© 2005 Heron Publishing—Victoria, Canada
Variability in net ecosystem exchange from hourly to inter-annual time scales at adjacent pine and hardwood forests: a wavelet
analysis
Paul C. Stoy (1, 2, 3), Gabriel G. Katul (1), Mario B. S. Siqueira (1), Jehn-Yih Juang (1), Heather R. McCarthy (1), Hyun-Seok Kim (1), A. Christopher Oishi (1, 3) and Ram Oren (1)
1. Nicholas School of the Environment and Earth Sciences, Box 90328, Duke University, Durham, NC 27708-0328, USA / 2. Corresponding author (pcs3@duke.edu) / 3. University Program in Ecology, Duke University, Durham, NC, 27708, USA / Received August 6, 2004; accepted February 6, 2005; published online May 2, 2005
Summary
Orthonormal wavelet transformation (OWT) is a computationally efficient technique for quantifying underlying frequencies in
nonstationary and gap-infested time series, such as eddy-covariance-measured net ecosystem exchange of CO2 (NEE). We employed OWT to analyze the frequency characteristics of synchronously measured and modeled NEE at adjacent pine
(PP) and hardwood (HW) ecosystems. Wavelet cospectral analysis showed that NEE at PP was more correlated to light and vapor
pressure deficit at the daily time scale, and NEE at HW was more correlated to leaf area index (LAI) and temperature, especially
soil temperature, at seasonal time scales. Models were required to disentangle the impacts of environmental drivers on the
components of NEE, ecosystem carbon assimilation (Ac) and ecosystem respiration (RE). Sensitivity analyses revealed that using air temperature rather than soil temperature in RE models improved the modeled wavelet spectral frequency response on time scales longer than 1 day at both ecosystems. Including
LAI improved RE model fit on seasonal time scales at HW, and incorporating parameter variability improved the RE model response at annual time scales at both ecosystems. Resolving variability in canopy conductance, rather than leaf-internal
CO2, was more important for modeling Ac at both ecosystems. The PP ecosystem was more sensitive to hydrologic variables that regulate canopy conductance: vapor pressure
deficit on weekly time scales and soil moisture on seasonal to interannual time scales. The HW ecosystem was sensitive to
water limitation on weekly time scales. A combination of intrinsic drought sensitivity and non-conservative water use at PP
was the basis for this response. At both ecosystems, incorporating variability in LAI was required for an accurate spectral
representation of modeled NEE. However, nonlinearities imposed by canopy light attenuation were of little importance to spectral
fit. The OWT revealed similarities and differences in the scale-wise control of NEE by vegetation with implications for model
simplification and improvement.
Keywords:
eddy covariance, hardwood forest, multiscale methods, net ecosystem exchange, orthonormal wavelet transformation, Pinus taeda, process-based models, southeastern USA.
