Constructed wetlands have traditionally been categorized based on their hydrological regime and the resultant flow characteristic (Vymazal, 2007). The type and magnitude of N removal processes can vary based on the type of CWs as microbial growth and activity depend on wetland design and operational condition (Vymazal, 2013b). For example, N removal rates can vary from 40 to 50% with removed loads ranging between 250 and 630 g N m⁻² yr⁻¹ (Vymazal, 2007). The influence of wetland flow characteristics on microbial structure and function have been previously investigated by Peralta et al. (2010) who found that natural wetlands had significantly different assemblages of denitrifiers in comparison to restored wetlands. The comparison of denitrifying genes (narG, nirS, nosZ) in sediments within two different types of wetlands, estuarine vs. wastewater effluent-fed CWs, indicated that nitrite-reducing gene nirS was dominant over narG and nosZ in the effluent-fed wetland (Chon et al., 2011). Moreover, the abundance of specific microbial communities such as Nitrosomonas spp. as the N transforming bacteria can vary based on the type of CWs (Flood et al., 1999; Silyn-Roberts and Lewis, 2001). The population and composition of AOB were found to be different in vertical and horizontal CWs, with a higher percentage of Nitrosospira-like sequences (Ibekwe et al., 2003; Gorra et al., 2007; Tietz et al., 2007) in comparison to an overland flow system which did not show any changes in AOB composition (Sundberg et al., 2007a).

Specific design features of conventional wetland systems can bring about changes to N removal and alter the main removal mechanisms in wetlands. Vertical subsurface flow CWs (VSSF-CWs) with partially saturated conditions operating under low organic loads favored simultaneous nitrification and denitrification processes (Pelissari et al., 2017). Moreover, VFCWs with high redox potentials favor aerobic microbial processes such as ammonification and nitrification (Kadlec et al., 2000). The comparison between VF, SF and HFCWs showed a significantly higher biochemical oxygen demand removal and nitrification but relatively lower denitrification in VF-CWs than the SF and HFCWs (Vymazal, 2007). Nitrification and denitrification processes have been shown to be the major N removal mechanisms in HSSF-CWs rather than volatilization, adsorption, and plant uptake (Cooper et al., 1997; Vymazal, 2007).

A wide range of technologies from biofiltration systems (Shirdashtzadeh et al., 2017; Wu et al., 2017) to CWs (Wu et al., 2016) have employed plants to treat wastewater because of their complex interactions with pollutants and microorganisms (Harris et al., 1996; Abal et al., 2002; Brix, 2020). Indeed, plants are one of the most ubiquitous components of CWs, and can directly uptake and assimilate nutrients (Vymazal, 2007, 2013a; López et al., 2016), stabilize the bed surface, serve as substrate for microbial attachment, release oxygen (Peng et al., 2014) and stimulate the growth of N transforming microbes (Li et al., 2018b; Han et al., 2020). Plants also regulate hydraulic conditions and reduce wind stress, which supports sedimentation and prevents re-suspension (Dieter, 1990; Vymazal, 2013a). Nitrogen attenuation by plants is a process encompassing several steps including uptake, assimilation, translocation and as the plant is aging, recycling and remobilization while the main process is the absorbance of nitrogen from the soil in the form of nitrate (NO3-) and ammonium (NH4+-N). However, the studies on N take up by plants and microorganisms reveal that microbes may take up different N forms than plants which may lead to less competition (Schimel and Chapin, 1996; Kaye and Hart, 1997; Hodge et al., 2000; Lipson and Näsholm, 2001).

Biofilms created by submerged plants (or a part of plants) provide large surfaces for microcolonies which are composed of different bacterial communities such as denitrifiers (Zhang et al., 2016). In this regard, microbial communities of planted wetland systems have been found to have higher number of soil microbes and higher activities of soil enzymes (Salvato et al., 2012) accompanied by higher N removal rates (Lin et al., 2002; Yousefi and Mohseni-Bandpei, 2010), compared to unplanted wetlands (Lai et al., 2011; Huang et al., 2012; Boog et al., 2014). The enhanced microbial density, activity, and diversity in the plant rhizosphere create an effective N transformation zone (Picard et al., 2005; Kadlec and Wallace, 2008; Faulwetter et al., 2009; Truu et al., 2009) due to the abundance of organic matter (Gagnon et al., 2007; Truu et al., 2009; Xu et al., 2017) and the presence of the oxygenated root zone (Lai et al., 2012; Peng et al., 2014). The oxygenated root zone supports aerobic processes even under flooded conditions with a bulk of influent NO3- reduced in the vicinity of plant roots (Han et al., 2020).

