library(marlin)
library(tidyverse)
#> ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
#> ✔ dplyr 1.1.4 ✔ readr 2.1.5
#> ✔ forcats 1.0.0 ✔ stringr 1.5.1
#> ✔ ggplot2 3.5.1 ✔ tibble 3.2.1
#> ✔ lubridate 1.9.3 ✔ tidyr 1.3.1
#> ✔ purrr 1.0.2
#> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
#> ✖ dplyr::filter() masks stats::filter()
#> ✖ dplyr::lag() masks stats::lag()
#> ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
resolution <- c(10,10)
years <- 20
seasons <- 4
steps <- years * seasons
time_step <- 1 / seasons
critter_diffusion <- 0.01
# for now make up some habitat
critter_habitat <- expand_grid(x = 1:resolution[1], y = 1:resolution[2]) %>%
dplyr::mutate(habitat = dnorm((x ^ 2 + y ^ 2), 20, 200),
habitat = habitat / max(habitat) * critter_diffusion) |>
mutate(habitat = habitat * as.numeric(x > 4)) |>
pivot_wider(names_from = y, values_from = habitat) %>%
select(-x) %>%
as.matrix()
larval_habitat <- expand_grid(x = 1:resolution[1], y = 1:resolution[2]) %>%
dplyr::mutate(habitat = dnorm((x ^ 2 + y ^ 2), 20, 200),
habitat = habitat / max(habitat) * critter_diffusion) |>
mutate(habitat = habitat * as.numeric(x <= 4)) |>
pivot_wider(names_from = y, values_from = habitat) %>%
select(-x) %>%
as.matrix()
image(critter_habitat)
fauna <-
list(
"snapper" = create_critter(
scientific_name = "Lutjanus jocu",
habitat = critter_habitat, # pass habitat as lists
recruit_habitat = critter_habitat, # pass habitat as lists
adult_diffusion = critter_diffusion, # standard deviation of the number of patches moved by adults
fished_depletion = .2, # desired equilibrium depletion with fishing (1 = unfished, 0 = extinct),
density_dependence = "global_habitat", # recruitment form, where 1 implies local recruitment
seasons = seasons
)
)
fleets <- list(
"longline" = create_fleet(
list("snapper" = Metier$new(
critter = fauna$snapper,
price = 10,
sel_form = "logistic",
sel_start = 1,
sel_delta = .01,
catchability = 0,
p_explt = 1
)
),
base_effort = prod(resolution),
resolution = resolution
)
)
fleets <- tune_fleets(fauna, fleets)
sim <- simmar(fauna, fleets)
proc_sim <- process_marlin(sim, keep_age = FALSE)
min(proc_sim$fauna$n)
#> [1] 0.01249221
plot_marlin(proc_sim, plot_type = "space", plot_var = "c", max_scale = FALSE)
#> Warning in plot_marlin(proc_sim, plot_type = "space", plot_var = "c", max_scale
#> = FALSE): Can only plot one time step for spatial plots, defaulting to last of
#> the supplied steps
