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Contrasting wolf responses to different paved roads and traffic volume levels. Biodiversity and Conservation 30: 3133.
DOI: 10.1007/s10531-021-02239-y
On reliable identification of factors influencing wildlife-vehicle collisions along roads. Journal of Environmental Management 237: 297.
DOI: 10.1016/j.jenvman.2019.02.076
How climate change and wildlife management affect population structure in wild boars. Scientific Reports 10: .
DOI: 10.1038/s41598-020-64216-9
Minor rural road networks: values, challenges, and opportunities for biodiversity conservation. Nature Conservation 11: 129.
DOI: 10.3897/natureconservation.11.4434
Life in the fast lane: roadkill risk along an urban–rural gradient. Journal of Urban Ecology 7: .
DOI: 10.1093/jue/juaa039
Magnitude, patterns and composition of wildlife roadkill in the Serengeti ecosystem, northern Tanzania. African Zoology 56: 173.
DOI: 10.1080/15627020.2021.1952896
Stochastic smoothing of point processes for wildlife-vehicle collisions on road networks. Stochastic Environmental Research and Risk Assessment 36: 1563.
DOI: 10.1007/s00477-021-02072-3
Temporal patterns of ungulate-vehicle collisions in Lithuania. Journal of Environmental Management 273: 111172.
DOI: 10.1016/j.jenvman.2020.111172
Patterns of vertebrate road-kills in a pre-Saharan Tunisian area. Journal of Arid Environments 193: 104595.
DOI: 10.1016/j.jaridenv.2021.104595
Spatio-Temporal Patterns of Wildlife Road Mortality in Golestan National Park-North East of Iran. Open Journal of Ecology 06: 312.
DOI: 10.4236/oje.2016.66031
Spatiotemporal identification of roadkill probability and systematic conservation planning. Landscape Ecology 34: 717.
DOI: 10.1007/s10980-019-00807-w
Wildlife-vehicle collisions - Influencing factors, data collection and research methods. Biological Conservation 251: 108758.
DOI: 10.1016/j.biocon.2020.108758
Temporal patterns of wild boar-vehicle collisions in Estonia, at the northern limit of its range. European Journal of Wildlife Research 62: 787.
DOI: 10.1007/s10344-016-1042-9
The ecology of human–nature interactions. Proceedings of the Royal Society B: Biological Sciences 287: 20191882.
DOI: 10.1098/rspb.2019.1882
Animal-vehicle collisions during the COVID-19 lockdown in early 2020 in the Krakow metropolitan region, Poland. Scientific Reports 12: .
DOI: 10.1038/s41598-022-11526-9
Dogs are the main species involved in animal-vehicle collisions in southern Spain: Daily, seasonal and spatial analyses of collisions. PLOS ONE 13: e0203693.
DOI: 10.1371/journal.pone.0203693
Temporal patterns of wildlife roadkill in the UK. PLOS ONE 16: e0258083.
DOI: 10.1371/journal.pone.0258083
Comparative Study of Animal Carcass Survey Methods on Roads. SSRN Electronic Journal : .
DOI: 10.2139/ssrn.3994310
Modeling road traffic safety based on point patterns of wildlife-vehicle collisions. Science of The Total Environment 846: 157237.
DOI: 10.1016/j.scitotenv.2022.157237
Wild boar populations up, numbers of hunters down? A review of trends and implications for Europe. Pest Management Science 71: 492.
DOI: 10.1002/ps.3965
Sustainable Landscape Planning to Mitigate Wildlife–Vehicle Collisions. Land 10: 737.
DOI: 10.3390/land10070737
Landscape and population drivers of ungulate-vehicle collisions in Portugal. Applied Geography 151: 102859.
DOI: 10.1016/j.apgeog.2022.102859
Impact of Road Fencing on Ungulate–Vehicle Collisions and Hotspot Patterns. Land 10: 338.
DOI: 10.3390/land10040338
Long-term monitoring by roadkill counts of mammal populations living in intensively cultivated landscapes. Biodiversity and Conservation 28: 97.
DOI: 10.1007/s10531-018-1638-3
Application of long-term collected data for conservation: Spatio-temporal patterns of mortality in Japanese serow. Journal of Veterinary Medical Science 83: 349.
DOI: 10.1292/jvms.20-0393
Wildlife-vehicle collisions in Spain. European Journal of Wildlife Research 61: 399.
