Dr. Lindsay Campbell

Assistant Professor

I am interdisciplinary research scientist with a focus on the spatial ecology of medically important arthropod vectors. My research focuses on investigating distributions, abundances, and functional connectivity of vector species. I use a variety of tool sets to investigate these questions, including geographic information systems and remotely-sensed satellite imagery, and I draw from methods developed in the fields of distributional ecology, landscape ecology, and landscape genetics.

Identifying the potential distribution of medically important vector species provides a first step toward understanding where pathogen transmission may occur. Several factors influence vector distributions, including broad-scale climatic factors, such as temperature and precipitation patterns, and local biotic habitats, including land use and cover. Changes in vector distributions may result from a variety of sources, including movement of vector species into new geographic regions, human disturbance to the landscape, and climate change. Advances in modeling approaches facilitate prediction of vector species distributions across geographic areas, and outputs from these models produces maps showing where there may be suitable habitats for a species to survive. These maps can be used to inform veterinary and public health agencies, along with vector control districts, to help improve surveillance efforts.  

In addition to identifying vector distributions, several vector-borne and zoonotic disease systems experience periodic escalations in disease incidence, referred to as epizootics. Often, these periods result in large-scale outbreaks in spillover hosts, such as humans or livestock. The periodic nature of these events indicate that disease system components must converge in a specific way for widespread transmission to occur. In many cases epizootic potential links closely to environmental conditions that impact vector densities and abundances. Modeling approaches that incorporate field collected abundance data and remotely sensed environmental variables, such as temperature and precipitation, can identify environmental precursors that contribute to high vector densities and abundances, providing critical information about where and when potential transmission may occur.

The field of landscape genetics combines population genetics with landscape ecology to investigate genetic differentiation and diversity across the landscape. A key component to these analyses is identifying the influence of environmental variables on observed patterns. This approach is ideal for spatial vector ecology because understanding patterns of functional connectivity, or “the degree to which landscapes impede or facilitate species movements,” provides the opportunity to delineate patterns in vector populations, while gaining knowledge regarding environmental drivers that contribute to connectivity. Modeling approaches that utilize molecular genetic data with landscape topography, land use and land cover, and climate variables can reveal patterns across geographic areas. This information can be used to inform vector control strategies, work toward interventions, and inform public health agencies of potential pathogen transmission risk.