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Concepts and applications in functional diversity
Functional Ecology ( IF 4.6 ) Pub Date : 2021-07-16 , DOI: 10.1111/1365-2435.13882 Stefano Mammola 1, 2 , Carlos P. Carmona 3 , Thomas Guillerme 4 , Pedro Cardoso 1
中文翻译：
功能多样性中的概念和应用
更新日期：2021-09-07
Functional Ecology ( IF 4.6 ) Pub Date : 2021-07-16 , DOI: 10.1111/1365-2435.13882 Stefano Mammola 1, 2 , Carlos P. Carmona 3 , Thomas Guillerme 4 , Pedro Cardoso 1
Affiliation
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- The use of functional diversity analyses in ecology has grown exponentially over the past two decades, broadening our understanding of biological diversity and its change across space and time. Virtually all ecological sub-disciplines recognise the critical value of looking at species and communities from a functional perspective, and this has led to a proliferation of methods for estimating contrasting dimensions of functional diversity.
- Differences between these methods and their development generated terminological inconsistencies and confusion about the selection of the most appropriate approach for addressing any particular ecological question, hampering the potential for comparative studies, simulation exercises and meta-analyses.
- Two general mathematical frameworks for estimating functional diversity are prevailing: those based on dissimilarity matrices (e.g. Rao entropy, functional dendrograms) and those relying on multidimensional spaces, constructed as either convex hulls or probabilistic hypervolumes.
- We review these frameworks, discuss their strengths and weaknesses and provide an overview of the main R packages performing these calculations. In parallel, we propose a way for organising functional diversity metrics in a unified scheme to quantify the richness, divergence and regularity of species or individuals under each framework. This overview offers a roadmap for confidently approaching functional diversity analyses both theoretically and practically.
中文翻译：
功能多样性中的概念和应用
- 在过去的二十年中，生态学中功能多样性分析的使用呈指数增长，拓宽了我们对生物多样性及其跨时空变化的理解。几乎所有的生态子学科都认识到从功能角度观察物种和群落的关键价值，这导致了评估功能多样性对比维度的方法的激增。
- 这些方法及其发展之间的差异在选择最合适的方法来解决任何特定的生态问题方面产生了术语上的不一致和混乱，阻碍了比较研究、模拟练习和元分析的潜力。
- 用于估计函数多样性的两种通用数学框架盛行：基于相异矩阵（例如 Rao 熵、函数树状图）的框架和依赖多维空间的框架，构造为凸包或概率超体积。
- 我们回顾了这些框架，讨论了它们的优点和缺点，并概述了执行这些计算的主要 R 包。同时，我们提出了一种在统一方案中组织功能多样性指标的方法，以量化每个框架下物种或个体的丰富度、多样性和规律性。本概述为从理论上和实践上自信地进行功能多样性分析提供了路线图。
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