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Dear Dr. Kim,
I thank you for making the corrections and changes requested by the reviewers. I read and checked your valuable article carefully and am happy to inform you that the article has been accepted for publication in PeerJ.
Sincerely yours,
[# PeerJ Staff Note - this decision was reviewed and approved by Richard Schuster, a PeerJ Section Editor covering this Section #]
The manuscript is generally well written in clear, professional, and unambiguous English, suitable for an international audience. Minor grammatical and syntactical issues noted in the previous version have been effectively corrected in the revised manuscript. The article follows an appropriate structure, with a logical flow from introduction to conclusions.
Relevant literature is sufficiently cited, particularly regarding the limitations of single-gear models and the advantages of multi-gear approaches. The inclusion of additional global examples (e.g., Herron et al., 2018; Hilborn et al., 2020) strengthens the context and applicability of the study. Figures and tables are high quality, well-labeled, and now include improved, more interpretive captions.
The raw data have been provided, with expanded metadata and variable definitions that allow reproducibility. The manuscript is self-contained, presenting results clearly linked to the hypotheses and research objectives.
Suggestion:
None at this time; the revisions satisfactorily addressed prior concerns.
The study represents original and primary research that fits well within the Aims and Scope of PeerJ. The research questions are clearly stated, relevant, and meaningful, addressing a recognized gap in fishery stock assessments under multi-gear conditions.
The investigation is conducted to a high technical standard, with detailed model construction and thorough sensitivity analyses. The modifications to traditional Beverton & Holt models are well justified, and assumptions underlying the modeling approach are now clearly explained in the Methods and Discussion sections.
Methods are described in sufficient detail to allow replication, including the catch sampling procedures, selectivity curve estimation, and weighting methods for fishing mortality across multiple gears.
Suggestion:
None; methodological clarity has notably improved.
The findings are valid, robust, and appropriately linked to the original research questions.
The provision of raw data, sensitivity analyses for key parameters (K and M), and clear discussion of model assumptions enhances the credibility of the results. The authors appropriately refrained from conducting formal statistical significance testing between the two models, which is justified given the nature of model-derived estimates rather than sample-based comparisons.
The conclusions are clearly stated and firmly based on the findings.
The authors have addressed previous gaps by explicitly relating their results to initial hypotheses and providing biological and ecological interpretations of the outcomes (e.g., the influence of gear selectivity on optimal fishing mortality rates).
Suggestion:
Consider adding, in future studies, a more detailed uncertainty analysis that could incorporate parameter distributions rather than only point-based sensitivity analyses.
The authors have substantially improved the manuscript in response to reviewer feedback.
The broader relevance of the multi-gear approach to global fisheries management is now better articulated. Policy recommendations, although still general, have been enhanced by suggesting specific actions such as TAC reductions based on revised F40% estimates.
The manuscript is now clearly positioned as a significant contribution to fishery science, particularly in demonstrating practical modifications of per-recruit models for multi-gear fisheries.
All concerns previously raised have been adequately addressed in the revised version and no issues remain significant enough to warrant reconsideration. The language has been improved, relevant biological and contextual information has been added, and figures and abbreviations are now clearly presented.
The experimental design remains strong. The research question is clearly defined and addresses an important methodological gap in stock assessment. The authors have sufficiently justified and improved the methodological assumptions, model limitations, and data collection procedures raised in the previous review.
The findings are statistically sound and aligned with the research objectives. The authors have addressed all major concerns and now provide a balanced discussion, including model limitations and the implications of gear-specific selectivity on stock sustainability.
The authors have responded carefully and constructively to the comments. The revised manuscript reflects a clear effort to improve both the scientific rigor and communicative clarity of the work. I consider this manuscript ready for publication.
no comment.
no comment.
no comment.
No further comments are provided, as the authors have adequately addressed my previous comments.
Dear Dr. Kim
The reviewers have commented on your manuscript. You can find the attached reports. Based on the comments and suggestions of the expert reviewers, a minor revision is needed for your article
I request you check and correct the manuscript based on the reports (I ask you to pay particular attention to the comments of reviewer 2.).
Sincerely
**PeerJ Staff Note:** Please ensure that all review, editorial, and staff comments are addressed in a response letter and that any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate.
