Adult survival - conservation status relationship

\[ cons\_status = cons\_status\_mean^{(1 - adult\_survival\_st) / (adult\_survival\_st + 0.5)} \]

traits_landbirds_wind_final_1 <- readxl::read_xlsx('../tables_traits/traits_landbirds_wind_final_07072025.xlsx')

traits_landbirds_wind_final_1 |> 
  ggplot(aes(x = adult_survival)) +
  geom_histogram(fill = '#7ea8cb', colour = 'black') +
  theme_minimal()
g <-   traits_landbirds_wind_final_1 |> 
  mutate(across(where(is.numeric), round, 4)) |> 
  ggplot() +
  aes(x = adult_survival, y = cons_status, fill = factor(global_score),
      text = glue::glue(
        'Species: {eng_name_bli}
        Family: {family_name}
        adult_survival: {adult_survival}
        cons_status_score: {cons_status}
        Red List Status: {global_score}'
      )
      ) +
  geom_point(colour = 'black', pch = 21, size = 3, alpha = 0.8) +
  scale_fill_manual(values = c( '#ffffb2', '#fecc5c','#fd8d3c','#f03b20', '#bd0026', '#a50f15'), 'Red List Status') +
  # scale_fill_manual(values = c( '#6eabd0', '#b7e1b3','#edf7b6','#fee9ad', '#fcae8a', '#e17783'), 'Red List Status') +
  theme_minimal()

ggplotly(
  g, tooltip = 'text'

)