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积分投影模型中的随机稳定种群增长:理论与应用

Stochastic stable population growth in integral projection models: theory and application.

作者信息

Ellner Stephen P, Rees Mark

机构信息

Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA.

出版信息

J Math Biol. 2007 Feb;54(2):227-56. doi: 10.1007/s00285-006-0044-8. Epub 2006 Nov 23.

Abstract

Stochastic matrix projection models are widely used to model age- or stage-structured populations with vital rates that fluctuate randomly over time. Practical applications of these models rest on qualitative properties such as the existence of a long term population growth rate, asymptotic log-normality of total population size, and weak ergodicity of population structure. We show here that these properties are shared by a general stochastic integral projection model, by using results in (Eveson in D. Phil. Thesis, University of Sussex, 1991, Eveson in Proc. Lond. Math. Soc. 70, 411-440, 1993) to extend the approach in (Lange and Holmes in J. Appl. Prob. 18, 325-344, 1981). Integral projection models allow individuals to be cross-classified by multiple attributes, either discrete or continuous, and allow the classification to change during the life cycle. These features are present in plant populations with size and age as important predictors of individual fate, populations with a persistent bank of dormant seeds or eggs, and animal species with complex life cycles. We also present a case-study based on a 6-year field study of the Illyrian thistle, Onopordum illyricum, to demonstrate how easily a stochastic integral model can be parameterized from field data and then applied using familiar matrix software and methods. Thistle demography is affected by multiple traits (size, age and a latent "quality" variable), which would be difficult to accommodate in a classical matrix model. We use the model to explore the evolution of size- and age-dependent flowering using an evolutionarily stable strategy (ESS) approach. We find close agreement between the observed flowering behavior and the predicted ESS from the stochastic model, whereas the ESS predicted from a deterministic version of the model is very different from observed flowering behavior. These results strongly suggest that the flowering strategy in O. illyricum is an adaptation to random between-year variation in vital rates.

摘要

随机矩阵投影模型被广泛用于对年龄或阶段结构的种群进行建模,其生命率随时间随机波动。这些模型的实际应用依赖于一些定性特性,如长期种群增长率的存在、总人口规模的渐近对数正态性以及种群结构的弱遍历性。我们在此表明,通过利用(伊夫森,《苏塞克斯大学博士论文》,1991年;伊夫森,《伦敦数学学会会报》70卷,411 - 440页,1993年)中的结果来扩展(兰格和霍姆斯,《应用概率杂志》18卷,325 - 344页,1981年)中的方法,这些特性为一般的随机积分投影模型所共有。积分投影模型允许个体根据多个属性进行交叉分类,这些属性可以是离散的或连续的,并且允许分类在生命周期中发生变化。这些特征存在于以大小和年龄作为个体命运重要预测指标的植物种群、具有休眠种子或卵的持久库的种群以及具有复杂生命周期的动物物种中。我们还基于对伊利里亚蓟(Onopordum illyricum)进行的为期6年的实地研究给出了一个案例研究,以展示如何轻松地从实地数据对随机积分模型进行参数化,然后使用熟悉的矩阵软件和方法进行应用。蓟的种群统计学受到多个特征(大小、年龄和一个潜在的“质量”变量)的影响,这在经典矩阵模型中很难处理。我们使用该模型通过进化稳定策略(ESS)方法来探索大小和年龄依赖性开花的进化。我们发现观察到的开花行为与随机模型预测的ESS之间有密切的一致性,而从该模型的确定性版本预测的ESS与观察到的开花行为非常不同。这些结果强烈表明,伊利里亚蓟的开花策略是对生命率年间随机变化的一种适应。

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