Road crashes involving animals in Australia

As human societies urbanize, so does ecology; taxonomic, geographic, and other research trends in urban vertebrate ecology

The threat to biodiversity posed by urban expansion is well researched and supported. Since the late 1990s, the field of urban ecology has been expanding along with the developed landscapes it studies. Past reviews have shown unequal publication rates in urban ecology literature for taxonomic groups and research locations. Herein, we explore differences in the publication rate of urban studies by vertebrate groups, but also expand on previous investigations by broadening the scope of the literature searched, exploring trends in subtopics within the urban wildlife literature, identifying geographic patterns of such publications, and comparing the rate at which non-native and threatened and endangered species are studied in urban settings. We used linear and segmented regression to assess publication rates and Fisher's exact tests for comparisons between groups. All vertebrate groups show an increasing proportion of urban studies through time, with urban avian studies accelerating most sharply and herpetofauna appearing to be understudied. Non-native mammals are more studied than non-native birds, and threatened and endangered herpetofauna and mammals are more likely to be studied than threatened and endangered birds in urban areas. The plurality of urban wildlife studies are found in North America, while there is a dearth of studies from Africa, Asia, and South America. Our results can help inform decisions of urban ecologists on how to better fill in knowledge gaps and bring a greater degree of equity into the field.

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.

Using Self-Organizing Maps to find spatial relationships between wildlife-vehicle crashes and land use classes

The construction and expansion of roads cause significant impacts on the environment. The main potential impacts to biotic environment are vegetation suppression, reduction of the amount and composition of animal distribution due to forest fragmentation and increasing risks of animal (domestic and wildlife) vehicle collisions. The objective of this work was to establish a relationship between the different spatial patterns in wildlife-vehicle crash, by using spatial analysis and machine learning tools. Self-Organizing Maps (SOM), an artificial neural network (ANN), was selected to reorganize the multi-dimensional data according to the similarity between them. The results of the spatial pattern analysis were important to perceive that the point data pattern varies from an animal type to another. The events occur spatially clustered and are not uniformly distributed along the highway. SOM was able to analyze the relationship between multiple variables, linear and non-linear, such as ecological data, and established distinct spatial patterns per each animal type. In the studied area, most of the wildlife was run over very close to forest area and water bodies, and not so close to sugarcane fields, forestry and built environment. A considerable part of the wildlife-vehicle collisions occurred in areas with diverse landscape.

Characteristics of kangaroo-related motor vehicle crashes

BACKGROUND

Kangaroo-related motor vehicle collisions are common but there is limited literature on this topic. Drivers confronted by kangaroos may choose to swerve or to directly collide with the kangaroo. The effect of these differing crash mechanisms, along with the effect of vehicle type or time of day, has not yet been reported.

METHODS

A retrospective cohort study was performed, examining patients admitted to our tertiary trauma centre for kangaroo-related motor vehicle collisions between 2000 and 2020. Data on patient demographics, crash characteristics, and hospital stay were collected and analysed.

RESULTS

A total of 366 patients were included and were predominantly male (76%) with an median age of 40. Swerve crashes were more common (59%) than direct impact and swerving was a statistically significant predictor of reduced injury severity score on multivariable analysis (other significant factors were female sex and no rollover). Motor vehicle crashes and motorbike crashes had differing crash characteristics. Motor vehicle crashes were more likely the result of swerving, and swerving was less likely to cause ejection or require extrication but more likely to cause rollover. Motorbike crashes however, were more likely the result of head on collision and riders were more likely to be ejected from the vehicle, require extrication, or be involved in a rollover. In terms of time of day, there were more crashes at dawn and there was a trend towards higher injury severity score and length of stay for night-time crashes.

CONCLUSION

For kangaroo-related motor vehicle crashes, predictors of increased injury severity score on multivariable analysis were male sex, direct impact, and rollover. Motorbikes and motor vehicles had differing crash mechanisms and characteristics, as did night-time crashes when compared to daytime or twilight crashes.

LEVEL OF EVIDENCE

IV, prognostic.

