Skip to main content

Advertisement

SpringerLink
Log in

Quantifying microbial ecophysiological effects on the carbon fluxes of forest ecosystems over the conterminous United States

  • Published:
Climatic Change Aims and scope Submit manuscript

Abstract

There is a pressing need to develop earth system models (ESMs), in which ecosystem processes are adequately represented, to quantify carbon-climate feedbacks. In particular, explicit representation of the effects of microbial activities on soil organic carbon decomposition has been slow in ESM development. Here we revised an existing Q10-based heterotrophic respiration (RH) algorithm of a large-scale biogeochemical model, the Terrestrial Ecosystem Model (TEM), by incorporating the algorithms of Dual Arrhenius and Michaelis-Menten kinetics and microbial-enzyme interactions. The microbial physiology enabled model (MIC-TEM) was then applied to quantify historical and future carbon dynamics of forest ecosystems in the conterminous United States. Simulations indicate that warming has a weaker positive effect on RH than that traditional Q10 model has. Our results demonstrate that MIC-TEM is superior to traditional TEM in reproducing historical carbon dynamics. More importantly, the future trend of soil carbon accumulation simulated with MIC-TEM is more reasonable than TEM did and is generally consistent with soil warming experimental studies. The revised model estimates that regional GPP is 2.48 Pg C year−1 (2.02 to 3.03 Pg C year−1) and NEP is 0.10 Pg C year−1 (−0.20 to 0.32 Pg C year−1) during 2000–2005. Both models predict that the conterminous United States forest ecosystems are carbon sinks under two future climate scenarios during the 21st century. This study suggests that terrestrial ecosystem models should explicitly consider the microbial ecophysiological effects on soil carbon decomposition to adequately quantify forest ecosystem carbon fluxes at regional scales.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Allison SD, Wallenstein MD, Bradford MA (2010) Soil-carbon response to warming dependent on microbial physiology. Nat Geosci 3:336–340

    Article  Google Scholar 

  • Billings SA, Ballantyne F (2013) How interactions between microbial resource demands, soil organic matter stoichiometry, and substrate reactivity determine the direction and magnitude of soil respiratory responses to warming. Glob Chang Biol 19:90–102

    Article  Google Scholar 

  • Bond-Lamberty B, Thomson A (2010) A global database of soil respiration data. Biogeosciences 7:1915–1926

    Article  Google Scholar 

  • Bradford MA, Davies CA, Frey SD et al (2008) Thermal adaptation of soil microbial respiration to elevated temperature. Ecol Lett 11:1316–1327

    Article  Google Scholar 

  • Bradford MA, Watts BW, Davies CA (2010) Thermal adaptation of heterotrophic soil respiration in laboratory microcosms. Glob Chang Biol 16:1576–1588

    Article  Google Scholar 

  • Chen M, Zhuang Q, Cook DR et al (2011) Quantification of terrestrial ecosystem carbon dynamics in the conterminous United States combining a process-based biogeochemical model and MODIS and AmeriFlux data. Biogeosciences 8:2665–2688

    Article  Google Scholar 

  • Davidson EA, Janssens IA (2006) Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature 440:165–173

    Article  Google Scholar 

  • Davidson EA, Samanta S, Caramori SS, Savage K (2012) The dual Arrhenius and Michaelis–Menten kinetics model for decomposition of soil organic matter at hourly to seasonal time scales. Glob Chang Biol 18:371–384

    Article  Google Scholar 

  • Duan Q, Sorooshian S, Gupta V (1992) Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resour Res 28:1015–1031

    Article  Google Scholar 

  • Duan Q, Sorooshian S, Gupta VK (1994) Optimal use of the SCE-UA global optimization method for calibrating watershed models. J Hydrol 158:265–284

    Article  Google Scholar 

  • Eliasson PE, McMurtrie RE, Pepper DA, Stromgren M, Linder S, Agren GI (2005) The response of heterotrophic CO2 flux to soil warming. Glob Chang Biol 11:167–181

    Article  Google Scholar 

  • Frey SD, Drijber R, Smith H, Melillo J (2008) Microbial biomass, functional capacity, and community structure after 12 years of soil warming. Soil Biol Biochem 40:2904–2907

    Article  Google Scholar 

  • Friedlingstein P, Cox P, Betts R et al (2006) Climate-carbon cycle feedback analysis: results from the C4MIP model intercomparison. J Clim 19:3337–3353

    Article  Google Scholar 

  • Felzer B, Kicklighter D, Melillo J (2004) Effects of ozone on net primary production and carbon sequestration in the conterminous United States using a biogeochemistry model. Tellus 56B:230–248

