the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Mar 2026
Soil water content and salinity regulate the temperature sensitivity of CO2 and CH4 emissions in a coastal salt-affected land
Abstract. Soil carbon emissions from coastal saline-alkaline ecosystems significantly influence the global carbon cycle, yet their responses to key environmental drivers such as soil water content and salinity remain insufficiently understood. This study employed controlled incubation experiments using soils collected from the Yellow River Delta, China, to systematically investigate the effects of varying soil water content (5 %, 15 %, 30 %, 45 %, and 60 %) and salinity levels (S1: EC=1.9 dS/m; S2: 10.8 dS/m; S3: 58.8 dS/m; S4: 66.3 dS/m; S5: 96.0 dS/m) on CO2 and CH4 emissions and their temperature sensitivity (Q10). The results demonstrated that under constant temperature conditions, CO2 emission flux followed a unimodal pattern in response to increasing soil water content, peaking at 45 % water content, with CH4 flux exhibiting a similar trend. Soil salinity significantly suppressed the fluxes of both greenhouse gases, with reductions observed across all temperature levels as salinity increased. Both soil water content and salinity played substantial regulatory roles in modulating the Q10 of gas emissions. Specifically, Q10 values for CO2 and CH4 initially decreased and then increased with rising soil water content. Along the salinity gradient, the Q10 of CO2 decreased from S2 to S4, whereas the Q10 of CH4 increased progressively from S2 to S5. These findings reveal the complex and interactive effects of soil water content and salinity on carbon cycling processes in coastal saline-alkaline lands. The study provides crucial theoretical insights for improving the prediction of carbon cycle dynamics under climate change and offers a scientific basis for the adaptive management and conservation of these vulnerable ecosystems.
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CC1: 'Comment on egusphere-2026-217', Jinsheng Li, 03 Apr 2026
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AC3: 'Reply on CC1', Chao Yang, 06 Aug 2026
We sincerely thank you for the constructive comments, which have helped us improve the manuscript. We have carefully addressed and provided responses below.
Comment: All percentage-based soil water content values in the manuscript must clearly specify the reference basis. For example, 60% water content could be interpreted in multiple ways: 60% of total soil volume as water (volumetric water content); water mass as 60% of dry soil mass (gravimetric water content); water occupying 60% of total soil pore space (water saturation); or water reaching 60% of field capacity. Clearly defining the water content metric is essential for accurate interpretation of the results.
Response: We sincerely thank the editor for this critical technical correction, which eliminates ambiguity for readers from different disciplinary backgrounds. We have reviewed the entire manuscript and uniformly standardized all water content expressions, explicitly specifying that they all refer to gravimetric water content.
Revised text in the manuscript: We conducted a line-by-line review of the entire manuscript (Abstract, Introduction, Methods, Results, Discussion, all figure captions, and table footnotes). All percentage water content values have been uniformly annotated with the standard definition: gravimetric water content (g water per 100 g dry soil). The annotation has been applied consistently at every occurrence of water content values throughout the text.
Citation: https://doi.org/10.5194/egusphere-2026-217-AC3
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AC3: 'Reply on CC1', Chao Yang, 06 Aug 2026
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RC1: 'Comment on egusphere-2026-217', Anonymous Referee #1, 12 Apr 2026
The authors provide a straightforward analysis of soil CO2 and CH4 emissions under different soil water content and salinity levels. The results suggest that both greenhouse gases peak at ~45% water content and increase as salinity levels increase. The results also show that soil water content and salinity affect the temperature sensitivity (Q10) of CO2 and CH4 differently, indicating predictions of carbon cycling in coastal regions should include soil water content and salinity under climate change.
The experimental design appears sound, and the approach is appropriate for addressing the research question. However, I recommend providing a more detailed description of the methods to ensure readers can fully follow the experimental setup.
Comments:
Line 12 (Abstract): “Soil carbon emissions” – change to “Soil CO2 and CH4 emissions”
Line 80 – 85 (Methods): For better understanding of the results and discussion, it would be helpful to provide more detail on the study site conditions and the ecological meaning of the manipulated soil water content. For example, does this represent tidal ecosystems, wetlands, or systems influenced by freshwater-saltwater mixing?
