YangGouLiEtAl2021

Référence

Yang, Y., Gou, R., Li, W., Kassout, J., Wu, J., Wang, L., Peng, C., Lin, G. (2021) Leaf Trait Covariation and Its Controls: A Quantitative Data Analysis Along a Subtropical Elevation Gradient. Journal of Geophysical Research: Biogeosciences, 126(7). (Scopus )

Résumé

Elevation gradients are frequently treated as useful space-for-time substitutions for inferring trait variations in response to different environmental conditions. The independent variations in leaf traits in response to elevation are well understood, but far less is known about trait covariation and its controls. This limits our understanding of the principles and mechanisms of leaf trait covariation, especially along elevation gradients in subtropical forests. Here, we studied the covariation among seven functional traits, including leaf size (LS), leaf nitrogen per unit mass (Nmass), leaf nitrogen per unit area (Narea), leaf mass per area (LMA), leaf dry matter content (LDMC), leaf thickness (LT) and the leaf internal-to-ambient CO2 ratio (Ci:Ca, termed χ). Sampling was conducted on 41 species in a subtropical forest on Mount Huangshan, China, and the data were analyzed using multivariate analysis and variance partitioning procedures. We found that (a) The first three principal components captured 79% of the total leaf trait covariation, which was caused mainly by within site differences; (b) Nmass and LDMC were positively correlated with soil water content (SW) and negatively correlated with vapor pressure deficit (VPD), while χ showed negative relationships with elevation; and (c) 78% of the variation in the studied plant functional traits could be explained by climate, soil, and family controls in combination, while family distribution was the most important determining factor for trait covariation along the elevation gradient. Our findings provide relevant insights into plant adaptation to environmental gradients and present useful guidelines for ecosystem management and planning. © 2021. American Geophysical Union. All Rights Reserved.

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@ARTICLE { YangGouLiEtAl2021,
    AUTHOR = { Yang, Y. and Gou, R. and Li, W. and Kassout, J. and Wu, J. and Wang, L. and Peng, C. and Lin, G. },
    JOURNAL = { Journal of Geophysical Research: Biogeosciences },
    TITLE = { Leaf Trait Covariation and Its Controls: A Quantitative Data Analysis Along a Subtropical Elevation Gradient },
    YEAR = { 2021 },
    NOTE = { cited By 0 },
    NUMBER = { 7 },
    VOLUME = { 126 },
    ABSTRACT = { Elevation gradients are frequently treated as useful space-for-time substitutions for inferring trait variations in response to different environmental conditions. The independent variations in leaf traits in response to elevation are well understood, but far less is known about trait covariation and its controls. This limits our understanding of the principles and mechanisms of leaf trait covariation, especially along elevation gradients in subtropical forests. Here, we studied the covariation among seven functional traits, including leaf size (LS), leaf nitrogen per unit mass (Nmass), leaf nitrogen per unit area (Narea), leaf mass per area (LMA), leaf dry matter content (LDMC), leaf thickness (LT) and the leaf internal-to-ambient CO2 ratio (Ci:Ca, termed χ). Sampling was conducted on 41 species in a subtropical forest on Mount Huangshan, China, and the data were analyzed using multivariate analysis and variance partitioning procedures. We found that (a) The first three principal components captured 79% of the total leaf trait covariation, which was caused mainly by within site differences; (b) Nmass and LDMC were positively correlated with soil water content (SW) and negatively correlated with vapor pressure deficit (VPD), while χ showed negative relationships with elevation; and (c) 78% of the variation in the studied plant functional traits could be explained by climate, soil, and family controls in combination, while family distribution was the most important determining factor for trait covariation along the elevation gradient. Our findings provide relevant insights into plant adaptation to environmental gradients and present useful guidelines for ecosystem management and planning. © 2021. American Geophysical Union. All Rights Reserved. },
    AFFILIATION = { State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing, China; Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Tsinghua University, Beijing, China; Huangshan UNESCO Global Geopark Administrative Committee, Huangshan, Anhui, China; Laboratory of Applied Botany, BioAgrodiversity Team, Faculty of Sciences, Abdelmalek Essaadi University, Tetouan, Morocco; Department of Biological Sciences, Institute of Environmental Sciences, University of Quebec at Montreal, Montréal, QC, Canada; Institute of Ocean Engineering, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong, China },
    ART_NUMBER = { e2021JG006378 },
    AUTHOR_KEYWORDS = { elevation gradient; Mount Huangshan; multivariate analysis; plant functional traits },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1029/2021JG006378 },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111422699&doi=10.1029%2f2021JG006378&partnerID=40&md5=3ddb9a96e4543ddf693057f29075f02a },
}

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