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 ).