A review on the temporal pattern of deer-vehicle accidents: impact of seasonal, diurnal and lunar effects in cervids

Olfactory repellents decrease the number of ungulate-vehicle collisions on roads: Results of a two-year carcass study

An experimental study was conducted to test the effectiveness of olfactory repellents (ORE) as a mitigation measure to reduce ungulate-vehicle collisions (UVC). In the first phase, an extensive field survey was undertaken while employing the Before-After Control-Impact (BACI) study design. On the basis of ungulate mortality, 134 road sections were monitored on foot along both roadsides once a week. The monitoring lasted fourteen weeks per year in both 2021 (Before period) and 2022 (After period). In the after period, 2022, ORE were applied within the impact segments. The second phase consisted of data verification and statistical analysis. The data revealed a decrease in UVC of 68%. The confidence interval of this estimate suggested, however, a great deal of uncertainty about the true value. Therefore, the data were pooled, and the Bayesian inference was applied. On the level of moderate evidence, ORE decreased the number of UVC by at least 43% and at most 60%. We also observed that the ORE effect was more pronounced in the first seven weeks after installation than in the following seven weeks, suggesting ungulate habituation to ORE. We have therefore concluded that for a short period (ideally corresponding to UVC peaks) ORE could be considered an effective safety measure for secondary roads.

Wildlife-vehicle collisions: The disproportionate risk of injury faced by motorcyclists

We applied a generalized linear mixed-effects model to determine the factors leading to injuries from wildlife-vehicle collisions (WVCs). We used the Police database representing WVCs which took place on the Czech road network between 2009 and 2022. The majority of WVCs in Czechia are with roe deer, followed by wild boar, i.e., both relatively small ungulates. Less than 2 % of these encounters ends with an injury to the motor vehicle occupants. We found that the probability of sustaining injury was systematically higher for motorcyclists than for car occupants. The odds of sustaining an injury during WVC were roughly 1600 times higher for motorcyclists than for car occupants. When applying an evading manoeuvre, the odds of sustaining an injury were approximately 68 times higher for car occupants while only 2.3 times higher for motorcyclists compared to a direct hit to an animal. The lack of helmets (for motorcyclists) and missing seat belts (for car occupants) were additional factors which made the outcomes worse for WVCs. While the acceptance of a direct hit (preceded by braking) seems to be a reasonable strategy for car drivers, WVC awareness (including maintaining a lower speed during critical times and places) should be raised among motorcyclists as both manoeuvres are almost comparably dangerous for them.

Can highway tunnel constructıon change the habitat selection of roe deer (Capreolus capreolus Linnaeus, 1758)?

One of the main things wildlife does for survival is movement. Wild animals need movement to meet their needs, such as reproduction, breeding, foraging, and dispersal. Although wildlife species use roads for various purposes, they also use them when moving from one habitat to another. In recent years, especially when it comes to habitat fragmentation brought about by urbanization, wild animals frequently use highways. Highways have a wide range of effects on factors such as biodiversity, wildlife, and ecology. Roads can cause habitat loss, habitat fragmentation, and habitat degradation; alter the composition of vegetation; act as barriers to the flow of genes and movement; increase human access to pristine areas; and even increase the risk of extinction for many threatened species. Species belonging to the family Cervidae also include the species most affected by road networks. Roe deer (Capreolus capreolus Linnaeus, 1758) is the smallest of the 3 Cervid species living in Turkey. Roe deer are often injured or die in road accidents, and they are one of the most important species affected by the adverse effects of roads in Turkey. For this reason, it was investigated whether the road tunnel construction affected the distribution of roe deer in the region. In the study, the general distribution of roe deer in the Ilgaz Mountain, and the factors affecting their possible distribution were determined by ecological niche modeling. Data were taken between before (2012-2015) and after the highway tunnel built (2020-2022) in Ilgaz Mountain, which connects the Western Black Sea and Central Anatolia and is located in the middle of Kastamonu and Çankırı provinces. As a result of the modeling, it was found that before the construction of the tunnel, the most influential factor in the distribution of the deer was road density. After the tunnel construction, roads ceased to be the main factor affecting the distribution of the species. This study showed that roe deer are disturbed by the density of vehicles on the road passing through the middle of their habitat. With the decrease in the number of vehicles, they are more willing to cross the road and tend to use the areas close to the road as they are less disturbed.

