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The effects of spatial correlations and demographic stochasticity on population dynamics.

机译:空间相关性和人口统计随机性对人口动态的影响。

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摘要

Because of limited mobility and localized interactions, most organisms do not interact equally with all parts of their environment but instead with a limited neighborhood. The resulting spatial correlations affect population dynamics. The discreteness of organisms can also affect population dynamics. Because population size cannot change by less than one, and size-changing events such as births and deaths occur at distinct times, population dynamics are noisy. For large populations, this so-called “demographic stochasticity” is often ignorable, but when population size is small, either throughout the system or in a region, noise can have important consequences.; This dissertation explores the combined effects of spatial correlations and population discreteness. Chapter II discusses the limitations of many traditional physics techniques in analyzing ecological models. Chapters III and IV consider grid-based models. Every grid point can be vacant or occupied by an individual, and individuals interact according to simple, probabilistic rules. In chapter III, I develop approximate equations for the population mean and variance, including the effects of demographic stochasticity, by ignoring all but very short-range spatial correlations (a moment closure scheme). I apply this to a grid model and obtain expressions for population mean and variance. In chapter IV, I develop an empirical moment closure scheme based on observed spatial correlations. This leads to expressions for population mean and variance that are both simpler and more accurate, as well as to probability distributions for how long the population will take to reach a given, low level.; Subsequently, I turn to the effects of population discreteness on the spread of newly introduced species. In chapter V, I analyze a common class of one-dimensional, single-species invasion models and find three effects of population discreteness and demographic stochasticity on invasion speed. The result is that for very general conditions, the equation for mean population density predicts an invasion speed which is too fast. Studies of chemical waves suggest that the net result of particle discreteness and fluctuations is to introduce an effective concentration cutoff. Cutoffs work for ecological models only when per capita offspring numbers are low. I discuss the reasons for this in ch. VI.
机译:由于活动性和局部相互作用的限制,大多数生物不会与环境的所有部分平等地互动,而是与有限的邻居互动。产生的空间相关性影响种群动态。生物的离散性也会影响种群动态。由于人口数量的变化不能少于一,并且人口出生和死亡等规模变化事件在不同的时间发生,因此人口动态是嘈杂的。对于人口众多,这种所谓的“人口统计随机性”通常是可忽略的,但是当人口规模较小时,无论是在整个系统中还是在一个区域中,噪声都会产生重要的后果。本文探讨了空间相关性和种群离散性的综合作用。第二章讨论了许多传统物理技术在分析生态模型方面的局限性。第三章和第四章考虑了基于网格的模型。每个网格点都可以是空置的,也可以由个人占据,并且个人根据简单的概率规则进行交互。在第三章中,我通过忽略极短距离的空间相关性(矩闭合方案),为总体均值和方差(包括人口统计随机性的影响)开发了近似方程。我将其应用于网格模型并获得总体均值和方差的表达式。在第四章中,我基于观察到的空间相关性开发了经验矩闭合方案。这导致人口均值和方差的表达更加简单和准确,并且得出了人口达到给定的低水平所花费的时间的概率分布。随后,我将讨论种群离散性对新引进物种传播的影响。在第五章中,我分析了一类常见的一维单物种入侵模型,并发现了种群离散性和人口随机性对入侵速度的三种影响。结果是,在非常普遍的条件下,平均人口密度方程预测的入侵速度太快。化学波的研究表明,颗粒离散和波动的最终结果是引入了有效的浓度截止值。仅当人均后代数量较低时,临界值才可用于生态模型。我将在第一章中讨论其原因。 VI。

著录项

  • 作者

    Snyder, Robin Elizabeth.;

  • 作者单位

    University of California, Santa Barbara.;

  • 授予单位 University of California, Santa Barbara.;
  • 学科 Physics General.; Biology Ecology.
  • 学位 Ph.D.
  • 年度 2001
  • 页码 95 p.
  • 总页数 95
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 物理学;生态学(生物生态学);
  • 关键词

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