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Evaluation of 11 terrestrial carbon-nitrogen cycle models
 against observations from two temperate free-air CO2 enrichment studies

MPG-Autoren
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Zaehle,  Sönke
Terrestrial Biosphere Modelling & Data assimilation, Dr. S. Zähle, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;
Terrestrial Biosphere Modelling , Dr. Sönke Zähle, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Zitation

Zaehle, S., Medlyn, B. E., De Kauwe, M. G., Walker, A. P., Dietze, M. C., Hickler, T., et al. (2014). Evaluation of 11 terrestrial carbon-nitrogen cycle models
 against observations from two temperate free-air CO2 enrichment studies. New Phytologist, 202(3), 803-822. doi:10.1111/nph.12697.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0015-0D26-F
Zusammenfassung
We analysed the responses of 11 ecosystem models to elevated atmospheric [CO2] at two temperate forest ecosystems (Duke and ORNL Free-Air CO2 Enrichment (FACE) experiments) to test alternative representations of carbon-nitrogen cycle processes. We decomposed the model responses into component processes affecting the response to elevated [CO2] (eCO2) and confronted these with observations from the two FACE experiments. Most of the models reproduced the observed initial enhancement of NPP, but failed to predict the diverging long-term responses at the two sites, although many of them showed qualitative agreement with observed component processes. Models generally showed signs of progressive nitrogen limitation due to lower-than-observed plant nitrogen uptake. The degree of down-regulation depended on the simulated flexibility of stoichiometry, initial nitrogen availability, and the ecosystem’s capacity to retain nitrogen under eCO2. The diverging observations of the two FACE experiments are insufficient to fully constrain terrestrial responses to eCO2. Nonetheless, they indicate that improved representation of above-belowground interactions and better constraints on plant stoichiometry, are important for a predictive understanding of eCO2 effects. Given the importance of soil organic matter changes, improved accuracy in soil inventories to increase the signal to noise ratio are pivotal.