Assessment of the environmental impacts of conflict-driven Internally Displaced Persons: A sentinel-2 satellite based analysis of land use/cover changes in the Kas locality, Darfur, Sudan

Abdalrahman Ahmed; Brian Rotich; Kornel Czimber

doi:10.1371/journal.pone.0304034

Peer Review History

Original SubmissionJanuary 16, 2024
9 Feb 2024 Decision Letter - Bijeesh Kozhikkodan Veettil, Editor PONE-D-24-01879Assessment of the environmental impacts of conflict-driven Internally Displaced Persons: A sentinel-2 satellite based analysis of vegetation cover changes in the Kas locality, Darfur, SudanPLOS ONE Dear Dr. Ahmed, 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. Please submit your revised manuscript by Mar 25 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. 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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: No Reviewer #2: Partly ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: No 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: 1. The manuscript title suggests an assessment of the environmental impacts of conflict-driven internally displaced --- persons (IDPs). It is important to note that while the study may identify changes in vegetation cover, establishing a direct causal link between these changes and IDPs may be challenging. Other factors may also contribute to vegetation cover changes. 2. The choice of using only Random Forest (RF) classifier used in the research article can influence the accuracy and performance of land cover classification. Different algorithms have varying strengths and weaknesses, and their suitability depends on the specific study area and land cover types. It is important to consider and compare other algorithm(s) and evaluate their performance 3. The novelty of this paper is lacking. It is important to emphasize the distinctions between the current study and previous studies. 4. Include recommendation for future studies. Reviewer #2: In this paper, land use/land cover changes in the Kas locality of Darfur, Sudan were detected during the years 2016 to 2022 using a cross-tabulation approach and S2 images. Then, these changes, solely descriptively, were attributed to some driving factors such as resettlement of Internally Displaced Persons and Climate change. However, this differs from the work stated in the title of the paper, i.e. Assessment of the environmental impacts of conflict driven Internally Displaced Persons: A sentinel-2 satellite based analysis of vegetation cover changes in the Kas locality, Darfur, Sudan. In order to perform the work stated in the paper title, it is required to separate the impacts of conflict driven Internally Displaced Persons on land cover changes from those of other affecting factors, and then analyze them. Therefore, it is suggested to change the title, According to the work that was actually done in this research. A title like “Detecting vegetation cover changes in the Kas locality, Darfur, Sudan using S2 images and investigating their affecting factors” can be more appropriate. There are some suggestions, questions, and minor corrections in the attached file that I respectfully ask the authors to address them. Best regards. ****** 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. 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Revision 1
22 Mar 2024 Author Response RESPONSE TO REVIEWERS Dear reviewers, Thank you very much for your comments and suggestions on our paper titled “Assessment of the environmental impacts of conflict-driven Internally Displaced Persons: A sentinel-2 satellite-based analysis of vegetation cover changes in the Kas locality, Darfur, Sudan”. The comments are very insightful and helpful in improving the quality of our paper and provide important guidance to our research. We have carefully considered and paid special attention to every comment and have responded to each one of them as detailed below. The response to reviewers’ comments is in green color, while the corresponding changes to the text are highlighted in track changes in the revised version of the manuscript. We sincerely hope that the revisions will be satisfactory for your approval. Kind regards Corresponding author Reviewer #1 1. The manuscript title suggests an assessment of the environmental impacts of conflict-driven internally displaced persons (IDPs). It is important to note that while the study may identify changes in vegetation cover, establishing a direct causal link between these changes and IDPs may be challenging. Other factors may also contribute to vegetation cover changes. Thank you for your critical observation. We have expanded the study area to demonstrate and gain a deeper comprehension of the IDP settlement impacts on changes in vegetation cover (Figure 4, Table 6). To do this, we employed the SAGA tool in QGIS version 3.28.2 After applying a majority filter with a 20-radius, we isolated the built-up class using a raster calculator. Lastly, we created a buffer of 10 km from the settlement area; we classify this area as IDPs and climate change affected region (highly affected) and the remaining area as climate change affected region (low affected) (Figure 4) Despite IDPs being the main contributor to the changes in vegetation cover in the study area, there may be other underlying factors that also contribute to vegetation changes. We have acknowledged the contribution of other factors to vegetation cover changes in the discussion section as follows “The vegetation cover loss in the Kas locality of Darfur can be largely attributed to resettlement of IDPs from the displaced populations, in addition to other underlying factors” … “The variability of climatic conditions in the form of increased temperatures and variability of rainfall in the study area is also likely to play a role in the observed LULC changes [1] There have been significant variations in the rainfall patterns and temperatures in the study area over the past three decades with an estimated 0.4°C temperature rise per decade [1,2] Fluctuations in the seasonal precipitation patterns and temperature impacts the natural environment as they have the potential of creating drought-prone conditions [2,3] “ and conclusion section as follows: “Using Sentinel-2 satellite data and GIS, this study sought to understand how the vegetation cover has changed in South Darfur State between 2016 and 2022 largely because of IDP settlement, among other factors, brought about by renewed armed conflicts in the year 2014”. 