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entropart: An R Package to Measure and Partition Diversity

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  • Marcon, Eric
  • Hérault, Bruno

Abstract

entropart is a package for R designed to estimate diversity based on HCDT entropy or similarity-based entropy. It allows calculating species-neutral, phylogenetic and functional entropy and diversity, partitioning them and correcting them for estimation bias.

Suggested Citation

  • Marcon, Eric & Hérault, Bruno, 2015. "entropart: An R Package to Measure and Partition Diversity," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i08).
    • Handle: RePEc:jss:jstsof:v:067:i08
    DOI: http://hdl.handle.net/10.18637/jss.v067.i08
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    References listed on IDEAS

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    1. Wang, Ji-Ping, 2011. "SPECIES: An R Package for Species Richness Estimation," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i09).
    2. Chun-Huo Chiu & Anne Chao, 2014. "Distance-Based Functional Diversity Measures and Their Decomposition: A Framework Based on Hill Numbers," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-17, July.
    3. Dray, Stéphane & Dufour, Anne-Béatrice, 2007. "The ade4 Package: Implementing the Duality Diagram for Ecologists," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 22(i04).
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Alana Pacheco-Flores & Alejandro Casas & Ana I. Moreno-Calles & Roberto Lindig-Cisneros & Francisco Javier Rendón-Sandoval & Francisco Mora-Ardila & Fernando Estañol-Tecuatl & Gonzalo D. Álvarez-Ríos , 2024. "Secondary Succession in Fallow Agroforestry Systems Managed in Tropical Dry Forest in Western Mexico," Sustainability, MDPI, vol. 16(11), pages 1-19, June.
    2. Francisco J. Rendón-Sandoval & Alejandro Casas & Ana I. Moreno-Calles & Ignacio Torres-García & Eduardo García-Frapolli, 2020. "Traditional Agroforestry Systems and Conservation of Native Plant Diversity of Seasonally Dry Tropical Forests," Sustainability, MDPI, vol. 12(11), pages 1-27, June.
    3. Maurent, Eliott & Hérault, Bruno & Piponiot, Camille & Derroire, Géraldine & Delgado, Diego & Finegan, Bryan & Kientz, Mélaine Aubry & Amani, Bienvenu H.K. & Bieng, Marie Ange Ngo, 2023. "A common framework to model recovery in disturbed tropical forests," Ecological Modelling, Elsevier, vol. 483(C).

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