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Categorical Analysis of Neo- and Paleo-Endemism (CANAPE)

ps_canape.Rd

This function classifies sites into areas of significant endemism according to the scheme of Mishler et al. (2014). Categorization is based on randomization quantile values for PE, RPE, and CE (which Mishler et al. call "PE on the comparison tree").

Usage

ps_canape(rand, alpha = 0.05)

Arguments

rand

An object returned by running ps_rand with .

alpha

Numeric value between 0 and 1 giving the one-tailed p-value threshold to use when determining significance.

Value

An object of the same class as rand containing a variable called "canape", with values 0-4 corresponding to not-significant, mixed-, super-, neo-, and paleo-endemism, respectively.

Details

Endemism significance categories are defined as follows:

  • Endemism not significant: neither PE nor CE are significantly high at alpha.

  • Significant neoendemism: PE or CE are significantly high at alpha; RPE significantly low at alpha / 2 (two-tailed test).

  • Significant paleoendemism: PE or CE are significantly high at alpha; RPE significantly high at alpha / 2 (two-tailed test)..

  • Significant mixed-endemism: PE or CE are significantly high at alpha; RPE not significant.

  • Significant super-endemism: PE or CE are significantly high at alpha / 5; RPE not significant.

References

Mishler, B. D., Knerr, N., González-Orozco, C. E., Thornhill, A. H., Laffan, S. W., & Miller, J. T. (2014). Phylogenetic measures of biodiversity and neo-and paleo-endemism in Australian Acacia. Nature Communications, 5(1), 4473.

Examples

# \donttest{
# classic CANAPE using binary data and the curveball algorithm
# (note that a real analysis would require a much higher `n_rand`)
set.seed(123456)
ps <- ps_simulate(data_type = "binary")
rand <- ps_rand(ps, metric = c("PE", "RPE", "CE"),
                fun = "nullmodel", method = "curveball",
                n_rand = 25, burnin = 10000, progress = FALSE)
canape <- ps_canape(rand)
terra::plot(canape)

# }