Terrestrial biosphere models underestimate photosynthetic capacity and CO2 assimilation in the Arctic
No claim to original US Government works. New Phytologist © 2017 New Phytologist Trust.
| Veröffentlicht in: | The New phytologist. - 1979. - 216(2017), 4 vom: 01. Dez., Seite 1090-1103 |
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| 1. Verfasser: | |
| Weitere Verfasser: | , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2017
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| Zugriff auf das übergeordnete Werk: | The New phytologist |
| Schlagworte: | Journal Article Rubisco earth system models maximum carboxylation capacity (Vc,max) maximum electron transport rate (Jmax) photosynthesis temperature response function tundra Carbon Dioxide 142M471B3J mehr... |
| Zusammenfassung: | No claim to original US Government works. New Phytologist © 2017 New Phytologist Trust. 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 (Vc,max.25 and Jmax.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 CO2 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 Vc,max and Jmax were 17% lower than commonly used values. When scaled to 25°C, Vc,max.25 and Jmax.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 CO2 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 |
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| Beschreibung: | Date Completed 31.07.2018 Date Revised 30.09.2020 published: Print-Electronic Citation Status MEDLINE |
| ISSN: | 1469-8137 |
| DOI: | 10.1111/nph.14740 |