Interchange as the main factor determining wildlife–vehicle collision hotspots on the fenced highways: spatial analysis and applications

Cserkész, Tamás; Ottlecz, Barnabás; Cserkész‐Nagy, Ágnes; Fárkas, J.

doi:10.1007/s10344-013-0710-2

Cited by 45 publications

(36 citation statements)

References 31 publications

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“…During these last years many studies have brought up results on WVC for numerous countries, e.g. Spain (Colino-Rabanal et al 2012;Diaz-Varela et al 2011;Lagos et al 2012;Rodríguez-Morales et al 2013), Hungary (Cserkész et al 2013;Markolt et al 2012), Sweden (Neumann et al 2012), Poland (Tajchman et al 2010), USA (Danks and Porter 2010), Ireland (Haigh 2012).…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal patterns of wildlife-vehicle collisions in a region with a high-density road network

Мorelle¹,

Lehaire²,

Lejeune³

2013

114

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This paper is the first to report data on wildlife-vehicle collisions (WVC) in Wallonia, southern Belgium, characterised by one of the densest road network worldwide. With the collaboration of police we identified 3965 accidents involving "free ranging animal" between 2003 and 2011. We observed that these accidents with free ranging animals result in 13% of cases in injuries for the drivers or passengers, and in less than 1% of cases in fatalities (death). 78% of these casualties involve wild animals, among which wild boar take the largest part (39%). During the covered period we observed an annual increase of WVC of 21%. For wild boar and red deer, this increase was significantly correlated with hunting statistics, used as an index of population density. The temporal analysis demonstrated an increase of WVC during night time with peak of accidents at dusk and dawn. Monthly distribution revealed the role of breeding, dispersal and hunting in shaping temporal patterns of accidents. Spatial analysis, focusing on wild boar, roe deer, red deer and red fox demonstrated clustering of accidents for all these species, until scale between 20 to 70 km. Mapping of accidents via Kernel density analysis permitted us to highlight areas with high risk of WVC risk. Our study suggests that the problem of car accidents due to wildlife is an increasing concern in Wallonia but results on spatial and temporal patterns should help for setting up mitigation measures in the most sensible areas. Moreover we suggest that police data source should be used for nationwide analysis and for comparison between countries.

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Section: Introductionmentioning

confidence: 99%

Spatio-temporal patterns of wildlife-vehicle collisions in a region with a high-density road network

Мorelle¹,

Lehaire²,

Lejeune³

2013

114

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show abstract

“…We considered that mortality hotspots were absent if the number of roadkills per segment was always lower than the upper Poisson confidence limit. Malo's hotspot identification method was used because it seems to perform better than other common methods of hotspot identification (Cserk esz et al, 2013;Gomes et al, 2009), and it allows easy comparison between sampling schedules because hotspots are identified within a fixed spatial scale (500-m segments).…”

Section: Identification Of Roadkill Hotspotsmentioning

confidence: 99%

Sampling effects on the identification of roadkill hotspots: Implications for survey design

Santos

Marques

Lourenço

et al. 2015

Journal of Environmental Management

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a b s t r a c tAlthough locating wildlife roadkill hotspots is essential to mitigate road impacts, the influence of study design on hotspot identification remains uncertain. We evaluated how sampling frequency affects the accuracy of hotspot identification, using a dataset of vertebrate roadkills (n ¼ 4427) recorded over a year of daily surveys along 37 km of roads. "True" hotspots were identified using this baseline dataset, as the 500-m segments where the number of road-killed vertebrates exceeded the upper 95% confidence limit of the mean, assuming a Poisson distribution of road-kills per segment. "Estimated" hotspots were identified likewise, using datasets representing progressively lower sampling frequencies, which were produced by extracting data from the baseline dataset at appropriate time intervals (1e30 days). Overall, 24.3% of segments were "true" hotspots, concentrating 40.4% of roadkills. For different groups, "true" hotspots accounted from 6.8% (bats) to 29.7% (small birds) of road segments, concentrating from <40% (frogs and toads, snakes) to >60% (lizards, lagomorphs, carnivores) of roadkills. Spatial congruence between "true" and "estimated" hotspots declined rapidly with increasing time interval between surveys, due primarily to increasing false negatives (i.e., missing "true" hotspots). There were also false positives (i.e., wrong "estimated" hotspots), particularly at low sampling frequencies. Spatial accuracy decay with increasing time interval between surveys was higher for smaller-bodied (amphibians, reptiles, small birds, small mammals) than for larger-bodied species (birds of prey, hedgehogs, lagomorphs, carnivores). Results suggest that widely used surveys at weekly or longer intervals may produce poor estimates of roadkill hotspots, particularly for small-bodied species. Surveying daily or at two-day intervals may be required to achieve high accuracy in hotspot identification for multiple species.

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“…Furthermore, static wildlife warning signs are often implemented in the operation and maintenance phase. Fences are generally considered to reduce AVCs with 75-80% [18][19][20], but animals sometimes manage to enter the road area despite fencing [21], and the effectiveness may also depend on the length of the road section [22]. Furthermore, when gaps are present in the wildlife fence, e.g.…”

Section: Introductionmentioning

confidence: 99%

Speed reduction effects over distance of animal-vehicle collision countermeasures – a driving simulator study

Jägerbrand

Antonson

Ahlström

2018

Eur. Transp. Res. Rev.

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Purpose: This study examined if speed reduction effects from animal-vehicle collision (AVC) countermeasures are merely local or do extend to a wider area, and what implications the results have on road planning practice regarding AVCs. Methods: Twenty-five drivers drove repeatedly on a 9-km long road stretch in a high-fidelity driving simulator. The development of vehicle speed in the surrounding of an automatic speed camera, a wildlife warning sign and a radio message, were investigated in a full factorial within-subject experiment. The factors wildlife fence (with/without) and forest (dense/open landscape) were also included. Results: The radio warning message had the largest influence on vehicle speed with a speed reduction of 8 km/h that lasted beyond 1 km and 2 km after the implementation. Eighty-eight per cent of the drivers reported being made extra aware of AVC due to the radio message, which was also associated with stress, insecurity and unsafety. The warning sign reduced vehicle speed by 1.5 km/h, but speed reductions were not significantly reduced 1 km after the implementation. Only 8 % of the drivers felt insecure/unsafe after passing the wildlife warning sign, explaining its limited impact on speed. There were no main effects of the automatic speed camera on vehicle speed at longer distances after implementation. Conclusions: We recommend that AVC countermeasures should be of various design, occur at various segments along the road, and preferably be adaptive and geo-localized to minimize habituation effects on drivers.

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Interchange as the main factor determining wildlife–vehicle collision hotspots on the fenced highways: spatial analysis and applications

Cited by 45 publications

References 31 publications

Spatio-temporal patterns of wildlife-vehicle collisions in a region with a high-density road network

Spatio-temporal patterns of wildlife-vehicle collisions in a region with a high-density road network

Sampling effects on the identification of roadkill hotspots: Implications for survey design

Speed reduction effects over distance of animal-vehicle collision countermeasures – a driving simulator study

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