iNEXT4steps {iNEXT.4steps}

Main function for complete 4-step analysis

Description

iNEXT4steps computes all statistics in the complete 4-step analysis and visualizes the output. It computes sample completeness, observed and asymptotic diversity, size-based and coverage-based standardized diversity, and evenness.

Usage

iNEXT4steps(
  data,
  q = seq(0, 2, 0.2),
  datatype = "abundance",
  nboot = 30,
  conf = 0.95,
  nT = NULL,
  details = FALSE
)

Arguments

data

(a) For datatype = "abundance", data can be input as a vector of species abundances (for a single assemblage), matrix/data.frame (species by assemblages), or a list of species abundance vectors.
(b) For datatype = "incidence_raw", data can be input as a list of matrix/data.frame (species by sampling units); data can also be input as a matrix/data.frame by merging all sampling units across assemblages based on species identity; in this case, the number of sampling units (nT, see below) must be input.

q

a numerical vector specifying the orders of q that will be used to compute sample completeness and evenness as well as plot the relevant profiles. Default is seq(0, 2, by = 0.2).

datatype

data type of input data: individual-based abundance data (datatype = "abundance") or species by sampling-units incidence matrix (datatype = "incidence_raw") with all entries being 0 (non-detection) or 1 (detection).

nboot

a positive integer specifying the number of bootstrap replications when assessing sampling uncertainty and constructing confidence intervals. Enter 0 to skip the bootstrap procedures. Default is 30.

conf

a positive number < 1 specifying the level of confidence interval. Default is 0.95.

nT

(required only when datatype = "incidence_raw" and input data in a single matrix/data.frame) a vector of positive integers specifying the number of sampling units in each assemblage. If assemblage names are not specified (i.e., names(nT) = NULL), then assemblages are automatically named as "Assemblage1", "Assemblage2",..., etc.

details

a logical variable to indicate whether the detailed numerical values for each step are displayed. Default is FALSE.

Value

a list of three of objects:

$summary Numerical table for each individual step.

Assemblage

the assemblage names.

qTD

'Species richness' represents the taxonomic diversity of order q=0; 'Shannon diversity' represents the taxonomic diversity of order q=1, 'Simpson diversity' represents the taxonomic diversity of order q=2.

TD_obs

the observed taxonomic diversity value of order q.

TD_asy

the estimated asymptotic diversity value of order q.

s.e.

the bootstrap standard error of the estimated asymptotic diversity of order q.

qTD.LCL, qTD.UCL

the bootstrap lower and upper confidence limits for the estimated asymptotic diversity of order q at the specified level in the setting (with a default value of 0.95).

Pielou J'

a widely used evenness measure based on Shannon entropy.

$figure six figures including five individual figures (for STEPS 1, 2a, 2b, 3 and 4 respectively) and a complete set of five plots.

$details (only when details = TRUE). The numerical output for plotting all figures.

Examples

## Complete 4-step analysis for abundance data
data(Data_spider)
Four_Steps_out1 <- iNEXT4steps(data = Data_spider, datatype = "abundance")
Four_Steps_out1


## Complete 4-step analysis for incidence data
data(Data_woody_plant)
Four_Steps_out2 <- iNEXT4steps(data = Data_woody_plant, datatype = "incidence_raw")
Four_Steps_out2