Distinctive Microbial Processes and Controlling Factors of Nitrous Oxide Emission in an Agricultural River Network: Perspective in Riparian Zone Type and Season

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Authors,

The authors investigate nitrous oxide (N₂O) emissions in an agricultural river network, comparing natural and artificial riparian zones across seasons and evaluating the applicability of IPCC EF5r emission factors. I find the article interesting; however, it presents several significant gaps in information that should be addressed by the authors.

Majors:

-The Introduction places a strong emphasis on heterotrophic bacterial denitrification, while other relevant microbial groups (cyanobacteria, and microalgae) are largely overlooked. I recommend broadening this section to provide a more balanced overview of the microbial diversity involved in aquatic N₂O production, please.

-Since functional genes related to nitrogen cycling (nirS, nirK, nosZ, nifH, ureC) are a major component of the results, their relevance should be briefly mentioned in the introduction, please.

-L69…: The role of organic carbon is introduced but not sufficiently developed. Given that DOC later emerges as a major driver of N₂O emissions in the results, the authors should expand this section to better explain its role.

-In the introduction the transition from general microbial N₂O processes to the specific role of riparian zones is abrupt.

-L101: The authors should explicitly explain why these specific locations and sampling periods were chosen and how they are representative of agricultural river networks, please.

-L107: The number of biological replicates for water and sediment samples is not clearly stated.

-L111: The definition of “artificial riparian” is too brief. Please provide more detailed information on the construction materials, age, hydrological connectivity,…..

-L115: Sorry but, it is unclear whether measurements were taken once or repeatedly during sampling.

-L139: The assumptions underlying the IPCC-based estimation of N₂O emissions (use of default EF5r values and global atmospheric N₂O concentration,….) should be more clearly stated, please

-L147: The description of DNA extraction, qPCR, and high-throughput sequencing lacks sufficient technical detail. Please specify DNA extraction yields, qPCR efficiencies…

-In the discussion, the authors mainly attribute N₂O production to bacterial processes. However, it is now well established that N₂O production is not restricted to bacteria. As recently seen, photosynthetic microorganisms, particularly microalgae such as Chlamydomonas, are also capable of producing N₂O from nitrite that is high dependent of nitrate reductase, please discuss.

-L184:“the river network became the source of atmospheric N₂O” implies a causal conclusion. Please clarify that this inference is based on observed supersaturation levels and avoid overinterpretation, please.

-L240:The α-diversity results are extensively described, but their relevance to N₂O emissions is not explicitly stated.

-L264:Although nitrifying bacteria abundances are reported, their direct relationship with measured N₂O emissions for mi is not clear,  please clarify

-L323: The relative abundances of functional genes are presented without clarifying the reference (relative to total genes, total reads…). Please clarify

-Several figures lack essential information such as sample size, statistical tests used, and definition of error bars

- L371: The subsection title implies a definitive conclusion “overestimation”, please change.

- L393: This paragraph reiterates results already presented. The authors should synthesize and focus on their implications, please

-L421: Interpretations based on nirS/nirK ratios would be strengthened by including absolute gene abundances, please consider

-L438: I think that the discussion of co-occurrence networks is quite descriptive. The authors should more explicitly link network structure to ecosystem function and N₂O emission, please.

- L474: The PLS-PM model is interpreted as explaining causal mechanisms. Please clarify that this model describes statistical relationships rather than direct causality.

L486…..-Despite extensive discussion of microbial processes, the potential role of N2O emisions from nitrite in photosynthetic microorganisms (C. reinhardtii), is not considered. Please discuss this

-I think that the final part of the discussion would benefit from a clearer link to broader implications for river management, greenhouse gas mitigation, and refinement of emission factors, please consider that.

Author Response

General Comment: The authors investigate nitrous oxide (N₂O) emissions in an agricultural river network, comparing natural and artificial riparian zones across seasons and evaluating the applicability of IPCC EF_5r emission factors. I find the article interesting; however, it presents several significant gaps in information that should be addressed by the authors.

General Response: We sincerely thank the reviewer for the thorough and constructive comments. We have carefully revised the manuscript accordingly. Below, we provide a point-by-point response. All changes are highlighted in the revised manuscript.

 

Comment 1: The Introduction places a strong emphasis on heterotrophic bacterial denitrification, while other relevant microbial groups (Cyanobacteria and microalgae) are largely overlooked. I recommend broadening this section to provide a more balanced overview of the microbial diversity involved in aquatic N₂O production, please.

Response 1: We appreciate this insightful comment and fully agree that N₂O production in aquatic systems is not restricted to heterotrophic bacterial denitrification. In the revised manuscript, we have broadened the Introduction to provide a more balanced overview of microbial groups involved in aquatic N₂O production. Specifically, we now highlight that, in addition to heterotrophic bacteria, other microbial groups such as cyanobacteria and microalgae have been reported to produce N₂O via nitrite reduction and nitrate reductase-dependent pathways under oxic or fluctuating redox conditions. Accordingly, a new paragraph was added in Lines 66-67 to emphasize the broader diversity of microbial communities involved in nitrogen cycling: “Microbial communities are highly diverse, comprising bacteria, archaea, fungi, and protozoa. These microorganisms play pivotal roles in the microbial N cycling [1]”

In addition, we have explicitly addressed the role of cyanobacteria in the Discussion. In Lines 525-535, “Module III represents a phototrophy-driven regime dominated by Cyanobacteria and strongly shaped by seasonal dynamics. The enrichment of Cyanobacteria in spring indicates a close coupling between primary production and downstream nitrogen cycling. Through photosynthetic exudation and biomass turnover, Cyanobacteria supply labile organic carbon, which can indirectly stimulate heterotrophic denitrification in sediments and overlying water [2]. In addition, diel oxygen fluctuations associated with photosynthesis and respiration generate transient redox gradients that favor incomplete denitrification and episodic N₂O release. Beyond these indirect effects, growing evidence suggests that phototrophic microorganisms can directly produce N₂O from nitrite under oxic or redox-fluctuating conditions, highlighting Module III as a potential seasonal source of N₂O.”

Furthermore, we have expanded the Discussion in Lines 589–596 to incorporate recent evidence for direct N₂O production by photosynthetic microorganisms. “Beyond bacterial denitrification, emerging evidence suggested that photosynthetic microorganisms may also contribute to N₂O production from nitrite. Microalgae and cyanobacteria have been shown to reduce NO₃^- to N₂O via nitrate reductase–dependent pathways under oxic or fluctuating redox conditions[3]. Given the seasonal enrichment of phototrophic taxa observed in this study, particularly in spring, phototrophic N₂O production from nitrite may represent a complementary and previously underappreciated pathway contributing to N₂O emissions in agricultural river networks.”

 

Comment 2: Since functional genes related to nitrogen cycling (nirS, nirK, nosZ, nifH, ureC) are a major component of the results, their relevance should be briefly mentioned in the introduction, please.

Response 2: We appreciate this valuable comment. To improve coherence between the Introduction and Results, we have added a brief description of key nitrogen-cycling functional genes and their relevance to N₂O production and consumption in the Introduction. Specifically, a sentence was added in Lines 71–74 describing the roles of nirS, nirK, and nosZ: “The nitrite reductase genes nirS and nirK mediate the reduction of NO₂^- to NO during denitrification, directly preceding N₂O formation, whereas nosZ encodes nitrous oxide reductase responsible for N₂O reduction to N₂ [4].” Although nifH and ureC are included in the Results as indicators of broader nitrogen transformation potential, their detailed functional roles in nitrogen fixation and urea hydrolysis were not elaborated in the Introduction to maintain focus on microbial pathways directly involved in N₂O production and consumption.

