Vapor Pressure Deficit Thresholds and Their Impacts on Gross Primary Productivity in Xinjiang Arid Grassland Ecosystems

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

please see the attached file

Comments for author File: Comments.pdf

Author Response

Dear Reviewer,
We are very grateful to you for your time and constructive comments on our
manuscript. We have carefully read the comments and suggestions, which are truly
valuable for improvement of our paper. We have implemented the comments and
suggestions accordingly. Our responses are given in a point-by-point manner below.
We wish to submit the revised manuscript for further consideration in this journal and
look forward to hearing from you in due course.
Comment 1: In the Abstract, authors should summarize the unsolved scientific
problem after the first sentence.
Response 1: Following your suggestion to improve clarity and focus, we have
explicitly added the core unsolved scientific problem after the opening sentence in
Lines 12-13: "However, the threshold of the response mechanism of grassland in arid
regions to atmospheric drought remains unclear." This revision effectively highlights
the research gap addressed by our study.
Comment 2: In lines 14, MODIS data is not included into multi-source remote
sensing data?
Response 2: We acknowledge the omission and have revised the statement at Line
14 to explicitly include MODIS: "using MODIS and other multi-source remote
sensing data (2000--2020)"
Comment 3: In lines 14, the sentence “distinct topographic controls on VPD
distribution……” is logically incorrect. VPD is highly associated with precipitation,
temperature, evapotranspiration, solar radiation, underlying surface factors such as
topography, elevation are only explanatory factors, in which they can explain the
spatial patterns of VPD, but it cannot be said that topography controls or decides on
VPD.
Response 3: We agree with the reviewer's point regarding the inaccurate
implication of topographic "control". Consequently, we have removed the problematic
statement at Lines 14 and replaced it with an objective description based on
observational data: "Results show intensified atmospheric drought in central
Tianshan Mountains and southern Junggar Basin, with VPD exhibiting a
widespread increasing trend (significant increase: 15.75%, extremely significant
increase: 4.68%)".
Comment 4: In the Figure 1b, vegetation growth reflected by using NDVI/LAI
should be displayed within the grassland area, rather than just the grassland region as
it is now visible.
Response 4: Thank you for this helpful suggestion. We agree that constraining the
LAI visualization specifically to the grassland area provides a more accurate
representation. We have revised Figure 1b accordingly, now displaying the vegetation
growth indices LAI only within the defined grassland boundaries. The updated figure
can be found in the manuscript (Line 121).
Figure 1. Overview of the Xinjiang Area (a) Geographic Location and Elevation; (b)
Grassland distribution and average grassland LAI; (c) Trend of average temperature
change; (d) Trend of average precipitation variation.
Comment 5: In the Section 3.1, Why didn't the author introduce the area proportion
of each grading and the slope of the GPP trend when explaining Figure 1, so, I felt that
the writing is not enough sufficient to read. I think there are similar writing problems
in the later parts as well, that is, the explanation about the figures is not sufficient.
Response 5: Thank you for this important point. We fully agree that providing
more detailed data significantly enhances the readability and informativeness of figure
interpretations. Following your suggestion, we have systematically revised and
improved the descriptions associated with figures throughout the manuscript.
Specifically:
In Section 3.1 (Lines 250-257), when explaining Figure 2a (spatial distribution of
GPP trends), we have added the specific area proportions corresponding to each
significance level (significant increase, extremely significant increase, decrease) and
provided a more detailed description of the spatial distribution characteristics of these
trend areas (e.g., "a predominant portion of the area (comprising 58.75%) experienced
a significant GPP increase", "areas exhibiting an extremely significant increase (making
up 41.21%) were primarily clustered in...", "regions showing a decrease (constituting
6.38%) were sporadically distributed in...").
Simultaneously, we have conducted a thorough review of the explanatory text for
all subsequent figures in the paper. We have ensured that the descriptions of relevant
figures now sufficiently incorporate key statistical data (such as proportions, areas,
value ranges, trend characteristics) and provide clearer analyses of spatial/temporal
patterns to make the discussion more thorough and easier to understand.
Comment 6: In Figure 6, GPP is not only related with many direct factors (PRE,
TEM, VPD), but also highly relying on indirect factors, more details please see the
paper “The direct and indirect effects of the environmental factors on global terrestrial
gross primary productivity over the past four decades”, therefore, if possible, authors
can supplementary a more improved structure map to explore the impacts of VPD on
GPP.
Response 6: We appreciate the suggestion regarding indirect factors and the cited
