Coral Bleaching

2024 “no bleaching” scenario

Code

library(tidyverse)
library(sf)
library(reefspawn)

seedval = 321


coral_size_2024 <- simulate_coralsize(coralsize |> filter(year==2011), 
                                      distribution = "rlnorm", 
                                      ndraws = 2000,
                                      seed = seedval)

sf_plot <- setplot(20,10) # default EPSG:3857
coralsizepredictions <- posterior_coral_predict(brm = brm_sizedistribution,
                                                newdata = coral_size_2024, 
                                                seed = seedval)

communities <- simulate_community(setplot = sf_plot,
                                  coralcover = 40,
                                  size = coral_size_2024,
                                  seed = seedval)

populations <- simulate_populations(setplot = sf_plot,
                                    size = coral_size_2024,
                                    community = communities,
                                    return="sf",
                                    seed = seedval)


reproductive_populations <- simulate_spawning(populations = populations,
                                        setplot = sf_plot,
                                        seed = 123)

map_populations(setplot = sf_plot,
                populations = reproductive_populations, # or reproductive output, same sf population
                interactive = TRUE)

2024 “bleaching” scenario

Code

reproductive_populations_postbleaching <- simulate_bleaching(populations = reproductive_populations)

map_populations(setplot = sf_plot, 
                populations = reproductive_populations_postbleaching, 
                interactive = TRUE)

Mortality estimates

Code

library(DT)

# colony level info:
colony_output <- reproductive_populations_postbleaching |> 
  as.data.frame() |> 
  group_by(status, species) |> 
  summarise(n = n(), .groups = "drop") |> 
  pivot_wider(names_from = status, values_from = n, values_fill = 0) |> 
  mutate(
    prebleaching_n = bleached + unbleached,
    postbleaching_n = unbleached,
    percent_mortality = round((bleached / prebleaching_n) * 100, 1)
  ) |> select(-bleached, -unbleached)

reactable::reactable(
  head(colony_output, 20),
  defaultPageSize = 20,
  pagination = FALSE,
  searchable = FALSE,
  highlight = TRUE,
  bordered = TRUE,
  striped = TRUE
)           

Reproductive output estimates

Code

population_output <- reproductive_populations_postbleaching |> 
  as.data.frame() |> 
  group_by(status, species) |> 
  summarise(
    mean_output = mean(output),
    total_output = sum(output),
    .groups = "drop"
  ) |> 
  pivot_wider(
    names_from = status,
    values_from = c(mean_output, total_output),
    names_glue = "{.value}_{status}"
  ) |> 
  mutate(
    mean_output_change = round(100 * (mean_output_unbleached - mean_output_bleached) / mean_output_unbleached, 1),
    total_output_change = round(100 * (total_output_unbleached - total_output_bleached) / total_output_unbleached, 1),
    mean_output_postbleaching = scales::comma(round(mean_output_unbleached, 1)),
    mean_output_prebleaching = scales::comma(round(mean_output_bleached, 1)),
    total_output_postbleaching = scales::comma(total_output_bleached),
    total_output_prebleaching = scales::comma(total_output_unbleached)
  ) |> 
  select(species, mean_output_prebleaching, mean_output_postbleaching, mean_output_change, 
         total_output_prebleaching, total_output_postbleaching, total_output_change)


reactable::reactable(
  head(population_output, 20),
  defaultPageSize = 20,
  pagination = FALSE,
  searchable = FALSE,
  highlight = TRUE,
  bordered = TRUE,
  striped = TRUE
)