Li Zixuan, Zhou Hantao, Zheng Minfang, Chen Mengya, Zhang Run, Chen Min
College of Ocean and Earth Sciences, Xiamen University, Xiamen, 361102, China.
College of Ocean and Earth Sciences, Xiamen University, Xiamen, 361102, China.
Mar Environ Res. 2025 May;207:107060. doi: 10.1016/j.marenvres.2025.107060. Epub 2025 Mar 5.
Increased nutrient loading in coastal waters poses a threat to marine ecosystems. To develop effective management strategies, a clearer understanding of nitrogen cycle dynamics for the main species is crucial for understudied urbanized areas. By employing stable isotopes of nitrate (δN and δO) and the rarely reported nitrite isotopes, we found a decoupling between physical mixing and microbial transformative processes in the Xiamen Bay. During the dry season, dominated by endmember mixing, the SIAR (Stable Isotope Analysis in R) model identifies manure (50%) as the primary nitrate source, followed by fertilizer, sewage, and rainfall. Microbial processes govern nitrogen cycling during the wet season, as evidenced by the relatively low ε value (∼2.4‰) using the Rayleigh fractionation model. This likely reflects distinct environmental conditions in coastal waters compared to the open ocean, such as limited light and iron availability. Nitrite isotope ratios implicate ammonia oxidation and nitrite oxidation as the primary drivers of nitrite variability during the wet season. This suggests that seasonal nitrite accumulation in summer may result from a decoupling of these processes in response to temperature fluctuations. Theoretical calculations of the nitrite reservoir, based on key parameters like temperature and substrate concentration, further support this argument. Our findings highlight the highly dynamic nature of nitrate and nitrite cycling in coastal environments. This underscores the need for further research in these understudied coastal systems, particularly in the context of intensifying human activities and climate change.
沿海水域营养物质负荷增加对海洋生态系统构成威胁。为制定有效的管理策略,对于研究较少的城市化地区而言,更清晰地了解主要物种的氮循环动态至关重要。通过使用硝酸盐(δN和δO)的稳定同位素以及鲜少报道的亚硝酸盐同位素,我们发现厦门湾的物理混合与微生物转化过程之间存在解耦现象。在旱季,以端元混合为主,R语言中的稳定同位素分析(SIAR)模型确定粪便(50%)是主要的硝酸盐来源,其次是化肥、污水和降雨。微生物过程在雨季控制着氮循环,使用瑞利分馏模型得到的相对较低的ε值(约2.4‰)证明了这一点。这可能反映了与开阔海洋相比沿海水域独特的环境条件,如光照和铁的可用性有限。亚硝酸盐同位素比值表明氨氧化和亚硝酸盐氧化是雨季亚硝酸盐变化的主要驱动因素。这表明夏季亚硝酸盐的季节性积累可能是这些过程因温度波动而解耦的结果。基于温度和底物浓度等关键参数对亚硝酸盐库的理论计算进一步支持了这一观点。我们的研究结果突出了沿海环境中硝酸盐和亚硝酸盐循环的高度动态性。这强调了在这些研究较少的沿海系统中进行进一步研究的必要性,特别是在人类活动加剧和气候变化的背景下。