PONE-D-24-33277Habitat suitability mapping and landscape connectivity analysis to predict African swine fever spread in wild boar population: a focus on Northern ItalyPLOS ONE

Dear Dr. Faustini,

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.

Dear Authors, the topic of the manuscript is interesting, and you are working with a valuable dataset. However, as highlighted by the reviewers, all sections require improvements. While ensemble modeling can be a powerful tool, it may also lead to misinterpretations if not applied properly. Simply adding more statistics does not necessarily result in better outcomes. Morevoer, since the main objective of your manuscript focuses on connectivity and the role of corridors, these aspects should be discussed in greater detail. I encourage you to carefully address the reviewers' constructive comments.

Please submit your revised manuscript by Nov 01 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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We look forward to receiving your revised manuscript.

Kind regards,

Francesco Bisi, Ph.D.

Academic Editor

PLOS ONE

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2. Thank you for stating in your Funding Statement: 

The research project was made possible by the financial support provided to G.F. by the Società Italiana di Patologia ed Allevamento dei Suini (SIPAS, https://www.sipas.org/chi-siamo/) and by the Erasmus + for traineeship mobility program (https://erasmus-plus.ec.europa.eu/opportunities/opportunities-for-individuals/students/traineeships-abroad-for-students). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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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: Partly

Reviewer #2: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

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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

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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: No

Reviewer #2: Yes

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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: I appreciate the effort of the authors to pull together this information, however, evaluating all possible models in the Biomod2 package does not seem like an ideal study design. Even more confusing is the reason for choosing GBM as more preferred. The authors have a suitable dataset to use a few models for their purposes. With their knowledge and data available, a model or even a few could be chosen but certainly 11 models are not needed to be evaluated. Then we have to delve into the evaluation criteria for why the other 8 models are not suitable which just detracts from the focus of your study design..predicting ASF across the landscape.

In my comments below, I tried to assist the authors on how to address some of these issue so their objectives and methods are more clear and support their findings with some specific comments by line:

Title: Habitat suitability mapping and landscape connectivity analysis to predict African swine fever spread in wild boar population: a focus on northern Italy. I believe populations should be plural or place an “a” before “wild boar” if authors are suggesting this is one single wild population throughout their study site where records are documented?

Introduction

Lines 44 and 51: Defining African swine fever as ASF and African swine fever virus as ASFV seems confusing and unnecessary. The authors then go into ASFV genotype I and ASFV genotype II but reference ASF to discuss the disease in general terms. It is difficult for the reader to know which is meant or which is most appropriate each time either are used. I would suggest do not define ASFV and refer to these as genotype I and genotype II each time it is needed. Then use ASF when discussing the disease in general. Furthermore, there is no mention of these in the remainder of the manuscript aside from ASF.

Lines Line 116: “different wild boar presence data types” is very confusing as written. I would suggest “Presence/absence data for wild boar differs considerably, although often in relation to a common/similar set of environmental variables describing topography, climate, human disturbance and land cover [29].” The authors then need to cite more than one manuscript if these types do differ in the literature.

Line 122: ENET needs to be spelled out prior to using an acronym because most won’t be familiar with this term.

Line 128: “..dispose of..” I am not sure what this means? This entire sentence is very confusing and might be better split into 2 separate sentences.

Materials and methods

Line 177: Supplement Table S1. This information is often overlooked and I appreciate this table. This is the most complete and detailed variable table I have ever reviewed, thank you for this great summary table!

Lines 170-188: A few points of clarity would be helpful in this section.

1. Density – are these within a 100 x 100 m raster that lines up with all of your rasters? If not, how do you get percentage assigned to each raster cell for bare, herbaceous, and tree cover?

2. Bilinear sampling of 30x30 m raster to derive 100x100m rasters? If so, this should be presented in your “percentage of forest” in your S1 Table.

3. By “overall mean” do you mean “annual mean” for each year from 2014-2023 or a single static 10 year mean from all years: 2014-2023?

a. A mean for a 10 year window, if that is what was done, is of no value so please be clear here. Each year of wild boar data should be matched to variables when available. Specifically, NDVI could have massive fluctuations from year to year so a 10 year average does not seem acceptable in any way?

