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Description

Functional Guilds, Invasion Status, Endemism, and Rarity of Ants.

Provides functions for the analysis of ant communities, aiming to standardize workflows in myrmecology. The package automates the assignment of species to functional guilds based on trophic strategies, feeding habits, and foraging behavior, using established classification frameworks (Silva et al., 2015 <doi:10.7476/9788574554419>; Silvestre et al., 2003 <isbn:9588151236>; Delabie et al., 2000 <https://www.researchgate.net/publication/44961742_Sampling_Ground-Dwelling_Ants_Case_Studies_from_the_World%27s_Rain_Forests>), and also includes a novel classification system implemented within the package, developed from ant species occurring in urban environments. It also includes routines to flag exotic species of Brazil (Vieira, 2025, unpublished master's thesis), identify endemic species (Silva et al., 2025 <doi:10.37885/250920259>), and classify species rarity and rarity forms of the Atlantic Forest (Silva et al., 2024 <doi:10.1016/j.biocon.2024.110640>). The package reduces manual effort and improves reproducibility, supporting research and biodiversity management of Neotropical ant communities.

AntClassify

R-CMD-check

AntClassify is an R package designed to standardize ant community analyses, particularly for Neotropical and Brazilian Atlantic Forest assemblages. It automates:

  • Classification of species into functional guilds based on trophic strategies and foraging behavior. The package offers two approaches: (1) classification using established criteria from the literature (Delabie et al., 2000; Silvestre et al., 2003; Silva et al., 2015), and (2) a built-in classification derived from urban ant communities.
  • Identification of exotic species recorded in Brazil (Vieira, 2025).
  • Identification of endemic species of the Atlantic Forest (Silva et al., 2025).
  • Classification of rarity based on geographic distribution and local abundance (Silva et al., 2024).

By automating these tasks, AntClassify reduces manual effort and increases reproducibility, making it a practical tool for researchers working with ant assemblages.

Installation

You can install the development version of AntClassify from GitHub:

# install.packages("remotes")
remotes::install_github("cogdebora/AntClassify")

Once the package is accepted on CRAN, you will also be able to install it with:

install.packages("AntClassify")

Example

Below is a reproducible example using a standardized test dataset:

library(AntClassify)

# Create test dataset (same structure used in package tests)
ant_test_data <- data.frame(
  "Pheidole megacephala" = 10,
  "Strumigenys emmae" = 5,
  "Paratrechina longicornis" = 8,
  "Hypoponera leninei" = 3,
  "Camponotus fallatus" = 2,
  "Ectatomma brunneum" = 1,
  "Ectatomma permagnum" = 1,
  "Pheidole aberrans" = 1,
  "Pheidole fimbriata" = 1,
  "Pheidole obscurithorax" = 1,
  check.names = FALSE
)

# Run full pipeline
results <- antclassify(ant_test_data)

# View outputs
results$exotic$table
results$endemic$table
results$rarity$table

# Plot outputs
print(results$exotic$plot)
print(results$endemic$plot)
print(results$rarity$plot)

For more detailed examples and function documentation, see the package vignettes:

vignette("AntClassify")

Citation

If you use AntClassify in your research, please cite the following references:

  • Silva, N. S., Maciel, E. A., Prado, L. P., Silva, O. G., Barbosa, D. A., Andrade-Silva, J., ... & Morini, M. S. (2024). Ant rarity and vulnerability in Brazilian Atlantic Forest fragments. Biological Conservation, 296, 110640. DOI: https://doi.org/10.1016/j.biocon.2024.110640

  • Silva, N. S., Gonçalves, D. C. de O., Wazema, C. T., Barbosa, D. A., Prado, L. P. do, Andrade-Silva, J., Fernandes, T. T., Silva, R. R., & Morini, M. S. de C. (2025). Endemism and vulnerability of ants in the phytophysiognomies of the Brazilian Atlantic Forest. In Brazilian Myrmecology: Exploring the World’s Richest Ant Fauna (Cap. 16, pp. 371–394). Editora Científica Digital. DOI: https://doi.org/10.37885/250920259

  • Vieira, V. B. (2024). Quem são e onde estão as formigas exóticas do Brasil? [Dissertação de Mestrado, Universidade Federal do Paraná]. Curitiba, PR, Brasil.

  • Silvestre, R., Brandão, C. R. F., & Silva, R. R. (2003). Grupos funcionales de hormigas: el caso de los gremios del Cerrado. In F. Fernández (Ed.), Introducción a las Hormigas de las Región Neotropical (pp. 113–148). Instituto Alexander Von Humboldt.

  • Silva, R. R., Silvestre, R., Brandão, C. R. F., Morini, M. S. C., & Delabie, J. H. C. (2015). Grupos trófi cos e guildas em formigas poneromorfas. In: Delabie, Jacques H. C. et al. As formigas poneromorfas do Brasil. Ilhéus: Editus, 2015. p. 163-179.

  • Delabie, J. H. C., Agosti, D., & Nascimento, I. C. (2000). Litter ant communities of the Brazilian Atlantic rain forest region. Sampling Ground-dwelling Ants: case studies from the world’s rain forests. Curtin University of Technology School of Environmental Biology Bulletin,v. 18.

Additionally, if you use the package itself, please cite:

  • Gonçalves, D. C. O., et al. (2026). AntClassify: An R package for ant community analysis (Version 0.1.0) [Computer software].
    https://github.com/cogdebora/AntClassify.
Metadata

Version

0.2.1

License

Unknown

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