Line 87 – 97 (Methods): “In May 2022” – can add a brief seasonal description for May. Clarify the sample characteristics: “Line 87: soil sampling was conducted across the main salinity gradients of the study area” vs. “Line 91: Soils from points with identical vegetation types were composited” vs. “Line 96: soils were categorized into five salinity gradients” – do the composited samples represent salinity gradients or vegetation type?
Line 99 – 108 (Methods): Please provide more detail on the incubation setup. For example:
- were soils from 0–20 cm mixed and then packed into PVC columns?
- what chemicals were used to establish different salinity and soil water content treatments?
- what was the initial water content of the soil samples?
- how was soil water content set and monitored during incubation?
- was soil water content measured on a gravimetric or volumetric basis?
- may need to consider the effect of drying and rewetting on microbial activity (e.g., Beem et al., 2021).
Line 107, 113 (Methods): “Flux measurements were conducted over a 10-day period…” – clarify measurement frequency (e.g., once after stabilization?). Measurement time (9–11 am) may not be relevant in a controlled incubation where temperature is maintained continuously.
Line 116 – 118 (Methods): Please clarify the dependent variables. Why was one- or two-way ANOVA used instead of a three-way ANOVA?
Figures: Figures 1 and 2 appear to contain similar information as Figures 3 and 4, with only different visualization styles (bar vs. scatter). Figures 5–6 also seem similar to Figures 7–8. Where do the scatter points come from? For example, in Figure 3 at 5% water content and 5°C, Methods mention “five replicates,” but more than five points are shown – likely related to measurement frequency? Please clarify.
Citation: https://doi.org/10.5194/egusphere-2026-217-RC1 -
AC1: 'Reply on RC1', Chao Yang, 06 Aug 2026
We sincerely thank you for the constructive comments, which have helped us improve the manuscript. We have carefully addressed each point and provided point-by-point responses below.
Comment 1：Abstract, lines 12–13: "Soil CO₂ emission fluxes showed a unimodal pattern with increasing soil water content" – It is suggested to add a modifier or revise the wording to "Soil CO₂ emission fluxes exhibited a unimodal response to increasing soil water content" to improve readability.
Response: We thank the reviewer for this valuable suggestion to refine the wording in the Abstract. We have incorporated this modification into the revised manuscript.
Revised text in the manuscript: The corresponding sentence in the Abstract has been revised as follows: "Under controlled incubation conditions, the results showed that soil CO₂ emission fluxes exhibited a significant unimodal response to increasing soil gravimetric water content, with the peak occurring at the 45% water content treatment; CH₄ emission fluxes displayed a similar unimodal pattern."
Comment 2：Introduction, Hypothesis 2, lines 70–71: "Salinity increase would suppress carbon gas emission potential..." – Please revise to "This study hypothesizes that salinity increase would suppress..." to align with the hypothetical wording of Hypotheses 1 and 3.
Response: We thank the reviewer for noting the inconsistency in the wording of the three hypotheses. We have revised all hypotheses to adopt a uniform hypothetical tone.
Revised text in the manuscript: All three hypotheses have been rephrased as follows:
Hypothesis 1: "...this study hypothesizes that soil water content significantly regulates soil CO₂ and CH₄ emission fluxes and their temperature sensitivity coefficients (Q₁₀)."
Hypothesis 2: "This study hypothesizes that increasing soil salinity suppresses CO₂ and CH₄ emission potentials and alters their temperature sensitivity (Q₁₀)."
Hypothesis 3: "...this study hypothesizes that there is a significant interactive effect between soil water content and salinity on soil carbon emissions."
Comment 3：Methods, lines 90–91: "Soils from sampling points with the same vegetation type were mixed together" – Please clarify whether the soils from different points with the same vegetation type were thoroughly homogenized before subsampling, to avoid misunderstanding regarding the handling of spatial heterogeneity.
