Calculates traits' phylogenetic inertia and regresses this against trait similarity among co-existing species (sensu Cavender-Bares et al. 2004 Figure 6)
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",
...
)
comparative.comm
for analysis
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
)
how to compare distance matrices (only the lower
triangle;), one of: lm
(linear regression),
quantile
(DEFAULT; rq
),
mantel
(mantel
)
number of permutations for ecological null model
(eco.rnd
); default 1000
how to measure phylogenetic inertia, one of:
lambda
(default), delta
, kappa
, blom.k
;
see phy.signal
.
number of independent swap iterations to perform
(if specified in eco.rnd
; DEFAULT 1000)
whether to incorporate species' abundances (default: TRUE)
additional parameters to pass on to model fitting functions and plotting functions
fingerprint.regression
object
fingerprint.regression
object
plot the observed slopes (DEFAULT: slope
), or the
median difference between the simulations and the observed values
(corrected
)
label for x-axis (default "Ecological Trait Coexistence")
label for y-axis (default "Phylogenetic inertia")
Will Pearse and Jeannine Cavender-Bares
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.
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.
eco.xxx.regression
phy.signal
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"))
Run the code above in your browser using DataLab