monitoringOutcomes

Overview

R functions to reproduce the analysis carried out in : "Identifying key needs for the integration of social–ecological outcomes in arctic wildlife monitoring" (DOI: 10.1111/cobi.13257).

The following R functions (see R/) relate to the following figures.

• Fig 1: dartdiag.R
• Fig 2a-b: walktrapdendro4.R
• Fig 2c: edge_clustering.R
• Fig 3: connectivity2a.R
• Fig S3: 3netscomp2a.R

The sets of links and nodes required to create the figures are included in the data folder (basically the data associated with the paper); three versions are furnished. See the How to section to reproduce the figures of the manuscript. Note that for some figures, the nodes coordinates are randomized to avoid such behavior, we used set.seed() below.

An R package?

We have used a standard R package to:

1. efficiently assess the quality of our code (here we simply used R CMD check);

2. readily share our code.

We however acknowledge that despite the form of a standard R package, the code presented is more a organized script than a package (i.e. functions included are not general).

To install this package, one very convenient way is to use devtools. Note that one of the packages required, graphicsutils, is not available on the CRAN, so it should be installed with devtools too. So one way to install this package is to type the following line in your R console:

install.packages("devtools")
devtools::install_github("inSileco/graphicsutils")
devtools::install_github("KevCaz/monitoringOutcomes")

How to

Before calling any function, load the package:

devtools::load_all()

Figure 1

library(Cairo)
vec_col <-  c("#f1bf5f", "#058544", "#27ade3")
data(nodes)
data(links)

## PNG
png("inst/fig/fig1.png", width=8, height=10, units="in", res=300)
  dartdiag(nodes, links, vec_col, arrowPNG = TRUE)
dev.off()

## SVG
CairoSVG("inst/fig/fig1.svg", width=8, height=10)
  dartdiag(nodes, links, vec_col)
dev.off()

Figure 2 a and b

data(nodes2)
data(links2)

## PNG
set.seed(3466)
png("inst/fig/fig2ab.png", units="in", res=300, width=8.5, heigh=6)
  walktrap_dendro(links2, nodes2, vec_col)
dev.off()

## SVG
set.seed(3466)
CairoSVG("inst/fig/fig2ab.svg", width=8.5, heigh=6)
  walktrap_dendro(links2, nodes2, vec_col)
dev.off()

Figure 2c

data(nodes3)
data(links3)
## PNG
png("inst/fig/fig2c.png", units="in", res=300, width=8.5, heigh=6)
  connectivity2a(links3, nodes3,  cex_crl = 1.5)
dev.off()

## SVG
CairoSVG("inst/fig/fig2c.svg", width = 8.5, height = 6)
  connectivity2a(links3, nodes3, vec_col, cex_crl = 1.5)
dev.off()

Figure 3

set.seed(2)
data(links2)
data(nodes2)
vec_names <- sort(gsub(paste0(nodes2[,1L], "  ", nodes2[,2L]), pattern= "^n", replacement = ""))
png("inst/fig/fig3.png", units = "in", res = 300, width = 8,  height = 4.5)
  edge_clustering(links2, vec_names, vec_col)
dev.off()

## SVG
set.seed(2)
CairoSVG("inst/fig/fig3.svg",  width = 8, height = 4.5)
  edge_clustering(links2, vec_names, vec_col)
dev.off()

Figure S3

set.seed(81932)
data(nodes2)
data(links2)
png("inst/fig/figS3.png", units="in", res=300, width = 8, height = 5)
  netcomp2a(links2, nodes2, vec_col)
dev.off()

## SVG
set.seed(81932)
CairoSVG("inst/fig/figS3.svg", width = 8, height =  5)
  netcomp2a(links2, nodes2, vec_col)
dev.off()