Spatiotemporal Evolution and Driving Factors of NPP in the LanXi Urban Agglomeration from 2000 to 2023

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The overall research is valuable. However, the findings on changes in vegetation NPP due to climate change and human activities will be merit attention once the manuscript is refined as below:

1. At some places language does not read naturally or meet scientific standards. I recommend having the manuscript reviewed by a native English speaker or a professional editor. Below are a few examples, though this issue is present throughout the manuscript:

• • Line 22: “...with this power increasing...” This phrase is unclear and needs rephrasing for clarity
  • Line 26: “...only climate change and only human activities...” The repetition of “only” is awkward and redundant.

2. The abstract requires major revision. It reads more like a preliminary results section rather than a concise summary of the study.

3. The figure quality is poor; In most of the figures, the fonts are unreadable or too small to interpret effectively.

4. You said it will help global researchers, but didn't make any discussion on global prospective. I suggest to add a paragraph discussing how your results will help them.

Author Response

Response to Reviewer 1 Comments

comments and suggestions for Authors

The overall research is valuable. However, the findings on changes in vegetation NPP due to climate change and human activities will be merit attention once the manuscript is refined as below:

Point 1:

At some places language does not read naturally or meet scientific standards. I recommend having the manuscript reviewed by a native English speaker or a professional editor. Below are a few examples, though this issue is present throughout the manuscript:

Line 22: “...with this power increasing...” This phrase is unclear and needs rephrasing for clarity; Line 26: “...only climate change and only human activities...” The repetition of “only” is awkward and redundant.

Response 1:

Thank you very much for your valuable comments regarding the language quality of our manuscript. We apologize for the unclear or awkward expressions that arose from our limited English proficiency.In response to your suggestion, we have conducted a thorough English editing and comprehensive revision of the entire manuscript to significantly improve the language quality and scientific clarity.  

Lines11-33: Additionally, the specific issues you raised were carefully addressed.In response to your comments, we have thoroughly and carefully polished and revised the abstract section . All issues you pointed out have been fully addressed, and the problematic expressions have been corrected. The relevant problems you mentioned no longer exist in the revised version. Please refer to the updated manuscript for details.

We sincerely appreciate your constructive feedback, which has greatly enhanced the overall quality of our work.

 

Point 2:

The abstract requires major revision. It reads more like a preliminary results section rather than a concise summary of the study.

Response 2:

Thank you very much for your valuable comments on our study. We carefully reviewed your evaluation of the abstract section, particularly your observation that the current abstract reads more like a detailed listing of results rather than serving as a concise summary. We fully agree with your suggestion and recognize that, in a high-level academic paper, the abstract should succinctly and clearly present the core objectives, methodology, main findings, and academic as well as practical significance, rather than focusing on exhaustive details.

In response, we have undertaken a comprehensive and structural revision of the abstract. The opening of the abstract has been rewritten to highlight the specific scientific issues addressed by this study and emphasize the global representativeness of the selected region, as well as to clarify the theoretical and practical significance of this work. For the methodology, we now adopt a more concise and general description of the data sources and the integrated multi-model research approach. In the section on main findings, we have removed the previous itemized and data-heavy statements, retaining only qualitative conclusions that reflect the overall trends and spatial patterns, with a particular emphasis on the interaction between dominant driving factors. Finally, we have added a statement at the end of the abstract underlining the implications of this study for ecosystem management in arid and ecotone urban agglomerations, as well as its reference value for similar regions globally, thereby making the abstract more complete and directly addressing your suggestions.

We believe that, following this round of revision, the abstract is now more concise and structurally sound, and more effectively highlights the academic innovation and practical value of our research, which will better facilitate international readers’ understanding of the study’s core contributions. We sincerely appreciate your constructive feedback; your advice has played a vital role in improving the academic rigor and international presentation of our manuscript. We also welcome any further comments and criticism you may have, so that we may continue to enhance the quality of our work.

Lines 11-32: Abstract:  This study quantitatively evaluates the effects of Human activities (HAs) and climate change (CC) on the terrestrial ecosystem carbon cycle, providing a scientific basis for ecosystem management and the formulation of sustainable development policies in urban agglomerations located in arid and ecotone regions. Using the LanXi urban agglomeration in China as a case study, we simulated the spatiotemporal variation of vegetation net primary productivity (NPP) from 2000 to 2023 based on MODIS remote sensing data and the CASA model. Trend analysis and the Hurst index were employed to identify the dynamic trends and persistence of NPP. Furthermore, the Geographical Detector model with optimized parameters, along with nonlinear residual analysis, was employed to investigate the driving mechanisms and relative contributions of HAs and CC to NPP variation. The results indicate that NPP in the LanXi urban agglomeration exhibited a fluctuating upward trend, with an average annual increase of 4.26 gC/m2 per year. Spatially, this trend followed a pattern of “higher in the center, lower in the east and west,” with more than 95% of the region showing an increase in NPP. Precipitation, mean annual temperature, evapotranspiration, and land use types were identified as the primary driving factors of NPP change. The interaction among these factors demonstrated a stronger explanatory power through factor coupling. Compared with linear residual analysis, the nonlinear model showed clear advantages, indicating that vegetation NPP in the LanXi urban agglomeration was jointly influenced by HAs and CC. These findings can further act as a basis for resource and environmental research in similar ecotone regions globally, such as Central Asia, the Mediterranean Basin, the southwestern United States, and North Africa.

