Ecological connectivity: Flow connectivity vs. least cost modelling
Year: 2014
Type: article
Abstract: Recently I have introduced a modelling approach (flow connectivity) to ecological connectivity that is alternative to circuit theory, and is able to fix the weak point of the "from-to" connectivity approach. Flow connectivity also holds for mountain and hilly landscapes that are not composed of source and sink habitats. In this paper I compare the recently-introduced flow connectivity (FC) modelling to the commonly-used least cost (LC) modelling. LC path analysis is an attractive technique for analysing and designing habitat corridors because it: 1) allows quantitative comparisons of potential movement routes over large study areas, 2) can incorporate simple or complex models of habitat effects on movement and 3) offers the potential to escape the limitations of analyses based solely on structural connectivity (i.e. designating areas as patch, matrix or corridor) by modelling connectivity as it might be perceived by a species on a landscape. I evidence here that flow connectivity has the same advantages when compared to LC modelling as with regard to circuit theory. Four main differences emerged. LC modelling a) is a "from-to" approach to ecological connectivity, b) it seeks global path optimization, c) it allows for biotic paths where the biotic effort is ascending, and d) it is undirected (it does not depend on the direction of the path). FC has opposite properties. Moreover, costdistance models are based on two biologically improbable assumptions: (1) dispersers have complete knowledge of their surroundings, and (2) they do select the least cost route from this information. Instead, the predicted path lengths and the biotic efforts predicted by both FC and LC modelling in a case study about wolf in the Ceno valley (Parma, Italy) resulted not significantly different, but this result is contingent upon the case study.
Author: Alessandro Ferrarini
Institution: University of Parma
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
SDG: Life on land
Open Access status: green
OpenAlex ID: W2183442023