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Extension of the gambin model to multimodal species abundance distributions

Lookup NU author(s): Dr Colin Gillespie

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This is the authors' accepted manuscript of an article that has been published in its final definitive form by Wiley-Blackwell Publishing Ltd., 2019.

For re-use rights please refer to the publisher's terms and conditions.


Abstract

© 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.


Publication metadata

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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