A new growing degree-day phenology model for wheat stem sawfly (Hymenoptera: Cephidae) in Colorado wheat fields

Henrique V. Vieira; Benjamin Z. Bradford; Adam Osterholzer; Erika S. Peirce; Darren Cockrell; Frank Peairs; Kenneth Frost; Russell Groves; Punya Nachappa

doi:10.1371/journal.pone.0320497

Peer Review History

Original SubmissionSeptember 13, 2024
13 Sep 2024 Author Response https://doi.org/10.1371/journal.pone.0320497.r001
23 Oct 2024 Decision Letter - Babasaheb B. Fand, Editor PONE-D-24-40436A new degree-day phenology model for wheat stem sawfly (Hymenoptera: Cephidae) in Colorado wheat fieldsPLOS ONE Dear Dr. Nachappa, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. ============================== I have now completed the review of MS PONE-D-24-40436. Based on the opinions of two reviewers and my own, the paper can be considered for publication pending the suggested revision. The authors are required to do the revision of their MS in line with the reviewer comments. The MS is fairly good with a relevance to entomological science, especially the pest management point of view. However, before considering the paper for publication, authris need to answer following queries 1. What was the basis of selection of lower and upper threshold temperatures? Have you directly used the values from literature? How the values were corrected for field application? Laboratory estimates of LTT and UTT should not directly be used for predicting field phenology of pests. First they needs to be corrected using temperature data and coefficient of variation technique of GDD accumulations across the years using a range of threshold combinations. For more detail, please see Beasley and Adams, 1996 (Pink bollworm phenology model) and Fand et al (2021), Scientific Reports (Degree day model for pink bollworm) 2. How the model was validated for field prediction of WSS phenology at different locations? What was the accuracy of model for reproducibility of the results? 3. Language and flow of text needs to be carefully checked. ============================== Please submit your revised manuscript by Dec 07 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols . We look forward to receiving your revised manuscript. Kind regards, Babasaheb B. Fand, PhD Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. Please note that PLOS ONE has specific guidelines on code sharing for submissions in which author-generated code underpins the findings in the manuscript. In these cases, we expect all author-generated code to be made available without restrictions upon publication of the work. Please review our guidelines at https://journals.plos.org/plosone/s/materials-and-software-sharing#loc-sharing-code and ensure that your code is shared in a way that follows best practice and facilitates reproducibility and reuse. 3. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. Additional Editor Comments: I have now completed the review of MS PONE-D-24-40436. Based on the opinions of two reviewers and my own, the paper can be considered for publication pending the suggested revision. The authors are required to do the revision of their MS in line with the reviewer comments. The MS is fairly good with a relevance to entomological science, especially the pest management point of view. However, before considering the paper for publication, authris need to answer following queries 1. What was the basis of selection of lower and upper threshold temperatures? Have you directly used the values from literature? How the values were corrected for field application? Laboratory estimates of LTT and UTT should not directly be used for predicting field phenology of pests. First they needs to be corrected using temperature data and coefficient of variation technique of GDD accumulations across the years using a range of threshold combinations. For more detail, please see Beasley and Adams, 1996 (Pink bollworm phenology model) and Fand et al (2021), Scientific Reports (Degree day model for pink bollworm) 2. How the model was validated for field prediction of WSS phenology at different locations? What was the accuracy of model for reproducibility of the results? 3. Language and flow of text needs to be carefully checked. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: No ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: The research tackles an important agricultural issue the wheat stem sawfly, a major pest in wheat production, particularly in Colorado. Developing a phenology model to predict the lifecycle of this pest has clear practical implications for improving pest management strategies. The focus on creating a degree-day model is relevant, as it is a widely used approach in entomological studies to predict insect development stages. The significance of this model for broader geographic regions or different crop systems is not discussed. While the focus on Colorado is appreciated, the paper would be stronger if the authors addressed whether this model has any potential applicability in other wheat-growing regions affected by the wheat stem sawfly. The use of degree-day accumulation to model the phenology of the wheat stem sawfly is scientifically sound. The methodology appears to follow a logical sequence of steps to build the model based on temperature data and insect development thresholds. Data collection from wheat fields in Colorado is appropriate and ensures that the model