5. Daisy world

14.04.2026

library(gen3sis2)
library(ggplot2)
library(terra)
#> terra 1.9.11
library(patchwork)
#> 
#> Attaching package: 'patchwork'
#> The following object is masked from 'package:terra':
#> 
#>     area

Creating environmental variables

envar <- terra::rast(
  xmin = -180,
  xmax = 180,
  ymin = -90,
  ymax = 90,
  resolution = 20
)

envar <- c(envar,envar)
names(envar) <- c("temperature","irradiation")

temperature <- c(-22.80, -2.09, 13.24, 22.84, 26.33, 23.37, 13.59, -3.36, -27.85)
irradiation <- c(2.37, 3.62, 4.50, 4.99, 5.10, 4.83, 4.18, 3.15, 1.74)

r_values <- values(envar)

start_cell <- 1
for (i in 1:9){
  if(i != 1){
    start_cell <- end_cell + 1
  }
  end_cell <- start_cell + (ncol(envar)-1)
  r_values[start_cell:end_cell,"temperature"] <- temperature[i]
  r_values[start_cell:end_cell,"irradiation"] <- irradiation[i]
}
values(envar) <- r_values
names(envar) <- c("temperature","irradiation")
plot(envar)

Create spaces

tempr <- envar[["temperature"]]
irrar <- envar[["irradiation"]]

n_ts <- 100 # number of time-steps
raster_list <- list(
  temperature = rep(tempr, n_ts),
  irradiation = rep(irrar, n_ts)
)

cf <- function(source, dest){
  return(1/1000)
}

dir_spaces <- tempdir()

create_spaces_raster(
  raster_list = raster_list,
  cost_function = cf,
  directions = 16,
  output_directory = dir_spaces,
  full_dists = T,
  overwrite_output = TRUE,
  verbose = TRUE,
  duration = list(from = 99, to = 0, by = -1, unit = "Ma"),
  geodynamic = FALSE
)

Run simulation

configuration <- create_input_config(
  config_file = system.file("extdata/TestConfigs/daisy_world.R", package="gen3sis2"), 
  config_name = "DaisyWorld"
)

sim <- run_simulation(
  config = configuration,
  space = dir_spaces,
  verbose = 0
)

Plot

# df<-read.csv("/home/yogh/Documentos/projects/testing_gen3sis/daisy_world/DaisyWorld/global_temperature.txt")
df$time_step <- 1:nrow(df)

p1 <- ggplot(df, aes(x = time_step)) +
  geom_line(aes(y = mean_temperature[[1]], color = "Baseline temperature")) +
  geom_line(aes(y = mean_temperature, color = "Mean temperature")) +
  scale_color_manual(
    name = element_blank(),
    values = c(
      "Baseline temperature" = "green",
      "Mean temperature" = "red")
  ) +
  labs(
    x = element_blank(),
    y = "Mean global temperature"
  ) +
  theme_bw()

p2 <- ggplot(df, aes(x = time_step)) +
  geom_line(aes(y = white_prevalence, color = "White daisy")) +
  geom_line(aes(y = black_prevalence, color = "Black daisy")) +
  scale_color_manual(
    name = element_blank(),
    values = c(
      "Black daisy" = "black",
      "White daisy" = "navajowhite3")
  ) +
  labs(
    x = "Time-step",
    y = "Species prevalence"
  ) + 
  theme_bw()

p1 / p2 + 
  plot_layout(guides = "collect") & 
  theme(legend.position = "bottom")