Modeling Culex tarsalis abundance on the northern Colorado front range using a landscape-level approach

Area of Science:

• Environmental Science
• Medical Entomology
• Geographic Information Science

Background:

• Mosquito-borne diseases, such as West Nile virus (WNV), pose significant public health risks.
• Effective mosquito control relies on understanding the ecological factors influencing mosquito populations.
• Remote sensing and GIS offer powerful tools for mapping and predicting mosquito habitats.

Purpose of the Study:

• To investigate the relationship between landscape heterogeneity and the abundance of Culex tarsalis, the primary WNV vector in Colorado.
• To develop predictive models for Cx. tarsalis abundance using GIS-based environmental data.
• To inform operational mosquito control strategies by identifying key larval habitats.

Main Methods:

• Collected adult Cx. tarsalis abundance data using CDC miniature light traps over four years (2007-2010).
• Utilized Geographic Information System (GIS) data to analyze environmental variables at multiple spatial extents.
• Developed multiple regression models to predict monthly Cx. tarsalis abundance based on landscape features.

Main Results:

• Cx. tarsalis abundance was negatively correlated with elevation, indicating higher populations in low-lying areas.
• The perimeter of larval sites at a 500m spatial extent was a significant predictor of mosquito abundance.
• Irrigated crops at a 500m extent improved model predictions, particularly in August, highlighting the role of irrigation in habitat creation.

Conclusions:

• Landscape features, especially irrigation and water management, are critical for Cx. tarsalis larval habitat suitability.
• GIS-based models can accurately predict Cx. tarsalis abundance and identify high-risk areas for control.
• Operational application of these findings can optimize larval control efforts, reducing WNV transmission risk.