ph_comtrait {phylocomr}

comtrait

Description

Calculate measures of trait dispersion within each community, and compare observed patterns to those expected under a null model.

Usage

ph_comtrait(
  sample,
  traits,
  binary = NULL,
  metric = "variance",
  null_model = 0,
  randomizations = 999,
  abundance = TRUE
)

Arguments

sample

(data.frame/character) sample data.frame or path to a sample file

traits

(data.frame/character) traits data.frame or path to a traits file

binary

(logical) a logical vector indicating what columns are to be treated as binary characters - all others are treated as continuous

metric

(integer) metric to calculate. One of variance, mpd, mntd, or range (converted to phylocom integer format internally)

null_model

(integer) which null model to use. See Details.

randomizations

(numeric) number of randomizations. Default: 999

abundance

(logical) If TRUE (default) computed accounting for abundance. Otherwise, uses presence-absence.

Details

See phylocomr-inputs for expected input formats

If you give a data.frame to traits parameter it expects data.frame like

• species - the taxon labels matching the sample data to sample parameter

• col1,col2,col3,etc. - any number of trait columns - column names do not matter

When giving a data.frame to traits make sure to pass in a binary vector for what traits are to be treated as binary.

Value

data.frame of the form:

• trait - Trait name

• sample - Sample name

• ntaxa - Number of taxa in sample

• mean - Mean value of trait in sample

• metric - Observed metric in sample

• meanrndmetric - Mean value of metric in null models

• sdrndmetric - Standard deviation of metric in null models

• sesmetric - Standardized effect size of metric

• ranklow - Number of randomizations with metric lower than observed

• rankhigh - Number of randomizations with metric higher than observed

• runs - Number of randomizations

Null models

• 0 - This null model shuffles trait values across species.

• 1 - Species in each sample become random draws from sample pool. This null model maintains the species richness of each sample, but the identities of the species occurring in each sample are randomized. For each sample, species are drawn without replacement from the list of all species actually occurring in at least one sample

• 2 - Species in each sample become random draws from traits data. This null model maintains the species richness of each sample, but the identities of the species occurring in each sample are randomized. For each sample, species are drawn without replacement from the list of all species with trait values. This function is redundant since by definition the sample and trait species must match, but is included for consistency with the comstruct function.

• 3 - Independent swap: Same as for ph_comdist and ph_comstruct

Taxon name case

In the sample and trait tables, if you're passing in a file, the names in the third and first columns, respectively, must be all lowercase; if not, we'll lowercase them for you. If you pass in a data.frame, we'll lowercase them for your. All phylo tip/node labels are also lowercased to avoid any casing problems

Examples

## Not run: 
sfile <- system.file("examples/sample_comstruct", package = "phylocomr")
tfile <- system.file("examples/traits_aot", package = "phylocomr")

# from files
sample_str <- paste0(readLines(sfile), collapse = "\n")
sfile2 <- tempfile()
cat(sample_str, file = sfile2, sep = '\n')

traits_str <- paste0(readLines(tfile), collapse = "\n")
tfile2 <- tempfile()
cat(traits_str, file = tfile2, sep = '\n')

ph_comtrait(sample = sfile2, traits = tfile2)

# from data.frame
sampledf <- read.table(sfile, header = FALSE,
  stringsAsFactors = FALSE)
traitsdf_file <- system.file("examples/traits_aot_df",
  package = "phylocomr")
traitsdf <- read.table(text = readLines(traitsdf_file), header = TRUE,
  stringsAsFactors = FALSE)
ph_comtrait(sample = sampledf, traits = traitsdf,
  binary = c(FALSE, FALSE, FALSE, TRUE))

## End(Not run)