A spatiotemporal risk prediction of wildlife-vehicle collisions using machine learning for dynamic warnings

INTRODUCTION

The technology in the automotive industry is becoming increasingly safer in the age of automated driving, but the number of accidents is still high, especially in wildlife-vehicle collisions (WVCs). To better avoid these accidents, patterns involved in these accidents must be detected.

METHOD

This paper presents a spatiotemporal risk prediction of WVCs, including various road and environmental characteristics. A process of data preparation using GIS automated by Python scripts was developed to enable a spatiotemporal link of diverse features for the subsequent predictive data analysis. Different machine learning (ML) approaches were applied- random forest (RF), feedforward neural networks (FNN), and support vector machine classifier (SVM) - including automated ML to predict the risk of WVCs. Therefore, a dataset of approximately 731,000 accidents reported to the police in Bavaria over a period of 10 years (2010-2019) was used. In addition, non-accidents were randomly generated in Python over time and space for the supervised ML processes. As the actual risk probability for WVCs and non-WVCs is not entirely known, the impact of different training ratios between accidents and non-accidents was tested on the risk prediction quality (RPQ) (25%, 50%, 75%, 90% WVCs) of the double-weighted sensitivity and single-weighted specificity rate.

RESULTS

The test yielded high mean values of RPQ as an indicator for a suitable WVC prediction. Both RF (86.6%) and FNN (86.7%) were identified as suitable choices for WVC risk prediction in terms of RPQ. The SVM yielded a lower prediction quality, even though acceptable results could be achieved within a shorter runtime.

PRACTICAL APPLICATIONS

Spatial transferability was verified since the algorithm was trained on the dataset of Bavaria (excluding Upper Bavaria) and successfully tested in Upper Bavaria. WVC forecasts were also proven through training with datasets from 2010-2017 and in prediction for 2018 and 2019.

Recursive use of home ranges and seasonal shifts in foraging behavior by a generalist carnivore

Coyotes (Canis latrans) colonized the southeastern United States over the last century as large predators, including the red wolf (Canis rufus) and eastern cougar (Puma concolor), were extirpated from the region. As a generalist carnivore, the coyote preys on white‐tailed deer (Odocoileus virginianus) and various smaller mammals, birds, and vegetation. While resource selection by coyotes has been well documented at the home‐range scale, little is known about their foraging behavior, which is an important factor in thoroughly understanding influences of coyotes on prey and sympatric carnivores. We assessed third‐order resource selection of coyotes at sites across Alabama, Georgia, and South Carolina during 2015–2016. Using GPS collars, we tracked 41 resident coyotes across four calendar seasons and identified suspected foraging areas using recursive analysis where individuals repeatedly returned to known locations. We found that resident coyotes selected for open landcover types throughout the year, while avoiding primary and secondary roads. Additionally, resident coyotes avoided forested landcover types while selecting for forest edges except from April to June when they foraged within interior forest away from edges. Previous studies have documented substantive predation rates on white‐tailed deer neonates by coyotes, and that fawn mortality may increase in forested landscapes away from forest edge. Our findings indicate that foraging coyotes may select forest cover types during spring where fawns are more vulnerable to predation. Additionally, there has been debate in the literature as to how coyotes obtain consistent levels of deer in their diets outside of fawning and fall hunting seasons. Our study indicates that use of road‐kill carcasses by coyotes was an unlikely explanation for the presence of deer in coyote diets throughout the year, as coyotes in our study were not observed using roads during foraging excursions.

A dataset of road-killed vertebrates collected via citizen science from 2014-2020

Data on road-killed animals is essential for assessing the impact of roads on biodiversity. In most European countries data on road-killed huntable wildlife exists, but data on other vertebrate species (e.g. amphibians, reptiles, small mammals) is scarce. Therefore, we conducted a citizen science project on road-killed vertebrates as a useful supplement to data on huntable wildlife collected by public authorities. The dataset contains 15198 reports with 17163 individual road-killed vertebrates collected by 912 participants. The reports were made in 44 countries, but the majority of data was reported in Austria. We implemented a data validation routine which led to three quality levels. Reports in quality level 1 are published via GBIF, reports in quality level 2 via Zenodo and reports in quality level 3 were deleted. The dataset is relevant for the scientific community studying impacts of roads on fauna as well as for those who are responsible for road planning and implementing mitigation measures.

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.