 

Point 3:

The figure quality is poor; In most of the figures, the fonts are unreadable or too small to interpret effectively.

Response 3: 

Thank you very much for your valuable comments and suggestions regarding the quality of our figures. We have carefully reviewed your feedback, particularly concerning issues such as small fonts and lack of legibility. We fully recognize that clear, standardized, and easily identifiable figures are crucial for effective scientific communication and for facilitating the understanding of international peers.In response to your suggestions, we have conducted a thorough review and comprehensive revision of all figures in the manuscript. The specific improvements are as follows:  

Lines 156-158:Figure 1, The figure has been completely redrawn; font sizes have been increased to enhance readability; and additional annotations have been added separately to Figures 1a and 1b for clarification.

Lines 176-179:Figure 2, This figure has been redrawn with updated layout, explicit clarification of the role of the CASA model, and all abbreviations have been replaced with their full terms.

Lines 276-279:Figure 3, Reproduced using Excel; font size has been increased; and unnecessary captions have been removed.

Lines 280-281:Figure 4, Redrawn with improved resolution; all fonts in ArcGIS have been set to 36pt; and layout has been optimized.

Lines 326-328:Figure 6, Redrawn; subplot annotations in Figures 6a and 6c have been revised; figure layouts have been optimized; and font sizes have been increased throughout.

Lines :Figure 7, The original figure has been deleted, as all the main results are adequately shown in the following figure. Specific results from this figure are not discussed in detail, and the original color scheme made it almost illegible.

Lines 352-354 :Figure 7--originally figure8, Alphabetical labels for the driving factors have been updated, and font sizes have been adjusted.

Lines 370-372 :Figure 8(originally Figure 9): Redrawn; alphabetical labels for the driving factors have been updated; and unnecessary figure captions have been removed.

Lines 411-414 :Figure 10(originally Figure 11):Redrawn; font sizes have been increased; and the figure legend has been reformatted for clarity.

Lines 429-431 :Figure 11(originally Figure 12), Redrawn; font sizes have been increased; and all abbreviations are explicitly explained in the figure captions.

We believe that these improvements have greatly enhanced the clarity, readability, and professionalism of the figures, thereby improving the overall quality and presentation of the manuscript. Thank you again for your constructive feedback.

 

Point 4:

You said it will help global researchers, but didn't make any discussion on global prospective. I suggest to add a paragraph discussing how your results will help them.

Response 4: 

Thank you for your insightful suggestion regarding the global perspective of our work. We fully recognize that while our research focuses on the Lanxi urban agglomeration in Northwest China, the theoretical framework, methodologies, and main findings have important implications for urban and ecotonal regions worldwide, especially in arid and semi-arid zones.In response to your recommendation, we have added a dedicated paragraph in the Discussion section to explicitly address the global relevance and applicability of our results. Specifically, we highlight that many urban agglomerations located in ecological transition zones across Central Asia, the Mediterranean basin, North Africa, and the southwestern United States face similar challenges related to the impacts of climate change and intensified human activities on ecosystem functioning. The integrated methodological approach and the nonlinear diagnostic techniques developed in our study can be adapted and applied in these regions to disentangle the complex drivers of NPP dynamics, quantitatively assess the relative contributions of climate and anthropogenic factors, and support targeted strategies for ecosystem restoration and sustainable management. We believe that this addition strengthens the international value and relevance of our research, directly addressing your suggestion.We sincerely thank you for prompting us to broaden the discussion and enhance the global significance of our manuscript. Your constructive feedback has greatly improved the quality and impact of our work.

Lines 569-582:Although this study focuses on the Lanxi urban agglomeration, a representative ecological transition zone in Northwest China, the methodologies and key findings have broad relevance to similar arid and semi-arid ecological transition zones and rapidly urbanizing regions worldwide. Urban agglomerations in Central Asia [54], Northern Africa [55], the southwestern United States, and the Mediterranean similarly face complex ecosystem challenges under the combined pressures of HAs and CC [56]. The integrated nonlinear residual model and optimized geographical detector effectively clarify the multi-factor coupling mechanisms driving vegetation productivity across different spatial scales and locations, providing valuable methodological insights for cross-regional and interdisciplinary ecosystem management and sustainable land-use planning. These findings offer scientific evidence and decision-making support for urban agglomerations in global arid and ecological transition zones to address CC, evaluate human impacts, and design effective ecological restoration and conservation strategies

[54]Tao C, Tang G, Ye Y, et al. Unraveling the relative impacts of climate change and human activities on grassland productivity in Central Asia over last three decades. Science of The Total Environment,2020,743,140649. https://doi.org/10.1016/j.scitotenv.2020.140649.

[55]Sabastine U, et al.Assessing the spatio-temporal variability of vegetation productivity in Africa: quantifying the relative roles of climate variability and human activities. International Journal of Digital Earth, 2017, 10, 9. https://doi.org/10.1080/17538947.2016.1265017.

