Golem Grad Tortoises

animals
Published

March 3, 2026

Hermann’s tortoise health by sex and locality.

Load Packages

require(pacman)
p_load(tidytuesdayR, tidyverse, janitor, here, trashpanda, ggside, magick)

Load Data

tuesdata <- tidytuesdayR::tt_load('2026-03-03')
clutch_size_cleaned <- tuesdata$clutch_size_cleaned
tortoise_body_condition_cleaned <- tuesdata$tortoise_body_condition_cleaned

Plot

plot <- tortoise_body_condition_cleaned |> 
  mutate(sex = case_when(sex == "f" ~ "Female",
                         sex == "m" ~ "Male",
                         .default = sex)) |> 
  mutate(locality = case_when(locality == "Konjsko" ~ "Konjsko (Mainland)",
                         .default = locality)) |> 
  ggplot(aes(
    x = straight_carapace_length_mm, 
    y = body_condition_index, 
    fill = locality)) +
  stat_ellipse(
    geom = "polygon", 
    alpha = 0.3, 
    colour = "black",
    linewidth = 0.5) +
  facet_wrap(~sex) +
  scale_fill_viridis_d("Locality") +
  labs(x = "Straight Carapace Length (mm)",
       y = "Body Condition Index",
       title = "Female Golem Grad tortoises are healthier on the mainland",
       subtitle = str_wrap("In this dense island population, male Hermann’s tortoises vastly outnumber and harass females, causing injury, reduced reproduction, and lower survival, with long-term data predicting the last female will disappear by 2083. It appears this effect is greater on the Beach and Plateau compared to the mainland.")) +
  theme_cole(remove_grid = TRUE, base_size = 15) +
  theme(axis.line = element_line(colour = "black"),
        strip.text = element_text(size = 20),
        plot.title = element_text(hjust = 0),
        plot.subtitle = element_text(hjust = 0),
        panel.border = element_rect(colour = "black", fill = NA)) +
  add_caption_cwb() 

# Save and display images
current_dir <- dirname(knitr::current_input())
plot_name <- "golem_grad_tortoises.png"

ggsave(plot = plot, 
       dpi = "screen",
       width = 20,
       height = 15,
       device = ragg::agg_png,
       filename = file.path(current_dir, plot_name))


# Read the big plot
img <- image_read(file.path(current_dir, plot_name))

# Force 16:9 aspect ratio with minimal padding
# Target size: 1200x675 px (16:9)
img_card <- image_scale(img, "1200x675")           # scale to fit inside 16:9
img_card <- image_extent(
  img_card,
  geometry = "1200x675",
  gravity = "center"
)

# Save as card preview
image_write(img_card, path = file.path(current_dir, "preview.png"))

knitr::include_graphics(
  file.path(current_dir, plot_name)
)

References

cite_packages(format = "rmd")

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