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

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

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

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.

Factors promoting hunting groups' sustainable harvest of moose in a co-management system

Collaboration between and within management levels and involvement of local communities (co-management) increases sustainable management of natural resources. In Finland, moose (Alces alces) are harvested by hunting groups within a co-management system, providing meat and social benefits. We computed the 14-year change in moose harvest (2007-2020) for 4320 hunting groups. Moose harvest declined on average 1.1% per year, but with substantial variation in moose harvest changes between the hunting groups. We extracted information describing the collaboration between the hunting groups, their democratic status as well as leader dynamics, and the year of establishment. A hunting group's moose harvest was more stable (i.e. declined less) when the hunting group was (1) established a longer time ago; (2), had more changes in leadership over time, but did not depend on collaboration with other local hunting groups (in terms of jointly holding moose hunting licenses), whether the hunting group was a registered society (presumed to be more democratic than a non-registered one) or had consecutive leaders that shared a surname (presumed to be related). We conclude that encouraging resource users' early establishment in groups and groups' long-term persistence and promoting democratic leadership roles improves stable benefits from a natural resource in a co-management system.

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.

Calf/female ratio and population dynamics of wild forest reindeer in relation to wolf and moose abundances in a managed European ecosystem

BACKGROUND

The alternative prey hypothesis describes the mechanism for apparent competition whereby the mortality of the secondary prey species increases (and population size decreases decreases) by the increased predation by the shared predator if the population size of the primary prey decreases. Apparent competition is a process where the abundance of two co-existing prey species are negatively associated because they share a mutual predator, which negatively affects the abundance of both prey Here, we examined whether alternative prey and/or apparent competition hypothesis can explain the population dynamics and reproductive output of the secondary prey, wild forest reindeer (Rangifer tarandus fennicus) in Finland, in a predator-prey community in which moose (Alces alces) is the primary prey and the wolf (Canis lupus) is the generalist predator.

METHODS

We examined a 22-year time series (1996-2017) to determine how the population size and the calf/female ratio of wild forest reindeer in Eastern Finland were related to the abundances of wolf and moose. Only moose population size was regulated by hunting. Summer predation of wolves on reindeer focuses on calves. We used least squares regression (GLS) models (for handling autocorrelated error structures and resulting pseudo-R2s) and generalized linear mixed (GLMs) models (for avoidance of negative predictions) to determine the relationships between abundances. We performed linear and general linear models for the calf/female ratio of reindeer.

RESULTS AND SYNTHESIS

The trends in reindeer population size and moose abundance were almost identical: an increase during the first years and then a decrease until the last years of our study period. Wolf population size in turn did not show long-term trends. Change in reindeer population size between consecutive winters was related positively to the calf/female ratio. The calf/female ratio was negatively related to wolf population size, but the reindeer population size was related to the wolf population only when moose abundance was entered as another independent variable. The wolf population was not related to moose abundance even though it is likely to consist the majority of the prey biomass. Because reindeer and moose populations were positively associated, our results seemed to support the alternative prey hypothesis more than the apparent competition hypothesis. However, these two hypotheses are not mutually exclusive and the primary mechanism is difficult to distinguish as the system is heavily managed by moose hunting. The recovery of wild forest reindeer in eastern Finland probably requires ecosystem management involving both habitat restoration and control of species abundances.