 

Comment 3: -L69…: The role of organic carbon is introduced but not sufficiently developed. Given that DOC later emerges as a major driver of N₂O emissions in the results, the authors should expand this section to better explain its role.

Response 3: Thank you for pointing this out. We have expanded the discussion of organic carbon in the Introduction, with particular emphasis on the role of dissolved organic carbon (DOC). The revised text now explains how DOC regulates microbial respiration, redox conditions, and denitrification efficiency, thereby influencing N₂O production and accumulation. Accordingly, the original text in Lines 74–80 has been revised to: “Heterotrophic denitrification is strongly regulated by carbon and nitrogen availability, with organic carbon (OC) serving as the primary electron donor and oxidized nitrogen species (NO₃^- and NO₂^-) acting as terminal electron acceptors. Variations in OC quantity and quality, nitrogen substrates, and dissolved oxygen (DO) conditions jointly influence microbial respiration, redox dynamics, and electron allocation within denitrifying communities, thereby shaping the balance between N₂O production and consumption [5-7].”

 

Comment 4: In the introduction, the transition from general microbial N₂O processes to the specific role of riparian zones is abrupt.

Response 4: We appreciate this helpful comment. To improve the logical flow of the Introduction, we have revised the transition between the general description of microbial N₂O production processes and the specific focus on riparian zones. In the revised version, a transitional paragraph has been added to explicitly link microbial nitrogen transformation processes with the unique biogeochemical and hydrological functions of riparian zones in agricultural river networks. A new transitional paragraph was added in Lines 84-88 of the Introduction to bridge general microbial N₂O processes and the role of riparian zones. “Riparian zones, as key interfaces between terrestrial and aquatic systems, exert strong control over nitrogen inputs, organic carbon availability, and redox gradients. Artificial riparian zones, particularly impermeable cement banks, can significantly alter the distribution of nirS- and nirK-harboring denitrifying communities, thereby potentially affecting N₂O production [8,9].”

 

Comment 5: L101: The authors should explicitly explain why these specific locations and sampling periods were chosen and how they are representative of agricultural river networks, please.

Response 5: We thank the reviewer for this helpful comment. In the revised manuscript, we have expanded the description of the study area and sampling design to clearly explain the rationale for both site selection and sampling periods. Specifically, we clarify that Jiashan County is characterized by a dense plain river network surrounded by intensive farmland and continuous agricultural drainage, making it highly representative of typical agricultural river systems in the Yangtze River Delta and eastern China. Accordingly, relevant text has been added in Lines 106–108 and 114–116, including: “The area is characterized by a dense network of agricultural rivers and intensive farmland drainage, making it highly representative of typical agricultural river systems in eastern China.” and “The studied rivers receive continuous runoff and drainage inputs from surrounding farmlands, offering favorable conditions for examining the transport and transformation of agriculturally derived nitrogen.”

In addition, we have explicitly justified the choice of sampling periods. As stated in Lines 118–121 “Spring and autumn were selected to represent two contrasting but hydrologically stable periods in agricultural river systems. Spring typically corresponds to enhanced microbial activity and increased nitrogen inputs following agricultural fertilization, whereas autumn reflects more stable nutrient conditions and reduced biological activity.”

Comment 6: L107 The number of biological replicates for water and sediment samples is not clearly stated.

Response 6: We thank the reviewer for pointing out this lack of clarity. In the revised manuscript, we have explicitly stated the number of biological replicates for both water and sediment samples in the Methods section to improve transparency and reproducibility. The number of biological replicates has been added in line 122-123，“……with two to three independent biological replicates per category.”

 

Comment 7:-L111: The definition of “artificial riparian” is too brief. Please provide more detailed information on the construction materials, age, hydrological connectivity,…..

Response 7: We thank the reviewer for this helpful comment. In the revised manuscript, we have expanded the definition and description of artificial riparian zones to provide additional structural and hydrological details. Specifically, the following information has been added in Lines 127–130: “The artificial riparian zones were constructed with impermeable cement revetments, had been stabilized for more than 10 years, and exhibited limited lateral hydrological connectivity with surrounding soils. Consequently, sediment accumulation at the river bottom was absent.”

 

Comment 8: L115: Sorry but, it is unclear whether measurements were taken once or repeatedly during sampling.

Response 8: We thank the reviewer for pointing out this lack of clarity. In the revised manuscript, we have clarified that measurements were conducted repeatedly during each sampling event, and that the reported values represent averages of these repeated measurements. The measurement frequency has been clarified in Lines 135-136 of the revised manuscript: “During each sampling process, all on-site parameters were measured three times and the average value was calculated”.

 

Comment 9: -L139: The assumptions underlying the IPCC-based estimation of N₂O emissions (use of default EF_5r values and global atmospheric N₂O concentration,….) should be more clearly stated, please.

Response 9: We thank the reviewer for this important comment. In the revised manuscript, we have clarified the key assumptions underlying the IPCC-based estimation of N₂O emissions to improve transparency. “Specifically, emission rates were calculated using the thin boundary layer model based on the concentration gradient between surface water and the atmosphere, together with gas transfer velocities (k) derived from seven widely accepted wind-based models.” The assumptions associated with the IPCC-based N₂O emission estimation have been clarified in Lines 155-158 of the revised manuscript. Seven widely used wind-based models were applied to estimate k, following equations proposed in previous studies (Table S1).

 

Comment 10: -L147: The description of DNA extraction, qPCR, and high-throughput sequencing lacks sufficient technical detail. Please specify DNA extraction yields, qPCR efficiencies…

Response 10: We thank the reviewer for this valuable comment. In the revised manuscript, we have expanded the description of DNA extraction, qPCR, and high-throughput sequencing to provide additional technical details. Specifically, The Methods section has been revised accordingly in Lines 184-185 and Lines 187-189: “with A260/A280 ratios between 1.8 and 2.0 and DNA yields ranged from 10 to 150 ng·g^-1.” and “Standard curves were generated using serial dilutions of plasmid DNA, yielding amplification efficiencies between 90% to 105% and correlation coefficients (R²) greater than 0.99.”

 

Comment 11: -In the discussion, the authors mainly attribute N₂O production to bacterial processes. However, it is now well established that N₂O production is not restricted to bacteria. As recently seen, photosynthetic microorganisms, particularly microalgae such as Chlamydomonas, are also capable of producing N₂O from nitrite that is high dependent of nitrate reductase, please discuss.

Response 11: We thank the reviewer for this important and constructive comment. We agree that N₂O production in aquatic systems is not restricted to bacterial processes and that photosynthetic microorganisms, particularly microalgae, can also contribute to N₂O formation via nitrite reduction mediated by nitrate reductase.

In the revised Discussion, we have expanded the text to explicitly acknowledge and discuss N₂O production by photosynthetic microorganisms, including microalgae such as Chlamydomonas. We note that algal-derived N₂O production has been reported under oxic or fluctuating redox conditions in nitrite-rich environments and may represent an additional, previously underestimated N₂O source in eutrophic aquatic systems.

