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在随机环境中对有限总体的积分投影模型。

Integral projection models for finite populations in a stochastic environment.

机构信息

Centre for Conservation Biology, Department of Biology, Norwegian University of Science and Technology, N-7491 Trondheim, Norway.

出版信息

Ecology. 2011 May;92(5):1146-56. doi: 10.1890/10-0500.1.

Abstract

Continuous types of population structure occur when continuous variables such as body size or habitat quality affect the vital parameters of individuals. These structures can give rise to complex population dynamics and interact with environmental conditions. Here we present a model for continuously structured populations with finite size, including both demographic and environmental stochasticity in the dynamics. Using recent methods developed for discrete age-structured models we derive the demographic and environmental variance of the population growth as functions of a continuous state variable. These two parameters, together with the expected population growth rate, are used to define a one-dimensional diffusion approximation of the population dynamics. Thus, a substantial reduction in complexity is achieved as the dynamics of the complex structured model can be described by only three population parameters. We provide methods for numerical calculation of the model parameters and demonstrate the accuracy of the diffusion approximation by computer simulation of specific examples. The general modeling framework makes it possible to analyze and predict future dynamics and extinction risk of populations with various types of structure, and to explore consequences of changes in demography caused by, e.g., climate change or different management decisions. Our results are especially relevant for small populations that are often of conservation concern.

摘要

当连续变量(如体型或栖息地质量)影响个体的重要参数时,就会出现连续型的种群结构。这些结构可以产生复杂的种群动态,并与环境条件相互作用。在这里,我们提出了一个具有有限大小的连续结构种群模型,包括动态中的人口统计学和环境随机性。我们使用最近为离散年龄结构模型开发的方法,将种群增长的人口统计学和环境方差推导为连续状态变量的函数。这两个参数,连同预期的种群增长率,被用来定义种群动态的一维扩散近似。因此,由于复杂结构模型的动态可以用仅三个种群参数来描述,所以实现了复杂度的大幅降低。我们提供了用于模型参数数值计算的方法,并通过特定示例的计算机模拟证明了扩散近似的准确性。一般的建模框架使得分析和预测具有各种结构类型的种群的未来动态和灭绝风险成为可能,并探索由气候变化或不同管理决策等因素引起的人口统计学变化的后果。我们的结果对于经常受到保护关注的小种群尤其重要。

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