Basic Reporting Evaluation
Clear and Unambiguous, Professional English Used Throughout:
The manuscript is generally well-written in clear and professional English, making it accessible to an international audience.
However, there are some grammatical errors and awkward sentence structures that could be improved for better readability.
Suggestion: A thorough proofreading or language revision (possibly by a native English speaker or professional editing service) is recommended to enhance clarity and fluency.
Literature References, Sufficient Field Background/Context Provided:
The study includes relevant literature on stock assessment models, particularly Beverton and Holt’s yield per recruit (YPR) model and its applications.
The introduction provides a solid background on sailfin sandfish fisheries management in Korea and the need for a multi-gear approach.
However, additional references comparing multi-gear stock assessments in other fisheries worldwide would strengthen the broader applicability of the study.
Suggestion: Expand the literature review to include global case studies on multi-gear stock assessments.
Professional Article Structure, Figures, and Tables:
The manuscript follows a logical structure, with clear section headings and well-organized content.
Figures and tables are relevant and effectively support the results.
However, figure captions should be expanded to provide more interpretation of trends rather than just descriptions of what is shown.
Suggestion: Improve figure descriptions to highlight key findings and implications more explicitly.
Raw Data Shared:
The manuscript states that data is available, and raw data files have been provided.
It would be helpful if more metadata were included to explain the structure and variables in the dataset for easier reproducibility.
Suggestion: Provide a clearer explanation of raw data sources, processing steps, and variable definitions.
Self-contained with Relevant Results to Hypotheses:
The manuscript is self-contained and presents relevant results that align with the stated hypotheses.
The findings logically follow the research questions and are well-integrated into the discussion.
However, the connection between results and hypotheses could be made more explicit in the discussion.
Suggestion: Clearly restate how the findings support or challenge the initial hypotheses in the conclusion section.
Strengths:
The introduction clearly presents the importance of sailfin sandfish stock assessment and its relevance to fisheries management in Korea.
The historical context of stock management policies (e.g., TAC system) is well explained.
The gap in existing research is identified, emphasizing the limitations of single-gear models for stock assessment.
Areas for Improvement:
More justification for using a multi-gear model
While the need for a multi-gear approach is mentioned, a stronger rationale should be provided with more references to similar studies in other fisheries.
Suggestion: Expand on the advantages of multi-gear models over single-gear models with examples from global fisheries management.
Clarify the novelty of the study
The introduction lacks a direct statement on how this study differs from previous assessments of sailfin sandfish stocks.
Suggestion: Clearly define whether the multi-gear model has been applied to other species before and how this study builds on or differs from prior work.
Improve flow and conciseness
Some sentences are overly detailed and could be streamlined for better readability.
Suggestion: Remove redundant explanations about Beverton and Holt models that could be shifted to the Methods section.
Experimental Design Evaluation
Original Primary Research within Aims and Scope of the Journal:
The study presents original primary research on stock assessment of sailfin sandfish using a modified multi-gear YPR and SBPR model, which aligns well with the journal’s focus on fisheries science and resource management.
The methodology and results contribute to improving stock assessment techniques, making it relevant and valuable to fisheries researchers and policymakers.
No concerns regarding scope or originality.
Research Question Well Defined, Relevant & Meaningful:
The study clearly defines its research objective: assessing the impact of multiple fishing gears with different selectivity on stock assessment models.
It addresses a practical fisheries management issue, namely the limitations of single-gear stock assessment models in accurately estimating fishing mortality and optimal fishing intensity.
The research fills an important knowledge gap by modifying the traditional Beverton and Holt model to accommodate multi-gear selectivity.
The study provides a strong justification for its relevance to sustainable fisheries management.
Rigorous Investigation Performed to a High Technical & Ethical Standard:
The methodology is technically rigorous, using well-established stock assessment models and modifying them appropriately for multi-gear applications.
The study employs sensitivity analysis to test the robustness of key parameters (growth coefficient (K) and natural mortality (M)), which enhances the credibility of findings.
However, ethical considerations are not explicitly mentioned in terms of data collection, use of fishery data, or compliance with regulatory frameworks.
Suggestion: A brief statement on ethical approval, data permissions, or compliance with national fisheries regulations would strengthen the manuscript.
