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Predictive Modeling of Ungulate–Vehicle Collision in the Republic of Korea

SIMPLE SUMMARY: Ungulate–vehicle collisions (UVC) often threaten human life and property due to the large body size of ungulates. The purpose of this study is to understand factors contributing to UVC of three ungulate species (Capreolus pygargus, Hydropotes inermis, and Sus scrofa) in the Republic...

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Autores principales: Kim, Kyungmin, Andersen, Desiree, Jang, Yikweon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10451958/
https://www.ncbi.nlm.nih.gov/pubmed/37626954
http://dx.doi.org/10.3390/biology12081068
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author Kim, Kyungmin
Andersen, Desiree
Jang, Yikweon
author_facet Kim, Kyungmin
Andersen, Desiree
Jang, Yikweon
author_sort Kim, Kyungmin
collection PubMed
description SIMPLE SUMMARY: Ungulate–vehicle collisions (UVC) often threaten human life and property due to the large body size of ungulates. The purpose of this study is to understand factors contributing to UVC of three ungulate species (Capreolus pygargus, Hydropotes inermis, and Sus scrofa) in the Republic of Korea using predictive modeling. We relied on the UVC data of the Korea Roadkill Observation System, a government-sponsored web-based system that is required for road workers to report roadkill incidents on all major road types across the country with a standardized data collection method. There were 25,755 UVC datapoints between 2019 and 2021. The UVC frequencies tended to be the highest in the most active seasons of the year, such as dispersal or mating seasons. Factors critical for UVC frequencies were different among three ungulate species, suggesting individualized mitigation plans. ABSTRACT: Animal–vehicle collisions (AVC) threaten animals as well as human life and property. AVC with ungulates, called ungulate–vehicle collision (UVC), often seriously endangers human safety because of the considerable body size of ungulates. In the Republic of Korea, three ungulate species, Capreolus pygargus, Hydropotes inermis, and Sus scrofa, account for a large proportion of AVC. This study aimed to understand the characteristics of UVC by examining various parameters related to habitat, traffic, and seasonality using MaxEnt. The results showed that the peak UVC seasons coincided with the most active seasonal behaviors of the studied ungulates. For the modeling results, in C. pygargus, habitat variables are most important for models across seasons, and UVC events are most likely to occur in high mountain chains. In H. inermis, habitat and traffic variables are most important for models across seasons. Although the important habitat for the models were different across seasons for S. scrofa, the maximum speed was consistently critical for models across all seasons. Factors critical to UVC in the Republic of Korea were different for the three ungulate species and across seasons, indicating that seasonal behavior should be considered along with landscape and traffic characteristics to mitigate UVC.
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spelling pubmed-104519582023-08-26 Predictive Modeling of Ungulate–Vehicle Collision in the Republic of Korea Kim, Kyungmin Andersen, Desiree Jang, Yikweon Biology (Basel) Article SIMPLE SUMMARY: Ungulate–vehicle collisions (UVC) often threaten human life and property due to the large body size of ungulates. The purpose of this study is to understand factors contributing to UVC of three ungulate species (Capreolus pygargus, Hydropotes inermis, and Sus scrofa) in the Republic of Korea using predictive modeling. We relied on the UVC data of the Korea Roadkill Observation System, a government-sponsored web-based system that is required for road workers to report roadkill incidents on all major road types across the country with a standardized data collection method. There were 25,755 UVC datapoints between 2019 and 2021. The UVC frequencies tended to be the highest in the most active seasons of the year, such as dispersal or mating seasons. Factors critical for UVC frequencies were different among three ungulate species, suggesting individualized mitigation plans. ABSTRACT: Animal–vehicle collisions (AVC) threaten animals as well as human life and property. AVC with ungulates, called ungulate–vehicle collision (UVC), often seriously endangers human safety because of the considerable body size of ungulates. In the Republic of Korea, three ungulate species, Capreolus pygargus, Hydropotes inermis, and Sus scrofa, account for a large proportion of AVC. This study aimed to understand the characteristics of UVC by examining various parameters related to habitat, traffic, and seasonality using MaxEnt. The results showed that the peak UVC seasons coincided with the most active seasonal behaviors of the studied ungulates. For the modeling results, in C. pygargus, habitat variables are most important for models across seasons, and UVC events are most likely to occur in high mountain chains. In H. inermis, habitat and traffic variables are most important for models across seasons. Although the important habitat for the models were different across seasons for S. scrofa, the maximum speed was consistently critical for models across all seasons. Factors critical to UVC in the Republic of Korea were different for the three ungulate species and across seasons, indicating that seasonal behavior should be considered along with landscape and traffic characteristics to mitigate UVC. MDPI 2023-07-30 /pmc/articles/PMC10451958/ /pubmed/37626954 http://dx.doi.org/10.3390/biology12081068 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kim, Kyungmin
Andersen, Desiree
Jang, Yikweon
Predictive Modeling of Ungulate–Vehicle Collision in the Republic of Korea
title Predictive Modeling of Ungulate–Vehicle Collision in the Republic of Korea
title_full Predictive Modeling of Ungulate–Vehicle Collision in the Republic of Korea
title_fullStr Predictive Modeling of Ungulate–Vehicle Collision in the Republic of Korea
title_full_unstemmed Predictive Modeling of Ungulate–Vehicle Collision in the Republic of Korea
title_short Predictive Modeling of Ungulate–Vehicle Collision in the Republic of Korea
title_sort predictive modeling of ungulate–vehicle collision in the republic of korea
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10451958/
https://www.ncbi.nlm.nih.gov/pubmed/37626954
http://dx.doi.org/10.3390/biology12081068
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