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Summary

  • The initial submission of this article was received on September 16th, 2022 and was peer-reviewed by 2 reviewers and the Academic Editor.
  • The Academic Editor made their initial decision on October 14th, 2022.
  • The first revision was submitted on November 8th, 2022 and was reviewed by the Academic Editor.
  • The article was Accepted by the Academic Editor on November 14th, 2022.

Version 0.2 (accepted)

· Nov 14, 2022 · Academic Editor

Accept

Thank you for the thorough revision and congratulations on this excellent manuscript.

[# PeerJ Staff Note - this decision was reviewed and approved by Konstantinos Kormas, a PeerJ Section Editor covering this Section #]

Version 0.1 (original submission)

· Oct 14, 2022 · Academic Editor

Minor Revisions

Both reviewers have emphasized the high standard to which this work has been performed and the findings are presented, with which I wholeheartedly agree. Overall, the reviewers’ assessment of your work is favourable, and includes detailed suggestions that we hope will help shape a revision of your manuscript.

These suggestions include:
- Further clarification, additional detail, literature support (where applicable), or additional references for specific statements in the introduction and discussion;
- Streamlining of order of reporting between the methods and results section for consistency;
- More detail on sample sizes, analyses or statistical tools to be included in the results section;
- Specific suggestions to add additional analysis and/or adjust color palette in plots.

[# PeerJ Staff Note: It is PeerJ policy that additional references suggested during the peer-review process should only be included if the authors are in agreement that they are relevant and useful #]

[# PeerJ Staff Note: Please ensure that all review and editorial comments are addressed in a response letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate. #]

Reviewer 1 ·

Basic reporting

This is an excellent paper covering a key question in wild animal gut microbiota ecology and evolution. It calls on a range of data types to contextualize the microbial community analyses. I have no major concerns with either the analyses or the presentation of the paper, and my suggestions below are targeted toward presenting this paper to the broadest possible audience.

Introduction

Line 86: what have longitudinal studies revealed that single time-point studies can’t? Alternatively, what might they reveal that can’t be learned from single time points? (for example you reference buffering of seasonal energy needs on line 144 – that could be introduced here)

Lines 87-95: the claim that selection is reduced on islands on the surface seems at odds with the claim that they are ideal laboratories to study coevolution. Is there available evidence to suggest that reduced selection pressure from interspecific competition or predation on islands allows selection due to coevolution to become more detectable? Or os there some other argument to be made to reconcile the two statements?

Line 104: Can you provide an approximate date of common ancestry based on the literature?

Line 130: Since omnivory is fairly rare in small lizards, can you discuss the specifics here? For example, what parts of the plants to they feed on and on the seasonality of the plant feeding? This might be particularly useful in setting up the seasonality results in lines 337-345.

Methods

Line 260: Please explain why you choose to split the dataset into seasons here, then recombine the results later? Could a single season dominate the analysis without the splitting step, or is there another reason?

Results

Line 298: Were any of the island-specific core microbial taxa present across more than one island?

Line 328: typo – should the marginal year effect p value read 0.0396?

Discussion

Line 553: delete ‘Following’ from the sentence

Line 555: ‘sampling events’ rather than ‘sampling’

Line 583 or Line 604-614: I suggest a brief discussion of what is known about the gut microbiota of other largely carnivorous or insectivorous taxa that have shifted to a more omnivorous diet. For example, baleen whales (ie Sanders et al. 2015) or bonnethead sharks (ie Leigh et al. 2018), among others.

Line 587: I would add Amato et al. 2015 to the citation list (DOI 10.1007/s00248-014-0554-7)

Line 622: I’m not sure this claim follows from your data. While it is a possible interpretation, I would qualify the claim and/or suggest future work to confirm the hypothesis.

Figures

Figure 3, 4, 7: Are the color palettes in these figures colorblind friendly? They look like they might be, but if not the red and green might be difficult to distinguish.

Figure S2: ‘Phylum’ and ‘Family’ legend labels are identical.

Experimental design

Methods

Line 150: Can you provide the sample sizes per time point as well for each island?

Line 154: Can you provide the sample sizes for each time point?

Validity of the findings

All findings are valid and well presented. This paper is an important contribution to the field.

·

Basic reporting

“Insular holobionts: persistence and seasonal plasticity of the Balearic wall lizard (Podarcis lilfordi) gut microbiota (#77184)”

The study was conducted from 2017 to 2018 on three island lizard populations, during two seasons (spring and autumn) in order to identify the effect of islet, sex, lifestyle and season on the composition of the gut microbiota. The authors found microbiota diversity was strongly marked by seasonality with no sex effect and a marginal life stage and annual effect.
The work is well structured, with a satisfactory experimental design, relevant figures and well presented results. However, below are some comments that could improve the paper.
It is necessary to maintain consistency in the order between the chapter of methods and that of the results, for example the results of beta diversity appear in the text before those of alpha diversity, although the order is reversed in the methods. The same is true between the results shown in figure 5 and figure 6, they must also be mentioned in this order in the methods chapter.

Lines 524-527: It is recommended to cite also other references:
Raia, P., Guarino, F.M., Turano, M. et al. The blue lizard spandrel and the island syndrome. BMC Evol Biol 10, 289 (2010). https://doi.org/10.1186/1471-2148-10-289
Monti, D. M., Raia, P., Vroonen, J., Maselli, V., Van Damme, R., & Fulgione, D. (2013). Physiological change in an insular lizard population confirms the reversed island syndrome. Biological Journal of the Linnean Society, 108(1), 144-150

Experimental design

In order to identify Bacteria taxa driving differences in microbiota composition across populations I also suggest to use the ANCOM-II method and make a comparison with the other methods used.
Figure 3: provide the variance explained by the coordinates.
Beta and alpha diversity analyses: Did the authors do a pairwise analysis? Clarify it in the text.

Validity of the findings

Analyzing the results, the population/islet showing the greatest differences is EC, but looking at the number of samples making up the 3 populations, it can be seen that it is not always homogeneous, especially for the EC population, with only 19 samples. Is it likely that the differences that emerged were due to this element? Did the authors carry out a test to assess whether the number of samples in the three groups is suitable for the different analyzes?

Additional comments

Line 162: close the parenthesis after “old” and include the two references in a new parenthesis.
Line 212: add space after the parenthesis, and adjust the word “and”.

Line 428: cite appropriately the reference cited in the text.

Figure 3: I recommend adding letters to the panels of the figure and a specification in the caption that can help the reader in interpreting the results.

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