An analysis of rodent density patterns and its spatial–temporal correlations using geographically and temporally weighted regression in southeastern China

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Authors: Mingyu Luo, Jinna Wang, Mingyong Tao, Hanran Ji, Guoqin Jiang, Qinmei Liu, Tianqi Li, Zhou Guan, Juan Hou, Zhenyu Gong
Cited by: 2
References: 28

Abstract

Introduction: Rodents are significant vectors, harboring diverse pathogenic microorganisms which can spread a variety of infectious diseases. Surveillance on rodent density patterns should be prioritized as early warning indicators for prevention and control of infectious diseases. We aimed to analyze spatial and temporal heterogeneity of rodent density patterns in Zhejiang Province, and analyze the spatial and temporal correlations between rodent density, meteorological, land use and vegetation factors. Methods: Collect rodent surveillance data, meteorological factors, and vegetation factors in Zhejiang Province from 2019 to 2023. Analyze the temporal and spatial distribution of rodent density patterns. Employ the GTWR model to analyze the spatial and temporal correlations between rodent density, meteorological, land use and vegetation factors. Results: The rodent density in southern Zhejiang Province was higher than that in northern Zhejiang Province, and the species richness of wild rodents also exceeded that in northern Zhejiang Province. The effects of meteorological and vegetation factors on rodent density varied across geographical spatial distributions, which might primarily be related to the distribution range of rodent species in different habitat sites. Discussions: Meteorological and vegetation factors could influence the rodent density, particularly that of wild rodents, by offering a suitable environment for growth and development as well as food sources.

Fields of Study & Subjects

Animal Ecology and Behavior Studies Yersinia bacterium plague ectoparasites research Viral Infections and Vectors

Publication details

Journal / source
Frontiers in Veterinary Science
Publisher
Frontiers Media SA
Volume
12
Pages
1690571–1690571
Publication date
8 January 2026
Language
EN