PONE-D-20-25422

Quantifying impacts of stony coral tissue loss disease on corals in Southeast Florida through surveys and 3D photogrammetry

PLOS ONE

Dear Dr. Combs,

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.

Reviewer 1 in particular notes that there is a significant literature on photogrammetry techniques on coral reefs, and further attention to this would improve both the introduction and discussion, rather than relying on citations to other taxa. They also require increased clarity in the methods regarding validation of the accuracy of the model, including what site-specific community parameters would impact the 3D model generation. Reviewer 2 also brings up a salient point here, which is that there was no direct comparison to 2D methods, so claims of increased accuracy are not demonstrated. They do recommend that a relatively rapid post-hoc statisitical comparison with 2D screen grabs could be considered, or more cautious language. I would suggest the former to increase the rigour of your study, but either would be sufficient. Reviewer 1 also questions the clarity of statistical analysis, and believes that further investigation into why shape area and error varies with location is either required, or explained in the text.

Both reviewer 1 and I are curious as to why the grouping of disease prevalence is at the county level rather than the location/site scale, particularly since you do not discuss different management, water quality or land use differences between counties (See Fig 3). By working at the location scale, this would allow comparison of more similar replicates, and would also be more accessible to a person not familiar with the geography of Florida. If you feel that county is an important part of the puzzle that makes it a more appropriate unit of replicate than location (more than just indicating a north - south gradient for example), it would be useful to explain this decision. 

Both reviewers identify the recommendation of 'culling' as unjustified, or presented with too high a level of certainty, particularly since the effort, efficacy and description of what other interventions are available are not given (if there is only one colony in an area infected, but it is large, why not remove that if it leads to a better outcome than other interventions?). Without evidence presented here, or citations to small colonies dying more quickly or being disease vectors, this management recommendation goes far beyond the work.  Indeed, in Fig S2 It could be argued that there is some evidence that some larger colonies might lose tissue at a faster rate than some small colonies. In the discussion you also state that "disease lesion area did not correlate with total colony size suggesting that larger colonies do not exhibit a higher proportion of diseased tissue" - this could imply they show the same proportional loss or lower. I strongly suggest you present more data on proportional loss of colony tissue (not just absolute loss) if this is an argument you wish to make. Even so, suggesting culling small colonies as a management measure would still be extreme and would require a stronger argument with references to small colonies as vectors or disease reservoirs. The argument also begs the question - what is a small colony? Nor are what interventions that might be possible shy of culling the entire colony described. 

Finally, there is a significant amount of relevant context and data in the SI. It would be good to see some of the tables and figures into the main text, particularly concerning the disease incidence, colony size and disease spread data.

Please submit your revised manuscript by Nov 30 2020 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: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Fraser Andrew Januchowski-Hartley, Ph.D.

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.  We note that Figure 2 in your submission contain map images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright.

We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission:

2.1.    You may seek permission from the original copyright holder of Figure 2 to publish the content specifically under the CC BY 4.0 license. 

We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:

“I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.”

Please upload the completed Content Permission Form or other proof of granted permissions as an "Other" file with your submission.

In the figure caption of the copyrighted figure, please include the following text: “Reprinted from [ref] under a CC BY license, with permission from [name of publisher], original copyright [original copyright year].”

2.2.    If you are unable to obtain permission from the original copyright holder to publish these figures under the CC BY 4.0 license or if the copyright holder’s requirements are incompatible with the CC BY 4.0 license, please either i) remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only.

The following resources for replacing copyrighted map figures may be helpful:

USGS National Map Viewer (public domain): http://viewer.nationalmap.gov/viewer/

The Gateway to Astronaut Photography of Earth (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/

Maps at the CIA (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.html

NASA Earth Observatory (public domain): http://earthobservatory.nasa.gov/

Landsat: http://landsat.visibleearth.nasa.gov/

USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://eros.usgs.gov/#

Natural Earth (public domain): http://www.naturalearthdata.com/

[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: 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: Reviewer comments:

This study monitors SCTL disease prevalence at four locations in the Florida Reef Tract over three months and fate-tracks colony-level impacts using under water photogrammetry and 3D modelling of Montastrea cavernosa colonies at one location.

