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Optimality principles explaining divergent responses of alpine vegetation to environmental change.
Zhu, Ziqi; Wang, Han; Harrison, Sandy P; Prentice, Iain Colin; Qiao, Shengchao; Tan, Shen.
Afiliación
  • Zhu Z; Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing, China.
  • Wang H; Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing, China.
  • Harrison SP; Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing, China.
  • Prentice IC; School of Archaeology, Geography and Environmental Sciences (SAGES), University of Reading, Reading, UK.
  • Qiao S; Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing, China.
  • Tan S; Georgina Mace Centre for the Living Planet, Department of Life Sciences, Imperial College London, Ascot, UK.
Glob Chang Biol ; 29(1): 126-142, 2023 01.
Article en En | MEDLINE | ID: mdl-36176241
ABSTRACT
Recent increases in vegetation greenness over much of the world reflect increasing CO2 globally and warming in cold areas. However, the strength of the response to both CO2 and warming in those areas appears to be declining for unclear reasons, contributing to large uncertainties in predicting how vegetation will respond to future global changes. Here, we investigated the changes of satellite-observed peak season absorbed photosynthetically active radiation (Fmax ) on the Tibetan Plateau between 1982 and 2016. Although climate trends are similar across the Plateau, we identified robust divergent responses (a greening of 0.31 ± 0.14% year-1 in drier regions and a browning of 0.12 ± 0.08% year-1 in wetter regions). Using an eco-evolutionary optimality (EEO) concept of plant acclimation/adaptation, we propose a parsimonious modelling framework that quantitatively explains these changes in terms of water and energy limitations. Our model captured the variations in Fmax with a correlation coefficient (r) of .76 and a root mean squared error of .12 and predicted the divergent trends of greening (0.32 ± 0.19% year-1 ) and browning (0.07 ± 0.06% year-1 ). We also predicted the observed reduced sensitivities of Fmax to precipitation and temperature. The model allows us to explain these changes Enhanced growing season cumulative radiation has opposite effects on water use and energy uptake. Increased precipitation has an overwhelmingly positive effect in drier regions, whereas warming reduces Fmax in wetter regions by increasing the cost of building and maintaining leaf area. Rising CO2 stimulates vegetation growth by enhancing water-use efficiency, but its effect on photosynthesis saturates. The large decrease in the sensitivity of vegetation to climate reflects a shift from water to energy limitation. Our study demonstrates the potential of EEO approaches to reveal the mechanisms underlying recent trends in vegetation greenness and provides further insight into the response of alpine ecosystems to ongoing climate change.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Dióxido de Carbono / Ecosistema Tipo de estudio: Prognostic_studies País/Región como asunto: Asia Idioma: En Revista: Glob Chang Biol Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Dióxido de Carbono / Ecosistema Tipo de estudio: Prognostic_studies País/Región como asunto: Asia Idioma: En Revista: Glob Chang Biol Año: 2023 Tipo del documento: Article País de afiliación: China
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