Metabolism Effects on Foraging Across Temperatures
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Note that this starter code incorporates many of the strategies we’ve discussed in past lectures: turning a theme into a function, creating a color palette (and also point shape and size scales), and axis labels outside of the ggplot code, and using {ggtext} to apply markdown to plot text:
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## setup ----
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#.........................load libraries.........................
library(tidyverse)
#..........................read in data..........................
# read in Google Sheet ----
lobs <- googlesheets4::read_sheet("https://docs.google.com/spreadsheets/d/1DkDVcl_9rlaqznHfa_v1V1jtZqcuL75Q6wvAHpnCHuk/edit#gid=2143433533") |>
mutate(temp = as.factor(temp))
# alternatively, read in csv file ----
# lobs <- read_csv(here::here("week6", "data", "metabolism-foraging-data.csv")) |>
# mutate(temp = as.factor(temp))
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## create lobster plot ----
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#..........................create theme..........................
lob_theme <- function(){
theme_light() +
theme(
axis.title.x = ggtext::element_markdown(size = 16,
margin = margin(t = 10, r = 0, b = 0, l = 0),
lineheight = 1.5),
axis.title.y = ggtext::element_markdown(size = 16,
margin = margin(t = 0, r = 10, b = 0, l = 0),
lineheight = 1.5),
axis.text = element_text(color = "black", size = 14),
panel.border = element_rect(colour = "black", linewidth = 0.7),
panel.grid = element_blank(),
legend.title = element_text(size = 15),
legend.text = element_text(size = 13),
legend.position = c(0.95, 0.95),
legend.justification = c(0.95, 0.95),
legend.box.background = element_rect(color = "black", linewidth = 0.9)
)
}
#..........................create scales.........................
lob_palette <- c("11" = "#7B8698",
"16" = "#BAD7E5",
"21" = "#DC7E7C",
"26" = "#7D3E40")
lob_shapes <- c("11" = 15,
"16" = 16,
"21" = 17,
"26" = 18)
lob_sizes <- c("11" = 6,
"16" = 6,
"21" = 6,
"26" = 7)
#........................create plot text........................
x_axis_lab <- glue::glue("Resting Metabolic Rate<br>
(mg O<sub>2</sub> kg<sup>-1</sup> min<sup>-1</sup>)")
y_axis_lab <- glue::glue("Maximum Consumption Rate<br>
(prey consumed predator<sup>-1</sup> 24hr<sup>-1</sup>)")
#............................plot data...........................
lob_plot <- ggplot(lobs, aes(x = SMR, y = avg_eaten,
color = temp, shape = temp, size = temp)) +
geom_point() +
scale_color_manual(values = lob_palette, name = "Temperature (ºC)") +
scale_shape_manual(values = lob_shapes, name = "Temperature (ºC)") +
scale_size_manual(values = lob_sizes, name = "Temperature (ºC)") +
scale_x_continuous(breaks = seq(0, 1.5, by = 0.2)) +
scale_y_continuous(breaks = seq(0, 35, by = 5)) +
labs(x = x_axis_lab,
y = y_axis_lab) +
lob_theme()
lob_plot
Here, we use geom_text() + geom_rect() to add text and a rectangle to our plot. We need to supply coordinates to place each on our plot.
Notice that our text looks oddly blurry and bold, and our rectangle is opaque (despite adjusting alpha) and has a weird, thick border.
Alternatively, annotate() requires that we define a geom type (e.g. "text", "rect"). We can also omit the show.lengend argument, since annotate() doesn’t produce a legend.
Note: Determining coordinates for any annotation requires a lot of trial and error. Pick values that you think are close and then tweak from there.
We can specify the "curve" geom type to draw a curved line. Use the arrow argument + arrow() function to add an arrow tip on the end:
lob_plot +
annotate(
geom = "text",
x = 0.1,
y = 25,
label = "Important lobsters",
size = 4,
color = "black",
hjust = "inward"
) +
annotate(
geom = "rect",
xmin = 0.25, xmax = 0.85,
ymin = 8.5, ymax = 18,
alpha = 0.5,
fill = "gray70", color = "black"
) +
annotate(
geom = "curve",
x = 0.3, xend = 0.5,
y = 23.8, yend = 19,
curvature = -0.15,
arrow = arrow(length = unit(0.3, "cm"))
)
geom_text() adds plain text
Annotations sit on top of data points, which may be undesirable…
geom_text() adds plain text
If we have just a few lobsters that we want to call attention to, we can use annotate() to label them. Let’s start with lobster IV10:
Your turn! Create another text label and arrow pointing to lobster IV19 (the farthest dark red diamond to the right). You don’t need to choose this exact location for your text and arrow:
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A solution (you may have chosen a different placement for your text and arrow):
lob_plot +
annotate(
geom = "text",
x = 0.3, y = 20.1,
label = "IV10",
hjust = "left",
size = 5
) +
annotate(
geom = "curve",
x = 0.29, xend = 0.184,
y = 20, yend = 9.43,
arrow = arrow(length = unit(0.3, "cm")),
linewidth = 0.6
) +
annotate(
geom = "text",
x = 1.19,
y = 5.25,
label = "IV19",
hjust = "right",
size = 5
) +
annotate(
geom = "curve",
x = 1.2, xend = 1.31,
y = 5, yend = 14,
arrow = arrow(length = unit(0.3, "cm")),
linewidth = 0.6
)
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## setup ----
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#.........................load libraries.........................
