Coupling Coordination and Spatiotemporal Dynamic Evolution between Agricultural Carbon Emissions and Agricultural Modernization in China 2010–2020
Round 1
Reviewer 1 Report
The present manuscript entitled “Coupling Coordination and Spatiotemporal Dynamic Evolution between Agricultural Carbon Emissions and Agricultural Modernization in China” by Xia et al. deals with agricultural carbon emissions and agricultural modernization in China from 2010 to 2020 through joint employment of spatial autocorrelation and coupling coordination degree modeling. After a careful review, I found this work very interesting and suitable for publication in the “Agriculture” journal. Also, the special issue theme is wisely selected by the authors. Considering the importance of coupling the coordination degree between agricultural carbon emissions and agricultural modernization, the study provides a timely report for different regions of China. However, I have observed that the article needs moderate improvements along with some grammatical and syntax error corrections. I suggest accepting this paper pending a suitable minor revision. My specific comments are:
1. Indicate the study period (years) in the title.
2. Abstract: Add one sentence about the concluding remark and novelty of the article at the end of the abstract.
3. Avoid using keywords that already appeared in the title.
4. Several abbreviations are not defined at their first use: GDP, USD, UN, and many others throughout the manuscript.
5. The hypothesis proposed in the article could better sound if a graphical representation of the coupling coordination degree between agricultural carbon emissions and agricultural modernization within the introduction section. Also, indicate several factors that affect the whole process.
6. Linking the hypothesis to sustainable development goals is highly encouraged as it will take the reader’s attention to a more modern approach.
7. Avoid using impersonal terms such as us, we, our, etc.
8. Line 121: Wind Database1: Citation can be shifted to the main reference list.
9. All equations should be placed separately in the text rather than within the paragraph.
10. Table 1: Correct the digits to the same decimal points.
11. Figure 4: x axial has 0 to -0.3 value which has no relevance to the graph. Correct it accordingly.
12. Texts in most of the figures are not visible at first sight. Authors should revise and provide high-quality images.
13. Figure 7 and similar: Very poor quality and arrangement.
14. The conclusion should indicate the relevance of the study toward SDG implementation in China in the selected sector.
Author Response
Thank you again for your helpful comments and suggestions. We have revised the paper according to the specific comments below in the main text. We have also completed another round of English language editing for grammatical issues. Attached pdf is itemized response to the comments and suggestions.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Abstract: It needs to be revised properly, included numerical values in it for interest of readings and novelty.
Introduction: It needs presentation of rationale of research and its significance with clear objectives.
Methodology: Permission or copy right letters for data taken from other sources.
Results: it needs revision of English and pictures some not so clear. Low resultion
Discussion: It should include clear rationale and justification of research paper, revise it as major.
Conclusion: Include take home message in clear form.
References: Cross check in text and reference section and also format in unisonic way as per policy of Journal.
Author Response
Thank you for your helpful comments and suggestions. We have revised the paper according to the specific comments below in the main text. We have also completed another round of English language editing for grammatical issues. Attached pdf is itemized response to the comments and suggestions.
Author Response File: Author Response.pdf
Reviewer 3 Report
The climate change-related economic problem analysed in the manuscript is scientifically sound. The research question of the paper is well-defined. The data selection and the methodology applied are adequate. The statistical and econometric analysis performed correctly. The structure of the paper meets the requirements. My only suggestion is that the limitation should be highlighted a bit more.
Author Response
Thank you for your helpful comments and suggestions. We have revised the paper according to the specific comments. We have also completed another round of English language editing for grammatical issues. Attached pdf is itemized response to the comments and suggestions.
Author Response File: Author Response.pdf
Reviewer 4 Report
This manuscript jointly uses spatial autocorrelation and coupling coodination modeling methods to assess the coupling coodination and spatial temporal dynamic evolution between agriculyural carbon emissions and agricultural modenization in China from 2010 to 2020. My comments are mainly on the content that is related to the applications and the interpretations of the global and local Moran’s I indices. Although these two indices are used and interpreted basically correctly, some issues still need to be clarified and addressed. I recommend the authors to refer the references Anselin (1995; 1996) attached at the end of the comments to ammend the following issues and further improve the interpretations of the related results.
1. In Equations (1) and (2), the spatial weights Wij should be interpreted and how to define them among the provinces needs to be clarified, which is important to the interpretations of the related results especially for local Moran’s I. Moreover, a “bar” over the x’s in the numerator in Equation (1) is missed.
2. In the last paragraph of Section 2.5, the definition of Moran scatterplot should be briefly described. The interpretation about “H-H” and “L-L” is somewhat inexact. The points in the first and third quadrants all show H-H and L-L schemes, respectively. It is no need for them to show “clusters”.
3. In the first paragraph of Section 3.3.3, the term “confidence level” should be "significance level" in terms of statistics. Moreover, what “confidence coefficient” in Table 5 refers to? I suggest report the p-values of the test and clarify what kind of test (e.g., the normal distribution approximation test or the random permutation test) is used here.
4. In the last paragraph on Page 13, the conclusion in the second sentence indeed comes from the regression lines with positive slopes in Figure 8, because the slope of the regression line in a Moran scatterplot is just the value of the global Moran I. This point should be clarified.
5. In the last paragraph on Page 14, what does the “Local indicators of spatial association (LISA) diagrams” mean? It would be helpful to give an explanation on the relationship between the Moran scatterplots in Figure 8 and the heat maps in Figure 9. Moreover, to well support the claims that “The spatial distribution is not significant in most provinces … …but no "H-L" or "L-H" ones”, the significance level and the test used should be pointed out.
[1] Anselin L, 1995, Local indicators of spatial association—LISA. Geographical Analysis, 27(2): 93-115.
[2] Anselin L, 1996, The Moran scatterplot as an ESDA tool to assess local instability in spatial association. In Ficher MM, Scholten HJ, Unwin D (eds), Spatial Analytical Perspectives on GIS, Talor and Francis, London, pp. 111-125.
Author Response
Thank you for these comments and suggestions. We have revised the paper according to the specific comments in the main text. All issues have been addressed in respective places. Attached we provide itemized response your comments and suggestions. Thank you very much.
Author Response File: Author Response.pdf
