Literature DB >> 25821878

A strong test of the maximum entropy theory of ecology.

Xiao Xiao1, Daniel J McGlinn, Ethan P White.   

Abstract

The maximum entropy theory of ecology (METE) is a unified theory of biodiversity that predicts a large number of macroecological patterns using information on only species richness, total abundance, and total metabolic rate of the community. We evaluated four major predictions of METE simultaneously at an unprecedented scale using data from 60 globally distributed forest communities including more than 300,000 individuals and nearly 2,000 species.METE successfully captured 96% and 89% of the variation in the rank distribution of species abundance and individual size but performed poorly when characterizing the size-density relationship and intraspecific distribution of individual size. Specifically, METE predicted a negative correlation between size and species abundance, which is weak in natural communities. By evaluating multiple predictions with large quantities of data, our study not only identifies a mismatch between abundance and body size in METE but also demonstrates the importance of conducting strong tests of ecological theories.

Mesh:

Year:  2015        PMID: 25821878     DOI: 10.1086/679576

Source DB:  PubMed          Journal:  Am Nat        ISSN: 0003-0147            Impact factor:   3.926


  8 in total

1.  Habitat suitability model with maximum entropy approach for European roe deer (Capreolus capreolus) in the Black Sea Region.

Authors:  Ozkan Evcin; Omer Kucuk; Emre Akturk
Journal:  Environ Monit Assess       Date:  2019-10-24       Impact factor: 2.513

Review 2.  Information theory: A foundation for complexity science.

Authors:  Amos Golan; John Harte
Journal:  Proc Natl Acad Sci U S A       Date:  2022-07-27       Impact factor: 12.779

3.  An extensive comparison of species-abundance distribution models.

Authors:  Elita Baldridge; David J Harris; Xiao Xiao; Ethan P White
Journal:  PeerJ       Date:  2016-12-22       Impact factor: 2.984

4.  Modeling the spatial and temporal dynamics of riparian vegetation induced by river flow fluctuation.

Authors:  Xiaoguang You; Jingling Liu
Journal:  Ecol Evol       Date:  2018-03-05       Impact factor: 2.912

5.  Energetic equivalence underpins the size structure of tree and phytoplankton communities.

Authors:  Daniel M Perkins; Andrea Perna; Rita Adrian; Pedro Cermeño; Ursula Gaedke; Maria Huete-Ortega; Ethan P White; Gabriel Yvon-Durocher
Journal:  Nat Commun       Date:  2019-01-16       Impact factor: 14.919

6.  Derivations of the Core Functions of the Maximum Entropy Theory of Ecology.

Authors:  Alexander B Brummer; Erica A Newman
Journal:  Entropy (Basel)       Date:  2019-07-21       Impact factor: 2.524

7.  Remarks on the Maximum Entropy Principle with Application to the Maximum Entropy Theory of Ecology.

Authors:  Marco Favretti
Journal:  Entropy (Basel)       Date:  2017-12-27       Impact factor: 2.524

8.  Maximum Entropy and Theory Construction: A Reply to Favretti.

Authors:  John Harte
Journal:  Entropy (Basel)       Date:  2018-04-14       Impact factor: 2.524

  8 in total

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