D. J. Hayes


2019

DOI bib
Global vegetation biomass production efficiency constrained by models and observations
Yue He, Shushi Peng, Yongwen Liu, Xiangyi Li, Kai Wang, Philippe Ciais, M. Altaf Arain, Yuanyuan Fang, Joshua B. Fisher, Daniel S. Goll, D. J. Hayes, D. N. Huntzinger, Akihiko Ito, Atul K. Jain, Ivan A. Janssens, Jiafu Mao, Matteo Campioli, A. M. Michalak, Changhui Peng, Josep Peñuelas, Benjamin Poulter, Dahe Qin, Daniel M. Ricciuto, Kevin Schaefer, Christopher R. Schwalm, Xiaoying Shi, Hanqin Tian, Sara Vicca, Yaxing Wei, Ning Zeng, Qiuan Zhu
Global Change Biology, Volume 26, Issue 3

Plants use only a fraction of their photosynthetically derived carbon for biomass production (BP). The biomass production efficiency (BPE), defined as the ratio of BP to photosynthesis, and its variation across and within vegetation types is poorly understood, which hinders our capacity to accurately estimate carbon turnover times and carbon sinks. Here, we present a new global estimation of BPE obtained by combining field measurements from 113 sites with 14 carbon cycle models. Our best estimate of global BPE is 0.41 ± 0.05, excluding cropland. The largest BPE is found in boreal forests (0.48 ± 0.06) and the lowest in tropical forests (0.40 ± 0.04). Carbon cycle models overestimate BPE, although models with carbon-nitrogen interactions tend to be more realistic. Using observation-based estimates of global photosynthesis, we quantify the global BP of non-cropland ecosystems of 41 ± 6 Pg C/year. This flux is less than net primary production as it does not contain carbon allocated to symbionts, used for exudates or volatile carbon compound emissions to the atmosphere. Our study reveals a positive bias of 24 ± 11% in the model-estimated BP (10 of 14 models). When correcting models for this bias while leaving modeled carbon turnover times unchanged, we found that the global ecosystem carbon storage change during the last century is decreased by 67% (or 58 Pg C).

2018

DOI bib
Missing pieces to modeling the Arctic-Boreal puzzle
Joshua B. Fisher, D. J. Hayes, Christopher R. Schwalm, D. N. Huntzinger, Eric Stofferahn, Kevin Schaefer, Yiqi Luo, Stan D. Wullschleger, Scott J. Goetz, Charles E. Miller, P. C. Griffith, Sarah Chadburn, Abhishek Chatterjee, Philippe Ciais, Thomas A. Douglas, Hélène Genet, Akihiko Ito, C. S. R. Neigh, Benjamin Poulter, Brendan M. Rogers, Oliver Sonnentag, Hanqin Tian, Weile Wang, Yongkang Xue, Zong‐Liang Yang, Ning Zeng, Zhen Zhang
Environmental Research Letters, Volume 13, Issue 2

Author(s): Fisher, JB; Hayes, DJ; Schwalm, CR; Huntzinger, DN; Stofferahn, E; Schaefer, K; Luo, Y; Wullschleger, SD; Goetz, S; Miller, CE; Griffith, P; Chadburn, S; Chatterjee, A; Ciais, P; Douglas, TA; Genet, H; Ito, A; Neigh, CSR; Poulter, B; Rogers, BM; Sonnentag, O; Tian, H; Wang, W; Xue, Y; Yang, ZL; Zeng, N; Zhang, Z | Abstract: NASA has launched the decade-long Arctic-Boreal Vulnerability Experiment (ABoVE). While the initial phases focus on field and airborne data collection, early integration with modeling activities is important to benefit future modeling syntheses. We compiled feedback from ecosystem modeling teams on key data needs, which encompass carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance dynamics. A suite of variables was identified as part of this activity with a critical requirement that they are collected concurrently and representatively over space and time. Individual projects in ABoVE may not capture all these needs, and thus there is both demand and opportunity for the augmentation of field observations, and synthesis of the observations that are collected, to ensure that science questions and integrated modeling activities are successfully implemented.