Global language endangerment: scale and geographic concentration

Nearly half of the world’s critically endangered languages are concentrated in the Pacific region, making Papunesia the global epicenter of language loss risk.

This visualization examines the global distribution of 8,612 documented languages from Glottolog 5.2.1, revealing critical patterns in language endangerment. A treemap shows that only 31% of languages are considered safe, while 745 are critically endangered (moribund or nearly extinct). Geographic analysis demonstrates that 303 of these critically endangered languages (41%) are concentrated in the Pacific region, particularly across Indonesia, Papua New Guinea, Philippines, and Pacific islands.

Figure 1: Two-panel visualization showing global language endangerment. Left panel: treemap displaying distribution of 8,612 languages by status - 2,704 not endangered (light blue-gray), 1,835 shifting (light gray), 1,629 threatened (medium gray), 1,225 extinct (dark gray), 434 moribund (red), and 311 nearly extinct (dark red). Right panel: map of the Pacific region showing 303 critically endangered languages (41% of the global total) concentrated in Papunesia, represented as red dots clustered across Indonesia, Papua New Guinea, the Philippines, and the Pacific islands.

Steps to Create this Graphic

1. Load Packages & Setup

```{r}
#| label: load
#| warning: false
#| message: false
#| results: "hide"

## 1. LOAD PACKAGES & SETUP ----
suppressPackageStartupMessages({
if (!require("pacman")) install.packages("pacman")
pacman::p_load(
    tidyverse,     # Easily Install and Load the 'Tidyverse'
    ggtext,        # Improved Text Rendering Support for 'ggplot2'
    showtext,      # Using Fonts More Easily in R Graphs
    janitor,       # Simple Tools for Examining and Cleaning Dirty Data
    skimr,         # Compact and Flexible Summaries of Data
    scales,        # Scale Functions for Visualization
    glue,          # Interpreted String Literals
    treemapify,    # Create Treemap Visualizations
    patchwork,     # The Composer of Plots
    maps           # Draw Geographical Maps
)
})

### |- figure size ----
camcorder::gg_record(
  dir    = here::here("temp_plots"),
  device = "png",
  width  = 14,
  height = 12,
  units  = "in",
  dpi    = 320
)

# Source utility functions
suppressMessages(source(here::here("R/utils/fonts.R")))
source(here::here("R/utils/social_icons.R"))
source(here::here("R/utils/image_utils.R"))
source(here::here("R/themes/base_theme.R"))
```

2. Read in the Data

```{r}
#| label: read
#| include: true
#| eval: true
#| warning: false

tt <- tidytuesdayR::tt_load(2025, week = 51)

endangered_status <- tt$endangered_status |> clean_names()
families <- tt$families |> clean_names()
languages <- tt$languages |> clean_names()

# tidytuesdayR::readme(tt)
rm(tt)
```

3. Examine the Data

```{r}
#| label: examine
#| include: true
#| eval: true
#| results: 'hide'
#| warning: false

glimpse(endangered_status)
glimpse(families)
glimpse(languages)
```

