Stabilizing spatially-structured populations through adaptive Limiter Control.

Stabilizing the dynamics of complex, non-linear systems is a major concern across several scientific disciplines including ecology and conservation biology. Unfortunately, most methods proposed to reduce the fluctuations in chaotic systems are not applicable to real, biological populations. This is...

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Main Authors: Pratha Sah, Sutirth Dey
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4143321?pdf=render
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spelling doaj-6fad2fbfea314dceb440fdac90ee057d2020-11-25T01:45:46ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0198e10586110.1371/journal.pone.0105861Stabilizing spatially-structured populations through adaptive Limiter Control.Pratha SahSutirth DeyStabilizing the dynamics of complex, non-linear systems is a major concern across several scientific disciplines including ecology and conservation biology. Unfortunately, most methods proposed to reduce the fluctuations in chaotic systems are not applicable to real, biological populations. This is because such methods typically require detailed knowledge of system specific parameters and the ability to manipulate them in real time; conditions often not met by most real populations. Moreover, real populations are often noisy and extinction-prone, which can sometimes render such methods ineffective. Here, we investigate a control strategy, which works by perturbing the population size, and is robust to reasonable amounts of noise and extinction probability. This strategy, called the Adaptive Limiter Control (ALC), has been previously shown to increase constancy and persistence of laboratory populations and metapopulations of Drosophila melanogaster. Here, we present a detailed numerical investigation of the effects of ALC on the fluctuations and persistence of metapopulations. We show that at high migration rates, application of ALC does not require a priori information about the population growth rates. We also show that ALC can stabilize metapopulations even when applied to as low as one-tenth of the total number of subpopulations. Moreover, ALC is effective even when the subpopulations have high extinction rates: conditions under which another control algorithm had previously failed to attain stability. Importantly, ALC not only reduces the fluctuation in metapopulation sizes, but also the global extinction probability. Finally, the method is robust to moderate levels of noise in the dynamics and the carrying capacity of the environment. These results, coupled with our earlier empirical findings, establish ALC to be a strong candidate for stabilizing real biological metapopulations.http://europepmc.org/articles/PMC4143321?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Pratha Sah
Sutirth Dey
spellingShingle Pratha Sah
Sutirth Dey
Stabilizing spatially-structured populations through adaptive Limiter Control.
PLoS ONE
author_facet Pratha Sah
Sutirth Dey
author_sort Pratha Sah
title Stabilizing spatially-structured populations through adaptive Limiter Control.
title_short Stabilizing spatially-structured populations through adaptive Limiter Control.
title_full Stabilizing spatially-structured populations through adaptive Limiter Control.
title_fullStr Stabilizing spatially-structured populations through adaptive Limiter Control.
title_full_unstemmed Stabilizing spatially-structured populations through adaptive Limiter Control.
title_sort stabilizing spatially-structured populations through adaptive limiter control.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2014-01-01
description Stabilizing the dynamics of complex, non-linear systems is a major concern across several scientific disciplines including ecology and conservation biology. Unfortunately, most methods proposed to reduce the fluctuations in chaotic systems are not applicable to real, biological populations. This is because such methods typically require detailed knowledge of system specific parameters and the ability to manipulate them in real time; conditions often not met by most real populations. Moreover, real populations are often noisy and extinction-prone, which can sometimes render such methods ineffective. Here, we investigate a control strategy, which works by perturbing the population size, and is robust to reasonable amounts of noise and extinction probability. This strategy, called the Adaptive Limiter Control (ALC), has been previously shown to increase constancy and persistence of laboratory populations and metapopulations of Drosophila melanogaster. Here, we present a detailed numerical investigation of the effects of ALC on the fluctuations and persistence of metapopulations. We show that at high migration rates, application of ALC does not require a priori information about the population growth rates. We also show that ALC can stabilize metapopulations even when applied to as low as one-tenth of the total number of subpopulations. Moreover, ALC is effective even when the subpopulations have high extinction rates: conditions under which another control algorithm had previously failed to attain stability. Importantly, ALC not only reduces the fluctuation in metapopulation sizes, but also the global extinction probability. Finally, the method is robust to moderate levels of noise in the dynamics and the carrying capacity of the environment. These results, coupled with our earlier empirical findings, establish ALC to be a strong candidate for stabilizing real biological metapopulations.
url http://europepmc.org/articles/PMC4143321?pdf=render
work_keys_str_mv AT prathasah stabilizingspatiallystructuredpopulationsthroughadaptivelimitercontrol
AT sutirthdey stabilizingspatiallystructuredpopulationsthroughadaptivelimitercontrol
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