is grounded in field observations rather than purely theoretical assumptions. It would be beneficial for the authors to explain in more detail how the degree-day model was validated. Were independent datasets used to test the model’s accuracy, or was it only fitted to the original data? Without clear validation or calibration steps, the reliability of the model may be called into question. The authors should also consider addressing potential variability in microclimates within wheat fields. How was spatial variability in temperature accounted for, and does this affect the applicability of the model across diverse field conditions? The discussion lacks a critical assessment of the model's limitations. All models come with inherent assumptions and limitations, yet these are not adequately discussed. The potential integration of this model into Integrated Pest Management (IPM) programs is briefly mentioned, but the paper does not elaborate on how farmers or agricultural professionals might implement the model in practice. What tools or platforms are available for farmers to access and use this model, and what training or resources would they need? The authors should consider comparing their model with existing tools or models for predicting the development of other agricultural pests. This would provide a better sense of the relative strengths or weaknesses of their approach. The ecological and economic impacts of using this model are not fully explored. The authors could provide insights into how this model might reduce pesticide use or crop damage, and what economic benefits could be realized by wheat growers. Include more detailed data on the model validation process and how its predictions align with real-world observations. Provide more comprehensive quantitative results, particularly regarding the accuracy and reliability of the model under varying conditions. Address the limitations of the model and how it might be affected by climate variability or extreme conditions. Expand the discussion on practical applications, such as how the model could be integrated into IPM strategies or decision-support tools for farmers. Enhance the graphical presentation of results, including comparison plots between model predictions and observed phenological events. Reviewer #2: The idea of the research is concerned with an important topic in the field of Modeling of the Wheat stem sawfly (WSS), Cephus cinctus Norton (Hymenoptera: Cephidae), to a phenology model that predicts adult WSS emergence and population peak based on growing DD (GDD). A better understanding of WSS emergence, population size, and related environmental factors is critical to building efficient and effective integrated pest management (IPM) strategies for this pest. Where wheat fields were sampled for adult WSS from mid-April to the end of June between 2011 and 2023 in several field sites in two locations in Colorado. ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy . Reviewer #1: No Reviewer #2: Yes: Nabil Abo Kaf ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step. Attachments Attachment Submitted filename: Vieira et al. PLOSONE_Final - updated.docx Attachment Submitted filename: Research evaluation 11.docx https://doi.org/10.1371/journal.pone.0320497.r002
Revision 1
6 Jan 2025 Author Response Editor Comments 1. What was the basis of selection of lower and upper threshold temperatures? Have you directly used the values from literature? How the values were corrected for field application? Laboratory estimates of LTT and UTT should not directly be used for predicting field phenology of pests. First they needs to be corrected using temperature data and coefficient of variation technique of GDD accumulations across the years using a range of threshold combinations. For more detail, please see Beasley and Adams, 1996 (Pink bollworm phenology model) and Fand et al (2021), Scientific Reports (Degree day model for pink bollworm) We used values of 10°C and 30°C for the LTT and UTT, respectively, because these are the most common thresholds used for phenology models of insects, are supported by previous research on WSS (see references in lines 117-120), and GDD accumulations using these thresholds are commonly available from weather data services. Using the methods described in the editor’s references could result in the selection of thresholds that are not available from weather data services (such as the 13.4°C/35.5°C thresholds selected in for the pink bollworm model) so would have to be computed by the interested party from a daily weather record, which would reduce the usefulness of the model to the grower community. In addition, because this is a single generation phenology model that occurs early in the season, and the fit of the model is quite strong as described in the manuscript, we believe our selection of LTT and UTT are justified. 