Response: We thank the reviewer for pointing out this ambiguity. We have supplemented the description with detailed operational procedures following the original sentence.
Revised text in the manuscript: A supplemental explanation has been added after the original sentence: "Soils from sampling points with the same vegetation type were mixed and homogenized by thorough stirring to obtain a composite homogenized soil sample for each vegetation type, which was then sealed in polyethylene bags and transported to the laboratory for pre-treatment and incubation experiments."
Comment 4: Results, lines 134–135: "CO₂ fluxes showed a clear unimodal correlation" – Please ensure terminology consistency with the Abstract throughout the manuscript, using either "unimodal response" or "unimodal trend" uniformly.
Response: We have identified the terminological inconsistency between the Results and Abstract sections and have revised the entire manuscript to adopt the standard wording used in the Abstract.
Revised text in the manuscript: The relevant sentence in the Results section has been revised as follows: "...CO₂ emission fluxes exhibited a significant unimodal response to the soil gravimetric water content gradient, consistent with the trend summarized in the Abstract."
Comment 5: Discussion, lines 232–234: "Substrate supply replaced activation energy as the limiting factor" – The tone is overly absolute. Please revise to "the limiting effect of substrate supply on reaction kinetics may outweigh the limiting effect of activation energy."
Response: We sincerely thank the reviewer for this linguistic refinement. The original statement overstated the absolute dominance of substrate limitation. We have revised the wording to adopt a more rigorous ecological phrasing, consistent with our tentative inference based on available evidence.
Revised text in the manuscript: The original statement: "...substrate supply replaced the activation energy required for reaction kinetics as the dominant rate-limiting factor..." has been revised to:"...the limiting effect of substrate supply on microbial respiration may outweigh the constraint imposed by the activation energy required for biochemical reactions, thereby becoming an important limiting factor controlling heterotrophic soil respiration."
Comment 6: Figures 1 and 2: The lowercase and uppercase letters used to denote significant differences are crowded. The caption should clearly state: lowercase letters indicate differences among different water content (or salinity) treatments at the same temperature, and uppercase letters indicate differences among different temperature treatments at the same water content (or salinity). Although the original text contains some description, it could be further clarified.
Response: We thank the reviewer for this suggestion to improve figure readability. We have revised the captions to clearly distinguish the definitions of lowercase and uppercase significance markers.
Revised text in the manuscript: Figure 1 caption (revised):
"Figure 1. CO₂ emission fluxes across temperature gradients under different soil gravimetric water content treatments. Lowercase letters (a, b, c...) indicate significant differences among water content treatments at the same incubation temperature (P < 0.05); uppercase letters (A, B, C...) indicate significant differences among temperature treatments at the same water content level."
Comment 7：Figures 3–8: The coefficient of determination (R²) values in each subplot are not presented with a consistent number of decimal places (e.g., 0.99 and 0.95 appear simultaneously). Please unify all R² values to two decimal places throughout the manuscript.
Response: We acknowledge the inconsistent formatting of R² values across all fitted plots. We will regenerate the figures with uniformly formatted R² values and simultaneously update all corresponding text descriptions in the manuscript.
Revised text in the manuscript: 1. All R² values displayed in figures have been rounded to two decimal places (e.g., 0.952 → 0.95; 0.99 remains 0.99).
- All textual descriptions of model goodness-of-fit (R²) in the Results and Discussion sections have been unified to two decimal places.
Comment 8: Tables 2 and 3: Please add a brief footnote explaining the meaning of parameter b and the formula for calculating Q₁₀ from b (although this is explained in the main text, tables should be independently readable). Additionally, it is suggested to highlight the minimum Q₁₀ value within each gradient group in the tables or in the notes to emphasize key results.
Response: We thank the reviewer for this practical suggestion to improve table readability and interpretability. We have added a unified footnote to both tables and have bolded the minimum Q₁₀ values for easy identification.
