The relationship between least-cost and resistance distance.

Least-cost modelling and circuit theory are common analogs used in ecology and evolution to model gene flow or animal movement across landscapes. Least-cost modelling estimates the least-cost distance, whereas circuit theory estimates resistance distance. The bias added in choosing one method over t...

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Main Authors: Robby R Marrotte, Jeff Bowman
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5369686?pdf=render
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spelling doaj-4b08ef1fa6fc4495812dad751916a1092020-11-24T21:52:03ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01123e017421210.1371/journal.pone.0174212The relationship between least-cost and resistance distance.Robby R MarrotteJeff BowmanLeast-cost modelling and circuit theory are common analogs used in ecology and evolution to model gene flow or animal movement across landscapes. Least-cost modelling estimates the least-cost distance, whereas circuit theory estimates resistance distance. The bias added in choosing one method over the other has not been well documented. We designed an experiment to test whether both methods were linearly related. We also tested the sensitivity of these metrics to variation in Euclidean distance, spatial autocorrelation, the number of pixels representing the landscape, and data aggregation. We found that least-cost and resistance distance were not linearly related unless a transformation was applied. Resistance distance was less sensitive to the number of pixels representing a landscape and was also less sensitive than least-cost distance to the Euclidean distance between nodes. Spatial autocorrelation did not affect either method or the relationship between methods. Resistance distance was more sensitive to aggregation in any form compared to least-cost distance. Therefore, the metric used to infer movement or gene flow and the manipulations applied to the data used to calculate these metrics may govern findings.http://europepmc.org/articles/PMC5369686?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Robby R Marrotte
Jeff Bowman
spellingShingle Robby R Marrotte
Jeff Bowman
The relationship between least-cost and resistance distance.
PLoS ONE
author_facet Robby R Marrotte
Jeff Bowman
author_sort Robby R Marrotte
title The relationship between least-cost and resistance distance.
title_short The relationship between least-cost and resistance distance.
title_full The relationship between least-cost and resistance distance.
title_fullStr The relationship between least-cost and resistance distance.
title_full_unstemmed The relationship between least-cost and resistance distance.
title_sort relationship between least-cost and resistance distance.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2017-01-01
description Least-cost modelling and circuit theory are common analogs used in ecology and evolution to model gene flow or animal movement across landscapes. Least-cost modelling estimates the least-cost distance, whereas circuit theory estimates resistance distance. The bias added in choosing one method over the other has not been well documented. We designed an experiment to test whether both methods were linearly related. We also tested the sensitivity of these metrics to variation in Euclidean distance, spatial autocorrelation, the number of pixels representing the landscape, and data aggregation. We found that least-cost and resistance distance were not linearly related unless a transformation was applied. Resistance distance was less sensitive to the number of pixels representing a landscape and was also less sensitive than least-cost distance to the Euclidean distance between nodes. Spatial autocorrelation did not affect either method or the relationship between methods. Resistance distance was more sensitive to aggregation in any form compared to least-cost distance. Therefore, the metric used to infer movement or gene flow and the manipulations applied to the data used to calculate these metrics may govern findings.
url http://europepmc.org/articles/PMC5369686?pdf=render
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