Methods Described with Sufficient Detail & Information to Replicate:
The study provides a detailed explanation of model modifications, allowing readers to understand how the multi-gear model was constructed.
Selectivity curves and model equations are clearly described, making the methodology reproducible.
However, the data collection process lacks some details:
How were fishing effort and catch data collected?
Were there independent validations or observer programs?
What are the potential sources of bias in the data?
Suggestion: Expand the data collection section to specify sampling procedures, validation methods, and data quality controls to improve replicability.
Strengths:
The study design is well-structured, with a clear breakdown of stock assessment models and data sources.
The modification of Beverton and Holt’s YPR model into a multi-gear model is well-explained.
The selection curves for different fishing gears (Danish seine vs. gillnet) are well-illustrated and supported by relevant references.
Areas for Improvement:
Provide more details on the data collection process
While the models are well-described, the data sources (e.g., sample size, sampling period, and data validation methods) need more clarification.
Suggestion: Specify how catch composition data was obtained and whether observer programs, logbooks, or electronic monitoring were used.
Clarify assumptions in the modified models
The modifications to the multi-gear YPR and SBPR models are described, but the assumptions behind these modifications should be explicitly stated.
Suggestion: Add a short paragraph explaining the assumptions related to gear selectivity, natural mortality estimates, and fishing effort allocation.
Justify parameter choices with references
Several parameters (e.g., natural mortality (M) and growth coefficient (K)) were used in sensitivity analysis, but their selection lacks justification.
Suggestion: Cite past studies that used similar parameter values or provide reasoning for choosing specific values.
Strengths:
The results are logically structured, beginning with selectivity curves and progressing to mortality rates, yield per recruit (YPR), and spawning biomass per recruit (SBPR).
Comparisons between single-gear and multi-gear models are clearly presented with numerical values and graphical support.
The sensitivity analysis effectively highlights the influence of key parameters on stock assessment outcomes.
Areas for Improvement:
Enhance interpretation of findings
While statistical results are provided, more biological and ecological interpretations are needed.
Suggestion: Discuss why the multi-gear model produced higher optimal fishing intensities (F0.1, F40%) and how this aligns with the real-world fishing dynamics of sailfin sandfish.
Consider statistical significance
The manuscript states that the YPR estimates showed no significant differences between single-gear and multi-gear models. However, no statistical test is mentioned to confirm this.
Suggestion: If statistical tests (e.g., paired t-tests, ANOVA) were performed to compare models, these should be mentioned in the Methods.
Improve figure labeling and descriptions
Figures are relevant but could be better explained in the text to avoid forcing the reader to interpret them independently.
Suggestion: Provide more detailed captions that summarize the key takeaway from each figure (e.g., highlighting trends in fishing intensity across models).
Strengths:
The management implications of using multi-gear models are well-articulated.
The discussion links findings to previous research and highlights risks associated with using single-gear models for fishery assessments.
The need for adaptive fisheries management is emphasized, particularly regarding the risk of overfishing if single-gear models continue to be used.
Areas for Improvement:
Strengthen connection to global fisheries management
The discussion focuses heavily on Korean fisheries but lacks a broader perspective on how multi-gear approaches have been successfully applied elsewhere.
Suggestion: Compare findings to other fisheries that use multi-gear stock assessment models to reinforce the validity of the approach.
Consider uncertainty and limitations
The study does not fully address potential limitations, such as data quality issues, unreported catches, or uncertainty in parameter estimates.
Suggestion: Add a paragraph discussing possible sources of error, uncertainties in mortality estimates, and how model assumptions could impact results.
Policy recommendations could be more concrete
While the study suggests reducing fishing intensity, the specific management actions needed are not clearly outlined.
Suggestion: Recommend specific policy measures such as adjusting TAC quotas, enforcing gear restrictions, or implementing seasonal closures.
Overall Assessment and Recommendations
Strengths:
The study presents a well-structured stock assessment using an innovative multi-gear approach.
The methodology is rigorous, and the models are appropriately applied to sailfin sandfish stock in Korean waters.
The results have clear management implications and emphasize the risks of overfishing under single-gear models.
Areas for Improvement:
The introduction should better justify the need for multi-gear models with additional references.
The methods section requires more details on data collection, parameter selection, and model assumptions.
The results need stronger interpretations and statistical validation of comparisons between models.
