Stomatal responses of terrestrial plants to global change

被引:0
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作者
Xingyun Liang
Defu Wang
Qing Ye
Jinmeng Zhang
Mengyun Liu
Hui Liu
Kailiang Yu
Yujie Wang
Enqing Hou
Buqing Zhong
Long Xu
Tong Lv
Shouzhang Peng
Haibo Lu
Pierre Sicard
Alessandro Anav
David S. Ellsworth
机构
[1] Chinese Academy of Sciences,Guangdong Provincial Key Laboratory of Applied Botany, South China Botanical Garden
[2] Gannan Normal University,College of Life Sciences
[3] Jiangsu Second Normal University,School of Geographical Sciences
[4] Guangdong Academy of Forestry,Guangdong Provincial Key Laboratory of Silviculture, Protection and Utilization
[5] Guangzhou,Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden
[6] Chinese Academy of Sciences,Department of Ecology & Evolutionary Biology
[7] Princeton University,High Meadows Environmental Institute
[8] Princeton University,Division of Geological and Planetary Sciences
[9] California Institute of Technology,State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau
[10] Pasadena,Department of Geography, Faculty of Arts and Sciences
[11] Northwest A&F University,ENEA, Climate Modeling Laboratory
[12] Beijing Normal University,Hawkesbury Institute for the Environment
[13] ARGANS Ltd,undefined
[14] CR Casaccia,undefined
[15] Western Sydney University,undefined
来源
Nature Communications | / 14卷
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摘要
Quantifying the stomatal responses of plants to global change factors is crucial for modeling terrestrial carbon and water cycles. Here we synthesize worldwide experimental data to show that stomatal conductance (gs) decreases with elevated carbon dioxide (CO2), warming, decreased precipitation, and tropospheric ozone pollution, but increases with increased precipitation and nitrogen (N) deposition. These responses vary with treatment magnitude, plant attributes (ambient gs, vegetation biomes, and plant functional types), and climate. All two-factor combinations (except warming + N deposition) significantly reduce gs, and their individual effects are commonly additive but tend to be antagonistic as the effect sizes increased. We further show that rising CO2 and warming would dominate the future change of plant gs across biomes. The results of our meta-analysis provide a foundation for understanding and predicting plant gs across biomes and guiding manipulative experiment designs in a real world where global change factors do not occur in isolation.
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