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Batch Analysis from a Single Data Frame

Source: R/batch_analysis.R
batch_analysis.Rd

Computes all diversity indices for one or more sample sites from a single data frame (e.g., imported from Excel). The function automatically detects the site column, taxonomic columns, and abundance column, splits the data by site, and returns a summary data frame with species count and 14 diversity indices per site.

Usage

batch_analysis(
  data,
  site_column = NULL,
  tax_columns = NULL,
  abundance_column = "Abundance",
  correction = c("none", "miller_madow", "grassberger", "chao_shen"),
  parallel = FALSE,
  n_cores = NULL
)

Arguments

data

A data frame containing species data. Must include at minimum a species column, at least one taxonomic rank column, and an abundance column. Optionally includes a site/plot column for multi-site analysis.

site_column

Character string specifying the name of the site column. If NULL (default), the function searches for columns named "Site", "site", "Alan", "alan", "Plot", or "plot". If no such column is found, all data is treated as a single site.

tax_columns

Character vector specifying the names of the taxonomic columns (from Species to highest rank). If NULL (default), the function auto-detects columns named "Species", "Genus", "Family", "Order", "Class", "Phylum", and "Kingdom" (case-insensitive).

abundance_column

Character string specifying the name of the abundance column. Default is "Abundance" (case-insensitive match).

correction

Bias correction for the Shannon index. One of "none" (default), "miller_madow", "grassberger", or "chao_shen". Passed to shannon(). See shannon() for details.

parallel

Logical. If TRUE, use parallel processing to compute indices for multiple sites concurrently. Default FALSE.

n_cores

Number of CPU cores to use when parallel = TRUE. Default NULL uses up to 2 cores (CRAN policy limit).

Value

A data frame with one row per site and columns: Site, N_Species, Shannon, Simpson, Delta, Delta_star, AvTD, VarTD, uTO, TO, uTO_plus, TO_plus, uTO_max, TO_max, uTO_plus_max, TO_plus_max.

Details

When no site column is present (or all values are identical), the entire data set is treated as a single community.

The function calculates the following indices per site:

  • Shannon: Shannon-Wiener entropy (shannon)

  • Simpson: Gini-Simpson index (simpson)

  • Delta: Clarke & Warwick taxonomic diversity (delta)

  • Delta_star: Clarke & Warwick taxonomic distinctness (delta_star)

  • AvTD: Average taxonomic distinctness (avtd)

  • VarTD: Variation in taxonomic distinctness (vartd)

  • uTO: Unweighted taxonomic diversity (Ozkan pTO, all levels)

  • TO: Weighted taxonomic diversity (Ozkan pTO, all levels)

  • uTO_plus: Unweighted taxonomic distance (Ozkan pTO, all levels)

  • TO_plus: Weighted taxonomic distance (Ozkan pTO, all levels)

  • uTO_max: Unweighted taxonomic diversity (informative levels only)

  • TO_max: Weighted taxonomic diversity (informative levels only)

  • uTO_plus_max: Unweighted taxonomic distance (informative levels only)

  • TO_plus_max: Weighted taxonomic distance (informative levels only)

See also

compare_indices for analysis with pre-built community vectors, build_tax_tree for building taxonomic trees manually.

Examples

# Single-site data (no Site column)
df <- data.frame(
  Species   = c("sp1", "sp2", "sp3", "sp4"),
  Genus     = c("G1", "G1", "G2", "G2"),
  Family    = c("F1", "F1", "F1", "F2"),
  Order     = c("O1", "O1", "O1", "O1"),
  Abundance = c(10, 20, 15, 5),
  stringsAsFactors = FALSE
)
batch_analysis(df)
#> taxdiv -- Batch Analysis
#>   Sites: 1 
#>   Indices: 14 
#> 
#>  Site N_Species  Shannon Simpson    Delta Delta_star AvTD    VarTD      uTO
#>   All         4 1.279854     0.7 1.326531   1.857143    2 0.666667 3.413215
#>        TO uTO_plus  TO_plus  uTO_max   TO_max uTO_plus_max TO_plus_max
#>  5.066836  4.04615 5.837909 3.413215 5.066836      4.04615    5.837909

# Multi-site data (with Site column)
df2 <- data.frame(
  Site      = c("A", "A", "A", "B", "B", "B"),
  Species   = c("sp1", "sp2", "sp3", "sp1", "sp3", "sp4"),
  Genus     = c("G1", "G1", "G2", "G1", "G2", "G2"),
  Family    = c("F1", "F1", "F1", "F1", "F1", "F2"),
  Order     = c("O1", "O1", "O1", "O1", "O1", "O1"),
  Abundance = c(10, 20, 15, 5, 25, 10),
  stringsAsFactors = FALSE
)
batch_analysis(df2)
#> taxdiv -- Batch Analysis
#>   Sites: 2 
#>   Indices: 14 
#> 
#>  Site N_Species  Shannon  Simpson    Delta Delta_star     AvTD    VarTD
#>     A         3 1.060857 0.641975 1.111111   1.692308 1.666667 0.222222
#>     B         3 0.900256 0.531250 0.833333   1.529412 2.000000 0.666667
#>       uTO       TO uTO_plus  TO_plus  uTO_max   TO_max uTO_plus_max TO_plus_max
#>  2.442117 3.132154 2.577008 3.270155 2.442117 3.132154     2.577008    3.270155
#>  2.804266 4.533563 3.767722 5.559482 2.804266 4.533563     3.767722    5.559482