Literature DB >> 25817196

Effects of dispersal on total biomass in a patchy, heterogeneous system: Analysis and experiment.

Bo Zhang1, Xin Liu2, D L DeAngelis3, Wei-Ming Ni4, G Geoff Wang5.   

Abstract

An intriguing recent result from mathematics is that a population diffusing at an intermediate rate in an environment in which resources vary spatially will reach a higher total equilibrium biomass than the population in an environment in which the same total resources are distributed homogeneously. We extended the current mathematical theory to apply to logistic growth and also showed that the result applies to patchy systems with dispersal among patches, both for continuous and discrete time. This allowed us to make specific predictions, through simulations, concerning the biomass dynamics, which were verified by a laboratory experiment. The experiment was a study of biomass growth of duckweed (Lemna minor Linn.), where the resources (nutrients added to water) were distributed homogeneously among a discrete series of water-filled containers in one treatment, and distributed heterogeneously in another treatment. The experimental results showed that total biomass peaked at an intermediate, relatively low, diffusion rate, higher than the total carrying capacity of the system and agreeing with the simulation model. The implications of the experiment to dynamics of source, sink, and pseudo-sink dynamics are discussed.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Laboratory experiment; Mathematical theory; Simulation modeling; Spatial heterogeneity; Vegetation growth

Mesh:

Year:  2015        PMID: 25817196     DOI: 10.1016/j.mbs.2015.03.005

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  3 in total

1.  Dispersal and spatial heterogeneity: single species.

Authors:  Donald L DeAngelis; Wei-Ming Ni; Bo Zhang
Journal:  J Math Biol       Date:  2015-04-11       Impact factor: 2.259

2.  Dynamics of a consumer-resource reaction-diffusion model : Homogeneous versus heterogeneous environments.

Authors:  Xiaoqing He; King-Yeung Lam; Yuan Lou; Wei-Ming Ni
Journal:  J Math Biol       Date:  2019-01-02       Impact factor: 2.259

3.  Impact of State-Dependent Dispersal on Disease Prevalence.

Authors:  Daozhou Gao; Yuan Lou
Journal:  J Nonlinear Sci       Date:  2021-07-03       Impact factor: 3.621

  3 in total

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