library(tidyverse)
#..........................read in data..........................
# read in Google Sheet ----
mono <- googlesheets4::read_sheet("https://docs.google.com/spreadsheets/d/1o0-89RFp2rI2y8hMQWy-kquf_VIzidmhmVDXQ02JjCA/edit#gid=164128885")
# alternatively, read in csv ----
mono <- read_csv(here::here("week6", "data", "mono.csv"))
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## create Mono Lake plot ----
##~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
ggplot(data = mono, aes(x = year, y = lake_level)) +
geom_line() +
labs(x = "\nYear",
y = "Lake surface level\n(feet above sea level)\n",
title = "Mono Lake levels (1850 - 2017)\n",
caption = "Data: Mono Basin Clearinghouse") +
scale_x_continuous(limits = c(1850, 2020),
expand = c(0,0),
breaks = seq(1850, 2010, by = 20)) +
scale_y_continuous(limits = c(6350, 6440),
breaks = c(6370, 6400, 6430),
expand = c(0,0),
labels = scales::label_comma()) +
theme_light() +
theme(
plot.title.position = "plot",
plot.title = element_text(size = 16),
axis.title = element_text(size = 12),
axis.text = element_text(size = 10),
plot.caption = element_text(face = "italic")
)
Let’s say we want to call particular attention to the sharp decline in lake surface level between 1941 - 1983 as a result of unrestricted water diversions. Let’s do so using annotate() (note the order of our annotation layers matters!).
ggplot(data = mono, aes(x = year, y = lake_level)) +
annotate(
geom = "rect",
xmin = 1941, xmax = 1983,
ymin = 6350, ymax = 6440,
fill = "gray90"
) +
geom_line() +
labs(x = "\nYear",
y = "Lake surface level\n(feet above sea level)\n",
title = "Mono Lake levels (1850 - 2017)\n",
caption = "Data: Mono Basin Clearinghouse") +
scale_x_continuous(limits = c(1850, 2020),
expand = c(0,0),
breaks = seq(1850, 2010, by = 20)) +
scale_y_continuous(limits = c(6350, 6440),
breaks = c(6370, 6400, 6430),
expand = c(0,0),
labels = scales::label_comma()) +
annotate(
geom = "text",
x = 1962, y = 6425,
label = "unrestricted diversions\n(1941 - 1983)",
size = 3
) +
theme_light() +
theme(
plot.title.position = "plot",
plot.title = element_text(size = 16),
axis.title = element_text(size = 12),
axis.text = element_text(size = 10),
plot.caption = element_text(face = "italic")
)
We can add any other important information to provide better context for our readers. Let’s say we’re also interested in shrimp abundances, which decline above 6,360 feet. Here, we add a baseline at that elevation, along with text:
ggplot(data = mono, aes(x = year, y = lake_level)) +
annotate(
geom = "rect",
xmin = 1941, xmax = 1983,
ymin = 6350, ymax = 6440,
fill = "gray90"
) +
geom_line() +
labs(x = "\nYear",
y = "Lake surface level\n(feet above sea level)\n",
title = "Mono Lake levels (1850 - 2017)\n",
caption = "Data: Mono Basin Clearinghouse") +
scale_x_continuous(limits = c(1850, 2020),
expand = c(0,0),
breaks = seq(1850, 2010, by = 20)) +
scale_y_continuous(limits = c(6350, 6440),
breaks = c(6370, 6400, 6430),
expand = c(0,0),
labels = scales::label_comma()) +
annotate(
geom = "text",
x = 1962, y = 6425,
label = "unrestricted diversions\n(1941 - 1983)",
size = 3
) +
geom_hline(yintercept = 6360,
linetype = "dashed") +
annotate(
geom = "text",
x = 1910, y = 6366,
label = "Decreased shrimp abundance expected\n(6,360 feet above sea level)",
size = 3
) +
theme_light() +
theme(
plot.title.position = "plot",
plot.title = element_text(size = 16),
axis.title = element_text(size = 12),
axis.text = element_text(size = 10),
plot.caption = element_text(face = "italic")
)