DOI: 10.1007/s10344-015-0907-7
Road and traffic factors correlated to wildlife–vehicle collisions in Galicia (Spain). Wildlife Research 42: 25.
DOI: 10.1071/WR14060
Spatial and temporal dynamics of wild boars Sus scrofa hunted in Alpine environment. European Journal of Wildlife Research 67: .
DOI: 10.1007/s10344-021-01484-4
Look both ways: factors affecting roadkill probability in Blue-black Grassquits (Volatinia jacarina). Canadian Journal of Zoology 98: 603.
DOI: 10.1139/cjz-2020-0004
Impact of agrarian land use and land cover practices on survival and conservation of nilgai antelope (Boselaphus tragocamelus) in and around the Abohar wildlife sanctuary, northwestern India. Écoscience 26: 279.
DOI: 10.1080/11956860.2019.1587862
No clear effect of odour repellents on roe deer behaviour in the vicinity of roads. Wildlife Biology 2020: 1.
DOI: 10.2981/wlb.00744
Temporal patterns of moose-vehicle collisions with and without personal injuries. Accident Analysis & Prevention 98: 167.
DOI: 10.1016/j.aap.2016.09.024
Assessment of ecological passages along road networks within the Mediterranean forest using GIS-based multi criteria evaluation approach. Environmental Monitoring and Assessment 187: .
DOI: 10.1007/s10661-015-5009-1
Hotspots and hotmoments of wildlife roadkills along a main highway in a high biodiversity area in Brazilian Amazonia. Acta Amazonica 53: 42.
DOI: 10.1590/1809-4392202201871
Overabundant wild ungulate populations in Europe: management with consideration of socio‐ecological consequences. Mammal Review 50: 353.
DOI: 10.1111/mam.12202
Assessing agricultural damage by wild boar using drones. Wildlife Society Bulletin 42: 568.
DOI: 10.1002/wsb.916
Inter-Individual Variability of Stone Marten Behavioral Responses to a Highway. PLoS ONE 9: e103544.
DOI: 10.1371/journal.pone.0103544
The influence of time factors on the dynamics of roe deer collisions with vehicles. Landscape and Ecological Engineering 14: 221.
DOI: 10.1007/s11355-017-0343-9
Do roe deer react to wildlife warning reflectors? A test combining a controlled experiment with field observations. European Journal of Wildlife Research 63: .
DOI: 10.1007/s10344-017-1130-5
A spatiotemporal risk prediction of wildlife-vehicle collisions using machine learning for dynamic warnings. Journal of Safety Research 83: 269.
DOI: 10.1016/j.jsr.2022.09.001
Wildlife warning reflectors do not mitigate wildlife–vehicle collisions on roads. Accident Analysis & Prevention 120: 64.
DOI: 10.1016/j.aap.2018.08.003
Secrets of Success in a Landscape of Fear: Urban Wild Boar Adjust Risk Perception and Tolerate Disturbance. Frontiers in Ecology and Evolution 5: .
DOI: 10.3389/fevo.2017.00157
Speed reduction effects over distance of animal-vehicle collision countermeasures – a driving simulator study. European Transport Research Review 10: .
DOI: 10.1186/s12544-018-0314-8
On the correlation structure between point patterns and linear networks. Spatial Statistics 29: 192.
DOI: 10.1016/j.spasta.2018.12.001
Using Self-Organizing Maps to find spatial relationships between wildlife-vehicle crashes and land use classes. Anais da Academia Brasileira de Ciências 94: .
DOI: 10.1590/0001-3765202220210727
Assessing the consistency of hotspot and hot-moment patterns of wildlife road mortality over time. Perspectives in Ecology and Conservation 15: 56.
DOI: 10.1016/j.pecon.2017.03.003
Road orientation affects the impact of roads on wildlife. Wildlife Research 50: 39.
DOI: 10.1071/WR21149
Landscape effects on wild boar home range size under contrasting harvest regimes in a human-dominated agro-ecosystem. European Journal of Wildlife Research 63: .
DOI: 10.1007/s10344-017-1090-9
Détermination des facteurs spatiotemporels expliquant le risque de collision routière avec des cervidés sur l’autoroute Claude-Béchard (85) au Témiscouata. Le Naturaliste canadien 143: 40.