Identification of roadkill hotspots and the factors affecting wombat vehicle collisions using the citizen science tool, WomSAT

Roads directly impact wildlife through vehicle collisions. In Australia only a few studies have examined the impact of environmental characteristics on wombat roadkill. We analysed wombat roadkills reported into WomSAT, a website and application where citizen scientists can upload sightings of wombats, to map wombat roadkill across their distribution. We used Maxent software to identify the main factors influencing wombat roadkill hotspots. A total of 2391 wombat deaths on roads were reported by 567 citizen scientists from 2015 to 2019. More wombat roadkill deaths occurred in winter, with most unaffected by sarcoptic mange. The average daily solar exposure, distance to populated areas, precipitation of warmest quarter (bio 18), temperature seasonality (bio 4), and precipitation seasonality (bio 15) were identified as the main factors influencing wombat roadkill. The most roadkills reported per kilometre (3.7/km) occurred on Old Bega Road and Steeple Flat Road, in the New South Wales southern tablelands. Reduced reporting corresponded with a reduced number of citizen scientists continuing to report sightings over time, reflecting the limitations of the data collected by citizen scientists. However, data should continue to be collected by citizen scientists as it is an easy and low-cost method of collecting data over large areas, and can provide information to managers to support conservation efforts directed at reducing roadkill. Our study emphasises the need to continue to engage and reward citizen scientists for their efforts.

Intelligent Systems Using Sensors and/or Machine Learning to Mitigate Wildlife-Vehicle Collisions: A Review, Challenges, and New Perspectives

Worldwide, the persistent trend of human and animal life losses, as well as damage to properties due to wildlife-vehicle collisions (WVCs) remains a significant source of concerns for a broad range of stakeholders. To mitigate their occurrences and impact, many approaches are being adopted, with varying successes. Because of their increased versatility and increasing efficiency, Artificial Intelligence-based methods have been experiencing a significant level of adoption. The present work extensively reviews the literature on intelligent systems incorporating sensor technologies and/or machine learning methods to mitigate WVCs. Included in our review is an investigation of key factors contributing to human-wildlife conflicts, as well as a discussion of dominant state-of-the-art datasets used in the mitigation of WVCs. Our study combines a systematic review with bibliometric analysis. We find that most animal detection systems (excluding autonomous vehicles) are relying neither on state-of-the-art datasets nor on recent breakthrough machine learning approaches. We, therefore, argue that the use of the latest datasets and machine learning techniques will minimize false detection and improve model performance. In addition, the present work covers a comprehensive list of associated challenges ranging from failure to detect hotspot areas to limitations in training datasets. Future research directions identified include the design and development of algorithms for real-time animal detection systems. The latter provides a rationale for the applicability of our proposed solutions, for which we designed a continuous product development lifecycle to determine their feasibility.

Travel-weary to travel-worry: the epidemiology of injury-related traveller deaths in Australia, 2006-2017

OBJECTIVE

To explore injury deaths in international and domestic interstate travellers, together with those newly arrived to Australia.

METHODS

A population-based cohort study of all injury-related deaths between 1January 2006 and 31 December 2017 registered with Births Death and Marriages in Australia was conducted using Australian Bureau of Statistics' (ABS) Cause of Death information. Population data on travellers were obtained from Tourism Research Australia.

RESULTS

There were 4,503 injury-related traveller deaths (domestic interstate:3,055; international:934; new arrivals:514). The average annual age-standardised mortality rates in domestic interstate travellers was 0.75 per 100,000, compared with 2.22 per 100,000 in international travellers. Leading causes of injury-related death were land transport incidents (n=1495, 33.2%), self-harm (n=786, 17.5%) and falls (n=513, 11.4%), with differences in mechanism by state/territory, traveller type and age group. Intentional self-harm was common amongst all visitor types, however, it was the primary cause of death in new arrivals Conclusion: Age-standardised mortality rates were almost three-fold higher in international than domestic travellers. New arrivals, international and domestic travellers have different injury profiles, and each require specific prevention strategies.

IMPLICATIONS FOR PUBLIC HEALTH

While COVID has restricted travel to and within Australia, this has provided an opportunity for exploration, reflection, and consideration of risk factors for travellers, and to develop targeted injury prevention strategies for visitor types, so travel experience can be optimised and the magnitude of harm can be reduced.

