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Abstract
<p class="first" id="d7387750e69">Connectivity among populations and habitats is important
for a wide range of ecological
processes. Understanding, preserving, and restoring connectivity in complex landscapes
requires connectivity models and metrics that are reliable, efficient, and process
based. We introduce a new class of ecological connectivity models based in electrical
circuit theory. Although they have been applied in other disciplines, circuit-theoretic
connectivity models are new to ecology. They offer distinct advantages over common
analytic connectivity models, including a theoretical basis in random walk theory
and an ability to evaluate contributions of multiple dispersal pathways. Resistance,
current, and voltage calculated across graphs or raster grids can be related to ecological
processes (such as individual movement and gene flow) that occur across large population
networks or landscapes. Efficient algorithms can quickly solve networks with millions
of nodes, or landscapes with millions of raster cells. Here we review basic circuit
theory, discuss relationships between circuit and random walk theories, and describe
applications in ecology, evolution, and conservation. We provide examples of how circuit
models can be used to predict movement patterns and fates of random walkers in complex
landscapes and to identify important habitat patches and movement corridors for conservation
planning.
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