2.3 Circuit theory-based connectivity models
Circuitscape uses circuit theory to model connectivity in heterogeneous landscapes. Its most common applications include modeling movement and gene flow of plants and animals, as well as identifying areas important for connectivity conservation. We used Circuitscape software (v4.0, www.circuitscape.org) and cost distance functions to assess landscape functional connectivity (McClure et al., 2016 ). First, we built several background layers, which affected species movement and were transferred into raster maps of 1 km2 resolution. Next, these raster maps were converted into a resistance surface based on their values and corresponding weight, reflecting its opposition to species movement. Landscapes are represented as conductive surfaces, with low resistances assigned to landscape features types that are most permeable to movement, and high resistances assigned to movement barriers. The landscape raster cells represent the circuit nodes, and neighboring nodes are connected by resistors. The focal nodes are defined as the cells within the boundaries of core areas. For each pair of core areas, one core area is assumed to be the source node (i.e. the starting point), while the other is considered as the exit node (i.e. the ending point). The starting point node will arbitrarily be connected to a 1 Amp current source, while the ending point will be connected to ground (the exit of the circuit). Current will flow across the resistance surface from the source to the ground. Effective resistances will be calculated iteratively between all pairs of focal nodes. We ran models using the pairwise method and eight neighboring cells. A cumulative current density map was produced, with values at each cell representing the amount of current flowing through the node. Higher current density indicates areas through which dispersers have a high likelihood (or necessity) of passing. High current through a node or branch indicates that removing or converting it will have a high impact on connectivity (McRae et al., 2008 ).