reference. We fully understand and agree with the critical role of indirect factors (e.g.,
those mediated through soil moisture) highlighted in that paper for regulating GPP,
and we recognize the significant value of a more comprehensive structural map (such
as an SEM path diagram) in elucidating both the direct and indirect pathways of VPD
impacts on GPP. We have explicitly elaborated on these complexities in the Discussion
section (Lines 512-519): while this study focused on atmospheric drought
(characterized via VPD) to reveal its independent effects, we clearly acknowledge the
role of soil moisture stress in regulating productivity in arid regions. The lack of soil
moisture data limits our understanding of how VPD and soil drought jointly affect
GPP. Future studies need to examine the combined impacts of atmospheric vapor
pressure deficit and soil water availability on GPP. We believe that frankly
acknowledging this limitation in the Discussion and outlining clear future directions
helps address the current inability to fully visualize indirect influences in the figure.
We are deeply grateful again for your insightful comment, which is essential for
refining our work.
Comment 7: In the Figure 8c, how is the ridge coefficient between VPD and GPP
calculated? Simultaneously inputting the coefficients calculated from the four
changing parameters, or controlling the other three to remain unchanged, only VPD is
used to calculate the coefficients? I firstly think that only four direct influencing factors
are considered to dissociate the impacts of VPD on GPP is not sufficient. Secondly, If
the other three factors change over a long time series in your well-built model, then
the impact of VPD on GPP is inaccurate.
Response 7: We sincerely appreciate these insightful technical questions, which are
vital for the precise articulation of our methodology and interpretation of the results.
Ridge coefficient calculation: We employed the standard multivariate ridge
regression approach (now described in detail in the revised Section 2.3.3 "Ridge
Regression Analysis"). The ridge regression model is fitted by simultaneously
inputting all four predictors (PRE, TEM, SSR, VPD). The ridge coefficients are
estimated by incorporating a penalty function (L2 regularization) to reduce the
variance of the coefficient estimates, while all predictors are present in the model.
Therefore, the ridge coefficient for VPD displayed in Figure 8c was not obtained by
"holding the other three factors strictly constant" or by "calculating using VPD alone".
Instead, it represents the stabilized weight of VPD's contribution to GPP, estimated
within the holistic model that accounts for the inter-correlations among all four factors.
We acknowledge your concerns: firstly, regarding the potential insufficiency of
considered factors, we have addressed this in the Discussion (Lines 506-508), noting
that due to spatial constraints and the relatively short temporal scale, the model
conclusions (including factor contributions) may not be universally applicable to all
sub-regions or capture longer-term dynamics; secondly, the potential bias you
highlight (i.e., long-term changes in other factors influencing the estimated effect of
VPD) is an inherent challenge in multivariate regression analysis. To enhance the rigor
of result interpretation, we have explicitly clarified this computational principle of the
ridge coefficients and what they represent – namely, the "stabilized association
strength within a multi-factor coexisting model" – in the Results section (Lines 408-
415). We fully concur that incorporating more relevant factors (such as soil moisture)
would yield a more comprehensive model, representing a key direction for future
research. We are deeply grateful for your meticulous review, which has significantly
enhanced the transparency of our methods and the robustness of our conclusions.
Comment 8: There are some writing errors, the authors should conduct a detailed
self-examination. I will not list them one by one.
Response 8: We place great importance on the accuracy of language expression and
the fluency of the writing. Upon receiving your comment, we immediately conducted
multiple rounds of meticulous self-examination and revision of the entire manuscript.
Specific actions taken include: (1) carefully proofreading the text sentence by sentence,
focusing on correcting grammar, spelling, punctuation, and ensuring accurate
terminology usage; (2) utilizing professional grammar-checking tools to assist in
identifying potential errors; (3) optimizing sentence structures to enhance clarity and
logical coherence; (4) ensuring consistency and accuracy in figure/table captions and
reference formatting per journal guidelines; and (5) paying special attention to the
rigor of method descriptions, result presentations, and conclusion derivations in key
sections.
Finally, we sincerely thank you for your valuable suggestions, which have
significantly contributed to enhancing the overall quality of the manuscript. We have
carefully revised the manuscript in accordance with your comments.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The subject of this manuscript agrees with the aims and scope of Sustainability, particularly in its focus on vegetation-climate interactions within arid grassland ecosystems.

