Temporal patterns of deer-vehicle collisions consistent with deer activity pattern and density increase but not general accident risk

Trends and Characteristics of Human Casualties in Wildlife-Vehicle Accidents in Lithuania, 2002-2022

We analyzed 474 human casualties in wildlife-vehicle accidents (WVAs) that occurred between 2002 and 2022 in Lithuania, which is a small northern European country. The study revealed the escalating trend of WVAs, since 2018 surpassing other transport accidents, although the number of casualties per WVA was ca. 100 times lower compared to other transport accidents. Moose was the primary contributor, responsible for 66.7% of fatalities and 47.2% of injuries, despite much lower species abundance compared to roe deer, which is the main species involved in WVAs without human casualties. Temporal patterns highlighted seasonal, daily, and hourly variations, with the majority of casualties occurring during dusk or dawn in May and September, on weekends, and between 20:00 and 22:00. Spatially, main roads with high traffic density exhibited the highest casualties per unit length. Most casualties occurred after hitting an animal directly with cars and motorcycles being most vulnerable vehicles. The effectiveness of WVA prevention measures was inconclusive: 9.5% of fatalities and 1.4% of injuries were registered in the area of the warning sign, and 10.4% of all casualties occurred on fenced road segments. These findings suggest the need for a critical evaluation of the current prevention strategies in reducing human casualties associated with WVAs.

Deer activity levels and patterns vary along gradients of food availability and anthropogenic development

Animal activity reflects behavioral decisions that depend upon environmental context. Prior studies typically estimated activity distributions within few areas, which has limited quantitative assessment of activity changes across environmental gradients. We examined relationships between two response variables, activity level (fraction of each day spent active) and pattern (distribution of activity across a diel cycle) of white-tailed deer (Odocoileus virginianus), with four predictors-deer density, anthropogenic development, and food availability from woody twigs and agriculture. We estimated activity levels and patterns with cameras in 48 different 10.36-km2 landscapes across three larger regions. Activity levels increased with greater building density, likely due to heightened anthropogenic disturbance, but did not vary with food availability. In contrast, activity patterns responded to an interaction between twigs and agriculture, consistent with a functional response in habitat use. When agricultural land was limited, greater woody twig density was associated with reduced activity during night and evening. When agricultural land was plentiful, greater woody twig density was associated with more pronounced activity during night and evening. The region with the highest activity level also experienced the most deer-vehicle collisions. We highlight how studies of spatial variation in activity expand ecological insights on context-dependent constraints that affect wildlife behavior.

Application of Bayesian Space-Time interaction models for Deer-Vehicle crash hotspot identification

The objective of this research was to identify and prioritize deer-vehicle crash (DVC) hotspots using five years of crash data. This study applied Bayesian spatiotemporal models for the identification of the DVC hotspots. The Bayesian spatiotemporal model allows to observe area-specific trends in the DVC data and highlights specific locations where DVC occurrence is deteriorating or improving over time. Census Tracts (CTs) were used as the geographic units to aggregate DVC, land use, and transportation infrastructure related data of Minnesota (MN) for the year 2015 to 2019. Several tests were conducted to evaluate the performance of the hotspot identification methods. The result showed that Type-I spatiotemporal interaction model (Model-2) outperforms other four space-time models in terms of predicting DVC frequency in CTs and hotspot identification performance test measures. Results showed that forest area, vegetation, and wetland percentages were positively associated with DVC frequency, whereas the percentage of developed land use was negatively associated with DVC frequency. The findings of this study suggest that the deer population plays an important role in DVCs, which indicates that deer population management is necessary to minimize the DVC risks. Using the final Type-I spatiotemporal interaction model, 65 "High-High" CTs were identified, where both the posterior mean of the decision parameter (potential for safety improvement) and the area-specific trend were higher. The distribution of the identified hotspots showed that the risk of DVCs was more in suburban areas with mixed land use conditions. These CTs represent high-risk zones, which need immediate safety improvement measures to reduce the DVC risks. As DVC can occur at any roadway segment location, DVC hotspots information is important for safety engineers and policymakers to implement area specific countermeasures.