[56]Gang, C., et al. "Comparative assessment of grassland NPP dynamics in response to climate change in China, North America, Europe and Australia from 1981 to 2010." Journal of Agronomy and Crop Science 20114, (2015): 57-68. https://doi.org/10.1111/jac.12088

 

Response: We are deeply grateful for the valuable insights you have shared. We are confident that with these insights, we will be able to make significant improvements. We also wish you every success in your research endeavors.

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript "Research on Spatiotemporal Evolution and Driving Factors of NPP in Lanxi Urban Agglomeration from 2000 to 2023" by Tao Long et al. aims to NPP trends China's Lanxi Urban Agglomeration for last to decades and main factors driving this trends.

This is a well-written and structured work relying solely on remote sensing methods. I could find only two minor flaws in the text :
1. I think that Figure 7 can by removed, since all main result from it are represented in next figure. Specific results from this figure are not discussed in details, and chosen colors makes it barely readable. 
2. Lines 355-356 - absolutely unclear why random forest is overfit, link which should explain it is in chinese and even after machine translation I could not find any additional information why R² 0.8 is overfitting. 

The only major drawback concerns the conceptualisation of the article. The use of only remote sensing methods leads to the situation when the basic assessments and conclusions of the article are made solely on the basis of NPP data from MODIS MOD17A3HGF, which itself is a combination of several model computations. In addition, it is well known that although MODIS MOD17A3HGF is a long-known and extensively tested tool for many ecosystems, its NPP predictions are far from ideal. For example, this has been shown for a number of ecosystems in China (https://www.mdpi.com/2072-4292/14/7/1634, figure 5). Therefore, it is strongly recommended that the authors periodically mention in the text that the NPP is modelled, not measured NPP, and highlight these facts in the discussion.

The level of English is great.

Author Response

Response to Reviewer 2 Comments

comments and suggestions for Authors

The manuscript "Research on Spatiotemporal Evolution and Driving Factors of NPP in Lanxi Urban Agglomeration from 2000 to 2023" by Tao Long et al. aims to NPP trends China's Lanxi Urban Agglomeration for last to decades and main factors driving this trends.This is a well-written and structured work relying solely on remote sensing methods. I could find only two minor flaws in the text :

Point 1:

I think that Figure 7 can by removed, since all main result from it are represented in next figure. Specific results from this figure are not discussed in details, and chosen colors makes it barely readable.

Response 1: 

Thank you very much for your thorough review and positive assessment of our manuscript, as well as for your valuable suggestions. Your constructive feedback and specific recommendations have not only recognized the overall structure and language of our work but have also provided clear guidance for further improvement. Regarding the issue of Figure 7, we sincerely appreciate your careful examination and advice. Upon further review, we also found that the main results originally shown in Figure 7 are now presented more clearly and comprehensively in the revised figures. In addition, the color scheme and visual clarity of the original Figure 7 were indeed suboptimal. To improve the conciseness and readability of the manuscript, we have deleted Figure 7 and revised the corresponding descriptions in the main text to ensure content continuity without omitting any key information. Please note that the original Figure 8 has now been renumbered as Figure 7, and the corresponding sequence has been adjusted accordingly.

Lines 352-354 :Figure 7. Factor detection results for NPP driving factors.

Lines 331-334:Note:PET,potential evapotranspiration ; EVP,actual evapotranspiration ; PRE, annual precipitation; DEM digital elevation model; POP population density; GDP, economic density ;LU, land use type ;MAT, mean annual temperature

 

Point 2:

Lines 355-356 - absolutely unclear why random forest is overfit, link which should explain it is in chinese and even after machine translation I could not find any additional information why R²0.8 is overfitting.

Response 2: 

Regarding your concern about the unclear explanation of “random forest overfitting” in lines 355–356, we fully acknowledge the validity of your question. We have revised and clarified the relevant section in the manuscript. Specifically, we found that the fitting accuracy of the random forest model was significantly higher than that of other models. Therefore, we conducted partial validation using the test dataset to check for overfitting. The R² values for test datasets in other regions dropped significantly, which indicated the presence of overfitting. To address this issue and ensure the validity of our study, we have added further explanations in the discussion section. The relevant descriptions have been updated in the revised manuscript.

Lines 382-384:However, to ensure the robustness of the model, validation was conducted using data from adjacent regions. The resulting decline in the R2 value for the random forest model indicated potential overfitting

 

Point 3:

The only major drawback concerns the conceptualisation of the article. The use of only remote sensing methods leads to the situation when the basic assessments and conclusions of the article are made solely on the basis of NPP data from MODIS MOD17A3HGF, which itself is a combination of several model computations. In addition, it is well known that although MODIS MOD17A3HGF is a long-known and extensively tested tool for many ecosystems, its NPP predictions are far from ideal. For example, this has been shown for a number of ecosystems in China (https://www.mdpi.com/2072-4292/14/7/1634, figure 5). Therefore, it is strongly recommended that the authors periodically mention in the text that the NPP is modelled, not measured NPP, and highlight these facts in the discussion.