2. How the model was validated for field prediction of WSS phenology at different locations? What was the accuracy of model for reproducibility of the results? Our model is region-specific having been derived from WSS data from specific locations and environmental factors pertaining to eastern Colorado winter wheat fields. This is the first effort towards improving management for WSS in eastern Colorado. We have not validated the model at other locations because we do not have phenological events data for any additional sites across different years. The applicability of the model in other wheat-growing regions affected by sawfly will require model validation in each region, along with an evaluation of GDD accumulation rates that consider these regional differences. Additionally, genetic variability among WSS populations may influence developmental thresholds and temperature responses, posing a challenge to applying the model across different regions, especially since the biological characteristics of WSS were originally studied using populations from the northern Great Plains. We have discussed this in lines 333-342. 3. Language and flow of text needs to be carefully checked. Thank you for your feedback. We have checked and improved the language and flow of the manuscript. Review Comments to the Author Reviewer #1: The research tackles an important agricultural issue the wheat stem sawfly, a major pest in wheat production, particularly in Colorado. Developing a phenology model to predict the lifecycle of this pest has clear practical implications for improving pest management strategies. The focus on creating a degree-day model is relevant, as it is a widely used approach in entomological studies to predict insect development stages. Thank you for your supportive comments. As mentioned in the paper, wheat stem sawfly has been a hard pest to manage, and we believe that the applicability of this model can improve monitoring techniques for this pest. The significance of this model for broader geographic regions or different crop systems is not discussed. While the focus on Colorado is appreciated, the paper would be stronger if the authors addressed whether this model has any potential applicability in other wheat-growing regions affected by the wheat stem sawfly. Thank you for that suggestion. We have discussed the application of our model to other regions in lines 333-342. The use of degree-day accumulation to model the phenology of the wheat stem sawfly is scientifically sound. The methodology appears to follow a logical sequence of steps to build the model based on temperature data and insect development thresholds. Data collection from wheat fields in Colorado is appropriate and ensures that the model is grounded in field observations rather than purely theoretical assumptions. Thank you for your positive input. We were very intentional when thinking about the methodology. It would be beneficial for the authors to explain in more detail how the degree-day model was validated. Were independent datasets used to test the model’s accuracy, or was it only fitted to the original data? Without clear validation or calibration steps, the reliability of the model may be called into question. The authors should also consider addressing potential variability in microclimates within wheat fields. How was spatial variability in temperature accounted for, and does this affect the applicability of the model across diverse field conditions? Include more detailed data on the model validation process and how its predictions align with real-world observations. Provide more comprehensive quantitative results, particularly regarding the accuracy and reliability of the model under varying conditions. We have addressed this above. Our model is region-specific having been derived from WSS data from specific locations and environmental factors pertaining to eastern Colorado winter wheat fields. We have not validated the model at other locations because we do not have phenological events data for any additional sites across different years. The applicability of the model in other wheat-growing regions affected by sawfly will require model validation in each region, along with an evaluation of GDD accumulation rates that consider these regional differences. Additionally, genetic variability among WSS populations may influence developmental thresholds and temperature responses, posing a challenge to applying the model across different regions, especially since the biological characteristics of WSS were originally studied using populations from the northern Great Plains. We have discussed this in lines 333-342. The discussion lacks a critical assessment of the model's limitations. All models come with inherent assumptions and limitations, yet these are not adequately discussed. Thank you for your feedback on this matter. This is addressed by incorporating to previous provided feedback. Lines 333-342. The potential integration of this model into Integrated Pest Management (IPM) programs is briefly mentioned, but the paper does not elaborate on how farmers or agricultural professionals might implement the model in practice. What tools or platforms are available for farmers to access and use this model, and what training or resources would they need? We have disseminated information about the model to Colorado wheat growers through the Colorado Wheat website (https://coloradowheat.org/) and newsletters. Growers and agricultural professionals can easily track the accumulated GDD using any online phenology and DD model calculator such as the Colorado Climate Center (CoAgMet)- https://coagmet.colostate.edu/ or the IPM Weather Data, Degree-Days, and Plant Disease Risk Models at Oregon State University Integrated Plant Protection Center's uspest.org/wea. We made changes mentioning that in lines 327-332. The authors should consider comparing their model with existing tools or models for predicting the development of other