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The seasonal temperature dependency of photosynthesis and respiration in two deciduous forests
Author(s) -
Jarvis Andrew J.,
Stauch Vanessa J.,
Schulz Karsten,
Young Peter C.
Publication year - 2004
Publication title -
global change biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.146
H-Index - 255
eISSN - 1365-2486
pISSN - 1354-1013
DOI - 10.1111/j.1529-8817.2003.00743.x
Subject(s) - eddy covariance , environmental science , flux (metallurgy) , calibration , series (stratigraphy) , atmospheric sciences , covariance , ecosystem respiration , deciduous , climatology , ecosystem , mathematics , ecology , statistics , physics , chemistry , biology , paleontology , organic chemistry , geology
Novel nonstationary and nonlinear dynamic time series analysis tools are applied to multiyear eddy covariance CO 2 flux and micrometeorological data from the Harvard Forest and University of Michigan Biological Station field study sites. Firstly, the utility of these tools for partitioning the gross photosynthesis and bulk respiration signals within these series is demonstrated when employed within a simple model framework. This same framework offers a promising new method for gap filling missing CO 2 flux data. Analysing the dominant seasonal components extracted from the CO 2 flux data using these tools, models are inferred for daily gross photosynthesis and bulk respiration. Despite their simplicity, these models fit the data well and yet are characterized by well‐defined parameter estimates when the models are optimized against calibration data. Predictive validation of the models also demonstrates faithful forecasts of annual net cumulative CO 2 fluxes for these sites.