Animal-vehicle collisions during the COVID-19 lockdown in early 2020 in the Krakow metropolitan region, Poland

The interrelations between human activity and animal populations are of increasing interest due to the emergence of the novel COVID-19 and the consequent pandemic across the world. Anthropogenic impacts of the pandemic on animals in urban-suburban environments are largely unknown. In this study, the temporal and spatial patterns of urban animal response to the COVID-19 lockdown were assessed using animal-vehicle collisions (AVC) data. We collected AVC data over two 6-month periods in 2019 and 2020 (January to June) from the largest metropolis in southern Poland, which included lockdown months. Furthermore, we used traffic data to understand the impact of lockdown on AVC in the urban area. Our analysis of 1063 AVC incidents revealed that COVID-19 related lockdown decreased AVC rates in suburban areas. However, in the urban area, even though traffic volume had significantly reduced, AVC did not decrease significantly, suggesting that lockdown did not influence the collision rates in the urban area. Our results suggest that there is a need to focus on understanding the effects of changes in traffic volume on both human behaviour and wildlife space use on the resulting impacts on AVC in the urban area.

A test of wildlife warning reflectors as a way to reduce risk of wildlife-train collisions

Looking for an effective method to reduce risk of animal-train collisions, we tested the system of wildlife warning reflectors, a method usually used on roads. The research was conducted in central Poland, along a 2.1 km stretch of the E65 railway line near Warsaw, during eight months, in the years 2010–2011. For six months of a test period, the reflectors were uncovered (active) and, for the next two months of the control period, they were covered (non-active). Digital cameras were used to register animal reactions to trains 24-hours per day. We compared the probability of escape (escape = 1; no reaction = 0) from an oncoming train during test and control periods of the research, in different parts of a day (i.e. day vs. night) and compared escape time of roe deer between day and night and with reflectors covered and uncovered. Roe deer (Capreolus capreolus), red fox (Vulpes vulpes) and brown hare (Lepus europaeus) were observed most often (702 observations in total). The status of reflectors (covered/uncovered) did not influence the probability of animals’ escape from an oncoming train. The only factors that affected the probability of escape were animal species and time of a day. Of the three species, roe deer was most likely to escape from an oncoming train (89% of probability at day and 52% during night, pooled data for covered and uncovered reflectors). Timing of roe deer escape from an oncoming train did not differ between day (6.4 seconds) and night, with either reflectors covered (7.5 seconds) or uncovered (4.6 seconds). The results indicated that wildlife warning reflectors were not effective to modify animal behaviour and to reduce risk of animal-train collisions.

Spatiotemporal Analysis of Road Crashes with Animals in Poland

This article describes the issue of the influences of the time factor and wildlife populations on road animal–vehicle crashes. The article presents problems associated with animal–vehicle crashes in Poland. They are the subject of many court disputes. For the purposes of the study, data on animal–vehicle road crashes were obtained from the SEWiK database, as well as data on the numbers of animals in hunting districts from 2016–2020. The relationship between the number of road crashes and time was analysed, and the relationships between the numbers of road crashes and the animal populations, as well as the locations, types, and categories of the hunting districts, were analysed as well. The factors related to changes in the wildlife populations, road crashes in previous years, and the lengths of the road networks were also analysed. The research shows no relationship between the abundance of a particular species and the number of road crashes. Instead, there is a correlation between the number of crashes in previous years and the road network length.

Deer Rescue in Tuscany: Retrospective Analysis and Assessment of Radiography Diagnoses

Simple Summary

Animal-vehicle collisions are the major cause of rescue and need for hospitalization in wildlife referral centers. Radiography is used to assess the traumatized animal and is a rapid means to evaluate various traumatic pathologies. Clinicians can exploit radiography when making rapid decisions about whether to euthanize or treat an animal. We evaluated data (reasons for rescue, diagnosed lesions, and outcome) from a population of hospitalized wildlife ungulates and we investigated the benefits of using radiography as a diagnostic tool.

