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Cited by 143Ecology and Vegetation Dynamics StudiesPlant Water Relations and Carbon DynamicsPlant responses to elevated CO2

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Robust leaf trait relationships across species under global environmental changes

Open access
Cui, Erqian, Weng, Ensheng, Yan, Enrong, Xia, Jianyang·2020·Nature Communications
DOI 10.1038/s41467-020-16839-9PMC PMC7293315
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Abstract

Recent studies show coordinated relationships between plant leaf traits and their capacity to predict ecosystem functions. However, how leaf traits will change within species and whether interspecific trait relationships will shift under future environmental changes both remain unclear. Here, we examine the bivariate correlations between leaf economic traits of 515 species in 210 experiments which mimic climate warming, drought, elevated CO 2 , and nitrogen deposition. We find divergent directions of changes in trait-pairs between species, and the directions mostly do not follow the interspecific trait relationships. However, the slopes in the logarithmic transformed interspecific trait relationships hold stable under environmental changes, while only their elevations vary. The elevation changes of trait relationship are mainly driven by asymmetrically interspecific responses contrary to the direction of the leaf economic spectrum. These findings suggest robust interspecific trait relationships under global changes, and call for linking within-species responses to interspecific coordination of plant traits.

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Fig. 1 Distribution of the global trait database and the hypotheses in this study. a Locations of the study sites in this dataset. The filled circles represent the distribution of field experiments and the open circles for the locations of environmentally controlled experiments. The inset shows the number of species for environmentally controlled and field experiments. Note that locations of the environmentally controlled experiments are determined by latitude and longitude of the experimental sites. b Hypotheses depicting possible effects of global environmental changes on log–log trait relationships (of the form logy=k×logx+b). Here, we assumed that the trait relationships remain constant (1), the scaling exponents of the trait relationships remain unchanged but the elevation vary (2), and/or the interspecific trait relationships vary (3) under global environmental changes. The arrows indicate the directions of trait plasticity.
Fig. 1 Distribution of the global trait database and the hypotheses in this study. a Locations of the study sites in this dataset. The filled circles represent the distribution of field experiments and the open circles for the locations of environmentally controlled experiments. The inset shows the number of species for environmentally controlled and field experiments. Note that locations of the environmentally controlled experiments are determined by latitude and longitude of the experimental sites. b Hypotheses depicting possible effects of global environmental changes on log–log trait relationships (of the form logy=k×logx+b). Here, we assumed that the trait relationships remain constant (1), the scaling exponents of the trait relationships remain unchanged but the elevation vary (2), and/or the interspecific trait relationships vary (3) under global environmental changes. The arrows indicate the directions of trait plasticity.CC BY · PubMed Central
Fig. 2 Percentage changes of leaf functional traits under global environmental factors. a Probability density of response ratios of leaf traits to warming, drought, eCO2, and nitrogen addition. b Effects of global environmental changes on leaf functional traits. Circles represent the global mean changes, and error bars are 95% credible intervals on the mean. The horizontal dashed line indicates 0 (no effect). The number of species under treatments of warming, drought, eCO2, and nitrogen addition are 44, 54, 143, and 124 for Am, 60, 74, 198, and 201 for Nm, and 86, 123, 208, and 171 for SLA (i.e., the numbers shown near the bars).
Fig. 2 Percentage changes of leaf functional traits under global environmental factors. a Probability density of response ratios of leaf traits to warming, drought, eCO2, and nitrogen addition. b Effects of global environmental changes on leaf functional traits. Circles represent the global mean changes, and error bars are 95% credible intervals on the mean. The horizontal dashed line indicates 0 (no effect). The number of species under treatments of warming, drought, eCO2, and nitrogen addition are 44, 54, 143, and 124 for Am, 60, 74, 198, and 201 for Nm, and 86, 123, 208, and 171 for SLA (i.e., the numbers shown near the bars).CC BY · PubMed Central
Fig. 3 Plasticity of species-level pairwise traits under global environmental changes. a–l Plasticity of species-level pairwise traits under global environmental changes (Supplementary Note 2). Each colored arrow represents the direction of one species. The bold black line represents the interspecific leaf trait relationship. The colored ellipses are 95% confidence level of the scatters. m Conceptual model depicting three possible directions of pairwise traits: follow the LES direction (red arrows); contrary to the LES direction with asymmetric response (black dashed arrows); contrary to the LES direction with symmetric response (black solid line). The black solid line represents the LES direction. The arrows represent the major directions of the pairwise traits.
Fig. 3 Plasticity of species-level pairwise traits under global environmental changes. a–l Plasticity of species-level pairwise traits under global environmental changes (Supplementary Note 2). Each colored arrow represents the direction of one species. The bold black line represents the interspecific leaf trait relationship. The colored ellipses are 95% confidence level of the scatters. m Conceptual model depicting three possible directions of pairwise traits: follow the LES direction (red arrows); contrary to the LES direction with asymmetric response (black dashed arrows); contrary to the LES direction with symmetric response (black solid line). The black solid line represents the LES direction. The arrows represent the major directions of the pairwise traits.CC BY · PubMed Central
Fig. 4 Robustness of leaf trait relationships under different global environmental changes. The panels show the effects of warming (a–c), drought (d–f), eCO2 (g–i) and nitrogen addition (j–l), respectively. The bold lines represent SMA regressions of leaf trait relationships. The ellipses show the 95% confidence level of the original scatter. The homogeneity among SMA slopes via a permutation test and for differences in SMA elevation via the SMA analog of standard ANCOVA. The statistics information is shown in Supplementary Table 3. The number of species under treatments of warming, drought, eCO2, and nitrogen addition are 42, 54, 137, and 118 for Am–SLA, 15, 26, 106, and 116 for Nm–SLA, and 35, 55, 174, and 146 for Nm–SLA (i.e., the numbers shown near the ellipses). The Significance of changes in slopes and elevations: NS: P > 0.05; *P < 0.05; **P < 0.01; ***P < 0.001.
Fig. 4 Robustness of leaf trait relationships under different global environmental changes. The panels show the effects of warming (a–c), drought (d–f), eCO2 (g–i) and nitrogen addition (j–l), respectively. The bold lines represent SMA regressions of leaf trait relationships. The ellipses show the 95% confidence level of the original scatter. The homogeneity among SMA slopes via a permutation test and for differences in SMA elevation via the SMA analog of standard ANCOVA. The statistics information is shown in Supplementary Table 3. The number of species under treatments of warming, drought, eCO2, and nitrogen addition are 42, 54, 137, and 118 for Am–SLA, 15, 26, 106, and 116 for Nm–SLA, and 35, 55, 174, and 146 for Nm–SLA (i.e., the numbers shown near the ellipses). The Significance of changes in slopes and elevations: NS: P > 0.05; *P < 0.05; **P < 0.01; ***P < 0.001.CC BY · PubMed Central
Fig. 5 Changes of elevations (b) for trait relationships under global environmental changes. The differences in SMA elevation via the SMA analog of standard ANCOVA. Significance: dashed borders: P > 0.05; *P < 0.05; **P < 0.01; ***P < 0.001.
Fig. 5 Changes of elevations (b) for trait relationships under global environmental changes. The differences in SMA elevation via the SMA analog of standard ANCOVA. Significance: dashed borders: P > 0.05; *P < 0.05; **P < 0.01; ***P < 0.001.CC BY · PubMed Central

