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Zhang Z, Wang X, Guo S, Li Z, He M, Zhang Y, Li G, Han X, Yang G. Divergent patterns and drivers of leaf functional traits of Robinia pseudoacacia and Pinus tabulaeformis plantations along a precipitation gradient in the Loess plateau, China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 348:119318. [PMID: 37857219 DOI: 10.1016/j.jenvman.2023.119318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 09/30/2023] [Accepted: 10/06/2023] [Indexed: 10/21/2023]
Abstract
Changes in precipitation patterns in arid and semi-arid regions can reshape plant functional traits and significantly affect ecosystem functions. However, the synchronous responses of leaf economical, anatomical, photosynthetic, and biochemical traits to precipitation changes and their driving factors have rarely been investigated, which hinders our understanding of plants' ecological adaptation strategies to drought tolerance in arid areas. Therefore, the leaf traits of two typical plantations (Robinia pseudoacacia, RP and Pinus tabulaeformis, PT) along the precipitation gradient in the Loess Plateau, including economical, anatomical, photosynthetic, and biochemical traits, were investigated in this study. The results show that the leaf photosynthetic traits of RP and PT increase along the precipitation gradient, whereas leaf biochemical traits decrease. The anatomical traits of PT decrease with increasing precipitation, whereas no significant variation was observed for RP. Random Forest analysis show that LNC, LDMC, Chl, and PRO are leaf traits that significantly vary with the precipitation gradient in both plantations. Correlation analysis reveals that the traits coordination of RP is better than that of PT. The LMG model was used to determine driving factors. The results suggest that MAP explains the variation of PT leaf traits better (30.38%-36.78%), whereas SCH and SPH contribute more to the variation of RP leaf traits (20.88%-41.76%). In addition, the piecewise Structural Equation Model shows that the climate and soil physical and chemical properties directly affect the selected leaf functional traits of RP, whereas only the soil chemical properties directly affect the selected leaf functional traits of PT. The results of this study contribute to the understanding of the ecological adaptation of plants to environmental gradients and highlight that correlations among leaf traits should be considered when predicting plant adaptation strategies under future global change scenarios.
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Affiliation(s)
- Zhenjiao Zhang
- College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, PR China; Shaanxi Engineering Research Center of Circular Agriculture, Yangling, 712100, Shaanxi, PR China
| | - Xing Wang
- College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, PR China; Shaanxi Engineering Research Center of Circular Agriculture, Yangling, 712100, Shaanxi, PR China
| | - Shujuan Guo
- A School of Agricultural Sciences, Zhengzhou University, Zhengzhou, 450001, Henan, PR China.
| | - Zhenxia Li
- College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, PR China; Shaanxi Engineering Research Center of Circular Agriculture, Yangling, 712100, Shaanxi, PR China
| | - Mengfan He
- College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, PR China; Shaanxi Engineering Research Center of Circular Agriculture, Yangling, 712100, Shaanxi, PR China
| | - Yunlong Zhang
- College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, PR China; Shaanxi Engineering Research Center of Circular Agriculture, Yangling, 712100, Shaanxi, PR China
| | - Guixing Li
- College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, PR China; Shaanxi Engineering Research Center of Circular Agriculture, Yangling, 712100, Shaanxi, PR China
| | - Xinhui Han
- College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, PR China; Shaanxi Engineering Research Center of Circular Agriculture, Yangling, 712100, Shaanxi, PR China.
| | - Gaihe Yang
- College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, PR China; Shaanxi Engineering Research Center of Circular Agriculture, Yangling, 712100, Shaanxi, PR China
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Zhang L, Liu X, Sun Z, Bu W, Bongers FJ, Song X, Yang J, Sun Z, Li Y, Li S, Cao M, Ma K, Swenson NG. Functional trait space and redundancy of plant communities decrease toward cold temperature at high altitudes in Southwest China. SCIENCE CHINA. LIFE SCIENCES 2023; 66:376-384. [PMID: 35876972 DOI: 10.1007/s11427-021-2135-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 05/31/2022] [Indexed: 12/01/2022]
Abstract
Plant communities in mountainous areas shift gradually as climatic conditions change with altitude. How trait structure in multivariate space adapts to these varying climates in natural forest stands is unclear. Studying the multivariate functional trait structure and redundancy of tree communities along altitude gradients is crucial to understanding how temperature change affects natural forest stands. In this study, the leaf area, specific leaf area, leaf carbon, nitrogen, and phosphorous content from 1,590 trees were collected and used to construct the functional trait space of 12 plant communities at altitudes ranging from 800 m to 3,800 m across three mountains. Hypervolume overlap was calculated to quantify species trait redundancy per community. First, hypervolumes of species exclusion and full species set were calculated, respectively. Second, the overlap between these two volumes was calculated to obtain hypervolume overlap. Results showed that the functional trait space significantly increased with mean annual temperature toward lower altitudes within and across three mountains, whereas species trait redundancy had different patterns between mountains. Thus, warming can widen functional trait space and alter the redundancy in plant communities. The inconsistent patterns of redundancy between mountains suggest that warming exerts varying influences on different ecosystems. Identification of climate-vulnerable ecosystems is important in the face of global warming.
