Addition of NDVI Layers Improves C. tarsalis Habitat Suitability Model
Culex tarsalis is one of the most common vectors for West Nile Virus (WNV) in Montana. WNV affects cattle and humans alike and can have detrimental neurological effects. A WNV prevention project has been trapping mosquitoes across Montana since 2003 and monitoring them for WNV since 2006. This project has connected students and faculty at Carroll College with collaborators at Montana State University. These trapped mosquitoes were sorted for the vector species Cx. tarsalis and tested for WNV using RT-PCR methods. This locality data, for species detection, in conjunction with available geographical database information was used to create a niche envelope model for species habitat suitability. The previous model used climate data, bird-host distribution, and land cover as predictors. The new model included normalized difference vegetation index (NDVI) as an additional predictor and was tested against the other variables using jackknife analysis. This niche modeling was accomplished using MaxEnt software and ArcGis Pro to create predictor layers. Using this model, a better habitat suitability model was created for Cx. tarsalis and thus could lead to an improved WNV risk model in the state of Montana. The WNV risk model could therefore be used to better predict the presence of WNV to the public, and thus prevent future infections.