Species-specific environmental drivers of mosquito abundance in a coastal lagoon system of Florida.

Mosquito abundance is strongly influenced by environmental conditions, yet species-specific responses to weather and land-cover variables remain insufficiently quantified in operational mosquito control programs. This study integrates multi-year surveillance data (2021-2024) with environmental predictors to identify drivers of mosquito abundance in a coastal landscape in Indian River County, Florida, USA with analyses focused on Culex nigripalpus, Aedes taeniorhynchus, and Aedes albopictus. Species-specific generalized linear mixed-effects models with a negative binomial distribution were used to relate mosquito abundance to lagged temperature, precipitation (including quadratic terms), and land-cover variables (wetlands, impervious surfaces, and marine lagoon habitats). Model performance was evaluated using temporal and spatial cross-validation. Distinct ecological responses were observed among species. Cx. nigripalpus was strongly associated with precipitation and wetland cover, with peak abundance at intermediate rainfall levels. Ae. taeniorhynchus showed strong positive associations with coastal and lagoon habitats and nonlinear responses to precipitation. In contrast, Ae. albopictus was primarily driven by temperature and impervious surface cover, with reduced abundance in wetland and coastal lagoon habitats. Spatial predictions revealed clear ecological partitioning among species. The results demonstrate that mosquito abundance in coastal landscapes is strongly structured by interactions among weather, land cover, and habitat type. Integrating environmental data with surveillance records offers a practical framework for predicting mosquito abundance and enables operational mosquito control programs to more precisely identify high-risk areas and optimal times for intervention, ultimately improving the efficiency and effectiveness of spatial and temporal targeting of vector control measures.