IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v15y2018i9p1848-d166048.html
   My bibliography  Save this article

Influence of Host and Environmental Factors on the Distribution of the Japanese Encephalitis Vector Culex tritaeniorhynchus in China

Author

Listed:
  • Boyang Liu

    (Department of Veterinary Surgery, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China)

  • Xiang Gao

    (Department of Veterinary Surgery, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China)

  • Jun Ma

    (Department of Veterinary Surgery, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China)

  • Zhihui Jiao

    (Department of Veterinary Surgery, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China)

  • Jianhua Xiao

    (Department of Veterinary Surgery, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China)

  • Hongbin Wang

    (Department of Veterinary Surgery, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China)

Abstract

Culex tritaeniorhynchus is an important vector that transmits a variety of human and animal diseases. Japanese encephalitis (JE), an endemic disease in the Asia-Pacific region, is primarily transmitted by Cx. tritaeniorhynchus . Insufficient monitoring of vector mosquitoes has led to a poor understanding of the distribution of Cx. tritaeniorhynchus in China. To delineate the habitat of Cx. tritaeniorhynchus and any host and environmental factors that affect its distribution, we used a maximum entropy modeling method to predict its distribution in China. Our models provided high resolution predictions on the potential distribution of Cx. tritaeniorhynchus . The predicted suitable habitats of the JE vector were correlated with areas of high JE incidence in parts of China. Factors driving the distribution of Cx. tritaeniorhynchus in China were also revealed by our models. Furthermore, human population density and the maximum NDVI were the most important predictors in our models. Bioclimate factors and elevation also significantly impacted the distribution of Cx. tritaeniorhynchus . Our findings may serve as a reference for vector and disease control.

