Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: McGlinn, Daniel J., Xiao, Xiao, White, Ethan P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3840416/
https://www.ncbi.nlm.nih.gov/pubmed/24282671
http://dx.doi.org/10.7717/peerj.212
_version_ 1782478511349432320
author McGlinn, Daniel J.
Xiao, Xiao
White, Ethan P.
author_facet McGlinn, Daniel J.
Xiao, Xiao
White, Ethan P.
author_sort McGlinn, Daniel J.
collection PubMed
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 (R(2) > 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.
format Online
Article
Text
id pubmed-3840416
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher PeerJ Inc.
record_format MEDLINE/PubMed
spelling pubmed-38404162013-11-26 An empirical evaluation of four variants of a universal species–area relationship McGlinn, Daniel J. Xiao, Xiao White, Ethan P. PeerJ Biodiversity 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 (R(2) > 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. PeerJ Inc. 2013-11-21 /pmc/articles/PMC3840416/ /pubmed/24282671 http://dx.doi.org/10.7717/peerj.212 Text en © 2013 McGlinn et al. http://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Biodiversity
McGlinn, Daniel J.
Xiao, Xiao
White, Ethan P.
An empirical evaluation of four variants of a universal species–area relationship
title 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_short 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
topic Biodiversity
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3840416/
https://www.ncbi.nlm.nih.gov/pubmed/24282671
http://dx.doi.org/10.7717/peerj.212
work_keys_str_mv AT mcglinndanielj anempiricalevaluationoffourvariantsofauniversalspeciesarearelationship
AT xiaoxiao anempiricalevaluationoffourvariantsofauniversalspeciesarearelationship
AT whiteethanp anempiricalevaluationoffourvariantsofauniversalspeciesarearelationship
AT mcglinndanielj empiricalevaluationoffourvariantsofauniversalspeciesarearelationship
AT xiaoxiao empiricalevaluationoffourvariantsofauniversalspeciesarearelationship
AT whiteethanp empiricalevaluationoffourvariantsofauniversalspeciesarearelationship