Revised text in the manuscript:
- A unified footnote has been added at the bottom of Tables 2 and 3:
"Footnote: Parameter b is the temperature sensitivity coefficient derived from the exponential flux model R = ae^(bT); Q₁₀ = e^(10b), representing the fold-increase in carbon gas emission rate for every 10°C increase in temperature. Bold values indicate the minimum Q₁₀ observed across the respective environmental gradient treatments."
- All minimum Q₁₀ values have been formatted in bold within the table cells.
Comment 9: Discussion, lines 255–258: The original text states that increasing salinity simultaneously reduces the abundances of both mcrA and pmoA genes. Please add a sentence explaining that net soil CH₄ emission is suppressed only when the decrease in methanogenesis (mcrA) exceeds that in methanotrophy (pmoA), or when substrate supply is insufficient, to avoid oversimplification.
Response: We fully recognize that the original text oversimplified the relationship between functional gene abundances and net methane fluxes. We have added qualifying statements to clarify the preconditions for net CH₄ suppression.
Revised text in the manuscript: The original text: "...as salinity increased, the abundance of methanogenic functional genes (e.g., mcrA) decreased, and methane oxidation-related genes (e.g., pmoA) also declined. These shifts in the overall microbial community ultimately suppressed net soil CH₄ production." has been revised to: "...as soil salinity increased, the abundance of the methanogenic marker gene mcrA decreased, while the methane-oxidizing functional gene pmoA also declined along the salinity gradient. Critically, net soil CH₄ emission
is likely to be suppressed when the salinity-induced reduction in methanogenic potential exceeded that in methanotrophic capacity, or when the availability of labile carbon substrates, rather than oxygen availability, became the primary limiting factor for methanogenic activity, thereby reducing net CH₄ production under high-salinity conditions. Collectively, these shifts in the functional gene pool contributed to the suppression of net CH₄ production under high salinity conditions. "
Comment 10: Discussion, lines 263–265: The Q₁₀ values for soil CO₂ under salinity stress reported in the literature range from 2.6 to 5.2, substantially higher than the values measured in this study (1.44–1.75). Please add a brief discussion explaining this discrepancy (e.g., ecosystem type, incubation conditions, substrate availability) to contextualize the results.
Response: We thank the reviewer for bringing attention to this apparent discrepancy. We have added a comparative discussion that unpacks the multiple factors contributing to this difference, while noting the consistent trend across all studies.
Revised text in the manuscript:
The following text has been added after the cited statement:
"...previously reported Q₁₀ values for CO₂ emission under salinity stress ranged from 2.6 to 5.2, with significant increases along salinity gradients (Yu et al., 2020; Haj-Amor et al., 2022)—values notably higher than those observed in this incubation study (1.44–1.75). This discrepancy may arise from multiple factors: first, the inherent differences in soil labile carbon substrate content across study regions, as substrate availability directly constrains the temperature sensitivity of microbial respiration; second, differences in experimental parameters (e.g., incubation duration, temperature range, moisture conditions), which directly affect Q₁₀ estimation; and third, differences in ecosystem background (inland agricultural saline soils vs. coastal saline-alkaline soils), which may lead to divergent microbial community composition and temperature adaptation strategies. Despite these numerical differences, the core trend—that increasing salinity enhances the temperature sensitivity of soil carbon mineralization—remains consistent across all referenced studies."
Comment 11: Figure 1 caption, line 452: "Significant differences among water content treatments at the same temperature are denoted by lowercase letters (P < 0.05)" – The description is clear, but the significance letters in Figure 1 are crowded. Please ensure that fonts are legible and positions are standardized.
Response: We thank the reviewer for the careful check of figure layout. During the final typesetting stage, we will adjust the font size and positions of significance markers in all bar charts to eliminate overlap and ensure uniform readability.
Revised text in the manuscript: During the final production phase, we will uniformly adjust the font sizes and coordinate positions of all significance letter markers in Figures 1 and all related bar charts to avoid visual overlap. Cross-checking will also be performed to ensure formatting consistency across all main and supplementary figures.