At the same time, we clarify that the present study primarily focuses on sediment-associated microbial communities, where bacterial nitrification and denitrification are expected to dominate N₂O production. To address the reviewer’s suggestion, we have added the following discussion in the revised manuscript:

In Lines 490-495: “Although our study focused primarily on sediment-associated microbial communities, these non-bacterial pathways may represent an additional N₂O source in eutrophic river systems and warrant further investigation. Recent studies have demonstrated that photosynthetic microorganisms, including microalgae such as Chlamydomonas, can produce N₂O from NO₂^- via nitrate reductase-dependent pathways, particularly under oxic or fluctuating redox conditions[3].”

In addition, in Lines 580-586, we further emphasize: “Beyond bacterial denitrification, emerging evidence suggests that photosynthetic microorganisms may also contribute to N₂O production from nitrite. Microalgae and cyanobacteria have been shown to reduce NO₃^- to N₂O via nitrate reductase–dependent pathways under oxic or fluctuating redox conditions[41].”

Comment 12: -L184: “the river network became the source of atmospheric N₂O” implies a causal conclusion. Please clarify that this inference is based on observed supersaturation levels and avoid overinterpretation, please.

Response 12: We thank the reviewer for this important comment. We agree that the original wording could be interpreted as implying a causal conclusion. In the revised manuscript, we have therefore rephrased this statement to clarify that the interpretation is based on observed N₂O supersaturation relative to atmospheric equilibrium, rather than on direct evidence of causality. Specifically, the sentence in Line 225-227 has been revised to: “N₂O supersaturation was commonly observed in the agricultural river network of the Yangtze River Delta, suggesting a tendency for net N₂O efflux to the atmosphere under the observed conditions.”

Comment 13: -L240: The α-diversity results are extensively described, but their relevance to N₂O emissions is not explicitly stated.

Response 13: We thank the reviewer for this constructive comment. In the revised manuscript, we have clarified the relevance of microbial α-diversity to N₂O emissions by explicitly linking diversity patterns to functional redundancy, niche differentiation, and the balance between N₂O-producing and N₂O-consuming processes. We now discuss how variations in α-diversity may influence the stability and efficiency of microbial nitrogen transformations, thereby indirectly affecting N₂O production and emission dynamics. We also emphasize that α-diversity reflects potential functional capacity rather than direct causality. Accordingly, a dedicated discussion has been added in Lines 456 - 464: “Microbial α-diversity patterns provide important context for understanding spatial and seasonal variability in N₂O emissions. Higher α-diversity in sediments compared to overlying water indicated greater functional redundancy among sediment-associated communities, which may stabilize nitrogen transformation processes [37]. In contrast, the lower and more seasonally variable diversity observed in the water column, particularly during spring, reflects a more disturbance-sensitive community (Table 2). The pronounced seasonal decline in diversity observed in artificial riparian zones may further reduce functional stability and favor incomplete nitrogen transformations, thereby promoting transient N₂O accumulation.”

 

Comment 14: -L264: Although nitrifying bacteria abundances are reported, their direct relationship with measured N₂O emissions for mi is not clear, please clarify.

Response 14: We thank the reviewer for this helpful comment. We agree that the direct relationship between nitrifying bacteria abundance and measured N₂O emissions required further clarification. In the revised manuscript, we have clarified this point in Lines 562–567. “Despite their measurable abundance, nitrifying bacteria were not the primary drivers of N₂O emissions in this study. However, except for the nitrification gene amoB, the gene amoA, hao, nxrA concentrations of all samples were present at very low abundances or were undetectable (< 0.4%) in this study. This suggested that nitrification played a limited direct role in controlling N₂O production.”

 

Comment 15: -L323: The relative abundances of functional genes are presented without clarifying the reference (relative to total genes, total reads…). Please clarify

Response 15: We thank the reviewer for pointing out this lack of clarity. In the revised manuscript, we have explicitly clarified the reference used for calculating the relative abundances of functional genes. Specifically, “The relative abundances of nitrogen-cycling functional genes were calculated by normalizing their copy numbers to the total 16S rRNA gene copy numbers in each sample, thereby accounting for differences in microbial biomass.” in 194 - 196.

 

Comment 16: -Several figures lack essential information such as sample size, statistical tests used, and definition of error bars.

Response 16: We thank the reviewer for pointing out this important issue. In the revised manuscript, we have carefully revised all relevant figure captions to include essential information, including the number of biological replicates (sample size), the statistical tests applied, and the definition of error bars. Specifically, information on sample size has been clarified in Lines 116-117: “Sampling was conducted during two representative seasons, from 6-9 October 2021 (autumn) and 22-24 April 2022 (spring).” In addition, information on statistical significance has been added to Figure 5 and Table 2. For Figure 1 and Figure 5, the following statement has been included in the figure captions: “Differences among groups were tested using one-way analysis of variance (ANOVA), with significance set at P < 0.05. Error bars represent standard deviation (SD) of independent biological replicates (n = 2–3).”

 

Comment 17: - L371: The subsection title implies a definitive conclusion “overestimation”, please change.

Response 17: We thank the reviewer for this helpful comment. We agree that the original subsection title could be interpreted as implying a definitive conclusion. In the revised manuscript, we have modified the subsection title to adopt a more neutral wording that avoids overinterpretation and better reflects the uncertainty and context dependence of the results. The subsection title has been revised in Line 407 as following: Evaluation of IPCC-based N₂O emission estimates for the Yangtze River Delta river network.

 

Comment 18: - L393: This paragraph reiterates results already presented. The authors should synthesize and focus on their implications, please.

Response 18: We thank the reviewer for this helpful comment. In the revised manuscript, we have rewritten this paragraph to reduce repetition of previously presented results and to emphasize their broader implications. The revised text now synthesizes key findings to highlight the methodological limitations of the IPCC-based approach, the influence of riparian type and local environmental conditions on N₂O emission estimates, and the implications for improving riverine N₂O budgets and greenhouse gas inventories. Specifically, the paragraph has been revised in lines 424-439 as follows: While diffusion-based models parameterized with field-measured N₂O concentrations (e.g., W1992 and F2007) produced emission estimates consistent with observed fluxes, the IPCC approach relies on a fixed EF_5r value combined with a global average atmospheric N₂O concentration. The IPCC methodology inherently neglected local hydrological, biogeochemical, and riparian zones controls, which can introduce substantial bias when applied to heterogeneous river systems. In our study, N₂O emission rates estimated using the IPCC methodology were higher than those derived from field-based measurements (Figure 2). The consistently lower EF_5r-e values observed in both natural and artificial riparian zones relative to the IPCC default EF_5r value further indicate that riverine N₂O emission factors were highly context dependent (Figure 1d). Moreover, mechanistic modeling studies of entire river networks have demonstrated that achieving the magnitude of the IPCC default EF_5r was not kinetically feasible in most river systems[35]. These findings suggested that future refinements of EF_5r should explicitly incorporate geographical context and riparian zones characteristics to better capture spatial heterogeneity in N₂O production and exchange, thereby reducing uncertainty in interwatershed N₂O emission assessments.

 

Comment 19: -L421: Interpretations based on nirS/nirK ratios would be strengthened by including absolute gene abundances, please consider.

Response 19: We thank the reviewer for this constructive suggestion. In the revised manuscript, we have therefore strengthened the interpretation by explicitly incorporating the absolute abundances of nirS and nirK genes into the analysis and discussion. Specifically, we now show that the observed patterns in nirS/nirK ratios are supported by clear differences in absolute gene abundances across seasons and riparian types. The revised interpretation has been added to the Results/Discussion section (Lines 469-474), as follows: “In this study, nirS abundance was highest in spring, particularly in sediments of natural riparian zones, indicating that nirS-type denitrifiers dominated nitrite reduction under organic-rich and more reduced conditions. In contrast, nirK exhibited relatively higher abundances in artificial riparian zones during spring, suggesting that nirK-type denitrifiers were favored under more oxic or redox-fluctuating environments.”

