An extensive comparison of species-abundance distribution models
A number of different models have been proposed as descriptions of the species-abundance distribution (SAD). Most evaluations of these models use only one or two models, focus on only a single ecosystem or taxonomic group, or fail to use appropriate statistical methods. We use likelihood and AIC to...
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doaj-c5f09745a7fe4c82975cc1c29a7c82de2020-11-24T23:06:46ZengPeerJ Inc.PeerJ2167-83592016-12-014e282310.7717/peerj.2823An extensive comparison of species-abundance distribution modelsElita Baldridge0David J. Harris1Xiao Xiao2Ethan P. White3Department of Biology, Utah State University, Logan, UT, United StatesDepartment of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL, United StatesDepartment of Biology, Utah State University, Logan, UT, United StatesDepartment of Biology, Utah State University, Logan, UT, United StatesA number of different models have been proposed as descriptions of the species-abundance distribution (SAD). Most evaluations of these models use only one or two models, focus on only a single ecosystem or taxonomic group, or fail to use appropriate statistical methods. We use likelihood and AIC to compare the fit of four of the most widely used models to data on over 16,000 communities from a diverse array of taxonomic groups and ecosystems. Across all datasets combined the log-series, Poisson lognormal, and negative binomial all yield similar overall fits to the data. Therefore, when correcting for differences in the number of parameters the log-series generally provides the best fit to data. Within individual datasets some other distributions performed nearly as well as the log-series even after correcting for the number of parameters. The Zipf distribution is generally a poor characterization of the SAD.https://peerj.com/articles/2823.pdfSpecies-abundance distributionInformaticsCommonnessRarityCitizen scienceAnimals |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Elita Baldridge David J. Harris Xiao Xiao Ethan P. White |
spellingShingle |
Elita Baldridge David J. Harris Xiao Xiao Ethan P. White An extensive comparison of species-abundance distribution models PeerJ Species-abundance distribution Informatics Commonness Rarity Citizen science Animals |
author_facet |
Elita Baldridge David J. Harris Xiao Xiao Ethan P. White |
author_sort |
Elita Baldridge |
title |
An extensive comparison of species-abundance distribution models |
title_short |
An extensive comparison of species-abundance distribution models |
title_full |
An extensive comparison of species-abundance distribution models |
title_fullStr |
An extensive comparison of species-abundance distribution models |
title_full_unstemmed |
An extensive comparison of species-abundance distribution models |
title_sort |
extensive comparison of species-abundance distribution models |
publisher |
PeerJ Inc. |
series |
PeerJ |
issn |
2167-8359 |
publishDate |
2016-12-01 |
description |
A number of different models have been proposed as descriptions of the species-abundance distribution (SAD). Most evaluations of these models use only one or two models, focus on only a single ecosystem or taxonomic group, or fail to use appropriate statistical methods. We use likelihood and AIC to compare the fit of four of the most widely used models to data on over 16,000 communities from a diverse array of taxonomic groups and ecosystems. Across all datasets combined the log-series, Poisson lognormal, and negative binomial all yield similar overall fits to the data. Therefore, when correcting for differences in the number of parameters the log-series generally provides the best fit to data. Within individual datasets some other distributions performed nearly as well as the log-series even after correcting for the number of parameters. The Zipf distribution is generally a poor characterization of the SAD. |
topic |
Species-abundance distribution Informatics Commonness Rarity Citizen science Animals |
url |
https://peerj.com/articles/2823.pdf |
work_keys_str_mv |
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