PONE-D-22-28513Broad-scale factors shaping the ecological niche and geographic distribution of Spirodela polyrhizaPLOS ONE

Dear Dr. Cobos,

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. Most of the referees found merit in this manuscript, especially pointing out the accurate framework implemented by the authors to select optimal environmental variables for model calibration. That said, some points need to be addressed before proceeding further with this manuscript. Firstly, hypotheses and objectives must be clearly specified as to put the study significance in appropriate evidence. Also, important details about methodological choices miss from the text (e.g. the rationale behind pseudo-absences placement and number, information on the modelling algorithms, etc), as well as ecological justification for the sizes of the calibration area or the distance considered to reduce sampling bias. Regarding this latter point, the authors should also make sure that the spatial autocorrelation in models' residuals was actually absent or not significant.

Please submit your revised manuscript by Mar 17 2023 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,

Mirko Di Febbraro

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and 

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. "Please upload a new copy of Figure 2 and 4 as the detail is not clear. Please follow the link for more information: " ext-link-type="uri" xlink:type="simple">https://blogs.plos.org/plos/2019/06/looking-good-tips-for-creating-your-plos-figures-graphics/"" " ext-link-type="uri" xlink:type="simple">https://blogs.plos.org/plos/2019/06/looking-good-tips-for-creating-your-plos-figures-graphics/"

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

Reviewer #4: Partly

**********

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

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

Reviewer #4: 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

Reviewer #3: Yes

Reviewer #4: 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: No

Reviewer #3: Yes

Reviewer #4: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The interesting paper entitled “Broad-scale factors shaping the ecological niche and geographic distribution of Spirodela polyrhiza” showed a multi-step approach to select relevant variables for modelling the ecological niche. A widely distributed aquatic plant species was used as a case study, but this approach can be widely replicated for different species, geographic regions and scales. The analysis led to interesting and reliable results on plant-specific ecology. Further thoughts on how underestimated factors, such as the calibration area and spatial resolution used, greatly influence the response of each model are also of interest.

Overall, I consider this manuscript suitable for publication in Plos One.

I have only a few concerns:

I suggest reporting the authority of the species when first mentioned.

L 136-137: the authors mention that to reduce autocorrelation bias, they thinned the records using a minimum point-to-point distance of ~30'. It would be useful to test and compare this autocorrelation to show and then discuss whether it was indeed reduced.

L 170: please cite the source from which the ecoregions were retrieved.

Attachments: for ease of reading, I suggest changing the format of the supporting figures (e.g. jpeg) or directly merging all this information (including descriptions) into one pdf file.

Reviewer #2: The main aim of the MS is to identify the abiotic factors that shape the distribution of Spirodela polyrhiza. This aim could be crucial to understand and predict the actual and future distribution of the target species, but in my opinion the methods used are completely wrong:

First of all raster resolution of explanatory variables at 10’ or 30’ cannot be acceptable, especially to investigate the distribution of a species that lives in the ponds.

Secondly, the authors try to disentangle some methodological issues in SDM/ENM (e.g. extend of the calibration areas, algorithms) that cannot be addressed using very coarse variables and considering only one species.

Specific methodological comment:

- Records that were outside of, but closer than ~5’ to the edge of environmental layers were moved to the nearest pixel with information – what? are you expected to find similar environmental condition within 100 km2

- minimum point-to-point distance of ~30’ – how many different environmental condition occurs in ~3600 km2 - not acceptable

- the broad distribution of this species makes it difficult for that method to be applied, why? Maybe is due to the coarse resolution of your approach?

- Modeling algorithms: how did you generate the pseudoabsence? how did you calibrate the models,? have you performed some how the cross validation?

- “We transferred all the models across the area comprising the union of the four calibration areas and compared those models to assess whether patterns of suitability values differed as a result of using distinct variables, calibration areas, and algorithms.” WHY? Is it a methodological or ecological MS? Not clear.

