An empirical evaluation of four variants of a universal species–area relationship

The Maximum Entropy Theory of Ecology (METE) predicts a universal species–area relationship (SAR) that can be fully characterized using only the total abundance (N) and species richness (S) at a single spatial scale. This theory has shown promise for characterizing scale dependence in the SAR. Howev...

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Main Authors: Daniel J. McGlinn, Xiao Xiao, Ethan P. White
Format: Article
Language:English
Published: PeerJ Inc. 2013-11-01
Series:PeerJ
Subjects:
Online Access:https://peerj.com/articles/212.pdf
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spelling doaj-9209748c7f6d477caf3d224e9d446f292020-11-24T20:57:48ZengPeerJ Inc.PeerJ2167-83592013-11-011e21210.7717/peerj.212212An empirical evaluation of four variants of a universal species–area relationshipDaniel J. McGlinn0Xiao Xiao1Ethan P. White2Department of Biology and the Ecology Center, Utah State University, Logan, UT, USADepartment of Biology and the Ecology Center, Utah State University, Logan, UT, USADepartment of Biology and the Ecology Center, Utah State University, Logan, UT, USAThe Maximum Entropy Theory of Ecology (METE) predicts a universal species–area relationship (SAR) that can be fully characterized using only the total abundance (N) and species richness (S) at a single spatial scale. This theory has shown promise for characterizing scale dependence in the SAR. However, there are currently four different approaches to applying METE to predict the SAR and it is unclear which approach should be used due to a lack of empirical comparison. Specifically, METE can be applied recursively or non-recursively and can use either a theoretical or observed species-abundance distribution (SAD). We compared the four different combinations of approaches using empirical data from 16 datasets containing over 1000 species and 300,000 individual trees and herbs. In general, METE accurately downscaled the SAR (R2 > 0.94), but the recursive approach consistently under-predicted richness. METE’s accuracy did not depend strongly on using the observed or predicted SAD. This suggests that the best approach to scaling diversity using METE is to use a combination of non-recursive scaling and the theoretical abundance distribution, which allows predictions to be made across a broad range of spatial scales with only knowledge of the species richness and total abundance at a single scale.https://peerj.com/articles/212.pdfAbundanceBiodiversitySpecies richnessEntropyInformation theoryScaling
collection DOAJ
language English
format Article
sources DOAJ
author Daniel J. McGlinn
Xiao Xiao
Ethan P. White
spellingShingle Daniel J. McGlinn
Xiao Xiao
Ethan P. White
An empirical evaluation of four variants of a universal species–area relationship
PeerJ
Abundance
Biodiversity
Species richness
Entropy
Information theory
Scaling
author_facet Daniel J. McGlinn
Xiao Xiao
Ethan P. White
author_sort Daniel J. McGlinn
title An empirical evaluation of four variants of a universal species–area relationship
title_short An empirical evaluation of four variants of a universal species–area relationship
title_full An empirical evaluation of four variants of a universal species–area relationship
title_fullStr An empirical evaluation of four variants of a universal species–area relationship
title_full_unstemmed An empirical evaluation of four variants of a universal species–area relationship
title_sort empirical evaluation of four variants of a universal species–area relationship
publisher PeerJ Inc.
series PeerJ
issn 2167-8359
publishDate 2013-11-01
description The Maximum Entropy Theory of Ecology (METE) predicts a universal species–area relationship (SAR) that can be fully characterized using only the total abundance (N) and species richness (S) at a single spatial scale. This theory has shown promise for characterizing scale dependence in the SAR. However, there are currently four different approaches to applying METE to predict the SAR and it is unclear which approach should be used due to a lack of empirical comparison. Specifically, METE can be applied recursively or non-recursively and can use either a theoretical or observed species-abundance distribution (SAD). We compared the four different combinations of approaches using empirical data from 16 datasets containing over 1000 species and 300,000 individual trees and herbs. In general, METE accurately downscaled the SAR (R2 > 0.94), but the recursive approach consistently under-predicted richness. METE’s accuracy did not depend strongly on using the observed or predicted SAD. This suggests that the best approach to scaling diversity using METE is to use a combination of non-recursive scaling and the theoretical abundance distribution, which allows predictions to be made across a broad range of spatial scales with only knowledge of the species richness and total abundance at a single scale.
topic Abundance
Biodiversity
Species richness
Entropy
Information theory
Scaling
url https://peerj.com/articles/212.pdf
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