Temporal patterns of wildlife roadkill in the UK

Wildlife-vehicle collisions are one of the main causes of mortality for wild mammals and birds in the UK. Here, using a dataset of 54,000+ records collated by a citizen science roadkill recording scheme between 2014–2019, we analyse and present temporal patterns of wildlife roadkill of the 19 most commonly reported taxa in the UK (84% of all reported roadkill). Most taxa (13 out of 19) showed significant and consistent seasonal variations in road mortality and fitted one of two seasonal patterns; bimodal or unimodal: only three species (red fox Vulpes vulpes, European polecat Mustela putorius and Reeves’ muntjac deer Muntiacus reevesi) showed no significant seasonality. Species that increase movement in spring and autumn potentially have bimodal patterns in roadkill due to the increase in mate-searching and juvenile dispersal during these respective time periods (e.g. European badger Meles meles). Unimodal patterns likely represent increased mortality due to a single short pulse in activity associated with breeding (e.g. birds) or foraging (e.g. grey squirrels Sciurus carolinensis in autumn). Importantly, these patterns also indicate periods of increased risk for drivers, potentially posing a greater threat to human welfare. In addition to behaviour-driven annual patterns, abiotic factors (temperature and rainfall) explained some variance in roadkill. Notably, high rainfall was associated with decreased observations of two bird taxa (gulls and Eurasian magpies Pica pica) and European rabbit Oryctolagus cuniculus. By quantifying seasonal patterns in roadkill, we highlight a significant anthropogenic impact on wild species, which is important in relation to conservation, animal welfare, and human safety.

The declining occurrence of moose (Alces alces) at the southernmost edge of its range raise conservation concerns

The border region between Austria, the Czech Republic, and Germany harbors the most south-western occurrence of moose in continental Europe. The population originated in Poland, where moose survived, immigrated from former Soviet Union or were reintroduced after the Second World War expanded west- and southwards. In recent years, the distribution of the nonetheless small Central European population seems to have declined, necessitating an evaluation of its current status. In this study, existing datasets of moose observations from 1958 to 2019 collected in the three countries were combined to create a database totaling 771 records (observations and deaths). The database was then used to analyze the following: (a) changes in moose distribution, (b) the most important mortality factors, and (c) the availability of suitable habitat as determined using a maximum entropy approach. The results showed a progressive increase in the number of moose observations after 1958, with peaks in the 1990s and around 2010, followed by a relatively steep drop after 2013. Mortality within the moose population was mostly due to human interactions, including 13 deadly wildlife-vehicle collisions, particularly on minor roads, and four animals that were either legally culled or poached. Our habitat model suggested that higher altitudes (ca. 700-1,000 m a.s.l.), especially those offering wetlands, broad-leaved forests and natural grasslands, are the preferred habitats of moose whereas steep slopes and areas of human activity are avoided. The habitat model also revealed the availability of large core areas of suitable habitat beyond the current distribution, suggesting that habitat was not the limiting factor explaining the moose distribution in the study area. Our findings call for immediate transboundary conservation measures to sustain the moose population, such as those aimed at preventing wildlife-vehicle collisions and illegal killings. Infrastructure planning and development activities must take into account the habitat requirements of moose.

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

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

The effect of wildlife carcass underreporting on KDE+ hotspots identification and importance

Many approaches have been developed in order to mitigate wildlife-vehicle collisions (WVC), their causes and consequences. Reliable data on the amount and location of killed animals along roads are therefore necessary. The existing WVC databases are usually, however, far from complete. This data underreporting causes problems when identifying the riskiest places along a transportation infrastructure. WVC data underreporting can distort the results of WVC hotspots determination. In this work, we simulated WVC hotspots identification and stability under various rates of WVC data underreporting. Our aim was to investigate whether WVC hotspots can be found at the original locations even when data are strongly underreported. We applied the KDE + method for WVC hotspots identification. The KDE + method also allows for hotspots ranking according to cluster strength and collective risk. These two measures were then used for detection of diminishing hotspot signals with a rising level of underreporting. We found that WVC hotspots with a greater cluster strength suffered less from underreporting whereas hotspots will lower values of both cluster strength and collective risk were not detected when underreporting in the data increased. Hotspots with a cluster strength above 0.5 were almost always detected when data underreporting remained below 50%. More than 50% of these hotspots (with cluster strength above 0.5) were detectable even when underreporting rate was between 50 and 80%. We further studied the effects of both spatial and temporal underreporting. Whereas temporal change of underreporting was not a problem in hotspots detection, spatial underreporting introduced significant errors producing both false positive and false negative results (hotspots). We conclude that both researchers and practitioners should be aware of the phenomenon of underreporting and should also try to maintain the same sampling effort of spatial reporting.

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.

