shift.pie.ggplot {AlleleShift}

Shifts of Allele Frequencies as Response to Climate Change

Description

The function shows changes in allele frequencies between the baseline and future/past climate.

Usage

shift.pie.ggplot(baseline.pie, future.pie,
	manual.colour.values = c("black", "grey", "firebrick3", "chartreuse4"),
	manual.colour.codes = c("A baseline ", "B", "A decreasing", "A increasing"))

pie.baker(freq.in, sort.index= "Pop.index",
	mean.change = FALSE, change.FUN = stats::median,
	freq.focus = "Allele.freq", ypos = 0,
	r0 = 0.1, r = 0.5, focus = 0.2 )

Arguments

baseline.pie, future.pie

Result from AlleleShift::pie.baker.

manual.colour.values

Colours to be used in the plot.

manual.colour.codes

Sequence for the manual colour values.

freq.in

Result from AlleleShift::predFreq.

sort.index

Sequence of the populations in the plot.

mean.change

Aggregate changes among alleles.

change.FUN

Function used the aggregate changes.

freq.focus

Allele frequency for which to calculate statistics, either 'Allele.freq' or 'Freq.e2'.

ypos, r0, r, focus

Arguments used for plotting, mainly as in geom_arc_bar

Value

The function generates a ggplot that depicts changes between baseline and future/past allele frequencies of the populations.

Author(s)

Roeland Kindt (World Agroforestry, CIFOR-ICRAF)

See Also

shift.dot.ggplot, shift.moon.ggplot, shift.waffle.ggplot, shift.surf.ggplot

Examples

# The data can be obtained via the count.model and freq.model calibrations.
# These procedures are not repeated here.
data(Poptri.freq.baseline)
data(Poptri.freq.future)

Poptri.baseline.pie <- pie.baker(Poptri.freq.baseline, r0=0.1,
                                 sort.index="Latitude.index")

Poptri.future.pie <- pie.baker(Poptri.freq.future, r0=0.1, 
                        freq.focus="Freq.e2",
                        sort.index="Latitude.index",
                        ypos=1)

ggpie1 <- shift.pie.ggplot(Poptri.baseline.pie, 
                           Poptri.future.pie)
ggpie1


# create an animation

## Not run: 

library(ggplot2)
library(ggforce)
library(gganimate)
library(gifski)
library(transformr)

# The data is an interpolation and extrapolation between the baseline and future climate.
# For actual application, interpolate between climate data from available sources

data(Poptri.1985to2085)

decades <- sort(unique(Poptri.1985to2085$Decade))

for (d in 1:length(decades)) {
  decade.focal <- decades[d]
  decade.data <- Poptri.1985to2085[Poptri.1985to2085$Decade == decade.focal, ]
  decade.pie <- pie.baker(decade.data, r0=0.1, 
                        freq.focus="Freq.e2",
                        sort.index="Latitude.index",
                        ypos=1)
  decade.pie <- cbind(Decade=rep(decade.focal, nrow(decade.pie)), decade.pie)
  
  if (d == 1) {
    future.pies <- decade.pie
  }else{
    future.pies <- rbind(future.pies, decade.pie)
  }
}

np <- length(unique(Poptri.baseline.pie$Pop))
manual.colour.values <- c("black", "grey", "firebrick3", "chartreuse4")
  
ggpie.all <- ggplot(data=future.pies, group=Decade) +
  scale_x_continuous(limits=c(0.5, np+0.5),
                     breaks=seq(from=1, to=np, by=1),
                     labels=levels(Poptri.baseline.pie$Pop)) +
  geom_arc_bar(data=Poptri.baseline.pie,
               aes(x0=sort.index, y0=ypos, r0=r0, r=0.4, 
                   start=start, end=end, fill=colour),
               size=0.04, alpha=1, colour="snow1") +                    
  geom_arc_bar(data=future.pies,
               aes(x0=sort.index, y0=ypos, r0=r0, r=0.4, 
                   start=start, end=end, fill=change.colour),
               size=0.04, alpha=1, colour="snow1") + 
  geom_point(data=subset(future.pies, increasing==TRUE),
            aes(x=sort.index, y=ypos),
            size=5, shape=21, fill=manual.colour.values[4], stroke=0.03, show.legend=FALSE) +
  geom_point(data=subset(future.pies, increasing==FALSE),
            aes(x=sort.index, y=ypos),
            size=5, shape=21, fill=manual.colour.values[3], stroke=0.03, show.legend=FALSE) +
  coord_flip() +
  xlab(element_blank()) +
  ylab(element_blank()) +
  labs(fill=" ") +
  scale_fill_manual(values=manual.colour.values, 
                    labels=c("A baseline ", "B", "A decreasing", "A increasing")) +
  theme(panel.grid = element_blank()) +
  theme(axis.text.x=element_blank()) +
  theme(axis.ticks.x = element_blank()) +
  theme(legend.position="top") +
  facet_grid( ~ Allele, scales="free")

ggpie.all
  
# note this will take quite a while!
ggpie.anim <- ggpie.all + 
  transition_states(as.factor(Decade), transition_length = 10, state_length = 100) +
  labs(title = "Decade: {closest_state}s")

ggpie.anim2 <- animate(ggpie.anim, fps=5, width=1280, height=720)

getwd()
anim_save(filename="Allele shift pie animation.gif", animation=ggpie.anim2)


## End(Not run)