The sensitivity of leastcost habitat graphs to re

Authors: Bronwyn Rayfield MarieJosée Fortin Andrew Fall

Publish Date: 2009/12/10

Volume: 25, Issue: 4, Pages: 519-532

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Abstract

Maintaining and restoring connectivity among highquality habitat patches is recognized as an important goal for the conservation of animal populations To provide an efficient measure of potential connectivity pathways in heterogeneous landscapes leastcost route analysis has been combined with graphtheoretical techniques In this study we use spatially explicit leastcost habitat graphs to examine how matrix quality and spatial configuration influence assessments of habitat connectivity We generated artificial landscapes comprised of three landcover types ranked consistently from low to high quality inhospitable matrix hospitable matrix and habitat We controlled the area and degree of fragmentation of each landcover in a factorial experiment for a total of 20 combinations replicated 100 times In each landscape we compared eight sets of relative landcover qualities cost values of 1 for habitat between 15 and 150 for hospitable matrix and 3–10000 for inhospitable matrix We found that the spatial location of leastcost routes was sensitive to differences in relative cost values assigned to landcover types and that the degree of sensitivity depended on the spatial structure of the landscape Highest sensitivity was found in landscapes with fragmented habitat and between 20 and 50 hospitable matrix sensitivity decreased as habitat fragmentation decreased and the amount of hospitable matrix increased As a means of coping with this sensitivity we propose identifying multiple lowcost routes between pairs of habitat patches that collectively delineate probable movement zones These probable movement zones account for uncertainty in leastcost routes and may be more robust to variation in landcover cost valuesWe would like to thank Josie Hughes for assistance with the implementation of the placement algorithm used to create simulated maps We are also grateful to Stephen Smith who was invaluable with data management and information technology services Many thanks are extended to the researchers in LE Lab and especially to Patrick James for helpful discussions and valuable comments on drafts Funding was generously provided by NSERC as a CGS to BR and an NSERC Discovery Grant to MJF

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