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  Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment

Kauwe, M. G. D., Medlyn, B. E., Walker, A. P., Zaehle, S., Asao, S., Guenet, B., et al. (2017). Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment. Global Change Biology, 23(9), 3623-3645. doi:10.1111/gcb.13643.

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 Urheber:
Kauwe, Martin G. De, Autor
Medlyn, Belinda E., Autor
Walker, Anthony P., Autor
Zaehle, Sönke1, 2, Autor           
Asao, Shinichi, Autor
Guenet, Bertrand, Autor
Harper, Anna B., Autor
Hickler, Thomas, Autor
Jain, Atul, Autor
Luo, Yiqi, Autor
Lu, Xingjie, Autor
Luus, Kristina3, Autor           
Parton, William J., Autor
Shu, Shijie, Autor
Wang, Ying-Ping, Autor
Werner, Christian, Autor
Xia, Jianyang, Autor
Pendall, Elise, Autor
Morgan, Jack A., Autor
Ryan, Edmund M., Autor
Carrillo, Yolima, AutorDijkstra, Feike A., AutorZelikova, Tamara J., AutorNorby, Richard J., Autor mehr..
Affiliations:
1Terrestrial Biosphere Modelling, Dr. Sönke Zähle, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1938309              
2Terrestrial Biosphere Modelling, Dr. Sönke Zähle, Department Biogeochemical Integration, Prof. Dr. Martin Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1497787              
3Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1688139              

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 Zusammenfassung: Multi-factor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date such models have only been tested against single-factor experiments. We applied 10 TBMs to the multi-factor Prairie Heating and CO2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multi-factor experiments can be used to constrain models, and to identify a road map for model improvement. We found models performed poorly in current ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m-2 yr-1). Comparison with data highlighted model failures particularly in respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against observations from single-factors experiments was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the N cycle models, N availability during the experiment.

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 Datum: 2017-01-152017-03-062017-08
 Publikationsstatus: Erschienen
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 Art der Begutachtung: -
 Identifikatoren: Anderer: BGC2596
DOI: 10.1111/gcb.13643
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Projektname : QUINCY
Grant ID : 647204
Förderprogramm : Horizon 2020 (H2020)
Förderorganisation : European Commission (EC)

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Titel: Global Change Biology
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: Oxford, UK : Blackwell Science
Seiten: - Band / Heft: 23 (9) Artikelnummer: - Start- / Endseite: 3623 - 3645 Identifikator: ISSN: 1354-1013
CoNE: https://pure.mpg.de/cone/journals/resource/954925618107