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Assemble a local community from a regional pool by rules

Source: R/assembly.R
assemble_community.Rd

Static community assembly, without population dynamics, following Kraft et al. (2007). Species are removed from the pool one at a time until the community has size species (or until the optional distance end point is reached):

Usage

assemble_community(
  traits,
  size,
  rule = c("limiting_similarity", "filtering", "neutral"),
  optimum = "ancestral",
  min_distance = NULL
)

Arguments

traits

Numeric vector (one trait) or matrix (one column per trait), with species names as names or row names. For example, the output of traits_ou().

size

Number of species in the local community.

rule

Assembly rule.

optimum

For rule = "filtering": the niche optimum, either "ancestral" (the root state, 0 by default in traits_ou()), "derived" (the maximum of each trait in the pool, one extreme corner of trait space), or a numeric vector with one value per trait.

min_distance

For rule = "limiting_similarity": optional end point. Removal stops as soon as no two remaining species are closer than this (a limit to similarity), even if more than size species remain.

Value

A list with community (names of the species kept) and removed (names of the species removed, in order of removal).

Details

  • "limiting_similarity": the GAUSE algorithm of Colwell & Winkler (1984), direct competition followed by diffuse competition. The pair of species closest in trait space is found and, of the two, the species with the smaller sum of distances to all remaining species (the greater "diffuse similarity") is removed. The process is repeated on the remaining species. Kraft et al. (2007) used this algorithm for their limiting similarity model.

  • "filtering": habitat filtering as in Kraft et al. (2007). The species farthest from a niche optimum in trait space are removed first.

  • "neutral": species are drawn at random, without regard to traits.

Distances are Euclidean, so several traits can be used at once (one column each). Ties are broken at random.

References

Colwell, R. K., & Winkler, D. W. (1984). A null model for null models in biogeography. In D. R. Strong, D. Simberloff, L. G. Abele, & A. B. Thistle (Eds.), Ecological Communities: Conceptual Issues and the Evidence (pp. 344–359). Princeton University Press. doi:10.1515/9781400857081.344

Kraft, N. J. B., Cornwell, W. K., Webb, C. O., & Ackerly, D. D. (2007). Trait evolution, community assembly, and the phylogenetic structure of ecological communities. The American Naturalist, 170, 271–283. doi:10.1086/519400

Examples

set.seed(1)
tr <- treeshapesim::sim_tree_shape(32)
x <- traits_ou(tr, n_traits = 2)
assemble_community(x, size = 16, rule = "limiting_similarity")$community
#>  [1] "t1"  "t2"  "t3"  "t7"  "t8"  "t12" "t13" "t14" "t16" "t22" "t23" "t25"
#> [13] "t26" "t29" "t30" "t32"
assemble_community(x, size = 16, rule = "filtering", optimum = "derived")$community
#>  [1] "t1"  "t2"  "t3"  "t6"  "t7"  "t9"  "t10" "t11" "t13" "t14" "t15" "t16"
#> [13] "t17" "t18" "t31" "t32"