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Article ; Online: An effect of canopy bridges on monkey-vehicle collision hotspots: Spatial and spatiotemporal analyses.

Cunneyworth, Pamela M K / Andrášik, Richard / Bíl, Michal

2023 Volume 85, Issue 6, Page(s) e23492

Abstract: Almost one-quarter of primate species are reported to be involved in vehicle collisions. To mitigate these collisions, canopy bridges are used though their effectiveness is not broadly substantiated. We studied bridge impact on 23 years of vehicle ... ...

Abstract	Almost one-quarter of primate species are reported to be involved in vehicle collisions. To mitigate these collisions, canopy bridges are used though their effectiveness is not broadly substantiated. We studied bridge impact on 23 years of vehicle collisions (2000-2022: N = 765) with colobus (Colobus angolensis palliatus), Sykes' (Cercopithecus mitis albogularis), and vervet (Chlorocebus pygerythrus hilgerti) monkeys in Diani, Kenya. Along a 9 km road, collisions did not decrease over the study duration, although bridges increased from 8 to 30. Using the kernel density estimation plus (KDE+) method, collisions appeared highly concentrated at some locations. These concentrations, called hotspots, represent hazardous road segments, though the hotspots for all three species overlapped for only 3% of the road length. We then inspected the collision hotspots over time, using the spatiotemporal extension of the KDE+ method. We compared hotspot presence in the 3 years before and after bridge installation to determine if bridges mitigated these hotspots. Hotspots disappeared for ~60% of bridges postinstallation, suggesting that bridges effectively reduce some collisions. However, of the bridges installed in locations that were not hotspots, 13% had hotspots emerge. Surprisingly, regardless of preinstallation hotspot occurrence, almost one-fifth of bridges had postinstallation hotspots. To understand the extent to which bridges mitigate collisions, other factors need consideration, including species attributes and crossing behavior, and road features and vehicle volume. We used the novel analytical method because it best suited our data set, given the challenges of determining the bridge impact zone and the low collision frequency.
MeSH term(s)	Animals ; Chlorocebus aethiops ; Haplorhini ; Colobus ; Primates ; Spatio-Temporal Analysis ; Spatial Analysis ; Accidents, Traffic
Language	English
Publishing date	2023-04-13
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1495834-X
ISSN	1098-2345 ; 0275-2565
ISSN (online)	1098-2345
ISSN	0275-2565
DOI	10.1002/ajp.23492
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Wildlife-vehicle collisions: The disproportionate risk of injury faced by motorcyclists.

Bíl, Michal / Andrášik, Richard / Bílová, Martina

Injury

2023 Volume 55, Issue 5, Page(s) 111301

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Animals ; Animals, Wild ; Accidents, Traffic ; Deer ; Seat Belts ; Motor Vehicles ; Wounds and Injuries
Language	English
Publishing date	2023-12-24
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	218778-4
ISSN	1879-0267 ; 0020-1383
ISSN (online)	1879-0267
ISSN	0020-1383
DOI	10.1016/j.injury.2023.111301
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The effect of wildlife carcass underreporting on KDE+ hotspots identification and importance.

Bíl, Michal / Andrášik, Richard

Journal of environmental management

2020 Volume 275, Page(s) 111254

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Accidents, Traffic ; Animals ; Animals, Wild ; Databases, Factual ; Transportation
Language	English
Publishing date	2020-08-22
Publishing country	England
Document type	Journal Article
ZDB-ID	184882-3
ISSN	1095-8630 ; 0301-4797
ISSN (online)	1095-8630
ISSN	0301-4797
DOI	10.1016/j.jenvman.2020.111254
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Article: The effect of wildlife carcass underreporting on KDE+ hotspots identification and importance

Bíl, Michal / Andrášik, Richard

Journal of environmental management. 2020 Dec. 01, v. 275

2020

Abstract	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.
Keywords	environmental management ; risk ; temporal variation ; wildlife
Language	English
Dates of publication	2020-1201
Publishing place	Elsevier Ltd
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	184882-3
ISSN	1095-8630 ; 0301-4797
ISSN (online)	1095-8630
ISSN	0301-4797
DOI	10.1016/j.jenvman.2020.111254
Database	NAL-Catalogue (AGRICOLA)

