. (1999). They found that wooded areas, where deer obtain most of their nutritional resources, near roads resulted in a higher chance for collisions (Finder et al., 1999).
The results from my survey tied with my quantitative data support the findings in the articles stated above. In my survey, it was determined that 53% of participants reported viewing deer while driving around the hours of sunset and 42% of participants reported seeing deer around the hours of sunrise. This is consistent with the findings from my research and other research of when white-tailed deer forage for food. Two participants were involved in a deer-vehicle accident during times consistent with peak movement. As the deer move more in the colder months to retrieve nutritional food, the chance of a collision is to increase as well. The deer are moving more frequently across roads and possibly even moving farther to cross roads that would not be crossed in warmer months.
Conclusion
The objective for my study was to observe deer movement in relation to changes in vegetation and connect those results to studies assessing deer-vehicle collisions. Throughout my experiment I encountered some limitations. This type of study would normally require at least one full cycle of all four seasons, if not several cycles. Due to the academic semester, I had a limited time to collect my data. Due to this limitation, I compared my data to data from multiple similar studies. Another limitation encountered was the inability to properly collect deer movement data. Due to budget restraints, I only used four trail cameras to capture deer movement which is simply inadequate for proper data. To correct this limitation, I would need several more trail cameras or an alternative tracking method such as GPS collars. Deer hunting season and rut also occurred while I was conducting my study. These factors could have also influenced the movement of deer along with the search for vegetation.
From these findings it can be seen that stronger precautions need to take place in order to protect human health and white-tailed deer welfare. Solutions have been previously studied and pose great benefit to protecting the lives of humans and deer. Reed et al. (1982) suggests the placement of fences in areas where white-tailed deer populations are high and accidents are more common. This is though to reduce the amount of deer-vehicle accidents, thus reducing the amount of money spent on repairs. The projected average cost of repairs to a vehicle involved in a deer collision from 1970 to 1978 was estimated to be anywhere from $324 to $564 (Reed et al., 1982). The installation of a fence can improve road safety, protect wildlife and human life, and save car owners from spending large amounts on repairs.
Another solution is to implement more effective lighting in areas where deer-vehicle accidents are common. This can promote road safety regarding deer-vehicle collisions. It was found that deer still crossed roads that were well lit, however drivers were able to avoid such accidents because they were able to see the area better (Reed et al., 1981).
Odor repellent is another solution to prevent deer-vehicle collisions. Odor repellents are more cost effective. According to Bíl et al. (2018),
odor repellents have proven to reduce the number of wildlife-vehicle accidents up to 56%. This solution can be a more cost friendly option compared to fence installment. Fraser (1982) also found that odor repellents such as cow manure, putrescent egg, creosote, and isobutyric acid can lower the occurrence of wildlife-vehicle accidents.
Understanding how white-tailed deer movement changes relate to deer-vehicle accident occurrence is an important factor in determining steps to increase road safety for humans and wildlife. With the results from my data and other studies, new paths for increasing road safety can be explored.
References
Allen, R. E., & McCullough, D. R. (1976). Deer-Car Accidents in Southern Michigan. The
Journal of Wildlife Management, 40(2), 317–325. https://doi.org/10.2307/3800431
Bíl, M., Andrášik, R., Bartonička, T., Křivánková, Z., & Sedoník, J. (2018). An evaluation of odor repellent effectiveness in prevention of wildlife-vehicle collisions. Journal of Environmental Management, 205, 209–214. https://doi.org/10.1016/j.jenvman.2017.09.081
Cook, K. E., and P. M. Daggett. 1995. Highway roadkill; associated issues of safety and impacts
on highway ecotones. Task force on natural resources, Transportation Research Board.
National Research Council, Washington D.C., USA.
DeYoung, Charles A., et al. “Linking White-Tailed Deer Density, Nutrition, and Vegetation in a
Stochastic Environment.” Wildlife Monographs, vol. 202, no. 1, 2019, pp. 1-63.,
doi:10.1002/wmon.1040
Finder, R. A., Roseberry, J. L., & Woolf, A. (1999, May 28). Site and landscape conditions at
white-tailed deer/vehicle collision locations in Illinois. Landscape and Urban Planning.