While the idea, study design and methodology is good, and I think it is great to see more applications of photogrammetry in coral reef research, I have concerns about the statistical evaluation of some results and especially about the model validation. As the fate-tracking is the main focus and the novelty of this work, a clear and detailed evaluation of the used methodology is important and this section should be improved before resubmission (see comments below).

In the introduction I would recommend that the authors give better credit to prior work on photogrammetry in coral reefs. Reading these papers will also help them to improve their model evaluation and compare the accuracy and precision of their methodology to similar applications.

Additional to the comments below I have attached a PDF with annotations, suggesting smaller changes where I think the text could be improved. Most of these suggestions should be easy to implement. If some time is invested on improving the model evaluation I believe this will be a nice contribution to the growing number of photogrammetry applications on coral reefs.

Introduction:

1) from L88: I think applications on cetacean and elasmobranch research are way out of the scope of this work. Better concentrate on referencing all the exciting research on coral reefs.

There is a lot of work that has been done on individual coral colonies to measure surface area, volume, carbon standing stock, coral growth and erosion rates ... I would recommend to read through them if the authors have not come across them before, also to get some inspiration for the section on accuracy and precision of 3D model building. I know all this literature can be overwhelming, but there is some good stuff in there and it will make your paper stronger. E.g.,

Bythell et al., 2001. Three-dimensional morphometric measurements of reef corals using underwater photogrammetry techniques. Coral Reefs

Cocito, Sgorbini, Peirano, & Valle, 2003. 3-D reconstruction of biological objects using underwater video technique and image processing. JEMBE

Courtney, Fisher, Raimondo, Oliver, & Davis, 2007. Estimating 3-dimensional colony surface area of field corals. JEMBE

Burns, Delparte, Gates, & Takabayashi, 2015. Utilizing underwater three-dimensional modeling to enhance ecological and biological studies of coral reefs.

Figueira et al., 2015. Accuracy and Precision of Habitat Structural Complexity Metrics Derived from Underwater Photogrammetry. Remote Sensing

Gutiérrez-Heredia, D'Helft, & Reynaud, 2015. Simple methods for interactive 3D modeling, measurements, and digital databases of coral skeletons. L&O methods

Lavy et al., 2015. A quick, easy and non-intrusive method for underwater volume and surface area evaluation of benthic organisms by 3D computer modelling. MEE

Ferreira et al. 2017. 3D photogrammetry quantifies growth and external erosion of individual coral colonies and skeletons. Sci Rep

Lange & Perry 2020. A quick, easy and non-invasive method to quantify coral growth rates using photogrammetry and 3D model comparisons. MEE

2) Also, in this section, I don’t think you need to cite aerial and scanner methods to prove your point, and the two studies you cite for coral growth did not use photogrammetry at all. Use Ferreira et al. 2017 and Lange & Perry 2020 if you want to keep this sentence. Alternatively you could explain photogrammetry and SfM first and then give examples of studies on reefs. Also see annotations in the PDF.

3) L. 104: optimized from what basis? You have not developed the photogrammetry technique, but a new application for it. Maybe say: “In this study we used photogrammetry techniques as described in [Young et al. ] in order to develop a new application, i.e to track SCTLD disease progression in M. cavernosa colonies.” or something similar?

Methods:

1) see annotations in PDF to improve clarity of the text.

2) L181: state version of Agisoft Metashape that you used as some versions seem to have issues and it will help for repeatability.

3) L. 215: I do not understand why site-specific “community parameters” (what is this anyways?) or even water quality should affect 3D model generation. This would mean that the method is not accurate and should not be used.

Related to this it does not make sense to compare the area of shapes among locations to evaluate the 3D models. So I am wondering why you did not just photograph the mock colony at the sites where you did the fate-tracking in order to calculate the accuracy of your methodology.

Concerning this there is two parameters you want to check:

A) accuracy, meaning how close to reality is your 3D model. Test this by comparing measured shape areas on your mock corals to known areas and calculate the mean error. (This is potentially how you got your 2.17 cm2?) If you notice that the error is bigger at a more turbid reef site, then you could conclude that the visibility affects the accuracy of model building/measurement. But direct comparison of shape areas among sites does not make sense.