4. Tidy Data

```{r}
#| label: tidy-fixed
#| warning: false

### |- Join all datasets ----
languages_combined <- languages |>
  left_join(endangered_status, by = "id") |>
  left_join(families, by = c("family_id" = "id")) |>
  mutate(
    status_label = case_when(
      status_code == 1 ~ "Not Endangered",
      status_code == 2 ~ "Threatened",
      status_code == 3 ~ "Shifting",
      status_code == 4 ~ "Moribund",
      status_code == 5 ~ "Nearly Extinct",
      status_code == 6 ~ "Extinct",
      TRUE ~ "Unknown"
    ),
    endangerment_broad = case_when(
      status_code == 1 ~ "Safe",
      status_code %in% 2:3 ~ "Threatened/Shifting",
      status_code %in% 4:5 ~ "Critical",
      status_code == 6 ~ "Extinct",
      TRUE ~ "Unknown"
    ),
    is_endangered = status_code %in% 2:5,
    n_countries = str_count(countries, ";") + 1
  )

### |- Overall endangerment summary ----
endangerment_summary <- languages_combined |>
  count(status_label, endangerment_broad, sort = TRUE) |>
  mutate(pct = n / sum(n))

### |- Pacific region critical languages ----
pacific_critical <- languages_combined |>
  filter(
    endangerment_broad == "Critical",
    !is.na(latitude), !is.na(longitude),
    longitude >= 100, longitude <= 180,
    latitude >= -50, latitude <= 20
  )

# Calculate total critical languages globally 
total_critical <- languages_combined |>
  filter(endangerment_broad == "Critical") |>
  nrow()

pacific_pct <- round(nrow(pacific_critical) / total_critical * 100)

### |- data for treemap labels  ----
endangerment_summary2 <- endangerment_summary |>
  filter(endangerment_broad != "Unknown") |>
  group_by(status_label) |>
  summarise(n = sum(n), .groups = "drop") |>
  mutate(
    pct = n / sum(n),
    status_label = fct_reorder(status_label, -n),
    label_txt = glue("{status_label}\n{comma(n)} ({scales::percent(pct, accuracy = 0.1)})"),
    text_color = if_else(status_label %in% c("Moribund", "Nearly Extinct"), "white", "gray10")
  )
```

5. Visualization Parameters

```{r}
#| label: params
#| include: true
#| warning: false

### |-  plot aesthetics ----
colors <- get_theme_colors(
    palette = list(
      col_not_endangered = "#E8EEF2",
      col_shifting = "#D0D0D0",
      col_threatened = "#A8A8A8",
      col_extinct = "#8A8A8A",
      col_moribund = "#E63946",
      col_nearly_extinct = "#C41E3A",
      col_map_bg = "gray96",
      col_map_border = "gray65",
      col_ink = "gray10",
      col_rule = "gray85"
  )
)

### |- titles and caption ----
main_title <- "Global language endangerment: scale and geographic concentration"

treemap_subtitle <- "Share of 8,612 documented languages by endangerment status (Glottolog 5.2.1)"

map_title <- "Papunesia: a global hotspot for critical endangerment"
map_subtitle <- glue(
    "{comma(nrow(pacific_critical))} of {comma(total_critical)} critically endangered languages ",
    "({pacific_pct}%) fall within the Pacific focus region"
)

caption_text <- create_social_caption(
    tt_year = 2025,
    tt_week = 51,
    source_text = "Glottolog 5.2.1 | Max Planck Institute for Evolutionary Anthropology"
)

key_takeaway <- glue(
    "Nearly **half of the world’s critically endangered languages** ",
    "are concentrated in the **Pacific region**, making **Papunesia** the global epicenter of language loss risk."
)

### |-  fonts ----
setup_fonts()
fonts <- get_font_families()

### |-  plot theme ----
# Start with base theme
base_theme <- create_base_theme(colors)

# Add weekly-specific theme elements
weekly_theme <- extend_weekly_theme(
  base_theme,
  theme(
    # Text styling
    plot.title = element_text(
      face = "bold", family = fonts$title, size = rel(1.4),
      color = colors$title, margin = margin(b = 10), hjust = 0
    ),
    plot.subtitle = element_text(
      face = "italic", family = fonts$subtitle, lineheight = 1.2,
      color = colors$subtitle, size = rel(0.8), margin = margin(b = 20), hjust = 0
    ),

    # Grid
    panel.grid.minor = element_blank(),
    panel.grid.major.x = element_blank(),
    panel.grid.major = element_line(color = "gray90", linewidth = 0.25),

    # Axes
    axis.title = element_text(size = rel(0.8), color = "gray30"),
    axis.text = element_text(color = "gray30"),
    axis.text.y = element_text(size = rel(0.85)),
    axis.ticks = element_blank(),

    # Facets
    strip.background = element_rect(fill = "gray95", color = NA),
    strip.text = element_text(
      face = "bold",
      color = "gray20",
      size = rel(0.9),
      margin = margin(t = 6, b = 4)
    ),
    panel.spacing = unit(1.5, "lines"),

    # Legend elements
    legend.position = "plot",
    legend.title = element_text(
      family = fonts$subtitle,
      color = colors$text, size = rel(0.8), face = "bold"
    ),
    legend.text = element_text(
      family = fonts$tsubtitle,
      color = colors$text, size = rel(0.7)
    ),
    legend.margin = margin(t = 15),

    # Plot margin
    plot.margin = margin(20, 20, 20, 20),
    
    # Panel framing (subtle  containers) 
    panel.border     = element_rect(color = colors$palette$col_rule, fill = NA, linewidth = 0.8),
  )
)

# Set theme
theme_set(weekly_theme)
```

