This package computes diversity for community data sets using the methods outlined by Jost (2006, 2007). While there are differing opinions on the ideal way to calculate diversity (e.g. Magurran 2004), this method offers the advantage of providing diversity numbers equivalents, independent alpha and beta diversities, and the ability to incorporate 'order' (q) as a continuous measure of the importance of rare species in the metrics. The functions provided in this package largely correspond with the equations offered by Jost in the cited papers. The package computes alpha diversities, beta diversities, gamma diversities, and similarity indices. Confidence intervals for diversity measures are calculated using a bootstrap method described by Chao et al. (2008). For datasets with many samples (sites, plots), sim.table creates tables of all pairwise comparisons possible, and for grouped samples sim.groups calculates pairwise combinations of within- and between-group comparisons.
|Author||Noah Charney, Sydne Record|
|Date of publication||2012-10-29 08:59:58|
|Maintainer||Noah Charney <firstname.lastname@example.org>|
bootstrap: Estimates Uncertainties with Bootstrapping
d: 'Numbers Equivalents' for Alpha, Beta and Gamma Diversity...
H: 'Standard Diversity Indices' for Alpha, Beta, and Gamma...
M.homog: MacArthur's Homogeneity Measure
normalize.rows: Converts absolute abundances to relative proportions of...
p.q.sum: Sum of proportional abundance of species
Rel.homog: Relative Homogeneity
simesants: Harvard Forest Simes Tract Ant Community Data
sim.groups: Within- and Between-Group Similarities
similarity: Similarity Summary Table
sim.table: Similarity Summary Table
turnover: Turnover Rate per Sample
vegetarian-package: Jost Diversity Measures for Community Data