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.

Classification of road traffic injury collision characteristics using text mining analysis: Implications for road injury prevention

Road traffic injuries are a leading cause of morbidity and mortality globally. Understanding circumstances leading to road traffic injury is crucial to improve road safety, and implement countermeasures to reduce the incidence and severity of road trauma. We aimed to characterise crash characteristics of road traffic collisions in Victoria, Australia, and to examine the relationship between crash characteristics and fault attribution. Data were extracted from the Victorian State Trauma Registry for motor vehicle drivers, motorcyclists, pedal cyclists and pedestrians with a no-fault compensation claim, aged > = 16 years and injured 2010-2016. People with intentional injury, serious head injury, no compensation claim/missing injury event description or who died < = 12-months post-injury were excluded, resulting in a sample of 2,486. Text mining of the injury event using QDA Miner and Wordstat was used to classify crash circumstances for each road user group. Crashes in which no other was at fault included circumstances involving lost control or avoiding a hazard, mechanical failure or medical conditions. Collisions in which another was predominantly at fault occurred at intersections with another vehicle entering from an adjacent direction, and head-on collisions. Crashes with higher prevalence of unknown fault included multi-vehicle collisions, pedal cyclists injured in rear-end collisions, and pedestrians hit while crossing the road or navigating slow traffic areas. We discuss several methods to promote road safety and to reduce the incidence and severity of road traffic injuries. Our recommendations take into consideration the incidence and impact of road trauma for different types of road users, and include engineering and infrastructure controls through to interventions targeting or accommodating human behaviour.

Vehicle fatalities involving collisions with kangaroos

A search was undertaken of the Forensic Science South Australia (FSSA), Australia, autopsy database over a 20-year period from 2000 to 2019 for all cases where vehicle crashes had involved kangaroos. There were six cases with an age range of 18-62 years (M=42 years) and a male-to-female ratio of 5:1. There were three crashes involving motor vehicles and three involving motorcycles. The three motor-vehicle crashes were initiated by impact with a kangaroo followed by a head-on crash with a truck (n=1) and a tree (n=2). In two of the motorcycle crashes, the cycle hit a kangaroo, resulting in the rider being unseated. In the third case, following impact with the animal, the cyclist hit a tree. In one of the latter cases, the only evidence of impact with a kangaroo was fur found by investigating officers adherent to the front-right indicator. Lethal injuries were located in the chest in six cases, the cranio-cervical region in five cases and the abdomen in three cases. Thus, in the majority of cases (n=5), death was due to multiple injuries. In the remaining case, death was caused by blunt chest trauma. This study shows that kangaroo-vehicle impacts may result in very significant blunt-force trauma. Motorcycle riders are particularly vulnerable. It may be only by careful examination of the vehicle/motorcycle for animal residues that the nature of the incident will be clarified.

Investigating the injury severity of single-vehicle truck crashes in a developing country

Trucking plays a vital role in economic development in every country, especially countries where it serves as the backbone of the economy. The fast growth of economy in Iran as a developing country has also been accompanied by an alarming situation in terms of fatalities in truck-involved crashes, among the drivers and passengers of the trucks as well as the other vehicles involved. Despite the sizable efforts to investigate the truck-involved crashes, very little is known about the safety of truck movements in developing countries, and about the single-truck crashes worldwide. Thus, this study aims to uncover significant factors associated with injury severities sustained by truck drivers in single-vehicle truck crashes in Iran. The explanatory factors tested in the models include the characteristics of drivers, vehicles, and roadways. A random threshold random parameters hierarchical ordered probit model is utilized to consider heterogeneity across observations. Several variables turned out to be significant in the model, including driver's education, advanced braking system deployment, presence of curves on roadways, and high speed-limit. Using those results, we propose safety countermeasures in three categories of 1) educational, 2) technological, and 3) road engineering to mitigate the severity of single-vehicle truck crashes.

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.

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.

