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Predicting global potential distribution of Peromyscopsylla hesperomys and Orchopeas sexdentatus and risk assessment for invading China under climate change

Bibliographic Data

ID22075575
AuthorsHongyun Li (0000-0003-3332-3132, National Institute for Communicable Disease Control and Prevention), Ying Liang (0000-0002-1314-8261, National Institute for Communicable Disease Control and Prevention), Ying Siu Liang (0000-0001-5618-197X, National Institute for Communicable Disease Control and Prevention), Dong Li (0000-0002-9480-993X, Shandong University), Li Dong (0000-0003-0650-1765), Cancan Li (0000-0001-7998-146X, Capital Medical University), Lu Zhang (0000-0002-8855-8492, National Institute for Communicable Disease Control and Prevention), Bin Wang (0000-0002-8591-8528, Jiamusi University), Delong Ma (0000-0003-1477-5176), Qunzheng Mu (National Institute for Communicable Disease Control and Prevention), Jun Wang (0000-0003-4485-7201, National Institute for Communicable Disease Control and Prevention), Haifeng Hou (0000-0002-1131-1619, Affiliated Hospital of Taishan Medical University, corresponding author), Qiyong Liu (0000-0003-4066-7988, Shandong University, corresponding author)
Year2023
Volume10
Pages1018327-1018327
Publication date2023-01-05
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2022.1018327
PMID36684875
OpenAlexW4313562163
LanguageEN
Citations received2
References cited27

Background: are regarded to be representative plague vectors in the United States. The incidence of plague is rising globally, possibly due to climate change and environmental damage. Environmental factors such as temperature and precipitation have a significant impact on the temporal and spatial distribution of plague vectors. Methods: Maximum entropy models (MaxEnt) were utilized to predict the distributions of these two fleas and their trends into the future. The main environmental factors influencing the distribution of these two fleas were analyzed. A risk assessment system was constructed to calculate the invasion risk values of the species. Results: . They have the potential to survive in suitable areas of China in the future. The risk assessment system indicated that the risk level for the invasion of these two species into China was moderate. Conclusion: In order to achieve early detection, early interception, and early management, China should perfect its monitoring infrastructure and develop scientific prevention and control strategies to prevent the invasion of foreign flea vectors

Biology · China · Climate change · Climatology · Computer security · Environmental health · Geography · Risk assessment · Animal Ecology and Behavior Studies · Computer Science · Environmental Science · Mathematics · Medicine · Mosquito-borne diseases and control · Yersinia bacterium, plague, ectoparasites research · Ecology · Geology

  • Projecting the potential distribution of Rickettsia japonica in China and Asian adjacent regions under climate change using the Maxent model

    Open Access•Xiaoxu Wang, Meng Shang et al.•Frontiers in Public Health•2025

  • Predicting the potential distribution areas of Leptotrombidium rubellum under current and future climate change

    Open Access•Qunzheng Mu, Fengfeng Li et al.•Frontiers in Public Health•2025

  • A statistical explanation of MaxEnt for ecologists

    Open Access•Jane Elith, Steven J Phillips et al.•Diversity and Distributions•2011

  • Original Article

    Open Access•Richard G Pearson, Christopher J Raxworthy et al.•Journal of Biogeography•2007

  • Species Distribution Models

    Jane Elith, John R Leathwick•Annual Review of Ecology,…•2009

  • Maximum entropy modeling of species geographic distributions

    Open Access•Steven J Phillips, Robert P Anderson et al.•Ecological Modelling•2006

  • Modeling of species distributions with Maxent

    Open Access•Steven J Phillips, Miroslav Dudík et al.•Ecography•2008

Unique citing works2
Citations per year2
Citation span2025 - 2025 (1)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 2

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