Understanding spatio-temporal patterns of deer-vehicle collisions to improve roadkill mitigation

Vehicles collide with hundreds of thousands of deer on European roads each year. This leads to animal deaths and suffering, economic damage and risks for human safety, making the reduction of road mortality a major field in conservation biology. In order to successfully reduce roadkill, we need improved knowledge regarding spatio-temporal patterns of deer-vehicle collisions (DVCs) on a landscape scale. Here, we analyzed >85,000 DVCs collected over 17 years in Denmark to investigate changes in the number of DVCs over time and to find spatio-temporal patterns of DVC occurrence. We used a use-availability design - originally developed for habitat selection analyses - to compare DVCs involving roe deer (Capreolus capreolus), red deer (Cervus elaphus) and fallow deer (Dama dama) with random road locations on a landscape scale. This approach enabled us to combine temporal (seasonal and diel variation), spatial (land cover, road density and type) and other relevant variables (deer population density, traffic, and deer activity) within the same analysis. We found that factors related to infrastructure and land cover were most important in explaining patterns of DVCs, but seasonal and diel changes, deer activity, and population density were also important in predicting the occurrence of DVCs. Importantly, patterns of DVCs were largely similar between the three deer species, with more DVCs occurring at intermediate traffic density, increasing forest cover, during dusk and dawn, and with increasing deer activity and population density. The strong and consistent patterns found here will allow the development of flexible mitigation measures. We propose that our findings could be used to develop a spatio-temporally flexible warning system for smartphones and navigation systems that is based on existing map providers, making it a widely available and cheap mitigation measure.

Effect of Daylight Saving Time clock shifts on white-tailed deer-vehicle collision rates

To devise effective measures for reducing hazardous wildlife-vehicle collisions, it is necessary to know when during the year accidents occur most frequently, and what factors cause the seasonal patterns. Daylight Saving Time (DST) 1-h clock-shifts around the spring and fall equinoxes at temperate zone latitudes are associated with increased vehicle accidents, attributed to driver error caused by disrupted sleep patterns and changes in visibility during peak driving times. Collision with deer is a significant cause of motor vehicle accidents in North America; in New York State alone, 65,000 vehicle accidents annually are caused by collision with white-tailed deer (Odocoileus virginianus). We asked whether white-tailed deer-vehicle collisions (DVC) increased in frequency after DST clock shifts in New York State, by analyzing 35,167 New York State DVC reports from 2005 to 2007. For the spring, when the clock is shifted an hour forward relative to sunrise (i.e. later sunrise and sunset), there was either no change or possibly a small decrease in workweek evening DVC after the clock shift. For fall, when the clock is shifted an hour back relative to sunrise (i.e. earlier sunrise and sunset), the DVC rate was far higher than spring. The DVC rate was higher after the clock shift than before, caused in part by an ongoing seasonal trend for increasing DVC associated with deer behavior around the time of rut, peaking about two weeks after the clock shift. However, there was also a reduction in workweek morning DVC after clock-shift, but an even greater increase in DVC in the evening. DVC rates are highest around dusk and during the fall, and the fall DST clock-shift caused more workweek commuter traffic to coincide with the annual hourly period of peak risk of DVC. We conclude that in New York State, DST clock-shift results in an increase in the number of DVC, and therefore injuries and property damage associated with such accidents. The justification for DST clock-shifts is controversial; when evaluating the benefits and costs, one should include the consequences for risk of wildlife-vehicle collisions, especially in regions where ungulate-vehicle accidents are frequent, and clock-shifts coincide with the rut or other periods of peak accident risk.

Wolves make roadways safer, generating large economic returns to predator conservation

Recent studies uncover cascading ecological effects resulting from removing and reintroducing predators into a landscape, but little is known about effects on human lives and property. We quantify the effects of restoring wolf populations by evaluating their influence on deer-vehicle collisions (DVCs) in Wisconsin. We show that, for the average county, wolf entry reduced DVCs by 24%, yielding an economic benefit that is 63 times greater than the costs of verified wolf predation on livestock. Most of the reduction is due to a behavioral response of deer to wolves rather than through a deer population decline from wolf predation. This finding supports ecological research emphasizing the role of predators in creating a "landscape of fear." It suggests wolves control economic damages from overabundant deer in ways that human deer hunters cannot.