Patterns and composition of medium and large vertebrate roadkill, based on six annual surveys along two adjoining highways in south-eastern Queensland, Australia

Six annual single-pass roadkill surveys along two adjoining rural Queensland highways near Carnarvon Gorge National Park revealed 612 medium-size to large vertebrates, representing more than 18 taxa. Most were mammals (92%), particularly macropods. Losses averaged 0.26 animals km–1 year–1 (range = 0.17–0.33), with variation possibly reflecting road repair/reconstruction and record seasonal rainfalls. Annual roadkill totals for the 390-km highway were projected to be over 5000 vertebrates, with more than half being large macropods. A consistent hotspot or ecological trap was noted along a 17-km high-traffic-volume stretch north of Roma. Because the sparsely populated outback is habitat for much Australian wildlife, multiyear baseline data are vital to identify the magnitude of the problem and inform future research.

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.

Animal-vehicle collisions in Victoria, Australia: An under-recognised cause of road traffic crashes

OBJECTIVE

Non-fatal injuries sustained from animal-vehicle collisions are a globally under-recognised road safety issue, with limited data on these crash types. The present study aimed to quantify the number and causes of major trauma events resulting from animal-vehicle collisions.

METHODS

The study was a retrospective analysis of major trauma cases occurring in Victoria, Australia, between 2007 and 2016, using data from the population-based Victorian State Trauma Registry. To identify animal-vehicle collisions, Victorian State Trauma Registry injury codes were combined with text-mining of the text description of the injury event.

RESULTS

Over the 10 year period, there were 152 major trauma patients who were admitted to Victorian trauma-receiving hospitals due to vehicle collisions with animals. The crude population-based incidence rate for animal-vehicle collisions increased by 6.7% per year (incidence rate ratio 1.07; 95% confidence interval 1.01-1.13; P = 0.02).

CONCLUSION

Development of systematic recording methods of animal-vehicle collisions will improve reporting of these crash types to assist future studies in implementing effective countermeasures.

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.

Canadian wildlife-vehicle collisions: An examination of knowledge and behavior for collision prevention

OBJECTIVES

This study examines drivers' responses to wildlife on Canadian roads. The objective of this paper is to demonstrate that knowledge of what to do when encountering wildlife on the road does not always translate into the appropriate behavior to avoid a collision.

METHODS

Data from the Traffic Injury Research Foundation's (TIRF) 2016 Road Safety Monitor (RSM) and data from TIRF's National Fatality Database from 2000 to 2014 were analyzed to test hypotheses based on the theory of planned behavior. Logistic regression and piecewise linear regression were used.

RESULTS

Analyses of the data showed that the prevalence of fatal WVCs has remained relatively consistent, and that the majority of persons killed in WVCs died in crashes that involved large mammals. The majority of fatalities occurred in the summer (182 or 38.4%) and fall (163 or 34.4%). The RSM data revealed that 60.9% [50.5, 70.4] of respondents who previously hit an animal indicated that drivers should slow down and steer straight when confronted with wildlife, while 47.3% [37.1, 57.6] of respondents indicated this was the action they took when they hit wildlife. Comparatively, 59.5% [56.6, 62.4] of respondent who have not hit an animal indicated this was an appropriate response. Additionally, 33.2% [24, 44] of respondents who previously hit an animal indicated that drivers should swerve to avoid a collision with wildlife, while 37.5% [28.2, 47.8] of respondents indicated this was the action they took when they hit wildlife.

CONCLUSIONS

Many drivers are unaware of what the safest method of WVC prevention is. Further, while a subgroup of drivers may have the knowledge and intention to slow down and steer straight even if the animal is directly in the path, i.e., the safest possible behavior, they are not necessarily adopting this behavior. Practical applications: Recommendations are formulated to address this discrepancy, as well as practical applications.

