Terrestrial biosphere models underestimate photosynthetic capacity and CO 2 assimilation in the Arctic

• Published in: New Phytologist
• Main Authors: Rogers, Alistair, Serbin, Shawn P., Ely, Kim S., Sloan, Victoria L., Wullschleger, Stan D.
• Other Authors: U.S. Department of Energy
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2017
• Subjects: Arctic; Barrow; Tundra; Alaska
• Online Access: http://dx.doi.org/10.1111/nph.14740; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fnph.14740; https://onlinelibrary.wiley.com/doi/pdf/10.1111/nph.14740; https://onlinelibrary.wiley.com/doi/full-xml/10.1111/nph.14740; https://nph.onlinelibrary.wiley.com/doi/am-pdf/10.1111/nph.14740; https://nph.onlinelibrary.wiley.com/doi/pdf/10.1111/nph.14740

Summary Terrestrial biosphere models (TBMs) are highly sensitive to model representation of photosynthesis, in particular the parameters maximum carboxylation rate and maximum electron transport rate at 25°C ( V c,max.25 and J max.25 , respectively). Many TBMs do not include representation of Arctic plants, and those that do rely on understanding and parameterization from temperate species. We measured photosynthetic CO 2 response curves and leaf nitrogen (N) content in species representing the dominant vascular plant functional types found on the coastal tundra near Barrow, Alaska. The activation energies associated with the temperature response functions of V c,max and J max were 17% lower than commonly used values. When scaled to 25°C, V c,max.25 and J max.25 were two‐ to five‐fold higher than the values used to parameterize current TBMs. This high photosynthetic capacity was attributable to a high leaf N content and the high fraction of N invested in Rubisco. Leaf‐level modeling demonstrated that current parameterization of TBMs resulted in a two‐fold underestimation of the capacity for leaf‐level CO 2 assimilation in Arctic vegetation. This study highlights the poor representation of Arctic photosynthesis in TBMs, and provides the critical data necessary to improve our ability to project the response of the Arctic to global environmental change.