A Graph‐Theory Framework for Evaluating Landscape Connectivity and Conservation Planning

摘要: Connectivity of habitat patches is thought to be important for movement genes, individuals, populations, and species over multiple temporal spatial scales. We used graph theory characterize aspects landscape connectivity in a network the North Carolina Piedmont (U.S.A). compared this with simulated networks known topology, resistance disturbance, rate movement. introduced measures such as compartmentalization clustering, which can identify locations on that may especially resilient human development or areas most suitable conservation. Our analyses indicated songbirds was well connected. Furthermore, had commonalities planar networks, exhibit slow movement, scale-free are resistant random disturbances. These results suggest high enough prevent negative consequences isolation but not so allow rapid spread disease. graph-theory framework provided insight into regional emergent global properties an intuitive visual way allowed us make inferences about rates paths movements vulnerability disturbance. This approach applied easily assessing any fragmented patchy landscape.