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This content will become publicly available on November 9, 2018

Title: Carbon cycle confidence and uncertainty: Exploring variation among soil biogeochemical models

Emerging insights into factors responsible for soil organic matter stabilization and decomposition are being applied in a variety of contexts, but new tools are needed to facilitate the understanding, evaluation, and improvement of soil biogeochemical theory and models at regional to global scales. To isolate the effects of model structural uncertainty on the global distribution of soil carbon stocks and turnover times we developed a soil biogeochemical testbed that forces three different soil models with consistent climate and plant productivity inputs. The models tested here include a first-order, microbial implicit approach (CASA-CNP), and two recently developed microbially explicit models that can be run at global scales (MIMICS and CORPSE). When forced with common environmental drivers, the soil models generated similar estimates of initial soil carbon stocks (roughly 1,400 Pg C globally, 0–100 cm), but each model shows a different functional relationship between mean annual temperature and inferred turnover times. Subsequently, the models made divergent projections about the fate of these soil carbon stocks over the 20th century, with models either gaining or losing over 20 Pg C globally between 1901 and 2010. Single-forcing experiments with changed inputs, tem- perature, and moisture suggest that uncertainty associated with freeze-thaw processes as wellmore » as soil textural effects on soil carbon stabilization were larger than direct temper- ature uncertainties among models. Finally, the models generated distinct projections about the timing and magnitude of seasonal heterotrophic respiration rates, again reflecting structural uncertainties that were related to environmental sensitivities and assumptions about physicochemical stabilization of soil organic matter. Here, by providing a computationally tractable and numerically consistent framework to evaluate models we aim to better understand uncertainties among models and generate insights about fac- tors regulating the turnover of soil organic matter.« less
ORCiD logo [1] ;  [2] ;  [3] ;  [4] ;  [5] ;  [6]
  1. Univ. of Colorado, Boulder, CO (United States); National Center for Atmospheric Research, Boulder, CO (United States)
  2. National Center for Atmospheric Research, Boulder, CO (United States); Colorado State Univ., Fort Collins, CO (United States)
  3. Princeton Univ., Princeton, NJ (United States)
  4. Chinese Academy of Sciences, Guangzhou (China); CSIRO Oceans and Atmosphere, Aspendale, VIC (Australia)
  5. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  6. National Center for Atmospheric Research, Boulder, CO (United States)
Publication Date:
Grant/Contract Number:
SC0014374; TES SC0014374; BSS SC0016364
Accepted Manuscript
Journal Name:
Global Change Biology
Additional Journal Information:
Journal Volume: 24; Journal Issue: 4; Journal ID: ISSN 1354-1013
Research Org:
Univ. of Colorado, Boulder, CO (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
54 ENVIRONMENTAL SCIENCES; biogeochemistry; carbon cycle; earth system models; global change; microbial models; soil organic matter; structural uncertainty; turnover time
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1410374