Trait correlation network analysis identifies biomass allocation traits and stem specific length as hub traits in herbaceous perennial plants

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Standard

Trait correlation network analysis identifies biomass allocation traits and stem specific length as hub traits in herbaceous perennial plants. / Kleyer, Michael; Trinogga, Juliane; Cebrián-Piqueras, Miguel A. et al.
In: Journal of Ecology, Vol. 107, No. 2, 01.03.2019, p. 829-842.

Research output: Journal contributionsJournal articlesResearchpeer-review

Harvard

Kleyer, M, Trinogga, J, Cebrián-Piqueras, MA, Trenkamp, A, Fløjgaard, C, Ejrnæs, R, Bouma, TJ, Minden, V, Maier, M, Mantilla-Contreras, J, Albach, DC & Blasius, B 2019, 'Trait correlation network analysis identifies biomass allocation traits and stem specific length as hub traits in herbaceous perennial plants', Journal of Ecology, vol. 107, no. 2, pp. 829-842. https://doi.org/10.1111/1365-2745.13066

APA

Kleyer, M., Trinogga, J., Cebrián-Piqueras, M. A., Trenkamp, A., Fløjgaard, C., Ejrnæs, R., Bouma, T. J., Minden, V., Maier, M., Mantilla-Contreras, J., Albach, D. C., & Blasius, B. (2019). Trait correlation network analysis identifies biomass allocation traits and stem specific length as hub traits in herbaceous perennial plants. Journal of Ecology, 107(2), 829-842. https://doi.org/10.1111/1365-2745.13066

Vancouver

Kleyer M, Trinogga J, Cebrián-Piqueras MA, Trenkamp A, Fløjgaard C, Ejrnæs R et al. Trait correlation network analysis identifies biomass allocation traits and stem specific length as hub traits in herbaceous perennial plants. Journal of Ecology. 2019 Mar 1;107(2):829-842. doi: 10.1111/1365-2745.13066

Bibtex

@article{da38c86ca7dd4d2a9d1e6aadd8b234d7,
title = "Trait correlation network analysis identifies biomass allocation traits and stem specific length as hub traits in herbaceous perennial plants",
abstract = "Correlations among plant traits often reflect important trade-offs or allometric relationships in biological functions like carbon gain, support, water uptake, and reproduction that are associated with different plant organs. Whether trait correlations can be aggregated to “spectra” or “leading dimensions,” whether these dimensions are consistent across plant organs, spatial scale, and growth forms are still open questions. To illustrate the current state of knowledge, we constructed a network of published trait correlations associated with the “leaf economics spectrum,” “biomass allocation dimension,” “seed dimension,” and carbon and nitrogen concentrations. This literature-based network was compared to a network based on a dataset of 23 traits from 2,530 individuals of 126 plant species from 381 plots in Northwest Europe. The observed network comprised more significant correlations than the literature-based network. Network centrality measures showed that size traits such as the mass of leaf, stem, below-ground, and reproductive tissues and plant height were the most central traits in the network, confirming the importance of allometric relationships in herbaceous plants. Stem mass and stem-specific length were “hub” traits correlated with most traits. Environmental selection of hub traits may affect the whole phenotype. In contrast to the literature-based network, SLA and leaf N were of minor importance. Based on cluster analysis and subsequent PCAs of the resulting trait clusters, we found a “size” module, a “seed” module, two modules representing C and N concentrations in plant organs, and a “partitioning” module representing organ mass fractions. A module representing the plant economics spectrum did not emerge. Synthesis. Although we found support for several trait dimensions, the observed trait network deviated significantly from current knowledge, suggesting that previous studies have overlooked trait coordination at the whole-plant level. Furthermore, network analysis suggests that stem traits have a stronger regulatory role in herbaceous plants than leaf traits.",
keywords = "allometry, biomass allocation, leaf economics spectrum, network centrality, plant development and life-history traits, stoichiometry, trait dimensions",
author = "Michael Kleyer and Juliane Trinogga and Cebri{\'a}n-Piqueras, {Miguel A.} and Anastasia Trenkamp and Camilla Fl{\o}jgaard and Rasmus Ejrn{\ae}s and Bouma, {Tjeerd J.} and Vanessa Minden and Martin Maier and Jasmin Mantilla-Contreras and Albach, {Dirk C.} and Bernd Blasius",
note = "Funding Information: We thank Silke Eilers for contributing to the field work in Denmark, as well as Regine Kayser, Katrin Bahloul, Helga Hots, Natali KD?nitz, Daniela Mei{\ss}ner, and many student assistants for laboratory work. We also thank the Associate Editor and two anonymous reviewers for many helpful suggestions to improve earlier drafts of the manuscript. This project was part of the collaborative research project “Sustainable coastal land management: Trade-offs in ecosystem services” (COMTESS), supported by the German Federal Ministry of Education and Research (grant number 01LL0911). English language services provided by stels-ol.de. Publisher Copyright: {\textcopyright} 2018 The Authors. Journal of Ecology {\textcopyright} 2018 British Ecological Society",
year = "2019",
month = mar,
day = "1",
doi = "10.1111/1365-2745.13066",
language = "English",
volume = "107",
pages = "829--842",
journal = "Journal of Ecology",
issn = "0022-0477",
publisher = "Wiley-Blackwell Publishing Ltd.",
number = "2",

}

RIS

TY - JOUR

T1 - Trait correlation network analysis identifies biomass allocation traits and stem specific length as hub traits in herbaceous perennial plants

AU - Kleyer, Michael

AU - Trinogga, Juliane

AU - Cebrián-Piqueras, Miguel A.