Abstract

Animal-vehicle collisions are the major cause of rescue and need for hospitalization in wildlife referral centers. Clinicians need easy-to-use tools to make rapid decisions about whether to euthanize or treat injured animals. The aim of the study was to evaluate the data (reasons for rescue, diagnosed lesions, and outcome) from a hospitalized population of wildlife ungulates and investigate the benefits of using radiography as a diagnostic tool. Data were collected from three wildlife referral centers in Tuscany (Italy). The following information was collected for each animal: reason for hospitalization, clinical examination, radiographic examination, definitive diagnosis, and outcome. A chi-squared test was used to assess the benefits of radiography in detecting different traumatic lesions. Prevalence was reported according to the reason for hospitalization, definitive diagnosis, radiographic diagnosis, and outcome. The main reason for hospitalization was traumatic lesions due to vehicle collisions and 71.1% of the animals did not survive. Radiography was more useful in patients with traumatic axial skeletal lesions and/or multiple traumas with respect to traumatic appendicular skeleton lesions. Our results show that radiography is a useful diagnostic technique for assessing wildlife emergencies and it could help the clinician in making medical decisions.

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.

Temporal patterns of roe deer traffic accidents: Effects of season, daytime and lunar phase

Wildlife-related accidents, especially deer-vehicle accidents, pose a serious problem for road safety and animal protection in many countries. Knowledge of spatial and temporal patterns of deer-vehicle accidents is inevitable for accident analysis and mitigation efforts with temporal deer-vehicle accident data being much more difficult to obtain in sufficient data quality. We described the temporal patterns of roe deer (Capreolus capreolus) roadkills occurring in the period 2002–2006 in southeastern Austria. Using a comprehensive dataset, consisting of 11.771 data points, we examined the influence of different time units (i.e. season, month, day of week, day of year), illumination categories (coarse and fine temporal resolution) and lunar phases on deer-vehicle accidents by performing linear and generalized additive models. Thereby, we identified peak accident periods within the analyzed time units. Highest frequencies of deer-vehicle accidents occurred in November, May and October, on Fridays, and during nights. Relationships between lunar phases and roe deer-vehicle accidents were analysed, providing evidence for high frequencies of deer-vehicle accidents during full moon phases. We suggest that deer-vehicle accidents are dependent both on human activity in traffic and wildlife activity, which is in turn affected by phenology, intra- and interspecific competition, climatic and astronomical events. Our results highlight, that short-term mitigation measures (e.g. traffic controls and speed limits) can be highly effective to reduce deer-vehicle accidents, but should be flexibly adapted to specific temporal periods.

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.

The scale-dependent effectiveness of wildlife management: A case study on British deer

Impacts of herbivory by wild ungulates represent a significant issue world-wide. To be effective, management of populations and impacts needs to be coordinated above the site scale, yet little research has investigated the appropriate spatial scale over which management should be integrated to be fully effective. In consideration of reduction of impacts in deciduous or mixed woodland habitats, we tested scale-specific management effectiveness in a lowland area of UK where moderate- to high-density populations of four deer species were the target of deliberate control programmes, and nonhuman predators were absent. We modelled the annual impact recorded between 2009 and 2015 in 98 woodlands as a function of cumulative culls of deer taken since the commencement of management. Analysis was repeated at different spatial scales by increasing the circular area around each focal woodland, from 2.5 km-radius up to 100 km-radius. Our findings suggest for the first time the geographical scale over which deer management needs to be coordinated for optimum effectiveness in decreasing their impact on woodland across relatively homogenous landscapes. For small bodied and relatively sedentary species (roe deer Capreolus capreolus; Reeves' muntjac Muntiacus reevesi), reductions in impacts within woodlands can be achieved by culling at the immediately local level, but some modest increase in effectiveness (probably relating to reductions in the degree of source-sink movement) may be expected with an increase in spatial scale of culling to around 30-70 km-radius. For larger-bodied, herding species with more extensive home-ranges (fallow deer Dama dama; red deer Cervus elaphus) management for reduction of woodland impacts was only really effective when coordinated above the single woodland-scale, with marked increases shown again up to a scale of 100 km-radius. Whilst future studies for different landscape types are still needed, our work emphasises that the spatial scale at which control plans are conducted can determine the effectiveness of wildlife management, possibly providing an advance on how to manage wildlife populations more effectively.

Railway mortality for several mammal species increases with train speed, proximity to water, and track curvature

Railways are a major source of direct mortality for many populations of large mammals, but they have been less studied or mitigated than roads. We evaluated temporal and spatial factors affecting mortality risk using 646 railway mortality incidents for 11 mammal species collected over 24 years throughout Banff and Yoho National Parks, Canada. We divided species into three guilds (bears, other carnivores, and ungulates), compared site attributes of topography, land cover, and train operation between mortality and paired random locations at four spatial scales, and described temporal patterns or mortality. Mortality risk increased across multiple guilds and spatial scales with maximum train speed and higher track curvature, both suggesting problems with train detection, and in areas with high proximity to and amount of water, both suggesting limitations to animal movement. Mortality risk was also correlated, but more varied among guilds and spatial scales, with shrub cover, topographic complexity, and proximity to sidings and roads. Seasonally, mortality rates were highest in winter for ungulates and other carnivores, and in late spring for bears, respectively. Our results suggest that effective mitigation could address train speed or detectability by wildlife, especially at sites with high track curvature that are near water or attractive habitat.

