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  Sensitivity of community-level trait–environment relationships to data representativeness: A test for functional biogeography

Borgy, B., Violle, C., Choler, P., Garnier, E., Kattge, J., Loranger, J., et al. (2017). Sensitivity of community-level trait–environment relationships to data representativeness: A test for functional biogeography. Global Ecology and Biogeography, 26(6), 729-739. doi:10.1111/geb.12573.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-002D-47AA-F Version Permalink: https://hdl.handle.net/11858/00-001M-0000-002D-56FC-D
Genre: Journal Article

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 Creators:
Borgy, Benjamin, Author
Violle, Cyrille, Author
Choler, Philippe, Author
Garnier, Eric, Author
Kattge, Jens1, Author           
Loranger, Jessy, Author
Amiaud, Bernard, Author
Cellier, Pierre, Author
Debarros, Guilhem, Author
Denelle, Pierre, Author
Diquelou, Sylvain, Author
Gachet, Sophie, Author
Jolivet, Claudy, Author
Lavorel, Sandra, Author
Lemauviel-Lavenant, Servane, Author
Mikolajczak, Alexis, Author
Munoz, François, Author
Olivier, Jean, Author
Viovy, Nicolas, Author
Affiliations:
1Interdepartmental Max Planck Fellow Group Functional Biogeography, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1938314              

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 Abstract: Aim: The characterization of trait–environment relationships over broad-scale gradients is a critical goal for ecology and biogeography. This implies the merging of plot and trait databases to assess community-level trait-based statistics. Potential shortcomings and limitations of this approach are that: (i) species traits are not measured where the community is sampled and (ii) the availability of trait data varies considerably across species and plots. Here we address the effect of trait data representativeness [the sampling effort per species and per plot] on the accuracy of (i) species-level and (ii) community-level trait estimates and (iii) the consequences for the shape and strength of trait–environment relationships across communities. Innovation: We combined information existing in databases of vegetation plots and plant traits to estimate community-weighted means [CWMs] of four key traits [specific leaf area, plant height, seed mass and leaf nitrogen content per dry mass] in permanent grasslands at a country-wide scale. We propose a generic approach for systematic sensitivity analyses based on random subsampling and data reduction to address the representativeness of incomplete and heterogeneous trait information when exploring trait–environment relationships across communities. Main conclusions: The accuracy of the CWMs was little affected by the number of individual trait values per species [NIV] but strongly affected by the cover proportion of species with available trait values [PCover]. A PCover above 80% was required for all four traits studied to obtain an estimation bias below 5%. Our approach therefore provides more conservative criteria than previously proposed. Restrictive criteria on both NIV and PCover primarily excluded communities in harsh environments, and such reduction of the sampled gradient weakened trait–environment relationships. These findings advocate systematic measurement campaigns in natural environments to increase species coverage in global trait databases, with

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 Dates: 2016-02-102017-03-202017-05
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: Other: BGC2637
DOI: 10.1111/geb.12573
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Title: Global Ecology and Biogeography
Source Genre: Journal
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Publ. Info: Oxford, U.K. : Blackwell Science
Pages: - Volume / Issue: 26 (6) Sequence Number: - Start / End Page: 729 - 739 Identifier: ISSN: 1466-822X
CoNE: https://pure.mpg.de/cone/journals/resource/954925579097