Integrating a generic focal species, metapopulation capacity, and connectivity to identify opportunities to link fragmented habitat

Abstract

Context A challenge devising revegetation strategies in fragmented landscapes is conserving for the widest spectrum of biodiversity. Habitat network reconstruction should improve landscape capacity to maintain species populations. However, the location of revegetation often fails to account for species occurrence and dispersal processes operating across spatial scales. Objectives Our objective was to integrate metapopulation theory with estimates of landscape capacity and dispersal pathways to highlight connectivity gaps. Maintenance of populations could thereby be facilitated through reconnecting habitat networks across regional and broader scales, with assumed benefit for the dispersal needs of less sensitive species. Methods Predicted occupancy and metapopulation capacity were calculated for a generic focal species derived from fragmentation-sensitive woodland birds, mammals and reptiles. A metapopulation connectivity analysis predicted regional dispersal links to identify likely routes through which individuals may move to contribute to the viability of the population.We used the revegetation programmes of the Brigalow–Nandewar Biolinks project, eastern New South Wales, Australia, to demonstrate our approach. Results Landscape capacity of the current landscape varied across the region. Low-value links between populations provided greatest opportunities for revegetation and improved landscape capacity. Where regional connectivity did not indicate a pathway between populations, broader scale connectivity provided guidance for revegetation. Conclusions The metapopulation-based model, coupled with a habitat dispersal network analysis, provided a platform to inform revegetation locations and better support biodiversity. Our approach has application for directing on-ground action to support viable populations, assess the impact of revegetation schemes or monitor the progress of staged implementations.