Temporal patterns of ungulate-vehicle collisions in Lithuania

Wildlife mortality caused by vehicles is a serious conservation and economic problem as collisions with large mammals are global, pervasive and increasing. We analysed 14,989 reports of ungulate-vehicle collisions (UVC) that occurred in Lithuania from 2002 to 2017. We analysed UVC data for four major ungulate species (roe deer, red deer, moose and wild boar) and checked for potential seasonal or daily trends. The temporal distribution of collisions was species-dependent. UVC analysis showed strong monthly and hourly pattern. Most occurrences took place before or during sunrise (dawn) and after or during sunset (dusk) during the year. In spring, the highest UVC peaks occurred early in the morning and late in the evening, while in winter these peaks occurred in late mornings and early evenings. With most UVC occurring on Fridays, daily variations were weak. We conclude that temporal variations of UVC distributions are result of a complex interaction of phenological factors and animal behaviour. The information provided in this study reinforces the knowledge on the dynamics and patterns of UVC and represents an important element for the identification of mitigation measures. Our findings suggest that efforts to reduce UVC should also focus on driver attitudes considering the seasonal and daily variations in UVC.

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.

Genetic Basis of Blood-Based Traits and Their Relationship With Performance and Environment in Beef Cattle at Weaning

The objectives of this study were to explore the usefulness of blood-based traits as indicators of health and performance in beef cattle at weaning and identify the genetic basis underlying the different blood parameters obtained from complete blood counts (CBCs). Disease costs represent one of the main factors determining profitability in animal production. Previous research has observed associations between blood cell counts and an animal’s health status in some species. CBC were recorded from approximately 570 Angus based, crossbred beef calves at weaning born between 2015 and 2016 and raised on toxic or novel tall fescue. The calves (N = ∼600) were genotyped at a density of 50k SNPs and the genotypes (N = 1160) were imputed to a density of 270k SNPs. Genetic parameters were estimated for 15 blood and 4 production. Finally, with the objective of identifying the genetic basis underlying the different blood-based traits, genome-wide association studies (GWAS) were performed for all traits. Heritability estimates ranged from 0.11 to 0.60, and generally weak phenotypic correlations and strong genetic correlations were observed among blood-based traits only. Genome-wide association study identified ninety-one 1-Mb windows that accounted for 0.5% or more of the estimated genetic variance for at least 1 trait with 21 windows overlapping across two or more traits (explaining more than 0.5% of estimated genetic variance for two or more traits). Five candidate genes have been identified in the most interesting overlapping regions related to blood-based traits. Overall, this study represents one of the first efforts represented in scientific literature to identify the genetic basis of blood cell traits in beef cattle. The results presented in this study allow us to conclude that: (1) blood-based traits have weak phenotypic correlations but strong genetic correlations among themselves. (2) Blood-based traits have moderate to high heritability. (3) There is evidence of an important overlap of genetic control among similar blood-based traits which will allow for their use in improvement programs in beef cattle.

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.

Roadkill mitigation is paved with good intentions: a critique of Fox et al. (2019)

In a recent publication, Fox et al. (2019) described a three-year trial of a ‘virtual fence’ installed to reduce wildlife roadkills in north-eastern Tasmania. The authors reported a 50% reduction in total roadkills, concluding that the ‘virtual fence’ had the potential to substantially reduce roadkill rates. The field of roadkill mitigation has a long history of promising techniques that are ultimately found wanting, so we evaluated the conceptual basis of the ‘virtual fence’ and the design and analysis of the trial. Of the two stimuli emitted by the ‘virtual fence’, its lights only partly match the sensory capabilities of the target species, its sound frequency is suitable but the intensity is unknown, and both stimuli are artificial and lack biological significance, so will be prone to habituation once novelty wanes. The trial, conducted in three phases, revealed a total of eight methodological flaws ranging from imprecise measurements, confounding effects of treatments, low statistical power, violation of test assumptions and failure to consider habituation. Greater caution is needed in interpreting the findings of this study, and well designed, long-term trials are required to properly assess the ‘virtual fence’.

