How Do Energy Price, Density, and Gini Changes Explain Biodiversity Outcomes? The Empirical Case of the United States
Round 1
Reviewer 1 Report
Comments and Suggestions for Authors1. The article utilizes cross-sectional data from only the year 2010, which may be insufficient for analyzing long-term impacts. It is recommended that the authors consider employing panel data to better capture the dynamic relationships between variables, particularly the influence of changes in income inequality on biodiversity conservation.
2. The authors have used only three explanatory variables, potentially overlooking other factors that may affect biodiversity, such as the level of economic development, population density, and educational level. It is suggested that the authors consider adding more control variables to enhance the explanatory power of the model.
3. The literature review should be upgraded adding the latest development in literature， such as doi.org/10.1016/j.jclepro.2024.141227.
4. There may be endogeneity issues between energy consumption, income inequality, and biodiversity conservation. For instance, areas with higher levels of biodiversity conservation may attract residents with a greater awareness of environmental protection, leading to lower levels of energy consumption and income inequality. It is recommended that the authors use instrumental variable methods or other techniques to address these endogeneity issues.
5. The article identifies a positive correlation between income inequality and biodiversity conservation but does not delve into the underlying mechanisms. It is advised that the authors further analyze the causes of this relationship, for example, whether income inequality leads to greater public concern for environmental protection, thereby promoting biodiversity conservation.
6. There are several grammatical errors and areas where the expression is not sufficiently clear in the article. It is recommended that the authors conduct a thorough proofreading and revision.
Author Response
Kindly please see the attachment!
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsStrengths of the Document
1. Clear and Logical Structure: The document features a well-defined structure that makes it easy to understand the topic and results. The introduction clearly establishes the research problem, followed by a review of relevant literature, description of the data and methods, empirical results, discussion, and conclusions.
2. Relevance of the Topic: The research tackles a highly important and current issue: the relationship between energy consumption, income inequality, and biodiversity in the context of the United States. It emphasizes the need to better understand how these factors interact and impact biodiversity conservation.
3. Robust Empirical Methodology: The study employs a solid empirical methodology based on Ordinary Least Squares (OLS) to analyze data from 39 U.S. states in 2010. This approach considers social, economic, and environmental factors, providing a comprehensive view of the problem.
4. Clearly Presented Results: The findings of the research are presented clearly and concisely in Table 3, facilitating interpretation. The document highlights the contrasting effects of energy density, prices, and changes in the Gini coefficient on biodiversity.
5. Thorough Referencing: The document includes a reference section with a comprehensive list of academic articles and other resources used in the research. The references cover a variety of topics related to biodiversity, energy consumption, environmental economics, and income inequality.
6. Acknowledgment of Limitations: The document adequately addresses the study's limitations, noting its cross-sectional nature, which prevents the analysis of long-term effects. The authors suggest that future research could benefit from the use of panel data, especially concerning income inequality variables.
Specific Suggestions for Improvement
1. Longitudinal Analysis: Given the limitations of a cross-sectional approach, it would be advisable to conduct longitudinal analyses using panel data. This would allow for a more in-depth examination of the long-term effects of energy density, energy prices, and income inequality on biodiversity.
2. Exploration of Causal Mechanisms: The surprising finding that higher inequality may be associated with greater biodiversity conservation warrants further investigation. It is suggested to explore the underlying causal mechanisms behind this relationship, such as the role of conservation policies in high-inequality contexts or the influence of interest groups on environmental protection.
3. Consideration of Other Factors: In addition to those mentioned, it would be beneficial to consider other elements that may influence biodiversity, such as conservation policies, climate change, land use, agricultural practices, and the introduction of invasive species.
4. Sensitivity Analysis: Implementing a sensitivity analysis would help evaluate the robustness of the results against various model specifications and datasets, thus verifying whether the findings hold consistent across different scenarios.
5. More Detailed Policy Implications: Expand the discussion on the policy implications of the findings and provide specific recommendations for policymakers on how they might use this information to promote biodiversity conservation and address challenges related to energy consumption and inequality.
6. Data Visualization: Incorporate more visualizations, such as graphs and maps, to illustrate key findings and enhance understanding of the information. For instance, a map depicting the spatial distribution of biodiversity, energy density, and income inequality in the U.S. could be very illustrative.
7. More Comprehensive Literature Review: While the literature review is adequate, it is recommended to broaden it to include more recent and diverse studies on the interrelationship between energy, inequality, and biodiversity. This would help better contextualize the study's findings.
Author Response
Kindly please see the attachment!
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsSome citations are missing, for example Wei et al. (2024) does not appear in the references.
Author Response
Comment: Some citations are missing, for example Wei et al. (2024) does not appear in the references.
Response: Thank you for the comment. It has been added to the references.
