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Today we are presenting a new package, lconnect. This package is intended to be a very simple approach to derive landscape connectivity metrics. Many of these metrics come from the interpretation of landscape as graphs.
Additionally, it also provides a function to prioritize landscape patches based on their contribution to the overall landscape connectivity. For now this function works only with the Integral Index of connectivity, by Pascual-Hortal & Saura (2006).
For now we only have a development version in GitHub, but a more definitive version should be uploaded to CRAN in the coming days.
Here’s a brief tutorial!
First install the package:
#load package from GitHub
#install.packages("devtools")
#remove.packages("lconnect", lib="~/R/win-library/3.5")
library(devtools)
install_github("FMestre1/lconnect")
library(lconnect)
Then, upload the landscape shapefile …
#Load data
vec_path <- system.file("extdata/vec_projected.shp", package = "lconnect")
…and create a ‘lconnect’ class object:
#upload landscape land <- upload_land(vec_path, habitat = 1, max_dist = 500) class(land) ## [1] "lconnect"
And now, let’s plot it:
plot(land, main="Landscape clusters")
If we wish we can derive patch importance (the contribution of each individual patch to the overall connectivity):
land1 <- patch_imp(land, metric="IIC") ## [1] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.1039501 ## [7] 0.1039501 0.0000000 0.1039501 0.0000000 0.0000000 0.1039501 ## [13] 0.3118503 21.9334719 0.0000000 15.5925156 2.5987526 0.1039501 ## [19] 0.1039501 0.2079002 0.0000000 0.0000000 0.0000000 0.0000000 ## [25] 0.9355509 0.0000000 14.2411642 2.9106029 0.2079002 12.9937630 ## [31] 0.3118503 0.7276507 0.0000000 7.5883576 0.5197505 70.2702703 class(land1)
Which produces an object of the class ‘pimp’:
## [1] "pimp"
And, finally, we can also plot the relative contribution of each patch to the landscape connectivity:
plot(land1, main="Patch prioritization (%)")
And that’s it!
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