Response 3: 

Thank you very much for your insightful comments regarding the methodological limitations of our study. We fully agree with your point that relying solely on remote sensing products (MODIS MOD17A3HGF) provides “model-simulated values” of NPP rather than direct field measurements, and that these datasets may exhibit certain biases across different ecosystems. In response, we have thoroughly addressed the limitations of the NPP data used in our work in the discussion section and have cited the latest assessment literature you recommended (Liu, G, 2022). Relevant statements have been revised and updated in both the discussion and the limitations and outlook sections, clearly indicating that “the NPP data adopted in this study are simulated values rather than in-situ measurements.” We also note our intention to validate NPP data in future studies, referring to relevant research to further enhance the rigor of our results. In the limitations section, we remind readers to be mindful of the uncertainties introduced by the use of modeled data. We believe these clarifications and acknowledgements strengthen the scientific rigor and transparency of our research conclusions. Once again, we sincerely thank you for your constructive suggestions regarding the structure, content, and academic standards of our manuscript, which have greatly improved the quality of our paper.

Lines 460-463:For NPP estimation, prior research has validated remote sensing-based NPP data using field measurements, such as grassland quadrat biomass and carbon cycling reference datasets from typical Chinese forest ecosystems [36], thereby enhancing the accuracy and reliability of findings.

Lines 597-600:It is also important to note that MODIS NPP data products inherently contain some uncertainties. Due to limitations, this study was unable to fully validate NPP results with field measurements, as performed in other studies. Enhancing validation with ground-truth data would improve the rigor of future work.

[36]Liu, G.; Shao, Q.; Fan, J.; Ning, J.; Rong, K.; Huang, H.; Liu, S.; Zhang, X.; Niu, L.; Liu, J. Change Trend and Restoration Potential of Vegetation Net Primary Productivity in China over the Past 20 Years. Remote Sens. 2022, 14, 1634. https://doi.org/10.3390/rs14071634

The level of English is great.

Response: We sincerely appreciate your support and recognition. We believe that with your valuable input, we can continuously improve. Thank you very much for sharing your insightful feedback. We sincerely wish that your scientific research will go well.

Reviewer 3 Report

Comments and Suggestions for Authors

-General comments. The authors of this study calculated the NPP of the Lanzhou-Xining urban agglomeration, and then explored the driving forces of NPP change and the contribution rate of climate change and human activities to NPP change. There is a lot of work, but the innovation is very average, and it is repetitive research.

-Specific comments.

--Title. Delete “Research on”.

--Abstract. The first sentence of the abstract is poorly written. The Lanzhou-Xining urban agglomeration has been analysed, and this expression is inappropriate and needs to be changed. This article is an analysis of the NPP of urban agglomerations, not an analysis of urban agglomerations. In the second sentence, are so many research methods used to analyze the characteristics and driving forces of NPP spatiotemporal changes? The expression is also not accurate and rigorous. It is advisable to write separately. What methods are used to simulate and analyze the spatiotemporal changes of NPP, and what methods are used to explore the driving forces of NPP changes?

-Introduction. Line 62, research on vegetation NPP in urban agglomerations is relatively scarce. But, why research on vegetation NPP in urban agglomerations is important? Overall, the introduction does not do a good job of identifying the shortcomings of the existing research. The innovation of this paper is average, and this paper is only a repetitive study. In particular, the repetition rate of this article is as high as 30%, so it is recommended that the author think carefully about what is the innovation of this article? and greatly reduce the repetition rate of this paper.

--Figure 1. Where does the border of Loess Plateau and Tibetan Plateau come from? References need to be given in the caption of the figure.

--Change “2.2 Research data” to “2.2 Data”.

--Change “2.2 Research Methods” to “2.2 Methods”.

--Figure 2. Figures need to be self-explanatory, and readers don't need to use text to understand them. There are too many abbreviations on the figure, and what they mean needs to be explained in the caption. Some words are misspelled, such as Time Variatio? And the word has grammatical errors. Please carefully check the whole figure and make detailed revisions. Why can't we see the CASA model in figure 2? What data is input into the CASA model to simulate the NPP?

-Figure 4. Please check the caption for spelling mistakes.

-Figure 6. 6a, slope? Too simple. Slope of NPP change.

-Figure 7. The full name of each acronym variable should be given in the caption. Similar comments for caption of figures 8, 9.

Author Response

Response to Reviewer 3 Comments

comments and suggestions for Authors

General comments. The authors of this study calculated the NPP of the Lanzhou-Xining urban agglomeration, and then explored the driving forces of NPP change and the contribution rate of climate change and human activities to NPP change. There is a lot of work, but the innovation is very average, and it is repetitive research.

General Response:

Thank you very much for your careful review and valuable comments on our research. We fully recognize and appreciate your perspectives and observations. You pointed out that the novelty of this study is rather limited and that there is a certain degree of repetition with previous research. This has provided us with important reflection and direction for improvement in our future work.

We sincerely acknowledge that the spatiotemporal variation of net primary productivity (NPP) and its driving mechanisms are hot topics in the field of ecology, with a large number of relevant studies already published. Our research indeed adopts established methods and models; thus, there are inherent similarities and elements of inheritance in our methodological approach, which results in relatively limited innovation.

