Abstract:

This study aimed to quantify the carbon stock contributed by reef-building oysters in the Dashentang oyster reef ecosystem, Tianjin. For the first time, the carbon stock of Crassostrea gigas (C. gigas) was evaluated using an inventory-based approach. Stepwise regression analysis was applied to examine the relationship between oyster carbon density and water quality parameters, thereby identifying the environmental factors that influence carbon density. In addition, a regression model was developed to predict the shell dry weight from shell height. Results revealed that in June and October 2024, the average total carbon density of C. gigas in the Dashentang Area of Tianjin was 34.37 t C/hm² and 25.81 t C/hm², respectively, corresponding to total carbon stocks of (6945.40±422.88) t C and (5214.01±458.33) t C, indicating higher carbon stock in June than in October. Water temperature and turbidity accounted for 77.6% of the total carbon density variability, thereby indicating that water temperature and turbidity influenced the carbon density in the study area. Furthermore, the goodness of fit of the power function ($ \ln y= $$ \ln0.002+2.126\ \ln x $) regression model for the shell dry weight and shell height demonstrated excellent fit (R²=0.958), confirming that shell dry weight can be reliably estimated from shell height for practical applications.

Key words: Dashentang, Tianjin, oyster reef ecosystem, Crassostrea gigas, carbon stock, regression analysis