Supplemental file S3 – R code

data1<-read.table(file="C:\\Users\\paolucci\\Google Drive\\Articoli\\Diapause\\Diap_tot.txt", header=TRUE)
dat<-subset(data1,Sub.Clade!="Corsica")
str(dat)
summary(dat)
names(dat)

library(ggplot2)
require(methods)
library(index)
library(car)
library(predictmeans)
library(nlme)

###Diapause model 
dat29<-dat[-29,] ##remove very influential point from the dataset based on Cook's distance
modd<-lme(Diapause ~  Tmean_n +I(Tmean_n^2)+I(Tmean_n^3), random=~1|Sub.Clade/Site,
data=dat29,na.action=na.omit, method="REML")
summary(modd)
cooks.distance(modd)

###mortality
modm<-lme(Mortality~  Diapause, random=~1|Sub.Clade/Site,
data=dat,na.action=na.omit, method="REML")
summary(modm)


################# Script to produce the figures
## plot base + points
dat29<-dat[-29,] 
pd <- ggplot(dat29, aes(x = Tmean_n, y = Diapause)) + geom_point()
print(pd)

fig2a<-pd + geom_point(aes(colour = factor(Sub.Clade)), size = 3)+
stat_smooth(method = "lm", formula = y ~ x + I(x^2)+I(x^3), size = 1,se = FALSE) +
scale_x_continuous(name="Mean temperature (°C)", limits=c(-2, 13)) +
scale_y_continuous(name="Individuals in prolonged diapause (%)", limits=c(0, 100))+ theme_bw()
 
pm <- ggplot(dat, aes(x = Diapause, y = Mortality)) + geom_point()
print(pm)
fig2b<-pm + geom_point(aes(colour = factor(Sub.Clade)), size = 3)+
stat_smooth(method = "lm", formula = y ~ x , size = 1,se = FALSE) +
scale_x_continuous(name="Individuals in prolonged diapause (%)", limits=c(0, 100)) +
scale_y_continuous(name="Mortality (%)", limits=c(0, 100))+ theme_bw()

# Multiple plot function
# Multiple plot function
#
# ggplot objects can be passed in ..., or to plotlist (as a list of ggplot objects)
# - cols:   Number of columns in layout
# - layout: A matrix specifying the layout. If present, 'cols' is ignored.
#
# If the layout is something like matrix(c(1,2,3,3), nrow=2, byrow=TRUE),
# then plot 1 will go in the upper left, 2 will go in the upper right, and
# 3 will go all the way across the bottom.
#
multiplot <- function(..., plotlist=NULL, file, cols=1, layout=NULL) {
  library(grid)

  # Make a list from the ... arguments and plotlist
  plots <- c(list(...), plotlist)

  numPlots = length(plots)

  # If layout is NULL, then use 'cols' to determine layout
  if (is.null(layout)) {
    # Make the panel
    # ncol: Number of columns of plots
    # nrow: Number of rows needed, calculated from # of cols
    layout <- matrix(seq(1, cols * ceiling(numPlots/cols)),
                    ncol = cols, nrow = ceiling(numPlots/cols))
  }

 if (numPlots==1) {
    print(plots[[1]])

  } else {
    # Set up the page
    grid.newpage()
    pushViewport(viewport(layout = grid.layout(nrow(layout), ncol(layout))))

    # Make each plot, in the correct location
    for (i in 1:numPlots) {
      # Get the i,j matrix positions of the regions that contain this subplot
      matchidx <- as.data.frame(which(layout == i, arr.ind = TRUE))

      print(plots[[i]], vp = viewport(layout.pos.row = matchidx$row,
                                      layout.pos.col = matchidx$col))
    }
  }
}

multiplot(fig2a,fig2b, cols=2)