Habitat Suitability Based Models for Ungulate Roadkill Prognosis

Roads do not only have a detrimental effect on nature (fragmenting habitats, isolating populations and threatening biodiversity), but the increasing numbers of wildlife-vehicle collisions are also a direct threat to humans and property. Therefore, mitigation measures should be placed with respect to animal distribution and movements across the roads. We simulated red deer, roe deer and wild boar movements in Lithuania, focusing on the two main highways A1 and A2. Using regional habitat suitability and linkage models, we calculated movement pathways and the most probable crossing zones in 2009. The prognostic value of these models was tested by comparing the pathway predictions to the real roadkill and roadkill cluster locations in 2002–2009 and 2010–2017. Across both periods and on both highways, the roe deer roadkill locations were significantly closer to the model-predicted pathways than to randomly selected points. The prediction of roadkill locations was also good for wild boar. The roe deer roadkill clusters and multi-species clusters were significantly better represented by the model than by random distribution. On both highways, the biggest differences in distance from the predicted locations were near big cities. We recommended wildlife movement models as an additional tool for planning wildlife-vehicle collision mitigation measures and we advise measures for increasing their predicting power.

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Comparison of environmental, biological and anthropogenic causes of wildlife–vehicle collisions among three large herbivore species

10.1101/385161 ◽

2018 ◽

Author(s):

Saint-Andrieux Christine ◽

Calenge Clément ◽

Bonenfant Christophe

Keyword(s):

Wild Boar ◽

Red Deer ◽

Roe Deer ◽

Management Unit ◽

Mitigation Measures ◽

Road Density ◽

Forest Patches ◽

Large Herbivore ◽

Vehicle Collisions ◽

Explanatory Factors

AbstractWildlife–vehicle collisions are of increasing concern with regards to the continuous and accelerating anthropogenic development. Preventing and mitigating collisions with wildlife will require a better understanding of the environmental and biological drivers of collision risks. Because species of large mammals differ in terms of food requirements, habitat selection and movement behaviours we tested at the management unit level if the density of collisions with red deer, roe deer and wild boar differed in terms of spatial distribution and explanatory factors. From 20,275 documented collisions in France between years 1990 and 2006, we found marked differences in the most influential environmental factors accounting for the density of collisions among the three species. The effect of road density was higher for the red deer than for the two other species and did not level off at our spatial-scale of observation. As expected, the annual hunting harvest – interpreted as a proxy of population abundance – was positively associated with the density of collisions for all species, being the strongest for red deer. While the collision density decreased with the proportion of forest in a management unit for wild boar, it increased with the fragmentation of forests for red deer that commute among forest patches between day and night. To reduce the number of wildlife– vehicle collisions, our results suggest to generalise road fencing and/or a control of abundance of large herbivore populations. Mitigation measures should target units where the collision risk is the highest for the most problematic species.

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

Wildlife Research ◽

10.1071/wr14060 ◽

2015 ◽

Vol 42 (1) ◽

pp. 25 ◽

Cited By ~ 8

Author(s):

Enrique Valero ◽

Juan Picos ◽

Laura Lagos ◽

Xana Álvarez

Keyword(s):

Roe Deer ◽

Multiple Logistic Regression Analysis ◽

Hierarchical Cluster ◽

Mitigation Measures ◽

Curvature Radius ◽

Nearest Neighbour ◽

Continuous Variables ◽

Hotspot Analysis ◽

Vehicle Collisions ◽

The Road

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.

