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Reconsideration of r/K Selection Theory Using Stochastic Control Theory and Nonlinear Structured Population Models
Despite the fact that density effects and individual differences in life history are considered to be important for evolution, these factors lead to several difficulties in understanding the evolution of life history, especially when population sizes reach the carrying capacity. r/K selection theory...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4919082/ https://www.ncbi.nlm.nih.gov/pubmed/27336169 http://dx.doi.org/10.1371/journal.pone.0157715 |
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author | Oizumi, Ryo Kuniya, Toshikazu Enatsu, Yoichi |
author_facet | Oizumi, Ryo Kuniya, Toshikazu Enatsu, Yoichi |
author_sort | Oizumi, Ryo |
collection | PubMed |
description | Despite the fact that density effects and individual differences in life history are considered to be important for evolution, these factors lead to several difficulties in understanding the evolution of life history, especially when population sizes reach the carrying capacity. r/K selection theory explains what types of life strategies evolve in the presence of density effects and individual differences. However, the relationship between the life schedules of individuals and population size is still unclear, even if the theory can classify life strategies appropriately. To address this issue, we propose a few equations on adaptive life strategies in r/K selection where density effects are absent or present. The equations detail not only the adaptive life history but also the population dynamics. Furthermore, the equations can incorporate temporal individual differences, which are referred to as internal stochasticity. Our framework reveals that maximizing density effects is an evolutionarily stable strategy related to the carrying capacity. A significant consequence of our analysis is that adaptive strategies in both selections maximize an identical function, providing both population growth rate and carrying capacity. We apply our method to an optimal foraging problem in a semelparous species model and demonstrate that the adaptive strategy yields a lower intrinsic growth rate as well as a lower basic reproductive number than those obtained with other strategies. This study proposes that the diversity of life strategies arises due to the effects of density and internal stochasticity. |
format | Online Article Text |
id | pubmed-4919082 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-49190822016-07-08 Reconsideration of r/K Selection Theory Using Stochastic Control Theory and Nonlinear Structured Population Models Oizumi, Ryo Kuniya, Toshikazu Enatsu, Yoichi PLoS One Research Article Despite the fact that density effects and individual differences in life history are considered to be important for evolution, these factors lead to several difficulties in understanding the evolution of life history, especially when population sizes reach the carrying capacity. r/K selection theory explains what types of life strategies evolve in the presence of density effects and individual differences. However, the relationship between the life schedules of individuals and population size is still unclear, even if the theory can classify life strategies appropriately. To address this issue, we propose a few equations on adaptive life strategies in r/K selection where density effects are absent or present. The equations detail not only the adaptive life history but also the population dynamics. Furthermore, the equations can incorporate temporal individual differences, which are referred to as internal stochasticity. Our framework reveals that maximizing density effects is an evolutionarily stable strategy related to the carrying capacity. A significant consequence of our analysis is that adaptive strategies in both selections maximize an identical function, providing both population growth rate and carrying capacity. We apply our method to an optimal foraging problem in a semelparous species model and demonstrate that the adaptive strategy yields a lower intrinsic growth rate as well as a lower basic reproductive number than those obtained with other strategies. This study proposes that the diversity of life strategies arises due to the effects of density and internal stochasticity. Public Library of Science 2016-06-23 /pmc/articles/PMC4919082/ /pubmed/27336169 http://dx.doi.org/10.1371/journal.pone.0157715 Text en © 2016 Oizumi et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Oizumi, Ryo Kuniya, Toshikazu Enatsu, Yoichi Reconsideration of r/K Selection Theory Using Stochastic Control Theory and Nonlinear Structured Population Models |
title | Reconsideration of r/K Selection Theory Using Stochastic Control Theory and Nonlinear Structured Population Models |
title_full | Reconsideration of r/K Selection Theory Using Stochastic Control Theory and Nonlinear Structured Population Models |
title_fullStr | Reconsideration of r/K Selection Theory Using Stochastic Control Theory and Nonlinear Structured Population Models |
title_full_unstemmed | Reconsideration of r/K Selection Theory Using Stochastic Control Theory and Nonlinear Structured Population Models |
title_short | Reconsideration of r/K Selection Theory Using Stochastic Control Theory and Nonlinear Structured Population Models |
title_sort | reconsideration of r/k selection theory using stochastic control theory and nonlinear structured population models |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4919082/ https://www.ncbi.nlm.nih.gov/pubmed/27336169 http://dx.doi.org/10.1371/journal.pone.0157715 |
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