Microbial functional genes involved in NO3- reduction processes such as denitrification, Anammox, dissimilatory nitrate reduction to ammonium (DNRA), and denitrifying anaerobic methane oxidation (DAMO)] (Wang et al., 2020b) and nitrification (Stottmeister et al., 2003) have been found in the plant rhizosphere. The rhizosphere mosaic characteristic of aerobic and anaerobic zones assist the process of nitrification and denitrification (Zhu et al., 2010). For example, greater numbers of nitrifying bacteria and higher bacterial activity were detected on plant roots compared to the bulk matrix (Kyambadde et al., 2006). The rhizosphere denitrifying bacteria had different community structure from bulk sediment revealed by PCR-denaturing gradient gel electrophoresis (DGGE) of nosZ. The results demonstrate the effect of vegetation on the functioning and structure of bacterial communities involved in N removal in CWs (Ruiz-Rueda et al., 2009).

Plants also play a significant role in the removal of NH4+ via nitrification-denitrification pathways (Coban et al., 2015). However, the rates of N removal such as denitrification can vary significantly among vegetation communities especially in less aerated systems (Vymazal, 1995; Toet et al., 2003; Bastviken et al., 2005; Sirivedhin and Gray, 2006; Hernandez and Mitsch, 2007). Wetland vegetation density has been found to control microbial community composition (Toscano et al., 2015; Zheng et al., 2016; Han et al., 2020), diversity (Ibekwe et al., 2007) and distribution (e.g., ammonia oxidizers and denitrifiers) (Zhang et al., 2017) via enhancing wetland retention time (Jadhav and Buchberger, 1995; Vymazal, 2013a).

Nutrient concentration can affect diversity, composition, and structure of microbial communities (Hu et al., 2014). It has been reported that nutrient availability can increase the richness of microorganisms, as water samples from natural sites contain higher bacterial richness and diversity than sediment and surface water sampled from urban runoff (Logue et al., 2012). However, other studies reported that nutrient availability can reduce the diversity of microbial communities (Van Horn et al., 2011). Among the different types of nutrients, total phosphorus (TP) and NO3- have been recognized as the main factors affecting the composition of microbial communities in urban aquatic systems (Wang et al., 2018). A higher concentration of NO3- has been correlated with increased occurrence of denitrifying genes (Zhang et al., 2016), higher denitrification rates in sediments (Vymazal, 1995; Bastviken et al., 2005; Sirivedhin and Gray, 2006) and more vigorous and robust populations of denitrifiers within wetland sediments (Vymazal, 1995; Bastviken et al., 2005; Sirivedhin and Gray, 2006).

Microbial denitrification is considered as the dominant N removal process at high NO3- loading rates (Spieles and Mitsch, 1999; Xu et al., 2017) while low concentration of NO3- results in coupled nitrification-denitrification as the major removal process in CWs. The rate of DNRA in CWs has been related to NO3- loss (Kendall et al., 2007), while the presence of both NH4+ and NO3- can inhibit NO3- uptake by microorganisms (Coban et al., 2015). Nitrosospira spp. has been detected as the prevalent group in low-ammonia (NH4+) environments (Kowalchuk et al., 2000; Bäckman et al., 2003), while Nitrosomonas species is the prevalent bacterial group at high NH4+ concentrations (Schramm et al., 1996; Juretschko et al., 1998; Okabe et al., 1999; Purkhold et al., 2003; Sundberg et al., 2007a; Tietz et al., 2007).

