General Comments

This manuscript investigates how alpine wetland degradation affects soil nitrogen (N) cycling through the lens of enzyme activities in the Gahai Wetland on the Qinghai-Tibet Plateau. The authors employ a three-year field study across four degradation stages, measuring four key N-cycling enzymes (urease, protease, nitrate reductase, nitrite reductase) and developing a novel Nitrogen Cycling Functional Balance (NCFB) index to assess the coordination between hydrolytic and reductive functions.

General Comment: Novelty and Contribution

This manuscript addresses an important knowledge gap concerning how alpine wetland degradation restructures soil nitrogen cycling, moving beyond descriptive assessments of individual enzyme activities to evaluate functional coordination between complementary N-transformation pathways. The novelty lies in three key aspects: (1) the development of a Nitrogen Cycling Functional Balance (NCFB) index that integrates hydrolytic and reductive enzyme functions into a single metric, providing a framework for quantifying functional reorganization rather than simply measuring activity levels; (2) the demonstration that degradation induces enzyme-specific divergent responses—urease and nitrate reductase increasing while protease and nitrite reductase decline—revealing that soil N cycling undergoes pathway-specific restructuring rather than uniform suppression; and (3) the multi-year temporal design that captures how interannual hydroclimatic variability, particularly drought, amplifies degradation-induced functional decoupling. The contribution is significant in providing a mechanistic understanding of how hydrological drying and resource depletion drive N-cycling destabilization in alpine wetlands, with implications for restoration priorities in these vulnerable ecosystems. The work is suitable for publication in SOIL, as it addresses soil biogeochemical cycling in a globally important ecosystem under anthropogenic pressure, though substantial revision is needed to address limitations related to potential enzyme assays, space-for-time substitution assumptions, and causal inference.  With careful revision addressing these issues, the manuscript would make a valuable contribution to SOIL. The multi-year design, enzyme-specific responses, and functional balance approach are significant strengths that merit publication after substantial revision.

Major Comments

1. Potential vs. in-situ enzyme activities (Section 2.5 and Discussion)

The authors measure potential enzyme activities under optimized laboratory conditions (24-hour incubation at constant temperature with excess substrate). However:

-Redox sensitivity: Nitrate reductase and nitrite reductase are particularly sensitive to redox conditions. Measuring them under aerobic laboratory conditions may not reflect in-situ activities in wetland soils, where anaerobic microsites and fluctuating redox conditions are critical for denitrification-related processes.

- Substrate availability: The NCFB index is calculated from potential activities measured under optimal conditions, not from actual rates constrained by in-situ substrate availability. This may overstate functional imbalances if the actual rates are co-limited by substrates.

- Enzyme stability: Some soil enzymes can remain active after extraction or in stored samples, potentially overestimating activity.

Required revisions:

- Add a dedicated subsection in the Discussion addressing the limitations of potential enzyme assays for inferring in-situ N cycling

- Discuss how potential activities might differ from in-situ rates, particularly for redox-sensitive enzymes

- Consider whether the NCFB index should be interpreted as "functional potential" rather than "functional balance"

- If possible, compare potential activities with any available in-situ rate measurements or cite literature on the relationship between potential and actual enzyme activities in similar systems

1. Space-for-time substitution assumptions (Section 2.2)

The authors use space-for-time substitution but do not adequately address its limitations. The four degradation stages are described as representing a degradation gradient, but:

- Were sites matched for parent material, topography, and historical land use?

- Is there evidence that the sites represent a true chronosequence (e.g., historical aerial photos, local knowledge of degradation timing)?

- Could differences among sites reflect inherent spatial heterogeneity rather than degradation stage?

Required revisions:

- Provide more information on how degradation stages were delineated (Table S1 is mentioned but not shown in the main text)

- Discuss the assumptions of space-for-time substitution and how the study design mitigates potential confounding factors

- If available, provide evidence that the sites represent a degradation trajectory (e.g., historical data, local knowledge)

1. Definition and interpretation of the NCFB index (Section 2.6, and Discussion)

The NCFB index is a central contribution, but its interpretation requires clarification:

- Why is the balance defined as hydrolytic minus reductive functions? This assumes that higher values are "better" (more coordinated), but this is a value judgment that may not be universally valid.

