Research on Forage–Livestock Balance in the Three-River-Source Region Based on Improved CASA Model

Dear Reviewer:

Thank you for your letter and for the reviewers’ comments concerning our manuscript entitled “Research on Forage-livestock Balance in the Three-River-Source Region Based on Improved CASA Model” (ID: remotesensing-3189749). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and have made correction which we hope meet with approval. The reviewer comments are laid out below in italicized font and specific concerns have been numbered. Our response is given in normal font and changes/additions to the manuscript are given in the red text in the body.

Comments 1: [I think it not necessary write such a long abstract, please write a short and precise abstract.]

Response 1: Thank you for highlighting this issue. I concur with your observation. Consequently, I have removed certain content and condensed the summary. Specifically, lines 12, 25, 27 and 32 on page 1 have been omitted. 

Comments 2: [Fig.1 put some information in the main text, rather than the fig caption. Remove the websites!]

Response 2: Thank you for pointing this out. I agree with this comment. Therefore, I have deleted the data source websites in the title of Figure 1 and put the area ratio of each grassland vegetation type in the fig caption in line 144-146 of section 2.1 on page 3.

Comments 3: [I've never seen a reference added to the title of a figure! Delete it and put it in the main text.] 

Response 3: Thank you for highlighting this matter. I fully concur with your comment. As a result, I have removed the reference and included it in line 49 of section 1 on page 2, while simultaneously updating the reference serial number.

Comments 4: [Why did you choose 2010 to 2020 for your research?] 

Response 4: Thank you for bringing this to my attention. This study designates the period from 2010 to 2022 as its focus, with 2010 marking the final year of the implementation of the overall plan for ecological protection and construction in the Three-River-Source Nature Reserve. Subsequently, the second phase of the Three-River-Source Region ecological project and the Qinghai-Tibet Plateau ecological project were initiated. However, the impacts of these initiatives, as well as the forage-livestock balance in the region in recent years, remain ambiguous. Therefore, this paper examines the forage-livestock balance in the Three-River-Source Region over the past 13 years (2010-2022) to provide a scientific foundation for the formulation of regional animal husbandry development policies. Since the statistical data regarding the year-end livestock count for the region is sourced from the statistical yearbook of the second year of each county, and the data for 2023 relies on the yet-to-be-published statistical yearbook of 2024, the comprehensive data for 2023 is unavailable. Thus, the research timeframe is constrained to 2022, leading to the selection of 2010-2022 as the study period.

Comments 5: [How is LSWI calculated? Is it taken directly from MOD13Q1?] 

Response 5: Thank you for pointing this out. The Land Surface Water Index (LSWI) is computed using the near-infrared (NIR) and mid-infrared (MIR) bands from MOD13Q1 data, defined by the equation LSWI = (ρ_NIR - ρ_MIR) / (ρ_NIR + ρ_MIR). For further details, please refer to lines 274-276 on page 6 and equation (7).

Comments 6: [Remove (4), (5), and (6) in section 2.2. and please describe what each data is used for?] 

Response 6: 

Thank you for bringing this to my attention. It is indeed accurate that the section on data sources is somewhat extensive; however, the data for items (4), (5), and (6) is of significant importance, and the article appears incomplete without it.

Item (4) provides data on grassland vegetation types, which is essential for calculating Net Primary Productivity (NPP) and grassland yield. The parameter values vary among different grassland types, as illustrated in Figure 1b. To compute NPP and grassland yield, this raster data must be input into the model to derive values specific to each grassland type.

Item (5) pertains to the data necessary for calculating actual livestock-carrying capacity. The year-end livestock numbers are utilized to determine this capacity at the county scale. For the detailed calculation process, please refer to formula (10) in section 2.3.3 on page 7, where Cn represents the year-end livestock number. Additionally, population density data is employed to spatialize the actual livestock-carrying capacity, as outlined on page 13, lines 462-466.

Finally, the field survey data in item (6) is used to validate the results of the grassland yield calculations, with the verification results displayed in Figure 4b on page 12.

Moreover, another reviewer suggested incorporating additional details in item (6), specifically regarding the instruments used and the overall methodology of the field investigation. After careful consideration, we have decided to retain items (4), (5), and (6) in Section 2.2 and to enhance the details in item (6) to ensure the article's completeness. I sincerely apologize for any inconvenience this may have caused and appreciate your valuable advice once again.

Comments 7: [How many filed measurements were collected? draw them in a fig. Could you please publicize these data?] 

