Abstract¶
The modeling of ecological connectivity across networks and landscapes is an active research area that spans the disciplines of ecology, conservation, and population genetics. Recently, concepts and algorithms from electrical circuit theory have been adapted to address these problems. The approach is based on linkages between circuit and random walk theories, and has several advantages over previous analytic approaches, including incorporation of multiple dispersal pathways into analyses. Here we describe Circuitscape, a computational tool developed for modeling landscape connectivity using circuit theory. Our Python implementation can quickly solve networks with millions of nodes, or landscapes with millions of raster cells.