- Have you considered the multicollinearity among explanatory variables?

Please consider to read many paper that suggest how perform the SDM/ENM, how create pseudo-absence, how to create ensemble models by combining different algorithms, how to perform cross validation and so on. Please not use a single species to address methodological question, consider to use virtual species for that. Hereunder some useful paper:

Barbet‐Massin, M., Jiguet, F., Albert, C. H., Thuiller, W. (2012). Selecting pseudo‐absences for species distribution models: how, where and how many?. Methods in ecology and evolution, 3(2), 327-338.

Bucklin, D. N., Basille, M., Benscoter, A. M., Brandt, L. A., Mazzotti, F. J., Romanach, S. S., ... Watling, J. I. (2015). Comparing species distribution models constructed with different subsets of environmental predictors. Diversity and distributions, 21(1), 23-35.

Connor, T., Hull, V., Viña, A., Shortridge, A., Tang, Y., Zhang, J., ... Liu, J. (2018). Effects of grain size and niche breadth on species distribution modeling. Ecography, 41(8), 1270-1282.

Muscarella, R., Galante, P. J., Soley‐Guardia, M., Boria, R. A., Kass, J. M., Uriarte, M., Anderson, R. P. (2014). ENM eval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models. Methods in ecology and evolution, 5(11), 1198-1205.

VanDerWal, J., Shoo, L. P., Graham, C., Williams, S. E. (2009). Selecting pseudo-absence data for presence-only distribution modeling: how far should you stray from what you know?. Ecological modelling, 220(4), 589-594.

Reviewer #3: The paper entitled "Broad-scale factors shaping the ecological niche and geographic distribution of Spirodela polyrhiza", investigates the effect of variable selection procedures for modeling the ecological niche of the aquatic Spirodela polyrriza, taking into account variability arising from using distinct algorithms, calibration areas, and spatial resolutions of variables. The authors show that the final set of variables selected based on statistical inference varied considerably depending on the combination of algorithm, calibration area, and spatial resolution used.

The article is clearly written, polished, well-edited, and scientifically sound. It is characterized by good originality. I recommend publishing with minor changes. I have a few comments.

Abstract

The abstract accurately describes the main objective of the study. It explains how the study was done, including the model organism used, without exceeding methodological details. The most important results are summarized, but their significance has not been sufficiently emphasized, specifically for the variation of the final set of variables selected based on the combination of algorithm, calibration area, and spatial resolution.

Introduction

The authors provide a careful overview of the challenge of selecting appropriate environmental variables when characterizing species' ecological niches, and what still ought to be done. The objectives of the study are clearly specified, but hypothesis are missing. The lack of clear hypothesis could prevent to really understand the significance and the importance of the study.

Methods

The Materials and Methods section provides enough detail to allow suitably skilled investigators to replicate the main steps of the study. However, the lack of specific information (e.g., method of generating pseudo-absences, method details of GLMs' model calibration, R packages adopted to evaluate GLMs' performance of candidate models) does not allow a full understanding of the code provided. Specific information should be included in detail, citing articles you followed for the choices/methods applied.

In addition, I suggest the authors explain why they adopted that specific ratio of the quantity of presence data to the number of background points/pseudo-absence data to fit models, specifying a reference that supports the choice. This is always a very sore point because according to some authors an inadequate number of background points or pseudo-absences (in this study 20,000 points for 964 occurrences; lines 138 and 190-191) could reduce the accuracy of the models. Model accuracy is generally affected both by this ratio, but also by the method used to generate pseudo-absences (see for example

Barbet-Massin et al., 2012 -

https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/j.2041-210X.2011.00172.x).

More specific comments here:

Line 136 - 138: I suggest the authors provide details on the reference that supports the choice of using the minimum point-to-point distance of ~30’ for the spatial thinning of species occurrence records.

