Literature DB >> 26226230

Population dynamics and competitive outcome derive from resource allocation statistics: The governing influence of the distinguishability of individuals.

Yu J Zhang1, John Harte2.   

Abstract

Model predictions for species competition outcomes highly depend on the assumed form of the population growth function. In this paper we apply an alternative inferential method based on statistical mechanics, maximizing Boltzmann entropy, to predict resource-constrained population dynamics and coexistence. Within this framework, population dynamics and competition outcome can be determined without assuming any particular form of the population growth function. The dynamics of each species is determined by two parameters: the mean resource requirement θ (related to the mean metabolic rate) and individual distinguishability Dr (related to intra- compared to interspecific functional variation). Our theory clarifies the condition for the energetic equivalence rule (EER) to hold, and provide a statistical explanation for the importance of species functional variation in determining population dynamics and coexistence patterns.
Copyright © 2015 Elsevier Inc. All rights reserved.

Keywords:  Boltzmann entropy; Individual distinguishability; Population dynamics; Resource allocation; Species coexistence

Mesh:

Year:  2015        PMID: 26226230     DOI: 10.1016/j.tpb.2015.07.003

Source DB:  PubMed          Journal:  Theor Popul Biol        ISSN: 0040-5809            Impact factor:   1.570


  3 in total

1.  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

2.  Maximum Entropy Theory of Ecology: A Reply to Harte.

Authors:  Marco Favretti
Journal:  Entropy (Basel)       Date:  2018-04-24       Impact factor: 2.524

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

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

  3 in total

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