A comparative analysis of host-parasitoid models with density dependence preceding parasitism.

IF 1.8 4区 数学 Q3 ECOLOGY Journal of Biological Dynamics Pub Date : 2020-12-01 DOI:10.1080/17513758.2020.1783005
Kelsey Marcinko, Mark Kot
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引用次数: 4

Abstract

We present a systematic comparison and analysis of four discrete-time, host-parasitoid models. For each model, we specify that density-dependent effects occur prior to parasitism in the life cycle of the host. We compare density-dependent growth functions arising from the Beverton-Holt and Ricker maps, as well as parasitism functions assuming either a Poisson or negative binomial distribution for parasitoid attacks. We show that overcompensatory density-dependence leads to period-doubling bifurcations, which may be supercritical or subcritical. Stronger parasitism from the Poisson distribution leads to loss of stability of the coexistence equilibrium through a Neimark-Sacker bifurcation, resulting in population cycles. Our analytic results also revealed dynamics for one of our models that were previously undetected by authors who conducted a numerical investigation. Finally, we emphasize the importance of clearly presenting biological assumptions that are inherent to the structure of a discrete-time model in order to promote communication and broader understanding.

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寄主-拟寄主模式在寄生前密度依赖的比较分析。
我们提出了一个系统的比较和分析四个离散时间,寄主-寄生虫模型。对于每个模型,我们指定密度依赖效应发生在寄主的生命周期寄生之前。我们比较了由Beverton-Holt和Ricker图产生的密度依赖性生长函数,以及寄生性函数,假设寄生性攻击为泊松分布或负二项分布。我们表明,过度补偿密度依赖导致周期加倍分岔,这可能是超临界或亚临界。泊松分布的强寄生性导致共存平衡通过neimmark - sacker分岔失去稳定性,导致种群周期。我们的分析结果还揭示了我们的一个模型的动力学,这是以前没有被进行数值调查的作者发现的。最后,我们强调明确提出离散时间模型结构固有的生物学假设的重要性,以促进交流和更广泛的理解。
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来源期刊
Journal of Biological Dynamics
Journal of Biological Dynamics ECOLOGY-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
4.90
自引率
3.60%
发文量
28
审稿时长
33 weeks
期刊介绍: Journal of Biological Dynamics, an open access journal, publishes state of the art papers dealing with the analysis of dynamic models that arise from biological processes. The Journal focuses on dynamic phenomena at scales ranging from the level of individual organisms to that of populations, communities, and ecosystems in the fields of ecology and evolutionary biology, population dynamics, epidemiology, immunology, neuroscience, environmental science, and animal behavior. Papers in other areas are acceptable at the editors’ discretion. In addition to papers that analyze original mathematical models and develop new theories and analytic methods, the Journal welcomes papers that connect mathematical modeling and analysis to experimental and observational data. The Journal also publishes short notes, expository and review articles, book reviews and a section on open problems.
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