agricultural pests. This would provide a better sense of the relative strengths or weaknesses of their approach. The ecological and economic impacts of using this model are not fully explored. The authors could provide insights into how this model might reduce pesticide use or crop damage, and what economic benefits could be realized by wheat growers. We have not evaluated the environmental and economic impact of the model because it was only released last year. We are planning to survey growers at the Wheat field days in the upcoming years to understand if using the model has reduced pesticide use or crop damage, and any other economic benefits. We added information about this in lines 301-307. Address the limitations of the model and how it might be affected by climate variability or extreme conditions. Thank you for pointing that out. Indeed, climate variability or extreme conditions can affect the model but given the large data set (13 years), we were able to account for some of that unpredictable variation in outlier years (e.g. 2012). In 2012, unusually warm and dry winter and spring conditions led to much earlier WSS emergence, causing the population peak to occur up to 20 days sooner than usual. However, extreme climate can affect the larvae during diapause which can have an impact on the emergence of adults and thereby the model. Hence, atypical years, such as those with abnormally cold winters or extreme heat in late summer, can affect the accurate estimation of population sizes for the following field season. We have discussed this in lines 318-324. Expand the discussion on practical applications, such as how the model could be integrated into IPM strategies or decision-support tools for farmers. Thanks for your feedback. This is indeed crucial for the goals of the project. I expanded on that in lines 301-307. Enhance the graphical presentation of results, including comparison plots between model predictions and observed phenological events. Figures 2, 3, and 4 illustrate comparisons between observed phenological events and model predictions. We have included a new figure (Figure 5) that illustrates the cumulative proportion of WSS captures from 2019 to 2024 in relation to cumulative Growing Degree Days. Any studies which estimated the base temperature for this particular pest. Whatever cited in the study is again a general observation. Yes, there are two studies that estimated the lower threshold for wheat stem sawfly. We have included the citations for that in lines 117-120. When the minimum temperature (Mean) for its emergence is 4.5 (Table 2). How did you study to assume or take 10⁰C as the base temperature for calculating the GDD? According to Salt (1947) and Perez-Mendoza and Weaver (2006), 10⁰C is the minimum temperature for development to occur in WSS. We have included the citation 120-123. The mean temperature of 4.5 indicates the average minimum temperature we can have according to the 13 years of data presented. In Table 2, we show the min temperature during emergence over the 13-year period can significantly influence WSS captures. In another words, years with unusually cold minimum temperatures during WSS emergence period, can indicate reduced WSS captures. GLM/GAM approach expand. We have described the model in lines 127-134. Reviewer #2: The idea of the research is concerned with an important topic in the field of Modeling of the Wheat stem sawfly (WSS), Cephus cinctus Norton (Hymenoptera: Cephidae), to a phenology model that predicts adult WSS emergence and population peak based on growing DD (GDD). A better understanding of WSS emergence, population size, and related environmental factors is critical to building efficient and effective integrated pest management (IPM) strategies for this pest. Where wheat fields were sampled for adult WSS from mid-April to the end of June between 2011 and 2023 in several field sites in two locations in Colorado. The inter-annual variability in emergence timing based on calendar date was substantially reduced when using a GDD model with a base temperature of 10°C, an upper threshold of 30°C, and a biofix of Jan 1. The model predicted initial WSS emergence at 148 DD, population peak at 224 DD, and decline at 354 DD. There also modeled the effects of environmental factors on mean WSS populations at each field site, finding that higher WSS populations are associated with longer emergence periods, less precipitation before emergence, milder temperatures during emergence, and milder maximum temperatures before and during emergence. By analyzing multiple years of comprehensive phenology data, they provide robust models to guide adult WSS forecasting and monitoring for the first time. Further, this data will aid in decision-making related to timely and effective management strategies to suppress populations of WSS. The conclusion is good. It shows the importance of the study in terms of the suitable by analyzing multiple years of comprehensive phenology data, there provided robust models to guide adult WSS forecasting and monitoring for the first time. Further, this data will aid in decision-making related to timely and effective management strategies to suppress populations of WSS, and it is complete and clear. Keywords are not provided in the research. We have included the key words. The introduction is comprehensive and it deals with the subject of the study with a high professionalism and presents