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Lookup NU author(s): Dr Colin GillespieORCiD
This is the authors' accepted manuscript of an article that has been published in its final definitive form by Wiley-Blackwell Publishing Ltd., 2019.
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© 2018 The Authors. Methods in Ecology and Evolution © 2018 British Ecological Society Species abundance distributions (SADs) are one of the most widely used tools in macroecology, and it has become increasingly apparent that many empirical SADs can best be described as multimodal. However, only a few SAD models have been extended to incorporate multiple modes and no software packages are available to fit multimodal SAD models. In this study, we present an extension of the gambin SAD model to multimodal SADs. We derive the maximum likelihood equations for fitting the bimodal gambin distribution and generalize this approach to fit gambin models with any number of modes. We present these new functions, along with additional functions to aid in the analysis of multimodal SADs, within an updated r package (“gambin”; version 2.4.0) that enables the fitting, plotting and evaluating of gambin models with any number of modes. We use a mixture of simulations and empirical datasets to test our new models, including tests of the sensitivity of the model parameters to the number of individuals and the number of species in a sample. We show that the new multimodal gambin models perform well under a variety of circumstances, and that the application of these new models to empirical SAD and other macroecological (e.g., species range size distributions) datasets can provide interesting insights. The updated software package is simple to use and provides straightforward yet flexible statistical analyses of multimodality in SAD-type datasets.
Author(s): Matthews TJ, Borregaard MK, Gillespie CS, Rigal F, Ugland KI, Kruger RF, Marques R, Sadler JP, Borges PAV, Kubota Y, Whittaker RJ
Publication type: Article
Publication status: Published
Journal: Methods in Ecology and Evolution
Year: 2019
Volume: 10
Issue: 3
Pages: 432-437
Print publication date: 01/03/2019
Online publication date: 13/11/2018
Acceptance date: 27/10/2018
Date deposited: 08/01/2019
ISSN (electronic): 2041-210X
Publisher: Wiley-Blackwell Publishing Ltd.
URL: https://doi.org/10.1111/2041-210X.13122
DOI: 10.1111/2041-210X.13122
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