B) precision, meaning how good is the reproducibility of your measurements. For this you should measure the surface of the same shape, or better the same coral colony, several times, including all the hand tracing around colonies etc. Then calculate the error, which will show you if you introduce considerable variability using your workflow.

You should calculate the coefficient of variation (error/average) in order to compare your errors to other studies doing surface area measurements. You cannot compare the error from small shapes (2 cm2) directly to the surface area of the colony.

L 240: I do not understand why these correlations were done and what they would tell us about the accuracy of the method.

Results:

1) I am wondering why did you choose to compare counties instead of locations as shown on the map? The latter would have the advantage that replications are more similar.

2) L 255-260: I don't think the figure supports these statements. I would say something along the line of “in Broward, disease prevalence stayed quite constant at around 10%, while in Palm Beach prevalence was usually very low, but peaked in March 2019 when ... of colonies were affected. Disease prevalence at Martin was very variable due to low numbers of live coral colonies...”

3) L 273: Has it been taken into account that colonies were measured repeatedly? Considering that the areas of your colonies are very different you might either have do more fancy statistics using repeated measures GLM/GAM (maybe using colony ID as fixed factor and site and time as explaining variables? sorry, not an expert myself) or you might have to calculate “loss of area” or “loss % of area” in order to make meaningful comparisons over time.

I know you calculated rate of change in healthy and diseased tissue, which I think might make more sense than comparing actual area. In general it is getting a bit confusing looking at so many parameters. I would suggest to think carefully which parameters are most useful in showing what you are interested in and rather use fewer but explain better what they mean.

E.g., I think the most interesting results and the best order in the section L277-309 would be (add numbers and statistics): “The rate of tissue loss did not differ among sites but was variable over time, with highest loss in the first observation interval. The diseased area however did stay constant over time, indicating that the lesion moves with the infected tissue.” Then add the correlations you think are useful. Not all are I think.

4) L287 and 288: S2 Fig should be S3 Fig?

5) L 312-L334: This whole section does not make sense to me. I do not understand why the areas of shapes should be different depending on location. This definitely does not increase trust in the method! It might in part be a relic of your different sample sizes and tests you do. Why do you run ANOVA then Kruskal Wallis and then 3-way PERMANOVA? I fail to understand what any of these significances mean and it is not explained in the results or discussion sections.

I would suggest to think carefully about what parameters actually tell you something about the accuracy/precision of the analysis (see comments above) and rewrite this section completely after the improved analysis.

Discussion:

This section could be improved by being very clear how the results compare to other studies and what can be said about the implications. See annotations in the PDF

1) L353: It is not clear what you are trying to say here. Also please make clear what you mean with L356-357. Next section can be shortened as suggested in PDF.

2) L363: This paragraph seems to be repeating discussions from the previous paragraph. Maybe you could combine those better without repeating yourself?

I think the order of these two paragraphs could be improved. E.g. “In the FRT, disease prevalence is typically higher (...%) than elsewhere in the TWA (~1-3%) [57]. Sites in Palm Beach in the present study showed relatively low background disease (6%), similar to prevalence across the NFRT after Hurricane Irma in Sept 2017 (6%???) (Walker 2018, 53). Highest values observed in this study were 20-45% at sites in Martin, but did not reach levels of up to 60% as reported in [17], likely due to low abundance of susceptible species after ongoing SCTLD impacts [53,58]”

3) L384: I thought Fig S2 showed that it does NOT correlate? Otherwise your next sentence does not make sense

4) I think the suggestion to cull small colonies is a bit drastic and not supported by your study. If there is other research supporting this approach please cite here.

5) L 384-393 could be condensed down to 1-2 sentences saying management should target larger colonies.

6) From L 403: This whole sections would have to be revised after analysis of accuracy/precision.

7) L406: It is not possible to compare the 2.17 cm2 shape error directly to the much larger colonies. Actually, this error seems very high considering that the shape on your mock coral is not very big?! Does that relate to about 10%? Calculate CV and compare to other studies. Also, if you have an error of about 10% you might want to check if the difference of total area/healthy area between time points would still be significant.

8) L409: you did not test the effect of colony size on model accuracy. Also, it does not make sense that water quality (do you mean turbidity/visibility?) affects the size of colonies. You are probably trying to say that lower visibility could result in lower model quality affecting measurements of surface area? Be precise in your wording.