 

The discussion section is notably well-articulated and insightful.

 

However, the manuscript is not yet suitable for publication in its current form. A number of substantive and technical issues require revision to improve the clarity, rigor, and completeness of the work. My detailed comments are outlined below for the authors consideration.

 

1. Introduction: The introduction is overly concise and lacks sufficient contextualization of the scientific importance of exploring the VPD–GPP relationship in the arid grasslands of Xinjiang. The authors should expand this section to discuss the ecological and climatological relevance of VPD in such environments and clearly articulate the limitations in the existing literature. Furthermore, the study objectives and its novel contributions should be explicitly stated.
2. Figure 1: In Figure 1a, the labels “high” and “low” should be removed to avoid interpretive bias. The map should remain neutral and rely on color scale legends for interpretation.
3. Lines 38–40: The statement regarding the coupling between VPD and soil moisture amplifying vegetation stress during compound drought–heatwave events requires further justification. Please provide appropriate literature support or revise the statement for accuracy. As currently phrased, it appears to overstate the role of the VPD–SM interaction.
4. Line 50:The possessive form “VPD’s” is informal and should be avoided. Please revise to a more formal construction, such as “the influence of VPD.”
5. Section 2.1, and Study Area Description: The description of the study area would benefit from additional details regarding the spatial and temporal patterns of VPD and GPP. Furthermore, the authors should briefly discuss the known or expected relationship between these variables in this specific region.
6. Table 1:It is unclear whether the “Resolution” values listed in Table 1 refer to the native resolution of the data sources or the final resolution used in analysis. Please clarify this in the table caption or accompanying text.
7. Lines 105–120: The data processing workflow lacks sufficient detail. The authors should provide a more thorough description of any resampling, quality control, gap-filling, or aggregation methods applied to the datasets prior to analysis.
8. Line 173: Please specify the purpose of the calculation formulas referenced here. The phrase is vague and does not indicate what is being computed.
9. Line 193: The word “where” following the formula should not be capitalized and should remain in the same paragraph for continuity.
10. Lines 191–194: There appears to be a contradiction between the statement referencing “all variables” and the subsequent listing of only four (VPD, PRE, TEM, SSR). Please clarify the scope of the variables included in the analysis.
11. Section 2.3.4: This section is overly brief and lacks sufficient methodological detail. Please provide information on model structure, assumptions, variables included, model validation metrics, and any software packages used.
12. Figure 2b:Ensure consistent formatting of axes, including line widths and font sizes, across subfigures for visual clarity.
13. Figure 2 and Lines 221–231:Define terms such as “Extremely Significant Decrease” and “Significant Decrease” using statistical criteria (e.g., p-value thresholds). This should be included in the text and/or figure caption.
14. Figure 3, Similarly, clarify the basis for classification of significance levels in Figure 3. Quantitative results should be reported for subfigures e–h to substantiate the visual trends.
15. Lines 283–312: The analysis presented in Section 3.3.2, “Major Controlling Factors of GPP,” lacks the necessary quantitative support and analytical depth to substantiate its conclusions. The identification of dominant drivers of GPP should be grounded in robust statistical metrics, such as effect sizes, sensitivity analyses, or variance partitioning results. As currently written, the discussion remains largely descriptive and does not provide sufficient empirical evidence to confirm the stated controlling factors.
16. Lines 306–307:The statement that “the effects of TEM and PRE on GPP did not significantly lead to negative outcomes” is unclear. What does authors mean?
17. Lin 374: Further clarification is needed regarding the selection of the critical VPD threshold of 0.61. Was this value empirically derived from a breakpoint or inflection point, such as the zero-crossing in Figure 8c? Additionally, the rationale for employing a linear fitting approach should be elaborated, including whether alternative, potentially more suitable, nonlinear models were considered and tested.
18. Discussion Section: The Discussion section is well-written and is a highlight of the paper.
19. Conclusions: The conclusions, including the abstract, are overly qualitative and general in tone. Given that the study presents multiple quantitative results, it is recommended that the authors integrate key numerical findings into these summary sections. Doing so will enhance the clarity, scientific rigor, and communicative value of the manuscript.
20. After reading the entire article, I did not understand how the conclusion in the abstract at Line 18, “primarily driven by atmospheric drought stress,” was derived. Could the author please explain further?
21. Numerous instances of awkward or imprecise phrasing reduce the readability and clarity of the manuscript.
22. The manuscript exhibits a similarity index of 31%, which exceeds acceptable thresholds for original research articles. The authors are advised to revise overlapping or redundant text to reduce duplication and ensure compliance with the journal originality requirements.

Comments on the Quality of English Language

Needs great improvements.

Author Response

Dear Reviewer 2,

 

We are very grateful to you for your time and constructive comments on our manuscript. We have carefully read the comments and suggestions, which are truly valuable for improvement of our paper. We have implemented the comments and suggestions accordingly. Our responses are given in a point-by-point manner below. We wish to submit the revised manuscript for further consideration in this journal and look forward to hearing from you in due course.

 

 

Comment 1: Introduction: The introduction is overly concise and lacks sufficient contextualization of the scientific importance of exploring the VPD–GPP relationship in the arid grasslands of Xinjiang. The authors should expand this section to discuss the ecological and climatological relevance of VPD in such environments and clearly articulate the limitations in the existing literature. Furthermore, the study objectives and its novel contributions should be explicitly stated.

