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Specify dispersal between populations in a metapopulation model

Source: R/dispersal.R
dispersal.Rd

Specify dispersal between populations, including stochasticity and density dependence in dispersal parameters

Usage

dispersal(
  kernel,
  stochasticity_masks = NULL,
  stochasticity_funs = NULL,
  density_masks = NULL,
  density_funs = NULL,
  proportion = FALSE
)

Arguments

kernel

numeric matrix specifying the probability of specific classes moving between two populations. Matrices have the same columns-move-to-rows structure as in the population dynamics matrices described in dynamics, so a non-zero value in cell (a, b) denotes a transition from class b in the source population to class a in the receiving population

stochasticity_masks

a logical matrix or list of logical matrices defining cells affected by stochasticity_funs. See Details and masks

stochasticity_funs

a function or list of functions with one element for each element of stochasticity_masks. See Details

density_masks

a logical matrix or list of logical matrices defining cells affected by density_funs. See Details and masks

density_funs

a function or list of functions with one element for each element of density_masks. See Details

proportion

logical indicating whether kernel is specified in absolute probabilities or as a proportion of the source population (defaults to FALSE). If TRUE, values in kernel are calculated as a proportion of the total probability an individual exits that class at any given time step

Value

dispersal object specifying probabilities of movement between populations in a metapopulation matrix model; for use with metapopulation

Examples

# define some populations, all with identical vital rates
nclass <- 5
popmat <- matrix(0, nrow = nclass, ncol = nclass)
popmat[reproduction(popmat, dims = 4:5)] <- c(10, 20)
popmat[transition(popmat)] <- c(0.25, 0.3, 0.5, 0.65)

# define a dynamics object
dyn <- lapply(
  1:3,
  function(i) dynamics(popmat)
)

# define metapopulation structure with populations
#   1 and 3 dispersing into population 2
pop_structure <- matrix(0, nrow = 3, ncol = 3)
pop_structure[1, 2] <- 1
pop_structure[3, 2] <- 1

# define dispersal between populations
dispersal_matrix <- matrix(0, nrow = nclass, ncol = nclass)
dispersal_matrix[survival(dispersal_matrix, dims = 20:25)] <- 0.2
pop_dispersal1 <- dispersal(dispersal_matrix, proportion = TRUE)
pop_dispersal2 <- dispersal(dispersal_matrix, proportion = FALSE)
pop_dispersal <- list(pop_dispersal1, pop_dispersal2)

# create metapopulation object
metapop <- metapopulation(pop_structure, dyn, pop_dispersal)

# simulate without covariates
sims <- simulate(metapop, nsim = 10)

# and plot the simulated trajectories
plot(sims)