Modeling the Effects of Climate Change on the Current and Future Potential Distribution of Berberis vulgaris L. with Machine Learning

Round 1

Reviewer 1 Report

In this manuscript, a method is proposed to analyze the geographical distribution and potential ecological niche of Berberis vulgaris L. The results achieved validate and prove the effectiveness of the proposed method. This manuscript is well-organized with associated results clearly presented. Specific comments are as follows:

(1) In Section 1, it should include related work of machine learning in the research direction of the article, and propose the problems and innovations that your article solves compared to existing work.

(2) In Section 2.1, the descriptions of Figure 1 and Table 1 should be expanded in the text to help readers better understand their content.

(3) Please provide the full names for the first occurrence of any English acronyms in the article. Review and correct instances where this has been overlooked.

(4) In Section 2.2, it is not explained why SSP1 4.5 and SSP5 8.5 are used.

(5) In Section 3, why was the Jackknife test chosen? Similar issues exist in other parts of the paper. Briefly introduce the methods and tools used, including the reasons for their selection.

(6) More recent works about machine learning should be included in this manuscript, like “A novel machine learning method for multiaxial fatigue life prediction: Improved adaptive neuro-fuzzy inference system. International Journal of Fatigue, 2024, 178: 108007.”

(7) If possible, add comparison with other machine learning methods or increase comparative analysis from other perspectives.

       (8) There are some spelling and formatting errors. Please check and correct them carefully. For example, at the end of paragraph 2 in Section 1, a period is missing.

There are some spelling and formatting errors. Please check and correct them carefully. For example, at the end of paragraph 2 in Section 1, a period is missing.

Author Response

Responses to the reviewer’s comments are given in table.

Author Response File: Author Response.pdf

Reviewer 2 Report

The authors have undertaken an interesting study on the impact of climate change on Berberis Vulgaris distribution, detailing their modeling process with commendable clarity and reproducibility. The meticulous description of the software and methods used is a notable aspect of this work.

However, the manuscript presents inconsistent results derived from two different versions of the SPSS software. The lack of discussion around this inconsistency is a significant oversight, as it bears directly on the relevance of the results of the study. It is imperative for the authors to critically assess and select the version of SPSS that yields the most reliable results, providing a robust scientific justification for this choice. Subsequently, a more in-depth discussion of the findings, using the selected SPSS version, should be undertaken, particularly focusing on the broader implications of these results.

Additionally, various sections of the discussion are rather vague and insufficiently supported by relevant literature. This lack of depth and citation weakens the manuscript's contribution to its field. To enhance the manuscript's impact and scholarly value, a more thorough and referenced discussion is essential.

In its current form, the study, while promising, falls short of making a robust contribution to the field of sustainability and applied machine learning. Strengthening these key areas would significantly enhance its value and relevance.

The manuscript would greatly benefit from thorough proofreading. It is essential to ensure consistency in tense usage and to refine the sentence structure throughout the document for enhanced clarity and readability.

Author Response

Responses to the reviewer’s comments are given in table.

Author Response File: Author Response.pdf

Reviewer 3 Report

Please see the attachment. 

Comments for author File: Comments.pdf

Author Response

Responses to the reviewer’s comments are given in table.

Author Response File: Author Response.pdf

Reviewer 4 Report

This study was conducted to estimate the current and future potential distribution areas of Berberis vulgaris in Turkey for the periods 2041-2060 and 2081-2100 according to the SSP2 45 and SSP5 8.5 scenarios based on the IPSL-CM6A-LR climate change model. This paper looks like interesting research, but it is difficult to assess its scientific value.

1) Why did the authors choose the plant Berberis vulgaris? Why did they choose Turkey? Why were the periods 2041-2060 and 2081-2100 chosen, which leaves the reader with many questions? This seems to be a question of research for the sake of research by the authors.

2) The predictions described in this paper predict results that cannot be tested for validity. Therefore, what is the author's motivation for choosing machine learning methods?

3) Overall, the research idea is also not very clear and the inputs and outputs of this prediction model are hard to find from the author's description.

This study was conducted to estimate the current and future potential distribution areas of Berberis vulgaris in Turkey for the periods 2041-2060 and 2081-2100 according to the SSP2 45 and SSP5 8.5 scenarios based on the IPSL-CM6A-LR climate change model. This paper looks like interesting research, but it is difficult to assess its scientific value.

1) Why did the authors choose the plant Berberis vulgaris? Why did they choose Turkey? Why were the periods 2041-2060 and 2081-2100 chosen, which leaves the reader with many questions? This seems to be a question of research for the sake of research by the authors.

2) The predictions described in this paper predict results that cannot be tested for validity. Therefore, what is the author's motivation for choosing machine learning methods?

3) Overall, the research idea is also not very clear and the inputs and outputs of this prediction model are hard to find from the author's description.

Author Response

Responses to the reviewer’s comments are given in table.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

I thank the authors for their diligence in addressing the clarifications regarding SSP2 and SSP5. The inclusion of the distinct attributes of SSP2 4.5 and SSP5 8.5 in the manuscript is indeed a positive advancement. However, I believe that a more detailed exposition of the significance and rationale behind selecting these two particular scenarios would greatly enhance the manuscript's comprehensiveness and provide the readers with a more profound understanding of their relevance to the study.

While the manuscript has shown improvement, it still appears to be in the nascent stages of refinement. I would like to propose a few amendments that could substantially elevate the quality of the manuscript. It is paramount that the authors substantiate their assertions with appropriate citations. Statements that are presently unsubstantiated, such as those between lines 73 and 75 and between lines 101 and 105, should either be fortified with pertinent literature or reconsidered.

Additionally, the organization of content warrants attention. The segment between lines 385 and 441, primarily a review of preceding studies, would be more aptly positioned in the introduction section. This restructuring would lend a more logical flow to the manuscript, establishing a robust groundwork in the introduction and reserving the discussion section for a nuanced exploration of this study's findings.

The discussion section should be an arena for a critical examination of the study's outcomes. I urge the authors to delve deeper into the implications of their findings, acknowledge the limitations of their study transparently, and offer thoughtful suggestions for future research directions. It would also be beneficial to elucidate how the study's advancements could potentially influence and propel further research in the field.

By implementing these suggestions, I believe the manuscript will not only gain academic rigor but also offer a more compelling and insightful contribution to the intertwined domains of sustainability and machine learning.

Author Response

Corrections and additions have been made to the article based on your suggestions and feedback. The improvements are highlighted within the text.

Author Response File: Author Response.pdf

Reviewer 3 Report

Thank you

Author Response

Dear reviewer,

Thank you very much for your valuable suggestions and corrections.

Sincerely,

Reviewer 4 Report

I have no more comments.

Author Response

Dear reviewer,

Thank you very much for your valuable suggestions and corrections.

Sincerely,