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Estimating parameters of a forest ecosystem C model with measurements of stocks and fluxes as joint constraints

  • Physiological ecology - Original Paper
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Abstract

We conducted an inverse modeling analysis, using a variety of data streams (tower-based eddy covariance measurements of net ecosystem exchange, NEE, of CO2, chamber-based measurements of soil respiration, and ancillary ecological measurements of leaf area index, litterfall, and woody biomass increment) to estimate parameters and initial carbon (C) stocks of a simple forest C-cycle model, DALEC, using Monte Carlo procedures. Our study site is the spruce-dominated Howland Forest AmeriFlux site, in central Maine, USA. Our analysis focuses on: (1) full characterization of data uncertainties, and treatment of these uncertainties in the parameter estimation; (2) evaluation of how combinations of different data streams influence posterior parameter distributions and model uncertainties; and (3) comparison of model performance (in terms of both predicted fluxes and pool dynamics) during a 4-year calibration period (1997–2000) and a 4-year validation period (“forward run”, 2001–2004). We find that woody biomass increment, and, to a lesser degree, soil respiration, measurements contribute to marked reductions in uncertainties in parameter estimates and model predictions as these provide orthogonal constraints to the tower NEE measurements. However, none of the data are effective at constraining fine root or soil C pool dynamics, suggesting that these should be targets for future measurement efforts. A key finding is that adding additional constraints not only reduces uncertainties (i.e., narrower confidence intervals) on model predictions, but at the same time also results in improved model predictions by greatly reducing bias associated with predictions during the forward run.

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Acknowledgments

Research at the Howland Forest was supported by the Office of Science (BER), US Department of Energy, through the Terrestrial Carbon Program under Interagency Agreement No. DE-AI02-07ER64355 and through the Northeastern Regional Center of the National Institute for Climatic Change Research. The Howland CO2 flux, climate, and ancillary ecological datasets are available at http://public.ornl.gov/ameriflux/Data/index.cfm subject to AmeriFlux “Fair-use” policies.

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Authors and Affiliations

  1. Department of Organismic and Evolutionary Biology, Harvard University Herbaria, Harvard University, 22 Divinity Avenue, Cambridge, MA, 02138, USA

    Andrew D. Richardson

  2. School of GeoSciences, University of Edinburgh, Edinburgh, EH9 3JN, UK

    Mathew Williams

  3. Northern Research Station, USDA Forest Service, 271 Mast Road, Durham, NH, 03824, USA

    David Y. Hollinger & Robert S. Evans

  4. Department of Geography, Environmental Monitoring and Modelling Research Group, King’s College London, Strand, London, WC2R 2LS, UK

    David J. P. Moore

  5. Department of Plant, Soil, and Environmental Sciences, University of Maine, Orono, ME, 04469, USA

    D. Bryan Dail, John T. Lee & Charles Rodrigues

  6. Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA, 02540, USA

    Eric A. Davidson, Holly Hughes & Kathleen Savage

  7. Department of Geography, Queen’s University, Kingston, ON, K7L 3N6, Canada

    Neal A. Scott

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  1. Andrew D. Richardson
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  2. Mathew Williams
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Correspondence to Andrew D. Richardson.

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Communicated by Russell Monson.

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Richardson, A.D., Williams, M., Hollinger, D.Y. et al. Estimating parameters of a forest ecosystem C model with measurements of stocks and fluxes as joint constraints. Oecologia 164, 25–40 (2010). https://doi.org/10.1007/s00442-010-1628-y

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  • DOI: https://doi.org/10.1007/s00442-010-1628-y

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