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Roadkill in a time of pandemic: the analysis of wildlife-vehicle collisions reveals the differential impact of COVID-19 lockdown over mammal assemblages

10.32942/osf.io/p3zft ◽

2021 ◽

Author(s):

Boštjan Pokorny ◽

Jacopo Cerri ◽

Elena Bužan

Keyword(s):

Wild Boar ◽

Large Scale ◽

Time Series Data ◽

Roe Deer ◽

Biological Significance ◽

Additive Models ◽

Series Data ◽

Vehicle Collisions ◽

Related Mortality

Collisions with vehicles are a major anthropogenic cause of mortality for wildlife, with conservation and evolutionary implications. Due to the COVID-19 pandemic, many countries worldwide enforced lockdowns which importantly reduced traffic, and therefore had unprecedented consequences for global wildlife populations. We modeled how the two lockdown periods in spring and autumn 2020 influenced wildlife-vehicle collisions in Slovenia (central Europe), by comparing long-term (for the period 2010–2020) and high-quality time series data on road mortality of seven mammalian species: European roe deer (n = 53,259),red fox (n = 9,889), European badger (n = 5,170), brown hare (n = 5,050), stone marten (n = 4,267), wild boar (n = 1,188), and red deer (n = 1,088). We decomposed 2010–2019 data through autoregressive Bayesian Generalized Additive Models, and then we compared 2020 data to forecasts, aiming to estimate anomalies in number of collisions during both lockdown periods. During the spring lockdown (16 March – 30 April 2020), we observed far less collisions than in the 2010–2019 average as well as in 2020 forecasts, for roe deer and badger. In the autumnal lockdown (20 October – 31 December 2020), we observed significantly less collisions for roe deer and wild boar. Traffic reduction in both lockdown periods had a major impact on roe deer, which in autumn and spring 2020 experienced 270–330 less road-related mortality cases than expected. COVID-19 lockdown reduced traffic-related mortality for the majority of studied species. In some species, this decrease reached a magnitude of biological significance, which can have long-term repercussions on both evolution and management. Obviously, large-scale sanitary policies, imposing a reduction to human mobility, can have large-scale impacts on wildlife. As pandemics may increase in the next decades, we encourage further research exploring the consequences of their enforcement over global change and wildlife conservation and evolution.

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Temporal Patterns of Vehicle Collisions with Roe Deer and Wild Boar in the Dinaric Area

Croatian journal of forest engineering ◽

10.5552/crojfe.2020.789 ◽

2020 ◽

Vol 41 (2) ◽

pp. 347-358 ◽

Cited By ~ 1

Author(s):

Joso Vrkljan ◽

Dubravka Hozjan ◽

Danijela Barić ◽

Damir Ugarković ◽

Krešimir Krapinec

Keyword(s):

Wild Boar ◽

Animal Species ◽

Temporal Dynamics ◽

Roe Deer ◽

Brown Bear ◽

Temporal Patterns ◽

Time Of Day ◽

Lunar Phase ◽

Large Species ◽

Vehicle Collisions

The purpose of this study was to determine the frequency of wildlife-vehicle collisions (WVC) based on the animal species, and to deepen the knowledge of temporal patterns of vehicle collisions with roe deer and wild boar. The study analyses the data from police reports on vehicle collisions with animals on state roads, by date and time, section of road, and animal species over a 5-year period (2012–2016). These data were analysed to determine the temporal dynamics of vehicle collisions with roe deer and wild boar by month, time of day, and moon phase. On the state roads in the Dinaric area, roe deer are most commonly involved in vehicle collisions (70.1% of all collisions), followed by wild boar (11.0%). Other large species involved in collisions were fallow deer (4.8%), brown bear (1.8%), red deer (0.9%), grey wolf (0.7%), and European mouflon (0.5%), respectively. Most collisions with roe deer occurred in the period April–August, with reduced frequency during autumn and winter. For wild boar, there was no association between month and frequency of collisions. At the annual level, collisions with roe deer were significantly higher during night (37%) and twilight (41%) than during the day (22%). For wild boar, most collisions occurred during twilight (26%) and night (72%), although the difference between these two periods was not statistically significant. For roe deer, collisions had no association with lunar phase, though wild boar collisions during twilight (dawn or dusk) were more common during twilight periods on days with less moonlight. Since vehicle collisions with wildlife showed certain temporal patterns, these should be taken into consideration in developing statistical models of spatial WVC patterns, and also in planning strategies and countermeasures to mitigate WVC issues.