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Metadata

Authors
Cui, E., Weng, E., Yan, E., & Xia, J.
Affiliations
  • State Key Laboratory of Estuarine and Coastal Research (CN)
  • Columbia University (US)
Corresponding author
Xia, Jianyang
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2020-06-12
Volume
11
Issue
1
Pages
2999-2999
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-020-16839-9
PMC
PMC7293315
OpenAlex
W3034255665
Cited by
143
References
69
Citations by year
2026: 18 · 2025: 29 · 2024: 33 · 2023: 24 · 2022: 27 · 2021: 10 · 2020: 2
FWCI
10.01
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Columbia Academic Commons (Columbia University)
Funders
National Natural Science Foundation of China (31722009, 41630528)
Topics
  • Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ecology and Vegetation Dynamics Studies
  • Physical Sciences › Environmental Science › Global and Planetary Change › Plant Water Relations and Carbon Dynamics
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant responses to elevated CO2
Keywords
leaf economic traits, leaf economics spectrum, global warming, drought, elevated CO2, nitrogen deposition, trait coordination, global change, plant functional traits
MeSH terms
Algorithms, Carbon Dioxide, Models, Biological, Nitrogen, Phenotype, Plants, Species Specificity, Ecosystem, Plant Leaves, Droughts, Climate Change, Global Warming

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