Hubbell's neutral model simulation applied to time series

Neutral species abundances simulation according to the Hubbell model. This model shows that losses in society can be replaced either by the birth of individuals or by immigration depending on their probabilities. The specific time between the events of birth or migration is calculated and time effect is considered to determine the next event.

Usage

simulateHubbellRates(
  n_species = NULL,
  x0 = NULL,
  names_species = NULL,
  migration_p = 0.01,
  metacommunity_probability = NULL,
  k_events = 1,
  growth_rates = NULL,
  error_variance = 0,
  norm = FALSE,
  t_end = 1000,
  ...
)

Arguments

n_species: Integer: number of species
x0: Numeric: initial species composition. If NULL, rep(100, n_species) is used.
names_species: Character: names of species. If NULL, paste0("sp", seq_len(n_species)) is used. (default: names_species = NULL)
migration_p: Numeric: the probability/frequency of migration from a metacommunity. (default: migration_p = 0.01)
metacommunity_probability: Numeric: Normalized probability distribution of the likelihood that species from the metacommunity can enter the community during the simulation. If NULL, rdirichlet(1, alpha = rep(1,n_species)) is used. (default: metacommunity_probability = NULL)
k_events: Integer: number of events to simulate before updating the sampling distributions. (default: k_events = 1)
growth_rates: Numeric: maximum growth rates(mu) of species. If NULL, rep(1, n_species) is used. (default: growth_rates = NULL)
error_variance: Numeric: the variance of measurement error. By default it equals to 0, indicating that the result won't contain any measurement error. This value should be non-negative. (default: error_variance = 0)
norm: Logical: whether the time series should be returned with the abundances as proportions (norm = TRUE) or the raw counts (default: norm = FALSE) (default: norm = FALSE)
t_end: Numeric: the end time of the simulationTimes, defining the modeled time length of the community. (default: t_end = 1000)
...: additional parameters, see utils to know more.

Value

simulateHubbellRates returns a TreeSummarizedExperiment class object

References

Rosindell, James et al. "The unified neutral theory of biodiversity and biogeography at age ten." Trends in ecology & evolution vol. 26,7 (2011).

Examples

set.seed(42)
tse <- simulateHubbellRates(n_species = 5)

miaViz::plotSeries(tse, x = "time")
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to max; returning -Inf


# no migration, all stochastic birth and death
set.seed(42)
tse1 <- simulateHubbellRates(n_species = 5, migration_p = 0)

# all migration, no stochastic birth and death
set.seed(42)
tse2 <- simulateHubbellRates(
    n_species = 5,
    migration_p = 1,
    metacommunity_probability = c(0.1, 0.15, 0.2, 0.25, 0.3),
    t_end = 20,
    t_store = 200
)

# all migration, no stochastic birth and death, but with measurement errors
set.seed(42)
tse3 <- simulateHubbellRates(
    n_species = 5,
    migration_p = 1,
    metacommunity_probability = c(0.1, 0.15, 0.2, 0.25, 0.3),
    t_end = 20,
    t_store = 200,
    error_variance = 100
)

# model with specified inputs
set.seed(42)
tse4 <- simulateHubbellRates(
    n_species = 5,
    migration_p = 0.1,
    metacommunity_probability = c(0.1, 0.15, 0.2, 0.25, 0.3),
    t_end = 200,
    t_store = 1000,
    k_events = 5,
    growth_rates = c(1.1, 1.05, 1, 0.95, 0.9)
)