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Jackknife Analysis for Ozkan's pTO Index (Islem 1 / Run 1)

Source: R/ozkan_pto_resample.R
ozkan_pto_jackknife.Rd

Implements the leave-one-out jackknife procedure from the Ozkan Excel macro (Islem 1). Removes each species one at a time, recalculates pTO, and identifies "happy" (contributing) and "unhappy" (non-contributing) species. A species is "happy" if its removal decreases the pTO index, indicating it positively contributes to the community's taxonomic diversity.

Usage

ozkan_pto_jackknife(community, tax_tree, component = "uTO_plus")

Arguments

community

A named numeric vector of species abundances. Names must match the first column of tax_tree.

tax_tree

A data frame with taxonomic hierarchy. First column is species names, subsequent columns are taxonomic ranks.

component

Character string specifying which pTO component to use for the happy/unhappy classification. One of "uTO_plus" (default), "TO_plus", "uTO", or "TO".

Value

A named list with components:

full_result

The ozkan_pto() result for the full community

jackknife_results

Data frame with leave-one-out results per species

species_status

Named logical vector: TRUE = happy (contributing), FALSE = unhappy (non-contributing)

n_happy

Number of happy species

n_unhappy

Number of unhappy species

Details

The jackknife procedure follows the Excel macro's Islem 1 logic:

  1. Compute pTO for the full community.

  2. For each species i, remove it and compute pTO for the remaining community (leave-one-out).

  3. Compare each leave-one-out result against the full-community value.

  4. If removing species i DECREASES the specified component (pTO becomes smaller), species i is classified as "happy" (contributing).

  5. If removing species i does NOT decrease the component, species i is classified as "unhappy" (non-contributing).

The happy/unhappy classification is used by ozkan_pto_resample() (Islem 2) and ozkan_pto_sensitivity() (Islem 3) to apply different resampling probabilities to each species category.

References

Ozkan, K. (2018). A new proposed measure for estimating taxonomic diversity. Turkish Journal of Forestry, 19(4), 336-346. DOI: 10.18182/tjf.441061

See also

ozkan_pto() for the core calculation, ozkan_pto_resample() for Run 2, ozkan_pto_full() for the full 3-run pipeline.

Examples

comm <- c(sp1 = 4, sp2 = 2, sp3 = 3, sp4 = 1, sp5 = 2)
tax <- data.frame(
  Species = paste0("sp", 1:5),
  Genus   = c("G1", "G1", "G1", "G2", "G2"),
  Family  = c("F1", "F1", "F1", "F1", "F1"),
  stringsAsFactors = FALSE
)
jk <- ozkan_pto_jackknife(comm, tax)
jk$species_status   # Which species are happy (contributing)?
#>  sp1  sp2  sp3  sp4  sp5 
#> TRUE TRUE TRUE TRUE TRUE 
jk$n_happy           # How many happy species?
#> [1] 5