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Published on: November 21, 2015
Global meta-analysis unravels mechanistic shifts in plant growth and physiological adaptability under nitrogen
Yuxiang Liang1, Qianqian Sheng1, Shizhu Shi2
1College of Landscape Architecture, Nanjing Forestry University, Nanjing, 210037, China; Co-Innovation Center for the Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China; Jin Pu Research Institute, Nanjing Forestry University, Nanjing, 210037, China; Research Center for Digital Innovation Design, Nanjing Forestry University, Nanjing, 210037, China.
Abstract:
Quantitatively elucidating plant responses to elevated nitrogen dioxide (eNO2) is essential for understanding global atmospheric nitrogen pollution and ecosystem nitrogen cycling, yet a comprehensive synthesis is still lacking. Here, we integrated data from 80 independent experiments worldwide and conducted a multivariate mixed-effects meta-analysis to evaluate the effects of eNO2 on 73 plant traits encompassing growth, physiology, and biochemistry. Overall, eNO2 significantly reduced plant growth performance and diminished environmental adaptability by disrupting water regulation, photosynthesis, mineral nutrient uptake, and hormone-mediated processes. Subgroup analyses based on the between-group heterogeneity (QB) statistic revealed that plant functional types were major determinants of response variability; specifically, clonal, herbaceous, deciduous, and C3 species exhibited greater sensitivity to eNO2. Linear and nonlinear dose-response analyses, including restricted cubic spline (RCS) models, further demonstrated that plant responses were jointly shaped by exposure concentration and duration, and that chronic low-level eNO2 could induce growth stimulation resembling hormone-like regulatory effects. Collectively, this study provides the comprehensive quantitative framework for understanding plant responses to eNO2, offering critical insights into the mechanisms underlying plant adaptation to atmospheric nitrogen pollution and informing the design of nitrogen-cycle manipulation experiments.
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