Using resistance distance from circuit theory to model dispersal through habitat corridors

Thiele J, Buchholz S, Schirmel J

Abstract

Aims: Resistance distance, based on circuit theory, is a promising metric for modelling effects of landscape configuration on dispersal of organisms and the resulting population and community patterns. The values of resistance distance reflect the likelihood of a random walker to reach from a source to a certain destination in the landscape. Although it has successfully been used to model genetic structures of animal populations, where it most often outperforms other isolation metrics, there are hardly any applications to plants and, in particular, to plant community data. Our aims were to test if resistance distance was a suitable metric for studying dispersal processes of plants in narrow habitat corridors (linear landscape elements). This would be the case, if dispersal processes (seed dispersal and migration) resembled random walks. Further, we compared the model performance of resistance distance against least-cost distance and Euclidean distance. Finally, we tested the suitability of different cost surfaces for calculations of least-cost and resistance distance. Methods: We used data from 50 vegetation plots located on semi-natural linear landscape elements (field margins, ditches, road verges) in eight agricultural landscapes of Northwest Germany. We mapped linear landscape elements, including hedges and tree rows, from aerial images in a Geographic Information System, converted the maps into raster layers, and assigned resistance values to the raster cells, where all cells outside of linear landscape elements received infinite resistance and, thus, represented barriers to dispersal. For all pairs of plots within study areas, we calculated Jaccard similarity assuming that it was a proxy (or correlate) of dispersal events between plots. Further, we calculated resistance distance and least-cost distance of the network of linear landscape elements and Euclidean distance between the plots. We modelled the effects of distance metrics on community similarity using binomial Generalized Linear Mixed Models. Important findings: Euclidean distance was clearly the least suitable isolation metrics. Further, we found that resistance distance performed better than least-cost distance at modelling Jaccard similarity. Predictions varied markedly between the two distance metrics suggesting that resistance distance comprises additional information about the landscape beyond spatial distance, such as the possible presence of multiple pathways between plots. Cost surfaces with equal cell-level resistances for all types of linear landscape elements performed better than more complex ones with habitat-specific resistances. We conclude that resistance distance is a highly suitable measure of isolation or, inversely, connectivity for studying dispersal processes of plants within habitat corridors. It is likely also suitable for assessing landscape permeability in other landscape types with areal habitats instead of narrow corridors. Resistance distance holds the potential to improve assessments of isolation (or connectivity) for models of regional population and meta-community dynamics.