### Introduction

### Theory, Examples & Exercises

en:rarefaction_r

Section: Diversity analysis

(library`iNEXT`

`iNEXT`

) calculates abundance- and incidence-based rarefaction of species on number of individals (or sites) or on sample coverage (a measure of completeness). The name stems from*in*terpolation-*ext*rapolation, since the function allows both inter- and extrapolation of the rarefaction curve (extrapolation works up to 2 times of max number of individuals or samples). Function`plot`

draws the rarefaction curves (optionally with confidence intervals) for any combination of number of individuals (or samples) x number of species x sample coverage (modified by the argument`type`

in the function`plot`

applied on`iNEXT`

object, see`?plot.iNEXT`

).(library`estimateD`

`iNEXT`

) - rarifies number of species per common number of individuals or sites, or per common level of coverage (completeness). Does not only for species richness (*q*= 0), but also for Shannon and Simpson diversity, respectively (*q*= 1 and*q*= 2).(library`rarefy`

`vegan`

) - calculates abundance-based rarefaction. Applies on sample x species matrix (cells must be genuine abundances, i.e. counts of individuals) or vector of abundances.(library`rarecurve`

`vegan`

) - draws rarefaction curve for each row in the data. No confidence intervals calculated.(library`specaccum`

`vegan`

) - calculates accumulation curve on the community data matrix (one curve per matrix);`plot`

draws the result (optionally with confidence interval).

en/rarefaction_r.txt · Last modified: 2019/03/22 22:04 by David Zelený