A Copula-Based Approach for Accommodating the Underreporting Effect in Wildlife‒Vehicle Crash Analysis

Wildlife‒vehicle collision (WVC) data usually contain two types: the reported WVC data and carcass removal data. Previous studies often found a discrepancy between the number of reported WVC and carcass removal data, and the quality of both datasets is affected by underreporting. Underreporting means the number of WVCs is not fully recorded in the database; neglecting the underreporting in WVC data may result in biased parameter estimation results. In this study, a copula regression model linking wildlife‒vehicle collisions and the underreporting outcome was proposed to consider the underreporting in WVC data. The WVC data collected from 10 highways in Washington State were analyzed using the copula regression model and the Negative Binomial (NB) model. The main findings from this study are as follows: (1) the Gaussian copula model can provide different modeling results when compared with the conventional modeling approach; (2) the hotspot identification results indicate that the Gaussian copula-based Empirical Bayes (EB) method can more accurately identify hotspots than the NB-based EB method. Thus, the proposed copula model may be a better alternative to the conventional NB model for modeling underreported WVC data.

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.

Dash Cam videos on YouTube™ offer insights into factors related to moose-vehicle collisions

To gain a better understanding of the dynamics of moose-vehicle collisions, we analyzed 96 videos of moose-vehicle interactions recorded by vehicle dash-mounted cameras (Dash Cams) that had been posted to the video-sharing website YouTube™. Our objective was to determine the effects of road conditions, season and weather, moose behavior, and driver response to actual collisions compared to near misses when the collision was avoided. We identified 11 variables that were consistently observable in each video and that we hypothesized would help to explain a collision or near miss. The most parsimonious logistic regression model contained variables for number of moose, sight time, vehicle slows, and vehicle swerves (AIC_cw = 0.529). This model had good predictive accuracy (AUC = 0.860, SE = 0.041). The only statistically significant variable from this model that explained the difference between moose-vehicle collisions and near misses was 'Vehicle slows'. Our results provide no evidence that road surface conditions (dry, wet, ice or snow), roadside habitat type (forested or cleared), the extent to which roadside vegetation was cleared, natural light conditions (overcast, clear, twilight, dark), season (winter, spring and summer, fall), the presence of oncoming traffic, or the direction from which the moose entered the roadway had any influence on whether a motorist collided with a moose. Dash Cam videos posted to YouTube™ provide a unique source of data for road safety planners trying to understand what happens in the moments just before a moose-vehicle collision and how those factors may differ from moose-vehicle encounters that do not result in a collision.

Consistent patterns of vehicle collision risk for six mammal species

The occurrence and rate of wildlife-vehicle collisions are related to both anthropocentric and environmental variables, however, few studies compare collision risks for multiple species within a model framework that is adaptable and transferable. Our research compares collision risk for multiple species across a large geographic area using a conceptually simple risk framework. We used six species of native terrestrial mammal often involved with wildlife-vehicle collisions in south-east Australia. We related collisions reported to a wildlife organisation to the co-occurrence of each species and a threatening process (presence and movement of road vehicles). For each species, we constructed statistical models from wildlife atlas data to predict occurrence across geographic space. Traffic volume and speed on road segments (also modelled) characterised the magnitude of threatening processes. The species occurrence models made plausible spatial predictions. Each model reduced the unexplained variation in patterns and distributions of species between 29.5% (black wallaby) and 34.3% (koala). The collision models reduced the unexplained variation in collision event data between 7.4% (koala) and 19.4% (common ringtail possum) with predictor variables correlating similarly with collision risk across species. Road authorities and environmental managers need simple and flexible tools to inform projects. Our model framework is useful for directing mitigation efforts (e.g. on road effects or species presence), predicting risk across differing spatial and temporal scales and target species, inferring patterns of threat, and identifying areas warranting additional data collection, analysis, and study.

Daylight saving time can decrease the frequency of wildlife-vehicle collisions

Daylight saving time (DST) could reduce collisions with wildlife by changing the timing of commuter traffic relative to the behaviour of nocturnal animals. To test this idea, we tracked wild koalas (Phascolarctos cinereus) in southeast Queensland, where koalas have declined by 80% in the last 20 years, and compared their movements with traffic patterns along roads where they are often killed. Using a simple model, we found that DST could decrease collisions with koalas by 8% on weekdays and 11% at weekends, simply by shifting the timing of traffic relative to darkness. Wildlife conservation and road safety should become part of the debate on DST.