AU - Trenkamp, Anastasia

AU - Fløjgaard, Camilla

AU - Ejrnæs, Rasmus

AU - Bouma, Tjeerd J.

AU - Minden, Vanessa

AU - Maier, Martin

AU - Mantilla-Contreras, Jasmin

AU - Albach, Dirk C.

AU - Blasius, Bernd

N1 - Funding Information: We thank Silke Eilers for contributing to the field work in Denmark, as well as Regine Kayser, Katrin Bahloul, Helga Hots, Natali KD?nitz, Daniela Meißner, and many student assistants for laboratory work. We also thank the Associate Editor and two anonymous reviewers for many helpful suggestions to improve earlier drafts of the manuscript. This project was part of the collaborative research project “Sustainable coastal land management: Trade-offs in ecosystem services” (COMTESS), supported by the German Federal Ministry of Education and Research (grant number 01LL0911). English language services provided by stels-ol.de. Publisher Copyright: © 2018 The Authors. Journal of Ecology © 2018 British Ecological Society

PY - 2019/3/1

Y1 - 2019/3/1

N2 - Correlations among plant traits often reflect important trade-offs or allometric relationships in biological functions like carbon gain, support, water uptake, and reproduction that are associated with different plant organs. Whether trait correlations can be aggregated to “spectra” or “leading dimensions,” whether these dimensions are consistent across plant organs, spatial scale, and growth forms are still open questions. To illustrate the current state of knowledge, we constructed a network of published trait correlations associated with the “leaf economics spectrum,” “biomass allocation dimension,” “seed dimension,” and carbon and nitrogen concentrations. This literature-based network was compared to a network based on a dataset of 23 traits from 2,530 individuals of 126 plant species from 381 plots in Northwest Europe. The observed network comprised more significant correlations than the literature-based network. Network centrality measures showed that size traits such as the mass of leaf, stem, below-ground, and reproductive tissues and plant height were the most central traits in the network, confirming the importance of allometric relationships in herbaceous plants. Stem mass and stem-specific length were “hub” traits correlated with most traits. Environmental selection of hub traits may affect the whole phenotype. In contrast to the literature-based network, SLA and leaf N were of minor importance. Based on cluster analysis and subsequent PCAs of the resulting trait clusters, we found a “size” module, a “seed” module, two modules representing C and N concentrations in plant organs, and a “partitioning” module representing organ mass fractions. A module representing the plant economics spectrum did not emerge. Synthesis. Although we found support for several trait dimensions, the observed trait network deviated significantly from current knowledge, suggesting that previous studies have overlooked trait coordination at the whole-plant level. Furthermore, network analysis suggests that stem traits have a stronger regulatory role in herbaceous plants than leaf traits.

AB - Correlations among plant traits often reflect important trade-offs or allometric relationships in biological functions like carbon gain, support, water uptake, and reproduction that are associated with different plant organs. Whether trait correlations can be aggregated to “spectra” or “leading dimensions,” whether these dimensions are consistent across plant organs, spatial scale, and growth forms are still open questions. To illustrate the current state of knowledge, we constructed a network of published trait correlations associated with the “leaf economics spectrum,” “biomass allocation dimension,” “seed dimension,” and carbon and nitrogen concentrations. This literature-based network was compared to a network based on a dataset of 23 traits from 2,530 individuals of 126 plant species from 381 plots in Northwest Europe. The observed network comprised more significant correlations than the literature-based network. Network centrality measures showed that size traits such as the mass of leaf, stem, below-ground, and reproductive tissues and plant height were the most central traits in the network, confirming the importance of allometric relationships in herbaceous plants. Stem mass and stem-specific length were “hub” traits correlated with most traits. Environmental selection of hub traits may affect the whole phenotype. In contrast to the literature-based network, SLA and leaf N were of minor importance. Based on cluster analysis and subsequent PCAs of the resulting trait clusters, we found a “size” module, a “seed” module, two modules representing C and N concentrations in plant organs, and a “partitioning” module representing organ mass fractions. A module representing the plant economics spectrum did not emerge. Synthesis. Although we found support for several trait dimensions, the observed trait network deviated significantly from current knowledge, suggesting that previous studies have overlooked trait coordination at the whole-plant level. Furthermore, network analysis suggests that stem traits have a stronger regulatory role in herbaceous plants than leaf traits.

KW - allometry

KW - biomass allocation

KW - leaf economics spectrum

KW - network centrality

KW - plant development and life-history traits

KW - stoichiometry

KW - trait dimensions

UR - http://www.scopus.com/inward/record.url?scp=85054075745&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/703d7083-20b4-357f-92f0-50327df7d9d7/

U2 - 10.1111/1365-2745.13066

DO - 10.1111/1365-2745.13066

M3 - Journal articles

AN - SCOPUS:85054075745

VL - 107

SP - 829

EP - 842

JO - Journal of Ecology

JF - Journal of Ecology

SN - 0022-0477

IS - 2

ER -

DOI

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