Denitrification Process and Denitrifying Bacterial Community Structure in Created Wetlands at Different Scales

Abstract

Denitrification is one of the main nitrogen removal processes in wetlands. However, a complex set of environmental controlling factors for denitrification leads to an extremely variable denitrification rates, complicating our understanding of the denitrification process. In this study, we assess the temporal patterns of denitrification rates as well as the spatial patterns with relation to the different hydrology and vegetation in two created flow-through wetlands in Ohio, USA. We measured denitrification rates in different sampling areas to include the inflow, middle, and outflow areas along the longitudinal gradient, and deepwater and shallow water (SR) edge sites with different water depths. The denitrification rates exhibited high temporal and spatial patterns, ranging from 34 to 660 ug N m-2 h-1. Denitrification rates in all sampling sites had a clear seasonal patterns with higher rates in spring and summer and lower in winter. Denitrification rates were significantly higher in the deepwater areas than in the shallow water areas. In vegetated areas, denitrification rates were slightly higher than non-vegetated areas, but it was not significant, possibly due to high connectivity of water flow between vegetated and open areas. These results suggest that temperature and nitrate concentrations are the primary factors determining temporal variation of denitrification while vegetation and water level regulate the biogeochemical characteristics such as carbon, nitrogen, and oxygen availability that lead to spatial variability of denitrification rates in wetlands. Denitrifying bacterial community structure was significantly affected by vegetation communities, resulting in significant differences between open water and vegetated areas. Water level changes did not appear to have a strong impact on the community structure of denitrifiers. This study implies the prevailing importance of substrate and chemical properties on microbial physiology over microbial community changes in determining denitrification rates in wetlands.;Water level drawdown caused by climate change represents a dramatic disturbance to wetland ecosystems. It is considered as a physiological water stress for microbial communities, possibly resulting in a decrease in microbial activity. At the same time, drying enhances oxygen availability and activates aerobic microbial processes. Therefore, the responses of microbial communities to drying could be complicated. Denitrifiers, which are facultative bacteria, are of great importance because denitrification is the main nitrogen removal process as well as greenhouse gas source. To better understand the response of denitrifying bacterial communities in terms of their function and structure to water level drawdown in wetlands, I investigated the denitrification rates and denitrifying bacterial community structures using an acetylene blocking method and terminal-restriction fragment length polymorphism (T-RFLP), respectively. The quantities of denitrifying bacteria were also determined by real-time PCR (RT-PCR). Redox potential and available NH4+ contents in sediment increased as the water table was lowered in experimental wetlands. Denitrification rates increased from an average of 223 (ug m-2 h-1) before the drying period to an average of 1249 (ug m-2 h-1) during the early period of the drying. NO3- contents in sediment showed a decreasing trend while denitrification increased. Denitrifying bacterial community structure based on T-RFs profile showed significant change by water level drawdown. The quantities of denitrifiers decreased while the diversity of denitrifiers increased with water level drawdown. According to the result of canonical correspondence analysis (CCA), this community change appeared to be related with two factors, primarily: NH4+ contents and redox potential. This result suggests that the function and structure of denitrifiers in a wetland would be strongly affected by the changes in nutrient availability and physicochemical properties due to water level drawdown.;습지는 다양한 생지화학적 기작이 진행되고, 수질정화, 야생동물 서식지 제공하는 등 여러 기능을 수행하는 것으로 알려져 있다. 그 중 습지의 생지화학적 기작을 통한 수질정화 기능은 환경공학 분야에서 각광받고 있는 기능 중 하나로 습지의 복원, 건설이 활발하게 진행되고 있다. 탈질기작은 탈질 미생물에 의해 혐기상태에서 진행되며 수체의 무기질소를 기체상태의 질소로 변형, 제거하여, 수체에서 질소를 영구적으로 제거할 수 있다는 장점을 갖고 있다. 