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

Accident Analysis & Prevention ◽

10.1016/j.aap.2013.07.032 ◽

2013 ◽

Vol 60 ◽

pp. 121-133 ◽

Cited By ~ 29

Author(s):

Beatriz Rodríguez-Morales ◽

Emilio Rafael Díaz-Varela ◽

Manuel Francisco Marey-Pérez

Keyword(s):

Wild Boar ◽

Roe Deer ◽

Spatiotemporal Analysis ◽

Nw Spain ◽

Vehicle Collisions

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

Wildlife Research ◽

10.1071/wr14060_co ◽

2015 ◽

Vol 42 (8) ◽

pp. 717

Author(s):

Enrique Valero ◽

Juan Picos ◽

Laura Lagos ◽

Xana Álvarez

Keyword(s):

Roe Deer ◽

Multiple Logistic Regression Analysis ◽

Hierarchical Cluster ◽

Mitigation Measures ◽

Curvature Radius ◽

Nearest Neighbour ◽

Continuous Variables ◽

Hotspot Analysis ◽

Vehicle Collisions ◽

The Road

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 ?2-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.

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Roadkill-Data-Based Identification and Ranking of Mammal Habitats

Land ◽

10.3390/land10050477 ◽

2021 ◽

Vol 10 (5) ◽

pp. 477

Author(s):

Andrius Kučas ◽

Linas Balčiauskas

Keyword(s):

Species Richness ◽

Land Cover ◽

Decision Support Techniques ◽

Mitigation Measures ◽

Spatial Decision Support ◽

Vehicle Collisions ◽

Vehicle Collision ◽

Ecological Corridor ◽

As Species ◽

The Relationship

Wildlife–vehicle collisions, as well as environmental factors that affect collisions and mitigation measures, are usually modelled and analysed in the vicinity of or within roads, while habitat attractiveness to wildlife along with risk to drivers remain mostly underestimated. The main goal of this study was the identification, characterisation, and ranking of mammalian habitats in Lithuania in relation to 2002–2017 roadkill data. We identified habitat patches as areas (varying from 1 to 1488 square kilometres) isolated by neighbouring roads characterised by at least one wildlife–vehicle collision hotspot. We ranked all identified habitats on the basis of land cover, the presence of an ecological corridor, a mammalian pathway, and roadkill hotspot data. A ranking scenario describing both habitat attractiveness to wildlife and the risk to drivers was defined and applied. Ranks for each habitat were calculated using multiple criteria spatial decision support techniques. Multiple regression analyses were used to identify the relationship between habitat ranks, species richness, and land cover classes. Strong relationships were identified and are discussed between the habitat patch ranks in five (out of 28) land cover classes and in eight (out of 28) species (97% of all mammal road kills). We conclude that, along with conventional roadkill hotspot identification, roadkill-based habitat identification and characterisation as well as species richness analysis should be used in road safety infrastructure planning.

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Influence of new irrigated croplands on wild boar (Sus scrofa) road kills in NW Spain

Animal Biodiversity and Conservation ◽

10.32800/abc.2012.35.0247 ◽

2012 ◽

Vol 35 (2) ◽

pp. 247-252 ◽

Cited By ~ 1

Author(s):

V. J. Colino–Rabanal, ◽

◽

J. Bosch ◽

Mª J. Muñoz ◽

S. J. Peris ◽

...

Keyword(s):

Wild Boar ◽

Sus Scrofa ◽

Forest Cover ◽

Population Expansion ◽

Mitigation Measures ◽

Nw Spain ◽

Vehicle Collisions ◽

Explanatory Variables ◽

Traffic Volumes ◽

Spatio Temporal

In recent decades, wild boar populations have increased both in number and distribution. This rise is partly related to the increase in cropland devoted to maize (Zea mays) cultivation, as wild boar find food and refuge in these areas. This population expansion has led to an increase in the number of wild boar vehicle collisions (WBVCs). The goal of the present study was to evaluate a set of spatio–temporal factors that influence WBVCs related to maize crops on the Northern Spanish Plateau (the region of Castile and Leon). We compared the maize pattern with the factors related to total WBVC numbers. We observed that whereas the total occurrence of WBVCs usually increased with forest cover and speed and traffic volumes, maize areas were one of the main explanatory variables in plateau models. To avoid collisions in these areas in future, a number of mitigation measures are outlined.

