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离散时间和连续时间消费者-资源模型之间稳定机制的比较方法。

A comparative approach to stabilizing mechanisms between discrete- and continuous-time consumer-resource models.

机构信息

Department of Electrical and Computer Engineering, Department of Biomedical Engineering, Department of Mathematical Sciences, Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE, United States of America.

出版信息

PLoS One. 2022 Apr 12;17(4):e0265825. doi: 10.1371/journal.pone.0265825. eCollection 2022.

DOI:10.1371/journal.pone.0265825
PMID:35413067
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9004756/
Abstract

There is rich literature on using continuous-time and discrete-time models for studying population dynamics of consumer-resource interactions. A key focus of this contribution is to systematically compare between the two modeling formalisms the stabilizing/destabilizing impacts of diverse ecological processes that result in a density-dependent consumer attack rate. Inspired by the Nicholson-Bailey/Lotka-Volterra models in discrete-time/continuous-time, respectively, we consider host-parasitoid interactions with an arbitrary parasitoid attack rate that is a function of both the host/parasitoid population densities. Our analysis shows that a Type II functional response is stabilizing in both modeling frameworks only when combined with other mechanisms, such as mutual interference between parasitoids. A Type III functional response is by itself stabilizing, but the extent of attack-rate acceleration needed is much higher in the discrete-time framework, and its stability regime expands with increasing host reproduction. Finally, our results show that while mutual parasitoid interference can stabilize population dynamics, cooperation between parasitoids to handle hosts is destabilizing in both frameworks. In summary, our comparative analysis systematically characterizes diverse ecological processes driving stable population dynamics in discrete-time and continuous-time consumer-resource models.

摘要

关于使用连续时间和离散时间模型来研究消费者-资源相互作用的种群动态,已有丰富的文献。本研究的一个重点是系统地比较这两种建模形式,研究不同的生态过程对消费者攻击率的密度依赖性的稳定/失稳影响。受离散时间/连续时间中的 Nicholson-Bailey/Lotka-Volterra 模型的启发,我们考虑了具有任意寄生攻击率的宿主-寄生生物相互作用,该攻击率是宿主/寄生生物种群密度的函数。我们的分析表明,只有当与其他机制(例如寄生生物之间的相互干扰)结合时,II 型功能反应在两种建模框架中才是稳定的。III 型功能反应本身是稳定的,但在离散时间框架中需要更高的攻击率加速程度,并且其稳定性范围随着宿主繁殖的增加而扩大。最后,我们的结果表明,尽管寄生生物之间的相互干扰可以稳定种群动态,但在两种框架中,寄生生物之间合作处理宿主是不稳定的。总之,我们的比较分析系统地描述了离散时间和连续时间消费者-资源模型中驱动稳定种群动态的各种生态过程。

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引用本文的文献

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本文引用的文献

1
Attack by a common parasitoid stabilizes population dynamics of multi-host communities.常见寄生蜂的攻击稳定了多宿主群落的种群动态。
J Theor Biol. 2021 Dec 21;531:110897. doi: 10.1016/j.jtbi.2021.110897. Epub 2021 Sep 8.
2
Stochasticity in host-parasitoid models informs mechanisms regulating population dynamics.宿主-寄生蜂模型中的随机性为调节种群动态的机制提供了信息。
Sci Rep. 2021 Aug 18;11(1):16749. doi: 10.1038/s41598-021-96212-y.
3
Stochastic dynamics of predator-prey interactions.捕食者-被捕食者相互作用的随机动力学。
PLoS One. 2021 Aug 12;16(8):e0255880. doi: 10.1371/journal.pone.0255880. eCollection 2021.
4
Global redistribution and local migration in semi-discrete host-parasitoid population dynamic models.半离散宿主-寄生蜂种群动态模型中的全球再分布与局部迁移
Math Biosci. 2020 Sep;327:108409. doi: 10.1016/j.mbs.2020.108409. Epub 2020 Jun 29.
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Linear functional response by two pupal Drosophila parasitoids foraging within single or multiple patch environments.两种果蝇蛹寄生蜂在单一或多个斑块环境中觅食时的线性功能反应。
PLoS One. 2017 Aug 22;12(8):e0183525. doi: 10.1371/journal.pone.0183525. eCollection 2017.
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Functional Response of Eretmocerus delhiensis on Trialeurodes vaporariorum by Parasitism and Host Feeding.德里浆角蚜小蜂对温室粉虱的寄生和取食寄主功能反应
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The effects of host-feeding on stability of discrete-time host-parasitoid population dynamic models.寄主取食对离散时间寄主-寄生蜂种群动态模型稳定性的影响。
Math Biosci. 2016 Feb;272:54-63. doi: 10.1016/j.mbs.2015.11.011. Epub 2015 Dec 11.
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Mutually beneficial host exploitation and ultra-biased sex ratios in quasisocial parasitoids.准社会性寄生蜂中互利的宿主利用与极端偏斜的性别比例
Nat Commun. 2014 Sep 12;5:4942. doi: 10.1038/ncomms5942.
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Heterogeneity in host-parasitoid interactions: 'Aggregation of risk' and the 'CV(2) > 1 Rule'.宿主-寄生蜂相互作用的异质性:“风险聚集”和“CV(2) > 1 法则”。
Trends Ecol Evol. 1993 Nov;8(11):400-5. doi: 10.1016/0169-5347(93)90041-M.