 

Comment 20: -L438: I think that the discussion of co-occurrence networks is quite descriptive. The authors should more explicitly link network structure to ecosystem function and N₂O emission, please.

Response 20: We thank the reviewer for this insightful comment. We agree that the initial discussion of the co-occurrence networks was overly descriptive. In the revised manuscript, we have substantially rewritten this section to explicitly link network structure to ecosystem function and N₂O emissions. Specifically, the revised discussion now interprets the co-occurrence network in terms of distinct functional regimes represented by different modules. Module I is discussed as a cooperation-dominated network characterized by strong positive associations among denitrifying and carbon-processing taxa, which likely enhance metabolic coordination and promote N₂O accumulation under favorable redox conditions. In contrast, Module II is interpreted as a competition-driven and functionally partitioned network, where weaker metabolic coupling among nitrifiers, sulfate-reducing, and fermentative bacteria may constrain efficient nitrification-denitrification coupling and limit sustained N₂O production. Module III is further discussed as a phototrophic-driven network dominated by Cyanobacteria, in which primary production, labile carbon supply, and redox oscillations may indirectly and directly stimulate seasonal N₂O emissions. Through this reorganization, the revised text explicitly connects microbial interaction patterns (network structure) to nitrogen transformation pathways (ecosystem function) and their implications for N₂O emissions, thereby moving beyond a purely descriptive interpretation of the co-occurrence networks.

The co-occurrence network discussion has been substantially revised and expanded in Lines 499-535 of the Discussion section: The “small-world” and highly modular network structure indicated that nitrogen cycling is driven not by isolated taxa, but by coordinated microbial assemblages operating within distinct ecological niches (Figure 4). Module I represented a cooperation-dominated functional regime, as it contained several well-documented denitrifying genera, including Flavobacterium, Hydrogenophaga, Arenimonas, and Rhodobacter [19,42,43] (Table S4). The dense positive associations within this module suggested enhanced microbial cooperation, communication, and coordinated activity in riparian zone environments. Such tightly integrated networks were likely to enhance nitrogen transformation rates and promote N₂O accumulation, particularly when electron donor availability and redox conditions favor incomplete denitrification. The coordinated regulation at the community level may amplify N₂O production beyond what would be expected from individual taxa alone [43]. Consistent with these observations, PICRUSt1 functional predictions indicated greater capacities for flagellar assembly, cell motility, and secretion in microbial communities from natural riparian zones compared to artificial riparian zones (Figure S6).

In contrast, Module II reflected a competition-driven and functionally partitioned regime, characterized by a predominance of negative correlations and pronounced niche differentiation. This module included nitrifiers, sulfate-reducing bacteria, and fermentative taxa that indirectly influence nitrogen cycling by regulating electron flow and substrate availability. For example, seven nitrifying bacteria were identified within Module II (Figure 4c), along with members of the phyla Firmicutes and Desulfobacterota. Sulfate-reducing genera such as Geothermobacter and Desulfatiglans may cooperate syntrophically with denitrifiers by using sulfate as an electron shuttle to facilitate organic matter degradation and nitrogen removal [44,45]. However, the dominance of competitive interactions within this module suggested weaker metabolic coupling, leading to more fragmented nitrogen transformation pathways and potentially limiting sustained N₂O production despite the presence of functionally relevant taxa [46].

Module III represents a phototrophy-driven regime dominated by Cyanobacteria and strongly shaped by seasonal dynamics. The enrichment of Cyanobacteria in spring indicates a close coupling between primary production and downstream nitrogen cycling. Through photosynthetic exudation and biomass turnover, Cyanobacteria supply labile organic carbon, which can indirectly stimulate heterotrophic denitrification in sediments and overlying water [47]. In addition, diel oxygen fluctuations associated with photosynthesis and respiration generate transient redox gradients that favor incomplete denitrification and episodic N₂O release. Beyond these indirect effects, growing evidence suggests that phototrophic microorganisms can directly produce N₂O from nitrite under oxic or redox-fluctuating conditions, highlighting Module III as a potential seasonal source of N₂O.

 

Comment 21: - L474: The PLS-PM model is interpreted as explaining causal mechanisms. Please clarify that this model describes statistical relationships rather than direct causality.

Response 21: We thank the reviewer for this important comment. We agree that partial least squares path modeling (PLS-PM) does not demonstrate direct causal relationships but rather describes statistical associations among variables. In the revised manuscript, we have clarified this point by revising the relevant text to avoid causal language. Specifically, in Lines 600-603, the text has been revised to state: “By integrating microbial functional genes with environmental variables, the PLS-PM analysis revealed that regulating external carbon and nitrogen inputs, especially DOC availability and nitrogen loading, may help reduce N₂O emissions from agricultural river networks.”

 

Comment 22: L486…..-Despite extensive discussion of microbial processes, the potential role of N₂O emissions from nitrite in photosynthetic microorganisms (C. reinhardtii), is not considered. Please discuss this

Response 22: We thank the reviewer for this insightful comment. We agree that, in addition to bacterial processes, photosynthetic microorganisms may also contribute to N₂O production from nitrite. In the revised manuscript, we have expanded the Discussion to explicitly address the potential role of N₂O emissions from nitrite in photosynthetic microorganisms, including microalgae such as Chlamydomonas reinhardtii. Specifically, we have added the following discussion in lines 589 - 599: “Beyond bacterial denitrification, emerging evidence suggests that photosynthetic microorganisms may also contribute to N₂O production from nitrite. Microalgae and cyanobacteria have been shown to reduce NO₃^- to N₂O via nitrate reductase–dependent pathways under oxic or fluctuating redox conditions[41]. Given the seasonal enrichment of phototrophic taxa observed in this study, particularly in spring, phototrophic N₂O production from nitrite may represent a complementary and previously underappreciated pathway contributing to N₂O emissions in agricultural river networks. In contrast, genes associated with anammox and dissimilatory nitrate reduction to ammonium (DNRA), such as hzsA, nirB and nrfA, were not detected, indicating that these pathways played a negligible role in the studied system.”

 

Comment 23:-I think that the final part of the discussion would benefit from a clearer link to broader implications for river management, greenhouse gas mitigation, and refinement of emission factors, please consider that.

Response 23: We thank the reviewer for this constructive suggestion. In response, we have revised the final part of the Discussion to more explicitly link our findings to broader implications for river management, greenhouse gas mitigation, and the refinement of emission factors. Specifically, we have added the following discussion in 598-605: “These results suggest that regulating external carbon and nitrogen inputs, particularly DOC availability and nitrogen loading, may help reduce N₂O emissions from agricultural river networks. Maintaining or restoring functional riparian zones could further stabilize microbial nitrogen transformations and limit conditions that favor incomplete denitrification and NO₂^- accumulation. The strong variability of EF_5r across riparian zone types and seasons highlights the need to refine emission factors by incorporating riparian structure, nutrient status, and microbial functional characteristics. Such refinements would improve the accuracy of regional and global greenhouse gas inventories.”

