Modeling Culex tarsalis Coquillett abundance on the northern Colorado Front Range using a landscape-level approach

Endemic and emerging vector-borne diseases are major health problems, and some of them are unlikely to be eliminated regardless of control efforts. The applications for remote sensing and Geographic Information System (GIS) data include the identification of larval mosquito habitats and forecasting of species distribution and abundance, thereby improving the ability to target control efforts to reduce the risk of transmission of vector-borne pathogens. The practicality for the incorporation of remotely sensed environmental data into a GIS has greatly enhanced the understanding for the spatial and temporal distribution patterns of vectors, thereby enabling improved vector control operations and disease management response. Since the initial detection of West Nile virus (WNV) in Colorado in 2002, the northern part of the Colorado Front Range has come to be recognized as a high-risk area for WNV infections in humans, with 7.5% of the national cases of WNV being reported from Boulder, Weld and Larimer counties during 2003-2011. Culex tarsalis Coquillett is recognized as the primary species of concern in the transmission of WNV to humans along the northern Colorado Front Range. Before implementing the tools needed to control the spread of a vector-borne disease, public health agencies and organization officials must consider the spatial and temporal factors which are driving the interactions between the pathogen, the vertebrate host(s), and the vector(s). A sound understanding of the vector biology will vastly improve the efficacy for its control. Previous research performed on the northern Colorado Front Range used National Land Cover Data (NLCD) and IKONOS satellite imagery to model adult mosquito abundance of Cx. tarsalis. I applied a landscape-level approach to elucidate the effects of landscape-level environmental factors (independent or predictor variables) at multiple spatial extents on monthly adult Cx. tarsalis abundance (dependent variable) in Fort Collins, Loveland and Johnstown, Colorado using GIS technology. Multiple regression models provided empirical evidence for the seasonal variability in adult Cx. tarsalis populations. A more detailed representation for the importance of spatial extent for elevation, slope, distance to and area of irrigated lands and the distance to larval mosquito sites was obtained from this study. Multiple regression models developed using stepAIC were able to explain and forecast monthly adult mosquito abundance with accuracies ranging from 43%-73% in Fort Collins and 36%-68% in Loveland and Johnstown. The expression of environmental variables also differed by month and year. Mean elevation within a 500 m buffer of mosquito trap locations in Fort Collins were negatively correlated with mean monthly adult Cx. tarsalis abundance. A positive relationship existed between mean monthly adult Cx. tarsalis abundance in Fort Collins and the perimeter of larval mosquito habitats within a 1.0 km buffer of traps and the distance to irrigated lands at a spatial extent of 500 m around traps. Mean elevation, slope and distance to larval mosquito sites at a spatial extent of 500 m provided improved predictive power for mean monthly adult Cx. tarsalis abundance in Loveland and Johnstown. My results indicate that landscape and topographic heterogeneity within the study area are interacting on a monthly basis in different ways, resulting in varying populations of adult Cx. tarsalis mosquitoes. I believe it is a combination of interactions between landscape variables identified in this study and weather variables which determines the seasonal spikes in mosquito abundance. The ability to understand the factors that drive vector abundance is critical in managing risk and will aid large scale Integrated Pest Management efforts.

Name thesis:degree_name

Master of Science (M.S.)

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Bioagricultural Sciences and Pest Management

Grantor dc:publisher

Colorado State University. Libraries

Year dc:date.issued

2012

Authors dc:creator

• Schurich, Jessica, author
• Kondratieff, Boris, advisor
• Kumar, Sunil, advisor
• Moore, Chester, committee member
• Eisen, Lars, committee member

• Colorado
• GIS
• landscape
• Culex tarsalis
• West Nile virus

Statement dc:rights

• Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.

Language dc:language.iso

eng, English

Identifier URI

https://doi.org/10.25675/3.018913

Identifier

ETDF2012400451BSPM

OAI identifier oai:identifier

oai:mountainscholar.org:10217/75116