Western grey kangaroos (Macropus fuliginosus) include fauna underpasses in their home range

Context The presence of large mammals on roads poses a serious risk to both the animals and motorists if collisions with vehicles occur. Fencing roads can reduce this risk, and it also limits the landscape-scale movements of animals. By also constructing fauna underpasses it may be possible to avoid collisions with vehicles, while, at the same time, allowing the natural movement of animals across the landscape. Aims We aimed to determine whether western grey kangaroos (Macropus fulignosus) would use fauna underpasses and to determine how this may affect their home range. Methods We used motion-activated infrared cameras to monitor the use of one large 8 × 3 m arched underpass and two 0.9-m-diameter fauna underpasses over 342 days between March 2011 and March 2012. The underpasses were situated between reserves separated by a four-lane fenced highway, with one reserve surrounded by residential properties. At the same time, 20 kangaroos (10 males and 10 females) were radio-tracked to determine the size of their home range and to test whether the animals incorporated the fauna underpasses into their daily movements. Key results The large fauna underpass was used 3116 times by individual kangaroos in groups of up to 21 animals, whereas the two smaller underpasses were used only twice. In total, 14 of the 20 radio-collared kangaroos used the large underpass over the course of the study, but underpass use did not affect home-range size. Kangaroos that did not use the underpass had a significantly higher proportion of their home range on residential properties surrounding one of the reserves than did those kangaroos that used the underpass. Conclusions The use of the underpass did not affect the size of the home range of the kangaroos, but it allowed the kangaroos to access grazing areas that would have been otherwise inaccessible. Fauna underpasses allow the safe passage of kangaroos between isolated remnant vegetation patches and may reduce significantly the risks posed to motorists and kangaroos from collisions. Implications Fencing roads and constructing fauna underpasses is a viable solution to reducing some of the problems of managing large kangaroos in peri-urban areas.

What's the Big Deal? Responder Experiences of Large Animal Rescue in Australia

Background: The management of large animals during disasters and emergencies creates difficult operational environments for responders. The aims of this study were to identify the exact challenges faced by Australian emergency response personnel in their interactions with large animals and their owners, and to determine the readiness for large animal rescue (LAR) in Australia. Methods: A survey tool collected the views and experiences of a broad cross section of emergency services personnel operating across Australia and across all hazards. Data were collected from 156 responders including Australian emergency services personnel, emergency managers such as federal agricultural departments, and local government. Results: Overall, many of the respondents had serious concerns, and felt that there were significant issues in relation to LAR in Australia. These included the coordination of emergency care for animals, physical management of large animals, inter-agency coordination, and dealing with animal owners. Very few respondents had received any formal training in LAR, with an overwhelming majority indicating they would attend formal training if it were made available. Discussion: Results help to guide the development of evidence-informed support tools to assist operational response and community engagement, and the production of professional development resources.

Road and traffic factors correlated to wildlife–vehicle collisions in Galicia (Spain)

Context Wildlife–vehicle collisions (WVC) are one of the major risk factors for the safety of drivers, as well as a great danger to wildlife that moves through the territory. In recent decades, given the growth of these accidents, some researches emerged to understand what are the main causes of this phenomenon and find the best solutions for implementation and try to solve this problem. Aims The aim of the present study was to analyse the road and traffic characteristics of road segments with a high occurrence of WVC in north-western Spain, specifically, the collisions with wild ungulates (roe deer and wild boar). Methods A nearest-neighbour analysis was used to analyse the spatial distribution of the WVC spots, and so as to identify these hotspots of accidents, we performed a hotspot analysis using the routine nearest-neighbour hierarchical cluster. Then, we calculated the WVC density of each road segment (KP). The existence of differences in the values of variables between high and low accident densities was analysed using a Mann–Whitney U-test for the continuous variables, and a χ2-test for the categorical ones. Then, multiple logistic regression analysis was used to identify which variables could predict the existence of KPs with a high density of WVC. Key results Our results showed that the daily traffic volume, the width of the road, the number of lanes and speed limit affect whether a particular road marker has a high or low density of WVC. Conclusions We conclude that high WVC is frequently characterised by wider lanes and shoulders, as well as gentler slopes, whereas in the sections with narrower roads and a shorter curvature radius, there are some conditions (low visibility and speed reduction) that reduce the probability of having an accident with ungulates. However, the speed at which it is possible to drive on a given road section is closely related to the occurrence of WVC. Implications These findings emphasise the importance of including mitigation measures in the decision-making when planning and designing infrastructure.