However, we have tried to reflect the value of our work in the following aspects: On one hand, we have extended the study period up to 2023, which compensates for the lack of updated data in some previous studies and makes the time series analysis more timely and continuous. Furthermore, we integrated multi-source remote sensing data and various quantitative analysis methods in an effort to more comprehensively and multidimensionally reveal the driving factors of NPP changes. On the other hand, we attempted to precisely distinguish the relative contributions of climate change and human activities to NPP changes, aiming to enhance the policy relevance of our conclusions. The research significance and value have been further supplemented and described in the last paragraph of the introduction, specifically:

Lines 125-131: This research ensures the timeliness and relevance of its findings through a multi-source, data-driven framework. By distinguishing the relative influence of climatic and anthropogenic drivers, it contributes a valuable scientific basis for developing effective strategies for ecosystem protection and restoration. Furthermore, the study offers meaningful references for similar NPP research in ecological transition zones worldwide.

Nevertheless, we are well aware that there remains substantial room for improvement in theoretical depth, model innovation, and the exploration of multi-scale coupling mechanisms. We very much appreciate your critical feedback and suggestions. Thus, in the section on limitations and future prospects, we have further stated our plan to introduce new dynamic models and big data technologies to deepen our understanding of ecosystem response mechanisms. At the same time, we will strengthen interdisciplinary integration and conduct in-depth analysis in combination with socio-economic development scenarios, striving for higher levels of originality and scientific value.Once again, we sincerely thank you for your candid advice, which is of great importance for improving the quality and academic standard of our research. We will continue to work hard to improve this work and strive to achieve more innovative and practical results in our future studies.

Point 1:

Title. Delete “Research on”.

Response 1: 

We agree with the reviewer’s suggestion and sincerely thank you for your thorough review of our manuscript. We have removed "Research on" from the title to improve its conciseness.

Lines 2-3: Spatiotemporal Evolution and Driving Factors of NPP in Lanxi Urban Agglomeration from 2000 to 2023

 

Point 2 

--Abstract. The first sentence of the abstract is poorly written. The Lanzhou-Xining urban agglomeration has been analysed, and this expression is inappropriate and needs to be changed. This article is an analysis of the NPP of urban agglomerations, not an analysis of urban agglomerations. In the second sentence, are so many research methods used to analyze the characteristics and driving forces of NPP spatiotemporal changes? The expression is also not accurate and rigorous. It is advisable to write separately. What methods are used to simulate and analyze the spatiotemporal changes of NPP, and what methods are used to explore the driving forces of NPP changes?

Response 2: 

We sincerely appreciate the reviewer’s careful and constructive feedback regarding the abstract section. We fully understand your concerns, especially about the inaccurate description in the first sentence of the abstract and the lack of precision and rigor in clarifying the application of research methods.

In response to your suggestions, we have carefully revised the abstract to improve both its logic and academic accuracy. Specifically, we have replaced the original expression of “analyzing the urban agglomeration” with “analyzing the NPP of the LanXi urban agglomeration,” which more precisely reflects that our research focuses on the net primary productivity of vegetation rather than the urban agglomeration as a whole. Furthermore, to address the previously ambiguous method description, we have separated the statements: we now clearly specify that the CASA model, trend analysis, and Hurst index are used to simulate and analyze the spatiotemporal dynamics of NPP, while the Optimal Parameters Geographical Detector and nonlinear residual analysis are applied to explore the driving mechanisms and contributions of climate change and human activities to NPP changes. This revision not only clarifies the technical route of our study but also avoids the problem of excessive generalization in methodological expression.

Lines 11-32: Abstract:This study quantitatively evaluates the effects of Human activities (HAs) and climate change (CC) on the terrestrial ecosystem carbon cycle, providing a scientific basis for ecosystem management and the formulation of sustainable development policies in urban agglomerations located in arid and ecotone regions. Using the LanXi urban agglomeration in China as a case study, we simulated the spatiotemporal variation of vegetation net primary productivity (NPP) from 2000 to 2023 based on MODIS remote sensing data and the CASA model. Trend analysis and the Hurst index were employed to identify the dynamic trends and persistence of NPP. Furthermore, the Geographical Detector model with optimized parameters, along with nonlinear residual analysis, was employed to investigate the driving mechanisms and relative contributions of HAs and CC to NPP variation. The results indicate that NPP in the LanXi urban agglomeration exhibited a fluctuating upward trend, with an average annual increase of 4.26 gC/m2 per year. Spatially, this trend followed a pattern of “higher in the center, lower in the east and west,” with more than 95% of the region showing an increase in NPP. Precipitation, mean annual temperature, evapotranspiration, and land use types were identified as the primary driving factors of NPP change. The interaction among these factors demonstrated a stronger explanatory power through factor coupling. Compared with linear residual analysis, the nonlinear model showed clear advantages, indicating that vegetation NPP in the LanXi urban agglomeration was jointly influenced by HAs and CC. These findings can further act as a basis for resource and environmental research in similar ecotone regions globally, such as Central Asia, the Mediterranean Basin, the southwestern United States, and North Africa.

We believe that the revised abstract now more accurately, clearly, and scientifically represents the research content and the study’s innovations. Thank you again for your professional and valuable suggestions, which have been very helpful in improving the quality of our manuscript. We look forward to your further guidance.

