LengthAdded {TreeSearch}

Contribution of character to leaf instability

Description

Would tree lengths change if a character was coded as ambiguous for each leaf (Pol and Escapa 2009)?

Usage

LengthAdded(trees, char, concavity = Inf)

PolEscapa(trees, char, concavity = Inf)

Arguments

trees

List of trees of class phylo, or multiPhylo object.

char

phyDat object containing a single character.

concavity

Determines the degree to which extra steps beyond the first are penalized. Specify a numeric value to use implied weighting (Goloboff 1993); concavity specifies k in k / e + k. A value of 10 is recommended; TNT sets a default of 3, but this is too low in some circumstances (Goloboff et al. 2018; Smith 2019). Better still explore the sensitivity of results under a range of concavity values, e.g. k = 2 ^ (1:7). Specify Inf to weight each additional step equally. Specify "profile" to employ profile parsimony (Faith and Trueman 2001).

Details

High values for a leaf indicate that its coding contributes to instability ("wildcard" or "roguish" behaviour; see Roguefor further details). The coding is in tension with other data, which may indicate that the assumptions of homology that underlie the character's construction and scoring require careful scrutiny – or that the taxon in question has been subject to convergent evolution.

When inapplicable tokens are present in a character, the applicability of each coding is maintained: i.e. a leaf coded with an applicable token is never allowed to take an inapplicable value; and an inapplicable token remains inapplicable.

Value

LengthAdded() returns a named numeric vector listing the mean absolute change to tree length resulting if the character were coded ambiguous for each leaf in turn, under the specified concavity constant.

Author(s)

Martin R. Smith ([e-mail])

References

Faith DP, Trueman JWH (2001). “Towards an inclusive philosophy for phylogenetic inference.” Systematic Biology, 50(3), 331–350. doi:10.1080/10635150118627.

Goloboff PA (1993). “Estimating character weights during tree search.” Cladistics, 9(1), 83–91. doi:10.1111/j.1096-0031.1993.tb00209.x.

Goloboff PA, Torres A, Arias JS (2018). “Weighted parsimony outperforms other methods of phylogenetic inference under models appropriate for morphology.” Cladistics, 34(4), 407–437. doi:10.1111/cla.12205.

Pol D, Escapa IH (2009). “Unstable taxa in cladistic analysis: identification and the assessment of relevant characters.” Cladistics, 25(5), 515–527. doi:10.1111/j.1096-0031.2009.00258.x.

Smith MR (2019). “Bayesian and parsimony approaches reconstruct informative trees from simulated morphological datasets.” Biology Letters, 15(2), 20180632. doi:10.1098/rsbl.2018.0632.

See Also

Other tree scoring: CharacterLength(), IWScore(), MinimumLength(), MorphyTreeLength(), TaxonInfluence()

Examples

trees <- inapplicable.trees[["Vinther2008"]]
dataset <- inapplicable.phyData[["Vinther2008"]]
char <- dataset[, 11]
added <- LengthAdded(trees, char)

PlotCharacter(
  tree = trees[[1]], 
  dataset = char,
  tip.color = 1 + added[trees[[1]]$tip.label] # Colour by added steps
) -> XX # Suppress return value; display plot only