Conclusions and general:

1) Different kinds of interventions should be mentioned in the introduction or discussion if it is the main discussion point in the conclusion.

2) L435: Why would interventions be unsuccessful in small colonies? They should work the same, just preserve less total area, right? So I understand prioritising big ones, but in sites were prevalence is low why not treat small ones too.

3) I think the discussion and conclusion sections will benefit from a second round of review after the improved model evaluation. Try to be very clear what the novelty of this work is (new application of photogrammetry method to accurately quantify tissue loss/disease progression over time) and what can be concluded from it (improve survey protocols, evaluate success of intervention methods... I don’t think culling of half the colonies is a good outcome here).

4) If you want people to take up this method, make the workflow easier to access. I know it is all in the GitHub repository, which is awesome, but I did not easily find the step-by-step guide and what you actually did to measure the areas. Maybe you could prepare a one-pager which is easy to print, stating the steps of image acquisition, model building and analysis to go into Suppl Methods. Or put a link in the methods which leads straight to the guide instead of the whole repository.

5) Also, it would be great if you could make the models (as .obj?) available in the repository.

Reviewer #2: The manuscript by Combs and colleagues presents the results of prevalence assessments and a time-series study of the progression of stony coral tissue loss disease (SCTLD) in the northern Florida Keys. The manuscript also presents the results of an assessment of the accuracy of a 3D photogrammetry modelling technique to track disease lesion progression, and describes the optimised method for use in future surveys. This manuscript was clear, concise, thorough, well organized, and well written. It provides sufficient detail for reproducibility studies and is timely given the on-going outbreak of this virulent and devastating coral disease. I hope that the method presented here can improve and speed-up survey techniques to improve our knowledge and ability to manage the disease.

I don’t have any significant concerns regarding any aspect of the manuscript. The most substantive comment I have is in reference to the conclusion that the model method presented here is “more accurate… than previously established methods”, when there wasn’t actually a quantitative comparison of this method with those previous methods. Thus, I think the conclusion is overreaching (summarised further below). This can either by addressed by a minor edit/softening of the language or a post-hoc statistical comparison of lesion size estimates made from the 2D video screen grabs. Otherwise, I only have minor comments and commend the authors on a well-done study.

General comments

- One of the major findings of this study is that the 3D model method presented is “more accurate data than previously established methods such as two-dimensional surface area estimation (ln 398-399).” I thought the assessment of the accuracy of the 3D method presented here was excellent and rigorous, but there was not a estimate of the disease lesions or the calibration templates/mock coral made from the same two-dimensional photographs to make a robust and unbiased statistical comparison of the two techniques. While I agree that this 3D model pipeline is achievable, it does still require ~40 min per colony of rendering, plus fairly expensive software and hardware for modelling and storage of large video files compared with the much simpler 2D method, so a quantitative comparison of the two methods would strengthen the argument and add justification for using the 3D model method presented here.

- The inclusion of more data from the disease surveys in the main text could be useful, and would balance the disease ecology with the methodological aspects of the study a bit better. Including which species were (and were not) affected at each site, and how disease prevalence changed over time by taxa within each site would be a nice addition to the main text. Line 365-7 mentions the “low abundance and species richness in Marin County sites compared with PB and Broward Counties”, but what is the density and species richness within each site?

- The manuscript is relatively sparse wrt figures and tables, with the vast majority of the information presented as supplementary. I would suggest including a few of these in the main text, particularly Fig S2 and possibly S4, again to balance out the ecology/methodology aspects of the manuscript.

Specific comments

- Line 193 – it is quite tricky to determine whether the stark white area of the lesion is still alive or newly dead, especially in an image/video. Would it be more appropriate to define the lesion area as the ‘stark white coral tissue or very newly dead white skeletal area’? If not, how was this distinction made? It is very difficult to tell in Figure 1, but the white lesion areas look like there is no live tissue to me.

- Line 282 – consider rounding the estimates of # of lesions per colony to the nearst whole number as that makes the most conceptual sense (or at least to the 10th which is probably a more appropriate significant digit)

- Line 360 – consider stating what the most susceptible species are.

- Line 384 – was the correlation between rates of tissue loss and total colony size positive or negative? Please specify.