Response 1: We sincerely thank you for your valuable and constructive feedback on the Introduction section. We fully agree on the need to more thoroughly contextualize the scientific background and significance of the study. In response to your suggestions, we have implemented significant revisions to the Introduction, detailed as follows:

1. Enhanced Discussion of VPD's Ecological and Climatological Relevance: At Lines 56-59, we added a statement highlighting the complex regulatory role of VPD in grassland ecosystems: “This biome-specific response is further complicated by the regulatory effects of VPD on grassland ecosystems: direct stomatal control of transpiration and indirect modulation via soil moisture-radiation feedbacks”. This underscores the critical role of VPD in regulating arid grassland ecological processes through both direct (stomatal conductance) and indirect pathways (soil moisture-radiation feedbacks), emphasizing its specific ecological and climatological importance in this environment.
2. Clear Articulation of Study Objectives: At Lines 74-78, we explicitly and concisely stated the research objectives: “Our primary objectives are to analyze the spatial and temporal evolution characteristics of VPD, elucidate its regulatory mechanisms on grassland gross primary productivity (GPP), and critically, to identify and quantify the specific VPD thresholds that impact GPP and assess the changes in their influence on grassland GPP”. This clearly delineates the three core aims of the work, particularly emphasizing the novel task of identifying and quantifying critical VPD thresholds.
3. Explicit Highlighting of Novel Contributions: At Lines 81-86, we introduced text emphasizing the study's novelty and significance: “By revealing the spatiotemporal variation patterns of VPD, clarifying that VPD is a key meteorological factor regulating vegetation productivity, its ecological effects, and defining the critical VPD thresholds for Xinjiang's grasslands, this study fills a key regional research gap. It provides a vital theoretical and scientific basis for developing differentiated ecological management strategies to enhance resilience in this vulnerable and ecologically significant arid region”. This section explicitly identifies the novel contributions as: revealing regional VPD spatiotemporal patterns, establishing VPD's role as a key regulatory factor, defining Xinjiang-grassland-specific critical VPD thresholds, thereby filling a key regional research gap, and providing a vital theoretical and scientific basis for developing differentiated ecological management strategies.

Through these revisions, we aimed to significantly enhance the depth of the Introduction, providing a more comprehensive background (particularly the ecological-climatological relevance of VPD in arid grasslands), clarifying limitations in existing regional research, precisely defining the study objectives, and strongly emphasizing the unique value and scientific contribution of this research. We are grateful again for your guidance, which has substantially improved the opening narrative of our manuscript.

 

Comment 2: Figure 1: In Figure 1a, the labels “high” and “low” should be removed to avoid interpretive bias. The map should remain neutral and rely on color scale legends for interpretation.

Response 2: Thank you for this precise suggestion. We fully agree on the importance of maintaining map neutrality. We have revised Figure 1a accordingly by removing the “high” and “low” labels. Map interpretation now relies solely on the color scale legend to avoid potential interpretive bias. The updated figure is located at Line 121 in the manuscript.

Figure 1. Overview of the Xinjiang Area (a) Geographic Location and Elevation; (b) Grassland distribution and average grassland LAI; (c) Trend of average temperature change; (d) Trend of average precipitation variation.

 

Comment 3: Lines 38–40: The statement regarding the coupling between VPD and soil moisture amplifying vegetation stress during compound drought–heatwave events requires further justification. Please provide appropriate literature support or revise the statement for accuracy. As currently phrased, it appears to overstate the role of the VPD–SM interaction.

Response 3: We have added a key reference (Seneviratne et al., 2010, cited in Lines 44--46) to substantiate the mechanism of SM depletion intensifying heat stress via VPD amplification.

 

Comment 4: Line 50: The possessive form “VPD’s” is informal and should be avoided. Please revise to a more formal construction, such as “the influence of VPD.”

Response 4: Thank you for your guidance on formal expression. We have revised Line 50 by replacing the possessive form "VPD’s" with the formal construction "the regulatory effects of VPD". The updated sentence (now at Lines 56–57) reads: "This biome-specific response is further complicated by the regulatory effects of VPD on grassland ecosystems: direct stomatal control of transpiration and indirect modulation via soil moisture-radiation feedbacks."

 

Comment 5: Section 2.1, and Study Area Description: The description of the study area would benefit from additional details regarding the spatial and temporal patterns of VPD and GPP. Furthermore, the authors should briefly discuss the known or expected relationship between these variables in this specific region.

Response 5: In Section 2.1 (Lines 109-119), we have now integrated detailed spatial patterns of VPD and GPP across Xinjiang. The revisions describe VPD's distinct topographical gradient—characterized by lower values in mountainous areas and higher values in plains/basins, with a weaker increasing trend in mountains—driven by combined climate-vegetation interactions. Simultaneously, GPP exhibits marked regional heterogeneity, showing higher values in Northern Xinjiang and lower values in Southern Xinjiang due to zonal hydrothermal differentiation. We further explicitly link their contrasting patterns to the complex interplay between atmospheric demand, water availability, and ecosystem productivity in this arid region. These additions comprehensively address the spatiotemporal characteristics and expected variable relationships. We sincerely appreciate your guidance in strengthening the regional context of our study.

 

Comment 6: In the figures in question, the dashed lines are not exactly vertical. They are more inclined and horizontal than vertical. Review!，

Response 6: Thank you for your precise clarification request regarding data resolution in Table 1. We have revised the table header from "Resolution" to "Original resolution" (Line 147) to explicitly indicate that these values represent the native spatial resolution of the raw data sources. This specification distinguishes them from any resampled resolutions used in subsequent analyses, eliminating potential ambiguity in data provenance interpretation. We greatly appreciate this suggestion, which enhances methodological transparency in our data processing workflow.

