Funded Research Projects: FOREST ECOLOGY

Collaborative Research: A landscape resistance mapping approach to understanding species invasion patterns

Research Sponsored By: National Science Foundation (NSF)
Principal Investigator: Patrick Tobin
Project Description
Understanding the factors that affect species range edges is fundamental to ecology. An understanding of these factors is critical to both predicting invasive species spread and informing species conservation efforts. At a range edge, movement patterns interplay with local population dynamics to determine spread dynamics. Regional patterns are formed by interactions between local population dynamics and landscape features. For invasive species these factors determine the rate and extent of spatial spread, and ultimately the consequences for local ecosystems. This project will center on a fundamental question in the field of spatial ecology: What are the drivers of geographical range expansion and how do multi-scale processes interact to shape invasion patterns? Few systems provide the spatiotemporal resolution to test population dynamics at an invasion front, primarily due to the challenges of studying low density populations outside of the established range, which consequently limits our broader understanding of invasive species range dynamics. We overcome this limitation by using the North American invasion of the gypsy moth and an exhaustive spatiotemporal dataset that annually quantifies the 2000 km range edge. This project combines cutting-edge landscape genetics with detailed analyses of local population dynamics to inform models simulating how local population processes, landscape connectivity, and anthropogenic movement of propagules integratively drive spread patterns. The research will address three main objectives: 1) use spatial genetic lineages to understand how landscape features and human traffic patterns affect movement, 2) quantify effects of landscape features and spatiotemporal covariance on the dynamics of low-density populations, and 3) determine how landscape features, human movement, and local population processes drive large-scale invasion patterns by simulating invasion on layered maps of population dynamic and movement parameters.