Multiple models and experiments underscore large uncertainty in soil carbon dynamics

Sulman, Benjamin N.; Moore, Jessica A.  M.; Abramoff, Rose; Averill, Colin; Kivlin, Stephanie; Georgiou, Katerina; Sridhar, Bhavya; Hartman, Melannie D.; Wang, Gangsheng; Wieder, William R.; Bradford, Mark A.; Luo, Yiqi; Mayes, Melanie A.; Morrison, Eric; Riley, William J.; Salazar, Alejandro; Schimel, Joshua P.; Tang, Jinyun; Classen, Aimée T.

doi:10.1007/s10533-018-0509-z

Multiple models and experiments underscore large uncertainty in soil carbon dynamics

Journal Article · Thu Oct 11 00:00:00 EDT 2018 · Biogeochemistry

DOI:https://doi.org/10.1007/s10533-018-0509-z· OSTI ID:1501396

Sulman, Benjamin N. ^[1]; Moore, Jessica A. M. ^[2]; Abramoff, Rose ^[3]; Averill, Colin ^[4]; Kivlin, Stephanie ^[5]; Georgiou, Katerina ^[6]; Sridhar, Bhavya ^[7]; Hartman, Melannie D. ^[8]; Wang, Gangsheng ^[9]; Wieder, William R. ^[10]; Bradford, Mark A. ^[11]; Luo, Yiqi ^[12]; Mayes, Melanie A. ^[13]; Morrison, Eric ^[14]; Riley, William J. ^[3]; Salazar, Alejandro ^[15]; Schimel, Joshua P. ^[16]; Tang, Jinyun ^[3]; Classen, Aimée T. ^[17]

Princeton Univ., Princeton, NJ (United States); Univ. of California, Merced, CA (United States). Sierra Nevada Research Inst.; University of Vermont
Univ. of New Hampshire, Durham, NH (United States); Univ. of Tennessee, Knoxville, TN (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Boston Univ., Boston, MA (United States)
Univ. of Tennessee, Knoxville, TN (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Stanford Univ., Stanford, CA (United States)
Cornell Univ., Ithaca, NY (United States)
Colorado State Univ., Fort Collins, CO (United States); National Center for Atmospheric Research, Boulder, CO (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Oklahoma, Norman, OK (United States)
National Center for Atmospheric Research, Boulder, CO (United States); Univ. of Colorado, Boulder, CO (United States)
Yale Univ., New Haven, CT (United States)
Northern Arizona Univ., Flagstaff, AZ (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Univ. of New Hampshire, Durham, NH (United States)
Purdue Univ., West Lafayette, IN (United States)
Univ. of California, Santa Barbara, CA (United States)
Univ. of Vermont, Burlington, VT (United States)

Soils contain more carbon than plants or the atmosphere, and sensitivities of soil organic carbon (SOC) stocks to changing climate and plant productivity are a major uncertainty in global carbon cycle projections. Despite a consensus that microbial degradation and mineral stabilization processes control SOC cycling, no systematic synthesis of long-term warming and litter addition experiments has been used to test process-based microbe-mineral SOC models. We explored SOC responses to warming and increased carbon inputs using a synthesis of 147 field manipulation experiments and five SOC models with different representations of microbial and mineral processes. Model projections diverged but encompassed a similar range of variability as the experimental results. Experimental measurements were insufficient to eliminate or validate individual model outcomes. While all models projected that CO₂ efflux would increase and SOC stocks would decline under warming, nearly one- third of experiments observed decreases in CO₂ flux and nearly half of experiments observed increases in SOC stocks under warming. Long-term measurements of C inputs to soil and their changes under warming are needed to reconcile modeled and observed patterns. Measurements separating the responses of mineral- protected and unprotected SOC fractions in manipulation experiments are needed to address key uncertainties in microbial degradation and mineral stabilization mechanisms. Conclusively, integrating models with experimental design will allow targeting of these uncertainties and help to reconcile divergence among models to produce more confident projections of SOC responses to global changes.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Univ. of Tennessee, Knoxville, TN (United States)

Sponsoring Organization:: National Oceanographic and Atmospheric Administration (NOAA); USDA; USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC02-05CH11231; AC05-00OR22725; SC0010562

OSTI ID:: 1501396

Alternate ID(s):: OSTI ID: 1504006
OSTI ID: 1563975

Journal Information:: Biogeochemistry, Journal Name: Biogeochemistry Journal Issue: 2 Vol. 141; ISSN 0168-2563

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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Soil Organic Matter Temperature Sensitivity Cannot be Directly Inferred From Spatial Gradients

Journal Article · Sun May 05 20:00:00 EDT 2019 · Global Biogeochemical Cycles · OSTI ID:1574331

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54 ENVIRONMENTAL SCIENCES
58 GEOSCIENCES
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Modeling
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Warming

Multiple models and experiments underscore large uncertainty in soil carbon dynamics

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