4. What are the “seasons” based on? Some citations for seasons in northern Italy would be advisable.

Lines 195-197: What variables were removed due to collinearity and multicollinearity? The authors state in line 213 that “Only non-collinear variables were incorporated” but these should be listed here in the methods if they were not included. Then delete Line 213? I see now these are in Table 1 (better to reference in Methods) but this table can be deleted. Simply include a sentence of which are not included because they don’t meet assumptions of collinearity/multicollinearity (i.e., opposite of Lines 328-332) in the methods not results.

Lines 227-232: In your introduction, the authors discuss that SDMs can be implemented based on data available and aim of the study. However, here the authors appear to go on a habitat suitability modeling exploration with everything in Biomod2 (11 methods) which is inappropriate and unnecessary post hoc analysis that goes against the authors own introduction. Why not select the best model that fits your data and use it instead of evaluating which is best based on some criteria that we really are not clear on? More on this later.

Results

Line 341: Here the authors refer to “annual” not “overall” leading to confusion on just how these were calculated?

Line 347: I am a bit confused here. In the Introduction, the authors were recommending an “ensemble modelling approach” but here they are saying just use one, GBM? So this entire effort of evaluating all of these models was not necessary?

Line 348: See my comments above for Lines 227-232 and Line 347. The authors claim GBM was preferred due to “easier parameterization” and “more realistic performance metrics?” I am not sure how you define this or justify it being a criteria for selecting the model chosen?

Line 347: What is a “privileged area?”

Figure 1-4: These figures appear blurry and may not be up to the quality required by the journal.

Figure 3: It seems to me that the suitability of habitat lines up with where the presence data is located for this region, regardless of season?

Figure 4: It is difficult to determine this figure for panel A. I suggest you zoom in on the connectivity map like in B and C but replace those panels with connectivity values instead of binary risk?

Discussion

Lines 4342-436: I am not sure the authors succeeded here based on my point above that the suitability and connectivity seem to follow the presence data? Using a 100 m resolution also seems too fine a scale considering the size of their study area. There may be too similar characteristics across the study area at the 100 m scale thus masking the variables that were really influencing wild boar distribution across your landscape? A larger scale, with your variables summarized to each raster cell (500m or 1000 m) might provide more value and identify more influential variables in your models?

Lines 442-449: Agreed, does the lack of low suitability in Po Valley make sense for how wild boar select habitat in Europe? Are there any detailed VHF or GPS data collected in this region to determine if wild boar prefer agriculture-forest valleys compared to forested, mountainous terrain?

Lines 484-486: The authors acknowledge the temporal pattern but it was not clear how these were modeled with “time” as stated in the methods? All climate variables are available daily, weekly, monthly correct? However, the authors used a static annual mean or 3-4 months seasonal mean which likely rendered these variables of limited value in their assessment. These climate variables and NDVI could have avoided these pitfalls the author outline if they were evaluated differently here?

Reviewer #2: Faustini et al. presented a ms entitled “Habitat suitability mapping and landscape connectivity analysis to predict African swine fever spread in wild boar population: a focus on Northern Italy” for publication in PLOS ONE. The paper deals with a relevant and interesting topic: a highly contagious disease affecting wild and domestic pigs (ASF) reported in Eastern Europe and, in January 2022, in North-western Italy. Thereafter, the expanding wild epidemic, has posed serious management problems related to the presence of Italian pig farms and trade.

I enjoyed reading this ms and I think that this study is a valuable contribution to improve the knowledge/management of this species.

However, despite the interesting topic and the potential of management implications for the target species (i.e., mapping of suitable habitats for wild boars and their potential dispersal corridors in Northern Italy, could be an important issue in preventing the ASF expansion), I believe that a revision is required (please, see my comments below).

General comments:

1) A first flaw that I found concerns the absence of an accurate description of ASF Genotype II expansion (speed, population crash, corridors) in the Eastern European countries. I believe this is a fundamental point: to better introduce the issue, the authors should describe the situation of the last 10 years in Eastern Europe in detail, also in relation to the economic impact of this epidemic.

2) I think the ms would gain more value with a reorganization of the discussion section. I suggest dealing first with the description of the choices made by wild boar, then the description of the potential expansion corridors (with details on the most important directions and their characteristics) and finally an analysis of the possible management and surveillance interventions. These three parts are already present in the discussion but should be better outlined, especially the part related to connectivity.