COVID-19 related travel restrictions prevented numerous wildlife deaths on roads: A comparative analysis of results from 11 countries

Millions of wild animals are killed annually on roads worldwide. During spring 2020, the volume of road traffic was reduced globally as a consequence of the COVID-19 pandemic. We gathered data on wildlife-vehicle collisions (WVC) from Czechia, Estonia, Finland, Hungary, Israel, Norway, Slovenia, Spain, Sweden, and for Scotland and England within the United Kingdom. In all studied countries WVC statistics tend to be dominated by large mammals (various deer species and wild boar), while information on smaller mammals as well as birds are less well recorded. The expected number of WVC for 2020 was predicted on the basis of 2015-2019 WVC time series representing expected WVC numbers under normal traffic conditions. Then, the forecasted and reported WVC data were compared. The results indicate varying levels of WVC decrease between countries during the COVID-19 related traffic flow reduction (CRTR). While no significant change was determined in Sweden, where the state-wide response to COVID-19 was the least intensive, a decrease as marked as 37.4% was identified in Estonia. The greatest WVC decrease, more than 40%, was determined during the first weeks of CRTR for Estonia, Spain, Israel, and Czechia. Measures taken during spring 2020 allowed the survival of large numbers of wild animals which would have been killed under normal traffic conditions. The significant effects of even just a few weeks of reduced traffic, help to highlight the negative impacts of roads on wildlife mortality and the need to boost global efforts of wildlife conservation, including systematic gathering of roadkill data.

Lunar Phases and Wildlife-Vehicle Collisions: Application of the Lunar Disk Percentage Method

Simple Summary

The moon is ubiquitous in the night sky and considered an important abiotic factor that influences animal activity. However, little is known about the relationship between moonlight and the daily, monthly, or seasonal frequency of wildlife–vehicle collisions (WVCs). Traditionally, the influence of moonlight on WVCs has been analyzed using the lunar phase (quarters) approach, which evaluates moonlight on a rough scale (only four 25% steps of the visible moon disc and a strict arrangement of phases over time). We used a different approach; we compared WVCs to the actual lunar disc illumination that is based on the specific daily percentage of the visible lunar disk (LDP). Our findings indicated a significant trend of increasing WVC frequencies with increasing LDP at night. We also examined the correlation between the daily numbers of WVCs and LDP for different months and seasons. Positive correlations between LDP and WVCs were stronger at night and during the late autumn–winter months, particularly in December, suggesting the importance of lunar illumination on WVCs. Our study suggests that the LDP approach may provide more possibilities for the evaluation and quantification of WVCs and lunar light relationships than the traditional lunar phase approach. The results can be useful for predicting and reducing WVCs at different times of the lunar illumination cycle and in different seasons.

Abstract

We investigated the relationship between lunar illumination based on the percentage of the visible lunar disk (LDP) and the frequency of wildlife–vehicle collisions (WVCs) in Lithuania. We analyzed WVC frequency during ten 10% LDP intervals to more precisely reflect the relationship between LDP and WVC. The 10% LDP interval approach showed a significant trend of increasing WVC frequencies with an increasing LDP at night. We also examined the correlation between the daily numbers of WVCs and LDP for different months and seasons. The relationship seemed to be stronger at night and during the late autumn–winter months, particularly in December, suggesting the importance of lunar illumination on WVCs. There was a weak positive correlation between LDP and overall daily number of WVCs (r_s = 0.091; p < 0.001) and between LDP and night WVCs (r_s = 0.104; p < 0.001). We found significant positive correlations for winter (December–February) (r_s = 0.118; p = 0.012) and autumn (August–November) (r_s = 0.127; p = 0.007). Our study suggests that the LDP interval approach may provide more possibilities for the evaluation and quantification of WVCs and lunar light relationships than the traditional lunar phase approach.

