摘要
仅在过去四十年,人类通过陆源输入向海洋排放的氮量就增加了一倍。氮输入量的增加导致了海洋严重的人为富营养化,造成海水透明度下降、耗氧量增加甚至威胁到人类健康和经济发展。硝化反应将NH4﹢经NO2﹣氧化为NO3﹣,是氮循环中连接生物固氮和厌氧反硝化作用的重要环节;同时还会消耗水体和沉积物中大量的氧气,导致陆架海域低氧甚至缺氧区的形成。反硝化作用把NO2﹣氧化为NO3﹣转化为气态的N2O或N2,对于缓解海水的富营养化、估算氮循环通量研究全球气候变化都具有重要的意义。因此,硝化和反硝化过程及其对环境因子变化(如气候变暖、难降解有机物污染及氮富营养化)的响应成为海洋环境科学中的一个重要的研究课题。
已有的研究表明,温度、盐度、溶解氧和NH4﹢含量等环境变量是影响硝化和反硝化速率的主要环境因子,而通过氨单加氧酶(amo)实现NH4﹢至NO2﹣转化的自养氨氧化细菌活性是硝化反应的限速因子。以DNA序列技术为基础的分子生物学实验手段可以实现对硝化细菌的特异性染色或扩增,进而不经过培养就能够对硝化细菌的数量和群落结构进行分析。反硝化细菌群落较复杂,难以采用分子生物学技术,但以传统的培养方法仍可以估算其数量及分布的趋势。尽管如此,关于硝化和反硝化过程、环境因子及细菌群落特征关系的系统性研究还极少。本论文选取长江口、黄河口以及英国的Colne河口区作为研究海域,测定了表层沉积物的硝化和反硝化速率,硝化和反硝化细菌数量的分布;与环境因子的相关性进行分析,讨论了硝化和反硝化作用的主要控制因子,为探讨环境因子的变化对硝化和反硝化过程的影响提供了理论依据;通过计算硝化和反硝化过程产生的N、O通量说明其重要的环境效应。
长江口夏初的硝化反应速率范围为100.3~514.3μmol·m-2·h-1,自近岸向远海逐渐降低;反硝化速率的范围是101.3~731.9μmol·m-2·h-1,以长江口外和杭州湾口的两个高值区为中心向外逐渐降低;硝化和反硝化过程有较高的耦合性,反硝化过程以与硝化作用耦合的反硝化作用为主。硝化细菌数量(以湿重计)在(1.87~3.53)×105cells·g-1之间,并表现出一定的耐盐性,反硝化细菌数量为(3.9×105~110.0×105) cells·g-1。在硝化细菌多样性相似度60%的高盐度海区硝化细菌数量对硝化速率的影响率高达87.7%,是影响硝化反应速率的主要因素。反硝化速率的决定因素是反硝化细菌数量,同时受环境中盐度、溶解氧和氨氮含量的显著影响。在该海域每天硝化作用转化的无机氮通量为4.68×105 kg,消耗的DO通量为6.07×104 mol,反硝化作用产生的氮通量约为8.19×105 kg,表明硝化作用是影响长江口海域夏初DIN形态分布和底层DO分布的主要因素之一。
黄河口海域硝化速率的范围是(30.3~76.5)μmol·m-2·h-1,在黄河口前方海域较高,向渤海方向和山东半岛方向逐渐降低。黄河口海域反硝化速率的范围是(3.49~19.09)μmol·m-2·h-1,在黄河口的前方海域和靠近莱州湾的海域形成一高值区,从两个高值区向四周海域呈放射状减少,在向渤海延伸的一端形成最低值区。硝化和反硝化过程无显著相关性。黄河口研究海域的硝化细菌数量范围是(1.87±0.19~3.53±0.34)×104 cells·g-1(湿重),站位间差异性不显著,反硝化细菌数量范围是(1.2~11.0)×103 cells·g-1。黄河口研究海域的硝化反应速率受多个环境因子的综合影响,硝化细菌数量的影响作用最大为72.9%,反硝化速率的主要影响因子是反硝化细菌数量,两者呈显著正相关关系,研究海区内硝化作用产生的氮和氧通量分别为1.65×105kg·N·d-1和1.37×104mol·d-1,反硝化作用去除的氮通量为4.10×104kg·N·d-1。
英国Colne河口海域冬季反硝化速率范围为(23.99±8.85~154.74±46.45)μmol·m-2·h-1,上游站位的速率值要明显高于入海口,其中耦合的反硝化作用占52.98~96.10%。夏季潜在硝化速率范围为3.33~8.89μmol·m-2·h-1,与反硝化速率及耦合的反硝化速率没有显著相关性,硝化细菌数量范围为(1.24~16.92)×106 cells·g-1,Hythe和Alresford站位的硝化细菌数量逐月递增,而Brightling站位的硝化细菌数量变化不明显,硝化细菌的种类主要属于β-和γ-Proteobacterium,其中β- Proteobacterium硝化细菌主要存在Nitrosomonas spp.和Nitrosospira spp.两属。在多样性相似度60%时,硝化细菌数量与潜在硝化反应速率呈现一定的相关性。
Human activity has increased the flux of nitrogen from land to the oceans by twofold globally over the past 40 years. The increasing loads of nitrogen have caused serious anthropogenic eutrophication which would contributes to series negative effects such as decreased water transparency, increased oxygen demand and even a threat to both human health and economy. As a critical link in nitrogen cycle, nitrification, the oxidation of ammonia to nitrate via nitrite, is thought to connect biological N fixation and anaerobic N losses. Moreover DO in the water column and the sediments can be depleted by intense nitrification, leading to the formation of hypoxic zone at continental shelves. Denitrification, the conversion of NO3﹣or NO2﹣into gaseous forms either N2O or N2, is of both fundamental and practical contribution to calculate nitrogen cycle flux, control nitrogen eutrophication and study global climate change. Thus there is considerable concern on the nitrification and denitrification process influenced by pollution, for example, global warming, contamination with recalcitrant organic compounds, and nitrogen overloading.