Point 3:

Introduction. Line 62, research on vegetation NPP in urban agglomerations is relatively scarce. But, why research on vegetation NPP in urban agglomerations is important? Overall, the introduction does not do a good job of identifying the shortcomings of the existing research. The innovation of this paper is average, and this paper is only a repetitive study. In particular, the repetition rate of this article is as high as 30%, so it is recommended that the author think carefully about what is the innovation of this article? and greatly reduce the repetition rate of this paper.

Response 3: 

Thank you very much for your valuable suggestions regarding the introduction of our manuscript. We fully agree with your view on the scarcity and importance of research related to NPP in urban agglomerations. In light of your advice, we have updated the introduction to address previous research gaps and to better articulate the significance of our study. Specifically, based on relevant scholarly work, we have added the following statements: Du et al. pointed out that urban agglomerations are regions where human activities are especially intense and frequent. Li et al. further noted that the discussion on urbanization as a key driver of NPP change remains far from settled. Therefore, urban agglomerations located in ecologically fragile areas exhibit particularly complex human–environment relationships, which have a profound impact on urban sustainability. The NPP of urban agglomerations is the result of coupled effects between ecological and climatic conditions and human activities. Such research has attracted worldwide attention from scholars, thus underscoring its importance.

Lines 91-98:Du [22] pointed out that urban agglomerations are regions where HAs are particularly frequent and intense, while Li [23] emphasized that the role of urbanization as a driving factor of NPP remains an unresolved issue. In ecologically fragile regions, urban agglomerations exhibit especially complex human-environment interactions, which have a profound impact on urban sustainability. The NPP of urban agglomerations is shaped by the coupled effects of ecological-climatic conditions and HAs. As a result, this topic has drawn increasing global scholarly attention, underscoring the significance of conducting research in this area.

 

With regard to the innovations of our study, we acknowledge that, compared to some previous studies, there are indeed elements of inheritance and reference in both the research methods and the study area. However, our aim was to adopt an integrative methodological approach to systematically reveal the spatiotemporal variations and driving mechanisms of NPP in the LanXi urban agglomeration and to extend the Chinese case to a global perspective. In doing so, we hope to provide more targeted scientific evidence for ecosystem regulation and urban planning. We will further highlight these innovative points in the manuscript, clearly delineate the differences from previous research, and emphasize the depth and significance of our work. Specifically, we have added a paragraph in the Discussion section to underscore the relevance of our study to regions such as Central Asia and the Mediterranean, while also strengthening the statement of research significance in the Introduction.

Lines 569-582:Although this study focuses on the Lanxi urban agglomeration, a representative ecological transition zone in Northwest China, the methodologies and key findings have broad relevance to similar arid and semi-arid ecological transition zones and rapidly urbanizing regions worldwide. Urban agglomerations in Central Asia [54], Northern Africa [55], the southwestern United States, and the Mediterranean similarly face complex ecosystem challenges under the combined pressures of HAs and CC [56]. The integrated nonlinear residual model and optimized geographical detector effectively clarify the multi-factor coupling mechanisms driving vegetation productivity across different spatial scales and locations, providing valuable methodological insights for cross-regional and interdisciplinary ecosystem management and sustainable land-use planning. These findings offer scientific evidence and decision-making support for urban agglomerations in global arid and ecological transition zones to address CC, evaluate human impacts, and design effective ecological restoration and conservation strategies

 

Regarding the issue of manuscript similarity, we highly appreciate the reviewer’s reminder. We recognize that some of our previous descriptions had a high degree of overlap with earlier studies. In response, we have thoroughly revised the manuscript, rephrased relevant sections with original wording, and placed greater emphasis on the unique perspectives and data analysis processes of our study to ensure the manuscript's originality and academic integrity. We are committed to closely monitoring the similarity rate and will conduct multiple rounds of similarity checks and revisions prior to final submission.

Once again, we sincerely thank you for your rigorous review and professional guidance, which have motivated us to further enhance the quality and academic standard of our manuscript.

 

Point 4:

Figure 1. Where does the border of Loess Plateau and Tibetan Plateau come from? References need to be given in the caption of the figure.

Response 4: 

Thank you very much for your valuable suggestion regarding Figure 1 in our manuscript. We realize that indicating the data sources enhances the rigor and readability of our study. Accordingly, we have added a note beneath the figure stating that all vector data used in this study were obtained from the Resource and Environment Science and Data Center, Chinese Academy of Sciences (www.resdc.cn).

Lines 157-158:Figure 1. Overview of the study area. Note: All vector spatial data were obtained from the Resource and Environmental Science and Data Center of the Chinese Academy of Sciences

 

Point 5:

Change “2.2 Research data” to “2.2 Data”.

Change “2.2 Research Methods” to “2.2 Methods”.

Response 5: 

Thank you for your attention to the details in our manuscript title and your suggestion to revise the section headings. We fully agree with your recommendations to change “2.2 Research Data” to “2.2 Data” and “2.3 Research Methods” to “2.3 Methods.” These modifications have been made as per your suggestion.

Line 159: 2.2 Data

Line 168:2.3 Methods

Point 6:

Figure 2. Figures need to be self-explanatory, and readers don't need to use text to understand them. There are too many abbreviations on the figure, and what they mean needs to be explained in the caption. Some words are misspelled, such as Time Variatio? And the word has grammatical errors. Please carefully check the whole figure and make detailed revisions. Why can't we see the CASA model in figure 2? What data is input into the CASA model to simulate the NPP?

