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Context-Dependency in Relationships Between Herbaceous Plant Leaf Traits and Abiotic Factors  ( SCI-EXPANDED收录)   被引量:7

文献类型:期刊文献

英文题名:Context-Dependency in Relationships Between Herbaceous Plant Leaf Traits and Abiotic Factors

作者:Zhang, Zhenchao[1,2] Sun, Jian[2] Liu, Miao[3] Shang, Hua[4] Wang, Jinniu[5] Wang, Jinsong[6] Zhou, Huakun[7] Li, Yong[8] Wang, Yi[2] Chen, Wanjie[9]

第一作者:Zhang, Zhenchao

通信作者:Sun, J[1]

机构:[1]Qingdao Agr Univ, Coll Grassland Sci, Key Lab Natl Forestry & Grassland Adm Grassland R, Qingdao, Peoples R China;[2]Chinese Acad Sci, Inst Tibetan Plateau Res, State Key Lab Tibetan Plateau Earth Syst Resource, Beijing, Peoples R China;[3]China Agr Univ, Coll Grassland Sci & Technol, Beijing, Peoples R China;[4]Rutgers State Univ, Dept Ecol Evolut & Nat Resources, New Brunswick, NJ USA;[5]Chinese Acad Sci, Chengdu Inst Biol, Chengdu, Peoples R China;[6]Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modelling, Beijing, Peoples R China;[7]Chinese Acad Sci, Northwest Inst Plateau Biol, Key Lab Restorat Ecol Cold Reg Qinghai, Xining, Peoples R China;[8]Chinese Acad Forestry, Inst Wetland Res, Beijing Key Lab Wetland Serv & Restorat, Beijing, Peoples R China;[9]Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing, Peoples R China

年份:2022

卷号:13

外文期刊名:FRONTIERS IN PLANT SCIENCE

收录:;Scopus(收录号:2-s2.0-85128383014);WOS:【SCI-EXPANDED(收录号:WOS:000807664300001)】;

基金:This work was financially supported by the National Science Foundation of China (Grant No. 41871040), the Second Tibetan Plateau Scientific Expedition and Research (Grant No. 2019QZKK0405), the Open Project of the Qinghai Provincial Key Laboratory of Restoration Ecology in Cold Area (2020-KF-05), the China Postdoctoral Science Foundation (2021M702682), the Agricultural Research System of China (CARS-34), and the First Class Grassland Science Discipline Programme in Shandong Province of China.

语种:英文

外文关键词:herbaceous plant; leaf trait; growth strategy; abiotic filtering; environmental stress; climatic region

摘要:Leaf traits are important indicators of plants' adaptive strategy to environmental changes. It is an established fact that leaf traits are jointly regulated by climatic and edaphic factors besides genetic factors. However, the relative importance of these abiotic forces in determining the general patterns of herbaceous plant leaf traits across different climatic regions in China is far from clear. We collected 1,653 observations of 542 species of herbaceous plant leaf traits including leaf mass per area, leaf nitrogen, and leaf phosphorus from 316 sampling sites across four climatic regions. We found that the leaf mass per area in the arid region was apparently larger than the others, whereas the smallest mass-based leaf nitrogen and mass-based leaf phosphorus were found in the humid region. Increased growing season temperature and evapotranspiration consistently promoted a conservative growth strategy indicated by higher relative benefit of leaf mass per area, especially in the arid region. Solar radiation in growing season promoted an acquisitive growth strategy indicated by higher relative benefits of mass-based leaf nitrogen and phosphorus in the humid region, but opposite patterns were found in the arid region and semi-humid region. Of all the soil nutrients including soil organic matter, total nitrogen, total phosphorus, and available nitrogen, soil available nitrogen was the strongest predictor of relative benefits of leaf traits associated with a nutrient acquisitive strategy, except in the nutrient-rich semi-humid region. There was a relatively larger number of abiotic factors contributing to relative benefits of leaf traits in the arid and humid regions. We concluded that plant functionality could respond divergently to the same factor facing different habitat conditions. Moreover, the relative benefits of leaf traits tended to be more vulnerable to abiotic filtering in more stressful conditions. Our findings have important implications for understanding the context-dependency of plant functionality to environmental filtering and further improving the predictability of plant dynamics under global change.

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