본 연구는 탈질기작 효율과 이에 관여하는 탈질 미생물의 군집구조가 습지 내에서 어떠한 패턴을 보이며, 조절인자가 무엇인지 밝히는 것을 목적으로 진행하였다. 실험은 서로 다른 스케일의 두 습지에서 진행하였는데, 첫번째 실험은 3, 4 장과 6장의 내용으로 2004년 건설된 메조코즘에서 진행되었으며, 두번째 실험은 생태계 수준의 Olentangy River Wetland Research Park (ORWRP) 습지에서 2008년 수행되었다. 연구결과, 탈질기작은 시공간적 패턴을 나타내며, 온도와 수체의 질산성 질소의 농도, 용존유기탄소의 농도 등 환경인자와 유의한 상관관계를 보이는 것으로 나타났다. 메조코즘의 경우, 탈질기작은 특히, 질산성 질소의 농도보다는 온도와 용존유기탄소의 농도와 유의한 상관관계를 보이는 대신, 생태계 스케일의 습지에서는 오히려 수체의 질산성 질소의 농도와 큰 상관관계를 나타내었다. 탈질 미생물 군집구조 분석결과, 군집구조는 습지의 수위변화에 따른 산화환원조건의 차이, 습지 내 무기질소의 농도의 영향을 받는 것으로 나타났다. 또한 건설 이후 운용이 장기간 진행되어 온 습지에 비해 새로 건설된 인공습지의 경우에 탈질 미생물의 군집구조가 시간에 따라 크게 변화하는 것으로 나타났다. 따라서, 습지의 탈질기작과 탈질 미생물 군집구조는 습지의 이화학적 요인에 의해 영향을 받는 것으로 판단된다. 하지만, 분자미생물학적 수준의 미생물 군집구조의 변화는 생태기작 수준의 탈질기능과 유의한 연관성은 본 연구 결과 나타나지 않았다.;Denitrification and its regulating factors are of great importance because denitrification is the main removal process of nitrogen in aquatic ecosystems. In addition, the by-product of denitrification is nitrous oxide is a much stronger greenhouse gas than carbon dioxide. However, estimation of denitrification rates in wetlands has difficulty with uncertainty mainly due to high spatio-temporal variations in the rates and complex regulating factors. It hampers development of mechanistic models for denitrification. As such, most of denitrification models are empirical and characterized by low predictability and numerous assumptions. In this study, we tested artificial neural networks (ANNs) as an alternative to classic empirical models for simulating denitrification rates in wetlands. I applied three different models - ANNs, multiple linear regression (MLR) with two different methods, and simplified mechanistic models - to denitrification rates determined in mesocosm-scale constructed wetlands for 2 years. MLR and simplified mechanistic models resulted in lower determination coefficients (R2) and they were not capable of explaining the denitrification process. Even though some conventional models have estimated similar averaged values to observed denitrification rates, they poorly predicted variation of denitrification rates. In contrast, ANNs achieved fairly high predictability with R2 of 0.761, indicating a high capacity to simulate denitrification dynamics. According to a sensitivity analysis of the ANNs, water temperature, denitrifying enzyme activity (DEA), and DO account for 60% of denitrification rates. These results indicate that the ANNs model clearly had a greater ability to simulate variations in denitrification rate than the linear regression model and the simplified mechanistic model applied in this study.;Constructed wetlands are generally created for water quality amelioration using natural biogeochemical processes of a wetland including denitrification. In order to perform the denitrification properly in constructed wetlands, not only environmental conditions, but also stabilizing and inhabitation of denitrifiers could be key factors to be considered. In this study, we observed the temporal dynamics of denitrifying bacterial community structure and gene copy number by terminal restriction fragment length polymorphism (T-RFLP) and real time PCR (RT-PCR), respectively. I also measured the denitrification process in newly constructed wetlands. Some major T-RFs seemed to become dominant in denitrifier communities during the wetland operation period, and the denitrifying bacterial community structure showed dissimilar results between years of wetland operation. With denitrifier community changes, denitrifying enzyme activity (DEA) had significant increasing trends with time at the first year and it was significantly high and stable in the second year of wetland operation. This result suggests that denitrifying bacterial community structure has become simplified to some specific species and the dominant denitrifiers may contribute to the high denitrifying activity. However, the actual denitrification rate did not exhibit an annual difference. Moreover, the relationship between denitrifying bacterial community structure and the denitrification process was not found. Denitrification rates showed seasonal trends, implying that the actual rate is more controlled by environmental conditions, even though the inhabited bacterial community had been significantly changed. Among the environmental factors, temperature and pH could primarily influence denitrification rates.