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Article: Ungulate-vehicle collision risk and traffic volume on roads

Bíl, Michal / Kubeček, Jan / Andrášik, Richard

European journal of wildlife research. 2020 Aug., v. 66, no. 4

2020

Abstract: We analyzed data from traffic counters installed on 143 Czech roads (motorways and primary roads) which precisely indicated current traffic volume during occurrences of ungulate-vehicle collisions (UVC). One thousand nine hundred ninety-five UVCs were ... ...

Abstract	We analyzed data from traffic counters installed on 143 Czech roads (motorways and primary roads) which precisely indicated current traffic volume during occurrences of ungulate-vehicle collisions (UVC). One thousand nine hundred ninety-five UVCs were identified over the period 2009–2015 on these 143 road segments. The overall range of annual average daily traffic (AADT) values, for the respective roads, was between 1547 and 78,320 AADT (vehicles/day). Almost 80% of UVC took place at volume lower than 1000 vehicles/h. We demonstrate that traffic volume has a different distribution during the day when compared with UVC distribution. The highest relative risk of UVC was identified for traffic up to 750 vehicles/h. The risk of UVC varied over the course of the year as it was influenced by ungulate locomotory activity. We concluded that the AADT, representing average annual daily traffic, does not accurately represent the actual traffic volume which is present during the night hours, where the majority of UVC usually occur. Therefore, there is a danger that UVC risk modeling, relying on AADT, will be distorted.
Keywords	accidents ; counters ; data analysis ; highways ; human-wildlife relations ; models ; relative risk ; traffic ; ungulates
Language	English
Dates of publication	2020-08
Size	p. 59.
Publishing place	Springer Berlin Heidelberg
Document type	Article
ZDB-ID	2141660-6
ISSN	1439-0574 ; 1612-4642
ISSN (online)	1439-0574
ISSN	1612-4642
DOI	10.1007/s10344-020-01397-8
Database	NAL-Catalogue (AGRICOLA)

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Article: Spatial analysis of wildlife-train collisions on the Czech rail network

Nezval, Vojtěch / Bíl, Michal

Applied geography. 2020 Dec., v. 125

2020

Abstract: Wildlife-train collisions (WTCs), particularly those with large mammals, pose a threat to the safety and continuity of rail operations. In this study, we collected 1,909 WTCs which took place in the Czech Republic between 2011 and 2019, in order to ... ...

Abstract	Wildlife-train collisions (WTCs), particularly those with large mammals, pose a threat to the safety and continuity of rail operations. In this study, we collected 1,909 WTCs which took place in the Czech Republic between 2011 and 2019, in order to identify the most hazardous WTC locations and their spatial pattern. 208 WTC hotspots were identified using the KDE+ method. They contained 782 collisions (41.2%) and accounted for 0.7% of the Czech rail network length. We also identified and ranked the most important WTC hotspots using a collective risk parameter. WTCs occurred more frequently in the vicinity of a forest or stream and were more distant from arable land or urban/industrial areas than from other places on the entire Czech rail network. The results can help in placing crash-safety measures as a large proportion of accidents only occurred on less than 1% of the rail network.
Keywords	arable soils ; forests ; geography ; rail transportation ; risk ; streams ; Czech Republic
Language	English
Dates of publication	2020-12
Publishing place	Elsevier Ltd
Document type	Article
Note	NAL-AP-2-clean
ISSN	0143-6228
DOI	10.1016/j.apgeog.2020.102304
Database	NAL-Catalogue (AGRICOLA)

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Book ; Online: CHILDA − Czech Historical Landslide Database

Bíl, Michal / Raška, Pavel / Dolák, Lukáš / Kubeček, Jan

eISSN: 1684-9981

2021

Abstract: National and regional historical landslide databases are increasingly viewed as providing empirical evidence for the geomorphic effects of ongoing environmental change and for supporting adaptive territorial planning. In this work, we present the design ... ...

