Usage
Atlhough these data are suitable for many kinds of analyses, the primary reason that I made this package is so I can easily make my own plots of these data. Here’s how I typically start with plotting the oxygen isotope data. I have set limits on the x-axis so it only shows 0-250 ka because that’s what I’m interested in:
library(ggplot2)
ggplot(lisiecki2005,
aes(Time,
d18O)) +
geom_line() +
scale_x_continuous(limits = c(0, 250),
name = "x 1000 years ago") +
scale_y_reverse(name = bquote(delta^18*O)) +
theme_bw()
And here’s how I start to plot the sea level data:
ggplot(spratt2016,
aes(age_calkaBP,
SeaLev_shortPC1)) +
geom_line() +
scale_x_continuous(limits = c(0, 250),
name = "x 1000 years ago") +
scale_y_continuous(name = "Sea Level, meters above present day") +
theme_bw()
Often we want to see the Marine isotope stages on these plots also.
This package includes the dataset LR04_MISboundaries of
start and end dates for each stage, so we can draw these stages easily.
I obtained these data from Lorraine Lisiecki’s web page: http://lorraine-lisiecki.com/LR04_MISboundaries.txt
Some care is required to get the MIS numbers positions in
easy-to-read locations. Here I use rep() and
seq() to help position the numbers.
# subset the MIS data for the last 250 ka years
mis_last_250ka <- LR04_MISboundaries[LR04_MISboundaries$LR04_Age_ka_start <= 250, ]
# plot the oxygen istope data line on top of the MIS lines
ggplot() +
geom_vline(data = mis_last_250ka, # add MIS lines
aes(xintercept = LR04_Age_ka_start),
colour = "blue") +
annotate("text",
label = mis_last_250ka$label_MIS,
x = mis_last_250ka$LR04_Age_ka_mid,
y = c(rep(3.0, 4),
seq(3.2, 2.7, length.out = 6),
rep(3.0, 2)),
size = 3) +
geom_line(data = lisiecki2005, # add d18O line
aes(Time,
d18O)) +
scale_x_continuous(limits = c(0, 250),
name = "x 1000 years ago") +
scale_y_reverse(name = bquote(delta^18*O)) +
theme_bw()
Sometimes we prefer to indicate the MIS by horizontal lines. Once again we have to carefully place the line segments and labels so they are clear to read:
ggplot() +
geom_segment(data = mis_last_250ka, # add MIS lines
aes(x = LR04_Age_ka_end,
xend = LR04_Age_ka_start,
y = seq(3, 2.5, length.out = nrow(mis_last_250ka)),
yend = seq(3, 2.5, length.out = nrow(mis_last_250ka))),
colour = "blue",
size = 1) +
annotate("text",
label = mis_last_250ka$label_MIS,
x = mis_last_250ka$LR04_Age_ka_mid,
y = c(seq(2.9, 2.7, length.out = 4),
seq(3.1, 2.8, length.out = 5),
seq(2.4, 2.3, length.out = 3)),
size = 3) +
geom_line(data = lisiecki2005, # add d18O line
aes(Time,
d18O)) +
scale_x_continuous(limits = c(0, 250),
name = "x 1000 years ago") +
scale_y_reverse(name = bquote(delta^18*O)) +
theme_bw()
And sometimes we might want shaded rectangles to indicate the MIS:
ggplot() +
annotate("rect",
xmin = mis_last_250ka$LR04_Age_ka_end,
xmax = mis_last_250ka$LR04_Age_ka_start,
ymin = -Inf,
ymax = Inf,
alpha = .2,
fill = rep(c("grey70", "white"),
nrow(mis_last_250ka)/2)) +
annotate("text",
label = mis_last_250ka$label_MIS,
x = mis_last_250ka$LR04_Age_ka_mid,
y = c(rep(3, 4),
seq(3.1, 2.8, length.out = 5),
rep(3, 3)),
size = 3) +
geom_line(data = lisiecki2005, # add d18O line
aes(Time,
d18O)) +
scale_x_continuous(limits = c(0, 250),
name = "x 1000 years ago") +
scale_y_reverse(name = bquote(delta^18*O)) +
theme_bw()
Maybe we want the MIS regions by themselves so we can plot some other
time series besides the ones includes here. We need to adjust the
y values in the annotate() function to ensure
that the MIS labels show in a readble way. Here I show an imaginary
variable that might have a maximum value of about 10. So I adjust the
y values in the annotate() function to
position the MIS labels just below 10 on the y axis.
ggplot() +
annotate("rect",
xmin = mis_last_250ka$LR04_Age_ka_end ,
xmax = mis_last_250ka$LR04_Age_ka_start,
ymin = -Inf,
ymax = Inf,
alpha = .2,
fill = rep(c("grey70", "white"),
nrow(mis_last_250ka)/2)) +
annotate("text",
label = mis_last_250ka$label_MIS,
x = mis_last_250ka$LR04_Age_ka_mid,
y = c(rep(9, 4),
seq(8.1, 9.9, length.out = 5),
rep(9, 3)),
size = 3) +
# add in other geoms here...
scale_x_continuous(limits = c(0, 250),
name = "x 1000 years ago") +
scale_y_continuous(limits = c(0, 10),
name = "Some other variable (units)") +
theme_bw()