The abundance of N transforming microbes has a significant correlation with organic matter content (Vymazal, 1995; Hernandez and Mitsch, 2007; Sundberg et al., 2007b; Kim et al., 2016), their availability and degradability potential (Kozub and Liehr, 1999; Sirivedhin and Gray, 2006). Dissolved organic matter (DOM) has been found as one of the major contributing factor to the microbial variation, composition and structure in surface waters (Logue and Lindström, 2008; Pang et al., 2014). The variation in loading rates of organic carbon has been found to influence microbial diversity (e.g., nitrifiers) and increase the competition among different microbial groups (Thompson et al., 1995; Schramm et al., 1996; Grunditz et al., 1998; Kowalchuk et al., 2000; Webster et al., 2002; Truu et al., 2005), with an uneven distribution of available organic matter known to cause a sparse and heterogeneous distribution of microbes in CWs. The chemical oxygen demand to nitrogen ratio (COD/N) has been used as an assessment method to represent the efficiency of wetland N removal (Wu et al., 2009; Rodziewicz et al., 2019).

Higher levels of diversity and abundance of AOB have been detected at higher COD (Prosser, 1990; Van Niel et al., 1993; Hunt et al., 2003; Zhao et al., 2011; Fan et al., 2013a; Si et al., 2019). Heterotrophic denitrification is negatively influenced by low carbon-to-nitrogen ratios (mol/mol) (Lee et al., 2009; Wu et al., 2009), while denitrification in some CWs have been significantly enhanced with increased COD/N because of enrichment by denitrifiers in CWs (Xu et al., 2017). The limitation of COD and the presence of NH4+ favor Anammox bacteria, where the abundance of amoA has been correlated with N removal efficiency (Zhang et al., 2017). Microbial N transforming processes in wetland bed sediments such as ammonification, nitrification and denitrification depend on characteristics of bed sediment such as nutrient availability (Vymazal, 1995; Bastviken et al., 2005; Sirivedhin and Gray, 2006; Truu et al., 2009; Repert et al., 2014). Soil nutrient concentration can significantly impact N removal, for example, wetlands with mineral soils showed more rapid N removal rates compared to those with organic soils (Gale et al., 1993). Moreover, some types of soil can provide better sources of carbon to promote microbial processes in CWs (Dordio and Carvalho, 2013).

Temperature correlates strongly with N removal in CWs by regulating microbial processes as metabolic rates at higher temperatures generally result in higher microbial growth and activity (Zhang et al., 2008; Faulwetter et al., 2009). Different functional groups of microbes have different growth temperature optima, for example, ammonia-oxidizing bacteria grow faster than nitrite oxidizing bacteria at temperatures above 15°C while nitrite oxidizing bacteria growth can be inhibited at 25°C (Paredes et al., 2007). Nitrosomonas and Nitrobacter require temperatures above 5°C for their growth (Cooper et al., 1996) while temperatures lower than 10°C inhibit nitrification (Herskowitz et al., 1987; Xie et al., 2003). Studies have reported different optimal temperatures for nitrification (Vymazal, 1995; Paul, 2014). Truu et al. (2009) reported a range of 28–36°C for nitrification while other studies reported optimal temperature to be as low as 0 to 5°C (Sundblad and Wittgren, 1991; Sundberg et al., 2007a). However, nitrifying communities can adapt to temperature variations and may maintain their activity at lower temperatures via their metabolic adaptation (Cookson et al., 2002).

Seasonal temperature increases of more than 6°C have been found to have a significant impact on NH4+ and total inorganic N removal via simultaneous partial nitrification and Anammox process (He et al., 2012). It has been reported that bacteria conducting nitrification and denitrification are sensitive to lower temperatures. However, bacteria in the upper layers were more sensitive to the temperature changes than bacteria in the lower layers of vertical flow filter systems (VSSF-CW) (Truu et al., 2009). Denitrification can only occur above 5°C in CWs (Herskowitz et al., 1987; Brodrick et al., 1988; Werker et al., 2002) with complete denitrification accomplished at 52°C (Liao et al., 2018). The increase of temperature from 4 to 25°C was found to have the largest positive effect on the potential rate of denitrification (increasing from 0.0021 to 0.8100 kg N₂O/kg sediment per day) (Sirivedhin and Gray, 2006). Although low temperatures (<5°C) can suppress denitrification in CWs (Werker et al., 2002; Burchell et al., 2007), no seasonal or spatial influences were observed on bacterial abundance or diversity, and lower temperatures did not change the N removal rates during winter period (Kern, 2003).