all the ideas related to the topic presented in the appropriate literature, where it referred to impact of weather on WSS phenology and ecology. Achhami et al. found that GDD correlated with pre-diapause larval mortality in barley cultivars. Beres et al. demonstrated that GDD was more effective than calendar days in estimating WSS population peaks in Montana wheat cultivars.The researchers pointed out the main problem modeling the seasonal phenology of WSS from field monitoring data. In addition, this approach has potential management implications, such as timing insecticide treatments to coincide with predictions of high pest pressure. Phenology models based on GDD have been successfully established and are very effective in supporting management strategies for insect pests. To date, several studies have examined the impact of weather on WSS phenology and ecology. Achhami et al. found that GDD correlated with pre-diapause larval mortality in barley cultivars. Beres et al. demonstrated that GDD was more effective than calendar days in estimating WSS population peaks in Montana wheat cultivars. In addition, Perez-Mendoza and Weaver demonstrated that temperature and humidity affect WSS larval development and adult emergence, using data from three Montana WSS populations to identify optimal conditions for shorter developmental times and extreme conditions where development ceases. These complementary studies provide valuable resources that can potentially help mitigate WSS damage. Here, we use a long-term data set based on multiple years of adult WSS monitoring in Colorado to predict the seasonal phenology of WSS and determine the effects of temperature and precipitation on WSS populations in Colorado winter wheat. In this study, Accumulated GDD have assisted farmers in various ways such as predicting insect emergence, and population peak, anticipating damage, determining optimal sampling times, and guiding appropriate management actions. This approach has potential management implications, such as timing insecticide treatments to coincide with predictions of high pest pressure. Phenology models based on GDD have been successfully established and are very effective in supporting management strategies for insect pests. Materials and methods Sample collection was good and clear, terms included Adult WSS monitoring was performed in winter wheat fields located at New Raymer and Orchard, CO. These sites were chosen because WSS was first reported here in 2011. These sites were monitored every year from 2011 to 2023 except for 2015, when data was not collected due to adverse weather conditions, which prevented sampling. The data includes 6-9 sites per year; the variation in the number of fields sampled per year is attributed to factors such as crop rotation and/or low WSS population density. In Colorado, due to the lack of water, growers follow the wheat-fallow rotation, which consists of leaving a portion of the land without sowing for one crop season; this helps with retaining moisture for the next field season. Therefore, the fields sampled had little variation in their geographical location through the 13 years. The sampling occurred on private land. At Attachments Attachment Submitted filename: Response to the Reviewers_Final.docx https://doi.org/10.1371/journal.pone.0320497.r003
20 Feb 2025 Decision Letter - Babasaheb B. Fand, Editor A new growing degree-day phenology model for wheat stem sawfly (Hymenoptera: Cephidae) in Colorado wheat fields PONE-D-24-40436R1 Dear Dr. Nachappa, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Babasaheb B. Fand, PhD Academic Editor PLOS ONE Additional Editor Comments (optional): Dear Authors I have now the evaluation reports of two reviewers for your manuscript. Based on their feedback, I recommend your manuscript for publication in plos one Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #2: All comments have been addressed ******** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #2: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #2: Yes ****** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #2: Yes ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #2: Yes ****** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #2: The authors have adhered to all notes and recorded them in the text. They have answered all the questions I asked in their explanation in the attached letter, and have included all the required points in the text in their designated places. ****** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy . Reviewer #2: Yes: Nabil Abo Kaf ******** https://doi.org/10.1371/journal.pone.0320497.r004
Formally Accepted
Acceptance Letter - Babasaheb B. Fand, Editor PONE-D-24-40436R1 PLOS ONE Dear Dr. Nachappa, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Babasaheb B. Fand Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0320497.r005

Open letter on the publication of peer review reports

PLOS recognizes the benefits of transparency in the peer review process. Therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. Reviewers remain anonymous, unless they choose to reveal their names.

We encourage other journals to join us in this initiative. We hope that our action inspires the community, including researchers, research funders, and research institutions, to recognize the benefits of published peer review reports for all parts of the research system.

Learn more at ASAPbio .