- What is the ecological significance of the shift from negative to positive correlation between hydrolytic and reductive functions (Figure S4)? The authors note this change but do not fully explain its meaning.

- Could the NCFB shift simply reflect changes in the relative abundance of different microbial groups rather than functional reorganization?

Required revisions:

- Provide a more explicit justification for the NCFB index formulation

- Explain what a "balanced" vs. "imbalanced" N-cycling system means in terms of ecosystem function

- Discuss alternative interpretations of the NCFB shift (e.g., microbial community composition changes, not just functional reorganization)

1. Carbon limitation as a driver (Section 4.1, Figure 5)

The SEM shows that SOC has a direct negative effect on NCFB (Figure 5b), which seems counterintuitive—higher SOC is associated with lower NCFB. This requires explanation:

- Is this a statistical artifact or a real ecological relationship?

- Does the negative relationship between SOC and NCFB reflect the fact that SOC includes recalcitrant carbon that does not support microbial activity?

- The authors focus on hydrological limitation but the SEM suggests more complex interactions with carbon availability.

Required revisions:

- Provide a more detailed interpretation of the negative SOC-NCFB relationship

- Consider whether the measure of SOC (total organic carbon) adequately captures the labile carbon fraction that drives microbial enzyme production

- Discuss whether the model should be refined to include a labile carbon pool

1. Hydroclimatic variability and drought effects (Section 3.3, 4.3)

The authors identify year 2020 as dry and 2021 as wet (implied), but the precipitation data are in the supplement (Figure S1) and the specific values are not presented in the main text:

- What were the actual precipitation amounts for 2019, 2020, and 2021?

- Are these departures from long-term averages significant?

- The conclusion that "drier conditions amplifying degradation effects" is important but needs quantitative support.

Required revisions:

- Present key precipitation statistics in the main text or clearly reference the supplement

- If possible, quantify the interaction between year (wet/dry) and degradation stage using statistical tests (the mixed models in Table 2 do not include year × degradation interactions)

- Discuss the implications of these findings for projections of future climate change effects on alpine wetlands

Minor Comments

1. Line 8: "three-year field investigation" - the methods describe sampling from 2019-2021, but the dates are not specified in the abstract. Consider adding "across 2019-2021" to the abstract.

1. Lines 135-140: The NCFB index is defined using z-scores. However, z-score standardization across all samples may be sensitive to outliers and assumes normal distributions. Please discuss this and consider alternative standardization approaches if appropriate.

1. Section 2.7: The statistical methods are generally appropriate, but:

- Why were Tukey's HSD tests used for multiple comparisons rather than, say, Dunnett's test (which compares each treatment to a control)?

- Were data transformation and the assumptions of the mixed models (normality, homogeneity of variance) checked and reported?

- The linear mixed models are described but the model specification (random intercepts only? random slopes?) is not fully detailed.

1. Figure 1: The enzyme-specific responses are clearly presented. However:

- The y-axis scales differ substantially among enzymes, making comparisons difficult. Consider adding a supplementary figure with standardized scales or including the ranges in the caption.

- The statistical comparisons are based on data aggregated across years and depths. Consider whether this aggregation masks important variation.

1. Figure 4: The RDA and correlation analyses are useful but:

- The RDA explains 66.2% and 8.62% of variation on axes 1 and 2, but the interpretation of axis 2 is not discussed.

- The "circle size" in Figure 4c is visually informative but the legend should clearly explain what it represents.

1. Lines 202-203: "the timing of maximum activity differed among enzymatic pathways" - this is an interesting observation that merits more discussion. What controls these differences in seasonal timing? Consider discussing this in relation to plant phenology, substrate availability, and environmental conditions.

1. Lines 207-213: The generalized additive mixed models (GAMMs) are mentioned briefly but the results are not shown. Please either present the GAMM results or remove the reference. If results are in the supplement, please cite the relevant figure.

1. Table 1: The table shows means ± standard deviation but does not indicate sample size. Please add n values to the table or footnote.

1. Table 2: The table shows F-values but not degrees of freedom. Please add df values or indicate that these are approximate F-tests from mixed models. Also, note that the table shows only main effects, but the text discusses interactions between degradation and year. Please clarify whether interactions were tested and, if not, why not.

