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ResistanceGA: An R package for the optimization of resistance surfaces using genetic algorithms
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Abstract
Understanding how landscape features affect functional connectivity among populations is a cornerstone of spatial ecology and landscape genetic analyses. However, parameterization of resistance surfaces that best describe connectivity is a challenging and often subjective process. ResistanceGA is an R package that utilizes a genetic algorithm to optimize resistance surfaces based on pairwise genetic data and effective distances calculated using CIRCUITSCAPE , least cost paths or random‐walk commute times. Functions in this package allow for the optimization of categorical and continuous resistance surfaces, and simultaneous optimization of multiple resistance surfaces. ResistanceGA provides a coherent framework to optimize resistance surfaces without a priori assumptions, conduct model selection, and make inference about the contribution of each surface to total resistance. ResistanceGA fills a void in the landscape genetic toolbox, allowing for unbiased optimization of resistance surfaces and for the simultaneous optimization of multiple resistance surfaces to create novel composite resistance surfaces, but could have broader applicability to other fields of spatial ecological research.
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Improvements to Circuitscape have been capitalized on by other software packages that depend on it, such as ResistanceGA which now calls the Julia version, and Omniscape.jl, our recent re-imagination and Julia implementation of McRae's Python-based Omniscape.
“Improvements to Circuitscape have also been capitalized on by other software packages that depend on it, such as ResistanceGA [55] which now calls the Julia version (see [186]), and Omniscape.jl[51], our recent re-imagination and Julia implementation of McRae's Python-based Omniscape, which was led by Vincent Landau.”
From Circuitscape in julia: empowering dynamic approaches to connectivity assessment (2021) · cites this paper as [55]
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Cited by
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Circuitscape in julia: empowering dynamic approaches to connectivity assessment
Hall, K. R., Anantharaman, R., Landau, V. A., Clark, M., Dickson, B. G., Jones, A., Platt, J., Edelman, A., & Shah, V. B. (2021) · Land · doi:10.3390/land10030301 · Cited by 115
Metadata
- Authors
- Peterman, W. E.
- Affiliations
- School of Environment and Natural Resources The Ohio State University Columbus OH USA
- Venue
- Methods in Ecology and Evolution
- Publisher
- Wiley
- Published
- 2018-02-27
- Volume
- 9
- Issue
- 6
- Pages
- 1638-1647
- ISSN
- 2041-210X
- Cited by
- 280
- References
- 4
- Language
- en
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