Remark: Evaluation of the Habitat and Potential of Taxus chinensis var. mairei in the Jiangnan Hilly Region
, Jiufen Liu 1,2,3,*, Xiaohuang Liu 2,3,*, Xiaofeng Zhao 2,3, Xueqi Xia 1 and Chao Wang 3Round 1
Reviewer 1 Report
Comments and Suggestions for Authorss
Forests-3101510
Remark: Evaluation of the Habitat and Potential of Taxus chinensis var. mairei in the Jiangnan Hilly Region
Add a brief explanation of the MaxEnt model's methodology and why it was chosen for this study. Highlight its advantages in handling presence-only data and its robustness in ecological niche modeling.
Provide more detail on how the correlation analysis was conducted. Mention the statistical methods used to identify and eliminate significantly correlated factors.
Explain the criteria for selecting the final 16 main variables. Discuss any domain knowledge or previous studies that supported the choice of these variables.
Include a brief discussion on the significance of the AUC value obtained (0.881) and how it compares to similar studies. Explain what this high AUC value implies about the model's performance.
In Table 2, consider providing a brief explanation or interpretation of why certain variables (e.g., precipitation in the warmest quarter, altitude) have high contribution rates. This will help in understanding their ecological importance.
Define what constitutes high, medium, and low habitat suitability more clearly. Mention any thresholds or criteria used to classify these suitability levels.
Discuss the ecological or conservation implications of finding 84.67% of the study area suitable for T. chinensis. What does this mean for the species' management and conservation strategies?
Briefly explain the different SSP (Shared Socioeconomic Pathways) scenarios used in the study (SSP1-2.6, SSP2-4.5, SSP5-8.53). Describe their relevance to future climate predictions.
Provide more details on how the models for future habitat suitability were validated. Mention any statistical tests or metrics used to ensure the reliability of these predictions.
Discuss the potential impact of climate change on the distribution of T. chinensis. Highlight any trends or patterns observed across the different SSP scenarios.
Explain the significance of the center-of-mass migration under different climate scenarios. Discuss how these movements could affect the species' habitat and survival in the long term.
Suggest future research directions to address these limitations and build on the current findings.
I recommend this manuscript for acceptance with minor revisions as outlined above.
Comments on the Quality of English Language
Author Response
Comments 1: Add a brief explanation of the MaxEnt model's methodology and why it was chosen for this study. Highlight its advantages in handling presence-only data and its robustness in ecological niche modeling.
Response 1: We agree with this comment. Therefore, we've added related content in the Introduction section.
“[ Among these, MaxEnt is widely used. MaxEnt is a machine-learning approach that estimates a target probability distribution by calculating the probability distribution of maximum entropy. Compared to other methods, MaxEnt has the advantages of using presence-only occurrence data, the ability to use both continuous and categorical variables, effective control of model fit through certain parameter settings, and simplicity of operation and repeated runs to test model robustness[10].]”
Comments 2: Provide more detail on how the correlation analysis was conducted. Mention the statistical methods used to identify and eliminate significantly correlated factors.
Response 2: Thank you for pointing this out. We have added relevant explanations
“ To avoid overfitting, the environmental variables were examined by Spearman correlation analysis using the SPSS 26 software package, according to the principle of correlation coefficients of environmental variables not exceeding 0.80[33]. If the correlation coefficient |r| between two environmental factors was greater than 0.80 , the factors that contributed less to the Maxent model predictions and had little ecological significance were preferentially excluded. “
Comments 3: Explain the criteria for selecting the final 16 main variables. Discuss any domain knowledge or previous studies that supported the choice of these variables.
Response 3: Regarding the factor selection, we selected these 16 factors with reference to the magnitude of factor contribution and ecological significance of the Maxent model outputs.
Comments 4: Include a brief discussion on the significance of the AUC value obtained (0.881) and how it compares to similar studies. Explain what this high AUC value implies about the model's performance.
Response 4: As suggested by the reviewer, we have added the related content.
“This has an AUC value of 0.881, which is significantly higher than that of random prediction (AUC = 0.5). The AUC value results illustrated that the predictions of the model were acceptable. “
Comments 5: In Table 2, consider providing a brief explanation or interpretation of why certain variables (e.g., precipitation in the warmest quarter, altitude) have high contribution rates. This will help in understanding their ecological importance.
Comments 5: Thank you very much for your valuable advice. To this end, we have added a relevant explanation in the Discussion 4.1 section
“Discussion 4.1 section“
Comments 6: Define what constitutes high, medium, and low habitat suitability more clearly. Mention any thresholds or criteria used to classify these suitability levels.
Response 6: We agree with this comment and explain it in the section 2.6.
“Based on the concept of ecological similarity, the predicted results were reclassified into four classes: ≤0.1 for non-suitable habitat; 0.1–0.3 for low habitat suitability; 0.3–0.5 for medium habitat suitability; and ≥0.5 for high habitat suitability[38].“
Comments 7: Discuss the ecological or conservation implications of finding 84.67% of the study area suitable for T. chinensis. What does this mean for the species' management and conservation strategies?
Response 7: We think this is an excellent suggestion. Some tree species that must be relocated can be introduced to suitable habitats according to the predicted results of the MaxEnt model. The results of this study can help to guide the scope of future practical research to further explore and discover the distribution points of T. chinensis.
Comments 8: Briefly explain the different SSP (Shared Socioeconomic Pathways) scenarios used in the study (SSP1-2.6, SSP2-4.5, SSP5-8.53). Describe their relevance to future climate predictions.
Response 8: Thank you for pointing this out. We mentioned in the introduction these three shared socioeconomic pathways.
