TITAN2 (version 2.4)

titan: Perform a threshold indicator taxa analysis

Description

titan() is the primary wrapper function controlling operation of all subroutines (txa.screen(), env.part(), getivz(), ivzsums(), obs.summ(), boot.titan(), small.boot()/big.boot(), sumz.tab()) apart from plotting functions within TITAN.

Usage

titan(
  env,
  txa,
  minSplt = 5,
  numPerm = 250,
  boot = TRUE,
  nBoot = 500,
  imax = FALSE,
  ivTot = FALSE,
  pur.cut = 0.95,
  rel.cut = 0.95,
  ncpus = 1,
  memory = FALSE,
  messaging = TRUE
)

Arguments

env

A vector of environmental values.

txa

A site by taxon matrix containing observed counts at each sampling location.

minSplt

The minimum split size to be used in partitioning.

numPerm

The number of replicates to be used during permutation.

boot

A logical indicating whether bootstrap resampling should be performed.

nBoot

The number of replicates to be used during bootstrap resampling.

imax

A logical indication whether taxon-specific change points should be determined using IndVal maxima or z-score maxima (as in Baker and King 2010, 2013).

ivTot

A logical indicating whether IndVal scores should be calculated using total relative abundance or the mean relative abundace originally proposed by Dufrene and Legendre (1997).

pur.cut

A proportion specifying the cutoff value for determining purity across all bootstrap replicates.

rel.cut

A proportion specifying the cutoff value for determining reliability across all bootstrap replicates.

ncpus

The number of processing cores to be used during processing. If greater than 1, TITAN will load and use the package 'snow' to perform parallel processing on each core.

memory

A logical indicating whether temporary files should be written to a scratch directory during bootstrap processing to preserve active memory. This function is sometimes necessary for large data files (e.g. more than 400 sampling sites and less than 100 taxa).

messaging

If TRUE, provide progress messages.

Value

A list with 13 items:

  • sppmaxDescription of 'comp1'

  • sumz.cpDescription of 'comp1'

  • envThe vector of environmental values used in the TITAN function call

  • taxaThe site-by-taxon matrix used in the TITAN function call

  • envlcsA vector of candidate partitions derived from subtracting 'minSplt' from 'env'

  • srtEnvA sorted version of environmental values

  • ivzScoresA matrix containing group membership, z scores, IndVals, and p values for each taxon at every candidate partition in 'envcls'

  • ivzA 2-column matrix containing parallel vectors of sum(z-) and sum(z+ scores for every candidate partition in 'envcls')

  • ivz.fA 2-column matrix containing parallel vectors of sum(z-) and sum(z+ scores filtered by pure and reliable taxa for every candidate partition in 'envcls')

  • maxSumzA 2-column matrix of environmental values at sum(z-) and sum(z+) maxima across all bootstrap replicates

  • maxFsumzA 2-column matrix of environmental values at filtered sum(z-) and sum(z+) maxima across all bootstrap replicates

  • metricArrayAn array of group membership, env change points, z scores, and p values equivalent to 'ivzScores' for each bootstrap replicate

  • targsA vector of arguments used in the TITAN function call

References

Baker, ME and RS King. 2010. A new method for detecting and interpreting biodiversity and ecological community thresholds. Methods in Ecology and Evolution 1(1): 25:37.

King, RS and ME Baker 2010. Considerations for identifying and interpreting ecological community thresholds. Journal of the North American Benthological Association 29(3):998-1008.

Baker ME and RS King. 2013. Of TITAN and straw men: an appeal for greater understanding of community data. Freshwater Science 32(2):489-506.

Examples

Run this code
# NOT RUN {
data(glades.env); str(glades.env)
data(glades.taxa); str(glades.taxa)

# small run to illustrate data structure
glades.titan <- titan(glades.env, glades.taxa, minSplt = 5,
  numPerm = 25, boot = TRUE, nBoot = 2, imax = FALSE,
  ivTot = FALSE, pur.cut = 0.95, rel.cut = 0.95, ncpus = 2, memory = FALSE
)
str(glades.titan, give.attr = FALSE)


# typical run
if (FALSE) {
glades.titan <- titan(glades.env, glades.taxa, minSplt = 5,
  numPerm = 250, boot = TRUE, nBoot = 100, imax = FALSE,
  ivTot = FALSE, pur.cut = 0.95, rel.cut = 0.95, ncpus = 7, memory = FALSE
)
}




# }

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