    Article  Google Scholar 

  • Hao GC, Zhuang Q, Pan JJ, Jin ZN, Zhu XD, Liu SQ (2014) Soil thermal dynamics of terrestrial ecosystems of the conterminous United States from 1948 to 2008: an analysis with a process-based soil physical model and AmeriFlux data. Clim Chang 126:135–150

    Article  Google Scholar 

  • Hanson P, Edwards N, Garten C, Andrews J (2000) Separating root and soil microbial contributions to soil respiration: a review of methods and observations. Biogeochem 48:115–146

    Article  Google Scholar 

  • Hanson PJ, O’Neill EG, Chambers MLS et al. (2003) Soil respiration and litter decomposition: North American temperate deciduous forest responses to changing precipitation regimes. Springer, pp 163–189

  • He Y, Zhuang Q, Harden J et al (2014) The implications of microbial and substrate limitation for the fates of carbon in different organic soil horizon types: a mechanistically based model analysis. Biogeosciences 11:2227–2266

    Article  Google Scholar 

  • Hopkins FM, Filley TR, Gleixner G et al (2014) Increased belowground carbon inputs and warming promote loss of soil organic carbon through complementary microbial responses. Soil Biol Biochem 76:57–69

    Article  Google Scholar 

  • Hubbard RM, Ryan MG, Elder K, Rhoades CC (2005) Seasonal patterns in soil surface CO2 flux under snow cover in 50 and 300 year old subalpine forests. Biogeochem 73:93–107

    Article  Google Scholar 

  • Intergovernmental Panel On Climate Change, Climate Change– The Physical Science Basis (2007) Contribution of working group i to the fourth assessment report of the IPCC. Cambridge University Press, New York

    Google Scholar 

  • Intergovernmental Panel On Climate Change, Climate Change 2013 – The Physical Science Basis (2013) Contribution of working group i to the fifth assessment report of the IPCC. Cambridge University Press, New York

    Google Scholar 

  • Kistler R, Collins W, Saha S et al (2001) The NCEP-NCAR 50-year reanalysis: monthly means CD-ROM and documentation B. Am Meteorol Soc 82:247–267

    Article  Google Scholar 

  • Law BE, Turner D, Campbel J et al. (2006) Carbon fluxes across regions: observational constraints at multiple scales. In: Scaling and uncertainty analysis in ecology, Springer, pp 167–190

  • McGuire AD, Melillo J, Joyce L et al (1992) Interactions between carbon and nitrogen dynamics in estimating net primary productivity for potential vegetation in North America. Glob Biogeochem Cycles 6:101–124

    Article  Google Scholar 

  • Melillo JM, McGuire AD, Kicklighter DW et al (1993) Global climate change and terrestrial net primary production. Nature 363:234–240

    Article  Google Scholar 

  • Ostroumov V, Siegert C (1996) Exobiological aspects of mass transfer in microzones of permafrost deposits. Adv Space Res 18:79–86

    Article  Google Scholar 

  • Pappas C, Fatichi S, Leuzinger S, Wolf A et al (2013) Sensitivity analysis of a process-based ecosystem model: pinpointing parameterization and structural issues. J Geophys Res-Biogeo 118:505–528

    Article  Google Scholar 

  • Potter C, Klooster S, Huete A, Genovese V (2007) Terrestrial carbon sinks for the United States predicted from MODIS satellite data and ecosystem modeling. Earth Interactions 11:1–21

    Article  Google Scholar 

  • Raich J, Rastetter E, Melillo J et al (1991) Potential net primary productivity in South America: application of a global model. Ecol Appl 1:399–429

    Article  Google Scholar 

  • Rousk J, Frey SD, Bååth E (2012) Temperature adaptation of bacterial communities in experimentally warmed forest soils. Glob Chang Biol 18:3252–3258

    Article  Google Scholar 

  • Running S, Nemani R, Heinsch F, Zhao M, Reeves M, Hashimoto H (2004) A continuous satellite-derived measure of global terrestrial primary production. Bioscience 54:547–560

    Article  Google Scholar 

  • Shi W, Yao H, Bowman D (2006) Soil microbial biomass, activity and nitrogen transformations in a turfgrass chronosequence. Soil Biol Biochem 38:311–319

    Article  Google Scholar 

  • Tang JY, Zhuang Q (2009) A global sensitivity analysis and Bayesian inference framework for improving the parameter estimation and prediction of a process-based terrestrial ecosystem model. J Geophys Res 114, D15303. doi:10.1029/2009JD011724

    Article  Google Scholar 

  • Tang JY, Riely WJ (2014) Weaker soil carbon-climate feedbacks resulting from microbial and abiotic interactions. Nat Clim Chang. doi:10.138/NCLIMATE2438

