Mapping organism spread potential by integrating dispersal and transportation processes using graph theory and catchment areas
Abstract:Geographical concepts and technologies are highly valued and have found useful applications in a wide range of geographical disciplines. Unfortunately there is a lack of communication between disciplines such as landscape ecology and transport geography. This presents a barrier to addressing geographical issues such as the spread of organisms, which in some instances require an integrated geography approach. In an attempt to encourage integrated geographical research on organism spread, that uses existing research from landscape ecology and transport geography, an integrated conceptual and technical framework is presented that could be used to produce maps that differentiate areas based on their spread potential. Conceptually, the terms patch connectivity and accessibility are recognised as being near identical in scope, and as such are suggested a useful basis for approaching the integration of movement modelling used in landscape ecology and transport geography. Technically, this integration can be achieved using modelling methodologies established in both disciplines, as the graph theory-based shortest path Dijkstra's Algorithm used in transport geography is demonstrated to be equivalent to raster GIS least-cost modelling used in landscape ecology. This conceptual and technical common ground has been used to create an analytical approach based on catchment areas that can map differing levels of spread potential across a landscape. A demonstration of how these graph theory methods can also be integrated to map spread potential as a combined function of both organism dispersal and transportation is also provided. The practical challenges and assumptions in applying the methodology are also highlighted, and to facilitate understanding and further development of the approach presented, example scripts and data for producing maps of spread potential are provided for use with a variety of software.
Document Type: Research Article
Affiliations: Centre for Biodiversity and Biosecurity, School of Environment, The University of Auckland, Auckland, New Zealand
Publication date: 2012-03-01