Predicting deer–vehicle collision risk across Victoria, Australia

The risk of deer–vehicle collisions (DVCs) is increasing in south-east Australia as populations of introduced deer expand rapidly. There are no investigations of the spatial and temporal patterns of DVC or predictions of where such collisions are most likely to occur. Here, we use an analytical framework to model deer distribution and vehicle movements in order to predict DVC risk across the State of Victoria. We modelled the occurrence of deer using existing occurrence records and geographic climatic variables. We estimated patterns of vehicular movements from records of average annual daily traffic and speeds. Given the low number of DVCs reported in Victoria, we used a generalised linear regression model fitted to DVCs in California, USA. The fitted model coefficients suggested high collision risk on road segments with high predicted deer occurrence, moderate traffic volume and high traffic speed. We used the California deer model to predict collision risk on Victorian roads and validated the predictions with two independent datasets of DVC records from Victoria. The California deer model performed well when comparing predictions of collision risk to the independent DVC datasets and generated plausible DVC risk predictions across the State of Victoria.

Detectability and activity patterns of sambar deer (Rusa unicolor) in Baw Baw National Park, Victoria

Introduced sambar deer (Rusa unicolor) are increasing in abundance and distribution across much of south-eastern Australia and causing damage to native ecosystems. However, the current paucity of knowledge surrounding many aspects of sambar deer ecology is limiting our capacity to make informed management decisions, and properly gauge the extent of deer impacts. Here we investigate correlates of sambar deer detectability and describe activity patterns of sambar deer in Baw Baw National Park (BBNP) to inform control operations. Camera traps were deployed in BBNP between October and December 2016. We used an occupancy modelling framework to investigate sambar deer detectability and camera trap record time stamps to determine sambar deer activity patterns. Sambar deer were found to be significantly more detectable near roads and in areas of sparse tree density and displayed strong crepuscular activity patterns. Control operations carried out along roads at dawn and dusk could be effective, at least in the short term. Likewise, aerial culling could be an effective control option for sambar deer populations in BBNP. This study highlights the utility of camera trap data to inform the application of control operations for cryptic invasive species.

Differences in Spatiotemporal Patterns of Vehicle Collisions with Wildlife and Livestock

Road ecology research has tended to focus on wildlife-vehicle collisions (WVCs) while omitting or failing to differentiate domestic (i.e., livestock) animal-vehicle collisions (DAVCs). This has limited our understanding of where, when, and how frequently DAVCs occur, and whether these patterns differ from those for WVCs. We used a 10-year collision data set for the U.S. state of Montana to compare temporal and spatial patterns of DAVCs versus WVCs at multiple scales. WVCs exhibited two diel peaks (dawn and dusk) versus only one prominent peak (late evening/early night) for DAVCs. Seasonal patterns of WVCs and DAVCs were broadly similar, but DAVCs exhibited a more pronounced late-fall peak. At the county scale, DAVCs were overrepresented relative to WVCs in most of eastern Montana and underrepresented in most of western Montana. WVC and DAVC hotpots did not show strong overlap at the 1-mile road segment scale. Our results suggest that DAVCs warrant greater attention, and they may represent a high priority for management and mitigation measures in some areas because (1) they can be locally common even when regionally rare, (2) they are more dangerous to motorists on a per-collision basis than WVCs, and (3) they can present a legal liability for livestock owners. Mitigation measures for DAVCs may differ from those for WVCs and require further development and testing. Future data collection efforts should include information not only on the location and timing of animal-vehicle collisions, but also on the species of animals killed.

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.

Home range size, vegetation density, and season influences prey use by coyotes (Canis latrans)