Liao et al. (2018) investigated denitrifying genes (nirK, nirS, narG, and nosZ) in CWs and found that temperature changes can cause shifts in microbial structure, diversity, and abundance. It has also been reported that sensitivity of microbial processes in CWs to temperature variations are higher in dry conditions compared to flooded conditions (Nurk et al., 2005). Low temperature was found to have a negative effect on the number of nitrifying bacteria and nitrification in a HFCW during the winter period (Kern, 2003). However, the impact of temperature on nitrification can be limited because low temperatures can enhance other environmental factors which are beneficial to the nitrifiers (e.g., increased redox potential). Heterotrophic activity of microorganisms is not likely to be impacted by temperature variation probably due to the mixed populations contributing to activities at different temperatures (Tao et al., 2007). Lastly, the sensitivity of N removal processes to temperature may depend on wastewater properties (Truu et al., 2009).

Microbial function and diversity depend on presence or absence of oxygen in CWs. Dissolved Oxygen (DO) is negatively correlated with the relative abundances of denitrifying genes (Zhang et al., 2016) and plays a significant role in N availability as it determines the oxidized and reduced forms of nitrogen. High DO levels was reported to have led to the increase in abundance of nitrifying bacteria, denitrifying bacteria, and anammox bacteria (Liu et al., 2018). DO is necessary for ammonification in the micro-gradient of aerobic and anaerobic zones of CWs, and also affects the steep redox gradients in wetlands leading to changes in the spatial distribution of microbial biomass in wetlands (Reddy and D'angelo, 1997; Scholz and Lee, 2005; Truu et al., 2009). Furthermore, the microsites with steep oxygen gradients within wetlands allow denitrification and nitrification to occur in sequence in very close proximity to each other (Kadlec and Wallace, 2008).

Aerobic nitrifying bacteria perform complete nitrification at the upper layers of a water body (Robertson and Kuenen, 1984; Kern, 2003; Nurk et al., 2005) or the oxygenated zones of rhizosphere (Zhu and Sikora, 1995; Martin et al., 1999; Münch et al., 2005) because of the presence of adequate amount of oxygen (Hammer, 1986; Tchobanoglous et al., 1991; Vymazal, 1995). At the water-sediment interface, which is characterized by an oxygen gradient, aerobic reactions can take place near the surface while anaerobic reactions take place at the deeper layer of bottom sediments (Reddy et al., 1984). Thus, the depth that microbial communities occupy in the bed sediments of CWs plays a significant role in defining the aerobic/anaerobic processes (Wei et al., 2021).

pH plays a vital role in development of microbial communities (Paredes et al., 2007; Vymazal, 2007; Mayes et al., 2009; Saeed and Sun, 2012), as ammonification, nitrification, denitrification and Anammox are all pH dependent processes (Vymazal, 1995; Bastviken et al., 2005; Sirivedhin and Gray, 2006; Wang et al., 2017). The optimal pH for ammonification was found to be 6.5 to 8.5 (Reddy et al., 1984; Vymazal, 1995; Saeed and Sun, 2012). The ideal pH for nitrifying bacteria ranges between 7.2 and 9.0 (Tchobanoglous et al., 1991; Cooper et al., 1996; Paredes et al., 2007; Vymazal, 2007), while pH between 7.5 and 7.8 can result in partial nitrification over nitrite oxidation (He et al., 2012). The optimal pH of denitrification ranges from 6 to 8, while it reduces at pH 5, and is negligible below pH 4 (Vymazal, 2007). Although pH can affect nitrification rates, its influence is reported to be negligible under neutral pH conditions (Reddy et al., 1984). Microbial mediated processes can also change the pH, as denitrification can increase pH by leading to higher wetland alkalinity.

Constructed wetlands experience different hydrologic and hydraulic behavior as well as different degrees of drying and re-wetting conditions. The impact of dry-weather condition and storm events on N transforming microbes in CWs have been studied by Converse et al. (2011), Vymazal (2014), Wu et al. (2015), Huang et al. (2018). Variations in wetland hydrology and hydraulics can account for the observed inconsistency in treatment rates and shifts in microbial communities (Chen et al., 2013; Bernardin-Souibgui et al., 2018; Huang et al., 2018; Kan, 2018; Rose et al., 2018).