6. Plot

```{r}
#| label: plot
#| warning: false

### |- Plot 1: Treemap ----
p1 <- ggplot(
    endangerment_summary2,
    aes(area = n, fill = status_label)
) +
    geom_treemap(color = "white", size = 2) +
    geom_treemap_text(
        aes(label = label_txt, color = text_color),
        place = "centre",
        fontface = "bold",
        size = 12,
        grow = FALSE,
        family = fonts$text,
        reflow = TRUE
    ) +
    scale_fill_manual(
        values = c(
            "Not Endangered"  = colors$palette$col_not_endangered,
            "Shifting"        = colors$palette$col_shifting,
            "Threatened"      = colors$palette$col_threatened,
            "Extinct"         = colors$palette$col_extinct,
            "Moribund"        = colors$palette$col_moribund,
            "Nearly Extinct"  = colors$palette$col_nearly_extinct
        )
    ) +
    scale_color_identity() +
    labs(
        # tag = "A",
        title = "Endangerment status distribution",
        subtitle = treemap_subtitle
    ) +
    theme(
        legend.position = "none",
        plot.margin = margin(t = 6, r = 10, b = 6, l = 6)
    )

### |- Plot 2: Map  ----
world_map <- map_data("world")

p2 <- ggplot() +
    geom_polygon(
        data = world_map,
        aes(x = long, y = lat, group = group),
        fill = colors$palette$col_map_bg,
        color = colors$palette$col_map_border,
        linewidth = 0.28
    ) +
    geom_point(
        data = pacific_critical,
        aes(x = longitude, y = latitude),
        shape = 21,
        fill  = colors$palette$col_moribund,
        color = "white",
        stroke = 0.35,
        alpha = 0.75,
        size  = 1.9
    ) +
    coord_fixed(
        xlim = c(100, 180),
        ylim = c(-50, 20),
        ratio = 1.3,
        expand = FALSE
    ) +
    labs(
        # tag = "B",
        title = map_title,
        subtitle = map_subtitle
    ) +
    theme_void() +
    theme(
        plot.title = element_text(
            face = "bold", family = fonts$title, size = 19.6,
            color = colors$title, margin = margin(b = 10), hjust = 0
        ),
        plot.subtitle = element_text(
            face = "italic", family = fonts$subtitle, lineheight = 1.2,
            color = colors$subtitle, size = 11.2, margin = margin(b = 20), hjust = 0
        ),
        panel.border = element_rect(color = colors$palette$col_rule, fill = NA, linewidth = 0.8),
        plot.margin = margin(t = 6, r = 6, b = 6, l = 10)
    )

### |- Combine plots ----
combined_plots <- p1 + p2 +
    plot_annotation(
        title    = main_title,
        subtitle = key_takeaway,
        caption  = caption_text,
        theme =  theme(
            plot.title = element_text(
                size = rel(2.3),
                family = fonts$title,
                face = "bold",
                color = colors$title,
                lineheight = 1.15,
                margin = margin(t = 8, b = 5)
            ),
            plot.subtitle = element_markdown(
                size = rel(0.80),
                family = fonts$subtitle,
                color = alpha(colors$subtitle, 0.88),
                lineheight = 1.5,
                margin = margin(t = 5, b = 20)
            ),
            plot.caption = element_markdown(
                size = rel(0.65),
                family = fonts$subtitle,
                color = colors$caption,
                hjust = 0,
                lineheight = 1.4,
                margin = margin(t = 20, b = 5)
            )
        )
    )
```