Strength of correlation between wildlife collision data and hunting bags varies among ungulate species and with management scale

Most European ungulate species are increasing in numbers and expanding their range. For the management and monitoring of these species, 64% of European countries rely on indirect proxies of abundance (e.g., hunting bag statistics). With increasing ungulate numbers, data on ungulate-vehicle collisions (UVC) may provide an important and inexpensive, complementary data source. Currently, it is unclear how bag statistics compare with UVC. A direct comparison of these two indices is important because both are used in ungulate management. We evaluated the relationship between UVC and ungulate hunting bags across bioclimatic, regional, and local scales, using five time lags (t−3 to t+1) for the five most common wild ungulate species in Sweden. For all species, hunting bags and UVC correlated positively, but correlation strength and time lags varied across scales and among species. The two indices correlated most strongly at the local management scale. Correlation between both indices was strong for the smaller deer species and wild boar, in particular, but much weaker for moose where we found the best fit using a 2-year time lag. For the other species, indices from the same year correlated best. We argue that the reason for moose data behaving differently is that, in Sweden, moose are formally managed using a 3-year time plan, while the other species are not. Accordingly, moose hunting bags are influenced more strongly by density-independent processes than bags of the other species. Consequently, the mismatch between the two indices may generate conflicting conclusions for management depending on the method applied.

In the wrong place at the wrong time: Moose and deer movement patterns influence wildlife-vehicle collision risk

Mitigation strategies for wildlife-vehicle collisions require sufficient knowledge about why, where and when collisions occur in order to be an efficient tool to improve public safety. Collisions with cervids are known to be influenced by spatial factors such as topography and forest cover. However, temporal changes in animal and motorist behaviors are often overlooked although they can increase the odds of cervid-vehicle collisions. Consequently, we evaluated potential factors influencing the spatiotemporal distribution of 450 collisions with moose and white-tailed deer that occurred between 1990 and 2015 along the 100-km long highway in southeastern Québec, Canada. Both spatial and temporal factors efficiently explained moose-vehicle collisions but not collisions with white-tailed deer, suggesting that the latter occurred more randomly along the highway. The risk of moose-vehicle collisions was mainly modulated by topographic and habitat variables, as the interactions between slope and elevation and slope and distance to suitable moose habitats had a strong effect on collision risk. Road sinuosity and the proportion of mature coniferous stands around the collision site positively influenced deer-vehicle collisions. A temporal increase in collision numbers was noted in different biological periods during which movement rates are known to be higher (e.g. post-winter dispersal and rut). These results suggest that cervid movement is the main factor influencing collision risk and frequency. Our results indicate that mitigation strategies aimed at decreasing the probability of collision with cervids must be species-specific and should focus more closely on animal movement.

Animal-vehicle collisions in Texas: How to protect travelers and animals on roadways

Animal-vehicle collisions (AVCs) are a growing problem in the United States, resulting in countless loss of animal life and considerable human injury and death every year, especially to motorcyclists. Due to underreporting, collision data generally provide a very low (highly biased) estimate of actual AVC counts and often lack key details, such as the species of animals involved. However, AVC reports cover entire states and nations, and can illuminate differences in wild versus domestic animal-vehicle collisions through statistical and spatial analysis. 51,522 animal-related crashes were reported to Texas police from 2010 through 2016, at a total cost over $1.3 billion annually to Texas motorists - not including the value of lost animal lives. AVC reports jump twice a day: between 5 and 8 AM and between 5 and 10 PM. Motorists are also significantly more likely to collide with a wild animal during the months of October, November, and December. Wildlife-vehicle collisions (WVC) are 64% of total reports, events involving domestic animals (like dogs and cattle) are 31%, and the remaining 5% of reports are unspecified. Most AVCs in the state occur at night in unlit locations, usually on rural roads with very low traffic volumes. Using ordinary least-squares (OLS) regression analysis across Texas' n = 254 counties, this work finds that less densely populated counties, marked as rural, and those with fewer vehicle-miles traveled (VMT) per capita but more lane-miles per capita, tend to experience the greatest number of AVCs per VMT, after controlling for county average rainfall, share of VMT onsystem roadways, job densities, and vehicle ownership (vehicles per capita). Intervention options for the mitigation of animal-vehicle collisions are numerous and diverse. For wildlife collisions specifically, this work finds that large crossing structures (underpasses and overpasses) at the highway link level return benefit-to-cost ratios near 3.0, while their lower-cost counterparts (wildlife fencing and animal detection systems) deliver ratios up to 30.

The Association Between Hunter-Killed Deer and Lyme Disease in New Jersey, 2000-2014

Years when the deer population is robust during the autumn hunting season may point toward an elevated risk of Lyme disease (LD) in the human population two summers later. We applied overdispersed Poisson regression models to county-specific data from New Jersey for each year from 2000 to 2014. The average relative risk of LD for each additional hunter-killed deer per square mile was 1.12 (1.10, 1.14) for 2000-2007 and 1.11 (1.09, 1.13) for 2008-2014. The hunting data already collected for conservation and wildlife management purposes may be a relevant component of LD surveillance activities.