Line 160 - 162: "We performed raster aggregation procedures (average of values) on CEC, OC, and pH to match the resolution of BIO variables, and on BIO and SR variables to match the resolution of variables at 30’. [..]" I do not really understand this sentence. Have you used a BIO variable as a snap raster to ensure all cells were properly aligned, and all rasters have the same cell resolutions? If this is the case, please specify the method applied (e.g., nearest neighbour method etc.), if not rephrase the sentence.

Line 162 - 164: "Although the set of variables representing soil conditions used at 10’ differs from the one at 30’, variable selection analyses will help to identify whether the variables selected differ between the two resolutions. [..]"

Does any other author support this??

Line 171 - 176: "Although a new simulation-based approach has been recently suggested as a reliable tool to estimate calibration areas [59], the broad distribution of this species makes it difficult for that method to be applied. Our chosen calibration areas are therefore reasonable options to calibrate models, considering that such areas should reflect what regions could have been accessible to the species and present relevant environments for comparisons [..]"

Does any other author support this?? Do you have a specific reference to cite?

Line 216-217: "The latter consideration assumes that using variables for which the entire spectrum of responses can be characterized makes for better models. [..]" Please cite and provide a reference for this sentence.

Line 218-219: "Biological relevance of variables was determined based on details about the species' natural history, phenology, and physiology in the literature, and our own experience with populations in the field and controlled environments [..]" No bibliographic reference was cited to justify the selection of biologically relevance variables. Please, integrate a citation

Line 260: “see below”. Where? Please, specify.

Results

The results relate to the research question, and the language adopted to express results is clear and concise. The tables and figures are appropriate, but very fragmented in many appendix documents. To explore the results in detail, the reader should open as many as 11 documents (.docx format) and have vector graphic software to open 26 images attached in the .eps format. I strong suggest aggregating appendixes and exporting images in a simple file format (e.g., jpg or .tif).

Discussion

The writing is very good and well-polished. I have no suggestion.

Reviewer #4: General comments

The authors of “Broad-scale factors shaping the ecological niche and geographic distribution of Spirodela polyrhiza” focused their research to define an innovative methodological approach in order to select the most appropriate set of environmental variables in ecological niche modeling. This aim is the basis for produce efficient ecological niche modeling, and even today it still not fully resolved. Currently the traditional methods to establish the set of environmental variables consists in different approach for example excluding the variables with very high multicollinearity problems, selecting the variable through expert based procedure supported by empirical evidences, and also letting algorithms that they eliminate the variables in order to optimize the fitting of ecological niche model produced. Furthermore as well described by authors, the final set of environmental variables in ecological niche modeling depends on many different factors. Firstly in the ecological niche modelling, these models can be produced to respond two different aims to analyze the ecology of species target and its environmental limits or to predict the geographic distribution of species target, and consequently these two different aims require to define dissimilar environmental variables. Moreover the set of environmental variables may varies depending on spatial resolution of environmental data used, on areas for model calibration, and also on algorithm used. These three last aspects will require further examines given that there are still few researches that they directly investigated these questions. In this context, the authors developed ecological niche models for Spirodela polyrhiza, a cosmopolitan free-floating aquatic plants on different calibration areas, using environmental variables at different spatial resolutions, using two niche model algorithms and also applying a multi-step approach to define the environmental. The occurrence data were downloaded from GBIF and Botanical Information and Ecology Network at global scale, successively these data were filtered maintaining 964 occurrences. The authors used environmental variables with different spatial resolution, in particular bioclimatic and solar radiation at 10’ of resolution acquired from WorldClim v2.1, soil variables as cation exchange capacity, organic carbon and ph from World Soil Information database at fine resolution of 250 m and coarser soil variables as total phosphorous, labile inorganic phosphorous and organic phosphorous at 30’ resolution. Furthermore, the authors considered four different areas for model calibration: first area was defined as buffers of 5° around S. polyrhiza occurrences, the second area consist in concave-hull polygons with a buffer of 5° around S. polyrhiza occurrences, the third area was the ecoregions occupied by the species buffered by 1° and finally the fourth area was the intersection of the previous three areas. Concerning the ecological niche model algorithms the authors calculated the generalized linear models (GLM with different weight, 1 for S. polyrhiza occurrences and 10,000 for pseudo-absence) and Maxent using 20,000 pseudo-absence and background data respectively. Finally, the environmental variables were selected using a multi-step approach that well summarize a large number of qualitative and quantitative approaches individually applied on previous studies. First step (that is only described in Figure 2) consist in inspection and/or treatment of variables, after a measure of linear correlation among variables, followed by exploration of variable values inside and outside the S. polyrhiza occurrence areas. At the end of the third step, the authors proposed a first selection of variables supported by ecological and historic information of species target. After, the variables were assembled between them in all combinations from two to total number of variables. Finally all these dataset were used in ecological niche models with different calibration areas and algorithms (GLM, Maxent) with a total of 10,180 and 5065 GLM models were tested at spatial resolution of 10’ and 30’ respectively and also for Maxent algorithms were produced 61,080 and 30,390 niche models at 10’ and 30’ respectively produced. The performance of each models was calculated using the following metrics: partial ROC, omission rate and Akaike information criterion for GLMs, and the AICc for Maxent. Ultimately, the authors defined the effects of environmental variables analyzing the best model for each algorithms (GLM, Maxent) and calibration area and in the two spatial resolutions (10’, 30’) through the use of jackknife analysis for Maxent and ANOVA for GLM.