Several environmental variables have been demonstrated to influence nitrification and denitrification including temperature, oxygen, ammonium, salinity and so on. Nitrification is always rate limited in most ecosystems by activities of autotrophic ammonia-oxidizing bacteria (AOB) that are responsible for the oxidation of ammonia to nitrite by the enzyme ammonia monooxygenase (amo). Recent advances in DNA-based techniques for direct whole microbial community analysis have made it possible to study AOB communities without culturing by using probes or PCR primers target amoA, a functional gene coding for the active subunit of amo. Although it’s difficult to use culcure-independent methodologies for a wide range of taxonomic groups, denitrifier quantity could be estimated by the application of MPN. However, as yet few special and systematical studies have reported on relationships ?among environmental variables, characteristic bacteria community and nitrification or denitrification process.
The present study was explored the processes of nitrification and denitrification occurring in surface sediment at the Changjiang River, Yellow River and Colne River Estuaries. The aim is to investigate: (i) the rates of nitrification and denitrification; (ii) distributions of nitrifier and dinitrifier; (iii) the role of bacteria in and the influence of environmental factors such as temperature and salinity on the nitrification and denitrification processes; (iv) the environmental effects of nitrification and denitrification through calculating the nitrogen and oxygen flux.
For Changjiang River Estuary, the nitrification rates ranged from 100.3μmol·m-2·h-1 to 514.3μmol·m-2·h-1 which decreased from nearshore to offshore. The denitrification rates were in the range between 101.3μmol·m-2·h-1 and 731.9μmol·m-2·h-1 and had a decreased gradient from nearshore to offshore sediment with two high value regions located at the mouth of Yangtze River and Hangzhou Bay respectively. The nitrifying bacteria were counted as (1.87-3.53)×105 cells·(gram wet weight) -1 and exhibited salt tolerance to some extent. The nitrifier quantity was a main factor to effect nitrification rates at high-salinity sea area, with an influence ratio of 87.7%, at a level of 60% biodiversity similarity. The quantities of denitrifying bacteria ranged from 3.9×105 cells·(gww)-1 to 110.0×105 cells·(gww)-1, which were significant correlated with the denitrification rate, indicated that denitrifying bacteria was the determining factor. The denitrification rate was also primarily affected by the salinity and the concentrations of DO and ammonia. Fluxes of transformed nitrogen and consumed oxygen by nitrification process were 4.68×105 kg·N and 6.07×104mol per day respectively, meanwhile the nitrogen flux by the denitrification process was calculated to be 8.19×105 kg·N·d-1, suggesting that nitrification and denitrification would be important factors for the distribution of DIN species and DO at bottom water in early summer.
For Yellow Riever Estuary, the range of the nitrification rates was between 30.3μmol·m-2·h-1 and 76.5μmol·m-2·h-1, with higher value at the mouth of Yellow River and decreasing gradually to adjacent area of Bohai Sea and Shandong Peninsula. In addition, denitrification rates ranged from 3.49μmol·m-2·h-1 to 19.09μmol·m-2·h-1. The distribution of denitrification rates showed radial decrease from two higher-value areas at the mouth of Yellow River and adjacent sea area of the Laizhou Bay to the lower-value area at the Bohai Sea extended area. Nitrification and denitrification processes have no significant correlation. The numbers of the nitrifier ranged from (1.87±0.19)×104 cells·(gww)-1 to (3.53±0.34)×104 cells·(gww)-1, meanwhile the numbers of denitrifier were counted as (1.2-11.0)×103 cells·(gww)-1, which had no significant differences among sampling sites. Nitrification was influences by many environment factors, and the most impact factor is nitrifier quantities with influence ratio of 72.9%. The remarkable correlation coefficient indicated that denitrifier quantity was the most impact factor for denitrification. The fluxes of Nitrogen and Oxygen generated by nitrification process were 1.65×105 kg·N·d-1 and 1.37×104 mol·d-1, respectively. And the flux removed by denitrification process was 4.10×104 kg·N·d-1.
For Colne River Estuary in UK, denitrification rate were measured between (23.99±8.85)μmol·m-2·h-1 and (154.74±46.45)μmol·m-2·h-1 in winter, with the values of upriver stations much higher than that of the river mouth. The percentages of coupled nitrification-denitrification in the total denitrification were from 52.98% to 96.10%. The range of potential nitrification rate was between 3.33μmol·m-2·h-1 and 8.89μmol·m-2·h-1 which has no significant correlation with denitrification rate or coupled nitrification-denitrification. The nitrifier quantities ranged from 1.24×106 cells·(gww)-1 to 16.92×106 cells·(gww)-1, with increasing monthly at Hythe and Alresford sites and varying unobviously at Brightlingsea site. Nitrifier populations were dominated byβ- andγ-Proteobacterium, while members of theβ-Proteobacterium were mainly belonging to the Nitrosomonas and Nitrosospira. Regression analysis showed that there was some correlation between nitrifier quantity and potential nitrificant rate at a level of 60% biodiversity similarity.
引文
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中国海洋环境保护:现状和对策,国家环保总局/水环境保护/海洋环境,http://www.zhb.gov.cn