Abstract:

Under the national strategy of "carbon peak and carbon neutrality", systematic assessment of the carbon sequestration potential of tea plants holds significant importance for realizing the value of ecological products in tea plantations. There is a huge difference in the growth rate of young tea plants under 2 years old and mature tea plants over 3 years old. By collecting the relevant research literature and fieldwork data of tea plant growth in domestic and international tea plantations from 1950 to 2023, this study constructed the model of tea plant biomass and carbon stock growth dynamics based on aboveground and belowground biomass data of young tea plants (0−2y) and mature tea plants (3−25y) to calculate and evaluate the carbon sequestration capacity of tea plants. The results showed that: (1) age−specific belowground biomass models of tea plants were established. Nonlinear model for mature tea plants (B_b=0.013B_a²−0.087B_a+3.269, R²=0.959, P<0.001) and linear model for young tea plants (B_b=0.665B_a−0.217, R²=0.933, P<0.001) were constructed based on the relationship between aboveground biomass (B_a) and belowground biomass(B_b). (2) The models for accounting tea plants carbon stock based on tea plants aboveground biomass were formed. Using the internationally recognized plant carbon conversion factor (0.5) provided by the Intergovernmental Panel on Climate Change(IPCC), carbon stock models for mature tea plants (C=0.006B_a²+0.492B_a+1.536, R²=0.995, P<0.001) and young tea plants(C=0.833B_a−0.108, R²=0.989, P<0.001) were developed based on total biomass data. (3) The tea plant carbon stock estimation model demonstrated simplicity and accuracy. Traditional methods relied on destructive whole−plant excavation to measure biomass, whereas the non−destructive model, based solely on aboveground biomass, enhanced both the efficiency and precision of carbon stock quantification. This approach offers distinct advantages for carbon stock quantification in tea plantations.

Key words: Carbon sink, Biomass, Carbon stock, Estimation model, Tea tree