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Affiliation(s)
- Lan Zhang
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Xiaojuan Liu
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.
| | - Zhenhua Sun
- Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, 666303, China
| | - Wensheng Bu
- Key Laboratory of State Forestry Administration on Forest Ecosystem Protection and Restoration of Poyang Lake Watershed, College of Forestry, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Franca J Bongers
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Xiaoyang Song
- Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, 666303, China
| | - Jie Yang
- Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, 666303, China
| | - Zhenkai Sun
- Key Laboratory of Tree Breeding and Cultivation, Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China
| | - Yin Li
- Fujian Provincial Key Laboratory of Resources and Environmental Monitoring and Sustainable Management and Utilization, Sanming University, Sanming, 365004, China
| | - Shan Li
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Min Cao
- Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, 666303, China
| | - Keping Ma
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.
| | - Nathan G Swenson
- Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, 46556, USA
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Shen S, Zhan C, Yang C, Fernie AR, Luo J. Metabolomics-centered mining of plant metabolic diversity and function: Past decade and future perspectives. MOLECULAR PLANT 2023; 16:43-63. [PMID: 36114669 DOI: 10.1016/j.molp.2022.09.007] [Citation(s) in RCA: 100] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 09/06/2022] [Accepted: 09/11/2022] [Indexed: 06/15/2023]
Abstract
Plants are natural experts in organic synthesis, being able to generate large numbers of specific metabolites with widely varying structures that help them adapt to variable survival challenges. Metabolomics is a research discipline that integrates the capabilities of several types of research including analytical chemistry, statistics, and biochemistry. Its ongoing development provides strategies for gaining a systematic understanding of quantitative changes in the levels of metabolites. Metabolomics is usually performed by targeting either a specific cell, a specific tissue, or the entire organism. Considerable advances in science and technology over the last three decades have propelled us into the era of multi-omics, in which metabolomics, despite at an earlier developmental stage than genomics, transcriptomics, and proteomics, offers the distinct advantage of studying the cellular entities that have the greatest influence on end phenotype. Here, we summarize the state of the art of metabolite detection and identification, and illustrate these techniques with four case study applications: (i) comparing metabolite composition within and between species, (ii) assessing spatio-temporal metabolic changes during plant development, (iii) mining characteristic metabolites of plants in different ecological environments and upon exposure to various stresses, and (iv) assessing the performance of metabolomics as a means of functional gene identification , metabolic pathway elucidation, and metabolomics-assisted breeding through analyzing plant populations with diverse genetic variations. In addition, we highlight the prominent contributions of joint analyses of plant metabolomics and other omics datasets, including those from genomics, transcriptomics, proteomics, epigenomics, phenomics, microbiomes, and ion-omics studies. Finally, we discuss future directions and challenges exploiting metabolomics-centered approaches in understanding plant metabolic diversity.
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Affiliation(s)
- Shuangqian Shen
- Sanya Nanfan Research Institute of Hainan University, Hainan Yazhou Bay Seed Laboratory, Sanya 572025, China; College of Tropical Crops, Hainan University, Haikou 570228, China
| | - Chuansong Zhan
- Sanya Nanfan Research Institute of Hainan University, Hainan Yazhou Bay Seed Laboratory, Sanya 572025, China; College of Tropical Crops, Hainan University, Haikou 570228, China
| | - Chenkun Yang
- Sanya Nanfan Research Institute of Hainan University, Hainan Yazhou Bay Seed Laboratory, Sanya 572025, China; College of Tropical Crops, Hainan University, Haikou 570228, China
| | - Alisdair R Fernie
- Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm 14476, Germany
| | - Jie Luo
- Sanya Nanfan Research Institute of Hainan University, Hainan Yazhou Bay Seed Laboratory, Sanya 572025, China; College of Tropical Crops, Hainan University, Haikou 570228, China.
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