Human–wildlife interactions in urban areas: a review of conflicts, benefits and opportunities

Wildlife has existed in urban areas since records began. However, the discipline of urban ecology is relatively new and one that is undergoing rapid growth. All wildlife in urban areas will interact with humans to some degree. With rates of urbanisation increasing globally, there is a pressing need to understand the type and nature of human–wildlife interactions within urban environments, to help manage, mitigate or even promote these interactions. Much research attention has focussed on the core topic of human–wildlife conflict. This inherent bias in the literature is probably driven by the ease with which it can be quantified and assessed. Human–wildlife conflicts in terms of disease transmission, physical attack and property damage are important topics to understand. Equally, the benefits of human–wildlife interactions are becoming increasingly recognised, despite being harder to quantify and generalise. Wildlife may contribute to the provision of ecosystem services in urban areas, and some recent work has shown how interactions with wildlife can provide a range of benefits to health and wellbeing. More research is needed to improve understanding in this area, requiring wildlife biologists to work with other disciplines including economics, public health, sociology, ethics, psychology and planning. There will always be a need to control wildlife populations in certain urban situations to reduce human–wildlife conflict. However, in an increasingly urbanised and resource-constrained world, we need to learn how to manage the risks from wildlife in new ways, and to understand how to maximise the diverse benefits that living with wildlife can bring.

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

The increasing number of deer-vehicle-accidents (DVAs) and the resulting economic costs have promoted numerous studies on behavioural and environmental factors which may contribute to the quantity, spatiotemporal distribution and characteristics of DVAs. Contrary to the spatial pattern of DVAs, data of their temporal pattern is scarce and difficult to obtain because of insufficient accuracy in available datasets, missing standardization in data aquisition, legal terms and low reporting rates to authorities. Literature of deer-traffic collisions on roads and railways is reviewed to examine current understanding of DVA temporal trends. Seasonal, diurnal and lunar peak accident periods are identified for deer, although seasonal pattern are not consistent among and within species or regions and data on effects of lunar cycles on DVAs is almost non-existent. Cluster analysis of seasonal DVA data shows nine distinct clusters of different seasonal DVA pattern for cervid species within the reviewed literature. Studies analyzing the relationship between time-related traffic predictors and DVAs yield mixed results. Despite the seasonal dissimilarity, diurnal DVA pattern are comparatively constant in deer, resulting in pronounced DVA peaks during the hours of dusk and dawn frequently described as bimodal crepuscular pattern. Behavioural aspects in activity seem to have the highest impact in DVAs temporal trends. Differences and variations are related to habitat-, climatic- and traffic characteristics as well as effects of predation, hunting and disturbance. Knowledge of detailed temporal DVA pattern is essential for prevention management as well as for the application and evaluation of mitigation measures.

Neighborhood and postal worker characteristics associated with dog bites in postal workers of the Brazilian National Postal Service in Curitiba

Dog bites are the third most common cause of absenteeism among postal workers of the Brazilian National Postal Service in Southern Brazil, with an average off-work time of approximately two days for each biting episode. The objective of this study was to evaluate the neighborhood characteristics involving dog bites that occurred during work time in postal workers, its impact on work and consequent preventive alternatives. A descriptive and analytical cross-sectional study was designed for all Curitiba postal workers. Data were descriptively analyzed and the hypothesis of correlation between median monthly income, population density and occurrence of dog bites was tested. A total of 34.9% of the postal workers answered the questionnaire and 64.6% of them had been bitten while working. The odds of bites occurring in a neighborhood increase by 1.035 times for every increase in one unit in the population density and decrease by 0.998 times for every increase of US$ 1.00 in the neighborhood median monthly income of the head of the family. The occurrence of dog bites among postal workers in Curitiba is related to income and population density and prevention strategies should address mailbox position and adequate fencing to provide protection for postal workers.

