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

• DOI: 10.1111/gcb.13643
• Publication Date: 2017-02-01T07:43:58Z
• Authors: Martin G. De Kauwe; Belinda E. Medlyn; Anthony P. Walker; Sönke Zaehle; Shinichi Asao; Bertrand Guenet; Anna B. Harper; Thomas Hickler; Atul K. Jain; Yiqi Luo; Xingjie Lu; Kristina Luus; William J. Parton; Shijie Shu; Ying‐Ping Wang; Christian Werner; Jianyang Xia; Elise Pendall; Jack A. Morgan; Edmund M. Ryan; Yolima Carrillo; Feike A. Dijkstra; Tamara J. Zelikova; Richard J. Norby
• Keywords: Growing season

Multifactor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date, such have only been tested against single-factor experiments. We applied 10 TBMs the multifactor Prairie Heating and CO2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were investigate how can be used constrain identify a road map model improvement. found performed poorly ambient conditions; there was wide spread simulated above-ground net primary productivity (range: 31-390 g C m-2 yr-1 ). Comparison with data highlighted failures particularly respect carbon allocation, phenology, impact of water stress on phenology. Performance observations from single-factors treatments also relatively poor. In addition, similar responses predicted different reasons across models: large differences among sensitivity and, N cycle models, availability during experiment. Models unable capture observed treatment effects phenology: they overestimated effect warming leaf onset did not allow -induced savings extend growing season length. Observed interactive (CO2 × warming) subtle contingent stress, species composition. As correctly represent these processes under conditions, little extra information gained by comparing predictions responses. outline series key areas which this future could improve grassland global change.