traitField: Calculate a species' trait field
In metricTester: Test Metric and Null Model Statistical Performance

Description Usage Arguments Details Value References Examples

Calculate the similarity in trait space of a species to those it occurs with.

1	traitField(trait.distance, picante.cdm, metric)

`trait.distance`	Symmetrical matrix summarizing pairwise trait distances. If it contains.
`picante.cdm`	A picante-style community data matrix with sites as rows, and species as columns.
`metric`	Phylogenetic metric of choice (see details).

This function is being deprecated. This and the rest of the first generation of field functions are being replaced by a two-step process akin to the calcMetrics set of functions. The user first preps the data with a prep function, then runs the desired metrics and nulls over the prepped object. This allows sets of metrics to be calculated over the same randomized matrix, rather than having to repeatedly generate the same random matrix for each metric. The trait distance matrix should be symmetrical and "complete". See example. Currently this is only programmed to use either non-abundance-weighted mean pairwise or interspecific abundance-weighted mean pairwise phylogenetic distance. Importantly, we are in the process of generalizing the phylo & trait field functions, so they operate more like the calcMetrics functions. In other words, the user will prep their data first, then choose which metrics to calculate and the function will detect whether to calculate phylo or trait fields based on the inputs. Take note of this, as code using the current forms of these functions is liable to break when these updates are made.

Named vector of species' trait fields.

Miller, Wagner, Harmon & Ricklefs. In review. Radiating despite a lack of character: closely related, morphologically similar, co-occurring honeyeaters have diverged ecologically.

#simulate tree with birth-death process
tree <- geiger::sim.bdtree(b=0.1, d=0, stop="taxa", n=50)

#simulate trait evolution up the tree. Make 2-d trait space and find distances between
#species in that space
traits <- evolveTraits(tree)

#calculate the distances betweeen species
dists <- as.matrix(dist(traits[[2]], diag=TRUE, upper=TRUE))

#simulate log-normal abundances
sim.abundances <- round(rlnorm(5000, meanlog=2, sdlog=1)) + 1

#simulate a community data matrix with these inputs
cdm <- simulateComm(tree, richness.vector=10:25, abundances=sim.abundances)

#example trait field calculations
exampleField <- traitField(trait.distance=dists, picante.cdm=cdm, metric="naw.mpd")