On the Statistical Mechanics of Alien Species Distribution

Many species of plants are found in regions to which they are alien. Their global distributions are characterised by a family of exponential functions of the kind that arise in elementary statistical mechanics (an example in ecology is MacArthur’s broken stick). We show here that all these functions...

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Main Authors: Michael G. Bowler, Colleen K. Kelly
Format: Article
Language:English
Published: MDPI AG 2017-12-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/19/12/674
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spelling doaj-a4942e2110954cf8a45f2e855d793d1f2020-11-25T00:20:25ZengMDPI AGEntropy1099-43002017-12-01191267410.3390/e19120674e19120674On the Statistical Mechanics of Alien Species DistributionMichael G. Bowler0Colleen K. Kelly1Department of Physics, University of Oxford, Keble Road, Oxford OX1 3RH, UKDepartment of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UKMany species of plants are found in regions to which they are alien. Their global distributions are characterised by a family of exponential functions of the kind that arise in elementary statistical mechanics (an example in ecology is MacArthur’s broken stick). We show here that all these functions are quantitatively reproduced by a model containing a single parameter—some global resource partitioned at random on the two axes of species number and site number. A dynamical model generating this equilibrium is a two-fold stochastic process and suggests a curious and interesting biological interpretation in terms of niche structures fluctuating with time and productivity, with sites and species highly idiosyncratic. Idiosyncrasy implies that attempts to identify a priori those species likely to become naturalised are unlikely to be successful. Although this paper is primarily concerned with a particular problem in population biology, the two-fold stochastic process may be of more general interest.https://www.mdpi.com/1099-4300/19/12/674statistical mechanicsresource partitioningstochastic processespopulation dynamics
collection DOAJ
language English
format Article
sources DOAJ
author Michael G. Bowler
Colleen K. Kelly
spellingShingle Michael G. Bowler
Colleen K. Kelly
On the Statistical Mechanics of Alien Species Distribution
Entropy
statistical mechanics
resource partitioning
stochastic processes
population dynamics
author_facet Michael G. Bowler
Colleen K. Kelly
author_sort Michael G. Bowler
title On the Statistical Mechanics of Alien Species Distribution
title_short On the Statistical Mechanics of Alien Species Distribution
title_full On the Statistical Mechanics of Alien Species Distribution
title_fullStr On the Statistical Mechanics of Alien Species Distribution
title_full_unstemmed On the Statistical Mechanics of Alien Species Distribution
title_sort on the statistical mechanics of alien species distribution
publisher MDPI AG
series Entropy
issn 1099-4300
publishDate 2017-12-01
description Many species of plants are found in regions to which they are alien. Their global distributions are characterised by a family of exponential functions of the kind that arise in elementary statistical mechanics (an example in ecology is MacArthur’s broken stick). We show here that all these functions are quantitatively reproduced by a model containing a single parameter—some global resource partitioned at random on the two axes of species number and site number. A dynamical model generating this equilibrium is a two-fold stochastic process and suggests a curious and interesting biological interpretation in terms of niche structures fluctuating with time and productivity, with sites and species highly idiosyncratic. Idiosyncrasy implies that attempts to identify a priori those species likely to become naturalised are unlikely to be successful. Although this paper is primarily concerned with a particular problem in population biology, the two-fold stochastic process may be of more general interest.
topic statistical mechanics
resource partitioning
stochastic processes
population dynamics
url https://www.mdpi.com/1099-4300/19/12/674
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