Projected distributions of 18 mosquito species in the Republic of Korea under climate change scenarios.

Authors

Jihun Ryu, Kwang Shik Choi

Published in

Parasites & vectors. Jun 21, 2026. Epub Jun 21, 2026.

Abstract

Climate change is altering mosquito distributions and may reshape the risk of mosquito-borne diseases in the Republic of Korea (ROK). However, nationwide, multi-species projections for medically important mosquitoes remain limited.
We compiled 1,969 spatially filtered occurrence records for 18 mosquito species and developed species distribution models using MaxEnt. Environmental predictors included bioclimatic, topographic, and land cover variables. Future distributions were projected for the 2030s, 2050s, and 2070s under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios using MIROC6 climate data. A Climate Change Vulnerability Index (CCVI) was calculated to compare species-specific range expansion and contraction.
Current habitat suitability patterns grouped the 18 species into nationwide, northern-preferring, southwestern-preferring, and southern-preferring distribution types. Topographic Wetness Index (36.6%), elevation (18.6%), and land cover type (18.4%) contributed more strongly to model performance than climatic variables alone. Under SSP5-8.5 in the 2070s, Aedes albopictus and Culex tritaeniorhynchus were projected to expand suitable habitat by 183.4% and 236.5%, respectively, whereas northern-preferring Anopheles species showed marked habitat contraction. Anopheles pullus and Anopheles belenrae were projected to lose 100.0% of their suitable habitat under the highest-emission scenario. The CCVI classified five species, mainly Anopheles, as highly vulnerable, one species as moderately affected, and 12 species as range-expanding.
These findings indicate that climate change may substantially reorganize mosquito communities in the ROK, reducing habitat suitability for several malaria vectors while expanding suitable areas for important arbovirus and Japanese encephalitis vectors. Adaptive surveillance and vector management should therefore integrate climate projections with local landscape and hydrological risk factors.

PMID:
42324574
Bibliographic data and abstract were imported from PubMed on 22 Jun 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.