To ensure reproductive success, Canis species establish contiguous mosaics of territories in suitable habitats to partition space and defend limiting resources. Consequently, Canis species can exert strong effects on prey populations locally because of their year-round maintenance of territories. We assessed prey use by coyotes (Canis latrans) by sampling scats from within known territories in southeastern Alabama and the Savannah River area of Georgia and South Carolina. We accounted for the size and habitat composition of coyote home ranges to investigate the influence of space use, vegetation density, and habitat type on coyote diets. Coyote use of prey was influenced by a combination of mean monthly temperature, home range size, vegetation density, and hardwood forests. For example, coyote use of adult white-tailed deer (Odocoileus virginianus) was associated with cooler months and smaller home ranges, whereas use of rabbits (Sylvilagus spp.) was associated with cooler months, larger home ranges, and less vegetation density. Coyotes in our study relied primarily on nutritionally superior mammalian prey and supplemented their diet with fruit when available, as their use of mammalian prey did not appreciably decrease with increasing use of fruit. We suggest that differential use of prey by coyotes is influenced by habitat heterogeneity within their home ranges, and prey-switching behaviors may stabilize local interactions between coyotes and their food resources to permit stable year-round territories. Given that habitat composition affects coyote prey use, future studies should also incorporate effects of habitat composition on coyote distribution and abundance to further identify coyote influences on prey communities.

Dogs are the main species involved in animal-vehicle collisions in southern Spain: Daily, seasonal and spatial analyses of collisions

Animal-vehicle collisions have become a serious traffic safety issue. Collisions have steadily increased over the last few decades, as have their associated socio-economic costs. Here, we explore the spatial and temporal patterns of animal-vehicle collisions reported to authorities in the province of Seville, southern Spain. Most animal-vehicle collisions involved domestic animals (>95%), particularly dogs (>80%), a pattern that sharply contrasts with that found in other Spanish and European regions, where collisions are mostly caused by game species. Dog-vehicle collisions were related to the traffic intensity of the roads and they were more frequent around dawn and dusk, coinciding with the peaks of activity of dogs. This pattern was consistent throughout the week, although on weekends there were fewer collisions due to lower traffic density at those times. These findings suggest that the aggregation of dog-vehicle collisions around twilight likely resulted from a combined effect of the activity peaks of dogs and traffic density. Seasonally, collisions increased in autumn and winter, coinciding with the period of intense hunting activity in the region. Further, during autumn and winter, rush hour partly overlaps with twilight due to longer nights in comparison with summer and spring, which may contribute to the increased rate of dog-vehicle collisions in these seasons. Spatially, satellite images of nighttime lights showed that dog-vehicle collisions were clustered near urban areas. Overall, the high incidence of stray dogs involved in animal-vehicle collisions highlights a road safety issue with this type of animals in the region.

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.

Seasonal and individual variation in the use of rail-associated food attractants by grizzly bears (Ursus arctos) in a national park

Similar to vehicles on roadways, trains frequently kill wildlife via collisions along railways. Despite the prevalence of this mortality worldwide, little is known about the relative importance of wildlife attractants associated with railways, including spilled agricultural products, enhanced vegetation, invertebrates, and carcasses of rail-killed ungulates. We assessed the relative importance of several railway attractants to a provincially-threatened population of grizzly bears (Ursus arctos) in Banff and Yoho National Parks, Canada, for which rail-caused mortality has increased in recent decades without known cause. We examined the relationship between the use of the railway and diet by fitting 21 grizzly bears with GPS collars in 2011-2013 and measuring the stable isotope values (δ15N, δ34S) derived from their hair. We also examined the importance of rail-associated foods to grizzly bears by analyzing 230 grizzly bear scats collected from May through October in 2012-2014, some of which could be attributed to GPS-collared bears. Among the 21 collared bears, 17 used the rail rarely (<9% of the days they were monitored), and only four bears (which included the three smallest bears and the largest bear in our sample) used the rail frequently (>20% of their monitored days). We found no significant relationships between δ15N and δ34S values measured from the hair of grizzlies and their frequency of rail use. Instead, δ15N increased with body mass, especially for male bears, suggesting large males consumed more animal protein during hair growth. All four bears that used the railway frequently produced scats containing grain. Almost half the scats (43%) collected within 150 m of the railway contained grain compared to only 7% of scats found >150 m from the railway. Scats deposited near the rail were also more likely to contain grain in the fall (85% of scats) compared to summer (14%) and spring (17%), and those containing grain were more diverse in their contents (6.8 ± 2.2 species vs. 4.9 ± 1.6, P < 0.001). Lastly, scats collected near the rail were more likely to contain ungulate hair and ant remains, especially in the summer. Our results support local management knowledge that some bears in the region use the railway to forage and supplement their diets with spilled grain, but that individual use of the railway and associated foods were highly variable. We suggest that managers continue to reduce the risk of bears being killed by trains by reactively removing grain and ungulate carcasses from the railway, reducing the amount of grain spilled by trains, and target mitigation to the specific individuals and locations that attract recurrent rail-based foraging.

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.