Table 1. Description of datasets used in this study.

Data	Year	Original resolution	Data sources
GPP	2000–2020	500 m	https://lpdaac.usgs.gov/products/mod17a2hv006
Grassland range	2021	500 m	https://lpdaac.usgs.gov/products/mcd12q1v006
LAI	2000-2020	0.05°	http://globalchange.bnu.edu.cn/research/laiv6
DEM	2020	90 m	https://zenodo.org/records/4700264
TEM	2000–2020	0.50°	https://crudata.uea.ac.uk/cru/data/hrg/cru_ts_4.06
PRE	2000–2020	4000 m	https://www.climatologylab.org/terraclimate.html
SSR	2000-2020	4000 m	https://www.climatologylab.org/terraclimate.html
VPD	2000-2020	4000 m	https://www.climatologylab.org/terraclimate.html

Note: Variable names and corresponding abbreviations. Gross primary productivity (GPP), leaf area index (LAI), digital elevation model (DEM), temperature (TEM), precipitation (PRE), downward surface shortwave radiation (SSR), and vapor pressure deficit (VPD).

 

Comment 7: Lines 105–120: The data processing workflow lacks sufficient detail. The authors should provide a more thorough description of any resampling, quality control, gap-filling, or aggregation methods applied to the datasets prior to analysis.

Response 7: Thank you for prompting a more detailed description of our data processing workflow. In Lines 139-146, we have now explicitly specified the key preprocessing steps applied to all datasets: VPD, SSR, and TEM were converted to annual means through monthly arithmetic averaging; PRE was aggregated into annual cumulative totals using R 4.41. All variables underwent spatial resampling to a unified 500-meter resolution via bilinear interpolation in ArcGIS 10.8, followed by rigorous pixel-scale matching to eliminate spatial heterogeneity errors arising from source/projection discrepancies. The temporal coverage (2000-2020) is also clearly stated. These additions comprehensively address the requested details on resampling, aggregation, quality control, and spatiotemporal consistency. We value this suggestion for strengthening methodological reproducibility.

 

Comment 8: Line 173: Please specify the purpose of the calculation formulas referenced here. The phrase is vague and does not indicate what is being computed.

Response 8: We acknowledge that the original phrasing in Line 173 was inadequately defined. The referenced formulas have now been removed to prevent potential misinterpretation, as their inclusion did not directly contribute to the core analysis. This revision streamlines the methodology description and eliminates vagueness.

 

Comment 9: Line 193: The word “where” following the formula should not be capitalized and should remain in the same paragraph for continuity.

Response 9: Thank you for your meticulous attention to formatting details. We have corrected Line 193 by changing "Where" to lowercase "where" and integrated it into the same paragraph (now at Line 213) to maintain textual continuity.

 

Comment 10: Lines 191–194: There appears to be a contradiction between the statement referencing “all variables” and the subsequent listing of only four (VPD, PRE, TEM, SSR). Please clarify the scope of the variables included in the analysis.

Response 10: Thank you for identifying this ambiguity in variable scope description. We have revised the phrasing in Lines 191-194 to clarify that the analysis specifically targets four key meteorological drivers: VPD, PRE, TEM, and SSR. The updated sentence (now at Line 205) reads:

"This method has been widely applied in previous studies to explore the relationships between GPP and key meteorological factors within a multivariate framework, providing more robust coefficient estimates."

 

Comment 11: Section 2.3.4: This section is overly brief and lacks sufficient methodological detail. Please provide information on model structure, assumptions, variables included, model validation metrics, and any software packages used.

Response 11: Thank you for prompting a more comprehensive methodological description. In Section 2.3.4 (Lines 237-244), we have expanded the description to clarify key aspects of the path analysis: The model was designed to elucidate both the direct effect of VPD on GPP and indirect pathways among meteorological factors through predefined path hypotheses. Prior to analysis, all variables were standardized to a mean of 0 and standard deviation of 1, with raster data resampled to a 500-meter resolution to match GPP's spatial scale and pixels containing missing values systematically excluded. Annual model fitting was conducted for the period 2000-2020 using the lavaan package in R 4.4.1, where standardized path coefficients (β) quantified driver contributions and statistical significance was assessed at p<0.05. Path diagrams were generated via the semPlot package.

 

Comment 12: Figure 2b:Ensure consistent formatting of axes, including line widths and font sizes, across subfigures for visual clarity.

Response 12: We have revised Figure 2b to ensure complete axis formatting alignment with all subfigures, including unified line widths and font sizes across all axes labels and tick marks. This adjustment significantly improves visual clarity and cross-panel comparability. The updated figure is now located at Line 263. We appreciate your attention to detail in strengthening the professionalism of our graphical presentation.