Foulquier et al. (2013) reported that the structure of bacterial communities under dry–wet cycles differ from those found under permanently inundated conditions. Moreover, a series of dry–wet stress cycles and the reduction in soil respiration rates have been linked to microbial community composition (Fierer et al., 2003). Thus, effective N removal requires stability in hydraulic response which influences retention, high contact between water and wetland components and flow distribution (Schimel et al., 2007; Wallenstein and Hall, 2012). The retention time, a key parameter is CW design, is a measure of the average amount of time that inflow to the wetland is retained before final discharge and has been shown to affect microbial community structure, composition, and abundance (Toet et al., 2005; Faulwetter et al., 2009).

Water level fluctuations is one of the key characteristics of CWs that can cause shifts in microbial communities as microbial composition, structure, and function are sensitive to the depth, frequency, and duration of fluctuations. The dynamics of wetland hydrology not only alter the response of wetland systems, but also alter the microbial genes responsible for N removal pathways (Bambauer et al., 1998; Fritsche et al., 1999; Kämpfer et al., 1999; Doronina et al., 2010; Drury et al., 2013; Eichmiller et al., 2013; Liu et al., 2013; Chen et al., 2014; Mo et al., 2016; Isabwe et al., 2018). Systems with high water levels contained significantly higher DO concentrations in their bed sediment which can change the microbial community structure and composition (Han et al., 2020; Huang et al., 2020). In addition, during periods of drawdown, enhanced diffusion of oxygen can lead to the promotion of nitrification process over denitrification (Baldwin and Mitchell, 2000; Knorr et al., 2008). The rates of microbial functions can be continually affected in seasonally dewatered zones compared to the permanently inundated areas. Saturated conditions limit the diffusion of oxygen in sediment and promote anaerobic processes such as denitrification over aerobic processes (e.g., nitrification) as the hydrological regime can regulate gas exchange between the atmosphere and sediments (Hefting et al., 2004; Reddy and DeLaune, 2008; Siljanen et al., 2011). Moreover, hydraulic fluctuations affect the steep redox gradients in CWs which control microbial mediated mechanisms (Reddy and D'angelo, 1997; Scholz and Lee, 2005). Periodic drying and wetting conditions can cause changes in microbial community dynamics (Huang et al., 2018; Kan, 2018; Rose et al., 2018). Previous studies have investigated the processes of microbial assembly and dynamics under wet and dry condition within CWs, creek, and watershed (Bambauer et al., 1998; Fritsche et al., 1999; Kämpfer et al., 1999; Doronina et al., 2010; Drury et al., 2013; Eichmiller et al., 2013; Liu et al., 2013; Chen et al., 2014; Mo et al., 2016; Huang et al., 2018; Isabwe et al., 2018; Kan, 2018; Rose et al., 2018).

During storm events, overland flow introduce new groups of microbes to the wetland, which can change microbial abundance and composition (Sundberg et al., 2007a). While drying and wetting conditions cause immediate physiological stresses to microorganisms, repeated dry–wet cycles can cause long-term effects at community level through the selection of taxa (Fierer et al., 2003; Mikha et al., 2005; Schimel et al., 2007; Xiang et al., 2008). Thus, storm events can change the microbial function, with the potential for alteration of subsequent biogeochemical transformations. Kan (2018) who tracked changes of bacterial community before, during, and after storm events found that the diversity of bacterial community significantly increased during the peak discharge, with the starting bacterial community being very different from the storm community. There are also differences in the distribution patterns of bacterial community, which are event specific, with each bacterial phylum showing distinct response to the event (Kan, 2018). During large storm events, functional genes changed notably and distinct bacterial groups (e.g., nitrifying and denitrifying genes) became the dominant groups (Merbt et al., 2015). During dry weather, the microbial communities have been shown to transform from heterotrophic at the inlet to predominantly autotrophic at the outlet (Huang et al., 2018) indicating a high spatial variation in composition of bacterial communities during dry weather (Petersen et al., 2005; Sercu et al., 2008; Parks and VanBriesen, 2009). Moreover, dry period water samples have been found with differences in the abundance of distinct bacterial families (Isabwe et al., 2018) with less diversity in comparison to the wet weather samples (Huang et al., 2018). The inconsistency of denitrification rates between the sampling locations have been best described by concentration of nitrogen in sediments and hydrological processes, including water residence times (Kjellin et al., 2007). The fluctuation of water regime reduces microbial mediated processes due to the negative impact on wetland vegetation (Greenway et al., 2007; Raulings et al., 2010; Vanderbosch and Galatowitsch, 2011; Webb et al., 2012).