clade_physig {sensiPhy}

Influential clade detection - Phylogenetic signal

Description

Estimate the influence of clade removal on phylogenetic signal estimates

Usage

clade_physig(
  trait.col,
  data,
  phy,
  clade.col,
  n.species = 5,
  n.sim = 100,
  method = "K",
  track = TRUE,
  ...
)

Arguments

trait.col

The name of a column in the provided data frame with trait to be analyzed (e.g. "Body_mass").

data

Data frame containing species traits with row names matching tips in phy.

phy

A phylogeny (class 'phylo') matching data.

clade.col

The column in the provided data frame which specifies the clades (a character vector with clade names).

n.species

Minimum number of species in a clade for the clade to be included in the leave-one-out deletion analysis. Default is 5.

n.sim

Number of simulations for the randomization test.

method

Method to compute signal: can be "K" or "lambda".

track

Print a report tracking function progress (default = TRUE)

...

Further arguments to be passed to phylosig

Details

This function sequentially removes one clade at a time, estimates phylogenetic signal (K or lambda) using phylosig and stores the results. The impact of a specific clade on signal estimates is calculated by the comparison between the full data (with all species) and reduced data estimates (without the species belonging to a clade).

To account for the influence of the number of species on each clade (clade sample size), this function also estimate a null distribution of signal estimates expected by the removal of the same number of species as in a given clade. This is done by estimating phylogenetic signal without the same number of species in the given clade. The number of simulations to be performed is set by 'n.sim'. To test if the clade influence differs from the null expectation for a clade of that size, a randomization test can be performed using 'summary(x)'.

Output can be visualised using sensi_plot.

Value

The function clade_physig returns a list with the following components:

trait.col: Column name of the trait analysed

full.data.estimates: Phylogenetic signal estimate (K or lambda) and the P value (for the full data).

sensi.estimates: A data frame with all simulation estimates. Each row represents a deleted clade. Columns report the calculated phylogenetic signal (K or lambda) (estimate), difference between simulation signal and full data signal (DF), the percentage of change in signal compared to the full data estimate (perc) and p-value of the phylogenetic signal with the reduced data (pval).

null.dist: A data frame with estimates for the null distribution of phylogenetic signal for all clades analysed.

data: Original full dataset.

Note

The argument "se" from phylosig is not available in this function. Use the argument "V" instead with intra_physig to indicate the name of the column containing the standard deviation or the standard error of the trait variable instead.

Author(s)

Gustavo Paterno

References

Paterno, G. B., Penone, C. Werner, G. D. A. sensiPhy: An r-package for sensitivity analysis in phylogenetic comparative methods. Methods in Ecology and Evolution 2018, 9(6):1461-1467

Blomberg, S. P., T. Garland Jr., A. R. Ives (2003) Testing for phylogenetic signal in comparative data: Behavioral traits are more labile. Evolution, 57, 717-745.

Pagel, M. (1999) Inferring the historical patterns of biological evolution. Nature, 401, 877-884.

Kamilar, J. M., & Cooper, N. (2013). Phylogenetic signal in primate behaviour, ecology and life history. Philosophical Transactions of the Royal Society B: Biological Sciences, 368: 20120341.

See Also

phylosig, clade_phylm,sensi_plot

Examples

data(alien)
alien.data<-alien$data
alien.phy<-alien$phy
# Logtransform data
alien.data$logMass <- log(alien.data$adultMass) 
# Run sensitivity analysis:
clade <- clade_physig(trait.col = "logMass", data = alien.data, n.sim = 20,
                 phy = alien.phy[[1]], clade.col = "family", method = "K")
summary(clade)
sensi_plot(clade, "Bovidae")
sensi_plot(clade, "Sciuridae")