Population of the temperate mosquito, Culex pipiens, decreases in response to habitat climatological changes in future

• Main Authors: K. Watanabe, S. Fukui, S. Ohta
• Format: Article
• Language: English
• Published: American Geophysical Union (AGU) 2017-06-01
• Series: GeoHealth
• Subjects: Culex pipiens; temperate regions; population dynamics; Physiology‐based Climate‐driven Mosquito Population model; climate change
• Online Access: https://doi.org/10.1002/2017GH000054

Abstract Predictions of the temporal distribution of vector mosquitoes are an important issue for human health because the response of mosquito populations to climate change could have implications for the risk of vector‐borne diseases. To elucidate the effects of climate change on mosquito populations inhabiting temperate regions, we developed a Physiology‐based Climate‐driven Mosquito Population model for temperate regions. For accurately reproducing the temporal patterns observed in mosquito populations, the key factors were identified by implementing the combinations of factors into the model. We focused on three factors: the effect of diapause, the positive effect of rainfall on larval carrying capacity, and the negative effect of rainfall as the washout mortality on aquatic stages. For each model, parameters were calibrated using weekly observation data of a Culex pipiens adult population collected in Tokyo, Japan. Based on its likelihood value, the model incorporating diapause, constant carrying capacity, and washout mortality was the best to replicate the observed data. By using the selected model and applying global climate model data, our results indicated that the mosquito population would decrease and adults’ active season would be shortened under future climate conditions. We found that incorporating the washout effect in the model settings or not caused a difference in the temporal patterns in the projected mosquito populations. This suggested that water resources in mosquito habitats in temperate regions should be considered for predicting the risk of vector‐borne diseases in such regions.