ArticlePLoS neglected tropical diseases2024
Temperature dependence of mosquitoes: Comparing mechanistic and machine learning approaches.
Article in PLoS neglected tropical diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Heatwaves Constrain the Future Persistence of Mosquito Vectors in Europe.Global change biology · 2026Article
- Rural dengue dynamics: the interplay of climate, built environment, and agriculture in Costa Rica.medRxiv : the preprint server for health sciences · 2026Article
- Climate sensitivity is widely but unevenly spread across zoonotic diseases.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Climate Change Favors African Malaria Vector Mosquitoes.Global change biology · 2025Article
- A Scoping Review of Mosquito Vector Range Shifts: Widespread Expansions and Evidence Gaps in Climate Attribution.Global change biology · 2025Article
- A systematic review of climate-change driven range shifts in mosquito vectors.bioRxiv : the preprint server for biology · 2025Article
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Abstract
Mosquito vectors of pathogens (e.g., Aedes, Anopheles, and Culex spp. which transmit dengue, Zika, chikungunya, West Nile, malaria, and others) are of increasing concern for global public health. These vectors are geographically shifting under climate and other anthropogenic changes. As small-bodied ectotherms, mosquitoes are strongly affected by temperature, which causes unimodal responses in mosquito life history traits (e.g., biting rate, adult mortality rate, mosquito development rate, and probability of egg-to-adult survival) that exhibit upper and lower thermal limits and intermediate thermal optima in laboratory studies. However, it remains unknown how mosquito thermal responses measured in laboratory experiments relate to the realized thermal responses of mosquitoes in the field. To address this gap, we leverage thousands of global mosquito occurrences and geospatial satellite data at high spatial resolution to construct machine-learning based species distribution models, from which vector thermal responses are estimated. We apply methods to restrict models to the relevant mosquito activity season and to conduct ecologically plausible spatial background sampling centered around ecoregions for comparison to mosquito occurrence records. We found that thermal minima estimated from laboratory studies were highly correlated with those from the species distributions (r = 0.87). The thermal optima were less strongly correlated (r = 0.69). For most species, we did not detect thermal maxima from their observed distributions so were unable to compare to laboratory-based estimates. The results suggest that laboratory studies have the potential to be highly transportable to predicting lower thermal limits and thermal optima of mosquitoes in the field. At the same time, lab-based models likely capture physiological limits on mosquito persistence at high temperatures that are not apparent from field-based observational studies but may critically determine mosquito responses to climate warming. Our results indicate that lab-based and field-based studies are highly complementary; performing the analyses in concert can help to more comprehensively understand vector response to climate change.
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