Roads and macropods: interactions and implications

Understanding the impacts of roads on wildlife and the natural environment is of increasing importance. Macropods (mostly kangaroos and wallabies) are a diverse and widespread taxon in Australia that has been significantly affected by the presence of roads in various ways. We reviewed the available literature on macropods and roads, assessing 60 scientific journal articles, reports and theses. Studies on road mortalities were the most prevalent (n = 29, with 12 on macropods only), revealing both spatial and temporal patterns in occurrence. Behavioural studies in relation to the road environment are limited (n = 2) yet could help our understanding of patterns of road-kill and other impacts. Some macropod populations are critically affected by the presence of roads (e.g. brush-tailed rock-wallaby, Petrogale penicillata) due to either proportionately high road mortalities and/or population fragmentation, and may face continued decline unless effective road-mitigation measures are implemented. Investigations of various types of road mitigation focussed on wildlife-exclusion fencing and road crossing structures as the most effective option, although the high cost of these measures appears to limit their implementation. Further research into several areas was identified, particularly on species where severe road impacts are likely to result in population declines.

Spatiotemporal analysis of vehicle collisions involving wild boar and roe deer in NW Spain

Ungulate-vehicle collisions pose a serious traffic safety hazard in the North of Spain. The understanding of underlying temporal and spatial structure of these non-random events is imperative to develop appropriate mitigation measures. This study analyses the temporal, spatial and spatiotemporal patterns of car crashes involving wild boar and roe deer in the province of Lugo (NW Spain) in the period 2006-2010 using geographic information systems (GIS) and spatial statistics. The temporal analysis--conducted at three scales: daily, weekly and seasonal--revealed that accidents are related to specific animal's life cycles and to interactions with human activities. The localization of collision points with GIS discovered the sections of the autonomic road network where accidents with the two studied species concentrate. Besides, the spatial arrangement of significant hotspots was mapped through kernel density estimation over two time scales (daily and seasonal), distinguishing among 41 sets, sequentially arranged to facilitate clustering comparison and determination of spatiotemporal risky areas. This work is of valuable help for road managers to design the appropriate mitigation measures that will improve traffic safety and animal welfare.

Nighttime driver detection distances for Tasmanian fauna: informing speed limits to reduce roadkill

Context. Roadkill is a wildlife management issue in areas where high traffic volume passes through relatively intact natural habitat. High density of roadkill in Tasmania is observed in concentrated ‘hotspots’, and local mitigation of vehicle speed may thus be an appropriate management response. Although warning signage is often advocated, this may not effectively reduce roadkill if the suggested speed does not provide sufficient time for the animal to be detected and for the vehicle to be stopped. Aims. The detection distance at night for common roadkill species and corresponding driving speeds to avoid collision were determined. The importance of animal size and fur colour in determining detection distance was also evaluated. Methods. Mounts of nine nocturnal Tasmanian mammal species were used to determine nighttime driver detection distances based on individual driver trials. These were converted to appropriate stopping speeds by accounting for reaction time and braking distance. Photographs and digital image analysis were used to evaluate fur brightness. Key results. A total of 339 individual detection distances for the 9 species were recorded for 18 drivers. Detection distance differed between the species tested at both high- and low-beam headlight settings. The endangered Tasmanian devil (Sarcophilus harrisii) had the shortest mean detection distance when headlights were on high beam (60.8 m), and the second shortest on low beam (33.9 m), which corresponded to a driving speed which would permit a safe stop of 54 km h–1 and 38 km h–1, respectively. The greatest detection distance was for the introduced hare (Lepus europaeus): 116 m (83 km h–1) and 50.4 m (48 km h–1), respectively. Conclusions. Nighttime driving speeds slower than 80 km h–1 may be effective in reducing roadkill in wildlife hotspots. Detection distance was significantly related to fur brightness, as determined by image analysis, and not animal size. Implications. The variation in detection distance allows species-specific nighttime driving speeds to be considered by individual drivers and by road and wildlife managers planning mitigation efforts for vulnerable species.