Citation: https://doi.org/10.5194/egusphere-2026-217-AC1
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RC2: 'Comment on egusphere-2026-217', Jan Vanderborght, 10 Jul 2026
Since it was very difficult to find reviewers and since there are two constructive review reports, I decided to post a very short review myself as editor in order to move the review process.
I think that it should be possible to address the reviewer comments and that after replying to the comments, the paper could be accepted.
I have one technical comment. When you mention soil water contents and give numbers in percentages, you should mention to what these percentages refer. A soil water content of 60% could mean several things: 60% of the total bulk soil volume is water (this is the volumetric water content); the water mass in a soil sample is 60% of the mass of the dry soil in that sample (this is gravimetric water content); the water in the soil fills 60% of the total pore space (this would be water saturation), the water in the soil corresponds to 60% of the water holding capacity of the soil (the pore space of the soil when the soil is at field capacity). It is very important that you define the water content precisely so that your results can be interpreted.
Citation: https://doi.org/10.5194/egusphere-2026-217-RC2 -
AC2: 'Reply on RC2', Chao Yang, 06 Aug 2026
We sincerely thank you for the constructive comments, which have helped us improve the manuscript. We have carefully addressed each point and provided point-by-point responses below.
Comment 1：Abstract, line 12: Please replace "soil carbon emissions" with "soil CO₂ and CH₄ emissions."
Response: We thank the reviewer for this precise suggestion to eliminate vague wording in the Abstract and to explicitly specify the two target greenhouse gases. We have incorporated this modification into the revised manuscript.
Revised text in the manuscript: The first sentence of the Abstract has been revised as follows:
"Soil CO₂ and CH₄ emissions in coastal saline-alkaline delta ecosystems play a critical role in regulating regional and global biogeochemical carbon cycles."
Comment 2: Methods, lines 80–85: To facilitate understanding of the Results and Discussion, please supplement the environmental background of the study area and the ecological significance of the water content gradients used in the experiments. For example, do these gradients simulate tidal wetlands or freshwater–seawater mixing wetlands?
Response: We agree that the ecological context of the water content gradients should be clarified. We have added a dedicated explanatory paragraph at the end of Section 2.1 (Study Area) to link each gradient level with the corresponding in situ hydrological conditions, thereby strengthening the connection between the experimental design and field reality.
Revised text in the manuscript: A new paragraph has been added at the end of Section 2.1:
"The study area is a typical coastal saline-alkaline ecosystem with significant soil salt accumulation and pronounced seasonal wet–dry alternation. The soil gravimetric water content gradient used in this experiment (5%–60%) covers the major hydrological variability observed in the field across the year: the lower end (5%) simulates extreme drought conditions during the spring dry period; the upper end (60%) represents the high-moisture state after concentrated rainfall during the rainy season; and the intermediate level (45%) approximates the average field water-holding capacity during the vegetation growing season in this region."
Comment 3: Methods, lines 87–97: "Soil sampling conducted in May 2022" – Please supplement the seasonal characteristics of May. Additionally, clarify the logical relationships among the three descriptions in the original text: "sampling along the main salinity gradient in the study area," "mixing and preparing samples from the same vegetation point," and "classifying soil samples into five salinity gradients." Readers may confuse whether the mixed samples represent salinity gradients or vegetation types.
Response: We sincerely thank the reviewer for pointing out the logical confusion in the field sampling description. This subsection has been substantially revised to establish a clear chronological sequence and to clarify the intrinsic relationships among vegetation stratification, sample homogenization, and salinity gradient classification.
Revised text in the manuscript: The field sampling paragraph has been completely revised as follows: "Soil sampling was conducted in May 2022, corresponding to the spring transition period with mild temperatures, receding tides, and rapid vegetation growth in the study area. Ten 50-m random transects were established along the full salinity gradient across the study area, with 5 sampling points evenly spaced along each transect, yielding a total of 50 surface (0–20 cm) soil core samples. Subsamples collected from points with the same vegetation community were thoroughly mixed and homogenized, then stored in sealed polyethylene bags and transported to the laboratory for pre-treatment. Within this study area, vegetation community composition serves as a reliable proxy for soil salinity; we therefore used vegetation type as the initial stratification criterion for grouping the mixed soil samples. After homogenization, the electrical conductivity (EC, measured in a 1:5 soil-to-water extract) of each composite sample was determined. Based on the measured EC values, the samples were classified into five independent salinity gradients (S1–S5). In summary, the five salinity gradients used in the subsequent incubation experiments reflect the natural distribution of salinity in the field, while vegetation distribution served only as the prior stratification criterion for spatial sampling."