Response 6: 

Thank you very much for your detailed and professional comments on Figure 2. In response to your concerns regarding insufficient self-explanation, excessive unexplained abbreviations, spelling and grammatical errors, and the inadequate presentation of the CASA model, we have reflected thoroughly and made comprehensive revisions. Our specific responses are as follows:

1.We have added a detailed depiction of the CASA (Carnegie-Ames-Stanford Approach) model process for generating NPP data, explicitly indicating the main input variables such as solar radiation, land cover data, vegetation indices, and air temperature. This addition fully demonstrates the sources of the NPP data.

2. We fully understand that figures should be self-explanatory so that readers can easily interpret them without consulting the main text. Therefore, we have redesigned and reformatted Figure 2. All abbreviations are now clearly defined and explained in the figure caption, and we have optimized the font size and color contrast to improve readability. For example, “Pre” has been changed to “Precipitation”; “LULC” to “Land cover”; “Slope” to “Slope analysis”; “OPGD” to “GeoDetector analysis”; and “Hurst” to “Hurst Index”. As you specifically pointed out, the spelling error “Time Variatio” has been corrected to “Time Variation,” and we have meticulously reviewed the entire figure to ensure there are no similar errors or grammatical mistakes.

We are very grateful for your meticulous attention to detail, which has greatly improved our awareness of scientific rigor and the quality of our figures. After these revisions, Figure 2 is now clearer, more standardized, and more complete, and it can better support the interpretation of our manuscript. We will continue to maintain rigorous quality control to ensure that all figures and tables in the manuscript meet the highest standards.

 

 

 

Point 7:

Figure 4. Please check the caption for spelling mistakes.

Response 7: 

Thank you for your careful review and for pointing out the spelling mistake in the caption of Figure 4. We have corrected the error by changing “roportion” to the correct spelling, “proportion.” The revised figure caption now reads:

Line 281: “Figure 4. Proportion of different types of NPP.”

Point 8:

Figure 6. 6a, slope? Too simple. Slope of NPP change.

Response 8: 

Thank you very much for your valuable suggestion regarding Figure 6. We agree that the original label “Slope” for panel 6a is too brief and may cause ambiguity. To improve accuracy and clarity, we have revised the label to “Slope of NPP change,” which more explicitly conveys the spatial trend of NPP variation depicted in this panel.We sincerely appreciate your careful review and constructive advice, which have greatly contributed to enhancing the quality of our manuscript.

Figure 6. NPP mean value change trend from 2000-2023

 

Point 9:

Figure 7. The full name of each acronym variable should be given in the caption. Similar comments for caption of figures 8, 9.

Response 9: 

Thank you very much for your valuable comments regarding the presentation and caption format of the figures. In response to your suggestions, we have made the following revisions:

First, as the data presented in Figure 8 have already been discussed in detail within the main text, we have removed Figure 7 in order to reduce redundancy and optimize the overall structure of the manuscript. Second, for Figures 8 and 9, we have thoroughly revised their captions by providing the full names and abbreviations for all variables.

Lines 331-334:The average VNNP from 2000 to 2023 was selected as the dependent variable (Y), while the driving factors (X) included potential evapotranspiration (PET), actual evapotranspiration (EVP), annual precipitation (PRE), digital elevation model (DEM), POP, economic density (GDP), slope (SLOPE), and mean annual temperature (MAT).

Moreover, in accordance with international standards, the subfigure labels have been changed from lowercase to uppercase letters, ensuring consistency with formatting in leading academic journals.During the revision process, we also referred to the formatting practices of related international journals, particularly the article by He and Long (2024) recently published in Sustainability [1], to further improve the standardization and international readability of our manuscript.

We sincerely appreciate your detailed review and constructive feedback. We believe these improvements will enhance the overall quality of our manuscript, and we welcome any further suggestions you may have.

[1]He, Y.; Long, Q. Spatiotemporal Characteristics and Driving Factors of Ecosystem Regulation Services Value at the Plot Scale. Sustainability 2024, 16, 4548. https://doi.org/10.3390/su16114548

 

Figure 7. Factor detection results for NPP driving factors.Note:

 

Figure 8. Interaction detection results for NPP driving factors.

Response: We are deeply grateful for the valuable insights you have shared. We are confident that with these insights, we will be able to make significant improvements. We also wish you every success in your research endeavors.

 

 

Reviewer 4 Report

Comments and Suggestions for Authors

Overall, the manuscript's theme is relevant. The structure and methodology of the manuscript are adequate, and the conclusion reflects the study's objective.
I strongly suggest the following revisions:
- Overall, the acronyms were not correctly identified in the text prior to their presentation. It is suggested that the acronym “CASA (Carnegie-Ames-Stanford Approach) Model” be described in the manuscript's introduction so that the reader can understand the meaning of the acronym and the context in which it is being applied. Other acronyms adopted also need to be identified more clearly prior to their presentation, such as those used in Figure 2 (LULC, Pre, Tem, OPGD, CC, HA) and Table 2. Throughout the text, it is possible to associate the acronyms with the terms used, but the reader needs to return to the previous item many times for understanding to be clear.
- Figures 1, 2, 9, 10 are not mentioned in the text. Their presentation needs to be indicated in the text prior to their presentation, as well as the details of the letters presented as part of the figure.
- The indication in the text prior of Figures 11a, 11b, 11c, 11d needs to be corrected, as it is only indicated as a, b, c, d.

