Effect of thinning intensity on the stem CO2 efflux of Larix principis-rupprechtii Mayr

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Abstract
Background: Stem CO2 efflux (ES) plays a critical role in the carbon budget of forest ecosystems. Thinning is a core practice for sustainable management of plantations. It is therefore necessary and urgent to study the effect and mechanism of thinning intensity (TI) on ES. Methods: In this study, five TIs were applied in Larix principis-rupprechtii Mayr 21-, 25-, and 41-year-old stands in North China in 2010. Portable infrared gas analyzer (Li-8100 A) was used to measure ES and its association with environmental factors at monthly intervals from May to October in 2013 to 2015. In addition, nutrients, wood structure and nonstructural carbon (NSC) data were measured in August 2016. Results: The results show that ES increased with increasing TI. The maximum ES values occurred at a TI of 35 % (3.29, 4.57 and 2.98 µmol∙m-2∙s-1) and were 1.54-, 1.94- and 2.89-fold greater than the minimum ES value in the CK stands (2.14, 2.35 and 1.03 µmol∙m-2∙s-1) in July for the 21-, 25- and 41-year-old forests, respectively. The ES of the trees in low-density stands was more sensitive to temperature than that of the trees in high-density stands. Soluble sugars (SS) and temperature are the main factors affecting ES. When the stand density is low enough as 41-year-old L. principis-rupprechtii forests with TI 35 %, bark thickness (BT) and humidity should be considered in addition to air temperature (Ta), wood temperature (Tw), sapwood width (SW), nitrogen concentration (N) and SS in the evaluation of ES. If a change in stand density is ignored, the CO2 released from individual 21-, 25- and 41-year-old trees could be underestimated by 168.89 %, 101.94 % and 200.49 %, respectively. CO2 release was estimated based on the stem equation in combination with the factors influencing ES for reference. Conclusions: We suggest that it is not sufficient to conventional models which quantify ES only by temperature and that incorporating the associated drivers (e.g. density, SS, SW and N) based on stand density into conventional models can improve the accuracy of ES estimates.
Funding Information
  • National Natural Science Foundation of China (31870387)

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