Comment 4: Methods, lines 99–108: Please provide complete details of the incubation setup, including:
- Was the 0–20 cm topsoil homogenized and packed into PVC columns?
- Which chemical reagents were used to adjust the salinity and water content gradients?
- What was the initial water content of the soil samples?
- How was soil water content regulated and monitored throughout the incubation period?
- Was water content determined by gravimetric or volumetric methods?
- The potential disturbance of wet–dry alternation on microbial activity should be considered (cite Beem et al., 2021).
Response: We thank the reviewer for providing this comprehensive checklist of experimental details, which has substantially improved the reproducibility of our experiments. We have significantly expanded Section 2.3 (Incubation Experimental Design) to address each point systematically, and we have added a pre-incubation step to mitigate the effects of wet–dry cycles on microbial activity.
Revised text in the manuscript: Section 2.3 has been expanded as follows:
"Field-collected 0–20 cm topsoil was air-dried under laboratory conditions, passed through a 2-mm sieve, homogenized, and packed into cylindrical PVC incubation columns (20 cm inner diameter, 30 cm height), with a 10-cm headspace reserved at the top of each column for periodic gas sampling; the bottom was sealed to prevent water leakage (Fig. S1). All packed soils were derived from the homogenized composite samples described in Section 2.2. The initial gravimetric water content of the air-dried soils ranged from 2.0% to 3.0%. Two independent controlled incubation experiments were conducted along a continuous temperature gradient (5, 10, 15, 20, 25, 30°C) to separately evaluate the individual effects of salinity and soil water content:
- Salinity gradient incubation experiment: Five naturally saline soils (S1–S5) were adjusted to a fixed target gravimetric water content of 60%. No exogenous salts or chemical amendments were added, and the salinity differences originated entirely from the inherent salt content of the field-collected composite soils (baseline physicochemical properties shown in Table 1).
- Water content gradient incubation experiment: Only the lowest-salinity soil (S1) was used, with five target gravimetric water content levels (5%, 15%, 30%, 45%, 60%) to eliminate confounding effects from salinity gradients.
Target gravimetric water contents were achieved by slowly adding deionized water to the air-dried soils prior to packing, with repeated stirring for homogenization. Throughout the incubation period, all columns were weighed every 48 h, and evaporative water loss was compensated by adding deionized water to maintain the column weight corresponding to the preset water content, while minimizing disturbance to salt distribution within the soil columns. Incubation temperatures were precisely controlled using programmable climate chambers with an accuracy of ±0.5°C.
To reduce the potential influence of drying-rewetting disturbances on microbial activity (Beem et al., 2021), all columns were pre-incubated at their respective target temperatures for 7 days before formal measurements. This period allowed microbial activity and soil conditions to stabilize after rewetting. Following this stabilization period, gas flux measurements were conducted continuously for 10 days, with sampling every 2 days (three consecutive replicate measurements per sample, yielding five independent sampling time points per temperature gradient). The final flux value used for each PVC column was the arithmetic mean of all five time-point measurements."
Comment 5: Methods, lines 107 and 113: "Flux measurements lasted for 10 days" – Please clarify the sampling frequency (multiple measurements after stabilization). The original text indicates sampling from 9:00–11:00 a.m.; however, since the experiment was conducted in a temperature-controlled chamber without diurnal fluctuations, this detail is unnecessary and can be removed.
Response: We agree that specifying a fixed sampling time is unnecessary under constant-temperature incubation conditions. We have removed this detail and have clearly stated the sampling frequency in the expanded method description (provided in response to Comment 4 above).