 

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11. Audet, J.; Wallin, M.B.; Kyllmar, K.; Andersson, S.; Bishop, K. Nitrous oxide emissions from streams in a Swedish agricultural catchment. Agr. Ecosyst. Environ. 2017, 236, 295-303, doi:10.1016/j.agee.2016.12.012.
12. Maavara, T.; Lauerwald, R.; Laruelle, G.G.; Akbarzadeh, Z.; Bouskill, N.J.; Van Cappellen, P.; Regnier, P. Nitrous oxide emissions from inland waters: Are IPCC estimates too high? Global Change Biol. 2019, 25, 473-488, doi:10.1111/gcb.14504.
13. Pishgar, R.; Dominic, J.A.; Sheng, Z.; Tay, J.H. Denitrification performance and microbial versatility in response to different selection pressures. Bioresour. Technol. 2019, 281, 72-83, doi:10.1016/j.biortech.2019.02.061.
14. Zumft, W.G. Cell biology and molecular basis of denitrification. Microbiol. Mol. Biol. Rev. 1997, 61, 533-+, doi:10.1128/.61.4.533-616.1997.
15. Props, R.; Denef, V.J. Temperature and Nutrient Levels Correspond with Lineage-Specific Microdiversification in the Ubiquitous and Abundant Freshwater Genus Limnohabitans. Appl. Environ. Microbiol. 2020, 86, e00140-00120, doi:10.1128/aem.00140-20.
16. Wang, R.; Xu, S.J.; Jiang, C.C.; Zhang, Y.; Bai, N.; Zhuang, G.Q.; Bai, Z.H.; Zhuang, X.L. Impacts of human activities on the composition and abundance of sulfate-reducing and sulfur-oxidizing microorganisms in polluted river sediments. Front. Microbiol. 2019, 10, 231, doi:10.3389/fmicb.2019.00231.
17. Qian, J.; Liu, R.L.; Wei, L.; Lu, H.; Chen, G.H. System evaluation and microbial analysis of a sulfur cycle-based wastewater treatment process for Co-treatment of simple wet flue gas desulfurization wastes with freshwater sewage. Water Res. 2015, 80, 189-199, doi:10.1016/j.watres.2015.05.005.
18. Li, Y.Q.; Jing, Z.M.; Jiang, S.H.; Wang, Z.X.; Li, T.; Sun, Z.Y.; Jiang, H.; Zhou, H.J.; Xu, Q.; Fang, G. Deep understanding of the methanogenic community and their interaction in batch high-solid anaerobic digestion of ensiled straw with leachate circulation. Energ. Fuels 2020, 34, 10980-10988, doi:10.1021/acs.energyfuels.0c01264.

 

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript is a well-designed, timely, and significant study that advances understanding of riparian controls on riverine N₂O emissions, but it needs minor revision before publishing.

• The main research question is: How do natural versus artificial riparian zones influence N₂O emissions from agricultural river networks, and what are the underlying microbial mechanisms and environmental drivers?
• The topic is highly relevant to climate science, biogeochemistry, and environmental microbiology.
• The study address a specific gap:
  • Riparian-specific mechanisms.
  • IPCC EF₅ᵣ validation.
  • Microbial niche differentiation.
• Specific improvements should the authors consider regarding the methodology:
  • Sampling replication: The study uses six groups across two seasons, but more spatial replicates within each riparian type would strengthen statistical robustness.
  • Gas flux measurements: The use of multiple wind-based models is good, but inclusion of direct flux measurements (e.g., floating chambers) could validate the diffusion-based estimates.
  • Soil–water exchange: The study acknowledges that IPCC methods ignore water–soil N₂O exchange, but more direct measurements of sediment–water fluxes could better constrain this process.
• Discussion: The discussion could more explicitly reconcile why denitrification (via nirS) is dominant in gene abundance, but N fixation and ammonification genes explain most N₂O variance.
• References: Include more recent reviews on riverine N₂O (e.g., 2022–2023) and consider citing studies on artificial vs. natural riparian effects from non-agricultural systems for broader context.
• Acknowledge limitations (e.g., single geographic region, two-season sampling) and suggest future multi-year, multi-region studies.

Comments on the Quality of English Language

• There are recurring grammatical errors (especially in article usage and tense consistency), typographical inconsistencies in units and symbols, and several overly complex sentences that hinder readability. We recommend a comprehensive proofread by a native English speaker or a professional editing service to correct these issues and enhance the clarity and precision of the writing.

Author Response

General Comment: The manuscript is a well-designed, timely, and significant study that advances understanding of riparian controls on riverine N₂O emissions, but it needs minor revision before publishing.

General response: We sincerely thank the reviewer for the positive and encouraging evaluation of our manuscript. We appreciate the recognition of the study as well-designed, timely, and significant in advancing the understanding of riparian controls on riverine N₂O emissions. We have carefully addressed all comments and suggestions provided by the reviewer and have made corresponding revisions throughout the manuscript. We believe that these revisions have improved the clarity, rigor, and overall quality of the study, and we hope that the revised version now meets the requirements for publication.

 

Comment1: Sampling replication: The study uses six groups across two seasons, but more spatial replicates within each riparian type would strengthen statistical robustness.

Response1: We thank the reviewer for this constructive suggestion. We agree that increasing spatial replication within each riparian type would improve statistical robustness. In this study, the sampling design aimed to balance spatial coverage and logistical feasibility, while capturing the main contrasts between riparian types (natural vs. artificial) and seasons (spring vs. autumn) in the agricultural river network. Each group included two to three independent biological replicates, which is comparable to the replication levels used in previous field studies of riverine N₂O emissions and microbial processes.

To address this point, we have clarified the sampling design and replication strategy in the Methods section and explicitly acknowledged this limitation in the Discussion. Specifically, we added the following sentence to the Methods in the lines 121-123: “For each site and sampling period, water and sediment samples were grouped into six categories, with two to three independent biological replicates per category.”
In the discussion, we added the following sentence in lines 611-615: “This study also has limitations. Denser spatial sampling within riparian zone types would help resolve fine-scale heterogeneity and strengthen statistical power. In addition, combining diffusion-based estimates with direct water-air and sediment–water flux measurements would improve flux validation and reduce uncertainty in riverine N₂O emission estimates.” Although the current level of replication was sufficient to reveal consistent patterns in N₂O emissions, microbial functional genes, and environmental drivers, we note that future studies with denser spatial sampling within riparian types would help resolve fine-scale heterogeneity and further strengthen statistical power.

 

Comment2: Gas flux measurements: The use of multiple wind-based models is good, but inclusion of direct flux measurements (e.g., floating chambers) could validate the diffusion-based estimates.

Response2: We thank the reviewer for this valuable suggestion. We agree that direct flux measurements, such as floating chamber methods, can provide important validation for diffusion-based N₂O flux estimates. In the present study, we applied multiple widely used wind-based gas transfer models to reduce uncertainty associated with individual parameterizations and to improve the robustness of diffusion-based estimates. We added the following sentence in lines 612-615: “In addition, combining diffusion-based estimates with direct water-air and sediment-water flux measurements would improve flux validation and reduce uncertainty in riverine N₂O emission estimates.”

 

Comment3: Soil-water exchange: The study acknowledges that IPCC methods ignore water–soil N₂O exchange, but more direct measurements of sediment-water fluxes could better constrain this process.