The results of this research demonstrated the potentiality of this approach to define the best set of environmental variables. Firstly, the graphical explorations and the linear correlation of environmental conditions across calibration areas and S. polyrhiza occurrences enables to display the variables with higher suitable conditions in order to reduce at 11 variables with 10’ of spatial resolution and 10 variables with 30’ of spatial resolution. Interestingly, the differences of environmental variables selected at different resolution, concerning 10’ resolution the soil and solar radiation variables were more suitable to analyze the S. polyrhiza occurrences whereas at 30’ resolution the bioclimatic and solar radiation variables were more suitable. Finally, the Maxent algorithm seems to work better compared to GLM given that the Maxent projections showed higher variability across for each spatial resolution and the calibration areas.

In general, this research the authors very well examine the problem due to the selection of environmental variables for niche ecological modelling. The manuscript is well structured in particular in introduction, methods and discussion, less the results that it requires a large number of information as the results of model evaluation (partial ROC, omission rate, Akaike information criterion for GLM and AICc for Maxent), and also the results of jackknife analysis for Maxent and ANOVA for GLM to measure/explore deviances for each environmental variables selected. Moreover, the results obtained for S. polyrhiza niche models are in line with large number of previous researches with different species target in which the bioclimatic, solar radiation and soil conditions variables were identified as the most important environmental variables that limit species growth at global scale. Consequently in the manuscript, miss a clear paragraph that describe innovative aspects to use these environmental variables in order to produce S. polyrhiza niche models. I consider that the use of traditionally methods to define the set of environmental variables allowed to achieve same or similar results. Please, provide you a motivation for this my question. Furthermore, several steps in text require more details and adequate motivations, for example miss ecological reason of dimensions and shapes of calibration areas, miss ecological reason of distance (30’) required to reduce the bias of spatial autocorrelation, and also miss the ecological reasons for choosing these environmental variables (bioclimatic, solar radiation, and soil conditions, for more details see Specific comments). Finally, the use of GBIF and BIEN underestimate the real spatial extension of S. polyrhiza. Can this problem effect the ecological niche model produced?

In consideration of above, this paper may be addressed in a major revision.

Specific comments

Line 10: Change the corresponding author email with an institutional email.

Lines 134 – 136: I did not understand this sentence. Are environmental variables not at global scale? Please rewrite this sentence, thank you.