Retrieved October 3, 2021, from
https://www.sciencedirect.com/science/article/pii/S0169204699000067
Flávio H. G. Rodrigues, & Emygdio L. A. Monteiro-Filho. (2000). Home Range and Activity Patterns
of Pampas Deer in Emas National Park, Brazil. Journal of Mammalogy, 81(4), 1136–1142.
http://www.jstor.org/stable/1383380
Foster, Michael Anthony. (2018) “Whitetail Deer Nutrition Essential to Animals’ Size and
Survival.” University of Georgia Extension, extension.uga.edu/story/6456/Whitetail-
Nutrition.html.
Fraser, D., & Hristienko, H. (1982). Moose-Vehicle Accidents in Ontario: A Repugnant
Solution? Wildlife Society Bulletin (1973-2006), 10(3), 266–270.
http://www.jstor.org/stable/3781016
Hamerstrom, F. N., and James Blake. “Winter Movements and Winter Foods of White-Tailed
Deer in Central Wisconsin.” Journal of Mammalogy, vol. 20, no. 2, [American Society of Mammalogists, Oxford University Press], 1939, pp. 206–15, https://doi.org/10.2307/1374379.
Hothorn, T., Müller, J., Held, L., Möst, L., & Mysterud, A. (2015). Temporal patterns of deer–vehicle collisions consistent with deer activity pattern and density increase but not general accident risk. Accident Analysis & Prevention, 81, 143–152. https://doi.org/10.1016/j.aap.2015.04.037
Hubbard, M. W., Danielson, B. J., & Schmitz, R. A. (2000). Factors Influencing the Location of
Deer-Vehicle Accidents in Iowa. The Journal of Wildlife Management, 64(3), 707–713. https://doi.org/10.2307/3802740
Leeuwenberg, F., S. Lara-Resende, F. H. G. Rodrigues, and M. X. A. Bezerril. 1997. Home range, activity and habitat use of the Pampas deer (Ozotoceros bezoarticus L. 1758, Artiodactyla, Cervidae) in the Brazilian Cerrado. Mammalia 61:487-495.
Oosenbrug, S. M., Mercer, E. W., & Ferguson, S. H. (1991). Moose-vehicle collisions in
Newfoundland-management considerations for the 1990’s. Alces: A Journal Devoted to
the Biology and Management of Moose, 27, 220-225.
Ortega-Santos, Jose Alfonso and Timothy Edward Fulbright. White-Tailed Deer
Habitat:Ecology and Management on Rangelands. 2, Expanded and Updated ed. Texas A&M University Press, 2013. Project MUSE https://muse.jhu.edu/book/23148.
Reed, D. F., Thomas D. I. Beck, & Woodard, T. N. (1982). Methods of Reducing Deer-Vehicle Accidents: Benefit-Cost Analysis. Wildlife Society Bulletin (1973-2006), 10(4), 349–354. http://www.jstor.org/stable/3781205
Reed, D. F., & Woodard, T. N. (1981). Effectiveness of Highway Lighting in Reducing Deer-Vehicle Accidents. The Journal of Wildlife Management, 45(3), 721–726. https://doi.org/10.2307/3808706
Sparrowe, R. D., & Springer, P. F. (1970). Seasonal Activity Patterns of White-Tailed Deer in Eastern
South Dakota. The Journal of Wildlife Management, 34(2), 420–431.
https://doi.org/10.2307/3799028
Tierson, W. C., Mattfeld, G. F., Sage, R. W., & Behrend, D. F. (1985). Seasonal Movements and
Home Ranges of White-Tailed Deer in the Adirondacks. The Journal of Wildlife Management, 49(3), 760–769. https://doi.org/10.2307/3801708
Volk, M. D., Kaufman, D. W., & Kaufman, G. A. (2007). Diurnal Activity and Habitat Associations of White-Tailed Deer in Tallgrass Prairie of Eastern Kansas. Transactions of the Kansas Academy of Science (1903-), 110(3/4), 145–154. http://www.jstor.org/stable/20476310
Williams, D.M., Dechen Quinn, A.C. & Porter, W.F. Landscape effects on scales of
movement by white-tailed deer in an agricultural–forest matrix. Landscape Ecol 27, 45–57 (2012). https://doi.org/10.1007/s10980-011-9664-5
Leave a Reply