Assessing landscape functional connectivity in a forest carnivore using path selection functions
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Understanding connectivity patterns in relation to habitat fragmentation is essential to landscape management. However, connectivity is often judged from expert opinion or species occurrence patterns, with very few studies considering the actual movements of individuals. Path selection functions provide a promising tool to infer functional connectivity from animal movement data, but its practical application remains scanty.
We aimed to describe functional connectivity patterns in a forest carnivore using path-level analysis, and to explore how connectivity is affected by land cover patterns and road networks.
We radiotracked 22 common genets in a mixed forest-agricultural landscape of southern Portugal. We developed path selection functions discriminating between observed and random paths in relation to landscape variables. These functions were used together with land cover information to map conductance surfaces.
Genets moved preferentially within forest patches and close to riparian habitats. Functional connectivity declined with increasing road density, but increased with the proximity of culverts, viaducts and bridges. Functional connectivity was favoured by large forest patches, and by the presence of riparian areas providing corridors within open agricultural land. Roads reduced connectivity by dissecting forest patches, but had less effect on riparian corridors due to the presence of crossing structures.
Genet movements were jointly affected by the spatial distribution of suitable habitats, and the presence of a road network dissecting such habitats and creating obstacles in areas otherwise permeable to animal movement. Overall, the study showed the value of path-level analysis to assess functional connectivity patterns in human-modified landscapes.
KeywordsConditional logistic regression Forest carnivores Genetta genetta Landscape conductance Movement behaviour Path-level analysis Road ecology
This study was funded by the Fundação para a Ciência e Tecnologia through grant SFRH/BD/66393/2009 to FC. Logistic support was given by the Conservation Biology Unit and Institute of Mediterranean Agricultural and Environmental Sciences, both from the University of Évora. Ana Galantinho, Pedro Costa and the MOVE project team collaborated in field work; Giovanni Manghi helped in GIS processing, and José Potes (Veterinarian Hospital, University of Évora) supervised the handling of genets. We thank the careful review of the manuscript by Santiago Saura and two anonymous reviewers. Authorization for capturing, handling and tracking genets was provided by the Instituto para a Conservação da Natureza e da Biodiversidade.
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