Description:
By defining ecological networks as graphs, graph-theoretic analyses become possible, allowing the identification of critical patches (nodes) and dispersal links (edges) between patches. However, standard application of graph theory in landscape ecology assumes networks that are static in time. Under climate change, this will clearly not be the case. We must extent the definition of graphs to incorporate the temporal dimension besides the usual spatial dimensions. These spatio-temporal graphs thus define connectivity in space and time, and their analysis should give us insight in how well future (climate) suitable habitat is connected to current suitable habitat.
Research objectives:
In the project we test different definitions of spatio-temporal networks with respect to how weight is assigned to nodes and edges, we test several commonly used graph indices, and if necessary we propose adapted or new ones. Care is taken to test the results with spatially explicit population models, including incidence function and age-structured population models adapted to deal with dynamic landscapes. 2D and 3D visualization techniques will be evaluated, to present the results of such analyses, and to communicate them to policy makers.
Results and products:
Products
- Methodology to analyze dynamic ecological networks represented as spatio-temporal graphs of species habitat
- Expertise on application of graph-theoretic approaches to landscape connectivity, relevant to both dynamic and static landscapes
- Publication in peer-reviewed journal
- Presentation at international symposium
- User-friendly software for application of the method, as part of and integrated in the existing toolbox for ecological network analysis |
