Mapping the potential distribution of major tick species in China

Yang, Xin; Gao, Zheng; Zhou, Tianli; Zhang, Jian; Wang, Luqi; Xiao, Lingjun; Wu, Hongjuan; Li, Sen ORCID: https://orcid.org/0000-0002-1177-7339. 2020 Mapping the potential distribution of major tick species in China [in special issue: Ecology, epidemiology, surveillance, and control of vectors and vector-borne pathogens in temperate regions] International Journal of Environmental Research and Public Health, 17 (14), 5145. 15, pp. https://doi.org/10.3390/ijerph17145145

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Official URL: http://dx.doi.org/10.3390/ijerph17145145

Abstract/Summary

Ticks are known as the vectors of various zoonotic diseases such as Lyme borreliosis and tick-borne encephalitis. Though their occurrences are increasingly reported in some parts of China, our understanding of the pattern and determinants of ticks’ potential distribution over the country remain limited. In this study, we took advantage of the recently compiled spatial dataset of distribution and diversity of ticks in China, analyzed the environmental determinants of ten frequently reported tick species and mapped the spatial distribution of these species over the country using the MaxEnt model. We found that presence of urban fabric, cropland, and forest in a place are key determents of tick occurrence, suggesting ticks were likely inhabited close to where people live. Besides, precipitation in the driest month was found to have a relatively high contribution in mapping tick distribution. The model projected that theses ticks could be widely distributed in the Northwest, Central North, Northeast, and South China. Our results added new evidence on the potential distribution of a variety of major tick species in China and pinpointed areas with a high potential risk of tick bites and tick-borne diseases for raising public health awareness and prevention responses

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.3390/ijerph17145145
UKCEH and CEH Sections/Science Areas:	UKCEH Fellows
ISSN:	1661-7827
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	tick, potential distribution, environmental factors, MaxEnt, machine learning
NORA Subject Terms:	Ecology and Environment Zoology
Date made live:	29 Jul 2020 16:29 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/528245

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.3390/ijerph17145145

UKCEH and CEH Sections/Science Areas:

UKCEH Fellows

ISSN:

1661-7827

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via Official URL link.

Additional Keywords:

tick, potential distribution, environmental factors, MaxEnt, machine learning