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Generate hypothetical realised webs using a power-law link distribution

Source: R/downsample.R
powerlaw_prey.Rd

PFWIM generates a series of replicate hypothetical realised food webs by reducing the feasible links for each consumer to match a target link distribution. The default distribution is a mixed exponential–power law in-degree distribution as described in Shaw (2024) and Roopnarine (2006).

Usage

powerlaw_prey(
  el,
  n_samp = 50,
  y = 2.5,
  func = function(r, M, y) exp(-r/(exp((y - 1) * (log(M)/y))))
)

Arguments

el

Data frame or matrix containing a feasible consumer–resource edgelist. Column 1 = resource, Column 2 = consumer.

n_samp

Integer. Number of replicate realised webs to generate. Default = 50.

y

Numeric. Parameter controlling the shape of the power-law distribution. Default = 2.5.

func

Function. Probability function of the in-degree r, total prey richness M, and parameter y. Must return a numeric value > 0. Default: function(r, M, y) exp(-r / (exp((y - 1) * (log(M) / y)))).

Value

A list of length n_samp. Each element is a data frame representing a realised food web edgelist with two columns:

resource

Resource species

consumer

Consumer species

Details

For each consumer in el, the number of prey links in a realised web is sampled according to the distribution defined by func. The sampled prey are drawn randomly without exceeding the maximum feasible prey for that consumer.

References

Shaw, J. (2024). PFWIM: Paleo Food-web Inference Model. Preprint. Roopnarine, P. (2006). Palaeoecology and food-web structure in fossil communities.

Examples

# Infer a minimal edgelist
edgelist <- infer_edgelist(
  data = data.frame(
    species = c("plankton","plant_1","plant_2","cod","rat","deer"),
    feeding = c("primary","primary","primary","secondary","secondary","secondary")
  ),
  cat_combo_list = data.frame(
    trait_type_resource = c("feeding","feeding","feeding"),
    trait_resource = c("primary","primary","primary"),
    trait_type_consumer = c("feeding","feeding","feeding"),
    trait_consumer = c("secondary","secondary","secondary")
  ),
  col_taxon = "species",
  certainty_req = "all"
)
#> [1] "feeding"
#> [1] "0 taxa dropped from web"

# Generate realized webs
webs <- powerlaw_prey(edgelist, n_samp = 3, y = 2.5)