US-IALE 2018

AUTHORS: Marie-Josee Fortin*, Department of Ecology and Evolutionary Biology, University of Toronto, Ontario, CanadaAntonio Golubski, Department of Ecology, Evolution, and Organismal Biology, Kennesaw State University, Kennesaw, Georgia, USA

ABSTRACT: Graph theory has contributed tremendously to spatial ecology by enabling quantitative analyses and modeling of how fragmented landscapes affect organisms movement and dispersal through them. However, the most commonly used network metrics are unable to effectively accommodate important direct and indirect effects within dispersal networks ranging from facilitation or inhibition of dispersal links between habitat patches by accounting for 'stepping stone' patches, microhabitat and matrix characteristics, and anthropogenic landscape features such as roads or dams, or even alternate dispersal routes. We suggest hypergraphs as a novel network framework that is well-suited to investigating networks containing both direct and indirect topological effects. To demonstrate their utility, we develop three potential hypergraph models addressing the aforementioned scenarios: the contribution of 'stepping stone' patches, and the disruption and/or creation of dispersal links by roads, or modification of dispersal link strength by alternate 'competing' routes. As researchers in spatial ecology seek tools that circumvent the limitations of graphs, hypergraphs offer a versatile option whose strengths are allowing to model more realistic animal dispersal behaviors in fragmented landscapes.