 

Comment 13: Figure 2 and Lines 221–231: Define terms such as “Extremely Significant Decrease” and “Significant Decrease” using statistical criteria (e.g., p-value thresholds). This should be included in the text and/or figure caption.

Response 13: We have addressed this by adding Table X in Section 2.3.1 (Line 175) that formally defines all trend significance categories. These definitions are now consistently applied in Lines 250-257, ensuring transparent interpretation of vegetation dynamics. We appreciate this suggestion for enhancing methodological rigor.

Table 2. Classification of Significance Levels in Linear Regression.

Category	Slope(R)	p-value Range
Extremely Significant Decrease	R < 0	p < 0.01
Significant Negative	R < 0	0.01≤ p <0.05
No Significant Decrease	R < 0	p ≥ 0.05
No Significant Increase	R > 0	p ≥ 0.05
Significant Increase	R > 0	0.01≤ p <0.05
Extremely Significant increase	R > 0	p < 0.01

 

Comment 14: Figure 3, Similarly, clarify the basis for classification of significance levels in Figure 3. Quantitative results should be reported for subfigures e–h to substantiate the visual trends.

Response 14: Thank you for prompting quantitative clarification of significance levels in Figure 3. We have now integrated precise statistical metrics across subfigures: VPD exhibited a widespread increasing trend (significant increase: 15.75%; extremely significant increase: 4.68%; Lines 271-272). TEM changes showed dominant spatial stability (no significant change: 95.08%) with localized cooling/warming signals in transitional zones (Lines 274-277). Crucially, the Tianshan Mountains' barrier effect drove divergent responses - Northern Xinjiang saw SSR increases (non-significant: 47.43%; significant: 7.93%) alongside PRE decreases (non-significant: 43.04%; significant: 1.29%), while Southern Xinjiang displayed inverse patterns. The Ili River Valley's exceptional SSR surge correlates with the Kunlun Mountains' elevated PRE trends (significant increase: 3.02%; extremely significant: 0.64%; Lines 279-286). These quantitative supplements substantiate all visual classifications using the Section 2.3.1 statistical thresholds.

 

Comment 15: Figure 3, Similarly, clarify the basis for classification of significance levels in Figure 3. Quantitative results should be reported for subfigures e–h to substantiate the visual trends.

Response 15: Thank you sincerely for your valuable feedback on the analysis in Section 3.3.2, "Major Controlling Factors of GPP," particularly your critical point regarding the need for enhanced quantitative support and analytical depth. We took your suggestions very seriously and have made substantial revisions to the relevant sections. In lines 323-331, we have added specific spatial percentage data (including low- and high-intensity classifications) detailing the positive and negative impacts of TEM, PRE, VPD, and SSR on GPP. These quantitative results clearly demonstrate that the effects of TEM and PRE are overwhelmingly positive (e.g., high-intensity positive effects for TEM cover 82.00% of the area, with only minimal negative effects), while the positive and negative effects of VPD and SSR are more balanced (e.g., the combined negative impact area for VPD is 18.46%). Further, in lines 339-345, we have strengthened our conclusion regarding the dominant positive influence of TEM and PRE on GPP by integrating the evidence from effect size distributions (e.g., 71.19% high-intensity positive effect for PRE) with the results from partial correlation analysis. Supported by the relatively balanced positive/negative effect patterns observed for VPD and SSR (e.g., combined positive impact areas for SSR total 92.98%, while negative areas total 7.02%), we have quantitatively substantiated the significant role these factor changes play in the decline of grassland productivity. These added quantitative metrics significantly enhance the rigor and persuasiveness of our analysis.

 

Comment 16: Lines 306–307: The statement that “the effects of TEM and PRE on GPP did not significantly lead to negative outcomes” is unclear. What does authors mean?

Response 16: Thank you for your critical inquiry regarding the statement in Lines 306–307. We acknowledge that the original phrasing – "the effects of TEM and PRE on GPP did not significantly lead to negative outcomes" – lacked clarity in conveying statistical justification. This has been revised in Lines 342–345 to: "This finding, quantified by the effect size distribution, was consistent with the results from the partial correlation analysis, further validating that the dominant effects of TEM and PRE on GPP were strongly positive." The revised statement eliminates ambiguity by anchoring the conclusion to a quantitative evidence framework.

 

Comment 17: Lin 374: Further clarification is needed regarding the selection of the critical VPD threshold of 0.61. Was this value empirically derived from a breakpoint or inflection point, such as the zero-crossing in Figure 8c? Additionally, the rationale for employing a linear fitting approach should be elaborated, including whether alternative, potentially more suitable, nonlinear models were considered and tested.

