Kevin Schaefer


2019

DOI bib
Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region
Erqian Cui, Kun Huang, M. Altaf Arain, Joshua B. Fisher, D. N. Huntzinger, Akihiko Ito, Yiqi Luo, Atul K. Jain, Jiafu Mao, A. M. Michalak, Shuli Niu, Nicholas C. Parazoo, Changhui Peng, Shushi Peng, Benjamin Poulter, Daniel M. Ricciuto, Kevin Schaefer, Christopher R. Schwalm, Xiaoying Shi, Hanqin Tian, Weile Wang, Jinsong Wang, Yaxing Wei, En‐Rong Yan, Liming Yan, Ning Zeng, Qiuan Zhu, Jianyang Xia
Global Biogeochemical Cycles, Volume 33, Issue 6

Global and regional projections of climate change by Earth system models are limited by their uncertain estimates of terrestrial ecosystem productivity. At the middle to low latitudes, the East Asian monsoon region has higher productivity than forests in Europe‐Africa and North America, but its estimate by current generation of terrestrial biosphere models (TBMs) has seldom been systematically evaluated. Here, we developed a traceability framework to evaluate the simulated gross primary productivity (GPP) by 15 TBMs in the East Asian monsoon region. The framework links GPP to net primary productivity, biomass, leaf area and back to GPP via incorporating multiple vegetation functional properties of carbon‐use efficiency (CUE), vegetation C turnover time (τveg), leaf C fraction (Fleaf), specific leaf area (SLA), and leaf area index (LAI)‐level photosynthesis (PLAI), respectively. We then applied a relative importance algorithm to attribute intermodel variation at each node. The results showed that large intermodel variation in GPP over 1901–2010 were mainly propagated from their different representation of vegetation functional properties. For example, SLA explained 77% of the intermodel difference in leaf area, which contributed 90% to the simulated GPP differences. In addition, the models simulated higher CUE (18.1 ± 21.3%), τveg (18.2 ± 26.9%), and SLA (27.4±36.5%) than observations, leading to the overestimation of simulated GPP across the East Asian monsoon region. These results suggest the large uncertainty of current TBMs in simulating GPP is largely propagated from their poor representation of the vegetation functional properties and call for a better understanding of the covariations between plant functional properties in terrestrial ecosystems.

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).

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Large loss of CO2 in winter observed across the northern permafrost region
Susan M. Natali, Jennifer D. Watts, Brendan M. Rogers, Stefano Potter, S. Ludwig, A. K. Selbmann, Patrick F. Sullivan, Benjamin W. Abbott, Kyle A. Arndt, Leah Birch, Mats Björkman, A. Anthony Bloom, Gerardo Celis, Torben R. Christensen, Casper T. Christiansen, R. Commane, Elisabeth J. Cooper, Patrick Crill, C. I. Czimczik, S. P. Davydov, Jinyang Du, Jocelyn Egan, Bo Elberling, Eugénie Euskirchen, Thomas Friborg, Hélène Genet, Mathias Göckede, Jordan P. Goodrich, Paul Grogan, Manuel Helbig, Elchin Jafarov, Julie D. Jastrow, Aram Kalhori, Yongwon Kim, J. S. Kimball, Lars Kutzbach, Mark J. Lara, Klaus Steenberg Larsen, Bang Yong Lee, Zhihua Liu, M. M. Loranty, Magnus Lund, Massimo Lupascu, Nima Madani, Avni Malhotra, Roser Matamala, J. W. Mcfarland, A. David McGuire, Anders Michelsen, C. Minions, Walter C. Oechel, David Olefeldt, Frans‐Jan W. Parmentier, Norbert Pirk, Benjamin Poulter, William L. Quinton, Fereidoun Rezanezhad, David Risk, Torsten Sachs, Kevin Schaefer, Niels Martin Schmidt, Edward A. G. Schuur, Philipp Semenchuk, Gaius R. Shaver, Oliver Sonnentag, Gregory Starr, Claire C. Treat, Mark P. Waldrop, Yihui Wang, Jeffrey M. Welker, Christian Wille, Xiaofeng Xu, Zhen Zhang, Qianlai Zhuang, Donatella Zona
Nature Climate Change, Volume 9, Issue 11

Recent warming in the Arctic, which has been amplified during the winter1-3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)4. However, the amount of CO2 released in winter is highly uncertain and has not been well represented by ecosystem models or by empirically-based estimates5,6. Here we synthesize regional in situ observations of CO2 flux from arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1662 Tg C yr-1 from the permafrost region during the winter season (October through April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (-1032 Tg C yr-1). Extending model predictions to warmer conditions in 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario-Representative Concentration Pathway (RCP) 4.5-and 41% under business-as-usual emissions scenario-RCP 8.5. Our results provide a new baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.

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.
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