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Zhang J, Ge J, Dayananda B, Li J. Effect of light intensities on the photosynthesis, growth and physiological performances of two maple species. FRONTIERS IN PLANT SCIENCE 2022; 13:999026. [PMID: 36311139 PMCID: PMC9597493 DOI: 10.3389/fpls.2022.999026] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 09/06/2022] [Indexed: 06/16/2023]
Abstract
Photoinhibition decreases photosynthetic capacity and can therefore affect the plant survival, growth, and distribution, but little is known about how it affects on kindred tree species. We conducted field experiments to measure the photosynthetic, growth and physiological performances of two maple species (Acer mono and A. pseudosieboldianum) seedlings at four light intensities (100%, 75%, 55%, and 20% of full light) and evaluated the adaptability of seedlings. We found that: (1) A. mono seedlings have larger light saturated photosynthetic rates (A max), the light saturation point (LSP), and lower light compensation point (LCP) than A. pseudosieboldianum seedlings, thus indicating that the former has a stronger light utilization ability. (2) A. mono seedlings under 75% light intensity and had higher seedling height (SH), basal stem diameter (BSD), leaf number (LN), leaf area per plant (LAPP) and total dry weight (TDW), while A. pseudosieboldianum seedling at 55% light intensity displayed greater growth advantages, which agreed with their response of light saturated photosynthetic rate. Morphological plasticity adjustments such as decreased root shoot ratio (RSR) and increased specific leaf area (SLA) showed how seedlings adapt to weak light environments. (3) 100% and 20% light intensities increased the malondialdehyde (MDA) content of two maple seedlings, indicating that very strong or very weak light could lead to the imbalance of reactive oxygen species (ROS) metabolism. The regulation of antioxidant enzyme activities such as superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT), as well as the content of osmoregulation substances such as free proline and soluble protein, are the main mechanisms of plant adaptation to light stress. Although both A. mono and A. pseudosieboldianum are highly shade tolerant, subtle differences in the photosynthetic, morphological and physiological traits underpinning their shade tolerance suggest A. pseudosieboldianum has the advantage to deal with the light threat. Future studies should focus on the expression level of photosynthesis-related genes and cell, to better understand the adaptation mechanism of plants to light variation which facilitates forest development, either natural or via silvicultural practices. This information expands our understanding of the light-regulating mechanism of trees, which contributes to develop management practices to support natural forest regeneration.
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Affiliation(s)
- Jinfeng Zhang
- Beijing Key Laboratory for Forest Resources and Ecosystem Processes, Beijing Forestry University, Beijing, China
| | - Jingru Ge
- Optoelectronic College, Beijing Institute of Technology, Beijing, China
| | - Buddhi Dayananda
- School of Agriculture and Food Sciences, The University of Queensland, Brisbane, QLD, Australia
| | - Junqing Li
- Beijing Key Laboratory for Forest Resources and Ecosystem Processes, Beijing Forestry University, Beijing, China
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Yan Z, Guo Z, Serbin SP, Song G, Zhao Y, Chen Y, Wu S, Wang J, Wang X, Li J, Wang B, Wu Y, Su Y, Wang H, Rogers A, Liu L, Wu J. Spectroscopy outperforms leaf trait relationships for predicting photosynthetic capacity across different forest types. THE NEW PHYTOLOGIST 2021; 232:134-147. [PMID: 34165791 DOI: 10.1111/nph.17579] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Accepted: 06/20/2021] [Indexed: 06/13/2023]
Abstract
Leaf trait relationships are widely used to predict ecosystem function in terrestrial biosphere models (TBMs), in which leaf maximum carboxylation capacity (Vc,max ), an important trait for modelling photosynthesis, can be inferred from other easier-to-measure traits. However, whether trait-Vc,max relationships are robust across different forest types remains unclear. Here we used measurements of leaf traits, including one morphological trait (leaf mass per area), three biochemical traits (leaf water content, area-based leaf nitrogen content, and leaf chlorophyll content), one physiological trait (Vc,max ), as well as leaf reflectance spectra, and explored their relationships within and across three contrasting forest types in China. We found weak and forest type-specific relationships between Vc,max and the four morphological and biochemical traits (R2 ≤ 0.15), indicated by significantly changing slopes and intercepts across forest types. By contrast, reflectance spectroscopy effectively collapsed the differences in the trait-Vc,max relationships across three forest biomes into a single robust model for Vc,max (R2 = 0.77), and also accurately estimated the four traits (R2 = 0.75-0.94). These findings challenge the traditional use of the empirical trait-Vc,max relationships in TBMs for estimating terrestrial plant photosynthesis, but also highlight spectroscopy as an efficient alternative for characterising Vc,max and multitrait variability, with critical insights into ecosystem modelling and functional trait ecology.
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Affiliation(s)
- Zhengbing Yan
- Division for Ecology and Biodiversity, School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Zhengfei Guo
- Division for Ecology and Biodiversity, School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Shawn P Serbin
- Environmental & Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, 11973, USA
| | - Guangqin Song
- Division for Ecology and Biodiversity, School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Yingyi Zhao
- Division for Ecology and Biodiversity, School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Yang Chen
- Division for Ecology and Biodiversity, School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Shengbiao Wu
- Division for Ecology and Biodiversity, School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Jing Wang
- Division for Ecology and Biodiversity, School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Xin Wang
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Xiangshan, Beijing, 100093, China
| | - Jing Li
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Xiangshan, Beijing, 100093, China
- University of Chinese Academy of Sciences, Yuquanlu, Beijing, 100049, China
| | - Bin Wang
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Xiangshan, Beijing, 100093, China
- University of Chinese Academy of Sciences, Yuquanlu, Beijing, 100049, China
| | - Yuntao Wu
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Xiangshan, Beijing, 100093, China
- University of Chinese Academy of Sciences, Yuquanlu, Beijing, 100049, China
| | - Yanjun Su
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Xiangshan, Beijing, 100093, China
- University of Chinese Academy of Sciences, Yuquanlu, Beijing, 100049, China
| | - Han Wang
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
- Joint Centre for Global Change Studies, Tsinghua University, Beijing, 100084, China
| | - Alistair Rogers
- Environmental & Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, 11973, USA
| | - Lingli Liu
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Xiangshan, Beijing, 100093, China
- University of Chinese Academy of Sciences, Yuquanlu, Beijing, 100049, China
| | - Jin Wu
- Division for Ecology and Biodiversity, School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong, China
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