Suggested Citation

  • Boyang Liu & Xiang Gao & Jun Ma & Zhihui Jiao & Jianhua Xiao & Hongbin Wang, 2018. "Influence of Host and Environmental Factors on the Distribution of the Japanese Encephalitis Vector Culex tritaeniorhynchus in China," IJERPH, MDPI, vol. 15(9), pages 1-15, August.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:9:p:1848-:d:166048
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/15/9/1848/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/15/9/1848/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Qiang Zhang & Jianfeng Li & Vijay Singh & Yungang Bai, 2012. "SPI-based evaluation of drought events in Xinjiang, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 64(1), pages 481-492, October.
    2. Bipin Kumar Acharya & Chunxiang Cao & Min Xu & Laxman Khanal & Shahid Naeem & Shreejana Pandit, 2018. "Present and Future of Dengue Fever in Nepal: Mapping Climatic Suitability by Ecological Niche Model," IJERPH, MDPI, vol. 15(2), pages 1-15, January.
    3. Shcheglovitova, Mariya & Anderson, Robert P., 2013. "Estimating optimal complexity for ecological niche models: A jackknife approach for species with small sample sizes," Ecological Modelling, Elsevier, vol. 269(C), pages 9-17.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yixin Tong & Honglin Jiang & Ning Xu & Zhengzhong Wang & Ying Xiong & Jiangfan Yin & Junhui Huang & Yue Chen & Qingwu Jiang & Yibiao Zhou, 2023. "Global Distribution of Culex tritaeniorhynchus and Impact Factors," IJERPH, MDPI, vol. 20(6), pages 1-15, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Holtmeyer, Melissa L. & Wang, Shuxiao & Axelbaum, Richard L., 2013. "Considerations for decision-making on distributed power generation in rural areas," Energy Policy, Elsevier, vol. 63(C), pages 708-715.
    2. Amaro, George & Fidelis, Elisangela Gomes & da Silva, Ricardo Siqueira & Marchioro, Cesar Augusto, 2023. "Effect of study area extent on the potential distribution of Species: A case study with models for Raoiella indica Hirst (Acari: Tenuipalpidae)," Ecological Modelling, Elsevier, vol. 483(C).
    3. Valentina Lucia Astrid Laface & Carmelo Maria Musarella & Gianmarco Tavilla & Agostino Sorgonà & Ana Cano-Ortiz & Ricardo Quinto Canas & Giovanni Spampinato, 2023. "Current and Potential Future Distribution of Endemic Salvia ceratophylloides Ard. (Lamiaceae)," Land, MDPI, vol. 12(1), pages 1-21, January.
    4. Feng Gao & Yuhu Zhang & Xiulin Ren & Yunjun Yao & Zengchao Hao & Wanyuan Cai, 2018. "Evaluation of CHIRPS and its application for drought monitoring over the Haihe River Basin, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 92(1), pages 155-172, May.
    5. H. Oğuz Çoban & Ömer K. Örücü & E. Seda Arslan, 2020. "MaxEnt Modeling for Predicting the Current and Future Potential Geographical Distribution of Quercus libani Olivier," Sustainability, MDPI, vol. 12(7), pages 1-17, March.
    6. Bruce G. Marcot & Anca M. Hanea, 2021. "What is an optimal value of k in k-fold cross-validation in discrete Bayesian network analysis?," Computational Statistics, Springer, vol. 36(3), pages 2009-2031, September.
    7. Holder, Anna M. & Markarian, Arev & Doyle, Jessie M. & Olson, John R., 2020. "Predicting geographic distributions of fishes in remote stream networks using maximum entropy modeling and landscape characterizations," Ecological Modelling, Elsevier, vol. 433(C).
    8. Fredrick Tom Otieno & John Gachohi & Peter Gikuma-Njuru & Patrick Kariuki & Harry Oyas & Samuel A. Canfield & Bernard Bett & Moses Kariuki Njenga & Jason K. Blackburn, 2021. "Modeling the Potential Future Distribution of Anthrax Outbreaks under Multiple Climate Change Scenarios for Kenya," IJERPH, MDPI, vol. 18(8), pages 1-15, April.
    9. Zeng, Yiwen & Low, Bi Wei & Yeo, Darren C.J., 2016. "Novel methods to select environmental variables in MaxEnt: A case study using invasive crayfish," Ecological Modelling, Elsevier, vol. 341(C), pages 5-13.
    10. Moreno-Amat, Elena & Mateo, Rubén G. & Nieto-Lugilde, Diego & Morueta-Holme, Naia & Svenning, Jens-Christian & García-Amorena, Ignacio, 2015. "Impact of model complexity on cross-temporal transferability in Maxent species distribution models: An assessment using paleobotanical data," Ecological Modelling, Elsevier, vol. 312(C), pages 308-317.
    11. Sillero, Neftalí & Arenas-Castro, Salvador & Enriquez‐Urzelai, Urtzi & Vale, Cândida Gomes & Sousa-Guedes, Diana & Martínez-Freiría, Fernando & Real, Raimundo & Barbosa, A.Márcia, 2021. "Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling," Ecological Modelling, Elsevier, vol. 456(C).
    12. Aldo Rafael Martínez-Sifuentes & José Antonio Hernández-Herrera & Luis Manuel Valenzuela-Núñez & Edwin Amir Briceño-Contreras & Ulises Manzanilla-Quiñones & Argel Gastélum-Arellánez & Ramón Trucíos-Ca, 2022. "Climate Change Impact on the Habitat Suitability of Pseudotsuga menziesii Mirb. Franco in Mexico: An Approach for Its Conservation," Sustainability, MDPI, vol. 14(14), pages 1-17, July.
    13. Herkt, K. Matthias B. & Barnikel, Günter & Skidmore, Andrew K. & Fahr, Jakob, 2016. "A high-resolution model of bat diversity and endemism for continental Africa," Ecological Modelling, Elsevier, vol. 320(C), pages 9-28.
    14. Aldo Rafael Martínez-Sifuentes & Juan Estrada-Ávalos & Ramón Trucíos-Caciano & José Villanueva-Díaz & Nuria Aidé López-Hernández & Juan de Dios López-Favela, 2023. "Predicting Climate Change Impacts on Candelilla ( Euphorbia antisyphilitica Zucc.) for Mexico: An Approach for Mexico’s Primary Harvest Area," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    15. Wan, Nian-Feng & Jiang, Jie-Xian & Li, Bo, 2014. "Modeling ecological two-sidedness for complex ecosystems," Ecological Modelling, Elsevier, vol. 287(C), pages 36-43.
    16. Sutton, G.F. & Martin, G.D., 2022. "Testing MaxEnt model performance in a novel geographic region using an intentionally introduced insect," Ecological Modelling, Elsevier, vol. 473(C).
    17. Bipin Kumar Acharya & Wei Chen & Zengliang Ruan & Gobind Prasad Pant & Yin Yang & Lalan Prasad Shah & Chunxiang Cao & Zhiwei Xu & Meghnath Dhimal & Hualiang Lin, 2019. "Mapping Environmental Suitability of Scrub Typhus in Nepal Using MaxEnt and Random Forest Models," IJERPH, MDPI, vol. 16(23), pages 1-14, December.
    18. Worthington, Thomas A. & Zhang, Tianjiao & Logue, Daniel R. & Mittelstet, Aaron R. & Brewer, Shannon K., 2016. "Landscape and flow metrics affecting the distribution of a federally-threatened fish: Improving management, model fit, and model transferability," Ecological Modelling, Elsevier, vol. 342(C), pages 1-18.
    19. Boria, Robert A. & Olson, Link E. & Goodman, Steven M. & Anderson, Robert P., 2014. "Spatial filtering to reduce sampling bias can improve the performance of ecological niche models," Ecological Modelling, Elsevier, vol. 275(C), pages 73-77.
    20. An Cao & Xueyi Shi, 2022. "The Effects of Climate Change on Habitat Connectivity: A Case Study of the Brown-Eared Pheasant in China," Land, MDPI, vol. 11(6), pages 1-17, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:15:y:2018:i:9:p:1848-:d:166048. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.