Revised text in the manuscript:
- All references to "sampling between 9:00–11:00 a.m. local time" have been deleted, as the constant-temperature controlled environment makes diurnal timing irrelevant.
- The expanded experimental description now clearly states: after 7 days of pre-incubation stabilization, flux measurements were taken every 2 days over a 10-day period, yielding five temporal sampling points; the mean values were used for subsequent statistical analysis.
Comment 6: Methods, lines 116–118: Please specify the experimental observation variables and explain why one-way and two-way ANOVA were used instead of three-way ANOVA.
Response: We thank the reviewer for the detailed methodological review. We have revised the manuscript accordingly, as detailed below:
- Distinction of observational variables:
The core response variables of this experiment are the net soil CO₂ and CH₄ fluxes (direct measurements). The temperature sensitivity coefficient Q₁₀ is not a direct measurement but a derived parameter estimated by fitting an exponential model to the flux data across temperature gradients. This hierarchical distinction has been clarified in the Methods section.
- Rationale for using one-way and two-way ANOVA instead of three-way ANOVA:
A three-way full-factorial ANOVA was not applied because the experimental design consisted of two separate incubation series (water content series: fixed low salinity S1; salinity series: fixed 60% water content) rather than a fully factorial manipulation of salinity, water content, and temperature, balancing the ecological mechanistic focus with experimental feasibility.
(1) Ecological consideration: Soil salinity and water content are intrinsically coupled in saline soils, because changes in water content alter salt concentration and osmotic conditions. A fully orthogonal three-factor design would include extreme treatments such as high salinity combined with high water content, which may represent conditions that are less frequent or difficult to interpret ecologically in our study area. The responses from such combinations would confound osmotic stress effects with physical dilution effects, hindering the independent interpretation of the effects of individual factors on temperature sensitivity of carbon emissions.
(2) Experimental constraints: A full-factorial design (5 salinity levels × 5 water content levels × 6 temperature levels = 150 treatment combinations; with 5 replicates as in this study, a total of 750 incubation units) would have substantially increased the experimental workload and exceeded the single-batch capacity of our incubators and the throughput of our gas chromatography system. Batch-wise operations would introduce temporal variation that could compromise Q₁₀ estimation.
It should be noted that, because the two factors were examined in separate experimental series rather than in a fully factorial design, the interactive effects beyond pairwise combinations are not fully captured in this study. Consequently, caution is needed when extrapolating the present findings to conditions with simultaneous extreme variations in both salinity and water content. We have added a corresponding statement in the Discussion section to acknowledge this limitation (revised Discussion, final paragraph): "the water content response was examined only under a low-salinity background, and the salinity response only under a fixed 60% water content condition; therefore, the interactive effects beyond pairwise combinations are not fully captured, and caution is needed when extrapolating to conditions with simultaneous extreme variations in both factors."
- Corresponding statistical model selection:
Since the two factors belong to separate experimental series, a single model cannot evaluate the complete higher-order interactive effects among the three factors. Accordingly, two-way ANOVA was used to evaluate the individual and pairwise interactive effects of salinity or water content with temperature on CO₂ and CH₄ fluxes within each experimental series; one-way ANOVA was used to compare the effects of different salinity or water content levels on Q₁₀ under fixed conditions. When significant treatment effects were detected (P < 0.05), the LSD method was used for post hoc multiple comparisons. All data are presented as means ± standard error (SE).
Revised text in the manuscript:
Modification 1: Addition of design rationale in the Experimental Design section
"The full-factorial salinity × water content × temperature design was not adopted for two main reasons. First, soil salinity and water content are intrinsically coupled in saline soils, because changes in water content alter salt concentration and osmotic conditions; a fully orthogonal full-factorial combination would include extreme treatments (e.g., high salinity × high water content) with limited ecological relevance to the study area, whose responses would confound osmotic stress with physical dilution effects, hindering the independent interpretation of individual factors on the temperature sensitivity of carbon emissions. Second, the full-factorial design (5×5×6 = 150 treatment combinations; with 5 replicates, 750 incubation units) exceeded the single-batch incubation capacity of our laboratory and the throughput of GC analysis, and the temporal variation introduced by batch-wise measurements could compromise Q₁₀ estimation. Therefore, the effects of salinity and water content were experimentally separated and evaluated in two separate incubation series (water content series: fixed low-salinity S1; salinity series: fixed 60% water content), balancing ecological mechanistic focus with experimental feasibility."
