Mosquito populations dynamics associated with climate variations.

Abstract Mosquitoes are responsible for the transmission of numerous serious pathogens. Members of the Aedes and Culex genera, which include many important vectors of mosquito-borne diseases, are highly invasive and adapted to man-made environments. They are spread around the world involuntarily by humans and are highly adapted to urbanized environments, where they are exposed to climate-related abundance drivers. We investigated Culicidae fauna in two urban parks in the city of Sao Paulo to analyze the correlations between climatic variables and the population dynamics of mosquitoes in these urban areas. Mosquitoes were collected monthly over one year, and sampling sufficiency was evaluated after morphological identification of the specimens. The average monthly temperature and accumulated rainfall for the collection month and previous month were used to explain climate-related abundance drivers for the six most abundant species ( Aedes aegypti, Aedes albopictus, Aedes fluviatilis, Aedes scapularis, Culex nigripalpus and Culex quinquefasciatus) and then analyzed using generalized linear statistical models and the Akaike Information Criteria corrected for small samples (AICc). The strength of evidence in favor of each model was evaluated using Akaike weights, and the explanatory model power was measured by McFadden's Pseudo-R 2 . Associations between climate and mosquito abundance were found in both parks, indicating that predictive models based on climate variables can provide important information on mosquito population dynamics. We also found that this association is species-dependent. Urbanization processes increase the abundance of a few mosquito species that are well adapted to man-made environments and some of which are important vectors of pathogens. Predictive models for abundance based on climate variables may help elucidate the population dynamics of urban mosquitoes and their impact on the risk of disease transmission, allowing better predictive scenarios to be developed and supporting the implementation of vector mosquito control strategies.