Response 17: Thank you for your inquiry regarding the basis for selecting the VPD threshold (0.61 kPa). We have clarified in Lines 408-415 that this threshold is defined as the x-intercept (i.e., where y=0) of the fitted line in the linear regression model, directly corresponding to the zero-crossing point in the ridge coefficient-VPD relationship (as shown in Figure 8c). Beyond 0.61 kPa, the ecosystem response fundamentally shifts: GPP is promoted at VPD ≤ 0.61 kPa but suppressed when VPD > 0.61 kPa. The linear regression approach was adopted due to its strong explanatory power (R² = 0.9575) for the ridge coefficient-VPD relationship and its capacity to directly quantify the systemic stress tipping point (y=0), which aligns with our objective to identify the critical transition where VPD shifts from promoting to suppressing GPP.

 

Comment 18: Discussion Section: The Discussion section is well-written and is a highlight of the paper.

Response 18: We sincerely appreciate your positive assessment of the Discussion section. This is a significant encouragement to us, and we will continue to uphold rigor and depth in our scientific discourse.

 

Comment 19: Conclusions: The conclusions, including the abstract, are overly qualitative and general in tone. Given that the study presents multiple quantitative results, it is recommended that the authors integrate key numerical findings into these summary sections. Doing so will enhance the clarity, scientific rigor, and communicative value of the manuscript.

Response 19: We sincerely appreciate your suggestions. In response to your call for enhanced quantification, we have integrated key numerical findings into the Abstract (Lines 12-14) including spatial percentages of VPD trends (significant increase: 15.75%, extremely significant: 4.68%), the dominant negative impact of VPD on GPP (path coefficient = -0.58), the 0.61 kPa tipping point, and the proportion of areas with significant GPP increases (58.75%). Correspondingly, the Conclusions (Lines 520-537) now reinforce: the quantified evidence that 58.75% of areas show significant GPP increases with growth slowdown under high VPD, the significant negative path coefficient of VPD (-0.58) from SEM, and critical data demonstrating regional VPD in key zones exceeded the threshold (0.66 kPa in 2000 rising to 0.74 kPa in 2008, +12.1%). These revisions ensure full alignment with quantitative results.

 

Comment 20: Conclusions: The conclusions, including the abstract, are overly qualitative and general in tone. Given that the study presents multiple quantitative results, it is recommended that the authors integrate key numerical findings into these summary sections. Doing so will enhance the clarity, scientific rigor, and communicative value of the manuscript.

Response 20: Thank you for your query regarding the derivation of the conclusion. We have added key quantitative evidence in Lines 20-21: "Integrated analyses demonstrate that VPD has dominant negative impact on GPP (path coefficient = -0.58, p<0.05), primarily driven by atmospheric drought stress." Here, "atmospheric drought" specifically refers to the moisture stress state characterized by elevated VPD —VPD directly measures air dryness, where higher values accelerate plant stomatal water loss, inducing physiological drought (i.e., atmospheric drought). The strongly negative path coefficient (-0.58, p<0.05) quantitatively confirms that increased VPD (intensified atmospheric drought) is the core mechanism suppressing GPP.

 

Comment 21: Numerous instances of awkward or imprecise phrasing reduce the readability and clarity of the manuscript.

Response 21: We sincerely appreciate your meticulous feedback on language expression and deeply apologize for any reduced readability caused by suboptimal phrasing. In response to your concerns regarding imprecise wording, we have implemented comprehensive language revisions throughout the manuscript: enhancing terminology precision, restructuring verbose sentences, correcting grammatical constructs, and strengthening logical connectors. These revisions have significantly improved textual clarity and coherence, and we are grateful for your guidance in elevating our academic writing standards.

 

Comment 22: The manuscript exhibits a similarity index of 31%, which exceeds acceptable thresholds for original research articles. The authors are advised to revise overlapping or redundant text to reduce duplication and ensure compliance with the journal originality requirements.

Response  22： We sincerely thank you for being vigilant about the originality criteria and apologize for the fact that the current similarity index (31%) exceeds the journal requirements. In response, we undertook a comprehensive revision of the entire manuscript: carefully rewriting sections with high similarity (e.g., literature review and methodological descriptions), removing unnecessary redundancy, and strengthening the original expression of core findings. The revised manuscript now has greatly reduced textual duplication and is in full compliance with the journal's originality policy. We remain committed to further improving citation practice and appreciate your expert guidance.

 

Finally, we sincerely thank you for your valuable suggestions, which contributed significantly to improving the overall quality of the manuscript. We have carefully revised the manuscript based on your comments.

 

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The paper presents interesting results. It's well-written and structured. My suggestions and comments are below.

 

Title.

I do not recommend using abbreviations in the title. Consider avoid them, even with increasing the title size. 

 

Introduction.

Although readers that are familiar with this field can understand what exactly vapor pressure deficit means, I suggest to include its definition.

 

Materials and Methods.

Please specify what climate parameters (TEM, PRE) – mean annual?

It is not clear from the text what the sample size (n) was for statistical analyses. Please specify.

Please specify software used.

It would be nice to illustrate TEM and other environmental variables besides elevation and grasslands.