Response 7: 

Thank you for pointing it out. We apologize for not clarifying this in the article, and we have revised the content in lines 211-212 on page 5 of the manuscript. The measured data were sourced from the National Forestry and Grassland Administration of China, covering the years 2010 to 2016 and 2020, with the number of verification points ranging from 100 to 900 each year. This paper specifically utilizes the measurement data from 2012 for validation, with a total of 497 measurements distributed as shown in the figure below. We sincerely apologize for any confusion. After consulting with the relevant expert, we learned that it is not feasible to publish the industry data; however, inquiries can be made through the website for access. Thank you once again for your understanding.

Please see the attachment for the picture "Distribution of verification points for field measurements".

Comments 8: [What does fig.5c refer to? Mean value or slope?] 

Response 8: Thank you for highlighting this issue. I apologize, but I am unable to locate the Figure 5c you mentioned. Figure 5 only includes panels a and b, which depict the mean annual actual livestock-carrying capacity and the change trend of actual livestock-carrying capacity, respectively. In contrast, Figure 2c presents the average NPP values for different grassland types across various years, while Figure 7c displays the average values of the improved CASA model, unimproved CASA model, and MOD17A3 NPP values for different grassland types. Both Figures 2c and 7c represent mean values.

Comments 9: [What did the ratios of belowground to aboveground productivity derived from? [49], [19] or [45]?] 

Response 9: Thank you for pointing this out. The method for converting NPP into grassland yield was based on the approaches outlined by Gill et al. [45] and Fan et al. [21] (note that the original reference [19] has been updated to [21]). The ratios of underground productivity to above-ground productivity were derived from Piao et al. [47]. Specifically, the ratios for alpine meadow, alpine steppe, temperate steppe, alpine desert and alpine scrub were found to be 7.92, 4.25, 4.25, 7.89 and 4.42, respectively.

Comments 10: [MOD17A3 is not an accurate simulation for the region. Why are there only 1739 pairs of data?] 

Response 10: Thank you for bringing this to my attention. In this paper, 2000 random points were generated using the random point tool to assess the simulation accuracy of the NPP produced by the improved and unimproved CASA models compared to MOD17A3 NPP. After excluding outliers and points that fell within no-data areas, 1739 pairs of data remained for analysis.

Comments 11: [Field measurements should be used to validate improved and unimproved models, not MOD17.] 

Response 11: Thank you for pointing this out. In this paper, field measurement data only were utilized to validate the grassland yield simulated by the improved CASA model (Figure 4b). Additionally, the MOD17A3 dataset served as a reference for verifying the NPP simulated by both the improved and unimproved CASA models (Figures 4a and 7a). Since the field measurements directly represent the yield of grassland, it was essential to employ the MOD17A3 dataset for NPP validation. The use of these two distinct verification datasets demonstrates that the improved CASA model presented in this study exhibits high accuracy and considerable credibility.

Comments 12: [Why your model simulated a sudden drop in 2022, and MOD17 is not observed the drop? If your model is closer to MOD17, it just means your model is inaccurate.] 

Response 12: Thank you for highlighting this issue. While the accuracy of the model does require enhancement, the overall trend and values of the improved model's NPP curve closely align with those of MOD17A3, showing a significant discrepancy only in 2022. The trend of the CASA model remains consistent before and after improvement, indicating that the differences observed in individual years between our model and MOD17A3 stem from variations in calculation models, data sources and parameters. In April 2022, several areas in the TRSR experienced mild to severe drought, with precipitation declining by over 80% compared to previous years. This led to a decrease in NDVI and a notable drop in NPP. Thus, it is reasonable for our model to reflect a decline in NPP for that year. Moving forward, further efforts should be made to enhance the model's accuracy.

Dear Reviewer:

Thank you for your letter and for the reviewers’ comments concerning our manuscript entitled “Research on Forage-livestock Balance in the Three-River-Source Region Based on Improved CASA Model” (ID: remotesensing-3189749). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and have made correction which we hope meet with approval. The reviewer comments are laid out below in italicized font and specific concerns have been numbered. Our response is given in normal font and changes/additions to the manuscript are given in the red text in the body.

Comments 1: [The paper " Research on Forage-livestock Balance in the Three-River-Source Region Based on Improved CASA Model" submitted by Chenlu Hu, Yichen Tian, Kai Yin, Huiping Huang, Liping Li and Qiang Chen is well structured, the methods are well presented and the results are sustained by the work flow and argumentation. The bibliography is relevant and I think that the paper can be published in present form.

The only issues I have and I think that the authors should modify are:

the scale of the final maps- it seems impossible to use the maps, taking into consideration the large surface of the study area and the complexity of it. The end user of this research will find it difficult to understand the results of the work, so I think that you should increase the size of the most important maps. I know that if we have the information in the Computer we believe that it can easily be accessed by the user, but they often see only the printed version.]