2. The choice of using only Random Forest (RF) classifier used in the research article can influence the accuracy and performance of land cover classification. Different algorithms have varying strengths and weaknesses, and their suitability depends on the specific study area and land cover types. It is important to consider and compare other algorithm(s) and evaluate their performance. Thank you for your insightful recommendation. In addition to the Random Forest (RF) classifier, we also considered and compared the Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) algorithms. The RF had a higher overall accuracy and kappa hat for both study years compared to the other classifiers (Table 3) hence our decision to adopt the RF classifier for this study. Additionally, the random forest classifier is a powerful machine learning technique since it applies feature significance properties and averages several predictions. Table 3. Overall accuracy (%) and kappa coefficient values of Three different Machine Learning (ML) algorithms used to classify Sentinel 2 satellite imagery. 3. The novelty of this paper is lacking. It is important to emphasize the distinctions between the current study and previous studies. Thank you for this vital comment. We have emphasized the novelty of the study in the last paragraph of the introduction section as follows: “Previous vegetation cover change research in Darfur [4–6] was done before 2016. All those studies were conducted in Central, Western, and Nouth Darfur. Our study is the first after the launch of Sentinel-2 satellite data for public use. This study therefore aims to provide the latest essential post 2014 spatial data on LULC changes in the Kas locality of Darfur, which is lacking owing to the ongoing conflicts. The results will further enhance the understanding of the repercussions of the 2014 conflict-driven IDPs on vegetation cover and overall environmental sustainability in the Kas locality of Darfur, Sudan.” 4. Include recommendation for future studies. We are grateful for your suggestion and have revised the conclusion section to Include recommendation for future studies as follows… “Recommendation for future studies include a detailed social survey and Key informant interviews in the study area, when peace returns, to establish the other factors contributing to LULC changes in the Kas locality”. Reviewer #2 In this paper, land use/land cover changes in the Kas locality of Darfur, Sudan were detected during the years 2016 to 2022 using a cross-tabulation approach and S2 images. Then, these changes, solely descriptively, were attributed to some driving factors such as resettlement of Internally Displaced Persons and Climate change. However, this differs from the work stated in the title of the paper, i.e. Assessment of the environmental impacts of conflict driven Internally Displaced Persons: A sentinel-2 satellite based analysis of vegetation cover changes in the Kas locality, Darfur, Sudan. In order to perform the work stated in the paper title, it is required to separate the impacts of conflict driven Internally Displaced Persons on land cover changes from those of other affecting factors, and then analyze them. Therefore, it is suggested to change the title, according to the work that was actually done in this research. A title like “Detecting vegetation cover changes in the Kas locality, Darfur, Sudan using S2 images and investigating their affecting factors” can be more appropriate. Many thanks for this suggestion. We have carried out further analysis on the images (Figure 4, Table 6) to separate the impacts of conflict driven Internally Displaced Persons on land cover changes from those of other affecting factors as follows “After the LULC was successfully classified, we subsequently used the Majority/minority filter in QGIS's SAGA tool to isolate the built-up class using a 20 radius. A raster buffer was made 10 km from the center of the IDPs settlements (Fig 4, Table 6) for comparative analysis of the vegetation cover in the immediate 10 km and next 5km buffer zones and to establish which of the two zones was highly affected. This analysis was conducted to help us better understand the changes in vegetation cover caused by the IDPs as opposed to other underlying drivers”. Suggestions, questions, and minor corrections in the manuscript. This feature of S2 has been neglected in this study! The use of a time-series of S2 images could lead to a more detailed investigation of the changes in the study area. Thank you for the observation. We have revised this part of the citation. Produce “Produces” changed to “produce” About 322000 people or more than 320000 people. About 321, 929 Changed to about 322,000 people. regions. Full stop added and its average annual rainfall “its” added to the sentence S2 is not a sensor. Its sensor is the multi-spectral instrument (MSI). Table 1 corrected and S2 replaced with multi-spectral instrument (MSI) Which level of processing was used for the level-1 data (level-1A, level-1B, or level-1C)? You could use S2 level-2A data which are