pez.endemism {pez}

Calculate (phylogenetic) endemism

Description

At present, only a small number of metrics, but we intend for this to grow with time. Note that metrics that incorporate abundance are mixed in with those that do not. Some of these metrics make sense when used with probabilities, for example those derived from an SDM; some do not. You will have to use your own judgement (as with everything in science!).

Usage

pez.endemism(data, sqrt.phy = FALSE)

Arguments

data

comparative.comm object

sqrt.phy

If TRUE (default is FALSE) your phylogenetic distance matrix will be square-rooted; specifying TRUE will force the square-root transformation on phylogenetic distance matrices (in the spirit of Leitten and Cornwell, 2014). See ‘details’ for details about different metric calculations when a distance matrix is used.

Value

data.frame with metric values.

Author(s)

Will Pearse, Dan Rosauer

References

BED Cadotte, M. W., & Jonathan Davies, T. (2010). Rarest of the rare: advances in combining evolutionary distinctiveness and scarcity to inform conservation at biogeographical scales. Diversity and Distributions, 16(3), 376-385.

PE Rosauer, D. A. N., Laffan, S. W., Crisp, M. D., Donnellan, S. C., & Cook, L. G. (2009). Phylogenetic endemism: a new approach for identifying geographical concentrations of evolutionary history. Molecular Ecology, 18(19), 4061-4072.

See Also

pez.shape pez.evenness pez.dispersion pez.dissimilarity

Examples

data(laja)
data <- comparative.comm(invert.tree, river.sites, invert.traits)
(output<-pez.endemism(data))