Graph theoretic methods for examining landscape connectivity and spatial movement patterns: application to the FMF grizzly bear research project

Abstract

Maintaining movement connections across fragmented landscapes is important for the long-term conservation of grizzly bear populations. The focus of this thesis is on applying graph theoretic methods in conjunction with RS, GIS and GPS to study connectivity associated with female grizzly bears in the Yellowhead Ecosystem, Alberta. Centroids of habitat patches provided the basis for graph nodes. Edges representing connections or movement paths between nodes were created using Least-Cost Path (LCP) modeling. Four alternative permeability surfaces were employed to generate functional linkages between habitat patches. Graph structures were developed using 1999 / 2000 GPS data and validated with 2001 I 2002 GPS data for grizzly bears at two spatial scales (individual and landscape levels). Final graph structures were analyzed to quantify connectivity levels and visually explore spatial movement patterns. Results demonstrated the graph theoretic model not only provides measurements related to connectivity but also identifies potential movement corridors across landscapes.