feat: complete part F
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2 changed files with 95 additions and 20 deletions
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@ -37,3 +37,7 @@ simulate_condor_population(0.659, 0.099, 0.099)
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```
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## Part F. Under the assumptions of Part d, suppose that a program of double-clutching persists for five years. Afterwards, all captive birds are returned to the wild. Compare the number of wild condors for this scenario to that in Part d.
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```{r}
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simulate_part_f(0.659, 0.138, 0.069)
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```
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111
project.R
111
project.R
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@ -38,26 +38,11 @@ captive_immature_to_adult_rate <- 1 / (captive_begin_breeding - 2)
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# an approximation which assumes an equal distribution of immature bird ages
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wild_immature_to_adult_rate <- 1 / (wild_begin_breeding - 2)
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# Simulates the Condor population over time using the given parameters.
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# * `rd1` - death rate of year one birds
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# * `rdI` - death rate of immature birds
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# * `rdA` - death rate of adult birds
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simulate_condor_population <- function(rd1, rdI, rdA) {
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# captive population groups
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c_Y0 <- c(30)
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c_Y1 <- c(30)
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c_I <- c(30)
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c_A <- c(30)
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# wild population groups
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w_Y0 <- c(100)
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w_Y1 <- c(100)
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w_I <- c(100)
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w_A <- c(100)
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years <- seq(1, simulation_years)
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for (t in 2:simulation_years) {
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simulate_condor_population_inner <- function(rd1, rdI, rdA,
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c_Y0, c_Y1, c_I, c_A,
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w_Y0, w_Y1, w_I, w_A,
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nyears, captive_dc) {
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for (t in (length(c_Y0) + 1):nyears) {
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# model captive population changes (year 1, immature, and adult)
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c_Y1[t] <- c_Y0[t - 1] - # last year's population
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rd1 * c_Y0[t - 1] # outflow to deaths
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@ -109,6 +94,16 @@ simulate_condor_population <- function(rd1, rdI, rdA) {
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(1 - rd_carrying) # deaths due to carrying capacity
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}
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list(
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c_Y0 = c_Y0, c_Y1 = c_Y1, c_I = c_I, c_A = c_A,
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w_Y0 = w_Y0, w_Y1 = w_Y1, w_I = w_I, w_A = w_A
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)
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}
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plot_populations <- function(c_Y0, c_Y1, c_I, c_A,
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w_Y0, w_Y1, w_I, w_A) {
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years <- seq(1, simulation_years)
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captive_population <- c_Y0 + c_Y1 + c_I + c_A
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plot(
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years,
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@ -139,3 +134,79 @@ simulate_condor_population <- function(rd1, rdI, rdA) {
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points(years, w_A, col = "blue")
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points(years, wild_population)
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}
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# Simulates the Condor population over time using the given parameters.
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# * `rd1` - death rate of year one birds
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# * `rdI` - death rate of immature birds
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# * `rdA` - death rate of adult birds
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simulate_condor_population <- function(rd1, rdI, rdA) {
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# captive population groups
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c_Y0 <- c(30)
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c_Y1 <- c(30)
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c_I <- c(30)
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c_A <- c(30)
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# wild population groups
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w_Y0 <- c(100)
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w_Y1 <- c(100)
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w_I <- c(100)
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w_A <- c(100)
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list2env(simulate_condor_population_inner(
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rd1, rdI, rdA,
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c_Y0, c_Y1, c_I, c_A,
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w_Y0, w_Y1, w_I, w_A,
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simulation_years, FALSE
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), envir = environment())
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plot_populations(
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c_Y0, c_Y1, c_I, c_A,
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w_Y0, w_Y1, w_I, w_A
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)
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}
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simulate_part_f <- function(rd1, rdI, rdA) {
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# captive population groups
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c_Y0 <- c(30)
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c_Y1 <- c(30)
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c_I <- c(30)
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c_A <- c(30)
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# wild population groups
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w_Y0 <- c(100)
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w_Y1 <- c(100)
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w_I <- c(100)
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w_A <- c(100)
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# simulate first 5 years
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list2env(simulate_condor_population_inner(
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rd1, rdI, rdA,
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c_Y0, c_Y1, c_I, c_A,
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w_Y0, w_Y1, w_I, w_A,
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5, TRUE
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), envir = environment())
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# release all in captivity
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w_Y0[5] <- w_Y0[5] + c_Y0[5]
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w_Y1[5] <- w_Y1[5] + c_Y1[5]
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w_I[5] <- w_I[5] + c_I[5]
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w_A[5] <- w_A[5] + c_A[5]
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c_Y0[5] <- 0
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c_Y1[5] <- 0
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c_I[5] <- 0
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c_A[5] <- 0
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# continue simulation
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list2env(simulate_condor_population_inner(
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rd1, rdI, rdA,
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c_Y0, c_Y1, c_I, c_A,
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w_Y0, w_Y1, w_I, w_A,
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simulation_years, FALSE
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), envir = environment())
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plot_populations(
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c_Y0, c_Y1, c_I, c_A,
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w_Y0, w_Y1, w_I, w_A
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)
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}
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