An integrated approach to model connectivity and identify modules for habitat networks

Abstract

BackgroundRecent studies show that modularity is a crucial aspect of habitat network connectivity that affects the likelihood of population persistence despite unpredictable perturbations, therefore, modularity should be considered while restoring connectivity in highly fragmented landscapes. However, what methods or models can be applied to an integrated analysis of connectivity and modularity are rarely discussed. ObjectivesAn integrated approach is proposed to model connectivity of habitat networks and identify module structure on the basis of comparing Least Cost Path (LCP) with circuit-theoretic model, Informap with Newman Girvan's modularity score Q method. MethodsTo measure connectivity between habitat patches, dispersal probability based on LCP and effective conductance based on circuit-theoretic model were calculated respectively and compared under different cost-weighted distance thresholds of 150, 500, 1000, 2500, 5000, 10,000. Then, results of six scenarios were compared using Infomap and Newman-Girvan's modularity score Q to demonstrate the utility of the two methods in identifying modular structure. These procedures were carried out in a simulated landscape. ResultsThe results show that (1) compared with effective conductance, dispersal probability is more sensitive to the change of cost-weighted distance thresholds.(2) increasing cost-weighted distance thresholds lead to a decrease in current density of pinch points and resistance distance of corridors between two habitats, but it improves habitat connectivity.(3) the results of modules identified by Newman-Girvan's method differ noticeably from that of Infomap, but Infomap can identify the hierarchical module structure of the habitat network. ConclusionOur approach offers an effective means for characterizing functional structure of habitat networks combining connectivity with modularity. Effective conductance has a wider application in identifying important landscape elements, and Infomap can extract multiple levels of network structure, which likely reflect structures determined by different ecological processes at different scales.