Journal
ECOLOGY LETTERS
Volume 22, Issue 3, Pages 506-517Publisher
WILEY
DOI: 10.1111/ele.13210
Keywords
Carbon cycle; Carboxylation; coordination; ecophysiology; electron transport; Jmax; light availability; nitrogen availability; temperature; V-cmax
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Funding
- Laboratory Directed Research and Development (LDRD) fund under the DOE, BER Office of Science at Lawrence Berkeley National Laboratory
- National Natural Science Foundation of China [31600388]
- The Fonds de recherche du Quebec - Nature et Technologies [FRQNT-2017-NC-198009]
- Natural Sciences and Engineering Research Council of Canada (NSERC) [2016-05716]
- Next-Generation Ecosystem Experiments (NGEE Arctic) project - Office of Biological and Environmental Research in the Department of Energy, Office of Science
- United States Department of Energy [DE-SC0012704]
- NASA [NNX10AJ94G, NNX08AN31G]
- USDA Hatch/McIntire-Stennis awards [WIS01809, WIS02010]
- Newton International fellowship [NF082365]
- MSCA fellowship [705432]
- NERC [NE/N012526/1] Funding Source: UKRI
- NASA [131028, NNX08AN31G, NNX10AJ94G, 97764] Funding Source: Federal RePORTER
- Royal Society [NF082365] Funding Source: Royal Society
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Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (V-cmax), 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 V-cmax 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 V-cmax dataset for C-3 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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