3) A detailed explanation/comparison of seasonal models is also missing. How does expansion relate to seasons?

4) The manuscript often reports the names of valleys, rivers, mountain areas with reference to the figures (e.g., Fig. 3 - L. 442-446) but these are not reflected in the maps. For a reader who is not familiar with these areas, it is difficult to interpret the results. Supplementary material with more detailed maps could be added.

5) Also the “discontinuous natural zones” (L. 471) should be represented in a map, according to their importance in connectivity

Minor comments:

Abstract: I suggest to delete the description of ASF Genotype I that is not the target of this ms.

L.439-441: “In addition to the higher resolution of the maps presented here compared to those found in the literature, the influence of each variable on wild boar presence was also detailed.”

Please include the references of the studies compared with the results obtained in this research.

L. 507-510: I think that high-traffic corridors need to be described: characteristics, directions and relationships with existing farms.

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Reviewer #1: No

Reviewer #2: No

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PONE-D-24-33277R1Habitat suitability mapping and landscape connectivity analysis to predict African swine fever spread in wild boar population: a focus on Northern ItalyPLOS ONE

Dear Dr. Faustini,

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.

==============================

ACADEMIC EDITOR: the manuscript requires minor revisions. Please carefully follow my comments below. 

==============================

Please submit your revised manuscript by Jan 18 2025 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,

Francesco Bisi, 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.

Additional Editor Comments:

Dear Authors,

I would like to thank you for considering and addressing most of the reviewers' comments. I believe the manuscript contributes significantly to the understanding of a very interesting and sensitive subject.

I must say that given the wide range of potential applications for suitability models, there may never be a "perfect" model or an entirely "wrong" one. Furthermore, due to the complexities of wild boar ecology, modeling its distribution will always present challenges. This species in Europe can be found in very different habitats, ranging from urban areas to mountainous regions up to 2000 m a.s.l. Initially, as Reviewer 1, I was skeptical about the use of NDVI data averaged over a ten-year period. However, I now realize that investigating the subject in greater detail would involve a vast array of additional covariates (e.g., beech and chestnut masting, snow cover, predator densities, hunting pressure), making the endeavor endless. Thus, I consider your selection of covariates appropriate.

However I would like to request a few additional improvements:

As suggested by Reviewer 1, please carefully confirm the number of variables used in the modeling process 11 or 13? Additionally, I agree with Reviewer 1 that Table 1 does not add substantial value to the main text and should be moved to the supplementary material.

Please carefully review the references, as suggested by Reviewer 1. For example, while working with grids in R, I currently use the "Terra" package, but I understand that the "Raster" package is still functional for older versions of R. Kindly verify which package was utilized and ensure the references reflect this accurately.

While reading the manuscript, I felt that the seasonal models were not well integrated into the overall narrative. It would be helpful to clarify why you chose to model seasonal distributions and to better explain why the finding of increased suitability in spring could be of any interest. Does this have any management implications?

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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: (No Response)

Reviewer #2: All comments have been addressed

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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: Partly

Reviewer #2: Yes

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

Reviewer #1: No

Reviewer #2: Yes

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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: No

Reviewer #2: Yes

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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

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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: I appreciate the effort of the authors to pull together this information, the manuscript has been improved considerably in the Introduction specifically, and I appreciate the authors efforts in addressing reviewer concerns. There were still a few concerns that were not addressed and one that I overlooked that I will go into detail below:

Materials and methods

Lines 215-217: What is reference 67 actually referring to here? There is no mention of a correlation tree or cluster dendrogram or raster package in the document? How can the raster package have been used when it was removed from CRAN for use in program R in December 2023? It appears the authors are citing a review (Anderson; Journal of Experimental Marine Biology and Ecology 289(2):303–305) of the book:

Analysis of Ecological Communities: Bruce McCune and James B. Grace, MjM Software Design, Gleneden Beach, USA, 2002, ISBN 0 9721290 0 6, US$ 35 (Pbk) May 2003.

Regardless, none of these terms appear in the book either as far as I can tell.

Line 224: “The variables included in the study for all scenarios were 11:…” Do the authors mean “overall” here instead of “all” to align with text and table 1 that refers to all seasons combined (Line 207)?

