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Finding and Filling the "Cracks" In Resistance Surfaces for Least-cost Modeling

Kristina Rothley, Simon Fraser University


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Least-cost modeling is an increasingly popular method used to measure the effective
distance between habitat patches and to assess the connectivity of existing landscapes
or potential reserves. For least-cost models to be reliable and credible, however,
the validity of input data must
be demonstrated. Least-cost modelers must also exercise extreme caution
when using any GIS-based analysis of this kind. Technical issues associated with
the raster-based representation of spatial data may introduce errors in otherwise
correct data that nullify results. In this paper, I address the potential presence
of "cracks" in the resistance input
layer of least-cost modeling exercises. Cracks result when narrow, costly
features, such as roads or train tracks, are represented in raster form. These
cracks lead to the erroneous identification of nonexistent "shortcuts"
across truly expensive barriers. In this paper, I use a hypothetical example
to explain resistance-layer cracks, how they occur, and the errors they generate
with respect to least-cost modeling. I then present a simple algorithm to reveal
the location of cracks and one approach to filling the cracks. Finally, these
methods are demonstrated on a real data set in which more than 1% of the raster
cells are shown to be cracks. The negative repercussions of faulty resistance
layers when conducting least-cost modeling can not be overstated. On the one
hand, unimportant or nonexistent least-cost paths on a landscape may be mislabeled
as important. As a result, conservation resources committed to protecting these paths
will be wasted. Conversely, truly critical corridors may be overlooked, jeopardizing
the organisms that rely on them.

Key words

connectivity analysis, cracks, least-cost modeling, resistance layers.

Copyright © 2005 by the author(s). Published here under license by The Resilience Alliance. This article is under a Creative Commons Attribution 4.0 International License. You may share and adapt the work provided the original author and source are credited, you indicate whether any changes were made, and you include a link to the license.

Ecology and Society. ISSN: 1708-3087