Author Response

Response to Reviewer 4 Comments

comments and suggestions for Authors

Overall, the manuscript's theme is relevant. The structure and methodology of the manuscript are adequate, and the conclusion reflects the study's objective.I strongly suggest the following revisions:

Point 1:

Overall, the acronyms were not correctly identified in the text prior to their presentation. It is suggested that the acronym “CASA (Carnegie-Ames-Stanford Approach) Model” be described in the manuscript's introduction so that the reader can understand the meaning of the acronym and the context in which it is being applied. Other acronyms adopted also need to be identified more clearly prior to their presentation, such as those used in Figure 2 (LULC, Pre, Tem, OPGD, CC, HA) and Table 2. Throughout the text, it is possible to associate the acronyms with the terms used, but the reader needs to return to the previous item many times for understanding to be clear.

Response 1: 

Thank you very much for your careful review and valuable comments regarding the use of acronyms in the manuscript. We sincerely apologize for not providing the full terms and definitions before introducing these acronyms, which may have caused confusion for readers. In accordance with your suggestion, we have made comprehensive revisions to the manuscript. Specifically, by learning the conventions of scientific research writing, we now clearly define the "Carnegie-Ames-Stanford Approach (CASA)" model. in the introduction to ensure readers understand the meaning and application context of the acronym. Furthermore, all other acronyms—including those used in Figure 2 (LULC, Pre, Tem, OPGD, CC, HA) and Table 2—are now defined in full upon their first appearance in the main text. We believe these adjustments will greatly enhance the clarity and readability of our manuscript. Thank you again for your thoughtful suggestions, which have been instrumental in improving the quality of our work.

Line 54: Carnegie-Ames-Stanford Approach (CASA)

Line 180: 2.3.1 CASA Model

Line 111-112:  OPGD(optimal parameter geographical detector)

 

Lines 331-334:The average VNNP from 2000 to 2023 was selected as the dependent variable (Y), while the driving factors (X) included potential evapotranspiration (PET), actual evapotranspiration (EVP), annual precipitation (PRE), digital elevation model (DEM), POP, economic density (GDP), slope (SLOPE), and mean annual temperature (MAT).

 

Point 2:

Figures 1, 2, 9, 10 are not mentioned in the text. Their presentation needs to be indicated in the text prior to their presentation, as well as the details of the letters presented as part of the figure.

Response 2: 

Thank you very much for your careful review and valuable reminder regarding the citation of Figures 1, 2, 9, and 10. We sincerely apologize for the oversight in not referring to these figures and their subpanels in the main text prior to their presentation,They have been specifically highlighted in yellow for clear visibility . In response, we have thoroughly revised the manuscript to include explicit references to these figures at appropriate points in the text, ensuring that readers are properly guided to their presentation and understand the details of the letters labeling different parts of each figure. We believe these corrections greatly enhance the clarity and coherence of the manuscript. We deeply appreciate your meticulous suggestions, which have significantly improved the quality of our work.

Line 134: “ As shown in Figure 1a”

Line 136: “Figure 1b”

Line 138: “Figure 1c”

Line 142: “Figure 1d”

Line 171: “in Figure 2”

Line 356-357: “LanXi urban agglomeration results from the coupling effects of multiple driving factors(Figure 8). ”(originally Figure 9)

Line 381-382: “SVM regression achieved 0.45, and random forest regression yielded the highest fit at 0.82(Figure 9).”(originally Figure 10)

Point 3:

The indication in the text prior of Figures 11a, 11b, 11c, 11d needs to be corrected, as it is only indicated as a, b, c, d.

Response 3: 

Thank you for your constructive suggestion regarding the citation of subfigures in the main text. We have carefully reviewed and revised the manuscript accordingly. Instead of referring to subfigures only as "a, b, c, d," we now use the full form, such as "Figure 11a, Figure 11b," etc., to ensure accuracy and clarity for the readers. We appreciate your attention to detail, which has helped us improve the overall quality and readability of our manuscript.

Line 395: As shown in Figure 10a,

Line 402:  Figure 10b,

 

Response: We are deeply grateful for the valuable insights you have shared. We are confident that with these insights, we will be able to make significant improvements. We also wish you every success in your research endeavors.

 

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

vegetation NPP=VPNN, this abbreviation has never been seen, it is recommended not to have this abbreviation. The abbreviation doesn't appear in Figure 2.
Figure 1b, DEM All three letters must be capitalized. In addition, the numbers of the 4 sub-figures are all Chinese parentheses, and they must be changed to English parentheses.
Figure 5, the number of the two subgraphs, also uses Chinese parentheses, which need to be changed to English parentheses. Figures 6 and 10 have the same problem.
The language of the text needs to be improved.

Author Response

Please see the attachment.

 

Author Response File: Author Response.pdf