Response3: We thank the reviewer for this valuable comment. We agree that direct measurements of sediment–water N₂O exchange would provide more detailed constraints on N₂O dynamics at the water–soil interface. In this study, our primary focus was to evaluate riverine N₂O emissions at the river-network scale and to assess the limitations of the IPCC EF_5r approach, which does not explicitly account for sediment–water exchange processes. To address this concern, we have emphasized in the Discussion that sediment–water N₂O exchange represents an important source of uncertainty in emission estimates. We also acknowledge that future studies incorporating direct sediment–water flux measurements, such as benthic chambers or high-resolution profiling techniques, would improve process-level understanding and better constrain the contribution of sediment-water exchange to overall riverine N₂O emissions. Accordingly, we have added the following sentence to the Discussion in line 612-615: “In addition, combining diffusion-based estimates with direct water-air and sediment-water flux measurements would improve flux validation and reduce uncertainty in riverine N₂O emission estimates.”

 

Comment4: Discussion: The discussion could more explicitly reconcile why denitrification (via nirS) is dominant in gene abundance, but N fixation and ammonification genes explain most N₂O variance.

Response4: We thank the reviewer for this insightful comment. We agree that it is important to clarify why nirS-type denitrification dominates in gene abundance, whereas nitrogen fixation (nifH) and ammonification (ureC) genes explain a larger proportion of the variability in N₂O emissions.

To address this point, we have revised the Discussion to explicitly reconcile this apparent discrepancy. Specifically, in Lines 557-562, we now emphasize that “Together with nitrogen fixation, ammonification represented an upstream process that controls the supply of reduced nitrogen substrates (e.g., NH₄⁺ and NO₂^-), thereby exerting a strong influence on downstream N₂O production potential. Although these pathways did not directly generate N₂O, their variability affects N₂O emissions by regulating substrate availability and redox conditions.” In addition, in Lines 578-582, we added that “The consistently high nirS abundance across sites and seasons indicated that denitrification represents a baseline and persistent N₂O-producing capacity in the system. However, because nirS abundance showed relatively limited spatial and temporal variability, it explained less variation in N₂O emissions than upstream functional genes such as nifH and ureC.”

 

Comment5: References: Include more recent reviews on riverine N₂O (e.g., 2022–2023) and consider citing studies on artificial vs. natural riparian effects from non-agricultural systems for broader context.

Response5: We thank the reviewer for this helpful suggestion. In response, we have expanded the reference list to include more recent reviews (2022–2023) on riverine and aquatic N₂O emissions, and we have also incorporated studies addressing differences between artificial and natural aquatic systems to provide a broader contextual framework. Specifically, we added two recent review articles to the manuscript:

(1) A review of indirect N₂O emission factors from artificial agricultural waters, which directly addresses the uncertainty and variability of emission factors in managed aquatic systems; and
(2) Hotspots and future trends of estuarine nitrogen cycle: A bibliometric review, which provides an updated synthesis of nitrogen cycling processes across aquatic environments.

In addition, we strengthened the contextual discussion by incorporating recent syntheses in the Discussion (Lines 587-589), stating: “Consistent with this mechanism, previous syntheses have shown that DOC. NO₃^- ratios strongly regulate aquatic N₂O dynamics, with lower ratios favoring higher N₂O accumulation [1].”

We also broadened the microbial perspective in the Introduction (Lines 66–67) by adding: “Microbial communities are highly diverse, comprising bacteria, archaea, fungi, and protozoa. These microorganisms play pivotal roles in the microbial N cycling[2]. ”

 

Comment 6: Acknowledge limitations (e.g., single geographic region, two-season sampling) and suggest future multi-year, multi-region studies.

Response 6: We thank the reviewer for this valuable suggestion. We acknowledge that this study is based on a single geographic region and two seasonal sampling campaigns, which may limit the generalization of the results across broader spatial and temporal scales.

The following text has been added to the Discussion in 611-615: “This study also has limitations. Denser spatial sampling within riparian zone types would help resolve fine-scale heterogeneity and strengthen statistical power. In addition, combining diffusion-based estimates with direct water-air and sediment-water flux measurements would improve flux validation and reduce uncertainty in riverine N₂O emission estimates.”

 

 

Comment 7: There are recurring grammatical errors (especially in article usage and tense consistency), typographical inconsistencies in units and symbols, and several overly complex sentences that hinder readability. We recommend a comprehensive proofread by a native English speaker or a professional editing service to correct these issues and enhance the clarity and precision of the writing.

Response 7: We thank the reviewer for this helpful and constructive comment. In response, the revised manuscript has undergone a comprehensive language revision. We carefully corrected grammatical and typographical errors, standardized units and symbols throughout the text, and simplified overly long or complex sentences to improve clarity and consistency. In addition, the manuscript was thoroughly proofread by a fluent English speaker with scientific writing experience to ensure that the language is clear, precise, and consistent.

 

 

Reference

1. Webb, J.R.; Clough, T.J.; Quayle, W.C. A review of indirect N₂O emission factors from artificial agricultural waters. Environ. Res. Lett. 2021, 16, 043005, doi:10.1088/1748-9326/abed00.
2. Liu, Y.; Feng, Y.; Han, S.; Gao, Y.; Xu, Z. Hotspots and future trends of estuarine nitrogen cycle: A bibliometric review. J. Hydrol. 2025, 657, 133056, doi:10.1016/j.jhydrol.2025.133056.

 

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have presented an interesting study. Here are some comments for incorporation:

1. There are several instances of stunted or incomplete sentences and improper word choice. Some examples are: Line 17 (constrained), line 42 (should be rivers'), line 85, lines 225-226, line 229-230, etc. Kindly read through the manuscript very carefully and update, as needed.
2. Keywords are generally different from the words used in the title.
3. Line 42: "(0.68–42 0.9 Tg·y-1", a bracket ")" is missing.
4. Throughout the manuscript, the term "riparian" is used. It is suggested to use the term "riparian zone" or "riparian region".
5. One of the key aspects of the manuscript is the differences in natural and artificial riparian zones. What % of the total riparian area is artificial? kindly mention it, as it will help in understanding the relevance and relative contribution of natural vs artificial riparian zones.
6. Kindly include a map of the study area.
7. kindly mention the volume of the samples collected and also the frequency. if the samples were collected only once or twice, kindly mention the dates as well.
8. Lines 139-140: define Cw and Ceq.
9. Line 149: "previous studies" should be supported by multiple references.
10. In Fig 1, what do "a", "b", "c" and "ab" represent? Also, what do the dashed line represent in 1(d)?
11. The details of the various IPCC and field measurement methods need to be provided in the Methods section.
12. Kindly explain, with relevant references (as needed), the differences observed between the microbial communities between different seasons.
13. With reference to Table 4 and line 379, the observations of the current study are in line with only some of the mentioned studies (in Table 4). kindly justify the differences from the mentioned studies.
14. What are the limitations of this study? kindly mention.
15. The results presented here are based on a regional experimental work. How can these results be used in a larger setting or a different riparian zone, in some other country?

Comments on the Quality of English Language

Already mentioned in the comments to the authors, above.

Author Response

Comment1: There are several instances of stunted or incomplete sentences and improper word choice. Some examples are: Line 17 (constrained), line 42 (should be rivers'), line 85, lines 225-226, line 229-230, etc. Kindly read through the manuscript very carefully and update, as needed.

Response1: We thank the reviewer for this careful and helpful comment. We agree that the previous version of the manuscript contained several stunted or incomplete sentences and instances of improper word choice. In the revised manuscript, we have carefully re-read the entire text and corrected these issues throughout.