On reliable identification of factors influencing wildlife-vehicle collisions along roads

Wildlife-vehicle collisions (WVCs) pose a serious global issue. Factors influencing the occurrence of WVC along roads can be divided in general into two groups: spatially random and non-random. The latter group consists of local factors which act at specific places, whereas the former group consists of globally acting factors. We analyzed 27,142 WVC records (roe deer and wild boar), which took place between 2012 and 2016 on Czech roads. Statistically significant clusters of WVCs occurrence were identified using the clustering (KDE+) approach. Local factors were consequently measured for the 75 most important clusters as cases and the same number of single WVCs outside clusters as controls, and identified by the use of odds ratio, Bayesian inference and logistic regression. Subsequently, a simulation study randomly distributing WVC in clusters into case and control groups was performed to highlight the importance of the clustering approach. All statistically significant clusters with roe deer (wild boar) contained 34% (27%) of all records related to this species. The overall length of the respective clusters covered 0.982% (0.177%) of the analyzed road network. The results suggest that the most pronounced signal identifying the statistically significant local factors is achieved when WVCs were divided according to their occurrence in clusters and outside clusters. We conclude that application of a clustering approach should precede regression modeling in order to reliably identify the local factors influencing spatially non-random occurrence of WVCs along the transportation infrastructure.

Spatiotemporal patterns of wildlife road mortality in the Pothwar Plateau, Pakistan

The current study investigated the impact of roads on native wildlife fauna in Pothwar Plateau, Pakistan. By conducting driven transects over a period of 24 months (March 2012–February 2014), we identified 131 carcasses resulting from wildlife-vehicle collisions or “road kill”, comprising 18 vertebrate species from seven different orders. The Asiatic jackal (Canis aureus; Linnaeus, 1758) was the most common road kill (37.4%), followed by the small Indian mongoose (Urva auropunctatus; Hodgson, 1836; 9.9%) and the red fox (Vulpes vulpes; Linnaeus, 1758; 8.4%). Road kill incidences included both nocturnal (55.6%) and diurnal species (44.5%). The maximum number of road kills were encountered in the Rawalpindi district area (46.6%), followed by Chakwal (36.6%), Jhelum (8.4%) and Attock (8.4%). The majority of road kills occurred on paved roads (93.9%; 0.009 road kill/km) with significantly fewer occurrences on unpaved roads (6.1%; 0.004 road kill/km). Similarly, 77% (0.009/km) of the road kills were found adjacent to protected areas. The majority of road kills (33%) occurred during the spring (February–April) but less in summer (May–July) and winter (November–January) (19.8% for both). The study provides important data on road mortality of wildlife species in the region bordering protected areas in the Pothwar Plateau, Pakistan, to initiate management and conservation strategies.

Wildlife warning reflectors do not mitigate wildlife-vehicle collisions on roads

Wildlife-vehicle collisions cause human fatalities and enormous economic and ecological losses on roads worldwide. A variety of mitigation measures have been developed over the past decades to separate traffic and wildlife, warn humans, or prevent wildlife from entering a road while vehicles are passing by, but only few are economical enough to be applied comprehensively. One such measure, wildlife warning reflectors, has been implemented over the past five decades. However, their efficacy is questioned because of contradictory study results and the variety of applied study designs and reflector models. We used a prospective, randomized non-superiority cross-over study design to test our hypothesis of the inefficacy of modern wildlife warning reflectors. We analyzed wildlife-vehicle collisions on 151 testing sites of approximately 2 km in length each. During the 24-month study period, 1984 wildlife-vehicle collisions were recorded. Confirmatory primary and exploratory secondary analyses using a log-link Poisson mixed model with normal nested random intercepts of observation year in road segment, involved species, and variables of the road segment and the surrounding environment showed that reflectors did not lower the number of wildlife-vehicle collisions by a relevant amount. In addition, variables of the road segment and the surrounding environment did not indicate differential effects of wildlife warning reflectors. Based on our results, we conclude that wildlife warning reflectors are not an effective tool for mitigating wildlife-vehicle collisions on roads.

