Global photosynthetic capacity is optimized to the environment

• Published in: Ecology Letters
• Main Authors: Smith, Nicholas G., Keenan, Trevor, Prentice, I. Colin, Wang, Han, Wright, Ian J., Niinemets, U., Crous, Kristine Y., Domingues, Tomas F., Guerrieri, Rossella, Ishida, F. Yoko, Weerasinghe, Lasantha
• Format: Article in Journal/Newspaper
• Language: English
• Published: Blackwell Publishing Ltd
• Subjects: Carbon cycle; Carboxylation; coordination; ecophysiology; electron transport; Jmax; light availability; nitrogen availability; temperature; Vcmax; Arctic; Canada; elk
• Online Access: http://hdl.handle.net/1885/186781; https://doi.org/10.1111/ele.13210; https://openresearch-repository.anu.edu.au/bitstream/1885/186781/5/01_Smith_Global_photosynthetic_capacity_2019.pdf.jpg

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. NGS and TFK were supported by the Laboratory Directed Research and Development (LDRD) fund under the auspices of DOE, BER Office of Science at Lawrence Berkeley National Laboratory. HW was supported by National Natural Science Foundation of China (31600388). VM was supported by The Fonds de recherche du Quebec – Nature et Technologies (FRQNT-2017-NC-198009) and Natural Sciences and Engineering Research Council of Canada (NSERC-Discovery-2016-05716). AR and SPS were supported by the Next-Generation Ecosystem Experiments (NGEE Arctic) project that is supported by the Office of Biological and Environmental Research in the Department of Energy, Office of Science, and through the United States Department of Energy contract No. DE-SC0012704 to Brookhaven National Laboratory. Contributions by PAT and ELK were supported by NASA grants NNX10AJ94G and NNX08AN31G, as well as USDA Hatch/McIntire-Stennis awards WIS01809 ...