Line 18 “constrained” was revised to “unclear.”

line 42, revised to “global riverine N₂O emissions range.”

line 85, revised to “global river’ N₂O emissions”

lines 264-265, revised to “Gas transfer velocities (k, cm h^-1) were calculated using seven widely accepted wind-based models (LM1986, RH2006, W1992, F2007, CC1998, N2000, and RC2001).”

line 267-268, revised to “EF_5r-e, e.g., the ratio of dissolved N₂O/NO₃⁻, ranged from 0.101 to 0.161% (0.130 ± 0.019), and about half of the most recent value from the IPCC (0.26%; 2019) (Figure 1d).”

In addition to these specific corrections, we conducted a comprehensive language revision to improve sentence structure, word choice, and overall clarity throughout the manuscript.

 

Comment2: Keywords are generally different from the words used in the title.

Response2: We thank the reviewer for this helpful comment. In response, we have revised the list of keywords to improve consistency with the terminology used in the title and main text. The updated keywords are: Nitrous oxide emissions; Riparian zones; Microbial processes; Emission factor. These keywords more accurately reflect the core themes of the study and align more closely with the wording of the title, thereby enhancing the clarity and discoverability of the manuscript.

 

Comment3: Line 42: "(0.68-42 0.9 Tg·y-1", a bracket ")" is missing.

Response3: We thank the reviewer for pointing out this typographical error. The missing closing bracket at Line 43 has been corrected in the revised manuscript. “…from 0.68 to 0.9 Tg·y^-1,”

 

Comment 4: Throughout the manuscript, the term "riparian" is used. It is suggested to use the term "riparian zone" or "riparian region".

Response4: We thank the reviewer for this helpful suggestion. In response, we have revised the manuscript to improve terminological consistency by replacing the term “riparian” with “riparian zone” as appropriate throughout the text. This revision enhances clarity and ensures a more precise description of the spatial context considered in the study.

Comment 5: One of the key aspects of the manuscript is the differences in natural and artificial riparian zones. What % of the total riparian area is artificial? Kindly mention it, as it will help in understanding the relevance and relative contribution of natural vs artificial riparian zones.

Response5: We thank the reviewer for this insightful comment. We agree that clarifying the prevalence of artificial riparian zones is important for understanding their relevance and relative contribution compared to natural riparian zones. In the study area, artificial riparian zones are widespread and represent a substantial proportion of riverbanks, reflecting long-term channel modification and bank reinforcement associated with intensive agricultural management. To address this point, we have added the following statement to the manuscript (Lines 108-111): “Artificial riparian zones were widespread in the region and constitute a substantial proportion of riverbanks, providing an ideal setting to compare natural and artificial riparian influences on riverine processes.”

 

Comment 6: Kindly include a map of the study area.

Response 6: We thank the reviewer for this helpful suggestion. In response, we have added a map of the study area to the Supporting Information as Figure S1, which illustrates the geographic location of the study region and the sampling sites.

 

Comment 7: kindly mention the volume of the samples collected and also the frequency. if the samples were collected only once or twice, kindly mention the dates as well.

Response 7: We thank the reviewer for this helpful comment. In response, we have clarified the sample volume, sampling frequency, and sampling dates in the Methods section. We thank the reviewer for this helpful comment. In response, we have clarified the sample volume, sampling frequency, and sampling dates in the Methods section. Specifically, during each sampling event, all in situ physicochemical parameters were measured three times, and mean values were used for subsequent analyses. Surface water samples (1 L) were collected at each site using a portable water sampler, and sediment samples were collected from the top 0-10 cm layer using a grab sampler. These details have been added to the revised manuscript (Lines 135-137). Sampling was conducted during two representative seasons: 6-9 October 2021 (autumn) and 22-24 April 2022 (spring). This information has been clarified in Lines 116-117.

 

Comment 8: Lines 139-140: define Cw and Ceq.

Response 8: We thank the reviewer for this helpful comment. In response, we have clarified the definitions of C_w and C_eq in the Methods section. Specifically, we added the following definitions in Lines 160-163: “The equilibrium concentration of N₂O in water (C_eq) was estimated using the global mean atmospheric N₂O concentration of 329 ppb. For the IPCC-based approach, the dissolved N₂O concentration in water (C_w) was calculated by multiplying the field-measured NO₃^--N concentration by the default IPCC emission factor EF_5r (0.26%).”

 

Comment 9: Line 149: "previous studies" should be supported by multiple references.

Response 9: We thank the reviewer for this helpful comment. In response, we have revised the relevant sentence at Line 149 and added multiple appropriate references to support the statement referring to “previous studies.” These additional citations strengthen the scientific basis of the statement and improve the completeness of the literature support in the revised manuscript.

 

Comment 10: In Fig 1, what do "a", "b", "c" and "ab" represent? Also, what do the dashed line represent in 1(d)?

Response 10: We thank the reviewer for this helpful comment. In response, we have clarified the meaning of the letters and dashed lines in the figure caption of Figure 1. Specifically, the letters “a”, “b”, “c”, and “ab” indicate statistically significant differences among groups based on one-way analysis of variance (ANOVA) followed by post hoc multiple comparisons. Differences among groups were tested using one-way analysis of variance (ANOVA), with significance set at P < 0.05. In panel (d), the dashed line indicates the IPCC default EF_5r value (0.26%). These explanations have now been explicitly added to the figure caption.

 

Comment 11: The details of the various IPCC and field measurement methods need to be provided in the Methods section.

Response 11: We thank the reviewer for this helpful comment. In response, we have expanded the Methods section to clarify the key steps involved in both the IPCC-based approach and the field measurement methods. Specifically, the calculations of dissolved N₂O saturation and N₂O emission rates have now been explicitly described in the main Methods section to improve transparency and readability. Additional methodological details, including the calculation of dissolved N₂O concentration, saturation, and emission rates, are provided in the Supporting Information as Method S1: Calculation of N₂O dissolved concentration, saturation and emission rates. Furthermore, the formulations used to estimate the gas transfer velocity (k, m h^-1) based on different wind-based models are summarized in Table S1: Formulations for estimating the gas transfer velocity. Together, these revisions provide a complete and detailed description of both IPCC-based and field measurement methods while keeping the main text concise.

 

Comment 12: Kindly explain, with relevant references (as needed), the differences observed between the microbial communities between different seasons.

Response 12: We thank the reviewer for this helpful comment. In response, we have expanded the Discussion to better explain the seasonal differences observed in microbial community composition, supported by relevant literature.

Specifically, we added the following discussion in Lines 525–530: “Module III represents a phototrophy-driven regime dominated by Cyanobacteria and strongly shaped by seasonal dynamics. The enrichment of Cyanobacteria in spring indicates a close coupling between primary production and downstream nitrogen cycling. Through photosynthetic exudation and biomass turnover, Cyanobacteria supply labile organic carbon, which can indirectly stimulate heterotrophic denitrification in sediments and overlying water [2]. In addition, diel oxygen fluctuations associated with photosynthesis and respiration generate transient redox gradients that favor incomplete denitrification and episodic N₂O release. Beyond these indirect effects, growing evidence suggests that phototrophic microorganisms can directly produce N₂O from nitrite under oxic or redox-fluctuating conditions, highlighting Module III as a potential seasonal source of N₂O.”

In addition, we further clarified the seasonal drivers of microbial activity and N₂O dynamics in Lines 544–548:”Higher N₂O concentrations in spring than in autumn can therefore be attributed to lower river discharge, higher nitrogen availability, and a greater proportion of labile, protein-like DOM, which together promote microbial activity and N₂O production. In contrast, increased discharge and more refractory DOM inputs in autumn dilute nitrogen substrates and suppress N₂O accumulation [50].” These additions explicitly link seasonal hydrological conditions, DOM quality, and microbial community shifts to the observed seasonal differences in N₂O production.