Editorial/Technical Comments

- Line 37: "wetland health and soil functional status" - consider defining "health" more precisely

- Line 27 and 96: "overgrazing" - the introduction mentions overgrazing as a driver but the methods do not describe how grazing intensity was assessed or whether grazing was controlled across sites. Please clarify.

- Line 101: "space-for-time substitution" - this approach is used but the justification for assuming that sites represent a degradation trajectory needs more clarification.

- Line 107: The sampling design is described but the number of replicates and the randomization scheme should be clarified

- Lines 172-174: The statement that "non-degraded wetlands maintained substantially higher SWC, NH₄⁺-N, and MBN" is supported by the data in Table 1, but the declines are large (SWC from 0.45 to 0.14 m³·m³; MBN from 45.26 to 29.45 mg·kg⁻¹). The ecological implications of these magnitudes could be discussed more explicitly.

This manuscript reports how degradation restructures enzyme-mediated soil nitrogen (N) cycling and its functional balance in alpine wetlands, based on a three-year field investigation across four degradation stages (non-degraded [ND], lightly degraded [LD], moderately degraded [MD], and heavily degraded [HD]) in the Gahai Wetland. The findings are novel and provide useful insights into the mechanisms underlying soil N cycling destabilization in degraded alpine wetlands, offering valuable implications for wetland restoration under a drier future climate. However, several key issues require clarification prior to publication. In particular, the delineation criteria for the four degradation stages remain unclear, and the lack of significant differences among the LD, MD, and HD stages in key figures (e.g., Figure 3) calls into question whether these four stages are distinct or appropriately defined. Furthermore, while the authors introduce a Nitrogen Cycling Functional Balance (NCFB) index, its functional significance and integration throughout the Abstract and main text are insufficiently articulated. I recommend a Moderate Revision to address these points.

Specific Comments

1. Lines 8–11: The authors state that four degradation stages were selected in the Gahai Wetland; however, the subsequent results are not linked to these individual stages and instead refer broadly to "degradation." What is the importance and rationale for selecting four distinct degradation stages? Additionally, while the Nitrogen Cycling Functional Balance (NCFB) index is introduced in the Abstract, it is not revisited in the subsequent results presented in the Abstract. What is the main motivation for developing this index?
2. Lines 69–70: Please introduce and explicitly define the criteria used to classify the four stages of alpine wetland degradation.
3. Lines 87–88: I suggest replacing the older FAO classification with the World Reference Base for Soil Resources system (WRB, 4th edition, 2022) for soil classification.
4. Lines 84–90: Please add relevant literature references to support these site descriptions and baseline soil characterizations.
5. Lines 100–105: It is critical to explain how the four degradation stages were delineated in the field. However, this information is missing from both the main text and the Supporting Information. Please provide the explicit diagnostic indicators (e.g., vegetation cover, water table depth, soil physical properties).
6. Lines 135–139: The NCFB index was calculated as the standardized difference between hydrolytic and reductive enzyme functions. Why was a difference metric chosen rather than a ratio? A difference metric can generate negative values depending on standardization, whereas a ratio would not be affected by baseline shifts and may offer easier cross-study comparability.
7. Lines 167–176 and Table 1: The manuscript lacks a map of the study area and sampling sites. Furthermore, can the physical and chemical properties listed in Table 1 statistically distinguish the ND, LD, MD, and HD plots? If so, I recommend adding an ordination diagram (e.g., PCA or PCoA) to illustrate the separation among the four degradation stages. If not, consider integrating these properties into the enzyme-specific response sections.
8. Line 218: Are only mean enzyme activities plotted in Figure 2? Please state this explicitly in the figure caption.
9. Line 233: Figure 3 is key to this work, yet there are no statistically significant differences among LD, MD, and HD. Does this lack of differentiation suggest that the four-stage degradation framework may be over-resolved or improperly categorized for these soils?
10. Line 265: In Figure 5a, the distinction between "Degradation" and "NCFB" as independent variables/paths is unclear. Please clarify how "Degradation" was operationalized quantitatively versus "NCFB."