Conservation and Development: Spatial Identification of Relative Poverty Areas Affected by Protected Areas in China and Its Spatiotemporal Evolutionary Characteristics

Round 1

Reviewer 1 Report

This study chooses an interesting perspective to study the relationship between poverty, environment, and economy. But it still needs to be improved until it is published.

(1) The full text needs to be as concise as possible, especially the Results, the Data and the Methods need to be further detailed. The logical relationship between the research results is not close, and the interpretation of research methods and data is not rigorous. There are many Chinese expressions, which affect readability.

(2) The research results do not reflect the important findings in the research, but only the description of the phenomenon. The author is requested to further elaborate in combination with the research objectives (line 90~96); In the keywords, attention is paid to nature conservation rather than the conservation. The author should pay attention to his writing attitude.

(3) In Table 2 and figure 3, please further explain which two variables are the spatial agglomeration Moran index and Lisa diagram. In addition, the color distribution of the grade shown in Figure 3 seems to be inconsistent with most similar studies, that is, red generally indicates the H-H area. The expressiveness of Figure 4 is insufficient. It is suggested to use Natural breakpoint classification instead of equal interval algorithm (line292)

(4) Simplify the content after Section 3.4, which is not readable and closely related to the previous text. It is suggested that the author should reduce the repetition of the same sentences (line313~325; line383~415, line512~539), and use summary sentences to explain the phenomena and research results as much as possible.

(5) Data processing and methods. The author should explain how the data with different resolutions (line 128， line133 ) and projections(that the author didn't explain ) are processed uniformly. In Table 1, explain why the weights of WN, we and WS are equal to 1 respectively? Similarly, why does the weight of sub dimensions add up to more than 1? This seems contrary to common sense; Explain the source of formula (3) and the calculation method of each parameter? In the data part, the distribution of PA and poor counties in 2014 is added; in the method part, the description of the Moran index and t-test should be added.

 

(6) The charts are normative and have poor performance. Indicate the source of administrative boundary data, add major cities (in Figure 8), add the location of typical counties described in the text, adjust the scale to display in whole numbers, and complete the South China Sea boundary.

Author Response

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Reviewer 2 Report

This study used comprehensive index, spatial analysis, and cluster analysis to investigate the evolutionary characteristics and driving factors of poverty from 2014 to 2019. On the whole, the framework is clear and has certain practical significance. A few tips:

1)      2.3. Mathods should be Methods

2)      How to determine the weight of economy, society, and natural environments? Is it reasonable?

3)      How to group the categories of PI? What method was used?

4)      Are there collinearity among different influence factors in tables 3 and 4? Has it been tested?

5)      In my opinion, it is appropriate to separate the discussion from the conclusion. There are too few discussions. It is suggested to put forward relevant opinions or suggestions on the improvement of poverty areas in combination with the latest relevant references.

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

 

Review of an article : “Conservation and Development: Spatial Identification of Relative Poverty Areas Affected by Protected Areas in China and its Spatiotemporal Evolutionary Characteristics”

 

The presented article describes the important topic of poverty in ecologically valuable areas. The research was done based on quantitative indicators. The topic is not new. By entering the keywords protected areas; relative poverty; into google scholar one can find several good articles. However, this approach also includes the aspect of spatial distribution and new quantitative indicators. The indicators used by the authors in the analysis were obtained from existing statistics and Gis studies. The article is clearly edited, written in an understandable language . It is enriched with numerous maps and charts that illustrate the obtained results. It is well written. The conclusions are supported by the results and recommendations are presented.

The article also contains minor shortcomings that should be corrected.

Comments on the text.

1. In determining a comprehensive poverty index, it is necessary to determine the weights of the three poverty indication subsystems,  environment, social, and economic. ( presented in table 1)

Please elaborate on how the weights are determined. I believe that the existing provision is not sufficient.

“To reflect the contribution of each index to the evaluation dimension and objective situation of each indicator, the weights of the index are calculated using the analytic hierarchy process and entropy method; the combination weights are subsequently determined based on the minimum relative information entropy”

The factor weights in the two indication subsystems each score 100%. The weights of the N indicator have 200%. Please add information about the Geographical Conditions section.

 

2. Section 2. 3 contains a typo

2.3 Mathods

3. 13 indicators were used in the analysis. They illustrate three groups of factors. Some of these indicators are defined by intermediate indicators and are defined using new approaches. E.g. I like the definition of the levels of urbanization and human activities by the indicator nighttime data. Please write a few sentences how these indicators were obtained, by what means whether from raster or vector maps by what GIS tools.

4. Another comment concerns the sentence

“„ According to the PI for 2014, the counties are grouped into four equal categories, namely, relatively poor county (0.647 < PI ≤ 0.855), relatively substandard county (0.612 < PI ≤ 0.647), standard county (0.581 < PI ≤ 0.612), and prosperous county (0.425 ≤ PI ≤ 0.582).”

In subsequent years (2019), we often get different ranges (we have different PI max and PI min). What did this look like in your study and did you take this into account. It is worth adding a sentence on this topic.

5.         Please look at and correct the sentence

“Using Equation (6), we calculated the PI contribution ratio C for each dimension to identify the driving factors of the evolution of the PI. Thus, the accuracy of poverty targeting as well as the targeting of poverty reduction measures can be enhanced. Figure 5 8.”

(there is no pattern 6 only 3 and figure 5)

6. Note to the sentence "The clustering results and F-test (Table 3) illustrate that the unweighted regression has nonsignificant clustering results in certain dimensions.

It is worth noting that we do not obtain clustering with the indicator "Percentage of added value of secondary and tertiary Industries"

 

8.         You wrote

“According to the evaluation of the PI degree, relatively poor counties are mainly distributed in the northwest provinces along the Hu Line and points to large differences from nonpoor counties in terms of per capita GDP, income level, and social conditions”

Please add one sentence about the Hu Line. I am not from China so please explain.

Author Response

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Author Response File: Author Response.docx

Reviewer 4 Report

the paper is an interesting contribution to the debate on the dialectic between conservation and development. The authors propose an analytical, geo-statistical model representing the aggregate poverty index in the counties of China affected by the presence of Protected Areas, and the dynamics of this index between 2014 and 2019.

 

The contribution is well-structured and the results are supported by the application of a robust methodology.

 

The section on method shows some critical issues.

lines 168-170 - in particular, it is not explained how the weighting factor system is determined; the authors mention the AHP and , but do not provide its known scheme;

 

lines 206-206 - please clarify: index i ando ei is not defined;

 

lines 209: the PI index is calculated using equation 1, whereas it is said here that it is calculated using equaions (1)-(3);

 

Line 335: Equation (6)? Three are listed

 

 

 

Author Response

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Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Please update the base map to the latest version.（Fig.1-5，fig7）

 

Author Response

Thank you for your suggestion on promoting the correctness of the maps. This time, we have overlaped the standard base map from Ministry of Natural Resources of the People’s Repubulic of China. And we have added a note about the source of the base map in the Data section. Please see the attachment. 

Author Response File: Author Response.pdf