Optimize resistance surfaces using Genetic Algorithms
To install this package, execute the following commands in R:
# Install 'devtools' package, if needed
if(!("devtools" %in% list.files(.libPaths()))) {
install.packages("devtools", repo = "http://cran.rstudio.com", dep = TRUE)
}
devtools::install_github("wpeterman/ResistanceGA", build_vignettes = TRUE) # Download package
library(ResistanceGA) # Loads package and the other dependnecies
If installation with build_vignettes = TRUE
fails, try installing the tinytex
R package and then attempt to install ResistanceGA
again.
Once the package is installed, you can view the ‘Getting Started’ vignette in R.
Optimization with CIRCUITSCAPE (v4) is still possible, although not actively supported in the most recent version. If you wish to optimize using CIRCUITSCAPE, it is highly recommended that you install Julia and the CIRCUITSCAPE Julia package. General instructions here. There is also a Julia_Guide
vignette with the package now.
This approach has been developed from the methods first utilized in Peterman et al. (2014). The first formal analysis using ResistanceGA was Ruiz-López et al. (2016). The primary citation for the package is Peterman (2018), Methods in Ecology.
Peterman, W.E., G.M. Connette, R.D. Semlitsch, and L.S. Eggert. 2014. Ecological resistance surfaces predict fine-scale genetic differentiation in a terrestrial woodland salamander. Molecular Ecology 23:2402–2413. PDF
Peterman, W. E. 2018. ResistanceGA: An R package for the optimization of resistance surfaces using genetic algorithms. Methods in Ecology and Evolution 9, 1638–1647.
doi:10.1111/2041-210X.12984. PDF
Ruiz-López, M.J., Barelli, C., Rovero, F., Hodges, K., Roos, C., Peterman, W.E., Ting, N., 2016. A novel landscape genetic approach demonstrates the effects of human disturbance on the Udzungwa red colobus monkey (Procolobus gordonorum). Heredity, Ruiz-López 116, 167–176. https://doi.org/10.1038/hdy.2015.82