Optimal prediction model of mosquito larval abundance in benthic macroinvertebrate communities of natural and artificial habitats, korean peninsula (2016-2017)

Dong Gun Kim, Hwang Goo Lee, Yeon Jae Bae

Research output: Contribution to journalArticlepeer-review

Abstract

Mosquitos are the most prolific invasive insect species contributing to spread of endemic or exotic diseases, which exert a large burden on human health. Humans continue to develop and use physical, chemical, and biological methods for control of mosquito-borne infections. However, mosquito control methods are usually more effective when they target larvae, density of which is closely associated with biological factors, such as the community index and the predator population. Predictive models of mosquito larval abundance were developed based on species richness and on diversity and richness index ratio of individual Odonata, Coleoptera and Hemiptera group (OCH index) to evaluate suitability of the models using r2 value and Akaike information criterion (AIC) score. The most suitable model had an r2 value of 0.532 and an AIC score of 2.659 and was employed to estimate mosquito larval abundance. The prediction model developed should help explain correlation between benthic macroinvertebrate communities and mosquito larval abundance.

Original languageEnglish
Pages (from-to)535-548
Number of pages14
JournalSoutheast Asian Journal of Tropical Medicine and Public Health
Volume51
Issue number4
Publication statusPublished - 2020 Jul

Bibliographical note

Funding Information:
The research was supported by the Korea Environmental Industry and Technology Institute through the Public Technology Program based on Environmental Policy, funded by the Ministry of Environment, South Korea (project no. 2016000210003)

Publisher Copyright:
© 2020, SEAMEO TROPMED Network. All rights reserved.

Keywords

  • Abundance prediction model
  • Benthic community
  • Coleoptera
  • Hemiptera
  • Macroinvertebrate
  • Mosquito larva
  • Odonata

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Infectious Diseases

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