Lines 224-228: In my previous review, I suggested “Simply include a sentence of which are not included because they don’t meet assumptions of collinearity/multicollinearity (i.e., opposite of Lines 328-332) in the methods not results.” The authors chose to not edit with my recommendations and also chose not to delete Table 1. Perhaps this time around I might provide a more compelling argument to deleting (or modifying) Table 1 due to the number of issues with it’s inclusion:

1. Out of 20 variables, 11 were acceptable to include in the overall analysis although Table 1 has x in 13 columns along with the total that confirms the 13 and not the 11?

2. The authors list the 11 here as well as several that were not included in overall or seasonal models which, in turn, is presenting "results" in the Materials and Methods? There is also a section in the Results (Lines 365-368) that says out of the 20 variables that 13 were selected in the overall and seasonal suitability models that references Table 1. It is not clear why some of this analysis is in the Materials and Methods and some is in Results?

3. Lines 226-228 identifies several variables that were excluded in all scenarios (overall and seasonal, I presume), and interestingly, 2 of the variables (Temperature and NDVI) are those averaged over a 10 year span that I mentioned was not appropriate in my previous review (see below comments from my previous review and author response).

4. Table 1 repeats some of what is in text in both sections and I would still suggest that it be deleted. If the authors believe it has value, then why not include mean (SDs) for each variable during each season and overall instead of just an x? An entire page for a table with x’s that could be included in 4 sentences in the Materials and Methods (like Lines 226-228 so one line for overall and one line for each season) does not seem necessary and I don’t see how it helps the “flow” considering it is also presented in the Results?

From my previous review:

Lines 484-486 (original submission): The authors acknowledge the temporal pattern but it was not clear how these were modeled with “time” as stated in the methods? All climate variables are available daily, weekly, monthly correct? However, the authors used a static annual mean or 3-4 months seasonal mean which likely rendered these variables of limited value in their assessment. These climate variables and NDVI could have been match with each week-month-year presence data were recorded?

To which the authors responded:

A: While it is true that climate variables are available at more granular temporal resolutions (daily, weekly, and monthly), our decision to employ annual or seasonal means was driven by the objective of focusing on broader climate trends relevant to wild boar habitat suitability. We added a sentence in the discussion in line 556-559 to recognize that a more dynamic approach, utilizing daily or weekly variables, could provide a richer understanding of how seasonal variability may influence habitat selection over time. We thank the reviewer for highlighting this important aspect, as it encourages us to refine our methodologies and consider more nuanced evaluations in subsequent studies.

Reviewer second response: Again, I suggested the authors assign temperature and NDVI to the monthly or even seasonal means instead of a 10 year mean (overall or seasonal). The authors identified, in their response and in the manuscript that a “more dynamic approach, utilizing daily or weekly variables, could provide a richer understanding…” however the authors chose not to do it in their revision? Instead, they argue how it can be done in the future? Furthermore, do the authors realize that both Temperature and NDVI were not included in any models (Based on Table 1 multicollinearity) and Precipitation was include in 3 of the 5 scenarios only? Regardless of what past research claims, the authors have the ability to match these variables to the annual/seasonal means to match them to the data but chose not to do so. The authors might be better off removing them entirely in the manuscript and models considering they provide no value based on how they were presented in the models (perhaps due to static 10 year averages)? Based on how you present them in Table 1, Temp and NDVI were not included in any models, correct?

Supporting information, S1 Files: This Gitlab repository does not exist or is not accessible to the reviewer. The authors agreed that it should be available “upon acceptance,” however, not available to the reviewer? It seems that accepted or not, a GitLab repo would be valuable to document your work and provide this analysis as an archive for your efforts. Including this link in your revisions has little value if a reviewer is not able to access it?

Reviewer #2: This revised version has improved a lot and accounted for most of the problems I identified when reading the first version.

I think the authors have made a considerable effort to increase the quality of their ms.

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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

Reviewer #2: No

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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.

Habitat suitability mapping and landscape connectivity analysis to predict African swine fever spread in wild boar populations: a focus on Northern Italy

PONE-D-24-33277R2

Dear Dr. Faustini,

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.

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Kind regards,

Francesco Bisi, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments: