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A functional approach to diversity profiles

机译:多样性概况的一种实用方法

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Diversity plays a central role in ecological theory and its conservation and management are important issues for the wellbeing and stability of ecosystems. The aim of this work is to provide a reliable theoretical framework for performing statistical analysis on ecological diversity by means of the joint use of diversity profiles and functional data analysis. We point out that ecological diversity is a multivariate concept as it is a function of the relative abundances of species in a biological community. For this, several researchers have suggested using parametric families of indices of diversity for obtaining more information from the data. Patil and Taillie introduced the concept of intrinsic diversity ordering which can be determined by using the diversity profile. It may be noted that the diversity profile is a non-negative and convex curve which consists of a sequence of measurements as a function of a given parameter. Thus, diversity profiles can be explained through a process that is described in a functional setting. Recent developments in environmental studies have focused on the opportunity to evaluate community diversity changes over space and/or correlation of diversity with environmental characteristics. For this, we develop an innovative analysis of diversity based on a functional data approach. Whereas conventional statistical methods process data as a sequence of individual observations, functional data analysis is designed to process a collection of functions or curves. Moreover, unconstrained models may lead to negative and/or non-convex estimates for the diversity profiles. To overcome this problem, a transformation is proposed which can be constrained to be non-negative and convex. We focus on some applications showing how functional data analysis provides an alternative way of understanding biological diversity and its interaction with natural and/or human factors.
机译:多样性在生态学理论中起着核心作用,其保护和管理是生态系统福祉和稳定的重要问题。这项工作的目的是通过联合使用多样性概况和功能数据分析,为进行生态多样性统计分析提供可靠的理论框架。我们指出,生态多样性是一个多元概念,因为它是生物群落中物种相对丰富度的函数。为此,一些研究人员建议使用参数化的多样性指数族从数据中获取更多信息。 Patil和Taillie引入了内在多样性排序的概念,该概念可以通过使用多样性配置文件来确定。可以注意到,分集曲线是非负的和凸的曲线,其由一系列测量作为给定参数的函数组成。因此,可以通过功能设置中描述的过程来解释多样性概况。环境研究的最新发展集中在评估社区在空间上的多样性变化和/或多样性与环境特征的相关性的机会上。为此,我们基于功能数据方法开发了一种创新的多样性分析。传统的统计方法将数据作为一系列单独的观察处理,而功能数据分析则设计为处理功能或曲线的集合。此外,不受约束的模型可能会导致分集剖面的负和/或非凸估计。为了克服这个问题,提出了一种变换,该变换可以被约束为非负的和凸的。我们关注于一些应用,这些应用显示了功能数据分析如何提供一种替代的方式来理解生物多样性及其与自然和/或人为因素的相互作用。

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