“SSP1-2.6 represents a sustainable development pathway with low greenhouse gas (GHG) emissions and a temperature increase controlled below 2°C by 2100; SSP2-4.5 represents a moderate development pathway with medium GHG emissions and a temperature increase controlled below 3°C by 2100; and SSP5-8.5 represents the conventional development pathway with high GHG emissions and a temperature increase controlled below 5°C by 2100[25].“
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Comments 9: Provide more details on how the models for future habitat suitability were validated. Mention any statistical tests or metrics used to ensure the reliability of these predictions.
Response 9: Thank you for pointing this out. We constructed the best-performing model by screening bioclimatic variables and optimizing model parameters, which was then applied to the prediction of T. chinensis’s suitable habitat within the study area.
Comments 10: Discuss the potential impact of climate change on the distribution of T. chinensis. Highlight any trends or patterns observed across the different SSP scenarios.
Response 10: Thanks to your comments. We have modified sections 3.3 and 4.2 regarding Future Changes in Suitable Habitat for T. chinensis
Comments 11: Explain the significance of the center-of-mass migration under different climate scenarios. Discuss how these movements could affect the species' habitat and survival in the long term.
Response 11: We agree with this comment and have added the related content it in the section 4.2.
“ Therefore, in order to better protect this rare tree species in the face of increasing climate warming in the future, consideration should be given to establishing artificial conservation bases at high altitudes and using the existing suitable habitat as a key conservation area.“
Comments 12: Suggest future research directions to address these limitations and build on the current findings.
Response 12: Inspired by your suggestion, we have included a discussion of this in the conclusion section
“ Finally, although this study compared and screened 16 climate, topography, and soil factors for simulation, some more important environmental factors were still neglected; these include the intensity of human activities, biological invasion, and other factors. Follow-up studies can add these factors to further improve the accuracy and credibility of the predictions of the MaxEnt model.“
Reviewer 2 Report
Comments and Suggestions for AuthorsAbstract
-More from the edited section
Introduction
Adding data on the amount of this type of tree remaining from the past and how much remains at present clearly shows the deterioration of the forest.
Update references to be current and relevant to the work and create credibility by citing from many regions; unrelated work, such as animal research, if not related, should not be cited because research on trees is studied all over the world.
Materials and Methods
Show the variable selection table in the model import. How many variables are used out of how many in the method?
In most methods, there is no reference to where it came from. Add references to the methods.
Results
Show the omission rate value and explain it.
The description of suitable areas should include a table of the distribution of areas at each level within the study area. In this city, what are the suitability levels and percentages? This will help to make it clearer.
In Section 3.3, it has been changed to a table showing where each SSP is located in order to make planning more clear. However, in this report, it only shows the percentage of the area. If there is a change in where and how to do it, it can cause confusion. If it is clearly explained, planning can be easier.
Discussion
The discussion would be much better if further comparisons were made with similar woods from other similar countries.
As for future prediction and planning, if the writing of the study results is revised as suggested, the areas that need to be managed will be written more clearly.
Conclusions
-Additional summary from the revised section
Author Response
Comments 1: Abstract:More from the edited section
Response 1: We agree with this comment. Therefore, we've rewritten the summary to add a lot of content.
Comments 2: Introduction: Adding data on the amount of this type of tree remaining from the past and how much remains at present clearly shows the deterioration of the forest.
Response 2: Thank you for pointing this out. Therefore, we have added past data for T. chinensis in the Introduction section to emphasize this point.
“[ According to the survey, it is estimated that there were 1.35 × 104 plants in about 9× 106 km2 in 16 counties of five prefectures in the Hengduan Mountain area of western Yunnan, but tens of thousands of T. chinensis have been peeled off and their leaves and branches have been chopped off in recent years[4]. ]”
Comments 3: Introduction: Update references to be current and relevant to the work and create credibility by citing from many regions; unrelated work, such as animal research, if not related, should not be cited because research on trees is studied all over the world.
Response 3: We think this is an excellent suggestion. We have updated the associated species.
“[ It has been shown to perform better than other SDMs due to its ability to maintain high prediction accuracy with small samples[10], and it has thus been widely used in research considering the prediction of suitable habitats and conservation for species including Qilian cypress[11], Codonopsis pilosula[12], Cunninghamia lanceolata[13], Thamnocalamus spathiflorus[14], and Hibiscus mutabilis[15].]”
Comments 4: Materials and Methods: 1.Show the variable selection table in the model import. How many variables are used out of how many in the method? 2.In most methods, there is no reference to where it came from. Add references to the methods.
Response 4: As suggested by the reviewer, we have added the variable selection table 2 and the more references.
“[Table 2.]”
Comments 5: Results: The description of suitable areas should include a table of the distribution of areas at each level within the study area. In this city, what are the suitability levels and percentages? This will help to make it clearer.
Response 5: We have re-written this part according to the Reviewer's suggestion and added the variable 5.
“[Table 5.] and Section 3.2”
Comments 6: Results: In Section 3.3, it has been changed to a table showing where each SSP is located in order to make planning more clear. However, in this report, it only shows the percentage of the area. If there is a change in where and how to do it, it can cause confusion. If it is clearly explained, planning can be easier.
Response 6: We agree with this comment and explain it in the article
Comments 7: Discussion: 1.The discussion would be much better if further comparisons were made with similar woods from other similar countries. 2.As for future prediction and planning, if the writing of the study results is revised as suggested, the areas that need to be managed will be written more clearly.
Response 7: We agree. We have re-written section 4.2
“Section 4.2”