Temporal patterns in road crossing behaviour in roe deer (Capreolus capreolus) at sites with wildlife warning reflectors

Every year, there are millions of documented vehicle collisions involving cervids across Europe and North America. While temporal patterns in collision occurrence are relatively well described, few studies have targeted deer behaviour as a critical component of collision prevention. In this study, we investigated weekly and daily patterns in road crossing behaviour in roe deer. Using road crossing events and movement data obtained from GPS telemetry, we employed mixed-effect models to explain frequency and timing of crossings at five road segments by a number of predictors including traffic volume, deer movement activity and the presence of wildlife warning reflectors. We analysed 13,689 road crossing events by 32 study animals. Individual variation in crossing frequency was high but daily patterns in crossing events were highly consistent among animals. Variation in the intensity of movement activity on a daily and seasonal scale was the main driver of road crossing behaviour. The seasonal variation in crossing frequency reflected differences in movement activity throughout the reproductive cycle, while daily variation in the probability to cross exhibited a clear nocturnal emphasis and reflected crepuscular activity peaks. The frequency of road crossings increased as a function of road density in the home-range, while traffic volume only exerted marginal effects. Movement activity of roe deer in our study coincided with commuter traffic mainly in the early morning and late afternoon during winter and during periods of high spatial activity such as the rut. Both timing and frequency of crossing events remained unchanged in the presence of reflectors. Our results emphasise the importance of behavioural studies for understanding roe deer vehicle-collision patterns and thus provide important information for collision prevention. We suggest that mitigation of collision risk should focus on strategic seasonal measures and animal warning systems targeting drivers.

Temporal patterns of moose-vehicle collisions with and without personal injuries

Collisions with wild ungulates are an increasing traffic safety issue in boreal regions. Crashes involving smaller-bodied deer species usually lead to vehicle damage only, whereas collisions with a large animal, such as the moose, increase the risk of personal injuries. It is therefore important to understand both the factors affecting the number of moose-vehicle collisions (MVCs) and the underlying causes that turn an MVC into an accident involving personal injuries or fatalities. As a basis for temporal mitigation measures, we examined the annual and monthly variation of MVCs with and without personal injuries. Using a 22-year-long (1990-2011) time series from Finland, we tested the effect of moose population density and traffic volume on the yearly number of all MVCs and those leading to personal injuries. We also examined the monthly distribution of MVCs with and without personal injuries, and contrasted the Finnish findings with collision data from Sweden (years 2008-2010) and Norway (years 2008-2011). Both moose population abundance indices and traffic volume were positively related to the yearly variation in the number of MVCs in Finland. The proportion of MVCs involving personal injuries decreased during our 22-year study period. The monthly distribution of all MVCs peaked during the autumn or winter depending on country, while MVCs involving personal injury peaked in summer. Our study indicates that efforts to reduce MVCs involving personal injuries need to address driver awareness and attitudes during summer, despite most MVCs occurring in autumn or winter.

Effectiveness of light-reflecting devices: A systematic reanalysis of animal-vehicle collision data

Every year, approximately 500 human fatalities occur due to animal-vehicle collisions in the United States and Europe. Especially heavy-bodied animals affect road safety. For more than 50 years, light-reflecting devices such as wildlife warning reflectors have been employed to alert animals to traffic when crossing roads during twilight and night. Numerous studies addressed the effectiveness of light-reflecting devices in reducing collisions with animals in past decades, but yielded contradictory results. In this study, we conducted a systematic literature review to investigate whether light-reflecting devices contribute to an effective prevention of animal-vehicle collisions. We reviewed 53 references and reanalyzed original data of animal-vehicle collisions with meta-analytical methods. We calculated an effect size based on the annual number of animal-vehicle collisions per kilometer of road to compare segments with and without the installation of light-reflecting devices for 185 roads in Europe and North America. Our results indicate that light-reflecting devices did not significantly reduce the number of animal-vehicle collisions. However, we observed considerable differences of effect sizes with respect to study duration, study design, and country. Our results suggest that length of the road segment studied, study duration, study design and public attitude (preconception) to the functioning of devices may affect whether the documented number of animal-vehicle collisions in- or decrease and might in turn influence whether results obtained were published.