Causes of interannual variability in ecosystem-atmosphere CO2 exchange in a northern Wisconsin forest using a Bayesian model calibration

Daniel M. Ricciuto, Martha P. Butler, Kenneth J. Davis, Bruce D. Cook, Peter S. Bakwin, Arlyn Andrews, Ronald M. Teclaw

Research output: Contribution to journalArticle

39 Scopus citations

Abstract

Variability in fluxes of CO2 observed at the WLEF tall tower in northern Wisconsin was analyzed for the years 1997-2004. During this time, the WLEF region was a source of CO2 to the atmosphere averaging 120 g C m-2 year-1, with a range of interannual variability of 140 g C m-2 year-1. Random uncertainty in annual sums of net ecosystem exchange (NEE) due to turbulent variability and gap-filling was estimated to be 15-20 g C m-2 year-1. Although magnitudes of NEE sums were affected systematically by the choice of friction velocity (u*) threshold, this choice had little effect on interannual variability of annual sums. The WLEF region was, on average, a source of carbon from 1997 to 2004 regardless of the u* threshold applied. Interannually, daytime NEE sums varied more than nighttime NEE sums, and spring and summer NEE sums varied more than autumn and winter NEE sums. Interannual variations in seasonal sums of daytime, nighttime and total NEE were often strongly correlated with changes in soil moisture and soil temperature. Standard nonlinear gap-filling regression models of respiration and gross ecosystem productivity were extended to incorporate the effects of soil moisture and phenology and combined into a single model of NEE. The Markov Chain Monte Carlo (MCMC) data assimilation technique was performed using observed WLEF NEE to derive full probability density functions (PDFs) of time-invariant model parameters. Prior values had little effect on posterior parameter PDFs, but significant differences in parameter PDFs occurred depending on whether daytime NEE, nighttime NEE, or total NEE data were used. This simple model was moderately successful in producing statistically significant correlations with interannual variations in annual and growing season NEE sums, but was generally unsuccessful in spring and autumn. In all cases, the model underestimated the degree of variability in NEE sums.

Original languageEnglish (US)
Pages (from-to)309-327
Number of pages19
JournalAgricultural and Forest Meteorology
Volume148
Issue number2
DOIs
StatePublished - Feb 13 2008

All Science Journal Classification (ASJC) codes

  • Forestry
  • Global and Planetary Change
  • Agronomy and Crop Science
  • Atmospheric Science

Fingerprint Dive into the research topics of 'Causes of interannual variability in ecosystem-atmosphere CO<sub>2</sub> exchange in a northern Wisconsin forest using a Bayesian model calibration'. Together they form a unique fingerprint.

  • Cite this