    Google Scholar 

  • Todd-Brown K, Randerson J, Hopkins F et al (2014) Changes in soil organic carbon storage predicted by Earth system models during the 21st century. Biogeosciences 11:2341–2356

    Article  Google Scholar 

  • Weedon JT, Kowalchuk GA, Aerts R et al (2012) Summer warming accelerates sub- arctic peatland nitrogen cycling without changing enzyme pools or microbial community structure. Glob Chang Biol 18:138–150

    Article  Google Scholar 

  • Wei H, Guenet B, Vicca S et al (2014) Thermal acclimation of organic matter decomposition in an artificial forest soil is related to shifts in microbial community structure. Soil Biol Biochem 71:1–12

    Article  Google Scholar 

  • Wieder WR, Bonan GB, Allison SD (2013) Global soil carbon projections are improved by modelling microbial processes. Nat Clim Chang 3:909–912

    Article  Google Scholar 

  • Xiao J, Zhuang Q, Baldocchi DD et al (2008) Estimation of net ecosystem carbon exchange for the conterminous United States by combining MODIS and AmeriFlux data. Agric Forest Meteorol 148:1827–1847

    Article  Google Scholar 

  • Xiao J, Zhuang Q, Law BE et al (2011) Assessing net ecosystem carbon exchange of US terrestrial ecosystems by integrating eddy covariance flux measurements and satellite observations. Agric Forest Meteorol 151:60–69

    Article  Google Scholar 

  • Xu XF, Schimel JP, Thornton PE, Song X, Yuan FM, Goswami S (2014) Substrate and environmental controls on microbial assimilation of soil organic carbon:a framework for Earth system models. Ecol Lett 17:547–555

    Article  Google Scholar 

  • Zhao M, Heinsch FA, Nemani RR, Running SW (2005) Improvements of the MODIS terrestrial gross and net primary production global data set. Remote Sens Environ 95:164–176

    Article  Google Scholar 

  • Zhou X, Luo Y, Gao C et al (2010) Concurrent and lagged impacts of an anomalously warm year on autotrophic and heterotrophic components of soil respiration: a deconvolution analysis. New Phyto 187:184–198

    Article  Google Scholar 

  • Zhu Q, Zhuang Q (2013) Modeling the effects of organic nitrogen uptake by plants on the carbon cycling of boreal ecosystems. Biogeosci Discussions 10:13455–13490

    Article  Google Scholar 

  • Zhuang Q, McGuire A, O’neill K et al (2002) Modeling soil thermal and carbon dynamics of a fire chronosequence in interior Alaska. JGR-Atmos 107:3–26

    Google Scholar 

  • Zhuang Q, McGuire A, Melillo J et al (2003) Carbon cycling in extratropical terrestrial ecosystems of the Northern Hemisphere during the 20th century: a modeling analysis of the influences of soil thermal dynamics. Tellus B 55:751–776

    Article  Google Scholar 

  • Zhuang Q, He Y, Lu Y et al (2010) Carbon dynamics of terrestrial ecosystems on the Tibetan Plateau during the 20th century: an analysis with a process-based biogeochemical model. Global Ecol Biogeogr 19:649–662

    Google Scholar 

Download references

Acknowledgments

We acknowledge the AmeriFlux community to provide the eddy flux data. This research is supported with projects funded to Q.Z., including NSF projects (DEB-#0919331; NSF-0630319), the NASA Land Use and Land Cover Change program (NASA-NNX09AI26G), Department of Energy (DE-FG02-08ER64599), and the NF Division of Information & Intelligent Systems (NSF-1028291).

Author information

Authors and Affiliations

  1. Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China

    Guangcun Hao & Weijun Shen

  2. Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, USA

    Guangcun Hao, Qianlai Zhuang, Qing Zhu, Yujie He & Zhenong Jin

  3. Department of Agronomy, Purdue University, West Lafayette, IN, USA

    Qianlai Zhuang

  4. Earth Science Division, Lawrence Berkeley National Lab, Berkeley, CA, USA

    Qing Zhu

Authors
  1. Guangcun Hao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qianlai Zhuang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qing Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yujie He
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhenong Jin
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Weijun Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Qianlai Zhuang.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(DOCX 287 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hao, G., Zhuang, Q., Zhu, Q. et al. Quantifying microbial ecophysiological effects on the carbon fluxes of forest ecosystems over the conterminous United States. Climatic Change 133, 695–708 (2015). https://doi.org/10.1007/s10584-015-1490-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10584-015-1490-3

Keywords

Search

Navigation