 

Results.

Line 227. Is it not clear where the Ili River Valley and the Junggar Basin are located? Consider to specify that on the Fig 1 or 2.

 

Discussion.

419. Check the ref.

Section 4.3. Among the limitations, I suggest to include possibilities to use more advanced methods, like machine learning with Shapley values for identification of key factors and their thresholds.

Author Response

Dear Reviewer 3,

 

We are very grateful to you for your time and constructive comments on our manuscript. We have carefully read the comments and suggestions, which are truly valuable for improvement of our paper. We have implemented the comments and suggestions accordingly. Our responses are given in a point-by-point manner below. We wish to submit the revised manuscript for further consideration in this journal and look forward to hearing from you in due course.

 

 

Response to Reviewer 3 Comments

Comment 1: Title. I do not recommend using abbreviations in the title. Consider avoid them, even with increasing the title size.

Response 1: We thank the reviewer for highlighting the importance of title clarity. We agree that avoiding abbreviations enhances readability, especially for interdisciplinary audiences. Consequently, we have revised the title to: "Vapor Pressure Deficit Thresholds and Their Impacts on Gross Primary Productivity in Xinjiang Arid Grassland Ecosystems" (Lines 2-3), replacing "VPD" and "GPP" with their full terms.

 

Comment 2: Introduction. Although readers that are familiar with this field can understand what exactly vapor pressure deficit means, I suggest to include its definition.

Response 2: We appreciate the reviewer's suggestion to enhance clarity for a broader audience. Following this advice, we have explicitly defined "Vapor Pressure Deficit (VPD)" in the Introduction section (Lines 29-31).

 

Comment 3: Materials and Methods. Please specify what climate parameters (TEM, PRE) – mean annual? It is not clear from the text what the sample size (n) was for statistical analyses. Please specify. Please specify software used. It would be nice to illustrate TEM and other environmental variables besides elevation and grasslands.

Response 3: We sincerely appreciate the reviewer's valuable and meticulous comments on the Materials and Methods section. Regarding the definition of the climate parameters (TEM, PRE), we have clarified in Lines 135-138 of the manuscript that: air temperature (TEM) is expressed as the mean annual value, while precipitation (PRE) is the annual cumulative sum. To address the lack of clarity on the sample size (n), we have explicitly stated in Lines 157-158 that: “n” denotes the number of years in the study period (2000–2020 n = 21 years). Concerning the request to specify the software used, we have added the necessary details throughout the relevant sections of “Section 2. Materials and Methods”, clearly indicating the specific software and versions employed. Finally, in response to the suggestion to illustrate additional environmental variables, we have gladly implemented this by adding new panels (c) and (d) to Figure 1: Panel (c) illustrates the spatial pattern of mean air temperature averaged over 2000–2020, and panel (d) illustrates the spatial pattern of mean precipitation averaged over the same period (2000–2020), accompanied by detailed descriptions in the figure caption. We believe these revisions significantly enhance the clarity, completeness, and reproducibility of the Materials and Methods section.

 

Comment 4: Results. Line 227. Is it not clear where the Ili River Valley and the Junggar Basin are located? Consider to specify that on the Fig 1 or 2.

Response 4: We thank the reviewer for the constructive comment on the Results section. Regarding the point raised in Line 227 concerning the unclear location of the Ili River Valley and the Junggar Basin in Figures 1 or 2, we fully understand and agree on its importance. Following this suggestion, we have clearly labeled the specific geographic locations of both the "Ili River Valley" and the "Junggar Basin" in Figure 1a. This addition ensures that readers can intuitively locate these two key regions and significantly enhances the clarity of Figure 1 and the spatial context of the Results section.

 

 

Comment 5: 419. Check the ref.

Response 5: We thank the reviewer for noting this. Following the suggestion, we have thoroughly reviewed and corrected the relevant references in Lines 454-456 of the manuscript to ensure their accuracy, currency, and adequate support for the study's conclusions. This revision further strengthens the academic rigor and argumentative credibility of the Discussion.

 

Comment 6: Section 4.3. Among the limitations, I suggest to include possibilities to use more advanced methods, like machine learning with Shapley values for identification of key factors and their thresholds.

Response 6: We appreciate the reviewer's insightful suggestion for future methodological development. We fully agree that advanced methods such as machine learning (e.g., Shapley values) could further enhance the scientific rigor in identifying key factors and their thresholds. Accordingly, we have added the following statement in the limitations discussion (Lines 504-506): "Future studies should explore machine learning techniques (e.g., Shapley value-based interpretability) to deepen the mechanistic understanding of ecosystem drivers." This addition significantly strengthens the methodological foresight and depth of the research outlook.

 

Finally, we sincerely thank you for your valuable suggestions, which have significantly contributed to enhancing the overall quality of the manuscript. We have carefully revised the manuscript in accordance with your comments.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Great job with the revised version and cover letter (reply to reviewers). I recommend accepting this manuscript.