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Title: Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

Abstract

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here in this study we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO 2 efflux (R H) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil R H (7.5 ± 2.4 PgCyr -1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil R H with both models. In contrast to strong temporal and local controls of soilmore » temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [1];  [6];  [7]
  1. Purdue Univ., West Lafayette, IN (United States). Dept. of Earth, Atmospheric, and Planetary Sciences
  2. Univ. of Georgia, Athens, GA (United States). Warnell School of Forestry and Natural Resources; Northeast Forestry Univ., Harbin (China). Center for Ecological Research
  3. Purdue Univ., West Lafayette, IN (United States). Dept. of Earth, Atmospheric, and Planetary Sciences; Purdue Univ., West Lafayette, IN (United States). Dept. of Agronomy
  4. U.S. Geological Survey, Menlo Park, CA (United States)
  5. Alaska Cooperative Fish and Wildlife Research Unit, U.S. Geological Survey, Univ. of Alaska, Fairbanks, AK (United States). U.S. Geological Survey, Alaska Cooperative Fish and Wildlife Research Unit
  6. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Climate Change Science Inst. and Environmental Sciences Division
  7. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Environmental Sciences Division
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE; National Science Foundation (NSF); National Aeronautic and Space Administration (NASA)
OSTI Identifier:
1355881
DOE Contract Number:  
AC05-00OR22725; FG02-08ER64599; NSF-1028291; NSF-0630319; DEB-#0919331; NASA-NNX09AI26G
Resource Type:
Journal Article
Journal Name:
Journal of Geophysical Research. Biogeosciences
Additional Journal Information:
Journal Volume: 120; Journal Issue: 12; Journal ID: ISSN 2169-8953
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; microbial life history traits; microbial dormancy; soil C:N ratio; Michaelis-Menten kinetics; temperate forest ecosystem; soil heterotrophic respiration

Citation Formats

He, Yujie, Yang, Jinyan, Zhuang, Qianlai, Harden, Jennifer W., McGuire, Anthony D., Liu, Yaling, Wang, Gangsheng, and Gu, Lianhong. Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests. United States: N. p., 2015. Web. doi:10.1002/2015JG003130.
He, Yujie, Yang, Jinyan, Zhuang, Qianlai, Harden, Jennifer W., McGuire, Anthony D., Liu, Yaling, Wang, Gangsheng, & Gu, Lianhong. Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests. United States. doi:10.1002/2015JG003130.
He, Yujie, Yang, Jinyan, Zhuang, Qianlai, Harden, Jennifer W., McGuire, Anthony D., Liu, Yaling, Wang, Gangsheng, and Gu, Lianhong. Fri . "Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests". United States. doi:10.1002/2015JG003130. https://www.osti.gov/servlets/purl/1355881.
@article{osti_1355881,
title = {Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests},
author = {He, Yujie and Yang, Jinyan and Zhuang, Qianlai and Harden, Jennifer W. and McGuire, Anthony D. and Liu, Yaling and Wang, Gangsheng and Gu, Lianhong},
abstractNote = {Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here in this study we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 PgCyr-1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil RH with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.},
doi = {10.1002/2015JG003130},
journal = {Journal of Geophysical Research. Biogeosciences},
issn = {2169-8953},
number = 12,
volume = 120,
place = {United States},
year = {2015},
month = {11}
}

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