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Using Plant Functional Traits to Explain Diversity–Productivity Relationships
BACKGROUND: The different hypotheses proposed to explain positive species richness–productivity relationships, i.e. selection effect and complementarity effect, imply that plant functional characteristics are at the core of a mechanistic understanding of biodiversity effects. METHODOLOGY/PRINCIPAL F...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3356333/ https://www.ncbi.nlm.nih.gov/pubmed/22623961 http://dx.doi.org/10.1371/journal.pone.0036760 |
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author | Roscher, Christiane Schumacher, Jens Gubsch, Marlén Lipowsky, Annett Weigelt, Alexandra Buchmann, Nina Schmid, Bernhard Schulze, Ernst-Detlef |
author_facet | Roscher, Christiane Schumacher, Jens Gubsch, Marlén Lipowsky, Annett Weigelt, Alexandra Buchmann, Nina Schmid, Bernhard Schulze, Ernst-Detlef |
author_sort | Roscher, Christiane |
collection | PubMed |
description | BACKGROUND: The different hypotheses proposed to explain positive species richness–productivity relationships, i.e. selection effect and complementarity effect, imply that plant functional characteristics are at the core of a mechanistic understanding of biodiversity effects. METHODOLOGY/PRINCIPAL FINDINGS: We used two community-wide measures of plant functional composition, (1) community-weighted means of trait values (CWM) and (2) functional trait diversity based on Rao’s quadratic diversity (FD(Q)) to predict biomass production and measures of biodiversity effects in experimental grasslands (Jena Experiment) with different species richness (2, 4, 8, 16 and 60) and different functional group number and composition (1 to 4; legumes, grasses, small herbs, tall herbs) four years after establishment. Functional trait composition had a larger predictive power for community biomass and measures of biodiversitity effects (40–82% of explained variation) than species richness per se (<1–13% of explained variation). CWM explained a larger amount of variation in community biomass (80%) and net biodiversity effects (70%) than FD(Q) (36 and 38% of explained variation respectively). FD(Q) explained similar proportions of variation in complementarity effects (24%, positive relationship) and selection effects (28%, negative relationship) as CWM (27% of explained variation for both complementarity and selection effects), but for all response variables the combination of CWM and FD(Q) led to significant model improvement compared to a separate consideration of different components of functional trait composition. Effects of FD(Q) were mainly attributable to diversity in nutrient acquisition and life-history strategies. The large spectrum of traits contributing to positive effects of CWM on biomass production and net biodiversity effects indicated that effects of dominant species were associated with different trait combinations. CONCLUSIONS/SIGNIFICANCE: Our results suggest that the identification of relevant traits and the relative impacts of functional identity of dominant species and functional diversity are essential for a mechanistic understanding of the role of plant diversity for ecosystem processes such as aboveground biomass production. |
format | Online Article Text |
id | pubmed-3356333 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-33563332012-05-23 Using Plant Functional Traits to Explain Diversity–Productivity Relationships Roscher, Christiane Schumacher, Jens Gubsch, Marlén Lipowsky, Annett Weigelt, Alexandra Buchmann, Nina Schmid, Bernhard Schulze, Ernst-Detlef PLoS One Research Article BACKGROUND: The different hypotheses proposed to explain positive species richness–productivity relationships, i.e. selection effect and complementarity effect, imply that plant functional characteristics are at the core of a mechanistic understanding of biodiversity effects. METHODOLOGY/PRINCIPAL FINDINGS: We used two community-wide measures of plant functional composition, (1) community-weighted means of trait values (CWM) and (2) functional trait diversity based on Rao’s quadratic diversity (FD(Q)) to predict biomass production and measures of biodiversity effects in experimental grasslands (Jena Experiment) with different species richness (2, 4, 8, 16 and 60) and different functional group number and composition (1 to 4; legumes, grasses, small herbs, tall herbs) four years after establishment. Functional trait composition had a larger predictive power for community biomass and measures of biodiversitity effects (40–82% of explained variation) than species richness per se (<1–13% of explained variation). CWM explained a larger amount of variation in community biomass (80%) and net biodiversity effects (70%) than FD(Q) (36 and 38% of explained variation respectively). FD(Q) explained similar proportions of variation in complementarity effects (24%, positive relationship) and selection effects (28%, negative relationship) as CWM (27% of explained variation for both complementarity and selection effects), but for all response variables the combination of CWM and FD(Q) led to significant model improvement compared to a separate consideration of different components of functional trait composition. Effects of FD(Q) were mainly attributable to diversity in nutrient acquisition and life-history strategies. The large spectrum of traits contributing to positive effects of CWM on biomass production and net biodiversity effects indicated that effects of dominant species were associated with different trait combinations. CONCLUSIONS/SIGNIFICANCE: Our results suggest that the identification of relevant traits and the relative impacts of functional identity of dominant species and functional diversity are essential for a mechanistic understanding of the role of plant diversity for ecosystem processes such as aboveground biomass production. Public Library of Science 2012-05-18 /pmc/articles/PMC3356333/ /pubmed/22623961 http://dx.doi.org/10.1371/journal.pone.0036760 Text en Roscher et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Roscher, Christiane Schumacher, Jens Gubsch, Marlén Lipowsky, Annett Weigelt, Alexandra Buchmann, Nina Schmid, Bernhard Schulze, Ernst-Detlef Using Plant Functional Traits to Explain Diversity–Productivity Relationships |
title | Using Plant Functional Traits to Explain Diversity–Productivity Relationships |
title_full | Using Plant Functional Traits to Explain Diversity–Productivity Relationships |
title_fullStr | Using Plant Functional Traits to Explain Diversity–Productivity Relationships |
title_full_unstemmed | Using Plant Functional Traits to Explain Diversity–Productivity Relationships |
title_short | Using Plant Functional Traits to Explain Diversity–Productivity Relationships |
title_sort | using plant functional traits to explain diversity–productivity relationships |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3356333/ https://www.ncbi.nlm.nih.gov/pubmed/22623961 http://dx.doi.org/10.1371/journal.pone.0036760 |
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