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The unified neutral theory of biodiversity: the untb package

The untb package provides R-centric functionality for working with Hubbell’s unified neutral theory of biogeography and biodiversity. A vignette is provided in the package. The canonical reference is Hubbell 2001; to cite the package in publications please use Hankin 2007.

Installation

You can install the released version of the untb package from CRAN with:

# install.packages("untb")  # uncomment this to install the package
library("untb")
set.seed(0)

The untb package in use

The package has two main classes, count and census. A count object is a named integer vector, with names being species and entries being respective counts. Thus:

x <- count(c(cats=9,pigs=3,dogs=2,rats=1,hogs=1,bats=1))
x
#> cats pigs dogs rats hogs bats 
#>    9    3    2    1    1    1
summary(x)
#> Number of individuals: 17 
#> Number of species: 6 
#> Number of singletons: 3 
#> Most abundant species: cats (9 individuals)
#> estimated theta:  2.861392

Above, we see 9 cats, 3 pigs, and so on. Function summary() gives further information. A census object is an unordered factor with entries being the species of each individual:

as.census(x)
#>  [1] cats cats cats cats cats cats cats cats cats pigs pigs pigs dogs dogs rats
#> [16] hogs bats
#> Levels: cats pigs dogs rats hogs bats

The package includes example datasets:

data(sahfos)
summary(sahfos)
#> Number of individuals: 460182 
#> Number of species: 54 
#> Number of singletons: 10 
#> Most abundant species: Echinodermata larvae (247200 individuals)
#> estimated theta:  4.649568

We can give a visual summary of a dataset in two ways:

plot(sahfos)
plot(preston(sahfos))

The package also includes the ability to generate random neutral assemblages:

summary(rand.neutral(1000,10))
#> Number of individuals: 1000 
#> Number of species: 47 
#> Number of singletons: 8 
#> Most abundant species: 2 (330 individuals)
#> estimated theta:  10.09543
summary(rand.neutral(1000,10))
#> Number of individuals: 1000 
#> Number of species: 52 
#> Number of singletons: 16 
#> Most abundant species: 4 (117 individuals)
#> estimated theta:  11.50422

References

  • S. P. Hubbell 2001. “The Unified Neutral Theory of Biodiversity and Biogeography”, Princeton University Press.

  • R. K. S. Hankin, 2007. “Introducing untb, an R package for simulating ecological drift under the unified nuetral theory of biodiversity”, Journal of Statistical Software 22(12)

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Version

Install

install.packages('untb')

Monthly Downloads

363

Version

1.7-7

License

GPL

Issues

Pull Requests

Stars

Forks

Maintainer

Robin K S Hankin

Last Published

August 20th, 2023

Functions in untb (1.7-7)

ghats

Tree counts in 1-ha plots from the Western Ghats mountains (South India)
optimal.prob

Returns an estimate of the fundamental biodiversity number
logkda

Etienne's K(D,A)
logS1

logarithms of Stirling numbers of the first kind
saunders

Dataset due to Saunders
simpson

Simpson's diversity index
optimal.params.gst

Estimation of local immigration using GST(k) statistics
sahfos

Biodiversity dataset provided by SAHFOS
rand.neutral

Random neutral ecosystem
summary.count

Summary methods for count and census objects
theta.prob

Posterior probabilities for theta
fisher

Various functionality to implement Fisher's logseries
+.count

Add two count objects
volkov

Expected frequency of species
species.count

Ecosystem diagnostics for output of untb()
vallade

Various functions from Vallade and Houchmandzadeh
preston

Preston diagram of an ecosystem
print.preston

Print and plot objects of class Preston
phi

Hubbell's phi
print.summary.count

Print method for summary objects
spitale

Counts of diatom species in springs of the Adamello-Brenta Nature Park
isolate

Randomly select a subset of an ecosystem
zsm

Zero sum multinomial distribution as derived by McKane
plot.count

Abundance curves
untb

Ecological drift simulation under the Unified Neutral Theory of Biodiversity
untb-package

Unified neutral theory of biodiversity
alonso

Various functions from Alonso and McKane 2004
etienne

Etienne's sampling formula
expected.abundance

Expected abundances under the neutral model
bci

Barro Colorado Island (BCI) dataset
copepod

Copepod data supplied by Phil Pugh
caruso

Dataset due to Caruso
count

Construct, coerce, and test for a count object
census

Construct, coerce, and test for a census object
butterflies

abundance data for butterflies
display.untb

Animation of neutral ecological drift
no.of.ind

Ecosystem diagnostics
optimal.params.sloss

Estimation of neutral community parameters using a two-stage maximum-likelihood procedure
extractor

Extract rows of a database in count form