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An evaluation of empirical regression models for predicting temporal variations in soil respiration in a cool-temperate deciduous broad-leaved forest

Author(s): Na-Yeon Lee

Journal: Journal of Ecology and Field Biology
ISSN 1975-020X

Volume: 33;
Issue: 2;
Start page: 165;
Date: 2010;
Original page

Keywords: empirical regression model | soil respiration | soil temperature | soil water content | temporal variation | validation

Soil respiration (RS) is a critical component of the annual carbon balance of forests, but few studies thus far haveattempted to evaluate empirical regression models in RS. The principal objectives of this study were to evaluate therelationship between RS rates and soil temperature (ST) and soil water content (SWC) in soil from a cool-temperatedeciduous broad-leaved forest, and to evaluate empirical regression models for the prediction of RS using ST and SWC.We have been measuring RS, using an open-flow gas-exchange system with an infrared gas analyzer during the snowfreeseason from 1999 to 2001 at the Takayama Forest, Japan. To evaluate the empirical regression models used for theprediction of RS, we compared a simple exponential regression (flux = aebt: Eq. [1]) and two polynomial multiple-regressionmodels (flux = aebt × (θν – c) × (d – θν)f: Eq. [2] and flux = aebt × (1 – (1 – (θν/c))2): Eq. [3]) that included two variables (ST:t and SWC: θν) and that utilized hourly data for RS. In general, daily mean RS rates were positively well-correlated withST, but no significant correlations were observed with any significant frequency between the ST and RS rates on periodsof a day based on the hourly RS data. Eq. (2) has many more site-specific parameters than Eq. (3) and resulted in somesignificant underestimation. The empirical regression, Eq. (3) was best explained by temporal variations, as it provideda more unbiased fit to the data compared to Eq. (2). The Eq. (3) (ST × SWC function) also increased the predictive abilityas compared to Eq. (1) (only ST exponential function), increasing the R2 from 0.71 to 0.78.
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