Global photosynthetic capacity is optimized to the environment

Smith, Nicholas G., Keenan, Trevor F., Prentice, I. Colin, Wang, Han, Wright, Ian J., Niinemets, Ülo, Crous, Kristine Y., Domingues, Tomas F., Guerrieri, Rossella, Ishida, F. Yoko, Kattge, Jens, Kruger, Eric L., Maire, Vincent, Rogers, Alistair, Serbin, Shawn P., Tarvainen, Lasse, Togashi, Henrique F., Townsend, Philip A., Wang, Meng, Weerasinghe, Lasantha K., and Zhou, Shuang-Xi (2019) Global photosynthetic capacity is optimized to the environment. Ecology Letters, 22 (3). pp. 506-517.

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Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (Vcmax), to simulate carbon assimilation and typically rely on empirical estimates, including an assumed dependence on leaf nitrogen determined from soil fertility. In contrast, new theory, based on biochemical coordination and co‐optimization of carboxylation and water costs for photosynthesis, suggests that optimal Vcmax can be predicted from climate alone, irrespective of soil fertility. Here, we develop this theory and find it captures 64% of observed variability in a global, field‐measured Vcmax dataset for C3 plants. Soil fertility indices explained substantially less variation (32%). These results indicate that environmentally regulated biophysical constraints and light availability are the first‐order drivers of global photosynthetic capacity. Through acclimation and adaptation, plants efficiently utilize resources at the leaf level, thus maximizing potential resource use for growth and reproduction. Our theory offers a robust strategy for dynamically predicting photosynthetic capacity in ESMs.

Item ID: 57162
Item Type: Article (Research - C1)
ISSN: 1461-0248
Keywords: carbon cycle, carboxylation, coordination, ecophysiology, electron transport, Jmax, light availability, nitrogen availability, temperature, V-cmax
Copyright Information: © 2019 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Funders: United States Department of Energy (US-DE), Fonds de recherche du Québec - Nature et Technologies (UQ-NT), National Natural Science Foundation of China (NNSFC), Natural Sciences and Engineering Research Council of Canada (NSERC), National Aeronautics and Space Administration (NASA), United States Department of Agriculture (USDA), Newton International, Marie Skłodowska-Curie Actions (MSCA)
Projects and Grants: US-DE contract No. DE‐SC0012704, UQ-NT Grant Number FRQNT‐2017‐NC‐198009, NNSFC 31600388, NSERC‐Discovery‐2016‐05716, NASA grant NNX10AJ94G, NASA grant NNX08AN31G, USDA Hatch/McIntire‐Stennis award WIS01809, USDA Hatch/McIntire‐Stennis award WIS02010, Newton International Fellowship n. NF082365, MSCA fellowship n. 705432
Date Deposited: 20 Feb 2019 07:38
FoR Codes: 41 ENVIRONMENTAL SCIENCES > 4101 Climate change impacts and adaptation > 410102 Ecological impacts of climate change and ecological adaptation @ 100%
SEO Codes: 96 ENVIRONMENT > 9603 Climate and Climate Change > 960305 Ecosystem Adaptation to Climate Change @ 100%
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