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  Global photosynthetic capacity is optimized to the environment

Smith, N. G., Keenan, T. F., Prentice, I. C., Wang, H., Wright, I. J., Niinemets, Ü., et al. (2019). Global photosynthetic capacity is optimized to the environment. Ecology Letters, 22(3), 506-517. doi:10.1111/ele.13210.

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 Creators:
Smith, Nicholas G., Author
Keenan, Trevor F., Author
Prentice, I. Colin, Author
Wang, Han, Author
Wright, Ian J., Author
Niinemets, Ülo, Author
Crous, Kristine Y., Author
Domingues, Tomas F., Author
Guerrieri, Rossella, Author
Ishida, F. Yoko, Author
Kattge, Jens1, Author           
Kruger, Eric L., Author
Maire, Vincent, Author
Rogers, Alistair, Author
Serbin, Shawn P., Author
Tarvainen, Lasse, Author
Togashi, Henrique F., Author
Townsend, Philip A., Author
Wang, Meng, Author
Weerasinghe, Lasantha K., Author
Zhou, Shuang‐Xi, Author more..
Affiliations:
1Interdepartmental Max Planck Fellow Group Functional Biogeography, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1938314              

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 Abstract: 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.

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 Dates: 2018-10-072018-11-072019-03
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: Other: BGC2978
DOI: 10.1111/ele.13210
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Title: Ecology Letters
Source Genre: Journal
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Publ. Info: Oxford, UK : Blackwell Science
Pages: - Volume / Issue: 22 (3) Sequence Number: - Start / End Page: 506 - 517 Identifier: ISSN: 1461-023X
CoNE: https://pure.mpg.de/cone/journals/resource/954925625294