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GUILDS

The GUILDS package combines a range of sampling formulas for the unified neutral model of biogeography and biodiversity. Alongside the sampling formulas, it includes methods to perform maximum likelihood optimization of the sampling formulas, methods to generate data given the neutral model, and methods to estimate the expected species abundance distribution. Sampling formulas included in the GUILDS package are the Etienne Sampling Formula (Etienne 2005), the guild sampling formula, where guilds are assumed to differ in dispersal ability (Janzen et al. 2015), and the guilds sampling formula conditioned on guild size (Janzen et al. 2015).

Furthermore it contains functions to generate data given the guilds model, with or without conditioning on guild size. C++ Code to obtain Sterling numbers of the first kind was adopted from the Tetame program by Jabot et al. (2008).

Updates

  • Version 1.4.7
    • added CITATION file
    • cleaned up C++ code
  • Version 1.4
    • Cleaner README and Vignettes
    • Extend support to M1 processors where sizeof(long double) < 16
    • Comply with R_CHECK_LENGTH_0_LOGIC2
  • Version 1.3
    • GUILDS is now on GitHub: https://github.com/thijsjanzen/GUILDS
    • Wrote code tests to check code integrity, code coverage is >95
    • Modified maximum likelihood functions to take into account theta_x = theta_y = theta / 2
    • added a function to plot preston-style plots
  • Version 1.2.1
    • Updated the User manual
  • Version 1.2
    • fixed memory leak issues by adding extra vector access checks
    • fixed memory leak issues by introducing vectors in KDA code
    • renamed logLik to avoid shadowing of the function logLik in the package stats
  • Version 1.1
    • removed malloc header from KDA code

References

Janzen, T., Haegeman B., Etienne, R.S. (2015) A sampling formula for communities with multiple dispersal syndromes. Journal of Theoretical Biology 374: 94-106

Etienne, R.S. (2005). A new sampling formula for neutral biodiversity. Ecology Letters, 8(3), 253-260.

Jabot, F., Etienne, R.S., & Chave, J. (2008). Reconciling neutral community models and environmental filtering: theory and an empirical test. Oikos 117: 1308-1320

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Version

Install

install.packages('GUILDS')

Monthly Downloads

1,032

Version

1.4.7

License

GPL-2

Issues

0

Pull Requests

1

Stars

2

Forks

1

Maintainer

Thijs Janzen

Last Published

March 11th, 2025

Functions in GUILDS (1.4.7)

generate.ESF

Generate community data under the standard neutral model of biodiversity, using the urn scheme as described in Etienne 2005
logLikelihood.ESF

Likelihood of the Etienne sampling formula
logLikelihood.Guilds.Conditional

Likelihood of the Guilds sampling formula, conditional on guild size
maxLikelihood.Guilds.Conditional

Maximization of the loglikelihood under the Guilds Model, conditioned on guild size.
maxLikelihood.Guilds

Maximization of the loglikelihood under the Guilds Model.
expected.SAD

Calculate the expected species abundance distribution of the standard neutral model, given theta, m and J
generate.Guilds.Cond

Generate Artificial data under the GUILDS model, conditioned on Guild size
expected.SAD.Guilds

Estimate the expected species abundance distribution of both guilds using the guilds model, provided theta, alpha_x, alpha_y and J.
expected.SAD.Guilds.Conditional

Estimate the expected species abundance distribution of both guilds using the guilds model, provided theta, alpha_x, alpha_y, conditional on the size of guild X, Jx and the size of guild Y, Jy.
generate.Guilds

Generate Artificial data under the GUILDS model
preston_plot

Barplot in Preston style of an abundance dataset
logLikelihood.Guilds

Likelihood of the Guilds sampling formula
maxLikelihood.ESF

Maximization of the loglikelihood given the standard Neutral Model, using the Etienne Sampling Formula
GUILDS-internal

Internal Guilds functions
GUILDS-package

Package implementing the Guilds sampling formula for the Neutral Theory of Biodiversity