Concepts and applications in functional diversity
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 communitie...
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| Published in | Functional ecology Vol. 35; no. 9; pp. 1869 - 1885 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Wiley Subscription Services, Inc
01.09.2021
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| Online Access | Get full text |
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| Abstract | 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.
A free Plain Language Summary can be found within the Supporting Information of this article.
A free Plain Language Summary can be found within the Supporting Information of this article. |
|---|---|
| AbstractList | 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.
A free Plain Language Summary can be found within the Supporting Information of this article.
A free Plain Language Summary can be found within the Supporting Information of this article. 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. A free Plain Language Summary can be found within the Supporting Information of this article. 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. A free Plain Language Summary can be found within the Supporting Information of this article. |
| Author | Carmona, Carlos P. Guillerme, Thomas Cardoso, Pedro Mammola, Stefano |
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| ContentType | Journal Article |
| Copyright | 2021 The Authors. published by John Wiley & Sons Ltd on behalf of British Ecological Society 2021. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| Notes | Funding information S.M. is supported by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 882221. T.G. acknowledges funding by European Research Council Consolidator grant no. 615709 ToLERates and Royal Society University Research Fellowship UF120016 awarded to Gavin H. Thomas. C.P.C. was supported by the Estonian Ministry of Education and Research (PSG293) and the European Regional Development Fund (Centre of Excellence EcolChange). Sabrina Russo Handling Editor ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
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| SubjectTerms | alpha diversity beta diversity Biodiversity biological trait Comparative studies Convexity Divergence Entropy Estimation functional dendrogram functional dispersion functional diversity functional regularity functional richness Hulls hypervolume Mathematical analysis meta-analysis space and time Species richness |
| Title | Concepts and applications in functional diversity |
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