Vertical gradients and seasonal variations in the stem CO2 efflux of Larix principis-rupprechtii Mayr

Abstract

Stem CO2 efflux (ES) plays an essential role in the carbon balance of forest ecosystems. Therefore, it is necessary to study the vertical and seasonal variations in ES in forests with different ages, especially in response to factors associated with temperature, nutrients and wood structure. In this study, we investigated ES and its association with temperature factors using a carbon flux system (Li-8100A) at monthly intervals during the growing season (May to September) and the non-growing season (October) from 2013 to 2015. In addition, we collected data on nutrients and wood structure in August 2016 from 16- (young), 25- (immature), and 41-year-old (mature) Larix principis-rupprechtii Mayr stands in North China. Our analysis showed that the ES values at stem positions near the crown and the root system were generally higher than those in the middle and that the minimum ES values in July occurred at 2.0 m (3.61 μmol m−2 s−1), 3.0 m (2.42 μmol m−2 s−1), and 5.0 m (4.03 μmol m−2 s−1) in the young, immature, and mature forests, respectively. Air temperature and wood temperature influenced the vertical variation in ES, as did stem nitrogen concentration and sapwood width. Compared to the method that uses the vertical ES gradient to determine tree-scale CO2 effluxes for 16-, 25- and 41-year-old L. principis-rupprechtii forests, the method that uses the ES value at the 1.3-m stem position underestimated the CO2 effluxes by 5%, 6%, and 24%, respectively. The ES and Q10 models for each stem position for the three forest ages in this study can be used to accurately estimate tree-scale CO2 effluxes. These results not only clarified the relationships between the vertical variation in ES and temperature, nutrient content and wood structure, but also revealed the likely response mechanisms of ES to these factors. Methodologically, incorporating the vertical variation in ES and the associated drivers into conventional models would improve the accuracy of annual ES estimates.