Modification 2: Revision of the Statistical Analysis section
"This experiment consisted of two independent incubation series in which salinity and water content were manipulated separately. Two-way ANOVA was therefore used to evaluate the individual and pairwise interactive effects of salinity or water content with temperature on CO₂ and CH₄ fluxes within each series; one-way ANOVA was used to compare the effects of different salinity or water content levels on Q₁₀ under fixed conditions. When significant effects were detected (P < 0.05), the LSD method was used for post hoc multiple comparisons. All results are presented as means ± standard error (SE)."
Modification 3: Addition of Q₁₀ significance annotations in Table 2
"Significance letters (lowercase letters indicate differences among treatments at the same temperature, P < 0.05) have been added to the Q₁₀ data columns in Table 2, with a footnote specifying that Q₁₀ comparisons were performed using one-way ANOVA with LSD post hoc tests."
Comment 7: Figures: Figures 1 and 2 are highly similar in information content to Figures 3 and 4, differing only in visualization format (bar charts vs. scatter plots). Similarly, Figures 5 and 6 are similar to Figures 7 and 8. The data source for the scatter plots should be explained: for example, in Figure 3 (5% water content, 5°C), the Methods mention only 5 replicates, but the number of scattered points is far greater than 5, presumably due to repeated sampling—please clarify.
Response: We understand the reviewer's concerns regarding figure redundancy and the origin of the scatter points. We have proposed an optimized figure layout: bar charts remain in the main text, while scatter plots are moved to Supplementary Materials. We have also added a clear textual explanation for the large number of scatter points.
Revised text in the manuscript:
- Response to figure redundancy:
Bar charts (Figures 1, 2, 5, and 6) are used for statistical comparison of discrete treatment group means, with significance letters indicating whether differences among treatments are significant. Scatter plots (Figures 3, 4, 7, and 8) display continuous fitted relationships between environmental gradients and carbon emission fluxes, with R² values indicating goodness-of-fit. These two types of figures serve fundamentally different analytical purposes. To streamline the main text and eliminate visual redundancy, all scatter plots (Figures 3, 4, 7, and 8) have been moved to Supplementary Figures S2–S5. Only bar charts are retained in the main text, with textual descriptions indicating the range of R² values from the exponential model fitting (see Supplementary figures).
- Response to the number of scatter points:
Each treatment combination consisted of 5 independent PVC columns (biological replicates). Over the 10-day measurement period, each column was sampled at 5 time points (once every 2 days). Thus, each treatment combination yielded 5 columns × 5 time-point measurements = 25 independent flux data points, corresponding to the numerous scatter points shown in the figures. We have added a unified explanatory note in the Methods section and in all Supplementary Figure captions:
"Each scatter point in Supplementary Figures S2–S5 represents an instantaneous flux measurement from a single column at a single time point (each environmental treatment comprised 5 biological replicates × 5 temporal samplings = 25 independent data points)."
Citation: https://doi.org/10.5194/egusphere-2026-217-AC2
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AC2: 'Reply on RC2', Chao Yang, 06 Aug 2026
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General assessment:
This study presents a well-designed incubation experiment investigating the effects of soil water content and salinity on CO2 and CH4 fluxes and their temperature sensitivity (Q10) in coastal saline-alkaline soils from the Yellow River Delta. The results are novel and provide valuable insights for carbon-climate feedback modeling in vulnerable ecosystems. The manuscript is clearly written and generally sound. I recommend acceptance after the following revisions.
The manuscript is scientifically sound and well written; the above suggestions aim to improve clarity, consistency, and interpretability.