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pez (version 1.2-4)

fingerprint.regression: Regress trait evolution against trait ecology (following Cavender-Bares et al. 2004)

Description

Calculates traits' phylogenetic inertia and regresses this against trait similarity among co-existing species (sensu Cavender-Bares et al. 2004 Figure 6)

Usage

fingerprint.regression(
  data,
  eco.rnd = c("taxa.labels", "richness", "frequency", "sample.pool", "phylogeny.pool",
    "independentswap", "trialswap"),
  eco.method = c("quantile", "lm", "mantel"),
  eco.permute = 1000,
  evo.method = c("lambda", "delta", "kappa", "blom.k"),
  eco.swap = 1000,
  abundance = TRUE,
  ...
)

# S3 method for fingerprint.regression print(x, ...)

# S3 method for fingerprint.regression summary(object, ...)

# S3 method for fingerprint.regression plot( x, eco = c("slope", "corrected"), xlab = "Community Trait Similarity", ylab = "Phylogenetic inertia", ... )

Arguments

data

comparative.comm for analysis

eco.rnd

null distribution with which to compare your community data, one of: taxa.labels (DEFAULT), richness, frequency, sample.pool, phylogeny.pool, independentswap, trialswap (as implemented in picante)

eco.method

how to compare distance matrices (only the lower triangle;), one of: lm (linear regression), quantile (DEFAULT; rq), mantel (mantel)

eco.permute

number of permutations for ecological null model (eco.rnd); default 1000

evo.method

how to measure phylogenetic inertia, one of: lambda (default), delta, kappa, blom.k; see phy.signal.

eco.swap

number of independent swap iterations to perform (if specified in eco.rnd; DEFAULT 1000)

abundance

whether to incorporate species' abundances (default: TRUE)

...

additional parameters to pass on to model fitting functions and plotting functions

x

fingerprint.regression object

object

fingerprint.regression object

eco

plot the observed slopes (DEFAULT: slope), or the median difference between the simulations and the observed values (corrected)

xlab

label for x-axis (default "Ecological Trait Coexistence")

ylab

label for y-axis (default "Phylogenetic inertia")

Author

Will Pearse and Jeannine Cavender-Bares

Details

While the term `fingerprint regression' is new to pez, the method is very similar to that employed in Cavender-Bares et al. 2004 Figure 6. For each trait, the phylogenetic inertia of species traits is regressed against their co-occurrence in the community matrix. Note that Pagel's lambda, delta, and kappa, and Blomberg's K, can be used, unlike the original where a mantel test was employed. Moreover, note also that Pianka's distance (as described in the manuscript) is used to measure species overlap.

References

Cavender-Bares J., Ackerly D.D., Baum D.A. & Bazzaz F.A. (2004) Phylogenetic overdispersion in Floridian oak communities. The Americant Naturalist 163(6): 823--843.

Kembel, S.W., Cowan, P.D., Helmus, M.R., Cornwell, W.K., Morlon, H., Ackerly, D.D., Blomberg, S.P. & Webb, C.O. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26(11): 1463--1464.

Pagel M. Inferring the historical patterns of biological evolution. Nature 401(6756): 877--884.

See Also

eco.xxx.regression phy.signal

Examples

Run this code
data(laja)
data <- comparative.comm(invert.tree, river.sites, invert.traits, river.env)
fingerprint.regression(data, eco.permute=10)
plot(fingerprint.regression(data, permute=10, method="lm"))

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