 

Comment 13: With reference to Table 4 and line 379, the observations of the current study are in line with only some of the mentioned studies (in Table 4). kindly justify the differences from the mentioned studies.

Response 13: We thank the reviewer for this important comment. We agree that the observations of the current study are consistent with only some of the studies listed in Table 4, and we have now clarified the reasons for these differences in the Discussion. These clarifications have been added to the revised Discussion section (line 414-423) to better contextualize our results within the broader literature: “In particular, our results were consistent with observations from moderately eutrophic rivers such as the Yangtze River mainstem [3] and the Wensum River[4], but substantially lower than values reported for highly nutrient-enriched watersheds, including the Taihu [5] and Chaohu basins [6]. The rivers and watersheds exhibiting higher N₂O emission rates and EF_5r values (e.g., Taihu and Chaohu) are typically characterized by intense eutrophication, elevated nitrogen inputs, and strong organic matter enrichment, which promote high N₂O supersaturation and emission. In contrast, river systems with lower N₂O fluxes, such as the Yangtze River mainstem and rivers on the Tibetan Plateau, generally experience lower nutrient concentrations, higher dissolved oxygen levels, or reduced residence times, which constrain incomplete denitrification and N₂O accumulation.”

 

Comment 14: What are the limitations of this study? Kindly mention.

Response 14: We thank the reviewer for this important comment. In response, we have explicitly acknowledged the limitations of this study in the Discussion section. “This study also has limitations. Denser spatial sampling within riparian zone types would help resolve fine-scale heterogeneity and strengthen statistical power. In addition, combining diffusion-based estimates with direct water-air and sediment-water flux measurements would improve flux validation and reduce uncertainty in riverine N₂O emission estimates.” These limitations and future directions have now been clearly stated in the revised manuscript in lines 611-615.

 

Comment 15: The results presented here are based on a regional experimental work. How can these results be used in a larger setting or a different riparian zone, in some other country?

Response 15: We thank the reviewer for this important comment. We agree that the present study is based on a regional investigation, and it is therefore necessary to clarify how the findings can be applied to broader spatial contexts or to riparian zones in other countries.

Although the data were collected from an agricultural river network in eastern China, the key mechanisms identified in this study are not region-specific. Our results highlight several general and transferable controls, including (1) the strong influence of riparian type (natural versus artificial) on carbon and nitrogen availability, (2) the dominant role of microbial nitrogen cycling pathways in regulating N₂O production, and (3) the limitations of applying a uniform IPCC EF_5r emission factor to heterogeneous river systems. These factors are common features of agricultural river networks worldwide and are therefore relevant beyond the study region.

To clarify this broader applicability, we have revised the Discussion in Lines 614–618 to state: “While the specific magnitudes of N₂O emissions may vary among countries due to differences in climate, hydrology, and land use, the identified relationships provide a conceptual and methodological basis for assessing riverine N₂O emissions and refining emission factors in diverse agricultural landscapes.”

Reference

1. Huang, Y.Y.; Li, P.P.; Chen, G.Q.; Peng, L.; Chen, X.C. The production of cyanobacterial carbon under nitrogen-limited cultivation and its potential for nitrate removal. Chemosphere 2018, 190, 1-8, doi:10.1016/j.chemosphere.2017.09.125.
2. Li, J.R.; Liang, E.H.; Deng, C.F.; Li, B.; Cai, H.T.; Ma, R.Q.; Xu, Q.; Liu, J.J.; Wang, T. Labile dissolved organic matter (DOM) and nitrogen inputs modified greenhouse gas dynamics: A source-to-estuary study of the Yangtze River. Water Res. 2024, 253, 121318, doi:10.1016/j.watres.2024.121318.
3. Yan, W.; Yang, L.; Wang, F.; Wang, J.; Ma, P. Riverine N₂O concentrations, exports to estuary and emissions to atmosphere from the Changjiang River in response to increasing nitrogen loads. Global Biogeochem. Cy. 2012, 26, GB4006, doi:10.1029/2010GB003984.
4. Hama-Aziz, Z.Q.; Hiscock, K.M.; Cooper, R.J. Indirect Nitrous Oxide Emission Factors for Agricultural Field Drains and Headwater Streams. Environmental Science & Technology 2017, 51, 301-307, doi:10.1021/acs.est.6b05094.
5. Song, K.; Senbati, Y.; Li, L.; Zhao, X.; Xue, Y.; Deng, M. Distinctive Microbial Processes and Controlling Factors Related to Indirect N2O Emission from Agricultural and Urban Rivers in Taihu Watershed. Environmental Science & Technology 2022, 56, 4642-4654, doi:10.1021/acs.est.1c07980.
6. Zhang, W.S.; Li, H.P.; Xiao, Q.T.; Jiang, S.Y.; Li, X.Y. Surface nitrous oxide (N2O) concentrations and fluxes from different rivers draining contrasting landscapes: Spatio-temporal variability, controls, and implications based on IPCC emission factor. Environmental Pollution 2020, 263, doi:10.1016/j.envpol.2020.114457.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I believe the authors have adequately addressed all of my comments and suggestions, and I accept the paper in its current version.

Author Response

Comment1: I believe the authors have adequately addressed all of my comments and suggestions, and I accept the paper in its current version.

Response1：We sincerely thank the reviewer for the positive evaluation of our manuscript. We greatly appreciate the time and effort invested in reviewing our work and for the constructive comments and suggestions provided throughout the review process. We are pleased that the revisions have adequately addressed all concerns, and we thank the reviewer for recommending acceptance of the manuscript in its current form.

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have incorporated most of the comments. Pls. check if you have included the response to comment#15 in your manuscript. It's mentioned in the "response to reviewer comments", however, I was unable to find it in the revised manuscript.  

Author Response

Comment1: The authors have incorporated most of the comments. Pls. check if you have included the response to comment#15 in your manuscript. It's mentioned in the "response to reviewer comments", however, I was unable to find it in the revised manuscript.  

Response1: We thank the reviewer for carefully checking the revised manuscript and for pointing out this omission. We apologize for the oversight during the revision process. We have now carefully revised the manuscript and ensured that the corresponding content addressing Comment #15 has been fully incorporated into the Discussion section. 

Comment 15: The results presented here are based on a regional experimental work. How can these results be used in a larger setting or a different riparian zone, in some other country?

Response 15: We thank the reviewer for this important comment. We agree that the present study is based on a regional investigation, and it is therefore necessary to clarify how the findings can be applied to broader spatial contexts or to riparian zones in other countries.

Although the data were collected from an agricultural river network in eastern China, the key mechanisms identified in this study are not region specific. Our results highlight several general and transferable controls, including (1) the strong influence of riparian type (natural versus artificial) on carbon and nitrogen availability, (2) the dominant role of microbial nitrogen cycling pathways in regulating N₂O production, and (3) the limitations of applying a uniform IPCC EF_5r emission factor to heterogeneous river systems. These factors are common features of agricultural river networks worldwide and are therefore relevant beyond the study region.

To clarify this broader applicability, we have revised the Discussion in Lines 617-620 to state: “Although absolute N2O emission magnitudes may vary among regions due to differences in climate, hydrology, and land use, the mechanisms identified here provide a transferable framework that can be tested and refined across broader spatial and temporal scales.”