- Line 388 – typo – suggest ‘greater preservation’

- Line 389 – is there justification for the statement that smaller colonies are more likely to succumb to SCTLD? It may take less time to succumb due to the rate of tissue loss, but is the likelihood of dying from the disease actually higher? Has much recovery been observed? I would suggest editing to “smaller infected colonies may succumb more quickly to SCTLD”

- Line 406 – perhaps you can expand on what you mean by ‘sufficient replication’? Does this mean replicate videos of each colony to render multiple models per colony?

- Line 413 – suggest ‘most commonly’

- Line 434 – suggest ‘regarding’ rather than ‘relative to’

- I wonder if it is worth commenting on how this model approach may work for other coral growth morphologies. Mcavernosa is a fairly simple mounding shape, but encrusting, foliose or branching corals may be much more difficult to accurately model?

- I have strong reservations about the mitigation technique of culling small colonies that is suggested in line 438 (and 389, see comment above). I understand that they may die more quickly than larger colonies and could act as sources of the disease. But the data presented here do not indicate that they are more susceptible (are there size-frequency distributions of healthy vs/ diseased corals in a population?), and the small colonies are often offspring of the few remaining colonies that have survived multiple selection events already and may be the best hope of the recovery of resilient communities, especially if there is any evidence that colonies can recover from this disease. Thus I much prefer the second option of focusing intervention resources on larger colonies and would urge caution when considering culling of smaller colonies.

- Fig 1. Typo in fig legend – add ‘a’ before ‘colony’

**********

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: 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.

Attachments

Attachment

Submitted filename: PONE-D-20-25422_reviewer.pdf

PONE-D-20-25422R1

Quantifying impacts of stony coral tissue loss disease on corals in Southeast Florida through surveys and 3D photogrammetry

PLOS ONE

Dear Dr. Combs,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit and is very close to appropriate standard for publication. Both reviewers are happy with how you have addressed their critiques and comments, but both do point out some minor errors and comments. In reviewer 1's case in particular, many of these are minor typographically errors or slight clarifications, but due to the process at PLoS One, you would not have the opportunity to correct them at a 'proofing' stage. Figure 5a also does not correspond to the Figure legend, and the panel appears to be a duplicate of Figure 6. Reviewer 2 would also like you to consider some additional disease ecology factors, and please see their attached pdf with some comments.

Please submit your revised manuscript by May 15 2021 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: http://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,

Fraser Andrew Januchowski-Hartley, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

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.

[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

Reviewer #2: (No Response)

**********

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

Reviewer #2: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

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 #1: Yes

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 #1: Yes

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 #1: Reviewer 1 Round 2

The authors did a good job addressing my questions and suggestions in their revised version of the manuscript and improved the photogrammetry method section and discussion section significantly. Well done!

Please find below a couple of very minor suggestions I noted down while reading over the manuscript, otherwise I am happy to recommend publication as is.

Check Figures 5 and 6 and the captions and references in the text. Figure 5 includes the disease lesion area plot (but note different font size) but this is not represented in the figure caption and text references and Figure 6 depicts the same plot.

L173: hovered approximately 1 m above

L176: overlap of filmed surface area

L183: (link does not work)

L249: site SLR North in April 2019

L253: What do you mean with species abundance? Overall colony abundance? or number of species? Also, was this parameter higher or lower at SLR (says varying in L254)

L289: tissue area (get rid of s)

L313: This first sentence seems out of place. Maybe better integrates in method section as the reason to use PERMANOVA. Then start with “Absolute and relative shape error did not vary across the pool and ...”

L316: Absolute shape error

L318: corresponded to a relative shape error of

L322: on measured colony surface area

L332-334: consider to move this sentence behind L337 starting with “Other ... observed over similar spatial scales” (as you note similar distance to Belize/Martinique)

L342: no site (get rid of s)

L343: near Miami in ...(year)

L346: comparatively sparse (or absent)

L360: on a coral colony level over just ... over the course of this study

L361: why “in contrast”?

L374: sufficient area (get rid of s)

L379: progression on a colony-level

381: I would not consider this a complex morphology. Would rephrase to “Healthy and diseased surface area of 24 coral colonies were quantified and compared over time”

385: did not vary across different depth and turbidity conditions (S2 Fig.)

L386: Average absolute shape error

L387: to a relative error of ...

