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

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Estimating parameters of a forest ecosystem C model with measurements of stocks and fluxes as joint constraints. / Richardson, Andrew D.; Williams, Mathew; Hollinger, David Y. et al.

In: Oecologia, Vol. 164, No. 1, 2010, p. 25 - 40.

Research output: Contribution to journalArticlepeer-review

Harvard

Richardson, AD, Williams, M, Hollinger, DY, Moore, DJP, Dail, DB, Davidson, EA, Scott, NA, Evans, RS, Hughes, H, Lee, JT, Rodrigues, C & Savage, K 2010, 'Estimating parameters of a forest ecosystem C model with measurements of stocks and fluxes as joint constraints', Oecologia, vol. 164, no. 1, pp. 25 - 40. https://doi.org/10.1007/s00442-010-1628-y

APA

Richardson, A. D., Williams, M., Hollinger, D. Y., Moore, D. J. P., Dail, D. B., Davidson, E. A., Scott, N. A., Evans, R. S., Hughes, H., Lee, J. T., Rodrigues, C., & Savage, K. (2010). Estimating parameters of a forest ecosystem C model with measurements of stocks and fluxes as joint constraints. Oecologia, 164(1), 25 - 40. https://doi.org/10.1007/s00442-010-1628-y

Vancouver

Richardson AD, Williams M, Hollinger DY, Moore DJP, Dail DB, Davidson EA et al. Estimating parameters of a forest ecosystem C model with measurements of stocks and fluxes as joint constraints. Oecologia. 2010;164(1):25 - 40. https://doi.org/10.1007/s00442-010-1628-y

Author

Richardson, Andrew D. ; Williams, Mathew ; Hollinger, David Y. et al. / Estimating parameters of a forest ecosystem C model with measurements of stocks and fluxes as joint constraints. In: Oecologia. 2010 ; Vol. 164, No. 1. pp. 25 - 40.

Bibtex Download

@article{f42b6dfc3f434faa8a8feacea9d0a74a,
title = "Estimating parameters of a forest ecosystem C model with measurements of stocks and fluxes as joint constraints",
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.",
author = "Richardson, {Andrew D.} and Mathew Williams and Hollinger, {David Y.} and Moore, {David J. P.} and Dail, {D. Bryan} and Davidson, {Eric A.} and Scott, {Neal A.} and Evans, {Robert S.} and Holly Hughes and Lee, {John T.} and Charles Rodrigues and Kathleen Savage",
year = "2010",
doi = "10.1007/s00442-010-1628-y",
language = "English",
volume = "164",
pages = "25 -- 40",
journal = "Oecologia",
issn = "0029-8549",
publisher = "Springer Verlag",
number = "1",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - Estimating parameters of a forest ecosystem C model with measurements of stocks and fluxes as joint constraints

AU - Richardson, Andrew D.

AU - Williams, Mathew

AU - Hollinger, David Y.

AU - Moore, David J. P.

AU - Dail, D. Bryan

AU - Davidson, Eric A.

AU - Scott, Neal A.

AU - Evans, Robert S.

AU - Hughes, Holly

AU - Lee, John T.

AU - Rodrigues, Charles

AU - Savage, Kathleen

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

U2 - 10.1007/s00442-010-1628-y

DO - 10.1007/s00442-010-1628-y

M3 - Article

VL - 164

SP - 25

EP - 40

JO - Oecologia

JF - Oecologia

SN - 0029-8549

IS - 1

ER -

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