Abstract

Bacterial metabolism plays a dual role [bacterial production (BP) and bacterial respiration (BR)] in the aquatic ecosystem and potentially leads to hypoxia in the coastal eutrophic area. Bacterial growth efficiency (BGE) is an important index showing the contribution of bacterial metabolism to marine biological production and carbon budget in the pelagic ecosystem. In this study, the spatial and seasonal variety as well as diurnal variation dynamics of BGE and associated ecological characteristics were investigated in a partly eutrophicated subtropical bay (the Daya Bay) located in the northern South China Sea. Furthermore, the relationship between bacterial metabolism and potential hypoxia event was analyzed. The average BGE was 0.14 and 0.22 in summer and winter, respectively, which was lower than the mean value ever reported in other coastal and estuarine waters. The diurnal variations of BGE and BP were widely fluctuated in the Daya Bay, with approximately 3-8 fold variation of BP and 2-3 fold variation of BR in different seasons, suggesting the importance of short-term ecological dynamics on evaluating the long-term ecological processes in the coastal waters. BR was the predominant contributor to the bacterial carbon demand; however, the variation of BGE was controlled by BP in both seasons. BGE was always high in the near-shore waters with higher eutrophic level and more active BP and BR. The bacterial metabolism could deplete dissolved oxygen (DO) in the Daya bay within about 9 days when the water body was enclosed and photosynthesis was prohibited. Therefore, low DO concentration and potential hypoxia was more likely to be found in the near-shore waters of the Daya Bay in summer, since the water was stratified and enclosed with poor water exchange capacity in this area. While in winter, hypoxia seldom occurred due to vertical mixing throughout the water column. Further biological-physical coupling research is recommended to find out the detailed formation mechanism of hypoxia in the bay, and to predict the potential hypoxia events and their environmental impacts in the future.

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