L389: rather than representing solid surfaces.

L404: may be able to determine

L406: the progression of disease

L411: what does non-discriminant mean? Do you mean “Compared to other coral diseases, impacts of SCTLD are not yet well described concerning host-specificity and spatio-temporal distribution”? Is that true? Lots of studies out on SCTLD

L412-416: would suggest to shorten and rephrase, e.g.: “Based on the results from this study, larger colonies should be prioritized for SCTLD mitigation measures.”

L417: remove alternative

L419-420:” ... longer timescales and multiple species are desirable to confirm observed patterns ... “ (3D mentioned in next sentence)

L422: not sure what redundancies and precautions you refer to. I suggest “... are a valuable approach for colony fate-tracking if high resolution imagery can be obtained.“

L425: more accurate than what?

Reviewer #2: The manuscript by Combs et al. reports the results of spatial and temporal field surveys of SCTLD in Florida and, using the survey results to inform site selection, undertook fate-tracking of individual Montastrea cavernosa colonies at the most impacted sites. The fate-tracking applied a structure-from-motion 3D photogrammetry technique to quantify rates of tissue loss and changes to lesion area and lesion number through time. The authors then used those data to improve our understanding of disease dynamics and make management recommendations.

The revised manuscript has addressed all the major concerns I raised in my previous review, including removing mention of culling, removing statements of direct comparisons with 2D methods that were not justified by the data, reanalysing the data at the location level, and including some of the supplementary data in the main text. Overall, I think the manuscript has been clarified and streamlined will be a useful addition to the literature on this important topic. I only have a few outstanding comments that warrant a minor review, most notably about the intervention recommendation, and have added some edits and comments in an annotated PDF, which I hope the authors will find useful.

• References: Some key references on disease ecology and SCTLD are missing, including Muller et al. 2020 Spatial Epidemiology of the Stony-Coral-Tissue-Loss Disease in Florida. Front Mar Sci 7:163; Meiling et al. (2020) and stony coral tissue loss disease (SCTLD) lesion progression slows in association with thermal stress. Frontiers in Marine Science, 7, 1128. More references are added in the annotated PDF file, and I urge the authors to review some of the key disease literature for the Caribbean in the discussion of ecological drivers including temperature, local pressures, etc.

• Intervention recommendation: Line 36, Line 374, Line 415: I think it is worth adding a caveat/qualifier here about what the end goal of the intervention is. If the goal is to minimise immediate loss of coral cover, then yes, perhaps it is best to prioritise the largest colonies. But, that doesn’t take into account other on-going processes. Firstly, one could argue that the smaller colonies represent younger and more locally adapted/stress tolerant genotypes, and applying intervention efforts across all colonies in a small high-value (heat tolerant)/well connected (larval source)/high-flow (i.e. pathogen source) area might be better than selecting only larger individuals in a broader area using the same amount of time/resources. Secondly, the disease appears to follow contagious transmission dynamics (Muller et al 2020), so if infected small colonies are left untreated in an area around larger colonies that are treated, it may remain a pathogen source to re-infect the larger colonies; I understand this argument led to your original suggestion of culling but that also doesn’t factor in other processes. I would urge you to add a qualifier as such and soften the language because the statement “should be prioritised” is quite strong when these other factors aren’t considered.

• Methods: Lines 142-147: The sentences “Statistical tests were run in the R statistical environment” and “non-parametric tests were implemented for all analyses unless otherwise noted”… seemed out of place and premature, because it isn’t clear what tests were run and why? I suggest moving line 146 up to start the section with “to assess variation in disease prevalence among sites and survey times”, and then you can explain the methodological details.

• Figures: It appears that Figures 5a and 6 are the same? Also, Figure 5b could be faceted by site to support the argument that tissue loss didn’t differ among sites.

**********

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: Yes: Ines Lange

Reviewer #2: 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.

Attachments

Attachment

Submitted filename: PONE-D-20-25422_R1_V2.pdf

Quantifying impacts of stony coral tissue loss disease on corals in Southeast Florida through surveys and 3D photogrammetry

PONE-D-20-25422R2

Dear Dr. Combs,

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 for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, 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,

Fraser Andrew Januchowski-Hartley, Ph.D.

Academic Editor

PLOS ONE