Biometric and Eddy Covariance Methods for Examining the Carbon Balance of a Larix principis-rupprechtii Forest in the Qinling Mountains, China

Abstract

The carbon balance of forests is controlled by many component processes of carbon acquisition and carbon loss and depends on the age of vegetation, soils, species composition, and the local climate. Thus, examining the carbon balance of different forests around the world is necessary to understand the global carbon balance. Nevertheless, the available information on the carbon balance of Larix principis-rupprechtii forests in the Qinling Mountains remains considerably limited. We provide the first set of results (2010–2013) from a long-term project measuring forest-atmosphere exchanges of CO2 at the Qinling National Forest Ecosystem Research Station (QNFERS), and compare the net ecosystem exchange (NEE) based on biometric measurements with those observed via the eddy covariance method. We also compare the total ecosystem respiration via scaled-up chamber and eddy covariance measurements. The net primary productivity (NPP) was 817.16 ± 81.48 g·C·m−2·y−1, of which ΔBliving and Dtotal accounted for 77.7%, and 22.3%, respectively. Total ecosystem respiration was 814.47 ± 64.22 g·C·m−2·y−1, and cumulative annual soil respiration, coarse woody debris respiration, stem respiration, and leaf respiration were 715.47 ± 28.48, 15.41 ± 1.72, 35.28 ± 4.78, and 48.31 ± 5.24 g·C·m−2·y−1, respectively, accounting for 87.85%, 1.89%, 4.33%, and 5.93% of the total ecosystem respiration. A comparison between ecosystem respiration from chamber measurements and that from eddy covariance measurements showed a strong linear correlation between the two methods (R2 = 0.93). The NEE of CO2 between forests and the atmosphere measured by eddy covariance was −288.33 ± 25.26 g·C·m−2·y−1, which revealed a carbon sink in the L. principis-rupprechtii forest. This number was 14% higher than the result from the biometric measurements (−336.71 ± 25.15 g·C·m−2·y−1). The study findings provided a cross-validation of the CO2 exchange measured via biometric and eddy covariance, which are beneficial for obtaining the true ecosystem fluxes, and more accurately evaluating carbon budgets.

Keywords

• carbon balance
• Qinling Mountains
• biomass regression model
• eddy covariance
• net primary productivity
• net ecosystem exchange