Testing bat abundance and diversity predictions by PREBAT, a connectivity-based habitat suitability model for insectivorous bats

Where large landscape modifications are planned, e.g. for infrastructure or exploitation, ecological impact assessments are required because of their potential effects on environment and species. Methods that make such assessments more standardized, efficient, and reliable are highly desirable. This paper proposes a new connectivity-based habitat model for bats (PREBAT), which could be used as a tool for impact assessments. Using data that was specifically collected for this purpose, the performance of PREBAT is critically analyzed and discussed. For this study, 50 sites within an area of 850 km2 in eastern Sweden were inventoried for four nights each using automatic ultrasound recorders to get an empiric measure of bat occurrence that could be compared with PREBAT predictions. The correlation between the predicted values from PREBAT and the observed bat activity (number of recordings) or species richness was tested using generalized linear mixed models. Predicted values of PREBAT are significantly correlated to the number of species that regularly (more than one night) occur at a given site, but not to the total number of species. PREBAT performed also much better at predicting the activity of forest-living species than overall bat activity, which makes PREBAT particularly suitable for predicting conflicts for those species. This study proposes a new habitat model for bats that takes spatial connectivity between habitat patches into account. PREBAT is shown to perform satisfyingly and has the potential to become a useful tool in assessing the ecological impact of large-scale landscape modifications.

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.

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.

Moose-Motor Vehicle Collision: A Continuing Hazard in Northern New England

BACKGROUND

Moose-motor vehicle collisions (MMVC) are especially dangerous to vehicle occupants because of the height and mass of the animal, which often collapses the roof and has a direct impact into the passenger compartment.

STUDY DESIGN

Public data on MMVC were obtained from the states of New England (NE), and trauma registry data from centers in NH and ME.

RESULTS

For all of NE, the annual incidence of reported MMVC has declined from a peak of >1,200 in 1998, but has still averaged >500 over the last 5 years, predominantly in ME, NH, and VT. Public education may have contributed to the decline, but the moose population has also apparently decreased due to environmental changes. In NE, MMVCs are most frequent in the summer months and evening hours. Maine data on crashes involving wild ungulates from 2003 to 2017 document 50,281 collisions with deer and 7,061 collisions with moose; 26 of the latter (0.37%) resulted in a human fatality. Logistic regression models demonstrate that vehicle occupant mortality, after controlling for multiple factors related to vehicle speed, is greatly increased when striking a moose rather than a deer (odds ratio [OR] 13.4, 95% CI 6.3, 28.7). In these data, there were no fatalities among occupants of Swedish cars, which are specifically engineered to tolerate MMVC. Three NH/ME trauma centers registered 124 cases of MMVC: median Injury Severity Score was 9; 5 patients died (4%); and 76 patients (61%) had injuries of the head, face, and/or cervical spine.

CONCLUSIONS

Moose-motor vehicle collisions remain a frequent and serious hazard to motor vehicle occupants in northern NE. Trauma services should recognize characteristic injury patterns. Continuing public education, cautious driving, and moose herd management are warranted.

Consequences of Increases in Wild Boar-Vehicle Accidents 2003–2016 in Sweden on Personal Injuries and Costs

This study examined whether the rising trends of wild boar (Sus scrofa)-vehicle accidents in Sweden are accompanied by a higher amount of personal injuries and costs. Temporal trends in accident frequencies and the number of persons injured in wild boar-vehicle accidents were examined for 2003–2016, and the cost of wild boar-vehicle accidents was calculated. Results show increases in the number of personal injuries, and increased costs, particularly after 2010–2012. The total number of wild boar accidents correlated with the number of injured persons as well as with the number of accidents with personal injuries. Approximately one person (1.13%) is injured per 100 wild boar-vehicle accidents, and approximately one accident per 200 wild boar-vehicle accidents will result in one or more persons with injuries (0.5%). However, most of the persons injured have slighter injuries. Although the number of wild boar-vehicle accidents and the number of persons injured in the accidents have increased, the frequency of accidents resulting in personal injuries is still at low levels in comparison with, for example, frequencies of personal injuries for moose accidents. The cost for wild boar-vehicle accidents has increased between 2003 to 2016 and is currently estimated to vary between approximately EUR 9.66–12.31 million per year.

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.