presented as bottom of atmosphere reflectance, and do not require atmospheric correction. Thank you for this suggestion. For the previous images, Sentinel 2 level-2A data were not available on 08-12-2016 when the images were acquired. Based on the recommendation, we have modified the image acquisition dates to 12-02-2016 and 20-02-2022 to utilize S2 level-2A data (Table 1). Red: B4, Green: B3, and Blue: B2. However, NIR pseudo color composite is suggested (i.e. Red: B8, Green: B4, and Blue: B3). Thank you for the suggestion. the NIR pseudo color (red: B8, Green: B4, and Blue: B3) have been utilized in addition to Red: B4, Green: B3, and Blue: B2. How did you tune the RF model? More precisely, how was the RF hyper-parameters such as the number and type of trees, and the number of features tuned?. Thank you for the inquiry. We used the default parameters setting of the Dzetsaka plugin in QGIS, which by default has a fixed number of 100 trees set. We have subsequently updated the statement to “A total of three classifiers—random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN)—were used to classify the Sentinel-2 images. The RF classifier is an ensemble method using decision trees as classifiers. For it to function, a large number of decision trees are feature-aggregated (bagging) using the bootstrap of the training sample. The final output is determined by the majority of the trees. [7,8]. The Dzetsaka classification tool in QGIS was utilized in this study to apply RF classification to the Sentinel-2A images. The random forest is a powerful learning technique since it applies feature significance properties and averages several predictions. A fixed number of 100 trees is set by default, and this has shown to be an appropriate size to avoid overfitting. [9–11] .During the construction each tree is split at every internal node using the square root of the number of features (n): max_features = √((n_features)) (1) From the training data (n_features), which consists of the pixel values defined by the ROIs (regions of interest), the features are determined and chosen at random. Thus, a suitable size for the training data set should be ensured. There is no predetermined size for this; it relies on the specific attributes of each data set and the intended class number. [12–14]. The KNN is a nonparametric memory-based supervised machine learning classifier. Following the calculation of the number of neighbors for which k is an integer value [15] KNN is used to solve both classification and regression problems [16]. This parameter (number of neighbors) in the Dzetsaka plugin is selected using a cross-validation technique to optimize the quality of output. [17]. KNN classification was applied to the study area using QGIS's dzetsaka classification tool. SVM, is a linear model for classification and regression problems that is mainly based on kernels, it was developed by Cortes and Vapnik [18]. The Gaussian kernel known as the radial basis function is the one used in Dzetsaka and provides high quality results for classifying tree species. [17]. SVMs have been utilized in this study as it widely used in remote sensing [19]. A mathematical formulation of the SVM can be found in Scikit learn [13,20]” What features were considered as inputs of the RF classifier? Did they only include the S2 bands (B2, B3, b4, AND b8)? It is suggested to use some vegetation indices (such as NDVI or SAVI), built-up indices (such as NDBI), texture analysis components. Many thanks for the suggestion. We have included the NDVI as an input of the RF classifier and we also added the NDVI map in the manuscript (Fig 3). Use the same term for the same concept. Both error matrix and confusion matrix are correct. But be consistent in using terms. Confusion matrix is a more common term. Thank you for the suggestion. The confusion matrix has been adopted as suggested and used consistently. This is not true. It is possible for Kappa to be negative. For a completely random classification, the kappa value is expected to be close to zero, and for worse classification (than a random classification), kappa becomes negative. Table 4? We appreciate your correction; a negative Kappa statistic can indeed occur. We have revised the statement to read, "The Kappa coefficient can be negative and range from 0 (showing no agreement) to 1 (perfect agreement). The kappa value should be around zero for a fully random classification, and negative for a worse classification (than a random classification) [21,22]” How do you explain the time difference between these statistics (2003-2014) and the satellite images used for LULC change detection (2016-2022)? We appreciate this significant observation. The statistics were meant to show the general trend of displaced persons in Darfur since the year 2003. The data were available up to the year 2014 when the ruling government halted the operation of most humanitarian organizations and NGOs in Darfur hence the lack of continuity of the official statistics on IDPs. We have therefore removed the table to avoid confusion. What are these numbers? Are these the references used? Check it out. The numbers represent the SDGs. We have revised them for clarity as follows: “…negatively affect the achievement of SDG6 (clean water and sanitation), SDG13 (climate action), SDG15 (life on land) and SDG16 peace justice and strong institutions)”. Is there any evidence to demonstrate that the detected vegetation cover changes were exclusively due to IDPs settlement? Thank you for your constructive comment. IDP settlement is the leading contributor to vegetation cover changes but not the exclusive cause of the changes (See details on the response to comment 1 above). Additional references [1] Kranz O, Sachs A, Lang S. Assessment of environmental changes