7. Save

```{r}
#| label: save
#| warning: false

### |-  plot image ----  
save_plot_patchwork(
  plot = combined_plots, 
  type = "tidytuesday", 
  year = 2025, 
  week = 51, 
  width  = 14,
  height = 12,
  )
```

8. Session Info

TipExpand for Session Info

R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26100)

Matrix products: default


locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: America/New_York
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base     

other attached packages:
 [1] here_1.0.1       maps_3.4.2.1     patchwork_1.3.0  treemapify_2.5.6
 [5] glue_1.8.0       scales_1.3.0     skimr_2.1.5      janitor_2.2.0   
 [9] showtext_0.9-7   showtextdb_3.0   sysfonts_0.8.9   ggtext_0.1.2    
[13] lubridate_1.9.3  forcats_1.0.0    stringr_1.5.1    dplyr_1.1.4     
[17] purrr_1.0.2      readr_2.1.5      tidyr_1.3.1      tibble_3.2.1    
[21] ggplot2_3.5.1    tidyverse_2.0.0  pacman_0.5.1    

loaded via a namespace (and not attached):
 [1] tidyselect_1.2.1   farver_2.1.2       fastmap_1.2.0      gh_1.4.1          
 [5] digest_0.6.37      timechange_0.3.0   lifecycle_1.0.4    rsvg_2.6.1        
 [9] magrittr_2.0.3     compiler_4.4.0     rlang_1.1.6        tools_4.4.0       
[13] utf8_1.2.4         yaml_2.3.10        knitr_1.49         labeling_0.4.3    
[17] htmlwidgets_1.6.4  bit_4.5.0          curl_6.0.0         xml2_1.3.6        
[21] camcorder_0.1.0    repr_1.1.7         tidytuesdayR_1.1.2 withr_3.0.2       
[25] grid_4.4.0         fansi_1.0.6        colorspace_2.1-1   gitcreds_0.1.2    
[29] cli_3.6.4          rmarkdown_2.29     crayon_1.5.3       generics_0.1.3    
[33] rstudioapi_0.17.1  tzdb_0.5.0         commonmark_1.9.2   parallel_4.4.0    
[37] ggplotify_0.1.2    base64enc_0.1-3    vctrs_0.6.5        yulab.utils_0.1.8 
[41] jsonlite_1.8.9     gridGraphics_0.5-1 hms_1.1.3          bit64_4.5.2       
[45] systemfonts_1.1.0  magick_2.8.5       gifski_1.32.0-1    codetools_0.2-20  
[49] stringi_1.8.4      gtable_0.3.6       munsell_0.5.1      pillar_1.9.0      
[53] rappdirs_0.3.3     htmltools_0.5.8.1  ggfittext_0.10.2   R6_2.5.1          
[57] httr2_1.0.6        rprojroot_2.0.4    vroom_1.6.5        evaluate_1.0.1    
[61] markdown_1.13      gridtext_0.1.5     snakecase_0.11.1   renv_1.0.3        
[65] Rcpp_1.0.13-1      svglite_2.1.3      xfun_0.49          fs_1.6.5          
[69] pkgconfig_2.0.3   

9. GitHub Repository

TipExpand for GitHub Repo

The complete code for this analysis is available in tt_2025_51.qmd.

For the full repository, click here.

10. References

TipExpand for References

1. Data Source:
   • TidyTuesday 2025 Week 50: The Languages of the World

11. Custom Functions Documentation

Note📦 Custom Helper Functions

This analysis uses custom functions from my personal module library for efficiency and consistency across projects.

Functions Used:

• fonts.R: setup_fonts(), get_font_families() - Font management with showtext
• social_icons.R: create_social_caption() - Generates formatted social media captions
• image_utils.R: save_plot() - Consistent plot saving with naming conventions
• base_theme.R: create_base_theme(), extend_weekly_theme(), get_theme_colors() - Custom ggplot2 themes

Why custom functions?
These utilities standardize theming, fonts, and output across all my data visualizations. The core analysis (data tidying and visualization logic) uses only standard tidyverse packages.

Source Code:
View all custom functions → GitHub: R/utils