Abundance-based approaches

J. Knape, Andreas Lindén
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Abstract

Across a wide range of different organisms, abundance data form one of the backbones for understanding the dynamics of populations. This type of data consists of measures of population size over time or space in the form of numbers of individuals, biomass, areal cover, or other measures. Abundance data contain no direct information about demographic processes but are available at larger scales or higher resolution in space and time than direct demographic data. This chapter introduces some of the basic statistical modeling strategies that can be used to learn about populations from abundance data in the absence of information about demographic details. These strategies include standard but flexible regression techniques, including mixed and additive models, time-series methods such as auto-regressive and state-space models, as well as simple population growth models derived from ecological theory.
Abundance-based方法
在各种不同的生物中,丰度数据是理解种群动态的主干之一。这种类型的数据包括以个体数、生物量、面积覆盖或其他措施的形式衡量随时间或空间变化的种群规模。丰度数据不包含关于人口过程的直接信息,但在空间和时间上比直接人口数据具有更大的尺度或更高的分辨率。本章介绍了一些基本的统计建模策略,这些策略可用于在缺乏人口统计细节信息的情况下从大量数据中了解人口。这些策略包括标准但灵活的回归技术,包括混合和加性模型,时间序列方法,如自回归和状态空间模型,以及从生态理论推导的简单人口增长模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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