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  • DeKauweGCB_submittedversion_Nov2016

    Rights statement: This is the peer reviewed version of the following article: De Kauwe, M. G., Medlyn, B. E., Walker, A. P., Zaehle, S., Asao, S., Guenet, B., Harper, A. B., Hickler, T., Jain, A. K., Luo, Y., Lu, X., Luus, K., Parton, W. J., Shu, S., Wang, Y.-P., Werner, C., Xia, J., Pendall, E., Morgan, J. A., Ryan, E. M., Carrillo, Y., Dijkstra, F. A., Zelikova, T. J. and Norby, R. J. (2017), Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment. Glob Change Biol, 23: 3623–3645. doi:10.1111/gcb.13643 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/GCB.13643/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

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

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Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment. / De Kauwe, Martin; Medlyn, Belinda; Walker, Anthony; Zaehle, Sonke; Asao, Shinichi; Guenet, Bertrand; Harper, Anna; Hickler, Thomas; Jain, Atul; Luo, Yiqi; Lu, Chris; Luus, Kristina; Parton, William; Shu, Shijie; Wang, Ying-Ping; Werner, Christian; Xia, Jianyang; Pendall, Elise; Morgan, Jack; Ryan, Edmund; Carrillo, Yolima; Dijkstra, Feike; Norby, Richard.

In: Global Change Biology, Vol. 23, No. 9, 09.2017, p. 3623-3645.

Research output: Contribution to journalJournal articlepeer-review

Harvard

De Kauwe, M, Medlyn, B, Walker, A, Zaehle, S, Asao, S, Guenet, B, Harper, A, Hickler, T, Jain, A, Luo, Y, Lu, C, Luus, K, Parton, W, Shu, S, Wang, Y-P, Werner, C, Xia, J, Pendall, E, Morgan, J, Ryan, E, Carrillo, Y, Dijkstra, F & Norby, R 2017, 'Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment', Global Change Biology, vol. 23, no. 9, pp. 3623-3645. https://doi.org/10.1111/gcb.13643

APA

De Kauwe, M., Medlyn, B., Walker, A., Zaehle, S., Asao, S., Guenet, B., Harper, A., Hickler, T., Jain, A., Luo, Y., Lu, C., Luus, K., Parton, W., Shu, S., Wang, Y-P., Werner, C., Xia, J., Pendall, E., Morgan, J., ... Norby, R. (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. https://doi.org/10.1111/gcb.13643

Vancouver

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

Author

De Kauwe, Martin ; Medlyn, Belinda ; Walker, Anthony ; Zaehle, Sonke ; Asao, Shinichi ; Guenet, Bertrand ; Harper, Anna ; Hickler, Thomas ; Jain, Atul ; Luo, Yiqi ; Lu, Chris ; Luus, Kristina ; Parton, William ; Shu, Shijie ; Wang, Ying-Ping ; Werner, Christian ; Xia, Jianyang ; Pendall, Elise ; Morgan, Jack ; Ryan, Edmund ; Carrillo, Yolima ; Dijkstra, Feike ; Norby, Richard. / Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment. In: Global Change Biology. 2017 ; Vol. 23, No. 9. pp. 3623-3645.

Bibtex

@article{33d9940f4960485aab52ab5faea8f193,
title = "Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment",
abstract = "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 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 single-factors 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 nitrogen cycle models, nitrogen availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they over-estimated the effect of warming on leaf onset and did not allow CO2-induced water savings to extend growing season length. Observed interactive (CO2 x warming) treatment effects were subtle and contingent on water stress, phenology and species composition. Since the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.",
keywords = "allocation, carbon dioxide, FACE , grassland, models, PHACE , phenology, soil moisture, temperature",
author = "{De Kauwe}, Martin and Belinda Medlyn and Anthony Walker and Sonke Zaehle and Shinichi Asao and Bertrand Guenet and Anna Harper and Thomas Hickler and Atul Jain and Yiqi Luo and Chris Lu and Kristina Luus and William Parton and Shijie Shu and Ying-Ping Wang and Christian Werner and Jianyang Xia and Elise Pendall and Jack Morgan and Edmund Ryan and Yolima Carrillo and Feike Dijkstra and Richard Norby",
note = "This is the peer reviewed version of the following article: De Kauwe, M. G., Medlyn, B. E., Walker, A. P., Zaehle, S., Asao, S., Guenet, B., Harper, A. B., Hickler, T., Jain, A. K., Luo, Y., Lu, X., Luus, K., Parton, W. J., Shu, S., Wang, Y.-P., Werner, C., Xia, J., Pendall, E., Morgan, J. A., Ryan, E. M., Carrillo, Y., Dijkstra, F. A., Zelikova, T. J. and Norby, R. J. (2017), Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment. Glob Change Biol, 23: 3623–3645. doi:10.1111/gcb.13643 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/GCB.13643/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.",
year = "2017",
month = sep,
doi = "10.1111/gcb.13643",
language = "English",
volume = "23",
pages = "3623--3645",
journal = "Global Change Biology",
issn = "1354-1013",
publisher = "Blackwell Publishing Ltd",
number = "9",

}

RIS

TY - JOUR

T1 - Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment

AU - De Kauwe, Martin

AU - Medlyn, Belinda

AU - Walker, Anthony

AU - Zaehle, Sonke

AU - Asao, Shinichi

AU - Guenet, Bertrand

AU - Harper, Anna

AU - Hickler, Thomas

AU - Jain, Atul

AU - Luo, Yiqi

AU - Lu, Chris

AU - Luus, Kristina

AU - Parton, William

AU - Shu, Shijie

AU - Wang, Ying-Ping

AU - Werner, Christian

AU - Xia, Jianyang

AU - Pendall, Elise

AU - Morgan, Jack

AU - Ryan, Edmund

AU - Carrillo, Yolima

AU - Dijkstra, Feike

AU - Norby, Richard

N1 - This is the peer reviewed version of the following article: De Kauwe, M. G., Medlyn, B. E., Walker, A. P., Zaehle, S., Asao, S., Guenet, B., Harper, A. B., Hickler, T., Jain, A. K., Luo, Y., Lu, X., Luus, K., Parton, W. J., Shu, S., Wang, Y.-P., Werner, C., Xia, J., Pendall, E., Morgan, J. A., Ryan, E. M., Carrillo, Y., Dijkstra, F. A., Zelikova, T. J. and Norby, R. J. (2017), Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment. Glob Change Biol, 23: 3623–3645. doi:10.1111/gcb.13643 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/GCB.13643/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

PY - 2017/9

Y1 - 2017/9

N2 - 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 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 single-factors 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 nitrogen cycle models, nitrogen availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they over-estimated the effect of warming on leaf onset and did not allow CO2-induced water savings to extend growing season length. Observed interactive (CO2 x warming) treatment effects were subtle and contingent on water stress, phenology and species composition. Since the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.

AB - 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 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 single-factors 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 nitrogen cycle models, nitrogen availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they over-estimated the effect of warming on leaf onset and did not allow CO2-induced water savings to extend growing season length. Observed interactive (CO2 x warming) treatment effects were subtle and contingent on water stress, phenology and species composition. Since the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.

KW - allocation

KW - carbon dioxide

KW - FACE

KW - grassland

KW - models

KW - PHACE

KW - phenology

KW - soil moisture

KW - temperature

U2 - 10.1111/gcb.13643

DO - 10.1111/gcb.13643

M3 - Journal article

VL - 23

SP - 3623

EP - 3645

JO - Global Change Biology

JF - Global Change Biology

SN - 1354-1013

IS - 9

ER -