Data from: The effect of cost surface parameterization on landscape resistance estimates
A cost or resistance surface is a representation of a landscape’s permeability to animal movement or gene flow and is a tool for measuring functional connectivity in landscape ecology and genetics studies. Parameterizing cost surfaces by assigning weights to different landscape elements has been cha...
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Zusammenfassung: | A cost or resistance surface is a representation of a landscape’s
permeability to animal movement or gene flow and is a tool for measuring
functional connectivity in landscape ecology and genetics studies.
Parameterizing cost surfaces by assigning weights to different landscape
elements has been challenging however, because true costs are rarely
known; thus, expert opinion is often used to derive relative weights.
Assigning weights would be made easier if the sensitivity of different
landscape resistance estimates to relative costs was known. We carried out
a sensitivity analysis of three methods to parameterize a cost surface and
two models of landscape permeability: least cost path and effective
resistance. We found two qualitatively different responses to varying cost
weights: linear and asymptotic changes. The most sensitive models (i.e.
those leading to linear change) were accumulated least cost and effective
resistance estimates on a surface coded as resistance (i.e. where
high-quality elements were held constant at a low-value, and low-quality
elements were varied at higher values). All other cost surface scenarios
led to asymptotic change. Developing a cost surface that produces a linear
response of landscape resistance estimates to cost weight variation will
improve the accuracy of functional connectivity estimates, especially when
cost weights are selected through statistical model fitting procedures. On
the other hand, for studies where cost weights are unknown and model
selection is not being used, methods where resistance estimates vary
asymptotically with cost weights may be more appropriate, because of their
relative insensitivity to parameterization. |
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DOI: | 10.5061/dryad.6b678210 |