Lines 137 – 138: The S. polyrhiza occurrences were subjected to a drastic reduction from 45,913 to 964 records. This reduction is due to minimum point-to-point distance (30’) set to eliminate the spatial autocorrelation problem. Please, you include in the manuscript an ecological motivation specific to S. polyrhiza to establish this distance.

Paragraph “Environmental variables”: In this paragraph misses a description how these environmental variables were important to S. polyrhiza growth.

Lines 157 – 160: Add a table with the environmental variables used describing their ecological importance specific to S. polyrhiza and the spatial resolution.

Lines 167 – 171: Please add references that they used similar methods to define calibration area, and also indicated the importance of these methods (buffer, concave-hull polygons, ecoregions, and the intersection of previous three areas) as calibration areas for S. polyrhiza.

Paragraph “Modeling algorithms”: Even if the calibration areas include large portion of territory around S. polyrhiza occurrences, these occurrences derived by GBIF and BIEN dataset that could be underestimated the areal of target species. Consequently, background or pseudo-absence points could be false negative. How you considered this question?

Lines 198 – 200 and Figure 2: In the main text miss a description of the first step displayed in Figure 2 “Inspection and/or treatment”. Furthermore, please add the same number for each step reported in main text in figure 2 to make the reading of manuscript easier.

Lines 212 – 216: The references of Fig. 3 and Fig. 4 were inverted in main text. After, these two figures (Fig. 3, Fig. 4) showed preliminary results of S. polyrhiza ecological niche model. In my researches, I prefer described these results in the results paragraph. Please move these two figures and add their description in results paragraph.

Figures 3, 4, 6, 7: Add in the main text or in the caption of these figures the reasons to display in the main text only the results with 10’ in spatial resolution.

Figures 6 and S11: Add a legend of suitability.

Lines 367 – 370: Based on this sentence, I have a question. The S. polyrhiza occurrences used in this research could be not include the total real occurrences, can this problem influenced the results of ecological niche models?

Lines 403 – 408: Add ecological reasons specific and references to S. polyrhiza and/or other species in order to motivate the inclusion of variables with complication in graphical explorations.

Lines 411 – 413: The temperature is certainly the main driver to limit the species growth at global scale, please add references.

Lines 419 – 421: The relationship between the target species and soil variables were more important in the finest ecological niche model. This describe an higher importance of soil condition at this fine scale, please add references to motivate this feature.

**********

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: Yes: Mauro Fois

Reviewer #2: No

Reviewer #3: No

Reviewer #4: 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.

Broad-scale factors shaping the ecological niche and geographic distribution of Spirodela polyrhiza

PONE-D-22-28513R1

Dear Dr. Cobos,

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,

Mirko Di Febbraro

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

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 #4: (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 #4: Yes

**********

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

Reviewer #1: Yes

Reviewer #4: 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 #4: 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 #4: 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: The authors addressed my previous concerns regarding autocorrelation bias and other few comments. In my opinion it can be accepted in this form

Reviewer #4: General comments

The paper “Broad-scale factors shaping the ecological niche and geographic distribution of Spirodela polyrhiza” has been considerably improved. In this last version all paragraphs are well structured and exhaustive. The authors have clearly answered my questions and added the information required in the manuscript. Only few details require further clarification before its publication.

Specific comments

Lines 245-246. In the pairwise correlation analysis, which algorithm was used? Please indicate.

Lines 245-249. References to Fig. 3 and Fig. 4 are invert.

Lines 257-259. In the caption of Fig. 3 indicate the icon for combinations of variables with high values of correlation.

Lines 317-319. The results report in S4 and S5 tables do not coincide with the affirmation of this phrase. In S4 table, the Omission rates values are greater than 0.05, and also the AICs values in S4 and S5 tables are of the order of the thousands. Please rewrite this phrase.

**********

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: Mauro Fois

Reviewer #4: No

**********