Back

Predicting Historic, Contemporary, And Future Distributions Of Culex Coronator Following Rapid Range Expansion

Magaletta, O.; Bauer, A.; Lee, Y.; Campbell, L. P.; Thongsripong, P.

2026-08-11 ecology
10.64898/2026.08.05.742963 bioRxiv
Show abstract

Invasive mosquito species pose substantial risks to human and animal health. Since 2004, Culex coronator, a mosquito vector species of public health concern, has shown rapid range expansion within the United States, spreading from a historically limited distribution in southern Texas to across the Gulf Coast region and into eastern and mid-Atlantic states. However, changes in environmental suitability associated with this expansion across historical, contemporary, and future climate conditions have not been evaluated. Here, we used species distribution models (SDMs) to compare predictions of abiotic suitability for Cx. coronator under historic (1960-1989) and recent (2000-2024) climate conditions calibrated on the historical range in the United States. We also created a contemporary SDM based on occurrence records prior to and following species range expansion (1960-2024), and further, to predict potential distributions under current and future climate conditions. Models calibrated on the historical range predicted only modest changes in suitability along the Gulf Coast region and failed to identify large areas of the humid subtropical eastern United States that are now occupied. In contrast, the contemporary model predicted widespread suitability across much of the southern and eastern United States. Future projections under the mid-range SSP3 scenario predicted increasing suitability at higher latitudes and elevations. Across all models, suitability was consistently low in arid and semi-arid regions, including along the historical western range limit, suggesting that moisture availability may constrain Cx. coronator distributions. Together, these results highlight the need to incorporate updated occurrence records when modeling invasive mosquito species to strengthen surveillance and control strategies.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.