Abstract	National and regional historical landslide databases are increasingly viewed as providing empirical evidence for the geomorphic effects of ongoing environmental change and for supporting adaptive territorial planning. In this work, we present the design and current content of the Czech Historical Landslide Database (CHILDA), the first of its kind for the territory of Czechia (the Czech Republic). We outline the CHILDA system, its functionality and technical solution. The database was established by merging and extending the fragmented regional datasets for highly landslide prone areas in Czechia. Currently, the database includes 699 records (619 landslides, 75 rockfalls, and 5 other movement types) encompassing the period from the oldest determined records (1132) up to 1989 which represents an important cultural, political and socioeconomic divide. Along with characterizing the content of the database, we discuss its further developments and applications.
Subject code	940
Language	English
Publishing date	2021-04-14
Publishing country	de
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: On reliable identification of factors influencing wildlife-vehicle collisions along roads.

Bíl, Michal / Andrášik, Richard / Duľa, Martin / Sedoník, Jiří

Journal of environmental management

2019 Volume 237, Page(s) 297–304

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Accidents, Traffic ; Animals ; Animals, Wild ; Bayes Theorem ; Deer ; Swine ; Transportation
Language	English
Publishing date	2019-02-23
Publishing country	England
Document type	Journal Article
ZDB-ID	184882-3
ISSN	1095-8630 ; 0301-4797
ISSN (online)	1095-8630
ISSN	0301-4797
DOI	10.1016/j.jenvman.2019.02.076
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: A detailed spatiotemporal analysis of traffic crash hotspots

Bíl, Michal / Andrášik, Richard / Sedoník, Jiří

Applied geography. 2019 June, v. 107

2019

Abstract: A number of traffic crash databases at present contain the precise positions and dates of these events. This feature allows for detailed spatiotemporal analysis of traffic crash patterns.We applied a clustering method for identification of traffic crash ... ...

Abstract	A number of traffic crash databases at present contain the precise positions and dates of these events. This feature allows for detailed spatiotemporal analysis of traffic crash patterns.We applied a clustering method for identification of traffic crash hotspots to the rural parts of primary roads in the Czech road network (3,933 km) where 55,296 traffic crashes occurred over 2010 – 2018. The data were analyzed using a 3-year time window which moved forward with a one-day step as an elementary temporal resolution. The spatiotemporal behavior of hotspots could therefore be analyzed in great detail.All the identified hotspots, during the monitored nine-year period, covered between 6.8% and 8.2% of the entire road network length in question. The percentage of traffic crashes within the hotspots remained stable over time at approximately 50%. Three elementary types of hotspots were identified when analyzing spatiotemporal crash patterns: hotspot emergence, stability and disappearance. Only 100 hotspots were stable (remained in approximately the same position) over the entire nine-year period. This approach can be applied to any traffic-crash time series when the precise positions and date of crashes are available.
Keywords	accidents ; databases ; roads ; time series analysis ; traffic
Language	English
Dates of publication	2019-06
Size	p. 82-90.
Publishing place	Elsevier Ltd
Document type	Article
ISSN	0143-6228
DOI	10.1016/j.apgeog.2019.04.008
Database	NAL-Catalogue (AGRICOLA)

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Article: On reliable identification of factors influencing wildlife-vehicle collisions along roads

Bíl, Michal / Richard Andrášik / Martin Duľa / Jiří Sedoník

Journal of environmental management. 2019 May 01, v. 237

2019

Abstract	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.
Keywords	Bayesian theory ; Capreolus capreolus ; odds ratio ; regression analysis ; roads ; wild boars
Language	English
Dates of publication	2019-0501
Size	p. 297-304.
Publishing place	Elsevier Ltd
Document type	Article
ZDB-ID	184882-3
ISSN	1095-8630 ; 0301-4797
ISSN (online)	1095-8630
ISSN	0301-4797
DOI	10.1016/j.jenvman.2019.02.076
Database	NAL-Catalogue (AGRICOLA)

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