count_quasi_exts {metafolio}

Take meta_sim output objects and count quasi extinctions

Description

Take meta_sim output objects and count quasi extinctions

Usage

count_quasi_exts(dat, quasi_thresh, ignore_pops_thresh = 5, duration = 1)

Arguments

dat

Input data. Should be a list of lists. The first level corresponds to the conservation plan and the second level corresponds to the replicate.

quasi_thresh

The quasi extinction threshold

ignore_pops_thresh

Threshold below which to ignore populations (e.g. if you started some populations with very low abundance and you don't want to count those populations.

duration

Number of years that the abundance must be below the quasi_thresh before being counted as quasi extinct.

Value

A list of matrices. The list elements correspond to the conservation plans. The columns of the matrix correspond to the subpopulations that were above the ignore_pops_thresh level. The rows of the matrix correspond to the replicates.

Examples

## Not run: 
set.seed(1)
w_plans <- list()
w_plans[[1]] <- c(5, 1000, 5, 1000, 5, 5, 1000, 5, 1000, 5)
w_plans[[2]] <- c(5, 5, 5, 1000, 1000, 1000, 1000, 5, 5, 5)
w_plans[[3]] <- c(rep(1000, 4), rep(5, 6))
w_plans[[4]] <- rev(w_plans[[3]])
plans_name_sp <- c("Full range of responses", "Most stable only",
"Lower half", "Upper half")
 n_trials <- 50 # number of trials at each n conservation plan
 n_plans <- 4 # number of plans
 num_pops <- c(2, 4, 8, 16) # n pops to conserve
 w <- list()
 for(i in 1:n_plans) { # loop over number conserved
  w[[i]] <- list()
  for(j in 1:n_trials) { # loop over trials
    w[[i]][[j]] <- matrix(rep(625, 16), nrow = 1)
    w[[i]][[j]][-sample(1:16, num_pops[i])] <- 5
  }
 }
arma_env_params <- list(mean_value = 16, ar = 0.1, sigma_env = 2, ma = 0)

x_arma_sp <- run_cons_plans(w, env_type = "arma", env_params = arma_env_params)
count_quasi_exts(x_arma_sp$plans_port, quasi_thresh = 200)

## End(Not run)