The discussion should expand on limitations, uncertainty, and global fisheries management implications.
More concrete policy recommendations should be provided for sustainable fishery management.
Final Recommendation: Minor to Moderate Revisions Required
This manuscript presents a valuable contribution to fisheries science, but addressing the suggested revisions will significantly strengthen its clarity, depth, and impact
The manuscript is well-structured, and the results are relevant for fisheries management. It follows a generally professional tone and logical structure, with well-constructed figures and tables that contribute to the clarity of the findings. Additionally, the availability of raw data ensures transparency in the study. However, several areas need improvement. The manuscript contains long and complex sentences that hinder readability and should be revised for clarity and conciseness. The study lacks biological details on Arctoscopus japonicus, particularly regarding its habitat and whether juveniles or adults are caught, which is crucial for evaluating selectivity and fishing mortality. Some figures are unclear, and abbreviations need better explanations. Furthermore, certain key claims, especially those related to multi-gear selectivity and fisheries management, require additional citations. While the reference list is mostly correct, it needs minor additions to fully support the claims made in the manuscript.
The study falls within the aims and scope of PeerJ and presents an important contribution to fisheries management. The research question is well-defined and addresses a gap in stock assessment methodologies by incorporating multiple fishing gears. The methodology is detailed and provides sufficient information for replication, and the sensitivity analysis strengthens the robustness of the results. However, the assumptions regarding gear selectivity should be better justified, particularly regarding the choice of selectivity functions. The methods do not explicitly address potential biases in data collection across different fishing gears, and the manuscript should briefly explain the potential limitations of the models used and their applicability to other fisheries.
The statistical analysis is rigorous and appropriate for the dataset. The results are well-linked to the original research question, and conclusions are logically drawn from the findings. The manuscript provides a comparative analysis between single-gear and multi-gear models, which is valuable for stock assessment. However, the discussion overemphasizes the advantages of the multi-gear model without fully addressing potential limitations, such as data constraints and model assumptions. Additionally, the impact of selectivity differences on stock sustainability should be more explicitly discussed to increase the importance of the outcomes of the study.
The manuscript should be revised for clarity and conciseness to improve readability, as several sections contain long and complex sentences that hinder comprehension. Expanding on the ecological and management implications of the findings will make the study more comprehensive, particularly in understanding how multi-gear selectivity affects stock sustainability. Because if you ignore these two factors, it becomes difficult to evaluate the results of this study meaningfully. Additionally, figures should be clarified with better axis labels and captions, ensuring that all abbreviations are properly explained, as following them within the text is not easy.
The paper addresses important and practical aspects of the sustainable use of fishery resources, using sailfin sandfish in Korean waters as an example, with a focus on multi-gear fisheries operations. The findings suggest potential underutilization of fishery resources due to the disregard of the characteristics of multi-gear fisheries, which has implications for fisheries management in the study area.
The analyses were based on fishery data and are not subject to evaluation in terms of experimental design.
One important aspect is whether the assumptions affect the results. If the results are robust to the assumptions and data handling, the findings appear more reliable.
The paper provides a thorough investigation into elements of improved management advice, considering both population sustainability and fisheries, by accounting for the multi-gear nature of the target species. The method is a sort of extension from single-gear analyses. However, it would be helpful if the authors could include this extension process by presenting the single-gear formula as well as the extended formula.
One question concerns the impact of selectivity for each gear. I found that selectivity was considered in the SBPR analysis but not in the YPR analysis. The authors should clarify this difference in treatment between the two evaluations.
Another question is whether the assumptions influence the results. For example, the authors used a single set of values for the weighting factors for F (w_i), possibly based on the average proportions over time. However, catch proportions may vary over time due to changes in the age composition of the resources and changes in fishing effort across fisheries. This is one aspect that should be clarified to assess the robustness of the results. It would be helpful if the authors could examine, to some extent, the sensitivity and/or robustness of the results to the assumptions, including the weighting factors.
Regarding the style of mathematical expressions, I suggest that the authors italicize the necessary symbols. Additionally, it would be preferable to avoid the use of sub-subscripts if possible. The authors may also consider inserting a center dot (e.g., between F and wi) to improve readability. Furthermore, the use of "F" in Fmax in L171 should be avoided.
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