induced by internally displaced person (IDP) camps in the Darfur region, Sudan, based on multitemporal MODIS data. Int J Remote Sens 2015;36:190–210. https://doi.org/10.1080/01431161.2014.999386. [2] Spröhnle K, Kranz O, Schoepfer E, Moeller M, Voigt S. Earth observation-based multi-scale impact assessment of internally displaced person (IDP) camps on wood resources in Zalingei, Darfur. Geocarto Int 2016;31:575–95. https://doi.org/10.1080/10106049.2015.1062053. [3] Mohamed MA, Anders J, Schneider C. Monitoring of changes in land use/land cover in Syria from 2010 to 2018 using multitemporal landsat imagery and GIS. Land (Basel) 2020;9. https://doi.org/10.3390/land9070226. [4] Spröhnle K, Kranz O, Schoepfer E, Moeller M, Voigt S. Earth observation-based multi-scale impact assessment of internally displaced person (IDP) camps on wood resources in Zalingei, Darfur. Geocarto Int 2016;31:575–95. https://doi.org/10.1080/10106049.2015.1062053. [5] Kranz O, Zeug G, Tiede D, Clandillon S, Bruckert D, Kemper T, et al. Monitoring Refugee/IDP camps to Support International Relief Action. Geoinformation for Disaster and Risk Management - Examples and Best Practices 2010:51–6. [6] Kranz O, Sachs A, Lang S. Assessment of environmental changes induced by internally displaced person (IDP) camps in the Darfur region, Sudan, based on multitemporal MODIS data. Int J Remote Sens 2015;36:190–210. https://doi.org/10.1080/01431161.2014.999386. [7] Ghosh A, Sharma R, Joshi PK. Random forest classification of urban landscape using Landsat archive and ancillary data: Combining seasonal maps with decision level fusion. Applied Geography 2014;48:31–41. https://doi.org/10.1016/j.apgeog.2014.01.003. [8] Maxwell AE, Warner TA, Fang F. Implementation of machine-learning classification in remote sensing: An applied review. Int J Remote Sens 2018;39:2784–817. https://doi.org/10.1080/01431161.2018.1433343. [9] Breiman L. Random Forests. vol. 45. 2001. [10] Sudhakar V, Venkata Sudhakar C, Reddy GU. Limestone mining area mapping and assessment at the Cement Industrial area using Spectral Index and Attachments Attachment Submitted filename: Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0304034.r002
8 Apr 2024 Decision Letter - Bijeesh Kozhikkodan Veettil, Editor PONE-D-24-01879R1Assessment of the environmental impacts of conflict-driven Internally Displaced Persons: A sentinel-2 satellite based analysis of vegetation cover changes in the Kas locality, Darfur, SudanPLOS ONE Dear Dr. Ahmed, 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. Please submit your revised manuscript by May 23 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. 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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. [Note: HTML markup is below. Please do not edit.] 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 #1: 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 #1: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: 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 #1: 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 #1: (No Response) ****** 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 #1: Change the phrase in the title "A sentinel-2 satellite based analysis of vegetation cover changes" to "A sentinel-2 satellite based analysis of land use/cover changes" The change from "vegetation cover changes" to "land use/cover changes" broadens the scope of the research, allowing for a more comprehensive analysis of the environmental impacts of conflict-driven displacement. ****** 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 #1: No ******** [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. https://doi.org/10.1371/journal.pone.0304034.r003
Revision 2
11 Apr 2024 Author Response RESPONSE TO REVIEWERS Dear reviewer, We greatly appreciate your input on our paper “Assessment of the environmental impacts of conflict-driven Internally Displaced Persons: A sentinel-2 satellite based analysis of vegetation cover changes in the Kas locality, Darfur, Sudan”. After thorough consideration, we have incorporated the suggested change, which has expanded the scope of our study as outlined below. The response to reviewer’ has been addressed in green color, while the corresponding changes to the text are highlighted in track changes in the revised version of the manuscript. Kind regards Corresponding author Reviewer #1 Reviewer #1: Change the phrase in the title "A sentinel-2 satellite based analysis of vegetation cover changes" to "A sentinel-2 satellite based analysis of land use/cover changes" Thank you for the suggestion. We have changed the phrase to “A sentinel-2 satellite based analysis of land use/cover changes”. The new title now reads “Assessment of the environmental impacts of conflict-driven Internally Displaced Persons: A sentinel-2 satellite based analysis of land use/cover changes in the Kas locality, Darfur, Sudan”. Attachments Attachment Submitted filename: Response to Reviewer.docx https://doi.org/10.1371/journal.pone.0304034.r004
15 Apr 2024 Decision Letter - Bijeesh Kozhikkodan Veettil, Editor Assessment of the environmental impacts of conflict-driven Internally Displaced Persons: A sentinel-2 satellite based analysis of land use/cover changes in the Kas locality, Darfur, Sudan PONE-D-24-01879R2 Dear Dr. Ahmed, 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, Bijeesh Kozhikkodan Veettil Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0304034.r005
Formally Accepted
7 May 2024 Acceptance Letter - Bijeesh Kozhikkodan Veettil, Editor PONE-D-24-01879R2 PLOS ONE Dear Dr. Ahmed, 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. Bijeesh Kozhikkodan Veettil Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0304034.r006

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