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Statistical analysis of species association indices

Published online by Cambridge University Press:  17 April 2024

Manuel Mendoza ,
Eduardo Mendoza Open the ORCID record for Eduardo Mendoza [Opens in a new window]  and
E. Gutiérrez-Peña Open the ORCID record for E. Gutiérrez-Peña [Opens in a new window]
Manuel Mendoza
Affiliation:
Departamento de Estadística, Instituto Tecnológico Autónomo de México, Ciudad de México, México
Eduardo Mendoza*
Affiliation:
Instituto de Investigaciones sobre los Recursos Naturales, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán, México
E. Gutiérrez-Peña
Affiliation:
Departamento de Probabilidad y Estadística, Universidad Nacional Autónoma de México, Ciudad de México, México
*
Corresponding author: Eduardo Mendoza; Email: eduardo.mendoza@umich.mx
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Abstract

The study of species association is of great interest in ecology due to its role in understanding key issues such as patterns of habitat use by animals, species coexistence, biotic interactions, and in general factors affecting community structure and assembly. There are many indices that ecologists commonly use, all based on the observed frequencies of organism occurrences, to evaluate the association between a pair of species. However, few of these indices correspond to proper statistical measures of association, and the inferential aspects of their analysis are often overlooked. In this paper, we propose a Bayesian approach based on a simple multinomial-Dirichlet structure to provide a comprehensive inferential framework for any set of association indices. Our approach provides a full statistical analysis for any association index of interest, free of special requirements on the sample size. We illustrate our procedure with a camera-trapping real-dataset, but the analysis of any other dataset of the same type can be readily produced using the R package basa that accompanies this paper.

Keywords

Bayesian ecologycamera-trapping data analysismammal coexistencepresence–absence data
Type
Method
Information
Journal of Tropical Ecology , Volume 40 , 2024 , e12
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Copyright
© The Author(s), 2024. Published by Cambridge University Press

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