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Impact of Road Fencing on Ungulate–Vehicle Collisions and Hotspot Patterns

Land ◽

10.3390/land10040338 ◽

2021 ◽

Vol 10 (4) ◽

pp. 338

Author(s):

Andrius Kučas ◽

Linas Balčiauskas

Keyword(s):

Traffic Accidents ◽

Road Traffic ◽

Mitigation Measures ◽

Traffic Intensity ◽

Road Traffic Accidents ◽

Annual Average ◽

Vehicle Collisions ◽

Vehicle Collision ◽

Annual Average Daily Traffic ◽

The Relationship

The number of road traffic accidents decreased in Lithuania from 2002 to 2017, while the ungulate–vehicle collision (UVC) number increased and accounted for approximately 69% of all wildlife–vehicle collisions (WVC) in the country. Understanding the relationship between UVCs, traffic intensity, and implemented mitigation measures is important for the assessment of UVC mitigation measure efficiency. We assessed the effect of annual average daily traffic (AADT) and wildlife fencing on UVCs using regression analysis of changes in annual UVCs and UVC hotspots on different categories of roads. At the highest rates, annual UVC numbers and UVC hotspots increased on lower category (national and regional) roads, forming a denser network. Lower rates of UVC increase occurred on higher category (main) roads, forming sparser road networks and characterized by the highest AADT. Before 2011, both UVC occurrence and fenced road sections were most common on higher-category roads. However, as of 2011, the majority of UVCs occurred on lower-category roads where AADT and fencing had no impact on UVCs. We conclude that wildlife fencing on roads characterized by higher speed and traffic intensity may decrease UVC numbers and at the same time shifting UVC occurrence towards roads characterized by lower speed and traffic intensity. Wildlife fencing re-allocates wildlife movement pathways toward roads with insufficient or no mitigation measures.

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Impact of Road Fencing on Ungulate-Vehicle Collisions and Hotspot Patterns

10.21203/rs.3.rs-47591/v1 ◽

2020 ◽

Author(s):

Andrius Kučas ◽

Linas Balčiauskas

Keyword(s):

Road Network ◽

Traffic Accidents ◽

Road Traffic ◽

Mitigation Measures ◽

Traffic Intensity ◽

Road Traffic Accidents ◽

Annual Average ◽

Vehicle Collisions ◽

Vehicle Collision ◽

Annual Average Daily Traffic

Abstract Background:The number of road traffic accidents was decreasing in Lithuania in 2002–2017, while ungulate-vehicle collision (UVC) number was increasing and accounted for about 69% of all wildlife-vehicle collisions (WVC) in the country. Identification of impact of locomotor wildlife behavior and locations where accidents occurs most frequently is important for the effective application of mitigation measures.Methods:We assessed the effect of annual average daily traffic (AADT) and wildlife fencing on UVC using regression analysis of changes in annual UVC and UVC hotspots (KDE+ method based clusters) for different categories of roads.Results:At the greatest rates annual UVC numbers and UVC hotspots increased on lower category (national and regional) roads forming denser network. Lower rates of UVC increase occurred on higher category (main) roads, forming sparser road network and characterised by highest AADT. Before 2011, both UVC occurrence and fenced road sections were most common on higher category roads. However, as of 2011, the majority of UVC occurred on lower category roads where AADT and fencing had no impact on UVC.Conclusions:We conclude that wildlife fencing on roads characterised by higher speed and traffic intensity may decrease UVC numbers, in the same time shifting UVC occurrence towards roads characterised by lower speed and traffic intensity. Wildlife fencing re-allocates wildlife movement pathways towards roads with insufficient or no mitigation measures.

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