Interaction Effect of Carbon Emission and Ecological Risk in the Yangtze River Economic Belt: New Insights into Multi-Simulation Scenarios

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

1. please add a description of the advantages of the PLUS model over other methods in the introduction section

2. The Scenarios 3 and 4 in 2.3.2, explain in detail why the amount of change for some land use types are special values such as 40%, 20%, etc.

3. check whether there is a conflict in the transfer of forest land to the central location of the study area shown in Figure 3

4. in Figure 4, the increase in cropland under the natural development scenario is too much, and the table of the amount of land use type area under different scenarios can be added to enhance the persuasive effect

5. explain why the spatial resolution of the ecological resilience index is lower than luce

6. in 3.4.1 used bivariate global spatial correlation to analyze the relationship between LUCE and ERI, add a detailed description of the parameters

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

To be honest, I find this manuscript difficult to engage with. The language is verbose and lacks clarity, making it challenging to understand.

The research methodology appears to be inadequately designed, leading to a misuse of statistical techniques. There seems to be a fundamental misunderstanding of inferential statistics, resulting in the misuse of statistical models.

The authors opted for spatial regression models to examine the relationship between environmental risk and land use carbon emissions. However, it's evident that these variables are not independent observations; rather, they are derived from the same land use patterns. Consequently, their significant correlation seems more a product of the authors' methodology than a reflection of true causality.

 

Additionally, the land use patterns were simulated using the PLUS model, a common cellular automata model. Regardless of scenario settings, a cellular automata model predicts land use changes based on the adjacency relationships among cells, inevitably introducing spatial autocorrelation in land use patterns. Consequently, if both the Environmental Risk Index (ERI) and Land Use Carbon Emissions (LUCE) were derived from these land use patterns, it's expected that both indicators would exhibit spatial autocorrelation. However, this autocorrelation doesn't necessarily imply the presence of spatial spillover effects. Therefore, the mere presence of a significant non-zero Moran’s I indicator does not justify the selection of spatial regression models. 

Comments on the Quality of English Language

The language is verbose and lacks clarity, making it challenging to understand.

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Minor mistakes:

- capital letter missing at the title of paragraph 3.2.2.

- Fig. 9 is hardly readable 

- Fig. 9 title: "... land se..." to be corrected in "... land use ...."

Author Response

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Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript has been improved, but there are still some issues with the research design. The research aims to investigate the interaction between carbon emissions and ecological risk during the land use process. According to the research framework, both LUCE (Land Use Carbon Emissions) and ERI (Ecological Risk Index) are estimated based on land use patterns. Since neither the dependent variable (ERI) nor the independent variable (LUCE) are independent observations, conducting empirical analysis with a spatial panel model is inappropriate. In other words, the author created the correlation between these two indicators. Therefore, the significance of the coefficients in the spatial panel model does not accurately reflect the interaction between carbon emissions and ecological risk.

Comments on the Quality of English Language

The English expression has been improved. I am not sure about the term "multi-simulation scenarios." It seems more accurate to say "multi-scenario simulations."

Author Response

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Author Response File: Author Response.pdf