DOI: 10.7202/1054116ar
Comparison of environmental, biological and anthropogenic causes of wildlife–vehicle collisions among three large herbivore species. Population Ecology 62: 64.
DOI: 10.1002/1438-390X.12029
Effects of Road Density and Pattern on the Conservation of Species and Biodiversity. Current Landscape Ecology Reports 2: 1.
DOI: 10.1007/s40823-017-0020-6
Roadkill of medium to large mammals along a Brazilian road (BR-262) in Southeastern Brazil: spatial distribution and seasonal variation. Studies on Neotropical Fauna and Environment 55: 216.
DOI: 10.1080/01650521.2020.1719006
Identification of Elk-vehicle incident hotspots on state route 20 in Washington State. Landscape Ecology 36: 1685.
DOI: 10.1007/s10980-021-01238-2
Developing a correction factor to apply to animal–vehicle collision data for improved road mitigation measures. Wildlife Research 48: 501.
DOI: 10.1071/WR20090
Impacts and Potential Mitigation of Road Mortality for Hedgehogs in Europe. Animals 10: 1523.
DOI: 10.3390/ani10091523
Temporal pattern of moose-vehicle collisions. Transportation Research Part D: Transport and Environment 92: 102715.
DOI: 10.1016/j.trd.2021.102715
BOARD INVITED REVIEW: Immunocontraception as a possible tool to reduce feral pig populations: recent and future perspectives. Journal of Animal Science 97: 2283.
DOI: 10.1093/jas/skz066
In the wrong place at the wrong time: Moose and deer movement patterns influence wildlife-vehicle collision risk. Accident Analysis & Prevention 135: 105365.
DOI: 10.1016/j.aap.2019.105365
Spatio-temporal pattern of vulnerable road user’s collisions hot spots and related risk factors for injury severity in Tunisia. Transportation Research Part F: Traffic Psychology and Behaviour 56: 477.
DOI: 10.1016/j.trf.2018.05.003
Traffic mortality of four ungulate species in southern Finland. Nature Conservation 11: 13.
DOI: 10.3897/natureconservation.11.4416
Lunar Phases and Wildlife–Vehicle Collisions: Application of the Lunar Disk Percentage Method. Animals 11: 908.
DOI: 10.3390/ani11030908
Factors Affecting Roadkills of Semi-Aquatic Mammals. Biology 11: 748.
DOI: 10.3390/biology11050748
An intelligent framework to detect and generate alert while cattle lying on road in dangerous states using surveillance videos. Multimedia Tools and Applications : .
DOI: 10.1007/s11042-023-15019-3
Temporal patterns of ungulate-vehicle collisions in a sparsely populated country. European Journal of Wildlife Research 66: .
DOI: 10.1007/s10344-020-01396-9
Application of KDE+ software to identify collective risk hotspots of ungulate-vehicle collisions in South Tyrol, Northern Italy. European Journal of Wildlife Research 64: .
DOI: 10.1007/s10344-018-1214-x
Multi-label deep learning models for continuous monitoring of road infrastructures. Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments : 1.
DOI: 10.1145/3389189.3397997
A Novel Methodology for Automating Spatio-Temporal Data Classification in Basketball Using Active Learning. 2021 IEEE 2nd International Conference on Pattern Recognition and Machine Learning (PRML) : 39.
DOI: 10.1109/PRML52754.2021.9520715
Predicting the Risk of Deer-vehicle Collisions by Inferring Rules Learnt from Deer Experience and Movement Patterns in the Vicinity of Roads. 2020 10th International Conference on Advanced Computer Information Technologies (ACIT) : 368.
DOI: 10.1109/ACIT49673.2020.9208843
DEPENDENCE OF VEHICLE COLLISIONS WITH ROE DEER ON SPATIAL AND TEMPORAL FACTORS IN LITHUANIA. The 11th International Conference ENVIRONMENTAL ENGINEERING 11th ICEE SELECTED PAPERS : .
DOI: 10.3846/enviro.2020.651
Handbook of the Mammals of Europe. Chapter 17-1: 1.
DOI: 10.1007/978-3-319-65038-8_17-1
Carrion Ecology and Management. Chapter 8: 183.
DOI: 10.1007/978-3-030-16501-7_8
Terrestrial Cetartiodactyla. Chapter 17: 1.
DOI: 10.1007/978-3-030-24475-0_17