Response 1: Thank you very much for your recognition of this article! I appreciate your suggestion. Therefore, I have increased the size of Figures 6a and 6b on pages 14-15 to enhance visibility of the key points and conclusions from this paper's forage-livestock balance study, making it easier for readers to engage with the content.

Comments 2: [Also, I think that the conclusion should be more detailed, describing the advantages and disadvantages of the model , but also talking about the real result, where are the problems, and how can we solve it.

Overall, I think that this is a good paper that deserves to be published. I see the influence of some experienced researchers who covered all the possible subjects correlated with this problem. Congrats!]

Response 2: Thank you for bringing this to my attention. I concur with your comment. Consequently, I have revised the conclusion to include a discussion of the advantages and disadvantages of the model, as well as the issues that need to be addressed, in lines 679-686 on page 19. Additionally, the research results of this paper are now clearly outlined in the second paragraph of the conclusion, with serial numbers added for clarity. Thank you once again for your valuable advice!

Dear Reviewer:

Thank you for your letter and for the reviewers’ comments concerning our manuscript entitled “Research on Forage-livestock Balance in the Three-River-Source Region Based on Improved CASA Model” (ID: remotesensing-3189749). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and have made correction which we hope meet with approval. The reviewer comments are laid out below in italicized font and specific concerns have been numbered. Our response is given in normal font and changes/additions to the manuscript are given in the red text in the body.

Comments 1: [This manuscript lacks mention of specific research questions explicitly before the data and methodology sections. I recommend in the introduction the objectives of this study should be specifically mentioned to make the study more interesting and meaningful for the audience.]

Response 1: Thank you for pointing this out. I agree with this comment. Therefore, I have included the purpose of this study in lines 78-81 of the introduction on page 2 to clarify the research question and enhance the overall interest of the paper.

Comments 2: [The field survey was conducted during the peak growth period of pasture 213 grasses (July-August) during 2010 - 2022. (lines 213 and 214) need specific details what instruments were used and how the entire field survey was conducted? A visual depiction of the process would enhance the quality of the work. Since this study included data from the year of 2010 I wonder if there were any differences in using field instruments for conducting field survey activities compared to the 2022 field surveys?]

Response 2: 

Thank you for highlighting this issue. I completely agree with your comment. As a result, I have added more details about the field survey in lines 214-218 on page 5, including information on the data source, quadrat settings and collection methods, to provide a clearer visual representation of the fieldwork. I apologize for any lack of clarity in the original article, and I have corrected the content in lines 211-212 on page 5 of the manuscript.

The field data were sourced from the National Forestry and Grassland Administration of China and cover the years 2010-2016 and 2020. Compared to 2010, the field survey in 2022 may employ more advanced instruments, such as an accurate GPS positioning system, which would facilitate more convenient and precise measurements of latitude and longitude. Since the 2020 field survey did not record additional information beyond latitude, longitude, elevation and grassland yield, an analysis of the measurements from 2010 and 2016 revealed a decrease in both vegetation coverage and average grass height in 2016. This indicates that grazing activities have impacted the grassland growth status in the area.

Dear Reviewer:

Thank you for your letter and for the reviewers’ comments concerning our manuscript entitled “Research on Forage-livestock Balance in the Three-River-Source Region Based on Improved CASA Model” (ID: remotesensing-3189749). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and have made correction which we hope meet with approval. The reviewer comments are laid out below in italicized font and specific concerns have been numbered. Our response is given in normal font and changes/additions to the manuscript are given in the red text in the body.

Comments 1: [no more questions. ]

Response 1: Thank you for taking the time to review my article. I am delighted that my previous response has received your recognition, and I will continue to enhance the manuscript. Your insightful comments and suggestions are immensely valuable to me. Thank you once again!

Dear Reviewer:

Thank you for your letter and for the reviewers’ comments concerning our manuscript entitled “Research on Forage-livestock Balance in the Three-River-Source Region Based on Improved CASA Model” (ID: remotesensing-3189749). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. We have studied comments carefully and have made correction which we hope meet with approval. The reviewer comments are laid out below in italicized font and specific concerns have been numbered. Our response is given in normal font and changes/additions to the manuscript are given in the red text in the body.

Comments 1: [I suggest the manuscript should have clear objectives/research questions outlined in the introduction. As of now it is hard to get it just by reading the description. ]

Response 1: Thank you for pointing this out. I agree with this comment. Consequently, I have incorporated the research significance at the end of the first paragraph and the fourth paragraph, respectively, to serve as a concise summary of these sections. Additionally, in the final paragraph of the introduction, I have outlined the specific research objectives and the primary issues addressed in the study. For further details, please refer to lines 51-53 on page 2 and lines 121-134 on page 3.